An Integrated Multivariate Analysis of Forest Communities of the Central Great Smoky Mountains

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Abstract
An integrated sequence of multivariate techniques was applied to vegetation and site data from 244 stands in the central Great Smoky Mountains National Park. The analyses included cluster analysis, stepwise multiple discriminant analysis with both species and site variables, reciprocal averaging, canonical analysis and canonical correlation. They provided a system of successive refinement and cumulative evidence for analysis of vegetation and vegetation-site relationships. Nineteen forest community types were identified and examined. At the broad level, the vegetation pattern was most directly related to elevation, topography and stand history. Some soil variables were important, specifically soil pH and clay content of the B horizon. The most useful measures of topographic effects were topographic position and total annual potential solar irradiation (a function of slope angle and aspect). The number of dead Castanea dentata remains provided a measure of past disturbance which was related to the vegetation pattern.