Forest fuel structure and loading along a gradient of gray-phase mountain pine beetle severity in Jasper National Park, Alberta, Canada
Bibliographic record
Abstract
Wildland fire fuels within the gray-phase of mountain pine beetle ( Dendroctonus ponderosae Hopkins) outbreak (4–10 years post mortality) are treated as homogenous despite potential variability. To assess if proportion of mortality due to mountain pine beetle in gray-phase stands significantly affects fuel structure, composition, and loading, detailed fuel measurements were collected across a range of severity in Jasper National Park, Alberta, Canada, by coincidence 1–3 years before a major wildfire. These were categorized based on outbreak severity thresholds of Light (<35%), Moderate (36%–65%), and Severe (>65%) beetle-induced pine mortality defined as the proportion of killed trees within a stand. The canopy fuels of both mature and small tree cohorts were significantly reduced with increasing outbreak severity. Severely affected stands showed a 49% reduction in mature tree canopy bulk density from original loading but increased herbaceous vegetation. Moderately affected stands had higher coarse woody debris loading (mean = 3.21 kg m– 2; SE = 0.49 kg m–2). These severity ratings can be used to quantify canopy fuel loss and signal potential shifts to other surface fuel types, barring fire. This is one of the first studies to showcase variability within gray-phase outbreak fuels, despite their prevalence in western Canada, and discuss the potential influences on fire behaviour.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".