Department of Earth Sciences, Environment and Resources, University of Naples Federico II, Napoli, Italy.
Department of Earth Sciences, University of Florence, Firenze, Italy.
PLoS One. 2019 Jan 25;14(1):e0210101. doi: 10.1371/journal.pone.0210101. eCollection 2019.
Recognizing evolutionary trends in phenotypic means and rates requires the application of phylogenetic comparative methods (PCMs). Most PCMs are unsuited to make full use of fossil information, which is a drawback, given the inclusion of such data improves, and in some cases even corrects, the proper understanding of trait evolution. Here we present a new computer application, written in R, that allows the simultaneous computation of temporal trends in phenotypic mean and evolutionary rate along a phylogeny, and to contrast such patterns among different clades within the tree. By using simulation experiments, we show the new implementation, names search.trend is as powerful as existing PCM tools in discerning macroevolutionary patterns in phenotypic means and rates, but differently from any other PCM allows comparing individual clades to each other, and provides rich information about trait evolution for all lineages in the tree.
识别表型均值和速率的进化趋势需要应用系统发育比较方法(PCMs)。大多数 PCMs 都不适合充分利用化石信息,这是一个缺点,因为包含这些数据可以改进,在某些情况下甚至可以纠正对性状进化的正确理解。在这里,我们介绍了一个新的计算机应用程序,它用 R 编写,可以沿系统发育同时计算表型均值和进化率的时间趋势,并对比树中不同分支之间的这种模式。通过使用模拟实验,我们表明新的实现,名为 search.trend 的程序在辨别表型均值和速率的宏观进化模式方面与现有的 PCM 工具一样强大,但与任何其他 PCM 不同的是,它允许相互比较各个分支,并为树中的所有谱系提供有关性状进化的丰富信息。