Testing hypotheses in evolutionary ecology with imperfect detection: capture-recapture structural equation modeling
Testing hypotheses in evolutionary ecology with imperfect detection: capture-recapture structural equation modeling
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DOI：
10.1890/11-0258.1
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发表时间：
2012-02-01
期刊：
影响因子：
4.8
通讯作者：
Gimenez, Olivier
中科院分区：
文献类型：
--
作者：
Cubaynes, Sarah;Doutrelant, Claire;Gimenez, Olivier
研究自然种群的进化机制通常需要测试涉及个体和环境变量之间直接和间接关系的多因素因果关系。为了提供无偏的人口统计参数估计，也必须考虑到对个人的不完美检测。为了解决这些问题，我们开发了一种将结构方程模型与捕获-再捕获模型（CR-SEM）相结合的新方法，该方法允许调查在人口统计参数中观察到的关于个体和环境变异性的竞争性假设。我们在贝叶斯框架中使用马尔可夫链蒙特卡罗抽样来(1)估计模型参数，(2)实施模型选择程序来评估关于因果机制的竞争假设，以及(3)使用后验预测检查来评估模型与数据的拟合。我们用两个关于野生鸟类种群的案例研究来说明我们方法的价值。我们首先通过分析普通黑鸟（Turdus merula）形态性状的选择梯度，证明CR-SEM可以用于量化选择对一组表型性状的作用。在对蓝山雀（Cyanistes caeruleus）的第二个案例研究中，我们说明了在考虑不同环境条件的情况下，使用CR-SEM来研究野生动物的进化权衡。
Studying evolutionary mechanisms in natural populations often requires testing multifactorial scenarios of causality involving direct and indirect relationships among individual and environmental variables. It is also essential to account for the imperfect detection of individuals to provide unbiased demographic parameter estimates. To cope with these issues, we developed a new approach combining structural equation models with capture-recapture models (CR-SEM) that allows the investigation of competing hypotheses about individual and environmental variability observed in demographic parameters. We employ Markov chain Monte Carlo sampling in a Bayesian framework to (1) estimate model parameters, (2) implement a model selection procedure to evaluate competing hypotheses about causal mechanisms, and (3) assess the fit of models to data using posterior predictive checks. We illustrate the value of our approach using two case studies on wild bird populations. We first show that CR-SEM can be useful to quantify the action of selection on a set of phenotypic traits with an analysis of selection gradients on morphological traits in Common Blackbirds (Turdus merula). In a second case study on Blue Tits (Cyanistes caeruleus), we illustrate the use of CR-SEM to study evolutionary trade-offs in the wild, while accounting for varying environmental conditions.