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Using an agent-based model to examine forest management outcomes in a fire-prone landscape in Oregon, USA

Thomas A. Spies, USDA Forest Service Pacific Northwest Research Station
Eric White, USDA Forest Service Pacific Northwest Research Station
Alan Ager, USDA Forest Service Rocky Mountain Research Station
Jeffrey D. Kline, USDA Forest Service Pacific Northwest Research Station
John P Bolte, Department of Biological and Ecological Engineering, Oregon State University
Emily K Platt, USDA Forest Service Region 6
Keith A. Olsen, Department of Forest Ecosystems & Society, Oregon State University
Robert J Pabst, Department of Forest Ecosystems & Society, Oregon State University
Ana M.G. Barros, Department of Forest Engineering, Resources & Management, Oregon State University
John D Bailey, Department of Forest Engineering, Resources & Management, Oregon State University
Susan Charnley, USDA Forest Service
Anita T Morzillo, Department of Natural Resources & the Environment, University of Connecticut
Jennifer Koch, Department of Geography and Environmental Sustainability, University of Oklahoma
Michelle M Steen-Adams, University of New England
Peter H Singleton, USDA Forest Service Pacific Northwest Research Station
James Sulzman, Oregon State University
Cynthia Schwartz, Oregon State University
Blair Csuti, Oregon State University

DOI: http://dx.doi.org/10.5751/ES-08841-220125

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Abstract

Fire-prone landscapes present many challenges for both managers and policy makers in developing adaptive behaviors and institutions. We used a coupled human and natural systems framework and an agent-based landscape model to examine how alternative management scenarios affect fire and ecosystem services metrics in a fire-prone multiownership landscape in the eastern Cascades of Oregon. Our model incorporated existing models of vegetation succession and fire spread and information from original empirical studies of landowner decision making. Our findings indicate that alternative management strategies can have variable effects on landscape outcomes over 50 years for fire, socioeconomic, and ecosystem services metrics. For example, scenarios with federal restoration treatments had slightly less high-severity fire than a scenario without treatment; exposure of homes in the wildland-urban interface to fire was also slightly less with restoration treatments compared to no management. Treatments appeared to be more effective at reducing high-severity fire in years with more fire than in years with less fire. Under the current management scenario, timber production could be maintained for at least 50 years on federal lands. Under an accelerated restoration scenario, timber production fell because of a shortage of areas meeting current stand structure treatment targets. Trade-offs between restoration outcomes (e.g., open forests with large fire-resistant trees) and habitat for species that require dense older forests were evident. For example, the proportional area of nesting habitat for northern spotted owl (Strix occidentalis) was somewhat less after 50 years under the restoration scenarios than under no management. However, the amount of resilient older forest structure and habitat for white-headed woodpecker (Leuconotopicus albolarvatus) was higher after 50 years under active management. More carbon was stored on this landscape without management than with management, despite the occurrence of high-severity wildfire. Our results and further applications of the model could be used in collaborative settings to facilitate discussion and development of policies and practices for fire-prone landscapes.

Key words

adaptation; ecosystem services; landscape; management; wildfire

Copyright © 2017 by the author(s). Published here under license by The Resilience Alliance. This article  is under a Creative Commons Attribution-NonCommercial 4.0 International License.  You may share and adapt the work for noncommercial purposes provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license.

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Ecology and Society. ISSN: 1708-3087