Guiding Fuzzy Cognitive Mapping With Structured Decision Making to Inform Complex Natural Resource Management Problems in Waiʻanae Hawaiʻi

Abstract

Fire is one example of a larger class of wicked environmental management problems that require community-based management for long-term success. This study aimed to support participatory decision making in a data poor and complex system by using Fuzzy Cognitive Mapping (FCM) within the decision-making framework Structured Decision Making (SDM) to develop a community-based wildfire management plan in partnership with a local group in Wai‘anae Hawaiʻi. SDM is an organized process to create and evaluate decisions that can clarify trade-offs and increase transparency. FCM is a semi-quantitative method to describe system relationships that can handle low data and high uncertainty. We used SDM to define the problem, articulate community concerns related to wildfire, and identify management actions. We then used FCM to model how these actions affected valued ecosystem services and other stakeholder-identified objectives. Modeling results highlighted the trade-offs across three valued ecosystem services from three community-led wildfire management actions. We found that native species outplanting was the most beneficial action to each of the three valued ecosystem services. Through this participatory research, we conclude that the SDM and FCM pairing provided an inclusive and cost-effective way to engage with a specific wildfire management context, and that the process effectively engaged stakeholders while tackling uncertainty. This process also aided consensus-building and group member communication. This pairing can be used to aid community decision-making across diverse management problems as it provides a way to elicit objectives and model trade-offs, even under uncertainty and data limitations, while including stakeholders impacted by such decisions.