An 8500-year history of climate-fire-vegetation interactions in the eastern maritime black spruce–moss bioclimatic domain, Québec, Canada
Bibliographic record
Abstract
The eastern, maritime portion of the black spruce – moss bioclimatic domain in Québec (Canada) is characterized by large wildfires with low occurrence. However, it is still poorly understood how climate–fire interactions influenced long-term vegetation dynamics in the boreal forest of eastern Québec. The long-term historical climate–fire–vegetation interactions in this region were investigated using a multiproxy (chironomids, charcoal, and pollen) paleoecological analysis of an 8500-year sediment core. Chironomid-inferred August air temperatures suggest that the warm Holocene Thermal Maximum (HTM; between ca. 7000–4000 cal yr BP) shifted to the cooler Neoglacial period (4000 cal yr BP to present), consistent with other temperature reconstructions across Québec. The shift to spruce-moss forest dominance around 4800 cal yr BP occurred nearly a thousand years before the climatic shift to the Neoglacial period and rather coincided with a shift from frequent low-severity small fires to infrequent but large and severe fire events. Our results suggest that long-term changes in the summer temperature are probably not the main factor controlling fire and vegetation dynamics in eastern Québec. It seems that, throughout the postglacial period, summer temperatures never fell below a threshold that could have induced a significant vegetation response.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".