Data from: A new Bayesian method for fitting evolutionary models to comparative data with intraspecific variation

Phylogenetic comparative methods that incorporate intraspecific variability are relatively new and, so far, not especially widely used in empirical studies. In the present short article we will describe a new Bayesian method for fitting evolutionary models to comparative data that incorporates intraspecific variability. This method differs from an existing likelihood-based approach in that it requires no a priori inference about species means and variances; rather it takes phenotypic values from individuals and a phylogenetic tree as input, and then samples species means and variances, along with the parameters of the evolutionary model, from their joint posterior probability distribution. One of the most novel and intriguing attributes of this approach is that jointly sampling the species means with the evolutionary model parameters means that the model and tree can influence our estimates of species mean trait values, not just the reverse. In the present implementation we first apply this method to the most widely used evolutionary model for continuously valued phenotypic trait data (Brownian motion). However the general approach has broad applicability, which we illustrate by also fitting the λ model, another simple model for quantitative trait evolution on a phylogeny. We test our approach via simulation and by analyzing two empirical datasets obtained from the literature. Finally, we have implemented the methods described herein in a new function for the R statistical computing environment, and this function will be distributed as part of the ‘phytools’ R library.

纳入种内变异的系统发育比较方法（phylogenetic comparative methods）问世时间相对较近，截至目前在实证研究中的应用尚未得到广泛普及。在这篇研究简报中，我们将介绍一种全新的贝叶斯方法（Bayesian method），用于为包含种内变异的比较数据适配进化模型。该方法与现有基于似然的研究路径存在显著差异：其无需针对物种均值与方差开展先验推断，仅以个体表型值与系统发育树作为输入，随后从物种均值、方差以及进化模型参数的联合后验概率分布中进行采样。该方法最具创新性与吸引力的特性之一在于，将物种均值与进化模型参数联合采样的逻辑，意味着模型与系统发育树能够对物种平均性状值的估计产生影响，而非仅存在单向的反向作用。在当前的实现方案中，我们首先将该方法应用于连续型表型性状数据中最常用的进化模型——布朗运动模型（Brownian motion）。不过该通用框架具备广泛的适用性，我们通过对λ模型（λ model）进行适配验证了这一点——λ模型是另一种用于系统发育上数量性状进化的简单模型。我们通过模拟实验以及对两篇文献中获取的两组实证数据集进行分析，对该方法的有效性进行了检验。最终，我们已在R统计计算环境的全新函数中实现了本文所述的方法，该函数将作为‘phytools’R库的一部分进行分发。