Collaborative Research: Phylogeographic Inference Using Approximated Likelihoods

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Where species live changes through time -- for example, mountains may rise, dividing one species into distinct populations, or a small group of individuals may hitch a ride in ballast water and start spreading within a new geographic area. To investigate the history of species through time, scientists often represent possible histories as models and compare the fit of observed data to these models. This grant will develop new modeling methods and software to allow scientists to test alternative, complex models that best fit observed data for various groups of organisms. A test case, using North American bats, will help ensure that the new software can accommodate various types of data effectively.This work has practical importance because the new methods can be used to help identify sources of invasive species. It is also important in conservation because these methods will provide information about whether a species in different river systems is one or multiple populations, whether hybridization is occurring between two related species, and what the effective population size of a species has been through time. Graduate students and postdoctoral students will be trained in these methods as well.