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Phylogenetic Comparative Methods for Evaluating the Evolutionary History of Function-Valued Traits

机译:系统发育比较方法,评价功能值特征的进化史

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摘要

Phylogenetic comparative methods offer a suite of tools for studying trait evolution. However, most models inherently assume fixed trait values within species. Although some methods can incorporate error around species means, few are capable of accounting for variation driven by environmental or temporal gradients, such as trait responses to abiotic stress or ontogenetic trajectories. Such traits, often referred to as function-valued or infinite-dimensional, are typically expressed as reaction norms, dose-response curves, or time plots and are described by mathematical functions linking independent predictor variables to the trait of interest. Here, I introduce a method for extending ancestral state reconstruction to incorporate function-valued traits in a phylogenetic generalized least squares (PGLS) framework, as well as extensions of this method for testing phylogenetic signal, performing phylogenetic analysis of variance(ANOVA), and testing for correlated trait evolution using recently proposed multivariate PGLS methods. Statistical power of function-valued comparative methods is compared to univariate approaches using data simulations, and the assumptions and challenges of each are discussed in detail. [ancestral state reconstruction; dose-response curves; evolution of tolerance; function-valued traits; infinite-dimensional traits; phenotypic plasticity; PGLS; phylogenetic comparative method; phylogenetic signal; reaction norms.]
机译:系统发育比较方法提供了一套用于研究性状进化的工具。但是,大多数模型固有地假设物种内的性状值固定。尽管某些方法可能会在物种均值周围引入误差,但很少有方法能够解释由环境或时间梯度驱动的变化,例如对非生物胁迫或个体发育轨迹的性状响应。此类特征通常称为函数值或无穷维,通常表示为反应范数,剂量响应曲线或时间图,并通过将独立预测变量与目标特征相联系的数学函数进行描述。在这里,我介绍了一种扩展祖先状态重构的方法,以将功能值特征整合到系统发育广义最小二乘(PGLS)框架中,以及该方法的扩展,用于测试系统发育信号,进行方差系统发育分析(ANOVA),以及使用最近提出的多元PGLS方法进行相关性状进化的测试。使用数据模拟将函数值比较方法的统计能力与单变量方法进行比较,并对每种方法的假设和挑战进行详细讨论。 [祖国重建;剂量反应曲线宽容的演变;功能价值特征无限维特征表型可塑性PGLS;系统发育比较方法;系统发生信号;反应规范。]

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