Clearing up the Crystal Ball: Understanding Uncertainty in Future Climate Suitability Projections for Amphibians

Abstract

Amphibian populations are threatened globally, and one of the hypotheses for these declines is climate change. Species distribution models are frequently used to predict changes in suitable habitat as a result of changing climates; however, these projections can be heavily influenced by choice of modeling approach. To evaluate global predictions for amphibians, we conducted a literature review of studies that utilize correlative species distribution models to project changes in climate suitability under various climate change scenarios. We paid particular attention to the use of model selection in choosing among candidate species distribution models (SDMs) so as to control for overparameterization of SDMs. In addition, we conducted a case study with three species of Slender Salamanders (Batrachoseps) to further investigate the impact of differences in modeling decisions on projected amphibian climate suitability. We found 83 studies (including the present case study) in which projections of future climate suitability were made for amphibian species. Of those studies, 36 included estimates of percent change in climate suitability and thus were included in our meta-analysis. These studies included projections for over 1000 species or species complexes, with the majority being Anurans (86%), and encompassed five continents with the most representation in South America, Europe, and North America. Across these studies, average projected change in climate suitability ranged from －70% to 167%, and these projected changes varied with dispersal assumptions representative concentration pathway (RCP) used, the projection year, and taxonomic order. Only three of the 36 studies reported the use of Akaike information criterion (AIC)-based model selection to choose a best-fit SDM. However, our case study demonstrated that predicted change in climate suitability varied whether the best-fit or default SDM was used for projections. Further, this result varied among species (ΔAIC = 0), suggesting that the impact of overparameterization differs across species. Our results illustrate that there is a pressing need to project climate suitability across more species and more geographic regions. In addition, we may need to revisit projections for previously investigated species to evaluate additional climate scenarios and whether overparameterization may have influenced projections. Our ability to accurately model future changes in climate suitability will be essential for successful conservation and management plans for amphibians.