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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Microbial community response to a decade of simulated global changes depends on the plant community

Global changes such as increased drought and atmospheric nitrogen deposition perturb both the microbial and plant communities that mediate terrestrial ecosystem functioning. However, few studies consider how microbial responses to global changes may be influenced by interactions with plant communities. To begin to address the role of microbial–plant interactions, we tested the hypothesis that the response of microbial communities to global change depends on the plant community. We characterized bacterial and fungal communities from 395 plant litter samples taken from the Loma Ridge Global Change Experiment, a decade-long global change experiment in Southern California that manipulates rainfall and nitrogen levels across two adjacent ecosystems, a grassland and a coastal sage scrubland. The differences in bacterial and fungal composition between ecosystems paralleled distinctions in plant community composition. In addition to the direct main effects, the global change treatments altered microbial composition in an ecosystem-dependent manner, in support of our hypothesis. The interaction between the drought treatment and ecosystem explained nearly 5% of the variation in bacterial community composition, similar to the variation explained by the ecosystem-independent effects of drought. Unexpectedly, we found that the main effect of drought was approximately four times as strong on bacterial composition as that of nitrogen addition, which did not alter fungal or plant composition. Overall, the findings underscore the importance of considering plant–microbe interactions when considering the transferability of the results of global change experiments across ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Special Issue: Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics

Microbial communities are networks of species, the interaction structure of which dynamically reorganizes in a varying environment. Even in a static condition, community dynamics are often difficult to predict due to highly nonlinear interspecies interactions. Understanding fundamental principles of microbial interactions is therefore key for predicting and harnessing community function and properties. As extensively reviewed previously, mathematical models and computational methods that can predictively link interactions to community behaviors are indispensable tools for achieving this goal. This Special Issue of Processes collects eleven papers from lead scientists and researchers active in the area under the topic of “Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics.” The collected papers cover various topics of interest: 1) two review/opinion papers discussing recent advances in biofilm modeling and specific issues for successful collaboration between experimentalists and theorists, 2) one paper on the dynamics of complex environmental communities, 3) six papers dealing with fundamental aspects of microbial interactions and stability in model communities, and 4) two papers on the development and utilization of microbial consortia for biotechnology applications.

Song, Hyun-Seob (ORCID:0000000221546358)↗

Community Proteogenomics Reveals the Systemic Impact of Phosphorus Availability on Microbial Functions in Tropical Soil

Phosphorus (P) is a scarce nutrient in many tropical ecosystems, yet how soil microbial communities cope with growth-limiting P deficiency at the gene and protein levels remains unknown. Here we report a metagenomic and metaproteomic comparison of microbial communities in P-deficient and P-rich soils in a 17-year fertilization experiment in a tropical forest. The large-scale proteogenomics analyses provided extensive coverage of many microbial functions and taxa in the complex soil communities. A >4-fold increase in the gene abundance of 3-phytase was the strongest response of soil communities to P deficiency. Phytase catalyzes the release of phosphate from phytate, the most recalcitrant P-containing compound in soil organic matter. Genes and proteins for the degradation of P-containing nucleic acids and phospholipids as well as the decomposition of labile carbon and nitrogen were also enhanced in the P-deficient soils. In contrast, microbial communities in the P-rich soils showed increased gene abundances for the degradation of recalcitrant aromatic compounds, the transformation of nitrogenous compounds, and the assimilation of sulfur. Overall, these results demonstrate the adaptive allocation of genes and proteins in soil microbial communities in response to shifting nutrient constraints.

Yao, Qiuming↗

Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction: COMMUNITY DATA-DRIVEN METABOLIC NETWORK MODELING

Metabolic network modeling of microbial communities provides an in-depth understanding of community-wide metabolic and regulatory processes. Compared to single organism analyses, community metabolic network modeling is more complex because it needs to account for interspecies interactions. To date, most approaches focus on reconstruction of high-quality individual networks so that, when combined, they can predict community behaviors as a result of interspecies interactions. However, this conventional method becomes ineffective for communities whose members are not well characterized and cannot be experimentally interrogated in isolation. Here, we tested a new approach that uses community-level data as a critical input for the network reconstruction process. This method focuses on directly predicting interspecies metabolic interactions in a community, when axenic information is insufficient. We validated our method through the case study of a bacterial photoautotroph-heterotroph consortium that was used to provide data needed for a community-level metabolic network reconstruction. Resulting simulations provided experimentally validated predictions of how a photoautotrophic cyanobacterium supports the growth of an obligate heterotrophic species by providing organic carbon and nitrogen sources.

