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Communication Dans Un Congrès Année : 2017

A Mathematical Model to Predict Hierarchical Rank in Macaca mulatta and M. sylvanus

Sebastian Sosa
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Brianne Beisner
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Krishna Balasubramanian
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Cédric Sueur
Peng Zhang
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Brenda Mccowan
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Résumé

Several, sometimes conflicting, explanatory frameworks have been put forward to posit inter- and intraspecific variation in non-human primate social relationships, particularly with regards to the emergence of the hierarchical structure, like the “prior attributes hypothesis” (i.e. through individuals’ intrinsic attributes), the “social dynamics hypothesis” (i.e. through processes of social behaviours), and the “ecological hypothesis” (i.e. through demographic and ecological factors). However, these hypotheses are considered non-mutually exclusive now. In the present study, we examine two individual attributes (age and matriline membership) for males and females in two macaque species ( Macaca mulatta and M. sylvanus ). The macaque genus is widely used as a biological model due to the numerous similarities (multimales, multifemales and multigenerational groups with matrilineal rank inheritance) and dissimilarities (dominance styles) across macaque species. We use a multiple hierarchical stepwise regression (MHSR) approach to build a multi-predictor model based on the “prior attributes hypothesis.” Our findings show that age and matriline membership explain most of the inter-individual variance in hierarchical rank for both sexes and both species (90.4–96.1% in female M. mulatta , 63.2–95.0% in male M. mulatta , 90.4–96.1% in female M. sylvanus , 63.2–95.0% in male M. sylvanus ), suggesting not only the potential value of the prior attributes hypothesis, but also its likely weight in the explanation of the hierarchical structure. This analytical protocol permits the comparison of hierarchical structure between sex categories within a group, and could also be viewed as a tool for inter-species hierarchical comparison. This model also highlights the necessity to consider the prior attributes hypothesis in self-organised models based on social dynamics to gain a holistic perspective of how hierarchical structures emerge.
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Dates et versions

hal-03827940 , version 1 (24-10-2022)

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  • HAL Id : hal-03827940 , version 1

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Sebastian Sosa, Brianne Beisner, Krishna Balasubramanian, Cédric Sueur, Peng Zhang, et al.. A Mathematical Model to Predict Hierarchical Rank in Macaca mulatta and M. sylvanus. 7th European Federation for Primatology Meeting. 30e Colloque de la Société Francophone de Primatologie Strasbourg, France, August 21-25, 2017, Aug 2017, Strasbourg, France. ⟨hal-03827940⟩
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