Beaulieu Jeremy M, O'Meara Brian C
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
Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996-1610, USA.
Syst Biol. 2016 Jul;65(4):583-601. doi: 10.1093/sysbio/syw022. Epub 2016 Mar 25.
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.
多样性的分布在不同的进化枝之间可能有很大差异。试图理解这些模式的研究通常采用状态依赖的物种形成和灭绝模型，以确定特定新性状的进化是否提高了物种形成率和/或降低了灭绝率。然而，目前仍不清楚这些模型是揭示了物种多样化的重要驱动因素，还是仅仅指出了涉及许多未测量和共同分布因素的更复杂模式。在这里，我们描述了一种对流行的状态依赖物种形成和灭绝模型的扩展，该扩展专门考虑了未测量因素的存在，这些因素可能会影响根据任何观察到的性状状态估计的多样化率，从而至少解决了对BiSSE（二元状态物种形成和灭绝）方法的一项主要批评。具体来说，我们的模型，即隐藏状态物种形成和灭绝模型（HiSSE），假设与模型中的每个观察状态相关的是“隐藏”状态，这些隐藏状态表现出与单独的观察状态相比潜在不同的多样化动态和转变率。我们还展示了我们的模型如何用作与性状无关的多样化模型，允许一个独立于性状进化的复杂多样化过程。在严格的模拟测试和应用于实证数据时，我们发现HiSSE表现相当不错，并且至少可以检测观察状态和隐藏状态之间的净多样化率差异，以及检测多样化率差异何时与观察状态不相关。我们总体上讨论了状态依赖物种形成和灭绝模型的其余问题，以及HiSSE在哪些重要方面提供了对性状依赖多样化的更细致入微的理解。
