Ecological security driving mechanisms and optimization of zoning in Chinese urban agglomerations: A case study of the central plains urban agglomeration
Jinyuan Zhang , Xuning Qiao , Yongju Yang , Liang Liu , Yalong Li , Shengnan Zhao
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引用次数: 0
Abstract
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.
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.