diff --git a/DESCRIPTION b/DESCRIPTION
index a2fc59d..477880e 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: spatialplanr
 Title: Help files for prioritzr Spatial Planning projects
-Version: 0.6.8
+Version: 0.6.9
 Authors@R: c(
     person(
       given = "Jason D.",
diff --git a/R/splnr_plotting.R b/R/splnr_plotting.R
index b97fecb..1643042 100644
--- a/R/splnr_plotting.R
+++ b/R/splnr_plotting.R
@@ -203,7 +203,7 @@ splnr_plot_costOverlay <- function(soln, Cost = NA, Cost_name = "Cost",
       high = "#d94801", # "#f16913",
       limits = c(
         0,
-        as.numeric(stats::quantile(dplyr::pull(Cost, Cost_name), 0.99))
+        as.numeric(stats::quantile(dplyr::pull(Cost, Cost_name), 0.99, na.rm = TRUE))
       ),
       # direction = 1,
       oob = scales::squish,
diff --git a/docs/404.html b/docs/404.html
index cc8d711..1668116 100644
--- a/docs/404.html
+++ b/docs/404.html
@@ -14,8 +14,8 @@
 <link rel="apple-touch-icon" type="image/png" sizes="60x60" href="https://mathmarecol.github.io/spatialplanr/apple-touch-icon-60x60.png">
 <script src="https://mathmarecol.github.io/spatialplanr/deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <link href="https://mathmarecol.github.io/spatialplanr/deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
-<script src="https://mathmarecol.github.io/spatialplanr/deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="https://mathmarecol.github.io/spatialplanr/deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
-<link href="https://mathmarecol.github.io/spatialplanr/deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="https://mathmarecol.github.io/spatialplanr/deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="https://mathmarecol.github.io/spatialplanr/deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet">
+<link href="https://mathmarecol.github.io/spatialplanr/deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet">
 <script src="https://mathmarecol.github.io/spatialplanr/deps/headroom-0.11.0/headroom.min.js"></script><script src="https://mathmarecol.github.io/spatialplanr/deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="https://mathmarecol.github.io/spatialplanr/deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="https://mathmarecol.github.io/spatialplanr/deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="https://mathmarecol.github.io/spatialplanr/deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="https://mathmarecol.github.io/spatialplanr/deps/search-1.0.0/fuse.min.js"></script><script src="https://mathmarecol.github.io/spatialplanr/deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="https://mathmarecol.github.io/spatialplanr/pkgdown.js"></script><meta property="og:title" content="Page not found (404)">
 <meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png">
 </head>
@@ -27,7 +27,7 @@
 
     <a class="navbar-brand me-2" href="https://mathmarecol.github.io/spatialplanr/index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html
index 1add8f3..33c7223 100644
--- a/docs/LICENSE-text.html
+++ b/docs/LICENSE-text.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>License • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="License"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>License • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="License"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/LICENSE.html b/docs/LICENSE.html
index ed33049..8a8256f 100644
--- a/docs/LICENSE.html
+++ b/docs/LICENSE.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>MIT License • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="MIT License"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>MIT License • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="MIT License"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/articles/ClimateSmart.html b/docs/articles/ClimateSmart.html
index 70b8818..63899fe 100644
--- a/docs/articles/ClimateSmart.html
+++ b/docs/articles/ClimateSmart.html
@@ -14,8 +14,8 @@
 <link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png">
 <script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
-<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
-<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet">
 <script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Climate-Smart Spatial Planning">
 </head>
 <body>
@@ -26,7 +26,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -117,7 +117,7 @@ <h3 id="analysis-region">Analysis Region<a class="anchor" aria-label="anchor" hr
 <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">Bndry</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/splnr_get_boundary.html">splnr_get_boundary</a></span><span class="op">(</span>Limits <span class="op">=</span> <span class="va">Region</span>, Type <span class="op">=</span> <span class="va">Type</span>, cCRS <span class="op">=</span> <span class="va">cCRS</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Reading layer `ne_10m_geography_marine_polys' from data source </span></span>
-<span><span class="co">#&gt;   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpMuMJpx/ne_10m_geography_marine_polys.shp' </span></span>
+<span><span class="co">#&gt;   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpHVmm7h/ne_10m_geography_marine_polys.shp' </span></span>
 <span><span class="co">#&gt;   using driver `ESRI Shapefile'</span></span>
 <span><span class="co">#&gt; Simple feature collection with 306 features and 37 fields</span></span>
 <span><span class="co">#&gt; Geometry type: MULTIPOLYGON</span></span>
@@ -202,12 +202,12 @@ <h4 id="climate-smart-spatial-planning">Climate-smart spatial planning<a class="
 using SSP5-8.5. For downstream analysis, we rename the column of
 interest (here: the velocity data) <code>metric</code>.</p>
 <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">metric_df</span> <span class="op">&lt;-</span> <span class="va">CoralSeaVelocity</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<code class="sourceCode R"><span><span class="va">metric</span> <span class="op">&lt;-</span> <span class="va">CoralSeaVelocity</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/rename.html" class="external-link">rename</a></span><span class="op">(</span>metric <span class="op">=</span> <span class="va">voccMag_transformed</span><span class="op">)</span></span></code></pre></div>
 <p>The climate velocity data can be visualized using the
 <code><a href="../reference/splnr_plot_climData.html">splnr_plot_climData()</a></code> function.</p>
 <div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="op">(</span><span class="va">ggclim</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/splnr_plot_climData.html">splnr_plot_climData</a></span><span class="op">(</span><span class="va">metric_df</span>, <span class="st">"metric"</span><span class="op">)</span> <span class="op">+</span></span>
+<code class="sourceCode R"><span><span class="op">(</span><span class="va">ggclim</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/splnr_plot_climData.html">splnr_plot_climData</a></span><span class="op">(</span><span class="va">metric</span>, <span class="st">"metric"</span><span class="op">)</span> <span class="op">+</span></span>
 <span>   <span class="fu"><a href="../reference/splnr_gg_add.html">splnr_gg_add</a></span><span class="op">(</span></span>
 <span>     Bndry <span class="op">=</span> <span class="va">Bndry</span>, overlay <span class="op">=</span> <span class="va">landmass</span>,</span>
 <span>     cropOverlay <span class="op">=</span> <span class="va">PUs</span>, ggtheme <span class="op">=</span> <span class="va">splnr_theme</span></span>
@@ -223,14 +223,14 @@ <h4 id="climate-smart-spatial-planning">Climate-smart spatial planning<a class="
 <div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">5</span><span class="op">)</span></span>
 <span></span>
-<span><span class="va">metric_df</span> <span class="op">&lt;-</span> <span class="va">CoralSeaVelocity</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span><span class="va">metric</span> <span class="op">&lt;-</span> <span class="va">CoralSeaVelocity</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/rename.html" class="external-link">rename</a></span><span class="op">(</span>metric <span class="op">=</span> <span class="va">voccMag_transformed</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span></span>
 <span>    metricOG <span class="op">=</span> <span class="va">metric</span>,</span>
 <span>    metric <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">metric</span> <span class="op">&gt;</span> <span class="fl">0.99</span>, <span class="fu"><a href="https://rdrr.io/r/stats/Uniform.html" class="external-link">runif</a></span><span class="op">(</span><span class="va">.</span>, <span class="fl">0.85</span>, <span class="fl">1.0</span><span class="op">)</span>, <span class="va">metric</span><span class="op">)</span></span>
 <span>  <span class="op">)</span></span>
 <span></span>
-<span><span class="op">(</span><span class="va">ggclim</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/splnr_plot_climData.html">splnr_plot_climData</a></span><span class="op">(</span><span class="va">metric_df</span>, <span class="st">"metric"</span><span class="op">)</span> <span class="op">+</span></span>
+<span><span class="op">(</span><span class="va">ggclim</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/splnr_plot_climData.html">splnr_plot_climData</a></span><span class="op">(</span><span class="va">metric</span>, <span class="st">"metric"</span><span class="op">)</span> <span class="op">+</span></span>
 <span>    <span class="fu"><a href="../reference/splnr_gg_add.html">splnr_gg_add</a></span><span class="op">(</span></span>
 <span>      Bndry <span class="op">=</span> <span class="va">Bndry</span>, overlay <span class="op">=</span> <span class="va">landmass</span>,</span>
 <span>      cropOverlay <span class="op">=</span> <span class="va">PUs</span>, ggtheme <span class="op">=</span> <span class="va">splnr_theme</span></span>
@@ -254,7 +254,7 @@ <h4 id="climate-smart-spatial-planning">Climate-smart spatial planning<a class="
 (here: <code>refugiaTarget = 1</code> to protect 100% of the 5% most
 climate-smart areas).</p>
 <div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">target</span> <span class="op">&lt;-</span> <span class="va">datEx_species_bin</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<code class="sourceCode R"><span><span class="va">targets</span> <span class="op">&lt;-</span> <span class="va">datEx_species_bin</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_geometry.html" class="external-link">st_drop_geometry</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
@@ -263,10 +263,11 @@ <h4 id="climate-smart-spatial-planning">Climate-smart spatial planning<a class="
 <span></span>
 <span></span>
 <span><span class="va">CPA_Approach</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/splnr_climate_priorityAreaApproach.html">splnr_climate_priorityAreaApproach</a></span><span class="op">(</span></span>
-<span>  featuresDF <span class="op">=</span> <span class="va">datEx_species_bin</span>,</span>
-<span>  metricDF <span class="op">=</span> <span class="va">metric_df</span>, </span>
-<span>  targetsDF <span class="op">=</span> <span class="va">target</span>, </span>
-<span>  direction <span class="op">=</span> <span class="op">-</span><span class="fl">1</span>, refugiaTarget <span class="op">=</span> <span class="fl">1</span></span>
+<span>  features <span class="op">=</span> <span class="va">datEx_species_bin</span>,</span>
+<span>  metric <span class="op">=</span> <span class="va">metric</span>, </span>
+<span>  targets <span class="op">=</span> <span class="va">targets</span>, </span>
+<span>  direction <span class="op">=</span> <span class="op">-</span><span class="fl">1</span>, </span>
+<span>  refugiaTarget <span class="op">=</span> <span class="fl">1</span></span>
 <span><span class="op">)</span></span>
 <span></span>
 <span><span class="va">out_sf</span> <span class="op">&lt;-</span> <span class="va">CPA_Approach</span><span class="op">$</span><span class="va">Features</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
@@ -276,7 +277,7 @@ <h4 id="climate-smart-spatial-planning">Climate-smart spatial planning<a class="
 <span>        <span class="fu">tidyselect</span><span class="fu">::</span><span class="fu"><a href="https://tidyselect.r-lib.org/reference/starts_with.html" class="external-link">starts_with</a></span><span class="op">(</span><span class="st">"Cost_"</span><span class="op">)</span></span>
 <span>      <span class="op">)</span>,</span>
 <span>    join <span class="op">=</span> <span class="fu">sf</span><span class="fu">::</span><span class="va"><a href="https://r-spatial.github.io/sf/reference/geos_binary_pred.html" class="external-link">st_equals</a></span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_join.html" class="external-link">st_join</a></span><span class="op">(</span><span class="va">metric_df</span>, join <span class="op">=</span> <span class="fu">sf</span><span class="fu">::</span><span class="va"><a href="https://r-spatial.github.io/sf/reference/geos_binary_pred.html" class="external-link">st_equals</a></span><span class="op">)</span></span>
+<span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_join.html" class="external-link">st_join</a></span><span class="op">(</span><span class="va">metric</span>, join <span class="op">=</span> <span class="fu">sf</span><span class="fu">::</span><span class="va"><a href="https://r-spatial.github.io/sf/reference/geos_binary_pred.html" class="external-link">st_equals</a></span><span class="op">)</span></span>
 <span></span>
 <span><span class="va">targets</span> <span class="op">&lt;-</span> <span class="va">CPA_Approach</span><span class="op">$</span><span class="va">Targets</span></span></code></pre></div>
 <p>We now add other information required to perform the spatial
@@ -335,7 +336,7 @@ <h3 id="alternative-approaches">Alternative Approaches<a class="anchor" aria-lab
 <h4 id="percentile-approach">Percentile Approach<a class="anchor" aria-label="anchor" href="#percentile-approach"></a>
 </h4>
 <div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">target</span> <span class="op">&lt;-</span> <span class="va">datEx_species_bin</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<code class="sourceCode R"><span><span class="va">targets</span> <span class="op">&lt;-</span> <span class="va">datEx_species_bin</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_geometry.html" class="external-link">st_drop_geometry</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
@@ -343,8 +344,11 @@ <h4 id="percentile-approach">Percentile Approach<a class="anchor" aria-label="an
 <span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>target <span class="op">=</span> <span class="fl">30</span><span class="op">)</span></span>
 <span></span>
 <span><span class="va">Percentile_Approach</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/splnr_climate_percentileApproach.html">splnr_climate_percentileApproach</a></span><span class="op">(</span></span>
-<span>  featuresDF <span class="op">=</span> <span class="va">datEx_species_bin</span>,</span>
-<span>  metricDF <span class="op">=</span> <span class="va">metric_df</span>, targetsDF <span class="op">=</span> <span class="va">target</span>, direction <span class="op">=</span> <span class="op">-</span><span class="fl">1</span>, percentile <span class="op">=</span> <span class="fl">35</span></span>
+<span>  features <span class="op">=</span> <span class="va">datEx_species_bin</span>,</span>
+<span>  metric <span class="op">=</span> <span class="va">metric</span>, </span>
+<span>  targets <span class="op">=</span> <span class="va">targets</span>, </span>
+<span>  direction <span class="op">=</span> <span class="op">-</span><span class="fl">1</span>, </span>
+<span>  percentile <span class="op">=</span> <span class="fl">35</span></span>
 <span><span class="op">)</span></span>
 <span><span class="co">#&gt; [1] "Lower values mean more climate-smart areas."</span></span>
 <span></span>
@@ -356,7 +360,7 @@ <h4 id="percentile-approach">Percentile Approach<a class="anchor" aria-label="an
 <span>      <span class="op">)</span>,</span>
 <span>    join <span class="op">=</span> <span class="fu">sf</span><span class="fu">::</span><span class="va"><a href="https://r-spatial.github.io/sf/reference/geos_binary_pred.html" class="external-link">st_equals</a></span></span>
 <span>  <span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_join.html" class="external-link">st_join</a></span><span class="op">(</span><span class="va">metric_df</span>, join <span class="op">=</span> <span class="fu">sf</span><span class="fu">::</span><span class="va"><a href="https://r-spatial.github.io/sf/reference/geos_binary_pred.html" class="external-link">st_equals</a></span><span class="op">)</span></span>
+<span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_join.html" class="external-link">st_join</a></span><span class="op">(</span><span class="va">metric</span>, join <span class="op">=</span> <span class="fu">sf</span><span class="fu">::</span><span class="va"><a href="https://r-spatial.github.io/sf/reference/geos_binary_pred.html" class="external-link">st_equals</a></span><span class="op">)</span></span>
 <span></span>
 <span><span class="va">targets</span> <span class="op">&lt;-</span> <span class="va">Percentile_Approach</span><span class="op">$</span><span class="va">Targets</span></span></code></pre></div>
 <p>We now add other information required to perform the spatial
@@ -407,7 +411,7 @@ <h4 id="percentile-approach">Percentile Approach<a class="anchor" aria-label="an
 <h4 id="feature-approach">Feature Approach<a class="anchor" aria-label="anchor" href="#feature-approach"></a>
 </h4>
 <div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">target</span> <span class="op">&lt;-</span> <span class="va">datEx_species_bin</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<code class="sourceCode R"><span><span class="va">targets</span> <span class="op">&lt;-</span> <span class="va">datEx_species_bin</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_geometry.html" class="external-link">st_drop_geometry</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
@@ -415,9 +419,9 @@ <h4 id="feature-approach">Feature Approach<a class="anchor" aria-label="anchor"
 <span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>target <span class="op">=</span> <span class="fl">0.3</span><span class="op">)</span></span>
 <span></span>
 <span><span class="va">Feature_Approach</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/splnr_climate_featureApproach.html">splnr_climate_featureApproach</a></span><span class="op">(</span></span>
-<span>  featuresDF <span class="op">=</span> <span class="va">datEx_species_bin</span>,</span>
-<span>  metricDF <span class="op">=</span> <span class="va">metric_df</span>, </span>
-<span>  targetsDF <span class="op">=</span> <span class="va">target</span>, </span>
+<span>  features <span class="op">=</span> <span class="va">datEx_species_bin</span>,</span>
+<span>  metric <span class="op">=</span> <span class="va">metric</span>, </span>
+<span>  targets <span class="op">=</span> <span class="va">targets</span>, </span>
 <span>  direction <span class="op">=</span> <span class="fl">1</span></span>
 <span><span class="op">)</span></span>
 <span><span class="co">#&gt; [1] "Higher values mean more climate-smart areas."</span></span>
@@ -429,7 +433,7 @@ <h4 id="feature-approach">Feature Approach<a class="anchor" aria-label="anchor"
 <span>        <span class="fu">tidyselect</span><span class="fu">::</span><span class="fu"><a href="https://tidyselect.r-lib.org/reference/starts_with.html" class="external-link">starts_with</a></span><span class="op">(</span><span class="st">"Cost_"</span><span class="op">)</span></span>
 <span>      <span class="op">)</span>,</span>
 <span>    join <span class="op">=</span> <span class="fu">sf</span><span class="fu">::</span><span class="va"><a href="https://r-spatial.github.io/sf/reference/geos_binary_pred.html" class="external-link">st_equals</a></span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_join.html" class="external-link">st_join</a></span><span class="op">(</span><span class="va">metric_df</span>, join <span class="op">=</span> <span class="fu">sf</span><span class="fu">::</span><span class="va"><a href="https://r-spatial.github.io/sf/reference/geos_binary_pred.html" class="external-link">st_equals</a></span><span class="op">)</span></span>
+<span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_join.html" class="external-link">st_join</a></span><span class="op">(</span><span class="va">metric</span>, join <span class="op">=</span> <span class="fu">sf</span><span class="fu">::</span><span class="va"><a href="https://r-spatial.github.io/sf/reference/geos_binary_pred.html" class="external-link">st_equals</a></span><span class="op">)</span></span>
 <span></span>
 <span><span class="va">targets</span> <span class="op">&lt;-</span> <span class="va">Feature_Approach</span><span class="op">$</span><span class="va">Targets</span></span></code></pre></div>
 <p>We now add other information required to perform the spatial
diff --git a/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-16-1.png b/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-16-1.png
index 5b70649..59d6015 100644
Binary files a/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-16-1.png and b/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-16-1.png differ
diff --git a/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-20-1.png b/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-20-1.png
index 3c15f24..712983a 100644
Binary files a/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-20-1.png and b/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-20-1.png differ
diff --git a/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-24-1.png b/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-24-1.png
index 3593088..de7574f 100644
Binary files a/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-24-1.png and b/docs/articles/ClimateSmart_files/figure-html/unnamed-chunk-24-1.png differ
diff --git a/docs/articles/GlobalFishingWatch.html b/docs/articles/GlobalFishingWatch.html
index 2162a59..e865f21 100644
--- a/docs/articles/GlobalFishingWatch.html
+++ b/docs/articles/GlobalFishingWatch.html
@@ -14,8 +14,8 @@
 <link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png">
 <script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
-<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
-<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet">
 <script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Global Fishing Watch">
 </head>
 <body>
@@ -26,7 +26,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-11-1.png b/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-11-1.png
index 8dd2167..56bfda4 100644
Binary files a/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-11-1.png and b/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-11-1.png differ
diff --git a/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-14-1.png b/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-14-1.png
index db434a6..9291bbd 100644
Binary files a/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-14-1.png and b/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-14-1.png differ
diff --git a/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-16-1.png b/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-16-1.png
index f67b90c..09c4095 100644
Binary files a/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-16-1.png and b/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-16-1.png differ
diff --git a/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-8-1.png b/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-8-1.png
index 749e8da..f9735d8 100644
Binary files a/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-8-1.png and b/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-8-1.png differ
diff --git a/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-9-1.png b/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-9-1.png
index 6bf932e..7aa129e 100644
Binary files a/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-9-1.png and b/docs/articles/GlobalFishingWatch_files/figure-html/unnamed-chunk-9-1.png differ
diff --git a/docs/articles/MultipleUse.html b/docs/articles/MultipleUse.html
index 6763450..88b12c1 100644
--- a/docs/articles/MultipleUse.html
+++ b/docs/articles/MultipleUse.html
@@ -14,8 +14,8 @@
 <link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png">
 <script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
-<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
-<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet">
 <script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Spatial Planning With Zones">
 </head>
 <body>
@@ -26,7 +26,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -107,7 +107,7 @@ <h3 id="analysis-region">Analysis Region<a class="anchor" aria-label="anchor" hr
 <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">Bndry</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/splnr_get_boundary.html">splnr_get_boundary</a></span><span class="op">(</span>Limits <span class="op">=</span> <span class="va">Region</span>, Type <span class="op">=</span> <span class="va">Type</span>, cCRS <span class="op">=</span> <span class="va">cCRS</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Reading layer `ne_10m_geography_marine_polys' from data source </span></span>
-<span><span class="co">#&gt;   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/Rtmp0tUE3F/ne_10m_geography_marine_polys.shp' </span></span>
+<span><span class="co">#&gt;   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/Rtmpu338hK/ne_10m_geography_marine_polys.shp' </span></span>
 <span><span class="co">#&gt;   using driver `ESRI Shapefile'</span></span>
 <span><span class="co">#&gt; Simple feature collection with 306 features and 37 fields</span></span>
 <span><span class="co">#&gt; Geometry type: MULTIPOLYGON</span></span>
diff --git a/docs/articles/index.html b/docs/articles/index.html
index fae856d..0a87c81 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Articles • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Articles"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Articles • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Articles"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/articles/spatialplanr.html b/docs/articles/spatialplanr.html
index c619024..835e30b 100644
--- a/docs/articles/spatialplanr.html
+++ b/docs/articles/spatialplanr.html
@@ -14,8 +14,8 @@
 <link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png">
 <script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
-<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
-<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet">
 <script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="A Basic Spatial Planning Workflow">
 </head>
 <body>
@@ -26,7 +26,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -110,7 +110,7 @@ <h3 id="analysis-region">Analysis Region<a class="anchor" aria-label="anchor" hr
 <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">Bndry</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/splnr_get_boundary.html">splnr_get_boundary</a></span><span class="op">(</span>Limits <span class="op">=</span> <span class="va">Region</span>, Type <span class="op">=</span> <span class="va">Type</span>, cCRS <span class="op">=</span> <span class="va">cCRS</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Reading layer `ne_10m_geography_marine_polys' from data source </span></span>
-<span><span class="co">#&gt;   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpYDUd6r/ne_10m_geography_marine_polys.shp' </span></span>
+<span><span class="co">#&gt;   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpNdQOCt/ne_10m_geography_marine_polys.shp' </span></span>
 <span><span class="co">#&gt;   using driver `ESRI Shapefile'</span></span>
 <span><span class="co">#&gt; Simple feature collection with 306 features and 37 fields</span></span>
 <span><span class="co">#&gt; Geometry type: MULTIPOLYGON</span></span>
diff --git a/docs/authors.html b/docs/authors.html
index 1a6983d..21e37c3 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Authors and Citation • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="Authors and Citation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Authors and Citation • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="Authors and Citation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -55,13 +55,13 @@ <h2 id="citation">Citation</h2>
 
