Floral symmetry affects bumblebee approach consistency in artificial flowers
Bibliographic record
Abstract
Bilateral symmetry has evolved from radial symmetry in several floral lineages, and multiple hypotheses have been proposed to account for the success of this floral plan. One of these hypotheses posits that bilateral symmetry (or, more generally, a reduced number of planes of floral symmetry) allows for more precise pollen placement on pollinators. Greater precision would maximize the efficacy of pollen transfer to conspecifics, while minimizing reproductive interference amongst plant species. Despite the intuitiveness of this hypothesis, it has little experimental support. Here, we tested whether a reduction in the number of floral planes of symmetry (as in the transition from radial to bilateral symmetry) increases the potential precision of pollen placement. We analyzed video recordings of bumblebees (Bombus impatiens) visiting artificial flowers to determine whether consistency in flower entry angle differed between radial (round) and disymmetric (rectangular) “flowers”. We observed more consistent entry angles for disymmetric flowers than for radial flowers, with entry angles to radial flowers 43% more variable on average (standard deviations of 30° vs. 21°). Bees trained on flowers with an intermediate (square) morphology exhibited a slight, non-significant preference for radial symmetry over disymmetry. Our results show that disymmetry—an evolutionarily intermediate form of floral symmetry—has the potential to increase pollen transfer to conspecific stigmas, relative to radial symmetry. Thus, evolutionary reduction in the number of planes of floral symmetry likely provides benefits in terms of pollen delivery, as suggested by the pollen-placement-accuracy hypothesis. These findings offer insight into the evolution of floral symmetry.
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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 | 0.001 |
| 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".