Post-spawning sexual selection in red and white Chinook salmon (<i>Oncorhynchus tshawytscha</i>)
Bibliographic record
Abstract
Post-copulatory processes, including sperm competition and cryptic female choice (CFC), can play important roles in the maintenance of polymorphisms. In Chinook salmon (Oncorhynchus tshawytscha), color morphs (red and white) exist due to genetic polymorphisms affecting carotenoid deposition in flesh, skin, and gametes. We investigated the role of post-spawning sexual selection in maintaining the polymorphism in a mixed population. First, we compared sperm velocity differences in water between morphs. Next, we measured color-based CFC via 2 methods: 1) sperm velocity in ovarian fluid and 2) in vitro competitive fertilization using paired red and white males. We found that red males had marginally faster sperm relative to white males in water, suggesting that carotenoid storage may affect sperm performance. However, ovarian fluid of red and white females influenced sperm velocity of red and white males differently, indicative of color-based CFC on sperm velocity. Furthermore, we found evidence of color-based CFC on paternity success during in vitro competitive fertilizations; however, sperm velocity in ovarian fluid did not predict results found under in vitro fertilization. Instead, in our study, sperm velocity in water was a significant predictor of fertilization success. When we accounted for this difference in sperm velocity (in water) between paired males, we partitioned the amount of variation in fertilization success that was attributed to individual level CFC (male pair × female) and male competitiveness (male pair) as 43% and 16%, respectively. In conclusion, post-spawning sexual selection processes represent important mechanisms contributing to the maintenance of the color polymorphism in nature.
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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".