Identifying conditions for successful landscape-scale conservation policy implementation in Vietnam

Project leader Pham Thu Thuy
Email t.pham@cgiar.org
Location Vietnam
Project status ON-GOING
Project start 2020-01-01
Project end 2021-12-31

This project studies how governance network structure moderates the ecological and livelihoods impacts of landscape-scale conservation interventions. The literature hypothesizes that strong social networks should be more effective at forest conservation. Strong social networks can also contribute to local problem-solving and resilience more generally. Furthermore, we would expect management to improve conditional on interaction between stakeholders that are interdependent because they jointly use or manage the same forested ecosystem. Where such interaction between interdependent stakeholders is absent, "governance gaps" may create inefficiencies or conflict. However, under these conditions, we expect to observe better conservation outcomes when third-party stakeholders mediate interaction between interdependent stakeholders.

The project tests the above hypotheses using remote-sensing data on land cover, newly collected archival data on conservation governance networks and existing GCS-REDD data on livelihoods, land-use practices, and policy networks. These data allow us to test whether conservation outcomes depend upon alignment between the patterns of stakeholder interaction and patterns of ecological connectivity, and to draw conclusions about the types of stakeholders that tend to promote social-ecological alignment. This can aid in the design of policy interventions to improve conservation outcomes in fragmented environmental governance settings. Second, we use provincial-scale data to test the impacts of PFES and REDD+ on ecological and livelihoods outcomes. Third, we use active outreach to support improved PFES and REDD+ governance, using policy briefs and conduct workshops with key stakeholders in forest management in Vietnam targeted to foster connections that could improve governance network function.

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