Pollen diversity collected by honey bees in the vicinity of <i>Vaccinium</i> spp. crops and its importance for colony development<sup>1</sup>This article is part of a Special Issue entitled “Pollination biology research in Canada: Perspectives on a mutualism at different scales”.
Bibliographic record
Abstract
Access to a rich diversity of flowering plants is very important for the development of honey bee colonies introduced in crops for pollination. The aim of this observational study was to determine the impact of surrounding pollen diversity on the health of honey bee colonies introduced in lowbush blueberries ( Vaccinium angustifolium Ait.) in June and cranberries ( Vaccinium macrocarpon Ait.) in July. The results suggest that monocultures of lowbush blueberries are not suitable for optimal brood rearing. In the blueberry environments we studied, the dominant pollen collected by honey bees were Alnus Mill. spp. and Taraxacum officinale F.H. Wigg., which are deficient in some essential amino acids. Significant reduction of brood rearing during honey bees’ stay in blueberry monocultures in June may, therefore, be explained by nutritional deficiencies. In July, the polliniferous flora in the vicinity of cranberry monocultures was poorer but of better nutritional quality. Pollen analysis allowed the identification of Brassicaceae, Trifolium L. spp., and V. macrocarpon as the three dominant taxa collected by honey bees during this period. The complete lists of plant taxa foraged by honey bees for pollen during the pollination of lowbush blueberries and cranberries are provided.
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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".