Tolerance traits related to climate change resilience are independent and polygenic
Bibliographic record
Abstract
The resilience of organisms to climate change through adaptive evolution is dependent on the extent of genetically based variation in key phenotypic traits and the nature of genetic associations between them. For aquatic animals, upper thermal tolerance and hypoxia tolerance are likely to be a important determinants of sensitivity to climate change. To determine the genetic basis of these traits and to detect associations between them, we compared naturally occurring populations of two subspecies of Atlantic killifish, Fundulus heteroclitus, that differ in both thermal and hypoxia tolerance. Multilocus association mapping demonstrated that 47 and 35 single nucleotide polymorphisms (SNPs) explained 43.4% and 51.9% of variation in thermal and hypoxia tolerance, respectively, suggesting that genetic mechanisms underlie a substantial proportion of variation in each trait. However, no explanatory SNPs were shared between traits, and upper thermal tolerance varied approximately linearly with latitude, whereas hypoxia tolerance exhibited a steep phenotypic break across the contact zone between the subspecies. These results suggest that upper thermal tolerance and hypoxia tolerance are neither phenotypically correlated nor genetically associated, and thus that rates of adaptive change in these traits can be independently fine-tuned by natural selection. This modularity of important traits can underpin the evolvability of organisms to complex future environmental change.
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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 | 0.000 | 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) | 0.000 | 0.001 |
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".