Planting of neonicotinoid-coated corn raises honey bee mortality and sets back colony development
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Worldwide occurrences of honey bee colony losses have raised concerns about bee health and the sustainability of pollination-dependent crops. While multiple causal factors have been identified, seed coating with insecticides of the neonicotinoid family has been the focus of much discussion and research. Nonetheless, few studies have investigated the impacts of these insecticides under field conditions or in commercial beekeeping operations. Given that corn-seed coating constitutes the largest single use of neonicotinoid, our study compared honey bee mortality from commercial apiaries located in two different agricultural settings, i.e. corn-dominated areas and corn-free environments, during the corn planting season. Data was collected in 2012 and 2013 from 26 bee yards. Dead honey bees from five hives in each apiary were counted and collected, and samples were analyzed using a multi-residue LC-MS/MS method. Long-term effects on colony development were simulated based on a honey bee population dynamic model. Mortality survey showed that colonies located in a corn-dominated area had daily mortality counts 3.51 times those of colonies from corn crop-free sites. Chemical analyses revealed that honey bees were exposed to various agricultural pesticides during the corn planting season, but were primarily subjected to neonicotinoid compounds (54% of analysed samples contained clothianidin, and 31% contained both clothianidin and thiamethoxam). Performance development simulations performed on hive populations' show that increased mortality during the corn planting season sets back colony development and bears contributions to collapse risk but, most of all, reduces the effectiveness and value of colonies for pollination services. Our results also have implications for the numerous large-scale and worldwide-cultivated crops that currently rely on pre-emptive use of neonicotinoid seed treatments.
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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 | 0.000 |
| 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 it