Exposure to exogenous egg cortisol does not rescue juvenile Chinook salmon body size, condition, or survival from the effects of elevated water temperatures
Bibliographic record
Abstract
Abstract Climate change is leading to altered temperature regimes which are impacting aquatic life, particularly for ectothermic fish. The impacts of environmental stress can be translated across generations through maternally derived glucocorticoids, leading to altered offspring phenotypes. Although these maternal stress effects are often considered negative, recent studies suggest this maternal stress signal may prepare offspring for a similarly stressful environment (environmental match). We applied the environmental match hypothesis to examine whether a prenatal stress signal can dampen the effects of elevated water temperatures on body size, condition, and survival during early development in Chinook salmon Oncorhynchus tshawytscha from Lake Ontario, Canada. We exposed fertilized eggs to prenatal exogenous egg cortisol (1,000 ng/ml cortisol or 0 ng/ml control) and then reared these dosed groups at temperatures indicative of current (+0°C) and future (+3°C) temperature conditions. Offspring reared in elevated temperatures were smaller and had a lower survival at the hatchling developmental stage. Overall, we found that our exogenous cortisol dose did not dampen effects of elevated rearing temperatures (environmental match) on body size or early survival. Instead, our eyed stage survival indicates that our prenatal cortisol dose may be detrimental, as cortisol‐dosed offspring raised in elevated temperatures had lower survival than cortisol‐dosed and control reared in current temperatures. Our results suggest that a maternal stress signal may not be able to ameliorate the effects of thermal stress during early development. However, we highlight the importance of interpreting the fitness impacts of maternal stress within an environmentally relevant context.
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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 | 0.001 |
| 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".