Honest signalling and the billboard effect: how Heliconiid pollinators respond to the trichromatic colour changing <i>Lantana camara</i> L. (Verbenaceae)
Bibliographic record
Abstract
Plants communicate with their pollinators through an astonishing range of signals that serve as either honest or deceptive cues which draw in and inform potential visitors of possible rewards. In wild type sweet sage, Lantana camara, floral colour signals were associated with nectar volume and sucrose concentration, and many pollinator taxa quickly learned to associate these varying colour signals with rewards. We tested the hypothesis that if sweet sage is employing a generalist pollinator strategy based on a trichromatic changing floral presentation system of honest rewards for pollinators, then the following predictions will be realized: 1) pre-change yellow flowers will be visited more frequently by pollinators than post change orange, or red flowers; 2) pre-change yellow flowers will produce higher quality and greater quantities of sucrose rewards than post-change orange, or red flowers; 3) inflorescences with higher ratios of rewarding flowers to unrewarding flowers are more attractive at short distances; and 4) inflorescences with a combination of pre-change rewarding and post-change rewarding and unrewarding flowers will act as a multi-coloured advertising billboard and as such be most attractive at long distances. We found corroboration for all of the aforementioned predictions. Thus, sweet sage evolved a generalized pollination visitation system based on honest signalling―of reward quantity and quality tied to colour changing visual signals acting in consort to produce a billboard that was easily perceived and deciphered. These resulted in high visitation rates by many different taxa of pollinators, thus contributing to higher individual plant 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".