title: Trail impacts in Sagarmatha (Mt. Everest) National Park, Nepal: a logistic regression analysis.
abstract: A trail study was conducted in the Sagarmatha (Mt. Everest) National Park, Nepal, during 1997-1998. Based on that study, this paper examines the spatial variability of trail conditions and analyzes factors that influence trail conditions. Logistic regression (multinomial logit model) is applied to examine the influence of use and environmental factors on trail conditions. The assessment of trail conditions is based on a four-class rating system: (class I, very little damaged; class II, moderately damaged, class III, heavily damaged; and class IV, severely damaged). Wald statistics and a model classification table have been used for data interpretation. Results indicate that altitude, trail gradient, hazard potential, and vegetation type are positively associated with trail condition. Trails are more degraded at higher altitude, on steep gradients, in areas with natural hazard potential, and within shrub/grassland zones. Strong correlations between high levels of trail degradation and higher frequencies of visitors and lodges were found. A detailed analysis of environmental and use factors could provide valuable information to park managers in their decisions about trail design, layout and maintenance, and efficient and effective visitor management strategies. Comparable studies on high alpine environments are needed to predict precisely the effects of topographic and climatic extremes. More refined approaches and experimental methods are necessary to control the effects of environmental factors.
authors.affiliation: Geography/Resource Recreation and Tourism Program, University of Northern British Columbia, Prince George, British Columbia, Canada. nepals@unbc.ca
authors.forename: S K
authors.initials: SK
authors.lastname: Nepal
mesh_terms: D002980:Climate; D003247:Conservation of Natural Resources; D017753:Ecosystem; D004777:Environment; D006801:Humans; D009390:Nepal; D011998:Recreation; D012044:Regression Analysis; D016138:Walking