Spatially explicit assessment of estuarine fish after Deepwater Horizon oil spill: trade-off in complexity and parsimony

A framework for linking population model development with ecological risk assessment objectives

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.

What are the roadblocks to using population models in ecotoxicology studies?

Understanding how pollution affects populations is critical for targeted environmental risk assessments and adequate protection of the environment. However, the vast majority of ecotoxicology studies still have a traditional focus of identifying effects on individual organisms and do not measure the effects at the population-level. Modelling tools that measure population effects of pollution are available and would add value to current ecotoxicology studies by aligning outcomes more closely to what needs to be protected. In this paper I outline three possible reasons why this knowledge gap still exists and consider how they could be adopted more broadly, including better considerations about what endpoints should be measured at the initial study design phase. The purpose of highlighting this knowledge gap is to assist in facilitating the integration of population-level endpoints into routine pollution monitoring programs and progress of ecologically relevant ecotoxicology research.