Forest ecosystems of a lower gulf coastal plain landscape: multifactor classification and analysis

The most common forestland classification techniques applied in the southea stern United States are vegetation-based. While not completely ignored, the application of multifactor, hierarchical ecosystem classifications are lim ited despite their widespread use in other regions of the eastern United St ates. We present one of the few truly integrated ecosystem classifications for the southeastern Coastal Plain. Our approach is iterative, including re connaissance, plot sampling, and multivariate analysis. Each ecosystem is d istinguished by differences in physiographic setting, landform, topographic relief, soils, and vegetation. The ecosystem classification is ground-base d, incorporating easily observed and measured factors of landform, soil tex ture, and vegetative cover associated into ecological species groups identi fied by two-way indicator species analysis. Canonical correspondence analys es (CCA) that measure the degree of distinctness among ecosystems using dif ferent combinations of physiographic, soil, and vegetation datasets are use d to verify the classification. The hierarchical ecosystem classification p rovides a framework for sustainable resource management of our study landsc ape as an alternative to traditional cover-type or vegetation-based classif ications in the southeastern Coastal Plain. This ecosystem classification p rovides a structural framework that mimics biological organization, by phys ical drivers, ensuring that information on various ecosystem components are available to assist management decisions made at the ecosystem level.