Environmental controls of the northern distribution limit of yellow birch in eastern Canada
Bibliographic record
Abstract
To evaluate environmental controls of yellow birch (Betula alleghaniensis Britton) distribution at its northern distribution limit in eastern Canada, we analyzed abundance, age structure, biomass accumulation rate, and growth sensitivity to climate of this species at 14 sites along a 200 km latitudinal gradient spanning three bioclimatic domains and reaching frontier populations of this species in western Quebec. We observed a large variability in seedling density across domains and presence of sites with abundant yellow birch regeneration within all three bioclimatic domains. Seedling density was positively correlated to mean age and abundance of yellow birch trees in the canopy, while sapling density was positively associated with dryer habitats. Growth patterns of canopy trees showed no effect of declining temperatures along the south–north gradient. Environmental controls of birch distribution at its northern limit were realized through factors affecting birch regeneration and not growth of canopy trees. At the stand scale, regeneration density was strongly controlled by local site conditions and not by differences in climate among sites. At the regional scale, climate variability could be an indirect driver of yellow birch distribution, affecting disturbance rates and, subsequently, availability of suitable sites for regeneration.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".