Recursive anisotropy: a spatial taphonomic study of the Early Pleistocene vertebrate assemblage of Tsiotra Vryssi, Mygdonia Basin, Greece

View Researcher's Other Codes

Disclaimer: The provided code links for this paper are external links. Science Nest has no responsibility for the accuracy, legality or content of these links. Also, by downloading this code(s), you agree to comply with the terms of use as set out by the author(s) of the code(s).

Please contact us in case of a broken link from here

Authors Recursive anisotropy: a spatial taphonomic study of the Early Pleistocene vertebrate assemblage of Tsiotra Vryssi, Mygdonia Basin, Greece
Journal/Conference Name Boreas
Paper Category , ,
Paper Abstract By applying advanced spatial statistical methods, spatial taphonomy complements the traditional taphonomic approach and enhances our understanding of biostratinomic and diagenetic processes. In this study, we elaborate on a specific aspect – spatial anisotropy – of taphonomic processes. We aim to unravel the taphonomic history of the Early Pleistocene vertebrate assemblage of Tsiotra Vryssi (Mygdonia Basin, Greece). Circular statistics are used for the fabric analysis of elongated elements; geostatistics (directional variograms), wavelet and point pattern analyses are applied for detecting anisotropy at the assemblage level. The anisotropy of magnetic susceptibility (AMS) of sedimentary magnetic minerals is also investigated. The results, integrated with preliminary remarks about the differential preservation of skeletal elements, sedimentological and micromorphological observations, suggest multiple dispersion events and recurrent spatial re-arrangement of a lag, (peri)autochthonous assemblage, consistent with the cyclical lateral switching of a braided fluvial system. Furthermore, this study offers a contribution to the building of a spatial taphonomic referential framework for the interpretation of other fossil vertebrate assemblages, including archaeo-palaeontological ones.
Date of publication 2019
Code Programming Language R
Comment

Copyright Researcher 2022