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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Resistance, Resilience, and Recovery of Dryland Soil Bacterial Communities Across Multiple Disturbances

Dryland ecosystems are sensitive to perturbations and generally slow to recover post disturbance. The microorganisms residing in dryland soils are especially important as they contribute to soil structure and nutrient cycling. Disturbance can have particularly strong effects on dryland soil structure and function, yet the natural resistance and recovery of the microbial components of dryland soils has not been well documented. In this study, the recovery of surface soil bacterial communities from multiple physical and environmental disturbances is assessed. Samples were collected from three field sites in the vicinity of Moab, UT, United States, 6 to 7 years after physical and climate disturbance manipulations had been terminated, allowing for the assessment of community recovery. Additionally, samples were collected in a transect that included three habitat patches: the canopy zone soils under the dominant shrubs, the interspace soils that are colonized by biological soil crusts, and edge soils at the plot borders. Field site and habitat patch were significant factors structuring the bacterial communities, illustrating that sites and habitats harbored unique soil microbiomes. Across the different sites and disturbance treatments, there was evidence of significant bacterial community recovery, as bacterial biomass and diversity were not significantly different than control plots. There was, however, a small number of 16S rRNA gene amplicon sequence variants that distinguished particular treatments, suggesting that legacy effects of the disturbances still remained. Taken together, these data suggest that dryland bacterial communities may possess a previously unappreciated potential to recover within years of the original disturbance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Effects of submerged macrophytes (Elodea nuttallii) on water quality and microbial communities of largemouth bass (Micropterus salmoides) ponds

Traditional aquaculture ponds are one of the most vulnerable ecosystems; thus, ecological aquaculture is increasingly valued for its beneficial ecological properties and ecosystem services. However, little is known about ecological aquaculture of largemouth bass with submerged vegetation. Here, we designed three ecological ponds of cultured largemouth bass with submerged macrophytes (the EM group) and three ponds with traditional aquaculture (the M group) to reveal the response of water quality, and phytoplankton and bacterial communities, to submerged macrophyte bioremediation during a 90-day culture period. We observed that Cyanobacterial outbreak occurred in the M group ponds from day 7 to the end of the experiment; however, there were no Cyanobacterial blooms in the EM group ponds throughout the culture period. Compared with the M group ponds, the EM group ponds, which had submerged hydrophytes, had significantly decreased concentrations of TP, TN, and COD Mn , but significantly increased DO concentrations throughout the experimental period. Moreover, ecological aquaculture with submerged macrophytes showed strong effects on the phytoplankton and bacterial community compositions. In particular, the M group ponds had higher phytoplankton density and mainly included Cyanobacteria, whereas the EM group had lower phytoplankton density and mainly included Chlorophyta. Moreover, higher alpha diversity, as determined by Ace and Simpson index values, was detected for bacterial communities in the EM group ponds. Furthermore, PCoA clearly grouped the bacterial communities according to the two culture modes throughout the culture period. These results indicate that ecological aquaculture with submerged macrophytes can improve water quality, control Cyanobacterial blooms, and affect the diversity and composition of bacterial communities. These valuable effects seem to be beneficial and consistent to maintaining aquaculture ecosystem stability.

Nie, Zhijuan↗
DOE OSTI2023

Effects of different cultivation media on root bacterial community characteristics of greenhouse tomatoes

Tomato, as a typical greenhouse crop, is commonly first planted as seedlings in a variety of substrates before being transplanted into soil. However, there is rare research on the characteristics of the bacterial community in tomato roots under this planting mode. In this study, tomatoes were planted in pots containing three different cultivation media, including soil and two types of substrates in a greenhouse, followed by a transplanting treatment. After collecting tomato root samples, high-throughput sequencing and bioinformatic analysis were used to compare the differences in bacterial diversity and functions between tomato roots before and after transplanting in different cultivation media. In total, 702776 sequences were obtained, and the OTUs were belonging to 109 genera, 58 families, 41 orders, 14 classes, and 12 phyla. Among the three cultivation media, the β -diversity was significant, and there was a slight difference in bacterial species diversity along with a large difference in their abundance at the genus level. Soil and both substrates had 79 bacterial genera in common, these genera accounted for 68.70%, 76.70%, and 71.17% of the total genera found in the soil, substrate 1, and substrate 2, respectively. After being transplanted from the two substrates to the soil, the bacterial community structure and abundance exhibited similarities with those found in the soil. Furthermore, based on microbial function prediction, the microbial communities in the two-substrate environment demonstrated a greater potential for promoting growth, while the microbial communities in the soil exhibited a greater tendency to exert their antibacterial potential. Our findings offer theoretical support for the creation of artificially reconstructed microbial communities in greenhouse cultivation.

