Natural fire frequency for the eastern Canadian boreal forest: consequences for sustainable forestry
Bibliographic record
Abstract
Given that fire is the most important disturbance of the boreal forest, climatically induced changes in fire frequency (i.e., area burnt per year) can have important consequences on the resulting forest mosaic age-class distribution and composition. Using archives and dendroecological data we reconstructed the fire frequency in four large sectors along a transect from eastern Ontario to central Quebec. Results showed a dramatic decrease in fire frequency that began in the mid-19th century and has been accentuated during the 20th century. Although all areas showed a similar temporal decrease in area burned, we observed a gradual increase in fire frequency from the west to Abitibi east, followed by a slight decrease in central Quebec. The global warming that has been occurring since the end of the Little Ice Age (~1850) may have created a climate less prone to large forest fires in the eastern boreal forest of North America. This interpretation is corroborated by predictions of a decrease in forest fires for that region of the boreal forest in the future. A longer fire cycle (i.e., the time needed to burn an area equivalent to the study area) has important consequences for sustainable forest management of the boreal forest of eastern Canada. When considering the important proportion of overmature and old-growth stands in the landscape resulting from the elongation of the fire cycles, it becomes difficult to justify clear-cutting practices over all the entire area as well as short rotations as a means to emulate natural disturbances. Alternative practices involving the uses of variable proportion of clear, partial, and selective cutting are discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 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".