Protection of ecosystem services is increasingly emphasized as a goal when assessing the risks of chemicals and other stressors to ecological systems. However, there remain wide gaps between current ecological risk-assessment endpoints and potential effects on services provided by ecosystems. Here, we present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. The framework builds on considerable advances in mechanistic effects models designed to span multiple levels of biological organization and account for various biological interactions and feedbacks. We will demonstrate the approach through two case studies. The first considers impacts of an endocrine-disrupting chemical on recreational and cultural services provided by two trout species in a nutrient-poor river system. The second case study considers direct and indirect effects of an organophosphate insecticide on interacting trophic levels in a lake ecosystem and consequences for services provided by clear water.
Results/Conclusions
In case study 1, reductions in sperm viability from chemical exposure result in reduced embryo survival; the extent to which these effects manifest at the population level depend on food level in the system, timing of exposure, hydrological conditions, and interactions between trout species. In case study 2, direct toxic effects of the pesticide on zooplankton result in impacts on some recreational fish species (due to reductions in their zooplankton food source) and in reductions in water clarity (due to increased growth of phytoplankton), but only if water clarity is driven by phytoplankton rather than suspended solids. In both cases, we demonstrate how a framework based on mechanistic models that predict impacts on ecosystem services resulting from chemical exposure, combined with economic valuation, can provide a useful approach for informing environmental management. This ongoing initiative is the product of a working group supported by the National Institute of Mathematical and Biological Synthesis (NIMBioS). We will describe the potential benefits of using this framework as well as the challenges that need to be addressed in future work.