61

ECOM II

Environmental data

Working environmental data

Eigenvalues

10.6

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

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