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Masters Theses
Date of Award
8-1984
Degree Type
Thesis
Degree Name
Master of Science
Major
Ecology and Evolutionary Biology
Major Professor
J. Frank McCormick
Committee Members
Edward R. Buckner, Peter White
Abstract
Forest fuel levels in western portions of the Great Smoky Mountains National Park were measured to determine community and site relationships. Data was collected from 93 permanent plots established in earlier studies of Uplands Field Research Laboratory, National Park Service. Dead and downed fuel volume was sampled using the planar intersect method. Other fuel variables included dead stem basal area and organic layer components. Community and site variables included elevation, topography, slope, aspect, site protection, distance from plot to nearest water, distance from plot to nearest ridgetop, disturbance history, live basal area, and community types.
Nine forest types were identified by the TWINSPAN hierarchical classification method. Discriminant analysis correctly classified all forest types when using species basal area. Analysis of sampling groups using site variables indicated overlap between forest types. Fuel variables were poor predictors of forest type.
Fuel level differences existed between disturbed and virgin stands. Virgin stands had twice as much total downed wood volume as disturbed stands. Predictive equations were more accurate for describing fuel levels in virgin stands that for disturbed sites or for virgin and disturbed stands combined.
Fuel level differences existed among forest types. Total organic layer depth for coniferous forest types was twice as high as deciduous forest types. The six deciduous forest types had one third the level of standing dead basal area as the coniferous forest types.
Elevation was the most significant continuous site variable for describing fuel levels. Fuels increased as elevation increased. A larger sample size is needed to examine the role of site variables within different forest types.
Recommended Citation
Nichols, Niki Stephanie, "Fuel Levels in Forests of the Great Smoky Mountains National Park. " Master's Thesis, University of Tennessee, 1984.
https://trace.tennessee.edu/utk_gradthes/3252