Microbiome structure and functional potential in permafrost soils of the Western Canadian Arctic
Bibliographic record
Abstract
Substantial amounts of topsoil organic matter (OM) in Arctic Cryosols have been translocated by the process of cryoturbation into deeper soil horizons (cryoOM), reducing its decomposition. Recent Arctic warming deepens the Cryosols´ active layer, making more topsoil and cryoOM carbon accessible for microbial transformation. To quantify bacteria, archaea and selected microbial groups (methanogens - mcrA gene and diazotrophs - nifH gene) and to investigate bacterial and archaeal diversity, we collected 83 soil samples from four different soil horizons of three distinct tundra types located in Qikiqtaruk (Hershel Island, Western Canada). In general, the abundance of bacteria and diazotrophs decreased from topsoil to permafrost, but not for cryoOM. No such difference was observed for archaea and methanogens. CryoOM was enriched with oligotrophic (slow-growing microorganism) taxa capable of recalcitrant OM degradation. We found distinct microbial patterns in each tundra type: topsoil from wet-polygonal tundra had the lowest abundance of bacteria and diazotrophs, but the highest abundance of methanogens. Wet-polygonal tundra, therefore, represented a hotspot for methanogenesis. Oligotrophic and copiotrophic (fast-growing microorganism) genera of methanogens and diazotrophs were distinctly distributed in topsoil and cryoOM, resulting in different rates of nitrogen flux into these horizons affecting OM vulnerability and potential CO2 and CH4 release.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".