Skip to Main Content
U.S. Forest Service
Caring for the land and serving people

United States Department of Agriculture

Home > Search > Publication Information

  1. Share via EmailShare on FacebookShare on LinkedInShare on Twitter
    Dislike this pubLike this pub
    Author(s): Brian R. Sturtevant; Andrew Fall; Daniel D. Kneeshaw; Neal P. P. Simon; Michael J. Papaik; Kati Berninger; Frederik Doyon; Don G. Morgan; Christian Messier
    Date: 2007
    Source: Ecology and Society 12(2):1-12
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: Download Publication  (6.02 MB)


    To assist forest managers in balancing an increasing diversity of resource objectives, we developed a toolkit modeling approach for sustainable forest management (SFM). The approach inserts a meta-modeling strategy into a collaborative modeling framework grounded in adaptive management philosophy that facilitates participation among stakeholders, decision makers, and local domain experts in the meta-model building process. The modeling team works iteratively with each of these groups to define essential questions, identify data resources, and then determine whether available tools can be applied or adapted, or whether new tools can be rapidly created to fit the need. The desired goal of the process is a linked series of domain-specific models (tools) that balances generalized "top-down" models (i.e., scientific models developed without input from the local system) with case-specific customized "bottom-up" models that are driven primarily by local needs. Information flow between models is organized according to vertical (i.e., between scale) and horizontal (i.e., within scale) dimensions. We illustrate our approach within a 2.1 million hectare forest planning district in central Labrador, a forested landscape where social and ecological values receive a higher priority than economic values. However, the focus of this paper is on the process of how SFM modeling tools and concepts can be rapidly assembled and applied in new locations, balancing efficient transfer of science with adaptation to local needs. We use the Labrador case study to illustrate strengths and challenges uniquely associated with a meta-modeling approach to integrated modeling as it fits within the broader collaborative modeling framework. Principle advantages of the approach include the scientific rigor introduced by peer-reviewed models, combined with the adaptability of meta-modeling. A key challenge is the limited transparency of scientific models to different participatory groups. This challenge can be overcome by frequent and substantive two-way communication among different groups at appropriate times in the model-building process, combined with strong leadership that includes strategic choices when assembling the modeling team. The toolkit approach holds promise for extending beyond case studies, without compromising the bottom-up flow of needs and information, to inform SFM planning using the best available science.

    Publication Notes

    • Check the Northern Research Station web site to request a printed copy of this publication.
    • Our on-line publications are scanned and captured using Adobe Acrobat.
    • During the capture process some typographical errors may occur.
    • Please contact Sharon Hobrla, if you notice any errors which make this publication unusable.
    • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.


    Sturtevant, Brian R.; Fall, Andrew; Kneeshaw, Daniel D.; Simon, Neal P. P.; Papaik, Michael J.; Berninger, Kati; Doyon, Frederik; Morgan, Don G.; Messier, Christian. 2007. A toolkit modeling approach for sustainable forest management planning: achieving balance between science and local needs. Ecology and Society 12(2):1-12


    decision support, ecosystem management, forest sustainability, interdisciplinary modeling, land planning, participatory modeling, scaling

    Related Search

    XML: View XML
Show More
Show Fewer
Jump to Top of Page