Estimation de la production de bois mort dans les forêts préindustrielles de l'Est-du-Québec
Bibliographic record
Abstract
RÉSUMÉ: Le bois mort joue un rôle important dans le soutien de la biodiversité forestière. Par contre, les estimations de la production de bois mort en forêts naturelles sont rares autant au Québec qu’ailleurs dans le monde. L’objectif de cette étude est d’estimer les taux annuels de production de bois mort dans la forêt préindustrielle de l’Est-du-Québec en se basant sur l'inventaire forestier d’arbres vivants faits en 1930, avant les coupes industrielles. Étant donné que l'abondance des tiges diminuait avec l'augmentation du diamètre des arbres, nous avons estimé la quantité d’arbres morts produite par classe de diamètre à partir de la différence d’effectifs entre les classes successives de diamètre. Les taux de production de bois mort par unité de temps ont ensuite été estimés à l’aide de relations âge-diamètre par espèce. Le taux maximal de production de bois mort provenait des peuplements conifériens avec 1,8 arbre mort/ha/an. Le sapin baumier (Abies balsamea (L.) Mill.) était le plus important producteur de bois mort à travers tout le paysage forestier de 1930. Nos estimés sont basés sur plus de 7300 placettes d'inventaire ce qui leur confère une robustesse et une représentativité importante. Cependant, l’utilisation de taux de croissance linéaires surestime probablement la production de bois mort des gros arbres. \nEn tenant compte de ce biais, il est possible d’appliquer nos estimés de production de bois mort à la majorité de la forêt tempérée nordique du Québec. Ces résultats fourniront des informations utiles aux gestionnaires forestiers qui pourront faire un meilleur aménagement en tenant compte du bois mort. -- Mot(s) clé(s) en français : bois mort, vieille forêt, forêt préindustrielle, Québec, aménagement écosystémique, forêt tempérée, inventaire forestier historique, Abies balsamea. -- ABSTRACT: Dead wood plays an important role in supporting forest biodiversity. However, estimates of recruitment rate of dead wood in natural forests are rare both in Quebec and around the world. The objective of this study is to estimate the annual rate of dead wood input per hectare in the preindustrial temperate forests of eastern Quebec, based on a detailed inventory of standing living trees made between 1928 and 1930, prior to extensive logging. Since the abundance of stems decreased with increasing diameter of trees, we estimated the amount of dead wood produced by diameter class by subtracting stems densities between consecutive diameter classes. Recruitment rates of dead wood per unit of time were estimated by using an age-diameter relationship. The highest recruitment rate of dead wood was produced in coniferous stands with 1.8 dead trees/ha/year. Balsam fir (Abies balsamea (L.) Mill.) was the biggest producer of dead wood stems throughout the 1930 forest landscape. \nOur estimates are based on more than 7300 inventory plots that confer to them robustness and an important representativeness. However the use of linear growth rates probably overestimated the recruitment rates of dead wood among larger trees. Acknowledging this bias, it’s possible to apply our estimates of dead wood recruitment at the majority of the northern temperate forest of Quebec. These results will lead to silvicultural guidelines to help managers set dead wood targets. -- Mot(s) clé(s) en anglais : dead wood, old-growth forest, pre-industrial forest, Quebec, ecosystem-based management, temperate forest, historical forest inventory, Abies balsamea.
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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".