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1. Beyond choice architecture: A building code for structuring climate risk management decisions

   https://doi.org/10.1017/bpp.2020.37  

   ÁRVAI, JOSEPH; GREGORY, ROBIN (January 2020, Behavioural Public Policy)

   null (Ed.)

   Although the need for urgent climate change action is clear, insights about how to make better climate risk management decisions are limited. While significant attention from behavioral researchers has focused on choice architecture, we argue that many of the contexts for addressing climate risks require increased attention to the needs of a deliberative and dynamic choice environment. A key facet of this kind of decision is the need for decision-makers and stakeholders to identify and balance conflicting economic, social and environmental objectives. This recognition of difficult, context-specific trade-offs highlights the need for structuring the decision-making process so that objectives are clearly articulated and prioritized. Equally, policy analyses and deliberations must effectively link priorities with climate risk management options. This restructuring of decision-making about climate change calls for more than a nudge. Scientific and technical efforts must be redirected to help stakeholders and decision-makers better understand the diverse implications of climate change management alternatives and to become better equipped to take actions commensurate with the urgency of the problem. 

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2. Listening to Stakeholders: Initiating Research on Subseasonal-to-Seasonal Heavy Precipitation Events in the Contiguous United States by First Understanding What Stakeholders Need

   https://doi.org/10.1175/BAMS-D-20-0313.1  

   VanBuskirk, Olivia; Ćwik, Paulina; McPherson, Renee A.; Lazrus, Heather; Martin, Elinor; Kuster, Charles; Mullens, Esther (October 2021, Bulletin of the American Meteorological Society)

   Abstract Heavy precipitation events and their associated flooding can have major impacts on communities and stakeholders. There is a lack of knowledge, however, about how stakeholders make decisions at the subseasonal-to-seasonal (S2S) time scales (i.e., 2 weeks to 3 months). To understand how decisions are made and S2S predictions are or can be used, the project team for “Prediction of Rainfall Extremes at Subseasonal to Seasonal Periods” (PRES 2 iP) conducted a 2-day workshop in Norman, Oklahoma, during July 2018. The workshop engaged 21 professionals from environmental management and public safety communities across the contiguous United States in activities to understand their needs for S2S predictions of potential extended heavy precipitation events. Discussions and role-playing activities aimed to identify how workshop participants manage uncertainty and define extreme precipitation, the time scales over which they make key decisions, and the types of products they use currently. This collaboration with stakeholders has been an integral part of PRES 2 iP research and has aimed to foster actionable science. The PRES 2 iP team is using the information produced from this workshop to inform the development of predictive models for extended heavy precipitation events and to collaboratively design new forecast products with our stakeholders, empowering them to make more-informed decisions about potential extreme precipitation events. 

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3. Views of RNAi approaches for weed management in turfgrass systems

   https://doi.org/10.1017/wsc.2023.37  

   Ethridge, Sandra R; Grieger, Khara; Locke, Anna M; Everman, Wesley J; Jordan, David L; Leon, Ramon G (July 2023, Weed Science)

   Abstract Public concern regarding the use of herbicides in urban areas (e.g., golf courses, parks, lawns) is increasing. Thus, there is a need for alternative methods for weed control that are safe for the public, effective against weeds, and yet selective to turfgrass and other desirable species. New molecular tools such as ribonucleic acid interference (RNAi) have the potential to meet all those requirements, but before these technologies can be implemented, it is critical to understand the perceptions of key stakeholders to facilitate adoption as well as regulatory processes. With this in mind, turfgrass system managers, such as golf course superintendents and lawn care providers, were surveyed to gain insight into the perception and potential adoption of RNAi technology for weed management. Based on survey results, turfgrass managers believe that cost of weed management and time spent managing weeds are the main challenges faced in their fields. When considering new weed management tools, survey respondents were most concerned about cost, efficacy, and efficiency of a new product. Survey respondents were also optimistic toward RNAi for weed management and would either use this technology in their own fields or be willing to conduct research to develop RNAi herbicides. Although respondents believed that the general public would have some concerns about this technology, they did not believe this to be the most important factor for them when choosing new weed management tools. The need for new herbicides to balance weed control challenges and public demands is a central factor for turfgrass managers’ willingness to use RNAi-based weed control in turfgrass systems. They believe their clientele will be accepting of RNAi tools, although further research is needed to investigate how a wider range of stakeholders perceive RNAi tools for turfgrass management more broadly. 

