Ecological security driving mechanisms and optimization of zoning in Chinese urban agglomerations: A case study of the central plains urban agglomeration
The global ecological security framework is facing unprecedented challenges and transformations, with ecological security issues transcending national and regional boundaries and evolving into a global concern. The Central Plains Urban Agglomeration (CPUA) serves as a critical urban growth pole in C...
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| Language: | English |
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Elsevier
2025-02-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25001190 |
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| author | Jinyuan Zhang Xuning Qiao Yongju Yang Liang Liu Yalong Li Shengnan Zhao |
| author_facet | Jinyuan Zhang Xuning Qiao Yongju Yang Liang Liu Yalong Li Shengnan Zhao |
| author_sort | Jinyuan Zhang |
| collection | DOAJ |
| description | The global ecological security framework is facing unprecedented challenges and transformations, with ecological security issues transcending national and regional boundaries and evolving into a global concern. The Central Plains Urban Agglomeration (CPUA) serves as a critical urban growth pole in China. In light of mounting ecological security challenges, including disparities in ecological efficiency and growing constraints from resource and environmental limitations, the CPUA urgently requires achieving a balance and mutually beneficial relationship between economic growth and ecological protection. This study examines 271 counties within the CPUA, utilizing both objective and subjective weighting methods to assess ecological security from a three-dimensional perspective, encompassing ecosystem health, landscape ecological risk, and ecosystem services over the period from 2000 to 2020. The analysis identifies dominant driving factors and spatial heterogeneity through the application of the Optimal Parameter Geodetic Detector (OPGD) and Multi-scale Geographically Weighted Regression (MGWR) models. Additionally, it combines the ’Three-dimensional Rubik’s Cube model with primary functional zoning to enhance the optimization of ecological security delineation. The results indicate that: (1) The ecological security situation in the CPUA remained stable from 2000 to 2020. The number of counties experiencing an upgrade in ecological security levels was greater than those experiencing a downgrade, with transitions primarily occurring between adjacent levels. Spatial disparities in ecological security were relatively small, and counties with lower ecological security levels tended to show greater clustering; (2) The explanatory power of the driving factors is ranked as follows: human factors > natural factors > landscape factors. Interaction detection factors exhibit varying degrees of dual-factor or nonlinear enhancement, with the combined strength of positive effects being greater than that of negative effects; (3) The spatial distribution characteristics of ecological security zones in the CPUA align with those of ecological security conditions. The CPUA is divided into “three zones, two belts, and one area,” with personalized ecological security model recommendations based on the primary functional zoning. This research furnishes a theoretical foundation for crafting scientifically informed ecological security policies for the CPUA and provides meaningful insights applicable to comparable urban agglomerations worldwide. |
| format | Article |
| id | doaj-art-9fdfd2f960ee40eea0a2d36c11718d30 |
| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-9fdfd2f960ee40eea0a2d36c11718d302025-02-08T04:59:59ZengElsevierEcological Indicators1470-160X2025-02-01171113190Ecological security driving mechanisms and optimization of zoning in Chinese urban agglomerations: A case study of the central plains urban agglomerationJinyuan Zhang0Xuning Qiao1Yongju Yang2Liang Liu3Yalong Li4Shengnan Zhao5School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003 China; Corresponding authors.School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003 China; Research Centre of Arable Land Protection and Urban-Rural High-Quality Development of Yellow River Basin, Henan Polytechnic University, Jiaozuo 454003 China; Corresponding authors.School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003 ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003 ChinaState Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Xinjiang Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003 China; Jiaozuo Municipal Natural Resources and Planning Bureau Shanyang Service Center, Jiaozuo 454003, ChinaThe global ecological security framework is facing unprecedented challenges and transformations, with ecological security issues transcending national and regional boundaries and evolving into a global concern. The Central Plains Urban Agglomeration (CPUA) serves as a critical urban growth pole in China. In light of mounting ecological security challenges, including disparities in ecological efficiency and growing constraints from resource and environmental limitations, the CPUA urgently requires achieving a balance and mutually beneficial relationship between economic growth and ecological protection. This study examines 271 counties within the CPUA, utilizing both objective and subjective weighting methods to assess ecological security from a three-dimensional perspective, encompassing ecosystem health, landscape ecological risk, and ecosystem services over the period from 2000 to 2020. The analysis identifies dominant driving factors and spatial heterogeneity through the application of the Optimal Parameter Geodetic Detector (OPGD) and Multi-scale Geographically Weighted Regression (MGWR) models. Additionally, it combines the ’Three-dimensional Rubik’s Cube model with primary functional zoning to enhance the optimization of ecological security delineation. The results indicate that: (1) The ecological security situation in the CPUA remained stable from 2000 to 2020. The number of counties experiencing an upgrade in ecological security levels was greater than those experiencing a downgrade, with transitions primarily occurring between adjacent levels. Spatial disparities in ecological security were relatively small, and counties with lower ecological security levels tended to show greater clustering; (2) The explanatory power of the driving factors is ranked as follows: human factors > natural factors > landscape factors. Interaction detection factors exhibit varying degrees of dual-factor or nonlinear enhancement, with the combined strength of positive effects being greater than that of negative effects; (3) The spatial distribution characteristics of ecological security zones in the CPUA align with those of ecological security conditions. The CPUA is divided into “three zones, two belts, and one area,” with personalized ecological security model recommendations based on the primary functional zoning. This research furnishes a theoretical foundation for crafting scientifically informed ecological security policies for the CPUA and provides meaningful insights applicable to comparable urban agglomerations worldwide.http://www.sciencedirect.com/science/article/pii/S1470160X25001190Ecological securitySpatial heterogeneityGeoprobe with optimal parametersThree-dimensional Rubik’s Cube ModelCentral Plains Urban Agglomeration |
| spellingShingle | Jinyuan Zhang Xuning Qiao Yongju Yang Liang Liu Yalong Li Shengnan Zhao Ecological security driving mechanisms and optimization of zoning in Chinese urban agglomerations: A case study of the central plains urban agglomeration Ecological Indicators Ecological security Spatial heterogeneity Geoprobe with optimal parameters Three-dimensional Rubik’s Cube Model Central Plains Urban Agglomeration |
| title | Ecological security driving mechanisms and optimization of zoning in Chinese urban agglomerations: A case study of the central plains urban agglomeration |
| title_full | Ecological security driving mechanisms and optimization of zoning in Chinese urban agglomerations: A case study of the central plains urban agglomeration |
| title_fullStr | Ecological security driving mechanisms and optimization of zoning in Chinese urban agglomerations: A case study of the central plains urban agglomeration |
| title_full_unstemmed | Ecological security driving mechanisms and optimization of zoning in Chinese urban agglomerations: A case study of the central plains urban agglomeration |
| title_short | Ecological security driving mechanisms and optimization of zoning in Chinese urban agglomerations: A case study of the central plains urban agglomeration |
| title_sort | ecological security driving mechanisms and optimization of zoning in chinese urban agglomerations a case study of the central plains urban agglomeration |
| topic | Ecological security Spatial heterogeneity Geoprobe with optimal parameters Three-dimensional Rubik’s Cube Model Central Plains Urban Agglomeration |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X25001190 |
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