The Influence of Permafrost and Fire upon Carbon Accumulation in High Boreal Peatlands, Northwest Territories, Canada
Bibliographic record
Abstract
Carbon and peat accumulation rates over the past 1200 yr were measured in relation to permafrost aggradation, maturity, ground fires, and degradation in a peatland with discontinuous permafrost near Fort Simpson, N.W.T., Canada. The White River volcanic ash layer, deposited 1200 yr ago, was used as a chronostratigraphic marker to compare peat and carbon accumulation among peat cores collected along transects over a consistent period of time. The aggradation of permafrost results in a change from unfrozen bog to forested peat plateau, and approximate decreases of 50 and 65% in carbon and vertical peat accumulation rates, respectively. Carbon and peat accumulation continue to decrease significantly with both increasing permafrost maturity and the number of ground fires. The transition from peat plateau to collapse bog through internal permafrost degradation results in up to a 72 and 200% increase in carbon and vertical peat accumulation rates, respectively. Permafrost degradation at the margins of a peat plateau can result in the formation of collapse fens, in which vertical peat accumulation increases significantly yet the carbon accumulation rates remain similar to the peat plateau. A warming climate may result in a shift towards higher carbon accumulation rates in peatlands associated with bog vegetation following peat plateau collapse, yet warmer peat temperatures, greater soil aeration, greater rates of peat decomposition, and an increase in burning may provide limits to the increase.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".