Answers are grounded in this paper and cite their sources.
Climate‐risk analyses designed to inform adaptation decisions should reflect the values, knowledge, and lived experiences of affected communities. However, most existing frameworks remain centered on economic metrics and give limited consideration to non‐economic drivers of adaptation behavior. This paper develops and applies the Values‐informed Mental Models (ViMM) framework, a structured, community‐engaged and co‐produced approach that integrates stakeholder values and risk understandings—drawing on both resident and expert knowledge—into the development of decision analyses for climate risk management. We apply the ViMM approach to household‐level flood adaptation in the Susquehanna River Valley, Pennsylvania, a flood‐prone region in the United States. Using a co‐produced mental model developed with residents and technical experts, along with qualitative interviews with homeowners, we identify how people understand flood‐risk pathways and which values—such as place attachment, autonomy, aesthetics, personal finances, and community support—inform their thinking. Node‐frequency comparisons highlight key gaps between resident perspectives and components emphasized in existing flood‐risk management frameworks. By mapping resident‐derived values to specific nodes and pathways, the ViMM framework provides a transparent method for designing value‐sensitive risk analyses that are grounded in multiple forms of expertise. Our results suggest that incorporating diverse value objectives can improve the relevance of risk assessments, reveal critical trade‐offs, and support more equitable and community‐centered adaptation strategies. The ViMM framework is broadly applicable across climate hazards and offers a systematic approach for integrating stakeholder knowledge and values into climate‐risk research and decision support.
No takes yet. Share an insight, caveat, or question.
Cooper et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: