Variation, selection and evolution of function-valued traits
Variation, selection and evolution of function-valued traits
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DOI：
10.1023/a:1013323318612
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发表时间：
2001-11-01
期刊：
影响因子：
1.5
通讯作者：
Carter, PA
中科院分区：
文献类型：
--
作者：
Kingsolver, JG;Gomulkiewicz, R;Carter, PA
我们描述了一个新兴的框架来理解变异，选择和进化的表型性状是数学函数。我们使用了一个具体的经验例子——毛虫生长速率的热性能曲线（TPCs）——来证明函数值性状的模型是如何自然地扩展了更熟悉的、相关的、数量性状的多变量模型。我们强调三点。首先，因为函数值特征是连续函数，它们的变化模式有重要的限制，这些限制不能被多变量模型捕获。功能价值性状的表型和遗传变异可以用方差-协方差函数及其相关的特征函数来量化：我们说明了这些是如何估计的，以及它们对tpc的生物学解释。其次，对函数值性状的选择本身就是一个函数，用选择梯度函数来定义。对于tpc，选择梯度描述了生物体的性能和适合度之间的关系如何随着温度的变化而变化。我们展示了TPCs的选择梯度函数的形式如何与选择过程中环境状态（毛虫温度）的频率分布相关。第三，利用遗传方差-协方差和选择梯度函数预测功能价值性状的进化响应。我们说明了即使平均表型和选择梯度本身是温度的线性函数，tpc的非线性进化反应也可能发生。最后，我们讨论了未来研究功能价值性状演化的一些方法和经验挑战。
We describe an emerging framework for understanding variation, selection and evolution of phenotypic traits that are mathematical functions. We use one specific empirical example - thermal performance curves (TPCs) for growth rates of caterpillars - to demonstrate how models for function-valued traits are natural extensions of more familiar, multivariate models for correlated, quantitative traits. We emphasize three main points. First, because function-valued traits are continuous functions, there are important constraints on their patterns of variation that are not captured by multivariate models. Phenotypic and genetic variation in function-valued traits can be quantified in terms of variance-covariance functions and their associated eigenfunctions: we illustrate how these are estimated as well as their biological interpretations for TPCs. Second, selection on a function-valued trait is itself a function, defined in terms of selection gradient functions. For TPCs, the selection gradient describes how the relationship between an organism's performance and its fitness varies as a function of its temperature. We show how the form of the selection gradient function for TPCs relates to the frequency distribution of environmental states (caterpillar temperatures) during selection. Third, we can predict evolutionary responses of function-valued traits in terms of the genetic variance-covariance and the selection gradient functions. We illustrate how non-linear evolutionary responses of TPCs may occur even when the mean phenotype and the selection gradient are themselves linear functions of temperature. Finally, we discuss some of the methodological and empirical challenges for future studies of the evolution of function-valued traits.