https://doi.org/10.5061/dryad.s1rn8pk9w

This README file lists the supplementary datasets, shapefiles, rasters, and R code used in the associated paper. It also provides a brief description of how each file was used in generating the results, and definitions for any abbreviated variables within datasets. Note: dates are all in the format ‘date-month-year’. 

Description of the data and file structure

Shapefiles.zip (and auxiliary files):

Sanctuary fenceline.shp

• Sanctuary fenceline.qpj
• Sanctuary fenceline.prj
• Sanctuary fenceline.dbf
• Sanctuary fenceline.cpg
• Sanctuary fenceline.shx

water sources.shp

• water sources.shx
• water sources.prj
• water sources.dbf
• water sources.cpg

Roads.shp

• Roads.shx
• Roads.prj
• Roads.dbf
• Roads.cpg

Individual Minimum Convex Polygons (MCPs):

Minimum convex polygons (MCPs) were generated for individual bilbies tracked in each season using movement data collected once during the day while resting (to a burrow), and several locations, while active at night. There are two ‘MCP’ files per bilby, per season. One shapefile is the raw polygon (Bilby Name.shp) and the other is the polygon with unavailable areas removed (i.e. actual area available) such as buildings and enclosed areas (Bilby Name_MCP_Available.shp). Parentheses indicate the number of bilby MCP shapefiles in each folder (excluding auxiliary files). The shapefiles are used to calculate MCP area in the associated paper and can be used in conjunction with the ‘third-order_RSF.R’ script. Metadata for bilbies can be found in the bilby_metadata.csv file.

Individual MCPs.zip

• MCPs_autumn2020 (30)
• MCPs_autumn2021 (16)
• MCPs_spring (18)
• MCPs_summer2020 (28)
• MCPs_summer2021 (21)
• MCPs_winter (20)

Rasters:

These include processed (i.e. clipped) soil texture data originally obtained from the SEED portal (State of New South Wales, Office of Environment and Heritage, 2018). Raw soil texture data has been clipped to the sanctuary extent by creating a bounding box around the sanctuary in QGIS. Seasonal food biomass rasters generated from the ‘Interpolation.R’ scripts are also provided. Rasters need to be in your working directory to run the ‘Third-order_RSF.R’ script.

Note: all shapefiles and rasters are projected to GDA94 / MGA zone 55 (EPSG:28355; https://epsg.io/28355) and units are in meters.

Rasters.zip

Soil type

• soil_silt_0_30_clipped.tif
• soil_sand_0_30_clipped.tif
• soil_clay_0_30_clipped.tif

Terrestrial invertebrate biomass (for each season)

• raster_Sum21.tif
• raster_Sum21.tfw
• raster_Sum20.tif
• raster_Sum20.tfw
• raster_Spr20.tif
• raster_Spr20.tfw
• raster_Win20.tif
• raster_Win20.tfw

Subterranean invertebrate biomass (for each season)

• raster_Sum21_soil.tif
• raster_Sum21_soil.tfw
• raster_Sum20_soil.tif
• raster_Sum20_soil.tfw
• raster_Spr20_soil.tif
• raster_Spr20_soil.tfw
• raster_Win20_soil.tif
• raster_Win20_soil.tfw

Subterranean plant biomass (for each season)

• raster_Sum21_plants.tif
• raster_Sum21_plants.tfw
• raster_Sum20_plants.tif
• raster_Sum20_plants.tfw
• raster_Spr20_plants.tif
• raster_Spr20_plants.tfw
• raster_Win20_plants.tif
• raster_Win20_plants.tfw

Data.zip

bilby_metadata.csv

Seasonal home range area (in m2 and hectares) determined from the 100% minimum convex polygon (MCP) around all locations collected for each individual bilby (indicated under ‘bilby_ID’) in summer, spring, winter and autumn. Number of observations included in the calculation of 100% MCPs is indicated under the ‘days_obs’ column. Whether the bilby was born within the sanctuary (W) or was a founder released to the sanctuary (C) and whether they are male (M) or female (F) is also provided.

