Sex-dependent shifts in visual detection thresholds under turbid conditions in an African cichlid
Bibliographic record
Abstract
Abstract Turbidity is increasing in freshwaters globally due to human activities and is known to affect visually mediated behaviours in fish. As anthropogenic impacts continue to degrade aquatic environments, it is critical to determine how sensory systems are affected and what this might mean for population persistence. We investigated the effect of turbidity on visual detection thresholds in an African cichlid fish (Pseudocrenilabrus multicolor) that experiences environmental extremes across its East African range. We tested the visual abilities of adult wild-caught fish from two sites representing the extremes of turbidity and oxygen (a high turbidity, high dissolved oxygen river and a low turbidity, low dissolved oxygen swamp). Further, we reared offspring of wild-caught parents from each population in a full-factorial high/low oxygen, high/low turbidity design to tease apart the influence of each stressor on visual detection thresholds. We used an optomotor response test to determine detection thresholds under increasing levels of turbidity for both wild-caught and lab-reared fish. Detection thresholds were higher in the wild-caught river population compared to the swamp population, and there was a strong sex difference, such that wild-caught males had higher detection thresholds than females regardless of population of origin. Our results suggest that there are sex-based differences in contrast detection abilities that could play a critical role in visual ecology for populations experiencing divergent turbidity regimes. In the rearing experiment, sex-based differences in detection thresholds were influenced by different aspects of the rearing treatment. Detection threshold varied significantly by oxygen-rearing treatment for males and by the interactive effects of oxygen and turbidity for females. This research improves our understanding of the effect of elevated turbidity on African cichlid vision and contributes to growing knowledge of how animals respond to environmental change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".