Soil microbial biomass and diversity respond to tillage and sulphur fertilizers
Bibliographic record
Abstract
There is little information on the effects of S management strategies on soil microorganisms under zero tillage systems o n the North American Prairies. Experiments were conducted to examine the effects of tillage and source and placement of S on soil microbial biomass (substrate induced respiration) and functional diversity (substrate utilization patterns) in a canola-wheat rotation under conventional and zero tillage systems at three sites in Gray Luvisolic and Black Chernozemic soils. Conventional tillage significantly reduced microbial biomass and diversity on an acidic and C-poor Luvisolic soil, but it had mostly no significant effects on the near-neutral, C-rich Luvisolic and Chernozemic soils, which underlines the importance of soil C in maintaining a healthy soil. Sulphur had no significant effects on soil microbial biomass, and its effects on microbial diversity were more frequent on the near-neutral Luvisol, which was more S-deficient, than on the acidic Luvisol or the Chernozem. Significant S effects on microbial diversity were observed both in the bulk soil (negative effects, compared with the control) and rhizosphere (positive effects) of the acidic Luvisol, but all significant effects (positive) were observed in root rhizospheres in the other soils. Sulphur by tillage interactions on acidic Luvisolic soil indicated that the negative effects of S in bulk soil occurred mostly under zero tillage, presumably because the fertilizer is concentrated in a smaller volume of soil than under conventional tillage. Sulphate S effects, either negative or positive, on microbial diversity were usually greater than elemental S effects. Therefore, S application can have direct, deleterious effects on soil microorganisms or indirect, beneficial effects through crop growth, the latter presumably due to increased root exudation in the rhizosphere of healthy crops. Key Words: Biolog, conservation tillage, microbial biodiversity, rhizosphere, soil biological quality, S fertilizer type and placement
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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 | 0.001 |
| 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) | 0.001 | 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".