Recent impact of fire on high-altitude balsam fir forests in south-central Quebec<sup>1</sup>This article is one of a selection of papers from the 7th International Conference on Disturbance Dynamics in Boreal Forests.
Bibliographic record
Abstract
The dynamics of high-altitude balsam fir ( Abies balsamea (L.) Mill.) forests is mainly driven by insect outbreaks and windthrows. However, very little work has been done on the role of fire on the development and maintenance of this ecosystem. In this study, we document the role of fire in the high-altitude balsam fir forests of the Réserve Faunique des Laurentides (RFL), southern Quebec. Sixteen sites were sampled among six different forest types described according to plant composition and fire evidence. At each site, the diameter structure was recorded and stand age was calculated based on tree-ring dating of individual trees and radiocarbon-dated surficial charcoal samples. Fire played a major role in the recent dynamics of high-altitude fir forests in the RFL. Over the last 250 years, nearly 50% of the study area burned during two fire conflagrations, i.e., around 1815 and in 1878. The fires triggered gradual changes in plant composition and forest structure, as shown by a succession of forest types ranging from white birch ( Betula papyrifera Marsh.) to spruce–fir types. Absence of surficial charcoal older than 300 years suggests that high-altitude forests of the RFL area were not subjected to a constant fire regime. It is possible that recent fires were caused by human activity.
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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) | 0.002 | 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".