Race to the canopy: the development of tree size hierarchies following a partial disturbance in a boreal old-growth forest
Bibliographic record
Abstract
In boreal old-growth forests, advance regeneration typically attains canopy dominance through growth release events following partial disturbances. We sampled competing Picea mariana (Mill.) and Abies balsamea (L.) in disturbed old-growth stands in Quebec, Canada, to understand the intra- and interspecific size hierarchy development. We reconstructed tree size development and examined the role of initial size difference, time between germination and a disturbance, and the strength of response to the disturbance in determining tree size hierarchies. Trees that regenerated first generally dominated their intraspecific competitors also following a disturbance event. However, prolonged time between germination and disturbance resulted in a less deterministic outcome. Tree size difference prior to disturbance also influenced the development of size hierarchies. In interspecific competition between individuals of the same diameter, A. balsamea had a 61% probability of gaining dominance over P. mariana, the probability being 50% if P. mariana was 5 mm larger than A. balsamea. Dominant trees generally had the strongest response to the disturbance, reinforcing the existing size hierarchies. The largest trees typically gain dominance after a partial disturbance. However, interspecific competition is less predictable than intraspecific competition, small initial size difference, and prolonged time in suppression potentially changing tree size hierarchies.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".