Clustering and canonical correspondence analysis of phytoplankton and environmental variables in Swedish lakes

Phytoplankton data consisting of 145 species from a limnological study of lakes from relatively undisturbed areas throughout Sweden were analysed in relation to 11 physical and chemical environmental variables. Three multivariate methods were applied: WPGMA clustering and TWINSPAN for classification, and detrended canonical correspondence analysis (DCCA), a recent technique which extracts ordination axes that can be related directly to variation in the environment. Three types of lakes were recognized consistently: acid humic lakes with Gonyostomum semen as the dominant species, very acid impoverished lakes with rather few, stress-tolerant species, and subarctic lakes with low total biomass but with a varied phytoplankton flora. DCCA allowed a straightforward display of the locations of lakes and species along environmental gradients (including the acidification gradient) reflected in phytoplankton composition. It is suggested that such analyses may be a useful tool for the early detection of environmental change.