High trophic overlap within the seabird community of Argentinean Patagonia: a multiscale approach
Bibliographic record
Abstract
Summary Food web interactions in animal communities can be investigated through the measurement of stable isotopes (e.g. δ 15 N, δ 13 C). We used this approach in a community of 14 species of seabirds breeding on the Argentinean Patagonian coast. Tissue samples were collected from nestling and adult seabirds, as well as prey, during three consecutive breeding seasons in 28 breeding colonies. Relative to those in other temperate and polar regions, this seabird community showed a high degree of overlap in trophic level (TL) among species (93% of species within a TL range of 0·7) and also a comparatively high mean trophic level (4·1). Relative positions of seabirds in relation to prey suggest that most species feed on pelagic fish and to a lesser extent on invertebrates. Stable isotope values of specialist feeders, Olrolg's ( Larus atlanticus ) and dolphin gulls ( Leucophaeus scoresbii ), which were previously assumed to feed mainly on crabs and sea lion excrement, respectively, suggested a broader diet than expected. Based on stable isotope values of individuals, groups of phylogenetically related species generally showed a high degree of overlap within each group. Given the degree of isotope overlap in this species‐rich community, coexistence could be interpreted as a consequence of superabundance of food or species diversification in morphology and foraging strategies. The short range of trophic level makes these seabirds vulnerable to the reduction of fish stocks due either to commercial fishing or stochastic fluctuations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".