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At least 199 records · Page 11

In Vivo Molecular Insights into Syntrophic Geobacter Aggregates

Direct interspecies electron transfer (DIET) has been considered as a novel and highly efficient strategy in both natural anaerobic environments and artificial microbial fuel cells. A syntrophic model consisting of Geobacter metallireducens and Geobacter sulfurreducens was studied in this work. We conducted in vivo molecular mapping of the outer surface of the syntrophic community as the interface of nutrients and energy exchange. System for Analysis at the Liquid Vacuum Interface combined with time-of-flight secondary ion mass spectrometry was employed to capture the molecular distribution of syntrophic Geobacter communities in the living and hydrated state. Principal component analysis with selected peaks revealed that syntrophic Geobacter aggregates were well differentiated from other control samples, including syntrophic planktonic cells, pure cultured planktonic cells, and single population biofilms. Our in vivo imaging indicated that a unique molecular surface was formed. Specifically, aromatic amino acids, phosphatidylethanolamine components, and large water clusters were identified as key components that favored the DIET of syntrophic Geobacter aggregates. Moreover, the molecular changes in depths of the Geobacter aggregates were captured using dynamic depth profiling. Our findings shed new light on the interface components supporting electron transfer in syntrophic communities based on in vivo molecular imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Total ecosystem carbon stocks at the marine-terrestrial interface: Blue carbon of the Pacific Northwest Coast, United States

The coastal ecosystems of temperate North America provide a variety of ecosystem services including high rates of carbon sequestration. Yet, little data exist for the carbon stocks of major tidal wetland types in the Pacific Northwest, United States. We quantified the total ecosystem carbon stocks (TECS) in seagrass, emergent marshes, and forested tidal wetlands, occurring along increasing elevation and decreasing salinity gradients. The TECS included the total aboveground carbon stocks and the entire soil profile (to as deep as 3 m). TECS significantly increased along the elevation and salinity gradients: 217 ± 60 Mg C/ha for seagrass (low elevation/high salinity), 417 ± 70 Mg C/ha for low marsh, 551 ± 47 Mg C/ha for high marsh, and 1,064 ± 38 Mg C/ha for tidal forest (high elevation/low salinity). Soil carbon stocks accounted for >98% of TECS in the seagrass and marsh communities and 78% in the tidal forest. Soils in the 0–100 cm portion of the profile accounted for only 48%–53% of the TECS in seagrasses and marshes and 34% of the TECS in tidal forests. Thus, the commonly applied limit defining TECS to a 100 cm depth would greatly underestimate both carbon stocks and potential greenhouse gas emissions from land-use conversion. The large carbon stocks coupled with other ecosystem services suggest value in the conservation and restoration of temperate zone tidal wetlands through climate change mitigation strategies. However, the findings suggest that long-term sea level rise effects such as tidal inundation and increased porewater salinity will likely decrease ecosystem carbon stocks in the absence of upslope wetland migration buffer zones.

Kauffman, J Boone↗

The Chicago Social Interaction Model (ChiSIM)

ChiSIM is a framework for implementing agent-based models that simulate the mixing of a synthetic population. In a ChiSIM based model, each agent, that is, each person in the simulated population, resides in a place (a household, dormitory or retirement home/long term care facility, for example), and moves among other places such as workplaces, homes, clinics, and community resources. Agents typically move between places according to their domain specific activity profile, such that each agent has a profile that determines at what times throughout the day they occupy a particular location. Once in a place, an agent mixes with other agents in some model or domain-specific way. For example, an agent may expose other agents to a disease in an epidemiological model.

Ozik, Jonathan↗

Combined analysis of microbial metagenomic and metatranscriptomic sequencing data to assess in situ physiological conditions in the premature infant gut

Microbes alter their transcriptomic profiles in response to the environment. The physiological conditions experienced by a microbial community can thus be inferred using meta-transcriptomic sequencing by comparing transcription levels of specifically chosen genes. However, this analysis requires accurate reference genomes to identify the specific genes from which RNA reads originate. In addition, such an analysis should avoid biases in transcript counts related to differences in organism abundance. In this study we describe an approach to address these difficulties. Sample-specific meta-genomic assembled genomes (MAGs) were used as reference genomes to accurately identify the origin of RNA reads, and transcript ratios of genes with opposite transcription responses were compared to eliminate biases related to differences in organismal abundance, an approach hereafter named the “diametric ratio” method. We used this approach to probe the environmental conditions experienced by Escherichia spp. in the gut of 4 premature infants, 2 of whom developed necrotizing enterocolitis (NEC), a severe inflammatory intestinal disease. We analyzed twenty fecal samples taken from four premature infants (4–6 time points from each infant), and found significantly higher diametric ratios of genes associated with low oxygen levels in samples of infants later diagnosed with NEC than in samples without NEC. We also show this method can be used for examining other physiological conditions, such as exposure to nitric oxide and osmotic pressure. These study results should be treated with caution, due to the presence of confounding factors that might also distinguish between NEC and control infants. Nevertheless, together with benchmarking analyses, we show here that the diametric ratio approach can be applied for evaluating the physiological conditions experienced by microbes in situ. Results from similar studies can be further applied for designing diagnostic methods to detect NEC in its early developmental stages.

