CN 11-5366/S     ISSN 1673-1530
“风景园林,不只是一本期刊。”

“城市-湿地复合体”生态网络韧性的多情景测度与响应——以广州市海珠区为例

Multi-scenario Measurement and Response of Ecological Network Resilience in Urban-Wetland Complexes: Case Studies of Haizhu District, Guangzhou

  • 摘要:
    目的 在城市时空动态演变中,对广州市海珠区未来发展的不同情景进行模拟,探索城市动态发展和区域协同引导下城市生态网络韧性测度方法与设计响应,在中观尺度下讨论城市可持续发展的导向及规划策略。
    方法 以广州市海珠区为例,提出“城市-湿地复合体”概念并总结其特征,运用斑块级土地利用变化模拟(patch-generating land use simulation, PLUS)模型,模拟2030年自然发展、城市扩张和生态优先3种情景下的土地利用格局,结合形态学空间格局分析(morphological spatial pattern analysis, MSPA)与图论方法,构建动态演进的生态网络并量化其韧性特征。通过介数中心性分析和节点删除算法,评估生态网络结构韧性与功能韧性,揭示“城市-湿地复合体”的韧性响应机制。
    结果 海珠区生态源地的分布与珠江河网、湿地公园(如海珠湿地)及城市绿地系统高度重合。自然发展情景下生态网络连通性、抗干扰能力和连接效率最高,结构韧性强;城市扩张情景下生态网络对关键节点依赖性增强,功能韧性较弱;生态优先情景下生态网络韧性阈值最高,韧性水平高。
    结论 生态网络是保障城市生态韧性的关键载体。“城市-湿地复合体”生态网络韧性测度,可以为中观尺度下城市生态敏感区的生态韧性强化及设计响应提供新思路。

     

    Abstract:
    Objective Urbanization has fragmented ecological habitats, threatening urban ecosystem sustainability. Ecological networks are crucial for maintaining resilience, with dynamic interactions between network systems and urban development. Amid the green transformation of cities, refining the framework for optimizing urban ecological networks is essential. However, current research mainly focuses on static optimization, neglecting the dynamic evolution between nature and urbanization, and overlooks land use/cover changes in mid-to-small-scale areas, weakening the social functions of ecological networks. This study aims to address the limitations of current static approaches to urban ecological network optimization by investigating the dynamic interplay between urbanization and ecological network resilience. Specifically, focusing on Haizhu District, Guangzhou, this research will discuss the following issues. 1) Simulate future urban development scenarios and potential disturbances, considering spatio-temporal dynamics and land use/cover changes at a mesoscale; 2) Develop and apply a framework for proactively measuring the resilience of urban ecological networks under these dynamic scenarios; 3) Propose targeted design responses and optimization strategies to enhance ecological network resilience, incorporating principles of regional coordination; 4) Ultimately, inform sustainable urban development orientations and operational strategies for Haizhu District, contributing to a more resilient and ecologically sound urban environment.
    Methods This study develops a theoretical framework to analyze the dynamic coupling between urban development and ecological networks, and proposes a new concept of "Urban-Wetland Complex" and summarizes it along with its characteristics. The framework is applied to Haizhu District, Guangzhou (90.42 km2), a representative wetland urban area in the Pearl River Delta, serving as a case study. Multi-source data, including land use and land cover change (LUCC) data, remote sensing imagery, and socio-economic statistics, are integrated to parameterize the patch-generating land use simulation (PLUS) model. This model is then used to simulate three future development scenarios: 1) natural evolution (baseline scenario without policy intervention), 2) ecological priority (scenario that maximizes ecological benefits), and 3) economic priority (scenario that maximizes economic efficiency). Based on multi-temporal land-use classification maps derived from these simulations, ecological networks are constructed under each scenario. A dual-dimensional resilience assessment model, encompassing both structural and functional aspects, is proposed to quantify the resilience of the network. Structural resilience is evaluated using Graph Theory metrics, specifically connectivity probability and network closure. Functional resilience is assessed through betweenness centrality analysis and node-deletion experiments, focusing on key node identification rate and overall network robustness.
    Results 1) Structural and functional resilience mechanisms: Structural resilience was primarily influenced by the degree of source fragmentation, the average length of ecological corridors, and network transmissibility. Functional resilience, in contrast, depended on the number of critical nodes and their sensitivity to node removal processes. The comparison of network resilience before and after node removal effectively identified key ecological nodes within the network. 2) Spatial patterns of ecological sources: Ecological sources in Haizhu District were largely consistent with the Pearl River network, wetland parks (e.g., Haizhu Wetland) and existing urban green space systems, reflecting the dominance of wetland−river interactions in shaping the ecological structure. 3) Scenario-based resilience performance: Under the natural development scenario, network connectivity, disturbance resistance, and connection efficiency were the highest, indicating superior structural resilience. The shortened average corridor length enhanced species migration efficiency, leading to improved overall network performance. Under the urban expansion scenario, the ecological network displayed a strong dependence on a limited number of critical nodes, resulting in weakened functional resilience and reduced spatial redundancy. Nodes were highly concentrated south of the wetlands, aligning with the phenomenon of ecological islanding induced by intensive development. Under the ecological priority scenario, the network exhibited the highest resilience threshold and overall stability. Secondary nodes such as Dawei Park and the riverside green belts formed a "core wetland−multi-tiered pivot" structure, enhancing spatial equilibrium and redundancy. However, the longer corridor paths in this scenario were more frequently interrupted by urban infrastructure and human disturbance.
    Conclusion This study advances on previous research on the identification of key ecological patches and corridors by incorporating a spatiotemporal perspective into the analysis of urban ecological networks. By assessing the evolution of landscape connectivity under multiple development scenarios, this study reveals the dynamic interactions between urban expansion and ecological resilience. The study further refines the methodological framework for evaluating urban ecological networks, establishing a three-dimensional analytical system integrating "network−resilience−potential". This framework not only provides scientific guidance for determining regional ecological development directions and optimizing land-use planning but also serves as a theoretical reference for understanding the dynamic coupling between nature and city in high-density urban environments. Ultimately, the findings contribute to bridging the gap between ecological modeling and spatial design, supporting the construction of adaptive, resilient, and sustainable urban ecological systems.

     

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