Soil microbial response to controlled-release urea under zero tillage and conventional tillage in western Canada
Bibliographic record
Abstract
Soil microorganisms mediate many important biological processes for sustainable agriculture. The effect of controlled-release urea (CRU), applied at recommended rates, on soil microbial communities was studied at six sites across western Canada from 2004 to 2006. Fertilizer treatments were CRU, regular urea and an unfertilized control. Wheat, canola and barley were grown in rotation at five sites, and silage corn was grown in all three years at one site, under conventional tillage (CT) or zero tillage (ZT). The fertilizers were side-banded at seeding time at 50-60 kg N ha-1 for wheat, barley and canola, and broadcast at 150 kg N ha-1 for corn. Microbial biomass C (MBC) and the functional diversity of soil bacteria were determined in crop rhizosphere and bulk soil. There were no fertilizer effects on MBC or bacterial diversity in 72-94% of the site-years. Where fertilizer had significant effects, they were usually positive effects relative to the control. CRU increased MBC or bacterial diversity more than urea in three site-years, but the reverse was observed in one site-year. Tillage had no significant effects on MBC or bacterial diversity in 78-94% of the site-years, and significant effects were usually in favour of ZT. Therefore, CRU applied at recommended rates probably does not have negative effects, and may even have positive effects, on soil biological processes.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".