Potential surrogate plants for use in semi-field pesticide risk assessment with <i>Megachile rotundata</i>
Bibliographic record
Abstract
Background Current regulatory pesticide risk assessments for bees are based primarily on the honey bee (Apis mellifera) and may not always be protective of solitary bees. To incorporate solitary bees into the risk assessment process, standardized methods to assess the hazard of pesticides under semi-field (Tier II) conditions will be needed. We conducted a series of experiments over 2 years to assess potential surrogate plants and adult release rates for use in semi-field experiments with the alfalfa leafcutting bee (ALB, Megachile rotundata). Methods We compared ALB foraging activity and reproduction on 12 m2 plots of flowering alfalfa (Medicago sativa) and buckwheat (Fagopyrum esculentum) at low (10♀/20♂) and high (20♀/40♂) adult release rates. The following year, we assessed the same endpoints on plots of purple tansy (Phacelia tanacetifolia) at a release rate of 10♀/15♂. Results Although ALB foraging activity was high on buckwheat plots, fewer adults were produced compared to alfalfa plots. On alfalfa, there were no differences in foraging activity, nesting, or reproduction between the low and high release rates. ALB readily foraged from purple tansy flowers, but females avoided purple tansy leaves for leaf cell construction. Discussion Our study suggests that buckwheat alone cannot support ALB during semi-field studies on small plots. For alfalfa, we recommend a maximum release rate of 10♀/20♂ in 12 m2 plots. Further study of higher ALB release rates on purple tansy is warranted. A mixed planting of purple tansy and a plant suitable for leaf piece collection (e.g., buckwheat) may provide favorable conditions for ALB activity and reproduction during semi-field testing.
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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 | 0.001 |
| 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 | 0.001 | 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".