Impacts of sedimentation on early-life phenotypes and gene expression in coho salmon (Oncorhynchus kisutch)
Bibliographic record
Abstract
Early-life environmental stressors may threaten species of conservation concern by impacting populations during vulnerable early life history stages. Here, I tested some of the effects of sediment stress and hypoxia during early-life development on phenotypic outcomes and gene expression in coho salmon (Oncorhynchus kisutch). I obtained O. kisutch eggs from the Sugsaw Hatchery located on Vancouver Island, BC, and reared them in one of three substrate (0% fine sediment, 10% fine sediment, 20% fine sediment) or one of two no substrate (normoxia/100% DO or hypoxia/50% DO) treatments to the alevin stage (n=180 per treatment). Survival did not differ between groups, but fish reared in hypoxia and 20% fine sediment exhibited significantly lower fork lengths and weights. Yolk sac area and volume were also lower in fish from the 20% fine sediment treatment, suggesting a decrease in yolk sac conversion efficiency. Gene expression analysis of three general (HIF1A_6, ALD_1, HemA1_1) and four hypoxia-specific (Anillin, Ncapd3, Ndc80, Kif4) biomarkers revealed significant upregulation of ALD_1 expression in hypoxia-reared fish, while fewer significant differences were detected in the remaining biomarkers. Overall, more research is necessary to elucidate the genomic mechanisms mediating the phenotypic changes that result from exposure to hypoxia and high sedimentation in early-life salmonids. Yet these findings suggest that there may be negative consequences of sedimentation and hypoxia during early-life salmonid development and that these are driven by complex molecular interactions that underlie early-life organisms’ responses to stress. Reduced growth and yolk sac conversion efficiency in fish reared without substrate, compared to high quality substrate further suggest that substrate environmental enrichment (EE) during early-life rearing may be beneficial for salmonids artificially reared in hatcheries.
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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) | 0.000 | 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 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".