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<p>As global urban green transitions advance, they concern not only emission-reduction performance but also the flows of resources, information, and ecosystem services among cities within a region. The regional socio-ecological network structure plays a pivotal role in this process. It shapes the efficiency and intensity of inter-city factor flows, thereby influencing the level of regional coordinated development. However, existing research has yet to systematically reveal the mechanisms by which green-transition factors influence the structure of regional socio-ecological spatial networks, and it has paid insufficient attention to potential nonlinear relationships. Using 127 cities in the Yangtze River Economic Belt as a case, we first construct a socio-ecological network with a gravity model and evaluate its structural attributes. We then apply an interpretable XGBoost-SHAP framework to quantify the individual and interactive contributions of green transition indicators to network connectivity. The results show that (1) from 2008 to 2022 the Urban Development Index (UDI) increased from 0.146 to 0.205, while the ecosystem-service value (ESV) remained essentially stable, yet the overall level of synergy between the two improved; (2) the composite structural index of the socio-ecological network was 0.074 in 2008, peaked at 0.141 in 2013, and fell to 0.112 by 2022; and (3) Green patents (TGP) and the share of clean electricity (SCE) are identified as the key determinants of network connectivity, with contribution rates of 39.23% and 26.42%, respectively. All indicators exhibit significant nonlinear threshold effects, as the marginal effects of the share of clean electricity, energy consumption intensity, and wastewater treatment rate shift from positive to negative after surpassing specific thresholds. These findings suggest that green transition has optimal operating ranges across different development stages. Policy interventions should therefore be calibrated according to city-specific conditions to avoid excessive promotion that may weaken network connectivity. Overall, this study provides actionable insights and quantitative evidence for advancing urban green transition and regional coordinated governance.</p>

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How does the green transition shape the structure of regional socio-ecological networks? evidence from the Yangtze river economic belt

  • 期刊论文

  • 发表日期：

    2026年7月8日

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  • Dongdong Gao,
  • Xin Gao,
  • Rong Chen,
  • Shuangjiao Cai,
  • Jie Tian

摘要

As global urban green transitions advance, they concern not only emission-reduction performance but also the flows of resources, information, and ecosystem services among cities within a region. The regional socio-ecological network structure plays a pivotal role in this process. It shapes the efficiency and intensity of inter-city factor flows, thereby influencing the level of regional coordinated development. However, existing research has yet to systematically reveal the mechanisms by which green-transition factors influence the structure of regional socio-ecological spatial networks, and it has paid insufficient attention to potential nonlinear relationships. Using 127 cities in the Yangtze River Economic Belt as a case, we first construct a socio-ecological network with a gravity model and evaluate its structural attributes. We then apply an interpretable XGBoost-SHAP framework to quantify the individual and interactive contributions of green transition indicators to network connectivity. The results show that (1) from 2008 to 2022 the Urban Development Index (UDI) increased from 0.146 to 0.205, while the ecosystem-service value (ESV) remained essentially stable, yet the overall level of synergy between the two improved; (2) the composite structural index of the socio-ecological network was 0.074 in 2008, peaked at 0.141 in 2013, and fell to 0.112 by 2022; and (3) Green patents (TGP) and the share of clean electricity (SCE) are identified as the key determinants of network connectivity, with contribution rates of 39.23% and 26.42%, respectively. All indicators exhibit significant nonlinear threshold effects, as the marginal effects of the share of clean electricity, energy consumption intensity, and wastewater treatment rate shift from positive to negative after surpassing specific thresholds. These findings suggest that green transition has optimal operating ranges across different development stages. Policy interventions should therefore be calibrated according to city-specific conditions to avoid excessive promotion that may weaken network connectivity. Overall, this study provides actionable insights and quantitative evidence for advancing urban green transition and regional coordinated governance.