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Selecting a Level of Conditioning for the Segmented Polynomial Taper Equation

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Using tree data collected from loblolly pine thinning study plots, different levels of conditioning were examined for the segmented polynomial taper equation presented by Max and Burkhart (1976). An eight-parameter model with minimum constraints (diameter at the tip of a tree is zero and the adjacent functions are continuous at the join points) did not perform better than a six-parameter model with an additional smoothness constraint in terms of fit and predictive ability.

The join points where the adjacent segments of a tree meet, the inflection points, were assumed known to further reduce the number of parameters in the model. A four-parameter model with inflection points at 11 and 75% of total tree height was slightly superior to the six- and eight-parameter models in estimating tree diameters. The fit statistics and predictive ability of the model were not sensitive to the lower and upper inflection points in the range of 9–12% and 70–80%, respectively. For. Sci. 49(2):324–330.
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Keywords: Pinus taeda; Tree volume; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; mensuration; natural resource management; natural resources; segmented regression; tree taper

Document Type: Miscellaneous

Affiliations: 1: Research Scientist Forintek Canada Corp., 319 rue Franquet, Sainte-Foy, QC, Canada, G1P 4R4, Phone: (418) 659-2647; Fax: (418) 659-2922 [email protected] 2: University Distinguished Professor Department of Forestry, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, Phone: (540) 231-5483; Fax: (540) 231-3698 [email protected]

Publication date: 2003-04-01

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.

    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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