Qualifying the effects of single and multiple stressors on the food web structure of Dutch drainage ditches using a literature review and conceptual models

Bracewell, Sally and Verdonschot, Ralf C.M. and Schäfer, Ralf B. and Bush, Alex and Lapen, David R. and Van den Brink, Paul J. (2019) Qualifying the effects of single and multiple stressors on the food web structure of Dutch drainage ditches using a literature review and conceptual models. Science of the Total Environment, 684. pp. 727-740. ISSN 0048-9697

Abstract

In September 2017, a workshop was held at Wageningen University and Research to determine the current state of knowledge of multiple stressor effects on aquatic ecosystems and to assess how to improve prediction of these effects. We developed a theoretical framework that integrates species-level responses to stressors to predict how these effects propagate through higher levels of biological organisation. Here, we present the application of the framework for drainage ditch ecosystems in the Netherlands. We used food webs to assess single and multiple stressor effects of common stressors on ditch communities. We reviewed the literature for the effects of targeted stressors (nutrients, pesticides, dredging and mowing, salinization, and siltation) on each functional group present in the food web and qualitatively assessed the relative sensitivity of groups. Using this information, we created a stressor-response matrix of positive and negative direct effects of each stressor-functional group combination. Fungicides, salinization, and sedimentation were identified as particularly detrimental to most groups, although destructive management practices, such as dredging with almost complete community removal, would take precedence depending on frequency. Using the stressor-response matrix we built, first, a series of conceptual null models of single stressor effects on food web structure and, second, a series of additive null models to illustrate potential paired-stressor effects. We compared these additive null models with published studies of the same pairs of combined single stressors to explore more complex interactions. Our approach serves as a first-step to considering multiple stressor scenarios in systems that are understudied or data-poor and as a baseline from which more complex models that include indirect effects and quantitative data may be developed. We make specific suggestions for appropriate management strategies that could be taken to support the biodiversity of these systems for individual stressors and their combined impacts.