Effect of long-term conventional tillage and no-tillage systems on soil and water quality at the field scale
Why this work is in the frame
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Bibliographic record
Abstract
No-tillage (NT) is becoming increasingly attractive to farmers because it clearly reduces soil erosion and production costs relative to conventional tillage (CT). However, the impacts of no-tillage on the quantity and quality of tile drainage water are less well known. Accordingly, two adjacent field scale on-farm CT and NT sites were established to compare the impacts of the two tillage systems on tile drainage and NO3-N loss in tile drainage water. The effect of the two tillage systems on soil structure, hydraulic conductivity, and earthworm population were also investigated. The total NO3-N loss in tile drainage water over the 5-yr period (1995-1999) was 82.3 kg N ha(-1) for the long-term NT site and 63.7 kg N ha(-1) for the long-term CT site. The long-term NT site had 48% more tile drainage (6,975 kL ha(-1)) than the long-term CT site (4,716 kL ha(-1)). The average flow weighted mean (FWM) NO3-N concentration in tile drainage water over the 5-yr period was 11.8 mg N L(-1) for the NT site and 13.5 mg N L(-1) for the CT site. For both tillage systems, approximately 80% of tile drainage and NO3-N loss in tile drainage water occurred during the November to April non-growing season. Long-term NT improved wet aggregate stability, increased near-surface hydraulic conductivity and increased both the number and mass of earthworms relative to long-term CT. The greater tile drainage and NO3-N loss under NT were attributed to an increase in continuous soil macropores, as implied by greater hydraulic conductivity and greater numbers of earthworms.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it