Local extinction risk of three species of lizard from Patagonia as a result of global warming
Bibliographic record
Abstract
Recently, Sinervo et al. (2010, Science, 328: 894–899) reported declines of lizard biodiversity due to local warming trends and altered thermal niches. Herein, we applied the Sinervo et al. (2010) physiological model to predict the local extinction risk of three species of lizard from Patagonia. Whereas the previous model used a single equation (for the extinctions of Blue Spiny Lizard (Sceloporus serrifer Cope, 1866) in the Yucatan Peninsula) relating environmental temperatures (Te) to hours of restriction (i.e., the period when lizards are forced into retreat sites because environmental temperatures are too high), we measured habitat-specific equations for the Te values of each species. We analyzed the vulnerability of Darwin’s Ground Gecko (Homonota darwinii Boulenger, 1885), Bariloche Lizard (Liolaemus pictus (Duméril and Bibron, 1837)), and Mountain Slope Lizard (Liolaemus elongatus Koslowsky, 1896) to climate change considering thermal physiological constraints on activity during the reproductive period. While Sinervo et al. (2010) predicted that the Phyllodactylidae family will not suffer from impacts of climate change, our physiological model predicted that 20% of the H. darwinii populations could become extinct by 2080. The physiological model also predicted that 15% of L. pictus populations and 26.5% of L. elongatus populations could become extinct by 2080. The most vulnerable populations are those located near the northern and eastern boundaries of their distributions.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".