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A Dynamic Programming Algorithm for Optimization of Lodgepole Pine Management

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Single-tree/distance-independent stand simulators can be adapted for dynamic programming (DP) optimization of thinnings and rotation age. Efficiency requires classification of trees for all but very short tree lists. Thinning types in conjunction with discrete basal-area, number-of-trees, and age classes define a DP network that allows the comparison of yields from more thinning regimes that have wider differences in sequences of diameter distributions than do networks without the thinning type dimension. Methods and results are demonstrated for a lodgepole pine (Pinus contorta Doug. ex Loud.) simulator developed for Central and Eastern Oregon. Optimal management regimes developed with and without quality premiums produce stands with high vigor indices and high resistance to attack by mountain pine beetle (Dendroctonus ponderosae Hopkins), suggesting that stocking control can be used to simultaneously maximize both net discounted revenue and insect resistance. However, managing stands with a maximum diameter limit to prevent attack substantially reduces net revenue when market premiums exist for large diameter trees. Forest Sci. 31:321-330.
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Keywords: Dendroctonus ponderosae; Pinus contorta; forest economics; mountain pine beetle; stand growth model

Document Type: Journal Article

Affiliations: Silviculturist (retired), Silvicultural Laboratory, Pacific Northwest Forest and Range Experiment Station, USDA Forest Service, Bend, Oregon, 97701

Publication date: 1985-06-01

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.

    2016 Impact Factor: 1.782 (Rank 17/64 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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