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Methods for inferring paleohabitats from the functional morphology of bovid phalanges
Institution:1. School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85282, USA;2. School of Social Science, Archaeology Program, University of Queensland, Brisbane QLD 4072, Australia;3. Paleoanthropology and Paleoenvironment Program, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia;4. Department of Anatomical Sciences, T8-023 Health Sciences Center, Stony Brook University, Stony Brook, NY 11794-8081, USA
Abstract:The functional morphology of postcranial remains can be used to infer habitat preference. This approach is typically considered an “ecomorphological” method, and has frequently been applied to bovid postcranial remains. Methods for predicting habitat preference from bovid postcrania currently exist for femora, metapodials, and astragali. Here we describe three methods for predicting paleohabitats using measurements of African bovid phalanges (proximal, intermediate, and distal). The proximal phalanx method correctly predicted the habitat preference for 130 of 183 modern bovid specimens (71.0%, 2.8 times better than chance, p < 0.0001). The intermediate phalanx method correctly predicted the habitat preference for 115 of 163 modern bovid specimens (70.6%, 2.8 times better than chance, p < 0.0001). The distal phalanx method correctly predicted the habitat preference for 87 of 122 modern bovid specimens (71.3%, 2.8 times better than chance, p < 0.0001). These accuracies compare well with those of existing such methods (1.8–3.4 times better than chance). Analysis of the probabilities associated with the habitat predictions allows confidence thresholds to be established that identify specific predictions which have <5% chance of being in error. This raises the effective accuracy of the methods to 95%. Extensive exploration and manipulation of the underlying data demonstrate that the habitat predictions are generally robust, and are relatively independent of body weight, taxonomy, and sample composition. These methods are broadly applicable, relatively accurate, and can be used to generate independent predictions of habitat from different elements, and thus constitute a useful approach to inferring past environments.
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