Data and Code in Simuation and Case Study

Phylogenetic signals are widely used in the ecological and evolutionary research area. Trait data used to detect phylogenetic signals can be continuous or discrete. Existing indices are either designed for continuous variables or for discrete variables, but not both. Moreover, most existing methods could only perform phylogenetic detection for each trait separately. Here, we developed a method, called M statistic, to detect the phylogenetic signals in continuous traits, discrete traits, and combinations of multiple traits. We compared the performance of our new approach with existing commonly used indices using simulated continuous data. The results showed that our method is not inferior to the existing methods. It also performed well in handling discrete variables and multi-variable combinations. Then we used the trait data of turtles (Testudines) to demonstrate the utility of our new method. We provided an R package called “phylosignalDB” to facilitate all calculations.系统发育信号（Phylogenetic signals）在生态与进化研究领域应用极为广泛。用于检测系统发育信号的性状数据（Trait data）可分为连续型与离散型两类。当前主流的检测指数要么仅适用于连续变量，要么仅针对离散变量设计，无法同时兼容两类变量。此外，多数现有方法仅能针对单个性状单独开展系统发育信号检测。本研究开发了一种名为M统计量（M statistic）的方法，可实现连续性状、离散性状及多性状组合的系统发育信号检测。我们通过模拟连续数据集，将新方法与现有常用检测指数进行了性能对比，结果显示本方法的性能不劣于现有同类方法，且在处理离散变量与多变量组合时同样表现优异。随后，我们利用龟类（龟鳖目 Testudines）的性状数据验证了新方法的实际应用价值，并开发了名为"phylosignalDB"的R包（R package）以简化所有相关计算流程。