Carbon loss in tile drainage and surface runoff from a clay loam soil after a half century of continuous and rotational cropping
Bibliographic record
Abstract
Tile drainage and surface runoff are major pathways for pollution of water resources by agricultural nutrients and chemicals. Little is known, however, of the pathways and amounts of carbon entry into water resources from agricultural land. This paper evaluates dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) losses in tile drainage and surface runoff from a Brookston clay loam after more than a half century of monoculture maize ( Zea mays L.), continuous bluegrass sod ( Poa Pratensis L.), and maize-oat ( Avena sativa L.)–alfalfa ( Medicago sativa L.)–alfalfa rotation. Water loss in tile drainage and surface runoff accounted for 27%, 32%, and 18% of annual precipitation (876 mm) for rotation, monoculture maize, and continuous sod, respectively. Tile drainage comprised 66%–89% of water loss from rotation and continuous sod, but only 15% from monoculture maize, with the remaining 85% of water loss from monoculture maize due to surface runoff. On an annualized basis, the measured dissolved C loss was 79 and 83 kg C ha–1 yr–1) from rotation and continuous sod, respectively, while 49 kg C ha–1 yr–1 was lost from monoculture maize. As up to 9% off-gassing loss of CO2 from water samples was measured, total dissolved carbon losses in tile drainage and runoff water were likely greater. For Brookston clay loam soil, leaching into tile drains was the dominant mechanism for dissolved carbon loss from long-term continuous sod and crop rotation, while surface runoff was the dominant mechanism for dissolved carbon loss from long-term monoculture maize.
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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 | 0.000 | 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".