The eight Sustainable Development Goals (SDGs) related to resources (2, 6, 7), economy (8, 9), and environment (12, 13, 15), collectively known as REE, form the core of the human-nature system. Understanding their complex interactions is crucial for identifying transformative and effective governance actions. However, the causal mechanisms underlying the REE-related SDGs remain elusive. We used expert elicitation to assess weighted, directed interactions among 69 targets of these SDGs and applied network analysis and machine learning to identify their higher-order impacts, capacity to maintain network robustness, community structures, similarities, and systemic and structural roles. Additionally, we used causal emergence analysis and link prediction to examine potential characteristics of the causal network at macro and micro scales, respectively. The results indicate that prioritizing target 9.4 (sustainable & clean industries) can accelerate overall SDG progress while enhancing synergies and maintaining systemic resilience. In the macro-network, where causal emergence occurs, macronode E dominated by ecological targets plays the strongest facilitating role. In the micro-network, four predicted links with the highest weights indicate that strengthening scientific research and technological innovation is expected to be a potential focal point for positive impact. However, its possible negative effects warrant careful consideration. Additionally, significant trade-offs may arise between energy development and species conservation in the REE nexus that should be avoided. This study offers new insights into the causal mechanisms and priorities of the SDGs in REE, promoting global human-nature system coupling and accelerating the achievement of the 2030 Agenda.
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