Effects of early-life exposure to sublethal levels of a common neonicotinoid insecticide on the orientation and migration of monarch butterflies (<i>Danaus plexippus</i>)
Bibliographic record
Abstract
Migratory insects use a variety of innate mechanisms to determine their orientation and maintain correct bearing. For long-distance migrants, like the monarch butterfly (Danaus plexippus), these journeys could be affected by exposure to environmental contaminants. Neonicotinoids are synthetic insecticides that work by affecting the nervous system of insects resulting in impairment of their mobility, cognitive performance and other physiological and behavioural functions. To examine how neonicotinoids might affect the ability of monarch butterflies to maintain a proper directional orientation on their ∼4,000 km migration, we grew swamp milkweed (Asclepias incarnata) in soil that was either untreated (0 ng/g: control) or mixed with low (15 ng/g of soil), or high (25 ng/g of soil) levels of the neonicotinoid clothianidin. Monarch caterpillars were raised on control or clothianidin-treated milkweed and, after pupation, either tested for orientation in a static flight simulator or radio-tracked in the wild during the fall migration period. Despite clothianidin being detectable in milkweed tissue consumed by caterpillars, there was no evidence that clothianidin influenced the orientation, vector strength (i.e., concentration of direction data around the mean), or the rate of travel of adult butterflies and nor was there evidence that morphological traits (i.e., mass and forewing length), testing time, wind speed, or temperature impacted directionality. While samples sizes for both flight simulator and radio-tracking tests were limited, our preliminary results suggest that clothianidin exposure during early caterpillar development does not affect the directed flight of adult migratory monarch butterflies or influence their orientation at the beginning of migration.
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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 | 0.000 |
| 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 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".