Integrating Ecological and Evolutionary Processes in Stochastic Biogeographical Models

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The causes of geographic variation in the number of species have long been debated, but we still lack a clear understanding of how spatial patterns of species diversity arise. Some attempt to explain them as a function of environmental variables, while others emphasize the role of earth history. Recent advances in simulation and mathematical models highlight random processes. The proposed work integrates all these approaches, by modeling the origin, adaptive shifts, and extinction of species' ranges in both space and time, using high-quality datasets for species distributions of several groups of organisms and detailed continental maps derived from remote sensing of Earth environments.Regional and global perspectives in ecology represent a rapidly growing group of related disciplines that build on past advances in understanding local ecological systems. The proposed work uses advanced contemporary computational technologies to support the interpretation and modeling of ecological systems at spatial scales and resolutions unimaginable just a decade ago. The reality of global climate change places urgent demands on scientists to predict and prepare for ecological and evolutionary effects of extinctions and shifts in species' geographic ranges, and to design reserves and corridors that mitigate range shifts driven by climate change. The work proposed aims to provide essential tools for this objective.