Nitrate reduction at the groundwater - salt marsh interface

The influence of groundwater discharge on the hydrology and biogeochemical cycling of nitrogen in a fringing intertidal wetland was studied by characterizing groundwater discharge, determining N-cycling rates in cores, and examining nitrate reduction in situ using 15N enrichment and natural gradient tracer techniques. Groundwater discharge was estimated by three independent methods: Darcy\u27s Law, a water/salt mass balance, and a subsurface tracer test. Seasonal patterns of discharge predicted by Darcy\u27s Law and the mass balance were similar. Discharge maxima and minima occurred in April and September, respectively. The water/salt mass balance provided the more reasonable estimate of groundwater flux at high flows, and the Darcy technique was better at estimating low flow at our site. The high discharge seasonally purged porewater from the marsh to the estuary, and marsh processing of groundwater solute loads would occur only during this period. Mineralization, nitrification, potential denitrification (DNF), and potential dissimilatory nitrate reduction to ammonium (DNRA) rates were estimated in cores during periods of high and low groundwater discharge. All N-cycling processes occurred in sediments \u3c1.5 meters deep. Natural abundance isotope measures, and core experiments indicated that coupled nitrification-denitrification was a sizeable sink for mineralized N. Mineralization, nitrification, and DNRA rates were 6--12x greater during Spring high discharge. DNF rates, were 10x higher during Fall low discharge. Despite accelerated mineralization and nitrification during high discharge, the DNF:DNRA ratio was \u3c1, indicating that more of the N cycled through nitrification was retained as ammonium rather than exported as dinitrogen through coupled nitrification-denitrification. Nitrate reduction pathways in the marsh were studied in situ by creating a nitrate plume enriched in 15N. Isotopic enrichment of the ammonium, PON, dissolved nitrous oxide, and dissolved dinitrogen pools initially accounted for 14--36% of the observed nitrate loss. Adjustment of these estimates with potential losses through gas evasion, and ammonium turnover, accounted for nearly all of the N missing from the mass balance. The adjusted mass balance indicated that 68% of the nitrate load was denitrified, and 30% was assimilated and retained in the marsh

Organic carbon abundance, distribution and metabolism at the Oyster, Virginia study site

This report describes a pilot study conducted at the DOE Subsurface Science Program\u27s study site in Oyster, VA. The objective of this study was to examine whether 2 organic matter associated with the solid and dissolved phases was labile enough to support microbial activity. Organic matter availability was assessed in two ways: (1) by quantifying the amount and distribution of total organic carbon (TOC) associated with the solid phase and (2) laboratory experiments to examine the utilization of dissolved organic matter by measuring total microbial respiration. In addition to assessing total respiration, we specifically addressed organic matter respiration via denitrification. The focus on denitrification was due to the environmental field conditions at the study site (low concentrations of dissolved oxygen and high nitrate concentrations) suggesting that nitrate respiration would be a likely process for organic matter utilization

Linking DNRA community structure and activity in a shallow lagoonal estuarine system

Dissimilatory nitrate reduction to ammonium (DNRA) and denitrification are two nitrate respiration pathways in the microbial nitrogen cycle. Diversity and abundance of denitrifying bacteria have been extensively examined in various ecosystems. However, studies on DNRA bacterial diversity are limited, and the linkage between the structure and activity of DNRA communities has yet to be discovered. We examined the composition, diversity, abundance, and activities of DNRA communities at five sites along a salinity gradient in the New River Estuary, North Carolina, USA, a shallow temporal/lagoonal estuarine system. Sediment slurry incubation experiments with N-15-nitrate were conducted to measure potential DNRA rates, while the abundance of DNRA communities was calculated using quantitative PCR of nrfA genes encoding cytochrome C nitrite reductase, commonly found in DNRA bacteria. A pyrosequencing method targeting nrfA genes was developed using an Ion Torrent sequencer to examine the diversity and composition of DNRA communities within the estuarine sediment community. We found higher levels of nrfA gene abundance and DNRA activities in sediments with higher percent organic content. Pyrosequencing analysis of nrfA genes revealed spatial variation of DNRA communities along the salinity gradient of the New River Estuary. Percent abundance of dominant populations was found to have significant influence on overall activities of DNRA communities. Abundance of dominant DNRA bacteria and organic carbon availability are important regulators of DNRA activities in the eutrophic New River Estuary