       <p>Everett J, Neubert S (2024).
 <em>spatialplanr: Help files for prioritzr Spatial Planning projects</em>.
-R package version 0.6.7, <a href="https://github.com/MathMarEcol/spatialplanr" class="external-link">https://github.com/MathMarEcol/spatialplanr</a>.
+R package version 0.6.9, <a href="https://github.com/MathMarEcol/spatialplanr" class="external-link">https://github.com/MathMarEcol/spatialplanr</a>.
 </p>
       <pre>@Manual{,
   title = {spatialplanr: Help files for prioritzr Spatial Planning projects},
   author = {Jason D. Everett and Sandra Neubert},
   year = {2024},
-  note = {R package version 0.6.7},
+  note = {R package version 0.6.9},
   url = {https://github.com/MathMarEcol/spatialplanr},
 }</pre>
     </div>
diff --git a/docs/deps/data-deps.txt b/docs/deps/data-deps.txt
index 8aa49e2..ca4dfd9 100644
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+++ b/docs/deps/data-deps.txt
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-<link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet" />
+<link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet" />
+<link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet" />
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 <script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script>
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new file mode 100644
index 0000000..151dd57
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+++ b/docs/deps/font-awesome-6.5.2/css/all.css
@@ -0,0 +1,8028 @@
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+
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+          animation-name: fa-beat-fade;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); }
+
+.fa-flip {
+  -webkit-animation-name: fa-flip;
+          animation-name: fa-flip;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out);
+          animation-timing-function: var(--fa-animation-timing, ease-in-out); }
+
+.fa-shake {
+  -webkit-animation-name: fa-shake;
+          animation-name: fa-shake;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, linear);
+          animation-timing-function: var(--fa-animation-timing, linear); }
+
+.fa-spin {
+  -webkit-animation-name: fa-spin;
+          animation-name: fa-spin;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 2s);
+          animation-duration: var(--fa-animation-duration, 2s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, linear);
+          animation-timing-function: var(--fa-animation-timing, linear); }
+
+.fa-spin-reverse {
+  --fa-animation-direction: reverse; }
+
+.fa-pulse,
+.fa-spin-pulse {
+  -webkit-animation-name: fa-spin;
+          animation-name: fa-spin;
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, steps(8));
+          animation-timing-function: var(--fa-animation-timing, steps(8)); }
+
+@media (prefers-reduced-motion: reduce) {
+  .fa-beat,
+  .fa-bounce,
+  .fa-fade,
+  .fa-beat-fade,
+  .fa-flip,
+  .fa-pulse,
+  .fa-shake,
+  .fa-spin,
+  .fa-spin-pulse {
+    -webkit-animation-delay: -1ms;
+            animation-delay: -1ms;
+    -webkit-animation-duration: 1ms;
+            animation-duration: 1ms;
+    -webkit-animation-iteration-count: 1;
+            animation-iteration-count: 1;
+    -webkit-transition-delay: 0s;
+            transition-delay: 0s;
+    -webkit-transition-duration: 0s;
+            transition-duration: 0s; } }
+
+@-webkit-keyframes fa-beat {
+  0%, 90% {
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  45% {
+    -webkit-transform: scale(var(--fa-beat-scale, 1.25));
+            transform: scale(var(--fa-beat-scale, 1.25)); } }
+
+@keyframes fa-beat {
+  0%, 90% {
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  45% {
+    -webkit-transform: scale(var(--fa-beat-scale, 1.25));
+            transform: scale(var(--fa-beat-scale, 1.25)); } }
+
+@-webkit-keyframes fa-bounce {
+  0% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  10% {
+    -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0);
+            transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); }
+  30% {
+    -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em));
+            transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); }
+  50% {
+    -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0);
+            transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); }
+  57% {
+    -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em));
+            transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); }
+  64% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  100% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); } }
+
+@keyframes fa-bounce {
+  0% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  10% {
+    -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0);
+            transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); }
+  30% {
+    -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em));
+            transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); }
+  50% {
+    -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0);
+            transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); }
+  57% {
+    -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em));
+            transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); }
+  64% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  100% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); } }
+
+@-webkit-keyframes fa-fade {
+  50% {
+    opacity: var(--fa-fade-opacity, 0.4); } }
+
+@keyframes fa-fade {
+  50% {
+    opacity: var(--fa-fade-opacity, 0.4); } }
+
+@-webkit-keyframes fa-beat-fade {
+  0%, 100% {
+    opacity: var(--fa-beat-fade-opacity, 0.4);
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  50% {
+    opacity: 1;
+    -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125));
+            transform: scale(var(--fa-beat-fade-scale, 1.125)); } }
+
+@keyframes fa-beat-fade {
+  0%, 100% {
+    opacity: var(--fa-beat-fade-opacity, 0.4);
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  50% {
+    opacity: 1;
+    -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125));
+            transform: scale(var(--fa-beat-fade-scale, 1.125)); } }
+
+@-webkit-keyframes fa-flip {
+  50% {
+    -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg));
+            transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } }
+
+@keyframes fa-flip {
+  50% {
+    -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg));
+            transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } }
+
+@-webkit-keyframes fa-shake {
+  0% {
+    -webkit-transform: rotate(-15deg);
+            transform: rotate(-15deg); }
+  4% {
+    -webkit-transform: rotate(15deg);
+            transform: rotate(15deg); }
+  8%, 24% {
+    -webkit-transform: rotate(-18deg);
+            transform: rotate(-18deg); }
+  12%, 28% {
+    -webkit-transform: rotate(18deg);
+            transform: rotate(18deg); }
+  16% {
+    -webkit-transform: rotate(-22deg);
+            transform: rotate(-22deg); }
+  20% {
+    -webkit-transform: rotate(22deg);
+            transform: rotate(22deg); }
+  32% {
+    -webkit-transform: rotate(-12deg);
+            transform: rotate(-12deg); }
+  36% {
+    -webkit-transform: rotate(12deg);
+            transform: rotate(12deg); }
+  40%, 100% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); } }
+
+@keyframes fa-shake {
+  0% {
+    -webkit-transform: rotate(-15deg);
+            transform: rotate(-15deg); }
+  4% {
+    -webkit-transform: rotate(15deg);
+            transform: rotate(15deg); }
+  8%, 24% {
+    -webkit-transform: rotate(-18deg);
+            transform: rotate(-18deg); }
+  12%, 28% {
+    -webkit-transform: rotate(18deg);
+            transform: rotate(18deg); }
+  16% {
+    -webkit-transform: rotate(-22deg);
+            transform: rotate(-22deg); }
+  20% {
+    -webkit-transform: rotate(22deg);
+            transform: rotate(22deg); }
+  32% {
+    -webkit-transform: rotate(-12deg);
+            transform: rotate(-12deg); }
+  36% {
+    -webkit-transform: rotate(12deg);
+            transform: rotate(12deg); }
+  40%, 100% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); } }
+
+@-webkit-keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); }
+  100% {
+    -webkit-transform: rotate(360deg);
+            transform: rotate(360deg); } }
+
+@keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); }
+  100% {
+    -webkit-transform: rotate(360deg);
+            transform: rotate(360deg); } }
+
+.fa-rotate-90 {
+  -webkit-transform: rotate(90deg);
+          transform: rotate(90deg); }
+
+.fa-rotate-180 {
+  -webkit-transform: rotate(180deg);
+          transform: rotate(180deg); }
+
+.fa-rotate-270 {
+  -webkit-transform: rotate(270deg);
+          transform: rotate(270deg); }
+
+.fa-flip-horizontal {
+  -webkit-transform: scale(-1, 1);
+          transform: scale(-1, 1); }
+
+.fa-flip-vertical {
+  -webkit-transform: scale(1, -1);
+          transform: scale(1, -1); }
+
+.fa-flip-both,
+.fa-flip-horizontal.fa-flip-vertical {
+  -webkit-transform: scale(-1, -1);
+          transform: scale(-1, -1); }
+
+.fa-rotate-by {
+  -webkit-transform: rotate(var(--fa-rotate-angle, 0));
+          transform: rotate(var(--fa-rotate-angle, 0)); }
+
+.fa-stack {
+  display: inline-block;
+  height: 2em;
+  line-height: 2em;
+  position: relative;
+  vertical-align: middle;
+  width: 2.5em; }
+
+.fa-stack-1x,
+.fa-stack-2x {
+  left: 0;
+  position: absolute;
+  text-align: center;
+  width: 100%;
+  z-index: var(--fa-stack-z-index, auto); }
+
+.fa-stack-1x {
+  line-height: inherit; }
+
+.fa-stack-2x {
+  font-size: 2em; }
+
+.fa-inverse {
+  color: var(--fa-inverse, #fff); }
+
+/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
+readers do not read off random characters that represent icons */
+
+.fa-0::before {
+  content: "\30"; }
+
+.fa-1::before {
+  content: "\31"; }
+
+.fa-2::before {
+  content: "\32"; }
+
+.fa-3::before {
+  content: "\33"; }
+
+.fa-4::before {
+  content: "\34"; }
+
+.fa-5::before {
+  content: "\35"; }
+
+.fa-6::before {
+  content: "\36"; }
+
+.fa-7::before {
+  content: "\37"; }
+
+.fa-8::before {
+  content: "\38"; }
+
+.fa-9::before {
+  content: "\39"; }
+
+.fa-fill-drip::before {
+  content: "\f576"; }
+
+.fa-arrows-to-circle::before {
+  content: "\e4bd"; }
+
+.fa-circle-chevron-right::before {
+  content: "\f138"; }
+
+.fa-chevron-circle-right::before {
+  content: "\f138"; }
+
+.fa-at::before {
+  content: "\40"; }
+
+.fa-trash-can::before {
+  content: "\f2ed"; }
+
+.fa-trash-alt::before {
+  content: "\f2ed"; }
+
+.fa-text-height::before {
+  content: "\f034"; }
+
+.fa-user-xmark::before {
+  content: "\f235"; }
+
+.fa-user-times::before {
+  content: "\f235"; }
+
+.fa-stethoscope::before {
+  content: "\f0f1"; }
+
+.fa-message::before {
+  content: "\f27a"; }
+
+.fa-comment-alt::before {
+  content: "\f27a"; }
+
+.fa-info::before {
+  content: "\f129"; }
+
+.fa-down-left-and-up-right-to-center::before {
+  content: "\f422"; }
+
+.fa-compress-alt::before {
+  content: "\f422"; }
+
+.fa-explosion::before {
+  content: "\e4e9"; }
+
+.fa-file-lines::before {
+  content: "\f15c"; }
+
+.fa-file-alt::before {
+  content: "\f15c"; }
+
+.fa-file-text::before {
+  content: "\f15c"; }
+
+.fa-wave-square::before {
+  content: "\f83e"; }
+
+.fa-ring::before {
+  content: "\f70b"; }
+
+.fa-building-un::before {
+  content: "\e4d9"; }
+
+.fa-dice-three::before {
+  content: "\f527"; }
+
+.fa-calendar-days::before {
+  content: "\f073"; }
+
+.fa-calendar-alt::before {
+  content: "\f073"; }
+
+.fa-anchor-circle-check::before {
+  content: "\e4aa"; }
+
+.fa-building-circle-arrow-right::before {
+  content: "\e4d1"; }
+
+.fa-volleyball::before {
+  content: "\f45f"; }
+
+.fa-volleyball-ball::before {
+  content: "\f45f"; }
+
+.fa-arrows-up-to-line::before {
+  content: "\e4c2"; }
+
+.fa-sort-down::before {
+  content: "\f0dd"; }
+
+.fa-sort-desc::before {
+  content: "\f0dd"; }
+
+.fa-circle-minus::before {
+  content: "\f056"; }
+
+.fa-minus-circle::before {
+  content: "\f056"; }
+
+.fa-door-open::before {
+  content: "\f52b"; }
+
+.fa-right-from-bracket::before {
+  content: "\f2f5"; }
+
+.fa-sign-out-alt::before {
+  content: "\f2f5"; }
+
+.fa-atom::before {
+  content: "\f5d2"; }
+
+.fa-soap::before {
+  content: "\e06e"; }
+
+.fa-icons::before {
+  content: "\f86d"; }
+
+.fa-heart-music-camera-bolt::before {
+  content: "\f86d"; }
+
+.fa-microphone-lines-slash::before {
+  content: "\f539"; }
+
+.fa-microphone-alt-slash::before {
+  content: "\f539"; }
+
+.fa-bridge-circle-check::before {
+  content: "\e4c9"; }
+
+.fa-pump-medical::before {
+  content: "\e06a"; }
+
+.fa-fingerprint::before {
+  content: "\f577"; }
+
+.fa-hand-point-right::before {
+  content: "\f0a4"; }
+
+.fa-magnifying-glass-location::before {
+  content: "\f689"; }
+
+.fa-search-location::before {
+  content: "\f689"; }
+
+.fa-forward-step::before {
+  content: "\f051"; }
+
+.fa-step-forward::before {
+  content: "\f051"; }
+
+.fa-face-smile-beam::before {
+  content: "\f5b8"; }
+
+.fa-smile-beam::before {
+  content: "\f5b8"; }
+
+.fa-flag-checkered::before {
+  content: "\f11e"; }
+
+.fa-football::before {
+  content: "\f44e"; }
+
+.fa-football-ball::before {
+  content: "\f44e"; }
+
+.fa-school-circle-exclamation::before {
+  content: "\e56c"; }
+
+.fa-crop::before {
+  content: "\f125"; }
+
+.fa-angles-down::before {
+  content: "\f103"; }
+
+.fa-angle-double-down::before {
+  content: "\f103"; }
+
+.fa-users-rectangle::before {
+  content: "\e594"; }
+
+.fa-people-roof::before {
+  content: "\e537"; }
+
+.fa-people-line::before {
+  content: "\e534"; }
+
+.fa-beer-mug-empty::before {
+  content: "\f0fc"; }
+
+.fa-beer::before {
+  content: "\f0fc"; }
+
+.fa-diagram-predecessor::before {
+  content: "\e477"; }
+
+.fa-arrow-up-long::before {
+  content: "\f176"; }
+
+.fa-long-arrow-up::before {
+  content: "\f176"; }
+
+.fa-fire-flame-simple::before {
+  content: "\f46a"; }
+
+.fa-burn::before {
+  content: "\f46a"; }
+
+.fa-person::before {
+  content: "\f183"; }
+
+.fa-male::before {
+  content: "\f183"; }
+
+.fa-laptop::before {
+  content: "\f109"; }
+
+.fa-file-csv::before {
+  content: "\f6dd"; }
+
+.fa-menorah::before {
+  content: "\f676"; }
+
+.fa-truck-plane::before {
+  content: "\e58f"; }
+
+.fa-record-vinyl::before {
+  content: "\f8d9"; }
+
+.fa-face-grin-stars::before {
+  content: "\f587"; }
+
+.fa-grin-stars::before {
+  content: "\f587"; }
+
+.fa-bong::before {
+  content: "\f55c"; }
+
+.fa-spaghetti-monster-flying::before {
+  content: "\f67b"; }
+
+.fa-pastafarianism::before {
+  content: "\f67b"; }
+
+.fa-arrow-down-up-across-line::before {
+  content: "\e4af"; }
+
+.fa-spoon::before {
+  content: "\f2e5"; }
+
+.fa-utensil-spoon::before {
+  content: "\f2e5"; }
+
+.fa-jar-wheat::before {
+  content: "\e517"; }
+
+.fa-envelopes-bulk::before {
+  content: "\f674"; }
+
+.fa-mail-bulk::before {
+  content: "\f674"; }
+
+.fa-file-circle-exclamation::before {
+  content: "\e4eb"; }
+
+.fa-circle-h::before {
+  content: "\f47e"; }
+
+.fa-hospital-symbol::before {
+  content: "\f47e"; }
+
+.fa-pager::before {
+  content: "\f815"; }
+
+.fa-address-book::before {
+  content: "\f2b9"; }
+
+.fa-contact-book::before {
+  content: "\f2b9"; }
+
+.fa-strikethrough::before {
+  content: "\f0cc"; }
+
+.fa-k::before {
+  content: "\4b"; }
+
+.fa-landmark-flag::before {
+  content: "\e51c"; }
+
+.fa-pencil::before {
+  content: "\f303"; }
+
+.fa-pencil-alt::before {
+  content: "\f303"; }
+
+.fa-backward::before {
+  content: "\f04a"; }
+
+.fa-caret-right::before {
+  content: "\f0da"; }
+
+.fa-comments::before {
+  content: "\f086"; }
+
+.fa-paste::before {
+  content: "\f0ea"; }
+
+.fa-file-clipboard::before {
+  content: "\f0ea"; }
+
+.fa-code-pull-request::before {
+  content: "\e13c"; }
+
+.fa-clipboard-list::before {
+  content: "\f46d"; }
+
+.fa-truck-ramp-box::before {
+  content: "\f4de"; }
+
+.fa-truck-loading::before {
+  content: "\f4de"; }
+
+.fa-user-check::before {
+  content: "\f4fc"; }
+
+.fa-vial-virus::before {
+  content: "\e597"; }
+
+.fa-sheet-plastic::before {
+  content: "\e571"; }
+
+.fa-blog::before {
+  content: "\f781"; }
+
+.fa-user-ninja::before {
+  content: "\f504"; }
+
+.fa-person-arrow-up-from-line::before {
+  content: "\e539"; }
+
+.fa-scroll-torah::before {
+  content: "\f6a0"; }
+
+.fa-torah::before {
+  content: "\f6a0"; }
+
+.fa-broom-ball::before {
+  content: "\f458"; }
+
+.fa-quidditch::before {
+  content: "\f458"; }
+
+.fa-quidditch-broom-ball::before {
+  content: "\f458"; }
+
+.fa-toggle-off::before {
+  content: "\f204"; }
+
+.fa-box-archive::before {
+  content: "\f187"; }
+
+.fa-archive::before {
+  content: "\f187"; }
+
+.fa-person-drowning::before {
+  content: "\e545"; }
+
+.fa-arrow-down-9-1::before {
+  content: "\f886"; }
+
+.fa-sort-numeric-desc::before {
+  content: "\f886"; }
+
+.fa-sort-numeric-down-alt::before {
+  content: "\f886"; }
+
+.fa-face-grin-tongue-squint::before {
+  content: "\f58a"; }
+
+.fa-grin-tongue-squint::before {
+  content: "\f58a"; }
+
+.fa-spray-can::before {
+  content: "\f5bd"; }
+
+.fa-truck-monster::before {
+  content: "\f63b"; }
+
+.fa-w::before {
+  content: "\57"; }
+
+.fa-earth-africa::before {
+  content: "\f57c"; }
+
+.fa-globe-africa::before {
+  content: "\f57c"; }
+
+.fa-rainbow::before {
+  content: "\f75b"; }
+
+.fa-circle-notch::before {
+  content: "\f1ce"; }
+
+.fa-tablet-screen-button::before {
+  content: "\f3fa"; }
+
+.fa-tablet-alt::before {
+  content: "\f3fa"; }
+
+.fa-paw::before {
+  content: "\f1b0"; }
+
+.fa-cloud::before {
+  content: "\f0c2"; }
+
+.fa-trowel-bricks::before {
+  content: "\e58a"; }
+
+.fa-face-flushed::before {
+  content: "\f579"; }
+
+.fa-flushed::before {
+  content: "\f579"; }
+
+.fa-hospital-user::before {
+  content: "\f80d"; }
+
+.fa-tent-arrow-left-right::before {
+  content: "\e57f"; }
+
+.fa-gavel::before {
+  content: "\f0e3"; }
+
+.fa-legal::before {
+  content: "\f0e3"; }
+
+.fa-binoculars::before {
+  content: "\f1e5"; }
+
+.fa-microphone-slash::before {
+  content: "\f131"; }
+
+.fa-box-tissue::before {
+  content: "\e05b"; }
+
+.fa-motorcycle::before {
+  content: "\f21c"; }
+
+.fa-bell-concierge::before {
+  content: "\f562"; }
+
+.fa-concierge-bell::before {
+  content: "\f562"; }
+
+.fa-pen-ruler::before {
+  content: "\f5ae"; }
+
+.fa-pencil-ruler::before {
+  content: "\f5ae"; }
+
+.fa-people-arrows::before {
+  content: "\e068"; }
+
+.fa-people-arrows-left-right::before {
+  content: "\e068"; }
+
+.fa-mars-and-venus-burst::before {
+  content: "\e523"; }
+
+.fa-square-caret-right::before {
+  content: "\f152"; }
+
+.fa-caret-square-right::before {
+  content: "\f152"; }
+
+.fa-scissors::before {
+  content: "\f0c4"; }
+
+.fa-cut::before {
+  content: "\f0c4"; }
+
+.fa-sun-plant-wilt::before {
+  content: "\e57a"; }
+
+.fa-toilets-portable::before {
+  content: "\e584"; }
+
+.fa-hockey-puck::before {
+  content: "\f453"; }
+
+.fa-table::before {
+  content: "\f0ce"; }
+
+.fa-magnifying-glass-arrow-right::before {
+  content: "\e521"; }
+
+.fa-tachograph-digital::before {
+  content: "\f566"; }
+
+.fa-digital-tachograph::before {
+  content: "\f566"; }
+
+.fa-users-slash::before {
+  content: "\e073"; }
+
+.fa-clover::before {
+  content: "\e139"; }
+
+.fa-reply::before {
+  content: "\f3e5"; }
+
+.fa-mail-reply::before {
+  content: "\f3e5"; }
+
+.fa-star-and-crescent::before {
+  content: "\f699"; }
+
+.fa-house-fire::before {
+  content: "\e50c"; }
+
+.fa-square-minus::before {
+  content: "\f146"; }
+
+.fa-minus-square::before {
+  content: "\f146"; }
+
+.fa-helicopter::before {
+  content: "\f533"; }
+
+.fa-compass::before {
+  content: "\f14e"; }
+
+.fa-square-caret-down::before {
+  content: "\f150"; }
+
+.fa-caret-square-down::before {
+  content: "\f150"; }
+
+.fa-file-circle-question::before {
+  content: "\e4ef"; }
+
+.fa-laptop-code::before {
+  content: "\f5fc"; }
+
+.fa-swatchbook::before {
+  content: "\f5c3"; }
+
+.fa-prescription-bottle::before {
+  content: "\f485"; }
+
+.fa-bars::before {
+  content: "\f0c9"; }
+
+.fa-navicon::before {
+  content: "\f0c9"; }
+
+.fa-people-group::before {
+  content: "\e533"; }
+
+.fa-hourglass-end::before {
+  content: "\f253"; }
+
+.fa-hourglass-3::before {
+  content: "\f253"; }
+
+.fa-heart-crack::before {
+  content: "\f7a9"; }
+
+.fa-heart-broken::before {
+  content: "\f7a9"; }
+
+.fa-square-up-right::before {
+  content: "\f360"; }
+
+.fa-external-link-square-alt::before {
+  content: "\f360"; }
+
+.fa-face-kiss-beam::before {
+  content: "\f597"; }
+
+.fa-kiss-beam::before {
+  content: "\f597"; }
+
+.fa-film::before {
+  content: "\f008"; }
+
+.fa-ruler-horizontal::before {
+  content: "\f547"; }
+
+.fa-people-robbery::before {
+  content: "\e536"; }
+
+.fa-lightbulb::before {
+  content: "\f0eb"; }
+
+.fa-caret-left::before {
+  content: "\f0d9"; }
+
+.fa-circle-exclamation::before {
+  content: "\f06a"; }
+
+.fa-exclamation-circle::before {
+  content: "\f06a"; }
+
+.fa-school-circle-xmark::before {
+  content: "\e56d"; }
+
+.fa-arrow-right-from-bracket::before {
+  content: "\f08b"; }
+
+.fa-sign-out::before {
+  content: "\f08b"; }
+
+.fa-circle-chevron-down::before {
+  content: "\f13a"; }
+
+.fa-chevron-circle-down::before {
+  content: "\f13a"; }
+
+.fa-unlock-keyhole::before {
+  content: "\f13e"; }
+
+.fa-unlock-alt::before {
+  content: "\f13e"; }
+
+.fa-cloud-showers-heavy::before {
+  content: "\f740"; }
+
+.fa-headphones-simple::before {
+  content: "\f58f"; }
+
+.fa-headphones-alt::before {
+  content: "\f58f"; }
+
+.fa-sitemap::before {
+  content: "\f0e8"; }
+
+.fa-circle-dollar-to-slot::before {
+  content: "\f4b9"; }
+
+.fa-donate::before {
+  content: "\f4b9"; }
+
+.fa-memory::before {
+  content: "\f538"; }
+
+.fa-road-spikes::before {
+  content: "\e568"; }
+
+.fa-fire-burner::before {
+  content: "\e4f1"; }
+
+.fa-flag::before {
+  content: "\f024"; }
+
+.fa-hanukiah::before {
+  content: "\f6e6"; }
+
+.fa-feather::before {
+  content: "\f52d"; }
+
+.fa-volume-low::before {
+  content: "\f027"; }
+
+.fa-volume-down::before {
+  content: "\f027"; }
+
+.fa-comment-slash::before {
+  content: "\f4b3"; }
+
+.fa-cloud-sun-rain::before {
+  content: "\f743"; }
+
+.fa-compress::before {
+  content: "\f066"; }
+
+.fa-wheat-awn::before {
+  content: "\e2cd"; }
+
+.fa-wheat-alt::before {
+  content: "\e2cd"; }
+
+.fa-ankh::before {
+  content: "\f644"; }
+
+.fa-hands-holding-child::before {
+  content: "\e4fa"; }
+
+.fa-asterisk::before {
+  content: "\2a"; }
+
+.fa-square-check::before {
+  content: "\f14a"; }
+
+.fa-check-square::before {
+  content: "\f14a"; }
+
+.fa-peseta-sign::before {
+  content: "\e221"; }
+
+.fa-heading::before {
+  content: "\f1dc"; }
+
+.fa-header::before {
+  content: "\f1dc"; }
+
+.fa-ghost::before {
+  content: "\f6e2"; }
+
+.fa-list::before {
+  content: "\f03a"; }
+
+.fa-list-squares::before {
+  content: "\f03a"; }
+
+.fa-square-phone-flip::before {
+  content: "\f87b"; }
+
+.fa-phone-square-alt::before {
+  content: "\f87b"; }
+
+.fa-cart-plus::before {
+  content: "\f217"; }
+
+.fa-gamepad::before {
+  content: "\f11b"; }
+
+.fa-circle-dot::before {
+  content: "\f192"; }
+
+.fa-dot-circle::before {
+  content: "\f192"; }
+
+.fa-face-dizzy::before {
+  content: "\f567"; }
+
+.fa-dizzy::before {
+  content: "\f567"; }
+
+.fa-egg::before {
+  content: "\f7fb"; }
+
+.fa-house-medical-circle-xmark::before {
+  content: "\e513"; }
+
+.fa-campground::before {
+  content: "\f6bb"; }
+
+.fa-folder-plus::before {
+  content: "\f65e"; }
+
+.fa-futbol::before {
+  content: "\f1e3"; }
+
+.fa-futbol-ball::before {
+  content: "\f1e3"; }
+
+.fa-soccer-ball::before {
+  content: "\f1e3"; }
+
+.fa-paintbrush::before {
+  content: "\f1fc"; }
+
+.fa-paint-brush::before {
+  content: "\f1fc"; }
+
+.fa-lock::before {
+  content: "\f023"; }
+
+.fa-gas-pump::before {
+  content: "\f52f"; }
+
+.fa-hot-tub-person::before {
+  content: "\f593"; }
+
+.fa-hot-tub::before {
+  content: "\f593"; }
+
+.fa-map-location::before {
+  content: "\f59f"; }
+
+.fa-map-marked::before {
+  content: "\f59f"; }
+
+.fa-house-flood-water::before {
+  content: "\e50e"; }
+
+.fa-tree::before {
+  content: "\f1bb"; }
+
+.fa-bridge-lock::before {
+  content: "\e4cc"; }
+
+.fa-sack-dollar::before {
+  content: "\f81d"; }
+
+.fa-pen-to-square::before {
+  content: "\f044"; }
+
+.fa-edit::before {
+  content: "\f044"; }
+
+.fa-car-side::before {
+  content: "\f5e4"; }
+
+.fa-share-nodes::before {
+  content: "\f1e0"; }
+
+.fa-share-alt::before {
+  content: "\f1e0"; }
+
+.fa-heart-circle-minus::before {
+  content: "\e4ff"; }
+
+.fa-hourglass-half::before {
+  content: "\f252"; }
+
+.fa-hourglass-2::before {
+  content: "\f252"; }
+
+.fa-microscope::before {
+  content: "\f610"; }
+
+.fa-sink::before {
+  content: "\e06d"; }
+
+.fa-bag-shopping::before {
+  content: "\f290"; }
+
+.fa-shopping-bag::before {
+  content: "\f290"; }
+
+.fa-arrow-down-z-a::before {
+  content: "\f881"; }
+
+.fa-sort-alpha-desc::before {
+  content: "\f881"; }
+
+.fa-sort-alpha-down-alt::before {
+  content: "\f881"; }
+
+.fa-mitten::before {
+  content: "\f7b5"; }
+
+.fa-person-rays::before {
+  content: "\e54d"; }
+
+.fa-users::before {
+  content: "\f0c0"; }
+
+.fa-eye-slash::before {
+  content: "\f070"; }
+
+.fa-flask-vial::before {
+  content: "\e4f3"; }
+
+.fa-hand::before {
+  content: "\f256"; }
+
+.fa-hand-paper::before {
+  content: "\f256"; }
+
+.fa-om::before {
+  content: "\f679"; }
+
+.fa-worm::before {
+  content: "\e599"; }
+
+.fa-house-circle-xmark::before {
+  content: "\e50b"; }
+
+.fa-plug::before {
+  content: "\f1e6"; }
+
+.fa-chevron-up::before {
+  content: "\f077"; }
+
+.fa-hand-spock::before {
+  content: "\f259"; }
+
+.fa-stopwatch::before {
+  content: "\f2f2"; }
+
+.fa-face-kiss::before {
+  content: "\f596"; }
+
+.fa-kiss::before {
+  content: "\f596"; }
+
+.fa-bridge-circle-xmark::before {
+  content: "\e4cb"; }
+
+.fa-face-grin-tongue::before {
+  content: "\f589"; }
+
+.fa-grin-tongue::before {
+  content: "\f589"; }
+
+.fa-chess-bishop::before {
+  content: "\f43a"; }
+
+.fa-face-grin-wink::before {
+  content: "\f58c"; }
+
+.fa-grin-wink::before {
+  content: "\f58c"; }
+
+.fa-ear-deaf::before {
+  content: "\f2a4"; }
+
+.fa-deaf::before {
+  content: "\f2a4"; }
+
+.fa-deafness::before {
+  content: "\f2a4"; }
+
+.fa-hard-of-hearing::before {
+  content: "\f2a4"; }
+
+.fa-road-circle-check::before {
+  content: "\e564"; }
+
+.fa-dice-five::before {
+  content: "\f523"; }
+
+.fa-square-rss::before {
+  content: "\f143"; }
+
+.fa-rss-square::before {
+  content: "\f143"; }
+
+.fa-land-mine-on::before {
+  content: "\e51b"; }
+
+.fa-i-cursor::before {
+  content: "\f246"; }
+
+.fa-stamp::before {
+  content: "\f5bf"; }
+
+.fa-stairs::before {
+  content: "\e289"; }
+
+.fa-i::before {
+  content: "\49"; }
+
+.fa-hryvnia-sign::before {
+  content: "\f6f2"; }
+
+.fa-hryvnia::before {
+  content: "\f6f2"; }
+
+.fa-pills::before {
+  content: "\f484"; }
+
+.fa-face-grin-wide::before {
+  content: "\f581"; }
+
+.fa-grin-alt::before {
+  content: "\f581"; }
+
+.fa-tooth::before {
+  content: "\f5c9"; }
+
+.fa-v::before {
+  content: "\56"; }
+
+.fa-bangladeshi-taka-sign::before {
+  content: "\e2e6"; }
+
+.fa-bicycle::before {
+  content: "\f206"; }
+
+.fa-staff-snake::before {
+  content: "\e579"; }
+
+.fa-rod-asclepius::before {
+  content: "\e579"; }
+
+.fa-rod-snake::before {
+  content: "\e579"; }
+
+.fa-staff-aesculapius::before {
+  content: "\e579"; }
+
+.fa-head-side-cough-slash::before {
+  content: "\e062"; }
+
+.fa-truck-medical::before {
+  content: "\f0f9"; }
+
+.fa-ambulance::before {
+  content: "\f0f9"; }
+
+.fa-wheat-awn-circle-exclamation::before {
+  content: "\e598"; }
+
+.fa-snowman::before {
+  content: "\f7d0"; }
+
+.fa-mortar-pestle::before {
+  content: "\f5a7"; }
+
+.fa-road-barrier::before {
+  content: "\e562"; }
+
+.fa-school::before {
+  content: "\f549"; }
+
+.fa-igloo::before {
+  content: "\f7ae"; }
+
+.fa-joint::before {
+  content: "\f595"; }
+
+.fa-angle-right::before {
+  content: "\f105"; }
+
+.fa-horse::before {
+  content: "\f6f0"; }
+
+.fa-q::before {
+  content: "\51"; }
+
+.fa-g::before {
+  content: "\47"; }
+
+.fa-notes-medical::before {
+  content: "\f481"; }
+
+.fa-temperature-half::before {
+  content: "\f2c9"; }
+
+.fa-temperature-2::before {
+  content: "\f2c9"; }
+
+.fa-thermometer-2::before {
+  content: "\f2c9"; }
+
+.fa-thermometer-half::before {
+  content: "\f2c9"; }
+
+.fa-dong-sign::before {
+  content: "\e169"; }
+
+.fa-capsules::before {
+  content: "\f46b"; }
+
+.fa-poo-storm::before {
+  content: "\f75a"; }
+
+.fa-poo-bolt::before {
+  content: "\f75a"; }
+
+.fa-face-frown-open::before {
+  content: "\f57a"; }
+
+.fa-frown-open::before {
+  content: "\f57a"; }
+
+.fa-hand-point-up::before {
+  content: "\f0a6"; }
+
+.fa-money-bill::before {
+  content: "\f0d6"; }
+
+.fa-bookmark::before {
+  content: "\f02e"; }
+
+.fa-align-justify::before {
+  content: "\f039"; }
+
+.fa-umbrella-beach::before {
+  content: "\f5ca"; }
+
+.fa-helmet-un::before {
+  content: "\e503"; }
+
+.fa-bullseye::before {
+  content: "\f140"; }
+
+.fa-bacon::before {
+  content: "\f7e5"; }
+
+.fa-hand-point-down::before {
+  content: "\f0a7"; }
+
+.fa-arrow-up-from-bracket::before {
+  content: "\e09a"; }
+
+.fa-folder::before {
+  content: "\f07b"; }
+
+.fa-folder-blank::before {
+  content: "\f07b"; }
+
+.fa-file-waveform::before {
+  content: "\f478"; }
+
+.fa-file-medical-alt::before {
+  content: "\f478"; }
+
+.fa-radiation::before {
+  content: "\f7b9"; }
+
+.fa-chart-simple::before {
+  content: "\e473"; }
+
+.fa-mars-stroke::before {
+  content: "\f229"; }
+
+.fa-vial::before {
+  content: "\f492"; }
+
+.fa-gauge::before {
+  content: "\f624"; }
+
+.fa-dashboard::before {
+  content: "\f624"; }
+
+.fa-gauge-med::before {
+  content: "\f624"; }
+
+.fa-tachometer-alt-average::before {
+  content: "\f624"; }
+
+.fa-wand-magic-sparkles::before {
+  content: "\e2ca"; }
+
+.fa-magic-wand-sparkles::before {
+  content: "\e2ca"; }
+
+.fa-e::before {
+  content: "\45"; }
+
+.fa-pen-clip::before {
+  content: "\f305"; }
+
+.fa-pen-alt::before {
+  content: "\f305"; }
+
+.fa-bridge-circle-exclamation::before {
+  content: "\e4ca"; }
+
+.fa-user::before {
+  content: "\f007"; }
+
+.fa-school-circle-check::before {
+  content: "\e56b"; }
+
+.fa-dumpster::before {
+  content: "\f793"; }
+
+.fa-van-shuttle::before {
+  content: "\f5b6"; }
+
+.fa-shuttle-van::before {
+  content: "\f5b6"; }
+
+.fa-building-user::before {
+  content: "\e4da"; }
+
+.fa-square-caret-left::before {
+  content: "\f191"; }
+
+.fa-caret-square-left::before {
+  content: "\f191"; }
+
+.fa-highlighter::before {
+  content: "\f591"; }
+
+.fa-key::before {
+  content: "\f084"; }
+
+.fa-bullhorn::before {
+  content: "\f0a1"; }
+
+.fa-globe::before {
+  content: "\f0ac"; }
+
+.fa-synagogue::before {
+  content: "\f69b"; }
+
+.fa-person-half-dress::before {
+  content: "\e548"; }
+
+.fa-road-bridge::before {
+  content: "\e563"; }
+
+.fa-location-arrow::before {
+  content: "\f124"; }
+
+.fa-c::before {
+  content: "\43"; }
+
+.fa-tablet-button::before {
+  content: "\f10a"; }
+
+.fa-building-lock::before {
+  content: "\e4d6"; }
+
+.fa-pizza-slice::before {
+  content: "\f818"; }
+
+.fa-money-bill-wave::before {
+  content: "\f53a"; }
+
+.fa-chart-area::before {
+  content: "\f1fe"; }
+
+.fa-area-chart::before {
+  content: "\f1fe"; }
+
+.fa-house-flag::before {
+  content: "\e50d"; }
+
+.fa-person-circle-minus::before {
+  content: "\e540"; }
+
+.fa-ban::before {
+  content: "\f05e"; }
+
+.fa-cancel::before {
+  content: "\f05e"; }
+
+.fa-camera-rotate::before {
+  content: "\e0d8"; }
+
+.fa-spray-can-sparkles::before {
+  content: "\f5d0"; }
+
+.fa-air-freshener::before {
+  content: "\f5d0"; }
+
+.fa-star::before {
+  content: "\f005"; }
+
+.fa-repeat::before {
+  content: "\f363"; }
+
+.fa-cross::before {
+  content: "\f654"; }
+
+.fa-box::before {
+  content: "\f466"; }
+
+.fa-venus-mars::before {
+  content: "\f228"; }
+
+.fa-arrow-pointer::before {
+  content: "\f245"; }
+
+.fa-mouse-pointer::before {
+  content: "\f245"; }
+
+.fa-maximize::before {
+  content: "\f31e"; }
+
+.fa-expand-arrows-alt::before {
+  content: "\f31e"; }
+
+.fa-charging-station::before {
+  content: "\f5e7"; }
+
+.fa-shapes::before {
+  content: "\f61f"; }
+
+.fa-triangle-circle-square::before {
+  content: "\f61f"; }
+
+.fa-shuffle::before {
+  content: "\f074"; }
+
+.fa-random::before {
+  content: "\f074"; }
+
+.fa-person-running::before {
+  content: "\f70c"; }
+
+.fa-running::before {
+  content: "\f70c"; }
+
+.fa-mobile-retro::before {
+  content: "\e527"; }
+
+.fa-grip-lines-vertical::before {
+  content: "\f7a5"; }
+
+.fa-spider::before {
+  content: "\f717"; }
+
+.fa-hands-bound::before {
+  content: "\e4f9"; }
+
+.fa-file-invoice-dollar::before {
+  content: "\f571"; }
+
+.fa-plane-circle-exclamation::before {
+  content: "\e556"; }
+
+.fa-x-ray::before {
+  content: "\f497"; }
+
+.fa-spell-check::before {
+  content: "\f891"; }
+
+.fa-slash::before {
+  content: "\f715"; }
+
+.fa-computer-mouse::before {
+  content: "\f8cc"; }
+
+.fa-mouse::before {
+  content: "\f8cc"; }
+
+.fa-arrow-right-to-bracket::before {
+  content: "\f090"; }
+
+.fa-sign-in::before {
+  content: "\f090"; }
+
+.fa-shop-slash::before {
+  content: "\e070"; }
+
+.fa-store-alt-slash::before {
+  content: "\e070"; }
+
+.fa-server::before {
+  content: "\f233"; }
+
+.fa-virus-covid-slash::before {
+  content: "\e4a9"; }
+
+.fa-shop-lock::before {
+  content: "\e4a5"; }
+
+.fa-hourglass-start::before {
+  content: "\f251"; }
+
+.fa-hourglass-1::before {
+  content: "\f251"; }
+
+.fa-blender-phone::before {
+  content: "\f6b6"; }
+
+.fa-building-wheat::before {
+  content: "\e4db"; }
+
+.fa-person-breastfeeding::before {
+  content: "\e53a"; }
+
+.fa-right-to-bracket::before {
+  content: "\f2f6"; }
+
+.fa-sign-in-alt::before {
+  content: "\f2f6"; }
+
+.fa-venus::before {
+  content: "\f221"; }
+
+.fa-passport::before {
+  content: "\f5ab"; }
+
+.fa-heart-pulse::before {
+  content: "\f21e"; }
+
+.fa-heartbeat::before {
+  content: "\f21e"; }
+
+.fa-people-carry-box::before {
+  content: "\f4ce"; }
+
+.fa-people-carry::before {
+  content: "\f4ce"; }
+
+.fa-temperature-high::before {
+  content: "\f769"; }
+
+.fa-microchip::before {
+  content: "\f2db"; }
+
+.fa-crown::before {
+  content: "\f521"; }
+
+.fa-weight-hanging::before {
+  content: "\f5cd"; }
+
+.fa-xmarks-lines::before {
+  content: "\e59a"; }
+
+.fa-file-prescription::before {
+  content: "\f572"; }
+
+.fa-weight-scale::before {
+  content: "\f496"; }
+
+.fa-weight::before {
+  content: "\f496"; }
+
+.fa-user-group::before {
+  content: "\f500"; }
+
+.fa-user-friends::before {
+  content: "\f500"; }
+
+.fa-arrow-up-a-z::before {
+  content: "\f15e"; }
+
+.fa-sort-alpha-up::before {
+  content: "\f15e"; }
+
+.fa-chess-knight::before {
+  content: "\f441"; }
+
+.fa-face-laugh-squint::before {
+  content: "\f59b"; }
+
+.fa-laugh-squint::before {
+  content: "\f59b"; }
+
+.fa-wheelchair::before {
+  content: "\f193"; }
+
+.fa-circle-arrow-up::before {
+  content: "\f0aa"; }
+
+.fa-arrow-circle-up::before {
+  content: "\f0aa"; }
+
+.fa-toggle-on::before {
+  content: "\f205"; }
+
+.fa-person-walking::before {
+  content: "\f554"; }
+
+.fa-walking::before {
+  content: "\f554"; }
+
+.fa-l::before {
+  content: "\4c"; }
+
+.fa-fire::before {
+  content: "\f06d"; }
+
+.fa-bed-pulse::before {
+  content: "\f487"; }
+
+.fa-procedures::before {
+  content: "\f487"; }
+
+.fa-shuttle-space::before {
+  content: "\f197"; }
+
+.fa-space-shuttle::before {
+  content: "\f197"; }
+
+.fa-face-laugh::before {
+  content: "\f599"; }
+
+.fa-laugh::before {
+  content: "\f599"; }
+
+.fa-folder-open::before {
+  content: "\f07c"; }
+
+.fa-heart-circle-plus::before {
+  content: "\e500"; }
+
+.fa-code-fork::before {
+  content: "\e13b"; }
+
+.fa-city::before {
+  content: "\f64f"; }
+
+.fa-microphone-lines::before {
+  content: "\f3c9"; }
+
+.fa-microphone-alt::before {
+  content: "\f3c9"; }
+
+.fa-pepper-hot::before {
+  content: "\f816"; }
+
+.fa-unlock::before {
+  content: "\f09c"; }
+
+.fa-colon-sign::before {
+  content: "\e140"; }
+
+.fa-headset::before {
+  content: "\f590"; }
+
+.fa-store-slash::before {
+  content: "\e071"; }
+
+.fa-road-circle-xmark::before {
+  content: "\e566"; }
+
+.fa-user-minus::before {
+  content: "\f503"; }
+
+.fa-mars-stroke-up::before {
+  content: "\f22a"; }
+
+.fa-mars-stroke-v::before {
+  content: "\f22a"; }
+
+.fa-champagne-glasses::before {
+  content: "\f79f"; }
+
+.fa-glass-cheers::before {
+  content: "\f79f"; }
+
+.fa-clipboard::before {
+  content: "\f328"; }
+
+.fa-house-circle-exclamation::before {
+  content: "\e50a"; }
+
+.fa-file-arrow-up::before {
+  content: "\f574"; }
+
+.fa-file-upload::before {
+  content: "\f574"; }
+
+.fa-wifi::before {
+  content: "\f1eb"; }
+
+.fa-wifi-3::before {
+  content: "\f1eb"; }
+
+.fa-wifi-strong::before {
+  content: "\f1eb"; }
+
+.fa-bath::before {
+  content: "\f2cd"; }
+
+.fa-bathtub::before {
+  content: "\f2cd"; }
+
+.fa-underline::before {
+  content: "\f0cd"; }
+
+.fa-user-pen::before {
+  content: "\f4ff"; }
+
+.fa-user-edit::before {
+  content: "\f4ff"; }
+
+.fa-signature::before {
+  content: "\f5b7"; }
+
+.fa-stroopwafel::before {
+  content: "\f551"; }
+
+.fa-bold::before {
+  content: "\f032"; }
+
+.fa-anchor-lock::before {
+  content: "\e4ad"; }
+
+.fa-building-ngo::before {
+  content: "\e4d7"; }
+
+.fa-manat-sign::before {
+  content: "\e1d5"; }
+
+.fa-not-equal::before {
+  content: "\f53e"; }
+
+.fa-border-top-left::before {
+  content: "\f853"; }
+
+.fa-border-style::before {
+  content: "\f853"; }
+
+.fa-map-location-dot::before {
+  content: "\f5a0"; }
+
+.fa-map-marked-alt::before {
+  content: "\f5a0"; }
+
+.fa-jedi::before {
+  content: "\f669"; }
+
+.fa-square-poll-vertical::before {
+  content: "\f681"; }
+
+.fa-poll::before {
+  content: "\f681"; }
+
+.fa-mug-hot::before {
+  content: "\f7b6"; }
+
+.fa-car-battery::before {
+  content: "\f5df"; }
+
+.fa-battery-car::before {
+  content: "\f5df"; }
+
+.fa-gift::before {
+  content: "\f06b"; }
+
+.fa-dice-two::before {
+  content: "\f528"; }
+
+.fa-chess-queen::before {
+  content: "\f445"; }
+
+.fa-glasses::before {
+  content: "\f530"; }
+
+.fa-chess-board::before {
+  content: "\f43c"; }
+
+.fa-building-circle-check::before {
+  content: "\e4d2"; }
+
+.fa-person-chalkboard::before {
+  content: "\e53d"; }
+
+.fa-mars-stroke-right::before {
+  content: "\f22b"; }
+
+.fa-mars-stroke-h::before {
+  content: "\f22b"; }
+
+.fa-hand-back-fist::before {
+  content: "\f255"; }
+
+.fa-hand-rock::before {
+  content: "\f255"; }
+
+.fa-square-caret-up::before {
+  content: "\f151"; }
+
+.fa-caret-square-up::before {
+  content: "\f151"; }
+
+.fa-cloud-showers-water::before {
+  content: "\e4e4"; }
+
+.fa-chart-bar::before {
+  content: "\f080"; }
+
+.fa-bar-chart::before {
+  content: "\f080"; }
+
+.fa-hands-bubbles::before {
+  content: "\e05e"; }
+
+.fa-hands-wash::before {
+  content: "\e05e"; }
+
+.fa-less-than-equal::before {
+  content: "\f537"; }
+
+.fa-train::before {
+  content: "\f238"; }
+
+.fa-eye-low-vision::before {
+  content: "\f2a8"; }
+
+.fa-low-vision::before {
+  content: "\f2a8"; }
+
+.fa-crow::before {
+  content: "\f520"; }
+
+.fa-sailboat::before {
+  content: "\e445"; }
+
+.fa-window-restore::before {
+  content: "\f2d2"; }
+
+.fa-square-plus::before {
+  content: "\f0fe"; }
+
+.fa-plus-square::before {
+  content: "\f0fe"; }
+
+.fa-torii-gate::before {
+  content: "\f6a1"; }
+
+.fa-frog::before {
+  content: "\f52e"; }
+
+.fa-bucket::before {
+  content: "\e4cf"; }
+
+.fa-image::before {
+  content: "\f03e"; }
+
+.fa-microphone::before {
+  content: "\f130"; }
+
+.fa-cow::before {
+  content: "\f6c8"; }
+
+.fa-caret-up::before {
+  content: "\f0d8"; }
+
+.fa-screwdriver::before {
+  content: "\f54a"; }
+
+.fa-folder-closed::before {
+  content: "\e185"; }
+
+.fa-house-tsunami::before {
+  content: "\e515"; }
+
+.fa-square-nfi::before {
+  content: "\e576"; }
+
+.fa-arrow-up-from-ground-water::before {
+  content: "\e4b5"; }
+
+.fa-martini-glass::before {
+  content: "\f57b"; }
+
+.fa-glass-martini-alt::before {
+  content: "\f57b"; }
+
+.fa-rotate-left::before {
+  content: "\f2ea"; }
+
+.fa-rotate-back::before {
+  content: "\f2ea"; }
+
+.fa-rotate-backward::before {
+  content: "\f2ea"; }
+
+.fa-undo-alt::before {
+  content: "\f2ea"; }
+
+.fa-table-columns::before {
+  content: "\f0db"; }
+
+.fa-columns::before {
+  content: "\f0db"; }
+
+.fa-lemon::before {
+  content: "\f094"; }
+
+.fa-head-side-mask::before {
+  content: "\e063"; }
+
+.fa-handshake::before {
+  content: "\f2b5"; }
+
+.fa-gem::before {
+  content: "\f3a5"; }
+
+.fa-dolly::before {
+  content: "\f472"; }
+
+.fa-dolly-box::before {
+  content: "\f472"; }
+
+.fa-smoking::before {
+  content: "\f48d"; }
+
+.fa-minimize::before {
+  content: "\f78c"; }
+
+.fa-compress-arrows-alt::before {
+  content: "\f78c"; }
+
+.fa-monument::before {
+  content: "\f5a6"; }
+
+.fa-snowplow::before {
+  content: "\f7d2"; }
+
+.fa-angles-right::before {
+  content: "\f101"; }
+
+.fa-angle-double-right::before {
+  content: "\f101"; }
+
+.fa-cannabis::before {
+  content: "\f55f"; }
+
+.fa-circle-play::before {
+  content: "\f144"; }
+
+.fa-play-circle::before {
+  content: "\f144"; }
+
+.fa-tablets::before {
+  content: "\f490"; }
+
+.fa-ethernet::before {
+  content: "\f796"; }
+
+.fa-euro-sign::before {
+  content: "\f153"; }
+
+.fa-eur::before {
+  content: "\f153"; }
+
+.fa-euro::before {
+  content: "\f153"; }
+
+.fa-chair::before {
+  content: "\f6c0"; }
+
+.fa-circle-check::before {
+  content: "\f058"; }
+
+.fa-check-circle::before {
+  content: "\f058"; }
+
+.fa-circle-stop::before {
+  content: "\f28d"; }
+
+.fa-stop-circle::before {
+  content: "\f28d"; }
+
+.fa-compass-drafting::before {
+  content: "\f568"; }
+
+.fa-drafting-compass::before {
+  content: "\f568"; }
+
+.fa-plate-wheat::before {
+  content: "\e55a"; }
+
+.fa-icicles::before {
+  content: "\f7ad"; }
+
+.fa-person-shelter::before {
+  content: "\e54f"; }
+
+.fa-neuter::before {
+  content: "\f22c"; }
+
+.fa-id-badge::before {
+  content: "\f2c1"; }
+
+.fa-marker::before {
+  content: "\f5a1"; }
+
+.fa-face-laugh-beam::before {
+  content: "\f59a"; }
+
+.fa-laugh-beam::before {
+  content: "\f59a"; }
+
+.fa-helicopter-symbol::before {
+  content: "\e502"; }
+
+.fa-universal-access::before {
+  content: "\f29a"; }
+
+.fa-circle-chevron-up::before {
+  content: "\f139"; }
+
+.fa-chevron-circle-up::before {
+  content: "\f139"; }
+
+.fa-lari-sign::before {
+  content: "\e1c8"; }
+
+.fa-volcano::before {
+  content: "\f770"; }
+
+.fa-person-walking-dashed-line-arrow-right::before {
+  content: "\e553"; }
+
+.fa-sterling-sign::before {
+  content: "\f154"; }
+
+.fa-gbp::before {
+  content: "\f154"; }
+
+.fa-pound-sign::before {
+  content: "\f154"; }
+
+.fa-viruses::before {
+  content: "\e076"; }
+
+.fa-square-person-confined::before {
+  content: "\e577"; }
+
+.fa-user-tie::before {
+  content: "\f508"; }
+
+.fa-arrow-down-long::before {
+  content: "\f175"; }
+
+.fa-long-arrow-down::before {
+  content: "\f175"; }
+
+.fa-tent-arrow-down-to-line::before {
+  content: "\e57e"; }
+
+.fa-certificate::before {
+  content: "\f0a3"; }
+
+.fa-reply-all::before {
+  content: "\f122"; }
+
+.fa-mail-reply-all::before {
+  content: "\f122"; }
+
+.fa-suitcase::before {
+  content: "\f0f2"; }
+
+.fa-person-skating::before {
+  content: "\f7c5"; }
+
+.fa-skating::before {
+  content: "\f7c5"; }
+
+.fa-filter-circle-dollar::before {
+  content: "\f662"; }
+
+.fa-funnel-dollar::before {
+  content: "\f662"; }
+
+.fa-camera-retro::before {
+  content: "\f083"; }
+
+.fa-circle-arrow-down::before {
+  content: "\f0ab"; }
+
+.fa-arrow-circle-down::before {
+  content: "\f0ab"; }
+
+.fa-file-import::before {
+  content: "\f56f"; }
+
+.fa-arrow-right-to-file::before {
+  content: "\f56f"; }
+
+.fa-square-arrow-up-right::before {
+  content: "\f14c"; }
+
+.fa-external-link-square::before {
+  content: "\f14c"; }
+
+.fa-box-open::before {
+  content: "\f49e"; }
+
+.fa-scroll::before {
+  content: "\f70e"; }
+
+.fa-spa::before {
+  content: "\f5bb"; }
+
+.fa-location-pin-lock::before {
+  content: "\e51f"; }
+
+.fa-pause::before {
+  content: "\f04c"; }
+
+.fa-hill-avalanche::before {
+  content: "\e507"; }
+
+.fa-temperature-empty::before {
+  content: "\f2cb"; }
+
+.fa-temperature-0::before {
+  content: "\f2cb"; }
+
+.fa-thermometer-0::before {
+  content: "\f2cb"; }
+
+.fa-thermometer-empty::before {
+  content: "\f2cb"; }
+
+.fa-bomb::before {
+  content: "\f1e2"; }
+
+.fa-registered::before {
+  content: "\f25d"; }
+
+.fa-address-card::before {
+  content: "\f2bb"; }
+
+.fa-contact-card::before {
+  content: "\f2bb"; }
+
+.fa-vcard::before {
+  content: "\f2bb"; }
+
+.fa-scale-unbalanced-flip::before {
+  content: "\f516"; }
+
+.fa-balance-scale-right::before {
+  content: "\f516"; }
+
+.fa-subscript::before {
+  content: "\f12c"; }
+
+.fa-diamond-turn-right::before {
+  content: "\f5eb"; }
+
+.fa-directions::before {
+  content: "\f5eb"; }
+
+.fa-burst::before {
+  content: "\e4dc"; }
+
+.fa-house-laptop::before {
+  content: "\e066"; }
+
+.fa-laptop-house::before {
+  content: "\e066"; }
+
+.fa-face-tired::before {
+  content: "\f5c8"; }
+
+.fa-tired::before {
+  content: "\f5c8"; }
+
+.fa-money-bills::before {
+  content: "\e1f3"; }
+
+.fa-smog::before {
+  content: "\f75f"; }
+
+.fa-crutch::before {
+  content: "\f7f7"; }
+
+.fa-cloud-arrow-up::before {
+  content: "\f0ee"; }
+
+.fa-cloud-upload::before {
+  content: "\f0ee"; }
+
+.fa-cloud-upload-alt::before {
+  content: "\f0ee"; }
+
+.fa-palette::before {
+  content: "\f53f"; }
+
+.fa-arrows-turn-right::before {
+  content: "\e4c0"; }
+
+.fa-vest::before {
+  content: "\e085"; }
+
+.fa-ferry::before {
+  content: "\e4ea"; }
+
+.fa-arrows-down-to-people::before {
+  content: "\e4b9"; }
+
+.fa-seedling::before {
+  content: "\f4d8"; }
+
+.fa-sprout::before {
+  content: "\f4d8"; }
+
+.fa-left-right::before {
+  content: "\f337"; }
+
+.fa-arrows-alt-h::before {
+  content: "\f337"; }
+
+.fa-boxes-packing::before {
+  content: "\e4c7"; }
+
+.fa-circle-arrow-left::before {
+  content: "\f0a8"; }
+
+.fa-arrow-circle-left::before {
+  content: "\f0a8"; }
+
+.fa-group-arrows-rotate::before {
+  content: "\e4f6"; }
+
+.fa-bowl-food::before {
+  content: "\e4c6"; }
+
+.fa-candy-cane::before {
+  content: "\f786"; }
+
+.fa-arrow-down-wide-short::before {
+  content: "\f160"; }
+
+.fa-sort-amount-asc::before {
+  content: "\f160"; }
+
+.fa-sort-amount-down::before {
+  content: "\f160"; }
+
+.fa-cloud-bolt::before {
+  content: "\f76c"; }
+
+.fa-thunderstorm::before {
+  content: "\f76c"; }
+
+.fa-text-slash::before {
+  content: "\f87d"; }
+
+.fa-remove-format::before {
+  content: "\f87d"; }
+
+.fa-face-smile-wink::before {
+  content: "\f4da"; }
+
+.fa-smile-wink::before {
+  content: "\f4da"; }
+
+.fa-file-word::before {
+  content: "\f1c2"; }
+
+.fa-file-powerpoint::before {
+  content: "\f1c4"; }
+
+.fa-arrows-left-right::before {
+  content: "\f07e"; }
+
+.fa-arrows-h::before {
+  content: "\f07e"; }
+
+.fa-house-lock::before {
+  content: "\e510"; }
+
+.fa-cloud-arrow-down::before {
+  content: "\f0ed"; }
+
+.fa-cloud-download::before {
+  content: "\f0ed"; }
+
+.fa-cloud-download-alt::before {
+  content: "\f0ed"; }
+
+.fa-children::before {
+  content: "\e4e1"; }
+
+.fa-chalkboard::before {
+  content: "\f51b"; }
+
+.fa-blackboard::before {
+  content: "\f51b"; }
+
+.fa-user-large-slash::before {
+  content: "\f4fa"; }
+
+.fa-user-alt-slash::before {
+  content: "\f4fa"; }
+
+.fa-envelope-open::before {
+  content: "\f2b6"; }
+
+.fa-handshake-simple-slash::before {
+  content: "\e05f"; }
+
+.fa-handshake-alt-slash::before {
+  content: "\e05f"; }
+
+.fa-mattress-pillow::before {
+  content: "\e525"; }
+
+.fa-guarani-sign::before {
+  content: "\e19a"; }
+
+.fa-arrows-rotate::before {
+  content: "\f021"; }
+
+.fa-refresh::before {
+  content: "\f021"; }
+
+.fa-sync::before {
+  content: "\f021"; }
+
+.fa-fire-extinguisher::before {
+  content: "\f134"; }
+
+.fa-cruzeiro-sign::before {
+  content: "\e152"; }
+
+.fa-greater-than-equal::before {
+  content: "\f532"; }
+
+.fa-shield-halved::before {
+  content: "\f3ed"; }
+
+.fa-shield-alt::before {
+  content: "\f3ed"; }
+
+.fa-book-atlas::before {
+  content: "\f558"; }
+
+.fa-atlas::before {
+  content: "\f558"; }
+
+.fa-virus::before {
+  content: "\e074"; }
+
+.fa-envelope-circle-check::before {
+  content: "\e4e8"; }
+
+.fa-layer-group::before {
+  content: "\f5fd"; }
+
+.fa-arrows-to-dot::before {
+  content: "\e4be"; }
+
+.fa-archway::before {
+  content: "\f557"; }
+
+.fa-heart-circle-check::before {
+  content: "\e4fd"; }
+
+.fa-house-chimney-crack::before {
+  content: "\f6f1"; }
+
+.fa-house-damage::before {
+  content: "\f6f1"; }
+
+.fa-file-zipper::before {
+  content: "\f1c6"; }
+
+.fa-file-archive::before {
+  content: "\f1c6"; }
+
+.fa-square::before {
+  content: "\f0c8"; }
+
+.fa-martini-glass-empty::before {
+  content: "\f000"; }
+
+.fa-glass-martini::before {
+  content: "\f000"; }
+
+.fa-couch::before {
+  content: "\f4b8"; }
+
+.fa-cedi-sign::before {
+  content: "\e0df"; }
+
+.fa-italic::before {
+  content: "\f033"; }
+
+.fa-table-cells-column-lock::before {
+  content: "\e678"; }
+
+.fa-church::before {
+  content: "\f51d"; }
+
+.fa-comments-dollar::before {
+  content: "\f653"; }
+
+.fa-democrat::before {
+  content: "\f747"; }
+
+.fa-z::before {
+  content: "\5a"; }
+
+.fa-person-skiing::before {
+  content: "\f7c9"; }
+
+.fa-skiing::before {
+  content: "\f7c9"; }
+
+.fa-road-lock::before {
+  content: "\e567"; }
+
+.fa-a::before {
+  content: "\41"; }
+
+.fa-temperature-arrow-down::before {
+  content: "\e03f"; }
+
+.fa-temperature-down::before {
+  content: "\e03f"; }
+
+.fa-feather-pointed::before {
+  content: "\f56b"; }
+
+.fa-feather-alt::before {
+  content: "\f56b"; }
+
+.fa-p::before {
+  content: "\50"; }
+
+.fa-snowflake::before {
+  content: "\f2dc"; }
+
+.fa-newspaper::before {
+  content: "\f1ea"; }
+
+.fa-rectangle-ad::before {
+  content: "\f641"; }
+
+.fa-ad::before {
+  content: "\f641"; }
+
+.fa-circle-arrow-right::before {
+  content: "\f0a9"; }
+
+.fa-arrow-circle-right::before {
+  content: "\f0a9"; }
+
+.fa-filter-circle-xmark::before {
+  content: "\e17b"; }
+
+.fa-locust::before {
+  content: "\e520"; }
+
+.fa-sort::before {
+  content: "\f0dc"; }
+
+.fa-unsorted::before {
+  content: "\f0dc"; }
+
+.fa-list-ol::before {
+  content: "\f0cb"; }
+
+.fa-list-1-2::before {
+  content: "\f0cb"; }
+
+.fa-list-numeric::before {
+  content: "\f0cb"; }
+
+.fa-person-dress-burst::before {
+  content: "\e544"; }
+
+.fa-money-check-dollar::before {
+  content: "\f53d"; }
+
+.fa-money-check-alt::before {
+  content: "\f53d"; }
+
+.fa-vector-square::before {
+  content: "\f5cb"; }
+
+.fa-bread-slice::before {
+  content: "\f7ec"; }
+
+.fa-language::before {
+  content: "\f1ab"; }
+
+.fa-face-kiss-wink-heart::before {
+  content: "\f598"; }
+
+.fa-kiss-wink-heart::before {
+  content: "\f598"; }
+
+.fa-filter::before {
+  content: "\f0b0"; }
+
+.fa-question::before {
+  content: "\3f"; }
+
+.fa-file-signature::before {
+  content: "\f573"; }
+
+.fa-up-down-left-right::before {
+  content: "\f0b2"; }
+
+.fa-arrows-alt::before {
+  content: "\f0b2"; }
+
+.fa-house-chimney-user::before {
+  content: "\e065"; }
+
+.fa-hand-holding-heart::before {
+  content: "\f4be"; }
+
+.fa-puzzle-piece::before {
+  content: "\f12e"; }
+
+.fa-money-check::before {
+  content: "\f53c"; }
+
+.fa-star-half-stroke::before {
+  content: "\f5c0"; }
+
+.fa-star-half-alt::before {
+  content: "\f5c0"; }
+
+.fa-code::before {
+  content: "\f121"; }
+
+.fa-whiskey-glass::before {
+  content: "\f7a0"; }
+
+.fa-glass-whiskey::before {
+  content: "\f7a0"; }
+
+.fa-building-circle-exclamation::before {
+  content: "\e4d3"; }
+
+.fa-magnifying-glass-chart::before {
+  content: "\e522"; }
+
+.fa-arrow-up-right-from-square::before {
+  content: "\f08e"; }
+
+.fa-external-link::before {
+  content: "\f08e"; }
+
+.fa-cubes-stacked::before {
+  content: "\e4e6"; }
+
+.fa-won-sign::before {
+  content: "\f159"; }
+
+.fa-krw::before {
+  content: "\f159"; }
+
+.fa-won::before {
+  content: "\f159"; }
+
+.fa-virus-covid::before {
+  content: "\e4a8"; }
+
+.fa-austral-sign::before {
+  content: "\e0a9"; }
+
+.fa-f::before {
+  content: "\46"; }
+
+.fa-leaf::before {
+  content: "\f06c"; }
+
+.fa-road::before {
+  content: "\f018"; }
+
+.fa-taxi::before {
+  content: "\f1ba"; }
+
+.fa-cab::before {
+  content: "\f1ba"; }
+
+.fa-person-circle-plus::before {
+  content: "\e541"; }
+
+.fa-chart-pie::before {
+  content: "\f200"; }
+
+.fa-pie-chart::before {
+  content: "\f200"; }
+
+.fa-bolt-lightning::before {
+  content: "\e0b7"; }
+
+.fa-sack-xmark::before {
+  content: "\e56a"; }
+
+.fa-file-excel::before {
+  content: "\f1c3"; }
+
+.fa-file-contract::before {
+  content: "\f56c"; }
+
+.fa-fish-fins::before {
+  content: "\e4f2"; }
+
+.fa-building-flag::before {
+  content: "\e4d5"; }
+
+.fa-face-grin-beam::before {
+  content: "\f582"; }
+
+.fa-grin-beam::before {
+  content: "\f582"; }
+
+.fa-object-ungroup::before {
+  content: "\f248"; }
+
+.fa-poop::before {
+  content: "\f619"; }
+
+.fa-location-pin::before {
+  content: "\f041"; }
+
+.fa-map-marker::before {
+  content: "\f041"; }
+
+.fa-kaaba::before {
+  content: "\f66b"; }
+
+.fa-toilet-paper::before {
+  content: "\f71e"; }
+
+.fa-helmet-safety::before {
+  content: "\f807"; }
+
+.fa-hard-hat::before {
+  content: "\f807"; }
+
+.fa-hat-hard::before {
+  content: "\f807"; }
+
+.fa-eject::before {
+  content: "\f052"; }
+
+.fa-circle-right::before {
+  content: "\f35a"; }
+
+.fa-arrow-alt-circle-right::before {
+  content: "\f35a"; }
+
+.fa-plane-circle-check::before {
+  content: "\e555"; }
+
+.fa-face-rolling-eyes::before {
+  content: "\f5a5"; }
+
+.fa-meh-rolling-eyes::before {
+  content: "\f5a5"; }
+
+.fa-object-group::before {
+  content: "\f247"; }
+
+.fa-chart-line::before {
+  content: "\f201"; }
+
+.fa-line-chart::before {
+  content: "\f201"; }
+
+.fa-mask-ventilator::before {
+  content: "\e524"; }
+
+.fa-arrow-right::before {
+  content: "\f061"; }
+
+.fa-signs-post::before {
+  content: "\f277"; }
+
+.fa-map-signs::before {
+  content: "\f277"; }
+
+.fa-cash-register::before {
+  content: "\f788"; }
+
+.fa-person-circle-question::before {
+  content: "\e542"; }
+
+.fa-h::before {
+  content: "\48"; }
+
+.fa-tarp::before {
+  content: "\e57b"; }
+
+.fa-screwdriver-wrench::before {
+  content: "\f7d9"; }
+
+.fa-tools::before {
+  content: "\f7d9"; }
+
+.fa-arrows-to-eye::before {
+  content: "\e4bf"; }
+
+.fa-plug-circle-bolt::before {
+  content: "\e55b"; }
+
+.fa-heart::before {
+  content: "\f004"; }
+
+.fa-mars-and-venus::before {
+  content: "\f224"; }
+
+.fa-house-user::before {
+  content: "\e1b0"; }
+
+.fa-home-user::before {
+  content: "\e1b0"; }
+
+.fa-dumpster-fire::before {
+  content: "\f794"; }
+
+.fa-house-crack::before {
+  content: "\e3b1"; }
+
+.fa-martini-glass-citrus::before {
+  content: "\f561"; }
+
+.fa-cocktail::before {
+  content: "\f561"; }
+
+.fa-face-surprise::before {
+  content: "\f5c2"; }
+
+.fa-surprise::before {
+  content: "\f5c2"; }
+
+.fa-bottle-water::before {
+  content: "\e4c5"; }
+
+.fa-circle-pause::before {
+  content: "\f28b"; }
+
+.fa-pause-circle::before {
+  content: "\f28b"; }
+
+.fa-toilet-paper-slash::before {
+  content: "\e072"; }
+
+.fa-apple-whole::before {
+  content: "\f5d1"; }
+
+.fa-apple-alt::before {
+  content: "\f5d1"; }
+
+.fa-kitchen-set::before {
+  content: "\e51a"; }
+
+.fa-r::before {
+  content: "\52"; }
+
+.fa-temperature-quarter::before {
+  content: "\f2ca"; }
+
+.fa-temperature-1::before {
+  content: "\f2ca"; }
+
+.fa-thermometer-1::before {
+  content: "\f2ca"; }
+
+.fa-thermometer-quarter::before {
+  content: "\f2ca"; }
+
+.fa-cube::before {
+  content: "\f1b2"; }
+
+.fa-bitcoin-sign::before {
+  content: "\e0b4"; }
+
+.fa-shield-dog::before {
+  content: "\e573"; }
+
+.fa-solar-panel::before {
+  content: "\f5ba"; }
+
+.fa-lock-open::before {
+  content: "\f3c1"; }
+
+.fa-elevator::before {
+  content: "\e16d"; }
+
+.fa-money-bill-transfer::before {
+  content: "\e528"; }
+
+.fa-money-bill-trend-up::before {
+  content: "\e529"; }
+
+.fa-house-flood-water-circle-arrow-right::before {
+  content: "\e50f"; }
+
+.fa-square-poll-horizontal::before {
+  content: "\f682"; }
+
+.fa-poll-h::before {
+  content: "\f682"; }
+
+.fa-circle::before {
+  content: "\f111"; }
+
+.fa-backward-fast::before {
+  content: "\f049"; }
+
+.fa-fast-backward::before {
+  content: "\f049"; }
+
+.fa-recycle::before {
+  content: "\f1b8"; }
+
+.fa-user-astronaut::before {
+  content: "\f4fb"; }
+
+.fa-plane-slash::before {
+  content: "\e069"; }
+
+.fa-trademark::before {
+  content: "\f25c"; }
+
+.fa-basketball::before {
+  content: "\f434"; }
+
+.fa-basketball-ball::before {
+  content: "\f434"; }
+
+.fa-satellite-dish::before {
+  content: "\f7c0"; }
+
+.fa-circle-up::before {
+  content: "\f35b"; }
+
+.fa-arrow-alt-circle-up::before {
+  content: "\f35b"; }
+
+.fa-mobile-screen-button::before {
+  content: "\f3cd"; }
+
+.fa-mobile-alt::before {
+  content: "\f3cd"; }
+
+.fa-volume-high::before {
+  content: "\f028"; }
+
+.fa-volume-up::before {
+  content: "\f028"; }
+
+.fa-users-rays::before {
+  content: "\e593"; }
+
+.fa-wallet::before {
+  content: "\f555"; }
+
+.fa-clipboard-check::before {
+  content: "\f46c"; }
+
+.fa-file-audio::before {
+  content: "\f1c7"; }
+
+.fa-burger::before {
+  content: "\f805"; }
+
+.fa-hamburger::before {
+  content: "\f805"; }
+
+.fa-wrench::before {
+  content: "\f0ad"; }
+
+.fa-bugs::before {
+  content: "\e4d0"; }
+
+.fa-rupee-sign::before {
+  content: "\f156"; }
+
+.fa-rupee::before {
+  content: "\f156"; }
+
+.fa-file-image::before {
+  content: "\f1c5"; }
+
+.fa-circle-question::before {
+  content: "\f059"; }
+
+.fa-question-circle::before {
+  content: "\f059"; }
+
+.fa-plane-departure::before {
+  content: "\f5b0"; }
+
+.fa-handshake-slash::before {
+  content: "\e060"; }
+
+.fa-book-bookmark::before {
+  content: "\e0bb"; }
+
+.fa-code-branch::before {
+  content: "\f126"; }
+
+.fa-hat-cowboy::before {
+  content: "\f8c0"; }
+
+.fa-bridge::before {
+  content: "\e4c8"; }
+
+.fa-phone-flip::before {
+  content: "\f879"; }
+
+.fa-phone-alt::before {
+  content: "\f879"; }
+
+.fa-truck-front::before {
+  content: "\e2b7"; }
+
+.fa-cat::before {
+  content: "\f6be"; }
+
+.fa-anchor-circle-exclamation::before {
+  content: "\e4ab"; }
+
+.fa-truck-field::before {
+  content: "\e58d"; }
+
+.fa-route::before {
+  content: "\f4d7"; }
+
+.fa-clipboard-question::before {
+  content: "\e4e3"; }
+
+.fa-panorama::before {
+  content: "\e209"; }
+
+.fa-comment-medical::before {
+  content: "\f7f5"; }
+
+.fa-teeth-open::before {
+  content: "\f62f"; }
+
+.fa-file-circle-minus::before {
+  content: "\e4ed"; }
+
+.fa-tags::before {
+  content: "\f02c"; }
+
+.fa-wine-glass::before {
+  content: "\f4e3"; }
+
+.fa-forward-fast::before {
+  content: "\f050"; }
+
+.fa-fast-forward::before {
+  content: "\f050"; }
+
+.fa-face-meh-blank::before {
+  content: "\f5a4"; }
+
+.fa-meh-blank::before {
+  content: "\f5a4"; }
+
+.fa-square-parking::before {
+  content: "\f540"; }
+
+.fa-parking::before {
+  content: "\f540"; }
+
+.fa-house-signal::before {
+  content: "\e012"; }
+
+.fa-bars-progress::before {
+  content: "\f828"; }
+
+.fa-tasks-alt::before {
+  content: "\f828"; }
+
+.fa-faucet-drip::before {
+  content: "\e006"; }
+
+.fa-cart-flatbed::before {
+  content: "\f474"; }
+
+.fa-dolly-flatbed::before {
+  content: "\f474"; }
+
+.fa-ban-smoking::before {
+  content: "\f54d"; }
+
+.fa-smoking-ban::before {
+  content: "\f54d"; }
+
+.fa-terminal::before {
+  content: "\f120"; }
+
+.fa-mobile-button::before {
+  content: "\f10b"; }
+
+.fa-house-medical-flag::before {
+  content: "\e514"; }
+
+.fa-basket-shopping::before {
+  content: "\f291"; }
+
+.fa-shopping-basket::before {
+  content: "\f291"; }
+
+.fa-tape::before {
+  content: "\f4db"; }
+
+.fa-bus-simple::before {
+  content: "\f55e"; }
+
+.fa-bus-alt::before {
+  content: "\f55e"; }
+
+.fa-eye::before {
+  content: "\f06e"; }
+
+.fa-face-sad-cry::before {
+  content: "\f5b3"; }
+
+.fa-sad-cry::before {
+  content: "\f5b3"; }
+
+.fa-audio-description::before {
+  content: "\f29e"; }
+
+.fa-person-military-to-person::before {
+  content: "\e54c"; }
+
+.fa-file-shield::before {
+  content: "\e4f0"; }
+
+.fa-user-slash::before {
+  content: "\f506"; }
+
+.fa-pen::before {
+  content: "\f304"; }
+
+.fa-tower-observation::before {
+  content: "\e586"; }
+
+.fa-file-code::before {
+  content: "\f1c9"; }
+
+.fa-signal::before {
+  content: "\f012"; }
+
+.fa-signal-5::before {
+  content: "\f012"; }
+
+.fa-signal-perfect::before {
+  content: "\f012"; }
+
+.fa-bus::before {
+  content: "\f207"; }
+
+.fa-heart-circle-xmark::before {
+  content: "\e501"; }
+
+.fa-house-chimney::before {
+  content: "\e3af"; }
+
+.fa-home-lg::before {
+  content: "\e3af"; }
+
+.fa-window-maximize::before {
+  content: "\f2d0"; }
+
+.fa-face-frown::before {
+  content: "\f119"; }
+
+.fa-frown::before {
+  content: "\f119"; }
+
+.fa-prescription::before {
+  content: "\f5b1"; }
+
+.fa-shop::before {
+  content: "\f54f"; }
+
+.fa-store-alt::before {
+  content: "\f54f"; }
+
+.fa-floppy-disk::before {
+  content: "\f0c7"; }
+
+.fa-save::before {
+  content: "\f0c7"; }
+
+.fa-vihara::before {
+  content: "\f6a7"; }
+
+.fa-scale-unbalanced::before {
+  content: "\f515"; }
+
+.fa-balance-scale-left::before {
+  content: "\f515"; }
+
+.fa-sort-up::before {
+  content: "\f0de"; }
+
+.fa-sort-asc::before {
+  content: "\f0de"; }
+
+.fa-comment-dots::before {
+  content: "\f4ad"; }
+
+.fa-commenting::before {
+  content: "\f4ad"; }
+
+.fa-plant-wilt::before {
+  content: "\e5aa"; }
+
+.fa-diamond::before {
+  content: "\f219"; }
+
+.fa-face-grin-squint::before {
+  content: "\f585"; }
+
+.fa-grin-squint::before {
+  content: "\f585"; }
+
+.fa-hand-holding-dollar::before {
+  content: "\f4c0"; }
+
+.fa-hand-holding-usd::before {
+  content: "\f4c0"; }
+
+.fa-bacterium::before {
+  content: "\e05a"; }
+
+.fa-hand-pointer::before {
+  content: "\f25a"; }
+
+.fa-drum-steelpan::before {
+  content: "\f56a"; }
+
+.fa-hand-scissors::before {
+  content: "\f257"; }
+
+.fa-hands-praying::before {
+  content: "\f684"; }
+
+.fa-praying-hands::before {
+  content: "\f684"; }
+
+.fa-arrow-rotate-right::before {
+  content: "\f01e"; }
+
+.fa-arrow-right-rotate::before {
+  content: "\f01e"; }
+
+.fa-arrow-rotate-forward::before {
+  content: "\f01e"; }
+
+.fa-redo::before {
+  content: "\f01e"; }
+
+.fa-biohazard::before {
+  content: "\f780"; }
+
+.fa-location-crosshairs::before {
+  content: "\f601"; }
+
+.fa-location::before {
+  content: "\f601"; }
+
+.fa-mars-double::before {
+  content: "\f227"; }
+
+.fa-child-dress::before {
+  content: "\e59c"; }
+
+.fa-users-between-lines::before {
+  content: "\e591"; }
+
+.fa-lungs-virus::before {
+  content: "\e067"; }
+
+.fa-face-grin-tears::before {
+  content: "\f588"; }
+
+.fa-grin-tears::before {
+  content: "\f588"; }
+
+.fa-phone::before {
+  content: "\f095"; }
+
+.fa-calendar-xmark::before {
+  content: "\f273"; }
+
+.fa-calendar-times::before {
+  content: "\f273"; }
+
+.fa-child-reaching::before {
+  content: "\e59d"; }
+
+.fa-head-side-virus::before {
+  content: "\e064"; }
+
+.fa-user-gear::before {
+  content: "\f4fe"; }
+
+.fa-user-cog::before {
+  content: "\f4fe"; }
+
+.fa-arrow-up-1-9::before {
+  content: "\f163"; }
+
+.fa-sort-numeric-up::before {
+  content: "\f163"; }
+
+.fa-door-closed::before {
+  content: "\f52a"; }
+
+.fa-shield-virus::before {
+  content: "\e06c"; }
+
+.fa-dice-six::before {
+  content: "\f526"; }
+
+.fa-mosquito-net::before {
+  content: "\e52c"; }
+
+.fa-bridge-water::before {
+  content: "\e4ce"; }
+
+.fa-person-booth::before {
+  content: "\f756"; }
+
+.fa-text-width::before {
+  content: "\f035"; }
+
+.fa-hat-wizard::before {
+  content: "\f6e8"; }
+
+.fa-pen-fancy::before {
+  content: "\f5ac"; }
+
+.fa-person-digging::before {
+  content: "\f85e"; }
+
+.fa-digging::before {
+  content: "\f85e"; }
+
+.fa-trash::before {
+  content: "\f1f8"; }
+
+.fa-gauge-simple::before {
+  content: "\f629"; }
+
+.fa-gauge-simple-med::before {
+  content: "\f629"; }
+
+.fa-tachometer-average::before {
+  content: "\f629"; }
+
+.fa-book-medical::before {
+  content: "\f7e6"; }
+
+.fa-poo::before {
+  content: "\f2fe"; }
+
+.fa-quote-right::before {
+  content: "\f10e"; }
+
+.fa-quote-right-alt::before {
+  content: "\f10e"; }
+
+.fa-shirt::before {
+  content: "\f553"; }
+
+.fa-t-shirt::before {
+  content: "\f553"; }
+
+.fa-tshirt::before {
+  content: "\f553"; }
+
+.fa-cubes::before {
+  content: "\f1b3"; }
+
+.fa-divide::before {
+  content: "\f529"; }
+
+.fa-tenge-sign::before {
+  content: "\f7d7"; }
+
+.fa-tenge::before {
+  content: "\f7d7"; }
+
+.fa-headphones::before {
+  content: "\f025"; }
+
+.fa-hands-holding::before {
+  content: "\f4c2"; }
+
+.fa-hands-clapping::before {
+  content: "\e1a8"; }
+
+.fa-republican::before {
+  content: "\f75e"; }
+
+.fa-arrow-left::before {
+  content: "\f060"; }
+
+.fa-person-circle-xmark::before {
+  content: "\e543"; }
+
+.fa-ruler::before {
+  content: "\f545"; }
+
+.fa-align-left::before {
+  content: "\f036"; }
+
+.fa-dice-d6::before {
+  content: "\f6d1"; }
+
+.fa-restroom::before {
+  content: "\f7bd"; }
+
+.fa-j::before {
+  content: "\4a"; }
+
+.fa-users-viewfinder::before {
+  content: "\e595"; }
+
+.fa-file-video::before {
+  content: "\f1c8"; }
+
+.fa-up-right-from-square::before {
+  content: "\f35d"; }
+
+.fa-external-link-alt::before {
+  content: "\f35d"; }
+
+.fa-table-cells::before {
+  content: "\f00a"; }
+
+.fa-th::before {
+  content: "\f00a"; }
+
+.fa-file-pdf::before {
+  content: "\f1c1"; }
+
+.fa-book-bible::before {
+  content: "\f647"; }
+
+.fa-bible::before {
+  content: "\f647"; }
+
+.fa-o::before {
+  content: "\4f"; }
+
+.fa-suitcase-medical::before {
+  content: "\f0fa"; }
+
+.fa-medkit::before {
+  content: "\f0fa"; }
+
+.fa-user-secret::before {
+  content: "\f21b"; }
+
+.fa-otter::before {
+  content: "\f700"; }
+
+.fa-person-dress::before {
+  content: "\f182"; }
+
+.fa-female::before {
+  content: "\f182"; }
+
+.fa-comment-dollar::before {
+  content: "\f651"; }
+
+.fa-business-time::before {
+  content: "\f64a"; }
+
+.fa-briefcase-clock::before {
+  content: "\f64a"; }
+
+.fa-table-cells-large::before {
+  content: "\f009"; }
+
+.fa-th-large::before {
+  content: "\f009"; }
+
+.fa-book-tanakh::before {
+  content: "\f827"; }
+
+.fa-tanakh::before {
+  content: "\f827"; }
+
+.fa-phone-volume::before {
+  content: "\f2a0"; }
+
+.fa-volume-control-phone::before {
+  content: "\f2a0"; }
+
+.fa-hat-cowboy-side::before {
+  content: "\f8c1"; }
+
+.fa-clipboard-user::before {
+  content: "\f7f3"; }
+
+.fa-child::before {
+  content: "\f1ae"; }
+
+.fa-lira-sign::before {
+  content: "\f195"; }
+
+.fa-satellite::before {
+  content: "\f7bf"; }
+
+.fa-plane-lock::before {
+  content: "\e558"; }
+
+.fa-tag::before {
+  content: "\f02b"; }
+
+.fa-comment::before {
+  content: "\f075"; }
+
+.fa-cake-candles::before {
+  content: "\f1fd"; }
+
+.fa-birthday-cake::before {
+  content: "\f1fd"; }
+
+.fa-cake::before {
+  content: "\f1fd"; }
+
+.fa-envelope::before {
+  content: "\f0e0"; }
+
+.fa-angles-up::before {
+  content: "\f102"; }
+
+.fa-angle-double-up::before {
+  content: "\f102"; }
+
+.fa-paperclip::before {
+  content: "\f0c6"; }
+
+.fa-arrow-right-to-city::before {
+  content: "\e4b3"; }
+
+.fa-ribbon::before {
+  content: "\f4d6"; }
+
+.fa-lungs::before {
+  content: "\f604"; }
+
+.fa-arrow-up-9-1::before {
+  content: "\f887"; }
+
+.fa-sort-numeric-up-alt::before {
+  content: "\f887"; }
+
+.fa-litecoin-sign::before {
+  content: "\e1d3"; }
+
+.fa-border-none::before {
+  content: "\f850"; }
+
+.fa-circle-nodes::before {
+  content: "\e4e2"; }
+
+.fa-parachute-box::before {
+  content: "\f4cd"; }
+
+.fa-indent::before {
+  content: "\f03c"; }
+
+.fa-truck-field-un::before {
+  content: "\e58e"; }
+
+.fa-hourglass::before {
+  content: "\f254"; }
+
+.fa-hourglass-empty::before {
+  content: "\f254"; }
+
+.fa-mountain::before {
+  content: "\f6fc"; }
+
+.fa-user-doctor::before {
+  content: "\f0f0"; }
+
+.fa-user-md::before {
+  content: "\f0f0"; }
+
+.fa-circle-info::before {
+  content: "\f05a"; }
+
+.fa-info-circle::before {
+  content: "\f05a"; }
+
+.fa-cloud-meatball::before {
+  content: "\f73b"; }
+
+.fa-camera::before {
+  content: "\f030"; }
+
+.fa-camera-alt::before {
+  content: "\f030"; }
+
+.fa-square-virus::before {
+  content: "\e578"; }
+
+.fa-meteor::before {
+  content: "\f753"; }
+
+.fa-car-on::before {
