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One Health initiatives have advanced zoonotic disease management by recognizing the interconnectedness of three sectors of governance (human, ecosystem, and animal) and by identifying options that can improve full‐system health. Although One Health has had many successes, its full realization may be inhibited by a lack of strategies to overcome simultaneous impediments in decision making and governance. Decision impediments that hinder management may include uncertainty, risk, resource limitations, and trade‐offs among objectives. Governance impediments arise from disparities in costs and benefits of disease management among sectors. Tools and strategies developed from decision science, collaboration, and negotiation theory can help articulate and overcome coinciding decision and governance impediments and enhance multisectoral One Health initiatives. In cases where collaboration and negotiation are insufficient to address disparities in cross‐sector costs and benefits, altering incentive structures might improve disease‐specific outcomes and improve the realization of One Health. 

Abstract Climate‐induced shifts in mosquito phenology and population structure have important implications for the health of humans and wildlife. The timing and intensity of mosquito interactions with infected and susceptible hosts are a primary determinant of vector‐borne disease dynamics. Like most ectotherms, rates of mosquito development and corresponding phenological patterns are expected to change under shifting climates. However, developing accurate forecasts of mosquito phenology under climate change that can be used to inform management programs remains challenging despite an abundance of available data. As climate change will have variable effects on mosquito demography and phenology across species it is vital that we identify associated traits that may explain the observed variation. Here, we review a suite of modeling approaches that could be applied to generate forecasts of mosquito activity under climate change and evaluate the strengths and weaknesses of the different approaches. We describe four primary life history and physiological traits that can be used to constrain models and demonstrate how this prior information can be harnessed to develop a more general understanding of how mosquito activity will shift under changing climates. Combining a trait‐based approach with appropriate modeling techniques can allow for the development of actionable, flexible, and multi‐scale forecasts of mosquito population dynamics and phenology for diverse stakeholders.