Acute Exposure to Worst-Case Concentrations of Amitraz Does Not Affect Honey Bee Learning, Short-Term Memory, or Hemolymph Octopamine Levels
Bibliographic record
Abstract
Amitraz, an acaricide used to treat Varroa destructor Anderson & Trueman, is one of the most commonly detected pesticides in honey bee (Apis mellifera L.) hives. Acaricides sometimes negatively impact honey bee cognition, but potential effects of amitraz on honey bee learning have been rarely studied. We topically exposed foragers to 95th percentile field-relevant levels of amitraz and, 24 h later, tested the ability of bees to associate a sucrose reward with a conditioned odor (learning response) using the proboscis extension response (PER). We then tested the ability of the bees to retain this memory 1 h and 2 h post-conditioning. Because amitraz is thought to affect octopamine metabolism in honey bees, and because octopamine is directly related to honey bee learning and memory, we also examined effects of exposure to amitraz on octopamine levels in honey bee hemolymph. We found that acute exposure to 95th percentile doses of amitraz had no impact on honey bee learning or short-term memory as measured by PER. Concentrations of octopamine in hemolymph from our low amitraz treatment were 1.4-fold higher than control levels, but other treatments had no effect. Our results from worst-case acute exposure experiments with worker bees in the laboratory suggest that typical field-relevant (within hive) exposures to amitraz probably have little effect on honey bee learning and memory.
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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 | 0.000 | 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 | 0.001 |
| 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".