Numerical taxonomy of Ginkgophyta fossils in China. (3rd October 2022)

• Record Type: Journal Article
• Authors: Wang, Jing-Jing; Xin, Cun-Lin; Wang, Lu-Han; Zhang, Ya-Mei; Jiao, Zhi-Peng; Di, Guo-Yun; Liu, Song-Xin
• Is Part Of: Historical biology. Volume 34:Number 10(2022)
• Page Start: 2037
• Page End: 2052
• Publication Date: 2022-10-03
• Subjects: Ginkgophyta -- numerical taxonomy -- bayes discriminant analysis -- china; Paleobiology -- Periodicals; Biology -- Periodicals; Evolution -- Periodicals; Paleontology -- Periodicals; Biology -- Periodicals; Paleontology -- Periodicals; Evolution -- Periodicals; 560.5
• DOI: 10.1080/08912963.2021.1999939
• Languages: English
• ISSNs: 0891-2963

Abstract

ABSTRACT: The categories of Ginkgophyta fossil plants are varied and distributed all over the world. Due to wide variations in leaf division along with the relatively similar epidermal structure between genera and species, it is difficult to identify Ginkgophyta fossils accurately. At this point, the current study sheds light on the quantitative numerical taxonomy of these plant fossils, depending on characterisation of fossil morphology and epidermal microstructures. Through principal component analysis and correlation analysis of specific characters, 15 traits are determined as the key characters in the identification of Ginkgophyta fossils. Cluster analysis was also used to divide the operational taxonomic units into 3 categories and 16 representative groups, which mostly correspond to the traditional classification, with some inconsistencies. Consequently, 8 genera of Ginkgophyta fossils are established as two new taxa: Ginkgophyllum, Rhipidopsis, Sinophyllum, Psygmophyllum and Pseudotorellia, Vittifoliolum, Eretmophyllum, Glossophyllum . In addition, Dicranophyllum should be assigned to Coniferophytina, and Saportaea nervosa can be temporarily attributed to Ginkgo .Finally, the Bayes discriminant model was established for the 38 species of Ginkgophyta fossil plants in 7 genera with relatively certain classification positions, and the discriminant model was tested using literature data. It is believed that the discriminant model has certain accuracy and can be applied to the classification and identification of Ginkgophyta fossil plants in the future.