Subdigital adhesive pad morphology varies in relation to structural habitat use in the Namib Day Gecko
Bibliographic record
Abstract
Summary Morphological features that lead to increased locomotor performance, such as faster sprint speed, are thought to evolve in concert with habitat use. The latter depends on available habitat structure and how the animal moves within that habitat. Thus, this behavioural variation will impact how natural selection acts on locomotion and morphology. Quantifying the interplay between escape behaviour and locomotor morphology across habitats that vary in structural composition could reveal how selection acts on locomotion at local levels. Substrate features, such as incline and topographical variation, are likely key drivers of morphological and functional disparity among terrestrial animals. We investigated the impact of habitat variation and escape behaviour on morphology, including the adhesive system, of Rhoptropus afer, a diurnal and cursorial gecko from Namibia. Substrate incline and topographical variation are likely important for this pad‐bearing gecko due to the trade‐off between adhering and sprinting (i.e. using adhesion results in decreased sprint speed). We corroborate the hypothesis that the adhesive system exhibits the greatest degree of reduction in populations that utilize the flattest terrain during an escape. Our findings suggest that the adhesive apparatus is detrimental to rapid locomotion on relatively horizontal surfaces and may thus be counterproductive to the evasion of predators in such situations. A broad scale analysis of geckos would determine whether diversity of adhesive morphology is driven primarily by habitat use. Phenotypic plasticity of the adhesive system and interspecific competition are plausible candidates for driving our results. However, it is unclear whether the differences we observed have a genetic basis. Future work should focus on how variation of the adhesive system impacts downstream locomotor components such as kinematics and mechanics and how the integration of these traits is related to habitat use.
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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 | 0.001 | 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".