Individual condition, standard metabolic rate, and rearing temperature influence steelhead and rainbow trout (<i>Oncorhynchus mykiss</i>) life histories
Bibliographic record
Abstract
We reared juvenile Oncorhychus mykiss with low and high standard metabolic rates (SMR) under alternative thermal regimes to determine how these proximate factors influence life histories in a partially migratory salmonid fish. High SMR significantly decreased rates of freshwater maturation and increased rates of smoltification in females, but not males, after 1 year of rearing. Warmer water temperatures significantly decreased rates of freshwater maturation and increased rates of smoltification in both sexes. Variation in individual growth influenced the probability of adopting anadromy or freshwater residency as life histories, but produced paradoxical results. Individuals with the highest growth performance within their respective temperature treatments had a higher probability of freshwater maturation, but warmer temperatures decreased freshwater maturation despite significantly increasing somatic growth. Whole-body lipid content was significantly lower for fish reared in the warm temperature treatment, which may explain the decreased probability of freshwater maturation for individuals exposed to warmer temperatures. Our results indicate that changes in somatic growth induced by altered thermal regimes can influence the relationship between body size and the probability of maturation. Accordingly, somatic growth may not be a robust predictor of shifts in the prevalence of anadromy and residency in partially migratory salmonids when compared across thermal regimes.
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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".