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Harvesting Loblolly Pine Plantations with Hardwood Competition and Stochastic Prices

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This paper presents numerical results of the effects of stochastic stumpage prices on economic optimal thinnings and rotation ages for loblolly pine (Pinus taeda L.) plantations in the Piedmont region of North Carolina. The numerical results are obtained with a dynamic programming model that provides optimal harvest levels as a function of price, stand density, and age. For numerical tractability the network is relatively coarse with a 5-year decision cycle and 50 trees/ac intervals for the harvest control variable. Sawtimber and pulpwood stumpage price probabilities are assumed to be independent and stationary and are based on the means and variances of past price observations. Optimal full-rotation management strategies for both pure and mixed-species plantations show that sawtimber and pulpwood price variation do not affect the timing and intensity of early commercial thinning. Stumpage price variation does affect the timing of dearcutting. Gains in present value are made by timing the clearcut to a period with high sawtimber stumpage price. Results on the effects of hardwood competition show that the opportunity cost of hardwood competition that persists through one rotation is higher than the cost of eliminating the hardwoods early on. The effects of restrictions in the size of the dynamic programming network and the stationarity assumptions in the stochastic price processes are discussed. For. Sci. 37(5):1266-1282.
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Keywords: Forest management; decision-making under uncertainty; dynamic programming; even-age management

Document Type: Journal Article

Affiliations: Assistant Professor, Department of Forestry, North Carolina State University, Raleigh, NC 27650

Publication date: 1991-11-01

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    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.
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    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

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    June 1, 2016 to Feb. 28, 2017

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