Seed rain and seedling establishment of the dioecious tree<i>Neolitsea sericea</i>(Lauraceae): effects of tree sex and density on invasion into a conifer plantation in central Japan
Bibliographic record
Abstract
We studied the effects of differences in parent sex and density on seed rain and seedling and (or) sapling recruitment in a dioecious tree species (Neolitsea sericea (Bl.) Koidz.) with bird-dispersed seeds. We established four microhabitats: male or female trees inside or outside a single patch. The density of bird-disseminated seeds was significantly higher beneath females and inside the patch than beneath males and single trees outside the patch; this led to higher density of emerged seedlings inside the patch. The survival rate of germinated seedlings was also higher inside the patch than below single trees. In contrast, the survival rate of saplings was highest beneath males outside the patch, although very few seeds are dispersed beneath single males. Seedling and sapling recruitment beneath females and inside the patch will be accelerated owing to higher density of dispersed seeds, high seedling survival, and greater sapling density. In contrast, recruitment beneath males will be very slow. However, microhabitats beneath males are probably more suitable for seedling and sapling recruitment than microhabitats beneath females, since the survival rate of saplings was higher beneath males. Parental sex-biased seed rain and seedling and (or) sapling recruitment in dioecious plants may explain the regeneration pattern at a local scale.
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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) | 0.001 | 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".