Pollinator responses to floral colour change, nectar and scent promote reproductive fitness in Quisqualis indica (Combretaceae)
Bibliographic record
Abstract
Floral colour change is visual signals for pollinators to avoid old flowers and increase pollination efficiency. Quisqualis indica flowers change colour from white to pink to red may be associated with a shift from moth to butterfly pollination. To test this hypothesis, we investigated Q. indica populations in Southwest China. Flowers secreted nectar continuously from the evening of anthesis until the following morning, then decreased gradually with floral colour change. The scent compounds in the three floral colour stages were similar; however, the scent composition was different, and the scent emission rate decreased from the white to red stage. Dichogamy in Q. indica prevents self-pollination and interference of male and female functions. Controlled pollinations demonstrated that this species is self-incompatible and needs pollinators for seed production. Different pollinators were attracted in each floral colour stage; mainly moths at night and bees and butterflies during the day. Observations of open-pollinated inflorescences showed that white flowers had a higher fruit set than pink or red flowers, indicating the high contribution of moths to reproductive success. We concluded that the nectar and scent secretion are related to floral colour change in Q. indica, in order to attract different pollinators and promote reproductive fitness.
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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".