RESUMO
OBJECTIVES: Grooming has important utilitarian and social functions in primates but little is known about grooming and its functional analogues in traditional human societies. We compare human grooming to typical primate patterns to test its hygienic and social functions. MATERIALS AND METHODS: Bayesian phylogenetic analyses were used to derive expected human grooming time given the potential associations between grooming, group size, body size, terrestriality, and several climatic variables across 69 primate species. This was compared against observed times dedicated to grooming, other hygienic behavior, and conversation among the Maya, Pumé, Sanöma, Tsimane', Yanomamö, and Ye'kwana (mean number of behavioral scans = 23,514). RESULTS: Expected grooming time for humans was 4% (95% Credible Interval = 0.07%-14%), similar to values observed in primates, based largely on terrestriality and phylogenetic signal (mean λ = 0.56). No other covariates strongly associated with grooming across primates. Observed grooming time across societies was 0.8%, lower than 89% of the expected values. However, the observed times dedicated to any hygienic behavior (3.0%) or "vocal grooming," that is conversation (7.3%), fell within the expected range. CONCLUSIONS: We found (i) that human grooming may be a (recent) phylogenetic outlier when defined narrowly as parasite removal but not defined broadly as personal hygiene, (ii) there was no support for thermoregulatory functions of grooming, and (iii) no support for the "vocal grooming" hypothesis of language having evolved as a less time-consuming means of bonding. Thus, human grooming reflects decreased hygienic needs, but similar social needs compared to primate grooming.
Assuntos
Asseio Animal/fisiologia , Primatas/fisiologia , Comportamento Social , Animais , Antropologia Física , Teorema de Bayes , Evolução Biológica , Humanos , Indígenas Sul-Americanos , Idioma , Modelos Estatísticos , Filogenia , América do SulRESUMO
Behavioral ecologists have recently begun using multilevel modeling for the analysis of social behavior. We present a multilevel modeling formulation of the Social Relations Model that is well suited for the analysis of dyadic network data. This model, which we adapt for count data and small datasets, can be fitted using standard multilevel modeling software packages. We illustrate this model with an analysis of meal sharing among Ye'kwana horticulturalists in Venezuela. In this setting, meal sharing among households is predicted by an association index, which reflects the amount of time that members of the households are interacting. This result replicates recent findings that interhousehold food sharing is especially prevalent among households that interact and cooperate in multiple ways. We discuss opportunities for human behavioral ecologists to expand their focus to the multiple currencies and cooperative behaviors that characterize interpersonal relationships in preindustrial societies. We discuss possible extensions to this statistical modeling approach and applications to research by human behavioral ecologists and primatologists.