Food webs represent the flux of matter and energy between resources and different components of biotic communities. Their analyses provide a powerful approach to link community structure to ecosystem processes, to estimate functional stability towards stressors and to assess indirect stressor effects in communities initiated by trophic interactions. A25 investigates the effects of present and previous stressor impacts on food webs and their recovery after stressor release by combining state of the art tools of food web analyses, namely stable isotope analysis of bulk samples (BSIA) and specific compounds (CSIA). The relatively low-effort BSIA allows sufficient number of analyses to reconstruct total food webs over long periods of time and across different stressor gradients. Higher-effort CSIA will then be applied in a targeted way to increase resolution for trophic position by more accurate fractionation factors (particularly amino-acid CSIA), to detect trophic baselines if resource sampling is not possible (e.g., in stored historic samples) and to explore details of the resources (particularly fatty-acid CSIA). In order to take best advantage of both methods, we merged within Phase II two formerly separated projects (A12 and A13), which dealt separately with BSIA and CSIA, respectively. Furthermore, we will expand the SIA approaches by quantitative fatty acid signature analysis (QFASA) of selected organisms. Fatty acids can only be produced by certain primary producers and thus QFASA can be used to track food sources.

A25 uses samples from both the field (Boye and Emscher catchment) with known stressor gradients and field flume experiments with controlled stressors (drought and flow modulation) to quantify stressor effects on key food web metrics. Building on the patterns observed in Phase I, we will test the underlying mechanisms explaining responses of key food web metrics, particularly trophic similarity, resource diversity and food chain length, for different stressor types. Based on Phase I results, we hypothesise that metrics such as trophic similarity respond consistently to different stressor types, whereas both food chain length and resource diversity show stressor-specific responses. Specifically, we assume that those food web metrics respond positively to resource-related stressors (such as organic rich wastewater) while they respond negatively to non-resource-related stressors (such as drought, flow modification). The food web analyses will be complemented by integrating parasites and their tropic position based on CSIA analyses. Furthermore, we will continue generating a long-term dataset of food web recovery for the Boye catchment, which will directly contribute to test RESIST Main Hypothesis 3 on the differences in recovery of functional vs. community diversity after stressor release. Through the integration of food web structures and processes, this project will contribute to a mechanistic understanding of the recovery of functions, functional diversity and trophic interactions and thus to key components of the ARC in the phase of recovery from stress.