Stream Microbial Communities as Potential Indicators of River and Landscape Disturbance in North-Central Arkansas

In the past decade, 29 shale basins have been actively developed across 20 states for extraction of natural gas (NG) via horizontal drilling/hydraulic fracturing (=fracking). This includes ~5000 wells within the Fayetteville shale of north-central Arkansas. Development often impacts both river- and landscapes, and management requires catchment-level evaluations over time, with organismal presence/absence as indicators. For this study next-generation sequencing was used to identify/characterize microbial communities within biofilm of eight Arkansas River tributaries, so as to gauge potential catchment influences. Streams spanned a gradient of landscape features and hydrological flows, with four serving as 'potentially impacted catchment zones' (PICZ) and four as 'minimally impacted catchment zones' (MICZ). Overall, 46 bacterial phyla and 141 classes were identified, with 24 phyla (52%) and 54 classes (38%) extending across samples. A principal coordinate analysis arrayed samples according to stream order, suggesting a relationship between communities and gradients. With regard to river- and landscape disturbance, three preliminary indicators emerged: (1) Synechococcophycideae and Oscillatoriophycideae (=Cyanobacteria that act as primary producers exhibiting a positive correlation with increased nitrogen and phosphorus) were significantly more abundant at PICZ sites (P<0.049), suggesting elevated nutrient availability; (2) Spartobacteria (a heterotroph negatively associated with salinity) was significantly more abundant at MICZ sites (p<0.01), suggesting lower concentrations of brine; (3) Actinobacteria, a bioremediator capable of complex and far-ranging removal of toxic pollutants, was significantly more prevalent at PICZ sites (p<0.039). Our results suggest that hydrology and location of NG well pads are potential covariates in defining microbial communities in study streams. However, long-term follow-up studies are needed to substantiate estimates and provide greater confidence in defining suggested impacts.