Pesticide exposure of wild bees and honey bees foraging from field border flowers in intensively managed agriculture areas
Bibliographic record
Abstract
Bees are critical for food crop pollination, yet their populations are declining as agricultural practices intensify. Pollinator-attractive field border plantings (e.g. hedgerows and forb strips) can increase bee diversity and abundance in agricultural areas; however, recent studies suggest these plants may contain pesticides. Pesticide exposure for wild bees remains largely unknown; however, this information is needed to inform agricultural practices and pesticide regulations meant to protect bees. It is important to determine whether border plantings that attract and support pollinators may also deliver pesticides to them. In this study, we collected various samples for pesticide residue analysis, including: multiple species of wild bees, honey bees, flowers from four types of bee-attractive field border plants, and soil. Silicone bands were also utilized as passive aerial samplers of pesticide residues. The five pesticides detected most frequently across all samples were the insecticide bifenthrin, the herbicides thiobencarb, metolaclor, and propanil, and the fungicide fluopyram. We detected the greatest number of parent pesticides in bands (24), followed by soil (21). Pesticides were also detected in field border plant flowers (16), which do not receive direct pesticide applications, and included many products which were not applied to adjacent field crops. Pesticide concentrations were lower in bees than in flowers but higher in bees than in soils. Pesticide residue per bee (ng/bee) increased with increasing wild bee size, though pesticide concentration (ng/g) did not increase. While honey bees and wild bees contained a similar number and concentration of pesticides overall, pesticide mixtures varied by bee type, and included some mixtures known to cause sublethal effects. The results from this study highlight the benefits of measuring more sample types to capture the total exposome of bees, including a greater range of bee species, as well as the need to consider exposure to pesticides at the landscape level.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".