How seasonality influences the thermal biology of lizards with different thermoregulatory strategies: a meta‐analysis
Bibliographic record
Abstract
ABSTRACT Ectotherms that maintain thermal balance in the face of varying climates should be able to colonise a wide range of habitats. In lizards, thermoregulation usually appears as a variety of behaviours that buffer external influences over physiology. Basking species rely on solar radiation to raise body temperatures and usually show high thermoregulatory precision. By contrast, species that do not bask are often constrained by climatic conditions in their habitats, thus having lower thermoregulatory precision. While much focus has been given to the effects of mean habitat temperatures, relatively less is known about how seasonality affects the thermal biology of lizards on a macroecological scale. Considering the current climate crisis, assessing how lizards cope with temporal variations in environmental temperature is essential to understand better how these organisms will fare under climate change. Activity body temperatures ( T b ) represent the internal temperature of an animal measured in nature during its active period (i.e. realised thermal niche), and preferred body temperatures ( T pref ) are those selected by an animal in a laboratory thermal gradient that lacks thermoregulatory costs (i.e. fundamental thermal niche). Both traits form the bulk of thermal ecology research and are often studied in the context of seasonality. In this study, we used a meta‐analysis to test how environmental temperature seasonality influences the seasonal variation in the T b and T pref of lizards that differ in thermoregulatory strategy (basking versus non‐basking). Based on 333 effect sizes from 137 species, we found that T b varied over a greater magnitude than T pref across seasons. Variations in T b were not influenced by environmental temperature seasonality; however, body size and thermoregulatory strategy mediated T b responses. Specifically, larger species were subjected to greater seasonal variations in T b , and basking species endured greater seasonal variations in T b compared to non‐basking species. On the other hand, the seasonal variation in T pref increased with environmental temperature seasonality regardless of body size. Thermoregulatory strategy also influenced T pref , suggesting that behaviour has an important role in mediating T pref responses to seasonal variations in the thermal landscape. After controlling for phylogenetic effects, we showed that T b and T pref varied significantly across lizard families. Taken together, our results support the notion that the relationship between thermal biology responses and climatic parameters can be taxon and trait dependent. Our results also showcase the importance of considering ecological and behavioural aspects in macroecological studies. We further highlight current systematic, geographical, and knowledge gaps in thermal ecology research. Our work should benefit those who aim to understand more fully how seasonality shapes thermal biology in lizards, ultimately contributing to the goal of elucidating the evolution of temperature‐sensitive traits in ectotherms.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.016 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".