Long-term fire history of maple (<i>Acer</i>) forest sites in the central St. Lawrence Lowland, Quebec
Bibliographic record
Abstract
In the St-Lawrence lowlands, sugar maple (Acer saccharum Marsh.) is considered the dominant species of old-growth deciduous forests, whereas red maple (Acer rubrum L.) tends to dominate sites recently disturbed by logging and agricultural practices. Considering that the long-term influence of fire is not documented for such stands, we reconstructed the postglacial tree composition (as deduced from charcoal species) and fire history of a sugar maple stand (Ste-Françoise area) and a red maple stand (Villeroy area) located southwest of Québec City, Canada. The sites are 10 km apart and show contrasting soil and landform features. Using botanical identification and 14C dating of soil macrocharcoal, we found that fire struck both maple stands 14–20 times since deglaciation. Most fires occurred in the early Holocene and during the last 2000 years, with the mid Holocene being a period with low fire frequency or no fires. During the last 1600 years, the Villeroy stand shifted from a Tsuga canadensis (L.) Carrière – conifer forest to a mixed forest and, most recently, to a red maple stand as fire became more frequent, possibly due to human activities of the last 400 years. This study confirms the influence of fire on the development of maple forests. Fire should be considered as an important disturbance factor in the dynamics of temperate deciduous and mixed forests.
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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 | 0.001 |
| 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 | 0.001 | 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".