Soil organic and inorganic carbon pools in the Loess Plateau: New estimation, change and trade-offs

Soil carbon pool accurate estimation is important for land use management and coping with future climate change. However, the size, distribution, and drivers of soil organic (SOC) and inorganic (SIC) carbon lack precise quantification regionally. We developed ensemble machine learning models to quantify SOC, SIC, and soil total carbon (STC) stocks across the Loess Plateau using a novel and spatially explicit dataset comprising 241 sites with paired SOC–SIC measurements in the 2 m soil profiles. The Loess Plateau’s soils stored 6.5 Pg C as SOC, 13.4 Pg C as SIC, and 19.9 Pg C as STC within the top 2 m, with 22 %, 16 %, and 18 % of these carbon pools distributed in the top 30 cm, respectively. Changes in SIC stocks are crucial for carbon accounting. Soil pH drives trade-offs between SOC and SIC, thereby playing a critical role in determining the contribution of SOC and SIC to net change in STC. Under future scenarios, soil acidification associated with climate change to terrestrial ecosystems will reduce Loess Plateau's STC (2 m) by 26–42 Tg C by 2100. Our study underscored the necessity of concurrently estimating changes in both SOC and SIC stocks to accurately assess soil carbon pool and formulated effective climate change mitigation strategies.