Vulnerability of amphibians to global warming
Bibliographic record
Abstract
Abstract Amphibians are the most threatened vertebrates, yet their resilience to rising temperatures remains poorly understood 1,2 . This is primarily because knowledge of thermal tolerance is taxonomically and geographically biased 3 , compromising global climate vulnerability assessments. Here we used a phylogenetically informed data-imputation approach to predict the heat tolerance of 60% of amphibian species and assessed their vulnerability to daily temperature variations in thermal refugia. We found that 104 out of 5,203 species (2%) are currently exposed to overheating events in shaded terrestrial conditions. Despite accounting for heat-tolerance plasticity, a 4 °C global temperature increase would create a step change in impact severity, pushing 7.5% of species beyond their physiological limits. In the Southern Hemisphere, tropical species encounter disproportionally more overheating events, while non-tropical species are more susceptible in the Northern Hemisphere. These findings challenge evidence for a general latitudinal gradient in overheating risk 4–6 and underscore the importance of considering climatic variability in vulnerability assessments. We provide conservative estimates assuming access to cool shaded microenvironments. Thus, the impacts of global warming will probably exceed our projections. Our microclimate-explicit analyses demonstrate that vegetation and water bodies are critical in buffering amphibians during heat waves. Immediate action is needed to preserve and manage these microhabitat features.
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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) | 0.012 | 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".