Understanding the structure of stakeholders − projects network in endangered lakes restoration programs using social network analysis

Environmental Science & Policy(2023)

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摘要
Lakes are among the most vulnerable wetlands. Many lakes are disappearing, which can result in adverse social and environmental consequences in the world. The success of water resources management projects for restoring these lakes depends on understanding relevant active stakeholders and their networks in these systems. This study identifies the network structure of stakeholder-operational restoration projects in the Urmia Lake, located in northwest Iran, an example of aquatic ecosystems vulnerable to anthropogenic activities and climate change. The study uses the Social Network Analysis (SNA) technique to learn stakeholders’ roles and positions for enhancing a coherent and adaptive management system for restoring this lake. Document analyses and interviews with key stakeholders of the Urmia Lake Restoration Program (ULRP) indicated the restoration projects and active stakeholders at the national, provincial, and local levels. SNA identifies that although the stakeholders have moderate interactions for implementing operational projects, both stakeholders and projects have varying influence and power in the network. The stakeholders are also classified into different groups in terms of varied restoration projects and their roles. The poor collaboration of different categories of stakeholders for implementing projects can reduce their effectiveness, lead to conflicts in their actions, and prohibit the sustainable restoration of endangered lakes. The restoration programs of inland wetlands, particularly endangered lakes in arid and semi-arid areas can use the capacity of influential stakeholders and key projects to develop the integrity of stakeholders and water policies, enhance their involvement in relevant restoration projects and improve water resources management.
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关键词
Stakeholders,Urmia lake restoration,Water resources,Operational project,Social network analysis
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