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A Generalized Approach to Stand Table Projection

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A new algorithm for stand table projection based on existing estimates of future basal area and survival is derived and demonstrated. An observed stand table is first projected by applying either an existing diameter growth equation or a growth equation derived from appropriate diameter distributional assumptions. The stand table is adjusted by an algorithm that equates the future stand table to existing estimate of basal area and survival. The algorithm does not use any species-specific parameters and can therefore be applied to any species for which future estimates of basal area and survival are available. This algorithm provides comparable estimates when the initial diameter distribution is close to the unimodal distribution assumed by parameter recovery procedures in diameter distribution growth and yield models. In fact, the algorithm reduces to the same future stand table when the initial stand table is actually generated by the diameter distribution derived by the parameter recovery procedure. However, if the observed stand table is multimodal, the prediction by this algorithm is better than predictions from the parameter recovery method alone. Favorable comparisons are also made with the stand table projection method introduced by Pienaar and Harrison (1988), for natural even-aged longleaf pine stands. For. Sci. 38(1):120-133.
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Keywords: Parameter recovery; Weibull distribution; diameter distribution; diameter growth equation; longleaf pine

Document Type: Journal Article

Affiliations: Assistant Professor, School of Forestry and Alabama Agricultural Experiment Station, Auburn University, Auburn, AL 36849-5418

Publication date: 1992-02-01

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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