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To understand biological diversification, it is important to account forlarge-scale processes that affect the evolutionary history of groups ofco-distributed populations of organisms. Such events predict temporallyclustered divergences times, a pattern that can be estimated using genetic datafrom co-distributed species. I introduce a new approximate-Bayesian method forcomparative phylogeographical model-choice that estimates the temporaldistribution of divergences across taxa from multi-locus DNA sequence data. Themodel is an extension of that implemented in msBayes. By reparameterizing themodel, introducing more flexible priors on demographic and divergence-timeparameters, and implementing a non-parametric Dirichlet-process prior overdivergence models, I improved the robustness, accuracy, and power of the methodfor estimating shared evolutionary history across taxa. The results demonstratethe improved performance of the new method is due to (1) more appropriatepriors on divergence-time and demographic parameters that avoid prohibitivelysmall marginal likelihoods for models with more divergence events, and (2) theDirichlet-process providing a flexible prior on divergence histories that doesnot strongly disfavor models with intermediate numbers of divergence events.The new method yields more robust estimates of posterior uncertainty, and thusgreatly reduces the tendency to incorrectly estimate models of sharedevolutionary history with strong support.

An Improved Approximate-Bayesian Model-choice Method for Estimating Shared Evolutionary History