Thermal tolerance in Pacific salmon: A systematic review of species, populations, life stages and methodologies
Bibliographic record
Abstract
Abstract Aquatic systems are warming and exceeding upper thermal limits (UTLs) for many fish species, yet understanding how they inform resilience to climate change is challenging. Using Pacific salmon ( Oncorhynchus spp.) as a model, we conducted a systematic review involving 168 papers investigating UTL in five species. We found considerable variation in UTL among species, within species and across life stages; largely attributed to methodological approaches (e.g. CT max /UILT, Aerobic/Cardiac Scope, Thermal Migration Barriers, Rearing Mortality, Thermal Preference/Avoidance). Given that each method has strengths and weaknesses owing to logistics, time scale and ecological realism, we offer a new framework for assessing vulnerability to warming that stresses the importance of considering UTL metrics in the context of intended use (i.e. the development of management guidelines, projections of future persistence and survival) and what aspect (physiological or behavioural) of thermal response a metric investigates. Comparing studies with identical UTL approaches revealed that within species, UTL was higher for populations historically encountering higher temperatures—suggesting local thermal adaptation. Within populations, UTL differed across the lifecycle, being highest in fry and lowest in embryo and migrating adults, but this was not universal. For spawning Pacific salmon, UTL has not been assessed and few studies have examined estuarine and marine stages. Ultimately, this data gap limits the life‐history thermal perspectives that can be drawn and may indicate a broader gap for all fishes, given that Pacific salmon are among the most well‐studied species. Our framework illustrates the inherent and methodological inconsistencies in UTL and offers a guide for how thermal limits can best be used to assess the warming tolerance and vulnerability of fishes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".