DOI: 10.5061/dryad.9kd51c5sf
title: Climate change scenarios forecast increased drought exposure for terrestrial vertebrates in the contiguous United States

description: Anthropogenic climate change is altering patterns of extreme weather
 events across the planet, with far-ranging consequences for biodiversity.
 Increases in the frequency, duration, and severity of droughts are
 anticipated to substantially impact natural ecosystems. Here, we predicted
 the extent to which 1,221 terrestrial vertebrates in the contiguous United
 States will be increasingly exposed to annual (12-month) and prolonged
 (36-month) drought, under three global climate models and two
 representative concentration pathways. On average, a 377% increase in
 annual drought exposure and a 579% increase in prolonged drought exposure
 are anticipated for the study area by 2050–2080, compared to 1950–2005.
 Species in the southwestern USA could see the largest increases in drought
 exposure, while this area also has the highest vertebrate diversity and an
 abundance of drought-threatened species. Our results aid in identifying
 vertebrates and ecoregions anticipated to see large increases in drought
 exposure, which can inform conservation strategies aimed at mitigating
 vertebrate extinction risks.
description: We used the standardized precipitation evapotranspiration index
 (SPEI) to calculate past and future drought occurrence in the contiguous
 United States. To this end, we used three Global Climate Models (GCM) and
 two Representative Concentration Pathways (RCP), for a historical and
 future period. We contextualized these findings using observed data for
 two recent periods. We analyzed changes in drought exposure across species
 ranges extracted from IUCN and 84 Level III Ecoregions of the United
 States.
description: # Climate change scenarios forecast increased drought exposure for
 terrestrial vertebrates
 [https://doi.org/10.5061/dryad.9kd51c5sf](https://doi.org/10.5061/dryad.9kd51c5sf) This dataset contains code and shapefiles needed to run the analysis of this paper. The R scripts contain specific information about each section of code, with additional content and instructions. ## Description of the data and file structure **Glossary:** SPEI: Standard Precipitation-Evaporation Index - the measurement of drought used in this research.\ MACAv2 dataset: downscaled projections of climate data used to obtain modeled historical and future climate data.\ PRISM dataset: observed climate data used to obtain observed drought data between 1953–1982 and 1991–2020.\ PET: Potential Evapotranspiration, a variable used in combination with precipitation to calculate SPEI values. **Code scripts:** **SPEI_calculations.R** Contains all the code necessary to transform the raw climate data from the MACAv2 and PRISM data into monthly SPEI rasters. Associated files: * none **SPEI_processing.R** Contains all code necessary to transform the SPEI data, and the associated historical and future periods into rasters of change in drought frequencies (SPEI &gt; 1.5). Associated files: * ranges_quartered.shp (shapefile of study area quartered through the centroid) **Results_analysis.R** Contains all the code necessary to run the analysis used to obtain the results and result visualizations. Associated files:    * ecoregions_raw.shp (shapefile of 74 level III ecoregions used to spatially summarize drought) * specieslist.xls (XLS of vertebrates included in this analysis)                                 * monthchanges.csv (CSV file with percentages of change in the number of drought months per quarter of the contiguous USA) * SpeciesChanges_final.csv (CSV file with projected changes in drought exposure for each vertebrate species under the various future scenarios) ## Sharing/Access information Specific instructions for downloading are provided in the R scripts described above. Data was derived from the following sources: * Species range data from IUCN: [https://www.iucnredlist.org/search/grid?searchType=species](https://www.iucnredlist.org/search/grid?searchType=species) * Study area polygon (cb_2018_us_state_5m.zip): [https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html](https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html) * Precipitation and PET data for MACAv2 downscaled projections (i.e., modeled climate data): [https://climate.northwestknowledge.net/MACA/data_portal.php](https://climate.northwestknowledge.net/) * PRISM observed climate data: [https://www.fs.usda.gov/rds/archive/products/RDS-2022-0086/_metadata_RDS-2022-0086.html](https://www.fs.usda.gov/rds/archive/products/RDS-2022-0086/_metadata_RDS-2022-0086.html )  ## Code/Software We used R 4.2.2, all necessary R packages can be found within the R scripts provided.