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dc.contributor.authorYousefpour, Rasoul
dc.contributor.authorTemperli, Christian
dc.contributor.authorJacobsen, Jette B.
dc.contributor.authorThorsen, Bo Jellesmark
dc.contributor.authorMeilby, Henrik
dc.contributor.authorLexer, Manfred J.
dc.contributor.authorLindner, Marcus
dc.contributor.authorBugmann, Harald
dc.contributor.authorBorges, José G.
dc.contributor.authorPalma, João H.N.
dc.contributor.authorRay, Duncan
dc.contributor.authorZimmermann, Niklaus E.
dc.contributor.authorDelzon, Sylvain
dc.contributor.authorKremer, Antoine
dc.contributor.authorKramer, Koen
dc.contributor.authorReyer, Christopher P. O.
dc.contributor.authorLasch-Born, Petra
dc.contributor.authorGarcia Gonzalo, Jordi
dc.contributor.authorHanewinkel, Marc
dc.description.abstractAdapting the management of forest resources to climate change involves addressing several crucial aspects to provide a valid basis for decision making. These include the knowledge and belief of decision makers, the mapping of management options for the current as well as anticipated future bioclimatic and socioeconomic conditions, and the ways decisions are evaluated and made. We investigate the adaptive management process and develop a framework including these three aspects, thus providing a structured way to analyze the challenges and opportunities of managing forests in the face of climate change. We apply the framework for a range of case studies that differ in the way climate and its impacts are projected to change, the available management options, and how decision makers develop, update, and use their beliefs about climate change scenarios to select among adaptation options, each being optimal for a certain climate change scenario. We describe four stylized types of decision-making processes that differ in how they (1) take into account uncertainty and new information on the state and development of the climate and (2) evaluate alternative management decisions: the “no-change,” the “reactive,” the “trend-adaptive,” and the “forward-looking adaptive” decision-making types. Accordingly, we evaluate the experiences with alternative management strategies and recent publications on using Bayesian optimization methods that account for different simulated learning schemes based on varying knowledge, belief, and information. Finally, our proposed framework for identifying adaptation strategies provides solutions for enhancing forest structure and diversity, biomass and timber production, and reducing climate change-induced damages. They are spatially heterogeneous, reflecting the diversity in growing conditions and socioeconomic settings within Europe.ca_ES
dc.description.sponsorshipThis work was supported by the Seventh Framework Program of the EC Grant Agreement No. 226544. We thank the MINECO “Ramón y Cajal” (Ref. RYC-2013-14262) for funding the research contract of JGG. KK was funded by the project Resilient Forests (KB-29-009-003) of the Dutch Ministry of Economic Affairs. BJT and JBJ acknowledge support from the Danish National Research Foundation (DNRF Grant No 96). This research has received also funding from the European Union's H2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 691149 (SuFoRun).ca_ES
dc.publisherResilience Allianceca_ES
dc.relation.isformatofReproducció del document publicat a:
dc.relation.ispartofEcology and Society, 2017, vol. 22, núm. 4, p. 40ca_ES
dc.rightscc-by-nc (c) Yousefpour, Rasoul et al., 2017ca_ES
dc.subjectBehavioral adaptationca_ES
dc.subjectForest managementca_ES
dc.subjectProcess-based modelsca_ES
dc.subjectSpatial planningca_ES
dc.titleA framework for modeling adaptive forest management and decision making under climate changeca_ES

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