Articles | Volume 23, issue 17
https://doi.org/10.5194/bg-23-6341-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-23-6341-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Dissolved organic carbon-mediated controls dominate soil carbon mineralization in response to freeze-thaw cycles
Jiaxin Yan
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang Key Laboratory of Agricultural Remote Sensing and Information Technology, Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, Zhejiang University, Hangzhou, 310012, China
Jinyang Zheng
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang Key Laboratory of Agricultural Remote Sensing and Information Technology, Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, Zhejiang University, Hangzhou, 310012, China
Shuai Zhang
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang Key Laboratory of Agricultural Remote Sensing and Information Technology, Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, Zhejiang University, Hangzhou, 310012, China
Mingming Wang
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang Key Laboratory of Agricultural Remote Sensing and Information Technology, Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, Zhejiang University, Hangzhou, 310012, China
Ting Sun
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang Key Laboratory of Agricultural Remote Sensing and Information Technology, Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, Zhejiang University, Hangzhou, 310012, China
Jiajun Mao
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang Key Laboratory of Agricultural Remote Sensing and Information Technology, Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, Zhejiang University, Hangzhou, 310012, China
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang Key Laboratory of Agricultural Remote Sensing and Information Technology, Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, Zhejiang University, Hangzhou, 310012, China
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We compiled a global dataset of soil carbon release rates from lab incubations across 721 soils and various temperatures. Many experiments did not reflect real-world conditions, especially for deeper soils and realistic temperature ranges. Simulation experiments showed that both carbon properties and environmental constraints equally drive temperature sensitivity. Current climate models miss these patterns, but our findings can help improve predictions of soil carbon responses to warming.
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A new dataset for topsoil bulk density (BD) and soil organic carbon (SOC) stock (0–20 cm) across Europe using machine learning was generated. The proposed approach performed better in BD prediction and slightly better in SOC stock prediction than earlier-published PTFs. The outcomes present a meaningful advancement in enhancing the accuracy of BD, and the resultant topsoil BD and SOC stock datasets across Europe enable more precise soil hydrological and biological modeling.
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Short summary
Freezing and thawing can speed soil carbon loss in cold regions, and climate change is altering how often these events occur. We incubated soils from different depths under freeze–thaw patterns and measured carbon dioxide release and dissolved carbon. Thaw bursts weakened with repeated cycles, yet higher frequency produced more total carbon loss. Dissolved carbon best predicted losses at all depths, while deeper soils relied more on enzymes and surface soils on organic matter protection.
Freezing and thawing can speed soil carbon loss in cold regions, and climate change is altering...
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