This action funds an NSF Postdoctoral Research Fellowship for FY 2009. The fellowship supports a research and training plan entitled "Integrating species distribution models, Geographic Information Systems and coalescent phylogenetic methods into phylogeography studies" for Jason Brown. The host institution for this research is the University of Michigan, and the sponsoring scientist is Lacey Knowles.
Integrating species distribution models, coalescent-based phylogenies and geographic information systems provides a novel perspective on biogeography and could substantially improve our understanding of current and historic species distribution patterns. A better understanding of these factors is particularly important for the conservation of amphibians (the focal taxa of this project), many of which have dramatically declined in the past quarter-century. Species distribution models are calculations that predict the distribution of a species using various climatic and geographic variables (e.g. temperature, rainfall). The resulting model generates a habitat suitability map based on a species' ecological tolerance, indicating areas of high and low suitability. This allows species distributions to be treated as gradients of suitable and unsuitable habitat; thereby more accurately reflecting the dispersal potential across particular landscapes. Using these "dispersal landscapes," coalescent-based phylogenies and geographic information systems, this research (1) estimates realistic dispersal networks between genealogical lineages, which can then be used to estimate key dispersal routes for each target species at several periods in time, and (2) uses modified "dispersal landscapes" to test biogeographic hypotheses at different periods in time.
The training and education objectives in include computer programming, theoretical biogeography and hypothesis testing, coalescent phylogenetics, and a continued development of expertise in Geographic Information Systems, with particular emphasis on the development of a rigorous and cohesive method for evaluating species dispersal networks, and statistical tests of reliability. The broader impacts of this research are to better understand species distributions for consideration in conservation and restoration projects.
