The Hefei Metropolitan Circle is located at the geographical pivot of eastern China (30°57′–32°32′N, 116°41′–118°52′E) (Figure 2) (Dai et al., 2025; Fan et al., 2022). The region exhibits a composite geomorphic structure: the Jiang Huai Divide transects its eastern western axis, while the northern sector predominantly comprises the extended Huang Huai Plain. Centrally, undulating hills and interlaced valleys dominate, whereas the southern zone features an interdigitated distribution of riparian wetlands and low elevation foothills. Hydrologically, the area demonstrates characteristic dual basin dynamics, with the Yangtze and Huai Rivers constituting primary drainage arteries, supplemented by 18 major tributaries including the Chao Lake and Chu River systems. This geographic template engenders three distinct ecological gradients: an eastern riparian wetland corridor along the Yangtze, a central complex urban ecotone, and a western ecological barrier formed by the Dabie Mountain foothills. Collectively, they foster diverse natural ecosystems and anthropogenic environments, constituting a region of pivotal ecological significance. However, accelerated urbanization in recent years has imposed significant pressure on regional ecosystem stability through expanding urban footprints and intensified anthropogenic disturbances. This has triggered a marked increase in LER frequency across the region. As the primary economic growth hub in central China, the Hefei Metropolitan Circle now necessitates urgent investigation into the spatiotemporal dynamics of its ecological “resilience-risk” nexus. Targeted zoning governance strategies must be developed to advance regional high quality development and ecological civilization advancement.

The year 2010 marked the conclusion of China’s 11th Five Year Plan, 2015 was both the final year of the 12th Five Year Plan and a pivotal year for environmental legislation, while 2020 represented the end of the 13th Five Year Plan and the year of China’s carbon neutrality commitment. Therefore, selecting these 3 years for studying ecological resilience and ecological risks allows for capturing the entire process of China’s macro strategic transition from “growth-first” to “green development.” Accordingly, this study utilizes land use data and socioeconomic data from the three periods of 2010, 2015, and 2020. All remote sensing imagery underwent standardized preprocessing including image cropping, atmospheric correction, and geometric rectification prior to analysis. Detailed data sources are provided in Table 1.

To investigate the spatiotemporal evolution of ER and its subsystems within the Hefei Metropolitan Circle during 2010–2020, Figure 3 was constructed. This analysis reveals pronounced spatiotemporal heterogeneity in regional ER and its components. Regarding resistance, a “high-periphery, low-core” spatial pattern persisted throughout the study period, with over 93% of grid units consistently classified as medium-low or lower levels, indicating minimal temporal variation. Conversely, adaptability exhibited diametrically opposed characteristics, maintaining high performance across all timeframes; grids with medium-high or higher adaptability exceeded 57% in all three temporal dimensions. The spatial configuration of recovery closely mirrored that of resistance, yet demonstrated a persistent decline: the proportion of grids with medium-high or higher recovery decreased from 27.04% (2010) to 27.00% (2015) and 26.24% (2020), signaling a gradual but sustained deterioration. Spatially, ER hotspots predominantly clustered in the northern sector, while over 60% of the region remained below medium-high resilience thresholds. Temporally, Table 5 underscores a systematic transition in ER dynamics over the decade. Deconstructing resilience hierarchy reveals critical shifts: Low resilience zones displayed dual expansion a 6.7% net area increase (+0.67 percentage points in spatial coverage) evidencing intensified pressure from rapid urbanization on ecologically vulnerable areas. Medium-low resilience zones contracted by 1.97 percentage points yet maintained dominant coverage (60.67%), reflecting inherent regional ecological fragility. Medium-resilience zones registered concurrent growth in area (+5.5%) and spatial proportion (+1.21%). High-resilience zones suffered precipitous declines, with area plummeting by 50.6% and spatial share diminishing to 0.54%. These findings collectively demonstrate suboptimal regional ER levels, necessitating urgent spatially differentiated governance frameworks tailored to local contexts to enhance holistic ER.

