The Presence of Denitrifiers In Bacterial Communities of Urban Stormwater Best Management Practices (BMPs).

Stormwater best management practices (BMPs) are engineered structures that attempt to mitigate the impacts of stormwater, which can include nitrogen inputs from the surrounding drainage area. The goal of this study was to assess bacterial community composition in different types of stormwater BMP soils to establish whether a particular BMP type harbors more denitrification potential. Soil sampling took place over the summer of 2015 following precipitation events. Soils were sampled from four bioretention facilities, four dry ponds, four surface sand filters, and one dry swale. 16S rRNA gene analysis of extracted DNA and RNA amplicons indicated high bacterial diversity in the soils of all BMP types sampled. An abundance of denitrifiers was also indicated in the extracted DNA using presence/absence of nirS, nirK, and nosZ denitrification genes. BMP soil bacterial communities were impacted by the surrounding soil physiochemistry. Based on the identification of a metabolically-active community of denitrifiers, this study has indicated that denitrification could potentially occur under appropriate conditions in all types of BMP sampled, including surface sand filters that are often viewed as providing low potential for denitrification. The carbon content of incoming stormwater could be providing bacterial communities with denitrification conditions. The findings of this study are especially relevant for land managers in watersheds with legacy nitrogen from former agricultural land use.

Fish abundances in shoreline habitats and submerged aquatic vegetation in a tidal freshwater embayment of the Potomac River.

Submerged aquatic vegetation (SAV) is considered an important habitat for juvenile and small forage fish species, but many long-term recruitment surveys do not effectively monitor fish communities in SAV. To better understand the impact of recent large increases of SAV on the fish community in tidal freshwater reaches of the Potomac River, we compared traditional seine sampling from shore with drop ring sampling of SAV beds (primarily Hydrilla) in a shallow water (depths, <1.5 m) embayment, Gunston Cove. To accomplish this, we developed species-specific catch efficiency values for the seine gear and calculated area-based density in both shoreline and SAV habitats in late summer of three different years (2007, 2008, and 2009). For the dominant species (Fundulus diaphanus, Lepomis macrochirus, Etheostoma olmstedi, Morone americana, Lepomis gibbosus, and Fundulus heteroclitus), density was nearly always higher in SAV, but overall, species richness was highest in shoreline habitats sampled with seines. Although historical monitoring of fish in Gunston Cove (and throughout Chesapeake Bay) is based upon seine sampling (and trawl sampling in deeper areas), the high densities of fish and larger areal extent of SAV indicated that complementary sampling of SAV habitats would produce more accurate trends in abundances of common species. Because drop ring samples cover much less area than seines and may miss rare species, a combination of methods that includes seine sampling is needed for biodiversity assessment. The resurgence of SAV in tidal freshwater signifies improving water quality, and methods we evaluated here support improved inferences about population trends and fish community structure as indicators of ecosystem condition.

Spatial and seasonal patterns in water quality in an embayment-mainstem reach of the tidal freshwater Potomac River, USA: a multiyear study.

Spatial and temporal patterns in water quality were studied for seven years within an embayment-river mainstem area of the tidal freshwater Potomac River. The purpose of this paper is to determine the important components of spatial and temporal variation in water quality in this study area to facilitate an understanding of management impacts and allow the most effective use of future monitoring resources. The study area received treated sewage effluent and freshwater inflow from direct tributary inputs into the shallow embayment as well as upriver sources in the mainstem. Depth variations were determined to be detectable, but minimal due mainly to the influence of tidal mixing. Results of principal component analysis of two independent water quality datasets revealed clear spatial and seasonal patterns. Interannual variation was generally minimal despite substantial variations in tributary and mainstem discharge among years. Since both spatial and seasonal components were important, data were segmented by season to best determine the spatial pattern. A clear difference was found between a set of stations located within one embayment (Gunston Cove) and a second set in the nearby Potomac mainstem. Parameters most highly correlated with differences were those typically associated with higher densities of phytoplankton: chlorophyll a, photosynthetic rate, pH, dissolved oxygen, BOD, total phosphorus and Secchi depth. These differences and their consistency indicated two distinct water masses: one in the cove harboring higher algal density and activity and a second in the river with lower phytoplankton activity. A second embayment not receiving sewage effluent generally had an intermediate position. While this was the most consistent spatial pattern, there were two others of a secondary nature. Stations closer to the effluent inputs in the embayment sometimes grouped separately due to elevated ammonia and chloride. Stations closer to tributary inflows into the embayment sometimes grouped separately due to dilution with freshwater runoff. Segmenting the datasets by spatial region resulted in a clarification of seasonal patterns with similar factors relating to algal activity being the major correlates of the seasonal pattern. A basic seasonal pattern of lower scores in the spring increasing steadily to a peak in July and August followed by a steady decline through the fall was observed in the cove. In the river, the pattern of increases tended to be delayed slightly in the spring. Results indicate that the study area can be effectively monitored with fewer study sites provided that at least one is located in each of the spatial regions.

Predicting levels of stress from biological assessment data: empirical models from the Eastern Corn Belt Plains, Ohio, USA.

Interest is increasing in using biological community data to provide information on the specific types of anthropogenic influences impacting streams. We built empirical models that predict the level of six different types of stress with fish and benthic macroinvertebrate data as explanatory variables. Significant models were found for six stressor factors: stream corridor structure; siltation; total suspended solids (TSS), biochemical oxygen demand (BOD), and iron (Fe); chemical oxygen demand (COD) and BOD; zinc (Zn) and lead (Pb); and nitrate and nitrite (NOx) and phosphorus (P). Model R2 values were lowest for the siltation factor and highest for TSS, BOD, and Fe. Model R2 values increased when spatial relationships were incorporated into the model. The models generally performed well when applied to a random subset of the data. Performance was more mixed when models were applied to data collected from a previous time period, perhaps because of a change in the spatial structure of these systems. These models may provide a useful indication of the levels of different stresses impacting stream reaches in the Eastern Corn Belt Plains ecoregion of Ohio, USA. More generally, the models provide additional evidence that biological communities can serve as useful indicators of the types of anthropogenic stress impacting aquatic systems.