Highly accelerated cardiac functional MRI in rodent hearts using compressed sensing and parallel imaging at 9.4T

Summary. Parallel Imaging and Compressed Sensing have individually been shown to speed up cardiac functional MRI in mice and rats at ultra-high magnetic fields whilst providing accurate measurement of the physiologically relevant parameters. This study demonstrates that the acquisition time for cine-MRI in rodent hearts can be significantly reduced further by combining both techniques

Can Artificial Intelligence‐Based Weather Prediction Models Simulate the Butterfly Effect?

We investigate error growth from small-amplitude initial condition perturbations, simulated with a recent artificial intelligence-based weather prediction model. From past simulations with standard physically-based numerical models as well as from theoretical considerations it is expected that such small-amplitude initial condition perturbations would grow very fast initially. This fast growth then sets a fixed and fundamental limit to the predictability of weather, a phenomenon known as the butterfly effect. We find however, that the AI-based model completely fails to reproduce the rapid initial growth rates and hence would incorrectly suggest an unlimited predictability of the atmosphere. In contrast, if the initial perturbations are large and comparable to current uncertainties in the estimation of the initial state, the AI-based model basically agrees with physically-based simulations, although some deficits are still present

Dynamic modeling of nitrogen losses in river networks unravels the coupled effects of hydrological and biogeochemical processes

The importance of lotic systems as sinks for nitrogen inputs is well recognized. A fraction of nitrogen in streamflow is removed to the atmosphere via denitrification with the remainder exported in streamflow as nitrogen loads. At the watershed scale, there is a keen interest in understanding the factors that control the fate of nitrogen throughout the stream channel network, with particular attention to the processes that deliver large nitrogen loads to sensitive coastal ecosystems. We use a dynamic stream transport model to assess biogeochemical (nitrate loadings, concentration, temperature) and hydrological (discharge, depth, velocity) effects on reach-scale denitrification and nitrate removal in the river networks of two watersheds having widely differing levels of nitrate enrichment but nearly identical discharges. Stream denitrification is estimated by regression as a nonlinear function of nitrate concentration, streamflow, and temperature, using more than 300 published measurements from a variety of US streams. These relations are used in the stream transport model to characterize nitrate dynamics related to denitrification at a monthly time scale in the stream reaches of the two watersheds. Results indicate that the nitrate removal efficiency of streams, as measured by the percentage of the stream nitrate flux removed via denitrification per unit length of channel, is appreciably reduced during months with high discharge and nitrate flux and increases during months of low-discharge and flux. Biogeochemical factors, including land use, nitrate inputs, and stream concentrations, are a major control on reach-scale denitrification, evidenced by the disproportionately lower nitrate removal efficiency in streams of the highly nitrate-enriched watershed as compared with that in similarly sized streams in the less nitrate-enriched watershed. Sensitivity analyses reveal that these important biogeochemical factors and physical hydrological factors contribute nearly equally to seasonal and stream-size related variations in the percentage of the stream nitrate flux removed in each watershed

Antibiotic Effects on Microbial Communities Responsible for Greenhouse Gas Emissions

Nitrous oxide (N2O) is a powerful greenhouse gas generated by nitrification and denitrification. The goal of this project is to examine the effects of antibiotics on microbial communities responsible for N2O emissions from terrestrial and aquatic ecosystems. We conducted laboratory and mesocosm experiments in soil samples. Higher N2O production was observed in soils exposed to tetracycline. This was associated with reduction of bacterial denitrifiers abundance and enhanced fungal abundance