Biology-based approaches to unravel multiple stressor impacts on aquatic ecosystems

Restoration measures to restore aquatic ecosystems are widely applied, but often remain ineffective, which may partly be attributed to a lack of considering multiple stressors acting on larger scales. To select measures for effective aquatic ecosystem restoration, we thus need to increase our knowledge of the interactions between the multitude of simultaneously acting stressors, their scale- and context-dependency and their impact on aquatic ecosystems.
In this thesis, it was argued that we would be able to provide this missing knowledge by departing from a biotic point of view. To this end, available building blocks for simulating macroinvertebrate responses to multiple stressors were explored. Next, we constructed an appropriate context for expressing macroinvertebrate-based ecological water quality by designing a biology-based classification.
In addition, diagnostic and predictive tools for quantifying macroinvertebrate responses to multiple environmental stressors were constructed within this context. We quantified the cumulative stress acting upon macroinvertebrate assemblages in lowland streams, accounting for impacts on multiple spatial scales. Furthermore, a network approach was adopted to predict the ecological status of stream sites.
For an improved understanding of multiple stressor impacts on macroinvertebrate assemblages in the future, we need the combined efforts of science and practice to formulate advanced theory, further develop and apply appropriate restoration methods and scientifically test our understanding in practice. An increased insight in how multiple stressors impact aquatic ecosystems, by departing from biology, will contribute to effective restoration and support the recovery of biodiversity, even in densely populated landscapes.