59 BASIC BIOLOGICAL SCIENCES↗

National Institute of Standards and Technology Requirements (Analysis Report)

EPOC uses the Deep Dive process to discuss and analyze current and planned science, research, or education activities and the anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. In October of 2022, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from the National Institute of Standards and Technology (NIST) for the purpose of a Deep Dive into scientific and research drivers. The goal of this activity was to help characterize the requirements for a number of campus use cases, and to enable cyberinfrastructure support staff to better understand the needs of the researchers within the community. Material for this event included the written documentation from each of the profiled research areas, documentation about the current state of technology support, and a write-up of the discussion that took place via e-mail and video conferencing. The case studies highlighted the ongoing challenges and opportunities that NIST has in supporting a cross-section of established and emerging research use cases. Each case study mentioned unique challenges which were summarized into common needs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

New York-Presbyterian and Columbia University Irving Medical Center Requirements (Analysis Report)

EPOC uses the Deep Dive process to discuss and analyze current and planned science, research, or education activities and the anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Between February and June 2024, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from New York-Presbyterian (NYP), Columbia University Irving Medical Center (CUIMC), and NYSERNet for the purpose of a Deep Dive into scientific and research drivers. The goal of this activity was to help characterize the requirements for a number of campus use cases, and to enable cyberinfrastructure support staff to better understand the needs of the researchers within the community. Material for this event included the written documentation from each of the profiled research areas, documentation about the current state of technology support, and a write-up of the discussion that took place via e-mail and video conferencing. The case studies highlighted the ongoing challenges and opportunities that NYP and CUIMC have in supporting a cross-section of established and emerging research use cases. Each case study mentioned unique challenges which were summarized into common needs.

97 MATHEMATICS AND COMPUTING↗

Salk Institute for Biological Studies Requirements (Analysis Report)

EPOC uses the Deep Dive process to discuss and analyze current and planned science, research, or education activities and the anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Between February and March 2024, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from the Salk Institute for Biological Studies (Salk) for the purpose of a Deep Dive into scientific and research drivers. The goal of this activity was to help characterize the requirements for a number of campus use cases, and to enable cyberinfrastructure support staff better to understand the needs of the researchers within the community. Material for this event included the written documentation from each of the profiled research areas, documentation about the current state of technology support, and a write-up of the discussion that took place via e-mail and video conferencing. The case studies highlighted the ongoing challenges and opportunities that Salk Institute for Biological Studies have in supporting a cross-section of established and emerging research use cases. Each case study mentioned unique challenges which were summarized into common needs.

59 BASIC BIOLOGICAL SCIENCES↗

JPL-TMF multiwavelength aerosol lidar

The JPL-TMF Lidar Facility began operation in 1985 with the completion of a XeCl excimer based stratospheric ozone DIAL system. As an adjunct to this system a Nd:YAG based tropospheric ozone and aerosol system was assembled. The tropospheric ozone system was designed to utilize the fourth harmonic (266 nm) of the Nd:YAG to produce 289 nm, 294 nm or 299 nm by SRS in the isotopic hydrogen gases. The aerosol lidar was developed using the fundamental (1064 nm) and second harmonic of the Nd:YAG (532 nm). Following the eruption of Mount Pinatubo most of the effort was put into obtaining data on the layer structure of the volcanic aerosol as a function of altitude and time on a regular basis. During this period the tropospheric ozone DIAL was not employed on a regular schedule. The stratospheric measurements were of primary interest; however with the volcanic aerosol concentrated at the 16 - 26 km altitude the ozone concentration profile was perturbed. The aerosol interference in the ozone measurements caused the lidar community to seek techniques of measurement of the aerosol which could be used in making realistic corrections to the ozone measurements. It is generally accepted that a reasonable technique of measurement would include at least one channel of Raman scattering from a blue wavelength and a minimum of three other supporting wavelengths. With the primary transmitters available at TMF, a four wavelength system was considered for configuration. The four wavelength aerosol lidar is based on the Nd:YAG fundamental, the second and third harmonics of the transmitter. The receiver will separate these three wavelengths as well as the Raman scattering from atmospheric nitrogen of the third harmonic.

