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A Scenario Approach to Stochastic Anticipatory Optimization in Stand Management

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A flexible model for stochastic optimization is developed that can be used with forest stand simulation models. Stochasticity is represented by a large set of scenarios, each of which is an outcome of stochastic processes. A stochastic environment is described by random yearly growth rate levels and catastrophes, such as wild fire or windthrow. The optimization model is defined in control variable space and includes the timing, intensity, and type of thinning, and rotation length for an even-aged stand. Single-tree growth and mortality models are used. Numerical results in a risk-neutral case show that the optimum rotation is shortened with an increasing probability of a catastrophe. Further, an increasing growth rate variation has mixed and weak effects that depend, in particular, on the tree mortality model. If a stand cannot be thinned, increasing risk-taking shortens the optimum rotation, given the model set used. For. Sci. 38(2):430-447.

Keywords: Norway spruce; Optimal harvesting; Picea abies; even-aged stand; risk

Document Type: Journal Article

Affiliations: Research Forester, Department of Forest Economics, Finnish Forest Research Institute, Unioninkatu 40 A, 00170 Helsinki, Finland

Publication date: 1992-04-01

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

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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