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Understand systemic risk from mangrove ecosystem through network analysis
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作者 Mimi Gong Ke Yu +7 位作者 Qiang Huang Yinglan A miriam aczel Ye Li Maofang Ran Yan Cheng Kaiji Li Shen Qu 《Fundamental Research》 2026年第2期636-646,共11页
Mangrove deforestation amplifies systemic risks by worsening extreme weather events,impeding socio-economic development,and exposing governance vulnerabilities.Yet,the extent to which mangrove dynamics-both loss and r... Mangrove deforestation amplifies systemic risks by worsening extreme weather events,impeding socio-economic development,and exposing governance vulnerabilities.Yet,the extent to which mangrove dynamics-both loss and restoration-interact with climate,socio-economic,and governance systems to mitigate systemic risk re-mains underexplored.Drawing on the economic concept of“product space,”we construct a Mangrove Multi-systemic Risk Space,a network-based framework linking indicators across mangrove change,climate impacts,socio-economic development,and policy interventions.The network reveals a bipartite structure,with distinct clusters for mangrove loss and expansion,each surrounded by synergistic indicators.The mangrove loss clus-ter is tightly coupled with greenhouse gas emissions and climate extremes,while the expansion cluster aligns with renewable energy,economic growth,and population dynamics.Within this space,we identify two types of structurally significant indicators:“influential”(e.g.,Ramsar site coverage)with high cascading potential,and“complex”indicators that require coordinated improvements across multiple dimensions,highlighting their sys-temic vulnerability.At the national level,the United States leads in achieving complex goals such as reducing extreme events,whereas New Zealand and Panama emerge as hubs of influential,well-performing indicators.These findings underscore the differentiated roles of mangrove-rich nations in mitigating systemic risk and call for strengthened global cooperation in mangrove conservation. 展开更多
关键词 Mangrove ecosystems Systemic risk Cascading effects Complex network analysis Multidimensional evaluation
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