Forest Fire-Conducive Drought Variability in the Southern Canadian Boreal Forest and Associated Climatology Inferred from Tree Rings
Bibliographic record
Abstract
Forest fires in Canada are directly influenced by the state of the climate system. The strong connection between climate and fire, along with the dynamic nature of the climate system, causes the extent, severity and frequency of fires to change over time. For instance, many reconstructions of the history of forest fires across boreal Canada report a general decrease in fire activity since ~1850 which could, in part, result from changes in climate. This paper describes progress in characterizing the variability in fire-conducive droughts in the central and eastern Canadian boreal forests during the past three centuries. An extensive network of drought-sensitive tree-ring records from Manitoba, Ontario and Quebec was used to develop five multi-century reconstructions of the mean July Canadian Drought Code and one reconstruction of mean July and August temperatures. Correlation analyses with regional fire statistics (common period 1959–1998) showed that drought estimates are accurate enough to approximate fire activity and, hence, the estimates are relevant for the study of climate change impacts on Canadian forests. Spatial correlation analysis over the period 1768–1998 revealed that variability between the west and east has increased since the mid–19th century, specifically the decade-to-decade variability and the frequency of extreme events. Based on the synoptic characteristics of recent droughts, we interpret this change in variability as a response to an increasing frequency of upper level ridging and troughing over western and eastern Canada, respectively. The increasing horizontal movement of humid air masses over eastern Canada since ~1850 could have contributed to the creation of moister conditions that are less suitable for fire.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".