Long‐term post‐fire changes in the northeastern boreal forest of Quebec
Bibliographic record
Abstract
Abstract. Natural dynamics in the boreal forest is influenced by disturbances. Fire recurrence affects community development and landscape diversity. Forest development was studied in the northeastern boreal forest of Quebec. The objective was to describe succession following fire and to assess the factors related to the changes in forest composition and structure. The study area is located in northeastern Quebec, 50 km north of Baie‐Comeau. We used the forest inventory data gathered by the Ministère des Ressources naturelles du Québec (MRNQ). In circular plots of 400 m2, the diameter at breast height (DBH) of all stems of tree species greater than 10 cm was recorded and in 40 m2 subplots, stems smaller than 10 cm were measured. A total of 380 plots were sampled in an area of 6000 km2. The fire history reconstruction was done based on historical maps, old aerial photographs and field sampling. A time‐since‐fire class, a deposit type, slope, slope aspect and altitude were attributed to each plot. Each plot was also described according to species richness and size structure characteristics. Traces of recent disturbance were also recorded in each plot. Changes in forest composition were described using ordination analyses (NMDS and CCA) and correlated with the explanatory variables. Two successional pathways were observed in the area and characterized by the early dominance of intolerant hardwood species or Picea mariana. With time elapsed since the last fire, composition converged towards either Picea mariana, Abies balsamea or a mixture of both species and the size structure of the coniferous dominated stands got more irregular. The environmental conditions varied between stands and explained part of the variability in composition. Their effect tended to decrease with increasing time elapsed since fire, as canopy composition was getting more similar. Gaps may be important to control forest dynamics in old successional communities.
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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) | 0.002 | 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".