Evaluation of 1,2-diacyl-3-acetyl triacylglycerol production in Yarrowia lipolytica.

Plants produce many high-value oleochemical molecules. While oil-crop agriculture is performed at industrial scales, suitable land is not available to meet global oleochemical demand. Worse, establishing new oil-crop farms often comes with the environmental cost of tropical deforestation. The field of metabolic engineering offers tools to transplant oleochemical metabolism into tractable hosts while simultaneously providing access to molecules produced by non-agricultural plants. Here, we evaluate strategies for rewiring metabolism in the oleaginous yeast Yarrowia lipolytica to synthesize a foreign lipid, 3-acetyl-1,2-diacyl-sn-glycerol (acTAG). Oils made up of acTAG have a reduced viscosity and melting point relative to traditional triacylglycerol oils making them attractive as low-grade diesels, lubricants, and emulsifiers. This manuscript describes a metabolic engineering study that established acTAG production at g/L scale, exploration of the impact of lipid bodies on acTAG titer, and a techno-economic analysis that establishes the performance benchmarks required for microbial acTAG production to be economically feasible.

MALDI-MS screening of microbial colonies with isomer resolution to select fatty acid desaturase variants.

Creating controlled lipid unsaturation locations in oleochemicals can be a key to many bioengineered products. However, evaluating the effects of modifications to the acyl-ACP desaturase on lipid unsaturation is not currently amenable to high-throughput assays, limiting the scale of redesign efforts to <200 variants. Here, we report a rapid MS assay for profiling the positions of double bonds on membrane lipids produced by Escherichia coli colonies after treatment with ozone gas. By MS measurement of the ozonolysis products of Δ6 and Δ8 isomers of membrane lipids from colonies expressing recombinant Thunbergia alata desaturase, we screened a randomly mutagenized library of the desaturase gene at 5 s per sample. Two variants with altered regiospecificity were isolated, indicated by an increase in 16:1 Δ8 proportion. We also demonstrated the ability of these desaturase variants to influence the membrane composition and fatty acid distribution of E. coli strains deficient in the native acyl-ACP desaturase gene, fabA. Finally, we used the fabA deficient chassis to concomitantly express a non-native acyl-ACP desaturase and a medium-chain thioesterase from Umbellularia californica, demonstrating production of only saturated free fatty acids.

The emergence of hydrogeophysics for improved understanding of subsurface processes over multiple scales.

A review of the emergence and development of hydrogeophysicsOutline of emerging techniques in hydrogeophysicsPresentation of future opportunities in hydrogeophysics.

Extrapolating active layer thickness measurements across Arctic polygonal terrain using LiDAR and NDVI data sets.

Landscape attributes that vary with microtopography, such as active layer thickness (ALT), are labor intensive and difficult to document effectively through in situ methods at kilometer spatial extents, thus rendering remotely sensed methods desirable. Spatially explicit estimates of ALT can provide critically needed data for parameterization, initialization, and evaluation of Arctic terrestrial models. In this work, we demonstrate a new approach using high-resolution remotely sensed data for estimating centimeter-scale ALT in a 5 km2 area of ice-wedge polygon terrain in Barrow, Alaska. We use a simple regression-based, machine learning data-fusion algorithm that uses topographic and spectral metrics derived from multisensor data (LiDAR and WorldView-2) to estimate ALT (2 m spatial resolution) across the study area. Comparison of the ALT estimates with ground-based measurements, indicates the accuracy (r2 = 0.76, RMSE ±4.4 cm) of the approach. While it is generally accepted that broad climatic variability associated with increasing air temperature will govern the regional averages of ALT, consistent with prior studies, our findings using high-resolution LiDAR and WorldView-2 data, show that smaller-scale variability in ALT is controlled by local eco-hydro-geomorphic factors. This work demonstrates a path forward for mapping ALT at high spatial resolution and across sufficiently large regions for improved understanding and predictions of coupled dynamics among permafrost, hydrology, and land-surface processes from readily available remote sensing data.

A new model for the biodegradation kinetics of oil droplets: application to the Deepwater Horizon oil spill in the Gulf of Mexico.