+  content: "\e4dd"; }
+
+.fa-sleigh::before {
+  content: "\f7cc"; }
+
+.fa-arrow-down-1-9::before {
+  content: "\f162"; }
+
+.fa-sort-numeric-asc::before {
+  content: "\f162"; }
+
+.fa-sort-numeric-down::before {
+  content: "\f162"; }
+
+.fa-hand-holding-droplet::before {
+  content: "\f4c1"; }
+
+.fa-hand-holding-water::before {
+  content: "\f4c1"; }
+
+.fa-water::before {
+  content: "\f773"; }
+
+.fa-calendar-check::before {
+  content: "\f274"; }
+
+.fa-braille::before {
+  content: "\f2a1"; }
+
+.fa-prescription-bottle-medical::before {
+  content: "\f486"; }
+
+.fa-prescription-bottle-alt::before {
+  content: "\f486"; }
+
+.fa-landmark::before {
+  content: "\f66f"; }
+
+.fa-truck::before {
+  content: "\f0d1"; }
+
+.fa-crosshairs::before {
+  content: "\f05b"; }
+
+.fa-person-cane::before {
+  content: "\e53c"; }
+
+.fa-tent::before {
+  content: "\e57d"; }
+
+.fa-vest-patches::before {
+  content: "\e086"; }
+
+.fa-check-double::before {
+  content: "\f560"; }
+
+.fa-arrow-down-a-z::before {
+  content: "\f15d"; }
+
+.fa-sort-alpha-asc::before {
+  content: "\f15d"; }
+
+.fa-sort-alpha-down::before {
+  content: "\f15d"; }
+
+.fa-money-bill-wheat::before {
+  content: "\e52a"; }
+
+.fa-cookie::before {
+  content: "\f563"; }
+
+.fa-arrow-rotate-left::before {
+  content: "\f0e2"; }
+
+.fa-arrow-left-rotate::before {
+  content: "\f0e2"; }
+
+.fa-arrow-rotate-back::before {
+  content: "\f0e2"; }
+
+.fa-arrow-rotate-backward::before {
+  content: "\f0e2"; }
+
+.fa-undo::before {
+  content: "\f0e2"; }
+
+.fa-hard-drive::before {
+  content: "\f0a0"; }
+
+.fa-hdd::before {
+  content: "\f0a0"; }
+
+.fa-face-grin-squint-tears::before {
+  content: "\f586"; }
+
+.fa-grin-squint-tears::before {
+  content: "\f586"; }
+
+.fa-dumbbell::before {
+  content: "\f44b"; }
+
+.fa-rectangle-list::before {
+  content: "\f022"; }
+
+.fa-list-alt::before {
+  content: "\f022"; }
+
+.fa-tarp-droplet::before {
+  content: "\e57c"; }
+
+.fa-house-medical-circle-check::before {
+  content: "\e511"; }
+
+.fa-person-skiing-nordic::before {
+  content: "\f7ca"; }
+
+.fa-skiing-nordic::before {
+  content: "\f7ca"; }
+
+.fa-calendar-plus::before {
+  content: "\f271"; }
+
+.fa-plane-arrival::before {
+  content: "\f5af"; }
+
+.fa-circle-left::before {
+  content: "\f359"; }
+
+.fa-arrow-alt-circle-left::before {
+  content: "\f359"; }
+
+.fa-train-subway::before {
+  content: "\f239"; }
+
+.fa-subway::before {
+  content: "\f239"; }
+
+.fa-chart-gantt::before {
+  content: "\e0e4"; }
+
+.fa-indian-rupee-sign::before {
+  content: "\e1bc"; }
+
+.fa-indian-rupee::before {
+  content: "\e1bc"; }
+
+.fa-inr::before {
+  content: "\e1bc"; }
+
+.fa-crop-simple::before {
+  content: "\f565"; }
+
+.fa-crop-alt::before {
+  content: "\f565"; }
+
+.fa-money-bill-1::before {
+  content: "\f3d1"; }
+
+.fa-money-bill-alt::before {
+  content: "\f3d1"; }
+
+.fa-left-long::before {
+  content: "\f30a"; }
+
+.fa-long-arrow-alt-left::before {
+  content: "\f30a"; }
+
+.fa-dna::before {
+  content: "\f471"; }
+
+.fa-virus-slash::before {
+  content: "\e075"; }
+
+.fa-minus::before {
+  content: "\f068"; }
+
+.fa-subtract::before {
+  content: "\f068"; }
+
+.fa-chess::before {
+  content: "\f439"; }
+
+.fa-arrow-left-long::before {
+  content: "\f177"; }
+
+.fa-long-arrow-left::before {
+  content: "\f177"; }
+
+.fa-plug-circle-check::before {
+  content: "\e55c"; }
+
+.fa-street-view::before {
+  content: "\f21d"; }
+
+.fa-franc-sign::before {
+  content: "\e18f"; }
+
+.fa-volume-off::before {
+  content: "\f026"; }
+
+.fa-hands-asl-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-american-sign-language-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-asl-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-hands-american-sign-language-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-gear::before {
+  content: "\f013"; }
+
+.fa-cog::before {
+  content: "\f013"; }
+
+.fa-droplet-slash::before {
+  content: "\f5c7"; }
+
+.fa-tint-slash::before {
+  content: "\f5c7"; }
+
+.fa-mosque::before {
+  content: "\f678"; }
+
+.fa-mosquito::before {
+  content: "\e52b"; }
+
+.fa-star-of-david::before {
+  content: "\f69a"; }
+
+.fa-person-military-rifle::before {
+  content: "\e54b"; }
+
+.fa-cart-shopping::before {
+  content: "\f07a"; }
+
+.fa-shopping-cart::before {
+  content: "\f07a"; }
+
+.fa-vials::before {
+  content: "\f493"; }
+
+.fa-plug-circle-plus::before {
+  content: "\e55f"; }
+
+.fa-place-of-worship::before {
+  content: "\f67f"; }
+
+.fa-grip-vertical::before {
+  content: "\f58e"; }
+
+.fa-arrow-turn-up::before {
+  content: "\f148"; }
+
+.fa-level-up::before {
+  content: "\f148"; }
+
+.fa-u::before {
+  content: "\55"; }
+
+.fa-square-root-variable::before {
+  content: "\f698"; }
+
+.fa-square-root-alt::before {
+  content: "\f698"; }
+
+.fa-clock::before {
+  content: "\f017"; }
+
+.fa-clock-four::before {
+  content: "\f017"; }
+
+.fa-backward-step::before {
+  content: "\f048"; }
+
+.fa-step-backward::before {
+  content: "\f048"; }
+
+.fa-pallet::before {
+  content: "\f482"; }
+
+.fa-faucet::before {
+  content: "\e005"; }
+
+.fa-baseball-bat-ball::before {
+  content: "\f432"; }
+
+.fa-s::before {
+  content: "\53"; }
+
+.fa-timeline::before {
+  content: "\e29c"; }
+
+.fa-keyboard::before {
+  content: "\f11c"; }
+
+.fa-caret-down::before {
+  content: "\f0d7"; }
+
+.fa-house-chimney-medical::before {
+  content: "\f7f2"; }
+
+.fa-clinic-medical::before {
+  content: "\f7f2"; }
+
+.fa-temperature-three-quarters::before {
+  content: "\f2c8"; }
+
+.fa-temperature-3::before {
+  content: "\f2c8"; }
+
+.fa-thermometer-3::before {
+  content: "\f2c8"; }
+
+.fa-thermometer-three-quarters::before {
+  content: "\f2c8"; }
+
+.fa-mobile-screen::before {
+  content: "\f3cf"; }
+
+.fa-mobile-android-alt::before {
+  content: "\f3cf"; }
+
+.fa-plane-up::before {
+  content: "\e22d"; }
+
+.fa-piggy-bank::before {
+  content: "\f4d3"; }
+
+.fa-battery-half::before {
+  content: "\f242"; }
+
+.fa-battery-3::before {
+  content: "\f242"; }
+
+.fa-mountain-city::before {
+  content: "\e52e"; }
+
+.fa-coins::before {
+  content: "\f51e"; }
+
+.fa-khanda::before {
+  content: "\f66d"; }
+
+.fa-sliders::before {
+  content: "\f1de"; }
+
+.fa-sliders-h::before {
+  content: "\f1de"; }
+
+.fa-folder-tree::before {
+  content: "\f802"; }
+
+.fa-network-wired::before {
+  content: "\f6ff"; }
+
+.fa-map-pin::before {
+  content: "\f276"; }
+
+.fa-hamsa::before {
+  content: "\f665"; }
+
+.fa-cent-sign::before {
+  content: "\e3f5"; }
+
+.fa-flask::before {
+  content: "\f0c3"; }
+
+.fa-person-pregnant::before {
+  content: "\e31e"; }
+
+.fa-wand-sparkles::before {
+  content: "\f72b"; }
+
+.fa-ellipsis-vertical::before {
+  content: "\f142"; }
+
+.fa-ellipsis-v::before {
+  content: "\f142"; }
+
+.fa-ticket::before {
+  content: "\f145"; }
+
+.fa-power-off::before {
+  content: "\f011"; }
+
+.fa-right-long::before {
+  content: "\f30b"; }
+
+.fa-long-arrow-alt-right::before {
+  content: "\f30b"; }
+
+.fa-flag-usa::before {
+  content: "\f74d"; }
+
+.fa-laptop-file::before {
+  content: "\e51d"; }
+
+.fa-tty::before {
+  content: "\f1e4"; }
+
+.fa-teletype::before {
+  content: "\f1e4"; }
+
+.fa-diagram-next::before {
+  content: "\e476"; }
+
+.fa-person-rifle::before {
+  content: "\e54e"; }
+
+.fa-house-medical-circle-exclamation::before {
+  content: "\e512"; }
+
+.fa-closed-captioning::before {
+  content: "\f20a"; }
+
+.fa-person-hiking::before {
+  content: "\f6ec"; }
+
+.fa-hiking::before {
+  content: "\f6ec"; }
+
+.fa-venus-double::before {
+  content: "\f226"; }
+
+.fa-images::before {
+  content: "\f302"; }
+
+.fa-calculator::before {
+  content: "\f1ec"; }
+
+.fa-people-pulling::before {
+  content: "\e535"; }
+
+.fa-n::before {
+  content: "\4e"; }
+
+.fa-cable-car::before {
+  content: "\f7da"; }
+
+.fa-tram::before {
+  content: "\f7da"; }
+
+.fa-cloud-rain::before {
+  content: "\f73d"; }
+
+.fa-building-circle-xmark::before {
+  content: "\e4d4"; }
+
+.fa-ship::before {
+  content: "\f21a"; }
+
+.fa-arrows-down-to-line::before {
+  content: "\e4b8"; }
+
+.fa-download::before {
+  content: "\f019"; }
+
+.fa-face-grin::before {
+  content: "\f580"; }
+
+.fa-grin::before {
+  content: "\f580"; }
+
+.fa-delete-left::before {
+  content: "\f55a"; }
+
+.fa-backspace::before {
+  content: "\f55a"; }
+
+.fa-eye-dropper::before {
+  content: "\f1fb"; }
+
+.fa-eye-dropper-empty::before {
+  content: "\f1fb"; }
+
+.fa-eyedropper::before {
+  content: "\f1fb"; }
+
+.fa-file-circle-check::before {
+  content: "\e5a0"; }
+
+.fa-forward::before {
+  content: "\f04e"; }
+
+.fa-mobile::before {
+  content: "\f3ce"; }
+
+.fa-mobile-android::before {
+  content: "\f3ce"; }
+
+.fa-mobile-phone::before {
+  content: "\f3ce"; }
+
+.fa-face-meh::before {
+  content: "\f11a"; }
+
+.fa-meh::before {
+  content: "\f11a"; }
+
+.fa-align-center::before {
+  content: "\f037"; }
+
+.fa-book-skull::before {
+  content: "\f6b7"; }
+
+.fa-book-dead::before {
+  content: "\f6b7"; }
+
+.fa-id-card::before {
+  content: "\f2c2"; }
+
+.fa-drivers-license::before {
+  content: "\f2c2"; }
+
+.fa-outdent::before {
+  content: "\f03b"; }
+
+.fa-dedent::before {
+  content: "\f03b"; }
+
+.fa-heart-circle-exclamation::before {
+  content: "\e4fe"; }
+
+.fa-house::before {
+  content: "\f015"; }
+
+.fa-home::before {
+  content: "\f015"; }
+
+.fa-home-alt::before {
+  content: "\f015"; }
+
+.fa-home-lg-alt::before {
+  content: "\f015"; }
+
+.fa-calendar-week::before {
+  content: "\f784"; }
+
+.fa-laptop-medical::before {
+  content: "\f812"; }
+
+.fa-b::before {
+  content: "\42"; }
+
+.fa-file-medical::before {
+  content: "\f477"; }
+
+.fa-dice-one::before {
+  content: "\f525"; }
+
+.fa-kiwi-bird::before {
+  content: "\f535"; }
+
+.fa-arrow-right-arrow-left::before {
+  content: "\f0ec"; }
+
+.fa-exchange::before {
+  content: "\f0ec"; }
+
+.fa-rotate-right::before {
+  content: "\f2f9"; }
+
+.fa-redo-alt::before {
+  content: "\f2f9"; }
+
+.fa-rotate-forward::before {
+  content: "\f2f9"; }
+
+.fa-utensils::before {
+  content: "\f2e7"; }
+
+.fa-cutlery::before {
+  content: "\f2e7"; }
+
+.fa-arrow-up-wide-short::before {
+  content: "\f161"; }
+
+.fa-sort-amount-up::before {
+  content: "\f161"; }
+
+.fa-mill-sign::before {
+  content: "\e1ed"; }
+
+.fa-bowl-rice::before {
+  content: "\e2eb"; }
+
+.fa-skull::before {
+  content: "\f54c"; }
+
+.fa-tower-broadcast::before {
+  content: "\f519"; }
+
+.fa-broadcast-tower::before {
+  content: "\f519"; }
+
+.fa-truck-pickup::before {
+  content: "\f63c"; }
+
+.fa-up-long::before {
+  content: "\f30c"; }
+
+.fa-long-arrow-alt-up::before {
+  content: "\f30c"; }
+
+.fa-stop::before {
+  content: "\f04d"; }
+
+.fa-code-merge::before {
+  content: "\f387"; }
+
+.fa-upload::before {
+  content: "\f093"; }
+
+.fa-hurricane::before {
+  content: "\f751"; }
+
+.fa-mound::before {
+  content: "\e52d"; }
+
+.fa-toilet-portable::before {
+  content: "\e583"; }
+
+.fa-compact-disc::before {
+  content: "\f51f"; }
+
+.fa-file-arrow-down::before {
+  content: "\f56d"; }
+
+.fa-file-download::before {
+  content: "\f56d"; }
+
+.fa-caravan::before {
+  content: "\f8ff"; }
+
+.fa-shield-cat::before {
+  content: "\e572"; }
+
+.fa-bolt::before {
+  content: "\f0e7"; }
+
+.fa-zap::before {
+  content: "\f0e7"; }
+
+.fa-glass-water::before {
+  content: "\e4f4"; }
+
+.fa-oil-well::before {
+  content: "\e532"; }
+
+.fa-vault::before {
+  content: "\e2c5"; }
+
+.fa-mars::before {
+  content: "\f222"; }
+
+.fa-toilet::before {
+  content: "\f7d8"; }
+
+.fa-plane-circle-xmark::before {
+  content: "\e557"; }
+
+.fa-yen-sign::before {
+  content: "\f157"; }
+
+.fa-cny::before {
+  content: "\f157"; }
+
+.fa-jpy::before {
+  content: "\f157"; }
+
+.fa-rmb::before {
+  content: "\f157"; }
+
+.fa-yen::before {
+  content: "\f157"; }
+
+.fa-ruble-sign::before {
+  content: "\f158"; }
+
+.fa-rouble::before {
+  content: "\f158"; }
+
+.fa-rub::before {
+  content: "\f158"; }
+
+.fa-ruble::before {
+  content: "\f158"; }
+
+.fa-sun::before {
+  content: "\f185"; }
+
+.fa-guitar::before {
+  content: "\f7a6"; }
+
+.fa-face-laugh-wink::before {
+  content: "\f59c"; }
+
+.fa-laugh-wink::before {
+  content: "\f59c"; }
+
+.fa-horse-head::before {
+  content: "\f7ab"; }
+
+.fa-bore-hole::before {
+  content: "\e4c3"; }
+
+.fa-industry::before {
+  content: "\f275"; }
+
+.fa-circle-down::before {
+  content: "\f358"; }
+
+.fa-arrow-alt-circle-down::before {
+  content: "\f358"; }
+
+.fa-arrows-turn-to-dots::before {
+  content: "\e4c1"; }
+
+.fa-florin-sign::before {
+  content: "\e184"; }
+
+.fa-arrow-down-short-wide::before {
+  content: "\f884"; }
+
+.fa-sort-amount-desc::before {
+  content: "\f884"; }
+
+.fa-sort-amount-down-alt::before {
+  content: "\f884"; }
+
+.fa-less-than::before {
+  content: "\3c"; }
+
+.fa-angle-down::before {
+  content: "\f107"; }
+
+.fa-car-tunnel::before {
+  content: "\e4de"; }
+
+.fa-head-side-cough::before {
+  content: "\e061"; }
+
+.fa-grip-lines::before {
+  content: "\f7a4"; }
+
+.fa-thumbs-down::before {
+  content: "\f165"; }
+
+.fa-user-lock::before {
+  content: "\f502"; }
+
+.fa-arrow-right-long::before {
+  content: "\f178"; }
+
+.fa-long-arrow-right::before {
+  content: "\f178"; }
+
+.fa-anchor-circle-xmark::before {
+  content: "\e4ac"; }
+
+.fa-ellipsis::before {
+  content: "\f141"; }
+
+.fa-ellipsis-h::before {
+  content: "\f141"; }
+
+.fa-chess-pawn::before {
+  content: "\f443"; }
+
+.fa-kit-medical::before {
+  content: "\f479"; }
+
+.fa-first-aid::before {
+  content: "\f479"; }
+
+.fa-person-through-window::before {
+  content: "\e5a9"; }
+
+.fa-toolbox::before {
+  content: "\f552"; }
+
+.fa-hands-holding-circle::before {
+  content: "\e4fb"; }
+
+.fa-bug::before {
+  content: "\f188"; }
+
+.fa-credit-card::before {
+  content: "\f09d"; }
+
+.fa-credit-card-alt::before {
+  content: "\f09d"; }
+
+.fa-car::before {
+  content: "\f1b9"; }
+
+.fa-automobile::before {
+  content: "\f1b9"; }
+
+.fa-hand-holding-hand::before {
+  content: "\e4f7"; }
+
+.fa-book-open-reader::before {
+  content: "\f5da"; }
+
+.fa-book-reader::before {
+  content: "\f5da"; }
+
+.fa-mountain-sun::before {
+  content: "\e52f"; }
+
+.fa-arrows-left-right-to-line::before {
+  content: "\e4ba"; }
+
+.fa-dice-d20::before {
+  content: "\f6cf"; }
+
+.fa-truck-droplet::before {
+  content: "\e58c"; }
+
+.fa-file-circle-xmark::before {
+  content: "\e5a1"; }
+
+.fa-temperature-arrow-up::before {
+  content: "\e040"; }
+
+.fa-temperature-up::before {
+  content: "\e040"; }
+
+.fa-medal::before {
+  content: "\f5a2"; }
+
+.fa-bed::before {
+  content: "\f236"; }
+
+.fa-square-h::before {
+  content: "\f0fd"; }
+
+.fa-h-square::before {
+  content: "\f0fd"; }
+
+.fa-podcast::before {
+  content: "\f2ce"; }
+
+.fa-temperature-full::before {
+  content: "\f2c7"; }
+
+.fa-temperature-4::before {
+  content: "\f2c7"; }
+
+.fa-thermometer-4::before {
+  content: "\f2c7"; }
+
+.fa-thermometer-full::before {
+  content: "\f2c7"; }
+
+.fa-bell::before {
+  content: "\f0f3"; }
+
+.fa-superscript::before {
+  content: "\f12b"; }
+
+.fa-plug-circle-xmark::before {
+  content: "\e560"; }
+
+.fa-star-of-life::before {
+  content: "\f621"; }
+
+.fa-phone-slash::before {
+  content: "\f3dd"; }
+
+.fa-paint-roller::before {
+  content: "\f5aa"; }
+
+.fa-handshake-angle::before {
+  content: "\f4c4"; }
+
+.fa-hands-helping::before {
+  content: "\f4c4"; }
+
+.fa-location-dot::before {
+  content: "\f3c5"; }
+
+.fa-map-marker-alt::before {
+  content: "\f3c5"; }
+
+.fa-file::before {
+  content: "\f15b"; }
+
+.fa-greater-than::before {
+  content: "\3e"; }
+
+.fa-person-swimming::before {
+  content: "\f5c4"; }
+
+.fa-swimmer::before {
+  content: "\f5c4"; }
+
+.fa-arrow-down::before {
+  content: "\f063"; }
+
+.fa-droplet::before {
+  content: "\f043"; }
+
+.fa-tint::before {
+  content: "\f043"; }
+
+.fa-eraser::before {
+  content: "\f12d"; }
+
+.fa-earth-americas::before {
+  content: "\f57d"; }
+
+.fa-earth::before {
+  content: "\f57d"; }
+
+.fa-earth-america::before {
+  content: "\f57d"; }
+
+.fa-globe-americas::before {
+  content: "\f57d"; }
+
+.fa-person-burst::before {
+  content: "\e53b"; }
+
+.fa-dove::before {
+  content: "\f4ba"; }
+
+.fa-battery-empty::before {
+  content: "\f244"; }
+
+.fa-battery-0::before {
+  content: "\f244"; }
+
+.fa-socks::before {
+  content: "\f696"; }
+
+.fa-inbox::before {
+  content: "\f01c"; }
+
+.fa-section::before {
+  content: "\e447"; }
+
+.fa-gauge-high::before {
+  content: "\f625"; }
+
+.fa-tachometer-alt::before {
+  content: "\f625"; }
+
+.fa-tachometer-alt-fast::before {
+  content: "\f625"; }
+
+.fa-envelope-open-text::before {
+  content: "\f658"; }
+
+.fa-hospital::before {
+  content: "\f0f8"; }
+
+.fa-hospital-alt::before {
+  content: "\f0f8"; }
+
+.fa-hospital-wide::before {
+  content: "\f0f8"; }
+
+.fa-wine-bottle::before {
+  content: "\f72f"; }
+
+.fa-chess-rook::before {
+  content: "\f447"; }
+
+.fa-bars-staggered::before {
+  content: "\f550"; }
+
+.fa-reorder::before {
+  content: "\f550"; }
+
+.fa-stream::before {
+  content: "\f550"; }
+
+.fa-dharmachakra::before {
+  content: "\f655"; }
+
+.fa-hotdog::before {
+  content: "\f80f"; }
+
+.fa-person-walking-with-cane::before {
+  content: "\f29d"; }
+
+.fa-blind::before {
+  content: "\f29d"; }
+
+.fa-drum::before {
+  content: "\f569"; }
+
+.fa-ice-cream::before {
+  content: "\f810"; }
+
+.fa-heart-circle-bolt::before {
+  content: "\e4fc"; }
+
+.fa-fax::before {
+  content: "\f1ac"; }
+
+.fa-paragraph::before {
+  content: "\f1dd"; }
+
+.fa-check-to-slot::before {
+  content: "\f772"; }
+
+.fa-vote-yea::before {
+  content: "\f772"; }
+
+.fa-star-half::before {
+  content: "\f089"; }
+
+.fa-boxes-stacked::before {
+  content: "\f468"; }
+
+.fa-boxes::before {
+  content: "\f468"; }
+
+.fa-boxes-alt::before {
+  content: "\f468"; }
+
+.fa-link::before {
+  content: "\f0c1"; }
+
+.fa-chain::before {
+  content: "\f0c1"; }
+
+.fa-ear-listen::before {
+  content: "\f2a2"; }
+
+.fa-assistive-listening-systems::before {
+  content: "\f2a2"; }
+
+.fa-tree-city::before {
+  content: "\e587"; }
+
+.fa-play::before {
+  content: "\f04b"; }
+
+.fa-font::before {
+  content: "\f031"; }
+
+.fa-table-cells-row-lock::before {
+  content: "\e67a"; }
+
+.fa-rupiah-sign::before {
+  content: "\e23d"; }
+
+.fa-magnifying-glass::before {
+  content: "\f002"; }
+
+.fa-search::before {
+  content: "\f002"; }
+
+.fa-table-tennis-paddle-ball::before {
+  content: "\f45d"; }
+
+.fa-ping-pong-paddle-ball::before {
+  content: "\f45d"; }
+
+.fa-table-tennis::before {
+  content: "\f45d"; }
+
+.fa-person-dots-from-line::before {
+  content: "\f470"; }
+
+.fa-diagnoses::before {
+  content: "\f470"; }
+
+.fa-trash-can-arrow-up::before {
+  content: "\f82a"; }
+
+.fa-trash-restore-alt::before {
+  content: "\f82a"; }
+
+.fa-naira-sign::before {
+  content: "\e1f6"; }
+
+.fa-cart-arrow-down::before {
+  content: "\f218"; }
+
+.fa-walkie-talkie::before {
+  content: "\f8ef"; }
+
+.fa-file-pen::before {
+  content: "\f31c"; }
+
+.fa-file-edit::before {
+  content: "\f31c"; }
+
+.fa-receipt::before {
+  content: "\f543"; }
+
+.fa-square-pen::before {
+  content: "\f14b"; }
+
+.fa-pen-square::before {
+  content: "\f14b"; }
+
+.fa-pencil-square::before {
+  content: "\f14b"; }
+
+.fa-suitcase-rolling::before {
+  content: "\f5c1"; }
+
+.fa-person-circle-exclamation::before {
+  content: "\e53f"; }
+
+.fa-chevron-down::before {
+  content: "\f078"; }
+
+.fa-battery-full::before {
+  content: "\f240"; }
+
+.fa-battery::before {
+  content: "\f240"; }
+
+.fa-battery-5::before {
+  content: "\f240"; }
+
+.fa-skull-crossbones::before {
+  content: "\f714"; }
+
+.fa-code-compare::before {
+  content: "\e13a"; }
+
+.fa-list-ul::before {
+  content: "\f0ca"; }
+
+.fa-list-dots::before {
+  content: "\f0ca"; }
+
+.fa-school-lock::before {
+  content: "\e56f"; }
+
+.fa-tower-cell::before {
+  content: "\e585"; }
+
+.fa-down-long::before {
+  content: "\f309"; }
+
+.fa-long-arrow-alt-down::before {
+  content: "\f309"; }
+
+.fa-ranking-star::before {
+  content: "\e561"; }
+
+.fa-chess-king::before {
+  content: "\f43f"; }
+
+.fa-person-harassing::before {
+  content: "\e549"; }
+
+.fa-brazilian-real-sign::before {
+  content: "\e46c"; }
+
+.fa-landmark-dome::before {
+  content: "\f752"; }
+
+.fa-landmark-alt::before {
+  content: "\f752"; }
+
+.fa-arrow-up::before {
+  content: "\f062"; }
+
+.fa-tv::before {
+  content: "\f26c"; }
+
+.fa-television::before {
+  content: "\f26c"; }
+
+.fa-tv-alt::before {
+  content: "\f26c"; }
+
+.fa-shrimp::before {
+  content: "\e448"; }
+
+.fa-list-check::before {
+  content: "\f0ae"; }
+
+.fa-tasks::before {
+  content: "\f0ae"; }
+
+.fa-jug-detergent::before {
+  content: "\e519"; }
+
+.fa-circle-user::before {
+  content: "\f2bd"; }
+
+.fa-user-circle::before {
+  content: "\f2bd"; }
+
+.fa-user-shield::before {
+  content: "\f505"; }
+
+.fa-wind::before {
+  content: "\f72e"; }
+
+.fa-car-burst::before {
+  content: "\f5e1"; }
+
+.fa-car-crash::before {
+  content: "\f5e1"; }
+
+.fa-y::before {
+  content: "\59"; }
+
+.fa-person-snowboarding::before {
+  content: "\f7ce"; }
+
+.fa-snowboarding::before {
+  content: "\f7ce"; }
+
+.fa-truck-fast::before {
+  content: "\f48b"; }
+
+.fa-shipping-fast::before {
+  content: "\f48b"; }
+
+.fa-fish::before {
+  content: "\f578"; }
+
+.fa-user-graduate::before {
+  content: "\f501"; }
+
+.fa-circle-half-stroke::before {
+  content: "\f042"; }
+
+.fa-adjust::before {
+  content: "\f042"; }
+
+.fa-clapperboard::before {
+  content: "\e131"; }
+
+.fa-circle-radiation::before {
+  content: "\f7ba"; }
+
+.fa-radiation-alt::before {
+  content: "\f7ba"; }
+
+.fa-baseball::before {
+  content: "\f433"; }
+
+.fa-baseball-ball::before {
+  content: "\f433"; }
+
+.fa-jet-fighter-up::before {
+  content: "\e518"; }
+
+.fa-diagram-project::before {
+  content: "\f542"; }
+
+.fa-project-diagram::before {
+  content: "\f542"; }
+
+.fa-copy::before {
+  content: "\f0c5"; }
+
+.fa-volume-xmark::before {
+  content: "\f6a9"; }
+
+.fa-volume-mute::before {
+  content: "\f6a9"; }
+
+.fa-volume-times::before {
+  content: "\f6a9"; }
+
+.fa-hand-sparkles::before {
+  content: "\e05d"; }
+
+.fa-grip::before {
+  content: "\f58d"; }
+
+.fa-grip-horizontal::before {
+  content: "\f58d"; }
+
+.fa-share-from-square::before {
+  content: "\f14d"; }
+
+.fa-share-square::before {
+  content: "\f14d"; }
+
+.fa-child-combatant::before {
+  content: "\e4e0"; }
+
+.fa-child-rifle::before {
+  content: "\e4e0"; }
+
+.fa-gun::before {
+  content: "\e19b"; }
+
+.fa-square-phone::before {
+  content: "\f098"; }
+
+.fa-phone-square::before {
+  content: "\f098"; }
+
+.fa-plus::before {
+  content: "\2b"; }
+
+.fa-add::before {
+  content: "\2b"; }
+
+.fa-expand::before {
+  content: "\f065"; }
+
+.fa-computer::before {
+  content: "\e4e5"; }
+
+.fa-xmark::before {
+  content: "\f00d"; }
+
+.fa-close::before {
+  content: "\f00d"; }
+
+.fa-multiply::before {
+  content: "\f00d"; }
+
+.fa-remove::before {
+  content: "\f00d"; }
+
+.fa-times::before {
+  content: "\f00d"; }
+
+.fa-arrows-up-down-left-right::before {
+  content: "\f047"; }
+
+.fa-arrows::before {
+  content: "\f047"; }
+
+.fa-chalkboard-user::before {
+  content: "\f51c"; }
+
+.fa-chalkboard-teacher::before {
+  content: "\f51c"; }
+
+.fa-peso-sign::before {
+  content: "\e222"; }
+
+.fa-building-shield::before {
+  content: "\e4d8"; }
+
+.fa-baby::before {
+  content: "\f77c"; }
+
+.fa-users-line::before {
+  content: "\e592"; }
+
+.fa-quote-left::before {
+  content: "\f10d"; }
+
+.fa-quote-left-alt::before {
+  content: "\f10d"; }
+
+.fa-tractor::before {
+  content: "\f722"; }
+
+.fa-trash-arrow-up::before {
+  content: "\f829"; }
+
+.fa-trash-restore::before {
+  content: "\f829"; }
+
+.fa-arrow-down-up-lock::before {
+  content: "\e4b0"; }
+
+.fa-lines-leaning::before {
+  content: "\e51e"; }
+
+.fa-ruler-combined::before {
+  content: "\f546"; }
+
+.fa-copyright::before {
+  content: "\f1f9"; }
+
+.fa-equals::before {
+  content: "\3d"; }
+
+.fa-blender::before {
+  content: "\f517"; }
+
+.fa-teeth::before {
+  content: "\f62e"; }
+
+.fa-shekel-sign::before {
+  content: "\f20b"; }
+
+.fa-ils::before {
+  content: "\f20b"; }
+
+.fa-shekel::before {
+  content: "\f20b"; }
+
+.fa-sheqel::before {
+  content: "\f20b"; }
+
+.fa-sheqel-sign::before {
+  content: "\f20b"; }
+
+.fa-map::before {
+  content: "\f279"; }
+
+.fa-rocket::before {
+  content: "\f135"; }
+
+.fa-photo-film::before {
+  content: "\f87c"; }
+
+.fa-photo-video::before {
+  content: "\f87c"; }
+
+.fa-folder-minus::before {
+  content: "\f65d"; }
+
+.fa-store::before {
+  content: "\f54e"; }
+
+.fa-arrow-trend-up::before {
+  content: "\e098"; }
+
+.fa-plug-circle-minus::before {
+  content: "\e55e"; }
+
+.fa-sign-hanging::before {
+  content: "\f4d9"; }
+
+.fa-sign::before {
+  content: "\f4d9"; }
+
+.fa-bezier-curve::before {
+  content: "\f55b"; }
+
+.fa-bell-slash::before {
+  content: "\f1f6"; }
+
+.fa-tablet::before {
+  content: "\f3fb"; }
+
+.fa-tablet-android::before {
+  content: "\f3fb"; }
+
+.fa-school-flag::before {
+  content: "\e56e"; }
+
+.fa-fill::before {
+  content: "\f575"; }
+
+.fa-angle-up::before {
+  content: "\f106"; }
+
+.fa-drumstick-bite::before {
+  content: "\f6d7"; }
+
+.fa-holly-berry::before {
+  content: "\f7aa"; }
+
+.fa-chevron-left::before {
+  content: "\f053"; }
+
+.fa-bacteria::before {
+  content: "\e059"; }
+
+.fa-hand-lizard::before {
+  content: "\f258"; }
+
+.fa-notdef::before {
+  content: "\e1fe"; }
+
+.fa-disease::before {
+  content: "\f7fa"; }
+
+.fa-briefcase-medical::before {
+  content: "\f469"; }
+
+.fa-genderless::before {
+  content: "\f22d"; }
+
+.fa-chevron-right::before {
+  content: "\f054"; }
+
+.fa-retweet::before {
+  content: "\f079"; }
+
+.fa-car-rear::before {
+  content: "\f5de"; }
+
+.fa-car-alt::before {
+  content: "\f5de"; }
+
+.fa-pump-soap::before {
+  content: "\e06b"; }
+
+.fa-video-slash::before {
+  content: "\f4e2"; }
+
+.fa-battery-quarter::before {
+  content: "\f243"; }
+
+.fa-battery-2::before {
+  content: "\f243"; }
+
+.fa-radio::before {
+  content: "\f8d7"; }
+
+.fa-baby-carriage::before {
+  content: "\f77d"; }
+
+.fa-carriage-baby::before {
+  content: "\f77d"; }
+
+.fa-traffic-light::before {
+  content: "\f637"; }
+
+.fa-thermometer::before {
+  content: "\f491"; }
+
+.fa-vr-cardboard::before {
+  content: "\f729"; }
+
+.fa-hand-middle-finger::before {
+  content: "\f806"; }
+
+.fa-percent::before {
+  content: "\25"; }
+
+.fa-percentage::before {
+  content: "\25"; }
+
+.fa-truck-moving::before {
+  content: "\f4df"; }
+
+.fa-glass-water-droplet::before {
+  content: "\e4f5"; }
+
+.fa-display::before {
+  content: "\e163"; }
+
+.fa-face-smile::before {
+  content: "\f118"; }
+
+.fa-smile::before {
+  content: "\f118"; }
+
+.fa-thumbtack::before {
+  content: "\f08d"; }
+
+.fa-thumb-tack::before {
+  content: "\f08d"; }
+
+.fa-trophy::before {
+  content: "\f091"; }
+
+.fa-person-praying::before {
+  content: "\f683"; }
+
+.fa-pray::before {
+  content: "\f683"; }
+
+.fa-hammer::before {
+  content: "\f6e3"; }
+
+.fa-hand-peace::before {
+  content: "\f25b"; }
+
+.fa-rotate::before {
+  content: "\f2f1"; }
+
+.fa-sync-alt::before {
+  content: "\f2f1"; }
+
+.fa-spinner::before {
+  content: "\f110"; }
+
+.fa-robot::before {
+  content: "\f544"; }
+
+.fa-peace::before {
+  content: "\f67c"; }
+
+.fa-gears::before {
+  content: "\f085"; }
+
+.fa-cogs::before {
+  content: "\f085"; }
+
+.fa-warehouse::before {
+  content: "\f494"; }
+
+.fa-arrow-up-right-dots::before {
+  content: "\e4b7"; }
+
+.fa-splotch::before {
+  content: "\f5bc"; }
+
+.fa-face-grin-hearts::before {
+  content: "\f584"; }
+
+.fa-grin-hearts::before {
+  content: "\f584"; }
+
+.fa-dice-four::before {
+  content: "\f524"; }
+
+.fa-sim-card::before {
+  content: "\f7c4"; }
+
+.fa-transgender::before {
+  content: "\f225"; }
+
+.fa-transgender-alt::before {
+  content: "\f225"; }
+
+.fa-mercury::before {
+  content: "\f223"; }
+
+.fa-arrow-turn-down::before {
+  content: "\f149"; }
+
+.fa-level-down::before {
+  content: "\f149"; }
+
+.fa-person-falling-burst::before {
+  content: "\e547"; }
+
+.fa-award::before {
+  content: "\f559"; }
+
+.fa-ticket-simple::before {
+  content: "\f3ff"; }
+
+.fa-ticket-alt::before {
+  content: "\f3ff"; }
+
+.fa-building::before {
+  content: "\f1ad"; }
+
+.fa-angles-left::before {
+  content: "\f100"; }
+
+.fa-angle-double-left::before {
+  content: "\f100"; }
+
+.fa-qrcode::before {
+  content: "\f029"; }
+
+.fa-clock-rotate-left::before {
+  content: "\f1da"; }
+
+.fa-history::before {
+  content: "\f1da"; }
+
+.fa-face-grin-beam-sweat::before {
+  content: "\f583"; }
+
+.fa-grin-beam-sweat::before {
+  content: "\f583"; }
+
+.fa-file-export::before {
+  content: "\f56e"; }
+
+.fa-arrow-right-from-file::before {
+  content: "\f56e"; }
+
+.fa-shield::before {
+  content: "\f132"; }
+
+.fa-shield-blank::before {
+  content: "\f132"; }
+
+.fa-arrow-up-short-wide::before {
+  content: "\f885"; }
+
+.fa-sort-amount-up-alt::before {
+  content: "\f885"; }
+
+.fa-house-medical::before {
+  content: "\e3b2"; }
+
+.fa-golf-ball-tee::before {
+  content: "\f450"; }
+
+.fa-golf-ball::before {
+  content: "\f450"; }
+
+.fa-circle-chevron-left::before {
+  content: "\f137"; }
+
+.fa-chevron-circle-left::before {
+  content: "\f137"; }
+
+.fa-house-chimney-window::before {
+  content: "\e00d"; }
+
+.fa-pen-nib::before {
+  content: "\f5ad"; }
+
+.fa-tent-arrow-turn-left::before {
+  content: "\e580"; }
+
+.fa-tents::before {
+  content: "\e582"; }
+
+.fa-wand-magic::before {
+  content: "\f0d0"; }
+
+.fa-magic::before {
+  content: "\f0d0"; }
+
+.fa-dog::before {
+  content: "\f6d3"; }
+
+.fa-carrot::before {
+  content: "\f787"; }
+
+.fa-moon::before {
+  content: "\f186"; }
+
+.fa-wine-glass-empty::before {
+  content: "\f5ce"; }
+
+.fa-wine-glass-alt::before {
+  content: "\f5ce"; }
+
+.fa-cheese::before {
+  content: "\f7ef"; }
+
+.fa-yin-yang::before {
+  content: "\f6ad"; }
+
+.fa-music::before {
+  content: "\f001"; }
+
+.fa-code-commit::before {
+  content: "\f386"; }
+
+.fa-temperature-low::before {
+  content: "\f76b"; }
+
+.fa-person-biking::before {
+  content: "\f84a"; }
+
+.fa-biking::before {
+  content: "\f84a"; }
+
+.fa-broom::before {
+  content: "\f51a"; }
+
+.fa-shield-heart::before {
+  content: "\e574"; }
+
+.fa-gopuram::before {
+  content: "\f664"; }
+
+.fa-earth-oceania::before {
+  content: "\e47b"; }
+
+.fa-globe-oceania::before {
+  content: "\e47b"; }
+
+.fa-square-xmark::before {
+  content: "\f2d3"; }
+
+.fa-times-square::before {
+  content: "\f2d3"; }
+
+.fa-xmark-square::before {
+  content: "\f2d3"; }
+
+.fa-hashtag::before {
+  content: "\23"; }
+
+.fa-up-right-and-down-left-from-center::before {
+  content: "\f424"; }
+
+.fa-expand-alt::before {
+  content: "\f424"; }
+
+.fa-oil-can::before {
+  content: "\f613"; }
+
+.fa-t::before {
+  content: "\54"; }
+
+.fa-hippo::before {
+  content: "\f6ed"; }
+
+.fa-chart-column::before {
+  content: "\e0e3"; }
+
+.fa-infinity::before {
+  content: "\f534"; }
+
+.fa-vial-circle-check::before {
+  content: "\e596"; }
+
+.fa-person-arrow-down-to-line::before {
+  content: "\e538"; }
+
+.fa-voicemail::before {
+  content: "\f897"; }
+
+.fa-fan::before {
+  content: "\f863"; }
+
+.fa-person-walking-luggage::before {
+  content: "\e554"; }
+
+.fa-up-down::before {
+  content: "\f338"; }
+
+.fa-arrows-alt-v::before {
+  content: "\f338"; }
+
+.fa-cloud-moon-rain::before {
+  content: "\f73c"; }
+
+.fa-calendar::before {
+  content: "\f133"; }
+
+.fa-trailer::before {
+  content: "\e041"; }
+
+.fa-bahai::before {
+  content: "\f666"; }
+
+.fa-haykal::before {
+  content: "\f666"; }
+
+.fa-sd-card::before {
+  content: "\f7c2"; }
+
+.fa-dragon::before {
+  content: "\f6d5"; }
+
+.fa-shoe-prints::before {
+  content: "\f54b"; }
+
+.fa-circle-plus::before {
+  content: "\f055"; }
+
+.fa-plus-circle::before {
+  content: "\f055"; }
+
+.fa-face-grin-tongue-wink::before {
+  content: "\f58b"; }
+
+.fa-grin-tongue-wink::before {
+  content: "\f58b"; }
+
+.fa-hand-holding::before {
+  content: "\f4bd"; }
+
+.fa-plug-circle-exclamation::before {
+  content: "\e55d"; }
+
+.fa-link-slash::before {
+  content: "\f127"; }
+
+.fa-chain-broken::before {
+  content: "\f127"; }
+
+.fa-chain-slash::before {
+  content: "\f127"; }
+
+.fa-unlink::before {
+  content: "\f127"; }
+
+.fa-clone::before {
+  content: "\f24d"; }
+
+.fa-person-walking-arrow-loop-left::before {
+  content: "\e551"; }
+
+.fa-arrow-up-z-a::before {
+  content: "\f882"; }
+
+.fa-sort-alpha-up-alt::before {
+  content: "\f882"; }
+
+.fa-fire-flame-curved::before {
+  content: "\f7e4"; }
+
+.fa-fire-alt::before {
+  content: "\f7e4"; }
+
+.fa-tornado::before {
+  content: "\f76f"; }
+
+.fa-file-circle-plus::before {
+  content: "\e494"; }
+
+.fa-book-quran::before {
+  content: "\f687"; }
+
+.fa-quran::before {
+  content: "\f687"; }
+
+.fa-anchor::before {
+  content: "\f13d"; }
+
+.fa-border-all::before {
+  content: "\f84c"; }
+
+.fa-face-angry::before {
+  content: "\f556"; }
+
+.fa-angry::before {
+  content: "\f556"; }
+
+.fa-cookie-bite::before {
+  content: "\f564"; }
+
+.fa-arrow-trend-down::before {
+  content: "\e097"; }
+
+.fa-rss::before {
+  content: "\f09e"; }
+
+.fa-feed::before {
+  content: "\f09e"; }
+
+.fa-draw-polygon::before {
+  content: "\f5ee"; }
+
+.fa-scale-balanced::before {
+  content: "\f24e"; }
+
+.fa-balance-scale::before {
+  content: "\f24e"; }
+
+.fa-gauge-simple-high::before {
+  content: "\f62a"; }
+
+.fa-tachometer::before {
+  content: "\f62a"; }
+
+.fa-tachometer-fast::before {
+  content: "\f62a"; }
+
+.fa-shower::before {
+  content: "\f2cc"; }
+
+.fa-desktop::before {
+  content: "\f390"; }
+
+.fa-desktop-alt::before {
+  content: "\f390"; }
+
+.fa-m::before {
+  content: "\4d"; }
+
+.fa-table-list::before {
+  content: "\f00b"; }
+
+.fa-th-list::before {
+  content: "\f00b"; }
+
+.fa-comment-sms::before {
+  content: "\f7cd"; }
+
+.fa-sms::before {
+  content: "\f7cd"; }
+
+.fa-book::before {
+  content: "\f02d"; }
+
+.fa-user-plus::before {
+  content: "\f234"; }
+
+.fa-check::before {
+  content: "\f00c"; }
+
+.fa-battery-three-quarters::before {
+  content: "\f241"; }
+
+.fa-battery-4::before {
+  content: "\f241"; }
+
+.fa-house-circle-check::before {
+  content: "\e509"; }
+
+.fa-angle-left::before {
+  content: "\f104"; }
+
+.fa-diagram-successor::before {
+  content: "\e47a"; }
+
+.fa-truck-arrow-right::before {
+  content: "\e58b"; }
+
+.fa-arrows-split-up-and-left::before {
+  content: "\e4bc"; }
+
+.fa-hand-fist::before {
+  content: "\f6de"; }
+
+.fa-fist-raised::before {
+  content: "\f6de"; }
+
+.fa-cloud-moon::before {
+  content: "\f6c3"; }
+
+.fa-briefcase::before {
+  content: "\f0b1"; }
+
+.fa-person-falling::before {
+  content: "\e546"; }
+
+.fa-image-portrait::before {
+  content: "\f3e0"; }
+
+.fa-portrait::before {
+  content: "\f3e0"; }
+
+.fa-user-tag::before {
+  content: "\f507"; }
+
+.fa-rug::before {
+  content: "\e569"; }
+
+.fa-earth-europe::before {
+  content: "\f7a2"; }
+
+.fa-globe-europe::before {
+  content: "\f7a2"; }
+
+.fa-cart-flatbed-suitcase::before {
+  content: "\f59d"; }
+
+.fa-luggage-cart::before {
+  content: "\f59d"; }
+
+.fa-rectangle-xmark::before {
+  content: "\f410"; }
+
+.fa-rectangle-times::before {
+  content: "\f410"; }
+
+.fa-times-rectangle::before {
+  content: "\f410"; }
+
+.fa-window-close::before {
+  content: "\f410"; }
+
+.fa-baht-sign::before {
+  content: "\e0ac"; }
+
+.fa-book-open::before {
+  content: "\f518"; }
+
+.fa-book-journal-whills::before {
+  content: "\f66a"; }
+
+.fa-journal-whills::before {
+  content: "\f66a"; }
+
+.fa-handcuffs::before {
+  content: "\e4f8"; }
+
+.fa-triangle-exclamation::before {
+  content: "\f071"; }
+
+.fa-exclamation-triangle::before {
+  content: "\f071"; }
+
+.fa-warning::before {
+  content: "\f071"; }
+
+.fa-database::before {
+  content: "\f1c0"; }
+
+.fa-share::before {
+  content: "\f064"; }
+
+.fa-mail-forward::before {
+  content: "\f064"; }
+
+.fa-bottle-droplet::before {
+  content: "\e4c4"; }
+
+.fa-mask-face::before {
+  content: "\e1d7"; }
+
+.fa-hill-rockslide::before {
+  content: "\e508"; }
+
+.fa-right-left::before {
+  content: "\f362"; }
+
+.fa-exchange-alt::before {
+  content: "\f362"; }
+
+.fa-paper-plane::before {
+  content: "\f1d8"; }
+
+.fa-road-circle-exclamation::before {
+  content: "\e565"; }
+
+.fa-dungeon::before {
+  content: "\f6d9"; }
+
+.fa-align-right::before {
+  content: "\f038"; }
+
+.fa-money-bill-1-wave::before {
+  content: "\f53b"; }
+
+.fa-money-bill-wave-alt::before {
+  content: "\f53b"; }
+
+.fa-life-ring::before {
+  content: "\f1cd"; }
+
+.fa-hands::before {
+  content: "\f2a7"; }
+
+.fa-sign-language::before {
+  content: "\f2a7"; }
+
+.fa-signing::before {
+  content: "\f2a7"; }
+
+.fa-calendar-day::before {
+  content: "\f783"; }
+
+.fa-water-ladder::before {
+  content: "\f5c5"; }
+
+.fa-ladder-water::before {
+  content: "\f5c5"; }
+
+.fa-swimming-pool::before {
+  content: "\f5c5"; }
+
+.fa-arrows-up-down::before {
+  content: "\f07d"; }
+
+.fa-arrows-v::before {
+  content: "\f07d"; }
+
+.fa-face-grimace::before {
+  content: "\f57f"; }
+
+.fa-grimace::before {
+  content: "\f57f"; }
+
+.fa-wheelchair-move::before {
+  content: "\e2ce"; }
+
+.fa-wheelchair-alt::before {
+  content: "\e2ce"; }
+
+.fa-turn-down::before {
+  content: "\f3be"; }
+
+.fa-level-down-alt::before {
+  content: "\f3be"; }
+
+.fa-person-walking-arrow-right::before {
+  content: "\e552"; }
+
+.fa-square-envelope::before {
+  content: "\f199"; }
+
+.fa-envelope-square::before {
+  content: "\f199"; }
+
+.fa-dice::before {
+  content: "\f522"; }
+
+.fa-bowling-ball::before {
+  content: "\f436"; }
+
+.fa-brain::before {
+  content: "\f5dc"; }
+
+.fa-bandage::before {
+  content: "\f462"; }
+
+.fa-band-aid::before {
+  content: "\f462"; }
+
+.fa-calendar-minus::before {
+  content: "\f272"; }
+
+.fa-circle-xmark::before {
+  content: "\f057"; }
+
+.fa-times-circle::before {
+  content: "\f057"; }
+
+.fa-xmark-circle::before {
+  content: "\f057"; }
+
+.fa-gifts::before {
+  content: "\f79c"; }
+
+.fa-hotel::before {
+  content: "\f594"; }
+
+.fa-earth-asia::before {
+  content: "\f57e"; }
+
+.fa-globe-asia::before {
+  content: "\f57e"; }
+
+.fa-id-card-clip::before {
+  content: "\f47f"; }
+
+.fa-id-card-alt::before {
+  content: "\f47f"; }
+
+.fa-magnifying-glass-plus::before {
+  content: "\f00e"; }
+
+.fa-search-plus::before {
+  content: "\f00e"; }
+
+.fa-thumbs-up::before {
+  content: "\f164"; }
+
+.fa-user-clock::before {
+  content: "\f4fd"; }
+
+.fa-hand-dots::before {
+  content: "\f461"; }
+
+.fa-allergies::before {
+  content: "\f461"; }
+
+.fa-file-invoice::before {
+  content: "\f570"; }
+
+.fa-window-minimize::before {
+  content: "\f2d1"; }
+
+.fa-mug-saucer::before {
+  content: "\f0f4"; }
+
+.fa-coffee::before {
+  content: "\f0f4"; }
+
+.fa-brush::before {
+  content: "\f55d"; }
+
+.fa-mask::before {
+  content: "\f6fa"; }
+
+.fa-magnifying-glass-minus::before {
+  content: "\f010"; }
+
+.fa-search-minus::before {
+  content: "\f010"; }
+
+.fa-ruler-vertical::before {
+  content: "\f548"; }
+
+.fa-user-large::before {
+  content: "\f406"; }
+
+.fa-user-alt::before {
+  content: "\f406"; }
+
+.fa-train-tram::before {
+  content: "\e5b4"; }
+
+.fa-user-nurse::before {
+  content: "\f82f"; }
+
+.fa-syringe::before {
+  content: "\f48e"; }
+
+.fa-cloud-sun::before {
+  content: "\f6c4"; }
+
+.fa-stopwatch-20::before {
+  content: "\e06f"; }
+
+.fa-square-full::before {
+  content: "\f45c"; }
+
+.fa-magnet::before {
+  content: "\f076"; }
+
+.fa-jar::before {
+  content: "\e516"; }
+
+.fa-note-sticky::before {
+  content: "\f249"; }
+
+.fa-sticky-note::before {
+  content: "\f249"; }
+
+.fa-bug-slash::before {
+  content: "\e490"; }
+
+.fa-arrow-up-from-water-pump::before {
+  content: "\e4b6"; }
+
+.fa-bone::before {
+  content: "\f5d7"; }
+
+.fa-user-injured::before {
+  content: "\f728"; }
+
+.fa-face-sad-tear::before {
+  content: "\f5b4"; }
+
+.fa-sad-tear::before {
+  content: "\f5b4"; }
+
+.fa-plane::before {
+  content: "\f072"; }
+
+.fa-tent-arrows-down::before {
+  content: "\e581"; }
+
+.fa-exclamation::before {
+  content: "\21"; }
+
+.fa-arrows-spin::before {
+  content: "\e4bb"; }
+
+.fa-print::before {
+  content: "\f02f"; }
+
+.fa-turkish-lira-sign::before {
+  content: "\e2bb"; }
+
+.fa-try::before {
+  content: "\e2bb"; }
+
+.fa-turkish-lira::before {
+  content: "\e2bb"; }
+
+.fa-dollar-sign::before {
+  content: "\24"; }
+
+.fa-dollar::before {
+  content: "\24"; }
+
+.fa-usd::before {
+  content: "\24"; }
+
+.fa-x::before {
+  content: "\58"; }
+
+.fa-magnifying-glass-dollar::before {
+  content: "\f688"; }
+
+.fa-search-dollar::before {
+  content: "\f688"; }
+
+.fa-users-gear::before {
+  content: "\f509"; }
+
+.fa-users-cog::before {
+  content: "\f509"; }
+
+.fa-person-military-pointing::before {
+  content: "\e54a"; }
+
+.fa-building-columns::before {
+  content: "\f19c"; }
+
+.fa-bank::before {
+  content: "\f19c"; }
+
+.fa-institution::before {
+  content: "\f19c"; }
+
+.fa-museum::before {
+  content: "\f19c"; }
+
+.fa-university::before {
+  content: "\f19c"; }
+
+.fa-umbrella::before {
+  content: "\f0e9"; }
+
+.fa-trowel::before {
+  content: "\e589"; }
+
+.fa-d::before {
+  content: "\44"; }
+
+.fa-stapler::before {
+  content: "\e5af"; }
+
+.fa-masks-theater::before {
+  content: "\f630"; }
+
+.fa-theater-masks::before {
+  content: "\f630"; }
+
+.fa-kip-sign::before {
+  content: "\e1c4"; }
+
+.fa-hand-point-left::before {
+  content: "\f0a5"; }
+
+.fa-handshake-simple::before {
+  content: "\f4c6"; }
+
+.fa-handshake-alt::before {
+  content: "\f4c6"; }
+
+.fa-jet-fighter::before {
+  content: "\f0fb"; }
+
+.fa-fighter-jet::before {
+  content: "\f0fb"; }
+
+.fa-square-share-nodes::before {
+  content: "\f1e1"; }
+
+.fa-share-alt-square::before {
+  content: "\f1e1"; }
+
+.fa-barcode::before {
+  content: "\f02a"; }
+
+.fa-plus-minus::before {
+  content: "\e43c"; }
+
+.fa-video::before {
+  content: "\f03d"; }
+
+.fa-video-camera::before {
+  content: "\f03d"; }
+
+.fa-graduation-cap::before {
+  content: "\f19d"; }
+
+.fa-mortar-board::before {
+  content: "\f19d"; }
+
+.fa-hand-holding-medical::before {
+  content: "\e05c"; }
+
+.fa-person-circle-check::before {
+  content: "\e53e"; }
+
+.fa-turn-up::before {
+  content: "\f3bf"; }
+
+.fa-level-up-alt::before {
+  content: "\f3bf"; }
+
+.sr-only,
+.fa-sr-only {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border-width: 0; }
+
+.sr-only-focusable:not(:focus),
+.fa-sr-only-focusable:not(:focus) {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border-width: 0; }
+:root, :host {
+  --fa-style-family-brands: 'Font Awesome 6 Brands';
+  --fa-font-brands: normal 400 1em/1 'Font Awesome 6 Brands'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Brands';
+  font-style: normal;
+  font-weight: 400;
+  font-display: block;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+.fab,
+.fa-brands {
+  font-weight: 400; }
+
+.fa-monero:before {
+  content: "\f3d0"; }
+
+.fa-hooli:before {
+  content: "\f427"; }
+
+.fa-yelp:before {
+  content: "\f1e9"; }
+
+.fa-cc-visa:before {
+  content: "\f1f0"; }
+
+.fa-lastfm:before {
+  content: "\f202"; }
+
+.fa-shopware:before {
+  content: "\f5b5"; }
+
+.fa-creative-commons-nc:before {
+  content: "\f4e8"; }
+
+.fa-aws:before {
+  content: "\f375"; }
+
+.fa-redhat:before {
+  content: "\f7bc"; }
+
+.fa-yoast:before {
+  content: "\f2b1"; }
+
+.fa-cloudflare:before {
+  content: "\e07d"; }
+
+.fa-ups:before {
+  content: "\f7e0"; }
+
+.fa-pixiv:before {
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+.fa-stack-exchange:before {
+  content: "\f18d"; }
+
+.fa-elementor:before {
+  content: "\f430"; }
+
+.fa-square-pied-piper:before {
+  content: "\e01e"; }
+
+.fa-pied-piper-square:before {
+  content: "\e01e"; }
+
+.fa-creative-commons-nd:before {
+  content: "\f4eb"; }
+
+.fa-palfed:before {
+  content: "\f3d8"; }
+
+.fa-superpowers:before {
+  content: "\f2dd"; }
+
+.fa-resolving:before {
+  content: "\f3e7"; }
+
+.fa-xbox:before {
+  content: "\f412"; }
+
+.fa-square-web-awesome-stroke:before {
+  content: "\e684"; }
+
+.fa-searchengin:before {
+  content: "\f3eb"; }
+
+.fa-tiktok:before {
+  content: "\e07b"; }
+
+.fa-square-facebook:before {
+  content: "\f082"; }
+
+.fa-facebook-square:before {
+  content: "\f082"; }
+
+.fa-renren:before {
+  content: "\f18b"; }
+
+.fa-linux:before {
+  content: "\f17c"; }
+
+.fa-glide:before {
+  content: "\f2a5"; }
+
+.fa-linkedin:before {
+  content: "\f08c"; }
+
+.fa-hubspot:before {
+  content: "\f3b2"; }
+
+.fa-deploydog:before {
+  content: "\f38e"; }
+
+.fa-twitch:before {
+  content: "\f1e8"; }
+
+.fa-ravelry:before {
+  content: "\f2d9"; }
+
+.fa-mixer:before {
+  content: "\e056"; }
+
+.fa-square-lastfm:before {
+  content: "\f203"; }
+
+.fa-lastfm-square:before {
+  content: "\f203"; }
+
+.fa-vimeo:before {
+  content: "\f40a"; }
+
+.fa-mendeley:before {
+  content: "\f7b3"; }
+
+.fa-uniregistry:before {
+  content: "\f404"; }
+
+.fa-figma:before {
+  content: "\f799"; }
+
+.fa-creative-commons-remix:before {
+  content: "\f4ee"; }
+
+.fa-cc-amazon-pay:before {
+  content: "\f42d"; }
+
+.fa-dropbox:before {
+  content: "\f16b"; }
+
+.fa-instagram:before {
+  content: "\f16d"; }
+
+.fa-cmplid:before {
+  content: "\e360"; }
+
+.fa-upwork:before {
+  content: "\e641"; }
+
+.fa-facebook:before {
+  content: "\f09a"; }
+
+.fa-gripfire:before {
+  content: "\f3ac"; }
+
+.fa-jedi-order:before {
+  content: "\f50e"; }
+
+.fa-uikit:before {
+  content: "\f403"; }
+
+.fa-fort-awesome-alt:before {
+  content: "\f3a3"; }
+
+.fa-phabricator:before {
+  content: "\f3db"; }
+
+.fa-ussunnah:before {
+  content: "\f407"; }
+
+.fa-earlybirds:before {
+  content: "\f39a"; }
+
+.fa-trade-federation:before {
+  content: "\f513"; }
+
+.fa-autoprefixer:before {
+  content: "\f41c"; }
+
+.fa-whatsapp:before {
+  content: "\f232"; }
+
+.fa-square-upwork:before {
+  content: "\e67c"; }
+
+.fa-slideshare:before {
+  content: "\f1e7"; }
+
+.fa-google-play:before {
+  content: "\f3ab"; }
+
+.fa-viadeo:before {
+  content: "\f2a9"; }
+
+.fa-line:before {
+  content: "\f3c0"; }
+
+.fa-google-drive:before {
+  content: "\f3aa"; }
+
+.fa-servicestack:before {
+  content: "\f3ec"; }
+
+.fa-simplybuilt:before {
+  content: "\f215"; }
+
+.fa-bitbucket:before {
+  content: "\f171"; }
+
+.fa-imdb:before {
+  content: "\f2d8"; }
+
+.fa-deezer:before {
+  content: "\e077"; }
+
+.fa-raspberry-pi:before {
+  content: "\f7bb"; }
+
+.fa-jira:before {
+  content: "\f7b1"; }
+
+.fa-docker:before {
+  content: "\f395"; }
+
+.fa-screenpal:before {
+  content: "\e570"; }
+
+.fa-bluetooth:before {
+  content: "\f293"; }
+
+.fa-gitter:before {
+  content: "\f426"; }
+
+.fa-d-and-d:before {
+  content: "\f38d"; }
+
+.fa-microblog:before {
+  content: "\e01a"; }
+
+.fa-cc-diners-club:before {
+  content: "\f24c"; }
+
+.fa-gg-circle:before {
+  content: "\f261"; }
+
+.fa-pied-piper-hat:before {
+  content: "\f4e5"; }
+
+.fa-kickstarter-k:before {
+  content: "\f3bc"; }
+
+.fa-yandex:before {
+  content: "\f413"; }
+
+.fa-readme:before {
+  content: "\f4d5"; }
+
+.fa-html5:before {
+  content: "\f13b"; }
+
+.fa-sellsy:before {
+  content: "\f213"; }
+
+.fa-square-web-awesome:before {
+  content: "\e683"; }
+
+.fa-sass:before {
+  content: "\f41e"; }
+
+.fa-wirsindhandwerk:before {
+  content: "\e2d0"; }
+
+.fa-wsh:before {
+  content: "\e2d0"; }
+
+.fa-buromobelexperte:before {
+  content: "\f37f"; }
+
+.fa-salesforce:before {
+  content: "\f83b"; }
+
+.fa-octopus-deploy:before {
+  content: "\e082"; }
+
+.fa-medapps:before {
+  content: "\f3c6"; }
+
+.fa-ns8:before {
+  content: "\f3d5"; }
+
+.fa-pinterest-p:before {
+  content: "\f231"; }
+
+.fa-apper:before {
+  content: "\f371"; }
+
+.fa-fort-awesome:before {
+  content: "\f286"; }
+
+.fa-waze:before {
+  content: "\f83f"; }
+
+.fa-bluesky:before {
+  content: "\e671"; }
+
+.fa-cc-jcb:before {
+  content: "\f24b"; }
+
+.fa-snapchat:before {
+  content: "\f2ab"; }
+
+.fa-snapchat-ghost:before {
+  content: "\f2ab"; }
+
+.fa-fantasy-flight-games:before {
+  content: "\f6dc"; }
+
+.fa-rust:before {
+  content: "\e07a"; }
+
+.fa-wix:before {
+  content: "\f5cf"; }
+
+.fa-square-behance:before {
+  content: "\f1b5"; }
+
+.fa-behance-square:before {
+  content: "\f1b5"; }
+
+.fa-supple:before {
+  content: "\f3f9"; }
+
+.fa-webflow:before {
+  content: "\e65c"; }
+
+.fa-rebel:before {
+  content: "\f1d0"; }
+
+.fa-css3:before {
+  content: "\f13c"; }
+
+.fa-staylinked:before {
+  content: "\f3f5"; }
+
+.fa-kaggle:before {
+  content: "\f5fa"; }
+
+.fa-space-awesome:before {
+  content: "\e5ac"; }
+
+.fa-deviantart:before {
+  content: "\f1bd"; }
+
+.fa-cpanel:before {
+  content: "\f388"; }
+
+.fa-goodreads-g:before {
+  content: "\f3a9"; }
+
+.fa-square-git:before {
+  content: "\f1d2"; }
+
+.fa-git-square:before {
+  content: "\f1d2"; }
+
+.fa-square-tumblr:before {
+  content: "\f174"; }
+
+.fa-tumblr-square:before {
+  content: "\f174"; }
+
+.fa-trello:before {
+  content: "\f181"; }
+
+.fa-creative-commons-nc-jp:before {
+  content: "\f4ea"; }
+
+.fa-get-pocket:before {
+  content: "\f265"; }
+
+.fa-perbyte:before {
+  content: "\e083"; }
+
+.fa-grunt:before {
+  content: "\f3ad"; }
+
+.fa-weebly:before {
+  content: "\f5cc"; }
+
+.fa-connectdevelop:before {
+  content: "\f20e"; }
+
+.fa-leanpub:before {
+  content: "\f212"; }
+
+.fa-black-tie:before {
+  content: "\f27e"; }
+
+.fa-themeco:before {
+  content: "\f5c6"; }
+
+.fa-python:before {
+  content: "\f3e2"; }
+
+.fa-android:before {
+  content: "\f17b"; }
+
+.fa-bots:before {
+  content: "\e340"; }
+
+.fa-free-code-camp:before {
+  content: "\f2c5"; }
+
+.fa-hornbill:before {
+  content: "\f592"; }
+
+.fa-js:before {
+  content: "\f3b8"; }
+
+.fa-ideal:before {
+  content: "\e013"; }
+
+.fa-git:before {
+  content: "\f1d3"; }
+
+.fa-dev:before {
+  content: "\f6cc"; }
+
+.fa-sketch:before {
+  content: "\f7c6"; }
+
+.fa-yandex-international:before {
+  content: "\f414"; }
+
+.fa-cc-amex:before {
+  content: "\f1f3"; }
+
+.fa-uber:before {
+  content: "\f402"; }
+
+.fa-github:before {
+  content: "\f09b"; }
+
+.fa-php:before {
+  content: "\f457"; }
+
+.fa-alipay:before {
+  content: "\f642"; }
+
+.fa-youtube:before {
+  content: "\f167"; }
+
+.fa-skyatlas:before {
+  content: "\f216"; }
+
+.fa-firefox-browser:before {
+  content: "\e007"; }
+
+.fa-replyd:before {
+  content: "\f3e6"; }
+
+.fa-suse:before {
+  content: "\f7d6"; }
+
+.fa-jenkins:before {
+  content: "\f3b6"; }
+
+.fa-twitter:before {
+  content: "\f099"; }
+
+.fa-rockrms:before {
+  content: "\f3e9"; }
+
+.fa-pinterest:before {
+  content: "\f0d2"; }
+
+.fa-buffer:before {
+  content: "\f837"; }
+
+.fa-npm:before {
+  content: "\f3d4"; }
+
+.fa-yammer:before {
+  content: "\f840"; }
+
+.fa-btc:before {
+  content: "\f15a"; }
+
+.fa-dribbble:before {
+  content: "\f17d"; }
+
+.fa-stumbleupon-circle:before {
+  content: "\f1a3"; }
+
+.fa-internet-explorer:before {
+  content: "\f26b"; }
+
+.fa-stubber:before {
+  content: "\e5c7"; }
+
+.fa-telegram:before {
+  content: "\f2c6"; }
+
+.fa-telegram-plane:before {
+  content: "\f2c6"; }
+
+.fa-old-republic:before {
+  content: "\f510"; }
+
+.fa-odysee:before {
+  content: "\e5c6"; }
+
+.fa-square-whatsapp:before {
+  content: "\f40c"; }
+
+.fa-whatsapp-square:before {
+  content: "\f40c"; }
+
+.fa-node-js:before {
+  content: "\f3d3"; }
+
+.fa-edge-legacy:before {
+  content: "\e078"; }
+
+.fa-slack:before {
+  content: "\f198"; }
+
+.fa-slack-hash:before {
+  content: "\f198"; }
+
+.fa-medrt:before {
+  content: "\f3c8"; }
+
+.fa-usb:before {
+  content: "\f287"; }
+
+.fa-tumblr:before {
+  content: "\f173"; }
+
+.fa-vaadin:before {
+  content: "\f408"; }
+
+.fa-quora:before {
+  content: "\f2c4"; }
+
+.fa-square-x-twitter:before {
+  content: "\e61a"; }
+
+.fa-reacteurope:before {
+  content: "\f75d"; }
+
+.fa-medium:before {
+  content: "\f23a"; }
+
+.fa-medium-m:before {
+  content: "\f23a"; }
+
+.fa-amilia:before {
+  content: "\f36d"; }
+
+.fa-mixcloud:before {
+  content: "\f289"; }
+
+.fa-flipboard:before {
+  content: "\f44d"; }
+
+.fa-viacoin:before {
+  content: "\f237"; }
+
+.fa-critical-role:before {
+  content: "\f6c9"; }
+
+.fa-sitrox:before {
+  content: "\e44a"; }
+
+.fa-discourse:before {
+  content: "\f393"; }
+
+.fa-joomla:before {
+  content: "\f1aa"; }
+
+.fa-mastodon:before {
+  content: "\f4f6"; }
+
+.fa-airbnb:before {
+  content: "\f834"; }
+
+.fa-wolf-pack-battalion:before {
+  content: "\f514"; }
+
+.fa-buy-n-large:before {
+  content: "\f8a6"; }
+
+.fa-gulp:before {
+  content: "\f3ae"; }
+
+.fa-creative-commons-sampling-plus:before {
+  content: "\f4f1"; }
+
+.fa-strava:before {
+  content: "\f428"; }
+
+.fa-ember:before {
+  content: "\f423"; }
+
+.fa-canadian-maple-leaf:before {
+  content: "\f785"; }
+
+.fa-teamspeak:before {
+  content: "\f4f9"; }
+
+.fa-pushed:before {
+  content: "\f3e1"; }
+
+.fa-wordpress-simple:before {
+  content: "\f411"; }
+
+.fa-nutritionix:before {
+  content: "\f3d6"; }
+
+.fa-wodu:before {
+  content: "\e088"; }
+
+.fa-google-pay:before {
+  content: "\e079"; }
+
+.fa-intercom:before {
+  content: "\f7af"; }
+
+.fa-zhihu:before {
+  content: "\f63f"; }
+
+.fa-korvue:before {
+  content: "\f42f"; }
+
+.fa-pix:before {
+  content: "\e43a"; }
+
+.fa-steam-symbol:before {
+  content: "\f3f6"; }
+:root, :host {
+  --fa-style-family-classic: 'Font Awesome 6 Free';
+  --fa-font-regular: normal 400 1em/1 'Font Awesome 6 Free'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Free';
+  font-style: normal;
+  font-weight: 400;
+  font-display: block;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+
+.far,
+.fa-regular {
+  font-weight: 400; }
+:root, :host {
+  --fa-style-family-classic: 'Font Awesome 6 Free';
+  --fa-font-solid: normal 900 1em/1 'Font Awesome 6 Free'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Free';
+  font-style: normal;
+  font-weight: 900;
+  font-display: block;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+.fas,
+.fa-solid {
+  font-weight: 900; }
+@font-face {
+  font-family: 'Font Awesome 5 Brands';
+  font-display: block;
+  font-weight: 400;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'Font Awesome 5 Free';
+  font-display: block;
+  font-weight: 900;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'Font Awesome 5 Free';
+  font-display: block;
+  font-weight: 400;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-v4compatibility.woff2") format("woff2"), url("../webfonts/fa-v4compatibility.ttf") format("truetype"); }
diff --git a/docs/deps/font-awesome-6.5.2/css/all.min.css b/docs/deps/font-awesome-6.5.2/css/all.min.css
new file mode 100644
index 0000000..269bcee
--- /dev/null
+++ b/docs/deps/font-awesome-6.5.2/css/all.min.css
@@ -0,0 +1,9 @@
+/*!
+ * Font Awesome Free 6.5.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2024 Fonticons, Inc.
+ */
+.fa{font-family:var(--fa-style-family,"Font Awesome 6 Free");font-weight:var(--fa-style,900)}.fa,.fa-brands,.fa-classic,.fa-regular,.fa-sharp,.fa-solid,.fab,.far,.fas{-moz-osx-font-smoothing:grayscale;-webkit-font-smoothing:antialiased;display:var(--fa-display,inline-block);font-style:normal;font-variant:normal;line-height:1;text-rendering:auto}.fa-classic,.fa-regular,.fa-solid,.far,.fas{font-family:"Font Awesome 6 Free"}.fa-brands,.fab{font-family:"Font Awesome 6 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diff --git a/docs/deps/font-awesome-6.5.2/css/v4-shims.css b/docs/deps/font-awesome-6.5.2/css/v4-shims.css
new file mode 100644
index 0000000..ea60ea4
--- /dev/null
+++ b/docs/deps/font-awesome-6.5.2/css/v4-shims.css
@@ -0,0 +1,2194 @@
+/*!
+ * Font Awesome Free 6.5.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2024 Fonticons, Inc.
+ */
+.fa.fa-glass:before {
+  content: "\f000"; }
+
+.fa.fa-envelope-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-envelope-o:before {
+  content: "\f0e0"; }
+
+.fa.fa-star-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-o:before {
+  content: "\f005"; }
+
+.fa.fa-remove:before {
+  content: "\f00d"; }
+
+.fa.fa-close:before {
+  content: "\f00d"; }
+
+.fa.fa-gear:before {
+  content: "\f013"; }
+
+.fa.fa-trash-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-trash-o:before {
+  content: "\f2ed"; }
+
+.fa.fa-home:before {
+  content: "\f015"; }
+
+.fa.fa-file-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-file-o:before {
+  content: "\f15b"; }
+
+.fa.fa-clock-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-clock-o:before {
+  content: "\f017"; }
+
+.fa.fa-arrow-circle-o-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-arrow-circle-o-down:before {
+  content: "\f358"; }
+
+.fa.fa-arrow-circle-o-up {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-arrow-circle-o-up:before {
+  content: "\f35b"; }
+
+.fa.fa-play-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-play-circle-o:before {
+  content: "\f144"; }
+
+.fa.fa-repeat:before {
+  content: "\f01e"; }
+
+.fa.fa-rotate-right:before {
+  content: "\f01e"; }
+
+.fa.fa-refresh:before {
+  content: "\f021"; }
+
+.fa.fa-list-alt {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-list-alt:before {
+  content: "\f022"; }
+
+.fa.fa-dedent:before {
+  content: "\f03b"; }
+
+.fa.fa-video-camera:before {
+  content: "\f03d"; }
+
+.fa.fa-picture-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-picture-o:before {
+  content: "\f03e"; }
+
+.fa.fa-photo {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-photo:before {
+  content: "\f03e"; }
+
+.fa.fa-image {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-image:before {
+  content: "\f03e"; }
+
+.fa.fa-map-marker:before {
+  content: "\f3c5"; }
+
+.fa.fa-pencil-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-pencil-square-o:before {
+  content: "\f044"; }
+
+.fa.fa-edit {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-edit:before {
+  content: "\f044"; }
+
+.fa.fa-share-square-o:before {
+  content: "\f14d"; }
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+.fa.fa-check-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-check-square-o:before {
+  content: "\f14a"; }
+
+.fa.fa-arrows:before {
+  content: "\f0b2"; }
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+.fa.fa-times-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+.fa.fa-times-circle-o:before {
+  content: "\f057"; }
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+.fa.fa-check-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+.fa.fa-check-circle-o:before {
+  content: "\f058"; }
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+.fa.fa-mail-forward:before {
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+  font-weight: 400; }
+
+.fa.fa-modx {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fort-awesome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-usb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-product-hunt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-mixcloud {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-scribd {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-pause-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-pause-circle-o:before {
+  content: "\f28b"; }
+
+.fa.fa-stop-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-stop-circle-o:before {
+  content: "\f28d"; }
+
+.fa.fa-bluetooth {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-bluetooth-b {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-gitlab {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpbeginner {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpforms {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-envira {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wheelchair-alt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wheelchair-alt:before {
+  content: "\f368"; }
+
+.fa.fa-question-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-question-circle-o:before {
+  content: "\f059"; }
+
+.fa.fa-volume-control-phone:before {
+  content: "\f2a0"; }
+
+.fa.fa-asl-interpreting:before {
+  content: "\f2a3"; }
+
+.fa.fa-deafness:before {
+  content: "\f2a4"; }
+
+.fa.fa-hard-of-hearing:before {
+  content: "\f2a4"; }
+
+.fa.fa-glide {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-glide-g {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-signing:before {
+  content: "\f2a7"; }
+
+.fa.fa-viadeo {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-viadeo-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-viadeo-square:before {
+  content: "\f2aa"; }
+
+.fa.fa-snapchat {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-ghost {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-ghost:before {
+  content: "\f2ab"; }
+
+.fa.fa-snapchat-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-square:before {
+  content: "\f2ad"; }
+
+.fa.fa-pied-piper {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-first-order {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-yoast {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-themeisle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-official {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-official:before {
+  content: "\f2b3"; }
+
+.fa.fa-google-plus-circle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-circle:before {
+  content: "\f2b3"; }
+
+.fa.fa-font-awesome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fa {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fa:before {
+  content: "\f2b4"; }
+
+.fa.fa-handshake-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-handshake-o:before {
+  content: "\f2b5"; }
+
+.fa.fa-envelope-open-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-envelope-open-o:before {
+  content: "\f2b6"; }
+
+.fa.fa-linode {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-address-book-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-address-book-o:before {
+  content: "\f2b9"; }
+
+.fa.fa-vcard:before {
+  content: "\f2bb"; }
+
+.fa.fa-address-card-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-address-card-o:before {
+  content: "\f2bb"; }
+
+.fa.fa-vcard-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-vcard-o:before {
+  content: "\f2bb"; }
+
+.fa.fa-user-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-user-circle-o:before {
+  content: "\f2bd"; }
+
+.fa.fa-user-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-user-o:before {
+  content: "\f007"; }
+
+.fa.fa-id-badge {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-drivers-license:before {
+  content: "\f2c2"; }
+
+.fa.fa-id-card-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-id-card-o:before {
+  content: "\f2c2"; }
+
+.fa.fa-drivers-license-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-drivers-license-o:before {
+  content: "\f2c2"; }
+
+.fa.fa-quora {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-free-code-camp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-telegram {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-thermometer-4:before {
+  content: "\f2c7"; }
+
+.fa.fa-thermometer:before {
+  content: "\f2c7"; }
+
+.fa.fa-thermometer-3:before {
+  content: "\f2c8"; }
+
+.fa.fa-thermometer-2:before {
+  content: "\f2c9"; }
+
+.fa.fa-thermometer-1:before {
+  content: "\f2ca"; }
+
+.fa.fa-thermometer-0:before {
+  content: "\f2cb"; }
+
+.fa.fa-bathtub:before {
+  content: "\f2cd"; }
+
+.fa.fa-s15:before {
+  content: "\f2cd"; }
+
+.fa.fa-window-maximize {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-window-restore {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-rectangle:before {
+  content: "\f410"; }
+
+.fa.fa-window-close-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-window-close-o:before {
+  content: "\f410"; }
+
+.fa.fa-times-rectangle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-rectangle-o:before {
+  content: "\f410"; }
+
+.fa.fa-bandcamp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-grav {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-etsy {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-imdb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-ravelry {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-eercast {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-eercast:before {
+  content: "\f2da"; }
+
+.fa.fa-snowflake-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-snowflake-o:before {
+  content: "\f2dc"; }
+
+.fa.fa-superpowers {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpexplorer {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-meetup {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
diff --git a/docs/deps/font-awesome-6.5.2/css/v4-shims.min.css b/docs/deps/font-awesome-6.5.2/css/v4-shims.min.css
new file mode 100644
index 0000000..09baf5f
--- /dev/null
+++ b/docs/deps/font-awesome-6.5.2/css/v4-shims.min.css
@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.5.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2024 Fonticons, Inc.
+ */
+.fa.fa-glass:before{content:"\f000"}.fa.fa-envelope-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-envelope-o:before{content:"\f0e0"}.fa.fa-star-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-star-o:before{content:"\f005"}.fa.fa-close:before,.fa.fa-remove:before{content:"\f00d"}.fa.fa-gear:before{content:"\f013"}.fa.fa-trash-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-trash-o:before{content:"\f2ed"}.fa.fa-home:before{content:"\f015"}.fa.fa-file-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-file-o:before{content:"\f15b"}.fa.fa-clock-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-clock-o:before{content:"\f017"}.fa.fa-arrow-circle-o-down{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-arrow-circle-o-down:before{content:"\f358"}.fa.fa-arrow-circle-o-up{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-arrow-circle-o-up:before{content:"\f35b"}.fa.fa-play-circle-o{font-family:"Font Awesome 6 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Awesome 6 Free";font-weight:400}.fa.fa-check-square-o:before{content:"\f14a"}.fa.fa-arrows:before{content:"\f0b2"}.fa.fa-times-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-times-circle-o:before{content:"\f057"}.fa.fa-check-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-check-circle-o:before{content:"\f058"}.fa.fa-mail-forward:before{content:"\f064"}.fa.fa-expand:before{content:"\f424"}.fa.fa-compress:before{content:"\f422"}.fa.fa-eye,.fa.fa-eye-slash{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-warning:before{content:"\f071"}.fa.fa-calendar:before{content:"\f073"}.fa.fa-arrows-v:before{content:"\f338"}.fa.fa-arrows-h:before{content:"\f337"}.fa.fa-bar-chart-o:before,.fa.fa-bar-chart:before{content:"\e0e3"}.fa.fa-twitter-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-twitter-square:before{content:"\f081"}.fa.fa-facebook-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-facebook-square:before{content:"\f082"}.fa.fa-gears:before{content:"\f085"}.fa.fa-thumbs-o-up{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-thumbs-o-up:before{content:"\f164"}.fa.fa-thumbs-o-down{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-thumbs-o-down:before{content:"\f165"}.fa.fa-heart-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-heart-o:before{content:"\f004"}.fa.fa-sign-out:before{content:"\f2f5"}.fa.fa-linkedin-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-linkedin-square:before{content:"\f08c"}.fa.fa-thumb-tack:before{content:"\f08d"}.fa.fa-external-link:before{content:"\f35d"}.fa.fa-sign-in:before{content:"\f2f6"}.fa.fa-github-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-github-square:before{content:"\f092"}.fa.fa-lemon-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-lemon-o:before{content:"\f094"}.fa.fa-square-o{font-family:"Font Awesome 6 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 <link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png">
 <script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
-<script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
-<link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet">
+<link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet">
 <script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="Help files for prioritzr Spatial Planning projects">
 <meta name="description" content="This package provides a range of tools for setting up, running and plotting a spatial plan using the prioritizr. It is only intended for use by the Mathematical Marine Ecology Lab at UQ, as it sets up projects using their approach and data sets.">
 <meta property="og:description" content="This package provides a range of tools for setting up, running and plotting a spatial plan using the prioritizr. It is only intended for use by the Mathematical Marine Ecology Lab at UQ, as it sets up projects using their approach and data sets.">
@@ -29,7 +29,7 @@
 
