Wild bees mediate fruit quality via seed set in highbush blueberry: A quantitative synthesis
Bibliographic record
Abstract
Insect-mediated pollination enhances global production of many crops, and evidence highlights that insect pollination can also improve crop quality. The link between insect-mediated pollination and crop quality is driven not only by insect pollinators, but by a complex of interactions between pollinators, plant genotype, levels of cross pollination, plant physiology, environmental conditions, farm management, etc. To further optimize food production, the link between insect-mediated pollination and crop quality requires additional examination. In this study, we used a dataset of 260 sites across multiple production regions to explore how flower visitation of honey bees and wild bees drives fruit quality in highbush blueberry, measured as fruit weight. Our hypothesis was that bee visitation mediates fruit quality through fruit set and seed set. These effects were evaluated using both linear and structural equation modeling (SEM). Our analyses show that seed set mainly influences fruit quality and SEM analyses reveal a positive cascading effect of wild bee visitation on fruit quality, mediated via seed set. Similar effects of fruit set or honey bee visitation on fruit quality were not detected. This study highlights that bee visitation mainly affects blueberry fruit quality via seed set and that analyses beyond the pollinator visitation-crop quality relation can inform pollination research and management. Possible measures to improve crop quality by enhancing pollinator visitation by means of farm management or landscape management are discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".