Data from: Multi-scale predictors of parasite risk in wild male savanna baboons (Papio cynocephalus)
| Main Authors: | Habig, Bobby, Jansen, David A.W.A.M., Akinyi, Mercy Y., Gesquiere, Laurence R., Alberts, Susan C., Archie, Elizabeth A. |
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| Format: | info dataset eJournal |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4022997 |
Daftar Isi:
- 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.
- parasiteThese data underlie the results of the main model (n=652) of Habig et al. 2019, Behavioral Ecology and Sociobiology: "Multi-scale predictors of parasite risk in wild male savanna baboons (Papio cynocephalus)". The study was conducted on adult males of a wild population of baboons in Amboseli, Kenya. The data set include measures of parasitism (log Trichuris egg counts, parasite taxa richness, and presence or absence of strongyles, Abbreviata, and Streptopharagus). The dataset also includes the following predictor variables: age, ordinal dominance rank, dispersal covariates (number of groups; consecutive male residency), group size, rank stability (stable versus unstable), ratio of cycling females to adult males, total amount of rainfall (in cm) in the three months before sample collection, and the mean daily maximum temperature (°C) in the three months before sample collection.parasite_2These data underlie the results of the subset model (n=545) of Habig et al. 2019, Behavioral Ecology and Sociobiology: "Multi-scale predictors of parasite risk in wild male savanna baboons (i)". The study was conducted on adult males of a wild population of baboons in Amboseli, Kenya. The data set include measures of parasitism (log Trichuris egg counts, parasite taxa richness, and presence or absence of strongyles, Abbreviata, and Streptopharagus). The dataset also includes the following predictor variables: age, ordinal dominance rank, dispersal covariates (number of groups; consecutive male residency), group size, rank stability (stable versus unstable), ratio of cycling females to adult males, total amount of rainfall (in cm) in the three months before sample collection, mean daily maximum temperature (°C) in the three months before sample collection, fecal glucocorticoid concentrations, fecal testosterone concentrations, and male social connectedness to females.Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: NSF IOS 1456832