The effect of a permafrost disturbance on growing-season carbon-dioxide fluxes in a high Arctic tundra ecosystem
Bibliographic record
Abstract
Abstract. Soil carbon stored in high-latitude permafrost landscapes is threatened by warming, and could contribute significant amounts of carbon to the atmosphere and hydrosphere as permafrost thaws. Permafrost disturbances, especially active layer detachments and retrogressive thaw slumps, have increased in frequency and magnitude across the Fosheim Peninsula, Ellesmere Island, Canada. To determine the effects of retrogressive thaw slumps on net ecosystem exchange (NEE) of CO2 in high Arctic tundra, we used two eddy covariance (EC) tower systems to simultaneously and continuously measure CO2 fluxes from a disturbed site and the surrounding undisturbed tundra. During the 32-day measurement period in the 2014 growing season the undisturbed tundra was a small net sink (NEE = −0.12 g C m−2 d−1); however, the disturbed terrain of the retrogressive thaw slump was a net source (NEE = +0.39 g C m−2 d−1). Over the measurement period, the undisturbed tundra sequestered 3.84 g C m−2, while the disturbed tundra released 12.48 g C m−2. Before full leaf out in early July, the undisturbed tundra was a small source of CO2, but shifted to a sink for the remainder of the sampling season (July), whereas the disturbed tundra remained a source of CO2 throughout the season. A static chamber system was also used to measure fluxes in the footprints of the two towers, in both disturbed and undisturbed tundra, and fluxes were partitioned into ecosystem respiration (Re) and gross primary production (GPP). Average GPP and Re found in disturbed tundra were smaller (+0.41 μmol m−2 s−1 and +0.50 μmol m−2 s−1, respectively) than those found in undisturbed tundra (+1.21 μmol m−2 s−1 and +1.00 μmol m−2 s−1, respectively). Our measurements indicated clearly that the permafrost disturbance changed the high Arctic tundra system from a sink to a source for CO2 during the growing season.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".