Subsoiling and conversion to conservation tillage enriched nitrogen cycling bacterial communities in sandy soils under long-term maize monoculture
Bibliographic record
Abstract
Desertification degrades soil health and severely reduces crop productivity. Conventional tillage practices can amplify these problems in arid and semi-arid regions. For semi-arid regions in Inner Mongolia, China, the effects of introducing different tillage practices such as subsoiling (SS), straw mulching (SM), and no-tillage (NT) on otherwise long-term conventional tilled maize monoculture systems, were examined in the context of sandy soil bacterial and archaeal community diversity. Results showed that after three to four years of introduction, subsoiling and conversion to conservation tillage practices had no immediate effect on the alpha-diversity of the soil microbial communities. The beta-diversity of the soil microbial communities was less affected by the introduced tillage practices than by the growing season conditions, soil moisture, total nitrogen, soil macro-aggregate, and organic matter. Importantly, the introduced tillage practices had a notable effect on soil microbial communities associated with nitrogen (N) cycling processes, especially N fixation, nitrate reduction, nitrification, and denitrification. In particular, several years of tillage change from long-term conventional tillage enhanced the abundance of KEGG orthologs (KOs) associated with N fixation function involving species in Rhodoplanes, Nitrospira, Skermanella, and Rhizobium according to PICURSt prediction. Rhodoplanes spp. are involved in nitrate reduction and denitrification processes, and Nitrospira spp. associated with nitrite oxidization. We conclude that, for maize monoculture systems in semi-arid sandy soils, the soil bacterial and archaeal communities associated with many beneficial N cycling processes can be significantly impacted by only three to four years of introduced conservation and subsoiling tillage practices.
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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".