Forecasting animal distribution through individual habitat selection: Insights for population inference and transferable predictions

Habitat selection models frequently use data collected from a small geographic area over a short window of time to extrapolate patterns of relative abundance to unobserved areas or periods of time. However, these types of models often poorly predict how animals will use habitat beyond the place and time of data collection because space-use behaviors vary between individuals and are context-dependent. Here, we present a modelling workflow to advance predictive distribution performance by explicitly accounting for individual variability in habitat selection behavior and dependence on environmental context. Using global positioning system (GPS) data collected from 238 individual pronghorn, (Antilocapra americana), across 3 years in Utah, we combine individual-year-season-specific exponential habitat-selection models with weighted mixed-effects regressions to both draw inference about the drivers of habitat selection and predict space-use in areas/times where/when pronghorn were not monitor..., , , # Forecasting Animal Distribution through Individual Habitat Selection: Insights for Population Inference and Transferable Predictions

[https://doi.org/10.5061/dryad.4f4qrfjmz](https://doi.org/10.5061/dryad.4f4qrfjmz)

**A note on data setup**: due to this being a sensitive species, we are unable to share the XY positions. To Implement this analysis, GPS data should be formatted with unique individual IDs, XY, and date-time stamp, as shown here:

         ID               x               y             datetime

 PR17F0001 44xxxx. 42xxxxx. 2017-12-18 20:15:00

 PR17F0001 44xxxx. 42xxxxx. 2017-12-18 22:30:00

 PR17F0001 44xxxx. 42xxxxx. 2017-12-19 01:00:00

 PR17F0001 44xxxx. 42xxxxx. 2017-12-19 03:15:00

 PR17F0001 44xxxx. 42xxxxx. 2017-12-19 05:30:00

This table can include any other information that may pertain to the question at hand for your system/species.

***For reproducibility, we have uploaded data files for implementing the analysis post-RSF.*** 
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