Systemic Resilience of the Sustainable Development Goals Causal Network: A Dynamic Assessment under Extreme Climate Stress Scenarios

Résumé fourni par la source

Climate change threatens progress on the Sustainable Development Goals (SDGs) by exposing their deep interdependencies. This study constructs a causal network model of the SDGs and tests system resilience under five extreme climate stressors: extreme heat, extreme precipitation, drought, tropical cyclones, and wildfires—using sequential node perturbation simulations. Results indicate that the SDG network is densely connected (density, 0.346; clustering coefficient, 0.629) and performs at 0.574 baseline level. Resilience varies sharply across stressors: extreme heat triggers the fastest performance decline—its resilience curve area is 31.4% lower than drought's—indicating high cascading failure risk. Both extreme heat and tropical cyclone cause critical transitions when the first 30% of nodes are removed. Vulnerability analysis across all scenarios consistently identifies SDG 6 (Clean Water and Sanitation) and SDG 13 (Climate Action) as structural hubs—high in betweenness centrality and failure frequency—making them pivotal for system stability. These findings reveal how climate risks amplify systemic vulnerability through SDG interlinkages. The perturbation framework offers a quantitative tool to pinpoint intervention priorities and guide resilience-building governance under climate stress.

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