Variation in fuel structure of boreal fens
Bibliographic record
Abstract
Wildfire frequency and severity in boreal peatlands can be limited by wet fuel conditions, but increases in burn severity can occur when lower water table positions cause drying of fuels. To date, most studies on northern peatland fires have focused on ombrotrophic bogs. Though minerotrophic fens are the most common type of peatland in North America, the influence of fuel structure and loading on potential fire behaviour in boreal fens is poorly understood. To investigate the potential for widespread flame front propagation across boreal fens, we quantified the fuel components present in three generalized boreal fen types (open, shrub, and treed fens) in northern Alberta, Canada. The loadings of aerial fuels, tall shrubs, and downed woody debris varied significantly among fen types. Fuel loads tended to be smallest in the open fens and largest in the treed fens. Open and shrub fens had larger loads of total surface fuels relative to treed fens, with short-statured shrubs being the dominant contributor to surface fuel load. Based on our observations of available fuel loads, each of the fen types may support moderate- to high-intensity fire following long-term drying, which may not only consume some fraction of the aboveground biomass, but also provide a substantial downward pulse of energy to initiate smouldering in the organic layer.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".