Combining bio-logging, stable isotopes and DNA metabarcoding to reveal the foraging ecology and diet of the Endangered Bermuda petrel Pterodroma cahow
Bibliographic record
Abstract
The foraging range of central-place predators is limited by spatiotemporal and energetic constraints. Gadfly petrels Pterodroma spp. are seabirds well adapted to travel vast distances in oceans with sustained wind conditions, although our understanding of their foraging ecology in these heterogeneous and highly dynamic environments is still limited. We studied the foraging behaviour, habitat use, ecological niche and diet of the Endangered Bermuda petrel P. cahow, endemic to the western North Atlantic. We used GPS loggers to track foraging trips during incubation and early chick-rearing in 2019 and 2022, and employed DNA metabarcoding coupled with stable isotope analyses to reveal dietary habits. Our analyses showed that petrels travelled over a vast area of the western North Atlantic while foraging over deep, pelagic waters. Specifically, in the early chick-rearing phase, they reduced their foraging range and time spent at sea compared to incubation. Foraging locations were associated with varying sets of environmental variables between breeding phases, including mesoscale oceanographic features, distance to the colony and wind speed. Petrels also showed narrow isotopic niches, and the ranges of δ15N and δ13C values suggested consistency in trophic habits. Finally, we found high taxonomic diversity in the diet, including exclusively meso-bathypelagic fishes and cephalopods. Our results contribute critical new knowledge on Bermuda petrel foraging-behaviour plasticity, a feature that can help predict how a small population of an endangered species may respond to climate-related changes in wind regimes and oceanic processes expected in the North Atlantic Ocean.
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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 | 0.002 | 0.001 |
| 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".