CommentA re-examination of the effects of fire suppression in the boreal forest
Bibliographic record
Abstract
A report by Ward and Tithecott (P.C. Ward and A.G. Tithecott. 1993. Ontario Ministry of Natural Resources, Aviation, Flood and Fire Management Branch, Publ. 305.) is frequently cited in the literature as providing evidence of the effects of fire suppression on the boreal forest. The study is based on 15 years of fire data and stand age data from Ontario, Canada. A re-examination of this report reveals serious flaws that invalidate the conclusions regarding effects of fire suppression on fire size and fire frequency. The fire-size data from the unprotected zone are censored in the small size classes because of detection resolution, invalidating comparisons of shapes of the distributions between the protected and unprotected zones. Use of different plotting scales gives the false appearance of large differences in the number of large fires between the two zones. Stand age data are used to show a change in fire frequency in the 20th century, and this change is attributed to fire suppression. However, no evidence is presented to conclude that this change in fire frequency is attributable to fire suppression and not to climate change. The estimate of the current fire cycle is based on too short a record to give a reliable estimate given the variation in annual area burned. Therefore, this report does not present sound evidence of fire suppression effects and should not be cited as such.
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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".