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A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals
Citation:
Forbes, V., C. Salice, B. Birnir, Randy Bruins, P. Calow, V. Ducrot, N. Galic, K. Garber, B. Harvey, H. Jager, A. Kanarek, R. Pastorok, S. Railsback, R. Rebarber, AND P. Thorbek. A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, 36(4):845–859, (2017).
Impact/Purpose:
The framework introduced here represents an ongoing initiative supported by the National Institute of Mathematical and Biological Synthesis (NIMBioS; http://www.nimbios.org/workinggroups/WG_o2e). Our multidisciplinary working group brings together population-, community-, and ecosystem ecologists, ecotoxicologists, and mathematicians with interest and expertise in developing dynamic, mechanistic models of complex systems to predict impacts on ecosystem processes and service delivery from data typically collected to support chemical risk assessments. Our aim is to develop, not only example models, but a general framework for model development, evaluation, and communication that can be applied across different ecosystem services and ecotoxicological endpoints. In this article, we focus on ecosystem services as protection goals for chemical risk assessment, describe the different kinds of models that can mechanistically link ecosystem service delivery to the most common types of effects data collected for chemical risk assessments and hence from which we can construct explicit relationships between valued ecosystem effects and the causes of those effects. In addition, we provide a framework whereby this might be done and outline two case studies that are being developed to provide proof of concept. Finally, we summarize the challenges that will need to be addressed for the framework to succeed.
Description:
Protection of ecosystem services is increasingly emphasized as a risk-assessment goal, but there are wide gaps between current ecological risk-assessment endpoints and potential effects on services provided by ecosystems. The authors present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. This framework builds on considerable advances in mechanistic effects models designed to span multiple levels of biological organization and account for various types of biological interactions and feedbacks. For illustration, the authors introduce 2 case studies that employ well-developed and validated mechanistic effects models: the inSTREAM individual-based model for fish populations and the AQUATOX ecosystem model. They also show how dynamic energy budget theory can provide a common currency for interpreting organism-level toxicity. They suggest that 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. The authors highlight the potential benefits of using this framework as well as the challenges that will need to be addressed in future work.
