An experimental displacement and over 50 years of tag-recoveries show that monarch butterflies are not true navigators
Bibliographic record
Abstract
Monarch butterflies (Danaus plexippus) breeding in eastern North America are famous for their annual fall migration to their overwintering grounds in Mexico. However, the mechanisms they use to successfully reach these sites remain poorly understood. Here, we test whether monarchs are true navigators who can determine their location relative to their final destination using both a "compass" and a "map". Using flight simulators, we recorded the orientation of wild-caught monarchs in southwestern Ontario and found that individuals generally flew in a southwest direction toward the wintering grounds. When displaced 2,500 km to the west, the same individuals continued to fly in a general southwest direction, suggesting that monarchs use a simple vector-navigation strategy (i.e., use a specific compass bearing without compensating for displacement). Using over 5 decades of field data, we also show that the directional concentration and the angular SD of recoveries from tagged monarchs largely conformed to two mathematical models describing the directional distribution of migrants expected under a vector-navigation strategy. A third analysis of tagged recoveries shows that the increasing directionality of migration from north to south is largely because of the presence of geographic barriers that guide individuals toward overwintering sites. Our work suggests that monarchs breeding in eastern North America likely combine simple orientation mechanisms with geographic features that funnel them toward Mexican overwintering sites, a remarkable achievement considering that these butterflies weigh less than a gram and travel thousands of kilometers to a site they have never seen.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".