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A new method for examining the co-occurrence network of fossil assemblages

Authors :
Shilong Guo
Wang Ma
Yunyu Tang
Liang Chen
Ying Wang
Yingying Cui
Junhui Liang
Longfeng Li
Jialiang Zhuang
Junjie Gu
Mengfei Li
Hui Fang
Xiaodan Lin
Chungkun Shih
Conrad C. Labandeira
Dong Ren
Source :
Communications Biology, Vol 6, Iss 1, Pp 1-12 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

Abstract Currently, studies of ancient faunal community networks have been based mostly on uniformitarian and functional morphological evidence. As an important source of data, taphonomic evidence offers the opportunity to provide a broader scope for understanding palaeoecology. However, palaeoecological research methods based on taphonomic evidence are relatively rare, especially for body fossils in lacustrine sediments. Such fossil communities are not only affected by complex transportation and selective destruction in the sedimentation process, they also are strongly affected by time averaging. Historically, it has been believed that it is difficult to study lacustrine entombed fauna by a small-scale quadrat survey. Herein, we developed a software, the TaphonomeAnalyst, to study the associational network of lacustrine entombed fauna, or taphocoenosis. TaphonomeAnalyst allows researchers to easily perform exploratory analyses on common abundance profiles from taphocoenosis data. The dataset for these investigations resulted from fieldwork of the latest Middle Jurassic Jiulongshan Formation near Daohugou Village, in Ningcheng County of Inner Mongolia, China, spotlighting the core assemblage of the Yanliao Fauna. Our data included 27,000 fossil specimens of animals from this deposit, the Yanliao Fauna, whose analyses reveal sedimentary environments, taphonomic conditions, and co-occurrence networks of this highly studied assemblage, providing empirically robust and statistically significant evidence for multiple Yanliao habitats.

Subjects

Subjects :
Biology (General)
QH301-705.5

Details

Language :
English
ISSN :
23993642
Volume :
6
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Communications Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.faeea60b4248c3aa64d7a3ea4e48c1
Document Type :
article
Full Text :
https://doi.org/10.1038/s42003-023-05417-6