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Relating Site Index to Ecological Factors in Black Spruce Stands: Tests of Hypotheses

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Modeling dominant height through site index, defined as dominant height at some fixed tree age, requires two equations. The site index must be estimated as the average height of dominant trees at base age, and dominant height must be modeled as a function of age and site index, each model having its own error term. This raises a problem when squared errors are minimized to estimate parameters of interest: the estimates are biased and inconsistent because the error terms are correlated with the explanatory variables. Two additional problems are the autocorrelation among error terms and variance heterogeneity within trees. The generalized method of moments (GMM), which simultaneously takes these problems into account, offers a tool to estimate parameters of the site index and dominant height equations consistently and without bias. Allowing parameters of the height growth model to depend on explanatory variables representing ecological region and drainage class provides useful insight into growth patterns, and improves prediction based on these models. A simulation study confirms that the GMM combined with prewhitening of the time series for each tree produces useful estimates of the parameters and valid statistical tests of hypotheses about their value. For. Sci. 45(4):484-491.
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Keywords: Simultaneous nonlinear equations; generalized method of moments; three-stage least squares; two-stage least squares

Document Type: Journal Article

Affiliations: Statistician, NRCan, CFS, Centre de foresterie des Laurentides, 1055 rue du P.E.P.S., Sainte-Foy, Québec, G1V 4C7, Canada--Phone: (418) 648-5283

Publication date: 1999-11-01

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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.

    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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