A strategy is presented for analysing marine biological survey data and relating the biotic patterns to environmental data. To avoid circular argument, biotic and environmental data are kept separate. The strategy is illustrated by a worked example using data on the distribution of 182 nematode species in 107 samples in the River Exe estuary. Nineteen stations are grouped Into 4 main clusters using complementary classification and multi-dimensional scaling (MDS) ordination techniques. These are both based on root-root transformed abundance data with the Bray-Curtis measure of similarity. Indicator species characterising each group are extracted using information statistics. Inverse analyses give clusters of co-occurring species which are strongly related to the station groups. Relationships of station groups to environmental variables are revealed by superimposing data for one variable at a time on the MDS plot, showing that some station groups differ in sediment granulometry and others in salinity, for example. Some of the other factors plotted show no difference between station groups. Similarly, physiognomic characteristics of the species are superimposed on the MDS plots of the inverse analysis of species groups, revealing differences in setal length and trophic status between the species groups. Finally, the 4 major station groups and species groups are related to one another in terms of morphological adaptation to the habitat
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