{"data":{"id":"10.6084/m9.figshare.c.4438787.v1","type":"dois","attributes":{"doi":"10.6084/m9.figshare.c.4438787.v1","prefix":"10.6084","suffix":"m9.figshare.c.4438787.v1","identifiers":[{"identifier":"https://doi.org/10.6084/m9.figshare.c.4438787.v1","identifierType":"DOI"}],"alternateIdentifiers":[{"alternateIdentifierType":"DOI","alternateIdentifier":"https://doi.org/10.6084/m9.figshare.c.4438787.v1"}],"creators":[{"name":"ARMAN, Samuel D.","nameType":"Personal","givenName":"Samuel D.","familyName":"ARMAN","affiliation":[],"nameIdentifiers":[]},{"name":"Prowse, Thomas A. A.","nameType":"Personal","givenName":"Thomas A. A.","familyName":"Prowse","affiliation":[],"nameIdentifiers":[]},{"name":"Couzens, Aidan M. C.","nameType":"Personal","givenName":"Aidan M. C.","familyName":"Couzens","affiliation":[],"nameIdentifiers":[]},{"name":"Ungar, Peter S.","nameType":"Personal","givenName":"Peter S.","familyName":"Ungar","affiliation":[],"nameIdentifiers":[]},{"name":"Prideaux, Gavin J.","nameType":"Personal","givenName":"Gavin J.","familyName":"Prideaux","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Supplementary material from \"Incorporating intraspecific variation into dental microwear texture analysis\""}],"publisher":"Figshare","container":{},"publicationYear":2019,"subjects":[{"subject":"Evolutionary Biology"},{"subject":"FOS: Biological sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"111602 Human Biophysics","subjectScheme":"FOR"},{"subject":"FOS: Basic medicine","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"90301 Biomaterials","subjectScheme":"FOR"},{"subject":"FOS: Medical engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"80109 Pattern Recognition and Data Mining","subjectScheme":"FOR"},{"subject":"FOS: Computer and information sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2019-03-19","dateType":"Created"},{"date":"2019-03-19","dateType":"Updated"},{"date":"2019","dateType":"Issued"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"Collection","resourceType":"Collection","resourceTypeGeneral":"Collection"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1098/rsif.2018.0957","relatedIdentifierType":"DOI"},{"relationType":"IsIdenticalTo","relatedIdentifier":"10.6084/m9.figshare.c.4438787","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"CC BY 4.0","rightsUri":"https://creativecommons.org/licenses/by/4.0"}],"descriptions":[{"description":"Dental microwear texture analysis (DMTA) quantifies microscopic scar or wear patterns left on teeth by different foods or extraneous ingested items such as grit. It can be a powerful tool for deducing the diets of extinct mammals. Here we investigate how intraspecific variation in the dental microwear of macropodids (kangaroos and their close relatives) can be used to maximize the dietary signal inferable from an inherently limited fossil record. We demonstrate significant intraspecific variation for every factor considered here for both scale-sensitive fractal analysis and International Organization for Standardization surface texture analysis variables. Intraspecific factors were then incorporated into interspecific (dietary) analyses through the use of Linear Mixed Effects modelling, incorporating Akaike's Information Criterion to compare models, and testing models through independent cross-validation. This revealed that for each DMTA variable only a small number of intraspecific factors need to be included to improve differentiation between species. Including \u003ci\u003especimen\u003c/i\u003e as a random factor accounted for stochastic inter-individual variation, and \u003ci\u003efacet\u003c/i\u003e, incorporated effects of sampling location. Intraspecific effects of \u003ci\u003eecoregion, microscope, tooth\u003c/i\u003e position and \u003ci\u003ewear\u003c/i\u003e were often but not universally important. We conclude that models of microwear data that include intraspecific variation allow for broader sampling and so can potentially improve the resolution of dietary reconstructions.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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