Developing ecological scenarios for the prospective aquatic risk assessment of pesticides.

The prospective aquatic environmental risk assessment (ERA) of pesticides is generally based on the comparison of predicted environmental concentrations in edge-of-field surface waters with regulatory acceptable concentrations derived from laboratory and/or model ecosystem experiments with aquatic organisms. New improvements in mechanistic effect modeling have allowed a better characterization of the ecological risks of pesticides through the incorporation of biological trait information and landscape parameters to assess individual, population and/or community-level effects and recovery. Similarly to exposure models, ecological models require scenarios that describe the environmental context in which they are applied. In this article, we propose a conceptual framework for the development of ecological scenarios that, when merged with exposure scenarios, will constitute environmental scenarios for prospective aquatic ERA. These "unified" environmental scenarios are defined as the combination of the biotic and abiotic parameters that are required to characterize exposure, (direct and indirect) effects, and recovery of aquatic nontarget species under realistic worst-case conditions. Ideally, environmental scenarios aim to avoid a potential mismatch between the parameter values and the spatial-temporal scales currently used in aquatic exposure and effect modeling. This requires a deeper understanding of the ecological entities we intend to protect, which can be preliminarily addressed by the formulation of ecological scenarios. In this article we present a methodological approach for the development of ecological scenarios and illustrate this approach by a case-study for Dutch agricultural ditches and the example focal species Sialis lutaria. Finally, we discuss the applicability of ecological scenarios in ERA and propose research needs and recommendations for their development and integration with exposure scenarios. Integr Environ Assess Manag 2016;12:510-521.