The analysis of vegetationenvironment relationships by canonical correspondence analysis
 Cajo J. F. Ter Braak
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Canonical correspondence analysis (CCA) is introduced as a multivariate extension of weighted averaging ordination, which is a simple method for arranging species along environmental variables. CCA constructs those linear combinations of environmental variables, along which the distributions of the species are maximally separated. The eigenvalues produced by CCA measure this separation.
As its name suggests, CCA is also a correspondence analysis technique, but one in which the ordination axes are constrained to be linear combinations of environmental variables. The ordination diagram generated by CCA visualizes not only a pattern of community variation (as in standard ordination) but also the main features of the distributions of species along the environmental variables. Applications demonstrate that CCA can be used both for detecting speciesenvironment relations, and for investigating specific questions about the response of species to environmental variables. Questions in community ecology that have typically been studied by ‘indirect’ gradient analysis (i.e. ordination followed by external interpretation of the axes) can now be answered more directly by CCA.
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 Title
 The analysis of vegetationenvironment relationships by canonical correspondence analysis
 Journal

Vegetatio
Volume 69, Issue 13 , pp 6977
 Cover Date
 19870401
 DOI
 10.1007/BF00038688
 Print ISSN
 00423106
 Online ISSN
 15735052
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Keywords

 Canonical correspondence analysis
 Correspondence analysis
 Direct gradient analysis
 Ordination
 Speciesenvironment relation
 Trend surface analysis
 Weighted averaging
 Authors

 Cajo J. F. Ter Braak ^{(1)} ^{(2)}
 Author Affiliations

 1. Statistics Department Wageningen, TNO Institute of Applied Computer Science, P.O. Box 100, 6700 AC, Wageningen, The Netherlands
 2. Research Institute for Nature Management, P.O. Box 46, 3956 ZR, Leersum, The Netherlands