Data from: Inferring diversification rate variation from phylogenies with fossils

Time-calibrated phylogenies of living species have been widely used to study the tempo and mode of species diversification. However, it is increasingly clear that inferences about species diversification — extinction rates in particular — can be unreliable in the absence of paleontological data. We introduce a general framework based on the fossilized birth-death process for studying speciation-extinction dynamics on phylogenies of extant and extinct species. Our model assumes that phylogenies can be modeled as a mixture of distinct evolutionary rate regimes and that a hierarchical Poisson process governs the number of such rate regimes across a tree. We implemented the model in BAMM, a computational framework that uses reversible jump Markov chain Monte Carlo to simulate a posterior distribution of macroevolutionary rate regimes conditional on the branching times and topology of a phylogeny. The implementation we describe can be applied to paleontological phylogenies, neontological phylogenies, and to phylogenies that include both extant and extinct taxa. We evaluate performance of the model on datasets simulated under a range of diversification scenarios. We find that speciation rates are reliably inferred in the absence of paleontological data. However, the inclusion of fossil observations substantially increases the accuracy of extinction rate estimates. We demonstrate that the inferences are relatively robust to at least some violations of model assumptions, including heterogeneity in preservation rates and misspecification of the number of occurrences in paleontological datasets.现生生物类群的时间校准系统发育树已被广泛用于研究物种分化的速率与模式。然而，越来越多的研究表明，在缺乏古生物学数据的情况下，对物种分化过程的推断——尤其是灭绝速率的推断——往往并不可靠。我们提出了一套基于化石出生死亡过程（fossilized birth-death process）的通用分析框架，用于探究现生与灭绝物种的系统发育树所对应的物种形成-灭绝动态。本模型假设系统发育树可被建模为多种不同演化速率模式的混合体，且树内这类速率模式的数量服从层级泊松过程（hierarchical Poisson process）约束。我们将该模型集成至BAMM这一计算框架中，该框架利用可逆跳马尔可夫链蒙特卡洛（reversible jump Markov chain Monte Carlo）算法，基于系统发育树的分支时间与拓扑结构，模拟宏观演化速率模式的后验分布。本文所描述的实现方法可应用于古生物系统发育树、现生生物系统发育树，以及同时包含现生与灭绝类群的系统发育树。我们通过在多种分化场景下模拟生成的数据集对模型性能进行了评估。结果显示，即便缺乏古生物学数据，物种形成速率仍可得到可靠的推断；但加入化石观测数据后，灭绝速率估计的准确性会得到显著提升。我们还证明，该推断至少在一定程度上对模型假设的违背具有鲁棒性，包括化石保存速率的异质性以及古生物数据集出现次数的误设定。