Factors affecting the production, growth, and survival of sprouting stems in the multi-stemmed understory shrub <i>Lindera triloba</i>
Bibliographic record
Abstract
We investigated the structure and dynamics of the multi-stemmed understory shrub Lindera triloba (Sieb. et Zucc.) Blume over 3 years in an old-growth coniferous forest, and quantitatively evaluated the factors affecting the ramet production, growth, and survival. Most genets sprouted continuously and exhibited multiple-stemmed structures with a few large and many small ramets. The skewed ramet-size distribution within genets resulted from the local crowding of neighboring trees, but not from the number of ramets within genets. This indicated that inter-plant competition is asymmetric (i.e., larger individuals outcompete one-sidedly smaller ones), but intra-plant competition (i.e., competition among ramets within genets) is symmetric (i.e., smaller ones also competitively affect larger ones). The local crowding of neighboring understory trees consistently negatively affected the ramet production, growth, and survival of L. triloba. Intra-genet crowding (i.e., crowding of ramets within genets) also negatively affected the ramet dynamics. On the other hand, the largest-ramet size within genets had positive relationships with the ramet dynamics, indicating that physiological integration within genets plays a role as supporting younger ramets. Based on our results, to fully understand genet persistence strategies in clonal shrub species, it is important to consider the effects of intra-genet crowding and modular integration, as well as plant-to-plant interaction.
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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 | 0.001 | 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".