     <a class="navbar-brand me-2" href="index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 06fb05a..1127035 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -6,7 +6,7 @@ articles:
   GlobalFishingWatch: GlobalFishingWatch.html
   MultipleUse: MultipleUse.html
   spatialplanr: spatialplanr.html
-last_built: 2024-10-31T03:47Z
+last_built: 2024-12-10T05:20Z
 urls:
   reference: https://mathmarecol.github.io/spatialplanr/reference
   article: https://mathmarecol.github.io/spatialplanr/articles
diff --git a/docs/reference/CoralSeaVelocity.html b/docs/reference/CoralSeaVelocity.html
index 65a8832..2db3236 100644
--- a/docs/reference/CoralSeaVelocity.html
+++ b/docs/reference/CoralSeaVelocity.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Example climate velocity for the example region of the coral sea — CoralSeaVelocity • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Example climate velocity for the example region of the coral sea — CoralSeaVelocity"><meta name="description" content="tsf file containing climate velocity (SSP5-8.5) of the coral sea"><meta property="og:description" content="tsf file containing climate velocity (SSP5-8.5) of the coral sea"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Example climate velocity for the example region of the coral sea — CoralSeaVelocity • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Example climate velocity for the example region of the coral sea — CoralSeaVelocity"><meta name="description" content="tsf file containing climate velocity (SSP5-8.5) of the coral sea"><meta property="og:description" content="tsf file containing climate velocity (SSP5-8.5) of the coral sea"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/IUCN_IA_Targets.html b/docs/reference/IUCN_IA_Targets.html
index 5e3e4c4..05c1c1c 100644
--- a/docs/reference/IUCN_IA_Targets.html
+++ b/docs/reference/IUCN_IA_Targets.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets"><meta name="description" content="tbl_df file containing IUCN and IA targets of the selected species of the coral sea"><meta property="og:description" content="tbl_df file containing IUCN and IA targets of the selected species of the coral sea"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets"><meta name="description" content="tbl_df file containing IUCN and IA targets of the selected species of the coral sea"><meta property="og:description" content="tbl_df file containing IUCN and IA targets of the selected species of the coral sea"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/MPAsCoralSea.html b/docs/reference/MPAsCoralSea.html
index cc8c627..68845b2 100644
--- a/docs/reference/MPAsCoralSea.html
+++ b/docs/reference/MPAsCoralSea.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Current MPAs of the Coral Sea — MPAsCoralSea • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Current MPAs of the Coral Sea — MPAsCoralSea"><meta name="description" content="sf file containing the current marine protected areas of the coral sea"><meta property="og:description" content="sf file containing the current marine protected areas of the coral sea"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Current MPAs of the Coral Sea — MPAsCoralSea • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Current MPAs of the Coral Sea — MPAsCoralSea"><meta name="description" content="sf file containing the current marine protected areas of the coral sea"><meta property="og:description" content="sf file containing the current marine protected areas of the coral sea"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/dat_PUs.html b/docs/reference/dat_PUs.html
index 7881a68..ef60146 100644
--- a/docs/reference/dat_PUs.html
+++ b/docs/reference/dat_PUs.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Planning Units — dat_PUs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Planning Units — dat_PUs"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Planning Units — dat_PUs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Planning Units — dat_PUs"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/dat_bathy.html b/docs/reference/dat_bathy.html
index f530c1f..0656491 100644
--- a/docs/reference/dat_bathy.html
+++ b/docs/reference/dat_bathy.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Bathymetry Data — dat_bathy • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Bathymetry Data — dat_bathy"><meta name="description" content="Bathymetry data downloaded via the oceandatr package"><meta property="og:description" content="Bathymetry data downloaded via the oceandatr package"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Bathymetry Data — dat_bathy • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Bathymetry Data — dat_bathy"><meta name="description" content="Bathymetry data downloaded via the oceandatr package"><meta property="og:description" content="Bathymetry data downloaded via the oceandatr package"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/dat_bndry.html b/docs/reference/dat_bndry.html
index 8d7297f..4b2f88b 100644
--- a/docs/reference/dat_bndry.html
+++ b/docs/reference/dat_bndry.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Boundary of planning units — dat_bndry • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Boundary of planning units — dat_bndry"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Boundary of planning units — dat_bndry • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Boundary of planning units — dat_bndry"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/dat_category.html b/docs/reference/dat_category.html
index 2d47bda..a724525 100644
--- a/docs/reference/dat_category.html
+++ b/docs/reference/dat_category.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Category vector — dat_category • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Category vector — dat_category"><meta name="description" content="A tibble containing specific grouping of features"><meta property="og:description" content="A tibble containing specific grouping of features"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Category vector — dat_category • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Category vector — dat_category"><meta name="description" content="A tibble containing specific grouping of features"><meta property="og:description" content="A tibble containing specific grouping of features"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/dat_category2.html b/docs/reference/dat_category2.html
index 5a4def9..eebe011 100644
--- a/docs/reference/dat_category2.html
+++ b/docs/reference/dat_category2.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Category vector — dat_category2 • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Category vector — dat_category2"><meta name="description" content="A tibble containing specific grouping of features"><meta property="og:description" content="A tibble containing specific grouping of features"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Category vector — dat_category2 • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Category vector — dat_category2"><meta name="description" content="A tibble containing specific grouping of features"><meta property="og:description" content="A tibble containing specific grouping of features"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
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@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
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diff --git a/docs/reference/dat_clim.html b/docs/reference/dat_clim.html
index 3e5d5e5..0cf497c 100644
--- a/docs/reference/dat_clim.html
+++ b/docs/reference/dat_clim.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Climate metric data — dat_clim • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Climate metric data — dat_clim"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Climate metric data — dat_clim • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Climate metric data — dat_clim"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
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@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
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diff --git a/docs/reference/dat_mpas.html b/docs/reference/dat_mpas.html
index d0d049f..9ea4b9d 100644
--- a/docs/reference/dat_mpas.html
+++ b/docs/reference/dat_mpas.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>MPA Data — dat_mpas • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="MPA Data — dat_mpas"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>MPA Data — dat_mpas • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="MPA Data — dat_mpas"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
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diff --git a/docs/reference/dat_region.html b/docs/reference/dat_region.html
index fa7ff80..bc1c44c 100644
--- a/docs/reference/dat_region.html
+++ b/docs/reference/dat_region.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Regionalisation — dat_region • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Regionalisation — dat_region"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Regionalisation — dat_region • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Regionalisation — dat_region"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
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diff --git a/docs/reference/dat_species_bin.html b/docs/reference/dat_species_bin.html
index 4ad6538..c41aff7 100644
--- a/docs/reference/dat_species_bin.html
+++ b/docs/reference/dat_species_bin.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Binary Species Data — dat_species_bin • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Binary Species Data — dat_species_bin"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Binary Species Data — dat_species_bin • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Binary Species Data — dat_species_bin"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/dat_species_bin2.html b/docs/reference/dat_species_bin2.html
index 6244bc2..35088f5 100644
--- a/docs/reference/dat_species_bin2.html
+++ b/docs/reference/dat_species_bin2.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Binary Species Data 2 — dat_species_bin2 • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Binary Species Data 2 — dat_species_bin2"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Binary Species Data 2 — dat_species_bin2 • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Binary Species Data 2 — dat_species_bin2"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/dat_species_prob.html b/docs/reference/dat_species_prob.html
index e2195ed..a34cc3d 100644
--- a/docs/reference/dat_species_prob.html
+++ b/docs/reference/dat_species_prob.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Probability Species Data — dat_species_prob • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Probability Species Data — dat_species_prob"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Probability Species Data — dat_species_prob • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Probability Species Data — dat_species_prob"><meta name="description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:description" content="An sf dataframe of planning units for spatial prioritisation"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/index.html b/docs/reference/index.html
index ef3a71e..7dba9c5 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Package index • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Package index"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Package index • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Package index"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/pipe.html b/docs/reference/pipe.html
index d4d6ac2..6ffcf9f 100644
--- a/docs/reference/pipe.html
+++ b/docs/reference/pipe.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Pipe operator — %&gt;% • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Pipe operator — %&gt;%"><meta name="description" content="See magrittr::%&amp;gt;% for details."><meta property="og:description" content="See magrittr::%&amp;gt;% for details."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Pipe operator — %&gt;% • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Pipe operator — %&gt;%"><meta name="description" content="See magrittr::%&amp;gt;% for details."><meta property="og:description" content="See magrittr::%&amp;gt;% for details."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/spDataFiltered.html b/docs/reference/spDataFiltered.html
index c4bd52b..fbfc515 100644
--- a/docs/reference/spDataFiltered.html
+++ b/docs/reference/spDataFiltered.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Example data — spDataFiltered • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Example data — spDataFiltered"><meta name="description" content="Example data"><meta property="og:description" content="Example data"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Example data — spDataFiltered • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Example data — spDataFiltered"><meta name="description" content="Example data"><meta property="og:description" content="Example data"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/spatialplanr-package.html b/docs/reference/spatialplanr-package.html
index bf90e9b..ef3b7b0 100644
--- a/docs/reference/spatialplanr-package.html
+++ b/docs/reference/spatialplanr-package.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>spatialplanr: Help files for prioritzr Spatial Planning projects — spatialplanr-package • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="spatialplanr: Help files for prioritzr Spatial Planning projects — spatialplanr-package"><meta name="description" content="
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>spatialplanr: Help files for prioritzr Spatial Planning projects — spatialplanr-package • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="spatialplanr: Help files for prioritzr Spatial Planning projects — spatialplanr-package"><meta name="description" content="
 This package provides a range of tools for setting up, running and plotting a spatial plan using the prioritizr. It is only intended for use by the Mathematical Marine Ecology Lab at UQ, as it sets up projects using their approach and data sets."><meta property="og:description" content="
 This package provides a range of tools for setting up, running and plotting a spatial plan using the prioritizr. It is only intended for use by the Mathematical Marine Ecology Lab at UQ, as it sets up projects using their approach and data sets."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_apply_cutoffs.html b/docs/reference/splnr_apply_cutoffs.html
index 630ce17..5f48800 100644
--- a/docs/reference/splnr_apply_cutoffs.html
+++ b/docs/reference/splnr_apply_cutoffs.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to apply cutoffs to feature data — splnr_apply_cutoffs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to apply cutoffs to feature data — splnr_apply_cutoffs"><meta name="description" content="Function to apply cutoffs to feature data"><meta property="og:description" content="Function to apply cutoffs to feature data"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to apply cutoffs to feature data — splnr_apply_cutoffs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to apply cutoffs to feature data — splnr_apply_cutoffs"><meta name="description" content="Function to apply cutoffs to feature data"><meta property="og:description" content="Function to apply cutoffs to feature data"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_arrangeFeatures.html b/docs/reference/splnr_arrangeFeatures.html
index 485218c..f1188fb 100644
--- a/docs/reference/splnr_arrangeFeatures.html
+++ b/docs/reference/splnr_arrangeFeatures.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Ensure all features are in the same order. — splnr_arrangeFeatures • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Ensure all features are in the same order. — splnr_arrangeFeatures"><meta name="description" content="splnr_arrangeFeatures() sorts your data based on longitude and latitude values."><meta property="og:description" content="splnr_arrangeFeatures() sorts your data based on longitude and latitude values."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Ensure all features are in the same order. — splnr_arrangeFeatures • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Ensure all features are in the same order. — splnr_arrangeFeatures"><meta name="description" content="splnr_arrangeFeatures() sorts your data based on longitude and latitude values."><meta property="og:description" content="splnr_arrangeFeatures() sorts your data based on longitude and latitude values."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_climate_featureApproach.html b/docs/reference/splnr_climate_featureApproach.html
index bc11832..1851672 100644
--- a/docs/reference/splnr_climate_featureApproach.html
+++ b/docs/reference/splnr_climate_featureApproach.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to run the feature approach — splnr_climate_featureApproach • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to run the feature approach — splnr_climate_featureApproach"><meta name="description" content="Function to run the feature approach"><meta property="og:description" content="Function to run the feature approach"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to run the feature approach — splnr_climate_featureApproach • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to run the feature approach — splnr_climate_featureApproach"><meta name="description" content="Function to run the feature approach"><meta property="og:description" content="Function to run the feature approach"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -45,9 +45,9 @@
     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">splnr_climate_featureApproach</span><span class="op">(</span></span>
-<span>  <span class="va">featuresDF</span>,</span>
-<span>  <span class="va">metricDF</span>,</span>
-<span>  <span class="va">targetsDF</span>,</span>
+<span>  <span class="va">features</span>,</span>
+<span>  <span class="va">metric</span>,</span>
+<span>  <span class="va">targets</span>,</span>
 <span>  <span class="va">direction</span>,</span>
 <span>  percentile <span class="op">=</span> <span class="fl">35</span>,</span>
 <span>  refugiaTarget <span class="op">=</span> <span class="fl">0.3</span></span>
@@ -58,15 +58,15 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
 
