A framework for linking population model development with ecological risk assessment objectives. (19th February 2018)

• Record Type: Journal Article
• Authors: Raimondo, Sandy; Etterson, Matthew; Pollesch, Nathan; Garber, Kristina; Kanarek, Andrew; Lehmann, Wade; Awkerman, Jill
• Is Part Of: Integrated environmental assessment and management. Volume 14:Number 3(2018)
• Page Start: 369
• Page End: 380
• Publication Date: 2018-02-19
• Subjects: Population modeling -- Ecological risk assessment -- Framework -- Uncertainty -- Model complexity; Environmental management -- Periodicals; Pollution -- Periodicals; Environmental toxicology -- Periodicals; Environmental risk assessment -- Periodicals; Environmental impact analysis -- Periodicals; 628
• DOI: 10.1002/ieam.2024
• Languages: English
• ISSNs: 1551-3777

Abstract

ABSTRACT: The value of models that link organism‐level impacts to the responses of a population in ecological risk assessments (ERAs) has been demonstrated extensively over the past few decades. There is little debate about the utility of these models to translate multiple organism‐level endpoints into a holistic interpretation of effect to the population; however, there continues to be a struggle for actual application of these models as a common practice in ERA. Although general frameworks for developing models for ERA have been proposed, there is limited guidance on when models should be used, in what form, and how to interpret model output to inform the risk manager's decision. We propose a framework for developing and applying population models in regulatory decision making that focuses on trade‐offs of generality, realism, and precision for both ERAs and models. We approach the framework development from the perspective of regulators aimed at defining the needs of specific models commensurate with the assessment objective. We explore why models are not widely used by comparing their requirements and limitations with the needs of regulators. Using a series of case studies under specific regulatory frameworks, we classify ERA objectives by trade‐offs of generality, realism, and precision and demonstrate how the output of population models developed with these same trade‐offs informs the ERA objective. We examine attributes for both assessments and models that aid in the discussion of these trade‐offs. The proposed framework will assist risk assessors and managers to identify models of appropriate complexity and to understand the utility and limitations of a model's output and associated uncertainty in the context of their assessment goals. Integr Environ Assess Manag 2018;14:369–380. Published 2017. This article is a US Government work and is in the public domain in the USA. Key Points: We present a framework for the development of population models for ecological risk assessment (ERA). We identify factors that currently prevent the use of population models in ERAs in regulatory decision making and develop a framework that addresses these inhibitory factors. The framework presents an approach that will guide the development of population models of varying levels of complexity based on the objective of the ERA. A series of case studies demonstrate the application of the framework under various regulatory statutes.