Cumulative effects of high temperature and low dissolved oxygen alter the acute thermal tolerance and cellular stress response in lake trout
Bibliographic record
Abstract
Abstract Lake trout ( Salvelinus namaycush ) is an important food fish in Northern communities, inhabiting cool, well-oxygenated water. Yet, climate change is reducing available habitat with extended summer stratification of lakes creating an upper thermal barrier (∼15 °C) and lower dissolved oxygen (DO) boundary (4-7 mg L -1 ). Together, these environmental factors can influence tolerance thresholds and climate change may lead to abiotic factors exceeding these physiological thresholds in lake trout habitats. Thresholds can shift with environmental acclimation in lake trout populations, but the functional basis of this shift has yet to be examined. The abundance of mRNA transcripts offers insight into underlying cellular responses to environmental stressors that can provide an early warning of fitness consequences. Here, we used a stress-response transcriptional profiling chip to investigate a suite of genes involved in thermal and general stress in lake trout acclimated to a range of temperatures (6-18 °C) and DO (normoxia: > 8.5 mg L -1 or hypoxia: 5.5-6.5 mg L -1 ), as well as following an acute thermal stress (i.e., CT max ). Transcriptional profiles were assessed in the gill, liver, and and epidermal mucus. Generally, fish acclimated to the greatest combined stressor (18 °C and hypoxia) had the largest transcriptional response, suggestive of a transition from a routine stress response to an extreme survival response. A noted temperature dependence occurred in liver tissue, which was not evident in gill or mucus tissues. Further, transcriptional responses in the gill and mucus were highly correlated ( r = 0.74-0.87), highlighting the potential use of these tissues for non-lethal sampling methods to enhance management and conservation strategies for lake trout across their distribution.
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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".