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1. To assess changes in stoichiometric constraints on stream benthos, we measured elemental composition of epilithon and benthic macroinvertebrates in intrinsically Plimited mountain rivers, upstream and downstream of low-level anthropogenic nutrient enrichment by effluents of municipal wastewater treatment plants. 2. While there was a broad range in the elemental composition of epilithon (C : P ratios of 200-16 500, C : N ratios of 8-280, N : P ratios of 8-535) and heptageniid mayfly scrapers (C : P ratios of 125-300, C : N ratios of 5.1-7.2, N : P ratios of 20-60), the average C : P ratio of epilithon was 10-fold lower and the average C : N ratio twofold lower at more nutrient-rich downstream sites. Nutrient ratios in benthic macroinvertebrates were lower than in epilithon and varied little between relatively nutrient-poor and nutrient-rich sites. 3. We modified the existing definition of producer-consumer elemental imbalance to allow for variation in consumer nutrient content. We defined this 'non-homeostatic' imbalance as the perpendicular distance between the producer and consumer C : P, C : N, or N : P ratios, and the 1 : 1 line. 4. At P-limited sites, the estimated mayfly N : P recycling ratio was higher than the N : P ratio in epilithon, suggesting nutrient recycling by consumers could accentuate Plimitation of epilithon. 5. Measuring the degree of producer-consumer nutrient imbalance may be important in predicting the magnitude of effects from nutrient enrichment and can help elucidate the causes and consequences of ecological patterns and processes in rivers.

Ten data sets from published studies of freshwater benthic macroinvertebrates were used to deduce the necessary level of taxonomic resolution (from genus to phylum) for assessing variation in community structure. Quantitative data sets describing communities of benthic invertebrates identified to genus were aggregated to family, order, class, and phylum. Bray-Curtis distances between each pair of communities in a given study were calculated at each level of taxonomic aggregation. Also, quantitative data were converted to qualitative (presence-absence) data and aggregated in the same manner. Jaccard's distances between communities were calculated for these data matrices. Correlations between the resulting distance matrices, calculated at different taxonomic resolutions, were quantified using Mantel's test (N. Mantel. 1967. Cancer Res. 27: 209-220). Distance matrices for different taxonomic resolutions were highly correlated (r >> 0.64) when based on quantitative data for all except 1 of the 10 studies. Correlations were lower and more variable for qualitative data sets. For the data sets investigated, genus-level identification did not usually provide a strikingly different description of community patterns than higher levels (e.g., family, order) of taxonomic identification.

The use of the reference condition approach (RCA) in environmental assessments is becoming more prevalent. Although the RCA was not explicitly described in Green's (1979) book on statistical methods for environmental biologists, we expanded his decision key for selecting an appropriate environmental study design to include this approach. The RCA compares the biological community at a potentially impacted ‘test’ site to communities found in minimally impacted ‘reference’ sites. However, to implement the RCA there are a number of assumptions and decisions that must be made. We compare several common multimetric and multivariate bioassessment methods to illustrate that four key decisions inherent in the RCA framework (i.e., criteria used for reference site selection, for grouping similar reference sites, for comparing test and reference sites, and for evaluating the cause of impacts) can markedly affect test site appraisals. Specific guidelines should be developed to select appropriate reference sites. Based on analyses of real and simulated data, we recommend a minimum of 20, but preferably 30 to 50 reference sites per group, and verification of groupings with more than one classification method. New approaches (e.g., test site analysis) incorporating the strengths of both multimetric and multivariate methods can be used to compare test and reference sites. Additional ecological information, models relating degree of impact to a stressor or habitat gradient, and variance partitioning can also be used to isolate the probable cause of impairment, and are particularly valuable when appropriate reference sites are unavailable.