Zhang, Xinjian↗
DOE OSTI2023

Comparing the response of the indigenous microbial community to crude oil amendment in oxic versus hypoxic conditions

The Caspian Sea is the world’s largest landlocked saline lake which lies between Europe and Asia. This region is particularly known for its large-scale oil reserves, pipelines, and drilling activities, which have contributed to the environmental decline of this lake. In addition to pollution from the petroleum industry, drainage from various river basins brings an influx of residential, industrial, and agricultural effluents that induce eutrophication and hypoxic conditions in deeper, colder waters, creating an oxygen gradient. The temperature and oxygen stratification in this environment has presented a unique opportunity to investigate the potential of the biodegradative processes carried out by the indigenous microbial community. We believe these indigenous microbes possess different metabolic capabilities to degrade oil as they adapted to declining oxygen concentrations and temperatures with increasing depths over a prolonged period. Hence, community structure and composition will vary with depth. Microcosms were set up to observe the indigenous microbial reaction after a 60 ppm native crude oil amendment over 115 days. Surface water microcosms were incubated at 28ºC and aerated while deep water microcosms were incubated at 8ºC under anaerobic conditions. These two environmental conditions represent the temperature and oxygen extremes along the gradient and were selected as we try to simulate the indigenous community’s response to this oil contamination. DNA was extracted and amplified from these microcosms and sequenced. Bioinformatic analysis was performed to track changes in the abundance of taxa present and biodiversity over different time points to show the progression of community structure. All microcosms showed the presence of hydrocarbon-degrading phyla, whose presence is consistent with other reports from oil-enriched environments. However, distinct communities were observed in oxic versus hypoxic microcosms. Orders of Bacteria related to sulfate and nitrogen cycling were found in hypoxic microcosms, indicating a possible mechanism for the anaerobic biodegradation of crude oil. GC-MS analysis of initial and final microcosms also provided evidence of degradation of hydrocarbon fractions in both warm, oxic and cold, hypoxic conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil

Abstract. The microbial community composition in subsoils remains understudied, and it is largely unknown whether subsoil microorganisms show a similar response to global warming as microorganisms at the soil surface do. Since microorganisms are the key drivers of soil organic carbon decomposition, this knowledge gap causes uncertainty in the predictions of future carbon cycling in the subsoil carbon pool (> 50 % of the soil organic carbon stocks are below 30 cm soil depth). In the Blodgett Forest field warming experiment (California, USA) we investigated how +4 ∘C warming in the whole-soil profile to 100 cm soil depth for 4.5 years has affected the abundance and community structure of microorganisms. We used proxies for bulk microbial biomass carbon (MBC) and functional microbial groups based on lipid biomarkers, such as phospholipid fatty acids (PLFAs) and branched glycerol dialkyl glycerol tetraethers (brGDGTs). With depth, the microbial biomass decreased and the community composition changed. Our results show that the concentration of PLFAs decreased with warming in the subsoil (below 30 cm) by 28 % but was not affected in the topsoil. Phospholipid fatty acid concentrations changed in concert with soil organic carbon. The microbial community response to warming was depth dependent. The relative abundance of Actinobacteria increased in warmed subsoil, and Gram+ bacteria in subsoils adapted their cell membrane structure to warming-induced stress, as indicated by the ratio of anteiso to iso branched PLFAs. Our results show for the first time that subsoil microorganisms can be more affected by warming compared to topsoil microorganisms. These microbial responses could be explained by the observed decrease in subsoil organic carbon concentrations in the warmed plots. A decrease in microbial abundance in warmed subsoils might reduce the magnitude of the respiration response over time. The shift in the subsoil microbial community towards more Actinobacteria might disproportionately enhance the degradation of previously stable subsoil carbon, as this group is able to metabolize complex carbon sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Community-Informed Urban Flood Modeling for Impact Mitigation

