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Improved Estimates of Site Index Curves Using a Varying-Parameter Model

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Current methods for developing site index curves from stem analysis data or from remeasured permanent plots commonly regress height on age (or age and site) using a nonlinear regression model fitted to the pooled observations. While this is a computationally efficient method, it does not satisfactorily account for between-tree differences in individual tree height growth. This paper presents a varying-parameter (linear random regression coefficient) model that is derived by fitting height growth models to each individual tree in the data set. A weighted least squares technique is then employed to combine these individual estimates to form a mean estimate of the parameters of a sigmoid height growth model. These parameters are then used to predict the height development of site trees. An example of the procedure is given using stem analysis data from primarily dominant trees in the young-growth mixed conifer forests of California. Forest Sci. 31:248-259.
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Keywords: Stem analysis data; height growth; sigmoid model

Document Type: Journal Article

Affiliations: Assistant Professor with the Department of Forestry and Resource Management, University of California, Berkeley, CA 94720

Publication date: 1985-03-01

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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