Diagnosing institutional barriers and opportunities for adaptation to climate change

Christoph Oberlack ()
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Christoph Oberlack: Albert-Ludwigs-University of Freiburg

Mitigation and Adaptation Strategies for Global Change, 2017, vol. 22, issue 5, No 7, 805-838

Abstract: Abstract Institutions are one of the decisive factors which enable, constrain and shape adaptation to the impacts of climate change, variability and extreme events. However, current understanding of institutions in adaptation situations is fragmented across the scientific community, evidence diverges, and cumulative learning beyond single studies is limited. This study adopts a diagnostic approach to elaborate a nuanced understanding of institutional barriers and opportunities in climate adaptation by means of a model-centred meta-analysis of 52 case studies of public climate adaptation in Europe. The first result is a novel taxonomy of institutional attributes in adaptation situations. It conceptually organises and decomposes the many details of institutions that empirical research has shown to shape climate adaptation. In the second step, the paper identifies archetypical patterns of institutional traps and trade-offs which hamper adaptation. Thirdly, corresponding opportunities are identified that enable actors to alleviate, prevent or overcome specific institutional traps or trade-offs. These results cast doubt on the validity of general institutional design principles for successful adaptation. In contrast to generic principles, the identified opportunities provide leverage to match institutions to specific governance problems that are encountered in specific contexts. Taken together, the results may contribute to more coherence and integration of adaptation research that we need if we are to foster learning about the role of institutions in adaptation situations in a cumulative fashion.

Keywords: Climate change adaptation; Institutions; Institutional diagnostics; Model-centred; Meta-analysis; Europe; Archetypes (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s11027-015-9699-z

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