The intensification of the hydrologic cycle due to climate change poses a threat to aging and under-designed water infrastructure systems which cannot adequately manage intense storm events. Developing a comprehensive plan for managing rain-driven flooding events is challenging due to uncertainties in the magnitude and frequency of future storm events and conflicting stakeholder objectives. In the City of Baltimore, Maryland, stormwater infrastructure is struggling to keep up with rainfall-driven (pluvial) flooding events, which regularly damage housing and disrupt transportation for residents. In this study, a hybrid of community engagement, numerical modeling, and artificial intelligence techniques are employed to explore prospective urban flooding adaptations. Community engagement drives the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed. The model integrates complex surface and subsurface stormwater infrastructure data from the City, high-resolution spatial data, insights from local public works experts, and the lived experiences of City residents. This co-developed model simulates adaptations of interest to stakeholders in the city, including green and grey infrastructure and operational management strategies. Stormwater management scenarios focused on inlet cleaning and spatially concentrated green infrastructure are found to be the most effective in reducing flood depths in community priority locations. Together, these adaptations can reduce the duration of intersection inundation by more than twenty minutes, allowing for quicker emergency response and restoration of typical transportation systems. Future work will combine this community engaged flooding model with the Deep Uncertainties Pathways framework to explore tradeoffs between adaptations and develop dynamic adaptations which align with community objectives, enhance climate resilience in Baltimore, and can be adjusted in response to changing future conditions.

Ava, Spangler [Pennsylvania State University]↗
DOE OSTI2026

MSD CoP Webinar: "Advances in MSD-LIVE to Support the MSD Community of Practice"

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Advances in MSD-LIVE to Support the MSD Community of Practice Presenters: Casey Burleyson and Zoe Guillen (Pacific Northwest National Laboratory) Abstract: The MultiSector Dynamics Living, Intuitive, Value-adding, Environment (MSD-LIVE; msdlive.org) is a cloud-based data management system and advanced computing platform that enables MSD researchers to document and archive their data, run their models and analysis tools, and share their data, software, and workflows within the MSD Community of Practice. Recently, several high-profile datasets have attracted many new users to MSD-LIVE. This webinar has two goals: 1) To refamiliarize the MSD community and new users with the components of the platform (e.g., the data repository, model training notebooks, and data dashboards) and to highlight examples of how these components are advancing MSD science and 2) To demonstrate new features in v3 of the platform, released in late 2025. The main new feature in v3 is the ability to interactively explore data in MSD-LIVE without downloading it. MSD-LIVE users can now click a button in our data repository and launch a blank Jupyter notebook with access to the underlying data on AWS. Users can use the notebook to write analysis, visualization, or subsetting routines that process the data directly on the AWS cloud. We also added a GitHub integration feature that allows users to share analysis or visualization code they develop with the community of MSD-LIVE users. The webinar will wrap up with a look at what's coming next for MSD-LIVE in 2026. Moderator: Patrick M. Reed (MSD CoP Facilitation Team) This webinar was held on: May 12th, 2026 from 1-2 PM EST.

Open Science↗
DOE OSTI2026

The relationship between gene traits and transcription in soil microbial communities varies by environmental stimulus

Codon and nucleotide frequencies are known to relate to the rate of gene transcription, yet how these traits shape transcriptional profiles of soil microbial communities remains unclear. Here we test the prediction that functional genes with high codon optimization and energetically lower cost nucleotides (i.e., nucleotides requiring less adenosine triphosphate (ATP) for synthesis) have higher transcriptional expression in a soil microbial community. In laboratory incubations, we subjected an agricultural soil to two separate short-term environmental changes: labile carbon (glucose) addition or a sudden 30-min increase in temperature from 20 °C to 60 °C. Using the total genomic codon frequencies to predict preferred codon usage for each taxon, we then estimated codon optimization for each transcript. On the community level, we found a higher average level of codon optimization after the addition of glucose. Synonymous nucleotide composition in the transcript pool also shifted towards energetically cheaper nucleotides, favoring uracil (U) over adenine (A) and cytosine (C) over guanine (G). Similarly, we found that encoded amino acid usage shifted towards energetically cheaper amino acids in response to labile carbon. In contrast, in communities responding to heat shock, there were no significant differences in the averaged gene traits of expressed transcripts. We used metagenome-assembled-genomes to further examine the ability of gene traits to predict transcriptional responses within and between taxa. We found that traits of individual genes could not reliably predict the level of transcription of a gene within or between taxa—highlighting the limits of this approach. However, we did find that when traits were averaged across several related genes, codon optimization was able to predict levels of transcription in metabolic pathways associated with growth and nutrient uptake in response to glucose. Similar relationships were not observed in response to heat, or for functions associated with stress—such as genes associated with sporulation or heat shock. These results demonstrate that gene traits, such as codon usage, nucleotide selection, and amino acid selection, relate to the transcriptional expression of genes in soil microbial communities and suggests that these relationships may be dependent on both gene function and the specific type of environmental stimuli.

