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Incorporating suborganismal processes into dynamic energy budget models for ecological risk assessment
Citation:
Murphy, C., R. Nisbet, P. Antczak, N. Garcia-Reyero, A. Gergs, K. Lika, T. Mathews, E. Muller, D. Nacci, A. Peace, C. Remien, I. Schultz, L. Stevenson, AND K. Watanabe. Incorporating suborganismal processes into dynamic energy budget models for ecological risk assessment. Integrated Environmental Assessment and Management. Allen Press, Inc., Lawrence, KS, 14(5):615-624, (2018). https://doi.org/10.1002/ieam.4063
Impact/Purpose:
This manuscript describes a conceptual framework of ecological models that permit us to explore and ultimately predict the ecological risks associated with contaminant exposures and other human-mediated stressors to wildlife populations. Here, we describe the linkage between molecular endpoints, bioenergetics and population models within an Adverse Outcome Pathways (AOPs) framework. The approach and processes described highlight the value of molecular tools to diagnose and predict effects of classes of chemical stressors that act through similar networks of AOPs. General impacts from this contribution include improved understanding by managers and scientists of links between human activities, natural dynamics, ecological stressors and ecosystem condition.
Description:
A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide “bottom‐up” mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a “top‐down” approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ‐level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage‐inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments.
URLs/Downloads:
DOI: Incorporating suborganismal processes into dynamic energy budget models for ecological risk assessment
https://doi.org/10.1002/ieam.4063