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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Data for Immediate Impacts of Soybean Cover Crop on Bacterial Community Composition and Diversity in Soil Under Long-Term Saccharum Monoculture

Saccharum yield decline results from long-term monoculture practices. Changes in cropping management can improve soil health and productivity. Below-ground bacterial community diversity and composition across soybean (Glycine max (L.) Merr) cover crop, Saccharum monoculture (30+ year) and fallowed soil were determined. Near full length (~1,400 base pairs) of 16S rRNA gene sequences were extracted from the rhizospheres of sugarcane and soybean and fallowed soil were compared. Higher soil bacterial diversity was observed in the soybean cover crop than sugarcane monoculture across all measured indices (observed operationational taxonomic units, Chao1, Shannon, reciprocal Simpson and Jackknife). Acidocateria, Proteobacteria, Bacteroidetes and Planctomycetes were the most abundant bacterial phyla across the treatments. Indicator species analysis identified nine indicator phyla. Planctomycetes, Armatimonadetes and candidate phylum FBP were associated with soybean; Proteobacteria and Firmicutes were linked with sugarcane and Gemmatimonadetes, Nitrospirae, Rokubacteria and unclassified bacteria were associated with fallowed soil. Non-metric multidimensional scaling analysis showed distinct groupings of bacterial operational taxonomic units (97% identity) according to management system (soybean, sugarcane or fallow) indicating compositional differences among treatments. This is confirmed by the results of the multi-response permutation procedures (A = 0.541, p = 0.00045716). No correlation between soil parameters and bacterial community structure was observed according to Mantel test (r = 211865, p = 0.14). Use of soybean cover-crop fostered bacterial diversity and altered community structure. This indicates cover crops could have a restorative effect and potentially promote sustainability in long-term Saccharum production systems.

Field Data↗
NASA NTRS2009

Hybrid diversity method utilizing adaptive diversity function for recovering unknown aberrations in an optical system

A method of recovering unknown aberrations in an optical system includes collecting intensity data produced by the optical system, generating an initial estimate of a phase of the optical system, iteratively performing a phase retrieval on the intensity data to generate a phase estimate using an initial diversity function corresponding to the intensity data, generating a phase map from the phase retrieval phase estimate, decomposing the phase map to generate a decomposition vector, generating an updated diversity function by combining the initial diversity function with the decomposition vector, generating an updated estimate of the phase of the optical system by removing the initial diversity function from the phase map. The method may further include repeating the process beginning with iteratively performing a phase retrieval on the intensity data using the updated estimate of the phase of the optical system in place of the initial estimate of the phase of the optical system, and using the updated diversity function in place of the initial diversity function, until a predetermined convergence is achieved.

Dean, Bruce H.↗
NASA NTRS2011

Deep Diversity: Novel Approach to Overcoming the PCR Bias Encountered During Environmental Analysis of Microbial Populations for Alpha-Diversity

Alpha-diversity studies are of crucial importance to environmental microbiologists. The polymerase chain reaction (PCR) method has been paramount for studies interrogating microbial environmental samples for taxon richness. Phylogenetic studies using this technique are based on the amplification and comparison of the 16S rRNA coding regions. PCR, due disproportionate distribution of microbial species in the environment, increasingly favors the amplification of the most predominant phylotypes with every subsequent reaction cycle. The genetic and chemical complexity of environmental samples are intrinsic factors that exacerbate an inherit bias in PCR-based quantitative and qualitative studies of microbial communities. We report that treatment of a genetically complex total genomic environmental DNA extract with Propidium Monoazide (PMA), a DNA intercalating molecule capable of forming a covalent cross-linkage to organic moieties upon light exposure, disproportionally inactivates predominant phylotypes and results in the exponential amplification of previously shadowed microbial ?-diversity quantified as a 19.5% increase in OUTs reported via phylogenetic screening using PhyloChip.

phylogenetic microarray technologies↗
DOE OSTI2023

Voltage-Based Strategies for Preventing Battery Degradation under Diverse Fast-Charging Conditions

Maintaining safe operating conditions is a key challenge for high-performance lithium-ion battery applications. The lithium-plating reaction remains a risk during charging, but limited studies consider the highly variable charging conditions possible in commercial cells. Here we combine pseudo-2D electrochemical modeling with data visualization methods to reveal important relationships between the measurable cell voltage and difficult-to-predict Li-plating onset criteria. An extensively validated model is used to compute Li plating for thousands of multistep charging conditions spanning diverse rates, temperatures, states-of-charge, and cell aging. Here we observe an empirical cell operating voltage limit below which plating does not occur across all conditions, and this limit varies with the battery state-of-charge and aging. A model sensitivity analysis also indicates that, when comparing two charging voltage profiles, the capacity difference at 4.0 V correlates well with the difference in the plating onset capacity. These results encourage simple strategies for Li-plating prevention that are complementary to existing battery controls.

