Bonat et al 2025. Seasonal habitat selection in an arboreal mammal identifies landscape characteristics that improve species resilience under climate change: Data and R scripts

These are the datasets utilised in Bonat et al (2025) Seasonal habitat selection in an arboreal mammal identifies landscape characteristics that improve species resilience under climate change.

We used local temperature data to assess habitat selection in an arboreal mammal. Species occupying the forest canopy are highly exposed to environmental conditions such as wind and solar radiation but can exploit shelter trees and gullies for protection. This provides an opportunity to better understand the role of microclimates in conservation planning.

We first combined seasonal GPS location data from collared koalas with publicly available remote sensing data to model habitat selection across two highly biodiverse sites in a World Heritage in NSW, Australia. We compared results to a finer-scale model using local temperature data from microclimates.
The repository contains processed datasets (Excel format) and R scripts (zip folder) used to conduct the analyses. Due to file size constraints, spatial map layers are not included.
Repository structure and usage
To reproduce the analyses, users should create an RStudio Project and organise the files using the following directory structure:
project_root/
├── project_name.Rproj
├── data/
├── figures/
├── Rscripts/

Place all provided .xlsx data files in the data/ directoryExtract all provided R scripts in the Rscripts/ directoryOutput figures generated by the scripts will be written to the figures/ directoryThe R scripts assume the project root is set as the working directory via the .Rproj file. Spatial map layers referenced in the scripts are derived from publicly available remote sensing data but are not included in this repository.