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Adaptive Decision Analysis in Forest Management Planning

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Abstract:

Societal responsibilities of forestry have diversified, and criteria other than those related to wood production have been given more weight. Demands for forest management planning methods have changed in line with the changes in the operational environment. Thus, forest planners are facing a growing demand for more versatile and customer-oriented decision aid systems and practices in which the data are cost effectively acquired and used. So far, forest planning research has concentrated mainly on the general development of multiobjective and participatory planning methods in the numerical framework. This focus has unintentionally led to practices for which the decision analysis process is often controlled only by the technical needs of the planning methods in a unified setting, independently of the problem characteristics. However, it is important to adapt the use of planning methodologies to each planning problem and use the available information about important variables efficiently. In this article, we introduce a theoretical and methodological framework for adaptive decision analysis (ADA) for forest management planning. In ADA, different decision-support service options, comprising both qualitative and quantitative components, are maintained and carried out flexibly in each planning case with the aid of an adapting processor and feedback management, resulting in computational, social, and organizational learning.

Keywords: adaptive planning; decisionmaking; learning; multicriteria evaluation; statistical models

Document Type: Research Article

Publication date: 2009-04-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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