compartmentalized metabolic network↗

An Open-Source Virtual Testbed for a Real Net-Zero Energy Community

Net zero energy communities (NZECs) are critical to ensure sustainability and resilience of modernized power systems. System modeling helps overcome technical challenges in designing and operating NZECs. In this paper, we present the modeling work based on a real NZEC. Two sets of models are developed: higher-fidelity physics-based models considering the interaction between subsystems of the studied NZEC and capturing fast-dynamics; and lower-fidelity data-driven models requiring less resource to establish and/or run. All models are validated against measurements from this real NZEC. In addition, we create a simulation framework which streamlines the processes for simulation and thus allows using developed models to form a virtual testbed. To demonstrate the usage of the virtual testbed, a case study is conducted where a building-to-grid integration control is evaluated via simulation. The evaluation results suggest that the tested control significantly smooths the power draw of the studied community and doesn’t sacrifice the thermal comfort to a great extent.

Huang, Sen↗

Efficacy of acetate-amended biostimulation for uranium sequestration: Combined analysis of sediment/groundwater geochemistry and bacterial community structure

Systematic flow-through column experiments were conducted using sediments and ground water collected from different subsurface localities at the U.S. Department of Energy's Integrated Field Research Challenge site in Rifle, Colorado. The principal purpose of this study is to gain a better understanding of the interactive effects of groundwater geochemistry, sediment mineralogy, and indigenous bacterial community structures on the efficacy of uranium removal from the groundwater with/without acetate amendment. Overall, we find that the subtle variations in the sediments' mineralogy, particle size, redox conditions, as well as contents of metal(loid) co-contaminants showed a pronounced effect on the associated bacterial population and composition, which mainly determines the system's performance with respect to uranium removal. Positive relationship was identified between the abundance of dissimilatory sulfate-reduction genes (i.e., drsA), markers of sulfatereducing bacteria, and the sediments' propensity to sequester aqueous uranium. In contrast, no obvious connections were observed between the abundance of common iron-reducing bacteria, e.g., Geobacter spp., and the sediments' ability to sequester uranium. In the sediments with low bacterial biomass and the absence of sulfate-reducing conditions, abiotic adsorption onto mineral surfaces such as phyllosilicates likely played a relatively major role in the attenuation of aqueous uranium; however, in these scenarios, acetate amendment induced detectable rebounds in the effluent uranium concentrations. The results of this study suggest that reductive immobilization of uranium can be achieved under predominantly sulfate-reducing conditions, and provide insight into the integrated roles of various biogeochemical components in long-term uranium sequestration.

58 GEOSCIENCES↗

Are You Philanthropy-Ready? How to Work with Foundations on Mission-Aligned Community Solar

Community solar is emerging as a popular way to deliver a range of economic and social benefits that go beyond clean energy. The US Department of Energy (DOE) has set a goal for America to deploy enough community solar projects to power the equivalent of five million households by 2025 and create $1 billion in energy bill savings. To reach the goal, DOE has created the Community Power Accelerator, as part of the National Community Solar Partnership (NCSP). The Accelerator is an online ecosystem bringing together developers, lenders, foundations, community organizations, and other stakeholders to support the deployment of mission-aligned community solar. The Accelerator is especially focused on projects that deliver "meaningful benefits" to customers and communities, including: access by low- to moderate-income households; greater bill savings; resilience and grid benefits; community ownership; and local workforce development. Many philanthropic organizations are looking at community solar as a way to capture these benefits in their grant-making and investment programs, while also reducing pollution and promoting environmental justice. To help community-based organizations (CBOs), non-profit organizations, and mission-aligned developers seeking philanthropic support, Berkeley Lab and the National Renewable Energy Lab prepared Are You Philanthropy-Ready? How to Work with Foundations on Mission-Aligned Community Solar. The guide provides an overview of how foundations work, gives tips on what they seek in a fundable project, and provides guidance on crafting effective proposals. In short, this guide aims to help the fund-seeker become philanthropy-ready.

14 SOLAR ENERGY↗

Nearly a decade-long repeatable seasonal diversity patterns of bacterioplankton communities in the eutrophic Lake Donghu (Wuhan, China)

Uncovering which environmental factors have the greatest influence on community diversity patterns and how ecological processes govern community turnover are key questions related to understanding community assembly mechanisms. Although we have good understanding of plant and animal community assembly, the mechanisms regulating diversity patterns of aquatic bacterial communities in lake ecosystems remains poorly understood. Here we present nearly a decade-long time-series study of bacterioplankton communities from the eutrophic Lake Donghu (Wuhan, China) using 16S rRNA gene amplicon sequencing. We found strong repeatable seasonal patterns for the overall community, common (detected in more than 50% samples) and dominant bacterial taxa (relative abundance > 1%). Moreover, community composition tracked the seasonal temperature gradient, indicating that temperature is an important environmental factor controlling observed diversity patterns. Total phosphorus also contributed significantly to the seasonal shifts in bacterioplankton composition. However, any spatial pattern across the main lake areas was overwhelmed by temporal variability in this eutrophic lake system. Phylogenetic analysis further indicated that 75%-82% of community turnover was governed by homogeneous selection, suggesting that the bacterioplankton communities are mainly controlled by niche-based processes. However, dominant niches available within seasons might be occupied by similar combinations of bacterial taxa with modest dispersal rates throughout this lake system. This study gives us important insights into community assembly and seasonal turnover of lake bacterioplankton, it may be also useful to predict temporal patterns of other planktonic communities.