Oil biodegradation by native bacteria is one of the most important natural processes that can attenuate the environmental impacts of marine oil spills. Existing models for oil biodegradation kinetics are mostly for dissolved oil. This work developed a new mathematical model for the biodegradation of oil droplets and applied the model to estimate the time scale for oil biodegradation under conditions relevant to the Deepwater Horizon oil spill in the Gulf of Mexico. In the model, oil is composed of droplets of various sizes following the gamma function distribution. Each oil droplet shrinks during the microbe-mediated degradation at the oil-water interface. Using our developed model, we find that the degradation of oil droplets typically goes through two stages. The first stage is characterized by microbial activity unlimited by oil-water interface with higher biodegradation rates than that of the dissolved oil. The second stage is governed by the availability of the oil-water interface, which results in much slower rates than that of soluble oil. As a result, compared to that of the dissolved oil, the degradation of oil droplets typically starts faster and then quickly slows down, ultimately reaching a smaller percentage of degraded oil in longer time. The availability of the water-oil interface plays a key role in determining the rates and extent of degradation. We find that several parameters control biodegradation rates, including size distribution of oil droplets, initial microbial concentrations, initial oil concentration and composition. Under conditions relevant to the Deepwater Horizon spill, we find that the size distribution of oil droplets (mean and coefficient of variance) is the most important parameter because it determines the availability of the oil-water interface. Smaller oil droplets with larger variance leads to faster and larger extent of degradation. The developed model will be useful for evaluating transport and fate of spilled oil, different remediation strategies, and risk assessment.

Monitoring CO2 intrusion and associated geochemical transformations in a shallow groundwater system using complex electrical methods.

The risk of CO(2) leakage from a properly permitted deep geologic storage facility is expected to be very low. However, if leakage occurs it could potentially impact potable groundwater quality. Dissolved CO(2) in groundwater decreases pH, which can mobilize naturally occurring trace metals commonly contained in aquifer sediments. Observing such processes requires adequate monitoring strategies. Here, we use laboratory and field experiments to explore the sensitivity of time-lapse complex resistivity responses for remotely monitoring dissolved CO(2) distribution and geochemical transformations that may impact groundwater quality. Results show that electrical resistivity and phase responses correlate well with dissolved CO(2) injection processes. Specifically, resistivity initially decreases due to increase of bicarbonate and dissolved species. As pH continues to decrease, the resistivity rebounds toward initial conditions due to the transition of bicarbonate into nondissociated carbonic acid, which reduces the total concentration of dissociated species and thus the water conductivity. An electrical phase decrease is also observed, which is interpreted to be driven by the decrease of surface charge density as well as potential mineral dissolution and ion exchange. Both laboratory and field experiments demonstrate the potential of field complex resistivity method for remotely monitoring changes in groundwater quality due to CO(2) leakage.

Effect of dissolved CO2 on a shallow groundwater system: a controlled release field experiment.

Capturing carbon dioxide (CO(2)) emissions from industrial sources and injecting the emissions deep underground in geologic formations is one method being considered to control CO(2) concentrations in the atmosphere. Sequestering CO(2) underground has its own set of environmental risks, including the potential migration of CO(2) out of the storage reservoir and resulting acidification and release of trace constituents in shallow groundwater. A field study involving the controlled release of groundwater containing dissolved CO(2) was initiated to investigate potential groundwater impacts. Dissolution of CO(2) in the groundwater resulted in a sustained and easily detected decrease of ~3 pH units. Several trace constituents, including As and Pb, remained below their respective detections limits and/or at background levels. Other constituents (Ba, Ca, Cr, Sr, Mg, Mn, and Fe) displayed a pulse response, consisting of an initial increase in concentration followed by either a return to background levels or slightly greater than background. This suggests a fast-release mechanism (desorption, exchange, and/or fast dissolution of small finite amounts of metals) concomitant in some cases with a slower release potentially involving different solid phases or mechanisms. Inorganic constituents regulated by the U.S. Environmental Protection Agency remained below their respective maximum contaminant levels throughout the experiment.

Persistent source influences on the trailing edge of a groundwater plume, and natural attenuation timeframes: the F-Area Savannah River Site.

At the Savannah River Site's F-Area, wastewaters containing radionuclides were disposed into seepage basins for decades. After closure and capping in 1991, the U.S. Department of Energy (DOE) has being monitoring and remediating the groundwater plume. Despite numerous studies of the plume, its persistence for over 20 years has not been well understood. To better understand the plume dynamics, a limited number of deep boreholes were drilled to determine the current plume characteristics. A mixing model was developed to predict plume tritium and nitrate concentrations. We found that the plume trailing edges have emerged for some contaminants, and that contaminant recharge from the basin's vadose zone is still important. The model's estimated time-dependent basin drainage rates combined with dilution from natural recharge successfully predicted plume tritium and nitrate concentrations. This new understanding of source zone influences can help guide science-based remediation, and improve predictions of the natural attenuation timeframes.

Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics.

Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.

Geophysical monitoring and reactive transport modeling of ureolytically-driven calcium carbonate precipitation.

Ureolytically-driven calcium carbonate precipitation is the basis for a promising in-situ remediation method for sequestration of divalent radionuclide and trace metal ions. It has also been proposed for use in geotechnical engineering for soil strengthening applications. Monitoring the occurrence, spatial distribution, and temporal evolution of calcium carbonate precipitation in the subsurface is critical for evaluating the performance of this technology and for developing the predictive models needed for engineering application. In this study, we conducted laboratory column experiments using natural sediment and groundwater to evaluate the utility of geophysical (complex resistivity and seismic) sensing methods, dynamic synchrotron x-ray computed tomography (micro-CT), and reactive transport modeling for tracking ureolytically-driven calcium carbonate precipitation processes under site relevant conditions. Reactive transport modeling with TOUGHREACT successfully simulated the changes of the major chemical components during urea hydrolysis. Even at the relatively low level of urea hydrolysis observed in the experiments, the simulations predicted an enhanced calcium carbonate precipitation rate that was 3-4 times greater than the baseline level. Reactive transport modeling results, geophysical monitoring data and micro-CT imaging correlated well with reaction processes validated by geochemical data. In particular, increases in ionic strength of the pore fluid during urea hydrolysis predicted by geochemical modeling were successfully captured by electrical conductivity measurements and confirmed by geochemical data. The low level of urea hydrolysis and calcium carbonate precipitation suggested by the model and geochemical data was corroborated by minor changes in seismic P-wave velocity measurements and micro-CT imaging; the latter provided direct evidence of sparsely distributed calcium carbonate precipitation. Ion exchange processes promoted through NH4+ production during urea hydrolysis were incorporated in the model and captured critical changes in the major metal species. The electrical phase increases were potentially due to ion exchange processes that modified charge structure at mineral/water interfaces. Our study revealed the potential of geophysical monitoring for geochemical changes during urea hydrolysis and the advantages of combining multiple approaches to understand complex biogeochemical processes in the subsurface.

Physicochemical heterogeneity controls on uranium bioreduction rates at the field scale.

It has been demonstrated in laboratory systems that U(VI) can be reduced to immobile U(IV) by bacteria in natural environments. The ultimate efficacy of bioreduction at the field scale, however, is often challenging to quantify and depends on site characteristics. In this work, uranium bioreduction rates at the field scale are quantified, for the first time, using an integrated approach. The approach combines field data, inverse and forward hydrological and reactive transport modeling, and quantification of reduction rates at different spatial scales. The approach is used to explore the impact of local scale (tens of centimeters) parameters and processes on field scale (tens of meters) system responses to biostimulation treatments and the controls of physicochemical heterogeneity on bioreduction rates. Using the biostimulation experiments at the Department of Energy Old Rifle site, our results show that the spatial distribution of hydraulic conductivity and solid phase mineral (Fe(III)) play a critical role in determining the field-scale bioreduction rates. Due to the dependence on Fe-reducing bacteria, field-scale U(VI) bioreduction rates were found to be largely controlled by the abundance of Fe(III) minerals at the vicinity of the injection wells and by the presence of preferential flow paths connecting injection wells to down gradient Fe(III) abundant areas.

Influence of soil heterogeneity on soybean plant development and crop yield evaluated using time-series of UAV and ground-based geophysical imagery.

