Differences in clonal integration between the sexes: long-term demographic patterns in the dioecious, multi-stemmed shrub <i>Lindera triloba</i>
Bibliographic record
Abstract
In clonal plants, ramets connected within a genet can share resources through clonal integration, and clonal integration often facilitates the growth and survival of young ramets. However, in dioecious plants, it is not fully understood whether female and male genets differ in their integration patterns affecting the demographic processes. To test between-sex differences in the demographic process in relation to clonal integration, we conducted a long-term census for the dioecious sprouting shrub Lindera triloba (Sieb. et Zucc.) Blume. In an old-growth forest, we selected 73 female and 82 male genets, and the recruitment, growth, and mortality of ramets within those genets were monitored over six years. Ramet recruitment was greater in males than in females, whereas ramet growth and survival rates did not differ, on average, between sexes. Females and males showed different sensitivities to factors affecting their ramet dynamics. The ramet recruitment, growth, and survival within male genets were significantly positively affected by the largest main ramet size, whereas females were not sensitive to the effect. This suggested that demographic patterns of ramets within male genets were more sensitive to assimilates translocated from the main ramets than those within female genets, and the role of clonal integration worked differently on ramet dynamics between sexes.
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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) | 0.001 | 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".