Distance doesn't matter: migration strategy in a seabird has no effect on survival or reproduction
Bibliographic record
Abstract
Migrating animals show remarkable diversity in migration strategies, even between individuals from the same population. Migrating longer distances is usually expected to be costlier in terms of time, energy expenditure and risks with potential repercussions for subsequent stages within the annual cycle. Such costs are expected to be balanced by increased survival, for example due to higher quality wintering areas or lower energy expenditure at lower latitudes. We compared reproductive parameters and apparent survival of lesser black-backed gulls ( Larus fuscus ) breeding in The Netherlands, whose winter range extends from the UK to West Africa, resulting in one-way migration distances that differ by more than 4500 km. Individuals migrating furthest arrived later in the colony than shorter distance migrants, but still laid in synchrony with the colony and consequently had a shorter pre-laying period. This shorter pre-laying period affected neither egg volumes nor hatching success. We found no relationship between migration distance and apparent survival probability, corresponding with previous research showing that annual energy expenditure and distance travelled throughout the year is similar across migration strategies. Combined, our results indicate an equal fitness payoff across migration strategies, suggesting there is no strong selective pressure acting on migration strategy within this population.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".