Quantifying the causal pathways contributing to natural selection

被引:16
|
作者
Henshaw, Jonathan M. [1 ,2 ]
Morrissey, Michael B. [3 ]
Jones, Adam G. [2 ]
机构
[1] Univ Freiburg, Inst Biol 1, D-79104 Freiburg, Germany
[2] Univ Idaho, Dept Biol Sci, Moscow, ID 83844 USA
[3] Univ St Andrews, Sch Biol, St Andrews KY16 9TF, Fife, Scotland
关键词
Causal derivative; causality; path analysis; structural equation modeling (SEM); SEXUAL SELECTION; EVOLUTION; EPISODES; TRAITS; MODELS; INFERENCE; EQUATION; BIASES;
D O I
10.1111/evo.14091
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The consequences of natural selection can be understood from a purely statistical perspective. In contrast, an explicitly causal approach is required to understandwhytrait values covary with fitness. In particular, key evolutionary constructs, such as sexual selection, fecundity selection, and so on, are best understood as selectionviaparticular fitness components. To formalize and operationalize these concepts, we must disentangle the various causal pathways contributing to selection. Such decompositions are currently only known for linear models, where they are sometimes referred to as "Wright's rules." Here, we provide a general framework, based on path analysis, for partitioning selection among its contributing causal pathways. We show how the extended selection gradient-which represents selection arising from a trait's causal effects on fitness-can be decomposed into path-specific selection gradients, which correspond to distinct causal mechanisms of selection. This framework allows for nonlinear effects and nonadditive interactions among variables, which may be estimated using standard statistical methods (e.g., generalized linear [mixed] models or generalized additive models). We thus provide a generalization of Wright's path rules that accommodates the nonlinear and nonadditive mechanisms by which natural selection commonly arises.
引用
收藏
页码:2560 / 2574
页数:15
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