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Project ID: 14-2-01-26

Year: 2014

Date Started: 08/01/2014

Date Completed: 03/01/2017

Title: Policy Scenarios for fire-adapted communities: understanding stakeholder risk-perceptions with FCM

Project Proposal Abstract: Fire adapted communities (FAC) are effective when the varied stakeholder groups within them understand the risks of wildfire and take proactive steps to manage these risks. Implementing policies for fire adaptation, however, remains difficult because they are not understood or supported uniformly across diverse stakeholders. To facilitate the creation of FACs, we propose the development of a novel approach, based on Fuzzy Cognitive Maps (FCM), that systematically collects mental model representations from a range of stakeholders to better understand their diverse perceptions of wildfire events, wildfire impacts, and wildfire management and ultimately predicts support for different fire management policies. Further, this information can be used to identify gaps between the risk-related reasoning about wildfire dynamics of fire management experts and the risk-related reasoning about wildfire dynamics of communities exposed to wildfire risks. Applying this method in the context of FAC will serve the needs of decision makers in multiple ways. First, we will be able to predict collaboration and conflict between stakeholder groups by capturing and typifying, (through FCM methodology) stakeholder mental models on wildfire risk exposure and effects. We hypothesize that similarity in mental models between stakeholder groups and between fire management experts is likely to result in collaboration between these groups, while groups with incongruent mental models will have competing policy preferences that could lead to conflict. Information about the degree of homogeneity or heterogeneity of the mental models of stakeholders in a community will support efforts to reach consensus among FACs stakeholders. Second, this research will allow fire management experts to anticipate the future responses to proposed fire management policies. We hypothesize that eliciting the internal mental models of stakeholders and translating these insights into mathematical models of perceptions, based on FCM methodology, will enable policy makers to simulate the outcomes of proposed policies on the stakeholder and community levels. They will thus be able to select policies that are likely to succeed, improve policies that are identified as unlikely to succeed, and prioritize activities based on these policy scenario results. Third we will identify target areas for improving risk communications. Finally, we hypothesize that comparing common stakeholder mental models, represented through FCM, with an expert-generated FCM model, will identify where stakeholder perception about wildfire risks and FAC policies differ from expert opinions. Insights can be used to improve outreach to stakeholders through more tailored risk communication strategies To test these hypotheses we will investigate three research questions: (1) To what degree are stakeholder mental models about wildfire risks homogenous or heterogeneous? (2) Do the differences in stakeholder mental models lead to different predictions about the impacts of wildfire events and different decisions about wildfire management policy support? (3) Does knowledge about differences and similarities in stakeholder mental models improve fire decision-makers' ability to effectively communicate with stakeholders, reach consensus decisions, and implement fire adaptive practices? To answer our research questions we will work closely with a wildfire prone community in the Pacific Northwest in conjunction with wildfire managers at Northwest Fire Science Consortium. The project will result in a general FCM-based social scientific approach that has never before been undertaken in the fire sciences, that is applicable to a range of fire-exposed communities on the urban wildland interface. It will provide one of the first applications of FCM to wildfire management and is the first one to systematically link insights into risk perceptions with concrete policy decision making.

Principal Investigator: Antonie J. Jetter

Agency/Organization: Portland State University

Branch or Dept: Department of Engineering and Technology Management

Other Project Collaborators




Branch or Dept

Agreements Contact

Jennifer L. Ward

Portland State University

Budget Contact

Jennifer L. Reed

Portland State University

Research & Strategic Partnerships

Co-Principal Investigator

Lisa M. Ellsworth

Oregon State University

Department of Fisheries & Wildlife

Co-Principal Investigator

Steven A. Gray

Michigan State University

Department of Community Agriculture, Recreation & Resource Studies

Project Locations

Fire Science Exchange Network







Pacific Coast States


Project Deliverables

Final Report view or print

("Results presented in JFSP Final Reports may not have been peer-reviewed and should be interpreted as tentative until published in a peer-reviewed source.")

  ID Type Title
    7872 Final Report Supplement Fuzzy Cognitive Mapping for Fire Science Applications: A Guide for Practitioners
  go to website 7871 Computer Model/Software/Algorithm Modifications & Improvements to Mentalmodeler FCM Software

Supporting Documents

There are no supporting documents available for this project.

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