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

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 reference systems. We introduce the basal mineral-matter reference systems (soils at time zero with natural porosity but no organic matter) and develop an approach based on equivalent mineral-matter volume (EMMV). To show the temporal bias, SOC change rates were re-calculated with the ESV method and modified methods that referenced to soils at time t1 (ESM, EMMM, EMMV-t1) or referenced to soils at time zero (EMMV-t0) using two datasets with contrasting SOC status. To show the s...