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. In recent decades, federal forest management in the Pacific Northwest has shifted from a focus on sustained-yield timber harvest through dispersed and aggregated patch clearcutting to a system of management based on static land allocations laid out by the 1994 Northwest Forest Plan. However, growing emphasis on ecosystem and landscape management has spurred interest in alternative management strategies that focus on dynamic natural processes [1–3]. One such method is the use of historical disturbance as a guide for ecosystem management, which involves applying information about past natural disturbances to inform practices such as timber harvest, prescribed burning, or wildfire suppression [4]. This coarse-filter approach to conservation—known variously as disturbance-based management (DBM), emulation of natural disturbance, and management guided by a historical range of variability—is based upon the principle that plant and animal communities that evolved under dynamic ecosystem conditions will be most resilient and productive under management scenarios which emulate natural disturbance regimes [5, 6]. As scientists and
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