Graduate Program in Zoology, Universidade Federal do Paraná, Curitiba, PR 81531-990, Brazil.
Department of Ecology and Evolution, University of Arizona, Tucson, Arizona 85721.
Evolution. 2018 Oct;72(10):2257-2266. doi: 10.1111/evo.13574. Epub 2018 Sep 10.
In a previous paper, we used simulations and empirical data to show that BAMM (Bayesian Analysis of Macroevolutionary Mixtures) can give misleading estimates of rates and rate shifts. In simulations, BAMM underestimated rate shifts across every tree analyzed, and assigned incorrect rates to most clades in most trees. In empirical analyses, BAMM behaved as expected from simulations, and assigned different rates to clades when clades were analyzed alone versus across the tree (i.e., with rate heterogeneity). Rabosky recently criticized our paper, focusing primarily on the idea that our comparison of BAMM to another approach (method-of-moments estimators of Magallón and Sanderson, or MS estimators) was unfair to BAMM. Here, we provide further evidence that BAMM gives misleading rate estimates in empirical studies. We then describe how Rabosky's rown method comparisons were either acknowledged as being problematic or were described inaccurately (to favor BAMM). Finally, we show that the MS estimators can perform well when rates vary over time, despite untested assertions that they require constant rates to be accurate. Many other methods are available for analyzing diversification rates: we argue that BAMM should be avoided for estimating both diversification rates and rate shifts.
在之前的一篇论文中，我们使用模拟和实证数据表明，BAMM（贝叶斯混合宏观进化分析）可能会对速率和速率变化产生误导性估计。在模拟中，BAMM 低估了分析的每棵树的速率变化，并为大多数树中的大多数分支分配了不正确的速率。在实证分析中，BAMM 的表现符合模拟预期，当单独分析分支与跨树分析（即具有速率异质性）时，BAMM 会为分支分配不同的速率。Rabosky 最近批评了我们的论文，主要集中在我们将 BAMM 与另一种方法（Magallón 和 Sanderson 的矩估计方法，或 MS 估计器）进行比较对 BAMM 不公平的想法上。在这里，我们提供了进一步的证据表明，BAMM 在实证研究中给出了误导性的速率估计。然后，我们描述了 Rabosky 的rown 方法比较是如何被认为存在问题的，或者是如何被不准确地描述的（以支持 BAMM）。最后，我们表明，尽管有人声称 MS 估计器需要恒定的速率才能准确，但当速率随时间变化时，它们可以很好地发挥作用。有许多其他方法可用于分析多样化速率：我们认为，BAMM 应避免用于估计多样化速率和速率变化。
