Long-Term Dynamics and Driving Mechanisms of Forest Carbon Storage Under Ecological Restoration in Shaanxi Province, China

Understanding whether vegetation greening corresponds to changes in estimated forest carbon storage is important for evaluating ecological restoration under coupled climate change and human pressures. However, existing studies often rely on vegetation indices and have limited capacity to examine long-term forest carbon storage patterns or distinguish the roles of climatic and anthropogenic factors. This study integrates long-term remote sensing data with a two-way fixed effects model to examine forest ecosystem carbon storage in Shaanxi Province, China, from 1990 to 2023. Forest carbon storage was estimated by combining historical land-use data with static baseline carbon density coefficients derived from the 2012 field inventory, following an IPCC Tier 1-type approach. The carbon pools considered included aboveground biomass, belowground biomass, litter, and soil organic carbon. The results show that NDVI increased significantly, while estimated forest carbon storage increased by 4.27 × 107 t (21.04%), with evident regional heterogeneity. A mismatch was observed between vegetation greenness and estimated forest carbon storage, and NDVI showed weak and unstable associations with carbon storage after controlling for fixed effects. Nighttime light exhibited a significant negative association with carbon storage, whereas climatic factors were generally insignificant. These findings suggest that vegetation indices alone may not reliably represent land-use-based carbon storage estimates. This study provides empirical evidence for understanding forest carbon storage patterns under ecological restoration and highlights the need for dynamic carbon density parameters in future assessments.