Climate shapes patterns of sexual size and shape dimorphism across the native range of the green anole lizard,<i>Anolis carolinensis</i>(Squamata: Dactyloidae)
Bibliographic record
Abstract
Abstract Geographical variation in sexual size dimorphism (SSD) can result from the combined effects of environmental and sexual selection. To understand the determinants of SSD across geographical landscapes, we tested for relationships between SSD and climatic variables in the widespread lizard Anolis carolinensis. To distinguish alternative hypotheses for observed patterns of variation in SSD, we also examined sex-specific patterns of body size evolution and asked whether SSD was associated with certain patterns of sexual shape dimorphism. We found strong evidence for Rensch’s rule (an increase in male-biased SSD with average body size) in A. carolinensis and evidence for the reversed version of Bergmann’s rule (an increase in body size towards warmer environments) in males. Across populations, SSD was positively related to temperature; however, female body size was not related to any climatic variable, suggesting that the latitudinal gradient of SSD might be driven by a gradient in the intensity of sexual selection acting on males. Sexual size dimorphism was positively correlated with sexual dimorphism in head shape and negatively correlated with limb length dimorphism, suggesting that sexual selection in males might drive the evolution of SSD and that differences in size and limb shape between sexes might represent alternative strategies to avoid competition for the same resources.
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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".