Soil <scp><scp>C</scp></scp> erosion and burial in cropland
Bibliographic record
Abstract
Abstract Erosion influences the lateral and vertical distribution of soil in agricultural landscapes. A better understanding of the effects of erosion and redistribution on soil organic carbon (C) within croplands would improve our knowledge of how management practices may affect global C dynamics. In this study, the vertical and lateral distribution of soil organic C was characterized to evaluate the amounts and timescales of soil organic C movement, deposition and burial over the last 50 years in different agroecosystems across Canada. There was strong evidence that a substantial portion of eroded sediment and soil organic C was deposited as colluvium close to its source area, thereby burying the original topsoil. The deepest aggraded profile was in a potato field and contained over 70 cm of deposited soil indicating an accumulation rate of 152 Mg ha yr−1; aggraded profiles in other sites had soil deposition rates of 40–90 Mg ha−1 yr−1. The largest stock of soil organic C was 463 Mg ha−1 (to 60 cm depth) and soil C deposition ranged from about 2 to 4 Mg ha−1 yr−1 across all sites. A distinct feature observed in the aggraded profiles at every site was the presence of a large increase in soil organic C concentration near the bottom of the A horizon; the concentration of this C was greater than that at the soil surface. Compared to aggraded profiles, the SOC concentration in eroded profiles did not differ with depth, suggesting that dynamic replacement of soil organic C had occurred in eroded soils. A large amount of soil organic C is buried in depositional areas of Canadian croplands; mineralization of this stock of C appears to have been constrained since burial, but it may be vulnerable to future loss by management practices, land use change and a warming climate.
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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 | 0.001 | 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) | 0.001 | 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".