Relative importance of overstory canopy openness and seedling density on crown morphology and growth of<i>Acer nipponicum</i>seedlings
Bibliographic record
Abstract
We investigated the effects of overstory canopy openness and seedling density on seedling morphology and growth in the mid-successional species Acer nipponicum Hara in a cool-temperate forest. Studied seedlings were 46 seedlings of 30–160 cm height, and their overstory canopy openness ranged between 7.2% and 17.0%. Seedling density, measured as the number of conspecific neighboring seedlings within a 50 cm radius of the target seedling, ranged between 0 and 19. There were no significant correlations between seedling height, canopy openness, and seedling density. Multiple regression analysis showed that crown depth, leaf mass fraction, and leaf area index decreased with decreasing canopy openness and increasing seedling density, while the ratio of trunk-lateral branches mass increased. Overstory canopy openness did not affect crown area, leaf size, or petiole length, all of which decreased with increasing seedling density. Standardized regression coefficients indicated that seedling density affected morphology and growth more than canopy openness did. The morphological responses to canopy openness cannot be considered as adaptive plasticity, as total leaf area and leaf mass fraction decreased with decreasing light levels. In contrast, responses to seedling density indicate adaptive responses to neighborhood competition. The results highlight the importance of seedling density that influenced seedling growth and morphology independently of overstory canopy openness.
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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) | 0.000 | 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".