Understanding the interactions among agricultural processes, soil, and plants is necessary for optimizing crop yield and productivity. This study focuses on developing effective monitoring and analysis methodologies that estimate key soil and plant properties. These methodologies include data acquisition and processing approaches that use unmanned aerial vehicles (UAVs) and surface geophysical techniques. In particular, we applied these approaches to a soybean farm in Arkansas to characterize the soil-plant coupled spatial and temporal heterogeneity, as well as to identify key environmental factors that influence plant growth and yield. UAV-based multitemporal acquisition of high-resolution RGB (red-green-blue) imagery and direct measurements were used to monitor plant height and photosynthetic activity. We present an algorithm that efficiently exploits the high-resolution UAV images to estimate plant spatial abundance and plant vigor throughout the growing season. Such plant characterization is extremely important for the identification of anomalous areas, providing easily interpretable information that can be used to guide near-real-time farming decisions. Additionally, high-resolution multitemporal surface geophysical measurements of apparent soil electrical conductivity were used to estimate the spatial heterogeneity of soil texture. By integrating the multiscale multitype soil and plant datasets, we identified the spatiotemporal co-variance between soil properties and plant development and yield. Our novel approach for early season monitoring of plant spatial abundance identified areas of low productivity controlled by soil clay content, while temporal analysis of geophysical data showed the impact of soil moisture and irrigation practice (controlled by topography) on plant dynamics. Our study demonstrates the effective coupling of UAV data products with geophysical data to extract critical information for farm management.

Meanders as a scaling motif for understanding of floodplain soil microbiome and biogeochemical potential at the watershed scale.

BACKGROUND: Biogeochemical exports from watersheds are modulated by the activity of microorganisms that function over micron scales. Here, we tested the hypothesis that meander-bound regions share a core microbiome and exhibit patterns of metabolic potential that broadly predict biogeochemical processes in floodplain soils along a river corridor. RESULTS: We intensively sampled the microbiomes of floodplain soils located in the upper, middle, and lower reaches of the East River, Colorado. Despite the very high microbial diversity and complexity of the soils, we reconstructed 248 quality draft genomes representative of subspecies. Approximately one third of these bacterial subspecies was detected across all three locations at similar abundance levels, and ~ 15% of species were detected in two consecutive years. Within the meander-bound floodplains, we did not detect systematic patterns of gene abundance based on sampling position relative to the river. However, across meanders, we identified a core floodplain microbiome that is enriched in capacities for aerobic respiration, aerobic CO oxidation, and thiosulfate oxidation with the formation of elemental sulfur. Given this, we conducted a transcriptomic analysis of the middle floodplain. In contrast to predictions made based on the prominence of gene inventories, the most highly transcribed genes were relatively rare amoCAB and nxrAB (for nitrification) genes, followed by genes involved in methanol and formate oxidation, and nitrogen and CO2 fixation. Within all three meanders, low soil organic carbon correlated with high activity of genes involved in methanol, formate, sulfide, hydrogen, and ammonia oxidation, nitrite oxidoreduction, and nitrate and nitrite reduction. Overall, the results emphasize the importance of sulfur, one-carbon and nitrogen compound metabolism in soils of the riparian corridor. CONCLUSIONS: The disparity between the scale of a microbial cell and the scale of a watershed currently limits the development of genomically informed predictive models describing watershed biogeochemical function. Meander-bound floodplains appear to serve as scaling motifs that predict aggregate capacities for biogeochemical transformations, providing a foundation for incorporating riparian soil microbiomes in watershed models. Widely represented genetic capacities did not predict in situ activity at one time point, but rather they define a reservoir of biogeochemical potential available as conditions change. Video abstract.

The Snowmelt Niche Differentiates Three Microbial Life Strategies That Influence Soil Nitrogen Availability During and After Winter.

Soil microbial biomass can reach its annual maximum pool size beneath the winter snowpack and is known to decline abruptly following snowmelt in seasonally snow-covered ecosystems. Observed differences in winter versus summer microbial taxonomic composition also suggests that phylogenetically conserved traits may permit winter- versus summer-adapted microorganisms to occupy distinct niches. In this study, we sought to identify archaea, bacteria, and fungi that are associated with the soil microbial bloom overwinter and the subsequent biomass collapse following snowmelt at a high-altitude watershed in central Colorado, United States. Archaea, bacteria, and fungi were categorized into three life strategies (Winter-Adapted, Snowmelt-Specialist, Spring-Adapted) based upon changes in abundance during winter, the snowmelt period, and after snowmelt in spring. We calculated indices of phylogenetic relatedness (archaea and bacteria) or assigned functional attributes (fungi) to organisms within life strategies to infer whether phylogenetically conserved traits differentiate Winter-Adapted, Snowmelt-Specialist, and Spring-Adapted groups. We observed that the soil microbial bloom was correlated in time with a pulse of snowmelt infiltration, which commenced 65 days prior to soils becoming snow-free. A pulse of nitrogen (N, as nitrate) occurred after snowmelt, along with a collapse in the microbial biomass pool size, and an increased abundance of nitrifying archaea and bacteria (e.g., Thaumarchaeota, Nitrospirae). Winter- and Spring-Adapted archaea and bacteria were phylogenetically clustered, suggesting that phylogenetically conserved traits allow Winter- and Spring-Adapted archaea and bacteria to occupy distinct niches. In contrast, Snowmelt-Specialist archaea and bacteria were phylogenetically overdispersed, suggesting that the key mechanism(s) of the microbial biomass crash are likely to be density-dependent (e.g., trophic interactions, competitive exclusion) and affect organisms across a broad phylogenetic spectrum. Saprotrophic fungi were the dominant functional group across fungal life strategies, however, ectomycorrhizal fungi experienced a large increase in abundance in spring. If well-coupled plant-mycorrhizal phenology currently buffers ecosystem N losses in spring, then changes in snowmelt timing may alter ecosystem N retention potential. Overall, we observed that snowmelt separates three distinct soil niches that are occupied by ecologically distinct groups of microorganisms. This ecological differentiation is of biogeochemical importance, particularly with respect to the mobilization of nitrogen during winter, before and after snowmelt.

