HistoryTeeth Offer Clues to Human Diet Evolution
This Behind the Scenes article was provided to LiveScience in partnership with the National Science Foundation. University of Arkansas anthropology professor Peter Ungar has developed many talents during his distinguished career, spending hours crouched in forests in remote parts of the world studying monkeys, using dental techniques to create molds of teeth, and finding new ways to use modern-day technology to study the wear and tear on those teeth.Through all of these efforts, he is looking for clues as to what modern-day primates eat — and what that tells us about what our ancient human ancestors actually ate.
Most recently, Ungar and his colleagues, Frederick E. Grine of State University of New York at Stony Brook and Mark F. Teaford of
"The problem then is that you have to count and measure those features by hand, which introduces a high likelihood of human error. That's a very subjective process, and you're going to get variability between the measurements of any two researchers," Ungar said. "We needed an objective, automated, repeatable way to quantify wear on teeth."Ungar developed a way of using Geographic Information System software to create a different kind of map, using the software for dental topography, to show the mountains and valleys formed by the wear patterns on teeth. Just as GIS can be used to measure topographical features on a landscape, such as slope, elevation and aspect, Ungar found it could analyze dental features that are important to chewing and processing foods.
Specifically, the researchers used GIS to calculate slope and angularity values for each tooth; slope refers to the steepness of a tooth cusp, whereas angularity is a measure of overall jaggedness.In 2003, Ungar was able to increase the resolution of his measurements by using a white light scanning confocal microscope. The length, width and even depth information about specific features is automatically and objectively recorded by the instrument. The detailed, three-dimensional information allows researchers to determine characteristics of the surface, such as roughness and directionality of the wear using fractal analyses borrowed from mechanical engineering.
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