Your browser doesn't support javascript.
loading
Integrating climate model projections into environmental risk assessment: A probabilistic modeling approach.
Moe, S Jannicke; Brix, Kevin V; Landis, Wayne G; Stauber, Jenny L; Carriger, John F; Hader, John D; Kunimitsu, Taro; Mentzel, Sophie; Nathan, Rory; Noyes, Pamela D; Oldenkamp, Rik; Rohr, Jason R; van den Brink, Paul J; Verheyen, Julie; Benestad, Rasmus E.
Affiliation
  • Moe SJ; Norwegian Institute for Water Research (NIVA), Oslo, Norway.
  • Brix KV; EcoTox LLC, Miami, Florida, USA.
  • Landis WG; RSMAES, University of Miami, Miami, Florida, USA.
  • Stauber JL; College of the Environment, Western Washington University, Bellingham, Washington, USA.
  • Carriger JF; CSIRO Environment, Lucas Heights, Sydney, NSW, Australia.
  • Hader JD; La Trobe University, Wodonga, Victoria, Australia.
  • Kunimitsu T; Center for Environmental Solutions and Emergency Response, Office of Research and Development, USEPA, Land Remediation and Technology Division, Cincinnati, Ohio, USA.
  • Mentzel S; Department of Environmental Science, Stockholm University, Stockholm, Sweden.
  • Nathan R; CICERO Center for International Climate Research, Oslo, Norway.
  • Noyes PD; Norwegian Institute for Water Research (NIVA), Oslo, Norway.
  • Oldenkamp R; Department of Infrastructure Engineering, University of Melbourne, Melbourne, Victoria, Australia.
  • Rohr JR; Center for Public Health and Environmental Assessment, Office of Research and Development, USEPA, Integrated Climate Sciences Division, Washington, DC, USA.
  • van den Brink PJ; Chemistry for Environment and Health, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
  • Verheyen J; Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, USA.
  • Benestad RE; Aquatic Ecology and Water Quality Management Group, Wageningen University, Wageningen, The Netherlands.
Integr Environ Assess Manag ; 20(2): 367-383, 2024 Mar.
Article in En | MEDLINE | ID: mdl-38084033
ABSTRACT
The Society of Environmental Toxicology and Chemistry (SETAC) convened a Pellston workshop in 2022 to examine how information on climate change could be better incorporated into the ecological risk assessment (ERA) process for chemicals as well as other environmental stressors. A major impetus for this workshop is that climate change can affect components of ecological risks in multiple direct and indirect ways, including the use patterns and environmental exposure pathways of chemical stressors such as pesticides, the toxicity of chemicals in receiving environments, and the vulnerability of species of concern related to habitat quality and use. This article explores a modeling approach for integrating climate model projections into the assessment of near- and long-term ecological risks, developed in collaboration with climate scientists. State-of-the-art global climate modeling and downscaling techniques may enable climate projections at scales appropriate for the study area. It is, however, also important to realize the limitations of individual global climate models and make use of climate model ensembles represented by statistical properties. Here, we present a probabilistic modeling approach aiming to combine projected climatic variables as well as the associated uncertainties from climate model ensembles in conjunction with ERA pathways. We draw upon three examples of ERA that utilized Bayesian networks for this purpose and that also represent methodological advancements for better prediction of future risks to ecosystems. We envision that the modeling approach developed from this international collaboration will contribute to better assessment and management of risks from chemical stressors in a changing climate. Integr Environ Assess Manag 2024;20367-383. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Ecosystem / Climate Models Language: En Journal: Integr Environ Assess Manag Year: 2024 Document type: Article Affiliation country: Norway

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Ecosystem / Climate Models Language: En Journal: Integr Environ Assess Manag Year: 2024 Document type: Article Affiliation country: Norway