Old-growth forests in the temperate deciduous zone of Quebec: Identification and evaluation for conservation and research purposes
Bibliographic record
Abstract
The Quebec Department of Natural Resources (Ministère des ressources naturelles du Québec) is working to identify and protect old-growth forests in the deciduous forest zone of the province. A total of 88 sites was visited and a multivariate analysis of the main attributes of old growth allowed the development of quantitative definitions and criteria for identifying old-growth sugar maple (Acer saccharum), eastern hemlock (Tsuga canadensis), eastern white pine (Pinus strobus), eastern white-cedar (Thuja occidentalis), and red spruce (Picea rubens) stands. Life expectancy of various species according to environment was determined through a statistical analysis of 21 500 study trees taken from the province's forest inventory. Four different identification criteria for old-growth forests were developed that include a number of indicators for old growth. Along with advanced age of forest cover, the criteria that best reflected the nature of old-growth forests were the presence of large dead trees, low cutting intensity, and the importance of shade-tolerant species. Old-growth forests identified during this validation work occupy roughly 60 km 2 in Quebec's deciduous forest zone. Among other things, old-growth sugar maple stands of over 400 years old were discovered, containing stems with a diameter at breast height of 140 cm and a height of over 38 m. The very great potential of many of these exceptional forests for scientific research and biodiversity conservation is illustrated by the work carried out in the Boisé des Muir. Despite its small size, this sugar maple stand, which is over 300 years old, has advanced knowledge in fields as varied as forest dynamics, biodiversity, and climate studies, and has also served as a control site for various scientific studies. Key words: old-growth forests, definitions, criteria, indicators, inventory, Quebec, conservation, scientific value
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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 | 0.002 | 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".