The post-fire shift of temperate white pine-birch forest to boreal balsam fir forest in eastern Canada: climate-fire implications
Bibliographic record
Abstract
Extensive 14C dating and botanical identification of charcoal fragments located in the organic surface soil layer and buried in the mineral podzolic solum were used to reconstruct the successional pathways of a balsam fir forest site. The studied forest site developed in a context of continuous fire disturbance over the last 9000 years with at least 26 fires occurring at a mean interval of 330 years. Tree vegetation of the site followed a four-step trajectory consisting of an early-Holocene spruce forest and a late-Holocene mixedwood balsam fir forest. Boreal-like spruce-birch and temperate-like white pine-birch forests dominated the site between 7900 and 5900 cal. B.P. and 5600 and 1275 cal. B.P., respectively. Because all forest types developed repeatedly after fire since early deglaciation, changes in forest composition, in particular the shift of white pine forest to balsam fir forest, and concurrent decline of birch (yellow birch and/or paper birch) and pine populations were most likely related to progressive cooler and wetter conditions from mid- to late Holocene. Fire disturbance on this part of the southern boreal biome has been a continuous, positive regenerative process over the Holocene, allowing the successional turnover of boreal and temperate trees under the influence of climatic change.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".