Do methanotrophs drive phosphorus mineralization in soil ecosystem?
Bibliographic record
Abstract
Experiments were carried out to elucidate linkage between methane consumption and mineralization of phosphorous (P) from different P sources. The treatments were (i) no CH4 + no P amendment (absolute control), (ii) with CH4 + no P amendment (control), (iii) with CH4 + inorganic P as Ca3(PO4)2, and (iv) with CH4 + organic P as sodium phytate. P sources were added at 25 µg P·(g soil)−1. Soils were incubated to undergo three repeated CH4 feeding cycles, referred to as feeding cycle I, feeding cycle II, and feeding cycle III. CH4 consumption rate k (µg CH4 consumed·(g soil)−1·day−1) was 0.297 ± 0.028 in no P amendment control, 0.457 ± 0.016 in Ca3(PO4)2, and 0.627 ± 0.013 in sodium phytate. Rate k was stimulated by 2 to 6 times over CH4 feeding cycles and followed the trend of sodium phytate > Ca3(PO4)2 > no P amendment control. CH4 consumption stimulated P solubilization from Ca3(PO4)2 by a factor of 2.86. Acid phosphatase (µg paranitrophenol released·(g soil)−1·h−1) was higher in sodium phytate than the no P amendment control. Abundance of 16S rRNA and pmoA genes increased with CH4 consumption rates. The results of the study suggested that CH4 consumption drives mineralization of unavailable inorganic and organic P sources in the soil ecosystem.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".