Problem formulation (PF) is a critical initial step in planning risk assessments for chemical exposures to wildlife, used either explicitly or implicitly in various jurisdictions to include registration of new pesticides, evaluation of new and existing chemicals released to the environment, and characterization of impact when chemical releases have occurred. Despite improvements in our understanding of the environment, ecology, and biological sciences, few risk assessments have used this information to enhance their value and predictive capabilities. In addition to advances in organism-level mechanisms and methods, there have been substantive developments that focus on population- and systems-level processes. Although most of the advances have been recognized as being state-of-the-science for two decades or more, there is scant evidence that they have been incorporated into wildlife risk assessment or risk assessment in general. In this article, we identify opportunities to consider elevating the relevance of wildlife risk assessments by focusing on elements of the PF stage of risk assessment, especially in the construction of conceptual models and selection of assessment endpoints that target population- and system-level endpoints. Doing so will remain consistent with four established steps of existing guidance: (1) establish clear protection goals early in the process; (2) consider how data collection using new methods will affect decisions, given all possibilities, and develop a decision plan a priori; (3) engage all relevant stakeholders in creating a robust, holistic conceptual model that incorporates plausible stressors that could affect the targets defined in the protection goals; and (4) embrace the need for iteration throughout the PF steps (recognizing that multiple passes may be required before agreeing on a feasible plan for the rest of the risk assessment). Integr Environ Assess Manag 2024;20:658-673. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Hazard quotients based on a point-estimate comparison of exposure to a toxicity reference value (TRV) are commonly used to characterize risks for wildlife. Quotients may be appropriate for screening-level assessments but should be avoided in detailed assessments, because they provide little insight regarding the likely magnitude of effects and associated uncertainty. To better characterize risks to wildlife and support more informed decision making, practitioners should make full use of available dose-response data. First, relevant studies should be compiled and data extracted. Data extractions are not trivialpractitioners must evaluate the potential use of each study or its components, extract numerous variables, and in some cases, calculate variables of interest. Second, plots should be used to thoroughly explore the data, especially in the range of doses relevant to a given risk assessment. Plots should be used to understand variation in dose-response among studies, species, and other factors. Finally, quantitative dose-response models should be considered if they are likely to provide an improved basis for decision making. The most common dose-response models are simple models for data from a particular study for a particular species, using generalized linear models or other models appropriate for a given endpoint. Although simple models work well in some instances, they generally do not reflect the full breadth of information in a dose-response data set, because they apply only for particular studies, species, and endpoints. More advanced models are available that explicitly account for variation among studies and species, or that standardize multiple endpoints to a common response variable. Application of these models may be useful in some cases when data are abundant, but there are challenges to implementing and interpreting such models when data are sparse. Integr Environ Assess Manag 2014;10:3-11. (c) 2013 SETAC

Toxicity reference values (TRVs) are essential in models used in the prediction of the potential for adverse impacts of environmental contaminants to avian and mammalian wildlife; however, issues in their derivation and application continue to result in inconsistent hazard and risk assessments that present a challenge to site managers and regulatory agencies. Currently, the available science does not support several common practices in TRV derivation and application. Key issues include inappropriate use of hazard quotients and the inability to define the probability of adverse outcomes. Other common problems include the continued use of no‐observed‐ and lowest‐observed‐adverse‐effect levels (NOAELs and LOAELs), the use of allometric scaling for interspecific extrapolation of chronic TRVs, inappropriate extrapolation across classes when data are limited, and extrapolation of chronic TRVs from acute data without scientific basis. Recommendations for future TRV derivation focus on using all available qualified toxicity data to include measures of variation associated with those data. This can be achieved by deriving effective dose (EDx)‐based TRVs where x refers to an acceptable (as defined in a problem formulation) reduction in endpoint performance relative to the negative control instead of relying on NOAELs and LOAELs. Recommendations for moving past the use of hazard quotients and dealing with the uncertainty in the TRVs are also provided. Integr Environ Assess Manag 2010; 6:28–37. © 2009 SETAC

The Canadian Coast Guard is assessing the potential environmental impacts of contamination at 27 remote lightstations on the British Columbia coast. British Columbia has about 25,000 km of shoreline including thousands of islands, most of which are accessible only by boat or helicopter. The lightstations, which have been in use for up to 140 years, essentially consist of industrial installations maintained by resident Iightkeepers in settings of otherwise pristine coastal wilderness. The region is a hotspot of biological diversity. Previous studies had shown that heavy metals and petroleum hydrocarbon concentrations in surface soils exceeded provincial and federal environmental standards and guidelines at these stations. Contaminant sources include the historical use, degradation and dispersion of heavy metals based paints, waste dumping and incineration, and bulk petroleum hydrocarbon storage and transfer. This paper presents a study used for assessing potential impacts to endangered species and habitat elements fkom direct (contact) and indirect (food chain) exposure to the environmental contamination. An initial search of endangered species and habitat element records identified over 300 occurrences in marine and terrestrial environments among the sites. Variability in the extent and magnitude of contamination, anticipated transport and fate of contamination, and the distribution of sensitive receiving environments, including the presence of rare species, provided a basis to prioritise 14 lightstations for field study. The subsequent field investigations consisted of a qualitative habitat survey and collection of environmental samples of relevant exposure media (e.g., soil, plant tissue, soil invertebrate tissue, groundwater, surface water, and mussel tissue) for chemical analysis. Measured concentrations in exposure media were then input into a food chain © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email witpress@witpress.com Paper from: Coastal Environment, CA Brebbia (Editor). ISBN 1-85312-921-6

Ecological risk assessment (ERA) is an iterative process that can involve proceeding through several tiers of assessment prior to obtaining results with acceptable uncertainty. The first tier (e.g., screening-level risk assessment (SLRA)) is typically conservative and serves to narrow the scope of the assessment to the main issues of concern. The strategy for subsequent assessment tiers (e.g., detailed level risk assessment (DLRA)) is dependent on a number of factors and is difficult to prejudge. Consequently, while formal prescriptive guidance may be useful for the SLRA, it would probably be constraining for DLRA and reduce the effectiveness of the risk assessment process. This paper examines the level of detail required for SLRA and DLRA. Differences between the two include: type of information; levels of resources, conservatism and uncertainty; information used; range of substances of potential concern (SOPCs) and receptors considered; use of multiple lines of evidence; level of effects estimation; point versus probabilistic estimates of exposure and effects. The appropriate level of detail for both types of risk assessment is described, but not prescribed.

A wide variety of sediment quality values (SQVs) have been promulgated. Ecological risk assessment (ERA) provides a framework for objectively and systematically evaluating the risks posed by environmental contamination to ecological resources. SQV application to ERA should be restricted to the initial problem formulation stage where they can be used either alone (i.e., in jurisdictions with accepted SQVs) or in a weight-of-evidence approach (i.e., multiple SQV types; in jurisdictions without accepted SQVs) to screen out contaminants posing negligible risks to ecological receptors.