Links between methanotroph community composition and CH<sub>4</sub>oxidation in a pine forest soil
Bibliographic record
Abstract
The main gap in our knowledge about what determines the rate of CH(4) oxidation in forest soils is the biology of the microorganisms involved, the identity of which remains unclear. In this study, we used stable-isotope probing (SIP) following (13)CH(4) incorporation into phospholipid fatty acids (PLFAs) and DNA/RNA, and sequencing of methane mono-oxygenase (pmoA) genes, to identify the influence of variation in community composition on CH(4) oxidation rates. The rates of (13)C incorporation into PLFAs differed between horizons, with low (13)C incorporation in the organic soil and relatively high (13)C incorporation into the two mineral horizons. The microbial community composition of the methanotrophs incorporating the (13)C label also differed between horizons, and statistical analyses suggested that the methanotroph community composition was a major cause of variation in CH(4) oxidation rates. Both PLFA and pmoA-based data indicated that CH(4) oxidizers in this soil belong to the uncultivated 'upland soil cluster alpha'. CH(4) oxidation potential exhibited the opposite pattern to (13)C incorporation, suggesting that CH(4) oxidation potential assays may correlate poorly with in situ oxidation rates. The DNA/RNA-SIP assay was not successful, most likely due to insufficient (13)C-incorporation into DNA/RNA. The limitations of the technique are briefly discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".