Data from: Positron-emitting radiotracers spatially resolve unexpected biogeochemical relationships linked with methane oxidation in Arctic soils
Bibliographic record
Abstract
Arctic soils are marked by cryoturbic features, which impact soil-atmosphere methane (CH4) dynamics vital to global climate regulation. Cryoturbic diapirism alters C/N chemistry within frost boils by introducing soluble organic carbon and nutrients, potentially influencing microbial CH4 oxidation. CH4 oxidation in soils, however, requires a spatio-temporal convergence of ecological factors to occur. Spatial delineation of microbial activity with respect to these key microbial and biogeochemical factors at relevant scales is experimentally challenging in inherently complex and heterogeneous natural soil matrices. This work aims to overcome this barrier by spatially linking microbial CH4 oxidation with C/N chemistry and metagenomic characteristics. This is achieved by using positron-emitting radiotracers to visualize millimeter-scale active CH4 uptake areas in Arctic soils with and without diapirism. X-ray absorption spectroscopic speciation of active and inactive areas shows CH4 uptake spatially associates with greater proportions of inorganic N in diapiric frost boils. Metagenomic analyses reveal Ralstonia pickettii associates with CH4 uptake across soils along with pertinent CH4 and inorganic N metabolism associated genes. This study highlights the critical relationship between CH4 and N cycles in Arctic soils, with potential implications for better understanding future climate. Furthermore, our experimental framework presents a novel, widely applicable strategy for unraveling ecological relationships underlying greenhouse gas dynamics under global change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".