Data from: Winter coat color polymorphisms identify global hotspots for evolutionary rescue from climate change

• Main Authors: Mills, L. Scott, Bragina, Eugenia V., Kumar, Alexander V., Zimova, Marketa, Lafferty, Diana J.R., Feltner, Jennifer, Davis, Brandon M., Hacklander, Klaus, Alves, Paulo C., Good, Jeffrey M., Melo-Ferreira, Jose, Dietz, Andreas, Abramov, Alexei V., Lopatina, Natalia, Fay, Kairsten
• Format: Other/Unknown Material
• Language: unknown
• Published: Zenodo 2019
• Subjects: Mustela erminea; Vulpes lagopus; Mustela nivalis; Lepus americanus; Lepus timidus; Lepus townsendii; Mustela frenata; Lepus brachyurus
• Online Access: https://doi.org/10.5061/dryad.8m0p1

Maintenance of biodiversity in a rapidly changing climate will depend on the efficacy of evolutionary rescue, whereby population declines due to abrupt environmental change are reversed by shifts in genetically-driven adaptive traits. However, a lack of traits known to be under direct selection by anthropogenic climate change has limited the incorporation of evolutionary processes into global conservation efforts. In 22 vertebrate species, some individuals undergo a seasonal color molt from summer brown to winter white as camouflage against snow, while other individuals remain brown. Seasonal snow duration is decreasing globally, and fitness is lower for winter white animals on snowless backgrounds. Based on 2,713 georeferenced samples of known winter coat color – from 8 species across trophic levels – we identify environmentally driven clinal gradients in winter coat color, including polymorphic zones where winter brown and white morphs co-occur. These polymorphic zones, underrepresented by existing global protected area networks, indicate hotspots for evolutionary rescue in a changing climate. Mills_data_final_2018 This is the data used to build models predicting the probability of winter white for each species across their range. It is needed to run the R script. See README file for column descriptions and more information. rasterstack4cov This is the a raster stack of the three covariates (bio_2, bio_3 & snow) used in making the winter white probability maps. It is needed to run the R script. global_phenology_final_script This is the R script associated with the analyses from this publication. Note in order to make species maps you need to download and read into R their range maps from the IUCN red list website: http://www.iucnredlist.org/ Funding provided by: National Science Foundation Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000001 Award Number: 0841884