Distribution of organic carbon in the stable soil humic fractions as affected by tillage management
Bibliographic record
Abstract
Soil humus comprises a large and stable pool of soil organic matter (SOM); hence a better understanding of the fate of C in soil humic fractions can provide valuable information for the development of alternative tillage practices that will lead to long-term soil C sequestration. We used δ13C techniques to investigate the effects of tillage on the dynamics of native (C3–C) and corn derived C (C4–C) in fulvic acid (FA), humic acid (HA) and humin fractions. Humic substances were extracted from soils cropped to corn for 11 yr and managed under either conventional (CT) or no-tillage (NT), and from a conventionally tilled soil under > 55 yr of tobacco/rye rotation. No-tillage resulted in higher proportions of C4–C in the upper 5 cm and generally lower C4–C proportions below 5 cm than CT. Up to 31, 27 and 34% of C4–C were assimilated into FA, HA and humin fractions, respectively, indicating that even the humin fraction, often described as passive, old or resistant, acted as a sink of recently added C, and that it is heterogeneous with some of its components being young. Recovery of large proportions of C3–C in the humic fractions demonstrated their importance in the long-term stabilization of SOM. Within each sampling depth, there were no unique differences in the distribution of C3–C among the three humic fractions, suggesting similar turnover of C3–C in all the fractions. Therefore, there was no unique active fraction corresponding with the concept of C pools with defined turnover characteristics used in models of SOM turnover. Key words: Soil humic fractions, corn derived C, native C, δ13C techniques, tillage practices
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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 | 0.000 |
| 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".