Haner, David A.↗

Regional Assimilation of NASA Atmospheric Infrared Sounder (AIRS) Data

The NASA Short-term Prediction Research and Transition (SPORT) Center seeks to accelerate the infusion of NASA Earth Science Enterprise (ESE) observations, data assimilation and modeling research into NW S forecast operations and decision-making. The Atmospheric Infrared Sounder (AIRS), is expected to advance climate research and weather prediction into the 21 st century. It is one of six instruments onboard Aqua, a satellite that is part of NASA s Earth Observing System. AIRS, along with two partner microwave sounding instruments, represents the most advanced atmospheric sounding system ever deployed in space. The system is capable of measuring the atmospheric temperature in the troposphere with radiosonde accuracies of 1 K over 1 km-thick layers under both clear and cloudy conditions, while the accuracy of the derived moisture profiles will exceed that obtained by radiosondes. It is imperative that the scientific community is prepared to take full advantage of next-generation satellite data that will become available within the next decade. The purpose of this paper is to describe a procedure designed to optimally assimilate AIRS data at high spatial resolution over both land and ocean. The assimilation system used in this study is the Local Analysis and Prediction System (LAPS) developed at the Forecast System Laboratory used extensively around the globe. Results will focus on quality control issues associated with AIRS, optimal assimilation strategies, and the impact of the AIRS data on subsequent numerical forecasts at 12 km produced by the next generation Weather Research and Forecast (WRF) model.

Chou, Shih-Hung↗

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours

Shaw, Michael↗

An Evidenced-Based Approach for Estimating Decompression Sickness Risk in Aircraft Operations

Estimating the risk of decompression Sickness (DCS) in aircraft operations remains a challenge, making the reduction of this risk through the development of operationally acceptable denitrogenation schedules difficult. In addition, the medical recommendations which are promulgated are often not supported by rigorous evaluation of the available data, but are instead arrived at by negotiation with the aircraft operations community, are adapted from other similar aircraft operations, or are based upon the opinion of the local medical community. We present a systematic approach for defining DCS risk in aircraft operations by analyzing the data available for a specific aircraft, flight profile, and aviator population. Once the risk of DCS in a particular aircraft operation is known, appropriate steps can be taken to reduce this risk to a level acceptable to the applicable aviation community. Using this technique will allow any aviation medical community to arrive at the best estimate of DCS risk for its specific mission and aviator population and will allow systematic reevaluation of the decisions regarding DCS risk reduction when additional data are available.

Robinson, Ronald R.↗

Disentangling plant- and environment-mediated drivers of active rhizosphere bacterial community dynamics during short-term drought

Abstract Mitigating the effects of climate stress on crops is important for global food security. The microbiome associated with plant roots, the rhizobiome, can harbor beneficial microbes that alleviate stress, but the factors influencing their recruitment are unclear. We conducted a greenhouse experiment using field soil with a legacy of growing switchgrass and common bean to investigate the impact of short-term drought severity on the recruitment of active bacterial rhizobiome members. We applied 16S rRNA and 16S rRNA gene sequencing for both crops and metabolite profiling for switchgrass. We included planted and unplanted conditions to distinguish environment- versus plant-mediated rhizobiome drivers. Differences in community structure were observed between crops and between drought and watered and planted and unplanted treatments within crops. Despite crop-specific communities, drought rhizobiome dynamics were similar across the two crops. The presence of a plant more strongly explained the rhizobiome variation in bean (17%) than in switchgrass (3%), with a small effect of plant mediation during drought observed only for the bean rhizobiome. The switchgrass rhizobiome was stable despite changes in rhizosphere metabolite profiles between planted and unplanted treatments. We conclude that rhizobiome responses to short-term drought are crop-specific, with possible decoupling of plant exudation from rhizobiome responses.

