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Species abundances of Chironomidae (Insecta: Diptera) have often been excluded from studies of benthic river communities because of difficulties associated with sampling and identifying larvae . Chironomid pupal exuviae are easier to collect and identify and could be used to determine community structure if shown to be representative of local larval assemblages . Larvae were sampled along a 20 m chain secured over mid-channel gravels, upstream of two collection points for pupal exuviae . Proportional taxa abundances of pupal exuviae and larvae sampled from 130 m of stream were directly compared by a x2 test of independence and also separately fitted to four models of species abundance distribution . Observed proportions of taxa were not independent of the life stage sampled . The greatest discrepancies occurred with species of pupal exuviae that were absent as larvae from the gravel . The log series model provided the best fit with both pupal and larval data . Collections of pupal exuviae had greater species richness and evenness than samples of larvae . This was considered to be a consequence of sampling larvae from the gravel habitat alone .

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Phytoplankton were sampled fortnightly in summer and monthly in winter for 33 months to determine temporal and spatial variations in taxonomic structure and relate these to the physical and chemical environment. Using canonical correspondence analysis, environmental variables selected by stepwise regression were found to be correlated with the major variable(s) determining phytoplankton composition. An improved proportion of explained variance was achieved by classifying data into three seasonal subsets. The highest percentage of explained variance in phytoplankton composition was achieved for the months March to May (36·5%), the lowest variance explained was for the period June to September (28·6%). Within each season, general linear modelling was used to predict taxa responses to variations in particular environmental variables. Taxa responses to discharge are presented as examples for determining river management policies. The rationale of conceptual models and the empirical models used for this study are discussed. © 1997 John Wiley & Sons, Ltd.