Abstract:

[Objective] Urban agglomerations concentrate population and economic activities, often intensifying resource consumption, ecological-space loss, and inefficient ecological use. Blue-green spaces are essential components of urban ecosystems and provide multiple ecosystem services, including urban cooling, air purification, carbon storage, hydrological regulation, soil conservation, and biodiversity maintenance. In the highly urbanized Yangtze River Delta urban agglomeration, these spaces are increasingly characterized by fragmentation, declining connectivity, and greater morphological complexity. Existing studies have mainly examined the effects of landscape patterns on individual ecological benefits, while their influence on comprehensive ecological utilization efficiency and its spatial interactions remains insufficiently understood. A comprehensive assessment is therefore needed to clarify how blue-green landscape patterns shape ecological utilization efficiency at both local and regional scales. This study measures the ecological utilization efficiency of blue-green spaces in the core built-up areas of the Yangtze River Delta urban agglomeration, investigates the effects of landscape patterns and their spatial spillovers, and provides a scientific basis for optimizing blue-green spatial configuration and improving ecological utilization efficiency. [Methods] This paper uses manual visual interpretation to delineate rectangular core built-up areas as the research sample, constructs a 1 km×1 km grid as the analysis unit, measures the cooling, air purification, water yield, carbon storage, soil retention, and habitat quality of the blue and green spaces in the core built-up areas using the InVEST model, and evaluates the ecological utilization efficiency of urban blue and green spaces using the Super-SBM model. Using the landscape pattern index analysis method, at the class level, core indicators such as the average shape index of green patches (G_SHAPE_MN), the average nearest neighbor distance of green patches (G_ENN_MN), the green patch aggregation degree (G_AI), the average shape index of water patches (W_SHAPE_MN), and the connectivity of water patches (W_COHESION) are selected to quantitatively depict the aggregation degree, shape complexity, connectivity, and fragmentation degree of the blue and green spaces across multiple dimensions, and to quantify the landscape pattern of the blue and green spaces. Socioeconomic and meteorological environmental control variables are introduced, and the spatial Durbin model is used to further explore the impact of the landscape pattern of blue and green spaces on their ecological utilization efficiency and spatial spillover effects. [Results] 1) hydrological regulation and habitat quality are the core ecological benefits of the blue and green spaces in the Yangtze River Delta, followed by carbon storage, cooling, and air purification benefits, with soil retention being the lowest. 2) There are differences in ecological utilization efficiency among different regions in the Yangtze River Delta, with scale efficiency higher than pure technical efficiency, and comprehensive efficiency being influenced by the joint effect of both types of efficiency. The comprehensive efficiency is mainly between 0.75 and 1.00, showing a north-south gradient, with lower values in the north and higher values in the south. 76.70% of the built-up area grids are at medium-to-low efficiency, mainly concentrated in the central region of the Yangtze River Delta; pure technical efficiency is also between 0.75 and 0.90, and scale efficiency is generally higher, ranging from 0.90 to 1.00. In 2020, the comprehensive ecological utilization efficiency and pure technical efficiency of the blue and green spaces in the built-up areas of the Yangtze River Delta urban agglomeration were mostly still at medium-low efficiency levels, while scale efficiency was relatively higher. 3) The mean values of the comprehensive efficiency, pure technical efficiency, and scale efficiency of the blue and green spaces vary among provinces and municipalities. Comprehensive efficiency: Jiangsu>Zhejiang>Anhui>Shanghai; Pure technical efficiency: Zhejiang> Anhui>Jiangsu>Shanghai; Scale efficiency: Shanghai>Jiangsu>Anhui>Zhejiang. 4) The landscape pattern factors of blue and green spaces have a negative impact on their ecological utilization efficiency, indicating that the more complex the shape of the blue and green spaces, the larger the average area of the patches, and the more aggregated they are, the lower their ecological utilization efficiency will be; from the perspective of efficiency decomposition, the landscape pattern factors have a stronger impact on pure technical efficiency than scale efficiency, and the effect of green landscape pattern is significantly greater than that of water bodies, playing a more dominant role in influencing the ecological utilization efficiency. 5) The spatial impact of the blue and green space landscape pattern on the ecological utilization efficiency has a spillover effect. The indirect effect of the green and water-body landscape pattern is generally greater than the direct effect. That is, both have a greater impact on the comprehensive ecological utilization efficiency, pure technical efficiency, and scale efficiency of the surrounding units than on the current unit itself. The spillover effect plays a key role in the regional blue and green space ecological utilization efficiency. Moreover, this spillover effect has a particularly prominent impact on scale efficiency, which is significantly greater than the impact on pure technical efficiency. 6) Compared with other factors, the average patch shape index of green patches (G_SHAPE_MN) has the greatest impact on the ecological utilization efficiency, and it also has a strong spillover effect. That is, the more complex the shape of the green patches, the stronger the hindering effect on the ecological service configuration and cross-unit collaborative utilization of the surrounding area. [Conclusion] Green space patch shape complexity is a key factor constraining the ecological utilization efficiency of blue-green spaces and has significant spatial spillover effects. Given the limited potential for further expansion of blue-green spaces in built-up areas and their relatively high scale efficiency, optimization should shift from area expansion to spatial configuration and refined management. While ensuring ecological quality, greater attention should be paid to the spatial relationships among patches and between patches and built-up areas, with the aim of developing a simpler and moderately dispersed spatial structure and appropriately reducing patch-shape complexity. Local landscape patterns and ecological functions should be strengthened, while regional coordination and cross-regional ecological networks should also be promoted to avoid excessive complexity, regional competition, and negative spillover effects. Scientifically optimizing the spatial configuration of blue-green spaces and improving the ecological utilization efficiency of green spaces and water bodies are important pathways to enhancing their quality and efficiency.

Key words: urban blue and green spaces, landscape patterns, ecological benefits, InVEST model, ecological efficiency, Yangtze River Delta urban agglomeration

摘要：

【目的】旨在研究与测度长三角城市群核心建成区蓝绿空间生态利用效率，探究蓝绿空间景观格局对其生态利用效率的影响及空间溢出效应，为优化城市蓝绿空间形态布局、提升生态利用效率提供科学依据。【方法】以长三角城市群为研究对象，采用InVEST模型测度核心建成区蓝绿空间的降温、空气净化、产水量、碳储存、土壤保持、生境质量等6项生态效益，通过Super-SBM模型测度与评价城市蓝绿空间的生态利用效率；从聚集度、形状复杂度、连接度和破碎度等维度量化蓝绿空间的景观格局；采用空间杜宾模型，分析蓝绿空间景观格局对其生态利用效率的影响与空间溢出效应。【结果】1）2020年长三角城市群核心建成区生态利用效率在0.75－0.90之间；规模效率高于纯技术效率。2）蓝绿空间景观格局因子对其生态利用效率具有负向影响，且对纯技术效率的影响强于规模效率，其中绿地景观格局的作用显著大于水体。3）绿地斑块形状复杂度对生态利用效率的影响最大，且具有较强的负向空间溢出效应。【结论】绿地斑块形状复杂度是制约蓝绿空间生态利用效率提升的重要因素，并具有空间溢出效应。在蓝绿空间增量有限、规模效率较高的背景下，应将优化重点由面积扩张转向形态布局优化与精细化管理，适度降低绿地斑块形状复杂度、强化本地生态功能，促进蓝绿空间生态利用效率提升。

关键词: 城市蓝绿空间, 景观格局, 生态效益, InVEST模型, 生态利用效率, 长三角城市群