Key challenges and developments in wildlife ecological risk assessment: Problem formulation.

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 2022;00:1-16. © 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.

Multi-species Aquatic Toxicity Assessment of 1-Methyl-3-Nitroguanidine (MeNQ).

The Army is replacing traditional munitions with insensitive munitions (IM) resistant to accidental detonation. The aquatic toxicity of 1-methyl-3-nitroguanidine (MeNQ), which is being assessed for potential use in IM formulations, remains largely untested. The present study fills a number of critical data gaps for MeNQ aquatic toxicity by evaluating effects across two vertebrate and five invertebrate species. Specifically, responses in larval Pimephales promelas, Rana pipiens tadpoles, Chironomus dilutus, Lumbriculus variegatus, Hydra littoralis, Hyalella azteca, and Daphnia pulex were assessed in MeNQ exposures across various acute, subchronic, and chronic bioassays. Overall, survival was unaffected in most of the MeNQ exposures where significant lethal effects were only observed in D. pulex, H. littoralis, and C. dilutus and only at concentrations ≥ 2186 mg/L. Significant sublethal effects on growth were observed for C. dilutus at 903 mg/L and H. azteca at 1098 mg/L in 10-d assays. Significantly decreased reproduction was observed at 2775 mg/L for H. azteca in a chronic 35-d assay and at 174 mg/L for D. pulex in the 11-d three-brood assay representing a sublethal effect one order of magnitude more sensitive than the effective lethal concentration for D. pulex (2987 mg/L). Degradation of MeNQ in ultraviolet light (UV) greatly increased toxicity to D. pulex. Specifically, exposure to a MeNQ solution that was completely UV-degraded prior to D. pulex exposures resulted in an 11-d LC50 of 6.1 mg/L and a 50% reduction in reproduction at 3.125 mg/L, based on the original MeNQ parent-compound concentrations.

A weight of evidence assessment approach for adverse outcome pathways.

The adverse outcome pathway (AOP) is a framework to mechanistically link molecular initiating events to adverse biological outcomes. From a regulatory perspective, it is of crucial importance to determine the confidence for the AOP in question as well as the quality of data available in supporting this evaluation. A weight of evidence approach has been proposed for this task, but many of the existing frameworks for weight of evidence evaluation are qualitative and there is not clear guidance regarding how weight of evidence should be calculated for an AOP. In this paper we advocate the use of a subject matter expertise driven approach for weight of evidence evaluation based on criteria and metrics related to data quality and the strength of causal linkages between key events. As a demonstration, we notionally determine weight of evidence scores for two AOPs: Non-competitive ionotropic GABA receptor antagonism leading to epileptic seizures, and Antagonist-binding and stabilization of a co-repressor to the peroxisome proliferator-activated receptor α (PPARα) signaling complex ultimately causing starvation-like weight loss.

Limitations of toxicity characterization in life cycle assessment: Can adverse outcome pathways provide a new foundation?

Life cycle assessment (LCA) has considerable merit for holistic evaluation of product planning, development, production, and disposal, with the inherent benefit of providing a forecast of potential health and environmental impacts. However, a technical review of current life cycle impact assessment (LCIA) methods revealed limitations within the biological effects assessment protocols, including: simplistic assessment approaches and models; an inability to integrate emerging types of toxicity data; a reliance on linear impact assessment models; a lack of methods to mitigate uncertainty; and no explicit consideration of effects in species of concern. The purpose of the current study is to demonstrate that a new concept in toxicological and regulatory assessment, the adverse outcome pathway (AOP), has many useful attributes of potential use to ameliorate many of these problems, to expand data utility and model robustness, and to enable more accurate and defensible biological effects assessments within LCIA. Background, context, and examples have been provided to demonstrate these potential benefits. We additionally propose that these benefits can be most effectively realized through development of quantitative AOPs (qAOPs) crafted to meet the needs of the LCIA framework. As a means to stimulate qAOP research and development in support of LCIA, we propose 3 conceptual classes of qAOP, each with unique inherent attributes for supporting LCIA: 1) mechanistic, including computational toxicology models; 2) probabilistic, including Bayesian networks and supervised machine learning models; and 3) weight of evidence, including models built using decision-analytic methods. Overall, we have highlighted a number of potential applications of qAOPs that can refine and add value to LCIA. As the AOP concept and support framework matures, we see the potential for qAOPs to serve a foundational role for next-generation effects characterization within LCIA. Integr Environ Assess Manag 2016;12:580-590. Published 2015. This article is a US Government work and is in the public domain in the USA.