An unconventional approach to ecosystem unit classification in western North Carolina, USA
The authors used an unconventional combination of data transformation and multivariate analyses to reduce subjectivity in identification of ecosystem units in a mountainous region of western North Carolina, USA. Vegetative cover and environmental variables were measured on 79 stratified, randomly located, 0.1 ha sample plots in a 4000 ha watershed. Binary transformation of percent cover followed by direct and indirect ordination indicated the 185 inventoried species were associated primarily with soil A-horizon thickness, soil base saturation, and aspect. Redundant cluster analyses, consisting of divisive and agglomerative methods for multivariate classification of core plots, followed by selective discriminant analysis of remaining non-core plots, indicated that the continuum of vegetation and environment could be grouped into five ecosystem units. Approximately 20 herbaceous, shrubs, and tree species and several soil and topographic variables were highly significant discriminators of ecosystem units. The authors also demonstrated that redundant cluster analysis maybe used to subdivide ecosystem units into subunits of uniform understory composition and associated environment. Validation and refinement of classification units, linkage with faunal biological components, and arrangement into landscape areas suitable for resource management is needed before field application.