Transgenerational effects of egg nutrients on the early development of Chinook salmon (<i>Oncorhynchus tshawytscha</i>) across a thermal gradient
Bibliographic record
Abstract
The transgenerational effect of maternal diet, expressed as variation in the composition and quantity of egg nutrients available to offspring during endogenous development (i.e., prior to free-feeding), has the potential to greatly influence the response of offspring phenotypes to varying environmental conditions. For this study, we examined how natural variation in the fatty acid and proximate composition of eggs from three Chinook salmon (Oncorhynchus tshawytscha) populations influenced early development across a thermal gradient using a common garden hatchery experiment. We found that the relative quantity of fat, lean mass, and water in the eggs was similar among populations. However, the fatty acid composition of the eggs differed among all populations. After controlling for egg mass, egg fatty acid and proximate composition influenced hatch length, swim-up length, and hatch to swim-up growth. Importantly, the magnitude and direction of these egg quality effects depended on the population of origin and temperature. Overall, our results demonstrate that natural variation in egg nutrient composition, likely driven by maternal diet, has transgenerational effects on offspring development under varying thermal conditions.
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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".