Genetic Evidence for Male and Female Dispersal in Wild Lemur catta
Bibliographic record
Abstract
Lemur catta has traditionally been considered a species with male-biased dispersal; however, occasional female dispersal occurs. Using molecular data, we evaluated dispersal patterns in 2 L. catta populations in southwestern Madagascar: Tsimanampesotse National Park (TNP) and Bezà Mahafaly Special Reserve (BMSR). We also investigated the genetic differentiation between the populations and dispersal partner relatedness. Results showed minor genetic differentiation between the populations (ϴ(ST) = 0.039), which may indicate gene flow historically occurring in this region, made possible by the presence of L. catta groups between the sites. Different patterns of sex-biased dispersal were found between the sites using corrected assignment indices: male-biased dispersal in TNP, and a lack of sex-biased dispersal in BMSR. Observational evidence of female dispersal in BMSR supports these results and may imply intense female resource competition in and around BMSR, because small groups of 2-3 females have been observed dispersing within BMSR and entering the reserve from outside. These dispersing groups largely consisted of mothers transferring with daughters, although we have an aunt-niece pair transferring together. Genetic data suggest that males also transfer with relatives. Our data demonstrate that dispersal partners consist of same-sexed kin for L. catta males and females, highlighting the importance of kin selection.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".