Intra- and inter-individual variations in flight direction in a migratory butterfly co-vary with individual mobility
Bibliographic record
Abstract
Flight direction is a major component of an animal's migratory success. However, few studies have focused on variation in flight direction both between and within individuals, which is likely to be correlated with other traits implied in migration processes. We report patterns of intra- and inter-individual variation in flight direction in the large white butterfly Pieris brassicae. The presence of inter-individual variation in flight direction for individuals tested in the same conditions suggests that this trait is inherited in P. brassicae and we propose that a rapid loss of migratory skills may exist in the absence of selection for migration. The magnitude of intra-individual variation was negatively correlated to two surrogates of the potential for migration: mobility and wing length. Highly mobile and longed-winged individuals within the same family were found to fly in similar directions, whereas less mobile and short-winged individuals displayed divergent flight direction compared with the average direction of their kin. There was also a negative correlation between the variance to the mean flight direction of a family and its average mobility, but no correlation with wing length. We discuss these issues in terms of the evolution of traits potentially implied in both migration and dispersal in P. brassicae.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".