Predicting Wood Production by Canopy Trees in Forest Communities in the Western Great Smoky Mountains
Abstract:A sequence of multivariate techniques (after Golden 1981) including hierarchial classification, detrended correspondence analysis, and multiple discriminant analysis was used to classify forest types in the Great Smoky Mountains National Park. Multiple regressions were used to develop predictive equations for canopy tree productivity (periodic bole volume increment) from environmental variables and measurements of tree growth. An index of topographic shape was constructed to quantify the effects of landform on forest distribution and productivity. The topographic index "protection" was the most important variable for predicting forest productivity. Elevation was the most important variable determining vegetation distribution with protection the second. Predictability of forest productivity from environmental factors was lower on older logged and farmed sites than on undisturbed sites. For. Sci. 35(2):338-348.
Document Type: Journal Article
Affiliations: Associate Professor, Department of Biology, University of North Carolina at Chapel Hill
Publication date: 1989-06-01
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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
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