MEPS 253:17-24 (2003)  -  doi:10.3354/meps253017

ABSTRACT: The literature on the ecology of marine assemblages includes frequent examples of data analysis with no well-defined alternative hypotheses for the definition of environmental variables (independent matrix for multivariate methods). Alternative models, whereby spatial or temporal patterns are investigated, should be explicitly assumed. We present a parsimonious procedure for model selection in multivariate data combined with canonical correspondence analysis to determine the measure of explained variance for each tested model, using Akaike¹s information criterion (AIC) for model selection. The AIC procedure is an effective tool for model selection and, in contrast to other conventional procedures that use only 1 implicit model and ignore other community patterns, it provides a framework for ranking hierarchical patterns that adds an alternative non-disjunctive perspective to assemblage analysis. Hierarchical patterns are revealed as layers in a scale-dependent framework.

KEY WORDS: Akaike¹s information criterion · Model selection · Spatial models · Temporal models · Canonical correspondence analysis · Parsimony · Marine benthic communities · Community dynamics