The influence of overstory trees and abiotic factors on the sapling community in an old-growth<i>Fagus-Acer</i>forest
Bibliographic record
Abstract
We examine the influence of overstory trees and abiotic environmental factors on the patterns of spatial variation and species composition in the sapling community of an old-growth Fagus-Acer forest in southwestern Québec, Canada. Our main focus was to identify differences in the sapling distribution patterns of Fagus grandifolia and Acer saccharum, the two codominant species in the overstory, as well as the factors that determine the differences. Using canonical correspondence analysis (CCA), we show that soil moisture has the strongest influence on the spatial variation and species composition of the sapling community. Acer saccharum occurred on a wide range of soil moisture conditions, while Fagus grandifolia saplings were absent in dry habitats. Another factor that differentiates the distribution patterns of Fagus grandifolia and Acer saccharum saplings is the relative dominance of Fagus grandifolia trees in the overstory, which correlates negatively with pH and Ca availability in the forest floor. Acer saccharum saplings were not found on sites where Fagus grandifolia trees dominate the overstory, while Fagus grandifolia saplings are mostly limited to sites where Fagus grandifolia trees have high representation in the overstory. These findings are discussed in light of previous hypotheses on canopy tree replacement patterns in Fagus-Acer forests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".