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Using structured decision making with landowners to address private forest management and parcelization: balancing multiple objectives and incorporating uncertainty

Paige F. B. Ferguson, Department of Biological Sciences, University of Alabama; Warnell School of Forestry and Natural Resources, University of Georgia
Michael J Conroy, Warnell School of Forestry and Natural Resources, University of Georgia
John F Chamblee, Department of Anthropology, University of Georgia
Jeffrey Hepinstall-Cymerman, Warnell School of Forestry and Natural Resources, University of Georgia


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Parcelization and forest fragmentation are of concern for ecological, economic, and social reasons. Efforts to keep large, private forests intact may be supported by a decision-making process that incorporates landowners’ objectives and uncertainty. We used structured decision making (SDM) with owners of large, private forests in Macon County, North Carolina. Macon County has little land use regulation and a history of discordant, ineffective attempts to address land use and development. We worked with landowners to define their objectives, identify decision options for forest management, build a Bayesian decision network to predict the outcomes of decisions, and determine the optimal and least-desirable decision options. The optimal forest management options for an average, large, forested property (30 ha property with 22 ha of forest) in Macon County was crown-thinning timber harvest under the Present-Use Value program, in which enrolled property is taxed at the present-use value (growing timber for commercial harvest) rather than full market value. The least-desirable forest management actions were selling 1 ha and personal use of the forest (e.g., trails, firewood) with or without a conservation easement. Landowners reported that they enjoyed participating in the project (85%) and would reconsider what they are currently doing to manage their forest (69%). The decision that landowners initially thought would best meet their objectives did not match results from the decision network. This highlights the usefulness of SDM, which typically has been applied to decision problems involving public resources.

Key words

Bayesian decision network; conservation easement; decision analysis; forestry; fragmentation; heritage; present-use value; sustainability; timber harvest

Copyright © 2015 by the author(s). Published here under license by The Resilience Alliance. This article is under a Creative Commons Attribution 4.0 International License. You may share and adapt the work provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license.

Ecology and Society. ISSN: 1708-3087