Multiple stressors disrupt sex hormones and fitness outcomes: effects of hypoxia and turbidity on an African cichlid fish
Bibliographic record
Abstract
Abstract Freshwater organisms face a complex array of environmental stressors that can negatively affect endocrine function and subsequent fitness outcomes. Hypoxia and turbidity are two environmental stressors that are increasing due to human activities that could lead to endocrine disruption and reduced reproductive output. Our research addresses how hypoxia and elevated turbidity affect traits related to reproductive success, specifically sex hormone concentrations, investment in reproductive tissues and body size. We used wild fish from two populations (a river and a swamp) of an African cichlid, Pseudocrenilabrus multicolor, to produce offspring that were reared in a full factorial split brood rearing experiment (hypoxic/normoxic × clear/turbid). River and swamp populations represent divergent habitat types with respect to the stressors of interest, being well-oxygenated but turbid or hypoxic and clear, respectively. Overall, we found evidence for plastic responses to both stressors. Specifically, we found that there was an interactive effect of oxygen and turbidity on testosterone in males from both populations. Additionally, males of both populations reared under hypoxic conditions were significantly smaller in both mass and standard length than those raised under normoxic conditions and invested less in reproductive tissues (quantified as gonadosomatic index). Hypoxia and turbidity are experienced naturally by this species, and these environmental stressors did not affect the number of eggs laid by females when experienced in the absence of another stressor (i.e. normoxic/turbid or hypoxic/clear). However, there was an interactive effect of hypoxia and turbidity, as females reared and maintained under this treatment combination laid fewer eggs. This research underscores the importance of considering the possibility of stressor interactions when determining how anthropogenic stressors affect fitness outcomes.
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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".