To further investigate the spatiotemporal evolution of LER in the Hefei Metropolitan Circle (2010–2020), Figure 4 and Table 6 were developed. Key findings reveal divergent temporal trajectories across risk hierarchies: Low-risk areas experienced continuous contraction, decreasing from 1.3488 million hectares (21.26%) in 2010 to 1.2853 million hectares (20.26%) in 2020, indicating progressive encroachment on natural ecological baselines. Moderately low risk areas consistently dominated the landscape, with coverage increasing marginally from 68.70% to 69.53%, reflecting sustained stability in fundamental ecological conditions. Moderate risk areas exhibited minimal fluctuation, rising only 0.12 percentage points (4.63%–4.75%), suggesting localized ecological pressures remain manageable. Moderately high risk and high risk areas demonstrated counteracting trends: the former declined from 3.98% to 3.91%, while the latter increased from 1.43% to 1.55%, revealing heightened vulnerability in zones impacted by intensive anthropogenic activities. Spatially, low risk zones concentrated in the southwestern region with higher forest coverage, whereas high-risk areas clustered around water bodies. Overall, the ecological risk pattern demonstrated a “stable baseline with localized differentiation,” necessitating vigilance against the expansion of high risk zones and their potential threats to ER.

Figure 10 presents box plots illustrating the coupling coordination relationships between LER and ER (including its subsystems) in the Hefei Metropolitan Circle across multiple scales from 2010 to 2020. The results demonstrate that the mean coupling coordination degree between LER and ER remained below 0.5 at all scales, indicating a marginally coordinated state. Temporally, the coupling coordination across all three scales exhibited a slight downward trend, reflecting weakened synergies over the study period. Spatially, municipal-scale coupling coordination degrees showed outliers approaching zero, suggesting minimal regional heterogeneity, while the county scale exhibited the highest number of outliers, highlighting significant inter-county disparities. In contrast, grid-scale outliers were relatively smaller, emphasizing localized consistency in risk-resilience dynamics. These findings collectively indicate a persistent trade-off relationship between LER and ER in the Hefei Metropolitan Circle during the study period, where improvements in one metric often coincided with deteriorations in the other. This antagonistic interaction underscores the necessity for spatially differentiated governance strategies to address scale-specific ecological challenges.

Table 8 and Figure 11 present the spatial proportions and distribution of coupling coordination levels between LER and ER in the Hefei Metropolitan Circle across multiple scales from 2010 to 2020. The results reveal that, except for minor high-coupling-coordination areas at the municipal scale, county and grid scales exhibited predominantly low coordination levels. Spatially, the municipal scale was dominated by a “mildly uncoordinated” state, while “critically uncoordinated” states prevailed at county and grid scales. Temporal analysis highlighted significant divergence in coordination evolution across scales. At the municipal scale, the proportion of “extremely uncoordinated” areas remained unchanged at 18.08% over the decade, indicating persistent structural ecological challenges likely constrained by rigid macro-planning or systemic governance delays. A sudden surge in “severely uncoordinated” areas to 6.40% in 2015 (absent in other years) suggested potential transient ecological disturbances or data anomalies during this period. At the county scale, the proportion of “extremely uncoordinated” zones decreased from 2.25% to 0.82%, reflecting partial alleviation of high-risk pressures through localized governance. However, the “mildly uncoordinated” proportion rose from 14.45% to 18.97%, signaling enhanced diffusion of medium-low risks, potentially linked to marginal effects of land use transitions. The grid scale demonstrated a “polarized stabilization” pattern: the “critically uncoordinated” proportion increased from 48.04% to 51.75%, while the “marginally coordinated” proportion declined from 44.92% to 41.81%, revealing subtle degradation in small-scale coordination likely associated with ecological fragmentation driven by urban expansion. Additionally, the “primary coordination” level showed no significant improvement across scales, suggesting ER-building remains confined to passive adaptation. Overall, the multi-scale evolution of coupling coordination unveiled a “macro-rigidity, meso-improvement, micro-fluctuation” pattern, highlighting the urgent need for cross-scale collaborative governance mechanisms to address spatially heterogeneous challenges of risk transmission and resilience dissipation.

Under multi-scale perspectives, this study employed bivariate local Moran’s indices to delineate the spatial interactions between LER and ER (Figure 9). By further integrating coupling coordination analysis (Figure 11), the Hefei Metropolitan Circle was classified into distinct zoning units across three scales (Figure 12). Synthesizing multi-scale spatial interactions and coupling coordination relationships, the metropolitan circle was categorized into four zones: high-resilience zones, high-risk hotspots, risk-resilience uncoordinated zones, and risk-resilience coordinated zones.

