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dc.contributor.authorTurcotte, CM
dc.contributor.authorChoi, AM
dc.contributor.authorSpear, JK
dc.contributor.authorHernandez-Janer, EM
dc.contributor.authorDickinson, E
dc.contributor.authorTaboada, HG
dc.contributor.authorStock, MK
dc.contributor.authorVillamil, CI
dc.contributor.authorBauman, SE
dc.contributor.authorCayo Biobank Research Unit
dc.contributor.authorMartinez, MI
dc.contributor.authorBrent, LJN
dc.contributor.authorSnyder-Mackler, N
dc.contributor.authorMontague, MJ
dc.contributor.authorPlatt, ML
dc.contributor.authorWilliam, SA
dc.contributor.authorAnton, SC
dc.contributor.authorHigham, JP
dc.date.accessioned2024-03-14T12:05:14Z
dc.date.issued2024-03-06
dc.date.updated2024-03-06T11:13:04Z
dc.description.abstractObjectives 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.en_GB
dc.description.sponsorshipNational Science Foundationen_GB
dc.description.sponsorshipL.S.B. Leakey Foundationen_GB
dc.description.sponsorshipUniversity of Puerto Ricoen_GB
dc.description.sponsorshipNational Institutes of Health (NIH)en_GB
dc.identifier.citationArticle e24901en_GB
dc.identifier.doihttps://doi.org/10.1002/ajpa.24901
dc.identifier.grantnumberBCS-1754024en_GB
dc.identifier.grantnumberBCS-1648676en_GB
dc.identifier.grantnumberBCS-1800558en_GB
dc.identifier.grantnumberR01-AG060931en_GB
dc.identifier.grantnumberP40-OD012217en_GB
dc.identifier.urihttp://hdl.handle.net/10871/135553
dc.identifierORCID: 0000-0002-1202-1939 (Brent, Lauren)
dc.language.isoenen_GB
dc.publisherWileyen_GB
dc.rights.embargoreasonUnder embargo until 6 March 2025 in compliance with publisher policyen_GB
dc.rights© 2024 Wiley Periodicals LLC.en_GB
dc.subjectbody compositionen_GB
dc.subjectmorphometricsen_GB
dc.subjectOLS regressionen_GB
dc.subjectsoft tissue reconstructionen_GB
dc.subjectweight distributionen_GB
dc.titleMechanical and morphometric approaches to body mass estimation in rhesus macaques: A test of skeletal variablesen_GB
dc.typeArticleen_GB
dc.date.available2024-03-14T12:05:14Z
dc.identifier.issn2692-7691
dc.descriptionThis is the author accepted manuscript. The final version is available from Wiley via the DOI in this recorden_GB
dc.descriptionData availability statement: The data that supports the findings of this study are available in the supplementary material of this articleen_GB
dc.identifier.journalAmerican Journal of Biological Anthropologyen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2024-01-13
dcterms.dateSubmitted2023-07-05
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2024-03-06
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2024-03-06T11:13:07Z
refterms.versionFCDAM
refterms.dateFOA2025-03-06T00:00:00Z
refterms.panelAen_GB
refterms.dateFirstOnline2024-03-06


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