AME 75:187-205 (2015)  -  DOI: https://doi.org/10.3354/ame01758

ABSTRACT: Microbes drive chemical cycling and productivity within river ecosystems, but their influence may shift when intense allochthonous inputs accompany high freshwater inflow (flood) events. Investigating how floods influence microbial processes is fundamentally important for our understanding of river ecology, but is generally overlooked. We analysed bacterioplankton community composition (BCC) and abundance over 4 mo following an enormous flood event in the Hunter River, Australia, that resulted in a major fish kill. Concentrations of dissolved organic carbon (DOC) and inorganic nutrients (N and P) were up to 3 times higher during the flood event compared to prior and subsequent months. Bacterial cell abundances were up to 10 times higher at impacted sites during the flood event. Using Automated Ribosomal Intergenic Spacer Analysis we found significant shifts in BCC between the flood impacted month and subsequent months (p < 0.05). Distance linear modelling indicated that DOC and dissolved N and P correlated most strongly with BCC patterns during the high inflow, whereas community dynamics correlated most strongly with nitrogen oxides and ammonium during the river’s recovery phase. 16S rRNA amplicon pyrosequencing revealed that common soil-associated and facultative anaerobic genera of Proteobacteria were most dominant during the flood period, suggesting that a proportion of the bacterial community observed during this event were potentially inactive soil microbes transported into the river via terrestrial runoff. During the recovery period, Cyanobacteria and freshwater-associated genera of Actinobacteria and Proteobacteria became dominant in 16S rRNA pyrosequencing profiles. These observations indicate that allochthonous nutrients delivered via floods can significantly stimulate bacterial growth, underpinning substrate-controlled succession of bacterial communities and ultimately shaping the ecology within river ecosystems.

KEY WORDS: Bacterioplankton · ARISA · Lotic ecology · Network analyses