Impact of fire behavior on postfire forest development in a homogeneous boreal landscape
Bibliographic record
Abstract
Although behavior of stand-replacing wildfire has significant impacts on initial tree regeneration in the fire-prone boreal landscape, the unknown behavior of most past wildfires has precluded any evaluation of these impacts on the progressive development of late-successional forest ecosystems. In this study, the effects of fire behavior on long-term ecosystem development were evaluated by linking the banding pattern of tree density in a jack pine (Pinus banksiana Lamb.) - black spruce (Picea mariana (Mill.) BSP) forest on a flat and homogeneous landform in northern Quebec to a similar, previously documented pattern of unburned strips of tree crowns. Complex wildfire-atmosphere interactions during the spread of a 1941 stand-replacing wildfire created this pattern in stem density, most likely by differentially damaging the canopy-stored seed bank between areas of contrasting fire severity. Sites with initial differences in seedling densities have followed different recovery pathways and developed markedly different forest structures, as well as differences in species abundance. Compared with areas of severe crown fire, the present-day vegetation in areas of low crown fire severity shows a higher density of living pines in the canopy layer, higher spruce and dead pine densities in the subcanopy layer, a lower pine density in the understory layer, and a higher abundance of Cladina rangiferina (L.) and Cladina stellaris Opiz (Brodo) in the lichen mat. This close spatial connection between crown fire severity and the ecological processes driving ecosystem recovery may explain large differences in vegetation among sites in the boreal landscape.
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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".