16S rRNA amplicon sequencing↗

Soil characteristics and land-use drive bacterial community assembly patterns

ABSTRACT Land-use and soil characteristics drive variation in soil community composition, but the influences of these factors on dispersal and community assembly at regional scale remain poorly characterized. Land-use remains a consistent driver of soil community composition even when exhibiting patchy spatial distribution at regional scale. In addition, disturbed and early successional soils often exhibit stochastic community assembly patterns. These observations suggest local community composition is influenced by dispersal and assembly from regional species pools. We examined bacterial community assembly within agricultural cropland, old-field, and forested sites across 10 landscapes in the region around Ithaca, New York (USA). We found that the Sloan neutral model explained assembly well at regional scale (R2 = 0.763), but that both soil pH and land-use imposed selection that shaped community composition. We show that homogeneous selection was a dominant assembly process with respect to both soil pH and land-use regime, but that these two factors interacted in their effects on bacterial community assembly. We conclude that bacterial community assembly at a regional scale is driven by dispersal from regional species pools and local selection on the basis of soil pH and other soil characteristics that vary with land-use.

Microbiology↗

Assessing microbial community patterns under incipient soil formation from basalt

Microbial dynamics drive the biotic machinery of early soil evolution. However, integrated knowledge of microbial community establishment, functional associations, and community assembly processes in incipient soil is lacking. This study presents a novel approach of combining microbial phylogenetic profiling, functional predictions, and community assembly processes to analyze drivers of microbial community establishment in an emerging soil system. Rigorous sub-meter sampling of a basalt-soil lysimeter after two years of irrigation revealed the contrasting depth-dependent distribution patterns of soil parameters and community diversity. Phylogenetic analysis of 16S rRNA gene indicated the presence of diverse bacterial and archaeal phyla, with high relative abundance of Actinobacteria on the surface and a consistently high abundance of Proteobacteria at all depths. Predicted functional gene analysis suggested dominant autotrophy signatures, evidence of an incomplete nitrogen cycle, and predicted enzymes of iron (III) to iron (II) conversion followed by intracellular uptake, transport, and regulation. Null modeling revealed microbial community assembly predominantly governed by variable selection. The relative influence of the variable selection decreased with depth, indicating unique and relatively harsh environmental conditions near the surface and more benign conditions with depth. Additionally, high levels of dispersal influenced community composition near the center of the domain, suggesting that spatial processes interact with deterministic selection imposed by the environment. Characterizing the complexity in incipient soils can advance research insights about microbial community diversity and assembly in other incipient systems (e.g., transformation of marginal soils, or soils recovering from disturbances such as fire, erosion, intensive agricultural practices, or contamination).

Sengupta, Aditi↗

Community Planning for Solar: Compiling a Community Solar Action Plan

This document provides an annotated outline for a Community Solar Action Plan. This document is designed to assist community officials, volunteers, and regional planning agency staff in preparing a draft Community Solar Action Plan for a municipality, community, or other jurisdiction. Preparing a Community Solar Action Plan is the fifth step in the Community Planning for Solar process (ag.umass.edu/solarplanning). The plan is intended to be the culmination of the planning process. The contents of the plan will include summaries of information gathered as part of foregoing steps in the process, including completion of a Solar Resource and Infrastructure Assessment, administering of a Community Solar Survey, interpretation of survey results, and review of Solar Financing and Ownership Options and tools. Once the Community Solar Action Plan has been drafted, it should be reviewed by municipal board and commission members and presented at an open community forum. Any important comments or revisions can be incorporated before the final Community Solar Action Plan is approved and implemented. The approved Community Solar Action Plan is a living document that guides community solar planning action over time. As conditions change, new information becomes available, or actions progress over the life of the plan, adjustments may be necessary to maintain the plan's relevance. The Monitoring, Evaluating, and Updating Your Community Solar Action Plan fact sheet (Step 6, Item a) describes some things to consider when updating the Community Solar Action Plan over time.

