Mechanical and morphometric approaches to body mass estimation in rhesus macaques: A test of skeletal variables.

OBJECTIVES: Estimation of body mass from skeletal metrics can reveal important insights into the paleobiology of archeological or fossil remains. The standard approach constructs predictive equations from postcrania, but studies have questioned the reliability of traditional measures. Here, we examine several skeletal features to assess their accuracy in predicting body mass. MATERIALS AND METHODS: Antemortem mass measurements were compared with common skeletal dimensions from the same animals postmortem, using 115 rhesus macaques (male: n = 43; female: n = 72). Individuals were divided into training (n = 58) and test samples (n = 57) to build and assess Ordinary Least Squares or multivariate regressions by residual sum of squares (RSS) and AIC weights. A leave-one-out approach was implemented to formulate the best fit multivariate models, which were compared against a univariate and a previously published catarrhine body-mass estimation model. RESULTS: Femur circumference represented the best univariate model. The best model overall was composed of four variables (femur, tibia and fibula circumference and humerus length). By RSS and AICw, models built from rhesus macaque data (RSS = 26.91, AIC = -20.66) better predicted body mass than did the catarrhine model (RSS = 65.47, AIC = 20.24). CONCLUSION: Body mass in rhesus macaques is best predicted by a 4-variable equation composed of humerus length and hind limb midshaft circumferences. Comparison of models built from the macaque versus the catarrhine data highlight the importance of taxonomic specificity in predicting body mass. This paper provides a valuable dataset of combined somatic and skeletal data in a primate, which can be used to build body mass equations for fragmentary fossil evidence.

Quantifying the relationship between bone and soft tissue measures within the rhesus macaques of Cayo Santiago.

OBJECTIVES: Interpretations of the primate and human fossil record often rely on the estimation of somatic dimensions from bony measures. Both somatic and skeletal variation have been used to assess how primates respond to environmental change. However, it is unclear how well skeletal variation matches and predicts soft tissue. Here, we empirically test the relationship between tissues by comparing somatic and skeletal measures using paired measures of pre- and post-mortem rhesus macaques from Cayo Santiago, Puerto Rico. MATERIALS AND METHODS: Somatic measurements were matched with skeletal dimensions from 105 rhesus macaque individuals to investigate paired signals of variation (i.e., coefficients of variation, sexual dimorphism) and bivariate codependence (reduced major axis regression) in measures of: (1) limb length; (2) joint breadth; and (3) limb circumference. Predictive models for the estimation of soft tissue dimensions from skeletons were built from Ordinary Least Squares regressions. RESULTS: Somatic and skeletal measurements showed statistically equivalent coefficients of variation and sexual dimorphism as well as high epiphyses-present ordinary least square (OLS) correlations in limb lengths (R2 >0.78, 0.82), joint breadths (R2 >0.74, 0.83) and, to a lesser extent, limb circumference (R2 >0.53, 0.68). CONCLUSION: Skeletal measurements are good substitutions for somatic values based on population signals of variation. OLS regressions indicate that skeletal correlates are highly predictive of somatic dimensions. The protocols and regression equations established here provide a basis for reliable reconstruction of somatic dimension from catarrhine fossils and validate our ability to compare or combine results of studies based on population data of either hard or soft tissue proxies.