Reflexive learning in adaptive management: A case study of environmental water management in the Murray Darling Basin, Australia

Abstract

AbstractAdaptive management is a structured approach for people who must act despite uncertainty and complexity about what they are managing and the impacts of their actions. It is learning‐by‐doing through deliberate cycles of experimentation, review, and synthesis. However, understanding the processes of learning and how they relate to achieving resource management goals is in its infancy. Reflexive learning—a process of identifying and critically examining assumptions, values, and actions that frame knowledge—is critical to the effectiveness of adaptive management. It involves adaptive feedbacks between stakeholders as they examine assumptions, values, and actions. Adaptive management has been applied to environmental flows because it offers a system for making decisions about tradeoffs. In the Murray Darling Basin (MDB), Australia, adaptive management is applied as a cycle of plan, do, monitor, and learn, facilitated by short‐ and long‐term learning among stakeholders. An alternative conceptualization of adaptive management as an integration of single‐, double‐, and triple‐loop learning across multiple levels of governance is presented. This is applied to environmental flows in the MDB to map adaptive feedbacks of reflexive learning. At the lowest level of governance (Water Resource Planning Area), goals are assessed as Thresholds of Potential Concern related to flow‐ecology responses, which are reviewed every 3–6 years. At the second level of governance (Basin‐States), Water Management Targets are the key goals; reviewed and reframed every 6–10 years. The highest level of governance (the MDB) is concerned with policy targets, with review and reframing over 8–15 years. Feedbacks that generate reflexive learning are complex and require commitment to move through the modes of single‐, double‐, and triple‐loop learning. Effective adaptive management of environmental water requires practitioners to situate themselves within a matrix of information flow across modes of learning, levels of governance, and components of a social‐ecological system, where reflexive learning drives the achievement of management goals.