Stat-tracks and mediotypes: powerful tools for modern ichnology based on 3D models

This data was imported from PubMed:

Authors: Belvedere, M., Bennett, M.R., Marty, D., Budka, M., Reynolds, S.C. and Bakirov, R.

http://eprints.bournemouth.ac.uk/30285/

Journal: PeerJ

Volume: 6

Pages: e4247

ISSN: 2167-8359

DOI: 10.7717/peerj.4247

Vertebrate tracks are subject to a wide distribution of morphological types. A single trackmaker may be associated with a range of tracks reflecting individual pedal anatomy and behavioural kinematics mediated through substrate properties which may vary both in space and time. Accordingly, the same trackmaker can leave substantially different morphotypes something which must be considered in creating ichnotaxa. In modern practice this is often captured by the collection of a series of 3D track models. We introduce two concepts to help integrate these 3D models into ichnological analysis procedures. The mediotype is based on the idea of using statistically-generated three-dimensional track models (median or mean) of the type specimens to create a composite track to support formal recognition of a ichno type. A representative track (mean and/or median) is created from a set of individual reference tracks or from multiple examples from one or more trackways. In contrast, stat-tracks refer to other digitally generated tracks which may explore variance. For example, they are useful in: understanding the preservation variability of a given track sample; identifying characteristics or unusual track features; or simply as a quantitative comparison tool. Both concepts assist in making ichnotaxonomical interpretations and we argue that they should become part of the standard procedure when instituting new ichnotaxa. As three-dimensional models start to become a standard in publications on vertebrate ichnology, the mediotype and stat-track concepts have the potential to help guiding a revolution in the study of vertebrate ichnology and ichnotaxonomy.

This data was imported from Scopus:

Authors: Belvedere, M., Bennett, M.R., Marty, D., Budka, M., Reynolds, S.C. and Bakirov, R.

http://eprints.bournemouth.ac.uk/30285/

Journal: PeerJ

Volume: 2018

Issue: 1

eISSN: 2167-8359

DOI: 10.7717/peerj.4247

© 2018 Belvedere et al. Vertebrate tracks are subject to a wide distribution of morphological types. A single trackmaker may be associated with a range of tracks reflecting individual pedal anatomy and behavioural kinematics mediated through substrate properties which may vary both in space and time. Accordingly, the same trackmaker can leave substantially different morphotypes something which must be considered in creating ichnotaxa. In modern practice this is often captured by the collection of a series of 3D track models. We introduce two concepts to help integrate these 3D models into ichnological analysis procedures. The mediotype is based on the idea of using statistically-generated threedimensional track models (median or mean) of the type specimens to create a composite track to support formal recognition of a ichno type. Arepresentative track (mean and/or median) is created from a set of individual reference tracks or from multiple examples from one or more trackways. In contrast, stat-tracks refer to other digitally generated tracks which may explore variance. For example, they are useful in: understanding the preservation variability of a given track sample; identifying characteristics or unusual track features; or simply as a quantitative comparison tool. Both concepts assist in making ichnotaxonomical interpretations and we argue that they should become part of the standard procedure when instituting new ichnotaxa. As three-dimensional models start to become a standard in publications on vertebrate ichnology, the mediotype and stat-track concepts have the potential to help guiding a revolution in the study of vertebrate ichnology and ichnotaxonomy.

This data was imported from Web of Science (Lite):

Authors: Belvedere, M., Bennett, M.R., Marty, D., Budka, M., Reynolds, S.C. and Bakirov, R.

http://eprints.bournemouth.ac.uk/30285/

Journal: PEERJ

Volume: 6

ISSN: 2167-8359

DOI: 10.7717/peerj.4247

The data on this page was last updated at 04:52 on December 16, 2018.