<i>Corrigendum to</i> : Regional drought synchronised historical fires in dry forests of the Montane Cordillera Ecozone, Canada
Bibliographic record
Abstract
Understanding climate as a driver of low- to moderate-severity fires in the Montane Cordillera Ecozone of Canada is a priority given predicted and observed increases in frequency and severity of large fires due to climate change. We characterised historical fire-climate associations using 14 crossdated fire-scar records and tree-ring proxy reconstructions of summer drought and annual precipitation from the region. We compared fire-climate associations among years when fires burned in multiple study areas. From 1746 to 1945, there were 32 years with moderate fire synchrony in which four to six study areas recorded fire. During four high fire synchrony years, 7 to 10 study areas recorded fire. Below-average annual precipitation and summer drought synchronised fires, whereas infrequent years of high fire synchrony were preceded by a wet summer. After 1945, decreased fire occurrence and synchrony reflects fire exclusion, suppression and climatic variation. Global climate change manifests as blocking high-pressure ridges that superimpose on longer fire-seasons and increased droughts. Combined, they make dry forests increasingly susceptible to synchronous fires, which are difficult to suppress as observed during the record-breaking 2017, 2018 and 2021 fire seasons in British Columbia.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.076 | 0.016 |
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".