Urban−Rural Gradient Responses and Scale Effects of Trade-offs and Synergies Between Recreation and Habitat Services of Blue-Green Spaces in the Wuhan Metropolitan Area

Objective Recreation and habitat services are two core yet frequently conflicting ecosystem services provided by metropolitan blue-green spaces (BGS). Coordinating these two services is crucial for sustainable metropolitan development and high-quality human settlement construction. However, there is still a lack of systematic understanding of how the trade-off and synergy relationship between recreation and habitat services responds to urban-rural gradients and spatial scales, which seriously constrains the precise planning and management of BGS in metropolitan regions. Taking the Wuhan Metropolitan Area in central China, a rapidly urbanizing region with abundant blue-green resources, as a case study, this study integrates the dual perspectives of urban-rural gradients and spatial scales to systematically reveal the spatial heterogeneity and scale dependence of the trade-off and synergy relationship between recreation and habitat services. Specifically, the study aims to: 1) identify the nonlinear gradient responses of recreation and habitat services, as well as their quantitative trade-off and synergy relationship, across three urban hierarchies (core city, prefectural-level city, and county-level city); 2) clarify the scale dependence and critical scale thresholds of the spatial trade-off/synergy relationship between the two services; and 3) examine how spatial scale modulates the gradient response patterns of spatial trade-off and synergy relationships.

Methods An integrated “gradient-scale” analytical framework was developed by combining the maximum entropy (MaxEnt) model, the integrated valuation of ecosystem services and tradeoffs (InVEST) model, spatial autocorrelation analysis, and the generalized additive model (GAM). First, recreation service and habitat service were quantified separately. Recreation service was assessed using the MaxEnt model, with high-value recreational resource sites as sample points and a suite of environmental variables representing natural resource endowment and socioeconomic accessibility conditions. Habitat service was quantified using the Habitat Quality module of the InVEST model. Second, continuous urban-rural gradient sequences were constructed by generating 1-km interval buffers outward from the built-up boundaries of three hierarchical urban cores. Spearman’s rank correlation was then applied within each gradient buffer to identify the quantitative trade-off/synergy relationship between the two services. Third, a series of analytical grids ranging from 4 km² to 70 km² was established for multi-scale analysis, and global Moran’s I and bivariate Local Moran’s I were employed to characterize the spatial trade-off and synergy relationship at different scales. Finally, GAM was used to fit the nonlinear responses of service values, quantitative trade-off and synergy relationships, and spatial trade-off and synergy types along urban-rural gradients, identify critical gradient thresholds, and examine the cross-scale sensitivity and scale-modulating effects of gradient response curves.

Results 1) Recreation and habitat services exhibited distinct nonlinear gradient differentiation across urban hierarchies. Along all three urban-rural gradients, the gradient-distance thresholds at which habitat services began to recover or stabilize consistently lagged behind those of recreation services. The lag distances were 7.58 km, 7.74 km, and 2.89 km along the core-city, prefectural-level city, and county-level city gradients, respectively, corresponding to relative lag rates of 11.59%, 21.48%, and 34.45%. This indicates that, compared with recreation services, habitat services tend to respond more slowly and recover farther away from urban cores, and that such threshold-distance differences become increasingly pronounced at lower urban hierarchies. 2) The quantitative trade-off and synergy relationship between recreation and habitat services showed a consistent gradient pattern across hierarchies, shifting rapidly from trade-off to synergy with increasing urban-rural gradient distance. However, the critical threshold distances and the locations of the first synergy peaks differed substantially among urban hierarchies, suggesting that lower-tier cities can realize a quantitative win-win between recreation and habitat services within a more compact spatial range. 3) The spatial trade-off and synergy relationship between the two services exhibited pronounced scale dependence. The 30−50 km² interval was identified as a relatively stable scale range at which the spatial relationship was captured most clearly, whereas 50−60 km² emerged as the critical scale at which the dominant spatial relationship shifted from spatial synergy to spatial trade-off. As analytical scale increased, local spatial heterogeneity was progressively smoothed, and the area proportion of “high-high” synergy zones was especially sensitive to scale enlargement. 4) The response thresholds of spatial trade-off and synergy types and their transitions to urban-rural gradients were jointly regulated by spatial scale and urban hierarchy. With increasing spatial scale, the gradient thresholds associated with type transitions and relationship reversals generally moved toward urban centers, indicating that the spatial trade-off and synergy relationship is less stable in areas closer to urban cores. Moreover, the modulating effect of spatial scale on gradient response patterns was more pronounced in lower-tier cities, particularly in prefectural-level and county-level city systems.

Conclusion This study demonstrates that the trade-off and synergy relationship between recreation and habitat services in metropolitan BGS is not static, but varies systematically across urban-rural gradients and spatial scales. By identifying threshold distance differences between service responses, critical scale ranges for stable relationship recognition, and the scale-modulating effects on gradient response curves, the study deepens the understanding of multifunctional conflicts and coordination in metropolitan blue-green spaces. The findings provide a scientific basis for hierarchical and categorized planning, total amount regulation, spatial pattern optimization, and coordinated management of metropolitan BGS, and offer practical support for balancing recreation development and ecological conservation in rapidly urbanizing metropolitan regions. Future studies should further incorporate temporal dynamics, socioeconomic drivers, and multi-source behavioral data to test the broader applicability of these findings in other metropolitan contexts.