A phylogenetic comparative method for evaluating trait coevolution across two phylogenies for sets of interacting species

Evaluating trait correlations across species within a lineage via phylogenetic regression is fundamental to comparative evolutionary biology, but when traits of interest are derived from two sets of lineages that co-evolve with one another, methods for evaluating such patterns in a dual-phylogenetic context remain underdeveloped. Here we extend multivariate permutation-based phylogenetic regression to evaluate trait correlations in two sets of interacting species while accounting for their respective phylogenies. This extension is appropriate for both univariate and multivariate response data, and may utilize one or more independent variables, including environmental covariates. Imperfect correspondence between species in the interacting lineages can also be accommodated, such as when species in one lineage associate with multiple species in the other, or when there are unmatched taxa in one or both lineages. For both univariate and multivariate data, the method displays appropriate typ...

通过系统发育回归（phylogenetic regression）分析谱系内物种种间性状相关性，是比较进化生物学的基础性研究内容；但当目标性状来源于两类彼此协同进化的谱系时，在双系统发育框架下评估此类关联的方法仍未得到充分开发。本研究对基于置换的多元系统发育回归（multivariate permutation-based phylogenetic regression）方法进行拓展，以在兼顾两类互作物种各自系统发育关系的前提下，分析其性状相关性。该拓展方法可适配单变量与多变量响应数据，且支持纳入一个或多个自变量，包括环境协变量。该方法还可处理互作谱系间物种对应关系不完善的场景，例如某一类谱系中的物种与另一谱系中的多个物种存在关联，或两类谱系中存在未匹配的分类单元。针对单变量与多变量数据，该方法展现出适配的[原文此处内容未完整给出]