Department of Community Sustainability, Michigan State University
This December Robyn Wilson, Christian Beaudrie and I traveled to San Diego to report on a decision support framework we’re building to help organic farmers make ecological weed management decisions. This tool uses as its foundation mental models research done by Sarah Zwickle and the SDM principles that my colleagues and I rely on to improve complex, value-laden decisions.
Last spring, I traveled to New Orleans to meet with decision-makers and discuss efforts to manage the city’s sea-level rise and storm surge risks. This followed a trip to interview residents and build a “values-informed” mental model, ViMM, which depicts their values as a function of specific climate risk factors and management strategies. Our paper describing this model is now out in Risk Analysis, and the abstract is below.
“Individuals use values to frame their beliefs and simplify their understanding when con- fronted with complex and uncertain situations. The high complexity and deep uncertainty involved in climate risk management (CRM) lead to individuals’ values likely being coupled to and contributing to their understanding of specific climate risk factors and management strategies. Most mental model approaches, however, which are commonly used to inform our understanding of people’s beliefs, ignore values. In response, we developed a “Values- informed Mental Model” research approach, or ViMM, to elicit individuals’ values alongside their beliefs and determine which values people use to understand and assess specific cli- mate risk factors and CRM strategies. Our results show that participants consistently used one of three values to frame their understanding of risk factors and CRM strategies in New Orleans: (1) fostering a healthy economy, wealth, and job creation, (2) protecting and pro- moting healthy ecosystems and biodiversity, and (3) preserving New Orleans’ unique culture, traditions, and historically significant neighborhoods. While the first value frame is common in analyses of CRM strategies, the latter two are often ignored, despite their mirroring com- monly accepted pillars of sustainability. Other values like distributive justice and fairness were prioritized differently depending on the risk factor or strategy being discussed. These results suggest that the ViMM method could be a critical first step in CRM decision-support processes and may encourage adoption of CRM strategies more in line with stakeholders’ values.”
We used the mental models research method to generate a conceptual map of how Midwest farmers use knowledge, experience, and individual perceptions of weed-related risk to make weed management decisions. We discovered that Midwest farmer knowledge of ecological weed management practices is robust, and that the difficult trade-offs farmers make regarding cultivation, cover crops, and soil health determine what weed management practices they use. Midwest farmers balance the risks of cultivation and implementation of cover crops with their valuable benefits to soil health and weed suppression. Developing a decision support tool that provides a baseline of scientific evidence and that offers flexibility based on farmers’ experiences and values will clarify these trade-offs and guide effective decision-making.
Facilitating Ecological Weed Management Decisions by Assessing Risk-Benefit Tradeoffs
In an effort to reduce “carbon pollution” as well as prepare the U.S. for the impacts of climate change, President Obama’s 2013 Climate Action Plan calls for changes to be made to the nation’s energy system. In addition to focusing on alternative portfolios of different fuels and power-generation technologies, researchers and advisory panels have urged that changes to the nation’s energy system be based on a decision-making framework that incorporates stakeholders and accounts for real-world resource, supply, and demand constraints. To date, research and development on such a framework have proven elusive. The research reported here describes the development and test of a potential decision support framework that combines elements from structured decision-making (SDM) with portfolio analysis, methods that have been used independently to elicit preferences in complex decision contexts. This hybrid framework aimed to (1) provide necessary background information to users regarding the development of coupled climate-energy strategies; (2) account for users’ values and objectives; (3) allow for the construction of bespoke energy portfolios bounded by real-world supply and demand constraints; and (4) provide a more rigorous basis for addressing trade-offs. Results show that this framework was user-friendly, led to significant increases in users’ knowledge about energy systems and, importantly, led to more internally consistent decisions. For these reasons, this framework may serve as a suitable template for supporting decisions about energy transitions in the United States and abroad.
Decision support framework for developing regional energy strategies
Decisions about energy in developing communities are challenging from a technical standpoint, and because of the unique characteristics that typify them, e.g. limited infrastructure and government budgets, complex social and political arrangements, and economic vulnerability. Against the backdrop of these challenges, the government of Canada’s Northwest Territories (NWT) is attempting to reform the region’s energy system. This paper provides insights from the decision sciences, stemming from our work on the NWT’s energy planning process, about how to structure decisions about energy development and delivery so as to effectively meet a range of stakeholders’ objectives in a transparent and inclusive manner.
Structuring decisions about energy in developing communities: an example from Canada’s north
This article presents research aimed at developing and testing an online, multistakeholder decision-aiding framework for informing multiattribute risk management choices associated with energy development and climate change. The framework was designed to provide necessary background information and facilitate internally consistent choices, or choices that are in line with users’ prioritized objectives. In order to test different components of the decision-aiding framework, a six-part, 2 × 2 × 2 factorial experiment was conducted, yielding eight treatment scenarios. The three factors included: (1) whether or not users could construct their own alternatives; (2) the level of detail regarding the composition of alternatives users would evaluate; and (3) the way in which a final choice between users’ own constructed (or highest-ranked) portfolio and an internally consistent portfolio was presented. Participants’ self-reports revealed the framework was easy to use and providing an opportunity to develop one’s own risk-management alternatives (Factor 1) led to the highest knowledge gains. Empirical measures showed the internal consistency of users’ decisions across all treatments to be lower than expected and confirmed that providing information about alternatives’ composition (Factor 2) resulted in the least internally consistent choices. At the same time, those users who did not develop their own alternatives and were not shown detailed information about the composition of alternatives believed their choices to be the most internally consistent. These results raise concerns about how the amount of information provided and the ability to construct alternatives may inversely affect users’ real and perceived internal consistency.
