Interpretation of Soil Carbon and Nitrogen Dynamics in Agricultural and Afforested Soils
Bibliographic record
Abstract
Interpretation of soil organic C (SOC) dynamics depends heavily on analytical methods and management systems studied. Comparison of data from long‐term corn ( Zea mays )‐plot soils in Eastern North America showed mean residence times (MRTs) of SOC determined by 14 C dating were 176 times those measured with 13 C abundance following a 30‐yr replacement of C 3 by C 4 plants on the same soils. However, MRTs of the two methods were related ( r 2 = 0.71). Field 13 C MRTs of SOC were also related ( R 2 = 0.55 to 0.85) to those measured by 13 CO 2 evolution and curve fitting during laboratory incubation. The strong relations, but different MRTs, were interpreted to mean that the three methods sampled different parts of a SOC continuum. The SOC of all parts of this continuum must be affected by the same controls on SOC dynamics for this to occur. Methods for site selection, plant biomass, soil sampling and analysis were tested on agricultural, afforested‐agriculture, and native forest sites to determine the controls on SOC dynamics. Soil‐C changes after afforestation were −0.07 to 0.55 Mg C ha −1 yr −1 on deciduous sites and −0.85 to 0.58 Mg C ha −1 yr −1 under conifers. Soil N changes under afforestation ranged from −0.1 to 0.025 Mg N ha −1 yr −1 Ecosystem N accumulation was −0.09 to 0.08 Mg N ha −1 yr −1 Soil C and N sequestration but not plant biomass were related to soil Ca, Mg, and K contents. Comparative, independent assays of long‐term plots provides information for concept testing and the confidence necessary for decision‐makers determining C‐cycle policies.
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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 | 0.000 | 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".