Intra- and inter-annual shifts in foraging tactics by parental northern gannets Morus bassanus indicate changing prey fields
Bibliographic record
Abstract
Seabirds are constrained by central-place foraging during breeding, when the energy obtained from prey must outweigh the costs of travel, search, capture and transport. The distribution and phenology of the cold-blooded marine fishes they exploit are heavily influenced by oceanic climate. Northern gannets, the largest breeding seabird in the North Atlantic, use a generalist foraging strategy, preying on a wide array of pelagic fishes. They employ different foraging tactics for different prey types, with rapid, shallow V-shaped dives used for large, powerful prey such as mackerel, and U-shaped dives for smaller forage fishes like capelin. Here we assess intra- and inter-annual differences in foraging effort and influences of prey availability at the southernmost colony of the species at Cape St. Mary’s, Newfoundland, Canada. We compared foraging trip characteristics (total and maximum distance, directness, duration and number of dives) of parental gannets during the breeding seasons of 2019 (n = 10) and 2020 (n = 7) using GPS/time-depth recorders. Individual gannets shifted away from using U-shaped dives in early chick-rearing to primarily V-shaped dives in late chick-rearing. Shifts were abrupt and occurred in mid-August in 2019 and 2020. Maximum and total foraging trip distance and duration were significantly greater during early chick-rearing in 2020 than in 2019. Kernel density 50% utilization distributions were larger and expanded further from the colony during early chick-rearing in 2020 (7297 ± 1419 km2; mean ± SE) than 2019 (2382 ±797 km2). Increased foraging effort during early chick-rearing in 2020 was likely due to decreased capelin availability, resulting from earlier spawning, and greater variation in the timing of spawning among sites, which may have been influenced by warmer waters.
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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 | 0.000 |
| 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".