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dc.contributor.authorStar, Jonathan
dc.contributor.authorRowland, Erika L.
dc.contributor.authorBlack, Mary E.
dc.contributor.authorEnquist, Carolyn A.F.
dc.contributor.authorGarfin, Gregg
dc.contributor.authorHoffman, Catherine Hawkins
dc.contributor.authorHartmann, Holly
dc.contributor.authorJacobs, Katharine L.
dc.contributor.authorMoss, Richard H.
dc.contributor.authorWaple, Anne M.
dc.date.accessioned2017-03-02T23:06:33Z
dc.date.available2017-03-02T23:06:33Z
dc.date.issued2016
dc.identifier.citationSupporting adaptation decisions through scenario planning: Enabling the effective use of multiple methods 2016, 13:88 Climate Risk Managementen
dc.identifier.issn22120963
dc.identifier.doi10.1016/j.crm.2016.08.001
dc.identifier.urihttp://hdl.handle.net/10150/622731
dc.description.abstractScenario planning is a technique used to inform decision-making under uncertainty, and is increasingly applied in the field of climate change adaptation and policy. This paper describes applications that combine previously distinct scenario methods in new and innovative ways. It draws on numerous recent independent case studies to illustrate emerging practices, such as far stronger connections between researcher-driven and participatory approaches and cycling between exploratory and normative perspectives. The paper concludes with a call for greater support for, and collaboration among, practitioners with the argument that mixed methods are most effective for decision-making in the context of climate change challenges.
dc.description.sponsorshipU.S. Geological Survey [G15AP00172]en
dc.language.isoenen
dc.publisherELSEVIER SCIENCE BVen
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S2212096316300262en
dc.rightsPublished by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Copyright is held by the author(s) or the publisher. If your intended use exceeds the permitted uses specified by the license, contact the publisher for more information.en
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectScenario planningen
dc.subjectClimate adaptationen
dc.titleSupporting adaptation decisions through scenario planning: Enabling the effective use of multiple methodsen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Ctr Climate Adaptat Sci & Soluten
dc.contributor.departmentUniv Arizona, DOI Southwest Climate Sci Ctr, USGSen
dc.contributor.departmentUniv Arizona, Sch Nat Resources & Environmen
dc.identifier.journalClimate Risk Managementen
dc.description.noteOpen access journalen
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
refterms.dateFOA2018-06-18T02:29:01Z
html.description.abstractScenario planning is a technique used to inform decision-making under uncertainty, and is increasingly applied in the field of climate change adaptation and policy. This paper describes applications that combine previously distinct scenario methods in new and innovative ways. It draws on numerous recent independent case studies to illustrate emerging practices, such as far stronger connections between researcher-driven and participatory approaches and cycling between exploratory and normative perspectives. The paper concludes with a call for greater support for, and collaboration among, practitioners with the argument that mixed methods are most effective for decision-making in the context of climate change challenges.


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Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Copyright is held by the author(s) or the publisher. If your intended use exceeds the permitted uses specified by the license, contact the publisher for more information.
Except where otherwise noted, this item's license is described as Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Copyright is held by the author(s) or the publisher. If your intended use exceeds the permitted uses specified by the license, contact the publisher for more information.