Mechanisms of male-male interference during dispersal of orchid pollen
Bibliographic record
Abstract
Siring success of flowering plants depends on the fates of male gametophytes, which compete for access to stigmas, stylar resources and ovules. Although rarely considered, pollen may often compete during dispersal, affecting the processes required for export to stigmas; pollen pickup, transport and deposition. We quantified dispersal interference by tracking bee dispersal of stained Anacamptis morio (Orchidaceae) pollen from individual donor flowers and inferred the affected dispersal mechanisms based on the fit of a process-based model. During individual trials, all recipient flowers were either emasculated, precluding interference with donor pollen, or intact, adding potentially interfering pollen to the pollinator. The presence of competing pollinaria on bees reduced pickup of additional pollinaria, doubled the overall proportion of lost donor pollen and reduced total pollen export by 27%. Interference specifically increased loss of donor pollen between successive flower visits and variation in deposition among trials, and likely also reduced pollen contact with stigmas and pollen deposition when contact occurred. Thus, by altering pollen removal, transport and deposition, male-male interference during pollen dispersal can significantly, and perhaps commonly, limit plant siring success.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.013 |
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".