Specialist pollinators deplete pollen in the spring ephemeral wildflower <i><scp>C</scp>laytonia virginica</i>
Bibliographic record
Abstract
Pollinators that collect pollen - and specifically, pollen-specialist bees - are often considered to be the best pollinators of a (host) plant. Although pollen collectors and pollen specialists often benefit host plants, especially in the pollen that they deliver (their pollination "effectiveness"), they can also exact substantial costs because they are motivated to collect as much pollen as possible, reducing the proportion of pollen removed that is subsequently delivered to stigmas (their pollination "efficiency"). From the plant perspective, pollen grains that do not pollinate conspecific stigmas are "wasted", and potentially costly. We measured costs and benefits of nectar-collecting, pollen-collecting, and pollen-specialist pollinator visitation to the spring ephemeral Claytonia virginica. Visits by the pollen-specialist bee Andrena erigeniae depleted pollen quickly and thoroughly. Although all pollinators delivered roughly the same number of grains, the pollen specialist contributed most to C. virginica pollen delivery because of high visitation rates. However, the pollen specialist also removed a large number of grains; this removal may be especially costly because it resulted in the depletion of pollen grains in C. virginica populations. While C. virginica appears to rely on pollen transfer by the pollen specialist in these populations, nectar-collecting visitors could provide the same benefit at a lower cost if their visitation rates increased. Pollen depletion affects a pollinator's value to plants, but is frequently overlooked. If they lower the effectiveness of future floral visitors, visits by A. erigeniae females to C. virginica may be more detrimental than beneficial compared to other pollinators and may, in some circumstances, reduce plant fitness rather than increase it. Therefore, A. erigeniae and C. virginica may vary in their degree of mutualism depending on the ecological context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".