Optimum and maximum temperatures of sockeye salmon (<i>Oncorhynchus nerka</i>) populations hatched at different temperatures
Bibliographic record
Abstract
Temperature tolerance and heart rates were compared among nine sockeye salmon (Oncorhynchus nerka (Walbaum in Artedi, 1792)) populations, whose eggs were incubated at 10, 14, and 16 °C before rearing all hatchlings at a common temperature. Critical thermal maximum (CTmax) significantly differed among populations and temperature treatments. Populations with shorter migration distance and a lower migration and spawning temperature tended to have higher CTmax at 90 days posthatch. However, the relationship was reversed when fish of similar size were compared at 135–214 days posthatch. CTmax at 90 days posthatch was also positively related to body mass, which differed appreciably among populations at this development stage. With growth, the population differences in CTmax diminished from 3.1 to 1 °C. Elevated incubation temperature also decreased CTmax. Arrhenius breakpoint temperature (ABT) for maximum heart rate differed among populations incubated at 14 °C. The Chilko Lake population, which rear at 1.2 km above sea level, had the highest heart rate across all temperatures when incubated at 14 °C, but the lowest ABT among populations. This study provides clear evidence for the local adaptation among sockeye salmon populations with respect to temperature tolerance and cardiac capacity, information that adds to the debate on whether intraspecific variance is adaptive, or a constraint, or both.
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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".