Results_urban-fringe-rural.

The evolution of urban-fringe-rural structures profoundly impacts ecosystem services (ESs). However, the way in which trade-offs and synergies in ESs respond to changes in regional spatial structures has rarely been discussed. This knowledge gap hinders the development of spatially explicit strategies to mitigate ecological degradation while accommodating urban growth, ultimately perpetuating unsustainable landscape management practices characterized by reactive rather than preventive interventions. Such critical disconnect between structural dynamics and ES feedbacks has emerged as a major bottleneck to operationalizing landscape sustainability in metropolitan regions. This study selected Suzhou—a typical megacity in China—as an example to conduct an empirical study. The urban, urban fringe, and rural areas were firstly identified in 2010 and 2022 using Deep Neural Network (DNN) based on multi-source geographical data. Then, seven typical ESs were assessed using multiple models, and their interactions were examined through correlation analysis, coupling coordination degree model, and a self-organizing feature mapping network approach. At last, this study highlighted the complex responses of ESs relationships to dramatically changing spatial structure of urban-fringe-rural areas and proposed landscape management strategies. The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. The coupled coordination index among multiple ESs declines significantly in these areas, degrading from key coordination to key or mild trade-offs bundles. The results show ES interactions exhibit significant spatial variability under the evolution of metropolitan spatial structure, thus innovatively proposing integration of ESs synergies into urban-fringe-rural development framework to support overall landscape sustainability.

城乡交错带-乡村结构的演化对生态系统服务（ecosystem services，ESs）具有深远影响。然而，生态系统服务的权衡与协同效应如何响应区域空间结构变化这一问题，却鲜有探讨。这一认知缺口阻碍了兼顾城市增长与缓解生态退化的空间显式策略制定，最终使得以被动应对而非主动预防为特征的不可持续景观管理模式长期延续。结构动态与生态系统服务反馈之间的这种关键脱节，已成为大都市区推进景观可持续性落地的主要瓶颈。本研究选取中国典型特大城市苏州作为研究案例开展实证研究。首先基于多源地理数据，利用深度神经网络（Deep Neural Network，DNN）识别2010年与2022年的城市、城乡交错带与乡村区域；随后采用多模型评估7类典型生态系统服务，并通过相关性分析、耦合协调度模型以及自组织特征映射网络方法解析其交互关系。最后，本研究阐明了生态系统服务关系对城乡交错带-乡村空间结构剧烈变化的复杂响应，并提出了景观管理策略。研究结果如下：(1) 2010至2022年，苏州市城乡交错带-乡村空间结构发生显著变化，69.04%的乡村区域转化为城乡交错带区域，50.83%的交错带区域发展为城市区域；(2) 依据演化过程，研究区域进一步划分为城市维持区、城市扩张区、交错带维持区、交错带扩张区以及乡村留存区。多数生态系统服务的平均值沿城市-城乡交错带-乡村梯度呈现递增分布特征，而下降幅度最大的区域为交错带扩张区与城市扩张区；(3) 上述两类区域内生态系统服务对的交互关联更为紧密，且以协同效应为主导。多生态系统服务间的耦合协调指数在上述区域显著下降，从核心协调状态退化为核心权衡或轻度权衡的组合模式。研究结果表明，在大都市区空间结构演化过程中，生态系统服务交互作用呈现显著的空间异质性，因此本研究创新性地提出将生态系统服务协同效应纳入城乡交错带-乡村发展框架，以支撑全域景观可持续性。