TY - JOUR
T1 - Updating beliefs and combining evidence in adaptive forest management under climate change
T2 - A case study of Norway spruce (Picea abies L. Karst) in the Black Forest, Germany
AU - Yousefpour, Rasoul
AU - Temperli, Christian
AU - Bugmann, Harald
AU - Elkin, Che
AU - Hanewinkel, Marc
AU - Meilby, Henrik
AU - Jacobsen, Jette Bredahl
AU - Thorsen, Bo Jellesmark
N1 - Funding Information:
This study was conducted as part of the project MOTIVE ‘MOdels for adapTIVE forest management’ funded by the European Community's Seventh Framework Programme (FP7/2007–2013) under grant agreement n° 226544 . Elkin was funded by the project MOUNTLAND of the Competence Centre “Environment and Sustainability” of the ETH Domain, Switzerland, and Jacobsen and Thorsen further acknowledge support from the Danish National Science Foundation .
PY - 2013/6/5
Y1 - 2013/6/5
N2 - We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change.
AB - We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change.
KW - Adaptive decision-making
KW - Bayesian updating
KW - Biomass production
KW - Dempster's rule
KW - LandClim
UR - http://www.scopus.com/inward/record.url?scp=84875774571&partnerID=8YFLogxK
U2 - 10.1016/j.jenvman.2013.03.004
DO - 10.1016/j.jenvman.2013.03.004
M3 - Article
C2 - 23557671
AN - SCOPUS:84875774571
SN - 0301-4797
VL - 122
SP - 56
EP - 64
JO - Journal of Environmental Management
JF - Journal of Environmental Management
ER -