Governing for Learning: Institutional Foundations of Effective Adaptive Management

Fred Allen Johnson, William Pine

Adaptive management (AM) remains one of the most promising frameworks for managing conservation challenges under uncertainty, yet its potential is rarely realized in practice. Conservation agencies routinely make repeated decisions under uncertainty, but those decisions are often not structured in ways that allow learning to accumulate and improve future choices. This Perspectives article argues that success in AM depends less on technical sophistication than on governance systems that enable learning, accountability, and flexibility. Although the literature has extensively documented AM’s failures, it has rarely provided practitioners with an integrated framework addressing three connected questions: when is AM genuinely appropriate rather than rhetorically invoked, who should do what within an AM process, and how must governance structures be configured to make institutional learning possible? We address each question in turn, with particular attention to the structural, rather than technical, reasons why AM so often falls short, and to the underappreciated role of the decision analyst in bridging science, stakeholders, and governance. We argue that AM succeeds only when institutions are designed not merely to make decisions, but to learn from them.