Cassandra M. Turcotte, Audrey M. Choi, Jeffrey K. Spear, Eva M Hernandez-Janer, Edwin Dickinson, Hannah G. Taboada, Michala K. Stock, Catalina I. Villamil, Samuel E. Bauman, Cayo Biobank Research Unit, Melween I. Martinez, Lauren J. N. Brent, Noah Snyder-Mackler, Michael J. Montague, Michael L. Platt, Scott A. Williams, Susan C. Antón, James P. Higham
{"title":"用机械和形态计量学方法估算猕猴的体重:骨骼变量测试","authors":"Cassandra M. Turcotte, Audrey M. Choi, Jeffrey K. Spear, Eva M Hernandez-Janer, Edwin Dickinson, Hannah G. Taboada, Michala K. Stock, Catalina I. Villamil, Samuel E. Bauman, Cayo Biobank Research Unit, Melween I. Martinez, Lauren J. N. Brent, Noah Snyder-Mackler, Michael J. Montague, Michael L. Platt, Scott A. Williams, Susan C. Antón, James P. Higham","doi":"10.1002/ajpa.24901","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Objectives</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Materials and Methods</h3>\n \n <p>Antemortem mass measurements were compared with common skeletal dimensions from the same animals postmortem, using 115 rhesus macaques (male: <i>n</i> = 43; female: <i>n</i> = 72). Individuals were divided into training (<i>n</i> = 58) and test samples (<i>n</i> = 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.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>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).</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>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.</p>\n </section>\n </div>","PeriodicalId":29759,"journal":{"name":"American Journal of Biological Anthropology","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mechanical and morphometric approaches to body mass estimation in rhesus macaques: A test of skeletal variables\",\"authors\":\"Cassandra M. Turcotte, Audrey M. Choi, Jeffrey K. Spear, Eva M Hernandez-Janer, Edwin Dickinson, Hannah G. Taboada, Michala K. Stock, Catalina I. Villamil, Samuel E. Bauman, Cayo Biobank Research Unit, Melween I. Martinez, Lauren J. N. Brent, Noah Snyder-Mackler, Michael J. Montague, Michael L. Platt, Scott A. Williams, Susan C. Antón, James P. Higham\",\"doi\":\"10.1002/ajpa.24901\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Objectives</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Materials and Methods</h3>\\n \\n <p>Antemortem mass measurements were compared with common skeletal dimensions from the same animals postmortem, using 115 rhesus macaques (male: <i>n</i> = 43; female: <i>n</i> = 72). Individuals were divided into training (<i>n</i> = 58) and test samples (<i>n</i> = 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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>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).</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>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.</p>\\n </section>\\n </div>\",\"PeriodicalId\":29759,\"journal\":{\"name\":\"American Journal of Biological Anthropology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Biological Anthropology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/ajpa.24901\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ANTHROPOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Biological Anthropology","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ajpa.24901","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ANTHROPOLOGY","Score":null,"Total":0}
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.