EVOGENE seminar: Michael Hickerson - Merging Phylogeography with Community Ecology

Abstract
Comparative Phylogeography leverages information from multiple population genetic datasets to make regional-scale inferences about processes driving community assembly and diversification. While the recent focus has been on testing models of synchronous divergence and/or expansion, or synthesizing species historical demographic inferences to generate hypotheses about community assembly, current approaches have not been well grounded in ecological theory. Here I describe an individual-based integrative comparative phylogeographic model built from Macarthur and Wilson’s theory of island biogeography and Hubbell’s neutral theory of biodiversity to make joint regional predictions of species richness and the distribution of abundances, genetic diversities and traits across species through time. Machine learning enables reasonable precision and accuracy estimating the strength of deterministic processes such as environmental filtering and competition over stochastic processes (i.e. neutrality) as well as estimate the relative contributions of speciation vs immigration in the community assembly process given several datasets that span multiple scales of ecological sampling. For assemblages from which large-scale high-throughput abundance and genetic data are obtained, we show that the observed Shannon’s Index on abundances can be estimated using genetic data alone, and that our framework can work as a unified multi-scale model of biodiversity.