Consequences of pollinator availability and effectiveness for pollen transfer in a gynodioecious seed crop system
Bibliographic record
Abstract
Pollinator availability and effectiveness are important considerations in plant systems that depend on insect transfer of pollen. In mixed-flower systems (such as dioecious or gynodioecious systems), pollinators may distinguish between morphs, a behaviour which could have negative implications if it leads to reduced cross-pollination. We examined pollinator visitation, response, and effectiveness in hybrid canola seed production, a gynodioecious crop, to understand how pollinator behaviour contributes to cross-pollination between ‘male’ (hermaphroditic) and ‘female’ (male-sterile) morphs. The pollinator types found in these fields differ in visitation rate, size, and pollen load, factors that may affect pollen transfer between plants. The willingness of pollinators to move between male and female flowers can also affect pollen deposition. We used an interview bouquet to present unvisited female inflorescences to different pollinator types visiting male and female flowers to understand behavioural responses to floral morphs and the factors that contribute to better pollination effectiveness. Managed pollinators (honey and leafcutter bees) were far more abundant than wild pollinators in this system. Bees foraging on male flowers were less likely to accept a proffered female flower than those foraging on female flowers. Pollen deposition on stigmas was influenced by pollinator type (female leafcutter bees were the most effective) and increased with time spent on a flower. Pollinators transferring from a male flower to a female flower deposited more pollen than those that originated on female flowers, emphasizing the importance of transfer between male and female morphs. Surprisingly, pollinators carrying more pollen transferred less pollen to recipient stigmas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".