High‐resolution climate data reveal an increasing risk of warming‐driven activity restriction for diurnal and nocturnal lizards
Bibliographic record
Abstract
Abstract Widespread species experience a variety of climates across their distribution, which can structure their thermal tolerance, and ultimately, responses to climate change. For ectotherms, activity is highly dependent on temperature, its variability and availability of favourable microclimates. Thermal exposure and tolerance may be structured by the availability and heterogeneity of microclimates for species living along temperature and/or precipitation gradients – but patterns and mechanisms underlying such gradients are poorly understood. We measured critical thermal limits (CTmax and CTmin) for five populations of two sympatric lizard species, a nocturnal gecko (Chondrodactylus bibronii) and a diurnal skink (Trachylepis variegata) and recorded hourly thermal variation for a year in three types of microclimate relevant to the activity of lizards (crevice, full sun and partial shade) for six sites across a precipitation gradient. Using a combination of physiological and modelling approaches, we derived warming tolerance for the present and the end of the century. In the present climate, we found an overall wider thermal tolerance for the nocturnal species relative to the diurnal species, and no variation in CTmax but variable CTmin along the precipitation gradient for both species. However, warming tolerances varied significantly over the course of the day, across months and microhabitats. The diurnal skink was most restricted in its daily activity in the three driest sites with up to six daily hours of restricted activity in the open (i.e. outside refugia) during the summer months, while the impacts for the nocturnal gecko were less severe, due to its higher CTmax and night activity. With climate change, lizards will experience more months where activity is restricted and increased exposure to high temperatures even within the more sheltered microhabitats. Together our results highlight the importance of considering the relevant spatiotemporal scale and habitat for understanding the thermal exposure of diurnal and nocturnal species.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".