 
-<dl><dt id="arg-featuresdf">featuresDF<a class="anchor" aria-label="anchor" href="#arg-featuresdf"></a></dt>
+<dl><dt id="arg-features">features<a class="anchor" aria-label="anchor" href="#arg-features"></a></dt>
 <dd><p>feature <code>sf</code>object</p></dd>
 
 
-<dt id="arg-metricdf">metricDF<a class="anchor" aria-label="anchor" href="#arg-metricdf"></a></dt>
-<dd><p>climate metric data.frame with 'metric' as the column name of the metric values per planning unit.</p></dd>
+<dt id="arg-metric">metric<a class="anchor" aria-label="anchor" href="#arg-metric"></a></dt>
+<dd><p>climate metric <code>sf</code> object with 'metric' as the column name of the metric values per planning unit.</p></dd>
 
 
-<dt id="arg-targetsdf">targetsDF<a class="anchor" aria-label="anchor" href="#arg-targetsdf"></a></dt>
+<dt id="arg-targets">targets<a class="anchor" aria-label="anchor" href="#arg-targets"></a></dt>
 <dd><p><code>data.frame</code>with list of features under "feature" column and their corresponding targets under "target" column</p></dd>
 
 
@@ -91,19 +91,18 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">Features</span> <span class="op">&lt;-</span> <span class="va">dat_species_bin</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">target</span> <span class="op">&lt;-</span> <span class="va">Features</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
+<span class="r-in"><span><span class="va">targets</span> <span class="op">&lt;-</span> <span class="va">Features</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_geometry.html" class="external-link">st_drop_geometry</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/stats/setNames.html" class="external-link">setNames</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"feature"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>target <span class="op">=</span> <span class="fl">0.3</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">metric_df</span> <span class="op">&lt;-</span> <span class="va">dat_clim</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="va">Feature_Approach</span> <span class="op">&lt;-</span> <span class="fu">splnr_climate_featureApproach</span><span class="op">(</span></span></span>
-<span class="r-in"><span>  featuresDF <span class="op">=</span> <span class="va">dat_species_bin</span>,</span></span>
-<span class="r-in"><span>  metricDF <span class="op">=</span> <span class="va">metric_df</span>, targetsDF <span class="op">=</span> <span class="va">target</span>, direction <span class="op">=</span> <span class="fl">1</span></span></span>
+<span class="r-in"><span>  features <span class="op">=</span> <span class="va">dat_species_bin</span>,</span></span>
+<span class="r-in"><span>  metric <span class="op">=</span> <span class="va">dat_clim</span>,</span></span>
+<span class="r-in"><span>  targets <span class="op">=</span> <span class="va">targets</span>,</span></span>
+<span class="r-in"><span>  direction <span class="op">=</span> <span class="fl">1</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "Higher values mean more climate-smart areas."</span>
 <span class="r-in"><span><span class="va">out_sf</span> <span class="op">&lt;-</span> <span class="va">Feature_Approach</span><span class="op">$</span><span class="va">Features</span></span></span>
diff --git a/docs/reference/splnr_climate_percentileApproach.html b/docs/reference/splnr_climate_percentileApproach.html
index 4006d93..2a52a76 100644
--- a/docs/reference/splnr_climate_percentileApproach.html
+++ b/docs/reference/splnr_climate_percentileApproach.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to run the percentile approach — splnr_climate_percentileApproach • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to run the percentile approach — splnr_climate_percentileApproach"><meta name="description" content="Function to run the percentile approach"><meta property="og:description" content="Function to run the percentile approach"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to run the percentile approach — splnr_climate_percentileApproach • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to run the percentile approach — splnr_climate_percentileApproach"><meta name="description" content="Function to run the percentile approach"><meta property="og:description" content="Function to run the percentile approach"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -45,9 +45,9 @@
     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">splnr_climate_percentileApproach</span><span class="op">(</span></span>
-<span>  <span class="va">featuresDF</span>,</span>
-<span>  <span class="va">metricDF</span>,</span>
-<span>  <span class="va">targetsDF</span>,</span>
+<span>  <span class="va">features</span>,</span>
+<span>  <span class="va">metric</span>,</span>
+<span>  <span class="va">targets</span>,</span>
 <span>  <span class="va">direction</span>,</span>
 <span>  percentile <span class="op">=</span> <span class="fl">35</span></span>
 <span><span class="op">)</span></span></code></pre></div>
@@ -57,15 +57,15 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
 
 
-<dl><dt id="arg-featuresdf">featuresDF<a class="anchor" aria-label="anchor" href="#arg-featuresdf"></a></dt>
+<dl><dt id="arg-features">features<a class="anchor" aria-label="anchor" href="#arg-features"></a></dt>
 <dd><p>feature <code>sf</code>object</p></dd>
 
 
-<dt id="arg-metricdf">metricDF<a class="anchor" aria-label="anchor" href="#arg-metricdf"></a></dt>
-<dd><p>climate metric data.frame with 'metric' as the column name of the metric values per planning unit.</p></dd>
+<dt id="arg-metric">metric<a class="anchor" aria-label="anchor" href="#arg-metric"></a></dt>
+<dd><p>climate metric <code>sf</code> object with 'metric' as the column name of the metric values per planning unit.</p></dd>
 
 
-<dt id="arg-targetsdf">targetsDF<a class="anchor" aria-label="anchor" href="#arg-targetsdf"></a></dt>
+<dt id="arg-targets">targets<a class="anchor" aria-label="anchor" href="#arg-targets"></a></dt>
 <dd><p><code>data.frame</code>with list of features under "feature" column and their corresponding targets under "target" column</p></dd>
 
 
@@ -84,21 +84,19 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">Features</span> <span class="op">&lt;-</span> <span class="va">dat_species_bin</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">target</span> <span class="op">&lt;-</span> <span class="va">Features</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
+<span class="r-in"><span><span class="va">targets</span> <span class="op">&lt;-</span> <span class="va">dat_species_bin</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_geometry.html" class="external-link">st_drop_geometry</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/stats/setNames.html" class="external-link">setNames</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"feature"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>target <span class="op">=</span> <span class="fl">0.3</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">metric_df</span> <span class="op">&lt;-</span> <span class="va">dat_clim</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="va">Percentile_Approach</span> <span class="op">&lt;-</span> <span class="fu">splnr_climate_percentileApproach</span><span class="op">(</span></span></span>
-<span class="r-in"><span>  featuresDF <span class="op">=</span> <span class="va">dat_species_bin</span>,</span></span>
-<span class="r-in"><span>  metricDF <span class="op">=</span> <span class="va">metric_df</span>, targetsDF <span class="op">=</span> <span class="va">target</span>, direction <span class="op">=</span> <span class="fl">1</span></span></span>
+<span class="r-in"><span>  features <span class="op">=</span> <span class="va">dat_species_bin</span>,</span></span>
+<span class="r-in"><span>  metric <span class="op">=</span> <span class="va">dat_clim</span>,</span></span>
+<span class="r-in"><span>  targets <span class="op">=</span> <span class="va">targets</span>,</span></span>
+<span class="r-in"><span>  direction <span class="op">=</span> <span class="fl">1</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "Higher values mean more climate-smart areas."</span>
 <span class="r-in"><span><span class="va">out_sf</span> <span class="op">&lt;-</span> <span class="va">Percentile_Approach</span><span class="op">$</span><span class="va">Features</span></span></span>
diff --git a/docs/reference/splnr_climate_priorityAreaApproach.html b/docs/reference/splnr_climate_priorityAreaApproach.html
index 07d5e73..0d364df 100644
--- a/docs/reference/splnr_climate_priorityAreaApproach.html
+++ b/docs/reference/splnr_climate_priorityAreaApproach.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach"><meta name="description" content="Function to run the climate-priority-area approach"><meta property="og:description" content="Function to run the climate-priority-area approach"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach"><meta name="description" content="Function to run the climate-priority-area approach"><meta property="og:description" content="Function to run the climate-priority-area approach"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -45,9 +45,9 @@
     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">splnr_climate_priorityAreaApproach</span><span class="op">(</span></span>
-<span>  <span class="va">featuresDF</span>,</span>
-<span>  <span class="va">metricDF</span>,</span>
-<span>  <span class="va">targetsDF</span>,</span>
+<span>  <span class="va">features</span>,</span>
+<span>  <span class="va">metric</span>,</span>
+<span>  <span class="va">targets</span>,</span>
 <span>  <span class="va">direction</span>,</span>
 <span>  percentile <span class="op">=</span> <span class="fl">5</span>,</span>
 <span>  refugiaTarget <span class="op">=</span> <span class="fl">1</span></span>
@@ -58,15 +58,15 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
 
 
-<dl><dt id="arg-featuresdf">featuresDF<a class="anchor" aria-label="anchor" href="#arg-featuresdf"></a></dt>
+<dl><dt id="arg-features">features<a class="anchor" aria-label="anchor" href="#arg-features"></a></dt>
 <dd><p>feature <code>sf</code>object</p></dd>
 
 
-<dt id="arg-metricdf">metricDF<a class="anchor" aria-label="anchor" href="#arg-metricdf"></a></dt>
-<dd><p>climate metric data.frame with 'metric' as the column name of the metric values per planning unit.</p></dd>
+<dt id="arg-metric">metric<a class="anchor" aria-label="anchor" href="#arg-metric"></a></dt>
+<dd><p>climate metric <code>sf</code> object with 'metric' as the column name of the metric values per planning unit.</p></dd>
 
 
-<dt id="arg-targetsdf">targetsDF<a class="anchor" aria-label="anchor" href="#arg-targetsdf"></a></dt>
+<dt id="arg-targets">targets<a class="anchor" aria-label="anchor" href="#arg-targets"></a></dt>
 <dd><p><code>data.frame</code>with list of features under "feature" column and their corresponding targets under "target" column</p></dd>
 
 
@@ -89,20 +89,19 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">Features</span> <span class="op">&lt;-</span> <span class="va">dat_species_bin</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">target</span> <span class="op">&lt;-</span> <span class="va">Features</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
+<span class="r-in"><span><span class="va">targets</span> <span class="op">&lt;-</span> <span class="va">dat_species_bin</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu">sf</span><span class="fu">::</span><span class="fu"><a href="https://r-spatial.github.io/sf/reference/st_geometry.html" class="external-link">st_drop_geometry</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/stats/setNames.html" class="external-link">setNames</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"feature"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="pipe.html">%&gt;%</a></span></span></span>
 <span class="r-in"><span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>target <span class="op">=</span> <span class="fl">0.3</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">metric_df</span> <span class="op">&lt;-</span> <span class="va">dat_clim</span></span></span>
-<span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="va">CPA_Approach</span> <span class="op">&lt;-</span> <span class="fu">splnr_climate_priorityAreaApproach</span><span class="op">(</span></span></span>
-<span class="r-in"><span>  featuresDF <span class="op">=</span> <span class="va">dat_species_bin</span>,</span></span>
-<span class="r-in"><span>  metricDF <span class="op">=</span> <span class="va">metric_df</span>, targetsDF <span class="op">=</span> <span class="va">target</span>, direction <span class="op">=</span> <span class="op">-</span><span class="fl">1</span></span></span>
+<span class="r-in"><span>  features <span class="op">=</span> <span class="va">dat_species_bin</span>,</span></span>
+<span class="r-in"><span>  metric <span class="op">=</span> <span class="va">dat_clim</span>,</span></span>
+<span class="r-in"><span>  targets <span class="op">=</span> <span class="va">targets</span>,</span></span>
+<span class="r-in"><span>  direction <span class="op">=</span> <span class="op">-</span><span class="fl">1</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">out_sf</span> <span class="op">&lt;-</span> <span class="va">CPA_Approach</span><span class="op">$</span><span class="va">Features</span></span></span>
 <span class="r-in"><span><span class="va">targets</span> <span class="op">&lt;-</span> <span class="va">CPA_Approach</span><span class="op">$</span><span class="va">Targets</span></span></span>
diff --git a/docs/reference/splnr_convert_regionalisation.html b/docs/reference/splnr_convert_regionalisation.html
index 6ca24cf..1a4a29a 100644
--- a/docs/reference/splnr_convert_regionalisation.html
+++ b/docs/reference/splnr_convert_regionalisation.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation"><meta name="description" content=""><meta property="og:description" content=""><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation"><meta name="description" content=""><meta property="og:description" content=""><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_convert_toPUs.html b/docs/reference/splnr_convert_toPUs.html
index 1ceb2cc..bf51e85 100644
--- a/docs/reference/splnr_convert_toPUs.html
+++ b/docs/reference/splnr_convert_toPUs.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to interpolate data onto Planning Units — splnr_convert_toPUs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to interpolate data onto Planning Units — splnr_convert_toPUs"><meta name="description" content=""><meta property="og:description" content=""><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to interpolate data onto Planning Units — splnr_convert_toPUs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to interpolate data onto Planning Units — splnr_convert_toPUs"><meta name="description" content=""><meta property="og:description" content=""><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_create_polygon.html b/docs/reference/splnr_create_polygon.html
index 2477302..ebaea99 100644
--- a/docs/reference/splnr_create_polygon.html
+++ b/docs/reference/splnr_create_polygon.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function for creating polygon — splnr_create_polygon • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function for creating polygon — splnr_create_polygon"><meta name="description" content="splnr_create_polygon() allows you to create a polygon based on longitude and latitude coordinates in your input data."><meta property="og:description" content="splnr_create_polygon() allows you to create a polygon based on longitude and latitude coordinates in your input data."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function for creating polygon — splnr_create_polygon • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function for creating polygon — splnr_create_polygon"><meta name="description" content="splnr_create_polygon() allows you to create a polygon based on longitude and latitude coordinates in your input data."><meta property="og:description" content="splnr_create_polygon() allows you to create a polygon based on longitude and latitude coordinates in your input data."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_featureNames.html b/docs/reference/splnr_featureNames.html
index dd62f04..c0a73bf 100644
--- a/docs/reference/splnr_featureNames.html
+++ b/docs/reference/splnr_featureNames.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Returns the feature names — splnr_featureNames • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Returns the feature names — splnr_featureNames"><meta name="description" content="splnr_featureNames() allows you to extract the names of features you want to pass to a prioritizr prioritization.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Returns the feature names — splnr_featureNames • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Returns the feature names — splnr_featureNames"><meta name="description" content="splnr_featureNames() allows you to extract the names of features you want to pass to a prioritizr prioritization.
 It requires an sf object input and returns the column names of the object excluding any columns you specify in the exclude argument."><meta property="og:description" content="splnr_featureNames() allows you to extract the names of features you want to pass to a prioritizr prioritization.
 It requires an sf object input and returns the column names of the object excluding any columns you specify in the exclude argument."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_get_IUCNRedList.html b/docs/reference/splnr_get_IUCNRedList.html
index 63de344..fae6bdf 100644
--- a/docs/reference/splnr_get_IUCNRedList.html
+++ b/docs/reference/splnr_get_IUCNRedList.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Match Species to IUCN RedList — splnr_get_IUCNRedList • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Match Species to IUCN RedList — splnr_get_IUCNRedList"><meta name="description" content="First of all you will need your own API key, an alphanumeric string provided by IUCN that you need to send in every request;
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Match Species to IUCN RedList — splnr_get_IUCNRedList • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Match Species to IUCN RedList — splnr_get_IUCNRedList"><meta name="description" content="First of all you will need your own API key, an alphanumeric string provided by IUCN that you need to send in every request;
 the following function takes you to their website, where you will need to fill up a form (it might take 1-2 days to receive your key)
 rl_use_iucn()
 Once you receive an email with your API key, set it up as an environmental variable (it MUST be named IUCN_REDLIST_KEY)
@@ -47,7 +47,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_get_MPAs.html b/docs/reference/splnr_get_MPAs.html
index 77f876e..5992c2a 100644
--- a/docs/reference/splnr_get_MPAs.html
+++ b/docs/reference/splnr_get_MPAs.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Get marine parks from the WDPA. — splnr_get_MPAs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Get marine parks from the WDPA. — splnr_get_MPAs"><meta name="description" content="This code is a wrapper for the wonderful wdpar package written by Jeffrey O. Hanson. This data is then interfaced with the planning units.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Get marine parks from the WDPA. — splnr_get_MPAs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Get marine parks from the WDPA. — splnr_get_MPAs"><meta name="description" content="This code is a wrapper for the wonderful wdpar package written by Jeffrey O. Hanson. This data is then interfaced with the planning units.
 An sf object is returned with the PU area covered by the selected marine protected areas."><meta property="og:description" content="This code is a wrapper for the wonderful wdpar package written by Jeffrey O. Hanson. This data is then interfaced with the planning units.
 An sf object is returned with the PU area covered by the selected marine protected areas."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -94,7 +94,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">dat</span> <span class="op">&lt;-</span> <span class="fu">splnr_get_MPAs</span><span class="op">(</span>PlanUnits <span class="op">=</span> <span class="va">dat_PUs</span>, Countries <span class="op">=</span> <span class="st">"Australia"</span><span class="op">)</span></span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #BBBB00;">!</span> importing local data (version Apr 2024); use "force=TRUE" if you need latest version.</span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> Linking to GEOS 3.13.0, GDAL 3.9.3, PROJ 9.5.0; sf_use_s2() is TRUE</span>
+<span class="r-msg co"><span class="r-pr">#&gt;</span> Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUE</span>
 <span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>attribute variables are assumed to be spatially constant throughout all geometries</span>
 <span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>attribute variables are assumed to be spatially constant throughout all geometries</span>
 <span class="r-in"><span></span></span>
diff --git a/docs/reference/splnr_get_boundary.html b/docs/reference/splnr_get_boundary.html
index eeb4432..fd6953d 100644
--- a/docs/reference/splnr_get_boundary.html
+++ b/docs/reference/splnr_get_boundary.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Get the boundary of the planning region. — splnr_get_boundary • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Get the boundary of the planning region. — splnr_get_boundary"><meta name="description" content="splnr_get_boundary() allows to create an sf object of your planning region either based on specific coordinate information, or rnaturalearth inputs such as ocean data. Creating a boundary is often the first step in conservation planning and a requirement for downstream function sin spatialplanr."><meta property="og:description" content="splnr_get_boundary() allows to create an sf object of your planning region either based on specific coordinate information, or rnaturalearth inputs such as ocean data. Creating a boundary is often the first step in conservation planning and a requirement for downstream function sin spatialplanr."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Get the boundary of the planning region. — splnr_get_boundary • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Get the boundary of the planning region. — splnr_get_boundary"><meta name="description" content="splnr_get_boundary() allows to create an sf object of your planning region either based on specific coordinate information, or rnaturalearth inputs such as ocean data. Creating a boundary is often the first step in conservation planning and a requirement for downstream function sin spatialplanr."><meta property="og:description" content="splnr_get_boundary() allows to create an sf object of your planning region either based on specific coordinate information, or rnaturalearth inputs such as ocean data. Creating a boundary is often the first step in conservation planning and a requirement for downstream function sin spatialplanr."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -76,7 +76,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">Bndry</span> <span class="op">&lt;-</span> <span class="fu">splnr_get_boundary</span><span class="op">(</span>Limits <span class="op">=</span> <span class="st">"North Atlantic Ocean"</span>, Type <span class="op">=</span> <span class="st">"Ocean"</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Reading layer `ne_10m_geography_marine_polys' from data source </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpUmnXWF/ne_10m_geography_marine_polys.shp' </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpvzaEZa/ne_10m_geography_marine_polys.shp' </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   using driver `ESRI Shapefile'</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Simple feature collection with 306 features and 37 fields</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Geometry type: MULTIPOLYGON</span>
diff --git a/docs/reference/splnr_get_distCoast.html b/docs/reference/splnr_get_distCoast.html
index cd7854c..771f39a 100644
--- a/docs/reference/splnr_get_distCoast.html
+++ b/docs/reference/splnr_get_distCoast.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast"><meta name="description" content="The code takes a sf object and return it updated with a new coastDistance column.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast"><meta name="description" content="The code takes a sf object and return it updated with a new coastDistance column.
 The output inherits the crs from this sf object so ensure it is in the correct projection for your needs"><meta property="og:description" content="The code takes a sf object and return it updated with a new coastDistance column.
 The output inherits the crs from this sf object so ensure it is in the correct projection for your needs"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -107,7 +107,7 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span>                            Type <span class="op">=</span> <span class="st">"Oceans"</span>,</span></span>
 <span class="r-in"><span>                            cCRS <span class="op">=</span> <span class="va">cCRS</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Reading layer `ne_10m_geography_marine_polys' from data source </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpUmnXWF/ne_10m_geography_marine_polys.shp' </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpvzaEZa/ne_10m_geography_marine_polys.shp' </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   using driver `ESRI Shapefile'</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Simple feature collection with 306 features and 37 fields</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Geometry type: MULTIPOLYGON</span>
diff --git a/docs/reference/splnr_get_featureRep.html b/docs/reference/splnr_get_featureRep.html
index e63c1b7..c408047 100644
--- a/docs/reference/splnr_get_featureRep.html
+++ b/docs/reference/splnr_get_featureRep.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Prepare data to plot how well targets are met — splnr_get_featureRep • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare data to plot how well targets are met — splnr_get_featureRep"><meta name="description" content="Prepare data to plot how well targets are met"><meta property="og:description" content="Prepare data to plot how well targets are met"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Prepare data to plot how well targets are met — splnr_get_featureRep • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare data to plot how well targets are met — splnr_get_featureRep"><meta name="description" content="Prepare data to plot how well targets are met"><meta property="og:description" content="Prepare data to plot how well targets are met"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -47,7 +47,7 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
     <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">splnr_get_featureRep</span><span class="op">(</span></span>
 <span>  <span class="va">soln</span>,</span>
 <span>  <span class="va">pDat</span>,</span>
-<span>  targetsDF <span class="op">=</span> <span class="cn">NA</span>,</span>
+<span>  targets <span class="op">=</span> <span class="cn">NA</span>,</span>
 <span>  climsmart <span class="op">=</span> <span class="cn">FALSE</span>,</span>
 <span>  climsmartApproach <span class="op">=</span> <span class="fl">0</span>,</span>
 <span>  solnCol <span class="op">=</span> <span class="st">"solution_1"</span></span>
@@ -66,7 +66,7 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 <dd><p>The <code>prioritizr</code> problem</p></dd>
 
 
-<dt id="arg-targetsdf">targetsDF<a class="anchor" aria-label="anchor" href="#arg-targetsdf"></a></dt>
+<dt id="arg-targets">targets<a class="anchor" aria-label="anchor" href="#arg-targets"></a></dt>
 <dd><p><code>data.frame</code>with list of features under "feature" column and their corresponding targets under "target" column</p></dd>
 
 
diff --git a/docs/reference/splnr_get_gfw.html b/docs/reference/splnr_get_gfw.html
index 6d7eeeb..d80a8d3 100644
--- a/docs/reference/splnr_get_gfw.html
+++ b/docs/reference/splnr_get_gfw.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw"><meta name="description" content='The possibilities offered by this function are explained in vignette("GlobalFishingWatch")'><meta property="og:description" content='The possibilities offered by this function are explained in vignette("GlobalFishingWatch")'><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw"><meta name="description" content='The possibilities offered by this function are explained in vignette("GlobalFishingWatch")'><meta property="og:description" content='The possibilities offered by this function are explained in vignette("GlobalFishingWatch")'><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_get_kappaCorrData.html b/docs/reference/splnr_get_kappaCorrData.html
index 5590820..1bb3314 100644
--- a/docs/reference/splnr_get_kappaCorrData.html
+++ b/docs/reference/splnr_get_kappaCorrData.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData"><meta name="description" content="Conservation planning often requires the comparison of the outputs of the solutions of different conservation problems.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData"><meta name="description" content="Conservation planning often requires the comparison of the outputs of the solutions of different conservation problems.
 One way to compare solutions is by correlating the solutions using Cohen's Kappa.
 splnr_get_kappaCorrData() takes a list of prioritizr solutions to perform the Cohen's Kappa correlation between the solution.
 The resulting correlation matrix is symmetrical along the main diagonal and contains Cohen's Kappa of pairwise correlation between the solutions.
@@ -15,7 +15,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_get_selFreq.html b/docs/reference/splnr_get_selFreq.html
index fa98198..54e9b3d 100644
--- a/docs/reference/splnr_get_selFreq.html
+++ b/docs/reference/splnr_get_selFreq.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq"><meta name="description" content="When multiple spatial plans are generated, we are often interested in how many times a planning unit is selected across an array of solutions. This array can either be a list of the solutions of different conservation problems or generated through a portfolio approach with prioritizr.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq"><meta name="description" content="When multiple spatial plans are generated, we are often interested in how many times a planning unit is selected across an array of solutions. This array can either be a list of the solutions of different conservation problems or generated through a portfolio approach with prioritizr.
 splnr_get_selFreq() allows you to calculate the selection frequency of each planning unit of either a list or a portfolio of solutions. The resulting sf object can be passed for visualization to the spatialplanr function splnr_plot_selectionFreq()."><meta property="og:description" content="When multiple spatial plans are generated, we are often interested in how many times a planning unit is selected across an array of solutions. This array can either be a list of the solutions of different conservation problems or generated through a portfolio approach with prioritizr.
 splnr_get_selFreq() allows you to calculate the selection frequency of each planning unit of either a list or a portfolio of solutions. The resulting sf object can be passed for visualization to the spatialplanr function splnr_plot_selectionFreq()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_gg_add.html b/docs/reference/splnr_gg_add.html
index 2781003..7c65697 100644
--- a/docs/reference/splnr_gg_add.html
+++ b/docs/reference/splnr_gg_add.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Add-ons for plotting — splnr_gg_add • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Add-ons for plotting — splnr_gg_add"><meta name="description" content="This function allows to customise plots in a simple and reproducible way, by
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Add-ons for plotting — splnr_gg_add • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Add-ons for plotting — splnr_gg_add"><meta name="description" content="This function allows to customise plots in a simple and reproducible way, by
 giving the option for several inputs that can be included in maps produced
 with the other functions of this package.It can be combined with the
 spatialplanr spatial plotting functions."><meta property="og:description" content="This function allows to customise plots in a simple and reproducible way, by
@@ -13,7 +13,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_match_names.html b/docs/reference/splnr_match_names.html
index 420c66f..99f0ad0 100644
--- a/docs/reference/splnr_match_names.html
+++ b/docs/reference/splnr_match_names.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Substitute numbers for all_names in regionalisations — splnr_match_names • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Substitute numbers for all_names in regionalisations — splnr_match_names"><meta name="description" content="Many regionalisations have numeric values in the shape files that correspond
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Substitute numbers for all_names in regionalisations — splnr_match_names • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Substitute numbers for all_names in regionalisations — splnr_match_names"><meta name="description" content="Many regionalisations have numeric values in the shape files that correspond
 to a vector of names. Here we provide a function to quickly replace the
 numbers with names."><meta property="og:description" content="Many regionalisations have numeric values in the shape files that correspond
 to a vector of names. Here we provide a function to quickly replace the
@@ -11,7 +11,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot-3.png b/docs/reference/splnr_plot-3.png
index 27746d7..f87f503 100644
Binary files a/docs/reference/splnr_plot-3.png and b/docs/reference/splnr_plot-3.png differ
diff --git a/docs/reference/splnr_plot.html b/docs/reference/splnr_plot.html
index 53fc2c9..33184e2 100644
--- a/docs/reference/splnr_plot.html
+++ b/docs/reference/splnr_plot.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to plot data. — splnr_plot • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to plot data. — splnr_plot"><meta name="description" content="(For now can replace splnr_plot_cost(), splnr_plot_binFeature(), splnr_plot_MPAs(), splnr_plot_featureNo())"><meta property="og:description" content="(For now can replace splnr_plot_cost(), splnr_plot_binFeature(), splnr_plot_MPAs(), splnr_plot_featureNo())"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function to plot data. — splnr_plot • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function to plot data. — splnr_plot"><meta name="description" content="(For now can replace splnr_plot_cost(), splnr_plot_binFeature(), splnr_plot_MPAs(), splnr_plot_featureNo())"><meta property="og:description" content="(For now can replace splnr_plot_cost(), splnr_plot_binFeature(), splnr_plot_MPAs(), splnr_plot_featureNo())"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_MPAs.html b/docs/reference/splnr_plot_MPAs.html
index 8f4ea39..0715ab2 100644
--- a/docs/reference/splnr_plot_MPAs.html
+++ b/docs/reference/splnr_plot_MPAs.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot MPAs — splnr_plot_MPAs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot MPAs — splnr_plot_MPAs"><meta name="description" content="splnr_plot_MPAs() allows to plot either the outline or the area of MPAs existing in the planning region (for example extracted with the spatialplanrfunction splnr_get_MPAs()) in a customisable way using ggplot2. This function requires an sf object containing the information whether a planning unit in the planning region lies within an MPA or not in a column called wdpa and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="splnr_plot_MPAs() allows to plot either the outline or the area of MPAs existing in the planning region (for example extracted with the spatialplanrfunction splnr_get_MPAs()) in a customisable way using ggplot2. This function requires an sf object containing the information whether a planning unit in the planning region lies within an MPA or not in a column called wdpa and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot MPAs — splnr_plot_MPAs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot MPAs — splnr_plot_MPAs"><meta name="description" content="splnr_plot_MPAs() allows to plot either the outline or the area of MPAs existing in the planning region (for example extracted with the spatialplanrfunction splnr_get_MPAs()) in a customisable way using ggplot2. This function requires an sf object containing the information whether a planning unit in the planning region lies within an MPA or not in a column called wdpa and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="splnr_plot_MPAs() allows to plot either the outline or the area of MPAs existing in the planning region (for example extracted with the spatialplanrfunction splnr_get_MPAs()) in a customisable way using ggplot2. This function requires an sf object containing the information whether a planning unit in the planning region lies within an MPA or not in a column called wdpa and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_binFeature.html b/docs/reference/splnr_plot_binFeature.html
index 3efa93e..31778c2 100644
--- a/docs/reference/splnr_plot_binFeature.html
+++ b/docs/reference/splnr_plot_binFeature.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot binary feature — splnr_plot_binFeature • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot binary feature — splnr_plot_binFeature"><meta name="description" content="splnr_plot_binFeature() allows to plot presences and absences of a feature in the planning region in a customisable way using ggplot2. This function requires an sf object with binary information of a feature(0 for absences and 1 for presences, for example created from continuous data with the spatialplanr function splnr_apply_cutoffs()). It outputs a ggobject and can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="splnr_plot_binFeature() allows to plot presences and absences of a feature in the planning region in a customisable way using ggplot2. This function requires an sf object with binary information of a feature(0 for absences and 1 for presences, for example created from continuous data with the spatialplanr function splnr_apply_cutoffs()). It outputs a ggobject and can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot binary feature — splnr_plot_binFeature • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot binary feature — splnr_plot_binFeature"><meta name="description" content="splnr_plot_binFeature() allows to plot presences and absences of a feature in the planning region in a customisable way using ggplot2. This function requires an sf object with binary information of a feature(0 for absences and 1 for presences, for example created from continuous data with the spatialplanr function splnr_apply_cutoffs()). It outputs a ggobject and can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="splnr_plot_binFeature() allows to plot presences and absences of a feature in the planning region in a customisable way using ggplot2. This function requires an sf object with binary information of a feature(0 for absences and 1 for presences, for example created from continuous data with the spatialplanr function splnr_apply_cutoffs()). It outputs a ggobject and can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_circBplot.html b/docs/reference/splnr_plot_circBplot.html
index 519e128..b87edd5 100644
--- a/docs/reference/splnr_plot_circBplot.html
+++ b/docs/reference/splnr_plot_circBplot.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot circular barplot — splnr_plot_circBplot • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot circular barplot — splnr_plot_circBplot"><meta name="description" content="Plot circular barplot"><meta property="og:description" content="Plot circular barplot"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot circular barplot — splnr_plot_circBplot • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot circular barplot — splnr_plot_circBplot"><meta name="description" content="Plot circular barplot"><meta property="og:description" content="Plot circular barplot"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_climData.html b/docs/reference/splnr_plot_climData.html
index f164590..d188754 100644
--- a/docs/reference/splnr_plot_climData.html
+++ b/docs/reference/splnr_plot_climData.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot climate data — splnr_plot_climData • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot climate data — splnr_plot_climData"><meta name="description" content="Plot climate data"><meta property="og:description" content="Plot climate data"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot climate data — splnr_plot_climData • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot climate data — splnr_plot_climData"><meta name="description" content="Plot climate data"><meta property="og:description" content="Plot climate data"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_climKernelDensity.html b/docs/reference/splnr_plot_climKernelDensity.html
index d9f59ee..77c291d 100644
--- a/docs/reference/splnr_plot_climKernelDensity.html
+++ b/docs/reference/splnr_plot_climKernelDensity.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity"><meta name="description" content="Kernel Density Plots for climate-smart spatial plans"><meta property="og:description" content="Kernel Density Plots for climate-smart spatial plans"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity"><meta name="description" content="Kernel Density Plots for climate-smart spatial plans"><meta property="og:description" content="Kernel Density Plots for climate-smart spatial plans"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -97,9 +97,9 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>target <span class="op">=</span> <span class="fl">0.3</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="va">CPA</span> <span class="op">&lt;-</span> <span class="fu"><a href="splnr_climate_priorityAreaApproach.html">splnr_climate_priorityAreaApproach</a></span><span class="op">(</span></span></span>
-<span class="r-in"><span>  featuresDF <span class="op">=</span> <span class="va">dat_species_bin</span>,</span></span>
-<span class="r-in"><span>  metricDF <span class="op">=</span> <span class="va">dat_clim</span>,</span></span>
-<span class="r-in"><span>  targetsDF <span class="op">=</span> <span class="va">target</span>,</span></span>
+<span class="r-in"><span>  features <span class="op">=</span> <span class="va">dat_species_bin</span>,</span></span>
+<span class="r-in"><span>  metric <span class="op">=</span> <span class="va">dat_clim</span>,</span></span>
+<span class="r-in"><span>  targets <span class="op">=</span> <span class="va">target</span>,</span></span>
 <span class="r-in"><span>  direction <span class="op">=</span> <span class="op">-</span><span class="fl">1</span>,</span></span>
 <span class="r-in"><span>  refugiaTarget <span class="op">=</span> <span class="fl">1</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
diff --git a/docs/reference/splnr_plot_comparison.html b/docs/reference/splnr_plot_comparison.html
index b89a34a..6f7c1af 100644
--- a/docs/reference/splnr_plot_comparison.html
+++ b/docs/reference/splnr_plot_comparison.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot solution comparison — splnr_plot_comparison • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot solution comparison — splnr_plot_comparison"><meta name="description" content="Conservation planning often requires the comparison of the outputs of the solutions of different conservation problems. One way to compare solutions is by spatially visualising the different planning units that were selected in two separate solutions to conservation problems.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot solution comparison — splnr_plot_comparison • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot solution comparison — splnr_plot_comparison"><meta name="description" content="Conservation planning often requires the comparison of the outputs of the solutions of different conservation problems. One way to compare solutions is by spatially visualising the different planning units that were selected in two separate solutions to conservation problems.
 splnr_plot_comparison() allows to map the differences of two solutions in customisable way using ggplot2. This function requires two separate sf objects each containing a solution_1 column indicating the binary solution (selected vs not selected) of a prioritizr conservation problem. It outputs a ggobject and can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="Conservation planning often requires the comparison of the outputs of the solutions of different conservation problems. One way to compare solutions is by spatially visualising the different planning units that were selected in two separate solutions to conservation problems.
 splnr_plot_comparison() allows to map the differences of two solutions in customisable way using ggplot2. This function requires two separate sf objects each containing a solution_1 column indicating the binary solution (selected vs not selected) of a prioritizr conservation problem. It outputs a ggobject and can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_corrMat.html b/docs/reference/splnr_plot_corrMat.html
index bd1a2c8..956f2f8 100644
--- a/docs/reference/splnr_plot_corrMat.html
+++ b/docs/reference/splnr_plot_corrMat.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot correlation matrices — splnr_plot_corrMat • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot correlation matrices — splnr_plot_corrMat"><meta name="description" content="Conservation planning often requires the comparison of the outputs of the solutions of different conservation problems.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot correlation matrices — splnr_plot_corrMat • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot correlation matrices — splnr_plot_corrMat"><meta name="description" content="Conservation planning often requires the comparison of the outputs of the solutions of different conservation problems.
 One way to compare solutions is by correlating the solutions using Cohen's Kappa. splnr_plot_corrMat() allows to visualize the correlation matrix of the different solutions (for example produced with the spatialplanr function splnr_get_kappaCorrData())."><meta property="og:description" content="Conservation planning often requires the comparison of the outputs of the solutions of different conservation problems.
 One way to compare solutions is by correlating the solutions using Cohen's Kappa. splnr_plot_corrMat() allows to visualize the correlation matrix of the different solutions (for example produced with the spatialplanr function splnr_get_kappaCorrData())."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_cost.html b/docs/reference/splnr_plot_cost.html
index 3ed0b29..f4129ef 100644
--- a/docs/reference/splnr_plot_cost.html
+++ b/docs/reference/splnr_plot_cost.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot cost — splnr_plot_cost • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot cost — splnr_plot_cost"><meta name="description" content="splnr_plot_cost() allows to plot cost within each planning units of a planning region in a customisable way using ggplot2. This function requires an sf object with a cost column and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="splnr_plot_cost() allows to plot cost within each planning units of a planning region in a customisable way using ggplot2. This function requires an sf object with a cost column and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot cost — splnr_plot_cost • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot cost — splnr_plot_cost"><meta name="description" content="splnr_plot_cost() allows to plot cost within each planning units of a planning region in a customisable way using ggplot2. This function requires an sf object with a cost column and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="splnr_plot_cost() allows to plot cost within each planning units of a planning region in a customisable way using ggplot2. This function requires an sf object with a cost column and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_costOverlay-1.png b/docs/reference/splnr_plot_costOverlay-1.png
index 74dc603..f6e0d7f 100644
Binary files a/docs/reference/splnr_plot_costOverlay-1.png and b/docs/reference/splnr_plot_costOverlay-1.png differ
diff --git a/docs/reference/splnr_plot_costOverlay.html b/docs/reference/splnr_plot_costOverlay.html
index b674724..3389906 100644
--- a/docs/reference/splnr_plot_costOverlay.html
+++ b/docs/reference/splnr_plot_costOverlay.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot cost overlay — splnr_plot_costOverlay • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot cost overlay — splnr_plot_costOverlay"><meta name="description" content="splnr_plot_costOverlay() allows to plot the cost of each planning units of a planning region on top of the solution of a conservation problem created with prioritizr in a customisable way using ggplot2. This function requires a solution as an sf object with a column called solution_1 as well as a cost column and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="splnr_plot_costOverlay() allows to plot the cost of each planning units of a planning region on top of the solution of a conservation problem created with prioritizr in a customisable way using ggplot2. This function requires a solution as an sf object with a column called solution_1 as well as a cost column and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot cost overlay — splnr_plot_costOverlay • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot cost overlay — splnr_plot_costOverlay"><meta name="description" content="splnr_plot_costOverlay() allows to plot the cost of each planning units of a planning region on top of the solution of a conservation problem created with prioritizr in a customisable way using ggplot2. This function requires a solution as an sf object with a column called solution_1 as well as a cost column and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="splnr_plot_costOverlay() allows to plot the cost of each planning units of a planning region on top of the solution of a conservation problem created with prioritizr in a customisable way using ggplot2. This function requires a solution as an sf object with a column called solution_1 as well as a cost column and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_featureNo.html b/docs/reference/splnr_plot_featureNo.html
index f6f55bd..502876c 100644
--- a/docs/reference/splnr_plot_featureNo.html
+++ b/docs/reference/splnr_plot_featureNo.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot number of features — splnr_plot_featureNo • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot number of features — splnr_plot_featureNo"><meta name="description" content="splnr_plot_featureNo() allows you to use ggplot2 to visually inspect the number of features per planning unit that are used as inputs in the conservation problem. When all features are species, this map can be seen as a visualisation of species richness in the planning region."><meta property="og:description" content="splnr_plot_featureNo() allows you to use ggplot2 to visually inspect the number of features per planning unit that are used as inputs in the conservation problem. When all features are species, this map can be seen as a visualisation of species richness in the planning region."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot number of features — splnr_plot_featureNo • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot number of features — splnr_plot_featureNo"><meta name="description" content="splnr_plot_featureNo() allows you to use ggplot2 to visually inspect the number of features per planning unit that are used as inputs in the conservation problem. When all features are species, this map can be seen as a visualisation of species richness in the planning region."><meta property="og:description" content="splnr_plot_featureNo() allows you to use ggplot2 to visually inspect the number of features per planning unit that are used as inputs in the conservation problem. When all features are species, this map can be seen as a visualisation of species richness in the planning region."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_featureRep.html b/docs/reference/splnr_plot_featureRep.html
index 63c9ea3..69fba2d 100644
--- a/docs/reference/splnr_plot_featureRep.html
+++ b/docs/reference/splnr_plot_featureRep.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot how well targets are met — splnr_plot_featureRep • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot how well targets are met — splnr_plot_featureRep"><meta name="description" content="Plot how well targets are met"><meta property="og:description" content="Plot how well targets are met"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot how well targets are met — splnr_plot_featureRep • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot how well targets are met — splnr_plot_featureRep"><meta name="description" content="Plot how well targets are met"><meta property="og:description" content="Plot how well targets are met"><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_importanceScore.html b/docs/reference/splnr_plot_importanceScore.html
index 01f93e2..b5799ef 100644
--- a/docs/reference/splnr_plot_importanceScore.html
+++ b/docs/reference/splnr_plot_importanceScore.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot importance score — splnr_plot_importanceScore • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot importance score — splnr_plot_importanceScore"><meta name="description" content="Importance scores are a mean to reflect the irreplaceability of a planning unit in the solution of a prioirtizr conservation problem. Based on the prioritizr package, splnr_plot_importanceScore() allows to visualize three different types of importance scores with ggplot2 that should be used based on the conservation problem at hand. The prioritizr development team generally recommend using the replacement cost score, however this might be not be feasible for conservation problems with many planning units or features."><meta property="og:description" content="Importance scores are a mean to reflect the irreplaceability of a planning unit in the solution of a prioirtizr conservation problem. Based on the prioritizr package, splnr_plot_importanceScore() allows to visualize three different types of importance scores with ggplot2 that should be used based on the conservation problem at hand. The prioritizr development team generally recommend using the replacement cost score, however this might be not be feasible for conservation problems with many planning units or features."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot importance score — splnr_plot_importanceScore • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot importance score — splnr_plot_importanceScore"><meta name="description" content="Importance scores are a mean to reflect the irreplaceability of a planning unit in the solution of a prioirtizr conservation problem. Based on the prioritizr package, splnr_plot_importanceScore() allows to visualize three different types of importance scores with ggplot2 that should be used based on the conservation problem at hand. The prioritizr development team generally recommend using the replacement cost score, however this might be not be feasible for conservation problems with many planning units or features."><meta property="og:description" content="Importance scores are a mean to reflect the irreplaceability of a planning unit in the solution of a prioirtizr conservation problem. Based on the prioritizr package, splnr_plot_importanceScore() allows to visualize three different types of importance scores with ggplot2 that should be used based on the conservation problem at hand. The prioritizr development team generally recommend using the replacement cost score, however this might be not be feasible for conservation problems with many planning units or features."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -112,6 +112,12 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="op">(</span><span class="fu">splnr_plot_importanceScore</span><span class="op">(</span>soln <span class="op">=</span> <span class="va">dat_soln</span>, pDat <span class="op">=</span> <span class="va">dat_problem</span>, method <span class="op">=</span> <span class="st">"Ferrier"</span>, decimals <span class="op">=</span> <span class="fl">4</span><span class="op">)</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Ferrier Score.</span>
+<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for &lt;e2&gt;</span>
+<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for &lt;89&gt;</span>
+<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for &lt;a5&gt;</span>
+<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for &lt;e2&gt;</span>
+<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for &lt;89&gt;</span>
+<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for &lt;a5&gt;</span>
 <span class="r-plt img"><img src="splnr_plot_importanceScore-1.png" alt="" width="700" height="433"></span>
 </code></pre></div>
     </div>
diff --git a/docs/reference/splnr_plot_selectionFreq.html b/docs/reference/splnr_plot_selectionFreq.html
index 1d59c1a..ccc735b 100644
--- a/docs/reference/splnr_plot_selectionFreq.html
+++ b/docs/reference/splnr_plot_selectionFreq.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq"><meta name="description" content="When multiple spatial plans are generated, we are often interested in how many times a planning unit is selected across an array of solutions. This array can either be made up of the solutions to different conservation problems or generated through a portfolio approach with prioritizr.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq"><meta name="description" content="When multiple spatial plans are generated, we are often interested in how many times a planning unit is selected across an array of solutions. This array can either be made up of the solutions to different conservation problems or generated through a portfolio approach with prioritizr.
 Either way, this function requires an sf object input that contains a column (selFreq) with the selection frequency of each planning unit that can be generated with the spatialplanrfunction splnr_get_selFreq(). splnr_plot_selectionFreq() allows to visualize this selection frequency using ggplot2. It outputs a ggobject and can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="When multiple spatial plans are generated, we are often interested in how many times a planning unit is selected across an array of solutions. This array can either be made up of the solutions to different conservation problems or generated through a portfolio approach with prioritizr.
 Either way, this function requires an sf object input that contains a column (selFreq) with the selection frequency of each planning unit that can be generated with the spatialplanrfunction splnr_get_selFreq(). splnr_plot_selectionFreq() allows to visualize this selection frequency using ggplot2. It outputs a ggobject and can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_plot_solution.html b/docs/reference/splnr_plot_solution.html
index 5efd709..7dae912 100644
--- a/docs/reference/splnr_plot_solution.html
+++ b/docs/reference/splnr_plot_solution.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot prioritizr solution — splnr_plot_solution • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot prioritizr solution — splnr_plot_solution"><meta name="description" content="splnr_plot_solution() allows to plot the solution of a prioritizr conservation problem with our without in a customisable way using ggplot2. This function requires a solution as an sf object with a column called solution_1 and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="splnr_plot_solution() allows to plot the solution of a prioritizr conservation problem with our without in a customisable way using ggplot2. This function requires a solution as an sf object with a column called solution_1 and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Plot prioritizr solution — splnr_plot_solution • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot prioritizr solution — splnr_plot_solution"><meta name="description" content="splnr_plot_solution() allows to plot the solution of a prioritizr conservation problem with our without in a customisable way using ggplot2. This function requires a solution as an sf object with a column called solution_1 and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:description" content="splnr_plot_solution() allows to plot the solution of a prioritizr conservation problem with our without in a customisable way using ggplot2. This function requires a solution as an sf object with a column called solution_1 and outputs a ggobject. It can be combined with the spatialplanr function splnr_gg_add()."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_replace_NAs.html b/docs/reference/splnr_replace_NAs.html
index d3b0a08..3e38edf 100644
--- a/docs/reference/splnr_replace_NAs.html
+++ b/docs/reference/splnr_replace_NAs.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs"><meta name="description" content="splnr_replace_NAs() allows you to replace NA values in your data with the value of the nearest neighbour.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs"><meta name="description" content="splnr_replace_NAs() allows you to replace NA values in your data with the value of the nearest neighbour.
 The nearest neighbour is determined using st_nearest_feature() from the sf package."><meta property="og:description" content="splnr_replace_NAs() allows you to replace NA values in your data with the value of the nearest neighbour.
 The nearest neighbour is determined using st_nearest_feature() from the sf package."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_scale_01.html b/docs/reference/splnr_scale_01.html
index f31ca53..6af1290 100644
--- a/docs/reference/splnr_scale_01.html
+++ b/docs/reference/splnr_scale_01.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Scale spatial layers to between 0 and 1 — splnr_scale_01 • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Scale spatial layers to between 0 and 1 — splnr_scale_01"><meta name="description" content="splnr_scale_01() allows you to re-scale your data from values that are greater than 1 to values that are between 0 and 1."><meta property="og:description" content="splnr_scale_01() allows you to re-scale your data from values that are greater than 1 to values that are between 0 and 1."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Scale spatial layers to between 0 and 1 — splnr_scale_01 • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Scale spatial layers to between 0 and 1 — splnr_scale_01"><meta name="description" content="splnr_scale_01() allows you to re-scale your data from values that are greater than 1 to values that are between 0 and 1."><meta property="og:description" content="splnr_scale_01() allows you to re-scale your data from values that are greater than 1 to values that are between 0 and 1."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_targets_byCategory.html b/docs/reference/splnr_targets_byCategory.html
index 71c38b1..95135eb 100644
--- a/docs/reference/splnr_targets_byCategory.html
+++ b/docs/reference/splnr_targets_byCategory.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Assign targets to all features by category — splnr_targets_byCategory • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assign targets to all features by category — splnr_targets_byCategory"><meta name="description" content="splnr_targets_byCategory() allows to assign targets for conservation planning based on species categories."><meta property="og:description" content="splnr_targets_byCategory() allows to assign targets for conservation planning based on species categories."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Assign targets to all features by category — splnr_targets_byCategory • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assign targets to all features by category — splnr_targets_byCategory"><meta name="description" content="splnr_targets_byCategory() allows to assign targets for conservation planning based on species categories."><meta property="og:description" content="splnr_targets_byCategory() allows to assign targets for conservation planning based on species categories."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_targets_byIUCN.html b/docs/reference/splnr_targets_byIUCN.html
index 2ce6772..f4c20fa 100644
--- a/docs/reference/splnr_targets_byIUCN.html
+++ b/docs/reference/splnr_targets_byIUCN.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Assign targets bu IUCN Red List categories — splnr_targets_byIUCN • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assign targets bu IUCN Red List categories — splnr_targets_byIUCN"><meta name="description" content='splnr_targets_byIUCN() allows to assign targets for species used in conservation planning based on IUCN categories. Species can be extracted based on IUCN categories with the spatoalplnrfunction splnr_get_IUCNRedList().
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Assign targets bu IUCN Red List categories — splnr_targets_byIUCN • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assign targets bu IUCN Red List categories — splnr_targets_byIUCN"><meta name="description" content='splnr_targets_byIUCN() allows to assign targets for species used in conservation planning based on IUCN categories. Species can be extracted based on IUCN categories with the spatoalplnrfunction splnr_get_IUCNRedList().
 Accessing the IUCN database requires a login token from rl_use_iucn() that needs to be added to the environment using Sys.setenv(IUCN_REDLIST_KEY = "[Your Token]"). You can start by running rredlist::rl_use_iucn().'><meta property="og:description" content='splnr_targets_byIUCN() allows to assign targets for species used in conservation planning based on IUCN categories. Species can be extracted based on IUCN categories with the spatoalplnrfunction splnr_get_IUCNRedList().
 Accessing the IUCN database requires a login token from rl_use_iucn() that needs to be added to the environment using Sys.setenv(IUCN_REDLIST_KEY = "[Your Token]"). You can start by running rredlist::rl_use_iucn().'><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/splnr_targets_byInverseArea.html b/docs/reference/splnr_targets_byInverseArea.html
index e1e61d8..5658e20 100644
--- a/docs/reference/splnr_targets_byInverseArea.html
+++ b/docs/reference/splnr_targets_byInverseArea.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Assign targets by Inverse Area — splnr_targets_byInverseArea • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assign targets by Inverse Area — splnr_targets_byInverseArea"><meta name="description" content="This function takes a min (target_min) and max (target_max) target range and calculates an inverse area target for each feature based on areal coverage."><meta property="og:description" content="This function takes a min (target_min) and max (target_max) target range and calculates an inverse area target for each feature based on areal coverage."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Assign targets by Inverse Area — splnr_targets_byInverseArea • spatialplanr</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assign targets by Inverse Area — splnr_targets_byInverseArea"><meta name="description" content="This function takes a min (target_min) and max (target_max) target range and calculates an inverse area target for each feature based on areal coverage."><meta property="og:description" content="This function takes a min (target_min) and max (target_max) target range and calculates an inverse area target for each feature based on areal coverage."><meta property="og:image" content="https://mathmarecol.github.io/spatialplanr/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">spatialplanr</a>
 
