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A Compatible Height Prediction and Projection System for Individual Trees in Natural, Even-Aged Shortleaf Pine Stands

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Methods for predicting the future total heights of shortleaf pine (Pinus echinata) trees given current total height, age, site index, current and future dbh are developed. The height projection equation is compatible with an equation that predicts total height given dbh, age, and site index which can be used to estimate total heights if values of previous total height are not known. However, the system predicts future total heights more precisely if previous values of total height are known. Parameter estimates for the system of two equations were obtained by applying seemingly unrelated nonlinear regressions to the system of two equations, which had unequal sample sizes and restrictions on equation parameters. The data were from remeasured plots located in natural, even-aged shortleaf pine stands. These equations can be used to predict the heights of individual trees in an individual tree growth and yield simulator or to predict the average heights associated with dbh classes in diameter distribution growth and yield systems or stand table projections. For. Sci. 41(1):194-209.
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Keywords: Pinus echinata; Seemingly unrelated regressions

Document Type: Journal Article

Affiliations: Research Forester, Southern Forest Experiment Station, University of Arkansas at Monticello, Room 211 Forest Resources Building, P.O. Box 3516 UAM, Monticello, AR 71655

Publication date: 1995-02-01

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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