Pollen Loads and Specificity of Native Pollinators of Lowbush Blueberry
Bibliographic record
Abstract
The reproduction of lowbush blueberry (Vaccinium angustifolium Aiton) is closely tied to insect pollination, owing to self-incompatibility. Many species are known to have greater pollination efficiency than the introduced Apis mellifera L., commonly used for commercial purposes. In this study, we measured the pollen loads of several antophilous insect species, mostly Apoidea and Syrphidae, present in four lowbush blueberry fields in Lac-St-Jean, Québec. To measure pollen loads and species specificity toward V. angustifolium, we net-collected 627 specimens of pollinators, retrieved their pollen loads, identified pollen taxa, and counted pollen grains. We found that the sizes of pollen loads were highly variable among species, ranging from a few hundred to more than 118,000 pollen grains per individual. Bombus and Andrena species in particular carried large amounts of Vaccinium pollen and thus may have greater pollination efficiency. Also, two species (Andrena bradleyi Viereck and Andrena carolina Viereck) showed nearly monolectic behavior toward lowbush blueberry. Finally, we identified alternative forage plants visited by native pollinators, notably species of Acer, Rubus, Ilex mucronata, Ledum groenlandicum, and Taraxacum. Protecting these flowering plants should be part of management practices to maintain healthy pollinator communities in a lowbush blueberry agroecosystem.
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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 | 0.001 | 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".