Variation Partitioning Techniques
Pp. 55-60 (6)
Variation partitioning is another important statistical method in numerical
ecology studies. The purpose of variation partitioning is to decompose the variation
presented by the species compositions across the studied sites into different categories.
These categories of variation could be attributed to spatial covariates, environmental
covariates, climatic covariates or others. In community ecology, spatial component of
variation in the resultant ecological communities widely existed in ecological data sets.
This is because spatial autocorrelation was a very natural phenomenon describing the
similarity of neighboring objects (e.g., species richness, species community structure or
others). However, environmental gradients are also very dominant and widely observed
in ecological community structure. Thus, what are the relative importance of
environmental gradients and spatial autocorrelation on structuring ecological
communities? Variation partitioning helps address this question.
ANOVA, environment-trait relationship, F-statistics, Moran’s I index,
multivariate statistics, ordination analyses, spatial autocorrelation, spatial
statistics, species distribution and diversity patterns, temporal autocorrelation,
Department of Renewable Resources, University of Alberta Edmonton, T6G 2H1, Canada.