ArticleBMC ecology and evolution2022
Spatio-temporal variation of bacterioplankton community structure in the Pearl River: impacts of artificial fishery habitat and physicochemical factors.
Article in BMC ecology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- A review: Marine aquaculture impacts marine microbial communities.AIMS microbiology · 2024Review
- Mitogenome analysis reveals predominantly ancient Yellow River origin of population inhabiting Datong agro-pastoral ecotone along Great Wall.Molecular genetics and genomics : MGG · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial fishery habitat has been widely used in fishery resource protection and water habitat restoration. Although the bacterioplankton plays an important ecological role in fisheries ecosystems, the effect of artificial fishery habitat on bacterioplankton is not clear. In this study, high-throughput sequencing based on the 16S rRNA gene was carried out to study the characteristics of bacterioplankton community structure in artificial fishery habitat and to determine the principal environmental factors that shaped the composition, structure and function of bacterioplankton communities in an unfed aquaculture system.
resultsThe results indicated that the most dominant phyla were Proteobacteria (Alphaproteobacteria and Gammaproteobacteria), Actinobacteria, Cyanobacteria, and Bacteroidetes, which accounted for 28.61%, 28.37%, 19.79%, and 10.25% of the total abundance, respectively. The factors that cause the differences in bacterioplankton community were mainly manifested in three aspects, including the diversity of the community, the role of artificial fishery habitat, and the change of environmental factors. The alpha diversity analysis showed that the diversity and richness index of the bacterioplankton communities were the highest in summer, which indicated that the seasonal variation characteristics had a great influence on it. The CCA analysis identified that the dissolved oxygen, temperature, and ammonium salt were the dominant environmental factors in an unfed aquaculture system. The LEfSe analysis founded 37 indicator species in artificial structure areas (AS group), only 9 kinds existing in the control areas of the open-water group (CW group). Meanwhile, the KEGG function prediction analysis showed that the genes which were related to metabolism in group AS were significantly enhanced.
conclusionsThis study can provide reference value for the effect of artificial habitat on bacterioplankton community and provide fundamental information for the follow-up study of ecological benefits of artificial fishery habitat. It may be contributed to apply artificial fishery habitat in more rivers.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.