Thermal Performance of Three Rainbow Trout Strains at Above‐Optimal Temperatures
Bibliographic record
Abstract
Abstract Studies have predicted declines in trout habitat of over 50% given projected climate warming scenarios. Therefore, knowledge of the performance of trout strains at elevated temperature is critical for management of trout fisheries and trout strains under climate change. Our objectives were to compare the performance of three strains of Rainbow Trout Onchorynchus mykiss at elevated temperatures. We compared growth, consumption, and feed efficiency at 20°C and 22°C, and critical thermal maxima (CTM) among the strains. The Case Western strain is registered as a warm‐tolerant strain with the National Fish Strain Registry, and it did achieve a significantly higher CTM (31.29°C) than the Kamloops (31.14°C) but not the Wytheville (31.20°C) strain. Such small differences are likely not biologically significant. While the CTM of the Case Western strain was higher than that of the Kamloops, the Case Western strain consistently performed poorer than the other strains in feeding and growth experiments at 20°C and 22°C. Our results add to the growing body of literature suggesting that differences in thermal performance do exist between strains of trout. While there is debate about whether these differences are due to evolutionary adaptation to local environmental conditions or phenotypic plasticity, the differences being found in thermal performance of trout suggests future research aimed at improving thermal performance via thermal testing and selective breeding may yield stock with improved tolerance and growth at warmer temperatures. Received April 17, 2014; accepted June 24, 2014
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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".