Trophic interactions between the Kelp Gull (<i>Larus dominicanus</i>) and Royal and Cayenne terns (<i>Thalasseus maximus maximus</i> and <i>Thalasseus sandvicensis eurygnathus</i>, respectively) in a human-modified environment
Bibliographic record
Abstract
Many closely related seabirds nest in mixed colonies, and this association may result in interspecific interactions such as competition for common resources and kleptoparasitism. Trophic interactions were evaluated between the Kelp Gull (Larus dominicanus Lichtenstein, 1823) and Royal and Cayenne terns (Thalasseus maximus maximus (Boddaert, 1783) and Thalasseus sandvicensis eurygnathus (Saunders, 1876), respectively) nesting at a mixed-species colony in an area with high availability of recreational fishery waste for the opportunistic Kelp Gull. Diet analyses were based on gull chick stomach content samples and direct observations of food delivered to tern chicks in 2013 and 2014, complemented in 2014 with carbon and nitrogen stable isotope analysis of chick whole-blood samples. Main prey species of Kelp Gull chicks were Cynoscion guatucupa (Cuvier, 1830), a demersal species obtained from recreational fishery waste, Argentine anchovies (Engraulis anchoita Hubbs and Marini, 1935), and insects. Engraulis anchoita and Odontesthes spp. were the main prey of both tern species. Trophic niche and isotopic niche overlap between the Kelp Gull and Royal and Cayenne terns was low. Kelp Gull kleptoparasitism on Royal and Cayenne terns was ≤2.5% and <0.6%, respectively. The use of anthropogenic food subsidies by Kelp Gulls may be mediating the trophic relationships among species, favouring their use of predictable and abundant fishery waste over a more unpredictable pelagic schooling fish such as E. anchoita.
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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".