Variation in pollinator potential to carry a blueberry fungal pathogen and assessment of transfer efficiency in two managed bee species
Bibliographic record
Abstract
Plant diseases are ubiquitous in agricultural systems and are major sources of economic loss. Vaccinium corymbosum, or highbush blueberry, is an economically important crop affected by an insect-vectored, fungal pathogen, Monilinia vaccinii-corymbosi, or mummy berry disease. Highbush blueberry yield is maximized through outcrossed pollination; however, the pathogen is vectored by pollinators. We used field collections and molecular techniques to identify floral visitors to highbush blueberry and quantify levels of pathogen spores carried by each visiting species. We also conducted a cage trial using single flower visits to determine differences in vectoring efficiency between two managed pollinators, Apis mellifera and Bombus impatiens. We found that bees, flies, and wasps were all common visitors, and that all bee species and several fly and wasp species carried the pathogen. Of the bee species, A. mellifera most often tested positive for the pathogen, while Dolichovespula maculata (Bald-faced Hornet) tested positive most among wasps and Mallota posticata among flies. Considering only individuals that tested positive, mummyberry levels per individual were highest in D. maculata and Andrena bees, and relatively low in flies. In cage trials, we found no differences between A. mellifera and B. impatiens in pathogen load or transfer efficiency, suggesting that these managed species are equally capable of vectoring mummyberry during a single visit to a blighted stem and then a flower. This research demonstrates the variety of floral visitors that carry mummyberry and that two common commercial pollinator species have similar potential to vector mummyberry to blueberry flowers during a single visit.
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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 | 0.001 |
| 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".