Relationship between canopy disturbance history and current sapling density of <i>Fagus grandifolia</i> and <i>Acer saccharum</i> in a northern hardwood landscape
Bibliographic record
Abstract
To shed light on the currently increasing proportion of Fagus grandifolia Ehrh. saplings in the tolerant hardwood forests of Quebec, we studied 48 Acer saccharum Marsh. dominated stands with contrasting histories of canopy disturbance: old commercial clear-cutting (CC), old fire (F), and either one or two partial cuts (1PC and 2PC). Our results indicated that higher densities of both F. grandifolia and A. saccharum saplings were associated with partial cutting histories (1PC and 2PC) than with severe canopy disturbance (CC and F). The density of F. grandifolia saplings was not related to any soil or stand characteristics in stands with a history of severe canopy disturbance. However, in stands with a history of partial canopy disturbances, the relative density of F. grandifolia saplings as compared with A. saccharum was related to soil C/N ratio and the presence of F. grandifolia overstory trees, whereas the absolute density showed a negative relationship with stand basal area. Therefore, it appears that partial canopy disturbances favored the regeneration of F. grandifolia relative to A. saccharum, whereas severe canopy disturbances may have provided an advantage to A. saccharum. We suggest that the presence of a light threshold can explain this shift in sapling performance between these two species.
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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) | 0.002 | 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".