Citation:

Raimondo, S., M. Etterson, N. Pollesch, J. Awkerman, S. Purucker, AND D. Miller. Population Modeling for Ecological Risk Assessment (ERA). Ecological Risk Assessment Forum (ERAF) monthly meeting, Gulf Breeze, FL, March 21, 2023.

Impact/Purpose:

This invited presentation will be delivered to the EPA Ecological Risk Assessment Forum, a group of agency risk assessors that meet monthly to review and discuss issues related to ecological risk assessments (ERA). It highlights ORD's current research advancing ecological effects models for ERA. Models reviewed are developed or in development for birds,  fish, amphibians, pollinators, and crustaceans.

Description:

Establishing ecological protection goals for environmental contamination is rife with challenges and uncertainties. Spatial inhomogeneity, differential intra- and inter- species sensitivities, limited data on exposure and effects profiles, and an enormous diversity of ecological contexts represent some of the broad challenges for ecological risk assessments (ERA). Wildlife protection goals are often established at the population level or higher, yet effects of chemical exposure are measured on the molecular to the individual level of laboratory test species. The species selected for laboratory testing are typically based on practicality of culture and the endpoints measured are related to growth, reproduction, and survival. These measurements can be taken directly or related to measurements of sub-organismal processes.  Empirical observations of chemical effect at ecological, or even population-level scales are exceedingly rare, due in part to the fact that toxicological experiments at these scales are challenging, and expensive. Thus, ecological risk assessors often find themselves making inferences from available data, ecological and toxicological theory, and mathematical and statistical models to inform decisions for the protection of wildlife; each of these information sources introduces different uncertainties into the assessment. This approach is often sufficient for lower-tiered ERAs that are intended for screening chemical effects, but do not convey environmentally relevant scenarios for higher-tiered assessments that aim to improved environmental realism for refined risk evaluation. Here, we discuss a suite of Toxicity Translator models that make refined use of laboratory studies by providing information about population-level endpoints that are relevant to decision makers. These models can be used as either components within larger scale population models or on their own to translate test endpoints (e.g., EC20) into demographically informed endpoints such as alterations to size structure or metamorphosis success. We show that the application of toxicity translators can move chronic effects assessments away from reliance on confounded metrics such as No Observable Effects Concentrations (NOECs) and Risk Quotients (RQs) and provide endpoints that greatly improve the interpretation of available effects data for refined ERAs. 

Record Details: