Framework reveals how adaptive management approaches enhance conservation impact, indicating improved learning methods.
Conservation has successes to celebrate, but it is not on track to achieve global goals for biodiversity, climate, and people. There is an urgent need to learn how to increase conservation impact by identifying more effective conservation actions and how to scale them. We provide a framework for selecting learning approaches that support adaptive management at different stages in the maturity of a strategy. We use case studies from The Nature Conservancy (TNC), a global conservation organization, to illustrate the framework. During the “emerging” stage, teams used relatively rapid evidence synthesizing and generating practices (e.g., interviews, focus groups, expert input, pilot tests) to develop ideas, check assumptions, and refine or reformulate their theory of change (TOC). During the “validating” stage, teams used impact and performance evaluations to evaluate the effectiveness of conservation actions to inform decisions to adjust their TOC, expand, or exit. We suggest that teams can use similar approaches during the “scaling” stage to evaluate scaling mechanisms and verify conservation effectiveness in new contexts. These case studies had one or more enabling conditions for learning (i.e., motivation from individuals, partners, or donors; clear learning agenda questions; special expertise or support; technical feasibility; adaptive management processes). In sum, we argue conservation could accelerate learning and impact by using more rapid learning practices early in strategy development and shifting to using more rigorous evaluation & learning as a strategy matures. Future research could help support learning during the “scaling” stage by advancing evaluation methods that are suitable to these situations.
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Reddy et al. (2025) studied this question.
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