-    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.7</small>
+    <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.6.9</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/search.json b/docs/search.json
index 87022b1..dfaf36e 100644
--- a/docs/search.json
+++ b/docs/search.json
@@ -1 +1 @@
-[{"path":"https://mathmarecol.github.io/spatialplanr/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2023 Jason D. Everett Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"Climate-Smart Spatial Planning","text":"code written simplify process running prioritizr analysis given region. still work progress feel free submit pull requests new features code improvements.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"set-user-parameters","dir":"Articles","previous_headings":"Overview","what":"Set user parameters","title":"Climate-Smart Spatial Planning","text":"Set diameter planning units. units CRS (usually metres degrees). can also use customised ggplot theme can passed list splnr_gg_add() can used plots. example:","code":"Region <- \"Coral Sea\" # \"Australia\" Type <- \"Oceans\" # \"EEZ\" cCRS <- \"ESRI:54009\" # Mollweide PU_size <- 107460 # m splnr_theme <- list(   ggplot2::theme_bw(),   ggplot2::theme(     legend.position = \"right\",     legend.direction = \"vertical\",     text = ggplot2::element_text(size = 9, colour = \"black\"),     axis.text = ggplot2::element_text(size = 9, colour = \"black\"),     plot.title = ggplot2::element_text(size = 9),     axis.title = ggplot2::element_blank()   ) )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"analysis-region","dir":"Articles","previous_headings":"Overview","what":"Analysis Region","title":"Climate-Smart Spatial Planning","text":"Start analysis defining region setting planning units. Get boundary chosen region.","code":"Bndry <- splnr_get_boundary(Limits = Region, Type = Type, cCRS = cCRS) #> Reading layer `ne_10m_geography_marine_polys' from data source  #>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpMuMJpx/ne_10m_geography_marine_polys.shp'  #>   using driver `ESRI Shapefile' #> Simple feature collection with 306 features and 37 fields #> Geometry type: MULTIPOLYGON #> Dimension:     XY #> Bounding box:  xmin: -180 ymin: -85.19206 xmax: 179.9999 ymax: 90 #> Geodetic CRS:  WGS 84  landmass <- rnaturalearth::ne_countries(scale = \"medium\", returnclass = \"sf\") %>%   sf::st_transform(cCRS)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"create-planning-units","dir":"Articles","previous_headings":"Overview","what":"Create Planning Units","title":"Climate-Smart Spatial Planning","text":"","code":"PUs <- spatialgridr::get_grid(boundary = Bndry,                               crs = cCRS,                               output = \"sf_hex\",                               resolution = PU_size)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"get-the-features","dir":"Articles","previous_headings":"Overview","what":"Get the features","title":"Climate-Smart Spatial Planning","text":"example, use small subset charismatic megafauna species Coral Sea inform conservation plan. filtered Aquamaps (Aquamaps.org) species distribution models study area following species: species chosen based importance region represent example visualization purposes. Note: structure tribbleabove required downstream plotting. Common denotes common name species, Scientific scientific name format used Aquamaps, Category category species belongs Class represents importance species conservation plan.","code":"Dict <- tibble::tribble(   ~nameCommon, ~nameVariable, ~category,    \"Green sea turtle\", \"Chelonia_mydas\", \"Reptiles\",    \"Loggerhead sea turtle\", \"Caretta_caretta\", \"Reptiles\",    \"Hawksbill sea turtle\", \"Eretmochelys_imbricata\", \"Reptiles\",    \"Olive ridley sea turtle\", \"Lepidochelys_olivacea\", \"Reptiles\",    \"Saltwater crocodile\", \"Crocodylus_porosus\", \"Reptiles\",    \"Humpback whale\", \"Megaptera_novaeangliae\", \"Mammals\",    \"Common Minke whale\", \"Balaenoptera_acutorostrata\", \"Mammals\",    \"Dugong\", \"Dugong_dugon\", \"Mammals\",    \"Grey nurse shark\", \"Carcharias_taurus\", \"Sharks and rays\",    \"Tiger shark\", \"Galeocerdo_cuvier\", \"Sharks and rays\",    \"Great hammerhead shark\", \"Sphyrna_mokarran\",   \"Sharks and rays\",    \"Giant oceanic manta ray\", \"Mobula_birostris\", \"Sharks and rays\",    \"Reef manta ray\", \"Mobula_alfredi\", \"Sharks and rays\",    \"Whitetip reef shark\", \"Triaenodon_obesus\", \"Sharks and rays\",   \"Red-footed booby\", \"Sula_sula\", \"Birds\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"convert-the-probabilities-to-binary-data","dir":"Articles","previous_headings":"Overview > Get the features","what":"Convert the probabilities to binary data","title":"Climate-Smart Spatial Planning","text":"","code":"datEx_species_bin <- spDataFiltered %>%   dplyr::as_tibble() %>%   dplyr::mutate(dplyr::across(     -dplyr::any_of(c(\"geometry\")), # Don't apply to geometry     ~ dplyr::case_when(       . >= 0.5 ~ 1,       . < 0.5 ~ 0,       is.na(.data) ~ 0     )   )) %>%   sf::st_as_sf()  col_name <- spDataFiltered %>%   sf::st_drop_geometry() %>%   colnames()"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"climate-smart-spatial-planning","dir":"Articles","previous_headings":"Overview > Get the features","what":"Climate-smart spatial planning","title":"Climate-Smart Spatial Planning","text":"far, steps exactly spatial plan include climate change. make spatial plan climate smart, need climate metrics. use climate velocity data obtained x, y z models using SSP5-8.5. downstream analysis, rename column interest (: velocity data) metric. climate velocity data can visualized using splnr_plot_climData() function.  case, areas low climate velocity, areas define climate refugia example. Usually, combine several metrics (e.g. exposure, velocity etc.) multiple SSP scenarios get robust climate refugia. example, randomly set areas high velocity value 0.85-1 visualize output (CHANGE LATER BETTER DATA).  use climate priority area approach splnr_climate_priorityAreaApproach() detailed Buenafe et al (2023) determine climate refugia. Briefly, approach selects percentile (case 5%) suitable habitat feature considered climate-smart. also requires direction input indicating side metric range climate-smart areas can found. case, lower climate velocity denotes climate-smart (direction = -1), cases higher value might represent climate-smart planning units (direction = 1). Using approach also requires adaptation targets, since 5% suitable habitat species already protected climate-smart areas. can decide much 5% climate-smart areas supposed included spatial plan (: refugiaTarget = 1 protect 100% 5% climate-smart areas). now add information required perform spatial planning, cost, extract names used features.","code":"metric_df <- CoralSeaVelocity %>%   dplyr::rename(metric = voccMag_transformed) (ggclim <- splnr_plot_climData(metric_df, \"metric\") +    splnr_gg_add(      Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) set.seed(5)  metric_df <- CoralSeaVelocity %>%   dplyr::rename(metric = voccMag_transformed) %>%   dplyr::mutate(     metricOG = metric,     metric = ifelse(metric > 0.99, runif(., 0.85, 1.0), metric)   )  (ggclim <- splnr_plot_climData(metric_df, \"metric\") +     splnr_gg_add(       Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     )) target <- datEx_species_bin %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)   CPA_Approach <- splnr_climate_priorityAreaApproach(   featuresDF = datEx_species_bin,   metricDF = metric_df,    targetsDF = target,    direction = -1, refugiaTarget = 1 )  out_sf <- CPA_Approach$Features %>%   sf::st_join(     datEx_species_bin %>%       dplyr::select(         tidyselect::starts_with(\"Cost_\")       ),     join = sf::st_equals) %>%   sf::st_join(metric_df, join = sf::st_equals)  targets <- CPA_Approach$Targets out_sf$Cost_None <- rep(1, 397)  usedFeatures <- out_sf %>%   sf::st_drop_geometry() %>%   dplyr::select(     -tidyselect::starts_with(\"Cost_\"),     -tidyselect::starts_with(\"metric\")   ) %>%   names()"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"run-the-climate-smart-spatial-planning","dir":"Articles","previous_headings":"Overview > Get the features","what":"Run the climate-smart spatial planning","title":"Climate-Smart Spatial Planning","text":"prioritizrsteps including climate change running non-climate-smart spatial prioritization. can look resulting plan using splnr_plot_solution().  However, also interested climate-smart selected planning units solution actually . , can use kernel density plot.","code":"p1 <- prioritizr::problem(out_sf, usedFeatures, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(targets$target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_solnClim <- prioritizr::solve.ConservationProblem(p1) (ggSoln <- splnr_plot_solution(dat_solnClim) +    splnr_gg_add(      Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) (ggClimDens <- splnr_plot_climKernelDensity(   soln = list(dat_solnClim),   names = c(\"Input 1\"), type = \"Normal\",   legendTitle = \"Climate velocity (add unit)\",   xAxisLab = \"Climate velocity\" ))"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"percentile-approach","dir":"Articles","previous_headings":"Overview > Alternative Approaches","what":"Percentile Approach","title":"Climate-Smart Spatial Planning","text":"now add information required perform spatial planning, cost, extract names used features run prioritisation. can look resulting plan using splnr_plot_solution().  However, also interested climate-smart selected planning units solution actually . , can use kernel density plot","code":"target <- datEx_species_bin %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 30)  Percentile_Approach <- splnr_climate_percentileApproach(   featuresDF = datEx_species_bin,   metricDF = metric_df, targetsDF = target, direction = -1, percentile = 35 ) #> [1] \"Lower values mean more climate-smart areas.\"  out_sf <- Percentile_Approach$Features %>%   sf::st_join(     datEx_species_bin %>%       dplyr::select(         tidyselect::starts_with(\"Cost_\")       ),     join = sf::st_equals   ) %>%   sf::st_join(metric_df, join = sf::st_equals)  targets <- Percentile_Approach$Targets out_sf$Cost_None <- rep(1, 397)  usedFeatures <- out_sf %>%   sf::st_drop_geometry() %>%   dplyr::select(     -tidyselect::starts_with(\"Cost_\"),     -tidyselect::starts_with(\"metric\")   ) %>%   names()  p2 <- prioritizr::problem(out_sf, usedFeatures, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(targets$target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_solnClimPercentile <- prioritizr::solve.ConservationProblem(p2,                                                                 force = TRUE ) (ggSoln <- splnr_plot_solution(dat_solnClimPercentile) +    splnr_gg_add(      Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) (ggClimDens <- splnr_plot_climKernelDensity(   soln = list(dat_solnClimPercentile),   names = c(\"Input 1\"), type = \"Normal\",   legendTitle = \"Climate velocity (add unit)\",   xAxisLab = \"Climate velocity\" ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"feature-approach","dir":"Articles","previous_headings":"Overview > Alternative Approaches","what":"Feature Approach","title":"Climate-Smart Spatial Planning","text":"now add information required perform spatial planning, cost, extract names used features run prioritisation.  However, also interested climate-smart selected planning units solution actually . , can use kernel density plot","code":"target <- datEx_species_bin %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)  Feature_Approach <- splnr_climate_featureApproach(   featuresDF = datEx_species_bin,   metricDF = metric_df,    targetsDF = target,    direction = 1 ) #> [1] \"Higher values mean more climate-smart areas.\"  out_sf <- Feature_Approach$Features %>%   sf::st_join(     datEx_species_bin %>%       dplyr::select(         tidyselect::starts_with(\"Cost_\")       ),     join = sf::st_equals) %>%   sf::st_join(metric_df, join = sf::st_equals)  targets <- Feature_Approach$Targets out_sf$Cost_None <- rep(1, 397)  usedFeatures <- out_sf %>%   sf::st_drop_geometry() %>%   dplyr::select(     -tidyselect::starts_with(\"Cost_\"),     -tidyselect::starts_with(\"metric\")   ) %>%   names()  p3 <- prioritizr::problem(out_sf, usedFeatures, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(targets$target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_solnClimFeature <- prioritizr::solve.ConservationProblem(p3) (ggSoln <- splnr_plot_solution(dat_solnClimFeature) +    splnr_gg_add(      Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) (ggClimDens <- splnr_plot_climKernelDensity(   soln = list(dat_solnClimFeature),   names = c(\"Input 1\"), type = \"Normal\",   legendTitle = \"Climate velocity (add unit)\",   xAxisLab = \"Climate velocity\" ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"global-fishing-watch-r-package-gfwr","dir":"Articles","previous_headings":"","what":"Global Fishing Watch R Package (gfwr)","title":"Global Fishing Watch","text":"gfwr package provides convenient functions pull GFW data directly R usable formats. contains three main functions, including : get_vessel_info(), get_event() get_raster(). two first devoted retrieving information features one ore several specific vessels. last particular interest us allows us gather information global fishing watch raster fishing effort (details function appropriate section). mainly use splnr_get_gfw function created enable data retrieved processed variety ways, described . time spent fishing computed using Automatic Identification System (AIS) data, transmitted industrial fishing vessels. AIS data provides information location, speed, direction vessel, can used identify vessel actively fishing.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"ais-caveats-and-limitations","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr)","what":"AIS Caveats and limitations","title":"Global Fishing Watch","text":"AIS coverage vessels several limitations : 1. number vessels captured (AIS provides approximately 70’000 2.8 million identified fishing vessels). 2. size vessels (52-85% vessels larger 24 meters 1% vessels 12 meters).Good know: IMO mandates AIS vessels larger 36 meters. 3. AIS interference areas high vessel density. 4. terrestrial satellites receive messages near shore.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"installation","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr)","what":"Installation","title":"Global Fishing Watch","text":"","code":"remotes::install_github(\"GlobalFishingWatch/gfwr\") library(gfwr) library(spatialplanr)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"api","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr)","what":"API","title":"Global Fishing Watch","text":"access GFW APIs, need : 1. register GFW account . 2. Request API key . token, add .Renviron file (executing chunk ), writing (GFW_TOKEN = “YOUR_TOKEN”) file. (asked restart R changes take effect.) save key object used gfwr functions.","code":"usethis::edit_r_environ() key <- gfwr::gfw_auth()"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"fishing-effort-visualization","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr)","what":"Fishing effort visualization","title":"Global Fishing Watch","text":"region_id necessary use get_raster function. get_raster function gets raster fishing effort API converts response data frame contains occurrences vessel grid cell (data binned grid cells different resolution), Vessel IDs, Flag, Geartype Apparent fishing Hours basically amount fishing hours vessel per grid cell (geometry). Data can provided : - DAILY, MONTHLY YEARLY temporal resolutions.  - LOW (0.1 deg) HIGH (0.01 deg) spatial resolutions.  - VESSEL_ID, FLAG, GEARTYPE, FLAGANDGEARTYPE. (can remove option message = FALSE see columns types.)","code":"region_id <- gfwr::get_region_id(region_name = \"Australia\",                                   region_source = \"EEZ\",                                  key = gfwr::gfw_auth())$id gfwr::get_raster(   spatial_resolution = \"LOW\",   temporal_resolution = \"MONTHLY\",   group_by = \"FLAGANDGEARTYPE\",   start_date = \"2022-01-01\",   end_date = \"2023-01-01\",   region = region_id,   region_source = \"EEZ\",   key = gfwr::gfw_auth() )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"get_raster-caveats-and-limitations-","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Fishing effort visualization","what":"get_raster caveats and limitations.","title":"Global Fishing Watch","text":"Date range limited 1-year. Nevertheless, modifications, can get round problems splnr_get_gfw.","code":"data_sf_combined <- splnr_get_gfw(region = \"Australia\",                                    start_date = \"2019-01-01\",                                   end_date =  \"2023-12-31\",                                   temp_res = \"YEARLY\",                                   spat_res = \"LOW\",                                   compress = FALSE)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"visualization","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr)","what":"Visualization","title":"Global Fishing Watch","text":"display data, load :  - coastline rnaturalearth package modify get sf object, constrain boundaries given data.  - EEZ Polygons oceandatr package","code":"# Check and modify if necessary the spatial reference of data_sf_combined data_sf_combined <- sf::st_set_crs(data_sf_combined,                                     sf::st_crs(rnaturalearth::ne_coastline(scale = \"large\")))  coast_clipped <- rnaturalearth::ne_coastline(scale = \"large\") %>%   sf::st_as_sf() %>%   sf::st_intersection(sf::st_as_sfc(sf::st_bbox(data_sf_combined)))  # Load EEZ polygons eezs <- spatialgridr::get_boundary(name = \"Australia\", type = \"eez\", country_type = \"country\") %>%   sf::st_transform(crs = sf::st_crs(data_sf_combined)) %>%   sf::st_make_valid() %>%   sf::st_intersection(sf::st_as_sfc(sf::st_bbox(data_sf_combined)))"},{"path":[]},{"path":[]},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"year-on-year-comparison","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Here we display the Fishing Effort in Australia from 2019 to 2023.","what":"Year-on-year comparison","title":"Global Fishing Watch","text":"may need compare different timeframes, seasons, see patterns. Note : vessels adopted AIS (mainly economically developed countries) since deployment technologies, rise activities must seen context increase necessarily intense fishing activity.","code":"# We need to change the temporal range according to our need group by it to display the total fishing hours. <br> data_sf_combined <- splnr_get_gfw(region = \"Australia\",                                    start_date = \"2019-01-01\",                                    end_date = \"2023-12-31\",                                    temp_res = \"MONTHLY\",                                    key = gfwr::gfw_auth()) %>%   dplyr::group_by(Year, Month) %>%   dplyr::summarize(Total_Fishing_Hours = sum(ApparentFishingHrs))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"fishing-gear-type","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Here we display the Fishing Effort in Australia from 2019 to 2023.","what":"Fishing gear type","title":"Global Fishing Watch","text":"display Vessel activity ‘Micronesia’ 2020 according fishing gear type.","code":"data_sf_combined <- splnr_get_gfw(region = \"Micronesia\",                                    start_date = \"2019-12-31\",                                    end_date = \"2021-01-01\",                                    temp_res = \"MONTHLY\")"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"flags","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Here we display the Fishing Effort in Australia from 2019 to 2023.","what":"Flags","title":"Global Fishing Watch","text":"display Vessel activity Papua New Guinea according Vessels flags.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"supplementary-materials-","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Here we display the Fishing Effort in Australia from 2019 to 2023.","what":"Supplementary materials.","title":"Global Fishing Watch","text":"fishing detection model trained AIS data 503 vessels identified fishing activity 90% accuracy, means can identify fishing non-fishing activity high accuracy. details AIS operation limitations .","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"hierarchy-of-vessels-gear-types","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Here we display the Fishing Effort in Australia from 2019 to 2023.","what":"Hierarchy of vessels gear types :","title":"Global Fishing Watch","text":"Source : https://globalfishingwatch.org/datasets--code-vessel-identity/","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"Spatial Planning With Zones","text":"code written simplify process running prioritizr analysis given region. still work progress feel free submit pull requests new features code improvements. workflow shown based prioritizr introduction zones.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"set-user-parameters","dir":"Articles","previous_headings":"Overview","what":"Set user parameters","title":"Spatial Planning With Zones","text":"Set diameter planning units. units CRS (usually metres degrees). Choose CRS analysis. use Mollweide","code":"Region <- \"Coral Sea\" # \"Australia\" Type <- \"Oceans\" # \"EEZ\" PU_size <- 107460 # m cCRS <- \"ESRI:54009\""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"analysis-region","dir":"Articles","previous_headings":"Overview","what":"Analysis Region","title":"Spatial Planning With Zones","text":"Start analysis defining region setting planning units. Get boundary chosen region.","code":"Bndry <- splnr_get_boundary(Limits = Region, Type = Type, cCRS = cCRS) #> Reading layer `ne_10m_geography_marine_polys' from data source  #>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/Rtmp0tUE3F/ne_10m_geography_marine_polys.shp'  #>   using driver `ESRI Shapefile' #> Simple feature collection with 306 features and 37 fields #> Geometry type: MULTIPOLYGON #> Dimension:     XY #> Bounding box:  xmin: -180 ymin: -85.19206 xmax: 179.9999 ymax: 90 #> Geodetic CRS:  WGS 84  landmass <- rnaturalearth::ne_countries(   scale = \"medium\",   returnclass = \"sf\" ) %>%   sf::st_transform(cCRS)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"create-planning-units","dir":"Articles","previous_headings":"Overview","what":"Create Planning Units","title":"Spatial Planning With Zones","text":"can also use customised ggplot theme can passed list splnr_gg_add() can used plots. example:","code":"PUs <- spatialgridr::get_grid(boundary = Bndry,                               crs = cCRS,                               output = \"sf_hex\",                               resolution = PU_size) splnr_theme <- list(   ggplot2::theme_bw(),   ggplot2::theme(     legend.position = \"right\",     legend.direction = \"vertical\",     text = ggplot2::element_text(size = 9, colour = \"black\"),     axis.text = ggplot2::element_text(size = 9, colour = \"black\"),     plot.title = ggplot2::element_text(size = 9),     axis.title = ggplot2::element_blank()   ) )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"get-the-features","dir":"Articles","previous_headings":"Overview","what":"Get the features","title":"Spatial Planning With Zones","text":"example, use small subset charismatic megafauna species Coral Sea inform conservation plan. filtered Aquamaps (Aquamaps.org) species distribution models study area following species: species chosen based importance region represent example visualization purposes. Note: structure tribbleabove required downstream plotting. Common denotes common name species, Scientific scientific name format used Aquamaps, Category category species belongs Class represents importance species conservation plan.","code":"Dict <- tibble::tribble(   ~nameCommon, ~nameVariable, ~category,    \"Green sea turtle\", \"Chelonia_mydas\", \"Reptiles\",    \"Loggerhead sea turtle\", \"Caretta_caretta\", \"Reptiles\",    \"Hawksbill sea turtle\", \"Eretmochelys_imbricata\", \"Reptiles\",    \"Olive ridley sea turtle\", \"Lepidochelys_olivacea\", \"Reptiles\",    \"Saltwater crocodile\", \"Crocodylus_porosus\", \"Reptiles\",    \"Humpback whale\", \"Megaptera_novaeangliae\", \"Mammals\",    \"Common Minke whale\", \"Balaenoptera_acutorostrata\",   \"Mammals\",    \"Dugong\", \"Dugong_dugon\", \"Mammals\",    \"Grey nurse shark\", \"Carcharias_taurus\", \"Sharks and rays\",    \"Tiger shark\", \"Galeocerdo_cuvier\", \"Sharks and rays\",    \"Great hammerhead shark\", \"Sphyrna_mokarran\",   \"Sharks and rays\",    \"Giant oceanic manta ray\", \"Mobula_birostris\", \"Sharks and rays\",    \"Reef manta ray\", \"Mobula_alfredi\", \"Sharks and rays\",    \"Whitetip reef shark\", \"Triaenodon_obesus\", \"Sharks and rays\",   \"Red-footed booby\", \"Sula_sula\", \"Birds\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"convert-the-probabilities-to-binary-data-and-feature-names","dir":"Articles","previous_headings":"Overview > Get the features","what":"Convert the probabilities to binary data and feature names","title":"Spatial Planning With Zones","text":"","code":"datEx_species_bin <- spDataFiltered %>%   splnr_apply_cutoffs(Cutoffs = 0.5)  col_name <- spDataFiltered %>%   sf::st_drop_geometry() %>%   colnames()"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"spatial-planning-including-zones","dir":"Articles","previous_headings":"Overview > Get the features","what":"Spatial planning including zones","title":"Spatial Planning With Zones","text":"far, steps exactly spatial plan include zones. direct comparison, first run spatial plan include zoning. , define targets features (: 30% features) create conservation problem include area-based cost prioritisation. solve problem plot solution.  can also look well set target met. now look spatial plan needs extended include multiple management zones using zones().","code":"target <- rep(0.3, nrow(Dict))  p1 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(Cost1 = rep(1, 397)),   col_name,   \"Cost1\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE) s1 <- p1 %>%   prioritizr::solve.ConservationProblem()  (ggSoln <- splnr_plot_solution(s1) +     splnr_gg_add(PUs = PUs, Bndry = Bndry, overlay = landmass, cropOverlay = PUs, ggtheme = splnr_theme)) s1T <- s1 %>%   dplyr::select(tidyselect::starts_with(c(\"solution\"))) %>%   sf::st_drop_geometry() %>%   tibble::as_tibble()  r1 <- prioritizr::eval_feature_representation_summary(p1, s1T) print(r1) #> # A tibble: 15 × 5 #>    summary feature                    total_amount absolute_held relative_held #>    <chr>   <chr>                             <dbl>         <dbl>         <dbl> #>  1 overall Chelonia_mydas                       22            10         0.455 #>  2 overall Caretta_caretta                      22            10         0.455 #>  3 overall Eretmochelys_imbricata               24            10         0.417 #>  4 overall Lepidochelys_olivacea                22            10         0.455 #>  5 overall Crocodylus_porosus                   21             9         0.429 #>  6 overall Megaptera_novaeangliae              388           120         0.309 #>  7 overall Balaenoptera_acutorostrata          238            74         0.311 #>  8 overall Dugong_dugon                         13             5         0.385 #>  9 overall Carcharias_taurus                    22            10         0.455 #> 10 overall Galeocerdo_cuvier                    36            14         0.389 #> 11 overall Sphyrna_mokarran                    397           123         0.310 #> 12 overall Mobula_birostris                     20             8         0.4   #> 13 overall Mobula_alfredi                       20             8         0.4   #> 14 overall Triaenodon_obesus                    25            10         0.4   #> 15 overall Sula_sula                            13             5         0.385"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"different-cost-layers","dir":"Articles","previous_headings":"Overview > Get the features","what":"Different cost layers","title":"Spatial Planning With Zones","text":"first assume zones interest set features, separate cost layers. , need set targets zones, case 20% features first zone 5% features second zone. create zones object specify number zones features zone. , define two zones features. zones need specified cost targets. use one area-based cost one cost layer uses random numbers, pre-defined targets pass zonesobject problem formulation solving conservation problem. solution can plotted using function splnr_plot_solution() argument zones set TRUE.  can see now planning units selected, planning units either selected zone 1 zone 2.","code":"target2 <- matrix(NA, ncol = 2, nrow = nrow(Dict)) target2[, 1] <- 0.2 target2[, 2] <- 0.05 z2 <- prioritizr::zones(\"zone 1\" = col_name, \"zone 2\" = col_name) p2 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397), # when giving sf input, we need as many cost columns as we have zones     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s2 <- p2 %>%   prioritizr::solve.ConservationProblem() (gg_s2 <- splnr_plot_solution(   s2,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"different-features","dir":"Articles","previous_headings":"Overview > Get the features","what":"Different features","title":"Spatial Planning With Zones","text":"using sf objects zones(), input feature names zones() need length contain features. means zones features, interest specific zone, target set 0. example, want separate example data zone reptiles another zone containing taxa reptiles, can specify following targets: sets target reptiles first zone 30% rest 0%. second zone, targets non-reptiles 10% reptiles 0% interest zone. Target data given matrix working zones, transform data frame matrix end. define conservation problem way solve . can also look well targets met zone (combined). can see 15 features listed (number) overall summary, summary zone 1 summary zone 2. looking relative_held column tibble, observe summary zone 1 (row 16 onwards), features >30% targets met, whereas others (feature 6 7) low percentage suitable habitat within selected planning units. can extract common names two features: marine mammals thus target 0% zone 1 reptile-specific zone. percentage selected suitable habitat 0% despite target 0 proportion suitable habitat mammals selected incidentally selecting planning units zone meeting targets reptiles. applies zone 2. can also plot final solution :","code":"targets2b <- Dict %>%   dplyr::mutate(     targetZ1 = dplyr::if_else(category == \"Reptiles\", 30 / 100, 0),     targetZ2 = dplyr::if_else(category != \"Reptiles\", 10 / 100, 0)   ) %>%   dplyr::select(\"targetZ1\", \"targetZ2\") %>%   as.matrix() # NOTE: when using sf input, we need as many cost columns as we have zones p2b <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397),     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(targets2b) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s2b <- p2b %>%   prioritizr::solve.ConservationProblem() r2b <- s2b %>%   dplyr::select(tidyselect::starts_with(c(\"solution\"))) %>%   sf::st_drop_geometry() %>%   tibble::as_tibble() %>%   prioritizr::eval_feature_representation_summary(p2b, .) print(r2b, n = 45) #> # A tibble: 45 × 5 #>    summary feature total_amount absolute_held relative_held #>    <chr>   <chr>          <dbl>         <dbl>         <dbl> #>  1 overall 1                 44            11       0.25    #>  2 overall 2                 44            11       0.25    #>  3 overall 3                 48            11       0.229   #>  4 overall 4                 44            11       0.25    #>  5 overall 5                 42            11       0.262   #>  6 overall 6                776            43       0.0554  #>  7 overall 7                476            26       0.0546  #>  8 overall 8                 26             7       0.269   #>  9 overall 9                 44            11       0.25    #> 10 overall 10                72            13       0.181   #> 11 overall 11               794            48       0.0605  #> 12 overall 12                40            11       0.275   #> 13 overall 13                40            11       0.275   #> 14 overall 14                50            12       0.24    #> 15 overall 15                26             8       0.308   #> 16 zone 1  1                 22             8       0.364   #> 17 zone 1  2                 22             8       0.364   #> 18 zone 1  3                 24             8       0.333   #> 19 zone 1  4                 22             8       0.364   #> 20 zone 1  5                 21             8       0.381   #> 21 zone 1  6                388             4       0.0103  #> 22 zone 1  7                238             2       0.00840 #> 23 zone 1  8                 13             5       0.385   #> 24 zone 1  9                 22             8       0.364   #> 25 zone 1  10                36             8       0.222   #> 26 zone 1  11               397             8       0.0202  #> 27 zone 1  12                20             8       0.4     #> 28 zone 1  13                20             8       0.4     #> 29 zone 1  14                25             8       0.32    #> 30 zone 1  15                13             6       0.462   #> 31 zone 2  1                 22             3       0.136   #> 32 zone 2  2                 22             3       0.136   #> 33 zone 2  3                 24             3       0.125   #> 34 zone 2  4                 22             3       0.136   #> 35 zone 2  5                 21             3       0.143   #> 36 zone 2  6                388            39       0.101   #> 37 zone 2  7                238            24       0.101   #> 38 zone 2  8                 13             2       0.154   #> 39 zone 2  9                 22             3       0.136   #> 40 zone 2  10                36             5       0.139   #> 41 zone 2  11               397            40       0.101   #> 42 zone 2  12                20             3       0.15    #> 43 zone 2  13                20             3       0.15    #> 44 zone 2  14                25             4       0.16    #> 45 zone 2  15                13             2       0.154 Dict[[1]][6] #> [1] \"Humpback whale\" Dict[[1]][7] #> [1] \"Common Minke whale\" (gg_s2b <- splnr_plot_solution(   s2b,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"boundary-penalty","dir":"Articles","previous_headings":"Overview > Get the features","what":"Boundary penalty","title":"Spatial Planning With Zones","text":"Similar “normal” priritisations, zones also allows including boundary penalty. several options can done within zones zones.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"within-the-same-zone","dir":"Articles","previous_headings":"Overview > Get the features > Boundary penalty","what":"Within the same zone","title":"Spatial Planning With Zones","text":"zeros matrix denote penalty zones, whereas ones introduce boundary penalty define conservation problem. , introduce penalties within zone 1 zone 2 respectively. add_boundary_penalties() set penalty 0.5 zones defined zm1. purpose example, also set 10 second time limit prioritisation. results show less fragmentation previous solution without penalties:  boundary penalty can also introduced one zone:","code":"zm1 <- diag(2) print(zm1) #>      [,1] [,2] #> [1,]    1    0 #> [2,]    0    1 p3 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397), # when giving sf input, we need as many cost columns as we have zones     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_boundary_penalties(0.5, zone = zm1) %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(time_limit = 10, verbose = FALSE)  s3 <- p3 %>%   prioritizr::solve.ConservationProblem() (gg_s3 <- splnr_plot_solution(   s3,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   )) zm2 <- zm1 zm2[2, 2] <- 0  # NOTE: When using sf input, we need as many cost columns as we have zones p4 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397),     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_boundary_penalties(0.5, zone = zm2) %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(time_limit = 10, verbose = FALSE)  s4 <- p4 %>%   prioritizr::solve.ConservationProblem()  (gg_s4 <- splnr_plot_solution(   s4,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"across-zones","dir":"Articles","previous_headings":"Overview > Get the features > Boundary penalty","what":"Across zones","title":"Spatial Planning With Zones","text":"Similarly, penalties can applied zones specified problem.","code":"zm3 <- matrix(1, ncol = 2, nrow = 2) print(zm3) #>      [,1] [,2] #> [1,]    1    1 #> [2,]    1    1 p5 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397), # when giving sf input, we need as many cost columns as we have zones     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_boundary_penalties(0.5, zone = zm3) %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(time_limit = 10, verbose = FALSE)  s5 <- p5 %>%   prioritizr::solve.ConservationProblem()  (gg_s5 <- splnr_plot_solution(   s5,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"adding-constraints","dir":"Articles","previous_headings":"Overview > Get the features","what":"Adding constraints","title":"Spatial Planning With Zones","text":"Another addition often used conservation planning constraints. often lock lock areas interest various reasons. example, lock already existing MPAs one zones. using zones constraints, use prioritizr function add_manual_locked_constraints() requires input specific format, first prepare MPA data. need specify zone constraint applied , give information planning unit identifier, rename column interest “status” filter planning units locked . results can visualized :","code":"mpas <- MPAsCoralSea %>%   dplyr::mutate(zone = \"zone 1\") %>%   dplyr::rename(status = wdpa) %>%   tibble::rowid_to_column(\"pu\") %>%    sf::st_drop_geometry() %>%   tibble::tibble() %>%   dplyr::filter(status == 1) # NOTE: When using sf input, we need as many cost columns as we have zones p6 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397),     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_manual_locked_constraints(mpas) %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(time_limit = 10, verbose = FALSE)  s6 <- p6 %>%   prioritizr::solve.ConservationProblem() (gg_s6 <- splnr_plot_solution(   s6,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, lockIn = MPAsCoralSea,     nameLockIn = \"wdpa\", typeLockIn = \"Full\",     colorLockIn = \"lightgrey\", alphaLockIn = 0.2, overlay = landmass,     labelLockIn = \"Current MPAs\", cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"objective-functions","dir":"Articles","previous_headings":"Overview > Get the features","what":"Objective functions","title":"Spatial Planning With Zones","text":"far used minimum set objective function meet conservation targets whilst minimizing cost. However, objective function available prioritizr. example maximising mangrove ecosystem services, employed minimum shortfall objective function instead (Dabalà et al 2022). objective function, allocate budget exceeded (example area >30%) whilst still trying minimise cost meeting targets - targets might met (shortfall). Zones also works objective functions minimum set objective function. apply add_min_shortfall_objective() provide separate budgets two zones (8 0.3). can visualize output solving conservation problem.","code":"# NOTE: When using sf input, we need as many cost columns as we have zones p7 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397),     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_shortfall_objective(c(8, 0.3)) %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(time_limit = 10, verbose = FALSE) s7 <- p7 %>%   prioritizr::solve.ConservationProblem()  (gg_s7 <- splnr_plot_solution(   s7,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"alternative-linear-constraints","dir":"Articles","previous_headings":"Overview > Get the features","what":"Alternative: linear constraints","title":"Spatial Planning With Zones","text":"Sometimes spatial plan might needed requires minimising several costs , binary output (inside protected area/outside protected area) sufficient. case, using linear constraints instead zones might simpler time-efficient way forward. Linear constraints make sure planning units selected area meet criteria given constraint. example, using area-based cost (lowest number planning units meet target), might also simultaneously want minimise cost fisheries keep certain threshold. Inversely, might want minimise cost fisheries also select 30% area. example, fill first define targets random cost layer values ranging 0 1. define solve conservation problem: Based problem definition, want meet targets biodiversity features whilst selecting lowest number planning units possible. However, solution also depends threshold linear constraint specified add_linear_constraints()problem. Specifically, planning units selected solution can exceed 10% total cost planning units costRandom$CostR. can visualise solution :  NOTE: can also use multiple linear constraints plan, however, might require normalization input data constraints comparable units, careful tuning thresholds, prioritizr still able solve problem.","code":"target8 <- rep(0.3, nrow(Dict))  set.seed <- 10 # Add seed so the problem below solves each time  costRandom <- datEx_species_bin %>%   dplyr::mutate(CostR = runif(n = dim(.)[[1]])) %>%   dplyr::select(\"CostR\") p8 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(Cost1 = rep(1, 397)),   col_name,   \"Cost1\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(target8) %>%   prioritizr::add_linear_constraints(sum(costRandom$CostR) * 0.1,                                      sense = \"<=\", costRandom$CostR   ) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s8 <- p8 %>%   prioritizr::solve.ConservationProblem() (gg_s8 <- splnr_plot_solution(s8) +    splnr_gg_add(PUs = PUs, Bndry = Bndry, overlay = landmass, cropOverlay = PUs, ggtheme = splnr_theme))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"common-targets-across-zones","dir":"Articles","previous_headings":"Overview > Get the features","what":"Common targets across zones","title":"Spatial Planning With Zones","text":"Sometimes might required meet (common) conservation target across multiple zones, several zones contribute reaching target. , need define target across zones (: 30% features across zones): need bring data specific format requires us individual column feature specific zone, spp1 two zones (zone1 zone2), two separate columns input data: spp1_zone1 spp1_zone2. species names zone names exactly specified zones() object separated _. also extract new feature names create zones object, joining two newly created data frames file used prioriztisation. can see defined (random) cost layers cost layer zone2 three times costly zone1. setting solving conservation problem, can look resulting solution well targets met. overall summary shows every feature’s suitable habitat represented least 30% combined target set. However, can see features zone1 lot frequently selected zone2 zone2 three times costly.  plot also reflects observation PUs frequently selected zone1. wanted constrain , zone1 less often selected zone2 often?","code":"targetAcross <- dplyr::tibble(   feature = col_name,   zone = list(c(\"zone1\", \"zone2\"))[rep(1, length(col_name))],   target = rep(0.3, length(col_name)),   type = rep(\"relative\", length(col_name)) ) datSpecZone1 <- datEx_species_bin %>%   dplyr::rename_at(dplyr::vars(-geometry), ~ paste0(.x, \"_zone1\"))  featuresZone1 <- datSpecZone1 %>%   sf::st_drop_geometry() %>%   colnames()  datSpecZone2 <- datEx_species_bin %>%   dplyr::rename_at(dplyr::vars(-geometry), ~ paste0(.x, \"_zone2\"))  featuresZone2 <- datSpecZone2 %>%   sf::st_drop_geometry() %>%   colnames() z10 <- prioritizr::zones(   featuresZone1,   featuresZone2,   zone_names = c(\"zone1\", \"zone2\"),   feature_names = col_name )  out_sf <- datSpecZone1 %>%   sf::st_join(datSpecZone2, join = sf::st_equals) %>%   dplyr::mutate(     Cost1 = runif(n = dim(.)[[1]]) * 100,     Cost2 = runif(n = dim(.)[[1]]) * 300   ) p10 <- prioritizr::problem(out_sf,                            z10,                            cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_manual_targets(targetAcross) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s10 <- p10 %>%   prioritizr::solve.ConservationProblem() s10F <- s10 %>%   dplyr::select(tidyselect::starts_with(c(\"solution\"))) %>%   sf::st_drop_geometry() %>%   tibble::as_tibble()  r10 <- prioritizr::eval_feature_representation_summary(p10, s10F) print(r10) #> # A tibble: 45 × 5 #>    summary feature                    total_amount absolute_held relative_held #>    <chr>   <chr>                             <dbl>         <dbl>         <dbl> #>  1 overall Chelonia_mydas                       44            14         0.318 #>  2 overall Caretta_caretta                      44            14         0.318 #>  3 overall Eretmochelys_imbricata               48            15         0.312 #>  4 overall Lepidochelys_olivacea                44            14         0.318 #>  5 overall Crocodylus_porosus                   42            14         0.333 #>  6 overall Megaptera_novaeangliae              776           234         0.302 #>  7 overall Balaenoptera_acutorostrata          476           146         0.307 #>  8 overall Dugong_dugon                         26            10         0.385 #>  9 overall Carcharias_taurus                    44            14         0.318 #> 10 overall Galeocerdo_cuvier                    72            25         0.347 #> # ℹ 35 more rows (gg_s10 <- splnr_plot_solution(s10,                                zones = TRUE,                                colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),                                legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"targets-across-zones-with-linear-constraints","dir":"Articles","previous_headings":"Overview > Get the features","what":"Targets across zones with linear constraints","title":"Spatial Planning With Zones","text":"can include linear constraints zone1 , area exceed 30% whole area. need create matrix contains data constraint want include. Although want put linear constraint zone1, prioritizr still requires matrix many columns zones. Thus, set area cost 1 zone1 want constraint 0 zone2 want introduce linear constraint. define conservation problem add linear constraint 30% area. selected planning units now equally distributed across zones, also observable plot:  However, also expect cost spatial plan higher previous one.","code":"CostArea <- out_sf %>%   dplyr::mutate(     areaCostZone1 = rep(1, 397),     areaCostZone2 = rep(0, 397)   ) %>%   sf::st_drop_geometry() %>%   dplyr::select(\"areaCostZone1\", \"areaCostZone2\") %>%   as.matrix() p11 <- prioritizr::problem(out_sf,                            z10,                            cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_linear_constraints(sum(CostArea[, 1]) * 0.3,                                      sense = \"<=\", CostArea   ) %>%   prioritizr::add_manual_targets(targetAcross) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s11 <- p11 %>%   prioritizr::solve.ConservationProblem() s11F <- s11 %>%   dplyr::select(tidyselect::starts_with(c(\"solution\"))) %>%   sf::st_drop_geometry() %>%   tibble::as_tibble()  r11 <- prioritizr::eval_feature_representation_summary(p11, s11F) print(r11) #> # A tibble: 45 × 5 #>    summary feature                    total_amount absolute_held relative_held #>    <chr>   <chr>                             <dbl>         <dbl>         <dbl> #>  1 overall Chelonia_mydas                       44            14         0.318 #>  2 overall Caretta_caretta                      44            14         0.318 #>  3 overall Eretmochelys_imbricata               48            15         0.312 #>  4 overall Lepidochelys_olivacea                44            14         0.318 #>  5 overall Crocodylus_porosus                   42            14         0.333 #>  6 overall Megaptera_novaeangliae              776           234         0.302 #>  7 overall Balaenoptera_acutorostrata          476           144         0.303 #>  8 overall Dugong_dugon                         26             9         0.346 #>  9 overall Carcharias_taurus                    44            14         0.318 #> 10 overall Galeocerdo_cuvier                    72            24         0.333 #> # ℹ 35 more rows (gg_s11 <- splnr_plot_solution(   s11,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"targets-across-some-but-not-all-zones","dir":"Articles","previous_headings":"Overview > Get the features","what":"Targets across some (but not all) zones","title":"Spatial Planning With Zones","text":"example, want target 30% suitable reptile habitat zone 1 zone 2. Additionally, set target 20% zone 2 marine mammals target 5% sharks rays zone 3. create zones object three different zones: create joint sf object zones respective costs.","code":"targetAcrossSome <- Dict %>%   dplyr::mutate(     target = dplyr::case_when(       category == \"Reptiles\" ~ 30 / 100,       category == \"Mammals\" ~ 10 / 100,       category == \"Sharks and rays\" ~ 5 / 100,       TRUE ~ 0     ),     zone = dplyr::case_when(       category == \"Reptiles\" ~ list(c(\"zone1\", \"zone2\")),       category == \"Mammals\" ~ list(\"zone2\"),       category == \"Sharks and rays\" ~ list(\"zone3\"),       TRUE ~ list(c(\"zone1\", \"zone2\", \"zone3\"))     ),     type = rep(\"relative\", length(col_name))   ) %>%   dplyr::rename(feature = \"nameVariable\") %>%   dplyr::select(-\"category\", -\"nameCommon\") datSpecZone1 <- datEx_species_bin %>%   dplyr::rename_at(dplyr::vars(-geometry), ~ paste0(.x, \"_zone1\"))  featuresZone1 <- datSpecZone1 %>%   sf::st_drop_geometry() %>%   colnames()  datSpecZone2 <- datEx_species_bin %>%   dplyr::rename_at(dplyr::vars(-geometry), ~ paste0(.x, \"_zone2\"))  featuresZone2 <- datSpecZone2 %>%   sf::st_drop_geometry() %>%   colnames()  datSpecZone3 <- datEx_species_bin %>%   dplyr::rename_at(dplyr::vars(-geometry), ~ paste0(.x, \"_zone3\"))  featuresZone3 <- datSpecZone3 %>%   sf::st_drop_geometry() %>%   colnames()  z12 <- prioritizr::zones(   featuresZone1,   featuresZone2,   featuresZone3,   zone_names = c(\"zone1\", \"zone2\", \"zone3\"),   feature_names = col_name ) # NOTE: When using sf input, we need as many cost columns as we have zones out_sf <- datSpecZone1 %>%   sf::st_join(datSpecZone2, join = sf::st_equals) %>%   sf::st_join(datSpecZone3, join = sf::st_equals) %>%   dplyr::mutate(geometry = datEx_species_bin$geometry) %>%   sf::st_as_sf() %>%   dplyr::mutate(     Cost1 = runif(n = dim(.)[[1]]) * 100,     Cost2 = runif(n = dim(.)[[1]]) * 300,     Cost3 = runif(n = dim(.)[[1]]) * 200   ) p12 <- prioritizr::problem(out_sf,                            z12,                            cost_column = c(\"Cost1\", \"Cost2\", \"Cost3\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_manual_targets(targetAcrossSome) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s12 <- p12 %>%   prioritizr::solve.ConservationProblem() s12F <- s12 %>%   dplyr::select(tidyselect::starts_with(c(\"solution\"))) %>%   sf::st_drop_geometry() %>%   tibble::as_tibble()  r12 <- prioritizr::eval_feature_representation_summary(p12, s12F) print(r12) #> # A tibble: 60 × 5 #>    summary feature                    total_amount absolute_held relative_held #>    <chr>   <chr>                             <dbl>         <dbl>         <dbl> #>  1 overall Chelonia_mydas                       66            16        0.242  #>  2 overall Caretta_caretta                      66            16        0.242  #>  3 overall Eretmochelys_imbricata               72            17        0.236  #>  4 overall Lepidochelys_olivacea                66            16        0.242  #>  5 overall Crocodylus_porosus                   63            16        0.254  #>  6 overall Megaptera_novaeangliae             1164            64        0.0550 #>  7 overall Balaenoptera_acutorostrata          714            44        0.0616 #>  8 overall Dugong_dugon                         39             8        0.205  #>  9 overall Carcharias_taurus                    66            16        0.242  #> 10 overall Galeocerdo_cuvier                   108            19        0.176  #> # ℹ 50 more rows (gg_s12 <- splnr_plot_solution(   s12,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"navyblue\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\", \"Zone3\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"short-term","dir":"Articles","previous_headings":"Overview > Get the features > Next steps","what":"Short-term","title":"Spatial Planning With Zones","text":"Test run time zones compared normal prioritisation Communicate zones outcomes effectively (e.g. targets, cost overlay etc.)","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"longer-term","dir":"Articles","previous_headings":"Overview > Get the features > Next steps","what":"Longer-term","title":"Spatial Planning With Zones","text":"deal overlapping zones (moment prioritizr allocates PU single zone) connect climate-smart workflow zones handle inputs benefit using different objective functions (e.g. ecosystem services vs biodiversity features) Look commonly used data sets multiple use approaches think zone-specific costs, constraints, targets etc. Define (Waitt’s) understanding multiple-use want implement (can differ now future) EU Horizon 2020 MUSES-project: multiple use/multi-use “joint use resources close geographic proximity either single user multiple users. umbrella term covers multitude use combinations marine realm represents radical change concept exclusive resource rights inclusive sharing resources space one users.” Bonnevie et al. 2019: “multi-use specific co-location/coexistence resources shared.” Schupp et al. 2019: distinguishes different types multi-uses (one co-location) Types multiple use MSP according Schupp et al. 2019","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"A Basic Spatial Planning Workflow","text":"code written simplify process running prioritizr analysis given region. still work progress feel free submit pull requests new features code improvements.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"set-user-parameters","dir":"Articles","previous_headings":"Overview","what":"Set user parameters","title":"A Basic Spatial Planning Workflow","text":"can set region defined splnr_get_planningUnits. can also define region square boundaries (degrees) need. Choose CRS analysis. case use Mollweide Set diameter planning units. units CRS (usually metres degrees).","code":"Region <- \"Coral Sea\" # \"Australia\" Type <- \"Oceans\" # \"EEZ\" Region <- c(xmin = 150, xmax = 160, ymin = -40, ymax = -30) cCRS <- \"ESRI:54009\" PU_size <- 107460 # m"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"analysis-region","dir":"Articles","previous_headings":"Overview","what":"Analysis Region","title":"A Basic Spatial Planning Workflow","text":"Start analysis defining region setting planning units. Get boundary chosen region. Get land boundaries remove overlap. object “landmass” represents land mass removed (inverse = FALSE)","code":"Bndry <- splnr_get_boundary(Limits = Region, Type = Type, cCRS = cCRS) #> Reading layer `ne_10m_geography_marine_polys' from data source  #>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpYDUd6r/ne_10m_geography_marine_polys.shp'  #>   using driver `ESRI Shapefile' #> Simple feature collection with 306 features and 37 fields #> Geometry type: MULTIPOLYGON #> Dimension:     XY #> Bounding box:  xmin: -180 ymin: -85.19206 xmax: 179.9999 ymax: 90 #> Geodetic CRS:  WGS 84 landmass <- rnaturalearth::ne_countries(   scale = \"medium\",   returnclass = \"sf\" ) %>%   sf::st_transform(cCRS)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"create-planning-units","dir":"Articles","previous_headings":"Overview","what":"Create Planning Units","title":"A Basic Spatial Planning Workflow","text":"can check PUs look like  want add additional properties map, example landmass boundary, can use splnr_gg_add().  can also use customised ggplpot theme can passed list splnr_gg_add() can used plots. example:","code":"PUs <- spatialgridr::get_grid(boundary = Bndry,                                crs = cCRS,                               output = \"sf_hex\",                                resolution = PU_size) (ggPU <- splnr_plot(df = PUs) +    ggplot2::theme_bw()) # Plot Planning Units (ggPU <- splnr_plot(df = PUs) +    splnr_gg_add(      Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = \"Default\"    )) splnr_theme <- list(   ggplot2::theme_bw(),   ggplot2::theme(     legend.position = \"right\",     legend.direction = \"vertical\",     text = ggplot2::element_text(size = 9, colour = \"black\"),     axis.text = ggplot2::element_text(size = 9, colour = \"black\"),     plot.title = ggplot2::element_text(size = 9),     axis.title = ggplot2::element_blank()   ) )  (ggPU <- splnr_plot(PUs) +     splnr_gg_add(       Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"get-the-features","dir":"Articles","previous_headings":"Overview","what":"Get the features","title":"A Basic Spatial Planning Workflow","text":"example, use small subset charismatic megafauna species Coral Sea inform conservation plan. filtered Aquamaps (Aquamaps.org) species distribution models study area following species: species chosen based importance region represent example visualization purposes. Note: structure tribbleabove required downstream plotting. Common denotes common name species, nameVariable scientific name format used Aquamaps, TaxGroup taxonomic grouping species belongs Category represents importance species conservation plan.","code":"Dict <- tibble::tribble(   ~nameCommon, ~nameVariable, ~category,    \"Green sea turtle\", \"Chelonia_mydas\", \"Reptiles\",    \"Loggerhead sea turtle\", \"Caretta_caretta\", \"Reptiles\",    \"Hawksbill sea turtle\", \"Eretmochelys_imbricata\", \"Reptiles\",    \"Olive ridley sea turtle\", \"Lepidochelys_olivacea\", \"Reptiles\",    \"Saltwater crocodile\", \"Crocodylus_porosus\", \"Reptiles\",    \"Humpback whale\", \"Megaptera_novaeangliae\", \"Mammals\",    \"Common Minke whale\", \"Balaenoptera_acutorostrata\", \"Mammals\",    \"Dugong\", \"Dugong_dugon\", \"Mammals\",    \"Grey nurse shark\", \"Carcharias_taurus\", \"Sharks and rays\",    \"Tiger shark\", \"Galeocerdo_cuvier\", \"Sharks and rays\",    \"Great hammerhead shark\", \"Sphyrna_mokarran\", \"Sharks and rays\",    \"Giant oceanic manta ray\", \"Mobula_birostris\", \"Sharks and rays\",    \"Reef manta ray\", \"Mobula_alfredi\", \"Sharks and rays\",    \"Whitetip reef shark\", \"Triaenodon_obesus\", \"Sharks and rays\",   \"Red-footed booby\", \"Sula_sula\", \"Birds\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"convert-the-probabilities-to-binary-data","dir":"Articles","previous_headings":"Overview > Get the features","what":"Convert the probabilities to binary data","title":"A Basic Spatial Planning Workflow","text":"can now look feature data used spatial plan individually calling splnr_plot_binFeature(), example see binary habitat suitability map Green sea turtles:  suitable habitat Green sea turtles predicted Aquamaps restricted cells close coast. now compare predicted suitable habitat Humpback whales, can see fairly ubiquitous across whole Coral Sea.  example, reason classified species either representative suitable habitat wide-ranging within study region important restricted number cells. get better idea overall distribution used features, can also plot number features suitable habitat within planning unit study region.","code":"datEx_species_bin <- spDataFiltered %>%   splnr_apply_cutoffs(Cutoffs = 0.5) (ggFeature1 <- splnr_plot(   df = datEx_species_bin,   col_names = \"Chelonia_mydas\",   plot_title = \"Chelonia mydas\",   legend_labels = c(\"Absence\", \"Presence\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ) ) (ggFeature <- splnr_plot(   datEx_species_bin,   \"Megaptera_novaeangliae\",   plot_title = \"Megaptera novaeangliae\" ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   )) (ggFeatNo <- splnr_plot(df = datEx_species_bin,                          col_names =  colnames(datEx_species_bin %>%                                                  sf::st_drop_geometry()),                         plot_title = \"\",                          legend_title = \"Number of features\") +    splnr_gg_add(      PUs = PUs, Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"prepare-data-for-prioritisation","dir":"Articles","previous_headings":"Overview","what":"Prepare Data for prioritisation","title":"A Basic Spatial Planning Workflow","text":"spatial prioritization also need extract names features pass prioritizr. also create sf object contains information needed prioritization.","code":"feature_names <- splnr_featureNames(datEx_species_bin) out_sf <- datEx_species_bin"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"add-cost","dir":"Articles","previous_headings":"Overview > Prepare Data for prioritisation","what":"Add Cost","title":"A Basic Spatial Planning Workflow","text":"example, use minimum set objective function, aims minimize cost whilst meeting conservation targets. add area-based cost include little area possible spatial plan whilst meeting conservation targets. , planning units assigned equal cost 1.","code":"out_sf$Cost_None <- 1 (ggCost <- splnr_plot(out_sf, col_names = \"Cost_None\",                        legend_title = \"Cost\", legend_labels = \"1\") +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"fishing-effort","dir":"Articles","previous_headings":"","what":"A Basic Spatial Planning Workflow","title":"A Basic Spatial Planning Workflow","text":"gfwr package allows us recover data fisheries across world, set parameter compress TRUE recover Apparent fishing hours per coordinates.","code":"gfw_data <- splnr_get_gfw(region = 'Australia',                            start_date = \"2022-01-01\",                            end_date = \"2022-12-31\",                            temp_res = \"yearly\",                            cCRS = cCRS,                            compress = TRUE) %>%   sf::st_interpolate_aw(PUs, extensive = TRUE)  out_sf$Apparent.Fishing.Hours <- 0 # Add column to PUs out_sf$Apparent.Fishing.Hours[as.numeric(rownames(PUs))] <-    gfw_data$Apparent.Fishing.Hours # Put corresponding data in PUs   (ggCost <- splnr_plot(out_sf, col_names = \"Apparent.Fishing.Hours\") +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"other-features-1","dir":"Articles","previous_headings":"","what":"A Basic Spatial Planning Workflow","title":"A Basic Spatial Planning Workflow","text":"Many features can taken account cost layers prioritization, provide different features oceandatrpackage.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"set-targets","dir":"Articles","previous_headings":"Overview","what":"Set Targets","title":"A Basic Spatial Planning Workflow","text":"shown previously, assigned conservation features class reflecting importance planning region. Conservation targets assigned target based class, case 30% suitable habitat important 10% representative features. Note: assigned classes targets based ecological information chosen visualization purposes.","code":"catTarg <- c(\"Reptiles\" = 0.3, \"Mammals\" = 0.1, \"Sharks and rays\" = 0.1, \"Birds\" = 0.1)  target <- Dict %>%   splnr_targets_byCategory(catTarg, catName = \"category\")"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"set-up-conservation-problem","dir":"Articles","previous_headings":"Overview","what":"Set up conservation problem","title":"A Basic Spatial Planning Workflow","text":"","code":"datEx_problem <- prioritizr::problem(out_sf, feature_names, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(target$target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"solve-the-conservation-problem","dir":"Articles","previous_headings":"Overview","what":"Solve the conservation problem","title":"A Basic Spatial Planning Workflow","text":"","code":"datEx_soln <- datEx_problem %>%   prioritizr::solve.ConservationProblem()"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"visualize-output","dir":"Articles","previous_headings":"Overview","what":"Visualize Output","title":"A Basic Spatial Planning Workflow","text":"different ways visualize output prioritization can loosely grouped three categories: + Visualization solution + Visualization targets + Visualization importance scores","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"visualization-of-the-solution","dir":"Articles","previous_headings":"Overview > Visualize Output","what":"Visualization of the solution","title":"A Basic Spatial Planning Workflow","text":"plot shows optimal solution planning region meets selected targets chosen features smallest area possible. categorical map displays, planning units selected important meeting conservation targets (dark blue) selected (light blue). can also done overlay cost show solution avoids highly costly areas:  Note: example, cost equal planning units.","code":"(ggSoln <- splnr_plot(datEx_soln,                        col_names = \"solution_1\",                        legend_title = \"Solution\",                        legend_labels = c(\"0\",\"1\")) +    splnr_gg_add(      PUs = PUs, Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) (ggCostOverlay <- splnr_plot_costOverlay(   soln = datEx_soln,   Cost = NA,   Cost_name = \"Cost_None\" ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"visualization-of-targets","dir":"Articles","previous_headings":"Overview > Visualize Output","what":"Visualization of targets","title":"A Basic Spatial Planning Workflow","text":"visualize well targets met, first need extract much suitable habitat feature selected spatial plan. also includes potential incidental coverage feature included spatial plan can still found planning region.  circular bar plot, one additional step data preparation needs done.","code":"dfTarget <- splnr_get_featureRep(datEx_soln, datEx_problem,                                  climsmart = FALSE,                                   solnCol = \"solution_1\" )   (ggTarget <- splnr_plot_featureRep(dfTarget,                                     category = Dict,                                     renameFeatures = TRUE,                                    namesToReplace = Dict,                                     categoryFeatureCol = \"nameCommon\",                                    nr = 1, showTarget = TRUE, )) dfTargetCirc <- dfTarget %>% dplyr::select(\"feature\", \"value\", \"group\") %>% na.omit()  colors <- c(   \"important\" = \"darkgreen\",   \"representative\" = \"darkred\" ) legends <- c(\"Important\", \"Representative\")  (ggCircTarg <- splnr_plot_circBplot(df = dfTargetCirc, legend_list = legends, legend_color = colors, impTarget = 30, repTarget = 10))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"visualization-of-importance-scores","dir":"Articles","previous_headings":"Overview > Visualize Output","what":"Visualization of importance scores","title":"A Basic Spatial Planning Workflow","text":"Importance scores can help assess relative importance individual selected planning unit spatial plan (information, see https://prioritizr.net/reference/importance.html) , use two different importance scores, Ferrier Score Rarity Weighted Richness.  example, scores label similar -coastal- planning units important spatial plan.","code":"ggFerrier <- splnr_plot_importanceScore(   soln = datEx_soln,   pDat = datEx_problem,   method = \"Ferrier\",   decimals = 4,   legendTitle = \"Importance Score \\n(Ferrier Score)\" ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ) #> Ferrier Score.  ggRWR <- splnr_plot_importanceScore(   soln = datEx_soln,   pDat = datEx_problem,   method = \"RWR\",   decimals = 2,   legendTitle = \"Importance Score \\n(Rarity Weighted Richness)\" ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ) #> Rarity Wighted Richness.  (ggScores <- patchwork::wrap_plots(ggFerrier + ggRWR))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"comparing-spatial-plans","dir":"Articles","previous_headings":"Overview","what":"Comparing Spatial Plans","title":"A Basic Spatial Planning Workflow","text":"Sometimes can useful direct comparison two spatial plans. show achieve package, first need second conservation problem resulting solution. , second spatial plan include already existing marine protected areas area (https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA) following characteristics: * Status = c(“Designated”, “Established”, “Inscribed”) * Designation Type = c(“National”, “Regional”, “International”, “Applicable”) * IUCN Category = c(“Ia”, “Ib”, “II”, “III”, “IV”)  also include targets based IUCN categories prioritise species IUCN status : Vulnerable Endangered Critically Endangered Extinct Wild Extinct assign 30% target species within categories. species fall categories receive inverse area target, species greater area suitable habitat assigned lower target. can also adjust targets based IUCN Category. apply increased target 0.3 species increased thread level IUCN Red List(“EX”, “EW”, “CR”, “EN”, “VU”). Note: Accessing IUCN database requires login token rl_use_iucn() needs added environment using Sys.setenv(IUCN_REDLIST_KEY = \"[Token]\"). can start running rredlist::rl_use_iucn().","code":"# The user can download their own MPAs using this code, # but below we use data already within the package. LockedIn <- splnr_get_MPAs(PUs, \"Australia\") %>%   splnr_apply_cutoffs(0.5) %>%   dplyr::mutate(wdpa = as.logical(wdpa)) (ggMPA <- splnr_plot(MPAsCoralSea, \"wdpa\") +    splnr_gg_add(      PUs = PUs, Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) minTarget <- 0.1 maxTarget <- 0.2  # Create inverse area target IA_Targets <- splnr_targets_byInverseArea(   datEx_species_bin,   minTarget,   maxTarget ) IUCN_IA_Targets <- IA_Targets %>%   splnr_get_IUCNRedList(species_col = \"Species\") %>% # Add RL data to the df   splnr_targets_byIUCN(IUCN_target = 0.3)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"set-up-second-conservation-problem","dir":"Articles","previous_headings":"Overview > Comparing Spatial Plans","what":"Set up second conservation problem","title":"A Basic Spatial Planning Workflow","text":"locked areas already existing MPAs. want show overlap selected planning units current MPAs, can can add splnr_gg_add()function.  instead want see contours locked areas can set typeLockIn = \"Contours\"splnr_gg_add().","code":"datEx_problem2 <- prioritizr::problem(out_sf, feature_names, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(IA_Targets$target) %>%   prioritizr::add_locked_in_constraints(as.logical(MPAsCoralSea$wdpa)) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  # Add a solution object datEx_soln2 <- datEx_problem2 %>%   prioritizr::solve.ConservationProblem()  (ggSoln2 <- splnr_plot_solution(datEx_soln2) +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     )) (splnr_plot_solution(datEx_soln2) +    splnr_gg_add(      PUs = PUs, Bndry = Bndry, lockIn = MPAsCoralSea,      nameLockIn = \"wdpa\", typeLockIn = \"Full\",      colorLockIn = \"lightgrey\", alphaLockIn = 0.2, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) (splnr_plot_solution(datEx_soln2) +    splnr_gg_add(      lockIn = MPAsCoralSea,      nameLockIn = \"wdpa\", typeLockIn = \"Contours\",      colorLockIn = \"lightgrey\", alphaLockIn = 0.2, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"visualize-comparison","dir":"Articles","previous_headings":"Overview > Comparing Spatial Plans","what":"Visualize comparison","title":"A Basic Spatial Planning Workflow","text":"plot shows first solution (without current MPAs) differs second solution (including current MPAs. categorical map displays, planning units selected solution 2 solution 1 (red), solution 1 solution 2 (blue), selected solutions (grey).  correlation matrix shows similarity Cohen’s Kappa correlation solution 1 solution 2.","code":"(ggComp <- splnr_plot_comparison(datEx_soln, datEx_soln2) +    splnr_gg_add(      PUs = PUs, Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) CorrMat <- splnr_get_kappaCorrData(list(datEx_soln, datEx_soln2),                                    name_sol = c(\"soln1\", \"soln2\") )  (ggCorr <- splnr_plot_corrMat(CorrMat,                               AxisLabels = c(\"Solution 1\", \"Solution 2\") ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"plotting-selection-frequency","dir":"Articles","previous_headings":"Overview > Comparing Spatial Plans","what":"Plotting selection frequency","title":"A Basic Spatial Planning Workflow","text":"Sometimes multiple spatial plans generated, interested many times planning unit selected across array solutions. demonstrate can done using package, first create array (= portfolio) solutions. One example using portfolio","code":"datEx_soln_portfolio <- datEx_problem %>%   prioritizr::add_cuts_portfolio(5) %>% # create a portfolio of solutions   prioritizr::solve.ConservationProblem()  selFreq <- datEx_soln_portfolio %>% # calculate selection frequency   sf::st_drop_geometry() %>%   dplyr::mutate(selFreq = as.factor(rowSums(     dplyr::select(., dplyr::starts_with(\"solution_\"))   ))) %>%   sf::st_as_sf(geometry = datEx_soln_portfolio$geometry) %>%   dplyr::select(selFreq)  (ggselFreq <- splnr_plot_selectionFreq(selFreq) +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Jason D. Everett. Author, maintainer. Sandra Neubert. Author.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Everett J, Neubert S (2024). spatialplanr: Help files prioritzr Spatial Planning projects. R package version 0.6.7, https://github.com/MathMarEcol/spatialplanr.","code":"@Manual{,   title = {spatialplanr: Help files for prioritzr Spatial Planning projects},   author = {Jason D. Everett and Sandra Neubert},   year = {2024},   note = {R package version 0.6.7},   url = {https://github.com/MathMarEcol/spatialplanr}, }"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Help files for prioritzr Spatial Planning projects","text":"package designed assist students staff Mathematical Marine Ecology Lab University Queensland. may useful others well. code written simplify process running prioritizr analysis given region use workflows data MME Lab. still work progress feel free submit pull requests new features code improvements.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Help files for prioritzr Spatial Planning projects","text":"aware package early stages development. Functions documentation complete installing moment risk. still interested, can install development version GitHub :","code":"# install.packages(\"devtools\") devtools::install_github(\"https://github.com/MathMarEcol/spatialplanr\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/CoralSeaVelocity.html","id":null,"dir":"Reference","previous_headings":"","what":"Example climate velocity for the example region of the coral sea — CoralSeaVelocity","title":"Example climate velocity for the example region of the coral sea — CoralSeaVelocity","text":"tsf file containing climate velocity (SSP5-8.5) coral sea","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/CoralSeaVelocity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Example climate velocity for the example region of the coral sea — CoralSeaVelocity","text":"","code":"CoralSeaVelocity"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/CoralSeaVelocity.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Example climate velocity for the example region of the coral sea — CoralSeaVelocity","text":"CoralSeaVelocity data frame 397 rows 3 columns: vocMagg_transformed Climate velocity column geometry Geometry column sf object","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/CoralSeaVelocity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Example climate velocity for the example region of the coral sea — CoralSeaVelocity","text":"https://www.iucnredlist.org/","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/IUCN_IA_Targets.html","id":null,"dir":"Reference","previous_headings":"","what":"IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets","title":"IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets","text":"tbl_df file containing IUCN IA targets selected species coral sea","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/IUCN_IA_Targets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets","text":"","code":"IUCN_IA_Targets"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/IUCN_IA_Targets.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets","text":"IUCN_IA_Targets data frame 15 rows 4 columns: Species Species names found IUCN database Area km2 total suitable habitat species Target Individual species-specific target IUCN_Category IUCN category species","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/IUCN_IA_Targets.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets","text":"https://www.iucnredlist.org/","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/MPAsCoralSea.html","id":null,"dir":"Reference","previous_headings":"","what":"Current MPAs of the Coral Sea — MPAsCoralSea","title":"Current MPAs of the Coral Sea — MPAsCoralSea","text":"sf file containing current marine protected areas coral sea","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/MPAsCoralSea.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Current MPAs of the Coral Sea — MPAsCoralSea","text":"","code":"MPAsCoralSea"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/MPAsCoralSea.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Current MPAs of the Coral Sea — MPAsCoralSea","text":"MPAsCoralSea data frame 397 rows 17 columns: wdpa binary vector denoting presence absence current marine protected area","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/MPAsCoralSea.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Current MPAs of the Coral Sea — MPAsCoralSea","text":"https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_PUs.html","id":null,"dir":"Reference","previous_headings":"","what":"Planning Units — dat_PUs","title":"Planning Units — dat_PUs","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_PUs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Planning Units — dat_PUs","text":"","code":"dat_PUs"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_PUs.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Planning Units — dat_PUs","text":"dat_PUs data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_PUs.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Planning Units — dat_PUs","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bathy.html","id":null,"dir":"Reference","previous_headings":"","what":"Bathymetry Data — dat_bathy","title":"Bathymetry Data — dat_bathy","text":"Bathymetry data downloaded via oceandatr package","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bathy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bathymetry Data — dat_bathy","text":"","code":"dat_bathy"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bathy.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Bathymetry Data — dat_bathy","text":"dat_bathy data frame bathymetry data bathymetry Bathymetry data geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bathy.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Bathymetry Data — dat_bathy","text":"\"oceandatr package\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bndry.html","id":null,"dir":"Reference","previous_headings":"","what":"Boundary of planning units — dat_bndry","title":"Boundary of planning units — dat_bndry","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bndry.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Boundary of planning units — dat_bndry","text":"","code":"dat_bndry"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bndry.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Boundary of planning units — dat_bndry","text":"dat_bndry data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bndry.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Boundary of planning units — dat_bndry","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category.html","id":null,"dir":"Reference","previous_headings":"","what":"Category vector — dat_category","title":"Category vector — dat_category","text":"tibble containing specific grouping features","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Category vector — dat_category","text":"","code":"dat_category"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Category vector — dat_category","text":"dat_category data frame XXXX rows XXX columns: feature features available spatial prioritisation category categories features","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Category vector — dat_category","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category2.html","id":null,"dir":"Reference","previous_headings":"","what":"Category vector — dat_category2","title":"Category vector — dat_category2","text":"tibble containing specific grouping features","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Category vector — dat_category2","text":"","code":"dat_category2"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category2.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Category vector — dat_category2","text":"dat_category2 data frame XXXX rows XXX columns: feature features available spatial prioritisation category categories features","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category2.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Category vector — dat_category2","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_clim.html","id":null,"dir":"Reference","previous_headings":"","what":"Climate metric data — dat_clim","title":"Climate metric data — dat_clim","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_clim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Climate metric data — dat_clim","text":"","code":"dat_clim"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_clim.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Climate metric data — dat_clim","text":"dat_clim data frame 780 rows 3 columns: geometry sf geometry column metric climate metric information","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_clim.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Climate metric data — dat_clim","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_mpas.html","id":null,"dir":"Reference","previous_headings":"","what":"MPA Data — dat_mpas","title":"MPA Data — dat_mpas","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_mpas.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"MPA Data — dat_mpas","text":"","code":"dat_mpas"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_mpas.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"MPA Data — dat_mpas","text":"dat_mpas data frame XXXX rows XXX columns: geometry sf geometry column wdpa binary MPA information (1: MPA)","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_mpas.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"MPA Data — dat_mpas","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_region.html","id":null,"dir":"Reference","previous_headings":"","what":"Regionalisation — dat_region","title":"Regionalisation — dat_region","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_region.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Regionalisation — dat_region","text":"","code":"dat_region"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_region.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Regionalisation — dat_region","text":"dat_region data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_region.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Regionalisation — dat_region","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin.html","id":null,"dir":"Reference","previous_headings":"","what":"Binary Species Data — dat_species_bin","title":"Binary Species Data — dat_species_bin","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Binary Species Data — dat_species_bin","text":"","code":"dat_species_bin"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Binary Species Data — dat_species_bin","text":"dat_species_bin data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Binary Species Data — dat_species_bin","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin2.html","id":null,"dir":"Reference","previous_headings":"","what":"Binary Species Data 2 — dat_species_bin2","title":"Binary Species Data 2 — dat_species_bin2","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Binary Species Data 2 — dat_species_bin2","text":"","code":"dat_species_bin2"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin2.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Binary Species Data 2 — dat_species_bin2","text":"dat_species_bin2 data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin2.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Binary Species Data 2 — dat_species_bin2","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_prob.html","id":null,"dir":"Reference","previous_headings":"","what":"Probability Species Data — dat_species_prob","title":"Probability Species Data — dat_species_prob","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_prob.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Probability Species Data — dat_species_prob","text":"","code":"dat_species_prob"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_prob.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Probability Species Data — dat_species_prob","text":"dat_species_prob data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_prob.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Probability Species Data — dat_species_prob","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spDataFiltered.html","id":null,"dir":"Reference","previous_headings":"","what":"Example data — spDataFiltered","title":"Example data — spDataFiltered","text":"Example data","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spDataFiltered.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Example data — spDataFiltered","text":"","code":"spDataFiltered"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spDataFiltered.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Example data — spDataFiltered","text":"spDataFiltered data frame sample species data Species Species names","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spDataFiltered.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Example data — spDataFiltered","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spatialplanr-package.html","id":null,"dir":"Reference","previous_headings":"","what":"spatialplanr: Help files for prioritzr Spatial Planning projects — spatialplanr-package","title":"spatialplanr: Help files for prioritzr Spatial Planning projects — spatialplanr-package","text":"package provides range tools setting , running plotting spatial plan using prioritizr. intended use Mathematical Marine Ecology Lab UQ, sets projects using approach data sets.","code":""},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spatialplanr-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"spatialplanr: Help files for prioritzr Spatial Planning projects — spatialplanr-package","text":"Maintainer: Jason D. Everett JaseEverett@gmail.com (ORCID) Authors: Sandra Neubert sandra.neubert97@gmail.com (ORCID)","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_apply_cutoffs.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","title":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","text":"Function apply cutoffs feature data","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_apply_cutoffs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","text":"","code":"splnr_apply_cutoffs(features, Cutoffs, inverse = FALSE)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_apply_cutoffs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","text":"features sf dataframe feature information Cutoffs single value named vector cutoffs. inverse TRUE, values Cutoffs used. FALSE (default), values kept.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_apply_cutoffs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","text":"new sf dataframe cutoffs applied.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_apply_cutoffs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","text":"","code":"df <- splnr_apply_cutoffs(dat_species_prob, Cutoffs = 0.5)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_arrangeFeatures.html","id":null,"dir":"Reference","previous_headings":"","what":"Ensure all features are in the same order. — splnr_arrangeFeatures","title":"Ensure all features are in the same order. — splnr_arrangeFeatures","text":"splnr_arrangeFeatures() sorts data based longitude latitude values.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_arrangeFeatures.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Ensure all features are in the same order. — splnr_arrangeFeatures","text":"","code":"splnr_arrangeFeatures(df)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_arrangeFeatures.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Ensure all features are in the same order. — splnr_arrangeFeatures","text":"df sf object sort Lon Lat","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_arrangeFeatures.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Ensure all features are in the same order. — splnr_arrangeFeatures","text":"sorted sf object","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_arrangeFeatures.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Ensure all features are in the same order. — splnr_arrangeFeatures","text":"","code":"df <- dat_species_prob %>%   splnr_arrangeFeatures()"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_featureApproach.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to run the feature approach — splnr_climate_featureApproach","title":"Function to run the feature approach — splnr_climate_featureApproach","text":"Function run feature approach","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_featureApproach.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to run the feature approach — splnr_climate_featureApproach","text":"","code":"splnr_climate_featureApproach(   featuresDF,   metricDF,   targetsDF,   direction,   percentile = 35,   refugiaTarget = 0.3 )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_featureApproach.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to run the feature approach — splnr_climate_featureApproach","text":"featuresDF feature sfobject metricDF climate metric data.frame 'metric' column name metric values per planning unit. targetsDF data.framewith list features \"feature\" column corresponding targets \"target\" column direction direction = 1, metric values low (least climate-smart) high (climate-smart). direction = -1, metric values high (least climate-smart) low (climate-smart). percentile cut-threshold determining whether area climate priority area (e.g., lower 35th percentile warming upper 65th percentile acidification). Note percentile lower limit threshold. refugiaTarget target assigned climate-smart areas","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_featureApproach.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to run the feature approach — splnr_climate_featureApproach","text":"list two components: 1. data frame passed prioritizr creating conservation problem containing binary information per planning unit per feature. 2. targets features conservation problem CPA approach used.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_featureApproach.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to run the feature approach — splnr_climate_featureApproach","text":"","code":"Features <- dat_species_bin  target <- Features %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)  metric_df <- dat_clim   Feature_Approach <- splnr_climate_featureApproach(   featuresDF = dat_species_bin,   metricDF = metric_df, targetsDF = target, direction = 1 ) #> [1] \"Higher values mean more climate-smart areas.\" out_sf <- Feature_Approach$Features targets <- Feature_Approach$Targets"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_percentileApproach.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to run the percentile approach — splnr_climate_percentileApproach","title":"Function to run the percentile approach — splnr_climate_percentileApproach","text":"Function run percentile approach","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_percentileApproach.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to run the percentile approach — splnr_climate_percentileApproach","text":"","code":"splnr_climate_percentileApproach(   featuresDF,   metricDF,   targetsDF,   direction,   percentile = 35 )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_percentileApproach.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to run the percentile approach — splnr_climate_percentileApproach","text":"featuresDF feature sfobject metricDF climate metric data.frame 'metric' column name metric values per planning unit. targetsDF data.framewith list features \"feature\" column corresponding targets \"target\" column direction direction = 1, metric values low (least climate-smart) high (climate-smart). direction = -1, metric values high (least climate-smart) low (climate-smart). percentile cut-threshold determining whether area climate priority area (e.g., lower 35th percentile warming upper 65th percentile acidification). Note percentile lower limit threshold.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_percentileApproach.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to run the percentile approach — splnr_climate_percentileApproach","text":"list two components: 1. data frame passed prioritizr creating conservation problem containing binary information per planning unit per feature. 2. targets features conservation problem CPA approach used.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_percentileApproach.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to run the percentile approach — splnr_climate_percentileApproach","text":"","code":"Features <- dat_species_bin  target <- Features %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)  metric_df <- dat_clim   Percentile_Approach <- splnr_climate_percentileApproach(   featuresDF = dat_species_bin,   metricDF = metric_df, targetsDF = target, direction = 1 ) #> [1] \"Higher values mean more climate-smart areas.\" out_sf <- Percentile_Approach$Features targets <- Percentile_Approach$Targets"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_priorityAreaApproach.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","title":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","text":"Function run climate-priority-area approach","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_priorityAreaApproach.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","text":"","code":"splnr_climate_priorityAreaApproach(   featuresDF,   metricDF,   targetsDF,   direction,   percentile = 5,   refugiaTarget = 1 )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_priorityAreaApproach.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","text":"featuresDF feature sfobject metricDF climate metric data.frame 'metric' column name metric values per planning unit. targetsDF data.framewith list features \"feature\" column corresponding targets \"target\" column direction direction = 1, metric values low (least climate-smart) high (climate-smart). direction = -1, metric values high (least climate-smart) low (climate-smart). percentile cut-threshold determining whether area climate priority area (e.g., lower 35th percentile warming upper 65th percentile acidification). Note percentile lower limit threshold. refugiaTarget target assigned climate-smart areas","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_priorityAreaApproach.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","text":"list two components: 1. data frame passed prioritizr creating conservation problem containing binary information per planning unit per feature. 2. targets features conservation problem CPA approach used.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_priorityAreaApproach.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","text":"","code":"Features <- dat_species_bin  target <- Features %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)  metric_df <- dat_clim  CPA_Approach <- splnr_climate_priorityAreaApproach(   featuresDF = dat_species_bin,   metricDF = metric_df, targetsDF = target, direction = -1 ) out_sf <- CPA_Approach$Features targets <- CPA_Approach$Targets"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_regionalisation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation","text":"","code":"splnr_convert_regionalisation(dat, PUs, cat_name = NA, col_name = NA)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_regionalisation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation","text":"dat Dataset raster sf format. PUs sf object Planning Units cat_name character string categories regionalisation col_name name layer","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_regionalisation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation","text":"sf object containing Planning Units feature.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_regionalisation.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation","text":"wrapper splnr_Convert2PUs() deals need processes layer seperately dataset needs raster vector format. input contains continuous data, output area-averaged mean planning unit. input binary, output proportion planning unit covered.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_regionalisation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation","text":"","code":"if (FALSE) { # \\dontrun{ df <- splnr_convert_regionalisation(dat, PUs) } # }"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_toPUs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to interpolate data onto Planning Units — splnr_convert_toPUs","text":"","code":"splnr_convert_toPUs(dat, PlanUnits)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_toPUs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to interpolate data onto Planning Units — splnr_convert_toPUs","text":"dat Dataset filename dataset PlanUnits sf object Planning Units","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_toPUs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to interpolate data onto Planning Units — splnr_convert_toPUs","text":"sf object containing Planning Units feature.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_toPUs.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Function to interpolate data onto Planning Units — splnr_convert_toPUs","text":"dataset needs raster vector format. input contains continuous data, output area-averaged mean planning unit. input binary, output proportion planning unit covered.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_toPUs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to interpolate data onto Planning Units — splnr_convert_toPUs","text":"","code":"if (FALSE) { # \\dontrun{ df <- splnr_convert_toPUs(dat, PlanUnits) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_create_polygon.html","id":null,"dir":"Reference","previous_headings":"","what":"Function for creating polygon — splnr_create_polygon","title":"Function for creating polygon — splnr_create_polygon","text":"splnr_create_polygon() allows create polygon based longitude latitude coordinates input data.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_create_polygon.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function for creating polygon — splnr_create_polygon","text":"","code":"splnr_create_polygon(x, cCRS = \"EPSG:4326\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_create_polygon.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function for creating polygon — splnr_create_polygon","text":"x named vector lon/lat coordinates make sf polygon cCRS CRS use polygon","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_create_polygon.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function for creating polygon — splnr_create_polygon","text":"sf object polygon","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_create_polygon.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function for creating polygon — splnr_create_polygon","text":"","code":"splnr_create_polygon(x = dplyr::tibble(x = seq(-50, 50, by = 1), y = 120) %>%   dplyr::bind_rows(dplyr::tibble(x = 50, y = seq(120, 180, by = 1))) %>%   dplyr::bind_rows(dplyr::tibble(x = seq(50, -50, by = -1), y = 180)) %>%   dplyr::bind_rows(dplyr::tibble(x = -50, y = seq(150, 120, by = -1))))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_featureNames.html","id":null,"dir":"Reference","previous_headings":"","what":"Returns the feature names — splnr_featureNames","title":"Returns the feature names — splnr_featureNames","text":"splnr_featureNames() allows extract names features want pass prioritizr prioritization. requires sf object input returns column names object excluding columns specify exclude argument.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_featureNames.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Returns the feature names — splnr_featureNames","text":"","code":"splnr_featureNames(dat, exclude = NA)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_featureNames.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Returns the feature names — splnr_featureNames","text":"dat sf dataframe features exclude Character vector columns exclude","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_featureNames.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Returns the feature names — splnr_featureNames","text":"character vector names","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_featureNames.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Returns the feature names — splnr_featureNames","text":"","code":"df <- dat_species_prob %>%   splnr_featureNames()"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_IUCNRedList.html","id":null,"dir":"Reference","previous_headings":"","what":"Match Species to IUCN RedList — splnr_get_IUCNRedList","title":"Match Species to IUCN RedList — splnr_get_IUCNRedList","text":"First need API key, alphanumeric string provided IUCN need send every request; following function takes website, need fill form (might take 1-2 days receive key) rl_use_iucn() receive email API key, set environmental variable (MUST named IUCN_REDLIST_KEY) need re-step everytime restart R Sys.setenv(IUCN_REDLIST_KEY = \"\") add IUCN_REDLIST_KEY = \"\" .Renviron file permanently set Sys.getenv(\"IUCN_REDLIST_KEY\") #' check Evaluated DD: Data Deficient LC: Least Concern NT: Near Threatened VU: Vulnerable EN: Endangered CR: Critically Endangered EW: Extinct Wild EX: Extinct LRlc: Low risk – least concern LRnt: Low risk – near threatened LRcd: Low risk - conservation dependent Categories care cate <- c(\"EX\",\"EW\",\"CR\",\"EN\",\"VU\")","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_IUCNRedList.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Match Species to IUCN RedList — splnr_get_IUCNRedList","text":"","code":"splnr_get_IUCNRedList(df, species_col = \"Species\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_IUCNRedList.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Match Species to IUCN RedList — splnr_get_IUCNRedList","text":"df dataframe containing species matched IUCN redlist species_col string name column containting species name","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_IUCNRedList.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Match Species to IUCN RedList — splnr_get_IUCNRedList","text":"dataframe additional column IUCN_Category","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_IUCNRedList.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Match Species to IUCN RedList — splnr_get_IUCNRedList","text":"","code":"if (FALSE) { # \\dontrun{ df <- data.frame(Species = c(\"Diomedea exulans\", \"Hippocampus kuda\", \"Squatina squatina\")) %>%   splnr_get_IUCNRedList() } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_MPAs.html","id":null,"dir":"Reference","previous_headings":"","what":"Get marine parks from the WDPA. — splnr_get_MPAs","title":"Get marine parks from the WDPA. — splnr_get_MPAs","text":"code wrapper wonderful wdpar package written Jeffrey O. Hanson. data interfaced planning units. sf object returned PU area covered selected marine protected areas.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_MPAs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get marine parks from the WDPA. — splnr_get_MPAs","text":"","code":"splnr_get_MPAs(   PlanUnits,   Countries,   Status = c(\"Designated\", \"Established\", \"Inscribed\"),   Desig = c(\"National\", \"Regional\", \"International\", \"Not Applicable\"),   Category = c(\"Ia\", \"Ib\", \"II\", \"III\", \"IV\"),   ... )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_MPAs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get marine parks from the WDPA. — splnr_get_MPAs","text":"PlanUnits Planning Units sf object Countries character vector countries extract MPAs. get MPAs, use \"global\" . Status status field WDPA provides information whether protected area established, designated, proposed time data submitted. Desig designation type category type protected area legally/officially designated proposed. Category Stores IUCN Protected Area Management Categories (recorded field IUCN_CAT) protected areas categories reported ... arguments passed wdpa_fetch()","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_MPAs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get marine parks from the WDPA. — splnr_get_MPAs","text":"sf object MPAs intersected planning units","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_MPAs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get marine parks from the WDPA. — splnr_get_MPAs","text":"","code":"dat <- splnr_get_MPAs(PlanUnits = dat_PUs, Countries = \"Australia\") #> ! importing local data (version Apr 2024); use \"force=TRUE\" if you need latest version. #> Linking to GEOS 3.13.0, GDAL 3.9.3, PROJ 9.5.0; sf_use_s2() is TRUE #> Warning: attribute variables are assumed to be spatially constant throughout all geometries #> Warning: attribute variables are assumed to be spatially constant throughout all geometries  aust <- rnaturalearth::ne_countries(country = \"Australia\", returnclass = \"sf\")  gg <- ggplot2::ggplot() +   ggplot2::geom_sf(data = dat, ggplot2::aes(fill = wdpa)) +   ggplot2::geom_sf(data = aust, fill = \"grey50\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_boundary.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the boundary of the planning region. — splnr_get_boundary","title":"Get the boundary of the planning region. — splnr_get_boundary","text":"splnr_get_boundary() allows create sf object planning region either based specific coordinate information, rnaturalearth inputs ocean data. Creating boundary often first step conservation planning requirement downstream function sin spatialplanr.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_boundary.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the boundary of the planning region. — splnr_get_boundary","text":"","code":"splnr_get_boundary(Limits, Type = NULL, res = 1, cCRS = \"ESRI:54009\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_boundary.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the boundary of the planning region. — splnr_get_boundary","text":"Limits limits boundary. can either 4 element numeric named vector (c(xmin = 150, xmax = 160, ymin = -40, ymax = -30)), vector ocean/sea names, vector EEZs., Type type Limits provided. Options \"Ocean\" \"EEZ\". (required numeric \"Global\" limits provided) res resolution (degrees) create boundary polygon numeric limits provided. cCRS CRS boundary returned ","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_boundary.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the boundary of the planning region. — splnr_get_boundary","text":"boundary planning region","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_boundary.