AbstractsAnthropology

Identification of closely related species is an enduring problem in zooarchaeology. This problem poses particular challenges for the Canine Surrogacy Approach, a model based on the premise that stable isotope signatures of dog skeletal remains can be used as a proxy for those of humans. Where Canis archaeological specimens (C. familiaris, C. latrans, and C. lupus) are fragmentary or recovered from variable depositional contexts, they may lack morphological characteristics commonly used in identifying these species to taxon, potentially resulting in overly broad or incorrect identifications. This study aimed to find a method for distinguishing dog, coyote, and wolf skeletal remains when DNA analysis is not feasible. The primary goal of this study is to determine whether statistical analysis conducted with readily available software on osteometrics taken with standard lab equipment could act as a reasonable substitute for DNA analysis in identifying prehistoric canid remains. A secondary facet of this research problem is the need to assess the accuracy of visual zooarchaeological identification protocols commonly employed in the analysis of archaeological canid remains; this is achieved by comparing the results of visual and statistical identification methods. The overall purpose of this research is to present a method for bolstering accurate reporting of Canis remains in California and help lay the groundwork for the more widespread use of the Canine Surrogacy Approach (CSA) here. Several factors shape the success of statistical identification of archaeological dog remains, including: the nature and size of the reference data set; the number of species included in the analysis; the morphological variability of Canis familiaris and the high degree of overlap with their wild cousins, C. lupus and C. latrans; and the effects of taphonomy and site formation history on the surface characteristics and depositional context of archaeological canid remains. Future research will better distinguish and control for the role of each of these factors. Advisors/Committee Members: Fisher, Jacob L..