Biological and medical sciences↗
DOE OSTI2020

Direction-optimizing Label Propagation and its Application for Community Detection

Label Propagation is a machine learning algorithm typically used for classification. It has also been found to be an effective method for detecting communities in networks. It has two attractive features as a community detection method: it has nearly linear runtime and it requires no \textit{a priori} community information. We propose a new Direction Optimizing Label Propagation Algorithm (DOLPA) that relies on the use of {\em frontiers} and alternates between label {\em push} and label {\em pull} operations to enhance the performance of LPA. Specifically, DOLPA has parameters for tuning the processing order of vertices in a graph. This reduces the number of edges visited and improves the quality of solution. We apply DOLPA to community detection and present the design and implementation of the algorithm as well as its shared-memory parallelization using OpenMP. Empirically, we evaluate our algorithm using synthetic graphs as well as real-world networks. Compared with the state-of-art \textit{Parallel Label Propagation} algorithm, we achieve at least two times the F-Score while reducing the runtime by 50\% for synthetic graphs with overlapping communities. We also compare DOLPA against the state-of-art parallel implementation of the Louvain method using the same graphs and show that DOLPA achieves about three times the F-Score at 10\% the runtime. On real-world graphs, we get a speedup of up to $10\times$ using 64 threads.

Liu, X↗
DOE OSTI2020

Engineering roles and identities in the scientific community: toward participatory justice

This paper seeks to examine the roles and identities of engineers constituting one of the fundamental, but a completely indescribable community in modern big science with particle accelerators. Large communities of accelerator and detector specialists, which replaced experimenters and instrumentalists of the middle of the last century, themselves exhibit a complex structure and are divided. However, this division is in turn grounded on the division of those whose activities focus on the phenomena of nature considered independent of human beings and those who design processes and phenomena of an artificial, technical nature. Nevertheless, in terms of their modus operandi and identity, the kinship between engineers and experimental scientists is considerable. I argue that such exclusion of the engineering community from epistemic practices can serve as an example of participatory injustice. As one of the ways to transcend participatory injustice, I suggest that the communities should be encouraged to work together in epistemically tantamount roles while structural hindrances to the mobility between communities need to be alleviated.

Pronskikh, V.↗
DOE OSTI2021

A Community Roadmap for Scientific Workflows Research and Development

The landscape of workflow systems for scientific applications is notoriously convoluted with hundreds of seemingly equivalent workflow systems, many isolated research claims, and a steep learning curve. To address some of these challenges and lay the groundwork for transforming workflows research and development, the WorkflowsRI and ExaWorks projects partnered to bring the international workflows community together. This paper reports on discussions and findings from two virtual “Workflows Community Summits” (January and April, 2021). The overarching goals of these workshops were to develop a view of the state of the art, identify crucial research challenges in the workflows community, articulate a vision for potential community efforts, and discuss technical approaches for realizing this vision. To this end, participants identified six broad themes: FAIR computational workflows; AI workflows; exascale challenges; APIs, interoperability, reuse, and standards; training and education; and building a workflows community. We summarize discussions and recommendations for each of these themes.

Ferreira Da Silva, Rafael↗
DOE OSTI2022

Building a Culture of Equitable Access and Success for Marginalized Members in Today's Particle Physics Community

Diversity, Equity, Inclusion, and Accessibility (DEIA) are not only called for to ensure morality and justice in our society, they also support ongoing and future excellence in particle physics. Over the past decade, the particle physics community has devised programs to support DEIA along multiple axes, and the way we think about measuring and implementing these initiatives has evolved. DEIA in physics is a broad topic, so in this paper we focus on the experiences of marginalized communities and outline ways different stakeholders can build a culture of equitable access for the success of marginalized individuals. Specifically, we identify urgent needs in the following areas: (1) We need to acquire a better understanding of the status quo, both quantitatively and qualitatively, to assess the effectiveness of existing programs and to develop best practices; (2) we need to develop effective and inclusive ways to engage marginalized communities; (3) we need to create infrastructure to better support members of marginalized communities, on an academic, financial and personal level; (4) we need to create an environment conducive to equitable access and success by establishing community expectations, fostering inclusion in social interactions, and holding individuals and institutions accountable; and (5) we need to establish a mechanism to monitor progress in the area of DEIA, including the implementation of the recommendations enumerated in this paper and others during the Snowmass 2021 process.

