A field study of seed dispersal and seedling performance in the invasive exotic vine <i>Vincetoxicum rossicum</i>
Bibliographic record
Abstract
The exotic vine Vincetoxicum rossicum (Kleopow) Barbar. (Asclepiadaceae) is a major natural-areas pest throughout the Great Lakes Basin. Colonization of new areas by this herbaceous perennial occurs by comose wind-dispersed seeds. Previous experiments suggested a trade-off between seed dispersability and seed quality: smaller seeds dispersed farther but were less likely to emerge and seedlings were smaller when grown in competition with turf grasses in the greenhouse. We examined dispersability by trapping seeds at distances of 0–60 m from a seed source, and we assessed seedling performance by sowing seeds of known weight in an old field. Smaller seeds travelled significantly farther than larger seeds; however, the relationship between weight and distance dispersed was weak (r 2 = 0.043). Large seeds were significantly more likely to emerge, and the seedlings survive and grow taller; however, the relationships between seed size and these performance variables were also weak (r 2 ≤ 0.02). The dispersability–quality tradeoff is unlikely to play an important role in V. rossicum spread at the local scale, as even large seeds are competent dispersers and even seedlings from small seeds are capable of becoming established. Seedlings from polyembryonic seeds were more likely to successfully establish than seeds from which a single seedling emerged. The high seedling emergence (50% for seeds planted above ground; 72% for those buried to a depth of 1 cm) and survivorship (71%–100%, depending on embryony) are likely to contribute to the success of this species.
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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 | 0.001 | 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".