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ISRN Forestry
Volume 2012 (2012), Article ID 594067, 10 pages
http://dx.doi.org/10.5402/2012/594067
Research Article

Public Acceptance of Disturbance-Based Forest Management: Factors Influencing Support

1Department of Forest Ecosystems & Society, Oregon State University, 321 Richardson Hall, Corvallis, OR 97331, USA
2Forestry Division, Montana Department of Natural Resources & Conservation, 2705 Spurgin Road, Missoula, MT 59804, USA

Received 9 March 2012; Accepted 10 April 2012

Academic Editors: D. Czeszczewik, D. Huber, and B. Schirone

Copyright © 2012 Christine S. Olsen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Growing emphasis on ecosystem and landscape-level forest management across North America has spurred an examination of alternative management strategies which focus on emulating dynamic natural disturbance processes, particularly those associated with forest fire regimes. This topic is the cornerstone of research in the Blue River Landscape Study (BRLS) on the Willamette National Forest in the McKenzie River watershed of western Oregon. As scientists and managers work to unravel the ecological and economic implications of disturbance-based forest management, they must also consider public acceptance for such an approach. In this study, citizen opinions from the local attentive public in McKenzie River watershed communities are examined. Results suggest the attentive public has moderate to low levels of knowledge about landscape-level disturbance processes and terms. Further, public confidence in agencies and the information they provide appears to be low, though respondents indicated a somewhat higher level of trust for local agency personnel than agencies as institutions. Overall, respondents display cautious support of disturbance-based management (DBM), but many are still undecided. Findings also demonstrate support may be improved through transparent and inclusive decision-making processes that demonstrate the use of sound science in project planning, frank disclosure of risks and uncertainties, and clear management objectives.