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1 January 2013 Informing Recovery Management of the Threatened Blackside Dace, Chrosomus cumberlandensis, using a Bayesian-Belief Network Model
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Abstract

Integrated modeling frameworks allow resource managers to incorporate multiple sources of information (both data and expert judgment), acknowledge uncertainty, and make quantitative predictions about resource outcomes. To demonstrate the utility of an integrated-modeling approach for recovery planning of imperiled species, we developed a comprehensive model in the form of a Bayesian-belief network to support recovery of a federally listed stream fish, Chrosomus cumberlandensis (Blackside Dace). Our model quantitatively combined expert judgment and data from empirical studies to create a comprehensive model that is testable, transferable, and easily communicated. Sensitivity- and scenario-building analyses demonstrated that mining impacts such as elevated stream conductivity were the most influential variables affecting predicted local Blackside Dace population persistence. Our results suggest that mining impacts are a logical focal point for research and recovery actions for the species, but additional review and revision of the model are recommended. Taken as a whole, our effort enhances the current and future capacity for informed recovery-management of Blackside Dace populations.

Kevin T. McAbee, Nathan P. Nibbelink, Trisha D. Johnson, and Hayden T. Mattingly "Informing Recovery Management of the Threatened Blackside Dace, Chrosomus cumberlandensis, using a Bayesian-Belief Network Model," Southeastern Naturalist 12(sp4), 143-161, (1 January 2013). https://doi.org/10.1656/058.012.s416
Published: 1 January 2013
JOURNAL ARTICLE
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