Collaborative Research: Individual and Taxonomic Discrimination Through Laser Scan Analysis of Joint Congruence in Extant Hominoids

American Museum Natural History, New York NY

Investigators

Abstract

The allocation of fossil specimens to a taxon, and in some cases to an individual, is a frequent and important problem of paleontology. When multiple individuals of one (or more) species are recovered from a site, it is often vital to associate elements of a single individual in order to determine the number of individuals preserved, as well as examine proportions, functional adaptations and other factors. In this project, the PIs propose a relatively new approach to these problems, combining laser surface scans of opposing joint surfaces with advanced statistical analyses to examine ways to differentiate taxa and associate elements of unique individuals using a sample of extant hominoids where individuals are known. Previous studies using a laser scanner suffered from the lack of suitable computational power and statistical methodology. Delson and colleagues will build upon that work in combination with their own extensive familiarity with high-resolution scanning, geometric morphometric analysis and joint surfaces of extant and extinct catarrhine taxa. This work also has implications for analyses of forensic and archaeological accumulations of multiple-individual human remains. This study will focus on the bony components of two important joints: the elbow (humero-ulnar) and ankle (tibio-talar). Both of these joints are relatively "tight" showing a high degree of congruence where the proposed method has a higher chance of success. The elbow joint is "tighter" than the ankle, further allowing some evaluation of how tightly a joint articulates influences how well the method works. Finally, both of these joints are of functional interest among hominoids and are also well-represented in the human fossil record, the planned focus of later phases of research. Preliminary analysis of limited data has demonstrated that this basic approach can successfully discriminate between tibio-talar surfaces of different human individuals and among joints belonging to different hominoid species. The present study will collect additional data and concentrate on development of statistically powerful methods for their analysis. In addition to these questions, this work has broader impacts in that it will: 1) recruit Lehman College undergraduates from groups underrepresented in science to be research assistants; 2) enhance infrastructure through collaboration with other universities as well as British colleagues and by developing and freely distributing algorithms and software with which to analyze congruence patterns; 3) expand collaboration with computer scientists in the development of software and analytical methods; and 4) integrate research, teaching and wider dissemination of results by developing and freely distributing three-dimensional virtual models and visualizations of joint surfaces for use in teaching.