Holocene vegetation dynamics and hydrological variability in forested peatlands of the Clay Belt, eastern Canada, reconstructed using a palaeoecological approach
Bibliographic record
Abstract
Forested peatlands are widespread in boreal regions of Canada, and these ecosystems, which are major terrestrial carbon sinks, are undergoing significant transformations linked to climate change, fires and human activities. This study targets millennial‐scale vegetation dynamics and related hydrological variability in forested peatlands of the Clay Belt south of James Bay, eastern Canada, using palaeoecological data. Changes in peatland vegetation communities were reconstructed using plant macrofossil analyses, and variations in water‐table depths were inferred using testate amoeba analyses. High‐resolution analyses of macroscopic charcoal >0.5 mm were used to reconstruct local fire history. Our data showed two successional pathways towards the development of present‐day forested peatlands influenced by autogenic processes such as vertical peat growth and related drying, and allogenic factors such as the occurrence of local fires. The oldest documented peatland initiated in a wet rich fen around 8000 cal. a BP shortly after land emergence and transformed into a drier forested bog rapidly after peat inception that persisted over millennia. In the second site, peat started to accumulate from ~5200 cal. a BP over a mesic coniferous forest that shifted into a wet forested peatland following a fire that partially consumed the organic layer ~4600 cal. a BP . The charcoal records show that fires rarely occurred in these peatlands, but they have favoured the process of forest paludification and influenced successional trajectories over millennia. The macrofossil data suggest that Picea mariana (black spruce) persisted on the peatlands throughout their development, although there were periods of more open canopy due to local fires in some cases. This study brings new understanding on the natural variability of boreal forested peatlands which may help predict their response to future changes in climate, fire regimes and anthropogenic disturbances.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".