Species interactions and distinct microbial communities in high Arctic permafrost affected cryosols are associated with the CH <sub>4</sub> and CO <sub>2</sub> gas fluxes
Bibliographic record
Abstract
Summary Microbial metabolism of the thawing organic carbon stores in permafrost results in a positive feedback loop of greenhouse gas emissions. CO 2 and CH 4 fluxes and the associated microbial communities in Arctic cryosols are important in predicting future warming potential of the Arctic. We demonstrate that topography had an impact on CH 4 and CO 2 flux at a high Arctic ice‐wedge polygon terrain site, with higher CO 2 emissions and lower CH 4 uptake at troughs compared to polygon interior soils. The pmoA sequencing suggested that USCα cluster of uncultured methanotrophs is likely responsible for observed methane sink. Community profiling revealed distinct assemblages across the terrain at different depths. Deeper soils contained higher abundances of Verrucomicrobia and Gemmatimonadetes , whereas the polygon interior had higher Acidobacteria and lower Betaproteobacteria and Deltaproteobacteria abundances. Genome sequencing of isolates from the terrain revealed presence of carbon cycling genes including ones involved in serine and ribulose monophosphate pathways. A novel hybrid network analysis identified key members that had positive and negative impacts on other species. Operational Taxonomic Units (OTUs) with numerous positive interactions corresponded to Proteobacteria , Candidatus Rokubacteria and Actinobacteria phyla, while Verrucomicrobia and Acidobacteria members had negative impacts on other species. Results indicate that topography and microbial interactions impact community composition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".