Social bonds, social status and survival in wild baboons: a tale of two sexes

Abstract

People who are more socially integrated or have higher socio-economic status live longer. Recent studies in non-human primates show striking convergences with this human pattern: female primates with more social partners, stronger social bonds or higher dominance rank all lead longer lives. However, it remains unclear whether social environments also predict survival in male non-human primates, as it does in men. This gap persists because, in most primates, males disperse among social groups, resulting in many males who disappear with unknown fate and have unknown dates of birth. We present a Bayesian model to estimate the effects of time-varying social covariates on age-specific adult mortality in both sexes of wild baboons. We compare how the survival trajectories of both sexes are linked to social bonds and social status over the life. We find that, parallel to females, male baboons who are more strongly bonded to females have longer lifespans. However, males with higher dominance rank for their age appear to have shorter lifespans. This finding brings new understanding to the adaptive significance of heterosexual social bonds for male baboons: in addition to protecting the male's offspring from infanticide, these bonds may have direct benefits to males themselves. This article is part of the theme issue 'Evolution of the primate ageing process'.

Keywords: Bayesian model; dominance rank; mortality; primates; social relationships; time-varying covariates.

Figure 1.

Workflow of the Bayesian model and the MCMC routine. (Online version in colour.)

Figure 2.

Posterior densities of the κ parameters that measure the effects of social variables on female and male survival. White points show medians; thick black bars show 68% credible intervals; thinner black bars show 95% credible intervals of the posterior distributions. Negative effect sizes indicate that higher values of a predictor variable were associated with lower mortality risk. (Online version in colour.)

Figure 3.

Predicted effects of changes in social bond strength and dominance rank on log-mortality. The continuous lines represent the log-hazard of the Gompertz model based on the baseline parameters estimated by the Bayesian model. Lines labelled ‘low bond strength' and ‘high bond strength’ show one standard deviation of increase or decrease in DSI_F or DSI_M relative to the population mean standardized for age (solid line), and how that translates to log-mortality. The lines labelled ‘high status’ and ‘low status' show a change of one standard deviation of proportional dominance rank relative to the population mean standardized for age (solid line). (Online version in colour.)