Data from: On the correlated evolution of ecological lifestyle and thermal tolerance
Bibliographic record
Abstract
The breadth of thermal tolerance delineates the upper (CTmax/Tuc) and lower (CTmin/Tlc) temperatures relevant to survival and/or persistence of organisms, and it is a correlate of extinction risk under climate change. Theory suggests that tolerance breadth evolves with the range of environmental temperatures. For instance, a narrow tolerance breadth is classically observed in tropical vs temperate species, and tropical ectotherms may feature increased extinction risk under climate change due to the proximity of CTmax and mean environmental temperatures. Here, we underscore that an organism’s lifestyle influences the extent of thermal fluctuation in its environment. We predict that subterranean species feature a narrower thermal tolerance breadth than surface-dwelling species, as the former evolve under dampened thermal variance. Using thermal limits data, we test this hypothesis in reptiles, mammals, and arthropods. Subterranean species (n = 5 – 37 per taxon) featured reduced tolerance breadths compared to surface-dwelling species, and the difference was significant in reptiles and mammals; additionally, subterranean arthropods featured a significantly lower CTmax and significantly higher CTmin than surface species. Thus, classical theory on thermal tolerance extends beyond patterns of geolocation to species lifestyle, where evolution under dampened thermal variance can reduce thermal tolerance breadth and influence other thermal traits.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.027 |
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".