Boucher Florian C, Démery Vincent
Institute of Systematic Botany, University of Zurich, Zurich, Switzerland;
Laboratoire de Physico-Chimie Théorique, UMR Gulliver 7083, CNRS and ESPCI-ParisTech, Paris, France
Syst Biol. 2016 Jul;65(4):651-61. doi: 10.1093/sysbio/syw015. Epub 2016 Feb 10.
Our understanding of phenotypic evolution over macroevolutionary timescales largely relies on the use of stochastic models for the evolution of continuous traits over phylogenies. The two most widely used models, Brownian motion and the Ornstein-Uhlenbeck (OU) process, differ in that the latter includes constraints on the variance that a trait can attain in a clade. The OU model explicitly models adaptive evolution toward a trait optimum and has thus been widely used to demonstrate the existence of stabilizing selection on a trait. Here we introduce a new model for the evolution of continuous characters on phylogenies: Brownian motion between two reflective bounds, or Bounded Brownian Motion (BBM). This process also models evolutionary constraints, but of a very different kind. We provide analytical expressions for the likelihood of BBM and present a method to calculate the likelihood numerically, as well as the associated R code. Numerical simulations show that BBM achieves good performance: parameter estimation is generally accurate but more importantly BBM can be very easily discriminated from both BM and OU. We then analyze climatic niche evolution in diprotodonts and find that BBM best fits this empirical data set, suggesting that the climatic niches of diprotodonts are bounded by the climate available in Australia and the neighboring islands but probably evolved with little additional constraints. We conclude that BBM is a valuable addition to the macroevolutionary toolbox, which should enable researchers to elucidate whether the phenotypic traits they study are evolving under hard constraints between bounds.
我们对宏观进化时间尺度上的表型进化的理解,很大程度上依赖于使用随机模型来研究系统发育中连续性状的进化。两种使用最广泛的模型,即布朗运动模型和奥恩斯坦-乌伦贝克(OU)过程模型,它们的不同之处在于,后者对一个性状在一个进化枝中所能达到的方差包含约束条件。OU模型明确地模拟了向性状最优值的适应性进化,因此已被广泛用于证明对一个性状存在稳定选择。在这里,我们引入一种新的系统发育中连续性状进化模型:两个反射边界之间的布朗运动,即有界布朗运动(BBM)。这个过程也模拟了进化约束,但属于非常不同的类型。我们给出了BBM似然性的解析表达式,并提出一种数值计算似然性的方法,以及相关的R代码。数值模拟表明BBM表现良好:参数估计通常是准确的,但更重要的是,BBM很容易与BM和OU区分开来。然后我们分析了双门齿目的气候生态位进化,发现BBM最适合这个实证数据集,这表明双门齿目的气候生态位受到澳大利亚和邻近岛屿现有气候的限制,但可能在进化过程中几乎没有受到额外的约束。我们得出结论,BBM是宏观进化工具箱中的一个有价值的补充,它应该能使研究人员阐明他们所研究的表型性状是否在边界之间的严格约束下进化。