Effects of canopy heterogeneity on the sapling bank dynamics of a subalpine old-growth forest, central Japan
Bibliographic record
Abstract
Sapling bank dynamics under different canopy conditions were examined in 1997-1999 in a subalpine old-growth forest of the northern Yatsugatake Mountains, central Japan. Three 5 m × 5 m quadrats established each under different canopy conditions (evergreen coniferous canopy, deciduous broad-leaved canopy and canopy gap) within the forest revealed that conifer saplings (height > 15 cm tall but dbh < 5 cm) recruited in all quadrats under evergreen canopies and in some quadrats under deciduous canopies, but they did not recruit in other quadrats under deciduous canopies and in all quadrats under canopy gaps. The mortality rates of saplings were low in all size classes under evergreen canopies. On the other hand, smaller saplings died to a greater extent in canopy gaps because of size dependent mortality. Under deciduous canopies, patterns of sapling mortality varied with quadrats. Size distribution of saplings under different canopy conditions was maintained by recruitment, mortality and competitive pattern. Thus, canopy conditions may affect sapling recruitment, mortality and competitive pattern since canopy conditions influence the size distribution of saplings. A previous study showed that although Abies mariesii saplings were most dominant under evergreen and deciduous canopies and in canopy gaps, above about 15% relative photosynthetic photon flux density (PPFD), the relative density of A. veitchii increased with relative PPFD. This phenomenon was related to higher growth rate of A. veitchii saplings in the early stages of regeneration. In conclusion, sapling bank dynamics is influenced not only by the difference between closed canopy and gap but also by the difference between evergreen and deciduous canopies, and the main factor of this influence may be an understory light environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".