Identification of priority optimization areas and determination of optimal supply intervals for ecosystem services based on BBN and PPF-MRT

Urban fringe areas are the core zones where urbanization conflicts with ecological protection. Current optimization strategies often overlook the dynamic trade-offs and land-use specificity of ecosystem services (ES). Taking Henan Province as a case study, we first identified urban fringe areas using the Iso Cluster method. We then evaluated four ES—grain production (GP), carbon storage (CS), soil retention (SR), and water yield (WY)—using the InVEST model. On this basis, three key results were derived: (1) Prioritizing low-low cluster areas revealed that CS-SR and CS-WY clusters account for 21.6% and 26.2% of the total cluster area, making them optimization targets. (2) A Bayesian belief network (BBN) was combined with land-use scenarios to identify optimization zones for cropland and forest land. For example, in the cropland scenario, priority zones were concentrated in suburban and transitional areas. The CS-SR priority zone covered 1.73% of the total urban fringe area. In comparison, the CS-WY priority zone covered 10.23%. (3) Within the priority optimization areas, the PPF-MRT threshold methodology was developed, overcoming the limitations of traditional fixed-threshold approaches that cannot account for the multi-segmented and dynamic nature of threshold intervals. For example, in the cropland scenario, CS-WY exhibited multiple synergy intervals, with CS in the ranges of 442.76–451.03 t/ha and CS > 479.17 t/ha. This study presents a systematic framework for “spatial shortfall identification-land-use scenario optimization-dynamic threshold determination” in ecological governance of urban fringe areas. The framework offers practical guidance for the sustainable management of similar regions worldwide. • Prioritize ‘low-low’ ES clusters in urban fringes for targeted governance action. • Use VIF, correlations, and mechanisms to define causal paths in a Bayesian network. • Combine BBN with land-use scenarios to map priority areas for ES optimization. • Apply PPF-MRT in priority areas to define optimal ES supply intervals. • Establish an ‘identification-optimization’ planning framework for urban fringes.