Predicting sedimentary bedrock subsurface weathering fronts and weathering rates.

Although bedrock weathering strongly influences water quality and global carbon and nitrogen budgets, the weathering depths and rates within subsurface are not well understood nor predictable. Determination of both porewater chemistry and subsurface water flow are needed in order to develop more complete understanding and obtain weathering rates. In a long-term field study, we applied a multiphase approach along a mountainous watershed hillslope transect underlain by marine shale. Here we report three findings. First, the deepest extent of the water table determines the weathering front, and the range of annually water table oscillations determines the thickness of the weathering zone. Below the lowest water table, permanently water-saturated bedrock remains reducing, preventing deeper pyrite oxidation. Secondly, carbonate minerals and potentially rock organic matter share the same weathering front depth with pyrite, contrary to models where weathering fronts are stratified. Thirdly, the measurements-based weathering rates from subsurface shale are high, amounting to base cation exports of about 70 kmolc ha-1 y-1, yet consistent with weathering of marine shale. Finally, by integrating geochemical and hydrological data we present a new conceptual model that can be applied in other settings to predict weathering and water quality responses to climate change.

Evaluating temporal controls on greenhouse gas (GHG) fluxes in an Arctic tundra environment: An entropy-based approach.

There is significant spatial and temporal variability associated with greenhouse gas (GHG) fluxes in high-latitude Arctic tundra environments. The objectives of this study are to investigate temporal variability in CO2 and CH4 fluxes at Barrow, AK and to determine the factors causing this variability using a novel entropy-based classification scheme. In particular, we analyzed which geomorphic, soil, vegetation and climatic properties most explained the variability in GHG fluxes (opaque chamber measurements) during the growing season over three successive years. Results indicate that multi-year variability in CO2 fluxes was primarily associated with soil temperature variability as well as vegetation dynamics during the early and late growing season. Temporal variability in CH4 fluxes was primarily associated with changes in vegetation during the growing season and its interactions with primary controls like seasonal thaw. Polygonal ground features, which are common to Arctic regions, also demonstrated significant multi-year variability in GHG fluxes. Our results can be used to prioritize field sampling strategies, with an emphasis on measurements collected at locations and times that explain the most variability in GHG fluxes. For example, we found that sampling primary environmental controls at the centers of high centered polygons in the month of September (when freeze-back period begins) can provide significant constraints on GHG flux variability - a requirement for accurately predicting future changes to GHG fluxes. Overall, entropy results document the impact of changing environmental conditions (e.g., warming, growing season length) on GHG fluxes, thus providing clues concerning the manner in which ecosystem properties may be shifted regionally in a future climate.

Microbial communities across a hillslope-riparian transect shaped by proximity to the stream, groundwater table, and weathered bedrock.