59 BASIC BIOLOGICAL SCIENCES↗

United States cool surfaces deployment plan

Solar-reflective building envelope surfaces, such as cool roofs and walls, can be especially helpful in disadvantaged communities that often have poorly insulated older homes, aging or absent air conditioning units, steep utility bills, polluted air, and high vulnerability and exposure to extreme heat. With support from the U.S. Department of Energy, our project seeks to dramatically increase the climate-appropriate deployment of cool surfaces across the United States with an emphasis on their application to disadvantaged communities. First, we sought to identify cool-surface deployment barriers, opportunities, and models by (a) reviewing the history of cool-surface deployment activities, (b) interviewing cool-surface stakeholders, (c) researching successful energy-efficiency/green building deployment models; and (d) interviewing the actors who have implemented these models. Second, we conducted a workshop to engage stakeholders in development of a deployment plan. Third, we asked several U.S. federal agencies (a) how cool surfaces and cool surface stakeholders could support their missions and (b) how agency activities could support cool-surface deployment. Fourth, we identified a set of transformative ideas that form the core of the deployment plan. Transformative ideas include but are not limited to initiatives to (a) launch an educational campaign to make the general public and building professionals aware of how cool roofs and walls exclude unwanted solar heat; (b) create a “Cool Roof Prize” stimulating the development of affordable, high-performance cool asphalt roofing shingles; (c) conduct high-profile, large-scale demonstration programs that bring cool surfaces to disadvantaged heat-vulnerable communities; and (d) support local, regional, and state climate action (heat mitigation) plans with cool surfaces.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Community‐Level Metabolic Shifts Following Land Use Change in the Amazon Rainforest Identified by a Supervised Machine Leaning Approach

ABSTRACT The Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. This change in plant cover is known to alter the soil microbiome and the functions it mediates, but the genomic changes underlying this response are still unresolved. In this study, we used a combination of deep shotgun metagenomics complemented by a supervised machine learning approach to compare the metabolic strategies of tropical soil microbial communities in pristine forests and long‐term established pastures in the Amazon. Machine learning‐derived metagenome analysis indicated that microbial community structures (bacteria, archaea and viruses) and the composition of protein‐coding genes were distinct in each plant cover type environment. Forest and pasture soils had different genomic diversities for the above three taxonomic groups, characterised by their protein‐coding genes. These differences in metagenome profiles in soils under forests and pastures suggest that metabolic strategies related to carbohydrate and energy metabolisms were altered at community level. Changes were also consistent with known modifications to the C and N cycles caused by long‐term shifts in aboveground vegetation and were also associated with several soil physicochemical properties known to change with land use, such as the C/N ratio, soil temperature and exchangeable acidity. In addition, our analysis reveals that these alterations in land use can also result in changes to the composition and diversity of the soil DNA virome. Collectively, our study indicates that soil microbial communities shift their overall metabolic strategies, driven by genomic alterations observed in pristine forests and long‐term established pastures with implications for the C and N cycles.

carbon and nitrogen cycles↗

Impact of Drought on Ecohydrology of Southern California Grassland and Shrubland

Abstract Through their rooting profiles and water demands, plants affect the distribution of water in the soil profile. Simultaneously, soil water content controls plant development and interactions within and between plant communities. These plant-soil water feedbacks might vary across plant communities with different rooting depths and species composition. In semiarid environments, understanding these differences will be essential to predict how ecosystems will respond to drought, which may become more frequent and severe with climate change. In this study, we tested how plant-soil water feedbacks responded to drought in two contrasting ecosystem types—grassland and shrubland—in the coastal foothills of southern California. During years 5–8 of an ongoing precipitation manipulation experiment, we measured changes in plant communities and soil moisture up to 2 m depth. We observed different water use patterns in grassland and shrubland communities with distinct plant functional types and water use strategies. Drought treatment did not affect perennial, deep-rooted shrubs because they could access deep soil water pools. However, mid-rooted shrubs were sensitive to drought and experienced decreased productivity and die-off. As a result, water content actually increased with drought at soil depths from 50–150 cm. In grassland, biomass production by annual species, including annual grasses and forbs, declined with drought, resulting in lower water uptake from the surface soil layer. An opportunistic “live fast, die young“ life strategy allowed these species to recover quickly once water availability increased. Our results show how drought interacts with plant community composition to affect the soil water balance of semiarid ecosystems, information that could be integrated into global scale models.

