Evidence map›Paper›PMID 36360826›Full record

ArticleInternational journal of environmental research and public health2022

Changes in Microeukaryotic Communities in the Grand Canal of China in Response to Floods.

Wei Cai, Huiyu Li, Xin Wen, Huang Huang, Guwang Chen, Haomiao Cheng, Hainan Wu, Zhe Piao

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Wei CaiCollege of Environmental Science and Engineering, Yangzhou University, Huayang West Road #196, Yangzhou 225009, China.ORCID 0000-0003-3640-2899
Huiyu LiCollege of Environmental Science and Engineering, Yangzhou University, Huayang West Road #196, Yangzhou 225009, China.
Xin WenCollege of Environmental Science and Engineering, Yangzhou University, Huayang West Road #196, Yangzhou 225009, China.
Huang HuangCollege of Environmental Science and Engineering, Yangzhou University, Huayang West Road #196, Yangzhou 225009, China.
Guwang ChenCollege of Environmental Science and Engineering, Yangzhou University, Huayang West Road #196, Yangzhou 225009, China.
Haomiao ChengCollege of Environmental Science and Engineering, Yangzhou University, Huayang West Road #196, Yangzhou 225009, China.ORCID 0000-0003-4695-1875
Hainan WuCollege of Environmental Science and Engineering, Yangzhou University, Huayang West Road #196, Yangzhou 225009, China.
Zhe PiaoCollege of Environmental Science and Engineering, Yangzhou University, Huayang West Road #196, Yangzhou 225009, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Floods are frequent natural disasters and could have serious impacts on aquatic environments. Eukaryotic communities in artificial canals influenced by floods remain largely unexplored. This study investigated the spatiotemporal variabilities among eukaryotes in response to floods in the Grand Canal, China. Generally, 781,078 sequence reads were obtained from 18S rRNA gene sequencing, with 304,721 and 476,357 sequence reads detected before and after flooding, respectively. Sediment samples collected after the floods exhibited a higher degree of richness and biodiversity but lower evenness than those before the floods. The eukaryotic communities changed from Fungi-dominated before floods to Stramenopile-dominated after floods. The spatial turnover of various species was the main contributor to the longitudinal construction of eukaryotes both before the floods (

Indexed as

BiodiversityFloodsChinaEukaryotaHumansassembly mechanicsdistribution and structureeukaryotic communitiesflood influencefunctional analysisthe Grand Canal

Identifiers

PMID36360826
PMCPMC9655333

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Registered trials

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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.