Impacts of tillage practices on total, loose- and occluded-particulate, and humified organic carbon fractions in soils within a field in southern Ontario
Bibliographic record
Abstract
The effects of no-tillage (NT) and moldboard plowing (MP) on the distribution and storage of soil organic carbon (SOC) and different C fractions were determined along a transect on a private farm in southern Ontario, Canada, where a paired NT and MP strip traversing three soil series had been in existence for 19 yr. Soil samples were collected to a depth of 60 cm in seven increments. SOC was determined in each sample and for the top 30 cm, the organic carbon was fractionated into loose-, occluded-particulate organic matter (loose-POM and occluded-POM) and humified fraction (HF). After 19 yr, soils under NT contained significantly (P < 0.05) more SOC than soils under MP on both an equivalent depth basis and an equivalent mass basis. Greater concentrations of loose- and occluded-POM were found in NT than MP surface soils (0-10 cm). MP favored higher loose-POM contents than NT practices at a depth of 10-20 cm. The HF fraction accounted for most of the increase in SOC in the Huron and Brady soils, whereas the occluded POM accounted for more of the increase in the Fox soil. Our results indicate that the extent of SOC sequestration under NT is strongly dependent on soil type and cropping history. Key words: Tillage practices, soil organic carbon, C fraction, C sequestration
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".