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. 2023 Sep 28;11(10):2431.
doi: 10.3390/microorganisms11102431.

West-Siberian Chernozem: How Vegetation and Tillage Shape Its Bacteriobiome

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West-Siberian Chernozem: How Vegetation and Tillage Shape Its Bacteriobiome

Natalia Naumova et al. Microorganisms. .

Abstract

Managing soil biodiversity using reduced tillage is a popular approach, yet soil bacteriobiomes in the agroecosystems of Siberia has been scarcely studied, especially as they are related to tillage. We studied bacteriobiomes in Chernozem under natural steppe vegetation and cropped for wheat using conventional or no tillage in a long-term field trial in the Novosibirsk region, Russia, by using the sequence diversity of the V3/V4 region of 16S rRNA genes. Actinobacteria, Acidobacteria, and Proteobacteria summarily accounted for 80% of the total number of sequences, with Actinobacteria alone averaging 51%. The vegetation (natural vs. crop) and tillage (ploughed vs. no-till) affected the bacterial relative abundance at all taxonomic levels and many taxa, e.g., hundreds of OTUs. However, such changes did not translate into α-biodiversity changes, i.e., observed and potential OTUs' richness, Shannon, and Simpson, excepting the slightly higher evenness and equitability in the top 0-5 cm of the undisturbed soil. As for the β-biodiversity, substituting conventional ploughing with no tillage and maintaining the latter for 12 years notably shifted the soil bacteriobiome closer to the one in the undisturbed soil. This study, presenting the first inventory of soil bacteriobiomes under different tillage in the south of West Siberia, underscores the need to investigate the seasonality and longevity aspects of tillage, especially as they are related to crop production.

Keywords: 16S rRNA genes; conventional tillage; no tillage; soil bacteria; undisturbed steppe; wheat.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Principal component analysis (based on covariance) of the data matrix with soil samples as rows and bacterial phyla relative abundance as variables for analysis: location of soil samples in the plane of principal components 1 and 2 with convex hulls grouping either fields (a) or layers (b). Solid circles denote 0–5 cm layer, and open circles denote 5–15 cm layer.
Figure 2
Figure 2
Venns diagram of (a) the number of the dominant bacterial OTUs in soil under different tillage treatments with the number of common OTUs (OTUs were considered dominant if they accounted for ≥1% of the total number of sequence reads), and (b) of the total number of OTUs and the number of differentially abundant OTUs (at p ≤ 0.05 level, Fisher’s LSD test).
Figure 2
Figure 2
Venns diagram of (a) the number of the dominant bacterial OTUs in soil under different tillage treatments with the number of common OTUs (OTUs were considered dominant if they accounted for ≥1% of the total number of sequence reads), and (b) of the total number of OTUs and the number of differentially abundant OTUs (at p ≤ 0.05 level, Fisher’s LSD test).
Figure 3
Figure 3
Principal coordinates analysis of the soil bacteriobiome composition (genus level, Bray-Curtis dissimilarity distance) under different soil tillage management in the forest-steppe zone in West Siberia: location of samples in the plane of the first two coordinates. Symbols: solid circles denote 0–5 cm layer, open circles denote 5–15 cm layer.

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