Plasticity and overlap of trophic niches in tropical breeding Laridae
Bibliographic record
Abstract
Trophic ecology of seabirds in tropical regions remains poorly understood despite the large number of multispecies breeding colonies supported by these ecosystems. Here, we used the isotopic niche (δ15N and δ13C) of 5 Laridae species at 2 breeding areas in Cuba to analyze the plasticity and interspecific overlap of trophic niche determined from chick down and feather samples. The down samples reflected the female trophic regime before laying, while the feather samples incorporated the trophic regime of the chicks provided by the parents during rearing. Two main species groups were identified by their isotopic niche characteristics: species with small and quite stable isotopic niches (trophic specialists) and species with large and highly variable isotopic niches (trophic generalists). Laughing gull Leucophaeus atricilla, royal tern Thalasseus maximus, and sandwich tern T. sandvicensis were the generalists and showed significant isotopic niche differences between breeding areas and phases. Bridled tern Onychoprion anaethetus and roseate tern Sterna dougallii were trophic specialists, but only the former exhibited significant variations in isotopic niche breadth between breeding phases. Overall, trophic (inferred from isotopic) niche overlap was relatively low, suggesting that these tropical seabirds reduce competition through niche partitioning. We concluded that trophic niche plasticity and segregation appear to constitute an important adaptive strategy to ensure the breeding success of sympatrically breeding Laridae in north-central Cuba.
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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".