Acute measures of upper thermal and hypoxia tolerance are not reliable predictors of mortality following environmental challenges in rainbow trout (<i>Oncorhynchus mykiss)</i>
Bibliographic record
Abstract
Abstract Anthropogenic climate change threatens freshwater biodiversity and poses a challenge for fisheries management, as fish will increasingly be exposed to episodes of high temperature and low oxygen (hypoxia). Here, we examine the extent of variation in tolerance of acute exposure to these stressors within and among five strains of rainbow trout (Oncorhynchus mykiss) currently being used or under consideration for use in stocking programmes in British Columbia, Canada. We used incipient lethal oxygen saturation (ILOS) as an index of acute hypoxia tolerance, critical thermal maximum (CTmax) as an index of acute upper thermal tolerance and mortality following these two acute exposure trials to assess the relative resilience of individuals and strains to climate change-relevant stressors. We measured tolerance across two brood years and two life stages (fry and yearling), using a highly replicated design with hundreds of individuals per strain and life stage. There was substantial within-strain variation in CTmax and ILOS, but differences among strains, although statistically significant, were small. In contrast, there were large differences in post-trial mortality among strains, ranging from less than 2% mortality in the most resilient strain to 55% mortality in the least resilient. There was a statistically significant, but weak, correlation between CTmax and ILOS at both life stages for some strains, with thermally tolerant individuals tending to be hypoxia tolerant. These data indicate that alternative metrics of tolerance may result in different conclusions regarding resilience to climate change stressors, which has important implications for stocking and management decisions for fish conservation in a changing climate.
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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) | 0.000 | 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 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".