Examining Collective-Efficacy As A Framework For Watershed Scale Resource Management
2017-10
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Examining Collective-Efficacy As A Framework For Watershed Scale Resource Management
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2017-10
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This dissertation explores a collective-efficacy theoretical framework as it relates to climate change and extreme weather response and water and stormwater management in a northern Minnesota coastal community. A multi method research approach was implemented in two sub-watersheds of the Lower St. Louis River Basin near Duluth, Minnesota that included 27 interviews, two focus groups, a workshop, and bio-physical modeling of potential climate impacts. Perceived collective-efficacy to make decisions and take action to manage natural resources and potential future resource impacts from climate and extreme weather impacts emerged as a prominent theme in analysis. This dissertation explores collective-efficacy in the study community through three approaches, 1) perceived collective-efficacy for resource management and climate and extreme weather response as it relates to relationship to place, 2) the use of a collective-efficacy framework throughout a sequential community-based, multi methods, natural resource management study, and 3) the application of collective-efficacy principals in an applied tool for use in local decision making. An exploration of collective-efficacy in local communities can help identify barriers to effective decision making and opportunities for progress in climate and extreme weather preparedness. This work both builds the body of literature on climate response related collective-efficacy research and offers an applied path for stakeholders working collectively to address challenging natural resource management issues.
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University of Minnesota Ph.D. dissertation. 2017. Major: Natural Resources Science and Management. Advisor: Mae Davenport. 1 computer file (PDF); 222 pages.
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Perry, Vanessa. (2017). Examining Collective-Efficacy As A Framework For Watershed Scale Resource Management. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/193442.
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