Site fidelity by bees drives pollination facilitation in sequentially blooming plant species
Bibliographic record
Abstract
Plant species can influence the pollination and reproductive success of coflowering neighbors that share pollinators. Because some individual pollinators habitually forage in particular areas, it is also possible that plant species could influence the pollination of neighbors that bloom later. When flowers of a preferred forage plant decline in an area, site-fidelity may cause individual flower feeders to stay in an area and switch plant species rather than search for preferred plants in a new location. A newly blooming plant species may quickly inherit a set of visitors from a prior plant species, and therefore experience higher pollination success than it would in an area where the first species never bloomed. To test this, we manipulated the placement and timing of two plant species, Delphinium barbeyi and later-blooming Gentiana parryi. We recorded the responses of individually marked bumble bee pollinators. About 63% of marked individuals returned repeatedly to the same areas to forage on Delphinium. When Delphinium was experimentally taken out of bloom, most of those site-faithful individuals (78%) stayed and switched to Gentiana. Consequently, Gentiana flowers received more visits in areas where Delphinium had previously flowered, compared to areas where Delphinium was still flowering or never occurred. Gentiana stigmas received more pollen in areas where Delphinium disappeared than where it never bloomed, indicating that Delphinium increases the pollination of Gentiana when they are separated in time. Overall, we show that individual bumble bees are often site-faithful, causing one plant species to increase the pollination of another even when separated in time, which is a novel mechanism of pollination facilitation.
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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 | 0.001 |
| 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".