Tip rates, phylogenies and diversification: What are we estimating, and how good are the estimates?
Tip rates, phylogenies and diversification: What are we estimating, and how good are the estimates?
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DOI：
10.1111/2041-210x.13153
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发表时间：
2019-02
影响因子：
6.6
通讯作者：
Pascal O. Title;D. Rabosky
中科院分区：
文献类型：
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作者：
Pascal O. Title;D. Rabosky
物种特异性多样化率或“尖端率”可以从系统发育中快速计算出来，并广泛用于研究与地理、生态和表型相关的多样化率变化。这些小费率提供了许多理论和实践优势，例如放宽了特征依赖性多样化研究中费率同质性的假设。然而，文献中关于这些指标是否估计物种形成率或净多样化率存在很大的混乱。此外，还没有研究比较模拟多样化场景中小费率指标的相对性能和准确性。我们比较了三种无模型速率度量（逆终端分支长度；节点密度度量；DR 统计）和基于模型的方法（宏观进化混合物的贝叶斯分析 [BAMM]）的统计性能。我们将每种方法应用于在不同多样化过程下生成的大量模拟系统发育。我们总结了与利率变化类型、利率异质性程度和利率制度规模相关的绩效。我们还比较了这些指标估计物种形成率和净多样化率的能力。我们果断地证明，与净多样化相比，无模型的尖端速率指标可以更好地估计物种形成速率。净多样化率估计的误差随着相对灭绝率的增加而增加。相比之下，物种形成率估计的误差很低，并且对灭绝相对不敏感。总体而言，特别是当相对灭绝较高时，BAMM 推断出最准确的提示率，并且比非基于模型的方法表现出更低的误差。 DR 与真实的物种形成率高度相关，但表现出较高的误差方差，并且是非常小的速率体系的最佳指标。我们发现，在测试的指标中，DR 和 BAMM 是研究物种形成速率动态和性状依赖性多样化最有用的指标。尽管 BAMM 总体上比 DR 更准确，但这两种方法具有互补的优势。由于尖端速率指标是物种形成率更可靠的估计量，因此我们建议在物种形成和净多样化之间的区别很重要的任何情况下，使用这些指标的实证研究在得出生物学解释时应谨慎行事。
Species‐specific diversification rates, or ‘tip rates’, can be computed quickly from phylogenies and are widely used to study diversification rate variation in relation to geography, ecology and phenotypes. These tip rates provide a number of theoretical and practical advantages, such as the relaxation of assumptions of rate homogeneity in trait‐dependent diversification studies. However, there is substantial confusion in the literature regarding whether these metrics estimate speciation or net diversification rates. Additionally, no study has yet compared the relative performance and accuracy of tip rate metrics across simulated diversification scenarios. We compared the statistical performance of three model‐free rate metrics (inverse terminal branch lengths; node density metric; DR statistic) and a model‐based approach (Bayesian analysis of macroevolutionary mixtures [BAMM]). We applied each method to a large set of simulated phylogenies that had been generated under different diversification processes. We summarized performance in relation to the type of rate variation, the magnitude of rate heterogeneity and rate regime size. We also compared the ability of the metrics to estimate both speciation and net diversification rates. We show decisively that model‐free tip rate metrics provide a better estimate of the rate of speciation than of net diversification. Error in net diversification rate estimates increases as a function of the relative extinction rate. In contrast, error in speciation rate estimates is low and relatively insensitive to extinction. Overall, and in particular when relative extinction was high, BAMM inferred the most accurate tip rates and exhibited lower error than non‐model‐based approaches. DR was highly correlated with true speciation rates but exhibited high error variance, and was the best metric for very small rate regimes. We found that, of the metrics tested, DR and BAMM are the most useful metrics for studying speciation rate dynamics and trait‐dependent diversification. Although BAMM was more accurate than DR overall, the two approaches have complementary strengths. Because tip rate metrics are more reliable estimators of speciation rate, we recommend that empirical studies using these metrics exercise caution when drawing biological interpretations in any situation where the distinction between speciation and net diversification is important.