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Boundary arrangements at the research-stakeholder interface (Descriptions are inspired by Burton 2006; Michaels 2009; Edelenbos et al. 2011. An adapted version of this table has been published in Schut et al. 2013b.)

Boundary arrangements at the research-stakeholder interface (Descriptions are inspired by Burton 2006; Michaels 2009; Edelenbos et al. 2011. An adapted version of this table has been published in Schut et al. 2013b.)

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This paper seeks to contribute to a better understanding of the complex dynamics that shape the contribution of research to policy and innovation processes that address ‘competing claims’ on natural resources and their management. Research in the context of competing claims requires strategies that: (1) can cope with high uncertainty and unpredicta...

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... research-private sector, research-civil society) and how such boundary ar- rangements evolve and change over time. Table 2 provides examples of boundary arrangements that can emerge between research and stakeholders. Boundary arrangements at the research-stakeholder interface do not equal researchers' roles, as researchers may fulfil different roles and undertake different activities within each of the specific boundary arrangements (see Section 2.5). ...

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Urmia Lake, which is one of the largest hypersaline lakes in the world, has experienced an excessive reduction of water level because of climatic change and anthropogenic influences. To mitigate this tragedy, several agricultural water management schemes have been initiated. However, many restoration programs have proven ineffective. To counter the lake’s disappearance, effective climate-smart agriculture (CSA) interventions are imperative. Nevertheless, the potential benefits, opportunities, risks, costs and incentive mechanisms of CSA interventions have not been well documented. Therefore, this qualitative research was performed in the eastern part of the Urmia Lake basin to identify the best CSA intervention for restoration of the lake and investigate the major drivers of CSA development. Using the “benefits, opportunities, risks, and costs” method, 14 influential factors were explored. Also, fuzzy VIKOR analysis indicated an urgent need of developing water-smart agriculture (WSA) in the Urmia Lake basin, where water scarcity, poor water governance and low water use efficiency are significant problems. Interpretive structural modeling and MICMAC analysis suggested that policy making and planning, research and development, monitoring and evaluation, education and extension services, supports and services, institutions and degree of their collaborations, knowledge and attitude, and infrastructures and farm structures can enhance the application of WSA interventions. Some recommendations and implications are offered to facilitate the adoption and development of WSA practices and technologies.