Per-visit pollinator performance and regional importance of wild Bombus and Andrena (Melandrena) compared to the managed honey bee in New York apple orchards
Bibliographic record
Abstract
Declines in honey bee health and increasing demand for pollination services highlight a need to optimize crop pollination by wild bees. Apple is an economically important crop in eastern North America, requires insect pollination, and is visited by a diverse bee fauna, but a direct assessment of wild bee pollination in apple orchards is lacking. We combined measurements of two facets of pollination service, per-visit efficiency (fruit and seed set) and relative abundance, to estimate orchard-level, pollinator importance of mining bees ( Andrena subgenus Melandrena ), bumble bees ( Bombus ), and honey bees ( Apis mellifera L.). Average pollinator importance provided a relative measure that allowed comparison of pollination service among the three focal bees across the study region. On average, a wild bee visit resulted in higher pollen transfer to stigmas, but had the same probability of setting fruit and seed as a honey bee visit. Regionally, pollinator importance of Melandrena and Bombus were 32 and 14 % that of honey bees, respectively. Because per-visit performances were similar, such disparities in importance were based largely on differences in relative abundance. Although the summed pollinator importance of Melandrena and Bombus was less than that of the honey bee, these, and other, wild pollinators have a role to play in filling future pollination gaps, and thus, warrant further study and conservation.
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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 | 0.000 | 0.000 |
| 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".