Flight efficiency explains differences in natal dispersal distances in birds
Bibliographic record
Abstract
The factors responsible for variation in dispersal distances across species remain poorly understood. Previous comparative studies found differing results and equivocal support for theoretical predictions. Here I re-examine factors that influence natal dispersal distances in British birds while taking into account the cost of transport as estimated from proxies of long-distance flight efficiency. First, I show that flight efficiency, as estimated by the hand-wing index, the aspect ratio, or the lift-to-drag ratio, is a strong predictor of dispersal distances among resident species. Most migratory species showed a similar pattern, but a group of species with relatively low aerodynamic efficiency showed longer-than-expected dispersal distances, making the overall trend independent of flight efficiency. Ecological, behavioral, and life history factors had a small or nil influence on dispersal distances, with most of their influence likely mediated by adaptations for the use of space reflected in flight efficiency. This suggests that dispersal distances in birds are not determined by adaptive strategies for dispersal per se, but are predominantly influenced by the energetic cost of movement.
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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 | 0.002 |
| 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) | 0.002 | 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".