Dataset Information

Distribution patterns of dinoflagellate communities along the Songhua River.

ABSTRACT: Background:Dinoflagellates have the potential to pose severe ecological and economic damages to aquatic ecosystems. It is therefore largely needed to understand the causes and consequences of distribution patterns of dinoflagellate communities in order to manage potential environmental problems. However, a majority of studies have focused on marine ecosystems, while the geographical distribution patterns of dinoflagellate communities and associated determinants in freshwater ecosystems remain unexplored, particularly in running water ecosystems such as rivers and streams. Methods:Here we utilized multiple linear regression analysis and combined information on species composition recovered by high-throughput sequencing and spatial and environmental variables to analyze the distribution patterns of dinoflagellate communities along the Songhua River. Results:After high-throughput sequencing, a total of 490 operational taxonomic units (OTUs) were assigned to dinoflagellates, covering seven orders, 13 families and 22 genera. Although the sample sites were grouped into three distinctive clusters with significant difference (p < 0.05) in environmental variables, OTUs-based dinoflagellate communities among the three clusters showed no significant difference (p > 0.05). Among all 24 environmental factors, two environmental variables, including NO3-N and total dissolved solids (TDS), were selected as the significantly influential factors (p < 0.05) on the distribution patterns of dinoflagellate communities based on forward selection. The redundancy analysis (RDA) model showed that only a small proportion of community variation (6.1%) could be explained by both environmental (NO3-N and TDS) and dispersal predictors (watercourse distance) along the River. Variance partitioning revealed a larger contribution of local environmental factors (5.85%) than dispersal (0.50%) to the total variation of dinoflagellate communities. Discussion:Our findings indicated that in addition to the two quantifiable processes in this study (species sorting and dispersal), more unquantifiable stochastic processes such as temporal extinction and colonization events due to rainfall may be responsible for the observed geographical distribution of the dinoflagellate community along the Songhua River. Results obtained in this study suggested that deeper investigations covering different seasons are needed to understand the causes and consequences of geographical distribution patterns of dinoflagellate biodiversity in river ecosystems.

SUBMITTER: Gao Y

PROVIDER: S-EPMC6461062 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Distribution patterns of dinoflagellate communities along the Songhua River.

Gao Yangchun Y Chen Yiyong Y Xiong Wei W Li Shiguo S Zhan Aibin A

PeerJ 20190409

<h4>Background</h4>Dinoflagellates have the potential to pose severe ecological and economic damages to aquatic ecosystems. It is therefore largely needed to understand the causes and consequences of distribution patterns of dinoflagellate communities in order to manage potential environmental problems. However, a majority of studies have focused on marine ecosystems, while the geographical distribution patterns of dinoflagellate communities and associated determinants in freshwater ecosystems r ...[more]

PMID: 30993050

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Project description:Risks of pathogenic bacteria to the health of both human beings and water ecosystems have been widely acknowledged. However, traditional risk assessment methods based on fecal indicator bacteria and/or pure culture are not comprehensive at the community level, mainly owing to the limited taxonomic coverage. Here, we combined the technique of high-throughput sequencing and the concept of metacommunity to assess the potential pathogenic bacterial communities in an economically and ecologically crucial but highly polluted river-the North Canal River (NCR) in Haihe River Basin located in North China. NCR presented a significant environmental gradient, with the highest, moderate, and lowest levels of pollution in the up-, middle, and downstream. After multiple analyses, we successfully identified 48 genera, covering nine categories of potential pathogens (mainly human pathogens). The most abundant genus was Acinetobacter, which was rarely identified as a pathogen bacterium in previous studies of NCR. At the community level, we observed significant geographical variation of community composition and structure. Such a high level of geographical variation was mainly derived from differed abundance of species among sections along the river, especially the top seven Operational Taxonomic Units (OTUs). For example, relative abundance of OTU1 (Gammaproteobacteria/Acinetobacter) increased significantly from upstream towards downstream. Regarding the underlying mechanisms driving community geographical variation, environmental filtering was identified as the dominant ecological process and total nitrogen as the most influential environmental variable. Altogether, this study provided a comprehensive profile of potential pathogenic bacteria in NCR and revealed the underlying mechanisms of community succession. Owing to their high abundance and wide geographical distribution, we suggest that potential pathogens identified in this study should be incorporated into future monitoring and management programs in NCR. By revealing the correlation between environmental factors and community composition, the results obtained in this study have significant implications for early warning and risk assessment of potential pathogen bacteria, as well as management practices in highly polluted river ecosystems.

Dataset Information

Distribution patterns of dinoflagellate communities along the Songhua River.

Publications

Distribution patterns of dinoflagellate communities along the Songhua River.

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