Long-term dynamics of fire refuges in boreal mixedwood forests
Bibliographic record
Abstract
Burned areas in boreal mixedwood forests usually include tree patches that partially or entirely escaped fire. Some of these post-fire residual stands – called fire refuges – can escape several consecutive fires due to particular microsite conditions. Despite their potential importance as biodiversity hotspots, the long-term forest dynamics of fire refuges is unknown. High-resolution analysis of plant macroremains retrieved from forest organic matter profiles sampled in five fire refuges allowed us to describe up to 8000 years of forest dynamics. Our results display the importance of local conditions in forest dynamics. Wildfire was probably prevented by high moisture, as indicated by the presence of aquatic taxa and moisture-tolerant tree species. Lack of stand-replacing fire, coupled with organic matter accumulation, favored the millennial persistence of late-successional tree species. Shifts from spruce/larch dominance to fir/cedar dominance were noted at different occasions during the Holocene, probably resulting from endogenous processes.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".