PUTTING THINGS IN EVEN BETTER ORDER - THE ADVANTAGES OF CANONICAL CORRESPONDENCE-ANALYSIS

Canonical Correspondence Analysis (CCA) is quickly becoming the most w idely used gradient analysis technique in ecology. The CCA algorithm i s based upon Correspondence Analysis (CA), an indirect gradient analys is (ordination) technique. CA and a related ordination technique, Detr ended Correspondence Analysis, have been criticized for a number of re asons. To test whether CCA suffers from the same defects, I simulated data sets with properties that usually cause problems for DCA. Results indicate that CCA performs quite well with skewed species distributio ns, with quantitative noise in species abundance data, with samples ta ken from unusual sampling designs, with highly intercorrelated environ mental variables, and with situations where not all of the factors det ermining species composition are known. CCA is immune to most of the p roblems of DCA.