Abstract

Monitoring of macroinvertebrate communities is frequently used to define the ecological health status of rivers. Ideally, biomonitoring should also give an indication on the major stressors acting on the macroinvertebrate communities supporting the selection of appropriate management measures. However, most indices are affected by more than one stressor. Biological traits (e.g. size, generation time, reproduction) could potentially lead to more stressor-specific indices. However, such an approach has rarely been tested.In this study we classify 324 macroinvertebrate taxa as vulnerable (decreasing abundances) or tolerant (increasing abundances) along 21 environmental gradients (i.e. nutrients, major ions, oxygen and micropollutants) from 422 monitoring sites in Germany using Threshold Indicator Taxa Analysis (TITAN). Subsequently, we investigate which biological traits and taxonomic groups are associated with taxa classified as vulnerable or tolerant with regard to specific gradients.The response of most taxa towards different gradients was similar and especially high for correlated gradients. Traits associated with vulnerable taxa across most gradients included: larval aquatic life stages, isolated cemented eggs, reproductive cycle per year <1, scrapers, aerial and aquatic active dispersal and plastron respiration. Traits associated with tolerant taxa included: adult aquatic life stages, polyvoltinism, ovoviviparity or egg clutches in vegetation, food preference for dead animals or living microinvertebrates, substrate preference for macrophytes, microphytes, silt or mud and a body size >2–4cm.Our results question whether stressor-specific indices based on macroinvertebrate assemblages can be achieved using single traits, because we observed that similar taxa responded to different gradients and also similar traits were associated with vulnerable and tolerant taxa across a variety of water quality gradients. Future studies should examine whether combinations of traits focusing on specific taxonomic groups achieve higher stressor specificity.

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