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Constraining Individual Tree Diameter Increment and Survival Models for Loblolly Pine Plantations

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Among extant forest growth and yield models, individual tree growth models provide the most detailed information, which is useful for intensive forest management. However, individual tree growth models may be inaccurate for stand-level predictions because of the cumulative error resulting from individual tree predictions. This paper is aimed at developing a method to ensure that individual tree growth models not only provide precise individual tree predictions but also give precise stand-level estimation. Based on the conceptual relationships between basal area of each diameter class and the diameter increment of trees in the same diameter class, a constrained regression equation system is proposed. The same approach is also applied to modeling individual tree survival probability. An algorithm for estimating multiresponse regressions was developed. Results using data from unthinned loblolly pine (Pinus taeda L.) plantations show that the simultaneous equation system provides nearly the same individual tree diameter increment estimates as the unconstrained model but better estimates for basal area of each diameter class and for total stand basal area. The potential for improving stand mortality estimation with a constrained individual tree survival model where there is little mortality in the data is limited. For. Sci. 43(3):414-423.
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Keywords: Pinus taeda; growth model; simulation; simultaneous system

Document Type: Journal Article

Affiliations: Thomas M. Brooks Professor, Forest Biometrics in the Department of Forestry, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061-0324

Publication date: 1997-08-01

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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