The influence of multiple stressors on macroinvertebrate communities and ecosystem attributes in Northern Italy pre-Alpine rivers and streams

2020 
Abstract The definition of relationships among the attributes of macroinvertebrate communities and environmental gradients is fundamental to understand ecological dynamics. Testing the response of macroinvertebrate communities and the related metrics to the action of multiple drivers is crucial to provide reliable tools for the management and conservation of freshwater ecosystems. In this study habitat conditions, seasons and physical–chemical water characteristics were evaluated as potential limiting factors for macroinvertebrate communities. 42 sites, along 11 pre-Alpine rivers and streams, were surveyed for macroinvertebrate communities and water chemistry, collecting a total of 387 samples. Hydromorphological characteristics and habitat availability in each sampling site were assessed to describe different features of channel, banks and vegetation that can be relevant for management purposes. Macroinvertebrate community characteristics were summarized by both structural metrics (i.e. density, diversity and taxonomy-based) and ecosystem attributes derived from functional trait analysis. Functional traits are based on morphological and behavioural attributes associated with feeding, modes of attachment, concealment and locomotion, together with voltinism and drift propensity. In this framework, quantitative models have been developed to predict the potential characteristics of macroinvertebrate communities as a function of selected environmental variables. These relationships can be used to predict the effects of river restoration programs on macroinvertebrate diversity and ecosystem processes. The various metrics considered in this study may help to raise a better awareness in the natural functioning of river ecosystems, the selection of effective strategies for the conservation of biological communities, and the evaluation of river restoration success, thus supporting decision-making processes.
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