Adaptive management is a systematic approach to learning from outcomes to improve management. Although its virtues are commonly praised, it has been implemented infrequently in natural resource management because of the challenges of developing a feasible process that can be sustained over time. Our analysis of regional experiences from private, state, and federal lands in the Pacific Northwest (United States and Canada) finds that the questions addressed by private organizations tend to be more specific, associated with a narrower scope of uncertainties, and addressed in a shorter time frame with limited stakeholder involvement. On publicly managed lands, questions tend to be more complex and open-ended, usually driven by their mandate for multiple use and high level of stakeholder engagement. We present a structured adaptive management framework that translates theory into action by describing an implementation process and organizational structure, explicitly linking learning to management planning and implementation, and integrating the technical and social aspects of adaptive management. Forest managers and policymakers can customize our example according to their mandate and management objectives. The framework is particularly relevant to land management for multiple uses, where the uncertainties are abundant and complex, and the decisionmakers increasingly use mathematical modeling to inform their decisions.

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适应性管理的结构化框架：奥林匹克实验国家森林中的桥梁理论与实践

适应性管理是一种从结果中学习以改进管理的系统方法。尽管它的优点广受赞誉，但由于开发一个可行的，随着时间的流逝而可持续的过程所面临的挑战，它在自然资源管理中很少得到实施。我们对西北太平洋地区（美国和加拿大）的私人，州和联邦土地的区域经验进行的分析发现，私人组织所解决的问题往往更具体，不确定性范围更窄，而解决的时间更短利益相关者参与有限的时间框架。在公共管理的土地上，问题往往更为复杂和开放性，通常是由其对多种用途的授权和利益相关者高度参与的驱动。我们提供了一个结构化的适应性管理框架，该框架通过描述实施过程和组织结构，将学习与管理计划和实施明确地联系起来，并整合适应性管理的技术和社会方面，将理论转化为行动。森林经理和政策制定者可以根据其任务授权和管理目标定制我们的榜样。该框架特别适用于多种用途的土地管理，因为不确定性既丰富又复杂，决策者越来越多地使用数学模型为决策提供依据。并整合适应性管理的技术和社会方面。森林经理和政策制定者可以根据其任务授权和管理目标定制我们的榜样。该框架与不确定性丰富而复杂的多种用途的土地管理特别相关，决策者越来越多地使用数学模型来指导其决策。并整合适应性管理的技术和社会方面。森林经理和政策制定者可以根据其任务授权和管理目标定制我们的榜样。该框架特别适用于多种用途的土地管理，因为不确定性既丰富又复杂，决策者越来越多地使用数学模型为决策提供依据。