Contrasting methanotrophic communities between upland and polygonal tundra and their link to nitrogen metabolism and methane uptake in the Western Canadian Arctic
Bibliographic record
Abstract
ABSTRACT Atmospheric methane (CH 4 ) uptake by arctic soils is widespread in dry tundra ecosystems. However, the environmental controls regulating CH 4 uptake are poorly understood, particularly such as soil nutrient availability or microbial community composition. Here, we analyzed the relative abundance and community structure of functional gene markers associated with CH 4 and mineral nitrogen (N) cycling in two contrasting tundra types in the Western Canadian Arctic using a targeted metagenomics approach. Microbial data were compared to soil properties, macro- and micronutrient concentrations, and CH 4 fluxes during an entire growing season (May–August). We find that soil pH was the most important control on gene distribution between the studied microsites. Methanotrophs associated with the upland soil cluster α (USCα) dominated in polygonal tundra (low pH), while USCγ dominated in upland tundra (high pH). Methane uptake rates ranged from -15 to -27 μg CH 4 –C m -2 h -1 (growing season mean) and increased with higher relative abundances of USCα and USCγ. Although CH 4 uptake rates were similar between microsites, our microbial data indicate different mechanisms to cope with N limitation in these nutrient-limited tundra environments: upland tundra was characterized by genes involved in denitrification and N retention, while polygonal tundra contained genes associated with biological N fixation. Our study highlights the need for an integrated view on interactions between CH 4 oxidation and N availability for methanotrophs in arctic tundra soils.
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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) | 0.000 | 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 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".