Recent fire regime (1945–1998) in the boreal forest of western Québec
Bibliographic record
Abstract
:The forest fire regime was characterized for the boreal forest of western Québec using the provincial government’s digital databases (1945-1998). Lightning- and human-caused fires account for 71% and 29% of the total area burned, respectively. With regard to ignition sources, lightning was responsible for 38% of the fires while humans were the ignition agent for 62% of fires. The fire regime parameters (burn rate, fire occurrence, and size) were subjected to a stepwise regression analysis on the basis of regional landscape units. Models indicate that climatic factors, particularly summer precipitation and maximum temperatures, play a primary role in forest fire dynamics, regardless of the ignition source. Fire occurrence models were the most predictable with R2 values of 0.79 and 0.60 for lightning fires and human-caused fires, respectively. Models of burned areas reached an R2 value of 0.63 for lightning but only 0.22 for human-caused fires; on the other hand, the fire-size model for human-caused fires showed an R2 value of 0.57 but only 0.24 for lightning fires. In the case of human-induced fires, the density of the road network and sand deposits were important in fire occurrence and burned areas models. Once characterized, landscape units tend to group together naturally, forming extensive areas in which the fire regime is relatively homogeneous. The results of the regionalization based on lightning fire regimes are discussed from the standpoint of sustainable forest management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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".