Data from: An alternative approach to reduce algorithm-derived biases in monitoring soil organic carbon changes

Weixin Zhang, Yuanqi Chen, Leilei Shi, Xiaoli Wang, Yongwen Liu, Rong Mao, Xingquan Rao, Yongbiao Lin, Yuanhu Shao, Xiaobo Li, Cancan Zhao, Shengjie Liu, Shilong Piao, Weixing Zhu, Xiaoming Zou & Shenglei Fu
Quantifying soil organic carbon (SOC) changes is a fundamental issue in ecology and sustainable agriculture. However, the algorithm-derived biases in comparing SOC status have not been fully addressed. Although the methods based on equivalent soil mass (ESM) and mineral-matter mass (EMMM) reduced biases of the conventional methods based on equivalent soil volume (ESV), they face challenges in ensuring both data comparability and accuracy of SOC estimation due to unequal basis for comparison and using un-conserved...

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