Completing issue oceanhackweek#13

README.md

@@ -58,7 +58,7 @@ This tutorial is based on the [notes by Ben Tupper (Biglow Lab, Maine)](https://
 
 - OBIS (2023) Ocean Biodiversity Information System. Intergovernmental Oceanographic Commission of UNESCO. [www.obis.org](https://obis.org/). Accessed: 2023-08-08.  
 
-- Steven J. Phillips, Miroslav Dudík, Robert E. Schapire. [Internet] Maxent software for modeling species niches and distributions (Version 3.4.1). Available from url: [http://biodiversityinformatics.amnh.org/open_source/maxent/](http://biodiversityinformatics.amnh.org/open_source/maxent/). Accessed on 2023-8-10.  
+- Steven J. Phillips, Miroslav Dudík, Robert E. Schapire. [Internet] Maxent software for modeling species niches and distributions (Version 3.4.1). Available from url: [http://biodiversityinformatics.amnh.org/open_source/maxent/](http://biodiversityinformatics.amnh.org/open_source/maxent/). Accessed on 2023-08-10.  
 
 ## Tutorial developers
 - [Catherine Courtier](https://github.com/cacourtier):

index.md

@@ -12,34 +12,33 @@ Click to hear our song! Inspired by Myranda and AI!
 
 ## Overview
 This tutorial was developed during [OceanHackWeek2023](https://oceanhackweek.org/) to provide a simple workflow to developing a marine Species Distribution Model (SDM) using `R` programming. 
-
-
-
+
 ## Background
-
-Species Distribution Models are used to predict a species' geographic and environmental range, typically incorporating environmental data into the analysis. 
-
+Species Distribution Modelling (SDM) also known as niche/environmental/ecological modelling uses an algorithm to predict the distribution of a species across space and time using environmental data. An understanding of the relationship between the species of interest and the physical environment they occupy will inform the selection of relevant environmental factors that will be included in the model.  
+
+Biotic information is also needed by SDMs and at the very least locations of individuals are needed. Abundance or densities can also be used as inputs, but are not compulsory. It is worth noting that absences, that is, the locations where individuals of a species are **NOT** present is just as important because it provides information about the environmental conditions where individuals are not usually sighted. Often absences are not recorded in biological data, but we can use *background points* (also known as pseudo-absences), which provide information about the full range of environmental conditions available for the species interest in our study area.  
+
+For a review of the performance of different SDM algorithms, see the following publications:  
+- Valavi, Guillera-Arroita, Lahoz-Monfort, Elith (2021). Predictive performance of presence-only species distribution models: a benchmark study with reproducible code. DOI: [10.1002/ecm.1486](https://doi.org/10.1002/ecm.1486)  
+
+- Elith et al (2006). Novel methods improve prediction of species’ distributions from occurrence data. DOI: [10.1111/j.2006.0906-7590.04596.x](https://doi.org/10.1111/j.2006.0906-7590.04596.x)  
 
 ## Goals
-Many tutorials exist to run SDM models, however most readily available tutorials focus on terrestrial-based models. Our goal through this tutorial is to highlight a marine-based SDM tutorial.
+Many tutorials exist to run SDM models, however, most readily available tutorials focus on terrestrial-based models. Our goal through this tutorial is to highlight a marine-based SDM tutorial.  
 
 ## Datasets
 
-**Biological Data**
-
-Our dataset includes biological presence-only data of four species of sea turtles found in the Indian Ocean. The presence dataset includes four species of sea turtles:
-
+### **Biological Data**
+Our dataset includes biological presence-only data of four species of sea turtles found in the Indian Ocean. The four species of sea turtles included in our tutorial are:  
 - Loggerhead, *Caretta caretta*
 - Green, *Chelonia mydas*
 - Olive Ridley, *Lepidochelys olivacea*
 - Hawksbill, *Eretmochelys imbricata*
+
+However, for this tutorial example model, we will focus on Loggerhead sea turtles data from 2000 until 2023 sourced from the Ocean Biodiversity Information System (OBIS) via the `robis` package.  
 
