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To achieve effective ecosystem management and conservation while promoting regional sustainable development, a quantitative assessment of ecosystem services (ESs) supply, demand, and driving mechanisms is essential. Taking the Central Plains urban agglomeration (CPUA) as the study area, we focused on the water-soil-food-carbon nexus (WSFC-Nexus) and quantified the supply and demand of four important ESs: water yield (WY), soil conservation (SC), food production (FP), and carbon sequestration (CS). Additionally, we analyzed the relationship characteristics and assessed the supply–demand matching situations of ESs. On this basis, we integrated various data discretization methods into geographic detectors to address subjective classification limitations, thereby enhancing the accuracy of exploring the ESs supply–demand balance (SDB) mechanisms. Our results indicated that WY and CS exhibited predominantly positive coupling in supply and demand, whereas SC and FP showed primarily negative coupling. Significant synergies were observed on the supply side in WY–FP, WY–CS, and SC–CS, while SC–FP showed a distinct trade-off. Conversely, WY–SC and FP–CS showed no significant correlation. On the demand side, strong synergistic relationships were evident in WY–FP, WY–CS, and FP–CS, while trade-offs were observed in WY–SC, SC–FP, and SC–CS. The supply–demand matching of ESs differed between locations. The northern areas predominantly concentrated deficits in WY, the western regions widely spread deficits in SC and FP, and urban areas primarily observed deficits in CS. The impact of interactions between factors on the SDB of ESs was more significant than that of individual factors. The interaction between precipitation and land-use dominated WY; vegetation and terrain interaction significantly affected SC; and the interaction between vegetation and population substantially impacted FP and CS. This study contributes to clarifying the underlying mechanisms that drive the SDB of ESs and provides a theoretical basis for urban resource management and allocation in CPUA.
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Fang et al. (2025) studied this question.
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