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the boundary of the planning region. — splnr_get_boundary","text":"","code":"Bndry <- splnr_get_boundary(Limits = \"North Atlantic Ocean\", Type = \"Ocean\") #> Reading layer `ne_10m_geography_marine_polys' from data source  #>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpUmnXWF/ne_10m_geography_marine_polys.shp'  #>   using driver `ESRI Shapefile' #> Simple feature collection with 306 features and 37 fields #> Geometry type: MULTIPOLYGON #> Dimension:     XY #> Bounding box:  xmin: -180 ymin: -85.19206 xmax: 179.9999 ymax: 90 #> Geodetic CRS:  WGS 84 Bndry <- splnr_get_boundary(Limits = \"Global\") Bndry <- splnr_get_boundary(Limits = c(\"xmin\" = 150, \"xmax\" = 170, \"ymin\" = -40, \"ymax\" = -20))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"code takes sf object return updated new coastDistance column. output inherits crs sf object ensure correct projection needs","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"","code":"splnr_get_distCoast(dat_sf, custom_coast = NULL, res = NULL)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"dat_sf sf object. custom_coast sf coastline object (optional) res Allow user choose resolution (small, medium, large) rnaturalearth data used coastline.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"sf object distances nearest coast","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"Written Kristine Buenafe Written: March/April 2023 Modified Kilian Barreiro Updated: December 2023","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"","code":"bbox <- sf::st_bbox(c(xmin = 0, ymin = 0, xmax = 3, ymax = 3)) grid <- sf::st_make_grid(bbox, n = c(3, 3), what = \"polygons\") grid <- sf::st_sf(geometry = grid) %>%   sf::st_set_crs(\"EPSG:4326\") splnr_get_distCoast(grid) #> Simple feature collection with 9 features and 1 field #> Geometry type: POLYGON #> Dimension:     XY #> Bounding box:  xmin: 0 ymin: 0 xmax: 3 ymax: 3 #> Geodetic CRS:  WGS 84 #>                         geometry coastDistance_km #> 1 POLYGON ((0 0, 1 0, 1 1, 0 ...         544.9762 #> 2 POLYGON ((1 0, 2 0, 2 1, 1 ...         553.2552 #> 3 POLYGON ((2 0, 3 0, 3 1, 2 ...         442.2715 #> 4 POLYGON ((0 1, 1 1, 1 2, 0 ...         438.7047 #> 5 POLYGON ((1 1, 2 1, 2 2, 1 ...         480.9762 #> 6 POLYGON ((2 1, 3 1, 3 2, 2 ...         462.5574 #> 7 POLYGON ((0 2, 1 2, 1 3, 0 ...         335.6332 #> 8 POLYGON ((1 2, 2 2, 2 3, 1 ...         371.9517 #> 9 POLYGON ((2 2, 3 2, 3 3, 2 ...         406.2456  cCRS <- \"ESRI:54009\"  Bndry <- splnr_get_boundary(Limits = \"Coral Sea\",                             Type = \"Oceans\",                             cCRS = cCRS) #> Reading layer `ne_10m_geography_marine_polys' from data source  #>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpUmnXWF/ne_10m_geography_marine_polys.shp'  #>   using driver `ESRI Shapefile' #> Simple feature collection with 306 features and 37 fields #> Geometry type: MULTIPOLYGON #> Dimension:     XY #> Bounding box:  xmin: -180 ymin: -85.19206 xmax: 179.9999 ymax: 90 #> Geodetic CRS:  WGS 84  landmass <- rnaturalearth::ne_countries(   scale = \"medium\",   returnclass = \"sf\" ) %>%   sf::st_transform(cCRS)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_featureRep.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare data to plot how well targets are met — splnr_get_featureRep","title":"Prepare data to plot how well targets are met — splnr_get_featureRep","text":"Prepare data plot well targets met","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_featureRep.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare data to plot how well targets are met — splnr_get_featureRep","text":"","code":"splnr_get_featureRep(   soln,   pDat,   targetsDF = NA,   climsmart = FALSE,   climsmartApproach = 0,   solnCol = \"solution_1\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_featureRep.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare data to plot how well targets are met — splnr_get_featureRep","text":"soln prioritizr solution pDat prioritizr problem targetsDF data.framewith list features \"feature\" column corresponding targets \"target\" column climsmart logical denoting whether spatial planning done climate-smart (targets calculated differently) climsmartApproach either 0,1,2 3 depending climate-smart approach used (0 = None; 1 = Climate Priority Area; 2 = Feature; 3 = Percentile). solnCol Name column solution","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_featureRep.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare data to plot how well targets are met — splnr_get_featureRep","text":"tbl_df dataframe","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_featureRep.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prepare data to plot how well targets are met — splnr_get_featureRep","text":"","code":"pDat <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  soln <- pDat %>%   prioritizr::solve.ConservationProblem()  df <- splnr_get_featureRep(   soln = soln,   pDat = pDat )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":null,"dir":"Reference","previous_headings":"","what":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"possibilities offered function explained vignette(\"GlobalFishingWatch\")","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"","code":"splnr_get_gfw(   region,   start_date,   end_date,   temp_res,   spat_res = \"LOW\",   region_source = \"EEZ\",   key = gfwr::gfw_auth(),   cCRS = \"EPSG:4326\",   compress = FALSE )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"region Region studied (character) geojson shape filter raster start_date Start date (waited format : \"%Y-%m-%d\"). end_date End date (waited format : \"%Y-%m-%d\"). temp_res Temporal resolution (\"daily\",\"monthly\",\"yearly\"). spat_res Spatial resolution (\"low\" 0.1 degree, \"high\" 0.01 degree). region_source source region ('eez','mpa', 'rfmo' 'user_json') key Token GFW API (see details GlobalFishingWatch vignette). cCRS crs sf returned (default = \"EPSG:4326\"). compress Binary operator compress (aggregate) data per coordinates (default = FALSE).","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"sf object gfw data.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"parameters get_raster function, plus cCRS crs sf_modification  Different possible values can combined : Time Range, Flag, Geartype. (combination can : c('Time Range','Geartype'), want get sum fishing hours per date geartype, example want display drifting longline fishing specific year) Notes : moment limited EEZs region, can potentially restrict working area specific MPAs. Days indicated the__ start_date end_date __variables included data recovery. code takes several parameters described return sf object gfw data aggregated (param compress)","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"","code":"if (FALSE) { # \\dontrun{ gfw_data <- splnr_get_gfw('Australia', \"2021-01-01\", \"2022-12-31\", \"YEARLY\",     cCRS = \"ESRI:54009\", compress = TRUE) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_kappaCorrData.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","title":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","text":"Conservation planning often requires comparison outputs solutions different conservation problems. One way compare solutions correlating solutions using Cohen's Kappa. splnr_get_kappaCorrData() takes list prioritizr solutions perform Cohen's Kappa correlation solution. resulting correlation matrix symmetrical along main diagonal contains Cohen's Kappa pairwise correlation solutions. main diagonal always 1. correlation matrix obtained function can passed onto splnr_plot_corrMat().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_kappaCorrData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","text":"","code":"splnr_get_kappaCorrData(sol, name_sol)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_kappaCorrData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","text":"sol List prioritizr solutions (sf objects) solutions column name solution_1 name_sol Name tags different solutions","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_kappaCorrData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","text":"matrixOut matrix","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_kappaCorrData.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","text":"","code":"# 30 % target for problem/solution 1 dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  # 50 % target for problem/solution 2 dat_problem2 <- prioritizr::problem(   dat_species_bin %>%     dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.5) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln2 <- dat_problem2 %>%   prioritizr::solve.ConservationProblem()  corrMat <- splnr_get_kappaCorrData(list(dat_soln, dat_soln2), name_sol = c(\"soln1\", \"soln2\")) #> New names: #> • `soln1` -> `soln1...1` #> • `soln1` -> `soln1...2` #> New names: #> • `soln2` -> `soln2...1` #> • `soln2` -> `soln2...2` #> New names: #> • `` -> `...1` #> • `` -> `...2`"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_selFreq.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","title":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","text":"multiple spatial plans generated, often interested many times planning unit selected across array solutions. array can either list solutions different conservation problems generated portfolio approach prioritizr. splnr_get_selFreq() allows calculate selection frequency planning unit either list portfolio solutions. resulting sf object can passed visualization spatialplanr function splnr_plot_selectionFreq().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_selFreq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","text":"","code":"splnr_get_selFreq(solnMany, type = \"portfolio\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_selFreq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","text":"solnMany List portfolio prioritizr solutions type Either \"portfolio\" (sf object) portfolio produced using prioritizr \"list\" list solutions","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_selFreq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","text":"selFreq sf object containing column selection frequency (sum solutions).","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_selFreq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  # create conservation problem that contains a portfolio of solutions dat_soln_portfolio <- dat_problem %>%   prioritizr::add_cuts_portfolio(number_solutions = 5) %>%   prioritizr::solve.ConservationProblem()  selFreq <- splnr_get_selFreq(solnMany = dat_soln_portfolio, type = \"portfolio\") (splnr_plot_selectionFreq(selFreq))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_gg_add.html","id":null,"dir":"Reference","previous_headings":"","what":"Add-ons for plotting — splnr_gg_add","title":"Add-ons for plotting — splnr_gg_add","text":"function allows customise plots simple reproducible way, giving option several inputs can included maps produced functions package.can combined spatialplanr spatial plotting functions.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_gg_add.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add-ons for plotting — splnr_gg_add","text":"","code":"splnr_gg_add(   PUs = NULL,   colorPUs = \"grey80\",   Bndry = NULL,   colorBndry = \"black\",   overlay = NULL,   colorOverlay = \"grey20\",   overlay2 = NULL,   colorOverlay2 = \"grey30\",   overlay3 = NULL,   colorOverlay3 = \"grey40\",   contours = NULL,   colorConts = \"black\",   cropOverlay = NULL,   lockIn = NULL,   typeLockIn = \"Full\",   nameLockIn = NULL,   alphaLockIn = 0.5,   colorLockIn = \"black\",   legendLockIn = \"\",   labelLockIn = \"MPAs\",   ggtheme = \"Default\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_gg_add.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add-ons for plotting — splnr_gg_add","text":"PUs Planning Units sf object colorPUs color value outline planning units. Bndry planning region boundaries sf object colorBndry color value outline boundary. overlay sf object overlay polygon. colorOverlay color value overlay. overlay2 sf object overlay polygon. colorOverlay2 color value overlay. overlay3 sf object overlay polygon. colorOverlay3 color value overlay. contours sf object contours important visualise (e.g. outline sea mounts, ridges; can produced terra::.contour()); 6 different contours possible. colorConts color value contours. cropOverlay sf object boundary box used cropping overlay object. lockIn sf object binary data locked areas prioritisation (e.g. MPAs). typeLockIn Either \"Full\" \"Contours\"; \"Full\" maps locked areas top planning units; \"Contours\" draws outline locked areas. nameLockIn column data frame contains binary information locked areas plot alphaLockIn value (0-1) opacity locked areas plotted top plots. colorLockIn color value locked areas. legendLockIn character value title legend locked areas. Can empty (\"\"). labelLockIn legend label locked area (e.g. MPAs) ggtheme theme applied plot. Can either NA (default ggplot), \"Default\" (default spatialplanr: theme_bw() basic theme settings) user-defined list theme properties.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_gg_add.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add-ons for plotting — splnr_gg_add","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_gg_add.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add-ons for plotting — splnr_gg_add","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  splnr_plot_solution(dat_soln) +   splnr_gg_add(PUs = dat_PUs, ggtheme = \"Default\") #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one."},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_match_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Substitute numbers for all_names in regionalisations — splnr_match_names","title":"Substitute numbers for all_names in regionalisations — splnr_match_names","text":"Many regionalisations numeric values shape files correspond vector names. provide function quickly replace numbers names.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_match_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Substitute numbers for all_names in regionalisations — splnr_match_names","text":"","code":"splnr_match_names(dat, nam)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_match_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Substitute numbers for all_names in regionalisations — splnr_match_names","text":"dat sf data frame one column numeric/integer corresponding nam nam Named character vector names corresponding column dat recode","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_match_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Substitute numbers for all_names in regionalisations — splnr_match_names","text":"sf dataframe numeric regionalisations substituted category names","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_match_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Substitute numbers for all_names in regionalisations — splnr_match_names","text":"","code":"dat <- dat_region nam <- c(\"Region1\" = \"SE Aust\", \"Region2\" = \"Tas\", \"Region3\" = \"NE Aust\") df <- splnr_match_names(dat, nam)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to plot data. — splnr_plot","title":"Function to plot data. — splnr_plot","text":"(now can replace splnr_plot_cost(), splnr_plot_binFeature(), splnr_plot_MPAs(), splnr_plot_featureNo())","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to plot data. — splnr_plot","text":"","code":"splnr_plot(   df,   col_names = NULL,   paletteName = \"YlGnBu\",   colourVals = c(\"#c6dbef\", \"#3182bd\"),   plot_title = \"\",   legend_title = NULL,   legend_labels = NULL )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to plot data. — splnr_plot","text":"df dataframe containing data plotted. must include geometry column used geom_sf. col_names list column names include plot. specified, columns used colour plot. paletteName name colour palette use filling. Default \"YlGnBu\". colourVals colour values use col_names specified data binary. plot_title title plot. legend_title title legend. legend_labels vector strings containing labels use legend values.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to plot data. — splnr_plot","text":"ggplot object.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Function to plot data. — splnr_plot","text":"Written Kilian Barreiro Jason Everett Written: February 2024","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to plot data. — splnr_plot","text":"","code":"# Binary plot of species distribution splnr_plot(df = dat_species_bin,            col_names = \"Spp1\",            legend_title = \"Legend\",            legend_labels = c(\"Absent\", \"Present\")) #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one.   # Logical plot of species distribution splnr_plot(df = dat_species_bin %>%                 dplyr::mutate(dplyr::across(                   tidyselect::starts_with(\"Spp\"), as.logical)),            col_names = \"Spp1\",            legend_title = \"Legend\",            legend_labels = c(\"Absent\", \"Present\")) #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one.   # Continuous plot of bathymetry# splnr_plot(df = dat_bathy,            col_names = \"bathymetry\",            plot_title = \"Bathymetry\",            legend_title = \"Bathymetry (m)\") #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one.   # Plot Planning Units splnr_plot(df = dat_PUs) #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one.   # Multi binary features splnr_plot(df = dat_species_bin,            col_names = colnames(dat_species_bin %>%                                   sf::st_drop_geometry() %>%                                   dplyr::select(                                     tidyselect::starts_with(\"Spp\"))),            legend_title = \"Number of features\") #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one."},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_MPAs.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot MPAs — splnr_plot_MPAs","title":"Plot MPAs — splnr_plot_MPAs","text":"splnr_plot_MPAs() allows plot either outline area MPAs existing planning region (example extracted spatialplanrfunction splnr_get_MPAs()) customisable way using ggplot2. function requires sf object containing information whether planning unit planning region lies within MPA column called wdpa outputs ggobject. can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_MPAs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot MPAs — splnr_plot_MPAs","text":"","code":"splnr_plot_MPAs(   df,   colorVals = c(`TRUE` = \"blue\", `FALSE` = \"white\"),   showLegend = TRUE,   plotTitle = \"Locked In Areas\",   legendTitle = \"\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_MPAs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot MPAs — splnr_plot_MPAs","text":"df sf object marine protected areas colorVals list object named vectors match color value according name. \"TRUE\" stands selected planning units. showLegend logical command whether show legend solution (Default: TRUE). plotTitle character value title plot. Can empty (\"\"). legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_MPAs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot MPAs — splnr_plot_MPAs","text":"ggplot object plot","code":""},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_MPAs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot MPAs — splnr_plot_MPAs","text":"","code":"if (FALSE) { # \\dontrun{ splnr_plot_MPAs(dat_mpas) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_binFeature.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot binary feature — splnr_plot_binFeature","title":"Plot binary feature — splnr_plot_binFeature","text":"splnr_plot_binFeature() allows plot presences absences feature planning region customisable way using ggplot2. function requires sf object binary information feature(0 absences 1 presences, example created continuous data spatialplanr function splnr_apply_cutoffs()). outputs ggobject can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_binFeature.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot binary feature — splnr_plot_binFeature","text":"","code":"splnr_plot_binFeature(   df,   colInterest,   colorVals = c(Suitable = \"#3182bd\", `Not Suitable` = \"#c6dbef\"),   showLegend = TRUE,   plotTitle = \" \",   legendTitle = \"Habitat\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_binFeature.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot binary feature — splnr_plot_binFeature","text":"df data frame binary feature information colInterest column data frame contains binary information feature plot colorVals list object named vectors match color value according name. \"TRUE\" stands selected planning units. showLegend logical command whether show legend solution (Default: TRUE). plotTitle character value title plot. Can empty (\"\"). legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_binFeature.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot binary feature — splnr_plot_binFeature","text":"ggplot object plot","code":""},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_binFeature.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot binary feature — splnr_plot_binFeature","text":"","code":"if (FALSE) { # \\dontrun{ splnr_plot_binFeature(dat_species_bin, dat_species_bin$Spp1) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_circBplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot circular barplot — splnr_plot_circBplot","title":"Plot circular barplot — splnr_plot_circBplot","text":"Plot circular barplot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_circBplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot circular barplot — splnr_plot_circBplot","text":"","code":"splnr_plot_circBplot(   df,   legend_color,   legend_list,   indicateTargets = TRUE,   impTarget = NA,   repTarget = NA,   colTarget = \"red\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_circBplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot circular barplot — splnr_plot_circBplot","text":"df data frame following column names: feature, value, group legend_color vector list colors; group names corresponding colors legend_list list groups/legends groups indicateTargets logical whether show targets set impTarget target important features (%) repTarget target representative features (%) colTarget string colour value indicator line","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_circBplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot circular barplot — splnr_plot_circBplot","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_circBplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot circular barplot — splnr_plot_circBplot","text":"","code":"# DISCLAIMER: THIS SOLUTION IS NOT ACTUALLY RUN WITH THESE TARGETS YET  dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  s1 <- dat_soln %>%   tibble::as_tibble()  p1 <- dat_problem  df_rep_imp <- prioritizr::eval_feature_representation_summary(   p1,   s1[, \"solution_1\"] ) %>%   dplyr::select(feature, relative_held) %>%   dplyr::mutate(relative_held = relative_held * 100)  imp_layers <- c(\"Spp1\", \"Spp3\")  target <- data.frame(feature = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\")) %>%   dplyr::mutate(class = dplyr::if_else(.data$feature %in% imp_layers,     \"important\", \"representative\"   )) %>%   dplyr::mutate(target = dplyr::if_else(class == \"important\",     50 / 100, 30 / 100   ))  df <- merge(df_rep_imp, target) %>%   dplyr::select(-target) %>%   na.omit() %>%   dplyr::rename(value = relative_held) %>%   dplyr::rename(group = class)  colors <- c(   \"important\" = \"darkgreen\",   \"representative\" = \"darkred\" ) legends <- c(\"Important\", \"Representative\")  (splnr_plot_circBplot(df,   legend_list = legends,   legend_color = colors,   impTarget = 50, repTarget = 30 )) #> Warning: Removed 4 rows containing missing values or values outside the scale range #> (`geom_bar()`). #> Warning: Removed 6 rows containing missing values or values outside the scale range #> (`geom_text()`)."},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climData.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot climate data — splnr_plot_climData","title":"Plot climate data — splnr_plot_climData","text":"Plot climate data","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot climate data — splnr_plot_climData","text":"","code":"splnr_plot_climData(   df,   colInterest,   colorMap = \"C\",   plotTitle = \" \",   legendTitle = \"Climate metric\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot climate data — splnr_plot_climData","text":"df sf object climate metric information colInterest column data frame contains metric informatin colorMap character string indicating color map use (see https://ggplot2.tidyverse.org/reference/scale_viridis.html options) plotTitle character value title plot. Can empty (\"\"). legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot climate data — splnr_plot_climData","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climData.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot climate data — splnr_plot_climData","text":"","code":"splnr_plot_climData(df = dat_clim, colInterest = \"metric\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climKernelDensity.html","id":null,"dir":"Reference","previous_headings":"","what":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","title":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","text":"Kernel Density Plots climate-smart spatial plans","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climKernelDensity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","text":"","code":"splnr_plot_climKernelDensity(   soln,   names = NA,   type = \"Normal\",   colorMap = \"C\",   legendTitle = expression(\" °C y\"^\"-1\" * \"\"),   xAxisLab = expression(\"Climate warming ( °C y\"^\"-1\" * \")\") )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climKernelDensity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","text":"soln type \"Publication\": list prioirtizr solutions (e.g. solution_list = list(s1, s2)) containing \"metric\" column containing used climate metric information; type \"App\": needs prioritizr solution names list names solutions (names = c(\"Input 1\", \"Input 2\")) type plotting style kernel density plots. Either \"Publication\" gives axis information etc., \"App\" condenses information plot simplify stakeholders. colorMap character string indicating color map use (see https://ggplot2.tidyverse.org/reference/scale_viridis.html options) legendTitle character value title legend. Can empty (\"\"). xAxisLab characted value x Axis label depending climate metric input","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climKernelDensity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climKernelDensity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","text":"","code":"target <- dat_species_bin %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)  CPA <- splnr_climate_priorityAreaApproach(   featuresDF = dat_species_bin,   metricDF = dat_clim,   targetsDF = target,   direction = -1,   refugiaTarget = 1 )  out_sf <- CPA$Features %>%   dplyr::mutate(Cost_None = rep(1, 780)) %>%   sf::st_join(dat_clim, join = sf::st_equals)  usedFeatures <- out_sf %>%   sf::st_drop_geometry() %>%   dplyr::select(-tidyselect::starts_with(\"Cost_\"), -\"metric\") %>%   names()  p1 <- prioritizr::problem(out_sf, usedFeatures, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(CPA$Targets$target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_solnClim <- prioritizr::solve.ConservationProblem(p1) splnr_plot_climKernelDensity(dat_solnClim, type = \"Basic\") splnr_plot_climKernelDensity(soln = list(dat_solnClim), names = c(\"Input 1\"), type = \"Normal\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_comparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot solution comparison — splnr_plot_comparison","title":"Plot solution comparison — splnr_plot_comparison","text":"Conservation planning often requires comparison outputs solutions different conservation problems. One way compare solutions spatially visualising different planning units selected two separate solutions conservation problems. splnr_plot_comparison() allows map differences two solutions customisable way using ggplot2. function requires two separate sf objects containing solution_1 column indicating binary solution (selected vs selected) prioritizr conservation problem. outputs ggobject can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_comparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot solution comparison — splnr_plot_comparison","text":"","code":"splnr_plot_comparison(   soln1,   soln2,   legendTitle = \"Scenario 2 compared to Scenario 1:\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_comparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot solution comparison — splnr_plot_comparison","text":"soln1 first prioritizr solution soln2 second prioritizr solution legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_comparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot solution comparison — splnr_plot_comparison","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_comparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot solution comparison — splnr_plot_comparison","text":"","code":"# 30 % target for problem/solution 1 dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  # 50 % target for problem/solution 2 dat_problem2 <- prioritizr::problem(   dat_species_bin %>%     dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.5) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln2 <- dat_problem2 %>%   prioritizr::solve.ConservationProblem()  (splnr_plot_comparison(dat_soln, dat_soln2))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_corrMat.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot correlation matrices — splnr_plot_corrMat","title":"Plot correlation matrices — splnr_plot_corrMat","text":"Conservation planning often requires comparison outputs solutions different conservation problems. One way compare solutions correlating solutions using Cohen's Kappa. splnr_plot_corrMat() allows visualize correlation matrix different solutions (example produced spatialplanr function splnr_get_kappaCorrData()).","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_corrMat.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot correlation matrices — splnr_plot_corrMat","text":"","code":"splnr_plot_corrMat(   x,   colourGradient = c(\"#BB4444\", \"#FFFFFF\", \"#4477AA\"),   legendTitle = \"Correlation \\ncoefficient\",   AxisLabels = NULL,   plotTitle = \"\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_corrMat.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot correlation matrices — splnr_plot_corrMat","text":"x correlation matrix prioritizr solutions colourGradient list three colour values high positive, high negative correlation legendTitle character value title legend. Can empty (\"\"). AxisLabels list labels solutions correlated (Default: NULL). Length needs match number correlated solutions. plotTitle character value title plot. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_corrMat.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot correlation matrices — splnr_plot_corrMat","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_corrMat.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot correlation matrices — splnr_plot_corrMat","text":"","code":"# 30 % target for problem/solution 1 dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  # 50 % target for problem/solution 2 dat_problem2 <- prioritizr::problem(   dat_species_bin %>%     dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.5) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln2 <- dat_problem2 %>%   prioritizr::solve.ConservationProblem()  CorrMat <- splnr_get_kappaCorrData(list(dat_soln, dat_soln2), name_sol = c(\"soln1\", \"soln2\")) #> New names: #> • `soln1` -> `soln1...1` #> • `soln1` -> `soln1...2` #> New names: #> • `soln2` -> `soln2...1` #> • `soln2` -> `soln2...2` #> New names: #> • `` -> `...1` #> • `` -> `...2`  (splnr_plot_corrMat(CorrMat, AxisLabels = c(\"Solution 1\", \"Solution 2\"))) #> Scale for fill is already present. #> Adding another scale for fill, which will replace the existing scale. #> Scale for x is already present. #> Adding another scale for x, which will replace the existing scale."},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_cost.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot cost — splnr_plot_cost","title":"Plot cost — splnr_plot_cost","text":"splnr_plot_cost() allows plot cost within planning units planning region customisable way using ggplot2. function requires sf object cost column outputs ggobject. can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_cost.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot cost — splnr_plot_cost","text":"","code":"splnr_plot_cost(   Cost,   Cost_name = \"Cost\",   legendTitle = \"Cost\",   paletteName = \"YlGnBu\",   plotTitle = \"\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_cost.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot cost — splnr_plot_cost","text":"Cost sf object cost prioritizr Cost_name Name cost column legendTitle character value title legend. Can empty (\"\"). paletteName string (number) color palette use. Available palettes can found https://ggplot2.tidyverse.org/reference/scale_brewer.html. plotTitle character value title plot. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_cost.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot cost — splnr_plot_cost","text":"ggplot object plot","code":""},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_cost.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot cost — splnr_plot_cost","text":"","code":"if (FALSE) { # \\dontrun{ dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  dat_cost <- dat_soln %>%   dplyr::mutate(Cost = runif(n = dim(.)[[1]]))  (splnr_plot_cost(dat_cost)) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_costOverlay.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot cost overlay — splnr_plot_costOverlay","title":"Plot cost overlay — splnr_plot_costOverlay","text":"splnr_plot_costOverlay() allows plot cost planning units planning region top solution conservation problem created prioritizr customisable way using ggplot2. function requires solution sf object column called solution_1 well cost column outputs ggobject. can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_costOverlay.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot cost overlay — splnr_plot_costOverlay","text":"","code":"splnr_plot_costOverlay(   soln,   Cost = NA,   Cost_name = \"Cost\",   legendTitle = \"Cost\",   plotTitle = \"Solution overlaid with cost\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_costOverlay.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot cost overlay — splnr_plot_costOverlay","text":"soln prioritizr solution Cost sf object cost prioritizr.case prioritizrsolution contain cost, alternative cost object provided used generate solution (default: NA). Cost_name Name cost column legendTitle character value title legend. Can empty (\"\"). plotTitle character value title plot. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_costOverlay.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot cost overlay — splnr_plot_costOverlay","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_costOverlay.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot cost overlay — splnr_plot_costOverlay","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  splnr_plot_costOverlay(soln = dat_soln)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot number of features — splnr_plot_featureNo","title":"Plot number of features — splnr_plot_featureNo","text":"splnr_plot_featureNo() allows use ggplot2 visually inspect number features per planning unit used inputs conservation problem. features species, map can seen visualisation species richness planning region.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot number of features — splnr_plot_featureNo","text":"","code":"splnr_plot_featureNo(   df,   showLegend = TRUE,   paletteName = \"YlGnBu\",   plotTitle = \"Number of Features\",   legendTitle = \"Features\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot number of features — splnr_plot_featureNo","text":"df sf object features showLegend logical command whether show legend solution (Default: TRUE). paletteName string (number) color palette use. Available palettes can found https://ggplot2.tidyverse.org/reference/scale_brewer.html. plotTitle character value title plot. Can empty (\"\"). legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot number of features — splnr_plot_featureNo","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot number of features — splnr_plot_featureNo","text":"function requires sf object binary information features want include richness plot (0 absences 1 presences, example created continuous data spatialplanr function splnr_apply_cutoffs()). outputs ggobject can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot number of features — splnr_plot_featureNo","text":"","code":"if (FALSE) { # \\dontrun{ (splnr_plot_featureNo(dat_species_bin)) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureRep.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot how well targets are met — splnr_plot_featureRep","title":"Plot how well targets are met — splnr_plot_featureRep","text":"Plot well targets met","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureRep.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot how well targets are met — splnr_plot_featureRep","text":"","code":"splnr_plot_featureRep(   df,   category = NA,   categoryFeatureCol = NA,   renameFeatures = FALSE,   namesToReplace = NA,   nr = 1,   showTarget = NA,   plotTitle = \"\",   ... )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureRep.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot how well targets are met — splnr_plot_featureRep","text":"df df containing target information (resulting splnr_get_featureRep() function) category named data frame feature category grouping plot output categoryFeatureCol character column containing feature infromation plotted category data frame contain column named 'feature' can matched 'df' infromation. renameFeatures logical whether variable names used replaced common names namesToReplace data frame containing variable name ('nameVariable') common name ('nameCommon'). nr Number rows legend showTarget logical targets shown bar plot plotTitle character value title plot. Can empty (\"\"). ... arguments passed ggplot2::theme()","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureRep.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot how well targets are met — splnr_plot_featureRep","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureRep.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot how well targets are met — splnr_plot_featureRep","text":"","code":"pDat <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  soln <- pDat %>%   prioritizr::solve.ConservationProblem()   # including incidental species coverage df <- splnr_get_featureRep(   soln = soln,   pDat = pDat )  (splnr_plot_featureRep(df, category = dat_category))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot importance score — splnr_plot_importanceScore","title":"Plot importance score — splnr_plot_importanceScore","text":"Importance scores mean reflect irreplaceability planning unit solution prioirtizr conservation problem. Based prioritizr package, splnr_plot_importanceScore() allows visualize three different types importance scores ggplot2 used based conservation problem hand. prioritizr development team generally recommend using replacement cost score, however might feasible conservation problems many planning units features.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot importance score — splnr_plot_importanceScore","text":"","code":"splnr_plot_importanceScore(   soln,   pDat,   method = \"Ferrier\",   plotTitle = \"\",   colorMap = \"A\",   decimals = 4,   legendTitle = \"Importance Score\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot importance score — splnr_plot_importanceScore","text":"soln prioritizr solution pDat prioritizr problem method method calcualting importance scores. Can either \"Ferrier\" Ferrier Score, can used minimum set objective function, \"RWR\" Rarity Weighted Richness Score, \"RC\" Replacement Cost takes longer approaches due iterative process. plotTitle character value title plot. Can empty (\"\"). colorMap character string indicating color map use (see https://ggplot2.tidyverse.org/reference/scale_viridis.html options) decimals number decimals shown plot. Ferrier Score often requires higher number decimals (>4) two approaches (2) analysis work. legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot importance score — splnr_plot_importanceScore","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot importance score — splnr_plot_importanceScore","text":"function outputs ggobject can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot importance score — splnr_plot_importanceScore","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  (splnr_plot_importanceScore(soln = dat_soln, pDat = dat_problem, method = \"Ferrier\", decimals = 4)) #> Ferrier Score."},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_selectionFreq.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","title":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","text":"multiple spatial plans generated, often interested many times planning unit selected across array solutions. array can either made solutions different conservation problems generated portfolio approach prioritizr. Either way, function requires sf object input contains column (selFreq) selection frequency planning unit can generated spatialplanrfunction splnr_get_selFreq(). splnr_plot_selectionFreq() allows visualize selection frequency using ggplot2. outputs ggobject can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_selectionFreq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","text":"","code":"splnr_plot_selectionFreq(   selFreq,   plotTitle = \"\",   paletteName = \"Greens\",   legendTitle = \"Selection \\nFrequency\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_selectionFreq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","text":"selFreq sf object containing selection frequency planning unit array solutions plotTitle character value title plot. Can empty (\"\"). paletteName string (number) color palette use. Available palettes can found https://ggplot2.tidyverse.org/reference/scale_brewer.html. legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_selectionFreq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_selectionFreq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  # create conservation problem that contains a portfolio of solutions dat_soln_portfolio <- dat_problem %>%   prioritizr::add_cuts_portfolio(number_solutions = 5) %>%   prioritizr::solve.ConservationProblem()  selFreq <- splnr_get_selFreq(solnMany = dat_soln_portfolio, type = \"portfolio\") (splnr_plot_selectionFreq(selFreq))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_solution.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot prioritizr solution — splnr_plot_solution","title":"Plot prioritizr solution — splnr_plot_solution","text":"splnr_plot_solution() allows plot solution prioritizr conservation problem without customisable way using ggplot2. function requires solution sf object column called solution_1 outputs ggobject. can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_solution.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot prioritizr solution — splnr_plot_solution","text":"","code":"splnr_plot_solution(   soln,   colorVals = c(\"#c6dbef\", \"#3182bd\"),   showLegend = TRUE,   legendLabels = c(\"Not selected\", \"Selected\"),   plotTitle = \"Solution\",   legendTitle = \"Planning Units\",   zones = FALSE )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_solution.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot prioritizr solution — splnr_plot_solution","text":"soln prioritizr solution colorVals list object named vectors match color value according name. \"TRUE\" stands selected planning units. showLegend logical command whether show legend solution (Default: TRUE). legendLabels Character values (number zones + 1) legend labelled. plotTitle character value title plot. Can empty (\"\"). legendTitle character value title legend. Can empty (\"\"). zones logical value, indicating whether spatial plan contains zones (default = FALSE).","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_solution.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot prioritizr solution — splnr_plot_solution","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_solution.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot prioritizr solution — splnr_plot_solution","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  splnr_plot_solution(dat_soln)  # example 2 t2 <- matrix(NA, ncol = 2, nrow = 5) # create targets t2[, 1] <- 0.1 t2[, 2] <- 0.05  z2 <- prioritizr::zones(   \"zone 1\" = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   \"zone 2\" = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\") ) # when giving sf input, we need as many cost columns as we have zones p2 <- prioritizr::problem(   dat_species_bin %>% dplyr::mutate(     Cost1 = runif(n = dim(.)[[1]]),     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(t2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s2 <- p2 %>%   prioritizr::solve.ConservationProblem() (splnr_plot_solution(s2,   zones = TRUE, colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_replace_NAs.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","title":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","text":"splnr_replace_NAs() allows replace NA values data value nearest neighbour. nearest neighbour determined using st_nearest_feature() sf package.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_replace_NAs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","text":"","code":"splnr_replace_NAs(df, vari)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_replace_NAs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","text":"df sf dataframe vari Variable remove NAs ","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_replace_NAs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","text":"sf object NAs replaced nearest neighbour","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_replace_NAs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","text":"","code":"df <- dat_species_prob %>%   splnr_replace_NAs(\"Spp2\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_scale_01.html","id":null,"dir":"Reference","previous_headings":"","what":"Scale spatial layers to between 0 and 1 — splnr_scale_01","title":"Scale spatial layers to between 0 and 1 — splnr_scale_01","text":"splnr_scale_01() allows re-scale data values greater 1 values 0 1.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_scale_01.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Scale spatial layers to between 0 and 1 — splnr_scale_01","text":"","code":"splnr_scale_01(dat, col_name)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_scale_01.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Scale spatial layers to between 0 and 1 — splnr_scale_01","text":"dat sf dataframe col_name Name column scale","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_scale_01.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Scale spatial layers to between 0 and 1 — splnr_scale_01","text":"sf dataframe","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_scale_01.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Scale spatial layers to between 0 and 1 — splnr_scale_01","text":"","code":"df <- dat_species_prob %>%   dplyr::mutate(Spp1 = Spp1 * 100) %>%   splnr_scale_01(col_name = \"Spp1\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byCategory.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign targets to all features by category — splnr_targets_byCategory","title":"Assign targets to all features by category — splnr_targets_byCategory","text":"splnr_targets_byCategory() allows assign targets conservation planning based species categories.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byCategory.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign targets to all features by category — splnr_targets_byCategory","text":"","code":"splnr_targets_byCategory(dat, catTarg, catName = \"Category\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byCategory.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign targets to all features by category — splnr_targets_byCategory","text":"dat sf object features categories catTarg named character vector categories target catName optional argument name category column dat","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byCategory.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign targets to all features by category — splnr_targets_byCategory","text":"sf object targets added","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byCategory.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign targets to all features by category — splnr_targets_byCategory","text":"","code":"dat <- splnr_targets_byCategory(   dat = dat_category,   catTarg = c(\"Group1\" = 0.5, \"Group2\" = 0.2),   catName = \"category\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byIUCN.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","title":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","text":"splnr_targets_byIUCN() allows assign targets species used conservation planning based IUCN categories. Species can extracted based IUCN categories spatoalplnrfunction splnr_get_IUCNRedList(). Accessing IUCN database requires login token rl_use_iucn() needs added environment using Sys.setenv(IUCN_REDLIST_KEY = \"[Token]\"). can start running rredlist::rl_use_iucn().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byIUCN.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","text":"","code":"splnr_targets_byIUCN(dat, IUCN_target, IUCN_col = \"IUCN_Category\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byIUCN.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","text":"dat dataframe sf object IUCN categories IUCN_target Either numeric named numeric targets apply IUCN categories IUCN_col Optional string indicate name column IUCN categories","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byIUCN.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","text":"dataframe sf object","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byIUCN.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","text":"","code":"dat <- data.frame(IUCN_Category = c(\"EW\", \"EX\", NA), target = c(0.3, 0.3, 0.3)) IUCN_target <- c(\"EX\" = 0.8, \"EW\" = 0.6) dat <- splnr_targets_byIUCN(dat, IUCN_target)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byInverseArea.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign targets by Inverse Area — splnr_targets_byInverseArea","title":"Assign targets by Inverse Area — splnr_targets_byInverseArea","text":"function takes min (target_min) max (target_max) target range calculates inverse area target feature based areal coverage.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byInverseArea.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign targets by Inverse Area — splnr_targets_byInverseArea","text":"","code":"splnr_targets_byInverseArea(df, target_min, target_max)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byInverseArea.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign targets by Inverse Area — splnr_targets_byInverseArea","text":"df sf dataframe features calculate target_min minimum target inverse area target_max maximum target inverse area","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byInverseArea.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign targets by Inverse Area — splnr_targets_byInverseArea","text":"sf dataframe Inverse Area Targets added Target","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byInverseArea.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign targets by Inverse Area — splnr_targets_byInverseArea","text":"","code":"targets <- dat_species_prob %>%   splnr_targets_byInverseArea(target_min = 0.3, target_max = 0.8)"}]
+[{"path":"https://mathmarecol.github.io/spatialplanr/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2023 Jason D. Everett Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"Climate-Smart Spatial Planning","text":"code written simplify process running prioritizr analysis given region. still work progress feel free submit pull requests new features code improvements.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"set-user-parameters","dir":"Articles","previous_headings":"Overview","what":"Set user parameters","title":"Climate-Smart Spatial Planning","text":"Set diameter planning units. units CRS (usually metres degrees). can also use customised ggplot theme can passed list splnr_gg_add() can used plots. example:","code":"Region <- \"Coral Sea\" # \"Australia\" Type <- \"Oceans\" # \"EEZ\" cCRS <- \"ESRI:54009\" # Mollweide PU_size <- 107460 # m splnr_theme <- list(   ggplot2::theme_bw(),   ggplot2::theme(     legend.position = \"right\",     legend.direction = \"vertical\",     text = ggplot2::element_text(size = 9, colour = \"black\"),     axis.text = ggplot2::element_text(size = 9, colour = \"black\"),     plot.title = ggplot2::element_text(size = 9),     axis.title = ggplot2::element_blank()   ) )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"analysis-region","dir":"Articles","previous_headings":"Overview","what":"Analysis Region","title":"Climate-Smart Spatial Planning","text":"Start analysis defining region setting planning units. Get boundary chosen region.","code":"Bndry <- splnr_get_boundary(Limits = Region, Type = Type, cCRS = cCRS) #> Reading layer `ne_10m_geography_marine_polys' from data source  #>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpHVmm7h/ne_10m_geography_marine_polys.shp'  #>   using driver `ESRI Shapefile' #> Simple feature collection with 306 features and 37 fields #> Geometry type: MULTIPOLYGON #> Dimension:     XY #> Bounding box:  xmin: -180 ymin: -85.19206 xmax: 179.9999 ymax: 90 #> Geodetic CRS:  WGS 84  landmass <- rnaturalearth::ne_countries(scale = \"medium\", returnclass = \"sf\") %>%   sf::st_transform(cCRS)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"create-planning-units","dir":"Articles","previous_headings":"Overview","what":"Create Planning Units","title":"Climate-Smart Spatial Planning","text":"","code":"PUs <- spatialgridr::get_grid(boundary = Bndry,                               crs = cCRS,                               output = \"sf_hex\",                               resolution = PU_size)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"get-the-features","dir":"Articles","previous_headings":"Overview","what":"Get the features","title":"Climate-Smart Spatial Planning","text":"example, use small subset charismatic megafauna species Coral Sea inform conservation plan. filtered Aquamaps (Aquamaps.org) species distribution models study area following species: species chosen based importance region represent example visualization purposes. Note: structure tribbleabove required downstream plotting. Common denotes common name species, Scientific scientific name format used Aquamaps, Category category species belongs Class represents importance species conservation plan.","code":"Dict <- tibble::tribble(   ~nameCommon, ~nameVariable, ~category,    \"Green sea turtle\", \"Chelonia_mydas\", \"Reptiles\",    \"Loggerhead sea turtle\", \"Caretta_caretta\", \"Reptiles\",    \"Hawksbill sea turtle\", \"Eretmochelys_imbricata\", \"Reptiles\",    \"Olive ridley sea turtle\", \"Lepidochelys_olivacea\", \"Reptiles\",    \"Saltwater crocodile\", \"Crocodylus_porosus\", \"Reptiles\",    \"Humpback whale\", \"Megaptera_novaeangliae\", \"Mammals\",    \"Common Minke whale\", \"Balaenoptera_acutorostrata\", \"Mammals\",    \"Dugong\", \"Dugong_dugon\", \"Mammals\",    \"Grey nurse shark\", \"Carcharias_taurus\", \"Sharks and rays\",    \"Tiger shark\", \"Galeocerdo_cuvier\", \"Sharks and rays\",    \"Great hammerhead shark\", \"Sphyrna_mokarran\",   \"Sharks and rays\",    \"Giant oceanic manta ray\", \"Mobula_birostris\", \"Sharks and rays\",    \"Reef manta ray\", \"Mobula_alfredi\", \"Sharks and rays\",    \"Whitetip reef shark\", \"Triaenodon_obesus\", \"Sharks and rays\",   \"Red-footed booby\", \"Sula_sula\", \"Birds\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"convert-the-probabilities-to-binary-data","dir":"Articles","previous_headings":"Overview > Get the features","what":"Convert the probabilities to binary data","title":"Climate-Smart Spatial Planning","text":"","code":"datEx_species_bin <- spDataFiltered %>%   dplyr::as_tibble() %>%   dplyr::mutate(dplyr::across(     -dplyr::any_of(c(\"geometry\")), # Don't apply to geometry     ~ dplyr::case_when(       . >= 0.5 ~ 1,       . < 0.5 ~ 0,       is.na(.data) ~ 0     )   )) %>%   sf::st_as_sf()  col_name <- spDataFiltered %>%   sf::st_drop_geometry() %>%   colnames()"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"climate-smart-spatial-planning","dir":"Articles","previous_headings":"Overview > Get the features","what":"Climate-smart spatial planning","title":"Climate-Smart Spatial Planning","text":"far, steps exactly spatial plan include climate change. make spatial plan climate smart, need climate metrics. use climate velocity data obtained x, y z models using SSP5-8.5. downstream analysis, rename column interest (: velocity data) metric. climate velocity data can visualized using splnr_plot_climData() function.  case, areas low climate velocity, areas define climate refugia example. Usually, combine several metrics (e.g. exposure, velocity etc.) multiple SSP scenarios get robust climate refugia. example, randomly set areas high velocity value 0.85-1 visualize output (CHANGE LATER BETTER DATA).  use climate priority area approach splnr_climate_priorityAreaApproach() detailed Buenafe et al (2023) determine climate refugia. Briefly, approach selects percentile (case 5%) suitable habitat feature considered climate-smart. also requires direction input indicating side metric range climate-smart areas can found. case, lower climate velocity denotes climate-smart (direction = -1), cases higher value might represent climate-smart planning units (direction = 1). Using approach also requires adaptation targets, since 5% suitable habitat species already protected climate-smart areas. can decide much 5% climate-smart areas supposed included spatial plan (: refugiaTarget = 1 protect 100% 5% climate-smart areas). now add information required perform spatial planning, cost, extract names used features.","code":"metric <- CoralSeaVelocity %>%   dplyr::rename(metric = voccMag_transformed) (ggclim <- splnr_plot_climData(metric, \"metric\") +    splnr_gg_add(      Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) set.seed(5)  metric <- CoralSeaVelocity %>%   dplyr::rename(metric = voccMag_transformed) %>%   dplyr::mutate(     metricOG = metric,     metric = ifelse(metric > 0.99, runif(., 0.85, 1.0), metric)   )  (ggclim <- splnr_plot_climData(metric, \"metric\") +     splnr_gg_add(       Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     )) targets <- datEx_species_bin %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)   CPA_Approach <- splnr_climate_priorityAreaApproach(   features = datEx_species_bin,   metric = metric,    targets = targets,    direction = -1,    refugiaTarget = 1 )  out_sf <- CPA_Approach$Features %>%   sf::st_join(     datEx_species_bin %>%       dplyr::select(         tidyselect::starts_with(\"Cost_\")       ),     join = sf::st_equals) %>%   sf::st_join(metric, join = sf::st_equals)  targets <- CPA_Approach$Targets out_sf$Cost_None <- rep(1, 397)  usedFeatures <- out_sf %>%   sf::st_drop_geometry() %>%   dplyr::select(     -tidyselect::starts_with(\"Cost_\"),     -tidyselect::starts_with(\"metric\")   ) %>%   names()"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"run-the-climate-smart-spatial-planning","dir":"Articles","previous_headings":"Overview > Get the features","what":"Run the climate-smart spatial planning","title":"Climate-Smart Spatial Planning","text":"prioritizrsteps including climate change running non-climate-smart spatial prioritization. can look resulting plan using splnr_plot_solution().  However, also interested climate-smart selected planning units solution actually . , can use kernel density plot.","code":"p1 <- prioritizr::problem(out_sf, usedFeatures, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(targets$target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_solnClim <- prioritizr::solve.ConservationProblem(p1) (ggSoln <- splnr_plot_solution(dat_solnClim) +    splnr_gg_add(      Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) (ggClimDens <- splnr_plot_climKernelDensity(   soln = list(dat_solnClim),   names = c(\"Input 1\"), type = \"Normal\",   legendTitle = \"Climate velocity (add unit)\",   xAxisLab = \"Climate velocity\" ))"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"percentile-approach","dir":"Articles","previous_headings":"Overview > Alternative Approaches","what":"Percentile Approach","title":"Climate-Smart Spatial Planning","text":"now add information required perform spatial planning, cost, extract names used features run prioritisation. can look resulting plan using splnr_plot_solution().  However, also interested climate-smart selected planning units solution actually . , can use kernel density plot","code":"targets <- datEx_species_bin %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 30)  Percentile_Approach <- splnr_climate_percentileApproach(   features = datEx_species_bin,   metric = metric,    targets = targets,    direction = -1,    percentile = 35 ) #> [1] \"Lower values mean more climate-smart areas.\"  out_sf <- Percentile_Approach$Features %>%   sf::st_join(     datEx_species_bin %>%       dplyr::select(         tidyselect::starts_with(\"Cost_\")       ),     join = sf::st_equals   ) %>%   sf::st_join(metric, join = sf::st_equals)  targets <- Percentile_Approach$Targets out_sf$Cost_None <- rep(1, 397)  usedFeatures <- out_sf %>%   sf::st_drop_geometry() %>%   dplyr::select(     -tidyselect::starts_with(\"Cost_\"),     -tidyselect::starts_with(\"metric\")   ) %>%   names()  p2 <- prioritizr::problem(out_sf, usedFeatures, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(targets$target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_solnClimPercentile <- prioritizr::solve.ConservationProblem(p2,                                                                 force = TRUE ) (ggSoln <- splnr_plot_solution(dat_solnClimPercentile) +    splnr_gg_add(      Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) (ggClimDens <- splnr_plot_climKernelDensity(   soln = list(dat_solnClimPercentile),   names = c(\"Input 1\"), type = \"Normal\",   legendTitle = \"Climate velocity (add unit)\",   xAxisLab = \"Climate velocity\" ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/ClimateSmart.html","id":"feature-approach","dir":"Articles","previous_headings":"Overview > Alternative Approaches","what":"Feature Approach","title":"Climate-Smart Spatial Planning","text":"now add information required perform spatial planning, cost, extract names used features run prioritisation.  However, also interested climate-smart selected planning units solution actually . , can use kernel density plot","code":"targets <- datEx_species_bin %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)  Feature_Approach <- splnr_climate_featureApproach(   features = datEx_species_bin,   metric = metric,    targets = targets,    direction = 1 ) #> [1] \"Higher values mean more climate-smart areas.\"  out_sf <- Feature_Approach$Features %>%   sf::st_join(     datEx_species_bin %>%       dplyr::select(         tidyselect::starts_with(\"Cost_\")       ),     join = sf::st_equals) %>%   sf::st_join(metric, join = sf::st_equals)  targets <- Feature_Approach$Targets out_sf$Cost_None <- rep(1, 397)  usedFeatures <- out_sf %>%   sf::st_drop_geometry() %>%   dplyr::select(     -tidyselect::starts_with(\"Cost_\"),     -tidyselect::starts_with(\"metric\")   ) %>%   names()  p3 <- prioritizr::problem(out_sf, usedFeatures, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(targets$target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_solnClimFeature <- prioritizr::solve.ConservationProblem(p3) (ggSoln <- splnr_plot_solution(dat_solnClimFeature) +    splnr_gg_add(      Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) (ggClimDens <- splnr_plot_climKernelDensity(   soln = list(dat_solnClimFeature),   names = c(\"Input 1\"), type = \"Normal\",   legendTitle = \"Climate velocity (add unit)\",   xAxisLab = \"Climate velocity\" ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"global-fishing-watch-r-package-gfwr","dir":"Articles","previous_headings":"","what":"Global Fishing Watch R Package (gfwr)","title":"Global Fishing Watch","text":"gfwr package provides convenient functions pull GFW data directly R usable formats. contains three main functions, including : get_vessel_info(), get_event() get_raster(). two first devoted retrieving information features one ore several specific vessels. last particular interest us allows us gather information global fishing watch raster fishing effort (details function appropriate section). mainly use splnr_get_gfw function created enable data retrieved processed variety ways, described . time spent fishing computed using Automatic Identification System (AIS) data, transmitted industrial fishing vessels. AIS data provides information location, speed, direction vessel, can used identify vessel actively fishing.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"ais-caveats-and-limitations","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr)","what":"AIS Caveats and limitations","title":"Global Fishing Watch","text":"AIS coverage vessels several limitations : 1. number vessels captured (AIS provides approximately 70’000 2.8 million identified fishing vessels). 2. size vessels (52-85% vessels larger 24 meters 1% vessels 12 meters).Good know: IMO mandates AIS vessels larger 36 meters. 3. AIS interference areas high vessel density. 4. terrestrial satellites receive messages near shore.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"installation","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr)","what":"Installation","title":"Global Fishing Watch","text":"","code":"remotes::install_github(\"GlobalFishingWatch/gfwr\") library(gfwr) library(spatialplanr)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"api","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr)","what":"API","title":"Global Fishing Watch","text":"access GFW APIs, need : 1. register GFW account . 2. Request API key . token, add .Renviron file (executing chunk ), writing (GFW_TOKEN = “YOUR_TOKEN”) file. (asked restart R changes take effect.) save key object used gfwr functions.","code":"usethis::edit_r_environ() key <- gfwr::gfw_auth()"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"fishing-effort-visualization","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr)","what":"Fishing effort visualization","title":"Global Fishing Watch","text":"region_id necessary use get_raster function. get_raster function gets raster fishing effort API converts response data frame contains occurrences vessel grid cell (data binned grid cells different resolution), Vessel IDs, Flag, Geartype Apparent fishing Hours basically amount fishing hours vessel per grid cell (geometry). Data can provided : - DAILY, MONTHLY YEARLY temporal resolutions.  - LOW (0.1 deg) HIGH (0.01 deg) spatial resolutions.  - VESSEL_ID, FLAG, GEARTYPE, FLAGANDGEARTYPE. (can remove option message = FALSE see columns types.)","code":"region_id <- gfwr::get_region_id(region_name = \"Australia\",                                   region_source = \"EEZ\",                                  key = gfwr::gfw_auth())$id gfwr::get_raster(   spatial_resolution = \"LOW\",   temporal_resolution = \"MONTHLY\",   group_by = \"FLAGANDGEARTYPE\",   start_date = \"2022-01-01\",   end_date = \"2023-01-01\",   region = region_id,   region_source = \"EEZ\",   key = gfwr::gfw_auth() )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"get_raster-caveats-and-limitations-","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Fishing effort visualization","what":"get_raster caveats and limitations.","title":"Global Fishing Watch","text":"Date range limited 1-year. Nevertheless, modifications, can get round problems splnr_get_gfw.","code":"data_sf_combined <- splnr_get_gfw(region = \"Australia\",                                    start_date = \"2019-01-01\",                                   end_date =  \"2023-12-31\",                                   temp_res = \"YEARLY\",                                   spat_res = \"LOW\",                                   compress = FALSE)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"visualization","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr)","what":"Visualization","title":"Global Fishing Watch","text":"display data, load :  - coastline rnaturalearth package modify get sf object, constrain boundaries given data.  - EEZ Polygons oceandatr package","code":"# Check and modify if necessary the spatial reference of data_sf_combined data_sf_combined <- sf::st_set_crs(data_sf_combined,                                     sf::st_crs(rnaturalearth::ne_coastline(scale = \"large\")))  coast_clipped <- rnaturalearth::ne_coastline(scale = \"large\") %>%   sf::st_as_sf() %>%   sf::st_intersection(sf::st_as_sfc(sf::st_bbox(data_sf_combined)))  # Load EEZ polygons eezs <- spatialgridr::get_boundary(name = \"Australia\", type = \"eez\", country_type = \"country\") %>%   sf::st_transform(crs = sf::st_crs(data_sf_combined)) %>%   sf::st_make_valid() %>%   sf::st_intersection(sf::st_as_sfc(sf::st_bbox(data_sf_combined)))"},{"path":[]},{"path":[]},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"year-on-year-comparison","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Here we display the Fishing Effort in Australia from 2019 to 2023.","what":"Year-on-year comparison","title":"Global Fishing Watch","text":"may need compare different timeframes, seasons, see patterns. Note : vessels adopted AIS (mainly economically developed countries) since deployment technologies, rise activities must seen context increase necessarily intense fishing activity.","code":"# We need to change the temporal range according to our need group by it to display the total fishing hours. <br> data_sf_combined <- splnr_get_gfw(region = \"Australia\",                                    start_date = \"2019-01-01\",                                    end_date = \"2023-12-31\",                                    temp_res = \"MONTHLY\",                                    key = gfwr::gfw_auth()) %>%   dplyr::group_by(Year, Month) %>%   dplyr::summarize(Total_Fishing_Hours = sum(ApparentFishingHrs))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"fishing-gear-type","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Here we display the Fishing Effort in Australia from 2019 to 2023.","what":"Fishing gear type","title":"Global Fishing Watch","text":"display Vessel activity ‘Micronesia’ 2020 according fishing gear type.","code":"data_sf_combined <- splnr_get_gfw(region = \"Micronesia\",                                    start_date = \"2019-12-31\",                                    end_date = \"2021-01-01\",                                    temp_res = \"MONTHLY\")"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"flags","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Here we display the Fishing Effort in Australia from 2019 to 2023.","what":"Flags","title":"Global Fishing Watch","text":"display Vessel activity Papua New Guinea according Vessels flags.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"supplementary-materials-","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Here we display the Fishing Effort in Australia from 2019 to 2023.","what":"Supplementary materials.","title":"Global Fishing Watch","text":"fishing detection model trained AIS data 503 vessels identified fishing activity 90% accuracy, means can identify fishing non-fishing activity high accuracy. details AIS operation limitations .","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/GlobalFishingWatch.html","id":"hierarchy-of-vessels-gear-types","dir":"Articles","previous_headings":"Global Fishing Watch R Package (gfwr) > Here we display the Fishing Effort in Australia from 2019 to 2023.","what":"Hierarchy of vessels gear types :","title":"Global Fishing Watch","text":"Source : https://globalfishingwatch.org/datasets--code-vessel-identity/","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"Spatial Planning With Zones","text":"code written simplify process running prioritizr analysis given region. still work progress feel free submit pull requests new features code improvements. workflow shown based prioritizr introduction zones.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"set-user-parameters","dir":"Articles","previous_headings":"Overview","what":"Set user parameters","title":"Spatial Planning With Zones","text":"Set diameter planning units. units CRS (usually metres degrees). Choose CRS analysis. use Mollweide","code":"Region <- \"Coral Sea\" # \"Australia\" Type <- \"Oceans\" # \"EEZ\" PU_size <- 107460 # m cCRS <- \"ESRI:54009\""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"analysis-region","dir":"Articles","previous_headings":"Overview","what":"Analysis Region","title":"Spatial Planning With Zones","text":"Start analysis defining region setting planning units. Get boundary chosen region.","code":"Bndry <- splnr_get_boundary(Limits = Region, Type = Type, cCRS = cCRS) #> Reading layer `ne_10m_geography_marine_polys' from data source  #>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/Rtmpu338hK/ne_10m_geography_marine_polys.shp'  #>   using driver `ESRI Shapefile' #> Simple feature collection with 306 features and 37 fields #> Geometry type: MULTIPOLYGON #> Dimension:     XY #> Bounding box:  xmin: -180 ymin: -85.19206 xmax: 179.9999 ymax: 90 #> Geodetic CRS:  WGS 84  landmass <- rnaturalearth::ne_countries(   scale = \"medium\",   returnclass = \"sf\" ) %>%   sf::st_transform(cCRS)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"create-planning-units","dir":"Articles","previous_headings":"Overview","what":"Create Planning Units","title":"Spatial Planning With Zones","text":"can also use customised ggplot theme can passed list splnr_gg_add() can used plots. example:","code":"PUs <- spatialgridr::get_grid(boundary = Bndry,                               crs = cCRS,                               output = \"sf_hex\",                               resolution = PU_size) splnr_theme <- list(   ggplot2::theme_bw(),   ggplot2::theme(     legend.position = \"right\",     legend.direction = \"vertical\",     text = ggplot2::element_text(size = 9, colour = \"black\"),     axis.text = ggplot2::element_text(size = 9, colour = \"black\"),     plot.title = ggplot2::element_text(size = 9),     axis.title = ggplot2::element_blank()   ) )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"get-the-features","dir":"Articles","previous_headings":"Overview","what":"Get the features","title":"Spatial Planning With Zones","text":"example, use small subset charismatic megafauna species Coral Sea inform conservation plan. filtered Aquamaps (Aquamaps.org) species distribution models study area following species: species chosen based importance region represent example visualization purposes. Note: structure tribbleabove required downstream plotting. Common denotes common name species, Scientific scientific name format used Aquamaps, Category category species belongs Class represents importance species conservation plan.","code":"Dict <- tibble::tribble(   ~nameCommon, ~nameVariable, ~category,    \"Green sea turtle\", \"Chelonia_mydas\", \"Reptiles\",    \"Loggerhead sea turtle\", \"Caretta_caretta\", \"Reptiles\",    \"Hawksbill sea turtle\", \"Eretmochelys_imbricata\", \"Reptiles\",    \"Olive ridley sea turtle\", \"Lepidochelys_olivacea\", \"Reptiles\",    \"Saltwater crocodile\", \"Crocodylus_porosus\", \"Reptiles\",    \"Humpback whale\", \"Megaptera_novaeangliae\", \"Mammals\",    \"Common Minke whale\", \"Balaenoptera_acutorostrata\",   \"Mammals\",    \"Dugong\", \"Dugong_dugon\", \"Mammals\",    \"Grey nurse shark\", \"Carcharias_taurus\", \"Sharks and rays\",    \"Tiger shark\", \"Galeocerdo_cuvier\", \"Sharks and rays\",    \"Great hammerhead shark\", \"Sphyrna_mokarran\",   \"Sharks and rays\",    \"Giant oceanic manta ray\", \"Mobula_birostris\", \"Sharks and rays\",    \"Reef manta ray\", \"Mobula_alfredi\", \"Sharks and rays\",    \"Whitetip reef shark\", \"Triaenodon_obesus\", \"Sharks and rays\",   \"Red-footed booby\", \"Sula_sula\", \"Birds\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"convert-the-probabilities-to-binary-data-and-feature-names","dir":"Articles","previous_headings":"Overview > Get the features","what":"Convert the probabilities to binary data and feature names","title":"Spatial Planning With Zones","text":"","code":"datEx_species_bin <- spDataFiltered %>%   splnr_apply_cutoffs(Cutoffs = 0.5)  col_name <- spDataFiltered %>%   sf::st_drop_geometry() %>%   colnames()"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"spatial-planning-including-zones","dir":"Articles","previous_headings":"Overview > Get the features","what":"Spatial planning including zones","title":"Spatial Planning With Zones","text":"far, steps exactly spatial plan include zones. direct comparison, first run spatial plan include zoning. , define targets features (: 30% features) create conservation problem include area-based cost prioritisation. solve problem plot solution.  can also look well set target met. now look spatial plan needs extended include multiple management zones using zones().","code":"target <- rep(0.3, nrow(Dict))  p1 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(Cost1 = rep(1, 397)),   col_name,   \"Cost1\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE) s1 <- p1 %>%   prioritizr::solve.ConservationProblem()  (ggSoln <- splnr_plot_solution(s1) +     splnr_gg_add(PUs = PUs, Bndry = Bndry, overlay = landmass, cropOverlay = PUs, ggtheme = splnr_theme)) s1T <- s1 %>%   dplyr::select(tidyselect::starts_with(c(\"solution\"))) %>%   sf::st_drop_geometry() %>%   tibble::as_tibble()  r1 <- prioritizr::eval_feature_representation_summary(p1, s1T) print(r1) #> # A tibble: 15 × 5 #>    summary feature                    total_amount absolute_held relative_held #>    <chr>   <chr>                             <dbl>         <dbl>         <dbl> #>  1 overall Chelonia_mydas                       22            10         0.455 #>  2 overall Caretta_caretta                      22            10         0.455 #>  3 overall Eretmochelys_imbricata               24            10         0.417 #>  4 overall Lepidochelys_olivacea                22            10         0.455 #>  5 overall Crocodylus_porosus                   21             9         0.429 #>  6 overall Megaptera_novaeangliae              388           120         0.309 #>  7 overall Balaenoptera_acutorostrata          238            74         0.311 #>  8 overall Dugong_dugon                         13             5         0.385 #>  9 overall Carcharias_taurus                    22            10         0.455 #> 10 overall Galeocerdo_cuvier                    36            14         0.389 #> 11 overall Sphyrna_mokarran                    397           123         0.310 #> 12 overall Mobula_birostris                     20             8         0.4   #> 13 overall Mobula_alfredi                       20             8         0.4   #> 14 overall Triaenodon_obesus                    25            10         0.4   #> 15 overall Sula_sula                            13             5         0.385"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"different-cost-layers","dir":"Articles","previous_headings":"Overview > Get the features","what":"Different cost layers","title":"Spatial Planning With Zones","text":"first assume zones interest set features, separate cost layers. , need set targets zones, case 20% features first zone 5% features second zone. create zones object specify number zones features zone. , define two zones features. zones need specified cost targets. use one area-based cost one cost layer uses random numbers, pre-defined targets pass zonesobject problem formulation solving conservation problem. solution can plotted using function splnr_plot_solution() argument zones set TRUE.  can see now planning units selected, planning units either selected zone 1 zone 2.","code":"target2 <- matrix(NA, ncol = 2, nrow = nrow(Dict)) target2[, 1] <- 0.2 target2[, 2] <- 0.05 z2 <- prioritizr::zones(\"zone 1\" = col_name, \"zone 2\" = col_name) p2 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397), # when giving sf input, we need as many cost columns as we have zones     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s2 <- p2 %>%   prioritizr::solve.ConservationProblem() (gg_s2 <- splnr_plot_solution(   s2,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"different-features","dir":"Articles","previous_headings":"Overview > Get the features","what":"Different features","title":"Spatial Planning With Zones","text":"using sf objects zones(), input feature names zones() need length contain features. means zones features, interest specific zone, target set 0. example, want separate example data zone reptiles another zone containing taxa reptiles, can specify following targets: sets target reptiles first zone 30% rest 0%. second zone, targets non-reptiles 10% reptiles 0% interest zone. Target data given matrix working zones, transform data frame matrix end. define conservation problem way solve . can also look well targets met zone (combined). can see 15 features listed (number) overall summary, summary zone 1 summary zone 2. looking relative_held column tibble, observe summary zone 1 (row 16 onwards), features >30% targets met, whereas others (feature 6 7) low percentage suitable habitat within selected planning units. can extract common names two features: marine mammals thus target 0% zone 1 reptile-specific zone. percentage selected suitable habitat 0% despite target 0 proportion suitable habitat mammals selected incidentally selecting planning units zone meeting targets reptiles. applies zone 2. can also plot final solution :","code":"targets2b <- Dict %>%   dplyr::mutate(     targetZ1 = dplyr::if_else(category == \"Reptiles\", 30 / 100, 0),     targetZ2 = dplyr::if_else(category != \"Reptiles\", 10 / 100, 0)   ) %>%   dplyr::select(\"targetZ1\", \"targetZ2\") %>%   as.matrix() # NOTE: when using sf input, we need as many cost columns as we have zones p2b <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397),     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(targets2b) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s2b <- p2b %>%   prioritizr::solve.ConservationProblem() r2b <- s2b %>%   dplyr::select(tidyselect::starts_with(c(\"solution\"))) %>%   sf::st_drop_geometry() %>%   tibble::as_tibble() %>%   prioritizr::eval_feature_representation_summary(p2b, .) print(r2b, n = 45) #> # A tibble: 45 × 5 #>    summary feature total_amount absolute_held relative_held #>    <chr>   <chr>          <dbl>         <dbl>         <dbl> #>  1 overall 1                 44            11       0.25    #>  2 overall 2                 44            11       0.25    #>  3 overall 3                 48            11       0.229   #>  4 overall 4                 44            11       0.25    #>  5 overall 5                 42            11       0.262   #>  6 overall 6                776            43       0.0554  #>  7 overall 7                476            26       0.0546  #>  8 overall 8                 26             7       0.269   #>  9 overall 9                 44            11       0.25    #> 10 overall 10                72            13       0.181   #> 11 overall 11               794            48       0.0605  #> 12 overall 12                40            11       0.275   #> 13 overall 13                40            11       0.275   #> 14 overall 14                50            12       0.24    #> 15 overall 15                26             8       0.308   #> 16 zone 1  1                 22             8       0.364   #> 17 zone 1  2                 22             8       0.364   #> 18 zone 1  3                 24             8       0.333   #> 19 zone 1  4                 22             8       0.364   #> 20 zone 1  5                 21             8       0.381   #> 21 zone 1  6                388             4       0.0103  #> 22 zone 1  7                238             2       0.00840 #> 23 zone 1  8                 13             5       0.385   #> 24 zone 1  9                 22             8       0.364   #> 25 zone 1  10                36             8       0.222   #> 26 zone 1  11               397             8       0.0202  #> 27 zone 1  12                20             8       0.4     #> 28 zone 1  13                20             8       0.4     #> 29 zone 1  14                25             8       0.32    #> 30 zone 1  15                13             6       0.462   #> 31 zone 2  1                 22             3       0.136   #> 32 zone 2  2                 22             3       0.136   #> 33 zone 2  3                 24             3       0.125   #> 34 zone 2  4                 22             3       0.136   #> 35 zone 2  5                 21             3       0.143   #> 36 zone 2  6                388            39       0.101   #> 37 zone 2  7                238            24       0.101   #> 38 zone 2  8                 13             2       0.154   #> 39 zone 2  9                 22             3       0.136   #> 40 zone 2  10                36             5       0.139   #> 41 zone 2  11               397            40       0.101   #> 42 zone 2  12                20             3       0.15    #> 43 zone 2  13                20             3       0.15    #> 44 zone 2  14                25             4       0.16    #> 45 zone 2  15                13             2       0.154 Dict[[1]][6] #> [1] \"Humpback whale\" Dict[[1]][7] #> [1] \"Common Minke whale\" (gg_s2b <- splnr_plot_solution(   s2b,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"boundary-penalty","dir":"Articles","previous_headings":"Overview > Get the features","what":"Boundary penalty","title":"Spatial Planning With Zones","text":"Similar “normal” priritisations, zones also allows including boundary penalty. several options can done within zones zones.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"within-the-same-zone","dir":"Articles","previous_headings":"Overview > Get the features > Boundary penalty","what":"Within the same zone","title":"Spatial Planning With Zones","text":"zeros matrix denote penalty zones, whereas ones introduce boundary penalty define conservation problem. , introduce penalties within zone 1 zone 2 respectively. add_boundary_penalties() set penalty 0.5 zones defined zm1. purpose example, also set 10 second time limit prioritisation. results show less fragmentation previous solution without penalties:  boundary penalty can also introduced one zone:","code":"zm1 <- diag(2) print(zm1) #>      [,1] [,2] #> [1,]    1    0 #> [2,]    0    1 p3 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397), # when giving sf input, we need as many cost columns as we have zones     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_boundary_penalties(0.5, zone = zm1) %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(time_limit = 10, verbose = FALSE)  s3 <- p3 %>%   prioritizr::solve.ConservationProblem() (gg_s3 <- splnr_plot_solution(   s3,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   )) zm2 <- zm1 zm2[2, 2] <- 0  # NOTE: When using sf input, we need as many cost columns as we have zones p4 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397),     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_boundary_penalties(0.5, zone = zm2) %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(time_limit = 10, verbose = FALSE)  s4 <- p4 %>%   prioritizr::solve.ConservationProblem()  (gg_s4 <- splnr_plot_solution(   s4,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"across-zones","dir":"Articles","previous_headings":"Overview > Get the features > Boundary penalty","what":"Across zones","title":"Spatial Planning With Zones","text":"Similarly, penalties can applied zones specified problem.","code":"zm3 <- matrix(1, ncol = 2, nrow = 2) print(zm3) #>      [,1] [,2] #> [1,]    1    1 #> [2,]    1    1 p5 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397), # when giving sf input, we need as many cost columns as we have zones     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_boundary_penalties(0.5, zone = zm3) %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(time_limit = 10, verbose = FALSE)  s5 <- p5 %>%   prioritizr::solve.ConservationProblem()  (gg_s5 <- splnr_plot_solution(   s5,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"adding-constraints","dir":"Articles","previous_headings":"Overview > Get the features","what":"Adding constraints","title":"Spatial Planning With Zones","text":"Another addition often used conservation planning constraints. often lock lock areas interest various reasons. example, lock already existing MPAs one zones. using zones constraints, use prioritizr function add_manual_locked_constraints() requires input specific format, first prepare MPA data. need specify zone constraint applied , give information planning unit identifier, rename column interest “status” filter planning units locked . results can visualized :","code":"mpas <- MPAsCoralSea %>%   dplyr::mutate(zone = \"zone 1\") %>%   dplyr::rename(status = wdpa) %>%   tibble::rowid_to_column(\"pu\") %>%    sf::st_drop_geometry() %>%   tibble::tibble() %>%   dplyr::filter(status == 1) # NOTE: When using sf input, we need as many cost columns as we have zones p6 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397),     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_manual_locked_constraints(mpas) %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(time_limit = 10, verbose = FALSE)  s6 <- p6 %>%   prioritizr::solve.ConservationProblem() (gg_s6 <- splnr_plot_solution(   s6,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, lockIn = MPAsCoralSea,     nameLockIn = \"wdpa\", typeLockIn = \"Full\",     colorLockIn = \"lightgrey\", alphaLockIn = 0.2, overlay = landmass,     labelLockIn = \"Current MPAs\", cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"objective-functions","dir":"Articles","previous_headings":"Overview > Get the features","what":"Objective functions","title":"Spatial Planning With Zones","text":"far used minimum set objective function meet conservation targets whilst minimizing cost. However, objective function available prioritizr. example maximising mangrove ecosystem services, employed minimum shortfall objective function instead (Dabalà et al 2022). objective function, allocate budget exceeded (example area >30%) whilst still trying minimise cost meeting targets - targets might met (shortfall). Zones also works objective functions minimum set objective function. apply add_min_shortfall_objective() provide separate budgets two zones (8 0.3). can visualize output solving conservation problem.","code":"# NOTE: When using sf input, we need as many cost columns as we have zones p7 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(     Cost1 = rep(1, 397),     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_shortfall_objective(c(8, 0.3)) %>%   prioritizr::add_relative_targets(target2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(time_limit = 10, verbose = FALSE) s7 <- p7 %>%   prioritizr::solve.ConservationProblem()  (gg_s7 <- splnr_plot_solution(   s7,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"alternative-linear-constraints","dir":"Articles","previous_headings":"Overview > Get the features","what":"Alternative: linear constraints","title":"Spatial Planning With Zones","text":"Sometimes spatial plan might needed requires minimising several costs , binary output (inside protected area/outside protected area) sufficient. case, using linear constraints instead zones might simpler time-efficient way forward. Linear constraints make sure planning units selected area meet criteria given constraint. example, using area-based cost (lowest number planning units meet target), might also simultaneously want minimise cost fisheries keep certain threshold. Inversely, might want minimise cost fisheries also select 30% area. example, fill first define targets random cost layer values ranging 0 1. define solve conservation problem: Based problem definition, want meet targets biodiversity features whilst selecting lowest number planning units possible. However, solution also depends threshold linear constraint specified add_linear_constraints()problem. Specifically, planning units selected solution can exceed 10% total cost planning units costRandom$CostR. can visualise solution :  NOTE: can also use multiple linear constraints plan, however, might require normalization input data constraints comparable units, careful tuning thresholds, prioritizr still able solve problem.","code":"target8 <- rep(0.3, nrow(Dict))  set.seed <- 10 # Add seed so the problem below solves each time  costRandom <- datEx_species_bin %>%   dplyr::mutate(CostR = runif(n = dim(.)[[1]])) %>%   dplyr::select(\"CostR\") p8 <- prioritizr::problem(   datEx_species_bin %>% dplyr::mutate(Cost1 = rep(1, 397)),   col_name,   \"Cost1\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(target8) %>%   prioritizr::add_linear_constraints(sum(costRandom$CostR) * 0.1,                                      sense = \"<=\", costRandom$CostR   ) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s8 <- p8 %>%   prioritizr::solve.ConservationProblem() (gg_s8 <- splnr_plot_solution(s8) +    splnr_gg_add(PUs = PUs, Bndry = Bndry, overlay = landmass, cropOverlay = PUs, ggtheme = splnr_theme))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"common-targets-across-zones","dir":"Articles","previous_headings":"Overview > Get the features","what":"Common targets across zones","title":"Spatial Planning With Zones","text":"Sometimes might required meet (common) conservation target across multiple zones, several zones contribute reaching target. , need define target across zones (: 30% features across zones): need bring data specific format requires us individual column feature specific zone, spp1 two zones (zone1 zone2), two separate columns input data: spp1_zone1 spp1_zone2. species names zone names exactly specified zones() object separated _. also extract new feature names create zones object, joining two newly created data frames file used prioriztisation. can see defined (random) cost layers cost layer zone2 three times costly zone1. setting solving conservation problem, can look resulting solution well targets met. overall summary shows every feature’s suitable habitat represented least 30% combined target set. However, can see features zone1 lot frequently selected zone2 zone2 three times costly.  plot also reflects observation PUs frequently selected zone1. wanted constrain , zone1 less often selected zone2 often?","code":"targetAcross <- dplyr::tibble(   feature = col_name,   zone = list(c(\"zone1\", \"zone2\"))[rep(1, length(col_name))],   target = rep(0.3, length(col_name)),   type = rep(\"relative\", length(col_name)) ) datSpecZone1 <- datEx_species_bin %>%   dplyr::rename_at(dplyr::vars(-geometry), ~ paste0(.x, \"_zone1\"))  featuresZone1 <- datSpecZone1 %>%   sf::st_drop_geometry() %>%   colnames()  datSpecZone2 <- datEx_species_bin %>%   dplyr::rename_at(dplyr::vars(-geometry), ~ paste0(.x, \"_zone2\"))  featuresZone2 <- datSpecZone2 %>%   sf::st_drop_geometry() %>%   colnames() z10 <- prioritizr::zones(   featuresZone1,   featuresZone2,   zone_names = c(\"zone1\", \"zone2\"),   feature_names = col_name )  out_sf <- datSpecZone1 %>%   sf::st_join(datSpecZone2, join = sf::st_equals) %>%   dplyr::mutate(     Cost1 = runif(n = dim(.)[[1]]) * 100,     Cost2 = runif(n = dim(.)[[1]]) * 300   ) p10 <- prioritizr::problem(out_sf,                            z10,                            cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_manual_targets(targetAcross) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s10 <- p10 %>%   prioritizr::solve.ConservationProblem() s10F <- s10 %>%   dplyr::select(tidyselect::starts_with(c(\"solution\"))) %>%   sf::st_drop_geometry() %>%   tibble::as_tibble()  r10 <- prioritizr::eval_feature_representation_summary(p10, s10F) print(r10) #> # A tibble: 45 × 5 #>    summary feature                    total_amount absolute_held relative_held #>    <chr>   <chr>                             <dbl>         <dbl>         <dbl> #>  1 overall Chelonia_mydas                       44            14         0.318 #>  2 overall Caretta_caretta                      44            14         0.318 #>  3 overall Eretmochelys_imbricata               48            15         0.312 #>  4 overall Lepidochelys_olivacea                44            14         0.318 #>  5 overall Crocodylus_porosus                   42            14         0.333 #>  6 overall Megaptera_novaeangliae              776           234         0.302 #>  7 overall Balaenoptera_acutorostrata          476           146         0.307 #>  8 overall Dugong_dugon                         26            10         0.385 #>  9 overall Carcharias_taurus                    44            14         0.318 #> 10 overall Galeocerdo_cuvier                    72            25         0.347 #> # ℹ 35 more rows (gg_s10 <- splnr_plot_solution(s10,                                zones = TRUE,                                colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),                                legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"targets-across-zones-with-linear-constraints","dir":"Articles","previous_headings":"Overview > Get the features","what":"Targets across zones with linear constraints","title":"Spatial Planning With Zones","text":"can include linear constraints zone1 , area exceed 30% whole area. need create matrix contains data constraint want include. Although want put linear constraint zone1, prioritizr still requires matrix many columns zones. Thus, set area cost 1 zone1 want constraint 0 zone2 want introduce linear constraint. define conservation problem add linear constraint 30% area. selected planning units now equally distributed across zones, also observable plot:  However, also expect cost spatial plan higher previous one.","code":"CostArea <- out_sf %>%   dplyr::mutate(     areaCostZone1 = rep(1, 397),     areaCostZone2 = rep(0, 397)   ) %>%   sf::st_drop_geometry() %>%   dplyr::select(\"areaCostZone1\", \"areaCostZone2\") %>%   as.matrix() p11 <- prioritizr::problem(out_sf,                            z10,                            cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_linear_constraints(sum(CostArea[, 1]) * 0.3,                                      sense = \"<=\", CostArea   ) %>%   prioritizr::add_manual_targets(targetAcross) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s11 <- p11 %>%   prioritizr::solve.ConservationProblem() s11F <- s11 %>%   dplyr::select(tidyselect::starts_with(c(\"solution\"))) %>%   sf::st_drop_geometry() %>%   tibble::as_tibble()  r11 <- prioritizr::eval_feature_representation_summary(p11, s11F) print(r11) #> # A tibble: 45 × 5 #>    summary feature                    total_amount absolute_held relative_held #>    <chr>   <chr>                             <dbl>         <dbl>         <dbl> #>  1 overall Chelonia_mydas                       44            14         0.318 #>  2 overall Caretta_caretta                      44            14         0.318 #>  3 overall Eretmochelys_imbricata               48            15         0.312 #>  4 overall Lepidochelys_olivacea                44            14         0.318 #>  5 overall Crocodylus_porosus                   42            14         0.333 #>  6 overall Megaptera_novaeangliae              776           234         0.302 #>  7 overall Balaenoptera_acutorostrata          476           144         0.303 #>  8 overall Dugong_dugon                         26             9         0.346 #>  9 overall Carcharias_taurus                    44            14         0.318 #> 10 overall Galeocerdo_cuvier                    72            24         0.333 #> # ℹ 35 more rows (gg_s11 <- splnr_plot_solution(   s11,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"targets-across-some-but-not-all-zones","dir":"Articles","previous_headings":"Overview > Get the features","what":"Targets across some (but not all) zones","title":"Spatial Planning With Zones","text":"example, want target 30% suitable reptile habitat zone 1 zone 2. Additionally, set target 20% zone 2 marine mammals target 5% sharks rays zone 3. create zones object three different zones: create joint sf object zones respective costs.","code":"targetAcrossSome <- Dict %>%   dplyr::mutate(     target = dplyr::case_when(       category == \"Reptiles\" ~ 30 / 100,       category == \"Mammals\" ~ 10 / 100,       category == \"Sharks and rays\" ~ 5 / 100,       TRUE ~ 0     ),     zone = dplyr::case_when(       category == \"Reptiles\" ~ list(c(\"zone1\", \"zone2\")),       category == \"Mammals\" ~ list(\"zone2\"),       category == \"Sharks and rays\" ~ list(\"zone3\"),       TRUE ~ list(c(\"zone1\", \"zone2\", \"zone3\"))     ),     type = rep(\"relative\", length(col_name))   ) %>%   dplyr::rename(feature = \"nameVariable\") %>%   dplyr::select(-\"category\", -\"nameCommon\") datSpecZone1 <- datEx_species_bin %>%   dplyr::rename_at(dplyr::vars(-geometry), ~ paste0(.x, \"_zone1\"))  featuresZone1 <- datSpecZone1 %>%   sf::st_drop_geometry() %>%   colnames()  datSpecZone2 <- datEx_species_bin %>%   dplyr::rename_at(dplyr::vars(-geometry), ~ paste0(.x, \"_zone2\"))  featuresZone2 <- datSpecZone2 %>%   sf::st_drop_geometry() %>%   colnames()  datSpecZone3 <- datEx_species_bin %>%   dplyr::rename_at(dplyr::vars(-geometry), ~ paste0(.x, \"_zone3\"))  featuresZone3 <- datSpecZone3 %>%   sf::st_drop_geometry() %>%   colnames()  z12 <- prioritizr::zones(   featuresZone1,   featuresZone2,   featuresZone3,   zone_names = c(\"zone1\", \"zone2\", \"zone3\"),   feature_names = col_name ) # NOTE: When using sf input, we need as many cost columns as we have zones out_sf <- datSpecZone1 %>%   sf::st_join(datSpecZone2, join = sf::st_equals) %>%   sf::st_join(datSpecZone3, join = sf::st_equals) %>%   dplyr::mutate(geometry = datEx_species_bin$geometry) %>%   sf::st_as_sf() %>%   dplyr::mutate(     Cost1 = runif(n = dim(.)[[1]]) * 100,     Cost2 = runif(n = dim(.)[[1]]) * 300,     Cost3 = runif(n = dim(.)[[1]]) * 200   ) p12 <- prioritizr::problem(out_sf,                            z12,                            cost_column = c(\"Cost1\", \"Cost2\", \"Cost3\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_manual_targets(targetAcrossSome) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s12 <- p12 %>%   prioritizr::solve.ConservationProblem() s12F <- s12 %>%   dplyr::select(tidyselect::starts_with(c(\"solution\"))) %>%   sf::st_drop_geometry() %>%   tibble::as_tibble()  r12 <- prioritizr::eval_feature_representation_summary(p12, s12F) print(r12) #> # A tibble: 60 × 5 #>    summary feature                    total_amount absolute_held relative_held #>    <chr>   <chr>                             <dbl>         <dbl>         <dbl> #>  1 overall Chelonia_mydas                       66            16        0.242  #>  2 overall Caretta_caretta                      66            16        0.242  #>  3 overall Eretmochelys_imbricata               72            17        0.236  #>  4 overall Lepidochelys_olivacea                66            16        0.242  #>  5 overall Crocodylus_porosus                   63            16        0.254  #>  6 overall Megaptera_novaeangliae             1164            64        0.0550 #>  7 overall Balaenoptera_acutorostrata          714            44        0.0616 #>  8 overall Dugong_dugon                         39             8        0.205  #>  9 overall Carcharias_taurus                    66            16        0.242  #> 10 overall Galeocerdo_cuvier                   108            19        0.176  #> # ℹ 50 more rows (gg_s12 <- splnr_plot_solution(   s12,   zones = TRUE,   colorVals = c(\"#c6dbef\", \"#3182bd\", \"navyblue\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\", \"Zone3\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"short-term","dir":"Articles","previous_headings":"Overview > Get the features > Next steps","what":"Short-term","title":"Spatial Planning With Zones","text":"Test run time zones compared normal prioritisation Communicate zones outcomes effectively (e.g. targets, cost overlay etc.)","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/MultipleUse.html","id":"longer-term","dir":"Articles","previous_headings":"Overview > Get the features > Next steps","what":"Longer-term","title":"Spatial Planning With Zones","text":"deal overlapping zones (moment prioritizr allocates PU single zone) connect climate-smart workflow zones handle inputs benefit using different objective functions (e.g. ecosystem services vs biodiversity features) Look commonly used data sets multiple use approaches think zone-specific costs, constraints, targets etc. Define (Waitt’s) understanding multiple-use want implement (can differ now future) EU Horizon 2020 MUSES-project: multiple use/multi-use “joint use resources close geographic proximity either single user multiple users. umbrella term covers multitude use combinations marine realm represents radical change concept exclusive resource rights inclusive sharing resources space one users.” Bonnevie et al. 2019: “multi-use specific co-location/coexistence resources shared.” Schupp et al. 2019: distinguishes different types multi-uses (one co-location) Types multiple use MSP according Schupp et al. 2019","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"A Basic Spatial Planning Workflow","text":"code written simplify process running prioritizr analysis given region. still work progress feel free submit pull requests new features code improvements.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"set-user-parameters","dir":"Articles","previous_headings":"Overview","what":"Set user parameters","title":"A Basic Spatial Planning Workflow","text":"can set region defined splnr_get_planningUnits. can also define region square boundaries (degrees) need. Choose CRS analysis. case use Mollweide Set diameter planning units. units CRS (usually metres degrees).","code":"Region <- \"Coral Sea\" # \"Australia\" Type <- \"Oceans\" # \"EEZ\" Region <- c(xmin = 150, xmax = 160, ymin = -40, ymax = -30) cCRS <- \"ESRI:54009\" PU_size <- 107460 # m"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"analysis-region","dir":"Articles","previous_headings":"Overview","what":"Analysis Region","title":"A Basic Spatial Planning Workflow","text":"Start analysis defining region setting planning units. Get boundary chosen region. Get land boundaries remove overlap. object “landmass” represents land mass removed (inverse = FALSE)","code":"Bndry <- splnr_get_boundary(Limits = Region, Type = Type, cCRS = cCRS) #> Reading layer `ne_10m_geography_marine_polys' from data source  #>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpNdQOCt/ne_10m_geography_marine_polys.shp'  #>   using driver `ESRI Shapefile' #> Simple feature collection with 306 features and 37 fields #> Geometry type: MULTIPOLYGON #> Dimension:     XY #> Bounding box:  xmin: -180 ymin: -85.19206 xmax: 179.9999 ymax: 90 #> Geodetic CRS:  WGS 84 landmass <- rnaturalearth::ne_countries(   scale = \"medium\",   returnclass = \"sf\" ) %>%   sf::st_transform(cCRS)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"create-planning-units","dir":"Articles","previous_headings":"Overview","what":"Create Planning Units","title":"A Basic Spatial Planning Workflow","text":"can check PUs look like  want add additional properties map, example landmass boundary, can use splnr_gg_add().  