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Climate risks are growing. Research is increasingly important to inform the design of risk‐management strategies. Assessing such strategies necessarily brings values into research. But the values assumed within research (often only implicitly) may not align with those of stakeholders and decision makers. These misalignments are often invisible to researchers and can severely limit research relevance or lead to inappropriate policy advice. Aligning strategy assessments with stakeholders' values requires a holistic approach to research design that is oriented around those values from the start. Integrating values into research in this way requires collaboration with stakeholders, integration across disciplines, and attention to all aspects of research design. Here we describe and demonstrate a qualitative conceptual tool called a values‐informed mental model (ViMM) to support such values‐centered research design. ViMMs map stakeholders' values onto a conceptual model of a study system to visualize the intersection of those values with coupled natural‐human system dynamics. Through this mapping, ViMMs integrate inputs from diverse collaborators to support the design of research that assesses risk‐management strategies in light of stakeholders' values. We define a visual language for ViMMs, describe accompanying practices and workflows, and present an illustrative application to the case of flood‐risk management in a small community along the Susquehanna river in the Northeast United States. 

Abstract ContextClimate change is altering suitable habitat distributions of many species at high latitudes. Fleshy fruit-producing plants (hereafter, “berry plants”) are important in arctic food webs and as subsistence resources for human communities, but their response to a warming and increasingly variable climate at a landscape scale has not yet been examined. ObjectivesWe aimed to identify environmental determinants of berry plant distribution and predict how climate change might shift these distributions. MethodsWe used species distribution models to identify characteristics and predict the distribution of suitable habitat under current (2006–2013) and future climate conditions (2081–2100; representative concentration pathways 4.5, 6.0, & 8.5) for five berry plant species:Vaccinium uliginosumL.,Empetrum nigrumL.,Rubus chamaemorusL.,Vaccinium vitis-idaeaL., andViburnum edule(Michx.) Raf.. ResultsElevation, soil characteristics, and January and July temperatures were important drivers of habitat distributions. Future suitable habitat predictions showed net declines in suitable habitat area for all species modeled under almost all future climate scenarios tested. ConclusionsOur work contributes to understanding potential geographic shifts in suitable berry plant habitat with climate change at a landscape scale. Shifting and retracting distributions may alter where communities can harvest, suggesting that access to these resources may become restricted in the future. Our prediction maps may help inform climate adaptation planning as communities anticipate shifting access to harvesting locations.