Widespread recent ecosystem state shifts in high‐latitude peatlands of northeastern Canada and implications for carbon sequestration
Bibliographic record
Abstract
Northern peatlands are a major component of the global carbon (C) cycle. Widespread climate-driven ecohydrological changes in these ecosystems can have major consequences on their C sequestration function. Here, we synthesize plant macrofossil data from 33 surficial peat cores from different ecoclimatic regions, with high-resolution chronologies. The main objectives were to document recent ecosystem state shifts and explore their impact on C sequestration in high-latitude undisturbed peatlands of northeastern Canada. Our synthesis shows widespread recent ecosystem shifts in peatlands, such as transitions from oligotrophic fens to bogs and Sphagnum expansion, coinciding with climate warming which has also influenced C accumulation during the last ~100 years. The rapid shifts towards drier bog communities and an expansion of Sphagnum sect. Acutifolia after 1980 CE were most pronounced in the northern subarctic sites and are concurrent with summer warming in northeastern Canada. These results provide further evidence of a northward migration of Sphagnum-dominated peatlands in North America in response to climate change. The results also highlight differences in the timing of ecosystem shifts among peatlands and regions, reflecting internal peatland dynamics and varying responses of vegetation communities. Our study suggests that the recent rapid climate-driven shifts from oligotrophic fen to drier bog communities have promoted plant productivity and thus peat C accumulation. We highlight the importance of considering recent ecohydrological trajectories when modelling the potential contribution of peatlands to climate change. Our study suggests that, contrary to expectations, peat C sequestration could be promoted in high-latitude non-permafrost peatlands where wet sedge fens may transition to drier Sphagnum bog communities due to warmer and longer growing seasons.
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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 | 0.001 | 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".