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Character-rich craniodental specimens are often the best material for identifying mammalian fossils to the genus or species level, but what can be done with the many assemblages that consist primarily of dissociated postcrania? In localities lacking typically diagnostic remains, accurate identification of postcranial material can improve measures of mammalian diversity for wider-scale studies. Astragali, in particular, are often well-preserved and have been shown to have diagnostic utility in artiodactyls. The Thousand Creek fauna of Nevada (~8 Ma) represents one such assemblage rich in postcranial material but with unknown diversity of many taxa, including camelids. We use discriminant function analysis (DFA) of eight linear measurements on the astragali of contemporaneous camelids with known taxonomic affinity to produce a training set that can then be used to assign taxa to the Thousand Creek camelid material. The discriminant function identifies, at minimum, four classes of camels: “Hemiauchenia”, Alforjas, Procamelus, and ?Megatylopus. Adding more specimens to the training set may improve certainty and accuracy for future work, including identification of camelids in other faunas of similar age. For best statistical practice and ease of future use, we recommend using DFA rather than qualitative analyses of biplots to separate and diagnose taxa. Edward Byrd Davis. University of Oregon Museum of Natural and Cultural History and Department of Geological Sciences, 1680 East 15th Avenue, Eugene, Oregon 97403. edavis@uoregon.edu Brianna K. McHorse. University of Oregon Clark Honors College and Department of Biology, 1293 University of Oregon, Eugene, Oregon 97403. Current address: Harvard University Department of Organismic and Evolutionary Biology, 26 Oxford Street, Cambridge, Massachusetts 02138. bmchorse@fas.harvard.edu

A method for improved identification of postcrania from mammalian fossil assemblages: multivariate discriminant function analysis of camelid astragali