Local diversification enhances pollinator visitation to strawberry and may improve pollination and marketability
Bibliographic record
Abstract
Numerous studies show that semi-natural habitats within agricultural landscapes benefit native pollinating insects and increase resultant crop pollination services. More recently, evidence is emerging that agricultural diversification techniques on farms, as well as increased compositional and configurational heterogeneity within the cropped portion of landscapes, enhance pollinator communities. However, to date, only a few studies have investigated how diversifying the crops within the farm field itself (i.e., polyculture) influences wild pollinator communities and crop pollination services. In the Central Coast of California, we investigate how local crop diversification within fields, crossed with the proportion of natural habitat in the surrounding landscape, jointly affect pollinator communities and services to strawberry. On 16 organic farms varying in farm type (monoculture vs. polyculture) and proportion of natural land cover, we find that both factors enhance pollinator abundance and richness, although neither affect honey bee abundance. Further, natural cover has a stronger effect on pollinator richness on monoculture (vs. polyculture) farms. Although strawberry can self-pollinate, we document experimentally that pollinator exclusion doubles the probability of berry malformation, while excluding both pollinators and wind triples malformation, with corresponding effects on berry marketability. Finally, in post-hoc tests, we find that berry malformation is significantly higher with greater visitation by honey bees, and observed a trend that this reduction was mitigated by increased native bee richness. These results suggest that both polyculture and semi-natural habitat cover support more abundant and diverse pollinator communities, and that ambient levels of pollinator visitation to strawberry provide an important crop pollination service by improving berry marketability (i.e., by reducing berry malformation). Although further confirmation would be needed, our work suggests that honey bees alone do not provide sufficient pollination services. Prior work has shown that honey bees tend to visit only the top of the strawberry flower receptacle, while other native bees often crawl around the flower base, leading to more complete pollination of the achenes and, consequently, better formed berries. If honey bee visits reduced native bee visitation in our system, this could explain the unexpected correlation between increased honey bee visits and malformation.
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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) | 0.000 | 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".