Cold tolerance performance of westslope cutthroat trout (<i>Oncorhynchus clarkii lewisi</i>) and rainbow trout (<i>Oncorhynchus mykiss</i>) and its potential role in influencing interspecific hybridization
Bibliographic record
Abstract
Hybridization between rainbow trout (Oncorhynchus mykiss (Walbaum, 1792)) and westslope cutthroat trout (Oncorhynchus clarkii lewisi (Girard, 1856)) occurs commonly when rainbow trout are introduced into the range of westslope cutthroat trout. Typically, hybridization is most common in warmer, lower elevation habitats, but much less common in colder, higher elevation habitats. We assessed the tolerance to cold water temperature (i.e., critical thermal minimum, CTMin) in juvenile rainbow trout and westslope cutthroat trout to test the hypothesis that westslope cutthroat trout better tolerate low water temperature, which may explain the lower prevalence of rainbow trout and interspecific hybrids in higher elevation, cold-water habitats (i.e., the “elevation refuge hypothesis”). All fish had significantly lower CTMin values (i.e., were better able to tolerate low temperatures) when they were acclimated to 15 °C (mean CTMin = 1.37 °C) versus 18 °C (mean CTMin = 1.91 °C; p < 0.001). Westslope cutthroat trout tended to have lower CTMin than rainbow trout from two populations, second–generation (F 2 ) hybrids between two rainbow trout populations, and backcrossed rainbow trout at 15 °C (cross type × acclimation temperature interaction; p = 0.018). Differential adaptation to cold water temperatures may play a role in influencing the spatial distribution of hybridization between sympatric species of trout.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".