Readme

Licenses

Source code is © 2017-2024 by Philip Dyer and Claire Davies, and is licensed under GPL-3.0-only.

Documentation © 2017-2024 by Philip Dyer and Claire Davies, and is licensed under CC-BY-4.0.

All data in this repository is contained in CSV files.

Data were sourced from Australia’s Integrated Marine Observing System (IMOS) – IMOS is enabled by the National Collaborative Research Infrastructure Strategy (NCRIS). It is operated by a consortium of institutions as an unincorporated joint venture, with the University of Tasmania as Lead Agent.

IMOS and AODN provided the data under the CC-BY-4.0 licence, the data was further processed by Claire Davies, and is provided here under the CC-BY-4.0 license with permission from Claire Davies.

Overview

Code and data in this folder are made available for reproducing the thesis Novel methods for developing large-scale, data-driven, biologically informed bioregionalisations.

For updates to this code, see https://github.com/MathMarEcol/aus_cpr_for_bioregions

Phytoplankton and Zooplankton CPR data around Australia

This folder contains data and scripts for generating long form data.frames.

The data covers a range of surveys (ProjectNumber), and provides the Latitude, Longitude, SampleDateUTC of each sample.

At each sample site, taxa (TaxonGroup, TaxonName) with non-zero abunances are listed, in counts per cubic meter (ZAbund_m3).

Each survey uses different methodology and searched for different taxa, so pivoting to wide format must be done separately for each survey to avoid absences caused by a taxa simply not being searched for by a survey. Additionally, different methodology means that ZAbund_m3 are not comparable across surveys, even if the taxon is present in both surveys.

Usage

  library(lutz)
  library(glue)
  library(lubridate)
  library(data.table)
  library(tidyverse)
##full path to current directory
root_dir <- "/QRISdata/Q1215/AusCPR/"
stopifnot(
  file.exists(glue::glue("{root_dir}/phyto_other_phil_feb21.csv")),
  file.exists(glue::glue("{root_dir}/Brett_data_feb2020.csv")),
  file.exists(glue::glue("{root_dir}/zoop_phil_feb21.csv")),
  file.exists(glue::glue("{root_dir}/PhytoDataPhilFeb21.R")),
  file.exists(glue::glue("{root_dir}/zooDataPhilMar21.R"))
  )


source(glue::glue("{root_dir}/PhytoDataPhilFeb21.R"))

phyto_df <- load_phyto_data(root_dir)

source(glue::glue("{root_dir}/zooDataPhilMar21.R"))

zoo_df <- load_zoo_data(root_dir)