Effects of simulated spring thaw of permafrost from mineral cryosol on CO<sub>2</sub> emissions and atmospheric CH<sub>4</sub> uptake
Bibliographic record
Abstract
Abstract Previous studies investigating organic‐rich tundra have reported that increasing biodegradation of Arctic tundra soil organic carbon (SOC) under warming climate regimes will cause increasing CO2 and CH4 emissions. Organic‐poor, mineral cryosols, which comprise 87% of Arctic tundra, are not as well characterized. This study examined biogeochemical processes of 1 m long intact mineral cryosol cores (1–6% SOC) collected in the Canadian high Arctic. Vertical profiles of gaseous and aqueous chemistry and microbial composition were related to surface CO2 and CH4 fluxes during a simulated spring/summer thaw under light versus dark and in situ versus water saturated treatments. CO2 fluxes attained 0.8 ± 0.4 mmol CO2 m−2 h−1 for in situ treatments, of which 85 ± 11% was produced by aerobic SOC oxidation, consistent with field observations and metagenomic analyses indicating aerobic heterotrophs were the dominant phylotypes. The Q10 values of CO2 emissions ranged from 2 to 4 over the course of thawing. CH4 degassing occurred during initial thaw; however, all cores were CH4 sinks at atmospheric concentration CH4. Atmospheric CH4 uptake rates ranged from −126 ± 77 to −207 ± 7 nmol CH4 m−2 h−1 with CH4 consumed between 0 and 35 cm depth. Metagenomic and gas chemistry analyses revealed that high‐affinity Type II methanotrophic sequence abundance and activity were highest between 0 and 35 cm depth. Microbial sulfate reduction dominated the anaerobic processes, outcompeting methanogenesis for H2 and acetate. Fluxes, microbial community composition, and biogeochemical rates indicate that mineral cryosols of Axel Heiberg Island act as net CO2 sources and atmospheric CH4 sinks during summertime thaw under both in situ and water saturated states.
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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 | 0.000 | 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) | 0.001 | 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".