Pandora: A new morphometric and statistical software for analysing and distinguishing cut marks on bones

Cut mark studies have experienced a useful development in the last few years. These studies have allowed us to obtain important information about human prehistory spanning from the origin of meat consumption for chronologies around 2.5 Ma, the detection of human hunting behavior during the lower Ple...

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Detalles Bibliográficos
Autores: Palomeque González, Juan Francisco, Maté-González, Miguel Ángel, Yravedra Sainz de los Terreros, José, San Juan Blazquez, María, García Vargas, Elena, Martín Perea, David Manuel, Estaca Gómez, Verónica, González Aguilera, Diego, Domínguez Rodrigo, Manuel
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:España
Institución:Universidad de Salamanca (USAL)
Repositorio:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/155114
Acceso en línea:http://hdl.handle.net/10366/155114
Access Level:acceso abierto
Palabra clave:R project
Statistics
Geometric morphometry
Taphonomy
Cut marks
Pandora software
Descripción
Sumario:Cut mark studies have experienced a useful development in the last few years. These studies have allowed us to obtain important information about human prehistory spanning from the origin of meat consumption for chronologies around 2.5 Ma, the detection of human hunting behavior during the lower Pleistocene, or even to determine the uses of diverse raw materials on carcases. Amongst the different analyses applied to the study of cut marks, there has been an increasing interest in using morphometry in order to differentiate and characterize the raw materials with which the effectors were made. These techniques have proven to be extremely useful. Nevertheless, this 3D methodology demands the use of expensive equipment and does not allow using an extensive sample, making it a complex and problematic technique. Maté-González et al. (2015) considered an alternative technique, by combining different disciplines involving geometric morphometrics, photogrammetry and multivariate statistics (multidisciplinary methodology). Here, we try to continue with this work presenting Pandora, a new open software capable of analysing a useful amount of variables from a statistical and morphometric view, accelerating and simplifying the process.