Spatio-temporal variation of bacterioplankton community structure in the Pearl River: impacts of artificial fishery habitat and physicochemical factors
Abstract Background Artificial 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 th...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2022-02-01
|
| Series: | BMC Ecology and Evolution |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12862-022-01965-3 |
| _version_ | 1818500937283534848 |
|---|---|
| author | Sheng Bi Han Lai Dingli Guo Xuange Liu Gongpei Wang Xiaoli Chen Shuang Liu Huadong Yi Yuqin Su Guifeng Li |
| author_facet | Sheng Bi Han Lai Dingli Guo Xuange Liu Gongpei Wang Xiaoli Chen Shuang Liu Huadong Yi Yuqin Su Guifeng Li |
| author_sort | Sheng Bi |
| collection | DOAJ |
| description | Abstract Background Artificial 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. Results The 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. Conclusions This 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. |
| first_indexed | 2024-12-10T20:49:24Z |
| format | Article |
| id | doaj.art-c0f90a1ab2c3474ea96cd4a78cee93e2 |
| institution | Directory Open Access Journal |
| issn | 2730-7182 |
| language | English |
| last_indexed | 2024-12-10T20:49:24Z |
| publishDate | 2022-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Ecology and Evolution |
| spelling | doaj.art-c0f90a1ab2c3474ea96cd4a78cee93e22022-12-22T01:34:09ZengBMCBMC Ecology and Evolution2730-71822022-02-0122111310.1186/s12862-022-01965-3Spatio-temporal variation of bacterioplankton community structure in the Pearl River: impacts of artificial fishery habitat and physicochemical factorsSheng Bi0Han Lai1Dingli Guo2Xuange Liu3Gongpei Wang4Xiaoli Chen5Shuang Liu6Huadong Yi7Yuqin Su8Guifeng Li9State Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen UniversityState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen UniversityState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen UniversityState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen UniversityState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen UniversityState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen UniversityState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen UniversityState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen UniversityState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen UniversityState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen UniversityAbstract Background Artificial 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. Results The 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. Conclusions This 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.https://doi.org/10.1186/s12862-022-01965-3Bacterioplankton communityBacterial diversityMicrobial ecologyArtificial fishery habitatPearl River |
| spellingShingle | Sheng Bi Han Lai Dingli Guo Xuange Liu Gongpei Wang Xiaoli Chen Shuang Liu Huadong Yi Yuqin Su Guifeng Li Spatio-temporal variation of bacterioplankton community structure in the Pearl River: impacts of artificial fishery habitat and physicochemical factors BMC Ecology and Evolution Bacterioplankton community Bacterial diversity Microbial ecology Artificial fishery habitat Pearl River |
| title | Spatio-temporal variation of bacterioplankton community structure in the Pearl River: impacts of artificial fishery habitat and physicochemical factors |
| title_full | Spatio-temporal variation of bacterioplankton community structure in the Pearl River: impacts of artificial fishery habitat and physicochemical factors |
| title_fullStr | Spatio-temporal variation of bacterioplankton community structure in the Pearl River: impacts of artificial fishery habitat and physicochemical factors |
| title_full_unstemmed | Spatio-temporal variation of bacterioplankton community structure in the Pearl River: impacts of artificial fishery habitat and physicochemical factors |
| title_short | Spatio-temporal variation of bacterioplankton community structure in the Pearl River: impacts of artificial fishery habitat and physicochemical factors |
| title_sort | spatio temporal variation of bacterioplankton community structure in the pearl river impacts of artificial fishery habitat and physicochemical factors |
| topic | Bacterioplankton community Bacterial diversity Microbial ecology Artificial fishery habitat Pearl River |
| url | https://doi.org/10.1186/s12862-022-01965-3 |
| work_keys_str_mv | AT shengbi spatiotemporalvariationofbacterioplanktoncommunitystructureinthepearlriverimpactsofartificialfisheryhabitatandphysicochemicalfactors AT hanlai spatiotemporalvariationofbacterioplanktoncommunitystructureinthepearlriverimpactsofartificialfisheryhabitatandphysicochemicalfactors AT dingliguo spatiotemporalvariationofbacterioplanktoncommunitystructureinthepearlriverimpactsofartificialfisheryhabitatandphysicochemicalfactors AT xuangeliu spatiotemporalvariationofbacterioplanktoncommunitystructureinthepearlriverimpactsofartificialfisheryhabitatandphysicochemicalfactors AT gongpeiwang spatiotemporalvariationofbacterioplanktoncommunitystructureinthepearlriverimpactsofartificialfisheryhabitatandphysicochemicalfactors AT xiaolichen spatiotemporalvariationofbacterioplanktoncommunitystructureinthepearlriverimpactsofartificialfisheryhabitatandphysicochemicalfactors AT shuangliu spatiotemporalvariationofbacterioplanktoncommunitystructureinthepearlriverimpactsofartificialfisheryhabitatandphysicochemicalfactors AT huadongyi spatiotemporalvariationofbacterioplanktoncommunitystructureinthepearlriverimpactsofartificialfisheryhabitatandphysicochemicalfactors AT yuqinsu spatiotemporalvariationofbacterioplanktoncommunitystructureinthepearlriverimpactsofartificialfisheryhabitatandphysicochemicalfactors AT guifengli spatiotemporalvariationofbacterioplanktoncommunitystructureinthepearlriverimpactsofartificialfisheryhabitatandphysicochemicalfactors |