Contemporary Issues in Québec’s Temperate Forest — Part 1: Profile of the Forests
Bibliographic record
Abstract
We propose a series of papers presenting the main issues for Québec’s temperate forest arising from the multiplicity of rapid environmental and socioeconomic changes. This first paper presents a brief profile of Québec’s forests to establish a basis for the reflections presented in the remaining papers. Compilations show that the area dominated by deciduous species typical of the Northern temperate zone accounts for 8.8% of the province’s total forest, and that these species are also found mixed with coniferous species on 4.9% of the territory. The disturbances affecting these forests are generally more partial than severe. The most abundant species include shade-tolerant hardwoods such as sugar maple ( Acer saccharum Marsh., 152.4 Mm 3 ), red maple ( Acer rubrum L., 141.5 Mm 3 ), yellow birch ( Betula alleghaniensis Britt., 135.6 Mm 3 ) and American beech ( Fagus grandifolia Ehrh., 27.5 Mm 3 ). A demographic analysis shows that populations of the first 3 species have declined slightly in recent decades, whereas the American beech has tended to proliferate. Sugar maple and American beech are likely to become more abundant toward the northern boundary of their range, possibly due to climate change. However, beech bark disease may hinder the progression of the American beech in Québec.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".