Abstract

Aquatic ecosystems are amongst the most heavily altered ecosystems and exhibit a disproportional loss of biodiversity. Numerous stressors, such as nutrient enrichment, contaminant pollution, sedimentation and alterations in stream hydrology and habitat structure, account for these losses. Understanding these forces is of utmost importance to prevent riverine ecosystems from further deterioration and to provide helpful insights for restoration practices. In the present study, we analyse the response of biological indicators to a large number of environmental factors. For this, benthic invertebrate assemblages from 83 sites in Germany were described based on 25 metrics from four different metric types. The condition of the sites was described using 27 environmental factors: 13 for water quality, 4 for land use in the catchment and 10 for local scale habitat structure. The relative importance of single environmental predictors or predictor combinations for benthic invertebrate assemblages was analysed with single and multiple linear regression models. The results for the latter models were statistically supported via a bootstrap approach. The models revealed the importance of water quality and catchment-scale land use in explaining benthic invertebrate assemblages; in particular, chloride, oxygen, total organic carbon and the amounts of artificial surfaces and arable land were the most important predictors. Models including solely structural variables such as plan form, bank structures and substrate diversity had lower goodness of fit values than those for other variables. Regarding the four different assemblage metric types, functional metrics had on average lower goodness of fit values than composition/abundance, richness/diversity and sensitivity/tolerance metrics. Among the richness/diversity metrics, however, the model results for the Shannon–Wiener and Simpson diversity indices and evenness were poor. Our results show that catchment-related factors and water quality were of overriding importance in shaping biodiversity patterns and causing species loss. In contrast, structural degradation at a local scale was not the most significant stressor. This finding might explain why structural restoration at a reach scale often yields a low benefit–cost ratio and may be considered to represent inappropriate investment prioritisation.

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