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1.
Am J Phys Anthropol ; 174(1): 89-102, 2021 01.
Article in English | MEDLINE | ID: mdl-32845027

ABSTRACT

OBJECTIVES: In many primates, one of the most noticeable morphological developmental traits is the transition from natal fur and skin color to adult coloration. Studying the chronology and average age at such color transitions can be an easy and noninvasive method to (a) estimate the age of infants whose dates of birth were not observed, and (b) detect interindividual differences in the pace of development for infants with known birth dates. MATERIALS AND METHODS: Using a combination of photographs and field observations from 73 infant chacma baboons (Papio ursinus) of known ages, we (a) scored the skin color of six different body parts from pink to gray, as well as the color of the fur from black to gray; (b) validated our method of age estimation using photographic and field observations on an independent subset of 22 infants with known date of birth; and (c) investigated ecological, social, and individual determinants of age-related variation in skin and fur color. RESULTS: Our results show that transitions in skin color can be used to age infant chacma baboons less than 7 months old with accuracy (median number of days between actual and estimated age = 10, range = 0-86). We also reveal that food availability during the mother's pregnancy, but not during lactation, affects infant color-for-age and therefore acts as a predictor of developmental pace. DISCUSSION: This study highlights the potential of monitoring within- and between-infant variation in color to estimate age when age is unknown, and developmental pace when age is known.


Subject(s)
Hair Color/physiology , Papio ursinus/growth & development , Skin Pigmentation/physiology , Age Factors , Animals , Animals, Newborn , Anthropology, Physical , Female , Male
2.
Am J Primatol ; 74(9): 853-63, 2012 Sep.
Article in English | MEDLINE | ID: mdl-22644764

ABSTRACT

Differences in group size and habitat use are frequently used to explain the extensive variability in ranging patterns found across the primate order. However, with few exceptions, our understanding of primate ranging patterns stems from studies of single groups and both intra- and inter-specific meta-analyses. Studies with many groups and those that incorporate whole populations are rare but important for testing socioecological theory in primates. We quantify the ranging patterns of nine chacma baboon troops in a single population and use Spearman rank correlations and generalized linear mixed models to analyze the effects of troop size and human-modified habitat (a proxy for good quality habitat) on home range size, density (individuals/km(2) ), and daily path length. Intrapopulation variation in home range sizes (1.5-37.7 km(2) ), densities (1.3-12.1 baboons/km(2) ), and daily path lengths (1.80-6.61 km) was so vast that values were comparable to those of baboons inhabiting the climatic extremes of their current distribution. Both troop size and human-modified habitat had an effect on ranging patterns. Larger troops had larger home ranges and longer daily path lengths, while troops that spent more time in human-modified habitat had shorter daily path lengths. We found no effect of human-modified habitat on home range size or density. These results held when we controlled for the effects of both a single large outlier troop living exclusively in human-modified habitat and baboon monitors on our spatial variables. Our findings confirm the ability of baboons, as behaviorally adaptable dietary generalists, to not only survive but also to thrive in human-modified habitats with adjustments to their ranging patterns in accordance with current theory. Our findings also caution that studies focused on only a small sample of groups within a population of adaptable and generalist primate species may underestimate the variability in their respective localities.


Subject(s)
Behavior, Animal , Ecosystem , Papio ursinus/growth & development , Animals , Female , Geographic Information Systems , Homing Behavior , Linear Models , Male , Population Density , South Africa , Statistics, Nonparametric
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