A scalable model for methane consumption in arctic mineral soils
Bibliographic record
Abstract
Abstract Recent field studies have documented a surprisingly strong and consistent methane sink in arctic mineral soils, thought to be due to high‐affinity methanotrophy. However, the distinctive physiology of these methanotrophs is poorly represented in mechanistic methane models. We developed a new model, constrained by microcosm experiments, to simulate the activity of high‐affinity methanotrophs. The model was tested against soil core‐thawing experiments and field‐based measurements of methane fluxes and was compared to conventional mechanistic methane models. Our simulations show that high‐affinity methanotrophy can be an important component of the net methane flux from arctic mineral soils. Simulations without this process overestimate methane emissions. Furthermore, simulations of methane flux seasonality are improved by dynamic simulation of active microbial biomass. Because a large fraction of the Arctic is characterized by mineral soils, high‐affinity methanotrophy will likely have a strong effect on its net methane flux.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".