The lizard abides: cold hardiness and winter refuges of <i>Liolaemus pictus argentinus</i> in Patagonia, Argentina
Bibliographic record
Abstract
In environments where the temperature periodically drops below zero, it is remarkable that some lizards can survive. Behaviorally, lizards can find microsites for overwintering where temperatures do not drop as much as the air temperature. Physiologically, they can alter their biochemical balance to tolerate freezing or avoid it by supercooling. We evaluated the cold hardiness of a population of Liolaemus pictus argentinus Müller and Hellmich, 1939 in the mountains of Esquel (Patagonia, Argentina) during autumn. Additionally, we assessed the thermal quality (in degree-days) of potential refuges in a mid-elevation forest (1100 m above sea level (asl)) and in the high Andean steppe (1400 m asl). We analyzed the role of urea, glucose, total proteins, and albumin as possible cryoprotectants, comparing a group of lizards gradually exposed to temperatures lower than 0 °C with a control group maintained at room temperature. However, we found no evidence to support the presence of freeze tolerance or supercooling mechanisms in this species as related to the analyzed metabolites. Instead, the low frequency of degree-days below 0 °C and temperatures never lower than −3 °C in potential refuges suggest that L. p. argentinus might avoid physiological investments (such as supercooling and freeze tolerance) by behaviorally selecting appropriate refuges to overcome cold environmental temperatures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".