Linking knowledge and action for climate-ready fisheries: Emerging best practices across the US

Marine Policy(2023)

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摘要
Despite progress in understanding and predicting climate change impacts and possible responses for US marine fisheries, use of climate-related information in federal fishery management decisions remains limited. One barrier to progress in linking climate knowledge to management action is that individual management bodies’ efforts tend to be isolated, with few opportunities to coordinate or communicate about successes and shared challenges. To promote cross-regional learning, we distill eight best practices from emerging climate-focused efforts, drawn from a collaborative workshop, literature, and authors’ experiences. We conceptualize these best practices as interrelated—and incomplete—pieces of a knowledge-to-action “puzzle” that could be adopted based on regional context. One best practice, mapping out management processes and structure to identify “on-ramps” for climate information (3.1), represents a foundational centerpiece that enables other best practices. Three practices apply primarily to internal management processes: frame climate initiatives within existing management mandates and processes (3.2); strategically incorporate qualitative information to deal with uncertainty (3.3); and pilot initiatives with healthy or lower-risk stocks (3.4). Another set pertains to efforts that include broader stakeholders: engage stakeholders early and often (3.5), emphasize local priorities (3.6), employ structured processes to keep initiatives on track (3.7), and leverage collaborative research to build trust and overcome capacity constraints (3.8). We highlight emerging initiatives that demonstrate how these practices were implemented, discuss continued challenges, and identify opportunities where these practices could be expanded in support of climate-ready fisheries.
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关键词
Climate-resilient fisheries,Climate-adaptive fisheries,Fisheries management,Science-policy interface,Climate change,Climate-related information
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