Microhabitat use and prey capture of a bottom-feeding top predator, the European shag, shown by camera loggers
Bibliographic record
Abstract
Studies of the fine-scale use of foraging habitat are essential for understanding the role of seabirds in marine ecosystems. However, until recently, relationships between foraging and habitat usage were only possible at a coarse scale. We used miniaturized bird-borne digital still-picture camera loggers to obtain high-quality images of the foraging habitat used by 9 European shags Phalacrocorax aristotelis. Underwater images revealed that shags are almost exclusively benthic feeders, but used 2 very distinct foraging habitats: sandy areas and rocky areas with brittlestars, soft corals and kelp. We found no evidence that individuals specialize on a particular habitat. Birds were recorded in rocky and sandy areas over the course of a day and in some cases within a trip. Foraging behaviour differed markedly between habitats. In rocky areas birds foraged solitarily, over a wide range of depths (10 to 40 m) and travelled along the bottom while searching for bottom-living fish such as butterfish Pholis gunnellus. In contrast, shags using sandy habitat frequently fed with conspecifics, foraged mainly at 2 depths (24 or 32 m) and spent the bottom phase of the dive probing into the sand with their bill, presumably to catch lesser sandeels Ammodytes marinus, the major prey item in the diet. This study highlights the flexible foraging strategy of European shags and illustrates how image and dive data can be combined to improve our understanding of the factors influencing the foraging success of benthic feeders.
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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 | 0.001 | 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".