Evidence map›Paper›PMID 35501499›Full record

ArticleMicrobial ecology2023

Organic Matter Decomposition in River Ecosystems: Microbial Interactions Influenced by Total Nitrogen and Temperature in River Water.

Yibo Liu, Baiyu Zhang, Yixin Zhang, Yanping Shen, Cheng Cheng, Weilin Yuan, Ping Guo

Abstract read
PubMed Publisher
In one paragraph

Article in Microbial ecology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

1 citing paper in PubMed, 12 citations in OpenAlex.

  1. Community composition and co-occurrence of free-living and particle-attached bacteria in the source region of the Ganges and Brahmaputra Rivers.International microbiology : the official journal of the Spanish Society for Microbiology · 2025
    Article
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

7 authors at 3 institutions in 2 countries.

Yibo LiuKey Laboratory of Groundwater Resources and Environment Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, People's Republic of China.
Baiyu ZhangDepartment of Civil Engineering, Faculty of Engineering and Applied Science, Memorial University, St. John' s, NL, A1B 3X5, Canada.
Yixin ZhangDepartment of Landscape Architecture, Gold Mantis School of Architecture, Soochow University, Suzhou, China.
Yanping ShenKey Laboratory of Groundwater Resources and Environment Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, People's Republic of China.
Cheng ChengKey Laboratory of Groundwater Resources and Environment Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, People's Republic of China.
Weilin YuanKey Laboratory of Groundwater Resources and Environment Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, People's Republic of China.
Ping GuoKey Laboratory of Groundwater Resources and Environment Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, People's Republic of China. guoping@jlu.edu.cn.
Jilin University · CNMemorial University of Newfoundland · CASoochow University · CN

Funding

the National Science and Technology Major Project of the Ministry of Science and Technology of China 2018ZX07111005the Science and Technology Development Program of Jilin Province 20200801071GH
6 · The paper itself

Abstract

Microbes contribute to the organic matter decomposition (OMD) in river ecosystems. This study considers two aspects of OMD in river ecosystems which have not been examined in scientific studies previously, and these are the microbial interactions in OMD and the influence of environmental factors on microbial interactions. Cotton strip (CS), as a substitute for organic matter, was introduced to Luanhe River Basin in China. The results of CS assay, microbial sequencing, and redundancy analysis (RDA) showed that CS selectively enriched bacterial and fungal groups related to cellulose decomposition, achieving cotton strip decomposition (CSD). Bacterial phylum Proteobacteria and fungal phyla Rozellomycota and Ascomycota were the dominant groups associated with CSD. Network analysis and Mantel test results indicated that bacteria and fungi on CS cooperatively formed an interaction network to achieve the CSD. In the network, modules 2 and 4 were significantly positively associated with CSD, which were considered as the key modules in this study. The key modules were mainly composed of phyla Proteobacteria and Ascomycota, indicating that microbes in key modules were the effective decomposers of CS. Although keystone taxa were not directly associated with CSD, they may regulate the genera in key modules to achieve the CSD, since some keystone taxa were linked with the microbial genera associated with CSD in the key modules. Total nitrogen (TN) and temperature in water were the dominant environmental factors positively influenced CSD. The key modules 2 and 4 were positively influenced by water temperature and TN in water, respectively, and two keystone taxa were positively associated with TN. This profoundly revealed that water temperature and TN influenced the OMD through acting on the keystone taxa and key modules in microbial interactions. The research findings help us to understand the microbial interactions influenced by environmental factors in OMD in river ecosystems.

Indexed as

EcosystemRiversBacteriaMicrobial InteractionsNitrogenTemperatureWaterNitrogenWaterCotton stripDominant environmental factorsKey modulesKeystone taxaMicrobial interactionsOrganic matter decomposition

Identifiers

PMID35501499
OpenAlexW4225262852

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.