Effects of repeated daily acute heat challenge on the growth and metabolism of a cold-water stenothermal fish
Bibliographic record
Abstract
Temperature is an important environmental factor influencing fish physiology that varies both spatially and temporally in ecosystems. In small north-temperate lakes, cold water piscivores rely on nearshore prey; however, this region exceeds the optimal temperature of the foraging species during summer. To cope, piscivores make short excursions into the nearshore to feed and return to cold water to digest, but the physiological impacts of these repeated acute exposures to warm water are not well understood. We exposed juvenile lake trout (Salvelinus namaycush) to treatments where they were held at ≈10°C and exposed to either 17 or 22°C for 5 - 10 min daily for 53 days mimicking warm-water forays. Control fish, held at an average temperature of ≈10°C but not exposed to thermal variation, consumed more food and grew slightly faster than heat challenged fish, with no clear differences in body condition, hepatosomatic index, ventricle mass, or muscle concentrations of lactate dehydrogenase and cytochrome c oxidase. Aerobic metabolic rates measured at 10°C indicated that standard metabolic rates (SMR) were similar among treatments; however, fish that were repeatedly exposed to 17°C had higher maximum metabolic rates (MMR) and aerobic scopes (AS) than control fish and those repeatedly exposed to 22°C. There were no differences in MMR or AS between fish exposed to 22°C and control fish. These results suggest that although SMR of fish are robust to repeated forays into warmer environments, MMR displays plasticity, allowing fish to be less constrained aerobically in cold water after briefly occupying warmer waters.
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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 | 0.001 |
| 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".