Individual specialization in diet by a generalist marine predator reflects specialization in foraging behaviour
Bibliographic record
Abstract
1. We studied chick diet in a known-age, sexed population of a long-lived seabird, the Brünnich's guillemot (Uria lomvia), over 15 years (N = 136; 1993-2007) and attached time-depth-temperature recorders to examine foraging behaviour in multiple years (N = 36; 2004-07). 2. Adults showed specialization in prey fed to offspring, described by multiple indices calculated over 15 years: 27% of diet diversity was attributable to among-individual variation (within-individual component of total niche width = 0.73); average similarity of an individual's diet to the overall diet was 65% (mean proportional similarity between individuals and population = 0.65); diet was significantly more specialized than expected for 70% of individuals (mean likelihood = 0.53). These indices suggest higher specialization than the average for an across-taxa comparison of 49 taxa. 3. Foraging behaviour varied along three axes: flight time, dive depth and dive shape. Individuals showed specialized individual foraging behaviour along each axis. These foraging strategies were reflected in the prey type delivered to their offspring and were maintained over scales of hours to years. 4. Specialization in foraging behaviour and diet was greater over short time spans (hours, days) than over long time spans (years). Regardless of sex or age, the main component of variation in foraging behaviour and chick diet was between individuals. 5. Plasma stable isotope values were similar across years, within a given individual, and variance was low relative to that expected from prey isotope values, suggesting adult diet specialized across years. Stable isotope values were similar among individuals that fed their nestlings similar prey items and there was no difference in trophic level between adults and chicks. We suggest that guillemots specialize on a single foraging strategy regardless of whether chick-provisioning and self-feeding. With little individual difference in body mass and physiology, specialization likely represents learning and memorizing optimal feeding locations and behaviours. 6. There was no difference in survival or reproductive success between specialists and generalists, suggesting these are largely equivalent strategies in terms of evolutionary fitness, presumably because different strategies were advantageous at different levels of prey abundance or predictability. The development of individual specialization may be an important precursor to diversification among seabirds.
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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 | 0.000 | 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) | 0.001 | 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".