Genetic evidence for male‐biased dispersal in the<scp>Q</scp>inghai toad‐headed agamid<i><scp>P</scp>hrynocephalus vlangalii</i>and its potential link to individual social interactions
Bibliographic record
Abstract
Sex-biased dispersal has profound impacts on a species' biology and several factors have been attributed to its evolution, including mating system, inbreeding avoidance, and social complexity. Sex-biased dispersal and its potential link to individual social interactions were examined in the Qinghai toad-headed agamid (Phrynocephalus vlangalii). We first determined the pattern of sex-biased dispersal using population genetic methods. A total of 345 specimens from 32 sites in the Qaidam Basin were collected and genotyped for nine microsatellite DNA loci. Both individual-based assignment tests and allele frequency-based analyses were conducted. Females revealed much more genetic structure than males and all results were consistent with male-biased dispersal. First-generation migrants were also identified by genetic data. We then examined eight social interaction-related morphological traits and explored their potential link to sex-biased dispersal. Female residents had larger heads and longer tails than female migrants. The well-developed signal system among females, coupled with viviparity, might make remaining on natal sites beneficial, and hence promote female philopatry. Dominant females with larger heads were more likely to stay. Contrary to females, male migrants had larger heads and belly patches than residents, suggesting that dispersal might confer selective advantages for males. Such advantages may include opportunities for multiple mating and escaping from crowded sites. Large belly patches and several other morphological traits may assist their success in obtaining mates during dispersal. Furthermore, a relatively high relatedness (R = 0.06) among females suggested that this species might have rudimentary social structure. Case studies in "less" social species may provide important evidence for a better understanding of sex-biased dispersal.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".