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dc.contributor.authorMcAbee, Kevin Todd
dc.date.accessioned2014-03-04T03:27:22Z
dc.date.available2014-03-04T03:27:22Z
dc.date.issued2008-08
dc.identifier.othermcabee_kevin_t_200808_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/mcabee_kevin_t_200808_ms
dc.identifier.urihttp://hdl.handle.net/10724/24988
dc.description.abstractHigh uncertainty and few historic data hinder management of many imperiled species because recovery planning is often based heavily on expert opinion. While this is a practical place to begin, recovery planning must continually focus on incorporating the most up to date ecological knowledge. Decision analysis is one tool that can help managers quantitatively formalize the complex, uncertain and varying relationships found in most recovery management programs. I developed a model to support structured decision making for recovery management of the federally threatened blackside dace (Phoxinus cumberlandensis) by employing a Bayesian belief network (BBN). The completed model is an up to date description of the inputs and ecological variables believed by species experts to most impact recovery. Model analysis demonstrates variables that most influence management outcomes, which in turn can guide future research.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectBayesian belief networks
dc.subjectblackside dace (Phoxinus cumberlandensis)
dc.subjectendangered species
dc.subjectdecision analysis
dc.titleStructured decision making for recovery management of a threatened species, Phoxinus cumberlandensis (blackside dace)
dc.typeThesis
dc.description.degreeMS
dc.description.departmentForest Resources
dc.description.majorForest Resources
dc.description.advisorNathan Nibbelink
dc.description.committeeNathan Nibbelink
dc.description.committeeJames Long
dc.description.committeeC. Rhett Jackson
dc.description.committeeJames Peterson


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