A conceptual framework for analysing adaptive capacity and multi-level learning processes in resource governance regimes
|Adaptive capacity; Adaptive governance; Climate change adaptation; COMPLEXITY; Environmental Sciences; Environmental Sciences & Ecology; Environmental Studies; Geography; Institutions; Resources management; RIVER-BASIN MANAGEMENT; Social learning; TRANSITIONS; WATER-RESOURCES
|ELSEVIER SCI LTD
|GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
Governance failures are at the origin of many resource management problems. In particular climate change and the concomitant increase of extreme weather events has exposed the inability of current governance regimes to deal with present and future challenges. Still our knowledge about resource governance regimes and how they change is quite limited. This paper develops a conceptual framework addressing the dynamics and adaptive capacity of resource governance regimes as multi-level learning processes. The influence of formal and informal institutions, the role of state and non-state actors, the nature of multi-level interactions and the relative importance of bureaucratic hierarchies, markets and networks are identified as major structural characteristics of governance regimes. Change is conceptualized as social and societal learning that proceeds in a stepwise fashion moving from single to double to triple loop learning. Informal networks are considered to play a crucial role in such learning processes. The framework supports flexible and context sensitive analysis without being case study specific. First empirical evidence from water governance supports the assumptions made on the dynamics of governance regimes and the usefulness of the chosen approach. More complex and diverse governance regimes have a higher adaptive capacity. However, it is still an open question how to overcome the state of single-loop learning that seem to characterize many attempts to adapt to climate change. Only further development and application of shared conceptual frameworks taking into account the real complexity of governance regimes can generate the knowledge base needed to advance current understanding to a state that allows giving meaningful policy advice. (C) 2009 Elsevier Ltd. All rights reserved.
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checked on Mar 1, 2024