Food Web Structure Shapes the Morphology of Teleost Fish Brains
Bibliographic record
Abstract
Previous work showed that teleost fish brain size correlates with the flexible exploitation of habitats and predation abilities in an aquatic food web. Since it is unclear how regional brain changes contribute to these relationships, we quantitatively examined the effects of common food web attributes on the size of five brain regions in teleost fish at both within-species (plasticity or natural variation) and between-species (evolution) scales. Our results indicate that brain morphology is influenced by habitat use and trophic position, but not by the degree of littoral-pelagic habitat coupling, despite the fact that the total brain size was previously shown to increase with habitat coupling in Lake Huron. Intriguingly, the results revealed two potential evolutionary trade-offs: (i) relative olfactory bulb size increased, while relative optic tectum size decreased, across a trophic position gradient, and (ii) the telencephalon was relatively larger in fish using more littoral-based carbon, while the cerebellum was relatively larger in fish using more pelagic-based carbon. Additionally, evidence for a within-species effect on the telencephalon was found, where it increased in size with trophic position. Collectively, these results suggest that food web structure has fundamentally contributed to the shaping of teleost brain morphology.
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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".