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  • 标题:Temporal and spatial variation in bacterial communities on uniform substrates in non‐wadeable rivers
  • 本地全文:下载
  • 作者:Susanna A. Wood ; Laura Biessy ; Michael A. Pingram
  • 期刊名称:Environmental DNA
  • 电子版ISSN:2637-4943
  • 出版年度:2021
  • 卷号:3
  • 期号:5
  • 页码:1023-1034
  • DOI:10.1002/edn3.227
  • 语种:English
  • 出版社:Wiley
  • 摘要:Undertaking environmental assessments on non‐wadeable rivers is challenging due to their size, depth, and water velocity. The cotton strip assay (CSA) is a functional indicator used in assessing the ecological health of non‐wadeable rivers by measuring cellulose decomposition potential. Enhancing knowledge on the microbial communities responsible for decomposition would assist in developing a microbial‐based biotic index that could complement the CSA. The aims of this study were to explore the temporal and spatial variability of bacterial communities on cotton strips, identify environmental drivers of differences, and detect potential indicator taxa. Cotton strips were deployed at 12 sites, spanning a range of water quality and catchment land uses in three separate months. Each site was placed into an ecological health category (EHC) from A (healthy) to D (poor). Metabarcoding (16S rRNA) was used to characterize bacterial communities. There was a significant interaction between month and site and between month and EHC. Higher temperatures and pH were identified as key drivers of differences in bacterial communities in February (summer) and higher levels of ammoniacal nitrogen, nitrate/nitrite nitrogen, and turbidity in August (winter). After removal of amplicon sequence variants (ASVs) in low abundance, 27 taxa indicative of EHCs were identified. ASVs associated with EHC‐A were generally negatively correlated with modified land use and nitrate/nitrite nitrogen. In contrast, ASVs associated with EHC‐D were positively correlated to modified land use and temperature. With further validation, a molecular microbial index could be developed to aid in assessing the health of non‐wadeable rivers.
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