An unusually high upper thermal acclimation potential for rainbow trout
Bibliographic record
Abstract
Abstract Thermal acclimation, a compensatory physiological response, is central to species survival especially during the current era of global warming. By providing the most comprehensive assessment to date for the cardiorespiratory phenotype of rainbow trout (Oncorhynchus mykiss) at six acclimation temperatures from 15°C to 25°C, we tested the hypothesis that, compared with other strains of rainbow trout, an Australian H-strain of rainbow trout has been selectively inbred to have an unusually high and broad thermal acclimation potential. Using a field setting at the breeding hatchery in Western Australia, thermal performance curves were generated for a warm-adapted H-strain by measuring growth, feed conversion efficiency, specific dynamic action, whole-animal oxygen uptake (ṀO2) during normoxia and hypoxia, the critical maximum temperature and the electrocardiographic response to acute warming. Appreciable growth and aerobic capacity were possible up to 23°C. However, growth fell off drastically at 25°C in concert with increases in the time required to digest a meal, its total oxygen cost and its peak ṀO2. The upper thermal tipping points for appetite and food conversion efficiency corresponded with a decrease in the ability to increase heart rate during warming and an increase in the cost to digest a meal. Also, comparison of upper thermal tipping points provides compelling evidence that limitations to increasing heart rate during acute warming occurred well below the critical thermal maximum (CTmax) and that the faltering ability of the heart to deliver oxygen at different acclimation temperatures is not reliably predicted by CTmax for the H-strain of rainbow trout. We, therefore, reasoned the remarkably high thermal acclimation potential revealed here for the Australian H-strain of rainbow trout reflected the existing genetic variation within the founder Californian population, which was then subjected to selective inbreeding in association with severe heat challenges. This is an encouraging discovery for those with conservation concerns for rainbow trout and other fish species. Indeed, those trying to predict the impact of global warming should more fully consider the possibility that the standing intra-specific genetic variation within a fish species could provide a high thermal acclimation potential, similar to that shown here for rainbow 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".