Overwinter soil nitrogen dynamics in seasonally frozen soils
Bibliographic record
Abstract
An overwinter soil-monitoring study was conducted at two sites in southern Ontario. Soluble soil N accumulation at both sites occured in early winter, peaked when soil water was frozen, and then declined during the period that frozen soil water was present. The amount of soluble soil N accumulated was 48 ± 12 kg N ha−1 at one site, and 21 ± 6 kg N ha−1 at the other. In both cases, the overwinter accumulation approximately doubled the amount of soluble N in the soil. Similar trends were observed in both mineral and organic N, with 60 to 74% of the accumulation occurring in the organic form. No clear correlations between soluble nitrogen dynamics and soil extractable organic carbon or soil microbial biomass carbon dynamics were observed. Denitrification apparently occurred in shallow soil during the thaw period at one site. Since soil nitrate levels decreased before significant thawing occurred, leaching was probably not the primary dissipation mechanism. We hypothesize that the soluble N accumulation was due to death and lysis of soil microorganims during freezing and thawing. The presence of soil ice apparently decreased the lethality of the soil enviroment, allowing N dissipation to occur. Soil N dissipation could be due to gaseous losses, and is likely related to significant N2O fluxes commonly observed during spring thaw. Key words: Nitrogen, overwinter, soil ice
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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 | 0.001 | 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".