From a coupling coordination perspective, only Lu’an City and Wuhu City exhibited coordinated risk-resilience relationships at the municipal scale, while all other counties remained uncoordinated. At the county scale, coordinated relationships were observed in Nanqiao District, Hanshan County, Fanchang District, and Nanling County, with Jinzhai, Huoshan, and Shucheng Counties representing high-resilience/low-risk coordination. In contrast, grid-scale analysis revealed sporadic coordination in the southwestern and fragmented peripheral areas. Overall, the metropolitan circle demonstrated poor coupling coordination between LER and resilience across all scales. Spatial clustering analysis highlighted strong spatial dependency and negative correlations, particularly at the grid scale. Low-resilience/high-risk zones predominantly clustered in waterbody-rich regions such as Chaohu City and Huoqiu County, whereas high-resilience/low-risk zones concentrated in forest-dominated southwestern counties (Jinzhai, Huoshan, Shucheng). Low-resilience/low-risk and high-resilience/high-risk zones exhibited fragmented spatial distributions. These findings underscore the necessity for spatially adaptive governance strategies to address scale-specific ecological challenges and enhance systemic resilience.

Our analysis reveals a significant shift in regional ER over the decade: low resilience zones expanded considerably (increasing by 17.3% coverage), while high resilience extremes contracted markedly (decreasing by 12.8% coverage) (Table 5). These shifts likely indicate heightened volatility in ecosystem resilience, suggesting progressive destabilization across specific dimensions. Crucially, this destabilization appears driven by cumulative effects of climate change, natural disasters, and intensified anthropogenic disturbances (Fan et al., 2024). As evidenced in Figure 3d3, the Hefei Metropolitan Circle exhibited a marked expansion of low resilience zones alongside a significant contraction of high resilience areas in 2020. This spatial restructuring is likely attributable to synergistic pressures from extreme precipitation events and accelerated urbanization. Notably, the entire region particularly the Chaohu Lake Basin experienced historically unprecedented persistent rainfall. Water levels in Chaohu Lake surged to an all-time high (13.43 m), sustaining prolonged exceedance above flood alert thresholds throughout the monitoring period. Figure 3 further reveals broad spatial convergence among the subsystems of ER, indicating strong coupling and synergistic interactions between these components (Liu et al., 2022). Consequently, policymakers must adopt integrated approaches for ecosystem management that account for all resilience subsystems. Focusing exclusively on isolated facets while neglecting systemic interdependencies risks compromising holistic resilience outcomes. Effective stewardship requires holistic and systematic strategies to safeguard and enhance the stability of ER.

Analysis of LER patterns revealed that moderate to low risk levels predominated across the Hefei Metropolitan Area over the decade-long study period (Table 6). Both risk categories exhibited marginal yet discernible increases, with high risk zones demonstrating a lower growth rate compared to their moderate to low counterparts. Spatially, low risk clusters were primarily concentrated in southwestern forested regions, whereas high risk areas coincided predominantly with water bodies. These spatial patterns broadly align with existing literature, providing robust evidence for regional risk dynamics. These patterns resonate with established regional observations. For instance, Li et al. documented pronounced spatial heterogeneity in LERs across Harbin over a 20-year period, identifying significant risk clustering proximal to water bodies (Li Y. et al., 2025). Similarly, scenario-based simulations by Ma et al. projected substantial expansion of high-risk zones in Hainan Island under multiple developmental trajectories (Ma et al., 2025). Collectively, these studies underscore the critical influence of hydrographic features on ecological risk agglomeration and validate the robustness of our analytical framework. This resilience may be attributed to targeted governance frameworks implemented by environmental authorities. Local authorities have executed sustained conservation initiatives across the Hefei Metropolitan Area over the past decade, with particular emphasis on the Chaohu Lake watershed. Notable interventions include the Ten Lakeside Wetlands Initiative launched in 2018 and the subsequent enactment of the Chaohu Wetlands Protection Statutes in 2019. Consequently, despite coinciding with China’s most rapid urbanization phase, ecological degradation has been effectively contained—demonstrating that strategic policy interventions can decouple economic expansion from environmental deterioration.

