Fire Regime along Latitudinal Gradients of Continuous to Discontinuous Coniferous Boreal Forests in Eastern Canada
Bibliographic record
Abstract
Fire is the main disturbance in North American coniferous boreal forests. In Northern Quebec, Canada, where forest management is not allowed, the landscape is gradually constituted of more opened lichen woodlands. Those forests are discontinuous and show a low regeneration potential resulting from the cumulative effects of harsh climatic conditions and very short fire intervals. In a climate change context, and because the forest industry is interested in opening new territories to forest management in the north, it is crucial to better understand how and why fire risk varies from the north to the south at the transition between the discontinuous and continuous boreal forest. We used time-since-fire (TSF) data from fire archives as well as a broad field campaign in Quebec’s coniferous boreal forests along four north-south transects in order to reconstruct the fire history of the past 150 to 300 years. We performed survival analyses in each transect in order to (1) determine if climate influences the fire risk along the latitudinal gradient; (2) fractionate the transects into different fire risk zones; and (3) quantify the fire cycle—defined as the time required to burn an area equivalent to the size of the study area—of each zone and compare its estimated value with current fire activity. Results suggest that drought conditions are moderately to highly responsible for the increasing fire risk from south to north in the three westernmost transects. No climate influence was observed in the last one, possibly because of its complex physical environment. Fire cycles are shortening from south to north, and from east to west. Limits between high and low fire risk zones are consistent with the limit between discontinuous and continuous forests, established based on recent fire activity. Compared to the last 40 years, fire cycles of the last 150–300 years are shorter. Our results suggest that as drought episodes are expected to become more frequent in the future, fire activity might increase significantly, possibly leading to greater openings within forests. However, if fire activity increases and yet remains within the range of variability of the last 150–300 years, the limit between open and closed forests should stay relatively stable.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".