Dental microwear texture analysis: technical considerations
Introduction
Dental microwear can provide important evidence for the diets of extinct species. Classically, researchers count and measure individual features on images acquired from tooth surfaces by scanning electron microscopy (SEM) (see Grine et al., 2002 for review). This is a problem for two reasons: 1) identification and measurements of individual wear features are subject to high observer error rates; and 2) the SEM produces two-dimensional representations of 3D surfaces, representations that are dependent on the instrument settings and the orientation of the specimen on the stage (see Gordon, 1988). These limitations, and the intrinsic subjectivity they evince, lead to a frustrating lack of repeatability, with high intraobserver (7%) and interobserver (9%) error rates (Grine et al., 2002). Here we describe an observer error-free approach, microwear texture analysis, which yields objective measures of surface texture that do not change with repeated measurement of a given microwear surface. Initial work (Ungar et al., 2003, Scott et al., 2005) is summarized, and new efforts are presented. These new efforts offer a more complete characterization of microwear surface textures.
The many reviews of dental microwear research show the course of progress and resulting advances over the past half century (Teaford, 1988, Teaford, 1994, Teaford, 2006, Ungar, 1998, Rose and Ungar, 1998). Early research showed that microscopic patterns of use-wear reflect jaw movements and diet (Butler, 1952, Mills, 1955, Baker et al., 1959, Dahlberg and Kinzey, 1962, Walker, 1976). While these studies were qualitative and relied on binocular light microscopy, they hinted at the potential of this approach for the reconstruction of diets and subsistence practices in past peoples and extinct mammals.
By the late 1970s, researchers began to realize that poor depth of focus and limited resolution were keeping microwear from reaching its full potential as an analytical tool, so researchers turned to the SEM with its attractive images (Walker et al., 1978, Rensberger, 1978, Ryan, 1980). Standardization of imaging techniques and quantification of individual features followed (Gordon, 1980, Gordon, 1984a, Gordon, 1984b, Gordon, 1984c, Teaford and Walker, 1984) as researchers began to count and measure scratches and pits on photomicrographs. These and other studies gave us further evidence of the potential of dental microwear for reconstructing diets of extinct species and subsistence practices of past peoples.
Still, measurement of microwear features by calipers or digitizing tablets was time-consuming, and identifications of up to hundreds of individual features on a small photomicrograph were difficult. By the late 1980s, workers were looking for more objective, repeatable methods of dental microwear analysis (Kay, 1987). These new approaches still relied on SEM photomicrographs, but attempted automated measurement through efforts to threshold out individual features or analysis by Fourier transforms. These approaches never caught on though, in part because of technological limitations at the time. Ungar (1990) proposed a compromise semiautomated procedure that required observer identification of features, but also yielded computer-based tallies and measurements. While this has become a standard of sorts, it too has been plagued by subjectivity in the identification of features, and concomitant inter- and intra-observer error (Grine et al., 2002). Another criticism of such conventional studies is that they have proved costly and time intensive (Solounias and Semprebon, 2002, Semprebon et al., 2004). Indeed, the cost and time-consuming nature of such studies has led some to propose a return to variations on low-magnification light microscopy (Solounias and Semprebon, 2002, Godfrey et al., 2004, Semprebon et al., 2004, Merceron et al., 2004a, Merceron et al., 2004b, Merceron et al., 2005a, Merceron et al., 2005b, Nelson et al., 2005, Green et al., 2005).
Another problem with more conventional analyses results from the way the SEM forms a microwear image by interactions between a specimen's surface and the electron beam. Collector type and position, specimen geometry, types of electrons used, voltage, working distance, surface tilt, and other parameters all have effects that can lead to differing images for the same surfaces (Gordon, 1988, Pastor, 1993). So, a new, repeatable, and objective approach to dental microwear analysis was needed.
Boyde and Fortelius (1991) recognized the need for a new instrument for microwear analysis some 15 years ago, and suggested that the confocal microscope, with its ability to collect true 3D surface data might offer an answer. Ungar et al. (2003) more recently coupled confocal microscopy with scale-sensitive fractal analysis (SSFA) to offer a practical approach to characterizing microwear surface textures, an approach now known as dental microwear texture analysis (Scott et al., 2005). This paper reviews dental microwear texture analysis variables already described (Scott et al., 2005), adds new variables for distinguishing microwear surfaces, and offers new examples from four species of extant primates with differing diets. Because these new techniques are not prone to observer error, we can use microwear texture analysis as a tool to assess both within and between sample variability.
Section snippets
Materials and methods
Here we present data for four monkey species with contrasting diets to demonstrate the efficacy of this approach. These include two cercopithecoids, Lophocebus albigena (n = 15) and Trachypithecus cristatus (n = 12), and two platyrrhines, Alouatta palliata (n = 11) and Cebus apella (n = 13). High-resolution replicas of M2s were made following conventional procedures. Original specimens were cleaned with acetone-soaked cotton swabs, and vinyl impressions were made using President's Jet Regular Body
Results
Table 1 shows the Spearman's rho correlations calculated between Asfc, Smc, epLsar1.8 μm, Tfv, and HAsfc9 cells for the entire sample. Low correlations were evident for Asfc with Smc, epLsar1.8 μm, Tfv, and HAsfc9 cells and for Smc with epLsar1.8 μm and HAsfc9 cells. The greatest correlation was 0.41 between Asfc (Area scale fractal complexity) and Tfv (Textural fill volume).
Utility of microwear texture analysis
The microwear texture analysis approach described here has several advantages over conventional SEM-based microwear feature analysis. First, the white-light confocal microscope is a dramatic improvement over the SEM for microwear analysis. The Sensofar Plμ can detect remarkably small changes in relief (0.005 μm), and is capable of resolving microwear scale details in three dimensions (see Fig. 7, Fig. 8). This instrument is more economical and easier to use than SEMs. Not only is it less
Conclusions
Dental microwear can clearly offer important insights about diet in both extinct species and past peoples. Conventional microwear techniques have been limited by observer error, limitations inherent in characterizing 3D surfaces in two dimensions, and high cost in time and money. Simple inspection of 3D renderings makes these limits very clear. A wear surface may be a gentle rolling terrain into which deep features are carved, and these may in turn be overlain by irregular gouges crossed by
Acknowledgements
We thank the curators of the U.S. National Museum of Natural History and the Tappen Collection at the University of Minnesota. This project was funded by the U.S. National Science Foundation.
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