-However, for this tutorial example model, we will focus on Loggerhead sea turtles data from 2000 until 2023 sourced from the Ocean Biodiversity Information System (OBIS) via the `robis` package.
-
-
-**Environmental Data**
-
-This tutorial focuses on regions in the northern Indian Sea, specifically the western Arabian Sea, Persian Gulf, Gulf of Oman, Gulf of Aden and Red Sea. Environmental predictor variables were sourced via the `SMDpredictor` R package and includes:
+### **Environmental Data**
+This tutorial focuses on regions in the northern Indian Sea, specifically the western Arabian Sea, Persian Gulf, Gulf of Oman, Gulf of Aden and Red Sea. Environmental predictor variables were sourced via the `SMDpredictor` R package and includes:  
 
 -ENTER ALL FINAL PREDICTORS INCLUDED HERE
 
@@ -63,14 +62,13 @@ This tutorial is based on the [notes by Ben Tupper (Biglow Lab, Maine)](https://
 
 
 ## References
-
-- Bosch S, Fernandez S (2022). sdmpredictors: Species Distribution Modelling Predictor Datasets. R package version 0.2.14, [http://lifewatch.github.io/sdmpredictors/](http://lifewatch.github.io/sdmpredictors/).
-- OBIS (2023) Ocean Biodiversity Information System. Intergovernmental Oceanographic Commission of UNESCO. [www.obis.org](https://obis.org/). Accessed: 2023-08-08.
-
-- Steven J. Phillips, Miroslav Dudík, Robert E. Schapire. [Internet] Maxent software for modeling species niches and distributions (Version 3.4.1). Available from url: [http://biodiversityinformatics.amnh.org/open_source/maxent/](http://biodiversityinformatics.amnh.org/open_source/maxent/). Accessed on 2023-8-10.
+- Bosch S, Fernandez S (2022). sdmpredictors: Species Distribution Modelling Predictor Datasets. R package version 0.2.14, [http://lifewatch.github.io/sdmpredictors/](http://lifewatch.github.io/sdmpredictors/).  
+  
+- OBIS (2023) Ocean Biodiversity Information System. Intergovernmental Oceanographic Commission of UNESCO. [www.obis.org](https://obis.org/). Accessed: 2023-08-08.  
+  
+- Steven J. Phillips, Miroslav Dudík, Robert E. Schapire. [Internet] Maxent software for modeling species niches and distributions (Version 3.4.1). Available from url: [http://biodiversityinformatics.amnh.org/open_source/maxent/](http://biodiversityinformatics.amnh.org/open_source/maxent/). Accessed on 2023-08-10.  
 
 ## Tutorial developers
-
 - [Catherine Courtier](https://github.com/cacourtier):
 - [Mackenzie Fiss](https://github.com/mackenziefiss): Third-year PhD student at Northeastern University studying marine biogeochemistry (DOM) and microbial ecology.
 - [Denisse Fierro Arcos](https://github.com/lidefi87): PhD candidate at the [Institute for Marine and Antarctic Studies (IMAS)](https://www.imas.utas.edu.au/) and Data Officer at the [Integrated Marine Observing System (IMOS)](https://imos.org.au/)   
@@ -79,10 +77,10 @@ This tutorial is based on the [notes by Ben Tupper (Biglow Lab, Maine)](https://
 - [Jade Hong](https://github.com/sjhong0117): 
 - [Tylar Murray](https://github.com/7yl4r): USF IMaRS Software Engineer - code whisperer, data viz enthusiast, scientific generalist, compulsive overengineerer, & UX PhD  
 - [Caitlin O'Brien](https://github.com/caitobrien): Research Scientist, [Columbia Basin Research](https://www.cbr.washington.edu/people), School of Aquatic Fishery and Sciences, University of Washington
-- [Collins Ongore] () 
+- Collins Ongore
 - [Mary Solokas](https://github.com/marysolokas): John A. Knauss Marine Policy Fellow, National Oceanic and Atmospheric Administration
 - [Laura Tsang](https://github.com/lauratsang):
-- [Ben Tupper](https://github.com/btupper):
+- [Ben Tupper](https://github.com/btupper): Senior Research Associate at [Bigelow Laboratory for Ocean Science](https://github.com/BigelowLab)
 
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