Thermal tolerance in cutthroat trout of the southern Rocky Mountains
Bibliographic record
Abstract
With temperatures expected to rise across the southern Rocky Mountains, the ability of native fishes to tolerate stream warming has become a critical concern for those tasked with preserving coldwater species. We used common garden experiments to evaluate the thermal tolerance of cutthroat trout ( Oncorhynchus clarkii) fry from five populations important to managers representing three sub-species. Critical thermal maxima (CTMs) were evaluated through traditional exposure trials, while optimal growth and ultimate upper incipient lethal temperatures (UUILTs) were examined over the course of 21-day trials at six static temperature treatments. Whereas CTMs differed among populations (mean = 27.91 °C, SD = 0.35 °C), UUILTs did not (mean = 24.40 °C, SD = 0.04 °C). Comparison of cubic temperature-growth functions to the traditional quadratic functions showed that adding a third-order term for temperature can improve model fit, and revealed substantial differences in optimal growth temperatures (15.4–18.3 °C). Knowledge of these thermal tolerance thresholds will help to predict the consequences of a warming climate, identify suitable habitats for repatriation, and inform water quality temperature standards established to protect these fish into the future.
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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) | 0.000 | 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".