Hierarchical, multi-scale decomposition of species-environment relationships
Hierarchical, multi-scale decomposition of species-environment relationships
复制标题
DOI：
10.1023/a:1021571603605
复制
发表时间：
2002-11-01
影响因子：
5.2
通讯作者：
McGarigal, K
中科院分区：
文献类型：
--
作者：
Cushman, SA;McGarigal, K
我们提出了一种适应现有的方差划分方法来分解层次结构、多尺度数据集中的物种-环境关系。该方法将分层、多尺度的概念模型转化为方差的统计分解。它使用一系列局部规范排序，将物种-环境关系中可解释的差异划分为独立的和混淆的组成部分，便于测试不同组织级别的因素在驱动系统行为方面的相对重要性。我们在一个基于美国俄勒冈海岸山脉森林鸟类群落对不同栖息地尺度的响应的经验例子的背景下讨论了该方法。这个例子展示了鸟类群落变化的两层分解，可以用嵌套在三个空间尺度(地块、斑块和景观)的一系列栖息地因素来解释。这种方法特别适合于层次结构景观数据的问题。明确的多尺度方法是从在不同尺度层面进行单独分析向前迈出的重要一步，因为它允许全面分析不同尺度上因素的相互作用，并促进从理论上进行生态解释。
We present an adaptation of existing variance partitioning methods to decompose species-environment relationships in hierarchically-structured, multi-scaled data sets. The approach translates a hierarchical, multi-scale conceptual model into a statistical decomposition of variance. It uses a series of partial canonical ordinations to divide the explained variance in species-environment relationships into its independent and confounded components, facilitating tests of the relative importance of factors at different organizational levels in driving system behavior. We discuss the method in the context of an empirical example based on forest bird community responses to multiple habitat scales in the Oregon Coast Range, USA. The example presents a two-tiered decomposition of the variation in the bird community that is explainable by a series of habitat factors nested within three spatial scales (plot, patch, and landscape). This method is particularly suited for the problems of hierarchically structured landscape data. The explicit multi-scale approach is a major step forward from conducting separate analyses at different scale levels, as it allows comprehensive analysis of the interaction of factors across scales and facilitates ecological interpretation in theoretical terms.