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Estimating Tree Grades for Southern Appalachian Natural Forest Stands

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Log prices can vary significantly by grade: grade 1 logs are often several times the price per unit of grade 3 logs. Because tree grading rules derive from log grading rules, a model that predicts tree grades based on tree and stand-level variables might be useful for predicting stand values. The model could then assist in the modeling of timber supply and in economic optimization. Grade models are estimated for ten species groups found in the southern Appalachians, using data from several thousand trees and permanent plots in the USDA Forest Service's Forest Inventory and Analysis (FIA) database. The models correctly predicted grades of a majority of trees in both a test and a validation data set, and predictions of grade proportions across a sample of the population were usually within three percentage points of actual grade proportions. But success of models varied across species and diameter groups. Considering several measures of modeling success, the most accurate models were those predicting tree grades for softwoods and larger hardwoods. For. Sci. 44(1):73-86.
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Keywords: Ordered probit; forest value; grade distribution; southern Appalachians; tree quality

Document Type: Journal Article

Affiliations: Research Economist, USDA Forest Service, Forestry Sciences Laboratory, P.O. Box 12254, Research Triangle Park, NC, 27709. Phone. (919) 549-4033;, Fax: (919) 549-4047

Publication date: 1998-02-01

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.

    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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