Evolutionary sample size and consilience in phylogenetic comparative analysis

Phylogenetic comparative methods (PCMs) are commonly used to study evolution and adaptation. However, frequently used PCMs for discrete traits mishandle single evolutionary transitions. They erroneously detect correlated evolution in these situations. For example, hair and mammary glands cannot be said to have evolved in a correlated fashion because each evolved only once in mammals, but a commonly used model (Pagel’s Discrete) statistically supports correlated (dependent) evolution. Using simulations, we find that rate parameter estimation, which is central for model selection, is poor in these scenarios due to small effective (evolutionary) sample sizes of independent character state change. Pagel’s Discrete model also tends to favor dependent evolution in these scenarios, in part, because it forces evolution through state combinations unobserved in the tip data. This model prohibits simultaneous dual transitions along branches. Models with underlying continuous data distributions (e....系统发育比较方法（Phylogenetic Comparative Methods，PCMs）是研究生物演化与适应的常用研究手段。然而，当前常用于离散性状的PCMs在处理单次演化转变时存在明显缺陷，会在这类场景中错误地检测出协同演化信号。例如，毛发与乳腺不能被认为是协同演化而来，因为二者在哺乳类中均仅演化出现一次，但常用的佩格尔离散模型（Pagel’s Discrete）却在统计上支持二者存在协同（依赖型）演化。通过模拟实验，我们发现，由于独立性状状态转变的有效（演化）样本量过小，作为模型选择核心的速率参数估计在这类场景中表现不佳。佩格尔离散模型还倾向于在这类场景中判定存在依赖型演化，部分原因在于其强制演化通过类群末端数据中未观测到的状态组合进行，且该模型不允许在演化支上同时发生双重转变。基于连续数据分布的模型（e....