Abstract
The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation goals. One approach that shows considerable promise for addressing these challenges is adaptive management, which by now is broadly seen as a natural, intuitive, and potentially effective way to address decision-making in the face of uncertainties. Yet the concept of adaptive management continues to evolve, and its record of success remains limited. In this article, we present an operational framework for adaptive decision-making, and describe the challenges and opportunities in applying it to real-world problems. We discuss the key elements required for adaptive decision-making, and their integration into an iterative process that highlights and distinguishes technical and social learning. We illustrate the elements and processes of the framework with some successful on-the-ground examples of natural resource management. Finally, we address some of the difficulties in applying learning-based management, and finish with a discussion of future directions and strategic challenges.
Highlights
The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation needs and goals
We describe a framework that emphasizes key roles for both technical and social learning, and illustrate the framework with examples that show the successful use of adaptive decision-making for on-the-ground management of renewable natural resources
We have described an operational framework for adaptive management, one that accounts for the key components and processes needed for learning-based decision-making
Summary
The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation needs and goals. One approach that shows considerable promise is adaptive management, which is broadly seen as a natural, intuitive, and potentially effective way to make decisions in the face of uncertainties. Though it offers new opportunities to inform decisionmaking and improve the management of natural resources, the record of success for adaptive management remains limited. Flexible decision-making that can be adjusted in the face of uncertainties as outcomes from management actions and other events become better understood. Careful monitoring of these outcomes both advances scientific understanding and helps adjust policies or operations as part of an iterative learning process’’. The sequential cycle of learning and adaptation targets better understanding of the resource system, and better management based on that understanding
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