Parentage-based pedigree reconstruction reveals female matrilineal clusters and male-biased dispersal in nongregarious Asian great apes, the Bornean orang-utans (Pongo pygmaeus)

Authors


Natasha Arora, Fax: +41 44 635 68 04; E-mail: n.arora@aim.uzh.ch

Abstract

Philopatry and sex-biased dispersal have a strong influence on population genetic structure, so the study of species dispersal patterns and evolutionary mechanisms shaping them are of great interest. Particularly nongregarious mammalian species present an underexplored field of study: despite their lower levels of sociality compared to group-living species, interactions among individuals do occur, providing opportunities for cryptic kin selection. Among the least gregarious primates are orang-utans (genus: Pongo), in which preferential associations among females have nevertheless been observed, but for which the presence of kin structures was so far unresolved because of the equivocal results of previous genetic studies. To clarify relatedness and dispersal patterns in orang-utans, we examined the largest longitudinal set of individuals with combined genetic, spatial and behavioural data. We found that males had significantly higher mitochondrial DNA (mtDNA) variation and more unique haplotypes, thus underscoring their different maternal ancestries compared to females. Moreover, pedigree reconstruction based on 24 highly polymorphic microsatellite markers and mtDNA haplotypes demonstrated the presence of three matrilineal clusters of generally highly related females with substantially overlapping ranges. In orang-utans and possibly other nongregarious species, comparing average biparental relatedness (r) of males and females to infer sex-biased dispersal is extremely problematic. This is because the opportunistic sampling regime frequently employed in nongregarious species, combined with overlapping space use of distinct matrilineal clusters, leads to a strong downward bias when mtDNA lineage membership is ignored. Thus, in nongregarious species, correct inferences of dispersal can only be achieved by combining several genetic approaches with detailed spatial information.

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