A technique, which uses environmental data to predict the macroinvertebrate fauna of running water sites, was used to investigate the response of faunal communities to flow regulation below a set of upland reservoirs in Great Britain . Five variables (total oxidised nitrogen, alkalinity, chloride, substratum type and site distance from stream source) were used to predict family presence and abundance at 30 regulated sites . The predictions were compared with the observed fauna recorded in samples taking in spring, summer and autumn . Of the 37 commonly occurring families 22 showed statistically significant trends . Twelve of these occurred at lower abundances than predicted and the effect was greatest in Heptageniidae, Simuliidae, Elminthidae, Perlodidae and Rhyacophilidae. Ten families were more more abundant than predicted and these included Polycentropodidae, Sphaeriidae, Sialidae and some groups of chironomids and oligochaetes . Fifteen families showed no significant trends . Most families showed little difference in the observed and expected frequency of occurrence in the 30 sites but Taeniopterygidae and Perlidae amongst others occurred at less than the expected number of sites and Hydridae, Prodiamesinae and Muscidae occurred more commonly than expected . These faunal responses are discussed in relation to environmental changes arising from flow regulation . The possible uses of the predictive technique in simulating and assessing the effects of regulation on downstream fauna are outlined .

SUMMARY 1. The EC Water Framework Directive (2000/60/EC) recognises the need for biological monitoring. Indices derived from standard samples of macroinvertebrates are frequently used for the appraisal of the ecological quality of rivers. However, information on the errors or chance variation that can influence the value of an index is also important. 2. This paper describes a study to quantify the observed sampling variation in three ecological indices based on the Biological Monitoring Working Party (BMWP) score system across a wide range of river types and qualities. The indices are number of BMWP taxa, BMWP score and Average Score Per Taxon (ASPT). 3. The study sites were selected to encompass the four major groups within the River InVertebrate Prediction And Classification System (RIVPACS) site classification for Britain. Within each group, four sites which differed in ecological quality grade were chosen (total of 16 sites). At each site three standard RIVPACS samples were taken in each of spring, summer and autumn by trained staff. In each season, two samples were taken by one biologist and the third by a different individual to allow for within and between‐operator variation. 4. The effects of sampling variation within a season on the number of taxa, BMWP score and ASPT across all sites, irrespective of operator, could be represented by some simple parameters. We found that the sampling SD of the square root of the number of taxa, square root of BMWP score and the untransformed ASPT were roughly constant in each case, irrespective of site type or quality. For each index, SD for two and three seasons combined samples were smaller than for single season samples. 5. Inter‐operator influences on sample values were negligible (4–12% of total sampling SD) in this study. This underlines the importance of adequate training for all staff involved in extensive monitoring programmes which use standard procedures from one year to the next, but may involve different staff. 6. Indices for number of taxa, BMWP score and ASPT were all estimated with greater precision from combined season samples than from the averages of two or three seasons' samples. 7. This study enables us to estimate confidence intervals for the values of the number of taxa, BMWP score and ASPT based on single season, two or three season combined samples collected using standard RIVPACS procedures for any river site in Britain. The results can also be used in simulation models which incorporate the effects of sampling variation into assessments of the ecological quality of river sites based on the ratio of observed to RIVPACS expected values of these BMWP indices.

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This study assesses the impact of errors in sorting and identifying macroinvertebrate samples collected and analysed using different protocols (e.g. STAR-AQEM, RIVPACS). The study is based on the auditing scheme implemented in the EU-funded project STAR and presents the first attempt at analysing the audit data. Data from 10 participating countries are analysed with regard to the impact of sorting and identification errors. These differences are measured in the form of gains and losses at each level of audit for 120 samples. Based on gains and losses to the primary results, qualitative binary taxa lists were deducted for each level of audit for a subset of 72 data sets. Between these taxa lists the taxonomic similarity and the impact of differences on selected metrics common to stream assessment were analysed. The results of our study indicate that in all methods used, a considerable amount of sorting and identification error could be detected. This total impact is reflected in most functional metrics. In some metrics indicative of taxonomic richness, the total impact of differences is not directly reflected in differences in metric scores. The results stress the importance of implementing quality control mechanisms in macroinvertebrate assessment schemes.