The Foraging Ecology of the Endangered Cape Verde Shearwater, a Sentinel Species for Marine Conservation off West Africa
Bibliographic record
Abstract
Large Marine Ecosystems such as the Canary Current system off West Africa sustains high abundance of small pelagic prey, which attracts marine predators. Seabirds are top predators often used as biodiversity surrogates and sentinel species of the marine ecosystem health, thus frequently informing marine conservation planning. This study presents the first data on the spatial (GPS-loggers) and trophic (stable isotope analysis) ecology of a tropical seabird-the endangered Cape Verde shearwater Calonectris edwardsii-during both the incubation and the chick-rearing periods of two consecutive years. This information was related with marine environmental predictors (species distribution models), existent areas of conservation concern for seabirds (i.e. marine Important Bird Areas; marine IBAs) and threats to the marine environment in the West African areas heavily used by the shearwaters. There was an apparent inter-annual consistency on the spatial, foraging and trophic ecology of Cape Verde shearwater, but a strong alteration on the foraging strategies of adult breeders among breeding phases (i.e. from incubation to chick-rearing). During incubation, birds mostly targeted a discrete region off West Africa, known by its enhanced productivity profile and thus also highly exploited by international industrial fishery fleets. When chick-rearing, adults exploited the comparatively less productive tropical environment within the islands of Cape Verde, at relatively close distance from their breeding colony. The species enlarged its trophic niche and increased the trophic level of their prey from incubation to chick-rearing, likely to provision their chicks with a more diversified and better quality diet. There was a high overlap between the Cape Verde shearwaters foraging areas with those of European shearwater species that overwinter in this area and known areas of megafauna bycatch off West Africa, but very little overlap with existing Marine Important Bird Areas. Further investigation on the potential nefarious effects of fisheries on seabird communities exploiting the Canary Current system off West Africa is needed. Such negative effects could be alleviated or even dissipated if the 'fisheries-conservation hotspots' identified for the region, would be legislated as Marine Protected Areas.
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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".