Determining food requirements in marine top predators: a comparison of three independent techniques in Great Cormorants,<i>Phalacrocorax carbo</i><i>carbo</i>
Bibliographic record
Abstract
Assessment of food requirements is a key feature in the evaluation of the ecological status of the marine megafauna. However, this remains technically difficult because prey intake by marine top predators occurs mainly under water, out of sight. In this paper, we compare three independent methods currently available for use in quantitative dietary studies: (1) time-energy budget; (2) stomach-temperature measurements; and (3) automatic weighing. To this end, concurrent measurements were performed on Great Cormorants (Phalacrocorax carbo carbo) breeding in Normandy. According to the time-energy budget method, breeding males required 690 g of fish while incubating, 1050 g when rearing small chicks, and 1350 g when rearing large chicks; corresponding values for breeding females were 500, 760, and 970 g. These measurements are similar to estimates derived from automatic weighing data, which gave a mean food intake of 540 and 390 g for incubating males and females, 1150 and 830 g for those tending small chicks, and 1410 and 1010 g for those tending large ones, respectively. Stomach-temperature measurements, which can only be performed for birds raising small chicks, were lower (640 g fish in males and 450 g in females) than those obtained using the other two methods. We compare these results with former estimates obtained at the same study site and for other Great Cormorant subspecies and discuss the relative accuracies of the three techniques. Finally, we stress that better assessment of the ecological status of marine top predators requires further technical improvements and additional investigations outside of the reproductive phase.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".