{"title":"长江经济带生态文明时空异质性研究","authors":"Li Ma, Huiyuan Zhang, Xiaojie Meng, Qing Lu","doi":"10.1016/j.ecolind.2025.113808","DOIUrl":null,"url":null,"abstract":"<div><div>The pursuit of the ecological civilization embodies the strategy of China for sustainable development and the harmonious coexistence of humans and nature. The Yangtze River Economic Belt (YREB) serves as a critical region for this initiative. Although prior studies have assessed spatiotemporal differentiation and subsystem coordination in the ecological civilization development process in the YREB, revealing regional trends, municipal-scale dynamics and heterogeneity in development patterns remain underexplored. In this study, 118 YREB cities are explored, and a novel weight calculation method that combines a genetic algorithm with a dynamic deviation maximization model (GA-DM) is introduced to ensure objectivity. The ecological civilization progress index (ECPI) is established on the basis of Multicriteria Decision-Making (MCDM) theory, and a three-dimensional indicator system covering environmental, economic, and social dimensions is applied. The system incorporates remote sensing data, including net primary productivity, nighttime light index, and greenhouse gas emission data, to address traditional data limitations. The Getis-Ord Gi*, coupling coordination degree, and RFA-SHAP methods are applied to examine spatiotemporal differentiation, coupling coordination trends, and key influencing factors from 2013 to 2022. The results revealed that (1) the ECPI increased significantly, but the growth rates fluctuated and declined over time, revealing a “higher in the east, lower in the west” pattern, with a widening east-west gap; (2) the coupling coordination levels improved, with narrowing regional disparities, although these levels lagged in southwestern border cities; (3) the key factors influencing ecological civilization development in the YREB were initially led by economic subsystem, with this influence diminishing as the social subsystem gained strength and the environmental subsystem remained weak; and (4) primary drivers of ecological civilization progress in cities evolved distinctly, with shifts toward economy-environment-driven factors in eastern economic cities, mixed-type factors in central cities, and environment-driven factors in western cities, revealing pronounced regional heterogeneity. These drivers exhibit varied temporal and spatial impacts across the YREB. These findings reveal key influencing factors and regional disparities, providing a basis for formulating differentiated policies.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"177 ","pages":"Article 113808"},"PeriodicalIF":7.0000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatiotemporal heterogeneity of the ecological civilization in the Yangtze River economic belt\",\"authors\":\"Li Ma, Huiyuan Zhang, Xiaojie Meng, Qing Lu\",\"doi\":\"10.1016/j.ecolind.2025.113808\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The pursuit of the ecological civilization embodies the strategy of China for sustainable development and the harmonious coexistence of humans and nature. The Yangtze River Economic Belt (YREB) serves as a critical region for this initiative. Although prior studies have assessed spatiotemporal differentiation and subsystem coordination in the ecological civilization development process in the YREB, revealing regional trends, municipal-scale dynamics and heterogeneity in development patterns remain underexplored. In this study, 118 YREB cities are explored, and a novel weight calculation method that combines a genetic algorithm with a dynamic deviation maximization model (GA-DM) is introduced to ensure objectivity. The ecological civilization progress index (ECPI) is established on the basis of Multicriteria Decision-Making (MCDM) theory, and a three-dimensional indicator system covering environmental, economic, and social dimensions is applied. The system incorporates remote sensing data, including net primary productivity, nighttime light index, and greenhouse gas emission data, to address traditional data limitations. The Getis-Ord Gi*, coupling coordination degree, and RFA-SHAP methods are applied to examine spatiotemporal differentiation, coupling coordination trends, and key influencing factors from 2013 to 2022. The results revealed that (1) the ECPI increased significantly, but the growth rates fluctuated and declined over time, revealing a “higher in the east, lower in the west” pattern, with a widening east-west gap; (2) the coupling coordination levels improved, with narrowing regional disparities, although these levels lagged in southwestern border cities; (3) the key factors influencing ecological civilization development in the YREB were initially led by economic subsystem, with this influence diminishing as the social subsystem gained strength and the environmental subsystem remained weak; and (4) primary drivers of ecological civilization progress in cities evolved distinctly, with shifts toward economy-environment-driven factors in eastern economic cities, mixed-type factors in central cities, and environment-driven factors in western cities, revealing pronounced regional heterogeneity. These drivers exhibit varied temporal and spatial impacts across the YREB. These findings reveal key influencing factors and regional disparities, providing a basis for formulating differentiated policies.</div></div>\",\"PeriodicalId\":11459,\"journal\":{\"name\":\"Ecological Indicators\",\"volume\":\"177 \",\"pages\":\"Article 113808\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2025-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Indicators\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1470160X25007381\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1470160X25007381","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Spatiotemporal heterogeneity of the ecological civilization in the Yangtze River economic belt
The pursuit of the ecological civilization embodies the strategy of China for sustainable development and the harmonious coexistence of humans and nature. The Yangtze River Economic Belt (YREB) serves as a critical region for this initiative. Although prior studies have assessed spatiotemporal differentiation and subsystem coordination in the ecological civilization development process in the YREB, revealing regional trends, municipal-scale dynamics and heterogeneity in development patterns remain underexplored. In this study, 118 YREB cities are explored, and a novel weight calculation method that combines a genetic algorithm with a dynamic deviation maximization model (GA-DM) is introduced to ensure objectivity. The ecological civilization progress index (ECPI) is established on the basis of Multicriteria Decision-Making (MCDM) theory, and a three-dimensional indicator system covering environmental, economic, and social dimensions is applied. The system incorporates remote sensing data, including net primary productivity, nighttime light index, and greenhouse gas emission data, to address traditional data limitations. The Getis-Ord Gi*, coupling coordination degree, and RFA-SHAP methods are applied to examine spatiotemporal differentiation, coupling coordination trends, and key influencing factors from 2013 to 2022. The results revealed that (1) the ECPI increased significantly, but the growth rates fluctuated and declined over time, revealing a “higher in the east, lower in the west” pattern, with a widening east-west gap; (2) the coupling coordination levels improved, with narrowing regional disparities, although these levels lagged in southwestern border cities; (3) the key factors influencing ecological civilization development in the YREB were initially led by economic subsystem, with this influence diminishing as the social subsystem gained strength and the environmental subsystem remained weak; and (4) primary drivers of ecological civilization progress in cities evolved distinctly, with shifts toward economy-environment-driven factors in eastern economic cities, mixed-type factors in central cities, and environment-driven factors in western cities, revealing pronounced regional heterogeneity. These drivers exhibit varied temporal and spatial impacts across the YREB. These findings reveal key influencing factors and regional disparities, providing a basis for formulating differentiated policies.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.