A framework for modeling adaptive forest management and decision making under climate change

Rasoul Yousefpour; Christian   Temperli; Jette Bredahl Jacobsen; Bo Jellesmark Thorsen; Henrik Meilby; Manfred J. Lexer; Marcus Lindner; Harald Bugmann; Jose G. Borges; João H.N.   Palma; Duncan Ray; Niklaus E.  Zimmermann; Sylvain Delzon; Antoine Kremer; Koen Kramer; Christopher P. O.   Reyer; Petra  Lasch-Born; Jordi  Garcia-Gonzalo; Marc  Hanewinkel

doi:10.5751/ES-09614-220440

A framework for modeling adaptive forest management and decision making under climate change

Rasoul Yousefpour, Christian Temperli, Jette Bredahl Jacobsen, Bo Jellesmark Thorsen, Henrik Meilby, Manfred J. Lexer, Marcus Lindner, Harald Bugmann, Jose G. Borges, João H.N. Palma, Duncan Ray, Niklaus E. Zimmermann, Sylvain Delzon, Antoine Kremer, Koen Kramer, Christopher P. O. Reyer, Petra Lasch-Born, Jordi Garcia-Gonzalo , Marc Hanewinkel

Sektion for Miljø og Naturressourcer

37 Citationer (Scopus)

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Abstract

Adapting 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.

Originalsprog	Engelsk
Artikelnummer	40
Tidsskrift	Ecology and Society
Vol/bind	22
Udgave nummer	4
Antal sider	25
ISSN	1708-3087
DOI	https://doi.org/10.5751/ES-09614-220440
Status	Udgivet - dec. 2017

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Yousefpour, R., Temperli, C., Jacobsen, J. B., Thorsen, B. J., Meilby, H., Lexer, M. J., Lindner, M., Bugmann, H., Borges, J. G., Palma, J. H. N., Ray, D., Zimmermann, N. E., Delzon, S., Kremer, A., Kramer, K., Reyer, C. P. O., Lasch-Born, P., Garcia-Gonzalo , J., & Hanewinkel, M. (2017). A framework for modeling adaptive forest management and decision making under climate change. Ecology and Society, 22(4), Artikel 40. https://doi.org/10.5751/ES-09614-220440

Yousefpour, R, Temperli, C, Jacobsen, JB , Thorsen, BJ , Meilby, H, Lexer, MJ, Lindner, M, Bugmann, H, Borges, JG, Palma, JHN, Ray, D, Zimmermann, NE, Delzon, S, Kremer, A, Kramer, K, Reyer, CPO, Lasch-Born, P, Garcia-Gonzalo , J & Hanewinkel, M 2017, 'A framework for modeling adaptive forest management and decision making under climate change', Ecology and Society, bind 22, nr. 4, 40. https://doi.org/10.5751/ES-09614-220440

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title = "A framework for modeling adaptive forest management and decision making under climate change",

abstract = "Adapting 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.",

author = "Rasoul Yousefpour and Christian Temperli and Jacobsen, {Jette Bredahl} and Thorsen, {Bo Jellesmark} and Henrik Meilby and Lexer, {Manfred J.} and Marcus Lindner and Harald Bugmann and Borges, {Jose G.} and Palma, {Jo{\~a}o H.N.} and Duncan Ray and Zimmermann, {Niklaus E.} and Sylvain Delzon and Antoine Kremer and Koen Kramer and Reyer, {Christopher P. O.} and Petra Lasch-Born and Jordi Garcia-Gonzalo and Marc Hanewinkel",

year = "2017",

month = dec,

doi = "10.5751/ES-09614-220440",

language = "English",

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journal = "Ecology and Society",

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T1 - A framework for modeling adaptive forest management and decision making under climate change

AU - Yousefpour, Rasoul

AU - Temperli, Christian

AU - Jacobsen, Jette Bredahl

AU - Thorsen, Bo Jellesmark

AU - Meilby, Henrik

AU - Lexer, Manfred J.

AU - Lindner, Marcus

AU - Bugmann, Harald

AU - Borges, Jose G.

AU - Palma, João H.N.

AU - Ray, Duncan

AU - Zimmermann, Niklaus E.

AU - Delzon, Sylvain

AU - Kremer, Antoine

AU - Kramer, Koen

AU - Reyer, Christopher P. O.

AU - Lasch-Born, Petra

AU - Garcia-Gonzalo , Jordi

AU - Hanewinkel, Marc

PY - 2017/12

Y1 - 2017/12

N2 - Adapting 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.

AB - Adapting 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.

U2 - 10.5751/ES-09614-220440

DO - 10.5751/ES-09614-220440

M3 - Journal article

SN - 1708-3087

VL - 22

JO - Ecology and Society

JF - Ecology and Society

IS - 4

M1 - 40

ER -

A framework for modeling adaptive forest management and decision making under climate change

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