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Phylogeographic Inference Using Approximate Likelihoods

Brian C. O’Meara, Nathan D. Jackson, Ariadna Morales, Bryan C. Carstens
doi: https://doi.org/10.1101/025353
Brian C. O’Meara
1Department of Ecology and Evolutionary Biology, University of Tennessee-Knoxville
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Nathan D. Jackson
1Department of Ecology and Evolutionary Biology, University of Tennessee-Knoxville
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Ariadna Morales
2Department of Evolution, Ecology and Organismal Biology, The Ohio State University, 318 W. 12th Avenue, Columbus, OH, 43210-1293
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Bryan C. Carstens
2Department of Evolution, Ecology and Organismal Biology, The Ohio State University, 318 W. 12th Avenue, Columbus, OH, 43210-1293
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Abstract

The demographic history of most species is complex, with multiple evolutionary processes combining to shape the observed patterns of genetic diversity. To infer this history, the discipline of phylogeography has (to date) used models that simplify the historical demography of the focal organism, for example by assuming or ignoring ongoing gene flow between populations or by requiring a priori specification of divergence history. Since no single model incorporates every possible evolutionary process, researchers rely on intuition to choose the models that they use to analyze their data. Here, we develop an approach to circumvent this reliance on intuition. PHRAPL allows users to calculate the probability of a large number of demographic histories given their data, enabling them to identify the optimal model and produce accurate parameter estimates for a given system. Using PHRAPL, we reanalyze data from 19 recent phylogeographic investigations. Results indicate that the optimal models for most datasets parameterize both gene flow and population divergence, and suggest that species tree methods (which do not consider gene flow) are overly simplistic for most phylogeographic systems. These results highlight the importance of phylogeographic model selection, and reinforce the role of phylogeography as a bridge between population genetics and phylogenetics.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted August 24, 2015.
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Phylogeographic Inference Using Approximate Likelihoods
Brian C. O’Meara, Nathan D. Jackson, Ariadna Morales, Bryan C. Carstens
bioRxiv 025353; doi: https://doi.org/10.1101/025353
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Phylogeographic Inference Using Approximate Likelihoods
Brian C. O’Meara, Nathan D. Jackson, Ariadna Morales, Bryan C. Carstens
bioRxiv 025353; doi: https://doi.org/10.1101/025353

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