Understanding impacts of climatic variability on distributions of species

This project will improve understanding of what constrains where a species can live, both currently and in an altered future climate. Improved understanding of species’ geographic ranges is important for conservation and resource management and for controlling pest species and disease vectors. “Species distribution models” (SDMs) compare a list of locations a species has been seen to past climatic data to help understand what controls the species’ geographic distribution. SDMs can also project a species’ future distribution. SDMs are extremely widely applied. But SDMs have a major weakness that limits their effectiveness. Traditional SDMs use data on average climate, e.g., average temperature for 1980-2000. But researchers working in the field of stochastic demography know that climate variability in a location can also make a species unable to live there, even when the average climate is suitable. For instance, a reliable 6 inches of spring rainfall in a location, every year, may be ideal for a species. But suppose a second location gets 12 inches spring rainfall in some years and 0 in other years. It may be impossible for the species to live in the second location, even though both locations may have the same average spring rainfall. Traditional SDMs cannot accurately assess the influence of variability on species geographic ranges. Addressing this shortcoming is pressing because climate change will alter climatic variability, influencing species’ ranges. This research will fill this knowledge gap by integrating demographic methods into SDMs. The project will develop an understanding of how variability influences species niches and ranges in the present and future. The project will also provide training in ecology to hundreds of 3rd grade teachers and students in underserved schools. Software and other resources facilitating uptake of new methods will be released to other scientists and conservation and management practitioners. Objective 1 of the project is to develop theoretical and statistical foundations of a new approach to SDMs that we call XSDM, and to quantify the effectiveness of XSDM compared to existing methods. Objective 2 is to apply XSDM to thousands of species, broadly examining the role of interannual climatic variability in constraining species ranges. Objective 3 is to further expand XSDM to account for population age structure, allowing for the possibility that different life stages of a species have different environmental sensitivities. The research framework allows statistical assessment of the degree to which each increase in demographic complexity/realism of the model used is needed to understand a species’ niche and distribution. Objective 4 involves the provision of resources to the research and applied community to facilitate the broad uptake of XSDM. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.