Recent peat and carbon accumulation on changing permafrost landforms along the Mackenzie River valley, Northwest Territories, Canada
Bibliographic record
Abstract
Abstract Northwestern Canada is currently warming nearly four times faster than the global average, driving accelerated permafrost thaw and changes to ecosystem vegetation, hydrology and landscape structure across the landscape. While permafrost peatlands constitute a large carbon reservoir, there is no consensus yet on the direction and magnitude of changes to their vulnerable carbon balance. Here, we assessed changes in peatland ecosystems following permafrost thaw at three sites located along a 1000 km long climate and permafrost gradient along the Mackenzie River valley, Canada. Specifically, we examined vegetation succession over the last few decades to evaluate the possible impact of climate warming on peat and carbon accumulation. Results from the palaeoecological analysis of 20 surficial peat cores, supported by robust chronologies, show a return to Sphagnum accumulation since ca. 1980 CE in the sporadic and discontinuous permafrost zones and ca. 2000 CE in the continuous permafrost zone. The average rates of peat and carbon accumulation reached 4 mm yr−1 and 134 g C m−2 yr−1 at the northernmost site in the continuous permafrost zone. In contrast, peat and carbon accumulation reached 3 mm yr−1 and 81 g C m−2 yr−1, respectively, in the sporadic and discontinuous permafrost zones. This study highlights the need for a net carbon budget that integrates the recent accelerated Sphagnum growth and carbon uptake from the atmosphere to better assess the potential carbon emissions offset following permafrost thaw. High-resolution palaeoecological studies can offer insights into decadal-scale patterns of vegetation and carbon balance changes to improve model predictions of peat climate-carbon cycle feedbacks.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".