25 ENERGY STORAGE↗
DOE OSTI2023

Genetic diversity, population structure and anthracnose resistance response in a novel sweet sorghum diversity panel

Sweet sorghum is an attractive feedstock for the production of renewable chemicals and fuels due to the readily available fermentable sugars that can be extracted from the juice, and the additional stream of fermentable sugars that can be obtained from the cell wall polysaccharides in the bagasse. An important selection criterion for new sweet sorghum germplasm is resistance to anthracnose, a disease caused by the fungal pathogen Colletotrichum sublineolum. The identification of novel anthracnose-resistance sources present in sweet sorghum germplasm offers a fast track towards the development of new resistant sweet sorghum germplasm. We established a sweet sorghum diversity panel (SWDP) of 272 accessions from the USDA-ARS National Plant Germplasm (NPGS) collection that includes landraces from 22 countries and advanced breeding material, and that represents ~15% of the NPGS sweet sorghum collection. Genomic characterization of the SWDP identified 171,954 single nucleotide polymorphisms (SNPs) with an average of one SNP per 4,071 kb. Population structure analysis revealed that the SWDP could be stratified into four populations and one admixed group, and that this population structure could be aligned to sorghum’s racial classification. Results from a two-year replicated trial of the SWDP for anthracnose resistance response in Texas, Georgia, Florida, and Puerto Rico showed 27 accessions to be resistant across locations, while 145 accessions showed variable resistance response against local pathotypes. A genome-wide association study identified 16 novel genomic regions associated with anthracnose resistance. Four resistance loci on chromosomes 3, 6, 8 and 9 were identified against pathotypes from Puerto Rico, and two resistance loci on chromosomes 3 and 8 against pathotypes from Texas. In Georgia and Florida, three resistance loci were detected on chromosomes 4, 5, 6 and four on chromosomes 4, 5 (two loci) and 7, respectively. One resistance locus on chromosome 2 was effective against pathotypes from Texas and Puerto Rico and a genomic region of 41.6 kb at the tip of chromosome 8 was associated with resistance response observed in Georgia, Texas, and Puerto Rico. This publicly available SWDP and the extensive evaluation of anthracnose resistance represent a valuable genomic resource for the improvement of sorghum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Diverse MarR bacterial regulators of auxin catabolism in the plant microbiome

Abstract Chemical signalling in the plant microbiome can have drastic effects on microbial community structure, and on host growth and development. Previously, we demonstrated that the auxin metabolic signal interference performed by the bacterial genus Variovorax via an auxin degradation locus was essential for maintaining stereotypic root development in an ecologically relevant bacterial synthetic community. Here, we dissect the Variovorax auxin degradation locus to define the genes iadDE as necessary and sufficient for indole-3-acetic acid (IAA) degradation and signal interference. We determine the crystal structures and binding properties of the operon’s MarR-family repressor with IAA and other auxins. Auxin degradation operons were identified across the bacterial tree of life and we define two distinct types on the basis of gene content and metabolic products: iac -like and iad -like. The structures of MarRs from representatives of each auxin degradation operon type establish that each has distinct IAA-binding pockets. Comparison of representative IAA-degrading strains from diverse bacterial genera colonizing Arabidopsis plants show that while all degrade IAA, only strains containing iad -like auxin-degrading operons interfere with auxin signalling in a complex synthetic community context. This suggests that iad -like operon-containing bacterial strains, including Variovorax species, play a key ecological role in modulating auxins in the plant microbiome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Improving streamflow predictions across CONUS by integrating advanced machine learning models and diverse data

Accurate streamflow prediction is crucial to understand climate impacts on water resources and develop effective adaption strategies. A global long short-term memory (LSTM) model, using data from multiple basins, can enhance streamflow prediction, yet acquiring detailed basin attributes remains a challenge. To overcome this, we introduce the Geo-vision transformer (ViT)-LSTM model, a novel approach that enriches LSTM predictions by integrating basin attributes derived from remote sensing with a ViT architecture. Applied to 531 basins across the Contiguous United States, our method demonstrated superior prediction accuracy in both temporal and spatiotemporal extrapolation scenarios. Geo-ViT-LSTM marks a significant advancement in land surface modeling, providing a more comprehensive and effective tool for better understanding the environment responses to climate change.