can also use customised ggplpot theme can passed list splnr_gg_add() can used plots. example:","code":"PUs <- spatialgridr::get_grid(boundary = Bndry,                                crs = cCRS,                               output = \"sf_hex\",                                resolution = PU_size) (ggPU <- splnr_plot(df = PUs) +    ggplot2::theme_bw()) # Plot Planning Units (ggPU <- splnr_plot(df = PUs) +    splnr_gg_add(      Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = \"Default\"    )) splnr_theme <- list(   ggplot2::theme_bw(),   ggplot2::theme(     legend.position = \"right\",     legend.direction = \"vertical\",     text = ggplot2::element_text(size = 9, colour = \"black\"),     axis.text = ggplot2::element_text(size = 9, colour = \"black\"),     plot.title = ggplot2::element_text(size = 9),     axis.title = ggplot2::element_blank()   ) )  (ggPU <- splnr_plot(PUs) +     splnr_gg_add(       Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"get-the-features","dir":"Articles","previous_headings":"Overview","what":"Get the features","title":"A Basic Spatial Planning Workflow","text":"example, use small subset charismatic megafauna species Coral Sea inform conservation plan. filtered Aquamaps (Aquamaps.org) species distribution models study area following species: species chosen based importance region represent example visualization purposes. Note: structure tribbleabove required downstream plotting. Common denotes common name species, nameVariable scientific name format used Aquamaps, TaxGroup taxonomic grouping species belongs Category represents importance species conservation plan.","code":"Dict <- tibble::tribble(   ~nameCommon, ~nameVariable, ~category,    \"Green sea turtle\", \"Chelonia_mydas\", \"Reptiles\",    \"Loggerhead sea turtle\", \"Caretta_caretta\", \"Reptiles\",    \"Hawksbill sea turtle\", \"Eretmochelys_imbricata\", \"Reptiles\",    \"Olive ridley sea turtle\", \"Lepidochelys_olivacea\", \"Reptiles\",    \"Saltwater crocodile\", \"Crocodylus_porosus\", \"Reptiles\",    \"Humpback whale\", \"Megaptera_novaeangliae\", \"Mammals\",    \"Common Minke whale\", \"Balaenoptera_acutorostrata\", \"Mammals\",    \"Dugong\", \"Dugong_dugon\", \"Mammals\",    \"Grey nurse shark\", \"Carcharias_taurus\", \"Sharks and rays\",    \"Tiger shark\", \"Galeocerdo_cuvier\", \"Sharks and rays\",    \"Great hammerhead shark\", \"Sphyrna_mokarran\", \"Sharks and rays\",    \"Giant oceanic manta ray\", \"Mobula_birostris\", \"Sharks and rays\",    \"Reef manta ray\", \"Mobula_alfredi\", \"Sharks and rays\",    \"Whitetip reef shark\", \"Triaenodon_obesus\", \"Sharks and rays\",   \"Red-footed booby\", \"Sula_sula\", \"Birds\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"convert-the-probabilities-to-binary-data","dir":"Articles","previous_headings":"Overview > Get the features","what":"Convert the probabilities to binary data","title":"A Basic Spatial Planning Workflow","text":"can now look feature data used spatial plan individually calling splnr_plot_binFeature(), example see binary habitat suitability map Green sea turtles:  suitable habitat Green sea turtles predicted Aquamaps restricted cells close coast. now compare predicted suitable habitat Humpback whales, can see fairly ubiquitous across whole Coral Sea.  example, reason classified species either representative suitable habitat wide-ranging within study region important restricted number cells. get better idea overall distribution used features, can also plot number features suitable habitat within planning unit study region.","code":"datEx_species_bin <- spDataFiltered %>%   splnr_apply_cutoffs(Cutoffs = 0.5) (ggFeature1 <- splnr_plot(   df = datEx_species_bin,   col_names = \"Chelonia_mydas\",   plot_title = \"Chelonia mydas\",   legend_labels = c(\"Absence\", \"Presence\") ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ) ) (ggFeature <- splnr_plot(   datEx_species_bin,   \"Megaptera_novaeangliae\",   plot_title = \"Megaptera novaeangliae\" ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   )) (ggFeatNo <- splnr_plot(df = datEx_species_bin,                          col_names =  colnames(datEx_species_bin %>%                                                  sf::st_drop_geometry()),                         plot_title = \"\",                          legend_title = \"Number of features\") +    splnr_gg_add(      PUs = PUs, Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"prepare-data-for-prioritisation","dir":"Articles","previous_headings":"Overview","what":"Prepare Data for prioritisation","title":"A Basic Spatial Planning Workflow","text":"spatial prioritization also need extract names features pass prioritizr. also create sf object contains information needed prioritization.","code":"feature_names <- splnr_featureNames(datEx_species_bin) out_sf <- datEx_species_bin"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"add-cost","dir":"Articles","previous_headings":"Overview > Prepare Data for prioritisation","what":"Add Cost","title":"A Basic Spatial Planning Workflow","text":"example, use minimum set objective function, aims minimize cost whilst meeting conservation targets. add area-based cost include little area possible spatial plan whilst meeting conservation targets. , planning units assigned equal cost 1.","code":"out_sf$Cost_None <- 1 (ggCost <- splnr_plot(out_sf, col_names = \"Cost_None\",                        legend_title = \"Cost\", legend_labels = \"1\") +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"fishing-effort","dir":"Articles","previous_headings":"","what":"A Basic Spatial Planning Workflow","title":"A Basic Spatial Planning Workflow","text":"gfwr package allows us recover data fisheries across world, set parameter compress TRUE recover Apparent fishing hours per coordinates.","code":"gfw_data <- splnr_get_gfw(region = 'Australia',                            start_date = \"2022-01-01\",                            end_date = \"2022-12-31\",                            temp_res = \"yearly\",                            cCRS = cCRS,                            compress = TRUE) %>%   sf::st_interpolate_aw(PUs, extensive = TRUE)  out_sf$Apparent.Fishing.Hours <- 0 # Add column to PUs out_sf$Apparent.Fishing.Hours[as.numeric(rownames(PUs))] <-    gfw_data$Apparent.Fishing.Hours # Put corresponding data in PUs   (ggCost <- splnr_plot(out_sf, col_names = \"Apparent.Fishing.Hours\") +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"other-features-1","dir":"Articles","previous_headings":"","what":"A Basic Spatial Planning Workflow","title":"A Basic Spatial Planning Workflow","text":"Many features can taken account cost layers prioritization, provide different features oceandatrpackage.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"set-targets","dir":"Articles","previous_headings":"Overview","what":"Set Targets","title":"A Basic Spatial Planning Workflow","text":"shown previously, assigned conservation features class reflecting importance planning region. Conservation targets assigned target based class, case 30% suitable habitat important 10% representative features. Note: assigned classes targets based ecological information chosen visualization purposes.","code":"catTarg <- c(\"Reptiles\" = 0.3, \"Mammals\" = 0.1, \"Sharks and rays\" = 0.1, \"Birds\" = 0.1)  target <- Dict %>%   splnr_targets_byCategory(catTarg, catName = \"category\")"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"set-up-conservation-problem","dir":"Articles","previous_headings":"Overview","what":"Set up conservation problem","title":"A Basic Spatial Planning Workflow","text":"","code":"datEx_problem <- prioritizr::problem(out_sf, feature_names, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(target$target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"solve-the-conservation-problem","dir":"Articles","previous_headings":"Overview","what":"Solve the conservation problem","title":"A Basic Spatial Planning Workflow","text":"","code":"datEx_soln <- datEx_problem %>%   prioritizr::solve.ConservationProblem()"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"visualize-output","dir":"Articles","previous_headings":"Overview","what":"Visualize Output","title":"A Basic Spatial Planning Workflow","text":"different ways visualize output prioritization can loosely grouped three categories: + Visualization solution + Visualization targets + Visualization importance scores","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"visualization-of-the-solution","dir":"Articles","previous_headings":"Overview > Visualize Output","what":"Visualization of the solution","title":"A Basic Spatial Planning Workflow","text":"plot shows optimal solution planning region meets selected targets chosen features smallest area possible. categorical map displays, planning units selected important meeting conservation targets (dark blue) selected (light blue). can also done overlay cost show solution avoids highly costly areas:  Note: example, cost equal planning units.","code":"(ggSoln <- splnr_plot(datEx_soln,                        col_names = \"solution_1\",                        legend_title = \"Solution\",                        legend_labels = c(\"0\",\"1\")) +    splnr_gg_add(      PUs = PUs, Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) (ggCostOverlay <- splnr_plot_costOverlay(   soln = datEx_soln,   Cost = NA,   Cost_name = \"Cost_None\" ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"visualization-of-targets","dir":"Articles","previous_headings":"Overview > Visualize Output","what":"Visualization of targets","title":"A Basic Spatial Planning Workflow","text":"visualize well targets met, first need extract much suitable habitat feature selected spatial plan. also includes potential incidental coverage feature included spatial plan can still found planning region.  circular bar plot, one additional step data preparation needs done.","code":"dfTarget <- splnr_get_featureRep(datEx_soln, datEx_problem,                                  climsmart = FALSE,                                   solnCol = \"solution_1\" )   (ggTarget <- splnr_plot_featureRep(dfTarget,                                     category = Dict,                                     renameFeatures = TRUE,                                    namesToReplace = Dict,                                     categoryFeatureCol = \"nameCommon\",                                    nr = 1, showTarget = TRUE, )) dfTargetCirc <- dfTarget %>% dplyr::select(\"feature\", \"value\", \"group\") %>% na.omit()  colors <- c(   \"important\" = \"darkgreen\",   \"representative\" = \"darkred\" ) legends <- c(\"Important\", \"Representative\")  (ggCircTarg <- splnr_plot_circBplot(df = dfTargetCirc, legend_list = legends, legend_color = colors, impTarget = 30, repTarget = 10))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"visualization-of-importance-scores","dir":"Articles","previous_headings":"Overview > Visualize Output","what":"Visualization of importance scores","title":"A Basic Spatial Planning Workflow","text":"Importance scores can help assess relative importance individual selected planning unit spatial plan (information, see https://prioritizr.net/reference/importance.html) , use two different importance scores, Ferrier Score Rarity Weighted Richness.  example, scores label similar -coastal- planning units important spatial plan.","code":"ggFerrier <- splnr_plot_importanceScore(   soln = datEx_soln,   pDat = datEx_problem,   method = \"Ferrier\",   decimals = 4,   legendTitle = \"Importance Score \\n(Ferrier Score)\" ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ) #> Ferrier Score.  ggRWR <- splnr_plot_importanceScore(   soln = datEx_soln,   pDat = datEx_problem,   method = \"RWR\",   decimals = 2,   legendTitle = \"Importance Score \\n(Rarity Weighted Richness)\" ) +   splnr_gg_add(     PUs = PUs, Bndry = Bndry, overlay = landmass,     cropOverlay = PUs, ggtheme = splnr_theme   ) #> Rarity Wighted Richness.  (ggScores <- patchwork::wrap_plots(ggFerrier + ggRWR))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"comparing-spatial-plans","dir":"Articles","previous_headings":"Overview","what":"Comparing Spatial Plans","title":"A Basic Spatial Planning Workflow","text":"Sometimes can useful direct comparison two spatial plans. show achieve package, first need second conservation problem resulting solution. , second spatial plan include already existing marine protected areas area (https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA) following characteristics: * Status = c(“Designated”, “Established”, “Inscribed”) * Designation Type = c(“National”, “Regional”, “International”, “Applicable”) * IUCN Category = c(“Ia”, “Ib”, “II”, “III”, “IV”)  also include targets based IUCN categories prioritise species IUCN status : Vulnerable Endangered Critically Endangered Extinct Wild Extinct assign 30% target species within categories. species fall categories receive inverse area target, species greater area suitable habitat assigned lower target. can also adjust targets based IUCN Category. apply increased target 0.3 species increased thread level IUCN Red List(“EX”, “EW”, “CR”, “EN”, “VU”). Note: Accessing IUCN database requires login token rl_use_iucn() needs added environment using Sys.setenv(IUCN_REDLIST_KEY = \"[Token]\"). can start running rredlist::rl_use_iucn().","code":"# The user can download their own MPAs using this code, # but below we use data already within the package. LockedIn <- splnr_get_MPAs(PUs, \"Australia\") %>%   splnr_apply_cutoffs(0.5) %>%   dplyr::mutate(wdpa = as.logical(wdpa)) (ggMPA <- splnr_plot(MPAsCoralSea, \"wdpa\") +    splnr_gg_add(      PUs = PUs, Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) minTarget <- 0.1 maxTarget <- 0.2  # Create inverse area target IA_Targets <- splnr_targets_byInverseArea(   datEx_species_bin,   minTarget,   maxTarget ) IUCN_IA_Targets <- IA_Targets %>%   splnr_get_IUCNRedList(species_col = \"Species\") %>% # Add RL data to the df   splnr_targets_byIUCN(IUCN_target = 0.3)"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"set-up-second-conservation-problem","dir":"Articles","previous_headings":"Overview > Comparing Spatial Plans","what":"Set up second conservation problem","title":"A Basic Spatial Planning Workflow","text":"locked areas already existing MPAs. want show overlap selected planning units current MPAs, can can add splnr_gg_add()function.  instead want see contours locked areas can set typeLockIn = \"Contours\"splnr_gg_add().","code":"datEx_problem2 <- prioritizr::problem(out_sf, feature_names, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(IA_Targets$target) %>%   prioritizr::add_locked_in_constraints(as.logical(MPAsCoralSea$wdpa)) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  # Add a solution object datEx_soln2 <- datEx_problem2 %>%   prioritizr::solve.ConservationProblem()  (ggSoln2 <- splnr_plot_solution(datEx_soln2) +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     )) (splnr_plot_solution(datEx_soln2) +    splnr_gg_add(      PUs = PUs, Bndry = Bndry, lockIn = MPAsCoralSea,      nameLockIn = \"wdpa\", typeLockIn = \"Full\",      colorLockIn = \"lightgrey\", alphaLockIn = 0.2, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) (splnr_plot_solution(datEx_soln2) +    splnr_gg_add(      lockIn = MPAsCoralSea,      nameLockIn = \"wdpa\", typeLockIn = \"Contours\",      colorLockIn = \"lightgrey\", alphaLockIn = 0.2, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"visualize-comparison","dir":"Articles","previous_headings":"Overview > Comparing Spatial Plans","what":"Visualize comparison","title":"A Basic Spatial Planning Workflow","text":"plot shows first solution (without current MPAs) differs second solution (including current MPAs. categorical map displays, planning units selected solution 2 solution 1 (red), solution 1 solution 2 (blue), selected solutions (grey).  correlation matrix shows similarity Cohen’s Kappa correlation solution 1 solution 2.","code":"(ggComp <- splnr_plot_comparison(datEx_soln, datEx_soln2) +    splnr_gg_add(      PUs = PUs, Bndry = Bndry, overlay = landmass,      cropOverlay = PUs, ggtheme = splnr_theme    )) CorrMat <- splnr_get_kappaCorrData(list(datEx_soln, datEx_soln2),                                    name_sol = c(\"soln1\", \"soln2\") )  (ggCorr <- splnr_plot_corrMat(CorrMat,                               AxisLabels = c(\"Solution 1\", \"Solution 2\") ))"},{"path":"https://mathmarecol.github.io/spatialplanr/articles/spatialplanr.html","id":"plotting-selection-frequency","dir":"Articles","previous_headings":"Overview > Comparing Spatial Plans","what":"Plotting selection frequency","title":"A Basic Spatial Planning Workflow","text":"Sometimes multiple spatial plans generated, interested many times planning unit selected across array solutions. demonstrate can done using package, first create array (= portfolio) solutions. One example using portfolio","code":"datEx_soln_portfolio <- datEx_problem %>%   prioritizr::add_cuts_portfolio(5) %>% # create a portfolio of solutions   prioritizr::solve.ConservationProblem()  selFreq <- datEx_soln_portfolio %>% # calculate selection frequency   sf::st_drop_geometry() %>%   dplyr::mutate(selFreq = as.factor(rowSums(     dplyr::select(., dplyr::starts_with(\"solution_\"))   ))) %>%   sf::st_as_sf(geometry = datEx_soln_portfolio$geometry) %>%   dplyr::select(selFreq)  (ggselFreq <- splnr_plot_selectionFreq(selFreq) +     splnr_gg_add(       PUs = PUs, Bndry = Bndry, overlay = landmass,       cropOverlay = PUs, ggtheme = splnr_theme     ))"},{"path":"https://mathmarecol.github.io/spatialplanr/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Jason D. Everett. Author, maintainer. Sandra Neubert. Author.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Everett J, Neubert S (2024). spatialplanr: Help files prioritzr Spatial Planning projects. R package version 0.6.9, https://github.com/MathMarEcol/spatialplanr.","code":"@Manual{,   title = {spatialplanr: Help files for prioritzr Spatial Planning projects},   author = {Jason D. Everett and Sandra Neubert},   year = {2024},   note = {R package version 0.6.9},   url = {https://github.com/MathMarEcol/spatialplanr}, }"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Help files for prioritzr Spatial Planning projects","text":"package designed assist students staff Mathematical Marine Ecology Lab University Queensland. may useful others well. code written simplify process running prioritizr analysis given region use workflows data MME Lab. still work progress feel free submit pull requests new features code improvements.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Help files for prioritzr Spatial Planning projects","text":"aware package early stages development. Functions documentation complete installing moment risk. still interested, can install development version GitHub :","code":"# install.packages(\"devtools\") devtools::install_github(\"https://github.com/MathMarEcol/spatialplanr\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/CoralSeaVelocity.html","id":null,"dir":"Reference","previous_headings":"","what":"Example climate velocity for the example region of the coral sea — CoralSeaVelocity","title":"Example climate velocity for the example region of the coral sea — CoralSeaVelocity","text":"tsf file containing climate velocity (SSP5-8.5) coral sea","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/CoralSeaVelocity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Example climate velocity for the example region of the coral sea — CoralSeaVelocity","text":"","code":"CoralSeaVelocity"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/CoralSeaVelocity.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Example climate velocity for the example region of the coral sea — CoralSeaVelocity","text":"CoralSeaVelocity data frame 397 rows 3 columns: vocMagg_transformed Climate velocity column geometry Geometry column sf object","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/CoralSeaVelocity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Example climate velocity for the example region of the coral sea — CoralSeaVelocity","text":"https://www.iucnredlist.org/","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/IUCN_IA_Targets.html","id":null,"dir":"Reference","previous_headings":"","what":"IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets","title":"IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets","text":"tbl_df file containing IUCN IA targets selected species coral sea","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/IUCN_IA_Targets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets","text":"","code":"IUCN_IA_Targets"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/IUCN_IA_Targets.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets","text":"IUCN_IA_Targets data frame 15 rows 4 columns: Species Species names found IUCN database Area km2 total suitable habitat species Target Individual species-specific target IUCN_Category IUCN category species","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/IUCN_IA_Targets.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"IUCN and Inverse Area based Targets for Aquamaps example species — IUCN_IA_Targets","text":"https://www.iucnredlist.org/","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/MPAsCoralSea.html","id":null,"dir":"Reference","previous_headings":"","what":"Current MPAs of the Coral Sea — MPAsCoralSea","title":"Current MPAs of the Coral Sea — MPAsCoralSea","text":"sf file containing current marine protected areas coral sea","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/MPAsCoralSea.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Current MPAs of the Coral Sea — MPAsCoralSea","text":"","code":"MPAsCoralSea"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/MPAsCoralSea.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Current MPAs of the Coral Sea — MPAsCoralSea","text":"MPAsCoralSea data frame 397 rows 17 columns: wdpa binary vector denoting presence absence current marine protected area","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/MPAsCoralSea.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Current MPAs of the Coral Sea — MPAsCoralSea","text":"https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_PUs.html","id":null,"dir":"Reference","previous_headings":"","what":"Planning Units — dat_PUs","title":"Planning Units — dat_PUs","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_PUs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Planning Units — dat_PUs","text":"","code":"dat_PUs"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_PUs.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Planning Units — dat_PUs","text":"dat_PUs data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_PUs.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Planning Units — dat_PUs","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bathy.html","id":null,"dir":"Reference","previous_headings":"","what":"Bathymetry Data — dat_bathy","title":"Bathymetry Data — dat_bathy","text":"Bathymetry data downloaded via oceandatr package","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bathy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bathymetry Data — dat_bathy","text":"","code":"dat_bathy"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bathy.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Bathymetry Data — dat_bathy","text":"dat_bathy data frame bathymetry data bathymetry Bathymetry data geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bathy.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Bathymetry Data — dat_bathy","text":"\"oceandatr package\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bndry.html","id":null,"dir":"Reference","previous_headings":"","what":"Boundary of planning units — dat_bndry","title":"Boundary of planning units — dat_bndry","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bndry.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Boundary of planning units — dat_bndry","text":"","code":"dat_bndry"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bndry.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Boundary of planning units — dat_bndry","text":"dat_bndry data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_bndry.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Boundary of planning units — dat_bndry","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category.html","id":null,"dir":"Reference","previous_headings":"","what":"Category vector — dat_category","title":"Category vector — dat_category","text":"tibble containing specific grouping features","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Category vector — dat_category","text":"","code":"dat_category"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Category vector — dat_category","text":"dat_category data frame XXXX rows XXX columns: feature features available spatial prioritisation category categories features","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Category vector — dat_category","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category2.html","id":null,"dir":"Reference","previous_headings":"","what":"Category vector — dat_category2","title":"Category vector — dat_category2","text":"tibble containing specific grouping features","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Category vector — dat_category2","text":"","code":"dat_category2"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category2.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Category vector — dat_category2","text":"dat_category2 data frame XXXX rows XXX columns: feature features available spatial prioritisation category categories features","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_category2.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Category vector — dat_category2","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_clim.html","id":null,"dir":"Reference","previous_headings":"","what":"Climate metric data — dat_clim","title":"Climate metric data — dat_clim","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_clim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Climate metric data — dat_clim","text":"","code":"dat_clim"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_clim.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Climate metric data — dat_clim","text":"dat_clim data frame 780 rows 3 columns: geometry sf geometry column metric climate metric information","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_clim.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Climate metric data — dat_clim","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_mpas.html","id":null,"dir":"Reference","previous_headings":"","what":"MPA Data — dat_mpas","title":"MPA Data — dat_mpas","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_mpas.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"MPA Data — dat_mpas","text":"","code":"dat_mpas"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_mpas.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"MPA Data — dat_mpas","text":"dat_mpas data frame XXXX rows XXX columns: geometry sf geometry column wdpa binary MPA information (1: MPA)","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_mpas.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"MPA Data — dat_mpas","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_region.html","id":null,"dir":"Reference","previous_headings":"","what":"Regionalisation — dat_region","title":"Regionalisation — dat_region","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_region.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Regionalisation — dat_region","text":"","code":"dat_region"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_region.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Regionalisation — dat_region","text":"dat_region data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_region.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Regionalisation — dat_region","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin.html","id":null,"dir":"Reference","previous_headings":"","what":"Binary Species Data — dat_species_bin","title":"Binary Species Data — dat_species_bin","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Binary Species Data — dat_species_bin","text":"","code":"dat_species_bin"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Binary Species Data — dat_species_bin","text":"dat_species_bin data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Binary Species Data — dat_species_bin","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin2.html","id":null,"dir":"Reference","previous_headings":"","what":"Binary Species Data 2 — dat_species_bin2","title":"Binary Species Data 2 — dat_species_bin2","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Binary Species Data 2 — dat_species_bin2","text":"","code":"dat_species_bin2"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin2.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Binary Species Data 2 — dat_species_bin2","text":"dat_species_bin2 data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_bin2.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Binary Species Data 2 — dat_species_bin2","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_prob.html","id":null,"dir":"Reference","previous_headings":"","what":"Probability Species Data — dat_species_prob","title":"Probability Species Data — dat_species_prob","text":"sf dataframe planning units spatial prioritisation","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_prob.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Probability Species Data — dat_species_prob","text":"","code":"dat_species_prob"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_prob.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Probability Species Data — dat_species_prob","text":"dat_species_prob data frame XXXX rows XXX columns: geometry sf geometry column","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/dat_species_prob.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Probability Species Data — dat_species_prob","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spDataFiltered.html","id":null,"dir":"Reference","previous_headings":"","what":"Example data — spDataFiltered","title":"Example data — spDataFiltered","text":"Example data","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spDataFiltered.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Example data — spDataFiltered","text":"","code":"spDataFiltered"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spDataFiltered.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Example data — spDataFiltered","text":"spDataFiltered data frame sample species data Species Species names","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spDataFiltered.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Example data — spDataFiltered","text":"\"Made data\"","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spatialplanr-package.html","id":null,"dir":"Reference","previous_headings":"","what":"spatialplanr: Help files for prioritzr Spatial Planning projects — spatialplanr-package","title":"spatialplanr: Help files for prioritzr Spatial Planning projects — spatialplanr-package","text":"package provides range tools setting , running plotting spatial plan using prioritizr. intended use Mathematical Marine Ecology Lab UQ, sets projects using approach data sets.","code":""},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/spatialplanr-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"spatialplanr: Help files for prioritzr Spatial Planning projects — spatialplanr-package","text":"Maintainer: Jason D. Everett JaseEverett@gmail.com (ORCID) Authors: Sandra Neubert sandra.neubert97@gmail.com (ORCID)","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_apply_cutoffs.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","title":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","text":"Function apply cutoffs feature data","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_apply_cutoffs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","text":"","code":"splnr_apply_cutoffs(features, Cutoffs, inverse = FALSE)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_apply_cutoffs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","text":"features sf dataframe feature information Cutoffs single value named vector cutoffs. inverse TRUE, values Cutoffs used. FALSE (default), values kept.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_apply_cutoffs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","text":"new sf dataframe cutoffs applied.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_apply_cutoffs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to apply cutoffs to feature data — splnr_apply_cutoffs","text":"","code":"df <- splnr_apply_cutoffs(dat_species_prob, Cutoffs = 0.5)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_arrangeFeatures.html","id":null,"dir":"Reference","previous_headings":"","what":"Ensure all features are in the same order. — splnr_arrangeFeatures","title":"Ensure all features are in the same order. — splnr_arrangeFeatures","text":"splnr_arrangeFeatures() sorts data based longitude latitude values.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_arrangeFeatures.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Ensure all features are in the same order. — splnr_arrangeFeatures","text":"","code":"splnr_arrangeFeatures(df)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_arrangeFeatures.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Ensure all features are in the same order. — splnr_arrangeFeatures","text":"df sf object sort Lon Lat","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_arrangeFeatures.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Ensure all features are in the same order. — splnr_arrangeFeatures","text":"sorted sf object","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_arrangeFeatures.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Ensure all features are in the same order. — splnr_arrangeFeatures","text":"","code":"df <- dat_species_prob %>%   splnr_arrangeFeatures()"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_featureApproach.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to run the feature approach — splnr_climate_featureApproach","title":"Function to run the feature approach — splnr_climate_featureApproach","text":"Function run feature approach","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_featureApproach.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to run the feature approach — splnr_climate_featureApproach","text":"","code":"splnr_climate_featureApproach(   features,   metric,   targets,   direction,   percentile = 35,   refugiaTarget = 0.3 )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_featureApproach.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to run the feature approach — splnr_climate_featureApproach","text":"features feature sfobject metric climate metric sf object 'metric' column name metric values per planning unit. targets data.framewith list features \"feature\" column corresponding targets \"target\" column direction direction = 1, metric values low (least climate-smart) high (climate-smart). direction = -1, metric values high (least climate-smart) low (climate-smart). percentile cut-threshold determining whether area climate priority area (e.g., lower 35th percentile warming upper 65th percentile acidification). Note percentile lower limit threshold. refugiaTarget target assigned climate-smart areas","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_featureApproach.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to run the feature approach — splnr_climate_featureApproach","text":"list two components: 1. data frame passed prioritizr creating conservation problem containing binary information per planning unit per feature. 2. targets features conservation problem CPA approach used.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_featureApproach.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to run the feature approach — splnr_climate_featureApproach","text":"","code":"Features <- dat_species_bin  targets <- Features %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)  Feature_Approach <- splnr_climate_featureApproach(   features = dat_species_bin,   metric = dat_clim,   targets = targets,   direction = 1 ) #> [1] \"Higher values mean more climate-smart areas.\" out_sf <- Feature_Approach$Features targets <- Feature_Approach$Targets"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_percentileApproach.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to run the percentile approach — splnr_climate_percentileApproach","title":"Function to run the percentile approach — splnr_climate_percentileApproach","text":"Function run percentile approach","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_percentileApproach.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to run the percentile approach — splnr_climate_percentileApproach","text":"","code":"splnr_climate_percentileApproach(   features,   metric,   targets,   direction,   percentile = 35 )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_percentileApproach.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to run the percentile approach — splnr_climate_percentileApproach","text":"features feature sfobject metric climate metric sf object 'metric' column name metric values per planning unit. targets data.framewith list features \"feature\" column corresponding targets \"target\" column direction direction = 1, metric values low (least climate-smart) high (climate-smart). direction = -1, metric values high (least climate-smart) low (climate-smart). percentile cut-threshold determining whether area climate priority area (e.g., lower 35th percentile warming upper 65th percentile acidification). Note percentile lower limit threshold.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_percentileApproach.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to run the percentile approach — splnr_climate_percentileApproach","text":"list two components: 1. data frame passed prioritizr creating conservation problem containing binary information per planning unit per feature. 2. targets features conservation problem CPA approach used.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_percentileApproach.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to run the percentile approach — splnr_climate_percentileApproach","text":"","code":"targets <- dat_species_bin %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)  Percentile_Approach <- splnr_climate_percentileApproach(   features = dat_species_bin,   metric = dat_clim,   targets = targets,   direction = 1 ) #> [1] \"Higher values mean more climate-smart areas.\" out_sf <- Percentile_Approach$Features targets <- Percentile_Approach$Targets"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_priorityAreaApproach.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","title":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","text":"Function run climate-priority-area approach","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_priorityAreaApproach.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","text":"","code":"splnr_climate_priorityAreaApproach(   features,   metric,   targets,   direction,   percentile = 5,   refugiaTarget = 1 )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_priorityAreaApproach.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","text":"features feature sfobject metric climate metric sf object 'metric' column name metric values per planning unit. targets data.framewith list features \"feature\" column corresponding targets \"target\" column direction direction = 1, metric values low (least climate-smart) high (climate-smart). direction = -1, metric values high (least climate-smart) low (climate-smart). percentile cut-threshold determining whether area climate priority area (e.g., lower 35th percentile warming upper 65th percentile acidification). Note percentile lower limit threshold. refugiaTarget target assigned climate-smart areas","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_priorityAreaApproach.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","text":"list two components: 1. data frame passed prioritizr creating conservation problem containing binary information per planning unit per feature. 2. targets features conservation problem CPA approach used.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_climate_priorityAreaApproach.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to run the climate-priority-area approach — splnr_climate_priorityAreaApproach","text":"","code":"targets <- dat_species_bin %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)  CPA_Approach <- splnr_climate_priorityAreaApproach(   features = dat_species_bin,   metric = dat_clim,   targets = targets,   direction = -1 ) out_sf <- CPA_Approach$Features targets <- CPA_Approach$Targets"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_regionalisation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation","text":"","code":"splnr_convert_regionalisation(dat, PUs, cat_name = NA, col_name = NA)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_regionalisation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation","text":"dat Dataset raster sf format. PUs sf object Planning Units cat_name character string categories regionalisation col_name name layer","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_regionalisation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation","text":"sf object containing Planning Units feature.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_regionalisation.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation","text":"wrapper splnr_Convert2PUs() deals need processes layer seperately dataset needs raster vector format. input contains continuous data, output area-averaged mean planning unit. input binary, output proportion planning unit covered.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_regionalisation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to interpolate regionalisation data onto Planning Units — splnr_convert_regionalisation","text":"","code":"if (FALSE) { # \\dontrun{ df <- splnr_convert_regionalisation(dat, PUs) } # }"},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_toPUs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to interpolate data onto Planning Units — splnr_convert_toPUs","text":"","code":"splnr_convert_toPUs(dat, PlanUnits)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_toPUs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to interpolate data onto Planning Units — splnr_convert_toPUs","text":"dat Dataset filename dataset PlanUnits sf object Planning Units","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_toPUs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to interpolate data onto Planning Units — splnr_convert_toPUs","text":"sf object containing Planning Units feature.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_toPUs.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Function to interpolate data onto Planning Units — splnr_convert_toPUs","text":"dataset needs raster vector format. input contains continuous data, output area-averaged mean planning unit. input binary, output proportion planning unit covered.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_convert_toPUs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to interpolate data onto Planning Units — splnr_convert_toPUs","text":"","code":"if (FALSE) { # \\dontrun{ df <- splnr_convert_toPUs(dat, PlanUnits) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_create_polygon.html","id":null,"dir":"Reference","previous_headings":"","what":"Function for creating polygon — splnr_create_polygon","title":"Function for creating polygon — splnr_create_polygon","text":"splnr_create_polygon() allows create polygon based longitude latitude coordinates input data.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_create_polygon.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function for creating polygon — splnr_create_polygon","text":"","code":"splnr_create_polygon(x, cCRS = \"EPSG:4326\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_create_polygon.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function for creating polygon — splnr_create_polygon","text":"x named vector lon/lat coordinates make sf polygon cCRS CRS use polygon","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_create_polygon.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function for creating polygon — splnr_create_polygon","text":"sf object polygon","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_create_polygon.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function for creating polygon — splnr_create_polygon","text":"","code":"splnr_create_polygon(x = dplyr::tibble(x = seq(-50, 50, by = 1), y = 120) %>%   dplyr::bind_rows(dplyr::tibble(x = 50, y = seq(120, 180, by = 1))) %>%   dplyr::bind_rows(dplyr::tibble(x = seq(50, -50, by = -1), y = 180)) %>%   dplyr::bind_rows(dplyr::tibble(x = -50, y = seq(150, 120, by = -1))))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_featureNames.html","id":null,"dir":"Reference","previous_headings":"","what":"Returns the feature names — splnr_featureNames","title":"Returns the feature names — splnr_featureNames","text":"splnr_featureNames() allows extract names features want pass prioritizr prioritization. requires sf object input returns column names object excluding columns specify exclude argument.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_featureNames.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Returns the feature names — splnr_featureNames","text":"","code":"splnr_featureNames(dat, exclude = NA)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_featureNames.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Returns the feature names — splnr_featureNames","text":"dat sf dataframe features exclude Character vector columns exclude","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_featureNames.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Returns the feature names — splnr_featureNames","text":"character vector names","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_featureNames.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Returns the feature names — splnr_featureNames","text":"","code":"df <- dat_species_prob %>%   splnr_featureNames()"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_IUCNRedList.html","id":null,"dir":"Reference","previous_headings":"","what":"Match Species to IUCN RedList — splnr_get_IUCNRedList","title":"Match Species to IUCN RedList — splnr_get_IUCNRedList","text":"First need API key, alphanumeric string provided IUCN need send every request; following function takes website, need fill form (might take 1-2 days receive key) rl_use_iucn() receive email API key, set environmental variable (MUST named IUCN_REDLIST_KEY) need re-step everytime restart R Sys.setenv(IUCN_REDLIST_KEY = \"\") add IUCN_REDLIST_KEY = \"\" .Renviron file permanently set Sys.getenv(\"IUCN_REDLIST_KEY\") #' check Evaluated DD: Data Deficient LC: Least Concern NT: Near Threatened VU: Vulnerable EN: Endangered CR: Critically Endangered EW: Extinct Wild EX: Extinct LRlc: Low risk – least concern LRnt: Low risk – near threatened LRcd: Low risk - conservation dependent Categories care cate <- c(\"EX\",\"EW\",\"CR\",\"EN\",\"VU\")","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_IUCNRedList.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Match Species to IUCN RedList — splnr_get_IUCNRedList","text":"","code":"splnr_get_IUCNRedList(df, species_col = \"Species\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_IUCNRedList.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Match Species to IUCN RedList — splnr_get_IUCNRedList","text":"df dataframe containing species matched IUCN redlist species_col string name column containting species name","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_IUCNRedList.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Match Species to IUCN RedList — splnr_get_IUCNRedList","text":"dataframe additional column IUCN_Category","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_IUCNRedList.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Match Species to IUCN RedList — splnr_get_IUCNRedList","text":"","code":"if (FALSE) { # \\dontrun{ df <- data.frame(Species = c(\"Diomedea exulans\", \"Hippocampus kuda\", \"Squatina squatina\")) %>%   splnr_get_IUCNRedList() } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_MPAs.html","id":null,"dir":"Reference","previous_headings":"","what":"Get marine parks from the WDPA. — splnr_get_MPAs","title":"Get marine parks from the WDPA. — splnr_get_MPAs","text":"code wrapper wonderful wdpar package written Jeffrey O. Hanson. data interfaced planning units. sf object returned PU area covered selected marine protected areas.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_MPAs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get marine parks from the WDPA. — splnr_get_MPAs","text":"","code":"splnr_get_MPAs(   PlanUnits,   Countries,   Status = c(\"Designated\", \"Established\", \"Inscribed\"),   Desig = c(\"National\", \"Regional\", \"International\", \"Not Applicable\"),   Category = c(\"Ia\", \"Ib\", \"II\", \"III\", \"IV\"),   ... )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_MPAs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get marine parks from the WDPA. — splnr_get_MPAs","text":"PlanUnits Planning Units sf object Countries character vector countries extract MPAs. get MPAs, use \"global\" . Status status field WDPA provides information whether protected area established, designated, proposed time data submitted. Desig designation type category type protected area legally/officially designated proposed. Category Stores IUCN Protected Area Management Categories (recorded field IUCN_CAT) protected areas categories reported ... arguments passed wdpa_fetch()","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_MPAs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get marine parks from the WDPA. — splnr_get_MPAs","text":"sf object MPAs intersected planning units","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_MPAs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get marine parks from the WDPA. — splnr_get_MPAs","text":"","code":"dat <- splnr_get_MPAs(PlanUnits = dat_PUs, Countries = \"Australia\") #> ! importing local data (version Apr 2024); use \"force=TRUE\" if you need latest version. #> Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUE #> Warning: attribute variables are assumed to be spatially constant throughout all geometries #> Warning: attribute variables are assumed to be spatially constant throughout all geometries  aust <- rnaturalearth::ne_countries(country = \"Australia\", returnclass = \"sf\")  gg <- ggplot2::ggplot() +   ggplot2::geom_sf(data = dat, ggplot2::aes(fill = wdpa)) +   ggplot2::geom_sf(data = aust, fill = \"grey50\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_boundary.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the boundary of the planning region. — splnr_get_boundary","title":"Get the boundary of the planning region. — splnr_get_boundary","text":"splnr_get_boundary() allows create sf object planning region either based specific coordinate information, rnaturalearth inputs ocean data. Creating boundary often first step conservation planning requirement downstream function sin spatialplanr.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_boundary.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the boundary of the planning region. — splnr_get_boundary","text":"","code":"splnr_get_boundary(Limits, Type = NULL, res = 1, cCRS = \"ESRI:54009\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_boundary.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the boundary of the planning region. — splnr_get_boundary","text":"Limits limits boundary. can either 4 element numeric named vector (c(xmin = 150, xmax = 160, ymin = -40, ymax = -30)), vector ocean/sea names, vector EEZs., Type type Limits provided. Options \"Ocean\" \"EEZ\". (required numeric \"Global\" limits provided) res resolution (degrees) create boundary polygon numeric limits provided. cCRS CRS boundary returned ","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_boundary.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the boundary of the planning region. — splnr_get_boundary","text":"boundary planning region","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_boundary.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the boundary of the planning region. — splnr_get_boundary","text":"","code":"Bndry <- splnr_get_boundary(Limits = \"North Atlantic Ocean\", Type = \"Ocean\") #> Reading layer `ne_10m_geography_marine_polys' from data source  #>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpvzaEZa/ne_10m_geography_marine_polys.shp'  #>   using driver `ESRI Shapefile' #> Simple feature collection with 306 features and 37 fields #> Geometry type: MULTIPOLYGON #> Dimension:     XY #> Bounding box:  xmin: -180 ymin: -85.19206 xmax: 179.9999 ymax: 90 #> Geodetic CRS:  WGS 84 Bndry <- splnr_get_boundary(Limits = \"Global\") Bndry <- splnr_get_boundary(Limits = c(\"xmin\" = 150, \"xmax\" = 170, \"ymin\" = -40, \"ymax\" = -20))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"code takes sf object return updated new coastDistance column. output inherits crs sf object ensure correct projection needs","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"","code":"splnr_get_distCoast(dat_sf, custom_coast = NULL, res = NULL)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"dat_sf sf object. custom_coast sf coastline object (optional) res Allow user choose resolution (small, medium, large) rnaturalearth data used coastline.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"sf object distances nearest coast","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"Written Kristine Buenafe Written: March/April 2023 Modified Kilian Barreiro Updated: December 2023","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_distCoast.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to compute distances to nearest coastline for each centroid of each planning unit in the 'sf' object provided. — splnr_get_distCoast","text":"","code":"bbox <- sf::st_bbox(c(xmin = 0, ymin = 0, xmax = 3, ymax = 3)) grid <- sf::st_make_grid(bbox, n = c(3, 3), what = \"polygons\") grid <- sf::st_sf(geometry = grid) %>%   sf::st_set_crs(\"EPSG:4326\") splnr_get_distCoast(grid) #> Simple feature collection with 9 features and 1 field #> Geometry type: POLYGON #> Dimension:     XY #> Bounding box:  xmin: 0 ymin: 0 xmax: 3 ymax: 3 #> Geodetic CRS:  WGS 84 #>                         geometry coastDistance_km #> 1 POLYGON ((0 0, 1 0, 1 1, 0 ...         544.9762 #> 2 POLYGON ((1 0, 2 0, 2 1, 1 ...         553.2552 #> 3 POLYGON ((2 0, 3 0, 3 1, 2 ...         442.2715 #> 4 POLYGON ((0 1, 1 1, 1 2, 0 ...         438.7047 #> 5 POLYGON ((1 1, 2 1, 2 2, 1 ...         480.9762 #> 6 POLYGON ((2 1, 3 1, 3 2, 2 ...         462.5574 #> 7 POLYGON ((0 2, 1 2, 1 3, 0 ...         335.6332 #> 8 POLYGON ((1 2, 2 2, 2 3, 1 ...         371.9517 #> 9 POLYGON ((2 2, 3 2, 3 3, 2 ...         406.2456  cCRS <- \"ESRI:54009\"  Bndry <- splnr_get_boundary(Limits = \"Coral Sea\",                             Type = \"Oceans\",                             cCRS = cCRS) #> Reading layer `ne_10m_geography_marine_polys' from data source  #>   `/private/var/folders/_r/mcmw_qtn0m7cd23cbdqfszl40000gp/T/RtmpvzaEZa/ne_10m_geography_marine_polys.shp'  #>   using driver `ESRI Shapefile' #> Simple feature collection with 306 features and 37 fields #> Geometry type: MULTIPOLYGON #> Dimension:     XY #> Bounding box:  xmin: -180 ymin: -85.19206 xmax: 179.9999 ymax: 90 #> Geodetic CRS:  WGS 84  landmass <- rnaturalearth::ne_countries(   scale = \"medium\",   returnclass = \"sf\" ) %>%   sf::st_transform(cCRS)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_featureRep.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare data to plot how well targets are met — splnr_get_featureRep","title":"Prepare data to plot how well targets are met — splnr_get_featureRep","text":"Prepare data plot well targets met","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_featureRep.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare data to plot how well targets are met — splnr_get_featureRep","text":"","code":"splnr_get_featureRep(   soln,   pDat,   targets = NA,   climsmart = FALSE,   climsmartApproach = 0,   solnCol = \"solution_1\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_featureRep.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare data to plot how well targets are met — splnr_get_featureRep","text":"soln prioritizr solution pDat prioritizr problem targets data.framewith list features \"feature\" column corresponding targets \"target\" column climsmart logical denoting whether spatial planning done climate-smart (targets calculated differently) climsmartApproach either 0,1,2 3 depending climate-smart approach used (0 = None; 1 = Climate Priority Area; 2 = Feature; 3 = Percentile). solnCol Name column solution","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_featureRep.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare data to plot how well targets are met — splnr_get_featureRep","text":"tbl_df dataframe","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_featureRep.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prepare data to plot how well targets are met — splnr_get_featureRep","text":"","code":"pDat <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  soln <- pDat %>%   prioritizr::solve.ConservationProblem()  df <- splnr_get_featureRep(   soln = soln,   pDat = pDat )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":null,"dir":"Reference","previous_headings":"","what":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"possibilities offered function explained vignette(\"GlobalFishingWatch\")","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"","code":"splnr_get_gfw(   region,   start_date,   end_date,   temp_res,   spat_res = \"LOW\",   region_source = \"EEZ\",   key = gfwr::gfw_auth(),   cCRS = \"EPSG:4326\",   compress = FALSE )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"region Region studied (character) geojson shape filter raster start_date Start date (waited format : \"%Y-%m-%d\"). end_date End date (waited format : \"%Y-%m-%d\"). temp_res Temporal resolution (\"daily\",\"monthly\",\"yearly\"). spat_res Spatial resolution (\"low\" 0.1 degree, \"high\" 0.01 degree). region_source source region ('eez','mpa', 'rfmo' 'user_json') key Token GFW API (see details GlobalFishingWatch vignette). cCRS crs sf returned (default = \"EPSG:4326\"). compress Binary operator compress (aggregate) data per coordinates (default = FALSE).","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"sf object gfw data.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"parameters get_raster function, plus cCRS crs sf_modification  Different possible values can combined : Time Range, Flag, Geartype. (combination can : c('Time Range','Geartype'), want get sum fishing hours per date geartype, example want display drifting longline fishing specific year) Notes : moment limited EEZs region, can potentially restrict working area specific MPAs. Days indicated the__ start_date end_date __variables included data recovery. code takes several parameters described return sf object gfw data aggregated (param compress)","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_gfw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"The get_gfwData function recover the data of Global Fishing Watch and returns it as a sf object. — splnr_get_gfw","text":"","code":"if (FALSE) { # \\dontrun{ gfw_data <- splnr_get_gfw('Australia', \"2021-01-01\", \"2022-12-31\", \"YEARLY\",     cCRS = \"ESRI:54009\", compress = TRUE) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_kappaCorrData.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","title":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","text":"Conservation planning often requires comparison outputs solutions different conservation problems. One way compare solutions correlating solutions using Cohen's Kappa. splnr_get_kappaCorrData() takes list prioritizr solutions perform Cohen's Kappa correlation solution. resulting correlation matrix symmetrical along main diagonal contains Cohen's Kappa pairwise correlation solutions. main diagonal always 1. correlation matrix obtained function can passed onto splnr_plot_corrMat().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_kappaCorrData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","text":"","code":"splnr_get_kappaCorrData(sol, name_sol)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_kappaCorrData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","text":"sol List prioritizr solutions (sf objects) solutions column name solution_1 name_sol Name tags different solutions","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_kappaCorrData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","text":"matrixOut matrix","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_kappaCorrData.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prepare data to plot Cohen's Kappa correlation matrix — splnr_get_kappaCorrData","text":"","code":"# 30 % target for problem/solution 1 dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  # 50 % target for problem/solution 2 dat_problem2 <- prioritizr::problem(   dat_species_bin %>%     dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.5) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln2 <- dat_problem2 %>%   prioritizr::solve.ConservationProblem()  corrMat <- splnr_get_kappaCorrData(list(dat_soln, dat_soln2), name_sol = c(\"soln1\", \"soln2\")) #> New names: #> • `soln1` -> `soln1...1` #> • `soln1` -> `soln1...2` #> New names: #> • `soln2` -> `soln2...1` #> • `soln2` -> `soln2...2` #> New names: #> • `` -> `...1` #> • `` -> `...2`"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_selFreq.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","title":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","text":"multiple spatial plans generated, often interested many times planning unit selected across array solutions. array can either list solutions different conservation problems generated portfolio approach prioritizr. splnr_get_selFreq() allows calculate selection frequency planning unit either list portfolio solutions. resulting sf object can passed visualization spatialplanr function splnr_plot_selectionFreq().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_selFreq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","text":"","code":"splnr_get_selFreq(solnMany, type = \"portfolio\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_selFreq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","text":"solnMany List portfolio prioritizr solutions type Either \"portfolio\" (sf object) portfolio produced using prioritizr \"list\" list solutions","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_selFreq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","text":"selFreq sf object containing column selection frequency (sum solutions).","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_get_selFreq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prepare data to plot Selection Frequency of planning units — splnr_get_selFreq","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  # create conservation problem that contains a portfolio of solutions dat_soln_portfolio <- dat_problem %>%   prioritizr::add_cuts_portfolio(number_solutions = 5) %>%   prioritizr::solve.ConservationProblem()  selFreq <- splnr_get_selFreq(solnMany = dat_soln_portfolio, type = \"portfolio\") (splnr_plot_selectionFreq(selFreq))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_gg_add.html","id":null,"dir":"Reference","previous_headings":"","what":"Add-ons for plotting — splnr_gg_add","title":"Add-ons for plotting — splnr_gg_add","text":"function allows customise plots simple reproducible way, giving option several inputs can included maps produced functions package.can combined spatialplanr spatial plotting functions.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_gg_add.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add-ons for plotting — splnr_gg_add","text":"","code":"splnr_gg_add(   PUs = NULL,   colorPUs = \"grey80\",   Bndry = NULL,   colorBndry = \"black\",   overlay = NULL,   colorOverlay = \"grey20\",   overlay2 = NULL,   colorOverlay2 = \"grey30\",   overlay3 = NULL,   colorOverlay3 = \"grey40\",   contours = NULL,   colorConts = \"black\",   cropOverlay = NULL,   lockIn = NULL,   typeLockIn = \"Full\",   nameLockIn = NULL,   alphaLockIn = 0.5,   colorLockIn = \"black\",   legendLockIn = \"\",   labelLockIn = \"MPAs\",   ggtheme = \"Default\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_gg_add.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add-ons for plotting — splnr_gg_add","text":"PUs Planning Units sf object colorPUs color value outline planning units. Bndry planning region boundaries sf object colorBndry color value outline boundary. overlay sf object overlay polygon. colorOverlay color value overlay. overlay2 sf object overlay polygon. colorOverlay2 color value overlay. overlay3 sf object overlay polygon. colorOverlay3 color value overlay. contours sf object contours important visualise (e.g. outline sea mounts, ridges; can produced terra::.contour()); 6 different contours possible. colorConts color value contours. cropOverlay sf object boundary box used cropping overlay object. lockIn sf object binary data locked areas prioritisation (e.g. MPAs). typeLockIn Either \"Full\" \"Contours\"; \"Full\" maps locked areas top planning units; \"Contours\" draws outline locked areas. nameLockIn column data frame contains binary information locked areas plot alphaLockIn value (0-1) opacity locked areas plotted top plots. colorLockIn color value locked areas. legendLockIn character value title legend locked areas. Can empty (\"\"). labelLockIn legend label locked area (e.g. MPAs) ggtheme theme applied plot. Can either NA (default ggplot), \"Default\" (default spatialplanr: theme_bw() basic theme settings) user-defined list theme properties.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_gg_add.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add-ons for plotting — splnr_gg_add","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_gg_add.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add-ons for plotting — splnr_gg_add","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  splnr_plot_solution(dat_soln) +   splnr_gg_add(PUs = dat_PUs, ggtheme = \"Default\") #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one."},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_match_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Substitute numbers for all_names in regionalisations — splnr_match_names","title":"Substitute numbers for all_names in regionalisations — splnr_match_names","text":"Many regionalisations numeric values shape files correspond vector names. provide function quickly replace numbers names.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_match_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Substitute numbers for all_names in regionalisations — splnr_match_names","text":"","code":"splnr_match_names(dat, nam)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_match_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Substitute numbers for all_names in regionalisations — splnr_match_names","text":"dat sf data frame one column numeric/integer corresponding nam nam Named character vector names corresponding column dat recode","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_match_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Substitute numbers for all_names in regionalisations — splnr_match_names","text":"sf dataframe numeric regionalisations substituted category names","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_match_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Substitute numbers for all_names in regionalisations — splnr_match_names","text":"","code":"dat <- dat_region nam <- c(\"Region1\" = \"SE Aust\", \"Region2\" = \"Tas\", \"Region3\" = \"NE Aust\") df <- splnr_match_names(dat, nam)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Function to plot data. — splnr_plot","title":"Function to plot data. — splnr_plot","text":"(now can replace splnr_plot_cost(), splnr_plot_binFeature(), splnr_plot_MPAs(), splnr_plot_featureNo())","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function to plot data. — splnr_plot","text":"","code":"splnr_plot(   df,   col_names = NULL,   paletteName = \"YlGnBu\",   colourVals = c(\"#c6dbef\", \"#3182bd\"),   plot_title = \"\",   legend_title = NULL,   legend_labels = NULL )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function to plot data. — splnr_plot","text":"df dataframe containing data plotted. must include geometry column used geom_sf. col_names list column names include plot. specified, columns used colour plot. paletteName name colour palette use filling. Default \"YlGnBu\". colourVals colour values use col_names specified data binary. plot_title title plot. legend_title title legend. legend_labels vector strings containing labels use legend values.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function to plot data. — splnr_plot","text":"ggplot object.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Function to plot data. — splnr_plot","text":"Written Kilian Barreiro Jason Everett Written: February 2024","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Function to plot data. — splnr_plot","text":"","code":"# Binary plot of species distribution splnr_plot(df = dat_species_bin,            col_names = \"Spp1\",            legend_title = \"Legend\",            legend_labels = c(\"Absent\", \"Present\")) #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one.   # Logical plot of species distribution splnr_plot(df = dat_species_bin %>%                 dplyr::mutate(dplyr::across(                   tidyselect::starts_with(\"Spp\"), as.logical)),            col_names = \"Spp1\",            legend_title = \"Legend\",            legend_labels = c(\"Absent\", \"Present\")) #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one.   # Continuous plot of bathymetry# splnr_plot(df = dat_bathy,            col_names = \"bathymetry\",            plot_title = \"Bathymetry\",            legend_title = \"Bathymetry (m)\") #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one.   # Plot Planning Units splnr_plot(df = dat_PUs) #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one.   # Multi binary features splnr_plot(df = dat_species_bin,            col_names = colnames(dat_species_bin %>%                                   sf::st_drop_geometry() %>%                                   dplyr::select(                                     tidyselect::starts_with(\"Spp\"))),            legend_title = \"Number of features\") #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one."},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_MPAs.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot MPAs — splnr_plot_MPAs","title":"Plot MPAs — splnr_plot_MPAs","text":"splnr_plot_MPAs() allows plot either outline area MPAs existing planning region (example extracted spatialplanrfunction splnr_get_MPAs()) customisable way using ggplot2. function requires sf object containing information whether planning unit planning region lies within MPA column called wdpa outputs ggobject. can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_MPAs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot MPAs — splnr_plot_MPAs","text":"","code":"splnr_plot_MPAs(   df,   colorVals = c(`TRUE` = \"blue\", `FALSE` = \"white\"),   showLegend = TRUE,   plotTitle = \"Locked In Areas\",   legendTitle = \"\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_MPAs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot MPAs — splnr_plot_MPAs","text":"df sf object marine protected areas colorVals list object named vectors match color value according name. \"TRUE\" stands selected planning units. showLegend logical command whether show legend solution (Default: TRUE). plotTitle character value title plot. Can empty (\"\"). legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_MPAs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot MPAs — splnr_plot_MPAs","text":"ggplot object plot","code":""},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_MPAs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot MPAs — splnr_plot_MPAs","text":"","code":"if (FALSE) { # \\dontrun{ splnr_plot_MPAs(dat_mpas) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_binFeature.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot binary feature — splnr_plot_binFeature","title":"Plot binary feature — splnr_plot_binFeature","text":"splnr_plot_binFeature() allows plot presences absences feature planning region customisable way using ggplot2. function requires sf object binary information feature(0 absences 1 presences, example created continuous data spatialplanr function splnr_apply_cutoffs()). outputs ggobject can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_binFeature.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot binary feature — splnr_plot_binFeature","text":"","code":"splnr_plot_binFeature(   df,   colInterest,   colorVals = c(Suitable = \"#3182bd\", `Not Suitable` = \"#c6dbef\"),   showLegend = TRUE,   plotTitle = \" \",   legendTitle = \"Habitat\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_binFeature.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot binary feature — splnr_plot_binFeature","text":"df data frame binary feature information colInterest column data frame contains binary information feature plot colorVals list object named vectors match color value according name. \"TRUE\" stands selected planning units. showLegend logical command whether show legend solution (Default: TRUE). plotTitle character value title plot. Can empty (\"\"). legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_binFeature.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot binary feature — splnr_plot_binFeature","text":"ggplot object plot","code":""},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_binFeature.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot binary feature — splnr_plot_binFeature","text":"","code":"if (FALSE) { # \\dontrun{ splnr_plot_binFeature(dat_species_bin, dat_species_bin$Spp1) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_circBplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot circular barplot — splnr_plot_circBplot","title":"Plot circular barplot — splnr_plot_circBplot","text":"Plot circular barplot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_circBplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot circular barplot — splnr_plot_circBplot","text":"","code":"splnr_plot_circBplot(   df,   legend_color,   legend_list,   indicateTargets = TRUE,   impTarget = NA,   repTarget = NA,   colTarget = \"red\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_circBplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot circular barplot — splnr_plot_circBplot","text":"df data frame following column names: feature, value, group legend_color vector list colors; group names corresponding colors legend_list list groups/legends groups indicateTargets logical whether show targets set impTarget target important features (%) repTarget target representative features (%) colTarget string colour value indicator line","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_circBplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot circular barplot — splnr_plot_circBplot","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_circBplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot circular barplot — splnr_plot_circBplot","text":"","code":"# DISCLAIMER: THIS SOLUTION IS NOT ACTUALLY RUN WITH THESE TARGETS YET  dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  s1 <- dat_soln %>%   tibble::as_tibble()  p1 <- dat_problem  df_rep_imp <- prioritizr::eval_feature_representation_summary(   p1,   s1[, \"solution_1\"] ) %>%   dplyr::select(feature, relative_held) %>%   dplyr::mutate(relative_held = relative_held * 100)  imp_layers <- c(\"Spp1\", \"Spp3\")  target <- data.frame(feature = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\")) %>%   dplyr::mutate(class = dplyr::if_else(.data$feature %in% imp_layers,     \"important\", \"representative\"   )) %>%   dplyr::mutate(target = dplyr::if_else(class == \"important\",     50 / 100, 30 / 100   ))  df <- merge(df_rep_imp, target) %>%   dplyr::select(-target) %>%   na.omit() %>%   dplyr::rename(value = relative_held) %>%   dplyr::rename(group = class)  colors <- c(   \"important\" = \"darkgreen\",   \"representative\" = \"darkred\" ) legends <- c(\"Important\", \"Representative\")  (splnr_plot_circBplot(df,   legend_list = legends,   legend_color = colors,   impTarget = 50, repTarget = 30 )) #> Warning: Removed 4 rows containing missing values or values outside the scale range #> (`geom_bar()`). #> Warning: Removed 6 rows containing missing values or values outside the scale range #> (`geom_text()`)."},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climData.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot climate data — splnr_plot_climData","title":"Plot climate data — splnr_plot_climData","text":"Plot climate data","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot climate data — splnr_plot_climData","text":"","code":"splnr_plot_climData(   df,   colInterest,   colorMap = \"C\",   plotTitle = \" \",   legendTitle = \"Climate metric\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot climate data — splnr_plot_climData","text":"df sf object climate metric information colInterest column data frame contains metric informatin colorMap character string indicating color map use (see https://ggplot2.tidyverse.org/reference/scale_viridis.html options) plotTitle character value title plot. Can empty (\"\"). legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot climate data — splnr_plot_climData","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climData.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot climate data — splnr_plot_climData","text":"","code":"splnr_plot_climData(df = dat_clim, colInterest = \"metric\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climKernelDensity.html","id":null,"dir":"Reference","previous_headings":"","what":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","title":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","text":"Kernel Density Plots climate-smart spatial plans","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climKernelDensity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","text":"","code":"splnr_plot_climKernelDensity(   soln,   names = NA,   type = \"Normal\",   colorMap = \"C\",   legendTitle = expression(\" °C y\"^\"-1\" * \"\"),   xAxisLab = expression(\"Climate warming ( °C y\"^\"-1\" * \")\") )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climKernelDensity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","text":"soln type \"Publication\": list prioirtizr solutions (e.g. solution_list = list(s1, s2)) containing \"metric\" column containing used climate metric information; type \"App\": needs prioritizr solution names list names solutions (names = c(\"Input 1\", \"Input 2\")) type plotting style kernel density plots. Either \"Publication\" gives axis information etc., \"App\" condenses information plot simplify stakeholders. colorMap character string indicating color map use (see https://ggplot2.tidyverse.org/reference/scale_viridis.html options) legendTitle character value title legend. Can empty (\"\"). xAxisLab characted value x Axis label depending climate metric input","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climKernelDensity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_climKernelDensity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Kernel Density Plots for climate-smart spatial plans — splnr_plot_climKernelDensity","text":"","code":"target <- dat_species_bin %>%   sf::st_drop_geometry() %>%   colnames() %>%   data.frame() %>%   setNames(c(\"feature\")) %>%   dplyr::mutate(target = 0.3)  CPA <- splnr_climate_priorityAreaApproach(   features = dat_species_bin,   metric = dat_clim,   targets = target,   direction = -1,   refugiaTarget = 1 )  out_sf <- CPA$Features %>%   dplyr::mutate(Cost_None = rep(1, 780)) %>%   sf::st_join(dat_clim, join = sf::st_equals)  usedFeatures <- out_sf %>%   sf::st_drop_geometry() %>%   dplyr::select(-tidyselect::starts_with(\"Cost_\"), -\"metric\") %>%   names()  p1 <- prioritizr::problem(out_sf, usedFeatures, \"Cost_None\") %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(CPA$Targets$target) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_solnClim <- prioritizr::solve.ConservationProblem(p1) splnr_plot_climKernelDensity(dat_solnClim, type = \"Basic\") splnr_plot_climKernelDensity(soln = list(dat_solnClim), names = c(\"Input 1\"), type = \"Normal\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_comparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot solution comparison — splnr_plot_comparison","title":"Plot solution comparison — splnr_plot_comparison","text":"Conservation planning often requires comparison outputs solutions different conservation problems. One way compare solutions spatially visualising different planning units selected two separate solutions conservation problems. splnr_plot_comparison() allows map differences two solutions customisable way using ggplot2. function requires two separate sf objects containing solution_1 column indicating binary solution (selected vs selected) prioritizr conservation problem. outputs ggobject can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_comparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot solution comparison — splnr_plot_comparison","text":"","code":"splnr_plot_comparison(   soln1,   soln2,   legendTitle = \"Scenario 2 compared to Scenario 1:\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_comparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot solution comparison — splnr_plot_comparison","text":"soln1 first prioritizr solution soln2 second prioritizr solution legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_comparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot solution comparison — splnr_plot_comparison","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_comparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot solution comparison — splnr_plot_comparison","text":"","code":"# 30 % target for problem/solution 1 dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  # 50 % target for problem/solution 2 dat_problem2 <- prioritizr::problem(   dat_species_bin %>%     dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.5) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln2 <- dat_problem2 %>%   prioritizr::solve.ConservationProblem()  (splnr_plot_comparison(dat_soln, dat_soln2))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_corrMat.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot correlation matrices — splnr_plot_corrMat","title":"Plot correlation matrices — splnr_plot_corrMat","text":"Conservation planning often requires comparison outputs solutions different conservation problems. One way compare solutions correlating solutions using Cohen's Kappa. splnr_plot_corrMat() allows visualize correlation matrix different solutions (example produced spatialplanr function splnr_get_kappaCorrData()).","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_corrMat.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot correlation matrices — splnr_plot_corrMat","text":"","code":"splnr_plot_corrMat(   x,   colourGradient = c(\"#BB4444\", \"#FFFFFF\", \"#4477AA\"),   legendTitle = \"Correlation \\ncoefficient\",   AxisLabels = NULL,   plotTitle = \"\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_corrMat.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot correlation matrices — splnr_plot_corrMat","text":"x correlation matrix prioritizr solutions colourGradient list three colour values high positive, high negative correlation legendTitle character value title legend. Can empty (\"\"). AxisLabels list labels solutions correlated (Default: NULL). Length needs match number correlated solutions. plotTitle character value title plot. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_corrMat.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot correlation matrices — splnr_plot_corrMat","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_corrMat.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot correlation matrices — splnr_plot_corrMat","text":"","code":"# 30 % target for problem/solution 1 dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  # 50 % target for problem/solution 2 dat_problem2 <- prioritizr::problem(   dat_species_bin %>%     dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.5) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln2 <- dat_problem2 %>%   prioritizr::solve.ConservationProblem()  CorrMat <- splnr_get_kappaCorrData(list(dat_soln, dat_soln2), name_sol = c(\"soln1\", \"soln2\")) #> New names: #> • `soln1` -> `soln1...1` #> • `soln1` -> `soln1...2` #> New names: #> • `soln2` -> `soln2...1` #> • `soln2` -> `soln2...2` #> New names: #> • `` -> `...1` #> • `` -> `...2`  (splnr_plot_corrMat(CorrMat, AxisLabels = c(\"Solution 1\", \"Solution 2\"))) #> Scale for fill is already present. #> Adding another scale for fill, which will replace the existing scale. #> Scale for x is already present. #> Adding another scale for x, which will replace the existing scale."},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_cost.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot cost — splnr_plot_cost","title":"Plot cost — splnr_plot_cost","text":"splnr_plot_cost() allows plot cost within planning units planning region customisable way using ggplot2. function requires sf object cost column outputs ggobject. can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_cost.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot cost — splnr_plot_cost","text":"","code":"splnr_plot_cost(   Cost,   Cost_name = \"Cost\",   legendTitle = \"Cost\",   paletteName = \"YlGnBu\",   plotTitle = \"\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_cost.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot cost — splnr_plot_cost","text":"Cost sf object cost prioritizr Cost_name Name cost column legendTitle character value title legend. Can empty (\"\"). paletteName string (number) color palette use. Available palettes can found https://ggplot2.tidyverse.org/reference/scale_brewer.html. plotTitle character value title plot. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_cost.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot cost — splnr_plot_cost","text":"ggplot object plot","code":""},{"path":[]},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_cost.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot cost — splnr_plot_cost","text":"","code":"if (FALSE) { # \\dontrun{ dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  dat_cost <- dat_soln %>%   dplyr::mutate(Cost = runif(n = dim(.)[[1]]))  (splnr_plot_cost(dat_cost)) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_costOverlay.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot cost overlay — splnr_plot_costOverlay","title":"Plot cost overlay — splnr_plot_costOverlay","text":"splnr_plot_costOverlay() allows plot cost planning units planning region top solution conservation problem created prioritizr customisable way using ggplot2. function requires solution sf object column called solution_1 well cost column outputs ggobject. can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_costOverlay.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot cost overlay — splnr_plot_costOverlay","text":"","code":"splnr_plot_costOverlay(   soln,   Cost = NA,   Cost_name = \"Cost\",   legendTitle = \"Cost\",   plotTitle = \"Solution overlaid with cost\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_costOverlay.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot cost overlay — splnr_plot_costOverlay","text":"soln prioritizr solution Cost sf object cost prioritizr.case prioritizrsolution contain cost, alternative cost object provided used generate solution (default: NA). Cost_name Name cost column legendTitle character value title legend. Can empty (\"\"). plotTitle character value title plot. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_costOverlay.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot cost overlay — splnr_plot_costOverlay","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_costOverlay.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot cost overlay — splnr_plot_costOverlay","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  splnr_plot_costOverlay(soln = dat_soln)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot number of features — splnr_plot_featureNo","title":"Plot number of features — splnr_plot_featureNo","text":"splnr_plot_featureNo() allows use ggplot2 visually inspect number features per planning unit used inputs conservation problem. features species, map can seen visualisation species richness planning region.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot number of features — splnr_plot_featureNo","text":"","code":"splnr_plot_featureNo(   df,   showLegend = TRUE,   paletteName = \"YlGnBu\",   plotTitle = \"Number of Features\",   legendTitle = \"Features\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot number of features — splnr_plot_featureNo","text":"df sf object features showLegend logical command whether show legend solution (Default: TRUE). paletteName string (number) color palette use. Available palettes can found https://ggplot2.tidyverse.org/reference/scale_brewer.html. plotTitle character value title plot. Can empty (\"\"). legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot number of features — splnr_plot_featureNo","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot number of features — splnr_plot_featureNo","text":"function requires sf object binary information features want include richness plot (0 absences 1 presences, example created continuous data spatialplanr function splnr_apply_cutoffs()). outputs ggobject can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureNo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot number of features — splnr_plot_featureNo","text":"","code":"if (FALSE) { # \\dontrun{ (splnr_plot_featureNo(dat_species_bin)) } # }"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureRep.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot how well targets are met — splnr_plot_featureRep","title":"Plot how well targets are met — splnr_plot_featureRep","text":"Plot well targets met","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureRep.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot how well targets are met — splnr_plot_featureRep","text":"","code":"splnr_plot_featureRep(   df,   category = NA,   categoryFeatureCol = NA,   renameFeatures = FALSE,   namesToReplace = NA,   nr = 1,   showTarget = NA,   plotTitle = \"\",   ... )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureRep.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot how well targets are met — splnr_plot_featureRep","text":"df df containing target information (resulting splnr_get_featureRep() function) category named data frame feature category grouping plot output categoryFeatureCol character column containing feature infromation plotted category data frame contain column named 'feature' can matched 'df' infromation. renameFeatures logical whether variable names used replaced common names namesToReplace data frame containing variable name ('nameVariable') common name ('nameCommon'). nr Number rows legend showTarget logical targets shown bar plot plotTitle character value title plot. Can empty (\"\"). ... arguments passed ggplot2::theme()","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureRep.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot how well targets are met — splnr_plot_featureRep","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_featureRep.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot how well targets are met — splnr_plot_featureRep","text":"","code":"pDat <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  soln <- pDat %>%   prioritizr::solve.ConservationProblem()   # including incidental species coverage df <- splnr_get_featureRep(   soln = soln,   pDat = pDat )  (splnr_plot_featureRep(df, category = dat_category))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot importance score — splnr_plot_importanceScore","title":"Plot importance score — splnr_plot_importanceScore","text":"Importance scores mean reflect irreplaceability planning unit solution prioirtizr conservation problem. Based prioritizr package, splnr_plot_importanceScore() allows visualize three different types importance scores ggplot2 used based conservation problem hand. prioritizr development team generally recommend using replacement cost score, however might feasible conservation problems many planning units features.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot importance score — splnr_plot_importanceScore","text":"","code":"splnr_plot_importanceScore(   soln,   pDat,   method = \"Ferrier\",   plotTitle = \"\",   colorMap = \"A\",   decimals = 4,   legendTitle = \"Importance Score\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot importance score — splnr_plot_importanceScore","text":"soln prioritizr solution pDat prioritizr problem method method calcualting importance scores. Can either \"Ferrier\" Ferrier Score, can used minimum set objective function, \"RWR\" Rarity Weighted Richness Score, \"RC\" Replacement Cost takes longer approaches due iterative process. plotTitle character value title plot. Can empty (\"\"). colorMap character string indicating color map use (see https://ggplot2.tidyverse.org/reference/scale_viridis.html options) decimals number decimals shown plot. Ferrier Score often requires higher number decimals (>4) two approaches (2) analysis work. legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot importance score — splnr_plot_importanceScore","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot importance score — splnr_plot_importanceScore","text":"function outputs ggobject can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_importanceScore.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot importance score — splnr_plot_importanceScore","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  (splnr_plot_importanceScore(soln = dat_soln, pDat = dat_problem, method = \"Ferrier\", decimals = 4)) #> Ferrier Score. #> Warning: conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for <e2> #> Warning: conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for <89> #> Warning: conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for <a5> #> Warning: conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for <e2> #> Warning: conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for <89> #> Warning: conversion failure on '≥0.0038 ' in 'mbcsToSbcs': dot substituted for <a5>"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_selectionFreq.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","title":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","text":"multiple spatial plans generated, often interested many times planning unit selected across array solutions. array can either made solutions different conservation problems generated portfolio approach prioritizr. Either way, function requires sf object input contains column (selFreq) selection frequency planning unit can generated spatialplanrfunction splnr_get_selFreq(). splnr_plot_selectionFreq() allows visualize selection frequency using ggplot2. outputs ggobject can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_selectionFreq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","text":"","code":"splnr_plot_selectionFreq(   selFreq,   plotTitle = \"\",   paletteName = \"Greens\",   legendTitle = \"Selection \\nFrequency\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_selectionFreq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","text":"selFreq sf object containing selection frequency planning unit array solutions plotTitle character value title plot. Can empty (\"\"). paletteName string (number) color palette use. Available palettes can found https://ggplot2.tidyverse.org/reference/scale_brewer.html. legendTitle character value title legend. Can empty (\"\").","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_selectionFreq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_selectionFreq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot selection frequency of a planning unit in an array of prioritisations — splnr_plot_selectionFreq","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  # create conservation problem that contains a portfolio of solutions dat_soln_portfolio <- dat_problem %>%   prioritizr::add_cuts_portfolio(number_solutions = 5) %>%   prioritizr::solve.ConservationProblem()  selFreq <- splnr_get_selFreq(solnMany = dat_soln_portfolio, type = \"portfolio\") (splnr_plot_selectionFreq(selFreq))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_solution.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot prioritizr solution — splnr_plot_solution","title":"Plot prioritizr solution — splnr_plot_solution","text":"splnr_plot_solution() allows plot solution prioritizr conservation problem without customisable way using ggplot2. function requires solution sf object column called solution_1 outputs ggobject. can combined spatialplanr function splnr_gg_add().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_solution.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot prioritizr solution — splnr_plot_solution","text":"","code":"splnr_plot_solution(   soln,   colorVals = c(\"#c6dbef\", \"#3182bd\"),   showLegend = TRUE,   legendLabels = c(\"Not selected\", \"Selected\"),   plotTitle = \"Solution\",   legendTitle = \"Planning Units\",   zones = FALSE )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_solution.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot prioritizr solution — splnr_plot_solution","text":"soln prioritizr solution colorVals list object named vectors match color value according name. \"TRUE\" stands selected planning units. showLegend logical command whether show legend solution (Default: TRUE). legendLabels Character values (number zones + 1) legend labelled. plotTitle character value title plot. Can empty (\"\"). legendTitle character value title legend. Can empty (\"\"). zones logical value, indicating whether spatial plan contains zones (default = FALSE).","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_solution.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot prioritizr solution — splnr_plot_solution","text":"ggplot object plot","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_plot_solution.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot prioritizr solution — splnr_plot_solution","text":"","code":"dat_problem <- prioritizr::problem(dat_species_bin %>% dplyr::mutate(Cost = runif(n = dim(.)[[1]])),   features = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   cost_column = \"Cost\" ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(0.3) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  dat_soln <- dat_problem %>%   prioritizr::solve.ConservationProblem()  splnr_plot_solution(dat_soln)  # example 2 t2 <- matrix(NA, ncol = 2, nrow = 5) # create targets t2[, 1] <- 0.1 t2[, 2] <- 0.05  z2 <- prioritizr::zones(   \"zone 1\" = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\"),   \"zone 2\" = c(\"Spp1\", \"Spp2\", \"Spp3\", \"Spp4\", \"Spp5\") ) # when giving sf input, we need as many cost columns as we have zones p2 <- prioritizr::problem(   dat_species_bin %>% dplyr::mutate(     Cost1 = runif(n = dim(.)[[1]]),     Cost2 = runif(n = dim(.)[[1]])   ),   z2,   cost_column = c(\"Cost1\", \"Cost2\") ) %>%   prioritizr::add_min_set_objective() %>%   prioritizr::add_relative_targets(t2) %>%   prioritizr::add_binary_decisions() %>%   prioritizr::add_default_solver(verbose = FALSE)  s2 <- p2 %>%   prioritizr::solve.ConservationProblem() (splnr_plot_solution(s2,   zones = TRUE, colorVals = c(\"#c6dbef\", \"#3182bd\", \"black\"),   legendLabels = c(\"Not selected\", \"Zone 1\", \"Zone 2\") ))"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_replace_NAs.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","title":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","text":"splnr_replace_NAs() allows replace NA values data value nearest neighbour. nearest neighbour determined using st_nearest_feature() sf package.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_replace_NAs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","text":"","code":"splnr_replace_NAs(df, vari)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_replace_NAs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","text":"df sf dataframe vari Variable remove NAs ","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_replace_NAs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","text":"sf object NAs replaced nearest neighbour","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_replace_NAs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Remove NAs from spatial data using nearest neighbour — splnr_replace_NAs","text":"","code":"df <- dat_species_prob %>%   splnr_replace_NAs(\"Spp2\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_scale_01.html","id":null,"dir":"Reference","previous_headings":"","what":"Scale spatial layers to between 0 and 1 — splnr_scale_01","title":"Scale spatial layers to between 0 and 1 — splnr_scale_01","text":"splnr_scale_01() allows re-scale data values greater 1 values 0 1.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_scale_01.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Scale spatial layers to between 0 and 1 — splnr_scale_01","text":"","code":"splnr_scale_01(dat, col_name)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_scale_01.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Scale spatial layers to between 0 and 1 — splnr_scale_01","text":"dat sf dataframe col_name Name column scale","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_scale_01.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Scale spatial layers to between 0 and 1 — splnr_scale_01","text":"sf dataframe","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_scale_01.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Scale spatial layers to between 0 and 1 — splnr_scale_01","text":"","code":"df <- dat_species_prob %>%   dplyr::mutate(Spp1 = Spp1 * 100) %>%   splnr_scale_01(col_name = \"Spp1\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byCategory.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign targets to all features by category — splnr_targets_byCategory","title":"Assign targets to all features by category — splnr_targets_byCategory","text":"splnr_targets_byCategory() allows assign targets conservation planning based species categories.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byCategory.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign targets to all features by category — splnr_targets_byCategory","text":"","code":"splnr_targets_byCategory(dat, catTarg, catName = \"Category\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byCategory.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign targets to all features by category — splnr_targets_byCategory","text":"dat sf object features categories catTarg named character vector categories target catName optional argument name category column dat","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byCategory.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign targets to all features by category — splnr_targets_byCategory","text":"sf object targets added","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byCategory.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign targets to all features by category — splnr_targets_byCategory","text":"","code":"dat <- splnr_targets_byCategory(   dat = dat_category,   catTarg = c(\"Group1\" = 0.5, \"Group2\" = 0.2),   catName = \"category\" )"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byIUCN.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","title":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","text":"splnr_targets_byIUCN() allows assign targets species used conservation planning based IUCN categories. Species can extracted based IUCN categories spatoalplnrfunction splnr_get_IUCNRedList(). Accessing IUCN database requires login token rl_use_iucn() needs added environment using Sys.setenv(IUCN_REDLIST_KEY = \"[Token]\"). can start running rredlist::rl_use_iucn().","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byIUCN.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","text":"","code":"splnr_targets_byIUCN(dat, IUCN_target, IUCN_col = \"IUCN_Category\")"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byIUCN.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","text":"dat dataframe sf object IUCN categories IUCN_target Either numeric named numeric targets apply IUCN categories IUCN_col Optional string indicate name column IUCN categories","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byIUCN.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","text":"dataframe sf object","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byIUCN.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign targets bu IUCN Red List categories — splnr_targets_byIUCN","text":"","code":"dat <- data.frame(IUCN_Category = c(\"EW\", \"EX\", NA), target = c(0.3, 0.3, 0.3)) IUCN_target <- c(\"EX\" = 0.8, \"EW\" = 0.6) dat <- splnr_targets_byIUCN(dat, IUCN_target)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byInverseArea.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign targets by Inverse Area — splnr_targets_byInverseArea","title":"Assign targets by Inverse Area — splnr_targets_byInverseArea","text":"function takes min (target_min) max (target_max) target range calculates inverse area target feature based areal coverage.","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byInverseArea.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign targets by Inverse Area — splnr_targets_byInverseArea","text":"","code":"splnr_targets_byInverseArea(df, target_min, target_max)"},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byInverseArea.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign targets by Inverse Area — splnr_targets_byInverseArea","text":"df sf dataframe features calculate target_min minimum target inverse area target_max maximum target inverse area","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byInverseArea.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign targets by Inverse Area — splnr_targets_byInverseArea","text":"sf dataframe Inverse Area Targets added Target","code":""},{"path":"https://mathmarecol.github.io/spatialplanr/reference/splnr_targets_byInverseArea.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign targets by Inverse Area — splnr_targets_byInverseArea","text":"","code":"targets <- dat_species_prob %>%   splnr_targets_byInverseArea(target_min = 0.3, target_max = 0.8)"}]