Analysis of subsystem correlations revealed that resilience exhibited the most pronounced negative association with LER. This robust inverse relationship likely stems from the acute sensitivity of resilience metrics to ecosystem stability and integrity where heightened risk directly compromises buffering capacities essential for recovery. The robust negative association between ER (particularly its recovery metrics) and LER underscores the imperative of integrating risk mitigation as a core pillar in environmental governance frameworks. Effective conservation planning requires context-specific interventions that both suppress risk propagation and enhance systemic buffering capacities. The significant negative correlation between ER (including its subsystems) and LER further underscores the critical importance of incorporating LER mitigation as a core consideration in environmental conservation planning. Effective strategies must prioritize the enhancement of ecological resilience through regionally tailored adaptive measures. Critically, our analysis reveals a progressive intensification of the negative correlation between ecological resilience and LER with increasing spatial resolution. This scale-dependent amplification likely stems from inherent scaling effects (Wang C. et al., 2025). Consequently, environmental managers must explicitly account for spatial heterogeneity across administrative and ecological scales when formulating conservation policies or interventions. This multi-scale perspective is fundamental to ensuring both the effectiveness and long-term sustainability of implemented strategies.

Our analysis reveals a notably lower incidence of high coupling coordination values at the grid scale compared to broader spatial extents (Table 8). This pattern likely arises from the finer spatial resolution of grid-scale analysis, which more accurately captures localized heterogeneity and process dynamics (Liu et al., 2023). At broader spatial scales, our results indicate consistently higher coordination levels between landscape ecological risk and ER. This pattern likely reflects the combined influence of spatial averaging effects and the enhanced holistic stability inherent to integrated eco-system functioning. Elevated coupling coordination signifies greater ecosystem stability, where landscape pattern changes exert minimal disruptive influence on regional ER a critical determinant of ecological equilibrium (Zhang M. et al., 2023). Conversely, observed declines in coordination and localized decoupling likely result from the complex interplay of anthropogenic pressures (including resource overexploitation and pollution), climate change impacts, and endogenous ecosystem dynamics. Consequently, we urge policymakers to prioritize evidence-based conservation in future territorial planning by: Safeguarding ecologically sensitive zones and reinforcing critical habitat corridors through integrated ecological networks; Scaling up biodiversity protection initiatives and implementing robust ecological compensation mechanisms to minimize anthropogenic disturbance; Establishing cross-sectoral governance frame works to synchronize landscape configuration with resilience enhancement. his integrated approach is paramount for reconciling development pressures with long-term ecological integrity.

Compared to existing studies that predominantly emphasize theoretical analysis, this research introduces innovations in both its theoretical framework and analytical methodology: Firstly, by constructing a multi-scale analytical framework, it systematically reveals the spatiotemporal coupling relationships between LER and ER (including its subsystems), deepening the understanding of dynamic interaction mechanisms and coordinated evolution patterns among these elements. Secondly, moving beyond traditional theoretical limitations, it integrates practical zoning management with theoretical analysis. Based on the spatial heterogeneity and coupling coordination relationships of “resilience-risk,” it identifies which resilience subsystems (resistance, adaptation, or recovery) serve as critical leverage points for regulating regional ecological security. Furthermore, it proposes a spatially adaptive ecological management zoning scheme, providing a scientific basis and implementation pathway for optimizing regional ecological security patterns.

However, this study still has certain limitations. Urban ecological risks originate from complex sources, and the current ecological resilience assessment model fails to cover all dimensions of resilience. A more comprehensive evaluation system should be introduced in future research. The evolution of LER and ER exhibits nonlinear, long-term, and non-stationary characteristics, making a 10-year study period insufficient to fully capture their dynamics. Subsequent research could extend the study period and expand the scale range. Furthermore, the interaction mechanisms between the two warrant deeper exploration, such as multi-scale driving mechanisms and the regulatory role of landscape pattern optimization on resilience. More sophisticated models (e.g., dynamic simulation, agent-based modeling) could be employed for quantitative analysis. Future studies could also strengthen the following aspects: enhancing the analysis of socioeconomic driving mechanisms (e.g., land markets, planning policies) to reveal the profound impacts of human activities on ecosystems; conducting international comparative studies with metropolitan areas such as the Yangtze River Delta and Pearl River Delta to identify commonalities and differences, thereby improving the generalizability of conclusions; and developing predictive policy scenarios, such as simulating trends in landscape ecological risks around Chaohu Lake under different urban expansion rates, to propose preemptive management recommendations.