Soil formation is a very slow and complex process involving the interaction of abiotic factors and biotic factors. Among them, biotic factors are regarded as the most active agents in soil formation. However, the traditional soil classification systems are mainly based on the data of soil physiological and chemical properties along soil profiles, lacking of the data of soil microbiology.

Isohumosols is a soil order nominated based on Chinese Soils Taxonomic Classification. It is roughly equal to Mollisols, and also commonly called as black soils. To reveal the correlations between microbial communities and soil classification, a research group led by WANG Guanghua from Northeast Institute of Geography and Agroecology, CAS, collected soil samples based on the diagnostic horizons from Ustic and Udic Isohumosols in agricultural soils across Heilongjiang Province of China. The abundances and communities of bacteria, archaea, and fungi were investigated using qPCR and high-throughput sequencing methods.

According to the researchers, the abundances of bacteria, archaea, and fungi consistently decreased by more than 90% in C horizon (parent material horizons) compared with those in Ah horizons (humus horizons). In addition, all soil microbial community structures were obviously divided into Ustic and Udic groups, and a distinct succession of microbial communities was detected from Ah horizon to C horizon at individual sites. They highlighted that the soil microbial communities in C horizons could better characterize the formation of the two suborders of Isohumosols.

More importantly, a machine learning approach is employed to establish random forest (RF) modeling, results indicated that soil microbial communities of diagnostic horizons can well be served as quantitative indices reflecting the two suborders of Isohumosols with more than 95% accuracy and more than 92% accuracy in different soil diagnostic horizons.

This study established a good relationship between soil microbial communities and soil classification, which provided a model for subsequent related research and a theoretical basis for understanding soil formation processes from the perspective of microbiology.

Contact

WANG Guanghua

Northeast Institute of Geography and Agroecology

E-mail: wanggh@iga.ac.cn

Reference

Liu ZX, Gu HD, Yao Q, Jiao F, Liu JJ, Jin J, Liu XB, Wang GH. Microbial communities in the diagnostic horizons of agricultural Isohumosols in northeast China reflect their soil classification. Catena, 2022, 216: 106430. https://doi.org/10.1016/j.catena.2022.106430.