OPS 1-13 - The U.S. National Vegetation Classification for dry coniferous forests and woodlands of the southern Appalachian Mountains: A reassessment

Monday, August 7, 2017
Exhibit Hall, Oregon Convention Center
Thomas R. Wentworth1, Raafiah Haroon2, Kimberly Israel3, Michael T. Lee4, Brooklynn M. Newberry1, Robert K. Peet4, Michael P. Schafale5 and Alan S. Weakley4, (1)Plant & Microbial Biology, NC State University, Raleigh, NC, (2)Perll Diagnostics, Inc., Mechanicsburg, PA, (3)North Carolina Division of Parks and Recreation, Raleigh, NC, (4)Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, (5)NC Natural Heritage Program, NC Department of Natural and Cultural Resources, Raleigh, NC

Xeric to subxeric coniferous forests and woodlands of the southern Appalachian Mountains with a substantial component of yellow pines (Pinus echinata, P. pungens, P. rigida, and P. virginiana) have declined in area during recent decades because of fire suppression, drought, and outbreaks of southern pine beetle. The net result of these processes has been a shift in many yellow pine communities to dominance by drought-tolerant broad-leaved trees and shrubs. The possibility of a change in the global conservation status of yellow pine communities from vulnerable to imperiled prompted us to reconsider their existing classification, given the important supporting role of classification in conservation efforts. Even prior to widespread decline of yellow pine communities, classification efforts were hampered by their dynamic nature and their tendency to intergrade with a variety of other communities. We have been exploring numerical classification of a dataset consisting of over 1,000 permanent plot records extracted from the Carolina Vegetation Survey database, selected using criteria of location in the southern Appalachian region and having at least 10% combined cover of the four yellow pines. After homogenizing species’ taxonomic treatments and identifying outlier stands, we have used a combination of a priori assignments and quantitative methods (hierarchical cluster analysis and fuzzy clustering) to identify subsets of plot records corresponding best to the principal associations currently in use for these communities in the US National Vegetation Classification (USNVC).


Our current focus is on the utility of a core group of 11 USNVC associations currently recognized and the potential need to modify the existing classification structure. Ongoing analyses include numerical classification, ordination, determination of diagnostic species, and the identification of environmental constraints and dynamic trends affecting the distribution of southern Appalachian yellow pine communities.