Wildlife ecological risk assessment in the 21st century: Promising technologies to assess toxicological effects

Authors

Barnett A. Rattner, US Geological Survey
Thomas G. Bean, FMC Corporation
Val R. Beasley, University of Illinois at Urbana-Champaign
Philippe Berny, Université de Lyon
Karen M. Eisenreich, US Environmental Protection Agency
John E. Elliott, Environment and Climate Change Canada
Margaret L. Eng, Environment and Climate Change Canada
Phyllis C. Fuchsman, Ramboll
Mason D. King, Simon Fraser University
Rafael Mateo, IREC (CSIC‐UCLM)
Carolyn B. Meyer, Arcadis US Inc.
Jason M. O'Brien, Environment and Climate Change Canada
Christopher J. Salice, Towson University

Date of this Version

6-27-2023

Citation

Integrated Environmental Assessment and Management — Volume 00, Number 00—pp. 1–24. DOI: 10.1002/ieam.4806

Comments

Open access.

Abstract

Despite advances in toxicity testing and the development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air‐breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole-animal toxicity tests are central to hazard assessment, nonstandard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have the potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) are influenced by toxicants at individual, population, and community levels, and need to be factored into chemically based risk assessments to enhance the “eco” component of ERAs. Regulatory and logistical challenges often relegate such nonstandard endpoints and indirect effects to post-registration evaluations of pesticides and industrial chemicals and contaminated site evaluations. While NAMs are being developed, to date, their applications in ERAs focused on wildlife have been limited. No single magic tool or model will address all uncertainties in hazard assessment. Modernizing wildlife ERAs will likely entail combinations of laboratory‐ and field‐derived data at multiple levels of biological organization, knowledge collection solutions (e.g., systematic review, adverse outcome pathway frameworks), and inferential methods that facilitate integrations and risk estimations focused on species, populations, interspecific extrapolations, and ecosystem services modeling, with less dependence on whole‐animal data and simple hazard ratios.