Ecoregional Patterns of Spruce Budworm—Wildfire Interactions in Central Canada’s Forests
Bibliographic record
Abstract
Wildfires and outbreaks of the spruce budworm, Choristoneura fumiferana (Clem.), are the two dominant natural disturbances in Canada’s boreal forest. While both disturbances have specific impacts on forest ecosystems, it is increasingly recognized that their interactions also have the potential for non-linear behavior and long-lasting legacies on forest ecosystems’ structures and functions. Previously, we showed that, in central Canada, fires occurred with a disproportionately higher frequency during a ‘window of opportunity’ following spruce budworm defoliation. In this study, we use Ontario’s spatial databases for large fires and spruce budworm defoliation to locate where these two disturbances likely interacted. Classification tree and Random Forest procedures were then applied to find how spruce budworm defoliation history, climate, and forest conditions best predict the location of such budworm–fire interactions. Results indicate that such interactions likely occurred in areas geographically bound by hardwood content in the south, the prevalence of the three major spruce budworm host species (balsam fir, white spruce and black spruce) in the north, and climate moisture in the west. The occurrence of a spruce budworm–fire interaction inside these boundaries is related to the frequency of spruce budworm defoliation. These patterns provide a means of distinguishing regions where spruce budworm attacks are likely to increase fire risk.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".