Correlates of extinction risk in squamate reptiles: the relative importance of biology, geography, threat and range size
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Aim Evaluating the relative roles of biological traits and environmental factors that predispose species to an elevated risk of extinction is of fundamental importance to macroecology. Identifying species that possess extinction‐promoting traits allows targeted conservation action before precipitous declines occur. Such analyses have been carried out for several vertebrate groups, with the notable exception of reptiles. We identify traits correlating with high extinction risk in squamate reptiles, assess whether these differ with geography, taxonomy and threats, and make recommendations for future Red List assessments. Location Global. Methods We collected data on biological traits and environmental factors for a representative sample of 1139 species of squamate reptiles. We used phylogenetically controlled regression models to identify general correlates of extinction risk, threat‐specific correlates of risk and realm‐specific correlates of risk. We also assessed the relative importance of range size versus other factors through multiplicative bivariate models, partial regressions and variance partitioning. Results Range size was the most important predictor of extinction risk, reflecting the high frequency of reptiles assessed under range‐based IUCN criteria. Habitat specialists occupying accessible ranges were at a greater risk of extinction: although these factors never contributed more than 10% to the variance in extinction risk, they showed significant interactions with range size. The predictive power of our global models ranged from 23% to 29%. The general overall pattern remained the same among geographical, taxonomic and threat‐specific data subsets. Main conclusions Proactive conservation requires shortcuts to identify species at high risk of extinction. Regardless of location, squamate reptiles that are range‐restricted habitat specialists living in areas highly accessible to humans are likely to become extinct first. Prioritizing species that exhibit such traits could forestall extinction. Integration of data sources on human pressures, such as accessibility of species ranges, may aid robust and time‐efficient assessments of species extinction risk.
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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 | 0.002 |
| 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 | 0.000 |
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 it