biomass.csv

Food biomass (g/m2) data obtained from the sanctuary over four seasons and 16 sampling sites. Biomass was calculated by dividing the total mass (g) of food collected within a site and season by the sample area (m2). For assessing terrestrial invertebrate biomass (Type = “TER”), invertebrates were captured in five pitfall traps, within a 5 m2 sample area, over seven consecutive nights each season. For assessing subterranean invertebrates and plant material (seed, roots, and bulbs) biomass (Type = “SOIL”), soil cores were removed from a 1 m2 quadrat in five randomly selected locations for each site and season. More detail on the methods used for sampling can be found in the supplementary information and below (Table 1; Figure 2 in the main text of the associated paper). This data can be used to generate the interpolation rasters, and to replicate biomass comparisons described in the supplementary information to the associated paper.
 
Table 1: A description of the variables used and their units of measurement (if applicable).

weather.csv

Daily rainfall (mm) and maximum temperatures (°C) over the two years of this study (2020–2021) and drought year prior (2019). Data can be used to generate Figure A1 presented in the supplementary information.

Coefficient-Est-Results.csv

Results from the generalised linear mixed model for each sampling period including a unique number for each season/sampling period (seasonID) in ascending order from the oldest to most recent period, the predictors specified in the model (see Table 2 for abbreviations used), the coefficient estimate (estimate) for each predictor, the standard error (se) of the estimate, the lower 95% confidence interval (lcl), and upper 95% confidence level (ucl) of the estimate, the reference level for the model (sex), the p-value, and whether there was a significant result (signif) as either a yes (Y) or no (N). Where sex = F the reference level was female for the corresponding model. Where sex = M the reference level was male for the corresponding model.

Table 2: Predictor abbreviations and their meaning.

Note: a ‘*’ between two predictors indicates an interaction term.

Sharing/Access information

Soil texture data was derived from the following source:

State of New South Wales and Office of Environment and Heritage. 2018. Digital soil mapping of key soil properties over New South Wales. Version 1.2. https://datasets.seed.nsw.gov.au/dataset/digital-soil-maps-for-key-soil-properties-over-nsw. Office of Environment and Heritage, Sydney, Australia.

Weather data was derived from the following source:

Bureau of Meteorology (Australia). 2022. Climate data online. http://www.bom.gov.au/climate/averages/tables/cw_065070.shtml. Accessed 19 May 2022.

Code/Software

R code.zip

Biomass_comp.R

Annotated R script is provided to generate Figure A5 presented in the supplementary information. The code also contains methods for food biomass comparisons described in Appendix of the main paper. For the code to run, you will need to have the ‘biomass.csv’ file in your working directory.

Interpolation.R

Annotated R script is provided to replicate the food biomass interpolation rasters. You will need to have the ‘biomass.csv’ file in your working directory for the code to run.

Weather.R

Annotated R script is provided to generate Figure A1 presented in the supplementary information. For the code to run, you will need to have the ‘weather.csv’ file in your working directory.

Coefficient-Est-Plots.R

Annotated R script is provided to generate Figure 4 presented in the main text. For the code to run, you will need to have the ‘Coefficient-Est-Results.csv’ file in your working directory.

Third-order_RSF.R*

Annotated R script is provided for third-order (i.e. within home range) resource selection analysis presented in the associated paper. For the code to run, you will need the shapefiles and animal movement data in your working directory.

Full model.R (file for each sampling period: Sum21, Sum 20, Aut20, Aut21, Spring, Win)*

Annotated R script to replicate the model selection steps described in the associated paper. For the code to run, you will need the output generated from the Third-order_RSF.R script in your working directory for the corresponding season.

*Scripts require animal movement data to run. GPS/VHF radio-tracking data from the associated paper can be requested from the corresponding author (Kate Cornelsen: cornelsen.kate@gmail.com) upon reasonable request.