Rapid urbanization is fragmenting ecological spaces in megacities, threatening biodiversity and ecosystem services. Yet, it remains unclear whether, and under what conditions, urban ecological networks (ENs) can recover robustness once heavily disrupted. This study aims to (i) develop a dynamic assessment framework that couples network robustness and connectivity, and (ii) apply it to examine how ENs evolve under sustained urbanization and shifting policy regimes. Using multi-period data for Shenzhen, China (2000–2025), we simulate deliberate and random attacks on patches and corridors to derive data-driven thresholds that grade the importance of ecological elements, and integrate these with graph-based connectivity metrics to track changes in network structure and node centrality over time. Shenzhen’s EN exhibits a typical “fragmentation–reconfiguration–optimization” pathway, with a “rapid decline–deceleration–recovery” trajectory in robustness that closely aligns with the introduction of strict ecological control lines and subsequent restoration initiatives. The results show that targeted protection of residual core habitats, combined with strategic reconnection and infill greening in the urban interior, can reverse earlier losses in network robustness. The proposed robustness-informed framework provides operational guidance for prioritizing protection, restoration, and optimization of ecological space, and offers a transferable approach for adaptive EN planning in high-density tropical and subtropical megacities.

Understanding spatial competition between retail formats is vital for sustaining urban commercial vitality. In China’s rapidly evolving urban economy, the contrast between light‑asset and capital‑intensive formats within traditional retail has been increasingly shaped by urban redevelopment and changing consumer behavior. However, prior studies largely confine themselves to linear assumptions, neglecting nonlinear dynamics and complex interdependencies. They also lack systematic comparisons between light-asset and capital-intensive formats, especially when attempting to integrate objective urban features with perceptual dimensions. This study investigates how objective urban environment indicators and human perception jointly shape the spatial density of two traditional retail formats, light‑asset (convenience stores) and capital‑intensive (large-scale supermarkets and shopping malls), in Shenzhen, China. Using multi‑source geospatial data and an integrated framework combining XGBoost, SHAP, Partial Dependence Plots (PDP), Interpretive Structural Modeling (ISM), and Bayesian Networks (BN), we quantify nonlinear effects, interaction patterns, and probabilistic association pathways. Results reveal distinct locational logics: light‑asset retail thrives through widespread penetration, responding strongly to competition intensity, service‑function proximity, and perceptual synergies; capital‑intensive retail concentrates in high‑yield hubs, driven by facility networks, accessibility, and high‑quality aesthetic environments above defined thresholds. Human perception emerges as a core determinant, accounting for up to 28.95% of explanatory importance, often exerting threshold‑dependent effects. The ISM–BN analysis uncovers multi‑entry vs. sequential pathways to spatial clustering across formats. Findings advance retail location theory by linking built‑environment metrics with street-level perceptual attributes, offering actionable guidance for urban planners to tailor format‑specific, perception‑oriented, and threshold‑sensitive strategies for sustainable retail ecosystems.

Integrating adaptive cycle theory with the Pressure–State–Response (PSR) framework, this study proposes a Risk–Connectivity–Potential (RCP) model to assess ecological spatial resilience in Shenzhen from 2000 to 2025—an area that underwent exceptionally rapid transformation into a megacity, a distinctive feature of this study. The results reveal a nonlinear trajectory of “decline–partial recovery–renewed decline–low-level endpoint”, with the mean RCP_i decreasing by 91.7%. Spatially, pressure risk expanded from built-up cores to urban fringes, connectivity shifted from peripheral patches to central hubs, and restoration potential declined at urban–ecological interfaces while improving locally. The overall decrease in resilience appears to be more closely linked to deteriorating connectivity and restoration capacity than to rising pressure risk alone. The coordination analysis further indicates a progressive worsening of ecosystem functional harmony over time. A differentiated management strategy is subsequently developed based on temporal trend, fluctuation, and component-specific diagnostic patterns. The theoretical contribution lies in establishing an explicit operational correspondence between the PSR framework and the RCP model, linking resilience theory with spatially measurable indicators. The practical contribution is a spatially differentiated assessment framework that identifies where resilience declined and whether the observed pattern was associated with pressure, connectivity, restoration potential, or imbalance among these dimensions.

This study focuses on the evolutionary characteristics and patterns of ecological spaces in rapidly urbanizing regions, using the Guangdong-Hong Kong-Macao greater bay area as a representative case. Employing cross-sectional data spanning 1985–2023, we systematically analyzed the hierarchical structure of ecological networks and the evolution of robustness. Key findings reveal: (1) a relatively stable proportion of ecological space (∼60%), with a slight increase in core ecological zones (+1.27% from 1985 to 2023), contrasting with a decline in the ecosystem service value of peripheral patches; (2) fluctuating increases in ecological network robustness; (3) under random attack strategies (undifferentiated node loss), resilience exhibited an evolutionary trajectory of initial fluctuation followed by stabilization; (4) under targeted attack strategies (centralized node encroachment), resilience showed a reverse pattern of initial stability followed by fluctuation. These patterns demonstrate the ‘expansion-adjustment-stabilization’ response mechanism of ecological spaces in rapidly urbanizing regions and reveal the ‘strategy dependence’ of ecological network resistance to disturbance.