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Developing a Well-Behaved Dynamic Site Equation Using a Modified Hossfeld IV Function Y 3 = (axm )/(c + x m–1), a Simplified Mixed-Model and Scant Subalpine Fir Data

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I developed a dynamic height growth model by using a simplified form of mixed effects modeling and subalpine fir (Abies lasiocarpa [Hook.] Nutt .) stem analysis data. The new dynamic equation uses directly heights at any age to predict consistent heights (e.g., y 2 = f(t 2, t 1, y 1)  y 1 = f(t 1, t 2, y 2)) and f(t 3, t 1, y 1) = f(t 3, t 2, f(t 2, t 1, y 1))), and therefore constitutes compatible site index and height models in one common equation. The parameters for the model were estimated by analysis of fixed and random effects with corrections for first- and second-order serial autocorrelation. The correction for second-order autocorrelation was necessary to assure the model's proper representation of the data and to remove a seeming cross-sectional autocorrelation across different sites/series. Estimating the errors in site indices as random effects eliminated the effects of stochastic predictive variables. The proposed model has outperformed all other base-age specific and base-age invariant models in both the fit to the data and in its behavior during extrapolations. It also outperforms the model (developed on amabilis fir data) that is currently, operationally used for subalpine fir. The new model's advantages are parsimony, mathematical tractability, base-age invariance, and greater consistency in curvatures of the generated height-age trajectories. FOR. SCI. 49(4):539–554.
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Keywords: Site index models; base-age invariant; dynamic equations; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; inventory updates; mixed effects; natural resource management; natural resources

Document Type: Miscellaneous

Affiliations: B.D. Warnell School of Forest Resources, The University of Georgia, Athens, GA, 30602, Phone/Fax: 706-542-8169/8356

Publication date: 2003-08-01

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
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