Bibliographic record
Abstract
Climate change is expected to alter the Arctic’s carbon (C) balance and changes in these C-rich ecosystems may contribute to a positive feedback on global climate change. Low-center mudboils, a form of patterned ground in the Arctic, are distinct landforms in which the exchange of greenhouse gases between the atmosphere and soil has not been fully characterized, but which may have an important influence on the overall C balance of tundra ecosystems. Chamber systems were used to sample net ecosystem exchange of CO2 (NEE) and CO2 and CH4 effluxes along a 35-m transect intersecting two mudboils in a wet sedge fen in Canada’s Southern Arctic (lat. 64°52′N, long. 111°34′W) during the summer months in 2008. Mudboil features gave rise to dramatic variations in vegetation, soil temperature and thaw depth, and soil organic matter content along this transect. Variations in NEE were driven by variations in the amount of vascular vegetation, while CO2 and CH4 effluxes were remarkably similar among the two mudboil (CO2 effluxes: 1.1 ± 0.9 and 1.4 ± 0.7 µmol m-2 s-1; CH4 effluxes: 83.1 ± 189.4 and 23.1 ± 9.4 nmol m-2 s-1, ± 1 standard deviation) and the sedge fen (CO2 effluxes: 1.6 ± 0.7 mol m-2 s-1 ; CH4 effluxes: 28.0 ± 62.0 nmol m-2 s-1) sampling areas. Vegetation appeared to play an important role in limiting temporal variations in CH4 effluxes through plant mediated transport in both mudboil and sedge fen sampling areas. One of the mudboils had negligible vascular plant colonization presumably due to more active frost heave processes. The relatively high CO2 and CH4 efflux in this mudboil area was speculated to be a result of growth and decomposition of cryptogamic organisms, inflow of dissolved organic C, and warmer soil temperatures. Key words: Patterned ground, nonsorted circle, tundra, net ecosystem exchange, methane, carbon dioxide
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".