Ice age fish in a warming world: minimal variation in thermal acclimation capacity among lake trout (Salvelinus namaycush) populations
Bibliographic record
Abstract
In the face of climate change, the persistence of cold-adapted species will depend on their adaptive capacity for physiological traits within and among populations. The lake trout (Salvelinus namaycush) is a cold-adapted salmonid and a relict from the last ice age that is well suited as a model species for studying the predicted effects of climate change on coldwater fishes. We investigated the thermal acclimation capacity of upper temperature resistance and metabolism of lake trout from four populations across four acclimation temperatures. Individuals were reared from egg fertilization onward in a common environment and, at 2 years of age, were acclimated to 8, 11, 15 or 19°C. Although one population had a slightly higher maximal metabolic rate (MMR), higher metabolic scope for activity and faster metabolic recovery across all temperatures, there was no interpopulation variation for critical thermal maximum (CTM) or routine metabolic rate (RMR) or for the thermal acclimation capacity of CTM, RMR, MMR or metabolic scope. Across the four acclimation temperatures, there was a 3°C maximal increase in CTM and 3-fold increase in RMR for all populations. Above 15°C, a decline in MMR and increase in RMR resulted in sharply reduced metabolic scope for all populations acclimated at 19°C. Together, these data suggest there is limited variation among lake trout populations in thermal physiology or capacity for thermal acclimatization, and that climate change may impact lake trout populations in a similar manner across a wide geographical range. Understanding the effect of elevated temperatures on the thermal physiology of this economically and ecologically important cold-adapted species will help inform management and conservation strategies for the long-term sustainability of lake trout populations.
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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".