Pine cones facilitate ignition of forest floor duff
Bibliographic record
Abstract
The ignition and combustion of forest floor duff are poorly understood yet have been linked to soil heating and overstory tree mortality in many temperate coniferous forests. Research to date has focused on the characteristics of duff that facilitate ignition and spread, including fuel moisture, mineral content, and depth. Field observations suggest that the presence of pine cones on and within the forest floor might facilitate ignition of intermixed forest floor fuels. We investigated the effect of cone fuel additions on the ignition of underlying forest floor from fuels collected in long-unburned longleaf pine (Pinus palustris Mill.) forests in northern Florida, USA. Fuels were wetted to threshold gravimetric moisture contents to evaluate the relative effect on ignition. In stark contrast to fuel beds without cones, in which duff ignition only occurred in 17% of samples, those with cones added ignited the underlying duff 94% of the time. Flame heights were 40% taller and flaming duration was 47% longer in fuel beds with cones. Where present, pine cones act as vectors of ignition for forest floor fuels, and their role in fires deserves more attention to enhance our understanding of forest floor combustion.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".