Sex-specific microhabitat use is associated with sex-biased thermal physiology in <i>Anolis</i> lizards
Bibliographic record
Abstract
If fitness optima for a given trait differ between males and females in a population, sexual dimorphism may evolve. Sex-biased trait variation may affect patterns of habitat use, and if the microhabitats used by each sex have dissimilar microclimates, this can drive sex-specific selection on thermal physiology. Nevertheless, tests of differences between the sexes in thermal physiology are uncommon, and studies linking these differences to microhabitat use or behavior are even rarer. We examined microhabitat use and thermal physiology in two ectothermic congeners that are ecologically similar but differ in their degree of sexual size dimorphism. Brown anoles (Anolis sagrei) exhibit male-biased sexual size dimorphism and live in thermally heterogeneous habitats, whereas slender anoles (Anolis apletophallus) are sexually monomorphic in body size and live in thermally homogeneous habitats. We hypothesized that differences in habitat use between the sexes would drive sexual divergence in thermal physiology in brown anoles, but not slender anoles, because male and female brown anoles may be exposed to divergent microclimates. We found that male and female brown anoles, but not slender anoles, used perches with different thermal characteristics and were sexually dimorphic in thermal tolerance traits. However, field-active body temperatures and behavior in a laboratory thermal arena did not differ between females and males in either species. Our results suggest that sexual dimorphism in thermal physiology can arise from phenotypic plasticity or sex-specific selection on traits that are linked to thermal tolerance, rather than from direct effects of thermal environments experienced by males and females.
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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 | 0.001 | 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".