Stratified Effects of Tillage and Crop Rotations on Soil Microbes in Carbon and Nitrogen Cycles at Different Soil Depths in Long-Term Corn, Soybean, and Wheat Cultivation
Bibliographic record
Abstract
Understanding the soil bacterial communities involved in carbon (C) and nitrogen (N) cycling can inform beneficial tillage and crop rotation practices for sustainability and crop production. This study evaluated soil bacterial diversity, compositional structure, and functions associated with C-N cycling at two soil depths (0–15 cm and 15–30 cm) under long-term tillage (conventional tillage [CT] and no-till [NT]) and crop rotation (monocultures of corn, soybean, and wheat and corn–soybean–wheat rotation) systems. The soil microbial communities were characterized by metabarcoding the 16S rRNA gene V4–V5 regions using Illumina MiSeq. The results showed that long-term NT reduced the soil bacterial diversity at 15–30 cm compared to CT, while no significant differences were found at 0–15 cm. The bacterial communities differed significantly at the two soil depths under NT but not under CT. Notably, over 70% of the tillage-responding KEGG orthologs (KOs) associated with C fixation (primarily in the reductive citric acid cycle) were more abundant under NT than under CT at both depths. The tillage practices significantly affected bacteria involved in biological nitrogen (N2) fixation at the 0–15 cm soil depth, as well as bacteria involved in denitrification at both soil depths. The crop type and rotation regimes had limited effects on bacterial diversity and structure but significantly affected specific C-N-cycling genes. For instance, three KOs associated with the Calvin–Benson cycle for C fixation and four KOs related to various N-cycling processes were more abundant in the soil of wheat than in that of corn or soybean. These findings indicate that the long-term tillage practices had a greater influence than crop rotation on the soil bacterial communities, particularly in the C- and N-cycling processes. Integrated management practices that consider the combined effects of tillage, crop rotation, and crop types on soil bacterial functional groups are essential for sustainable agriculture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".