Large Carbon Losses From Burned Permafrost Peatlands During Post‐Fire Succession
Bibliographic record
Abstract
Abstract The carbon (C) storage of boreal peatlands is threatened by an intensifying wildfire regime. Between 2019 and 2023 we used eddy covariance and surface closed chambers to monitor two permafrost peatlands in boreal western Canada that burned in 2019 and 2007. Deeper thaw, warmer soils, and slow vegetation recovery caused the 2019 Burn to be a net carbon dioxide (CO 2 ) source (+130 g C m −2 yr −1 ) for four years post‐fire, despite reduced soil respiration. The 2007 Burn was a sink (−11 g C m −2 yr −1 ) 13–15 years post‐fire, similar to undisturbed peatlands. We estimate that wildfire caused a loss (∼2.9 kg C m −2 ) from permafrost peatlands, with ∼1.7 kg C m −2 due to combustion and ∼1.2 kg C m −2 due to net CO 2 losses during post‐fire succession. This highlights the importance of the post‐fire CO 2 losses and emphasizes the vulnerability of permafrost peatland soil C to fire.
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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) | 0.001 | 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".