Spatio-temporal mapping reveals changes in soil organic carbon stocks across the contiguous United States since 1955

作者：Chenconghai Yang, Feixue Shen, Li Xiang, Wenkai Cui, Lei Zhang, Lin Yang, Chenghu Zhou · 发表于：Communications Earth & Environment · 年份：2025 · DOI：10.1038/s43247-025-02605-6 · 被引用次数：14 · 研究领域：Soil Geostatistics and Mapping、Soil Carbon and Nitrogen Dynamics、Atmospheric and Environmental Gas Dynamics

Understanding spatio-temporal patterns of soil organic carbon (SOC) is critical for global climate change mitigation and sustainable soil management. However, information on long term dynamics of SOC over large area is lacking. Supported by soil samples collected over years and environmental covariates, space and time digital soil mapping (ST-DSM) has become an important and effective method to reveal the spatio-temporal changes of SOC. The contiguous United States (CONUS) has abundant and well-documented soil samples with time labels, which lays the groundwork for us to estimate the long-term SOC dynamics in multiple soil layers over that region with high resolution. Specifically, we propose leveraging time-series soil data from World Soil Information Service (WoSIS) and International Soil Carbon Network (ISCN) to build ST-DSM models at different soil depths based on matching environmental covariates and machine learning techniques (random forest framework). Then, multi-depth ST-DSM models are employed to generate spatial prediction of SOC in different layers (0–15 cm, 15–30 cm, 30–60 cm and 60–100 cm) from 1955 to 2014 at 250 m resolution and 5-year intervals (1955–1959, 1960–1964,…., 2010–2014). Meanwhile, predictive uncertainties are quantified via Quantile Regression Forest (QRF). Furthermore, we analyze the dynamic trends in SOC stocks across various depths and land uses. The results indicate that over 60 years, overall SOC stocks in 0–100 cm demonstrate a multi-stage c...