Climatically robust multi-scale species distribution models to support pronghorn recovery in California

We combined two climate-based distribution models with three finer-scale suitability models to identify habitat for pronghorn recovery in California now and into the future.
Location: California, United States 
Methods: We used a consensus approach to identify areas of suitable climate now (1980-2010) and future (2031-2060) for pronghorn in California. We compared the results of models from two separate hypotheses about their historical ecology in the state, specifically the migration hypothesis and the niche reduction hypothesis. We combined occurrences from GPS collars distributed across three populations of pronghorn in the state to create three distinct habitat models: (1) an ensemble model using Random Forests, Maxent, Classification and Regression Trees, and a Generalized Linear Model; (2) a step selection function; and (3) an expert-driven model. We evaluated consensus among both the climate models and the suitability models to prioritize areas for, and evaluate the prospects of,..., , , # Climatically robust multi-scale species distribution models to support pronghorn recovery in California

[https://doi.org/10.5061/dryad.bcc2fqzmx](https://doi.org/10.5061/dryad.bcc2fqzmx)

Data include raw pronghorn locations and environmental predictors to generate distribution and habitat models, and the outputs of these models.

## Description of the data and file structure

Data are of three kinds:

1. Pronghorn locations (\"all_gbif pronghorn.csv\"), downloaded from the Global Biodiversity Information Facility (Supplemental information on Zenodo)
2. Environmental predictors used to generate habitat or climate models (all distances in meters)
1. \"ag_agg.tif\": proportion cover of agriculture land type, derived from the CalFire vegetation layer
2. \"all_road dens.tif\": density of all roads within the raster cell, derived from TIGER lines
3. \"barren_agg.tif\": proportion cover of barren land type, derived from the CalFire vegetation layer
4. \"bulk_dens agg.tif\": bulk density ...