Bibliographic record
Abstract
Fungicides account for more than 35% of the global pesticide market and their use is predicted to increase in the future. While fungicides are commonly applied during bloom when bees are likely foraging on crops, whether real-world exposure to these chemicals - alone or in combination with other stressors - constitutes a threat to the health of bees is still the subject of great uncertainty. The first step in estimating the risks of exposure to fungicides for bees is to understand how and to what extent bees are exposed to these active ingredients. Here we review the current knowledge that exists about exposure to fungicides that bees experience in the field, and link quantitative data on exposure to acute and chronic risk of lethal endpoints for honey bees (Apis mellifera). From the 702 publications we screened, 76 studies contained quantitative data on residue detections in honey bee matrices, and a further 47 provided qualitative information about exposure for a range of bee taxa through various routes. We compiled data for 90 fungicides and metabolites that have been detected in honey, beebread, pollen, beeswax, and the bodies of honey bees. The risks posed to honey bees by fungicide residues was estimated through the EPA Risk Quotient (RQ) approach. Based on residue concentrations detected in honey and pollen/beebread, none of the reported fungicides exceeded the levels of concern (LOC) set by regulatory agencies for acute risk, while 3 and 12 fungicides exceeded the European Food Safety Authority (EFSA) chronic LOC for honey bees and wild bees, respectively. When considering exposure to all bees, fungicides of most concern include many broad-spectrum systemic fungicides, as well as the widely used broad-spectrum contact fungicide chlorothalonil. In addition to providing a detailed overview of the frequency and extent of fungicide residue detections in the bee environment, we identified important research gaps and suggest future directions to move towards a more comprehensive understanding and mitigation of the risks of exposure to fungicides for bees, including synergistic risks of co-exposure to fungicides and other pesticides or pathogens.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".