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    The most common forestland classification techniques applied in the southeastern United States are vegetation-based. While not completely ignored, the application of multifactor, hierarchical ecosystem classifications are limited despite their widespread use in other regions of the eastern United States. We present one of the few truly integrated ecosystem classifications for the southeastern Coastal Plain. Our approach is iterative, including reconnaissance, plot sampling, and multivariate analysis. Each ecosystem is distinguished by differences in physiographic setting, landform, topographic relief, soils, and vegetation. The ecosystem classification is ground-based, incorporating easily observed and measured factors of landform, soil texture, and vegetative cover associated into ecological species groups identified by two-way indicator species analysis. Canonical conrespondence analyses (CCA) that measure the degree of distinctness among ecosystems using different combinations of physiographic, soil, and vegetation datasets are used to verify the classification. The hierarchical ecosystem classification provides a framework for sustainable resource management of our study landscape as an alternative to traditional cover-type or vegetation-based classifications in the southeastern Coastal Plain. This ecosystem classification provides a structural framework that mimics biological organization, by physical drivers, ensuring that information on various ecosystem components are available to assist management decisions made at the ecosystem level.

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    Goebel, P. Charles; Palik, Brian J.; Kirkman, L. Katherine; Drew, Mark B.; West, Larry; Pederson, Dee C. 2001. Forest ecosystems of a Lower Gulf Coastal Plainlandscape: multifactor classification and analysis. Journal of the Torrey Botanical Society 128(1):47-75


    ecosystem classification, geomorphology, longleaf pine (Pinus palustris Mill.), wiregrass (Aristida stricta Michx.), ground-flora

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