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Oral Abstract Details

Using Public Participatory Modeling to Build Bayesian Belief Networks to Identify Lands Suited for Conservation, Working Forests, Agriculture, and Development. - (published)


Author(s):
Jon McCloskey, Robert Lilieholm, and Chris Cronan

Affiliation:
The University of Maine

Presentation Type:
Oral

Topic Area:
Application of ecological research in land-use planning

Abstract Text:
In Maine, providing research and development opportunities, vibrant communities, and environmental quality has been identified as an important economic development strategy. While 17% of the State’s land is protected from development, much of it remains as part of the working landscape producing wood fiber for the State’s forest products sector, food and forage under agricultural production, and open space for recreation. Thus, land use decisions involve multiple stakeholders, agencies, experts, and decision makers with different perspectives on how best to protect and enhance economic, environmental, and community assets. We engaged collaborators through the development of surveys and workshops modeled after Public Participatory Modeling (PPM) concepts and Structured Decision Making. We used the Delphi method to help collaborators identify biophysical and socio-economic metrics important for future land use changes. We used these metrics to create GIS data layers that we used as inputs into Bayesian Belief Networks (BBN). The BBNs enabled us to identify areas suited for: 1) working forests; 2) agricultural production; 3) ecosystem protection; and 4) future commercial and residential development. The suitability maps created in this process show commonalities and conflicts between these lands. The BBNs will serve as sub-models in a future Cellular Automata model that defines transition rules that will ultimately be used to detect drivers of land use change and generate different scenarios of future change. The tools developed will better inform land use planning for both conservation and development. The PPM workshops will increase stakeholder capacity to develop, understand and react to alternative futures. We also expect to see increased collaboration, expanded social capital, and better-targeted development and conservation proposals. To the extent that these outcomes are realized, we would expect to foster incremental improvements in quality-of-place and more sustainable rural economies across the Northern Forest region.