Modeling the carbon landscape of Northwest China: from climatic controls to vegetation-driven hotspots

Abstract Background As a sensitive response area to global climate change, the terrestrial ecosystem carbon sink function of the Northwest Arid Region of China is not only a core element in constructing the regional ecological security barrier but also a crucial strategic fulcrum for China to achieve its dual carbon goals. However, the spatial distribution and driving factors of multiple carbon density types in this region remain unclear. The research provides a scientific basis for optimizing ecological barrier construction and formulating gradient-based carbon sink management strategies in arid regions. Methodology Five types of carbon density data—including aboveground and belowground biomass carbon, soil organic and inorganic carbon, and dead organic matter carbon—were obtained through literature review and field investigations. Environmental drivers were analyzed using generalized dissimilarity modeling (GDM) and structural equation modeling (SEM), and spatial simulations were performed using three machine learning models: random forest (RF), support vector regression (SVR), and extreme gradient boosting (XGBoost). Results Climatic and soil factors were the primary drivers of carbon density variation. Among the models, XGBoost demonstrated the best performance in simulating all five types of carbon density. Spatially, high carbon density values were mainly concentrated in mountainous and oasis areas, while low values were found in the southern desert regions. Vegetation cover and precipitation were identified as dominant regulating factors. Conclusions Forest ecosystems play a central role in regional carbon storage. The findings offer a scientific foundation for enhancing ecological barrier construction and developing gradient-based carbon sink management strategies in arid regions.