Spatiotemporal dynamics and influencing factors of land carbon stock in Chengdu Plain using an integrated model

Understanding land carbon stock dynamics is essential for sustainable land use and ecological conservation amid rapid urbanisation. This study investigates how land use changes contribute to carbon sequestration, offering insights to support China's carbon peaking (2030) and carbon neutrality (2060) goals. Using high-resolution land use data (30 m) from 2000 to 2020 for the Chengdu Plain region, derived via Google Earth Engine and Random Forest classification, the Patch-generating Land Use Simulation (PLUS) model was applied to predict land use changes under four scenarios: natural development scenario (NDS), ecological protection scenario (EPS), cultivated land preservation scenario (CLDS), and economic development scenario (EDS) for 2030 and 2060. Carbon stock dynamics were quantified using the InVEST model, while the Optimised Parameter Geographical Detector (OPQD) model identified key drivers and their interactions. Between 2000 and 2020, cropland decreased by 4.14% while construction land increased by 4.15%, reflecting rapid urban expansion. Scenario simulations predict further cropland loss (2.80%-7.44%) and substantial construction land growth (26.89%-39.95%) by 2060, with forest and grassland recovery only under conservation scenarios. Carbon stock declined by 5.1%-5.5%, with the EPS and CLDS scenarios mitigating losses, while the NDS and EDS scenarios caused significant declines. Anthropogenic factors, such as urbanisation and economic growth, had a greater impact (> 15%) on carbon stock than natural factors (< 4%), with their interactions exhibiting nonlinear enhancement effects.This study underscores the benefits of conservation strategies and provides actionable insights for climate change mitigation, carbon trading, and sustainable urban planning. Further exploration of additional factors and predictive refinements will enhance regional ecological conservation efforts.