Predicting a ceiling for soil carbon sequestration on variable landscapes under no-till in eastern Canada
Bibliographic record
Abstract
Much of the crop production in eastern Canada occurs on landscapes where erosion/deposition has occurred. The potential to sequester C by reducing tillage will be greatest in those parts of landscapes where the organic carbon (OC) stocks are below a ceiling (OCc). However, the physical/biochemical basis for OCc is not understood and therefore it is difficult to predict where C sequestration will occur in landscapes with variable topography. In this research we tested two hypotheses proposed as the physical/biochemical basis for OCc: (1) OCc coincides with the steady state OC (OCss) stocks on non-eroded sites and (2) OCc coincides with a critical proportion of the capacity of the clay and silt fraction to absorb and retain OC (i.e., a critical saturation ratio). Comparison of data from sites with level and variable topography disproved the first hypothesis; OC stocks on level sites were, on average, 14 Mg ha-1 larger than OCc 15 yr after implementing no-till (NT) on variable landscapes. Further analyses of data from sites with variable topography indicated the saturation ratio in the surface 10 cm of soil must be less than 0.45 before NT results in C sequestration in the profile. Although the analyses are not incompatible with the second hypothesis, the critical saturation ratio is surprisingly small compared with values obtained from level sites. Additional tests of the second hypothesis are warranted on sites with variable topography in which C sequestration has been documented. Key words: Erosion, C capacity, saturation ratio, spatial variability, 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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".