Paternal effects on early life history traits in Northwest Atlantic cod, <i>Gadus morhua</i>
Bibliographic record
Abstract
It is important to understand parental effects on early life history of fish as manifested, for example, in individual fitness of offspring. Immediately after fertilization, parental contributions (both genetic and non-genetic) to embryos will affect larval ontogeny, physiology, morphology and survival. In marine fish, rates of natural mortality are highest during early life and are negatively correlated with rates of growth and body size. In these early life stages (eggs, larvae, young juveniles) subtle differences in mortality can cause large differences in recruitment and year-class success. Therefore, it is particularly critical to understand factors that contribute to variability in mortality during early life. This study focuses on evaluating the potential influence of paternity on rates of mortality and development in eggs and larvae of Northwest Atlantic cod, Gadus morhua. To accomplish this 12 males and two females were crossed using a full-factorial breeding design. Paternity had a strong influence on fertilization success, hatching success, cumulative embryonic mortality, larval standard length, eye diameter, yolk-sac area, and cumulative larval mortality. Female 1 showed an overall ‘weaker’ performance of offspring than Female 2, indicating that deviances can stem from differences in female quality. Nevertheless, paternal contributions to embryonic and larval development were still evident despite differences in female quality, showing that sire effects on offspring are undeniable and can serve as important sources of variation during early life stages in fishes. Overall, these findings have implications for furthering the understanding of recruitment variability and can be used to optimize reproductive output for the aquaculture industry. In addition, the data suggests that the choice of mate during spawning can play a large role in offspring fitness.
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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".