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Record W2184523412 · doi:10.26443/msurj.v3i1.126

Specialized morphology for a non-specialized diet: Liem’s paradox in an African cichlid fish

2008· article· en· W2184523412 on OpenAlexafffund
Aurélie Cosandey-Godin, Sandra A. Binning, Lauren J. Chapman

Bibliographic record

VenueMcGill Science Undergraduate Research Journal · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Biodiversity
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCichlidBiologyGeneralist and specialist speciesPredationTrophic levelOmnivoreEcologyFaunaMorphology (biology)ZoologyFish <Actinopterygii>HabitatFishery

Abstract

fetched live from OpenAlex

&#x0D; &#x0D; &#x0D; &#x0D; 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.&#x0D; &#x0D; &#x0D; &#x0D;

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.099
GPT teacher head0.341
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2008
Admission routes2
Has abstractyes

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