Data for: Beggars Can't be Choosers: Feral Buffalo Show More Constrained Movement and Resource Selection During the Dry Season in the Northern Territory

The code, data, and R objects in this repository accompany a paper titled 'Beggars Can’t be Choosers: Feral Buffalo Show More Constrained Movement and Resource Selection During the Dry Season in the Northern Territory '. This dataset supports the publication on seasonal movement and habitat selection patterns of feral water buffalo (Bubalus bubalis) in the Djelk Indigenous Protected Area, Northern Territory, Australia. The study aimed to inform evidence-based, adaptive management of this invasive species by examining how buffalo respond to environmental factors such as water availability, vegetation structure, fire history, and habitat types. The dataset includes the GPS data of 17 adult female buffalo over a 15-month period at hourly intervals paired with environmental covariates for both used and available (simulated GPS locations) to fit integrated step selection functions and model habitat selection. The R scipts, and accompanying data detail the modelling process from data pre-processing, movement model fitting and habitat selection analysis. File description Scripts Buffalo_issf_zenodo.Rmd used to sample random steps and extract covariate values at the start and end of each step outputs buftrk.Rdata buffalo_data_prep_SF removes phenological cateories with few steps (leading to model instabilities) and reduces the number of random steps for computational efficiency inputs buftrk.Rdata outputs pheno_start_end_dat_ssf10rs_2024-03-14.csv nbr_lag_SF.R extracts NBR values are different monthly lags inputs: NBR tifs (raw values and mask layers) outputs pheno_start_end_dat_NBR_lag_NAFImask_ssf10rs_2024-03-21.csv buffalo_population_ssf_nbr_NAFImask_dry.R fits iSSF models to continuous landscape variables (NDVI, NBR etc) in the dry season inputs: pheno_start_end_dat_NBR_lag_NAFImask_ssf10rs_2024-03-21.csv buffalo_population_ssf_nbr_NAFImask_wet.R fits iSSF models to continuous landscape variables (NDVI, NBR etc) in the dry season inputs: pheno_start_end_dat_NBR_lag_NAFImask_ssf10rs_2024-03-21.csv nbr_model_plotting.qmd plots the models fitted in the scripts above has rendered file: nbr_model_plotting.html veg_model_plotting.qmd fits iSSF models to categorical habitat variables (wet and dry season models) inputs: pheno_start_end_dat_ssf10rs_2024-03-14.csv has rendered file: veg_model_plotting.html