Methane-cycling communities in a permafrost-affected soil on Herschel Island, Western Canadian Arctic: active layer profiling of<i>mcrA</i>and<i>pmoA</i>genes
Bibliographic record
Abstract
In Arctic wet tundra, microbial controls on organic matter decomposition are likely to be altered as a result of climatic disruption. Here, we present a study on the activity, diversity and vertical distribution of methane-cycling microbial communities in the active layer of wet polygonal tundra on Herschel Island. We recorded potential methane production rates from 5 to 40 nmol h(-1) g(-1) wet soil at 10 °C and significantly higher methane oxidation rates reaching values of 6-10 μmol h(-1) g(-1) wet soil. Terminal restriction fragment length polymorphism (T-RFLP) and cloning analyses of mcrA and pmoA genes demonstrated that both communities were stratified along the active layer vertical profile. Similar to other wet Arctic tundra, the methanogenic community hosted hydrogenotrophic (Methanobacterium) as well as acetoclastic (Methanosarcina and Methanosaeta) members. A pronounced shift toward a dominance of acetoclastic methanogens was observed in deeper soil layers. In contrast to related circum-Arctic studies, the methane-oxidizing (methanotrophic) community on Herschel Island was dominated by members of the type II group (Methylocystis, Methylosinus, and a cluster related to Methylocapsa). The present study represents the first on methane-cycling communities in the Canadian Western Arctic, thus advancing our understanding of these communities in a changing Arctic.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".