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A new method for examining the co-occurrence network of fossil assemblages.
Guo, Shilong; Ma, Wang; Tang, Yunyu; Chen, Liang; Wang, Ying; Cui, Yingying; Liang, Junhui; Li, Longfeng; Zhuang, Jialiang; Gu, Junjie; Li, Mengfei; Fang, Hui; Lin, Xiaodan; Shih, Chungkun; Labandeira, Conrad C; Ren, Dong.
Afiliação
  • Guo S; College of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
  • Ma W; Department of Bioinformatics, Freshwind Biotechnology (Tianjin) Limited Company, Tianjin, 300301, PR China.
  • Tang Y; College of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
  • Chen L; College of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
  • Wang Y; Beijing Museum of Natural History, Beijing, 100050, PR China.
  • Cui Y; College of Life Sciences, South China Normal University, Guangzhou, 510631, PR China.
  • Liang J; Tianjin Natural History Museum, Tianjin, 300203, PR China.
  • Li L; Institute of Vertebrate Paleontology, College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, PR China.
  • Zhuang J; College of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
  • Gu J; College of Agronomy, Sichuan Agricultural University, Chengdu, Sichuan, 611130, PR China.
  • Li M; College of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
  • Fang H; Institute of Paleontology, Hebei GEO University, Shijiazhuang, 050031, PR China.
  • Lin X; Key Laboratory of Green Prevention and Control of Tropical Plant Diseases and Pests, Ministry of Education, School of Plant Protection, Hainan University, Haikou, 570228, PR China.
  • Shih C; College of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
  • Labandeira CC; Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC, 20013-7012, USA.
  • Ren D; College of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
Commun Biol ; 6(1): 1102, 2023 10 31.
Article em En | MEDLINE | ID: mdl-37907587
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ecossistema / Fósseis Limite: Animals País/Região como assunto: Asia Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ecossistema / Fósseis Limite: Animals País/Região como assunto: Asia Idioma: En Ano de publicação: 2023 Tipo de documento: Article