Evidence map›Paper›PMID 37907587›Full record

ArticleCommunications biology2023

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

Shilong Guo, Wang Ma, Yunyu Tang, Liang Chen, Ying Wang, Yingying Cui, Junhui Liang, Longfeng Li, Jialiang Zhuang, Junjie Gu and 6 more

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
5.7field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  4. The modern pattern of insect herbivory predates the advent of angiosperms by 60 My.Proceedings of the National Academy of Sciences of the United States of America · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 9 institutions in 2 countries.

Shilong Guo *College of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
Wang Ma *Department of Bioinformatics, Freshwind Biotechnology (Tianjin) Limited Company, Tianjin, 300301, PR China.
Yunyu Tang *College of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
Liang ChenCollege of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
Ying WangBeijing Museum of Natural History, Beijing, 100050, PR China.
Yingying CuiCollege of Life Sciences, South China Normal University, Guangzhou, 510631, PR China.
Junhui LiangTianjin Natural History Museum, Tianjin, 300203, PR China.
Longfeng LiInstitute of Vertebrate Paleontology, College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, PR China.
Jialiang ZhuangCollege of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
Junjie GuCollege of Agronomy, Sichuan Agricultural University, Chengdu, Sichuan, 611130, PR China.
Mengfei LiCollege of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
Hui FangInstitute of Paleontology, Hebei GEO University, Shijiazhuang, 050031, PR China.
Xiaodan LinKey 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.
Chungkun ShihCollege of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
Conrad C LabandeiraCollege of Life Sciences, Capital Normal University, Beijing, 100048, PR China.
Dong RenCollege of Life Sciences, Capital Normal University, Beijing, 100048, PR China. rendong@mail.cnu.edu.cn.ORCID 0000-0001-8660-0901
Capital Normal University · CNSmithsonian Institution · USBeijing Museum of Natural History · CNGansu Agricultural University · CNHainan University · CNHebei GEO University · CNSichuan Agricultural University · CNSouth China Normal University · CNTianjin Natural History Museum · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

EcosystemFossilsAnimalsChina

Identifiers

PMID37907587
PMCPMC10618518
OpenAlexW4388046232

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.