Riyanti Djalante, Cameron Holley, Frank Thomalla. Adaptive Governance and Managing Resilience to Natural Hazards[J]. International Journal of Disaster Risk Science, 2011, 2(4): 1-14. doi: 10.1007/s13753-011-0015-6
Citation: Riyanti Djalante, Cameron Holley, Frank Thomalla. Adaptive Governance and Managing Resilience to Natural Hazards[J]. International Journal of Disaster Risk Science, 2011, 2(4): 1-14. doi: 10.1007/s13753-011-0015-6

Adaptive Governance and Managing Resilience to Natural Hazards

doi: 10.1007/s13753-011-0015-6
  • Available Online: 2021-04-26
  • The increasing frequency, intensity, and severity of natural hazards is one of the most pressing global environmental change problems. From the local to the global level, governments and civil society need to increase resilience to these hazards. Despite what is now a very sizeable literature on designing governance systems to produce resilience, a substantial gap in the natural hazards scholarship remains because most studies have lacked grounding in comparable theories on governing for resilience. This article contributes to interdisciplinary research on the conceptual understanding of the interlinkages of adaptive governance (AG), resilience, and disaster risk reduction (DRR). Through better understanding of diversity of terminology, terms, and characteristics, we take a step forward towards mutual learning and intellectual experimentation between the three concepts. Our review shows that there are four characteristics of AG that are important to help increase resilience to natural hazards. These are polycentric and multilayered institutions, participation and collaboration, self-organization and networks, and learning and innovation. The article examines the development, tradeoffs, and benefits that arise from the implementation of the AG characteristics, and reviews their influence on resilience. Hazard and disaster case studies are then examined to see how each AG characteristic is viewed and implemented in disaster contexts. Based on this analysis, the contributions of AG to the DRR literature are identified, before outlining the implications for theory and further research.
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