Journal Article

Detecting Concerted Demographic Response across Community Assemblages Using Hierarchical Approximate Bayesian Computation

Yvonne L. Chan, David Schanzenbach and Michael J. Hickerson

in Molecular Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 31, issue 9, pages 2501-2515
Published in print September 2014 | ISSN: 0737-4038
Published online June 2014 | e-ISSN: 1537-1719 | DOI:

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  • Evolutionary Biology
  • Molecular and Cell Biology


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Methods that integrate population-level sampling from multiple taxa into a single community-level analysis are an essential addition to the comparative phylogeographic toolkit. Detecting how species within communities have demographically tracked each other in space and time is important for understanding the effects of future climate and landscape changes and the resulting acceleration of extinctions, biological invasions, and potential surges in adaptive evolution. Here, we present a statistical framework for such an analysis based on hierarchical approximate Bayesian computation (hABC) with the goal of detecting concerted demographic histories across an ecological assemblage. Our method combines population genetic data sets from multiple taxa into a single analysis to estimate: 1) the proportion of a community sample that demographically expanded in a temporally clustered pulse and 2) when the pulse occurred. To validate the accuracy and utility of this new approach, we use simulation cross-validation experiments and subsequently analyze an empirical data set of 32 avian populations from Australia that are hypothesized to have expanded from smaller refugia populations in the late Pleistocene. The method can accommodate data set heterogeneity such as variability in effective population size, mutation rates, and sample sizes across species and exploits the statistical strength from the simultaneous analysis of multiple species. This hABC framework used in a multitaxa demographic context can increase our understanding of the impact of historical climate change by determining what proportion of the community responded in concert or independently and can be used with a wide variety of comparative phylogeographic data sets as biota-wide DNA barcoding data sets accumulate.

Keywords: comparative phylogeography; approximate Bayesian computation; historical demography; response to climate change

Journal Article.  8404 words.  Illustrated.

Subjects: Evolutionary Biology ; Molecular and Cell Biology

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