Assamagan, Kétévi A.↗
DOE OSTI2022

If One GEB is Good, a Community of GEBs is Better

Energy efficient, connected, grid-interactive, smart and flexible buildings are key to decarbonization, lowering energy use and improving the nation’s electricity grid. The U.S. Department of Energy’s Connected Communities initiative works to demonstrate how coordinated groups of highly efficient buildings combined with other distributed energy resources (DERs), such as electric vehicle (EV) charging, batteries, storage, demand response and photovoltaic (PV) generation can reliably and cost-effectively serve as grid assets by strategically deploying efficiency and demand flexibility while reducing carbon emissions. In 2021, DOE competitively awarded $61 million to a diverse portfolio of 10 pilot projects to promote grid-interactive efficient buildings (GEBs) working together to reliably and cost-effectively serve as grid assets while decarbonizing. Two of the main tenets of the program are measuring the communities’ energy and carbon performance and understanding how to replicate project successes in other communities. This paper begins with a discussion of what Connected Communities are (including a brief history) and their many benefits, including reduced carbon emissions and increased building efficiency and demand flexibility. Next, it provides an overview of the 10 projects, highlighting the diversity of approaches to measure success and replicate the projects: geographic locations; building types; utility, regulatory, market environments; and building vintages that will be used to test the ability of buildings to serve as grid resources. It concludes with a discussion of anticipated project impacts and the metrics that will be used to evaluate the Connected Communities projects.

Nemtzow, David↗
DOE OSTI2023

Report of the 2021 U.S. Community Study on the Future of Particle Physics (Snowmass 2021) Summary Chapter

The 2021-22 High-Energy Physics Community Planning Exercise (a.k.a. ``Snowmass 2021'') was organized by the Division of Particles and Fields of the American Physical Society. Snowmass 2021 was a scientific study that provided an opportunity for the entire U.S. particle physics community, along with its international partners, to identify the most important scientific questions in High Energy Physics for the following decade, with an eye to the decade after that, and the experiments, facilities, infrastructure, and R&D needed to pursue them. This Snowmass summary report synthesizes the lessons learned and the main conclusions of the Community Planning Exercise as a whole and presents a community-informed synopsis of U.S. particle physics at the beginning of 2023. This document, along with the Snowmass reports from the various subfields, will provide input to the 2023 Particle Physics Project Prioritization Panel (P5) subpanel of the U.S. High-Energy Physics Advisory Panel (HEPAP), and will help to guide and inform the activity of the U.S. particle physics community during the next decade and beyond.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Connecting People to Data: Enabling Data Connected Communities through Enhancements to the Geothermal Data Repository: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) has implemented a series of new features designed to connect people to data. These features, which are based on feedback from the GDR user community and surveys of the greater geothermal research community, are designed to improve data quality and empower members of all communities to better engage with geothermal data resources by providing universal access to data and by improving the connections between data providers, subject matter experts, and the communities of people using GDR data. This paper will explore some of the recent enhancements made to the GDR to improve data discoverability, reduce submission time, and result in better quality data submissions. These improvements include the ability for users to save a list of their favorite datasets, search for insight into geothermal datasets or data availability, or sign up to receive notifications of future updates to specific datasets. These improvements aim to enhance the overall user experience of the GDR while further connecting communities to the data they need to inform decisions, advance geothermal research, and develop innovative solutions to local energy problems.

DOE↗
DOE OSTI2021

Evaluating the effects of a low-carbon energy transition on existing U.S. fossil energy communities

On-going efforts and the growing movement to transition from our current energy systems towards low-carbon and renewable sources have uncovered a range of challenges and concerns communities may face under this transition. An understanding of the current relationships and dynamics within communities can offer critical insights that stakeholders, as well as decision and policy makers can use to better support and affect the outcome of these transitions. To support this need, the National Energy Technology Laboratory has been developing a data-driven framework to aid in the characterization of fossil energy communities across the U.S. and offer insights to comprehensively address energy transaction concerns by different stakeholder groups and various stages associated with a low-carbon energy system. This presentation will offer details on our current work to integrate multiple environmental, social, and economic data variables, as well as key trends and insights that are being used to characterize these communities at a local and regional scale. These insights will be used to evaluate with alternative opportunities, including, but not limited to, hydrogen, rare earth elements and critical minerals, and energy storage, that could be aid in the transition for these communities from conventional energy resources.

Bauer, Jennifer↗
DOE OSTI2025

Response of Subsurface Nitrogen-Cycling Microbial Communities to Environmental Fluctuations (Final Technical Report)

Riparian floodplains are dynamic ecosystems linking terrestrial and riverine systems. These floodplains experience hydrological shifts such as changes in water table height, flooding, and drought and can be ‘hotspots’ of biogeochemical cycling due to shifting sediment moisture (and saturation) and subsurface exchanges of water, nutrients, and other compounds across different sediment layers. Subsurface microbial communities are the primary drivers of biogeochemical processes in floodplains, and thus their structure and function can directly influence both surface and groundwater quality. The microbial nitrogen (N) cycle is particularly important in floodplains as it affects nutrient availability and removal. Two functional guilds of chemoautotrophic (i.e. CO2-fixing) microorganisms are responsible for the first oxidative step of the N cycle, nitrification: ammonia-oxidizing archaea (AOA) and bacteria (AOB) catalyze the oxidation of ammonia to nitrite, while nitrite-oxidizing bacteria (NOB) oxidize nitrite to nitrate. Despite the critical role nitrification plays in N-cycling in both terrestrial and aquatic ecosystems, our understanding of the diversity, ecophysiology, and activity of nitrifying organisms in subsurface floodplain soils/sediments is extremely limited. To help address this critical knowledge gap, the overarching goal of this project was to determine how shifts in key environmental parameters and gradients impact microbial N-cycling communities/processes, with particular emphasis on nitrification, within hydrologically-variable floodplain sediments in the Wind River Basin near Riverton, Wyoming. The three specific objectives of this project were to: (1) to associate in situ environmental drivers of N cycling with distinct functional guilds; (2) determine the guild response to variation in key ecosystem drivers; and (3) develop a dynamic ecosystem model of the microbial N cycle with the Riverton subsurface using community genomic and biogeochemical data collected in the first two objectives. Over the course of this project, we employed both 16S rRNA gene amplicon sequencing and genome-resolved metagenomics to examine the phylogenetic diversity and metabolic potential of subsurface nitrifier communities within 68 samples collected across multiple sites, depths, and time points within the Riverton floodplain, allowing for both spatial and temporal investigations at different scales. This project benefitted tremendously from recent advances in high-throughput sequencing technologies coupled with dramatic improvements in the computational tools and algorithms available for analyzing such large, complex genomic datasets. By pairing these cutting-edge genomic approaches with depth-resolved sampling and detailed geochemical analyses of the Riverton floodplain, we have gained novel insights into the structure and function of subsurface nitrifier communities in relation to both hydrology and biogeochemistry. This project resulted in the most detailed and comprehensive characterization of N-cycling floodplain microbial communities to date and will hopefully inspire and pave the way for future studies using similar approaches in other floodplains. Indeed, such information is critical for understanding subsurface biogeochemical cycling and how elemental stores are altered from perturbations initiated by the water cycle within floodplains. Finally, because of the terrestrial-aquatic nature of the Riverton floodplain, results from this project are also of relevance to disciplines such as soil science, estuarine science, limnology & oceanography, biogeochemistry, geobiology, environmental engineering, as well as genomics and data science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Community Dynamics Drive Calcium Carbonate Production in an Enriched Consortium of Soil Microbes

Recently, there has been a focus on using soil microbes as a means to store carbon in the soil in the form of calcium carbonate, outcomes of which include soil stabilization and biocementation. The molecular processes involved in microbially induced calcium carbonate formation are known, but there is still a significant knowledge gap regarding how community interactions, emergent processes that are distinct from the roles of individual members, may drive the formation of carbonate. To answer these questions, we describe the development and application of a consortium of soil microbes consisting of one species each of the Rhodococcus , Microbacterium , and Curtobacterium genera and two species from the Bacillus genus. We term these five species cultivated together carbon storing consortium A (CSC-A). Growth assays show that only a subset of CSC-A members produces CaCO 3 with Rhodococcus producing the most CaCO 3 but the complete CSC-A produces significantly higher amounts of CaCO 3 compared to the sum total carbonate produced by all member species. The development of CSC-A shows that CaCO 3 production may be as much a community process as it is the contribution of individual species, requiring us to move beyond single species analysis to fully understand carbonate formation by microbial communities in nature. CSC-A will allow the scientific community to ask and answer key questions about the molecular interactions surrounding inorganic carbon formation in soil, an important knowledge gap that must be filled if we wish to stabilize soils and harness microbial processes for materials production.

calcium carbonate↗