14 SOLAR ENERGY↗

Occupant Preference-Aware Load Scheduling for Resilient Communities

The load scheduling of resilient communities in the islanded mode is subject to many uncertainties such as weather forecast errors and occupant behavior stochasticity. To date, it remains unclear how occupant preferences affect the effectiveness of the load scheduling of resilient communities. This paper proposes an occupant thermal preference-aware load scheduler for resilient communities operating in the islanded mode. First, key resilience indicators are selected to quantify its impacts on the load scheduling of a resilient community. A deterministic model predictive control-based load scheduling framework is adopted as the baseline. Then, a chance-constrained controller is proposed to address the occupant-induced uncertainty in room temperature setpoints. Finally, the chance-constrained controller is compared with the deterministic controller on a virtual community testbed based on a real-world net-zero energy community in Florida, U.S. Results have shown that the proposed chance-constrained controller performs better in terms of serving occupants’ thermal preference and the required battery sizes compared to the deterministic controller with the presence of the assumed stochastic occupant behavior. This work indicates that it is necessary to consider the stochasticity of the occupant behavior when designing optimal load schedulers for resilient communities.

Wang, Jing↗

Community Energy Planning: Best Practices and Lessons Learned in NREL's Work with Communities

The clean energy transition is accelerating due to local, state, and national actions combined with external market forces. Regardless of where goals are set and decisions are made, clean energy deployment occurs on the ground in communities. As a result, communities increasingly need technical expertise and assistance with planning for and managing the energy transition. Building on decades of work with state, local, and tribal jurisdictions, the National Renewable Energy Laboratory (NREL) increasingly provides community-driven modeling, analysis, and technical assistance to enable more data-driven and equitable community energy planning. To inform and enhance NREL's capabilities in community energy planning and provide a resource for others working in this space, the Joint Institute for Strategic Energy Analysis (JISEA) Sustainable Communities Catalyzer supported this best-practices presentation based on interviews with seasoned NREL practitioners and a literature review on equitable community energy planning. Findings include five best practices for community energy planning that NREL practitioners and others can apply to strengthen their impact: 1) do your homework in preparation for community interactions; 2) be humble, authentic, and honest in your interactions with community members; 3) respect community agency in every step of the process; 4) meet the community where they are; 5) democratize participation.

best practices↗

Impacts of nitrogen addition on switchgrass root-associated diazotrophic community structure and function

ABSTRACT Cellulosic bioenergy crops, like switchgrass (Panicum virgatum), have potential for growth on lands unsuitable for food production coupled with potential for climate mitigation. Sustainability of these systems lies in identifying conditions that promote high biomass yields on marginal lands under low-input agricultural practices. Associative nitrogen fixation (ANF) is a potentially important nitrogen (N) source for these crops, yet ANF contributions to plant N, especially under fertilizer N addition are unclear. In this study, we assess structure (nifH) and function (ANF) of switchgrass root-associated diazotrophic communities to long-term and short-term N additions using soil from three marginal land sites. ANF rates were variable and often unexpectedly high, sometimes 10× greater than reported in the literature, and did not respond in repeatable ways to long-term or short-term N. We found few impacts of N addition on root-associated diazotrophic community structure or membership. Instead, we found a very consistent root-associated diazotrophic community even though switchgrass seeds were germinated in soil from field sites with distinct diazotrophic communities. Ultimately, this work demonstrates that root-associated diazotrophic communities have the potential to contribute to switchgrass N demands, independent of N addition, and this may be driven by selection of the diazotrophic community by switchgrass roots.

Microbiology↗

Data-driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities

Data-driven science and technology have helped achieve meaningful results in areas such as materials/drug discovery and health care, but efforts to apply high-end data science algorithms to the areas of glass and ceramics are still limited. Many glass and ceramic researchers are interested in enhancing their work by using more data and data analytics to efficiently develop better functional materials. Simultaneously, the data science community is looking for a way to access materials data resources to test and validate their advanced computational learning algorithms. To bring together the glass/ceramic and data science communities to address this issue, The American Ceramic Society (ACerS) convened a Glass/Ceramics Data Science Workshop on February 6, 2018, at Nexight Group offices in Silver Spring, Maryland. The workshop, sponsored by the National Institute for Standards and Technology (NIST) Advanced Manufacturing Technologies (AMTech) program, brought together a select group of 20 key leaders in the data science, informatics, and glass/ceramics communities to identify the greatest opportunities and mechanisms for facilitating increased collaboration and coordination between these communities. This article summarizes workshop discussions about the current challenges that limit interactions and collaboration between the glass/ceramic and data science communities, opportunities for a coordinated approach that leverages existing knowledge in both communities, and a clear path toward the enhanced use of data science technologies for functional glass and ceramic research and development.

data science, ceramics, informatics↗