Vulnerability to global warming of the critically endangered Añelo Sand Dunes Lizard (<i>Liolaemus cuyumhue</i>) from the Monte Desert, Patagonia Argentina
Bibliographic record
Abstract
The body temperature of lizards is strongly influenced by the thermal quality of microhabitats, exploiting the favourable environmental temperatures, and avoiding exposure to extreme thermal conditions. For these reasons, reptile populations are considered to be especially vulnerable to changes in environmental temperatures produced by climate change. Here, we study the thermal physiology of the critically endangered Añelo Sand Dunes Lizard (Liolaemus cuyumhue Avila, Morando, Perez and Sites, 2009). We hypothesise that (i) there is a thermal coadaptation between optimal temperature for locomotor performance of L. cuyumhue and its thermal preference; (ii) L. cuyumhue lives in an environment with low thermal quality; and (iii) a rise in environmental temperatures due to global warming will impose a decrement in locomotor speed represented by lower warming tolerance and narrower thermal safety margins, increasing their already high vulnerability. We recorded field body temperatures (T b), preferred body temperatures (T pref), the operative temperature (T e), and the thermal sensitivity of locomotion at different body temperatures. Our results indicate that this lizard is not currently under environmental stress or exceeding its thermal limits, but that it is thermoregulating below T pref to avoid overheating, and that an increase in environmental temperature higher than 3.5 °C will strongly affect the use of microhabitats with direct sun exposure.
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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 | 0.000 |
| 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) | 0.001 | 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".