It is generally recognized that the magnitude of recreation resource impacts should be judged by their severity and spatial qualities, including extent, distribution, and association. Previous investigations, however, have primarily focused on assessing the severity of impacts, with limited examination of spatial qualities. The goal of this dissertation was to expand our understanding of the spatial dimension of recreation resource impacts and their assessment and evaluation. Two empirical data sets collected from a comprehensive recreation impact assessment and monitoring project in Great Smoky Mountains National Park provided the basis for the analyses. Three spatial issues were examined and presented as three papers, designed for journal submission. The purpose of the first paper was to improve our understanding of the dimensional structure and spatial patterns of camping impacts by means of multivariate analyses and mapping. Factor analysis of 195 established campsites on eight impact indicator variables revealed three dimensions of campsite impact: land disturbance, soil and groundcover damage, and tree-related damage. Cluster analysis yielded three distinctive campsite types that characterize both the intensity and areal extent of camping impacts. Spatial patterns and site attributes of these three campsite types and an additional group of primitive campsites were illustrated and discussed. The purpose of the second paper was to examine the influence of sampling interval on the accuracy of selected trail impact indicator estimates for the widely applied systematic point sampling method. A resampling-simulation method was developed and applied. Simulation results indicated that using systematic point sampling for estimating lineal extent of trail impact problems can achieve an excellent level of accuracy at sampling intervals of less than 100 m, and a reasonably good level of accuracy at intervals between 100 and 500 m. The magnitude of accuracy loss could be higher when the directions of loss are not considered. The responses of accuracy loss on frequency of occurrence estimates to increasing sampling intervals were consistent across impact types, approximating an inverse asymptotic curve. These findings suggest that systematic point sampling using an interval of less than 500 m can be an appropriate method for estimating the lineal extent, but not for estimating occurrence of trail impacts. Further investigations are called for to examine the generalizability of these results to other areas. The purpose of the third paper was to expand the scope of indices used for evaluating recreation resource impacts. Two specific objectives were to synthesize the recreation ecology and recreation resource management literature on the use of spatial indicators and indices, and to propose and apply selected spatial indices that are mostly lacking in the literature. Three spatial indices primarily adapted from the geography and ecology literature were proposed for application in recreation impact evaluation. Application results demonstrated that the Lorenz curve and associated Gini coefficient, and the linear nearest-neighbor analysis and associated LR ratio were effective in quantifying the spatial distribution patterns of trail impacts at landscape and trail scales, respectively. Application results of the third index, the impact association index, were less promising and require further refinements. Management implications and future directions of research were discussed in light of the findings of this dissertation. As the field of recreation ecology is emerging, this dissertation has demonstrated: (1) the value of recreation impact assessment and monitoring programs in providing data for examining the spatial dimension of impacts, and (2) the utility of spatial analytical approaches in understanding recreation impact assessment and evaluation. / Ph. D.

Several studies in the field of outdoor recreation management and planning have used computer simulation modeling to demonstrate its utility as a tool to help managers monitor encounters and similar visitor use-related indicators of quality. However, previous applications of computer simulation modeling to outdoor recreation planning and management have generally done little to assess the reliability, or precision, of model estimates. The purpose of this research is to explore several questions concerning the reliability of computer simulation model estimates for monitoring wilderness solitude-related indicators of quality. In particular, can reliable estimates of solitude-related indicators be generated for low use recreation environments, such as backcountry and wilderness areas? Is there a spatial component to questions about the reliability of computer simulation estimates for low use visitor landscapes? The research presented in this thesis examines the reliability of computer simulation estimates of wilderness solitude indicators that account for the timing and location of hiking and camping encounters in the backcountry of Great Smoky Mountains National Park. This study was designed to model visitor use and inter-group encounters in the Cosby and Big Creek areas of Great Smoky Mountains National Park, which are located within the park's proposed wilderness area. Two primary types of information about visitor use in the study area were collected to construct the computer simulation model in this study. First, information was gathered about the amount of visitation to the study area; second, information was collected about visitors' travel routes within the study area. Three alternative methods were used to estimate the number of replications needed to obtain desired levels of precision for the visitor-based and spatially based computer simulation model outputs. The results suggest that computer simulation models of visitor use can generate precise estimates for a small to moderate number of visitor-based and spatially-based outputs. However, there are constraints to generating precise estimates of use-related outputs as the number of outputs estimated simultaneously becomes large. This challenge is particularly pronounced in cases where at least some of the outputs are derived for low use attractions, trails, or camping locations. / Master of Science

Ecologists continue to debate the role of fire in forests of the southern Appalachian Mountains. How does climate influence fire in these humid, temperate forests? Did fire regimes change during the transition from Native American settlement to Euro-American settlement? Are fire regime changes resulting in broad vegetation changes in the forests of eastern North America? I used several approaches to address these questions. First, I used digitized fire perimeter maps from Great Smoky Mountains National Park and Shenandoah National Park for 1930-2009 to characterize spatial and temporal patterns of wildfire by aspect, elevation, and landform. Results demonstrate that fuel moisture is a primary control, with fire occurring most frequently during dry years, in dry regions, and at dry topographic positions. Climate also modifies topographic control, with weaker topographic patterns under drier conditions. Second, I used dendroecological methods to reconstruct historical fire frequency in yellow pine (Pinus, subgenus Diploxylon Koehne) stands at three field sites in the southern Appalachian Mountains. The fire history reconstructions extend from 1700 to 2009, with composite fire return intervals ranging from 2-4 years prior to the fire protection period. The two longest reconstructions record frequent fire during periods of Native American land use. Except for the recent fire protection period, temporal changes in land use did not have a significant impact on fire frequency and there was little discernible influence of climate on past fire occurrence. Third, I sampled vegetation composition in four different stand types along a topographic moisture gradient, including mesic cove, sub-mesic white pine (Pinus strobus L.) hardwood, sub-xeric oak (Quercus L.), and xeric pine forests in an unlogged watershed with a reconstructed fire history. Stand age structures demonstrate changes in establishment following fire exclusion in xeric pine stands, sub-xeric oak stands, and sub-mesic white pine-hardwood stands. Fire-tolerant yellow pines and oaks are being replaced by shade-tolerant, fire sensitive species such as red maple (Acer rubrum L.) and hemlock (Tsuga canadensis L. Carr.). Classification analysis and ordination of species composition in different age classes suggest a trend of successional convergence in the absence of fire with a shift from four to two forest communities.

Debris-slides are fast-moving landslides that occur in the Appalachian region including the Great Smoky Mountains National Park (GRSM). Various knowledge and data-driven approaches using spatial distribution of the past slides and associated factors could be used to estimate the region’s debris-slide susceptibility. This study developed two debris-slide susceptibility models for GRSM using knowledge-driven and data-driven methods in GIS. Six debris-slide causing factors (slope curvature, elevation, soil texture, land cover, annual rainfall, and bedrock discontinuity), and 256 known debris-slide locations were used in the analysis. Knowledge-driven weighted overlay and data-driven bivariate frequency ratio analyses were performed. Both models are helpful; however, each come with a set of advantages and disadvantages regarding degree of complexity, time-dependency, and experience of the analyst. The susceptibility maps are useful to the planners, developers, and engineers for maintaining the park’s infrastructures and delineating zones for further detailed geotechnical investigation.

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