Modelling of adaptation to climate change and decision-makers behaviours for the Veluwe forest area in the Netherlands
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Modelling of adaptation to climate change and decision-makers behaviours for the Veluwe forest area in the Netherlands. / Yousefpour, Rasoul; Didion, Markus; Jacobsen, Jette Bredahl; Meilby, Henrik; Hengeveld, Geerten M.; Schelhaas, Mart-Jan; Thorsen, Bo Jellesmark.
I: Forest Policy and Economics, Bind 54, 2015, s. 1-10.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Modelling of adaptation to climate change and decision-makers behaviours for the Veluwe forest area in the Netherlands
AU - Yousefpour, Rasoul
AU - Didion, Markus
AU - Jacobsen, Jette Bredahl
AU - Meilby, Henrik
AU - Hengeveld, Geerten M.
AU - Schelhaas, Mart-Jan
AU - Thorsen, Bo Jellesmark
PY - 2015
Y1 - 2015
N2 - We apply Bayesian updating theory to model how decision-makers may gradually learn about climate change and make use of this information in making adaptive forest management decisions. We develop modelling steps to i) simulate observation of a multi-dimensional climate system, ii) apply updating rules for beliefs about climate trends, iii) evaluate the performance of adaptive strategies, and iv) apply (i)–(iii) at the local and forest landscape scale to find and compare individual versus joint adaptive decisions. We search for optimal forest management decisions maximizing total biomass production as a measure of management performance. The results illustrate the benefits of updating beliefs to eventually utilize the positive effects and limit negative impacts of climate change on forest biomass production. We find that adaptive decision-making results in switching decisions over time and mostly differ from deterministic decisions ignoring any change in climate. Moreover, we find that the adaptation strategies are indispensable not only because of climate change but also because of the development of the forest biological system over time and the need to revisit decisions.
AB - We apply Bayesian updating theory to model how decision-makers may gradually learn about climate change and make use of this information in making adaptive forest management decisions. We develop modelling steps to i) simulate observation of a multi-dimensional climate system, ii) apply updating rules for beliefs about climate trends, iii) evaluate the performance of adaptive strategies, and iv) apply (i)–(iii) at the local and forest landscape scale to find and compare individual versus joint adaptive decisions. We search for optimal forest management decisions maximizing total biomass production as a measure of management performance. The results illustrate the benefits of updating beliefs to eventually utilize the positive effects and limit negative impacts of climate change on forest biomass production. We find that adaptive decision-making results in switching decisions over time and mostly differ from deterministic decisions ignoring any change in climate. Moreover, we find that the adaptation strategies are indispensable not only because of climate change but also because of the development of the forest biological system over time and the need to revisit decisions.
KW - Bayesian updating
KW - Behaviour of decision-makers
KW - Efficient beliefs
KW - Adaptive management
KW - Multivariate distribution
U2 - 10.1016/j.forpol.2015.02.002
DO - 10.1016/j.forpol.2015.02.002
M3 - Journal article
VL - 54
SP - 1
EP - 10
JO - Forest Policy and Economics
JF - Forest Policy and Economics
SN - 1389-9341
ER -
ID: 146382734