Elsevier, Environmental Science and Policy, (48), p. 147-162
DOI: 10.1016/j.envsci.2015.01.001
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Institutional feasibility defined as the ability of institutions to support adaptive capacity, is an important aspect of climate adaptation, through its influence on the implementation of adaptation measures to climate change. The objective of this study is to create a framework for assessing institutional preconditions that enable or constrain climate change adaptation measures in agriculture and to apply the framework to a case study in agriculture.We adopted and modified the Procedure for Institutional Compatibility Assessment (PICA). Institutions in our framework are characterized by a set of crucial institutional preconditions (CIPs) and indicators linked to each CIP. CIPs refer to both institutional incentives and constraints for implementation of adaptation measures (here to climate change). We applied a combination of ranking and scoring techniques based on information from workshops, interviews and a literature review to assess institutional incentives and constraints for adaptation measures, together indicating the institutional feasibility of implementation of adaptation measures. We selected and assessed three adaptation measures relevant to agriculture in Flevoland, a province in the Netherlands: (1) improvement of water management and irrigation facilities; (2) relocation of farms; and (3) development of new crop varieties.The two main constraining CIPs for the implementation of the measures were found to be (1) heterogeneity of actors' interests and (2) availability of resources. Based on the institutional feasibility analysis, the implementation of water management and improvement of irrigation facilities will potentially face fewer institutional constraints compared to the other two measures. We conclude that our approach proves applicable for institutional analyses of adaptation measures for current and future (climate) challenges at different levels of implementation, but that more applications are needed to test its validity and robustness.