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4. Reframing wildlife disease management problems with decision analysis

   https://doi.org/10.1111/cobi.14284  

   McEachran, Margaret_C; Harvey, Johanna_A; Mummah, Riley_O; Bletz, Molly_C; Teitelbaum, Claire_S; Rosenblatt, Elias; Rudolph, F_Javiera; Arce, Fernando; Yin, Shenglai; Prosser, Diann_J; et al (May 2024, Conservation Biology)

   Abstract Contemporary wildlife disease management is complex because managers need to respond to a wide range of stakeholders, multiple uncertainties, and difficult trade‐offs that characterize the interconnected challenges of today. Despite general acknowledgment of these complexities, managing wildlife disease tends to be framed as a scientific problem, in which the major challenge is lack of knowledge. The complex and multifactorial process of decision‐making is collapsed into a scientific endeavor to reduce uncertainty. As a result, contemporary decision‐making may be oversimplified, rely on simple heuristics, and fail to account for the broader legal, social, and economic context in which the decisions are made. Concurrently, scientific research on wildlife disease may be distant from this decision context, resulting in information that may not be directly relevant to the pertinent management questions. We propose reframing wildlife disease management challenges as decision problems and addressing them with decision analytical tools to divide the complex problems into more cognitively manageable elements. In particular, structured decision‐making has the potential to improve the quality, rigor, and transparency of decisions about wildlife disease in a variety of systems. Examples of management of severe acute respiratory syndrome coronavirus 2, white‐nose syndrome, avian influenza, and chytridiomycosis illustrate the most common impediments to decision‐making, including competing objectives, risks, prediction uncertainty, and limited resources. 

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5. Using social‐ecological models to explore stream connectivity outcomes for stakeholders and Yellowstone cutthroat trout

   https://doi.org/10.1002/eap.2915  

   Jossie, Elizabeth; Seaborn, Travis; Baxter, Colden V.; Burnham, Morey (September 2023, Ecological Applications)

   Abstract Despite growing interest in conservation and re‐establishment of ecological connectivity, few studies have explored its context‐specific social–ecological outcomes. We aimed to explore social and ecological outcomes to changing stream connectivity for both stakeholders and native fish species impacted by habitat fragmentation and nonnative species. We (1) investigated stakeholder perceptions of the drivers and outcomes of stream connectivity, and (2) evaluated the effects of stakeholder‐identified connectivity and nonnative species scenarios on Yellowstone cutthroat trout (YCT) populations. Our study was conducted in the Teton River, Idaho, USA. We integrated two modeling approaches, mental modeling and individual‐based ecological modeling, to explore social–ecological outcomes for stakeholders and YCT populations. Aggregation of mental models revealed an emergent pattern of increasing complexity as more types of stakeholders were considered, as well as gaps and linkages among different stakeholder knowledge areas. These results highlight the importance of knowledge sharing among stakeholders when making decisions about connectivity. Additionally, the results from the individual‐based models suggested that the potential for a large, migratory life history form of YCT, in addition to self‐preference mating where they overlap with rainbow trout, had the strongest effects on outcomes for YCT. Exploring social and ecological drivers and outcomes to changing connectivity is useful for anticipating and adapting to unintended outcomes, as well as making decisions for desirable outcomes. The results from this study can contribute to the management dialogue surrounding stream connectivity in the Teton River, as well as to our understanding of connectivity conservation and its outcomes more broadly. 

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