Evidence map›Paper›PMID 35614274›Full record

ArticleEnvironmental monitoring and assessment2022

Bacterioplankton community indicators for seasonal variation in a fragmented subtropical river.

Biao Zhao, Peng Song, Wanling Yang, Yongzhan Mai, Haiyan Li, Qianfu Liu, Yanyi Zeng, Yuan Gao, Wanlin Du, Chao Wang

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental monitoring and assessment, 2022. 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
1.4field-weighted citation impact, top 20% 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, 9 citations in OpenAlex.

  1. 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

10 authors at 5 institutions in 1 country.

Biao Zhao *Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China.
Peng Song *College of Agriculture, Henan University of Science and Technology, Luoyang, 471000, China.
Wanling YangPearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China.
Yongzhan MaiPearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China.
Haiyan LiPearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China.
Qianfu LiuPearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China.
Yanyi ZengPearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China.
Yuan GaoPearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China.
Wanlin DuPearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China.
Chao WangPearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China. chaowang@prfri.ac.cn.
Chinese Academy of Fishery Sciences · CNMinistry of Agriculture and Rural Affairs · CNHenan University of Science and Technology · CNGuangzhou Experimental Station · CNKey Laboratory of Guangdong Province · CN

Funding

Guangdong Basic and Applied Basic Research Foundation 2019A1515011589Guangdong Basic and Applied Basic Research Foundation 2021A1515012079
6 · The paper itself

Abstract

In this study, spatiotemporal investigations were conducted along five cascade dams in the main channel of the North River of China during 2019 to explore bacterioplankton community indicators of water environments in a fragmented, highly regulated river. Bacterioplankton communities were good bioindicators of temporal variation in river environments, especially when considering the bacterial class level. Specifically, the most dominant bacterial classes (Gammaproteobacteria, Oxyphotobacteria, and Actinobacteria) and sub-dominant bacterial classes (Bacteroidia, Betaproteobacteria, and Acidimicrobiia) exhibited obvious temporal variation. Rainfall, water temperature (WT), water transparency (SD), and pH were all highly associated with temporal variation. In contrast, bacterioplankton indicators of spatial variation were limited to individual dominant bacterial classes for individual study periods, while rainfall, total phosphorus (TP), and pH were also associated with spatial variation. Clustering of bacterioplankton community compositions revealed that temporal differences were much stronger than spatial differences, which is consistent with most environmental parameters exhibiting obvious temporal differences, but minimal spatial differences. A possible reason for these observations could be that river fragmentation caused by cascade dams weakened spatial differences in communities, with WT, rainfall, and river runoff playing key roles in these patterns. In conclusion, bacterioplankton communities were good bioindicators of water environments in the fragmented river ecosystem of this study and their temporal variation was more apparent than their spatial variation.

Indexed as

CyanobacteriaRiversAquatic OrganismsChinaEcosystemEnvironmental BiomarkersEnvironmental MonitoringRNA, Ribosomal, 16SSeasonsWaterEnvironmental BiomarkersRNA, Ribosomal, 16SWaterCascade damIndicating functionSpatiotemporal characteristicsWater environment

Identifiers

PMID35614274
OpenAlexW4281552450

What Socratic 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 Socratic graph.