Specialized morphology for a non-specialized diet: Liem’s paradox in an African cichlid fish
Bibliographic record
Abstract
Cichlid fishes of the East African Great Lakes represent some of the most diverse vertebrate faunas in the world, and trophic specialization, the specific adaptation of feeding structures to one type of prey, is often used to explain the coexistence of these closely related species. However, Liem’s Paradox suggests that organisms with specialized phenotypes may act primarily as generalist feeders in nature, which can create a mismatch between diet and morphology. Our goal was to study the diet of a widespread African cichlid, Astatoreochromis alluaudi, over the course of 1 year to test the hypothesis that the molluskvore-like morphology of this species is not an appropriate indicator of diet choice. Lake Saka, in Uganda, was sampled monthly throughout 2006, and stomach content analyses were performed on preserved specimens using established techniques to identify the relative importance of various prey items in the diet of A. alluaudi. Stomach content analyses indicated an omnivorous diet in all months, consisting mostly of insects, fish, and plant matter, whereas snails accounted for only a small portion of their overall diet. Although trophic morphology in this species is a plastic trait, specimens from Lake Saka exhibit a molluscivore-like morphology. Our data suggests that the morphology of this generalist feeder may have developed to exploit non-favoured resources, a clear example of Liem’s Paradox. This study emphasizes the importance of examining both stomach contents and trophic morphology before inferring the feeding ecology of a species.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".