Managed relocation (MR) has rapidly emerged as a potential intervention strategy in the toolbox of biodiversity management under climate change. Previous authors have suggested that MR (also referred to as assisted colonization, assisted migration, or assisted translocation) could be a last-alternative option after interrogating a linear decision tree. We argue that numerous interacting and value-laden considerations demand a more inclusive strategy for evaluating MR. The pace of modern climate change demands decision making with imperfect information, and tools that elucidate this uncertainty and integrate scientific information and social values are urgently needed. We present a heuristic tool that incorporates both ecological and social criteria in a multidimensional decision-making framework. For visualization purposes, we collapse these criteria into 4 classes that can be depicted in graphical 2-D space. This framework offers a pragmatic approach for summarizing key dimensions of MR: capturing uncertainty in the evaluation criteria, creating transparency in the evaluation process, and recognizing the inherent tradeoffs that different stakeholders bring to evaluation of MR and its alternatives.assisted migration ͉ climate change ͉ conservation biology ͉ conservation strategy ͉ sustainability science

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Summary1. Collaborative adaptive management (CAM) is regularly touted as the best way to handle natural resource management in the face of uncertainty, change and conflict. Successful applications of CAM have, however, been elusive in practice. 2. This article examines the Glen Canyon Dam Adaptive Management Program (AMP) in the United States, and other CAM efforts, to illustrate why and how procedural shortcomings may lead to natural resource management failures and reflect on how they may be overcome. 3. Synthesis and applications. To increase the chance of success, CAM efforts should set clear overarching goals and concrete and measurable objectives, employ tools and incentives to facilitate participation and foster collaboration, implement well-defined joint fact-finding protocols to promote shared learning and manage scientific uncertainty, and commit to monitoring and adapting their management regimes over time. Even in complex and contentious resource management contexts, future CAM efforts that integrate these design elements are likely to lead to more effective natural resource management.

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