Spatiotemporal dynamics and driving mechanisms of carbon sequestration advantage across ecological zones: a case study from 2000 to 2023 in the Zhangjiakou–Chengde region, China

Traditional carbon sink assessments based on absolute values often fail to capture relative sequestration advantages across heterogeneous landscapes. Using the Zhangjiakou–Chengde region as a case study, this research estimated Net Ecosystem Productivity (NEP) from 2000 to 2023 and integrated it with the National Ecosystem Assessment and Ecological Security Database of China to construct relative carbon sequestration advantages (CSA) for three ecological zones: Zone A (Bashang Plateau farming–pastoral ecotone), Zone B (Yan Mountains forest zone), and Zone C (upper Yongding River agro–pastoral mosaic). Drivers were analyzed using Pearson correlation, GeoDetector, and Partial Least Squares Structural Equation Modeling (PLS-SEM). Results show that Zone A had low and unstable sinks, with over 40% exhibiting CSA variability above 50 g C/m 2 ·a, while Zone B maintained high CSA (multi-year mean 100 g C/m 2 ·a) but with strong interannual variability, suggesting high capacity yet weak stability. Zone C displayed clear improvement, with 35.3% of its area enhancing. Vegetation condition (NDVI, transpiration) and precipitation emerged as dominant positive drivers, whereas evapotranspiration, land use intensity, and sensible heat flux exerted localized negative effects, with climate and hydrology influencing CSA mainly through indirect vegetation–energy pathways. Projections indicate that Zone A faces mixed evolution (34.1% both improving and degrading), Zone B carries the highest degradation risk (34.4%), and Zone C shows the greatest improvement potential (35.3%). This study establishes a CSA framework that combines spatial pattern analysis with multi-method driver identification, offering practical insights for region-specific carbon sink governance in ecologically diverse regions.