ABSTRACT The Qinghai‐Tibet Plateau (QTP), often referred as Earth's “Third Pole,” is warming nearly twice the global average, potentially amplifying carbon–climate feedbacks to a greater extent than in most other regions. However, substantial uncertainties remain regarding the magnitude, spatial distribution, and environmental controls of the region's soil organic carbon (SOC) stocks. Here we compiled a comprehensive dataset of 2442 soil profiles across the QTP and integrated it with high‐resolution (90 m) environmental covariates to generate spatially explicit, depth‐resolved SOC stock estimates using machine learning models. Independent validation using newly collected whole‐profile SOC measurements ( n = 53) demonstrated substantially improved predictive accuracy compared to existing global and regional mapping products (e.g., SoilGrids, HWSD, and WISE). Specifically, our estimates reached coefficients of determination ( R 2 ) of 0.63 and 0.49 for the 0–0.3 m topsoil and 0.3–1.0 m subsoil, respectively; while the existing mapping products only reached a R 2 of 0.01–0.35 in the topsoil and 0.01–0.15 in the subsoil. Across the QTP, our results estimated a total SOC stock of 62.0 (95% confidence interval: 54.9–69.1) Pg C within the top 2 m of soil, with more than 60% stored below 0.3 m depth. This value is much larger than most of the existing estimates in the same region. Alpine meadows ecosystems accounted for approximately 38% of the total SOC stock, primarily due to their extensive coverage, while swamp meadow ecosystems exhibited the highest SOC densities. Spatial uncertainty was highest in the sparsely sampled northwestern QTP. Contemporary climate and paleoclimate factors collectively contributed over 50% to the explained variance in SOC distribution across the soil profile, highlighting the dominant role of climatic factors on SOC spatial pattern. This spatially explicit, high‐resolution SOC mapping provides a baseline for constraining carbon–climate feedback assessments on the QTP and underscores the region's heightened vulnerability to ongoing climate warming.
Mao et al. (Sun,) studied this question.