Activity and diversity of methane-oxidizing bacteria along a Norwegian sub-Arctic glacier forefield
Bibliographic record
Abstract
Methane (CH4) is one of the most abundant greenhouse gases in the atmosphere and identification of its sources and sinks is crucial for the reliability of climate model outputs. Although CH4 production and consumption rates have been reported from a broad spectrum of environments, data obtained from glacier forefields are restricted to a few locations. We report the activities of methanotrophic communities and their diversity along a chronosequence in front of a sub-Arctic glacier using high-throughput sequencing and gas flux measurements. CH4 oxidation rates were measured in the field throughout the growing season during three sampling times at eight different sampling points in combination with laboratory incubation experiments. The overall results showed that the methanotrophic community had similar trends of increased CH4 consumption and increased abundance as a function of soil development and time of year. Sequencing results revealed that the methanotrophic community was dominated by a few OTUs and that a short-term increase in CH4 concentration, as performed in the field measurements, altered slightly the relative abundance of the OTUs.
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 | 0.001 |
| 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) | 0.001 | 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".