Hive Insulation Increases Foraging Activities of Bumble Bees (Bombus impatiens) in a Wild Blueberry Field in Quebec, Canada
Bibliographic record
Abstract
Common eastern bumble bees (Bombus impatiens Cresson) play an essential role in pollinating lowbush blueberries (LB) in northern Quebec, but their costs and the suboptimal weather conditions during pollination highlight the need to find appropriate hive management strategies. A study was conducted in a LB field in Saguenay (Québec, Canada) focusing on the effects of hive insulation (I+ and I−), heating (H+ and H−), and placement in a single-row tree line windbreak. High-definition time-lapse cameras monitored hive activities and bumble bee foraging behaviors. We found that the conventional management of placing hives in full sun without insulation (I−) resulted in the lowest levels of bumble bee foraging activity and overall hive traffic. Placing bumble bee hives against a windbreak resulted in the highest numbers of bees entering hives with pollen (+156%), leaving hives (+69%), and overall hive traffic (+76%). Insulating hives with extruded polystyrene foam gave intermediate results, with a 105% increase in foraging activity compared to the conventional management method (I−H−). Interestingly, placing hives on seedling mats to maintain colony temperatures above 15 °C (H+) tended to decrease foraging activity and overall hive traffic. Our results show that strategic placement of bumble bee hives against windbreaks can significantly increase the activity of Bombus workers from those hives and can be used as a simple, low-cost, and efficient bumble bee hive management method by LB growers.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".