54 ENVIRONMENTAL SCIENCES↗

Metabolically diverse microorganisms mediate methylmercury formation under nitrate-reducing conditions in a dynamic hydroelectric reservoir

Brownlee Reservoir is a mercury (Hg)-impaired hydroelectric reservoir that exhibits dynamic hydrological and geochemical conditions and is located within the Hells Canyon Complex in Idaho, USA. Methylmercury (MeHg) contamination in fish is a concern in the reservoir. While MeHg production has historically been attributed to sulfate-reducing bacteria and methanogenic archaea, microorganisms carrying the hgcA gene are taxonomically and metabolically diverse and the major biogeochemical cycles driving mercury (Hg) methylation are not well understood. In this study, Hg speciation and redox-active compounds were measured throughout Brownlee Reservoir across the stratified period in four consecutive years (2016–2019) to identify the location where and redox conditions under which MeHg is produced. Metagenomic sequencing was performed on a subset of samples to characterize the microbial community with hgcA and identify possible links between biogeochemical cycles and MeHg production. Biogeochemical profiles suggested in situ water column Hg methylation was the major source of MeHg. These profiles, combined with genome-resolved metagenomics focused on hgcA-carrying microbes, indicated that MeHg production occurs in this system under nitrate- or manganese-reducing conditions, which were previously thought to preclude Hg-methylation. Using this multidisciplinary approach, we identified the cascading effects of interannual variability in hydrology on the redox status, microbial metabolic strategies, abundance and metabolic diversity of Hg methylators, and ultimately MeHg concentrations throughout the reservoir. This work expands the known conditions conducive to producing MeHg and suggests that the Hg-methylation mitigation efforts by nitrate or manganese amendment may be unsuccessful in some locations.

54 ENVIRONMENTAL SCIENCES↗

A Flang Plugin for Fortran Feature Characterization

As new compute systems are developed, there is still a need to compile and execute codes authored in Fortran on these leading edge systems. In order to achieve this, development of compilers that support the latest hardware is continuously under development. Though the specification of Fortran is extensive, it is helpful to compiler authors to be able to prioritize the development of key features in order to get certain codes deemed important, e.g., applications of interest to leadership computing facilities, executable on leading edge compute systems. Identifying key features though is largely done through querying software experts or users of the Fortran applications of interest, who then manually report what features are and are not present. This exercise can both time consuming and error prone. To automate this process, we present a compiler plugin to Flang, the Fortran frontend for LLVM. This plugin is a tool that operates on the parse tree representation generated by Flang and detects key features based on walking parse tree nodes that correspond to features of interest. We show the result of our tool on four applications, three of which were manually profiled by software experts. We show the discrepancies between our tool and the manual characterization of the three applications, as well as generate a characterization for an application not yet profiled. We intend to open-source our tool in order to invite the community to benefit from the tool and make contributions for other features.

Cabrera, Anthony [ORNL]↗

How Well Satellite Remote Sensing Can Inform Surface Level Ozone Production Sensitivity to Precursor Trace Gas Emissions?

Surface-level ozone (O3) pollution mitigation strategies rely on a clear understanding of the atmospheric chemical processes involving O3, NOx (nitric oxide (NO) + nitrogen dioxide (NO2)) and volatile organic compounds (VOCs). A robust spatiotemporal classification of O3 photochemical regimes with relative chemical sensitivity of local O3 formation to emission reductions of NOx (NOx-limited regime) versus VOCs (radical-limited regime) is required to design anthropogenic emission reduction policies in order to improve surface air quality. Numerous studies found that the ratio of satellite-retrieved Vertical Column Densities (VCDs) of formaldehyde (HCHO) to NO2 can diagnose O3 production sensitivity. However, uncertainty still remains about the accuracy of such estimates using satellite-based retrievals. This study conducts an investigation to identify how well satellite data can inform surface-level O3 sensitivity by validating satellite-based estimates against aircraft-based retrievals taken during the Long Island Sound Tropospheric Ozone Study (LISTOS-2018) and Ozone Water-Land Environmental Transition Study (OWLETS-2) field campaigns. For this study, we use HCHO and NO2 retrievals from the Ozone Monitoring Instrument (OMI) onboard the Aura satellite, and high spatiotemporal resolution TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite. The Community Multiscale Air Quality (CMAQ) modelling system is used to provide trace gas vertical profiles to recalculate air mass factor for deriving consistent satellite-based VCDs. To demonstrate the ability of satellites to diagnose O3 production regimes, we validate satellite-derived O3 sensitivity regimes, along with the OMI and TROPOMI products applied, using HCHO and NO2 retrievals from the aircraft-based instruments: Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) spectrometer and Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) instruments deployed during the LISTOS-2018 and OWLETS-2 campaigns. The results of this work will advance our fundamental knowledge of the spatiotemporal evolution of the complex O3-NOx-VOC chemistry, and will advance our understanding about the quality of remote-sensing, suborbital, and satellite data for accurately observing surface-level O3 production sensitivity.

Satellite↗