Data and code for: "Natural History Collections at the Crossroads: Shifting Priorities and Data-Driven Opportunities"

# Wombat Value of Information (VOI) Analysis This repository contains the code and data for the manuscript "Natural History Collections at the Crossroads: Shifting Priorities and Data-Driven Opportunities" Owen Forbes1*, Peter H. Thrall1, Andrew G. Young1, Cheng Soon Ong2 1 CSIRO National Research Collections Australia, Canberra, ACT 2601, Australia 2 CSIRO Data61, Canberra, ACT 2601, Australia *Corresponding author: [e-mail] ## Repository Overview This project applies a Value of Information (VOI) analytical framework to wombat occurrence data from GBIF. It demonstrates a novel research prioritisation approach that integrates: - **Value of Information (VOI)**: Expected information gain from additional observations- **Need for Information (NFI)**: Habitat condition/loss metrics- **Cost of Information (COI)**: Remoteness areas affecting sampling feasibility The analysis uses a binomial model as a simple species distribution model, to evaluate the research value of new wombat observations across different locations in NSW and ACT, Australia. ## Repository Structure The repository consists of one main Quarto (.qmd) script and associated data files: - `Wombats_VOI.qmd`: Primary analysis script containing data cleaning, modelling, and visualisation ## Data Files ### GBIF Wombat Occurrence Data- `0014630-250127130748423.csv` - GBIF wombat occurrence export (download available from: https://www.gbif.org/occurrence/download/0014630-250127130748423 ) ### Environmental and Administrative Data- `HCAS31_AHC_2020_2022_NSW_50km_3577.tif` - Habitat condition raster for NSW (from CSIRO Habitat Condition Assessment System - subset of full dataset available from https://data.csiro.au/collection/csiro%3A63571v7 )- `RA_2021_AUST_GDA2020` - ABS Remoteness Areas 2021 shapefile (folder containing multiple files - available from https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files Specficic shapefile URL: https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files/RA_2021_AUST_GDA2020.zip ) ## Requirements - R (version 4.3.2 or later)- Required R packages: - tidyverse (v2.0.0) - for data manipulation and visualization - sf (v1.0-16) - for spatial data handling - lubridate (v1.9.3) - for date handling - raster (v3.6-26) - for raster data handling - ozmaps (v0.4.5) - for Australian state boundaries - terra (v1.7-71) - for efficient raster processing - exactextractr (v0.10.0) - for exact extraction from raster to polygons - patchwork (v1.2.0) - for combining plots - corrplot (v0.92) - for correlation matrix visualization - RColorBrewer (v1.1-3) - for color palettes - gridExtra (v2.3) - for arranging multiple plots - grid - for low-level graphics (base R) Install these packages before running the script. ## Analysis Process The analysis follows these key steps: 1. **Data Cleaning** - Filter to NSW and ACT wombat records - Remove records with high uncertainty (>10km) - Create a 50km grid system across NSW and ACT 2. **Temporal Analysis** - Calculate presence/absence of wombats in each grid cell by year - Determine empirical observation probability for each grid cell - Analyse temporal stability using 5-year sliding windows 3. **Value of Information Calculation** - Calculate expected information gain through KL divergence - Simulate adding new observations using the binomial model - Map VOI across NSW and ACT 4. **Need for Information Integration** - Import and process habitat condition data - Convert to habitat loss metric (NFI) - Integrate with VOI analysis 5. **Cost of Information** - Process remoteness area data as a proxy for sampling cost - Map remoteness areas across the study region 6. **Combined Analysis** - Create quadrant analysis combining VOI and NFI - Generate comprehensive visualisations of all three metrics ## How to Use 1. Download this repository to your local machine.2. Set your working directory to the location of the script.3. Ensure all required R packages are installed.4. Run the script in RStudio or your preferred R environment. ## Outputs The primary output is `combined_quadrant_analysis_100425.png`, which displays four panels:1. Value of Information (VOI) - Expected information gain across the study area2. Need for Information (NFI) - Habitat loss percentiles3. Cost of Information (COI) - Remoteness areas as a proxy for sampling cost4. VOI vs NFI Quadrant Analysis - Relationship between information value and need ## Citation If you use this code or methodology, please cite: Forbes, O., Thrall, P.H., Young, A.G., Ong, C.S. (2025). Natural History Collections at the Crossroads: Shifting Priorities and Data-Driven Opportunities. [Journal information pending]