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Data from: Multi-scale predictors of parasite risk in wild male savanna baboons (Papio cynocephalus)

Cite this dataset

Habig, Bobby et al. (2019). Data from: Multi-scale predictors of parasite risk in wild male savanna baboons (Papio cynocephalus) [Dataset]. Dryad.


Several factors are thought to shape male parasite risk in polygynous and polygynandrous mammals, including male-male competition, investment in potentially immunosuppressive hormones, and dispersal. Parasitism is also driven by processes occurring at larger scales, including host social groups and populations. To date, studies that test parasite-related costs of male behavior at all three scales—individual hosts, social groups, and the host population—remain rare. To fill this gap, we investigated multi-scale predictors of helminth parasitism in 97 male savanna baboons (Papio cynocephalus) living in the Amboseli ecosystem in Kenya over a five-year span. Controlling for multi-scale processes, we found that many of the classic indicators of male mating effort—high dominance rank, testosterone, and glucocorticoids—did not predict helminth infection risk. However, we identified two parasite-related costs associated with male behavior: (i) socially connected males exhibited higher Trichuris trichiura egg counts and greater parasite species richness than socially isolated males; and (ii) males with stable group residency exhibited higher parasite species richness than males who frequently dispersed to new social groups. At the population level, males harbored more parasites following periods of drought than rainfall. Lastly, parasites exhibited positive covariance suggesting that infection risk increases if a host already harbors one or more parasite taxa. These results indicate that multi-scale processes are important in driving male parasite risk, and that some aspects of male behavior are costly. Together, our results provide an unusually holistic perspective on the drivers of parasite risk in the context of male behaviors and life histories.

Usage notes


National Science Foundation, Award: NSF IOS 1456832


Amboseli National Park