Proceedings of the National Academy of Sciences · 2009 · 381 citations · 32 references
ManagementEnvironmental ManagementEnvironmental SciencesConservation PlanningEcosystem ManagementEnvironmental Decision-makingAdaptive ManagementConservation Decision-makingEnvironmental Decision SupportRelocation PolicyTranslocation PlanningDecision Tree VisualizationDecision-support ToolsEcological Decision SupportSocial Value CriteriaSocial Values In ScienceSocial Values Of NatureStructured Decision-makingValue-laden Science
Managed relocation has rapidly emerged as a potential biodiversity intervention under climate change, yet its use as a last‑alternative option and the urgent need for tools that integrate scientific uncertainty and social values highlight the complexity of decision making in this context. The authors propose a more inclusive strategy for evaluating managed relocation by presenting a heuristic tool that incorporates ecological and social criteria. The heuristic tool visualizes the integrated criteria by collapsing them into four classes plotted in a two‑dimensional space. The framework pragmatically summarizes MR dimensions by capturing evaluation uncertainty, enhancing transparency, and highlighting stakeholder trade‑offs.
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.
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