Bringing indices of species vulnerability to climate change into geographic space: an assessment across the Coronado national forest

Indices that rate the vulnerability of species to climate change in a given area are increasingly used to inform conservation and climate change adaptation strategies. These species vulnerability indices (SVI) are not commonly associated with landscape features that may affect local-scale vulnerability. To do so would increase their utility by allowing managers to examine how the distributions of vulnerable species coincide with environmental features such as topography and land use, and to detect landscape-scale patterns of vulnerability across species. In this study we evaluated 15 animal species that had been scored with the USDA-Forest Service Rocky Mountain Research Station’s system for assessing vulnerability of species to climate change. We applied the vulnerability scores to each species’ respective habitat models in order to visualize the spatial patterns of cross-species vulnerability across the biologically diverse Coronado national forest, and to identify the considerations of spatially referencing such indices. Across the study extent, cross-species vulnerability was higher in higher-elevation woodlands and lower in desert scrub. The results of spatially referencing SVI scores may vary according to the species examined, the area of interest, the selection of habitat models, and the method by which cross-species vulnerability indices are created. We show that it is simple and constructive to bring species vulnerability indices into geographic space: landscape-scale patterns of vulnerability can be detected, and relevant ecological and socioeconomic contexts can be taken into account, allowing for more robust conservation and management strategies.