Watersheds are important suppliers of freshwater for human societies. Within mountainous watersheds, microbial communities impact water chemistry and element fluxes as water from precipitation events discharge through soils and underlying weathered rock, yet there is limited information regarding the structure and function of these communities. Within the East River, CO watershed, we conducted a depth-resolved, hillslope to riparian zone transect study to identify factors that control how microorganisms are distributed and their functions. Metagenomic and geochemical analyses indicate that distance from the East River and proximity to groundwater and underlying weathered shale strongly impact microbial community structure and metabolic potential. Riparian zone microbial communities are compositionally distinct, from the phylum down to the species level, from all hillslope communities. Bacteria from phyla lacking isolated representatives consistently increase in abundance with increasing depth, but only in the riparian zone saturated sediments we found Candidate Phyla Radiation bacteria. Riparian zone microbial communities are functionally differentiated from hillslope communities based on their capacities for carbon and nitrogen fixation and sulfate reduction. Selenium reduction is prominent at depth in weathered shale and saturated riparian zone sediments and could impact water quality. We anticipate that the drivers of community composition and metabolic potential identified throughout the studied transect will predict patterns across the larger watershed hillslope system.

Landscape topography structures the soil microbiome in arctic polygonal tundra.

In the Arctic, environmental factors governing microbial degradation of soil carbon (C) in active layer and permafrost are poorly understood. Here we determined the functional potential of soil microbiomes horizontally and vertically across a cryoperturbed polygonal landscape in Alaska. With comparative metagenomics, genome binning of novel microbes, and gas flux measurements we show that microbial greenhouse gas (GHG) production is strongly correlated to landscape topography. Active layer and permafrost harbor contrasting microbiomes, with increasing amounts of Actinobacteria correlating with decreasing soil C in permafrost. While microbial functions such as fermentation and methanogenesis were dominant in wetter polygons, in drier polygons genes for C mineralization and CH4 oxidation were abundant. The active layer microbiome was poised to assimilate N and not to release N2O, reflecting low N2O flux measurements. These results provide mechanistic links of microbial metabolism to GHG fluxes that are needed for the refinement of model predictions.

Using strontium isotopes to evaluate the spatial variation of groundwater recharge.

Recharge of alluvial aquifers is a key component in understanding the interaction between floodplain vadose zone biogeochemistry and groundwater quality. The Rifle Site (a former U-mill tailings site) adjacent to the Colorado River is a well-established field laboratory that has been used for over a decade for the study of biogeochemical processes in the vadose zone and aquifer. This site is considered an exemplar of both a riparian floodplain in a semiarid region and a post-remediation U-tailings site. In this paper we present Sr isotopic data for groundwater and vadose zone porewater samples collected in May and July 2013 to build a mixing model for the fractional contribution of vadose zone porewater (i.e. recharge) to the aquifer and its variation across the site. The vadose zone porewater contribution to the aquifer ranged systematically from 0% to 38% and appears to be controlled largely by the microtopography of the site. The area-weighted average contribution across the site was 8% corresponding to a net recharge of 7.5 cm. Given a groundwater transport time across the site of ~1.5 to 3 years, this translates to a recharge rate between 5 and 2.5 cm/yr, and with the average precipitation to the site implies a loss from the vadose zone due to evapotranspiration of 83% to 92%, both ranges are in good agreement with previously published results by independent methods. A uranium isotopic (234U/238U activity ratios) mixing model for groundwater and surface water samples indicates that a ditch across the site is hydraulically connected to the aquifer and locally significantly affects groundwater. Groundwater samples with high U concentrations attributed to natural bio-reduced zones have 234U/238U activity ratios near 1, suggesting that the U currently being released to the aquifer originated from the former U-mill tailings.

Microbial Metagenomics Reveals Climate-Relevant Subsurface Biogeochemical Processes.

Microorganisms play key roles in terrestrial system processes, including the turnover of natural organic carbon, such as leaf litter and woody debris that accumulate in soils and subsurface sediments. What has emerged from a series of recent DNA sequencing-based studies is recognition of the enormous variety of little known and previously unknown microorganisms that mediate recycling of these vast stores of buried carbon in subsoil compartments of the terrestrial system. More importantly, the genome resolution achieved in these studies has enabled association of specific members of these microbial communities with carbon compound transformations and other linked biogeochemical processes-such as the nitrogen cycle-that can impact the quality of groundwater, surface water, and atmospheric trace gas concentrations. The emerging view also emphasizes the importance of organism interactions through exchange of metabolic byproducts (e.g., within the carbon, nitrogen, and sulfur cycles) and via symbioses since many novel organisms exhibit restricted metabolic capabilities and an associated extremely small cell size. New, genome-resolved information reshapes our view of subsurface microbial communities and provides critical new inputs for advanced reactive transport models. These inputs are needed for accurate prediction of feedbacks in watershed biogeochemical functioning and their influence on the climate via the fluxes of greenhouse gases, CO2, CH4, and N2O.