Vegetation influence and environmental controls on greenhouse gas fluxes from a drained thermokarst lake in the western Canadian Arctic
Bibliographic record
Abstract
Abstract. Thermokarst features are widespread in ice-rich regions of the circumpolar Arctic. The rate of thermokarst lake formation and drainage is anticipated to accelerate as the climate warms. However, it is uncertain how these dynamic features impact the terrestrial Arctic carbon cycle. Methane (CH4) and carbon dioxide (CO2) fluxes were measured during peak growing season using eddy covariance and chambers at Illisarvik, a 0.16 km2 thermokarst lake basin that was experimentally drained in 1978 on Richards Island, Northwest Territories, Canada. Vegetation in the basin differs markedly from the surrounding dwarf-shrub tundra and included patches of tall shrubs, grasses, and sedges with some bare ground and a small pond in the centre. During the peak growing season, temperature and wind conditions were highly variable, and soil water content decreased steadily. Basin-scaled net ecosystem CO2 exchange (NEE) measured by eddy covariance was −1.5 [CI95 %±0.2] g C−CO2 m-2d-1; NEE followed a marked diurnal pattern with no day-to-day trend during the study period. Variations in half-hourly NEE were primarily controlled by photosynthetic photon flux density and influenced by vapour pressure deficit, volumetric water content, and the presence of shrubs within the flux tower footprint, which varied with wind direction. Net methane exchange (NME) was low (8.7 [CI95 %±0.4] mgCH4m-2d-1) and had little impact on the growing season carbon balance of the basin. NME displayed high spatial variability, and sedge areas in the basin were the strongest source of CH4 while upland areas outside the basin were a net sink. Soil moisture and temperature were the main environmental factors influencing NME. Presently, Illisarvik is a carbon sink during the peak growing season. However, these results suggest that rates of growing season CO2 and CH4 exchange rates may change as the basin's vegetation community continues to evolve.
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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".