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Incorporating Whole-Stand and Individual-Tree Models in a Stand-Table Projection System

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A stand table provides number of trees per unit area for each diameter class. This article presents three methods to project a current stand table into the future by predicting mortality and diameter growth for each diameter class by use of an individual-tree model. The stand table was then adjusted to produce the same total number of trees and basal area per hectare as predicted from the whole-stand model. The three methods evaluated in this study were stand table adjustment, constrained least squares (LS), and modified constrained LS. Data from the Southwide Seed Source Study of loblolly pine (Pinus taeda L.) showed that incorporating the individual-tree model helped improve the projection of stand tables, as compared to a previous approach. The three methods produced comparable results; error indices from these methods were within 5% of one another. The constrained LS method consistently provided the best fit (lowest error indices) as compared to the other methods.

Keywords: constrained least squares; diameter growth; loblolly pine; pinus taeda; tree survival

Document Type: Research Article

Affiliations: Quang V. Cao, Professor of Forestry, Louisiana State University, School of Renewable Natural Resources, Baton Rouge, LA 70803—Phone: (225) 578-4218;, Fax: (225) 578-4227, Email:

Publication date: 2007-02-01

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.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 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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