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A Generalized Approach for Modeling and Localizing Stem Profile Curves

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The Max and Burkhart segmented taper equation was fitted using nonlinear mixed-effects modeling techniques to account for within- and between-individual variation in loblolly pine (Pinus taeda L.) stem profiles. Within- and between-tree residual variances and spatial autocorrelation between residuals were incorporated in the model with an error variance function and a continuous autocorrelation structure, respectively. However, most of the residual autocorrelation was accounted for by including random effects. Upper stem diameter measurements were used to estimate random effects parameters using an approximate Bayesian estimator, which localized stem profile curves for individual trees. The procedure was tested with an independent data set. Measures of precision and bias showed that upper stem diameter measurements and subsequent estimates of random effects improved the predictive capability of the taper equation mainly in the lower portion of the bole. The method can localize stem curves for trees growing under different site and management conditions. It also represents a general framework that can be applied to other taper equation forms, increasing their flexibility and efficiency in prediction for local conditions.

Keywords: Nonlinear mixed-effects model; Pinus taeda; taper equation

Document Type: Research Article

Publication date: 2006-12-01

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  • 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

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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