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dc.contributor.authorMoe, S. Jannicke
dc.contributor.authorBrix, Kevin V.
dc.contributor.authorLandis, Wayne G.
dc.contributor.authorStauber, Jenny L.
dc.contributor.authorCarriger, John F.
dc.contributor.authorHader, John D.
dc.contributor.authorKunimitsu, Taro
dc.contributor.authorMentzel, Sophie
dc.contributor.authorNathan, Rory
dc.contributor.authorNoyes, Pamela D.
dc.contributor.authorOldenkamp, Rik
dc.contributor.authorRohr, Jason R.
dc.contributor.authorvan den Brink, Paul J.
dc.contributor.authorVerheyen, Julie
dc.contributor.authorBenestad, Rasmus
dc.date.accessioned2024-06-17T08:01:49Z
dc.date.available2024-06-17T08:01:49Z
dc.date.created2024-01-29T07:26:04Z
dc.date.issued2024
dc.identifier.citationIntegrated Environmental Assessment and Management. 2024, 1-17.en_US
dc.identifier.issn1551-3777
dc.identifier.urihttps://hdl.handle.net/11250/3134239
dc.description.abstractThe 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;20:367–383. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).en_US
dc.language.isoengen_US
dc.publisherJohn Wiley & Sonsen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleIntegrating climate model projections into environmental risk assessment: A probabilistic modeling approachen_US
dc.title.alternativeIntegrating climate model projections into environmental risk assessment: A probabilistic modeling approachen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber1-17en_US
dc.source.journalIntegrated Environmental Assessment and Managementen_US
dc.identifier.doi10.1002/ieam.4879
dc.identifier.cristin2236372
dc.relation.projectMeteorologisk institutt: 181090en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal