BER Research Highlights

Search Date: September 18, 2020

21 Records match the search term(s):


October 10, 2019

Replicating Subsurface Processes in the Laboratory

October 10, 2018

The Science
Fluid flows with temperatures that are not constant are known as non-isothermal. Although changing thermal and hydrological conditions control rates of sediment biogeochemical processes in the Earth’s subsurface, these conditions are difficult to simulate in the laboratory. In this study, a novel 2 m–tall column system to control time- and depth-dependent temperature profiles and water saturation was developed, which is needed to more accurately reproduce subsurface processes in the laboratory.

The Impact
Temperature and moisture profiles in sediments are highly variable, and control biogeochemical processes, yet have not previously been reproduced in the laboratory. This study established field temperature and moisture profiles in a laboratory column system, and showed the importance of microbial respiration below the plant root zone by measuring carbon dioxide (CO2) production within the sediment column.

Summary
Transport between the soil surface and groundwater is commonly mediated through deeper portions of variably saturated sediments and the capillary fringe, where variations in temperature and water saturation strongly influence biogeochemical processes. Temperature control is particularly important because room temperature is not representative of most soil and sediment environments. The authors described and tested a novel sediment column design that allows laboratory simulation of thermal and hydrologic conditions found in many field settings. The 2.0 m–tall column was capable of replicating temperatures varying from 3 to 22°C, encompassing the full range of seasonal temperature variation observed in the deep, variably saturated sediments and capillary fringe of a semi-arid floodplain in western Colorado, United States. The water table was varied within the lower 0.8-m section of the column, while profiles of water content and matric (capillary) pressure were measured. CO2 collected from depth-distributed gas samplers under representative seasonal conditions reflected the influences of temperature and water-table depth on microbial respiration. Thus, realistic subsurface biogeochemical dynamics can be simulated in the laboratory through establishing column profiles that more accurately represent seasonal thermal and hydrologic conditions.

Contacts
BER Program Manager 
David Lesmes, SC-23.1, 301-903-2977

Principal Investigator
Susan Hubbard
Lawrence Berkeley National Laboratory
sshubbard@lbl.gov

Funding
This work was supported by the Office of Biological and Environmental Research within the U.S. Department of Energy Office of Science..

Publication
Tokunaga, T.K., Y. Kim, J. Wan, M. Bill, M. Conrad, and W. Dong, “Method for controlling temperature profiles and water table depths in laboratory sediment columns. Vadose Zone Journal 17(1),180085 (2018). [DOI:10.2136/vzj2018.04.0085].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


September 15, 2019

Abiotic and Biotic Controls on Soil Organo–Mineral Interactions

Kinetics, surface chemistry, microbial community structure, and other factors are key for predicting soil organic matter dynamics within a reactive transport modeling framework.

The Science
While there currently exists a suite of models representing soil organic matter (SOM) dynamics that span a range of complexity, some recent mechanistic models are more consistent with an emerging understanding of the persistence of SOM. Yet even these more recent models do not represent several processes that can be important for SOM dynamics. It is clear that next-generation models need to represent the full spectrum of quantitatively important mechanisms for determining SOM persistence—including rate-limited and equilibrium-based sorption, formation of soil aggregates, representative soil minerals, microbial community dynamics, and vegetation interactions—to accurately predict short- and long-term SOM dynamics.

The Impact
This study informs development of a robust predictive understanding of SOM dynamics. However, it is challenging to incorporate recommendations, such as mineral-associated organic matter and vegetation dynamics, in a reactive transport modeling framework. These emergent concepts require emergent technologies to appropriately characterize, e.g., molecular, soil, and root structure. Several technologies (e.g., FT-ICR-MS, NMR, STXM, and NEXAFS) are available today for such characterization, but these technologies have not yet been fully exploited nor have the resulting data/findings been fully incorporated into modeling studies. To enhance process understanding of SOM dynamics, streamlined coordination between technologies for characterization and emerging understanding for SOM modeling are needed.

Summary
Soils represent the largest store of actively cycling terrestrial organic carbon. This carbon is susceptible to release to the atmosphere as greenhouse gases, including carbon dioxide (CO2) and methane (CH4). However, significant gaps remain in understanding why certain soil organic matter (SOM) decomposes rapidly, and why thermodynamically unstable SOM can persist in soils for centuries. To fill this critical knowledge gap, a robust predictive understanding of SOM dynamics is essential, particularly for examining short-term and long-term changes in soil carbon storage and its feedback to climate. In this review paper, the authors argue that a representation of organic matter molecular structure, the activity of belowground communities, and mineral-associated organic matter (MAOM) are required to model SOM dynamics beyond first-order effects accurately. This argument is based on a review of the literature describing the current understanding of the main interacting biological, geochemical, and physical factors leading to SOM stabilization, and on an analysis of a suite of soil carbon models. The authors conclude by recommending several mechanisms that require implementation within the next generation of mechanistic models, including kinetic and equilibrium-based sorption, soil mineral surface chemistry, and vegetation dynamics to accurately predict short- and long-term SOM dynamics.

Contacts
BER Program Manager
Paul Bayer
Department of Energy
Paul.Bayer@science.doe.gov

Principal Investigator
Dipankar Dwivedi
Lawrence Berkeley National Laboratory
ddwivedi@lbl.gov

Funding
This material is based on work supported by the Office of Biological and Environmental Research (as part of the Watershed Function Scientific Focus Area), within the U.S. Department of Energy (DOE) Office of Science, and the Office of Advanced Scientific Computing (as part of the project “Deduce: Distributed Dynamic Data Analytics Infrastructure for Collaborative Environments”), within the DOE Office of Science, under Contract No. DE-AC02-05CH11231. Jinyun Tang acknowledges support from the Next-Generation Ecosystem Experiments (NGEE)–Arctic. The U.S. Department of Agriculture (USDA) National Institute of Food and Agriculture (NIFA) Postdoctoral Fellowship program supported Katerina Georgiou. Nicholas Bouskill acknowledges support from a DOE Early Career Research Project (#FP00005182). William Riley acknowledges support from the Terrestrial Ecosystem Science Scientific Focus Area of Berkeley Lab.

Publications
Dwivedi D, Tang J, Bouskill N, Georgiou K, Chacon SS, Riley WJ. "Abiotic and biotic controls on soil organo–mineral interactions: Developing model structures to analyze why soil organic matter persists." Reviews in Mineralogy and Geochemistry 85(1), 329–348  (2019). [DOI:10.2138/rmg.2019.85.11].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


August 24, 2019

New Approach for Studying How Microbes Influence Their Environment

A diverse group of scientists suggests a common framework and targeting of known microbial processes as a useful approach for understanding the role microbes play in how ecosystems function.

The Science
Co-authors of a paper in Nature Microbiology, including Pacific Northwest National Laboratory’s Emily Graham, propose a new conceptual research framework that would harness the ever-increasing wealth of information on microbiomes. This framework, offered as a new approach to formalizing inquiries into microbiome science, proposes to empirically link three distinct categories of microbiome characteristics to each other and to the broader ecosystem processes they affect. As a result, the framework would reveal how—at the ecosystem level—microorganisms influence the ecological systems they inhabit.

The Impact
The new conceptual framework, informed by decades of research on environmental microbiomes and ecosystem processes, offers a promising pathway for discovering empirical linkages between the microorganisms in an ecosystem and the processes of that ecosystem. The framework would also help focus future research on potential microbiome-ecosystem links that are most likely to be detected empirically.

Summary
Identifying relationships between microbiomes and the ecosystem-level processes they influence is an exceptionally hard research challenge. This situation exists because of the absence of a robust conceptual research framework that would help elucidate underlying causal mechanisms and an explosion in the availability of data on microbiomes in the natural environment. Current research frameworks for understanding the microbial role in ecosystem function are often limited in their applications because they do not align with mechanistic representations of microbial processes in models of ecosystem function.

Presently, causal relationships are implied yet rarely tested, and researchers mostly rely on identifying correlations between microbes and ecosystem properties. Correlative approaches limit the potential to expand the influence of a single microbiome-ecosystem relationship to additional systems, and they do not yield any information on mechanisms that can be transferred across systems. As a result, current frameworks often yield ambiguous results that fail to provide new insights into processes and blur the mechanisms by which microbiomes relate to system-level functioning.

The authors propose a new framework that targets microbial characteristics known to contribute to system-level processes of interest. The framework, intended to link measurable microbiome characteristics with ecosystem-level processes, is constructed based on three distinct categories of microbiome characteristics: microbial processes, microbial community properties, and microbial membership.

From there, the authors show how researchers can use existing methods of investigating microbial ecology to elucidate properties within each of these categories and to connect these three categories of microbial characteristics with each other.

Central to the framework is one particularly important idea: distinguishing microbial community properties that can be predicted (called community aggregated traits) and those that researchers are currently unable to be predict (called emergent properties).

Collectively, the framework introduces a new research paradigm for closing the gaps between empirical investigations and the ecosystem process models they seek to inform.

Contacts
BER Program Manager
Paul Bayer
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Subsurface Biogeochemical Research
paul.bayer@science.doe.gov

Principal Investigator
Emily B. Graham
Quantitative Ecosystem Ecologist, Pacific Northwest National Laboratory
emily.graham@pnl.gov

Funding
This work is a product of the Next Generation of Ecosystem Indicators Working Group, supported by the U.S. Geological Survey John Wesley Powell Center for Synthesis and Analysis. Preparation of this manuscript was supported by National Science Foundation DEB IOS #1456959 awarded to EKH. In addition, this work was also supported by the Office of Biological and Environmental Research, within the U.S. Department of Energy, as part of the Subsurface Biogeochemical Research Scientific Focus Area at Pacific Northwest National Laboratory.

Publication
Hall, E. K., E. S. Bernhard, R. L. Bier, M. A. Bradford, C. M. Boot, J. B. Cotner, P. A. del Giorgio, S. E. Evans, E. B. Graham, S. E. Jones, J. T. Lennon, K. J. Locey, D. Nemergut, B. B. Osborne, J. D. Rocca, J. S. Schimel, M. P. Waldrop, and M. W. Wallenstein. “Understanding how microbiomes influence the systems they inhabit.” Nature Microbiology 9, 977–82 (2018). [DOI: 10.1038/s41564-018-0201-z].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


August 01, 2019

Riverbed Sediment Types are Key for Understanding Biogeochemical Processes in Watersheds

August 2019

The use of riverine facies enables more accurate modeling of hydrologic exchange flows and biogeochemical processes.

The Science
Scientists produced a map that identifies different classes of sediments that compose the riverbed along the Hanford Reach of the Columbia River. These sediment classes, called facies, have distinct textures that play important roles in surface water/groundwater exchanges and biogeochemical activity.

The Impact
The riverbed sediments along the Hanford Reach of the Columbia River are strongly heterogeneous, making it challenging to incorporate their complexity in predictive models. This research categorized the sediments into facies to reduce the complexity of this very heterogeneous system into classes with distinct sediment texture that correspond to variations in hydrologic properties. The use of riverine facies thereby enables more accurate modeling of hydrologic exchange flows and biogeochemical processes.

Summary
In the Hanford Reach of the Columbia River, the texture of sediments on the riverbed have a strong influence on the exchange of groundwater and surface water greatly influences biogeochemical activity. This layer of sediments is strongly heterogeneous, making it a challenge to model, for example, the impact of increased river flows on biogeochemical activity.

To overcome this type of heterogeneity challenge in subsurface aquifers, researchers often make use of facies, a sediment classification scheme that groups complex geologic materials into a set of discrete classes according to distinguishing features. The facies can then be used to assign heterogenous material properties to grid cells of numerical models of aquifers found in the subsurface.

The usefulness of the facies approach, however, hinges on the ability to relate facies to quantitative properties needed for flow and reactive transport modeling. Previous research has shown that the grain size distribution of sediments in the riverbed is associated with properties of interest to the exchange of groundwater and surface water and related biogeochemical activity. Direct observational data on grain size distribution in the Hanford Reach of the Columbia River, however, is limited to selected locations with inadequate spatial coverage and resolution.

To map facies in the Hanford Reach of the Columbia River, the authors integrated high-resolution observations such as the river geomorphology, depth, slope, and signs of erosion with numerical simulations of historical river flows such as floods that are known to shape sediment texture by washing rocks and pebbles downstream. The team used machine-learning models to determine which factors have the best correspondence with distinct distributions of sediment texture, creating a facies map with four classes of sediment textures that correspond to variations in hydrologic properties.

Identification and mapping of facies in the Hanford Reach of the Columbia River will enable more accurate modeling of the behavior of surface water/groundwater exchanges as well as biogeochemical activity within the system. This understanding will enable more robust predictions of the fate and migration of groundwater contaminant plumes from the Hanford Site as well as the impact of nearby agricultural practices on biogeochemical activity in the river system.

Contacts
BER Program Manager
Paul Bayer
Department of Energy
Paul.Bayer@science.doe.gov

Principal Investigator
Zhangshuan Hou
Northwest National Laboratory
Zhangshuan.Hou@pnnl.gov

Funding
Funding for this research came from the Office of Biological and Environmental Research, within the U.S. Department of Energy (DOE) Office of Science, and Pacific Northwest Laboratory Subsurface Biogeochemical Research SFA.

Publications
Hou, Z., Scheibe, TD, Murray, CJ, et al. "Identification and mapping of riverbed sediment facies in the Columbia River through integration of field observations and numerical simulations." Hydrological Processes 33(8), 1245–59 (2019). [DOI:10.1002/hyp.13396].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


July 08, 2019

Predictive Numerical Modeling Provides Insights into Changes in Contaminant Mobility Under Increased and Extreme Precipitation Scenarios

Untangling the complex interactions between contaminant dilution and re-mobilization accompanying significant precipitation increases through numerical simulation.

The Science
Climate change—through precipitation regime shifts or extreme precipitation events—can have a significant impact on the mobility of residual contaminants at sites where remediation solutions and management are based on an expected range of site conditions. This study used numerical simulations to evaluate and quantify the impact of such shifts or events; in particular, the competing factors of dilution and re-mobilization. Results showed that contaminant concentrations immediately decreased following extreme precipitation events due to dilution, but subsequently increased several years later due to re-mobilization of contaminants from the source zone.

The Impact
The impact of changes in contaminant mobility and concentration due to extreme precipitation and shifts in the precipitation regime were found to last for several decades, depending on monitoring well locations, performance metrics and site conditions. The results of this study suggested critical considerations for the design of long-term engineered systems such as surface capping structures, and for not only monitoring their efficacy, but also for defining threshold levels of precipitation that could drastically alter the system behavior.

Summary
Through numerical modeling of un-saturated/saturated flow and transport, a team of scientists evaluated the effect of increasing and decreasing precipitation, as well as the impact of potential failure of surface barrier systems. The approach was demonstrated using a case study involving the simulation of the transport of non-reactive radioactive tritium at the U.S. Department of Energy's Savannah River Site F-Area. Results showed that such hydrological changes significantly impact groundwater concentrations. After an initial dilution effect, the modeling results identified a significant concentration increase some years later as a consequence of contaminant mobilization. Threshold levels of precipitation were identified, above which the contaminant concentration/exports were affected. The results suggest the importance of source zone monitoring to detect re-mobilization and highlight surface barrier design requirements needed to reduce the impact of hydrological changes.

Contacts
BER Program Manager
Paul Bayer
Department of Energy
Paul.Bayer@science.doe.gov

Principal Investigator
Haruko Wainwright
Lawrence Berkeley National Laboratory
HMWainwright@lbl.gov

Funding
This material is based upon work supported as part of the ASCEM project, which is funded by the U.S. Department of Energy (DOE) Office of Environmental Management, and as part of the Lawrence Berkeley National Laboratory (LBNL) Science Focus Area, which is funded by the Office of Biological and Environmental Research within the DOE Office of Science, both under Award Number DE-AC02-05CH11231 to LBNL. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science user facility supported by the DOE Office of Science under Contract No. DE-AC02-05CH11231. The first and second authors acknowledge the support by the National Science Foundation under Grant No. 1654009.

Publications
Libera, A., de Barros, F. P., Faybishenko, B., Eddy-Dilek, C., Denham, M., Lipnikov, K., Moulton, J. D., Maco, B. & Wainwright, H. (2019). Climate change impact on residual contaminants under sustainable remediation. Journal of Contaminant Hydrology 226103518 (2019). [DOI:10.1016/j.jconhyd.2019.103518].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


June 17, 2019

Using Remote Sensing to Determine the Relationship Between Soil Conditions and Plant Communities 

Combining above- and belowground measurements of a mountainous meadow plant community and soil characteristics to infer important patterns of ecosystem heterogeneity.

The Science
Integration of high-resolution remote sensing and geophysical data for the investigation of the co-variability between plant community distributions, soil electrical conductivity, and microtopographical properties was used to assess the spatial organization of meadow plants within a floodplain-hillslope system at the East River watershed in Colorado.

The Impact
This study fused satellite and Light Detection and Ranging (LiDAR) data, along with site characterization data to arrive at estimates of key meadow communities at high resolution. This type of information could be used on large scales to provide information on the spatial variability of soil properties, and it could also be used to capture plant community responses to perturbations over significant landscape areas.

Summary
In this study, the authors aimed to understand how soil and topographic properties influence the spatial distribution of plant communities within a floodplain-hillslope system, located in the mountainous East River watershed in Colorado. Watersheds are vulnerable to environmental change, including earlier snowmelt, changes in precipitation, and temperature trends, all of which can alter plant communities and associated water and nutrient cycles within the watershed. However, tractable yet accurate quantification of plant communities is challenging to do at a scale that also permits investigations of the key controls on their distribution. In this work, the team developed a framework that uses a new approach to estimate plant distributions, one which exploits both remote sensing (satellite) images and surface geophysical data. Joint consideration of the above-and-belowground datasets allowed the team to characterize both plant and soil properties at high spatial resolution and to identify the main environmental controls for plant distribution. The results show that soil moisture and microtopography strongly influence how plant communities are spatially distributed. Considering that each community responds to external perturbation in a different way, this method can be used within a multi-temporal framework to characterize environmental heterogeneity and to capture plant responses caused by climate-related perturbations.

Contacts
BER Program Manager 
Paul Bayer
Department of Energy
paul.bayer@science.doe.gov

Principal Investigator
Nicola Falco
Lawrence Berkeley National Laboratory
nicolafalco@lbl.gov

Funding
This work was supported by the Office of Biological and Environmental Research within the U.S. Department of Energy Office of Science. 

Publication
N. Falco, H. M. Wainwright, B. Dafflon, E. Léger, J. Peterson, H. Steltzer, C. Wilmer, J. C. Rowland, K. H. Williams, and S. S. Hubbard, “Investigating Microtopographic and Soil Controls on a Mountainous Meadow Plant Community Using High-Resolution Remote Sensing and Surface Geophysical Data.” Journal of Geophysical Research: Biogeosciences 124(6), 1618–36 (2019). [DOI:10.1029/2018JG004394].

Related Links
Data DOI: https://doi.org/10.21952/WTR/1490867

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


June 11, 2019

Predicting How Microbial Neighbors Influence Each Other

A new computational method reliably predicts interactions that depend on neighboring organisms in an environment.

The Science
Microbes in the soil form networks, which in turn make up larger communities. As the environment changes, so do the microbes and their relationships. For scientists to design or control these microbes, they must first understand their communities in nature (microbiomes). Soil ecologists know well that neighboring species influence some microbial interactions.  Researchers developed a new theoretical framework called minimal interspecies interaction adjustment (MIIA). It predicts how surrounding organisms and other factors drive changes in interactions in microbial communities.

The Impact
This new computational method improves the understanding of how microbes organize themselves into communities. It describes in detail how neighboring species affect interactions between microbes. This method also predicts major shifts in microbes’ influence on carbon and nitrogen cycles. This information could enable scientists to design and engineer groups and communities of microbes in the future.

Summary
Microbial community dynamics in soil and other habitats involve nonlinear interspecies interactions, so these dynamics are notoriously difficult to predict. Yet understanding how such microbiomes are organized in nature is necessary for designing them (such as for biofuel production) and for controlling them—for example, as a way to ensure that soils do not emit too much carbon into the Earth’s atmosphere. Meanwhile, ecologists know that interactions in microbial communities are influenced by neighboring species, or which organisms are around them. Until now, however, there has been no theoretical framework that can predict such context-dependent microbial interactions.

The research was motivated by the following fundamental ecological questions: How are interspecies interactions modulated by shifts in community composition and species populations? To what extent can interspecies relationships observed in simple cultures be translated into complex communities?

The researchers addressed these questions by demonstrating that the theoretical framework enables microbial interactions in binary, or one-to-one, cultures to be translatable into complex communities. The researchers also demonstrated the utility of this method in designing and engineering microbial consortia. In this regard, they found that microbial interactions can be significantly modulated when perturbed by a small number of neighboring species—but that the level of modulation diminishes as the number of new neighboring species increases.

This work, the authors say, can also be applied to questions of community ecology beyond microbes. It may provide a theoretical platform for better understanding all biological interaction systems.

Contacts
BER Program Manager
Dawn Adin
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Biological Systems Science Division (SC-23.2)
Foundational Genomics Research
dawn.adin@science.doe.gov

Principal Investigators
Hyun-Seob Song
Pacific Northwest National Laboratory
HyunSeob.Song@pnnl.gov

Janet Jansson
Pacific Northwest National Laboratory
janet.jansson@pnnl.gov

Funding
This research was supported by the Office of Biological and Environmental Research within the U.S. Department of Energy Office of Science, as part of the Foundational Scientific Focus Area (SFA), Soil Microbiome, and the Subsurface Biogeochemistry Research (SBR) SFA at Pacific Northwest National Laboratory.    

Publications
Song, H-S., J-Y. Lee, S. Haruta, W. C. Nelson, D-Y. Lee, S. R. Lindemann, J. K. Fredrickson, and H. C. Bernstein, “Minimal interspecies interaction adjustment (MIIA): Inference of neighbor-dependent interactions in microbial communities,” Frontiers in Microbiology 10, 1264 (2019). [DOI:10.3389/fmicb.2019.01264].

Topic Areas:

Division: SC-33.2 Biological Systems Science Division, BER


June 03, 2019

Multi-Omics Data are Key to Advancing Reactive Transport Models

3 June 2019

An overview of recent advances in reactive transport models identifies multi-omics data as the "current frontier" for understanding system-scale microbial behavior and dynamics.

The Science 
Reactive transport models (RTMs) are used to describe and predict the distribution of chemicals in time and space, in both marine and terrestrial (surface and near-surface) environments where microbially mediated processes govern biogeochemical patterns. Yet, challenges exist in modeling microbially driven systems, as well as in integrating data across the vast range of scales relevant to models of biogeochemical cycling.

In the April 2019 topical issue of the journal Elements on reactive transport modeling, Tim Scheibe of Pacific Northwest National Laboratory (PNNL) and coauthor Chistof Meile of the University of Georgia discuss common approaches that have been used to incorporate microbial community interactions and their influence on geochemical processes in RTMs, and future opportunities to leverage new instrument and data capabilities—including multi-omics—to create new and more realistic modeling approaches.

In particular, the authors argue that RTMs with multi-omics will help advance understanding of how complex microbial communities respond to environmental changes. These new models will also help identify microbial impacts on local and global elemental cycling, the fate of contaminants, redox transformations, and other processes mediated by microorganisms.

The Impact
Integrating multi-omics data into RTMs will improve predictive understanding of critical watershed processes such as carbon and nitrogen cycling within those watersheds and more broadly. Modeling informed by multi-omics will also reveal how critical microbial processes change in response to environmental perturbations—an urgent imperative for watersheds subject to increasingly frequent or sustained perturbations.

Summary
Representation of microbial processes in RTMs has advanced significantly over the past few decades, accounting for dynamic changes in biomass, functional regulation in response to environmental changes, and thermodynamic constraints. Current RTMs represent microbial functions with greater process fidelity and reduced empiricism.

The authors say that incorporating multi-omics data is a current frontier in RTMs, and offers great potential for improving scientific understanding of microbial processes and predictive modeling. To that end, they are engaged in research to integrate complex metagenomics, metabolomics, and other omics data into reaction network models. In turn, these can be linked with state-of-the-art RTMs in order to simulate system-scale behavior.

In the article, the authors introduce relevant case studies and discuss ways to integrate multi-omics data to inform and validate RTMs. Their results advance and enhance those modeling capabilities by identifying and promoting how to integrate multi-omics data into microbial models.

The result, the authors say, will be an improved predictive understanding of critical watershed processes such as carbon and nitrogen cycling within specific watersheds and more broadly. Modeling informed by multi-omics will also reveal how critical microbial processes change in response to environmental perturbations.

Funded by the Department of Energy’s (DOE) Biological and Environmental Research (BER) program, this article addresses BER’s mission to advance predictive understanding of how hydro-biogeochemically complex watersheds function by promoting a vision of microbial process modeling informed by omics data. The article also promotes the use of DOE-funded capabilities such as the Systems Biology Knowledgebase (KBase), and user facilities such as the Environmental Molecular Sciences Laboratory (EMSL) and the Joint Genome Institute.

With support from DOE’s Subsurface Biogeochemical Research (SBR) program, Scheibe and fellow scientists recently organized a  workshop to build a community of researchers around these ideas and to promote new advancements.

Contacts
BER Program Manager
Paul Bayer
U.S. Department of Energy, Office of Biological and Environmental Research
Paul.Bayer@science.doe.gov

Principal Investigator
Timothy D. Scheibe
Pacific Northwest National Laboratory
Tim.Scheibe@pnnl.gov

Funding
Subsurface Biogeochemical Research (SBR) program of the Office of Biological and Environmental Research (BER) within the U.S. Department of Energy Office of Science.  

Publication
Meile, C., and Scheibe, T.D. "Reactive transport modeling of microbial dynamics." Elements 15(2), 111–16 (2019). [DOI:10.2138/gselements.15.2.111].

Related Links

 

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


May 29, 2019

Insights into the Ecology, Evolution, and Metabolism of the Widespread Woesearchaeotal Lineages

May 29, 2019

Genome analyses and metabolic reconstructions of Woesearchaeota suggest heterotrophic lifestyles that are dependent on metabolic complementarity with other microbes.

The Science
Genomic analysis reveals the distribution of Woesearchaea across multiple habitat types. Metabolic reconstructions support an anaerobic, heterotrophic lifestyle albeit one with conspicuous deficiencies consistent with their inferred dependence on other microbes.

The Impact
The findings provide an ecological and evolutionary framework for Woesearchaeota at a global scale and indicate their potential ecological roles, especially in methanogenesis.

Summary
A large group of genomes for Woesearchaeota were analyzed and the organisms grouped into sublineages based on their DNA sequences. These archaea were found to be widely distributed in different types of environments, but they are primarily found in anaerobic terrestrial environments. Ecological patterns analysis and ancestor state reconstruction for specific subgroups reveal that the presence of oxygen is the key factor driving the distribution and evolutionary diversity of Woesearchaeota. A selective distribution to different biotopes and an adaptive colonization from oxygen free environments is proposed and supported by evidence of the presence of ferredoxin-dependent pathways in the genomes derived from anaerobic environments. Metabolic reconstructions support heterotrophic lifestyles, with conspicuous metabolic deficiencies, suggesting the requirement for metabolic complementarity with other microbes. Lineage abundance, distribution, and co-occurrence network analyses across diverse environments confirmed metabolic complementation and revealed a potential syntrophic relationship between Woesearchaeota and methanogens.

Contacts
BER Program Manager
Paul Bayer
Department of Energy
paul.bayer@science.doe.gov

Principal Investigator
Jillian Banfield
Lawrence Berkeley National Laboratory
jbanfield@lbl.gov

Funding
This work was supported by the Office of Biological and Environmental Research within the U.S. Department of Energy Office of Science.

Publication
X. Liu, M. Li, C.J. Castelle, A.I. Probst, Z. Zhou, J. Pan, Y. Liu, J.F. Banfield, J.D. Gu “Insights into the ecology, evolution, and metabolism of the widespread Woesearchaeotal lineages” Microboime, 6, 102 (2018). [DOI:10.1186/s40168-018-0488-2].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


May 29, 2019

Major New Microbial Groups Expand Diversity and Understanding of the Tree of Life

May 29, 2019

New evolutionary patterns and diversity revealed from genome-resolved metagenomics.

The Science
Understanding of microbial diversity has been dramatically expanded through analysis of genomes from groups of organisms previously inaccessible to laboratory-based identification and characterization.  

The Impact
Analysis of genomes from little-explored subsurface environments has uncovered new evolutionary patterns, including a group that may be ancestral to Eukaryotes, humanity’s own branch of life. Also evident are two major radiations of microorganisms that appear to live primarily via symbiosis with other bacteria and archaea. These organisms have ecosystem importance via impacts on their hosts, geochemical cycling, and potentially play roles in agriculture and human health.

Summary
The tree of life is arguably the most important organizing principle in biology and perhaps the most widely understood depiction of the evolutionary process. It explains how humanity is related to other organisms and where we may have come from. The tree has undergone some tremendous revolutions since the first version was sketched by Charles Darwin. A major innovation was the construction of phylogenetic trees using DNA sequence information, work that enabled the definition of the three domains of life: Bacteria, Archaea, and Eukaryotes. More recently, the three-domain topology has been questioned, and eukaryotes potentially relocated into the archaeal domain. Beyond this, and as described here, cultivation-independent genomic methods that access sequences from organisms that resist study in the laboratory have added many new lineages to the tree. Their inclusion clarifies the minority of life’s diversity represented by macroscopic, multi-celled organisms and underscores that humanity’s place in biology is dwarfed by bacteria and archaea.

Contacts
BER Program Manager 
Paul Bayer
Department of Energy
paul.bayer@science.doe.gov

Principal Investigator
Jillian Banfield
Lawrence Berkeley National Laboratory
jbanfield@lbl.gov

Funding
Support was provided by grants from the Lawrence Berkeley National Laboratory’s Genomes-to-Watershed Scientific Focus Area. The Office of Biological and Environmental Research within the U.S. Department of Energy (DOE) Office of Science funded the work under contract DE-AC02-05CH11231 and the DOE carbon cycling program DOE-SC10010566, the Innovative Genomics Institute at Berkeley and the Chan Zuckerberg Biohub.

Publication
C. J. Castelle and J. F. Banfield. “Major New Microbial Groups Expand Diversity and Alter our Understanding of the Tree of Life.” Cell 172(6), 1181–97 (2018). [DOI:10.1016/j.cell.2018.02.016].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


May 29, 2019

Recovery of Genomes from Complex Environmental Samples is Greatly Improved using a Novel Analytics Tool 

May 29, 2019

The Science
Genomes reconstructed directly from DNA sequences sampled from natural environments have revolutionized scientific understanding of microbial diversity and evolution. While this process can be difficult, a new automated method called DAS Tool integrates a flexible number of binning algorithms to calculate an optimized, non-redundant set of bins from a single assembly, thereby greatly improving the recovery of genomes from natural environments.

The Impact
The recovery of genomes, especially from complex environments such as soil, will be facilitated by the new automated DAS Tool.

Summary
Understanding of the metabolic capacities of microorganisms in natural environments is critical to prediction of ecosystem function. Analysis of organism-specific metabolic pathways and reconstruction of community interaction networks requires high-quality genomes. However, existing binning methods often fail to reconstruct a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and environment types. A dereplication, aggregation and scoring strategy, DAS Tool, was developed. This algorithm combines the strengths of a flexible set of established binning algorithms. DAS Tool applied to a constructed community generated more accurate bins than any automated method. Indeed, when applied to environmental and host-associated samples of different complexity, DAS Tool recovered substantially more near-complete genomes, including those for organisms from previously unreported lineages, than any single binning method alone. The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.

Contacts
BER Program Manager
Paul Bayer
Department of Energy
paul.bayer@science.doe.gov

Principal Investigator
Jillian Banfield
University of California, Berkeley
jbanfield@berkeley.edu

Funding
This work was supported in part by the Office of Biological and Environmental Research withn the U.S. Department of Energy Office of Science.

Publication
C.M.K. Sieber, A.J. Probst, A. Sharrar, B.C. Thomas, M. Hess, S.G. Tringe, and J.F. Banfield “Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy.” Nature Microbiology 3, 836 (2018). [DOI:10.1038/s41564-018-0171-1].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


May 28, 2019

Mechanisms of Groundwater Recharge in a Snowmelt-Dominated Headwater Basin

May 28, 2019

Snowmelt transported laterally through regolith material in the subsurface from mountain ridges to upper subalpine areas forms a preferential recharge zone resilient to drought.

The Science
LiDAR-derived snow observations are combined with an integrated hydrologic model to quantify spatially and temporally distributed water fluxes across varying climate conditions, and to understand the sensitivity of groundwater generation to snow dynamics, vegetation, and topography in a Colorado River headwater basin.

The Impact
The results of this work indicate that snowmelt is focused via interflow from steep, mountain ridges into the upper subalpine where slopes flatten and sparse conifer forests begin to grow. This mechanism of recharge appears resilient to drought and may buffer recharge under climate change. Seasonal snowmelt and water use by plants regulate small recharge rates in the lower elevations of this mountainous basin. Understanding the key mechanisms of groundwater recharge in headwater basins allows scientists to better predict headwater stream responses to precipitation changes, thereby improving water and environmental management.

Summary
Accumulated snow in mountain basins is a critical water source but little is known about how groundwater is influenced by changing snowpack. Airborne observations of mountain snowpack are combined with a physically based hydrologic model to better understand how snowmelt is partitioned across the landscape and routed to streams. Results indicate that groundwater is an important and stable source of water to a mountain stream, with the relative fraction of groundwater increasing during drought as a function of increased plant water use and decreased lateral soil water flow (called ‘interflow’). The study finds that the dominant mechanism generating groundwater is topography. Specifically, snowmelt is focused via interflow from steep mountain ridges into the upper subalpine. This mechanism of recharge appears resilient to drought. Lower in the basin, snowmelt occurs before peak vegetation water use to allow for some groundwater generation. Interflow and monsoon rains then subsidize plant water use once snowmelt ceases but do not generate substantive recharge.

Contacts
BER Program Manager
Paul Bayer
Department of Energy
paul.bayer@science.doe.gov

Principal Investigator
Rosemary Carroll
Desert Research Institute
Rosemary.carroll@dri.edu

Funding
This work was supported by the Office of Biological and Environmental Research within the U.S. Department of Energy Office of Science, and the U.S. Geological Survey 104(g) Grant/Cooperative Agreement No. G16AP00196.

Publication
R. W. H. Carroll, J. S. Deems, R. Niswonger, R. Schumer, and K. H. Williams. “The Importance of Interflow to Groundwater Recharge in a Snowmelt-Dominated Headwater Basin.” Geophysical Research Letters 46(11), 5899–5908 (2019). [DOI:10.1029/2019GL082447].

Related Links
Model input and output files: DOI:10.21952/WTR/1508390.

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


April 10, 2019

New Model Enables Scientists to Predict Hydrologic Exchange Fluxes at River Reach Scale

10 April 2019

Fluid dynamics modeling along a 7-kilometer river reach reveals factors controlling large-scale hydrologic exchange fluxes. 

The Science
Hydrologic exchange fluxes (HEFs) between rivers and surrounding subsurface environments strongly influence water temperatures and biogeochemical processes. Yet, quantitative measures of their effects on the strength and direction of such exchanges in large rivers are lacking. A study reported in Hydrological Processes, led by scientists at Pacific Northwest National Laboratory (PNNL), demonstrates the efficacy of a new coupled surface and subsurface fluid dynamics model in quantifying HEFs at kilometer scales. 

The Impact
In a world where dam-regulated river corridors are increasingly common, quantifying HEFs and their effects at river-reach scales is vitally important in protecting water quality and ecosystem health. Through three-dimensional (3D) application of computational fluid dynamics (CFD) modeling, combined with uncertainty quantification tools, the new model can quantify HEFs in a large-scale river channel extending 1 km wide and 7 km long. This a dramatic improvement over traditional simulations, which (at most) model just a few hundred meters of river corridor. 

Summary
HEFs are critical to shaping hydrological and biogeochemical processes along river corridors. Yet, in current research, numerical modeling studies to quantify riverine HEFs are typically confined to local-scale simulations in which the river is a few meters wide and up to a just few hundred meters long. Even then, such studies are challenging because of high computational demands and the complexity of riverine geomorphology and subsurface geology. In addition, there are limitations in field accessibility, and the physical demands of labor-intensive data collection along river shorelines. 

A new model, developed by a multi-institutional team, addresses these challenges. Their recently published paper in Hydrological Processes demonstrates a new coupled surface and subsurface water flow model that can be applied at large scales. 

The new model was validated against field-scale observations—including velocity measurements from an acoustic Doppler current profiler, a set of temperature profilers installed across the riverbed to measure vertical HEFs, and simulations from PFLOTRAN (a reactive transport model). Then, along a 7-km segment of the Columbia River that experiences high dam-regulated flow variations, the model was used to systematically investigate how HEFs could be influenced by surface water fluid dynamics, subsurface structures, and hydrogeological properties. 

The simulations demonstrated that reach-scale HEFs are dominated by the thickness of the riverbed alluvium layer, followed by alluvium permeability, the depth of the underlying impermeable layer, and the pressure boundary condition. 

These results are being used to guide the design and placement of new field sensor systems that will further enhance scientific understanding of HEFs in large dam-regulated rivers.

Contacts
BER Program Manager
Paul Bayer
U.S. Department of Energy Office of Biological and Environmental Research
Paul.Bayer@science.doe.gov 

Principal Investigator
Jie Bao
Pacific Northwest National Laboratory
Jie.Bao@Pnnl.gov 

Funding
Funding was provided by the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy (DOE), as part of the BER’s Subsurface Biogeochemistry Research (SBR) program.  This research is part of the SBR Scientific Focus Area project at PNNL.

Publication
Bao, J., T. Zhou, M. Huang, Z. Hou, W. Perkins, et al. “Modulating factors of hydrologic exchanges in a large-scale river reach: Insights from three-dimensional computational fluid dynamics simulations.” Hydrological Processes 32(23), 3446–63 (2018). [DOI:10.1002/hyp.13266].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


April 09, 2019

Improving Measurements of CO2 Fluxes from Landscapes

Understanding the links between instances of large swirling winds and CO2 fluxes is critical for closing the energy balance of the land surface and interpreting turbulent heat and carbon exchanges.

The Science
Turbulent vertical fluxes of heat, water vapor, and carbon dioxide (CO2) occur constantly between land surfaces and the atmosphere. For decades, measuring such fluxes has relied on eddy covariance (EC), a complex statistical technique. However, most studies using EC are unable to close the surface-energy balance between sensible and latent heat fluxes. This widely reported gap, known as the nonclosure problem of the surface energy balance, is commonly attributed to the influence of large-scale eddies of swirling wind on both kinds of heat fluxes.

A new paper by scientists at Washington State University and Pacific Northwest National Laboratory provides new insights into EC by investigating two understudied issues: (1) how CO2 fluxes are influenced by large eddies and (2) the mechanistic links between CO2 fluxes and energy balance nonclosure.

The results demonstrate, in part, that reductions in the magnitude of CO2 fluxes associated with large turbulent eddies are mechanistically linked to nonclosure of the surface energy budget.

The Impact
The research findings improve understanding of how nonclosure of the surface-energy balance impacts measurements of CO2 fluxes. They also provide direct evidence that further studies are needed to investigate how landscape heterogeneity—in this case, sagebrush terrain—influences CO2 fluxes.

Summary
The new study relies on a dataset collected by an EC flux system in a semi-arid sagebrush ecosystem in the Hanford Area of rural southeastern Washington. The research shows a link between nonclosure and reduced CO2 fluxes associated with large turbulent eddies. It attributes that link to the simultaneous influence of low-frequency motions on sensible and latent heat fluxes and on CO2 fluxes.

The researchers used a recently developed approach, ensemble empirical mode decomposition, to extract large eddies from the turbulence time series. Then they analyzed the impacts of amplitude and phase differences on flux contribution.

One challenge in this work was identifying occasional spectral gaps, especially under unstable atmospheric conditions when convective motions tend to overlap the scales between large eddies and small eddies. Based on previous work by these scientists, the authors defined large eddies as the sum of a certain number of oscillatory components that are largely responsible for the run-to-run variations in fluxes. There was no surprise at the nonclosure of the surface energy balance and therefore biases in CO2 fluxes. However, the researchers found that the energy balance closure ratio decreased as atmospheric instability increased. The underlying causes of that remain unclear. Work on finding those causes is underway.

The research team, which also includes researchers from Lanzhou University in China, collected the high-quality data from three eddy covariance flux sites within the Hanford Area.

Contacts
BER Program Manager
Paul Bayer
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Subsurface Biogeochemical Research
paul.bayer@science.doe.gov

Principal Investigator
Heping Liu
Washington State University
heping.liu@wsu.edu

Funding
This work was supported by the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy (DOE), as part of BER’s Subsurface Biogeochemical Research Program (SBR) at the Pacific Northwest National Laboratory.

Publications
Gao, Z., H. Liu, J. E. C. Missik, J. Yao, M. Huang, X. Chen, E. Arntzen, and D. P. McFarland. “Mechanistic links between underestimated CO2 fluxes and non-closure of the surface energy balance in a semi-arid sagebrush ecosystem.” Environmental Research Letters 14(4), 044016 (2019). [DOI:10.1088/1748-9326/ab082d].

Related Links

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


April 01, 2019

Multiomics Data Are Key to Advancing Reactive Transport Models

An overview of recent advances in reactive transport models identifies multiomics data as the “current frontier” for understanding system-scale microbial behavior and dynamics.

The Science
Reactive transport models (RTMs) are used to describe and predict the distribution of chemicals in time and space, in both marine and terrestrial (surface and near-surface) environments where microbially mediated processes govern biogeochemical patterns. Yet, challenges exist in modeling microbially driven systems, as well as in integrating data across the vast range of scales relevant to models of biogeochemical cycling.

In the April 2019 topical issue of the journal Elements on reactive transport modeling, Tim Scheibe of Pacific Northwest National Laboratory (PNNL) and coauthor Chistof Meile of the University of Georgia discuss common approaches that have been used to incorporate microbial community interactions and their influence on geochemical processes in RTMs, as well as future opportunities to leverage new instrument and data capabilities—including multiomics—to create new and more realistic modeling approaches.

In particular, the authors argue that RTMs with multiomics will help advance understanding of how complex microbial communities respond to environmental changes. These new models will also help identify microbial impacts on local and global elemental cycling, the fate of contaminants, redox transformations, and other processes mediated by microorganisms.

The Impact
Integrating multiomics data into RTMs will improve predictive understanding of critical watershed processes such as carbon and nitrogen cycling within those watersheds and more broadly. Modeling informed by multiomics will also reveal how critical microbial processes change in response to environmental perturbations—an urgent imperative for watersheds subject to increasingly frequent or sustained perturbations.

Summary
Representation of microbial processes in RTMs has advanced significantly over the past few decades, accounting for dynamic changes in biomass, functional regulation in response to environmental changes, and thermodynamic constraints. Current RTMs represent microbial functions with greater process fidelity and reduced empiricism.

The authors say that incorporating multiomics data is a current frontier in RTMs, and offers great potential for improving scientific understanding of microbial processes and predictive modeling. To that end, they are engaged in research to integrate complex metagenomics, metabolomics, and other omics data into reaction network models. In turn, these can be linked with state-of-the-art RTMs to simulate system-scale behavior.

In the article, the authors introduce relevant case studies and discuss ways to integrate multiomics data to inform and validate RTMs. Their results advance and enhance those modeling capabilities by identifying and promoting how to integrate multiomics data into microbial models.

The result, the authors say, will be an improved predictive understanding of critical watershed processes such as carbon and nitrogen cycling within specific watersheds and more broadly. Modeling informed by multiomics will also reveal how critical microbial processes change in response to environmental perturbations.

Funded by the Department of Energy’s (DOE) Biological and Environmental Research (BER) program, this article addresses BER’s mission to advance predictive understanding of how hydro-biogeochemically complex watersheds function by promoting a vision of microbial process modeling informed by omics data. The article also promotes the use of DOE-funded capabilities such as DOE’s Systems Biology Knowledgebase (KBase), and DOE user facilities such as the Environmental Molecular Sciences Laboratory (EMSL) and Joint Genome Institute.

With support from DOE’s Subsurface Biogeochemical Research (SBR) program, Scheibe and fellow scientists recently organized a  workshop to build a community of researchers around these ideas and to promote new advancements.

Contacts (BER PM)
Paul Bayer
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Subsurface Biogeochemical Research and DOE Environmental Molecular Sciences Laboratory
paul.bayer@science.doe.gov

PI Contact
Timothy D. Scheibe
Pacific Northwest National Laboratory
Tim.Scheibe@pnnl.gov

Funding
U.S. Department of Energy, Office of Science, Biological and Environmental Research (BER), Subsurface Biogeochemical Research (SBR) program.

Publication
Meile, C., and T. D. Scheibe. “Reactive transport modeling of microbial dynamics.” Elements 15(2), 111–16 (2019). [DOI: 10.2138/gselements.15.2.111]

Related Links

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


March 15, 2019

Assessing Sources of Uncertainty in Predictions from a Reactive Transport Model

Researchers used Bayesian networks to develop a new method for measuring and ranking which components contribute the most uncertainty to outputs from a reactive transport model.

The Science
A multi-institutional team of scientists developed a new sensitivity analysis framework using Bayesian networks to quantify which parameters and processes in complex multiphysics models are least understood. The method can guide continued development and refinement of predictive models of environmental systems by highlighting which components of complex systems require enhanced characterization data to reduce uncertainty.

The Impact
Sensitivity analysis is a numerical tool used to identify important parameters and processes that contribute to the overall uncertainty in model outputs. This new research applies a Bayesian network approach to sensitivity analysis frameworks. This approach increases the flexibility and power of the sensitivity analysis by quantifying the uncertainty contribution from a variety of controlling factors and ranking them; the results can better inform decisions on where to focus resources to improve the predictive capability of various multiphysics models.

Summary
Numerical modeling is an important tool for predicting the future behavior of complex systems that impact the environment and for managing natural resources. For example, Pacific Northwest National Laboratory researchers are developing numerical models to study the factors that control the exchange of river and groundwater in the Hanford Reach, the last free-flowing stretch of the Columbia River that defines the north and east boundaries of the Department of Energy’s Hanford Site.

Predictive uncertainty is inevitable in numerical models of systems such as the Hanford Reach because of the complex hydrological and biogeochemical properties of the natural system and limited site characterization data. To effectively and efficiently reduce predictive uncertainty with limited resources, researchers perform sensitivity analysis to rank the importance of different uncertainty sources that contribute to overall uncertainty in model predictions.

Current state-of-the-art sensitivity analysis frameworks are unable to describe the entire range of uncertainty sources involved in predictive models of complex systems. The integration of Bayesian network-based methods into these frameworks allows the full representation of uncertainty sources and the relationships between them, opening the door to performing sensitivity analysis on complex systems. For example, the networks allow researchers to computationally and graphically understand how uncertainty in one node of the network, or group of nodes, propagates through a network and impacts a model’s overall predictive uncertainty.

The authors implemented their Bayesian network–based method on a real-world biogeochemical model of the groundwater–surface water interface within the Hanford Site’s 300 Area. They used the framework to run model simulations to predict how factors such as variation in river stage under future climate scenarios and the release or damming of water in upstream hydroelectric dams would contribute to variations in groundwater–surface water exchange and impact biogeochemical processes that affect the rate of organic carbon consumption.

The team found that groundwater flow and reactive transport processes contribute most significantly to the predictive uncertainty in carbon consumption rate, and that future states of the climate, which defines the system’s driving forces, were less significant. Further analysis of the uncertainty contributed by groundwater flow processes revealed that the geological structural information, such as the thickness of the confining layer between the river and groundwater, was more important than the within-formation permeability field in controlling the flow processes.

The Bayesian network–based methodology in this research was implemented on a complex biogeochemical model of the Hanford Site 300 area, but it is mathematically rigorous and generally applicable for reducing uncertainty in a wide range of Earth system models.

Contacts
BER Program Manager
Paul Bayer
U.S. Department of Energy, Office of Biological and Environmental Research
Paul.Bayer@science.doe.gov

Principal Investigator
Xingyuan Chen
Pacific Northwest National Laboratory
Xingyuan.Chen@pnnl.gov

Funding
Funding for this research came from the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy (DOE) Office of Science, Subsurface Biogeochemical Research SFA at Pacific Northwest National Laboratory.

Publication
Dai, H., Chen, X., Ye, M., Song, X., Hammond, G., Hu, B., & Zachara, J.M. "Using Bayesian networks for sensitivity analysis of complex biogeochemical models." Water Resources Research 55(4), 3541–55 (2019). [DOI:10.1029/2018WR023589].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


February 19, 2019

Hexavalent Uranium Storage Mechanisms in Wet-Dry Cycled Sediments at Contaminated DOE Sites in the Western United States

February 19, 2019

New process observed for uranium accumulation and release at contaminated DOE sites.

The Science 
Sediments enriched in organic carbon are known for their remarkable ability to accumulate uranium in its reduced form, U(IV), which is sparingly soluble in groundwater, and to slowly release this uranium when it re-oxidizes to the soluble and mobile form, hexavalent uranium [U(VI)]. These sediment-groundwater interactions are important to DOE because they contribute to prolonged uranium groundwater plumes and render them extremely difficult to remediate at contaminated DOE legacy ore processing sites in Colorado, Wyoming, New Mexico, and the intermountain West. The research team used X-ray absorption and Mössbauer spectroscopy, hydrological and pore water analyses, sediment extractions, and elemental and mineralogical correlations to show that a large fraction of uranium accumulated in organic-enriched sediments at the contaminated Shiprock, New Mexico, site is present as solid-associated hexavalent uranium. U(VI) has not previously been observed to accumulate in shallow sediments in this region. The team proposes a new biogeochemical-hydrological process model for uranium redox cycling in sediments under varying moisture conditions.

The Impact
This study overturns two widely held assumptions about uranium behavior in Western organic-enriched alluvial sediments, namely (1) that uranium accumulates as U(IV) because (2) U(VI) reacts so strongly with groundwater that it is released immediately when U(IV) is oxidized. The project shows that biogeochemical redox cycling coupled to annual water table fluctuations causes hexavalent uranium to accumulate in shallow contaminated sediments. This finding is widely relevant to DOE sites across the western United States; the presence of multiple accumulation mechanisms helps to explain why uranium is so strongly retained in shallow sediments and, by extension, to explain why groundwater plumes in this region are much longer lived than originally expected.

Summary
Uranium is a major groundwater quality problem at contaminated former ore processing and nuclear complex sites across the United States. In the intermountain West, which hosts most of the U.S. legacy ore-processing sites, uranium groundwater plumes are not dissipating through the natural flushing by groundwater as originally expected. At many of these sites, uranium accumulates within organic-enriched, sulfidic sediments as sparingly soluble U(IV). When water tables drop during summer drought, moisture drains away and air enters sediment pore spaces, allowing oxygen to access and oxidize U(IV) and transform it into highly mobile U(VI).  When this happens, organic-enriched sediments release uranium back to groundwater, contributing to  plume longevity. Thus, seasonal water table fluctuations force a cascade of coupled biogeochemical processes that seasonally transform and release uranium, nutrients, and other contaminants to groundwater.

It widely believed that that oxidation of sediment-hosted U(IV) will lead to mobilization of uranium as U(VI). This recent study, however, shows exactly the opposite behavior: that oxidation reactions driven by annual water table fluctuations cause U(VI) to become trapped in sediments. To investigate this issue, Noël et al. (2019) examined the occurrence, distribution, and stability of reduced and oxidized iron, sulfur, and uranium species in shallow sediments at the Shiprock, New Mexico, site affected by annual water table fluctuations. The research used detailed molecular characterization involving X-ray absorption spectroscopy (XAS), Mössbauer spectroscopy and X-ray microspectroscopy. The team found that, during the oxidation stage, sediment-hosted U(IV) is oxidized to sediment-hosted U(VI) faster than dissolved U(VI) can be transported away. Thus, within individual pores, dissolved U(VI) becomes more concentrated in solution over time, helped by low diffusion in fine-grained sediments and evapotranspiration. the researchers posit that U(VI) eventually precipitates in solid phases that are kinetically stable against dissolution. Overall, this study shows that strong wet-dry and biogeochemical redox cycling accumulates both U(IV) and U(VI) in low-permeability sediments. This behavior suggests, somewhat surprisingly, that low-permeability organic-enriched zones could provide long-term storage for U(VI), which has major environmental implications for floodplain water quality. This work corroborates previous observations that reducing conditions are needed to accumulate uranium in sediment solid-phases, but counters the expectation that it predominantly accumulates as U(IV).

Contacts
BER Program Manager
Amy Swain
DOE Office of Biological and Environmental Research, Climate and Environmental Sciences Division
Amy.Swain@science.doe.gov

Principal Investigator
John Bargar
SLAC National Accelerator Laboratory, Stanford Synchrotron Radiation Lightsource
Bargar@slac.stanford.edu

Funding
Funding was provided by the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy (DOE) Office of Science, Subsurface Biogeochemistry Research (SBR) activity to the SLAC SFA program under contract DE-AC02-76SF00515 to SLAC. Use of the Stanford Synchrotron Radiation Laboratory (SSRL) is supported by the Office of Basic Energy Sciences within the DOE Office of Science. A portion of the research was performed using the Environmental Molecular Sciences Laboratory (EMSL), a DOE Office of Science user facility (located at PNNL) sponsored by the BER.  Sample collection at the Rifle, Colorado, site was supported by the Lawrence Berkeley National Laboratory Watershed Function SFA, sponsored by the BER Climate and Environmental Sciences Division. Sample collection at the Naturita and Grand Junction, Colorado, sites was supported by the DOE Office of Legacy Management.

Publications
Noël, V.; Boye, K.; Kukkadapu, R. K.; Li, Q.; Bargar, J. R. "Uranium storage mechanisms in wet-dry redox cycled sediments." Water Research 152, 251–63 (2019). [DOI:10.1016/j.watres.2018.12.040].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


February 13, 2019

New Model Shows Hydrologic Exchange Is Primarily Controlled by the Thickness of Permeable Riverbank Sediments 

A novel three-dimensional (3D) groundwater model reveals the roles of dynamic flow conditions, river morphology, and subsurface hydrogeology in controlling hydrologic exchange flows along a large dam-regulated river corridor.

The Science
Hydrologic exchange flows (HEFs) between groundwater and river water increase the contact between river water and subsurface sediments, and, thereby, play a critical role in biogeochemical and ecological functions along river corridors. In a recent study led by Pin Shuai and Xingyuan Chen at Pacific Northwest National Laboratory (PNNL), a multi-institutional team of researchers found that the dominant factors controlling the hydro-geochemical signatures of HEFs along a dam-regulated river reach are river channel morphology and a river channel’s subsurface hydrogeology. These features were found to control the locations of high exchange flow rates—that is, likely “hot spots” of biogeochemical activity. They also found that the magnitude and timing of river stage fluctuations, caused by dam operations, controlled hydrological “hot moments,” when biogeochemical activity was likely to be high.

The Impact
This research improves scientific understanding of hydro-geomorphic controls on HEFs at river-reach scale under high-frequency flow variations, an important issue in an era of increased worldwide interest in building hydropower dams. The paper also demonstrates the influences of river water intrusion on the migration of groundwater contaminant plumes—particularly for contaminant sources located within the preferential flow path shaped by ancient, deep river remnants called paleochannels. Importantly, the paper’s modeling approach and main findings are transferrable to other river corridor systems that experience regular, periodic fluctuations.

Summary
HEFs across the interface of a river and its aquifer have important implications for biogeochemical processes and for contaminant plume migration in river corridors, including those that are increasingly regulated by dams across the world. Yet little is known about the hydro-geomorphic factors that control the dynamics of HEFs under dynamic flow conditions.

To help close that knowledge gap, this follow-up study to Song et al. (2018) expands the model domain from a 2D transect to a simulated 3D river corridor. In this new paper, the modeling domain now covers the entire Hanford Reach of the Columbia River. The results demonstrate large spatial and temporal variability in exchange flow magnitude and direction in response to dynamic river flow conditions. The study also highlights the role of upstream dam operations in enhancing the exchange between river water and groundwater. In turn, that enhanced exchange posits a strong potential influence on associated biogeochemical processes and on the fate and transport of groundwater contaminant plumes in river corridors.

This is the first study to mechanistically simulate, at relatively fine resolution, reach-scale hydrologic exchange as it is influenced by dynamic river-stage variations, channel morphology, and subsurface hydrogeology. Because of complex geologic and dynamic flow boundary conditions, the authors faced a great challenge in running their large numerical model (60 x 60 km) using relatively fine model resolution.

However, they were able to develop a large groundwater model using PFLOTRAN, developed by the U.S. Department of Energy (DOE), a next-generation, massively parallel, reactive flow and transport simulator. This scheme, typically employed to simulate the migration of contaminants in groundwater, enabled researchers to use reasonably fine grids (100 m horizontally and 2 m vertically), while at the same time simulating the complexity of a large field setting. To perform their simulations, the researchers employed resources from DOE’s National Energy Research Scientific Computing Center (NERSC).

In all, the PNNL-led research aligns with DOE’s mission to provide next-generation science-based models of watershed systems. The next step, already underway, is to study the effect of dam operations on river corridor thermal regimes and the resulting implications for river ecology.

Contacts (BER PM)
Paul Bayer
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Subsurface Biogeochemical Research
paul.bayer@science.doe.gov

Contacts
BER Program Manager
Paul Bayer
U.S. Department of Energy, Office of Biological and Environmental Research
Paul.Bayer@science.doe.gov

Principal Investigator
Xingyuan Chen
Pacific Northwest National Laboratory
Xingyuan.Chen@pnnl.gov

Funding
This research was supported by the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy (DOE), as part of the Subsurface Biogeochemical Research Scientific Focus Area (SFA) at Pacific Northwest National Laboratory (PNNL). 

Publication
Shuai, P., X. Chen, X. Song, G.E. Hammond, J. Zachara, P. Royer, H. Ren, W.A. Perkins, M.C. Richmond, and M. Huang. “Dam Operations and Subsurface Hydrogeology Control Dynamics of Hydrologic Exchange Flows in a Regulated River Reach.” Water Resources Research 55(4), 2593–2612 (2019). [DOI:10.1029/2018WR024193].

Related Links

https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018WR024193

https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018WR022586

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


January 30, 2019

Streamflow Partitioning and Transit Time Distribution in Snow-Dominated Basins as a Function of Climate

January 30, 2019

The Science
Several models (PRMS-PEST-SAS) were coupled and applied to the snow-dominated East River Watershed to explore changes in water budgets and seasonal and annual responses in the streamflow transit time distributions.

The Impact
This research was the first to apply the coupled PRMS-PEST-SAS modeling system to a large-scale (85 km2) snow-dominated watershed. Results provide insight into how variation of the water budget and streamflow transit time are responding to climate change in this alpine snow-dominated system.

Summary
The modeling results show that during the snowmelt period of the year, the East River released younger water during high storage periods across seasonal and annual timescales (an “inverse storage effect”). However, wet years also appeared to increase hydrologic connectivity, which simultaneously flushed older water from the basin. During years with reduced snowpack, flow paths were inactivated and snowmelt remained in the subsurface to become older water that was potentially reactivated in subsequent wet years. Dry years were found more sensitive to warming temperatures than wet years through marked increases in the fraction of inflow lost to evapotranspiration at the expense of younger water to increase the mean age of streamflow.

Contacts
BER Program Manager
Paul Bayer
Department of Energy
Paul.bayer@science.doe.gov

Principal Investigator
Zhufeng Fang
Desert Research Institute
zhufeng.fang@dri.edu

Funding
Work was supported by the U.S. Geological Survey through the National Institute of Water Resources under Grant/Cooperative Agreement No. (G16AP00196), and the Lawrence Berkeley National Laboratory’s WFSFA through the Office of Biological and Environmental Research, within the U.S. Department of Energy Office of Science under contract DE-AC02-05CH11231.

Publication
Fang, Z., Carroll, R., Schumer, R., Harman, C., Wilusz, D., Williams, K. “Streamflow partitioning and transit time distribution in snow-dominated basins as a function of climate.” Journal of Hydrology 570, 726–38 (2019). [DOI:10.1016/j.jhydrol.2019.01.029].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


January 28, 2019

Hydrogen-Based Metabolism as an Ancestral Trait in Phyla Related to the Cyanobacteria

June 20, 2019

The common ancestor of oxygenic Cyanobacteria may have been an anaerobe in which fermentation and hydrogen metabolism were central metabolic features.

The Science
Bacteria from multiple phyla related to Cyanobacteria were genomically described using metagenomics and single cell genomics, and genes were predicted for all genomes. Metabolic capacities, some featuring novel complexes, were predicted using genome-based analyses. Capacities were mapped across lineages to detect environment- and lineage-specific lifestyles.

The Impact
The results suggest that the common ancestor of all of the phyla investigated may have been an anaerobe in which fermentation and H2 metabolism were central metabolic features. Capacities of phylogenetic neighbors to Cyanobacteria (the group in which oxygenic photosynthesis arose), such as Margulisbacteria, Saganbacteria, Melainabacteria and Sericytochromatia, constrain the metabolic platform in which aerobic respiration arose. The evolution of aerobic respiration was likely linked to the origins of oxygenic Cyanobacteria.

Summary
Margulisbacteria (RBX-1 and ZB3), Saganbacteria (WOR-1), Melainabacteria, and Sericytochromatia, close phylogenetic neighbors to Cyanobacteria, may constrain the metabolic platform in which aerobic respiration arose. In this study, the authors predict that sediment-associated Margulisbacteria have a fermentation-based metabolism featuring a variety of hydrogenases, a streamlined nitrogenase, and electron bifurcating complexes involved in cycling of reducing equivalents. The genomes of ocean-associated Margulisbacteria encode an electron transport chain that may support aerobic growth. Some Saganbacteria genomes encode various hydrogenases, and others may have the ability to use O2 under certain conditions via a putative novel type of heme copper O2 reductase. Similarly, Melainabacteria have diverse energy metabolisms and are capable of fermentation and aerobic or anaerobic respiration. The ancestor of all of these groups may have been an anaerobe in which fermentation and H2 metabolism were central metabolic features. The ability to use O2 as a terminal electron acceptor must have been subsequently acquired by these lineages.

Contacts
BER Program Manager
Paul Bayer
Department of Energy
paul.bayer@science.doe.gov

Principal Investigator
Jill F. Banfield
University of California, Berkeley
jbanfield@berkeley.edu

Funding
This work was supported by the Office of Biological and Environmental Research within the U.S. Department of Energy Office of Science.

Publication
P. B. Matheus Carnevali, F. Schulz, C. J. Castelle, R. S. Kantor, P. M. Shih, I. Sharon, J. M. Santini, M.R. Olm, Y. Amano, B.C. Thomas, K. Anantharaman, D. Burnstein, E. D. Becraft, R. Stepanauskas, T. Woyke, and J. F. Banfield, “Hydrogen-based metabolism as an ancestral trait in lineages sibling to the Cyanobacteria.” Nature Communications 10, 463 (2019). [DOI:10.1038/s41467-018-08246-y].

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER


January 07, 2019

Effects of Water Flow Variation in Large Rivers Exacerbated by Drought

Model shows frequent fluctuation in river flows, caused by dam operations, lead to greater changes in water temperature and biogeochemical reaction rates in river sediments.

The Science
Biogeochemical activity in the hyporheic zone (HZ), sediments where the flowing waters of a river mix with shallow groundwater, supports many of the biological processes that occur within a watershed. Through the creation of a cross sectional (2-D) model of the Columbia River Hanford Reach’s HZ, PNNL researchers, led by Xuehang Song and Xingyuan Chen, found that low flow conditions contribute to warmer waters in the HZ. This, in turn, increases the rate of biogeochemical activity in the sediments. Long-term analysis shows this effect is exacerbated during times of drought.

The Impact
Thermal and biogeochemical dynamics in the HZ are important to fluvial ecology, such as thermal refugia for fish spawning and growth, benthic food production, and nitrate removal. These results can enable natural resource managers to more accurately assess the ecological consequences of long-term frequent water flow variation in riverine systems. In turn, this information will inform dam operations in the context of river and watershed management planning.

Summary
Studies of thermal changes in HZs have largely focused on short-term analysis of steady state flow conditions in smaller streams. This study is among the first to model and conduct field analyses in a large river system with high frequency in flow variation. Large fluctuations in water flow levels are a common phenomenon in most river systems with hydroelectric dam operations. To assess the long-term impact of these fluctuations, PNNL researchers created a cross sectional (2-D) thermal-hydro-biogeochemical model of the Columbia River Hanford Reach’s HZ with data supported by field monitoring.

Researchers assessed multiple years’ worth of flow level fluctuation data seeking the most powerful variations, signals unique to dam operations. Inland ground water monitoring data was also used to track the hydraulic gradients driving flow in and out of the HZ. By comparing natural variations against dam-induced differences in flow level, the researchers tracked, over time, the change in temperature, carbon consumption, and other biogeochemical-relevant variables.

Through numerical simulation the model shows a long-term persistent cold-water zone in the riverbed after winter, verified by observational data from a multi-depth thermistor array. Frequent stage fluctuations when the mean flow level is low-particularly under drought conditions during summer and early fall-enhanced heat exchange between the river and the HZ, reaching a maximum temperature difference between 5° to 10°C. All biogeochemical reactions in the HZ were enhanced by increasing nutrient supply and creating more oxygenated conditions. Total carbon consumption, a primary indicator of biogeochemical activities in the HZ, increased by almost 20%. In addition, the model demonstrated that the variable properties of riverbed sediment, such as permeability, influence water residence times and nutrient supplies by controlling flow paths. These variables also determine the spatial distribution of biogeochemical reaction hot spots in the HZ.

Already working towards further improvements to this model, PNNL researchers are expanding the scope of their work from one 2-D cross sectional analysis to a 3-D analysis of the entire Columbia River Hanford Reach.

BER PM Contact
Paul Bayer, SC-23.1
David Lesmes, SC-23.1

PI Contact
Xingyuan Chen
Pacific Northwest National Laboratory
Xingyuan.Chen@pnnl.gov

Funding
Funding for this research came from the DOE Office of Science Office of Biological and Environmental Research’s  Subsurface Biogeochemical Research program for the PNNL Subsurface Biogeochemical Research SFA.

Publications
Song, X., X. Chen, J. Stegen, G. Hammond, H-S Seob, H. Dai, E. Graham, and J. Zachara. “Drought Conditions Maximize the Impact of High-Frequency Flow Variations on Thermal Regimes and Biogeochemical Function in the Hyporheic Zone.” Water Resources Research 54(10), 7361-7382 (2018). [DOI: 10.1029/2018WR022586]

Topic Areas:

Division: SC-33.1 Earth and Environmental Sciences Division, BER