Tayal, Kshitij↗
DOE OSTI2024

Mo than meets the eye: genomic insights into molybdoenzyme diversity of Seleniivibrio woodruffii strain S4T

Abstract Seleniivibrio woodruffii strain S4T is an obligate anaerobe belonging to the phylum Deferribacterota. It was isolated for its ability to respire selenate and was also found to respire arsenate. The high-quality draft genome of this bacterium is 2.9 Mbp, has a G+C content of 48%, 2762 predicted genes of which 2709 are protein-coding, and 53 RNA genes. An analysis of the genome focusing on the genes encoding for molybdenum-containing enzymes (molybdoenzymes) uncovered a remarkable number of genes encoding for members of the dimethylsulfoxide reductase family of proteins (DMSOR), including putative reductases for selenate and arsenate respiration, as well as genes for nitrogen fixation. Respiratory molybdoenzymes catalyze redox reactions that transfer electrons to a variety of substrates that can act as terminal electron acceptors for energy generation. Seleniivibrio woodruffii strain S4T also has essential genes for molybdate transporters and the biosynthesis of the molybdopterin guanine dinucleotide cofactors characteristic of the active centers of DMSORs. Phylogenetic analysis revealed candidate respiratory DMSORs spanning nine subfamilies encoded within the genome. Our analysis revealed the untapped potential of this interesting microorganism and expanded our knowledge of molybdoenzyme co-occurrence.

Louie, Tiffany S.↗
NASA NTRS2022

Using airborne and DESIS imaging spectroscopy to map plant diversity across the largest contiguous tract of tallgrass prairie on earth

Grassland ecosystems are under threat globally, primarily due to land-use and land-cover changes that have adversely affected their biodiversity. Given the negative ecological impacts of biodiversity loss in grasslands, there is an urgent need for developing an operational biodiversity monitoring system that functions in these ecosystems. In this paper, we assessed the capability of airborne and spaceborne imaging spectroscopy (also known as hyperspectral imaging) to capture plant α-diversity in a large naturally-assembled grassland while considering the impact of common management practices, specifically prescribed fire. We collected a robust in-situ plant diversity data set, including species composition and percent cover from 2500 sampling points with different burn ages, from recently-burned to transitional and pre-prescribed fire at the Joseph H. Williams Tallgrass Prairie Preserve in Oklahoma, USA. We expressed in-situ plant α-diversity using the first three Hill numbers, including species richness (number of observed species in a plant community), exponential Shannon entropy index (hereafter Shannon diversity; effective number of common species, where species are weighed proportional to their percent cover), and inverse Simpson concentration index (hereafter Simpson diversity; effective number of dominant species, where more weight is given to dominant species) at four different plot sizes, including 60 m × 60 m, 120 m × 120 m, 180 m × 180 m, and 240 m × 240 m. We collected full-range airborne hyperspectral data with fine spatial resolution (1 m) and visible and near-infrared spaceborne hyperspectral data from DESIS sensor with coarse spatial resolution (30 m), and used the spectral diversity hypothesis—i.e., that the variability in spectral data is largely driven by plant diversity—to estimate α-diversity remotely. In recently-burned plots and those at the transitional stage, both airborne and spaceborne data were capable of capturing Simpson diversity—a metric that calculates the effective number of dominant species by emphasizing abundant species and discounting rare species—but not species richness or Shannon diversity. Further, neither airborne nor spaceborne hyperspectral data sets were capable of capturing plant α-diversity of 60 m × 60 m or 120 m × 120 m plots. Based on these results, three main findings emerged: (1) management practices influence grassland biodiversity patterns that can be remotely detected, (2) both fine- and coarse-resolution remotely-sensed data can detect the effective number of dominant species (e.g., Simpson diversity), and (3) attention should be given to site-specific plant diversity field data collection to appropriately interpret remote sensing results. Findings of this study indicate the feasibility of estimating Simpson diversity in naturally-assembled grasslands using forthcoming spaceborne imagers such as National Aeronautics and Space Administration's Surface Biology and Geology mission.

