Summary 1. The application of environmental policy and legislation across large‐scale administrative units creates a growing need for standard tools to assess and monitor the ‘ecological health’ of rivers, a requirement that can be achieved through the description of ecological functions of lotic invertebrate species in river communities. 2. To assess alternative metrics, we tested how the functional structure (described by 14 biological traits) of invertebrate communities in 190 large river reaches differed with respect to differences in taxonomic resolution (species, genus, family), taxa weighting of traits (raw abundance, ln‐transformed abundance, presence–absence data) and consideration of alien species (inclusion or exclusion), and how these differences influenced the potential of functional descriptions to discriminate river reaches across a gradient of multiple human impacts. 3. Functional descriptions derived at the level of species, genera and families were very similar, whereas functional descriptions derived from raw abundances differed significantly from those derived from both ln‐transformed abundances and presence–absence data. Functional descriptions after the exclusion of alien species differed considerably from those including alien species. 4. Generally, the functional descriptions significantly discriminated river reaches according to the level of human impact. Taxonomic resolution scarcely influenced the discrimination of impact levels, whereas the use of raw abundances decreased impact discrimination in comparison with ln‐transformed abundances and presence–absence data. Exclusion of alien species also decreased discrimination of impact levels. 5. When considered separately, individual biological traits describing maximal size, number of descendants per reproductive cycle, number of reproductive cycles per individual, life duration of adults, reproductive method, parental care, body form and feeding habits had the highest potential to discriminate the level of human impact. 6. Our findings indicate that genus or perhaps family identifications are sufficient for large‐river biomonitoring using invertebrate traits. Although raw abundances could provide a better discrimination of low levels of human impact, presence–absence data should be sufficient to discriminate functional community changes caused by elevated levels of human impact across Europe.

1. Studies on biodiversity and ecosystem function require considering metrics for accurately describing the functional diversity of communities. The number of taxa (richness) is commonly used to characterise biological diversity. The disadvantage of richness as a measure of biological diversity is that all taxa are taken into account on an equal basis regardless of their abundance, their biological characteristics or their function in the ecosystem. 2. To circumvent this problem, we applied a recently described measure of biological diversity that incorporates dissimilarities among taxa. Dissimilarities were defined from biological traits (e.g. life history, morphology, physiology and behaviour) of stream invertebrate taxa and the resulting biological diversity index was considered as a surrogate for functional diversity. 3. As sampling effort is known to affect the number of taxa collected within a reach, we investigated how change in functional diversity is affected by sampling effort. We used stream invertebrate community data from three large European rivers to model accumulation curves and to assess the number of samples required to estimate (i.e. closeness to the maximal value) functional diversity and genera richness. We further evaluated the precision of estimates (i.e. similarity of temporal or spatial replicates) of the total functional diversity. 4. As expected, richness estimates were strongly dependent on sampling effort, and 10 replicate samples were found to underestimate actual richness. Moreover, richness estimates showed much variation with season and location. In contrast, functional diversity had greater accuracy with less sampling effort and the precision of the estimates was higher than richness both across sampling occasions and sampling reaches. These results are further arguments towards conducting research on the design of a biomonitoring tool based on biological traits.

1. Multiple biological invertebrate traits (e.g. body size, body form, dispersal potential) each described through multiple categories (e.g. small, intermediate or large body size) could serve as indicators of particular types of human impacts on large rivers. The trait composition of natural invertebrate communities is scarcely constrained by taxonomic differences among them, i.e. individual trait categories could be used to discriminate various types of human impacts across large geographic areas, which would require the definition of trait patterns for conditions of relatively low human impact. 2. Using large databases to link 14 biological traits (described through 66 categories) of invertebrate genera to their occurrence in running water reaches with known environmental conditions, we examined the accuracy of various approaches to predict expected trait variation across least impacted river reaches (LIRRs) of Europe in a stepwise analytical procedure. This procedure included Monte Carlo simulations and ultimately the assignment of test-LIRRs (reaches not used in previous analyses) to the previously defined LIRR conditions. 3. Distance from the source was an integrative variable capturing some (but not all) landscape features (e.g. altitude) or habitat variables (e.g. reach shear stress). Correspondingly, the relative abundance of many trait categories changed along 13 European running waters, although particularly the intensity of these changes differed among these 13 running waters. 4. 'Downstream models' (using only distance from the source as predictor) provided the least accurate predictions of expected invertebrate trait patterns when compared with 'landscape models' (using distance from the source in combination with altitude and/or latitude) or 'habitat models' (using reach shear stress, mean annual air temperature and/or pH of the water). Landscape models provided more accurate predictions than habitat models, but the improvement of predictions of expected invertebrate traits patterns obtained using landscape models was negligible in comparison with a simpler 'mean-model' approach, suggesting that defining LIRR conditions through simple descriptions of frequency distributions would be sufficient for the future biomonitoring of large European rivers. 5. To define these LIRR conditions, we used the average of the relative abundance of each trait category from 68 LIRRs ( ‡40 m wide) as expected LIRR values, and computed LIRR frequency distributions that described the deviations of the 68 individual LIRRs from these expected values. Computing such deviations from the expected LIRR values for 57 testLIRRs (also ‡40 m wide), 57 trait categories correctly assigned >90% of the test-LIRRs to LIRR conditions if the latter were defined through the entire range of the LIRR frequency distributions. To the 90%-range enveloped by the LIRR frequency distributions, 42 trait categories correctly assigned >80% and 12 categories >90% of the test-LIRRs. 6. Using a framework that required no regionalisation of a large geo...

No abstract

We compared the longitudinal plankton development in the two large rivers Rhine and Elbe by means of four Lagrangian sampling campaigns performed within the time span 2009-2011. The campaigns revealed low chlorophyll concentrations in the Rhine along a long river stretch (Rhine-km 170 to 854) with maximum values below 5 μg L À1 in 2010. In contrast, the Elbe (Elbe-km 4 to 582) showed high and longitudinally increasing chlorophyll concentrations with maximal values of 174 μg L À1 in 2009 and 123 μg L À1 in 2011. Additional samples of the benthic bivalves along the river stretches revealed high densities of the filter feeders in the Rhine that could potentially explain losses of plankton production. Their densities in the Elbe were significantly lower, making important losses to benthic filter feeders unlikely. However, strong phytoplankton growth was observed during the sampling campaign in 2011 in the Rhine coinciding with a low discharge event. This resulted in an exceptionally high chlorophyll value of up to 244 μg L À1 in the lower river sections, a value that was not reached in the last two decades of continuous water quality monitoring in the Rhine. Even though we cannot fully explain this phenomenon, it shows that phytoplankton has a high growth potential in the Rhine but is usually controlled by other mechanisms. Tributaries represented an additional and important source of plankton biomass and suspended substances in the Rhine, whereas they primarily diluted the plankton concentrations in the Elbe.