Soil constitutes the largest carbon reservoir in terrestrial ecosystems. A substantial portion of stable soil carbon does not originate directly from plant residues but from microbial necromass, forming an "invisible microbial-derived carbon pool." Accurately quantifying this hidden pool is critical to understanding the long-term stabilization mechanisms of soil carbon and enhancing the reliability of global carbon cycle models. However, inconsistencies in analytical methods across studies have long impeded direct comparisons and constrained large-scale, cross-regional syntheses.

To address this challenge, a research team led by the South China Botanical Garden of the Chinese Academy of Sciences (CAS), in collaboration with the CAS Shenyang Institute of Applied Ecology and the University of Maryland, has conducted a systematic, comprehensive study comparing the two mainstream analytical methods for amino sugars—key biomarkers for tracing microbial necromass in soils. The work establishes a clear, quantitative framework for methodological comparison in this field.

Using 395 field soil samples from diverse climatic zones and ecosystems across North America, the team systematically evaluated the performance of gas chromatography (GC) and high-performance liquid chromatography (HPLC) in quantifying amino sugars. They further integrated over 1,900 published datasets worldwide for a large-scale meta-analysis.

The results revealed high overall consistency and a strong correlation between the two methods, indicating the feasibility of integrating existing datasets. However, in soils with higher organic carbon and total nitrogen content—where the soil matrix is more complex—GC exhibited greater analytical stability and statistical explanatory power, more accurately capturing the relationships between microbial necromass and soil carbon-nitrogen gradients. This advantage is largely attributed to the more rigorous purification steps in GC analysis, which effectively mitigate matrix interference.

The study emphasizes that neither method is universally superior; instead, each has distinct appropriate applications. GC offers higher chemical resolution and stronger resistance to matrix interference, making it more suitable for mechanistic studies, isotope tracing, and high-precision quantification. In contrast, HPLC features a simpler workflow, higher throughput, and lower cost, rendering it better suited for large-scale surveys and long-term ecological monitoring. The researchers noted that the key lies not in choosing one method over the other, but in selecting the appropriate approach based on research objectives and soil conditions.

By establishing a clear quantitative comparison and evaluation framework, the study enables the integration of global data on soil microbial necromass accumulated over the past few decades, laying a scientific foundation for data interoperability across studies.

The findings were recently published in Soil Biology and Biochemistry. The research was supported by the National Natural Science Foundation of China and other funding initiatives.