Turbidity drives plasticity in the eyes and brains of an African cichlid
Bibliographic record
Abstract
Natural variation in environmental turbidity correlates with variation in the visual sensory system of many fishes, suggesting that turbidity may act as a strong selective agent on visual systems. Since many aquatic systems experience increased turbidity due to anthropogenic perturbations, it is important to understand the degree to which fish can respond to rapid shifts in their visual environment, and whether such responses can occur within the lifetime of an individual. We examined whether developmental exposure to turbidity (clear, <5 NTU; turbid, ∼9 NTU) influenced the size of morphological structures associated with vision in the African blue-lip cichlid Pseudocrenilabrus multicolor. Parental fish were collected from two sites (clear swamp, turbid river) in western Uganda. F1 broods from each population were split and reared under clear and turbid rearing treatments until maturity. We measured morphological traits associated with the visual sensory system (eye diameter, pupil diameter, axial length, brain mass, optic tectum volume) over the course of development. Age was significant in explaining variation in visual traits even when standardized for body size, suggesting an ontogenetic shift in the relative size of eyes and brains. When age groups were analyzed separately, young fish reared in turbid water grew larger eyes than fish reared in clear conditions. Population was important in the older age category, with swamp-origin fish having relatively larger eyes and optic lobes relative to river-origin fish. Plastic responses during development may be important for coping with a more variable visual environment associated with anthropogenically induced turbidity.
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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".