Intraspecific variation in tolerance of warming in fishes
Bibliographic record
Abstract
Intraspecific variation in key traits such as tolerance of warming can have profound effects on ecological and evolutionary processes, notably responses to climate change. The empirical evidence for three primary elements of intraspecific variation in tolerance of warming in fishes is reviewed. The first is purely mechanistic that tolerance varies across life stages and as fishes become mature. The limited evidence indicates strongly that this is the case, possibly because of universal physiological principles. The second is intraspecific variation that is because of phenotypic plasticity, also a mechanistic phenomenon that buffers individuals' sensitivity to negative impacts of global warming in their lifetime, or to some extent through epigenetic effects over successive generations. Although the evidence for plasticity in tolerance to warming is extensive, more work is required to understand underlying mechanisms and to reveal whether there are general patterns. The third element is intraspecific variation based on heritable genetic differences in tolerance, which underlies local adaptation and may define long-term adaptability of a species in the face of ongoing global change. There is clear evidence of local adaptation and some evidence of heritability of tolerance to warming, but the knowledge base is limited with detailed information for only a few model or emblematic species. There is also strong evidence of structured variation in tolerance of warming within species, which may have ecological and evolutionary significance irrespective of whether it reflects plasticity or adaptation. Although the overwhelming consensus is that having broader intraspecific variation in tolerance should reduce species vulnerability to impacts of global warming, there are no sufficient data on fishes to provide insights into particular mechanisms by which this may occur.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".