Local adaptation to cold temperatures by larval coho salmon (Oncorhynchus kisutch) from different populations throughout British Columbia
Bibliographic record
Abstract
The influence of environmental variables on larval development of coho salmon (Oncorhynchus kisutch), with specific focus on the influence of near-freezing incubation temperatures, was examined across populations within British Columbia.A survey across the geographical distribution within British Columbia was conducted to determine the range and variability of incubation temperatures experience by incubating coho salmon.Temperatures throughout incubation differed significantly among locations, averaging approximately 1 °C in colder interior locations and approximately 5 °C in warmer coastal locations.Environmental variables influenced egg size, fecundity, female size and gonadal somatic index, such that higher latitude of spawning grounds increased, larger systems decreased, and increased temperatures experienced by a population increased the four life-history traits.Suggesting significant effects of latitude of spawning grounds, size of spawning system and temperatures experienced by a population on shaping patterns of reproductive investment.A laboratory incubation study revealed no difference in survival and performance between families from a southern and a northern population reared at near-freezing incubation temperatures.These findings suggest plasticity in developmental processes of coho salmon, as each population was successful across a wide range of temperatures, and in particular developed successfully with minimal fitness effects at the extreme ranges of near-freezing temperatures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".