Data from: Potential effects of future climate change on global reptile distributions and diversity ...

• Main Authors: Biber, Matthias F., Voskamp, Alke, Hof, Christian
• Format: Dataset
• Language: English
• Published: Dryad 2023
• Subjects: bioclim; Biodiversity; Environmental niche model; Global warming; ISIMIP; lizard; snake; Species distribution model; species richness; turtle; FOS: Earth and related environmental sciences; Antarc*; Antarctica
• Online Access: https://dx.doi.org/10.5061/dryad.rn8pk0pgb; https://datadryad.org/stash/dataset/doi:10.5061/dryad.rn8pk0pgb

Aim: Until recently, complete information on global reptile distributions has not been widely available. Here, we provide the first comprehensive climate impact assessment for reptiles on a global scale. Location: Global, excluding Antarctica Time period: 1995, 2050, 2080 Major taxa studied: Reptiles Methods: We modelled the distribution of 6,296 reptile species and assessed potential global as well as realm-specific changes in species richness, the change in global species richness across climate space, and species-specific changes in range extent, overlap and position under future climate change. To assess the future climatic impact on 3,768 range-restricted species, which could not be modelled, we compared the future change in climatic conditions between both modelled and non-modelled species. Results: Reptile richness was projected to decline significantly over time, globally but also for most zoogeographic realms, with the greatest decrease in Brazil, Australia and South Africa. Species richness was ... : These data comprise the raw data and results of the article: Biber et al. (2023) Potential effects of future climate change on global reptile distributions and diversity. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13646 The methods used to generate these data are fully described in the main text of the paper, and all R code is provided below. Please see the usage notes for details. Code to reproduce the species distribution models, which we used in our analyses, is available at: https://github.com/christianhof/BioScen1.5_SDM ...