结构方程模型及其在生态学中的应用

A brief introduction of structural equation model and its application in ecology

基于多变量统计方法同时研究自然系统内多个因子之间的相互关系,是阐释复杂的自然系统的一个重要手段。相比传统的多变量统计法,结构方程模型基于研究者的先验知识预先设定系统内因子间的依赖关系,不仅能够判别各因子之间的关系强度(路径系数),还能对整体模型进行拟合和判断,从而能更全面地了解自然系统。由于结构方程模型只在近年才被应用到生态学的数据分析中,因此该文试图对其作一简略介绍,包括结构方程模型的定义和变量类型,结合事例研究展现结构方程模型分析的一般步骤、在生态学中的应用以及相关软件的介绍等。望能为相关研究人员提供直观的认识,加强结构方程模型在生态学数据分析中的应用。

Natural systems are essentially complex. In most cases, fully understanding natural systems requires the capacity to examine simultaneous influences and responses among multiple interacting factors. Compared with traditional multivariate methods, structural equation model （SEM） could specify the causal or dependent relationships among variables using the prior knowledge of researchers before conducting relevant experiments, i.e. initial models. SEM could not only identify the individual path coefficient for each relationship, but also estimate the whole model fit to determine whether to revise the initial models. We attempt to introduce SEM from the following aspects： definition and types of variables in SEM, detailed procedures for how to analyze data through SEM, some applications of SEM in ecology and recommended software. We encourage more researchers to apply SEM in ecological data analyses in order to improve understanding of natural systems and advance the field of ecology.