Consistent centennial‐scale change in European <scp>sub‐Arctic</scp> peatland vegetation toward <i>Sphagnum</i> dominance—Implications for carbon sink capacity
Bibliographic record
Abstract
Climate warming is leading to permafrost thaw in northern peatlands, and current predictions suggest that thawing will drive greater surface wetness and an increase in methane emissions. Hydrology largely drives peatland vegetation composition, which is a key element in peatland functioning and thus in carbon dynamics. These processes are expected to change. Peatland carbon accumulation is determined by the balance between plant production and peat decomposition. But both processes are expected to accelerate in northern peatlands due to warming, leading to uncertainty in future peatland carbon budgets. Here, we compile a dataset of vegetation changes and apparent carbon accumulation data reconstructed from 33 peat cores collected from 16 sub-arctic peatlands in Fennoscandia and European Russia. The data cover the past two millennia that has undergone prominent changes in climate and a notable increase in annual temperatures toward present times. We show a pattern where European sub-Arctic peatland microhabitats have undergone a habitat change where currently drier habitats dominated by Sphagnum mosses replaced wetter sedge-dominated vegetation and these new habitats have remained relatively stable over the recent decades. Our results suggest an alternative future pathway where sub-arctic peatlands may at least partly sustain dry vegetation and enhance the carbon sink capacity of northern 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".