Environmental data
Working environmental data
Correspondence Analysis
Canonical Correspondence Analysis (CCA)  is an ordination method widely used
among ecologists. This method allows the analysis of a species abundance matrix
with respect to a second table of explanatory environmental variables. Both the
species and environmental variable tables must refer to the same samples and must
therefore have the same number of samples.  CCA is a correspondence analysis of the
species data using linear constraints derived from a multiple linear
regression of the environmental variables against the species scores. The result is an
ordination that shows the relationship between the species, sites and environmental
variables. It is termed a  constrained ordination method as it is an extension of the
correspondence analysis with the environmental data acting as the constraint.
CCA is suited to community data sets where: (1) species responses to environmental
variables are unimodal (hump shaped), and (2) the important underlying
environmental variables have been measured. If you have not measured the most
important environmental variables, or your environmental variable measurements are
Copyright 2004  PISCES Conservation Ltd

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