Effect of Long-Term Agricultural Management on the Soil Microbiota Influenced by the Time of Soil Sampling - Fernandez Gnecco, Gabriela Amancay (2022)
Application of agrochemicals and mechanization enabled increasing agriculturalproductivity yet caused various environmental and soil health-related problems.Agricultural practices affect soil microorganisms, which are the key players of manyecosystem processes. However, less is known about whether this effect differs betweentime points. Therefore, soil was sampled in winter (without crop) and in summer (inthe presence of maize) from a long-term field experiment (LTE) in Bernburg (Germany)managed either under cultivator tillage (CT) or moldboard plow (MP) in combinationwith either intensive nitrogen (N)-fertilization and pesticides (Int) or extensive reducedN-fertilization without fungicides (Ext), respectively. High-throughput sequencing of 16SrRNA gene and fungal ITS2 amplicons showed that changes in the microbial communitycomposition were correlated to differences in soil chemical properties caused by tillagepractice. Microbial communities of soils sampled in winter differed only depending onthe tillage practice while, in summer, also a strong effect of the fertilization intensity wasobserved. A small proportion of microbial taxa was shared between soils from the twosampling times, suggesting the existence of a stable core microbiota at the LTE. Ingeneral, taxa associated with organic matter decomposition (such as Actinobacteria,Bacteroidetes, Rhizopus, and Exophiala) had a higher relative abundance under CT.Among the taxa with significant changes in relative abundances due to different long-termagricultural practices were putative pathogenic (e.g., Gibellulopsis and Gibberella) andbeneficial microbial genera (e.g., Chitinophagaceae, Ferruginibacter, and Minimedusa).In summary, this study suggests that the effects of long-term agricultural managementpractices on the soil microbiota are influenced by the soil sampling time, and this needsto be kept in mind in future studies for the interpretation of field data.