Architecture and neighbourhood competition of understorey saplings in a subalpine forest in central Japan
Bibliographic record
Abstract
We investigated the effects of both overstorey shading and understorey sapling competition on the sapling architecture of three conifers, Abies mariesii, A. veitchii, and Picea jezoensis var. hondoensis, in a subalpine forest in central Japan. With increased overstorey shading, the two Abies species tended to have flatter crowns than P. jezoensis var. hondoensis. Because a flattened crown enhances the efficiency of light interception under low light availability, both Abies species appear more adapted to shading. Conversely, P. jezoensis var. hondoensis seems better adapted to canopy gaps, because its conical crown provides an advantage for faster height growth. Unlike A. veitchii, A. mariesii increased its stem volume to support the greater snow-loading resulting from its flattened crown. Therefore, A. mariesii seems better designed for enduring shading under snowy conditions. However, A. veitchii showed faster height growth and thus presents regeneration traits intermediate between those of A. mariesii and P. jezoensis var. hondoensis. Because sapling competition is intense in sapling-crowded microsites conditions under less crowded overstorey conditions, saplings need faster height increase to escape from other sapling competition. Conversely, because sapling competition is weaker and more space is available under a closed understorey, saplings need to have flatter crowns to compensate for overstorey shading. Species-specific architecture in response to such living conditions is closely associated with the regeneration characteristics of the three conifers studied.
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".