Analysis of land use and carbon storage dynamics in the Panxi region, Southwest Sichuan, China: Spatiotemporal evolution and driving forces in multiple scenarios

Accurately assessing and predicting changes in terrestrial carbon storage (CS) is essential, especially given increasingly complex land use/land cover (LULC) patterns. Such efforts are crucial for China to achieve its dual goals of carbon peaking and carbon neutrality. As a key region within the national carbon strategy, the mountainous areas of Southwest China serve as important ecological barriers and major CS. In this study, we applied the PLUS, InVEST, and GeoDetector models to systematically analyze the spatiotemporal changes and driving mechanisms of LULC and CS in the ecologically sensitive Panxi region under multiple policy scenarios from 2000 to 2035. The results show: (1) From 2000 to 2020, CS in Panxi decreased by 4.25 × 10 6 t, mainly due to accelerated urbanization and construction land expansion, resulting in the loss of cultivated land and grassland, and worsening spatial imbalance in CS; (2) Scenario projections indicate that only the Ecological Protection Scenario (EPS) significantly increases regional CS, with gains of 0.17 × 10 6 t and 4.37 × 10 6 t in 2030 and 2035, respectively, highlighting the long-term benefits of ecological restoration measures; (3) NDVI (56 %), population (44 %), and altitude (37 %) are identified as the main driving factors, with the interaction between NDVI and population showing the strongest effect (q = 0.77). By integrating local policy considerations into scenario analysis, this study enhances the practical relevance of the modeling. These findings provide important guidance for optimizing regional land management, balancing ecological protection and economic development, and supporting China's dual carbon targets. • Integrated PLUS-InVEST-GeoDetector models simulate Panxi CS dynamics (2000–2035). • Urbanization led to a 4.25 × 10 6 t loss of carbon storage in Panxi during 2000–2020. • EPS boosts CS by 4.37 × 10 6 t by 2035, highlighting restoration benefits. • NDVI-population interaction (q = 0.77) is the strongest driver of regional CS variation.