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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Modeling the Ecological Consequences of Visitor Behavior in Off-Trail Areas Dispersed Recreation Use

D'Antonio, Ashley L. 01 August 2015 (has links)
Parks and protected areas are often created to protect important social, ecological, or cultural resources from impairment. In the United States, a large majority of these parks and protected areas are also public land where recreational activities such as hiking or scenic driving are allowed. Managers of many parks and protected areas must therefore try to protect resources while also allowing for recreation use that may put these resources at risk for damage. The field of recreation ecology is interested in understanding how recreation use in parks and protected areas can sometimes cause ecological impacts to vegetation, soil, wildlife, water, air, and soundscapes. This information is then used to help managers prevent undesirable ecological change. When visitors to parks and protected areas leave designated sites such as trails or roads, there is a greater chance that ecological impacts will occur. The studies presented here are designed to help managers better understand how visitor behavior off of designated trails may result in damage to plant communities. These studies examine data on both the social aspects of recreation use (such as visitor behavior and the number of visitors recreating) and the ecological aspects (specifically the plant communities found at popular recreation destinations). By looking at social and ecological data together, these studies can predict locations in parks or protected areas where ecological impact may occur as a result of recreation use. Managers can use these predictions to better allocate resources and time to managing recreation use at locations that are most at risk of impairment.

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