Canonical Correspondence Analysis
CCA seeks an ordination of the sites (samples) in terms of their biological components
which is optimised in terms of the influence of environmental factors.
What is CCA
Selecting Environmental variables
Linear combinations of environmental variables
Dummy Environmental variables
Transforming environmental variables
Circular environmental variables
The normal situation is for the biological data to comprise a sample (column) by
species (row) array. The species data would comprise quantitative counts of the
number of individuals in each sample. (See
Creating and editing a data set
Presentation of Results Your output
CCA produces an ordination of the species and sites. It also produces biplots that
show the inferred ranking of the species along an environmental variable. The output
from ECOM is divided into a number of different sections of a tabbed notebook. These
are described below.
Correlation of Env. Vars
What is CCA?
Canonical correspondence analysis (CCA; ter Braak 1986, 1994) is an ordination
method in which the ordination of the biological (main) matrix by correspondence
analysis or reciprocal averaging is constrained by a multiple regression on the
variables included in the environmental matrix.
In ecological terms, the ordination of sites and species is constrained by their
relationships to environmental variables. If the environmental variables included are
major determinants of community structure and abundance of species changes along
these environmental gradients then this technique aids interpretation of community
structure and identification of the features that mould it.
The alternative approach is to use ordination techniques such as Correspondence
Analysis or Principal Components Analysis which ordinate the community (sites
species) data alone and then undertake an auxiliary analysis to identify the
Copyright 2004 PISCES Conservation Ltd