3D shape analysis of grass silica short cell phytoliths : a new method for fossil classification and analysis of shape evolution

© 2020 The Authors. New Phytologist © 2020 New Phytologist Trust.

Bibliographische Detailangaben
Veröffentlicht in:The New phytologist. - 1979. - 228(2020), 1 vom: 11. Okt., Seite 376-392
1. Verfasser: Gallaher, Timothy J (VerfasserIn)
Weitere Verfasser: Akbar, Sultan Z, Klahs, Phillip C, Marvet, Claire R, Senske, Ashly M, Clark, Lynn G, Strömberg, Caroline A E
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2020
Zugriff auf das übergeordnete Werk:The New phytologist
Schlagworte:Journal Article Research Support, U.S. Gov't, Non-P.H.S. Poaceae archaeology machine learning microfossils paleobotany paleoecology phytoliths Silicon Dioxide 7631-86-9
Beschreibung
Zusammenfassung:© 2020 The Authors. New Phytologist © 2020 New Phytologist Trust.
Fossil grass silica short cell phytoliths (GSSCP) have been used to reconstruct the biogeography of Poaceae, untangle crop domestication history and detect past vegetation shifts. These inferences depend on accurately identifying the clade to which the fossils belong. Patterns of GSSCP shape and size variation across the family have not been established and current classification methods are subjective or based on a 2D view that ignores important 3D shape variation. Focusing on Poaceae subfamilies Anomochlooideae, Pharoideae, Pueliodieae, Bambusoideae and Oryzoideae, we observed in situ GSSCP to establish their orientation and imaged isolated GSSCP using confocal microscopy to produce 3D models. 3D geometric morphometrics was used to analyze GSSCP shape and size. Classification models were applied to GSSCP from Eocene sediments from Nebraska, USA, and Anatolia, Turkey. There were significant shape differences between nearly all recognized GSSCP morphotypes and between clades with shared morphotypes. Most of the Eocene GSSCP were classified as woody bamboos with some distinctive Nebraska GSSCP classified as herbaceous bamboos. 3D morphometrics hold great promise for GSSCP classification. It accounts for the complete GSSCP shape, automates size measurements and accommodates the complete range of morphotypes within a single analytical framework
Beschreibung:Date Completed 14.05.2021
Date Revised 14.05.2021
published: Print-Electronic
Citation Status MEDLINE
ISSN:1469-8137
DOI:10.1111/nph.16677