Cutover peatlands: A persistent source of atmospheric CO<sub>2</sub>
Bibliographic record
Abstract
Peatlands represent an important component of the global carbon cycle, storing 23 g C m −2 yr −1 . Peatland mining eliminates the carbon sink function of the peatland. In this paper we measure the total ecosystem respiration in a natural, 2 and 3 year (young) and 7 and 8 year (old) postcutover peatland near Sainte‐Marguerite‐Marie, Québec, during the summers of 1998 and 1999. Although the natural site was a source of CO 2 during the dry 1998 study season (138 g C m −2 ), CO 2 emissions were between 260 and 290% higher in the cutover sites (363 and 399 g C m −2 for young and old, respectively). Cutover site CO 2 emissions were only 88 and 112 g CO 2 ‐C m −2 at the young and old sites during the wet 1999 study season. Total ecosystem respiration was more dependent on the water table position than on changes in the thermal regime or the labile carbon of the peat in a dry summer, but the opposite was the case in a wet summer. CO 2 emissions increased with postharvest time regardless of a decrease in labile carbon, demonstrating that cutover peatlands are a large persistent source of atmospheric CO 2 . Direct measurement of the net ecosystem CO 2 exchange in cutover peatlands, as opposed to determining the loss of carbon from bulk density determinations, provides a better understanding of how peat drainage and harvesting operations affect the carbon balance in peatlands.
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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 | 0.000 | 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) | 0.001 | 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".