Network resilience of regional social-ecological systems under energy transition: measurement, drivers, and structural optimization in the Yangtze River Delta
エネルギー転換下における地域社会生態系のネットワーク・レジリエンス：測定、要因、構造最適化—長江デルタを事例に (AI 翻訳)
Guijun Li, Donghan Meng
🤖 gxceed AI 要約
日本語
本研究は、複雑ネットワーク理論を用いて、エネルギー転換下の地域社会生態系（SES）のレジリエンスを定量化する枠組みを提案する。長江デルタ都市圏を対象に、社会経済・生態要素の相互依存関係をネットワーク構造として可視化し、レジリエンスの測定、主要な推進要因の特定、構造最適化の経路を探る。結果、エネルギー転換が都市間の開発格差を拡大し、上海・南京・蘇州回廊を中心とする「中核-周辺」構造が強化されたこと、水資源賦存量、対外開放度、環境ガバナンスが重要な推進要因であることを示した。
English
This study proposes a complex network framework to quantify the resilience of regional social-ecological systems (SES) under energy transition. Using the Yangtze River Delta urban agglomeration as a case, it maps interdependencies among socioeconomic and ecological elements into a measurable network, identifying key drivers and structural optimization pathways. Findings show that energy transition amplifies urban development gradients, reinforcing a core-periphery structure centered on the Shanghai-Nanjing-Suzhou corridor, with water resources, openness, and environmental governance as critical resilience drivers.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本の地域エネルギー政策や国土計画に示唆を与える。特に、エネルギー転換が地域間格差を拡大させる可能性や、水資源・環境ガバナンスの重要性は、日本の地方都市や産業構造転換に応用可能な知見である。
In the global GX context
This paper contributes to global scholarship on regional resilience and energy transition, offering a network-based methodology applicable to other regions. It highlights the role of governance and natural endowments in shaping resilience, relevant for policymakers addressing just transitions and regional disparities.
👥 読者別の含意
🔬研究者:Provides a novel network-based framework for quantifying SES resilience under energy transition, useful for comparative regional studies.
🏢実務担当者:Offers insights into how regional integration and green innovation can enhance resilience, informing corporate location and investment strategies.
🏛政策担当者:Highlights the need for targeted policies to address regional disparities and support marginal areas in energy transition.
📄 Abstract（原文）
The global energy transition is profoundly reshaping the structure and function of regional social-ecological systems (SES). From a complex network perspective, this study develops an analytical framework to quantify SES resilience under energy transition. Taking the Yangtze River Delta urban agglomeration as a case study, this study maps the interdependencies among its socioeconomic and ecological elements into a measurable network structure. This allows us to measure system resilience, identify its key drivers, and explore their interactive effects, with the ultimate aim of informing structural optimization pathways. Key findings reveal that: (1) The energy transition has amplified the development gradient among cities. Core cities such as Shanghai, Hangzhou, Nanjing, and Hefei consolidate their leading positions through superior multidimensional resilience capital related to green innovation and infrastructure, whereas some cities in Anhui Province face heightened marginalization risks due to their reliance on traditional energy-intensive industries and insufficient capacity for energy transition. (2) Regionally, a dynamic “core-periphery” structure centered on the Shanghai-Nanjing-Suzhou corridor has been reinforced, with overall network resilience showing an upward trend. This improvement is primarily supported by enhanced connectivity fostered by regional integration and the growth of secondary nodes within emerging green energy and technology chains. (3) Critical drivers of resilience include water resource endowment, external openness, and proactive environmental governance. The nonlinear interactions among these factors highlight that SES resilience during the energy transition emerges from the complex synergy of natural conditions, economic restructuring dynamics, and adaptive policy interventions.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3389/fenvs.2026.1786465first seen 2026-05-17 07:02:16 · last seen 2026-05-28 05:05:54
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