Abstract Title
Dogs by Number: Building an Analytical Matrix for Canid Osteological Identification
Additional Funding Sources
The project described was supported by the Ronald E. McNair Post-Baccalaureate Achievement Program through the U.S. Department of Education under Award No. P217A170273.
Abstract
The relationship between humans and canids is temporally deep and complex. Skeletal remains of canids appear in paleontological and archaeological records throughout the world. However, accurate identification of canid species from skeletal elements is challenging as they are often incomplete, highly fragmentary, and absent of diagnostic features. Presently, canid species from prehistoric contexts are identified using subjective macroscopic observations of morphological traits. Misidentification of species inhibits interpretations of canid evolution, behavior, and human interaction in the past. Therefore, objective and statistical standards are essential.
This study builds an analytical matrix based upon size variation of skeletal elements of four canid species; Canis lupus, Canis latrans, Canis familiaris, and Vulpes vulpes. Fifteen measurements were taken from radii, femora, and mandibles (N=327) from prehistoric and modern samples of each species. Principle component analysis (PCA) and MANOVA were performed using all measurements. Results of PCA show distinct clustering, indicating size variation between canid species. Similarly, MANOVA validated a significant difference in measures between species. Therefore, applying metric analyses as vectors using these three skeletal elements are useful for clustering identification of canid species. Metrics can serve as a resource for understanding canid evolution and domestication in the past.
Dogs by Number: Building an Analytical Matrix for Canid Osteological Identification
The relationship between humans and canids is temporally deep and complex. Skeletal remains of canids appear in paleontological and archaeological records throughout the world. However, accurate identification of canid species from skeletal elements is challenging as they are often incomplete, highly fragmentary, and absent of diagnostic features. Presently, canid species from prehistoric contexts are identified using subjective macroscopic observations of morphological traits. Misidentification of species inhibits interpretations of canid evolution, behavior, and human interaction in the past. Therefore, objective and statistical standards are essential.
This study builds an analytical matrix based upon size variation of skeletal elements of four canid species; Canis lupus, Canis latrans, Canis familiaris, and Vulpes vulpes. Fifteen measurements were taken from radii, femora, and mandibles (N=327) from prehistoric and modern samples of each species. Principle component analysis (PCA) and MANOVA were performed using all measurements. Results of PCA show distinct clustering, indicating size variation between canid species. Similarly, MANOVA validated a significant difference in measures between species. Therefore, applying metric analyses as vectors using these three skeletal elements are useful for clustering identification of canid species. Metrics can serve as a resource for understanding canid evolution and domestication in the past.
Comments
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