Persistent interactive effects of developmental salinity and temperature in Atlantic killifish (Fundulus heteroclitus)
Bibliographic record
Abstract
Climate change alters multiple abiotic environmental factors in aquatic environments but relatively little is known about their interacting impacts, particularly in developing organisms where these exposures have the potential to cause long-lasting effects. To explore these issues, we exposed developing killifish embryos (Fundulus heteroclitus) to 26 °C or 20 °C and 20 ppt or 3 ppt salinity in a fully-factorial design. After hatching, fish were transferred to common conditions of 20 °C and 20 ppt to assess the potential for persistent developmental plasticity. Warm temperature increased hatching success and decreased hatch time, whereas low salinity negatively affected hatching success, but this was only significant in fish developed at 20 °C. Temperature, salinity, or their interaction affected mRNA levels of genes typically associated with thermal and hypoxia tolerance (hif1a, hsp90b, hsp90a, hsc70, and hsp70.2) across multiple developmental timepoints. These differences were persistent into the juvenile stage, where the fish that developed at 26 °C had higher expression of hif1a, hsp90b, hsp90a, and hsp70.2 than fish developed at 20 °C, and this was particularly evident for the group developed at both high temperature and salinity. There were also long-lasting effects of developmental treatments on body size after four months of rearing under common conditions. Fish developed at low salinity or temperature were larger than fish developed at high temperature or salinity, but there was no interaction between the two factors. These data highlight the complex nature of the developmental effects of interacting stressors which has important implications for predicting the resilience of fishes in the context of climate change.
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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".