Building trust through collaboration, institutional development, and social learning enhances efforts to foster ecosystem management and resolve multi‐scale society–environment dilemmas. One emerging approach aimed at addressing these dilemmas is adaptive co‐management. This method draws explicit attention to the learning (experiential and experimental) and collaboration (vertical and horizontal) functions necessary to improve our understanding of, and ability to respond to, complex social–ecological systems. Here, we identify and outline the core features of adaptive co‐management, which include innovative institutional arrangements and incentives across spatiotemporal scales and levels, learning through complexity and change, monitoring and assessment of interventions, the role of power, and opportunities to link science with policy.

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Environmental conservation initiatives, including marine protected areas (MPAs), have proliferated in recent decades. Designed to conserve marine biodiversity, many MPAs also seek to foster sustainable development. As is the case for many other environmental policies and programs, the impacts of MPAs are poorly understood. Social-ecological systems, impact evaluation, and common-pool resource governance are three complementary scientific frameworks for documenting and explaining the ecological and social impacts of conservation interventions. We review key components of these three frameworks and their implications for the study of conservation policy, program, and project outcomes. Using MPAs as an illustrative example, we then draw upon these three frameworks to describe an integrated approach for rigorous empirical documentation and causal explanation of conservation impacts. This integrated three-framework approach for impact evaluation of governance in social-ecological systems (3FIGS) accounts for alternative explanations, builds upon and advances social theory, and provides novel policy insights in ways that no single approach affords. Despite the inherent complexity of social-ecological systems and the difficulty of causal inference, the 3FIGS approach can dramatically advance our understanding of, and the evidentiary basis for, effective MPAs and other conservation initiatives.

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