Effects of Short-term Tillage of a Long-term No-Till Land on Available N and P in Two Contrasting Soil Types
Bibliographic record
Abstract
The effects of short-term (4 years) tillage (hereafter called reverse tillage [RT]) of land previously under long-term (29 or 30 years) no-till (NT), with straw management (straw removed [SRem] and straw retained [SRet]) and N fertilizer rate (0, 50 and 100 kg N ha-1 in SRet, and 0 kg N ha-1 in SRem plots) were determined in autumn 2011 on ammonium-N, nitrate-N and extractable P in the 0-7.5, 7.5-15 and 15-20 cm soil layers at Breton (Gray Luvisol [Typic Cryoboralf] loam) and Ellerslie (Black Chernozem [Albic Argicryoll] loam), Alberta, Canada. There was no significant effect of RT and straw on ammonium-N, nitrate-N and extractable P in soil. Ammonium-N in soil increased significantly (but small) with N rate in many cases at both sites. Nitrate-N in soil increased with increasing N rate from 0 to 100 kg N ha-1 rate at Ellerslie, and up to 50 kg N ha-1 rate at Breton. Etractable P in soil decreased markedly with increasing N rate up to 100 kg N ha-1 at Breton and up to 50 kg N ha-1 at Ellerslie. In summary, increased N fertilizer rates were usually associated with decreased extractable P and increased nitrate-N in soil, but RT and straw had no effect on these nutrients in soil.
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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 | 0.001 |
| 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".