Fine-scale spatiotemporal variations in bacterial community diversity in agricultural pond water

Sci Total Environ. 2024 Mar 10:915:170143. doi: 10.1016/j.scitotenv.2024.170143. Epub 2024 Jan 17.

Abstract

Microbial communities in surface waters are affected by environmental conditions and can influence changes in water quality. To explore the hypothesis that the microbiome in agricultural waters associates with spatiotemporal variations in overall water quality and, in turn, has implications for resource monitoring and management, we characterized the relationships between the microbiota and physicochemical properties in a model irrigation pond as a factor of sampling time (i.e., 9:00, 12:00, 15:00) and location within the pond (i.e., bank vs. interior sites and cross-sectional depths at 0, 1, and 2 m). The microbial communities, which were defined by 16S rRNA gene sequencing analysis, significantly varied based on all sampling factors (PERMANOVA P < 0.05 for each). While the relative abundances of dominant phyla (e.g., Proteobacteria and Bacteroidetes) were relatively stable throughout the pond, subtle yet significant increases in α-diversity were observed as the day progressed (ANOVA P < 0.001). Key water quality properties that also increased between the morning and afternoon (i.e., pH, dissolved oxygen, and temperature) positively associated with relative abundances of Cyanobacteria, though were inversely proportional to Verrucomicrobia. These properties, among additional parameters such as bioavailable nutrients (e.g., NH3, NO3, PO4), chlorophyll, phycocyanin, conductivity, and colored dissolved organic matter, exhibited significant relationships with relative abundances of various bacterial genera as well. Further investigation of the microbiota in underlying sediments revealed significant differences between the bank and interior sites of the pond (P < 0.05 for α- and β-diversity). Overall, our findings emphasize the importance of accounting for time of day and water sampling location and depth when surveying the microbiomes of irrigation ponds and other small freshwater sources.

Keywords: 16S rRNA gene sequencing; Irrigation water; Spatiotemporal variation; Water microbiome; Water quality.

MeSH terms

  • Cross-Sectional Studies
  • Cyanobacteria* / genetics
  • Ponds* / microbiology
  • Proteobacteria / genetics
  • RNA, Ribosomal, 16S / genetics

Substances

  • RNA, Ribosomal, 16S