Knowledge update in adaptive management of forest resources under climate change: a Bayesian simulation approach
Research output: Contribution to journal › Journal article › Research › peer-review
Standard
Knowledge update in adaptive management of forest resources under climate change : a Bayesian simulation approach. / Yousefpour, Rasoul; Jacobsen, Jette Bredahl; Meilby, Henrik; Thorsen, Bo Jellesmark.
In: Annals of Forest Science, Vol. 71, No. 2, 2014, p. 301-312.Research output: Contribution to journal › Journal article › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - JOUR
T1 - Knowledge update in adaptive management of forest resources under climate change
T2 - a Bayesian simulation approach
AU - Yousefpour, Rasoul
AU - Jacobsen, Jette Bredahl
AU - Meilby, Henrik
AU - Thorsen, Bo Jellesmark
N1 - Published online 6 Sep 2013
PY - 2014
Y1 - 2014
N2 - Context:We develop a modelling concept that updates knowledge and beliefs about future climate changes, to model a decision-maker’s choice of forest management alternatives, the outcomes of which depend on the climate condition.Aims:Applying Bayes’ updating, we show that while the true climate trajectory is initially unknown, it will eventually be revealed as novel information become available. How fast the decision-maker will form firm beliefs about future climate depends on the divergence among climate trajectories, the long-term speed of change, and the short-term climate variability.Methods:We simplify climate change outcomes to three possible trajectories of low, medium and high changes. We solve a hypothetical decision-making problem of tree species choice aiming at maximising the land expectation value (LEV) and based on the updated beliefs at each time step.Results:The economic value of an adaptive approach would be positive and higher than a non-adaptive approach if a large change in climate state occurs and may influence forest decisions.Conclusion:Updating knowledge to handle climate change uncertainty is a valuable addition to the study of adaptive forest management in general and the analysis of forest decision-making, in particular for irreversible or costly decisions of long-term impact.
AB - Context:We develop a modelling concept that updates knowledge and beliefs about future climate changes, to model a decision-maker’s choice of forest management alternatives, the outcomes of which depend on the climate condition.Aims:Applying Bayes’ updating, we show that while the true climate trajectory is initially unknown, it will eventually be revealed as novel information become available. How fast the decision-maker will form firm beliefs about future climate depends on the divergence among climate trajectories, the long-term speed of change, and the short-term climate variability.Methods:We simplify climate change outcomes to three possible trajectories of low, medium and high changes. We solve a hypothetical decision-making problem of tree species choice aiming at maximising the land expectation value (LEV) and based on the updated beliefs at each time step.Results:The economic value of an adaptive approach would be positive and higher than a non-adaptive approach if a large change in climate state occurs and may influence forest decisions.Conclusion:Updating knowledge to handle climate change uncertainty is a valuable addition to the study of adaptive forest management in general and the analysis of forest decision-making, in particular for irreversible or costly decisions of long-term impact.
U2 - 10.1007/s13595-013-0320-x
DO - 10.1007/s13595-013-0320-x
M3 - Journal article
VL - 71
SP - 301
EP - 312
JO - Annals of Forest Science
JF - Annals of Forest Science
SN - 1286-4560
IS - 2
ER -
ID: 99149150