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      Detecting Hidden Diversification Shifts in Models of Trait-Dependent Speciation and Extinction.

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          Abstract

          The distribution of diversity can vary considerably from clade to clade. Attempts to understand these patterns often employ state-dependent speciation and extinction models to determine whether the evolution of a particular novel trait has increased speciation rates and/or decreased extinction rates. It is still unclear, however, whether these models are uncovering important drivers of diversification, or whether they are simply pointing to more complex patterns involving many unmeasured and co-distributed factors. Here we describe an extension to the popular state-dependent speciation and extinction models that specifically accounts for the presence of unmeasured factors that could impact diversification rates estimated for the states of any observed trait, addressing at least one major criticism of BiSSE (Binary State Speciation and Extinction) methods. Specifically, our model, which we refer to as HiSSE (Hidden State Speciation and Extinction), assumes that related to each observed state in the model are "hidden" states that exhibit potentially distinct diversification dynamics and transition rates than the observed states in isolation. We also demonstrate how our model can be used as character-independent diversification models that allow for a complex diversification process that is independent of the evolution of a character. Under rigorous simulation tests and when applied to empirical data, we find that HiSSE performs reasonably well, and can at least detect net diversification rate differences between observed and hidden states and detect when diversification rate differences do not correlate with the observed states. We discuss the remaining issues with state-dependent speciation and extinction models in general, and the important ways in which HiSSE provides a more nuanced understanding of trait-dependent diversification.

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          Author and article information

          Journal
          Syst. Biol.
          Systematic biology
          Oxford University Press (OUP)
          1076-836X
          1063-5157
          Jul 2016
          : 65
          : 4
          Affiliations
          [1 ] National Institute for Biological and Mathematical Synthesis, University of Tennessee, Knoxville, TN 37996, USA Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996-1610, USA jbeaulieu@nimbios.org.
          [2 ] Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996-1610, USA.
          Article
          syw022
          10.1093/sysbio/syw022
          27016728
          bc2128a8-9f8d-42a5-b9ce-560e4426564f
          History

          hidden states,extinction,diversification,Comparative methods,speciation

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