Hamed Gholizadeh↗
NASA NTRS2007

Iterative-Transform Phase Retrieval Using Adaptive Diversity

A phase-diverse iterative-transform phase-retrieval algorithm enables high spatial-frequency, high-dynamic-range, image-based wavefront sensing. [The terms phase-diverse, phase retrieval, image-based, and wavefront sensing are defined in the first of the two immediately preceding articles, Broadband Phase Retrieval for Image-Based Wavefront Sensing (GSC-14899-1).] As described below, no prior phase-retrieval algorithm has offered both high dynamic range and the capability to recover high spatial-frequency components. Each of the previously developed image-based phase-retrieval techniques can be classified into one of two categories: iterative transform or parametric. Among the modifications of the original iterative-transform approach has been the introduction of a defocus diversity function (also defined in the cited companion article). Modifications of the original parametric approach have included minimizing alternative objective functions as well as implementing a variety of nonlinear optimization methods. The iterative-transform approach offers the advantage of ability to recover low, middle, and high spatial frequencies, but has disadvantage of having a limited dynamic range to one wavelength or less. In contrast, parametric phase retrieval offers the advantage of high dynamic range, but is poorly suited for recovering higher spatial frequency aberrations. The present phase-diverse iterative transform phase-retrieval algorithm offers both the high-spatial-frequency capability of the iterative-transform approach and the high dynamic range of parametric phase-recovery techniques. In implementation, this is a focus-diverse iterative-transform phaseretrieval algorithm that incorporates an adaptive diversity function, which makes it possible to avoid phase unwrapping while preserving high-spatial-frequency recovery. The algorithm includes an inner and an outer loop (see figure). An initial estimate of phase is used to start the algorithm on the inner loop, wherein multiple intensity images are processed, each using a different defocus value. The processing is done by an iterative-transform method, yielding individual phase estimates corresponding to each image of the defocus-diversity data set. These individual phase estimates are combined in a weighted average to form a new phase estimate, which serves as the initial phase estimate for either the next iteration of the iterative-transform method or, if the maximum number of iterations has been reached, for the next several steps, which constitute the outerloop portion of the algorithm. The details of the next several steps must be omitted here for the sake of brevity. The overall effect of these steps is to adaptively update the diversity defocus values according to recovery of global defocus in the phase estimate. Aberration recovery varies with differing amounts as the amount of diversity defocus is updated in each image; thus, feedback is incorporated into the recovery process. This process is iterated until the global defocus error is driven to zero during the recovery process. The amplitude of aberration may far exceed one wavelength after completion of the inner-loop portion of the algorithm, and the classical iterative transform method does not, by itself, enable recovery of multi-wavelength aberrations. Hence, in the absence of a means of off-loading the multi-wavelength portion of the aberration, the algorithm would produce a wrapped phase map. However, a special aberration-fitting procedure can be applied to the wrapped phase data to transfer at least some portion of the multi-wavelength aberration to the diversity function, wherein the data are treated as known phase values. In this way, a multiwavelength aberration can be recovered incrementally by successively applying the aberration-fitting procedure to intermediate wrapped phase maps. During recovery, as more of the aberration is transferred to the diversity function following successive iterations around the ter loop, the estimated phase ceases to wrap in places where the aberration values become incorporated as part of the diversity function. As a result, as the aberration content is transferred to the diversity function, the phase estimate resembles that of a reference flat.

Dean, Bruce H.↗
DOE OSTI2025

Reduced soil diazotroph diversity decreases nitrogen fixation rates, but depends on land management

Soil diazotrophs convert atmospheric nitrogen into plant-available ammonium through free-living nitrogen fixation (FLNF). This sustainable nitrogen source can reduce our dependence on synthetic fertilizer inputs in conventional agricultural systems. However, we know little about the effect of diazotroph diversity on FLNF, especially given that FLNF is intermediate within the broad-narrow functional spectrum. Here, we determined how management-mediated shifts in diazotroph diversity would impact their ecosystem function (FLNF) by quantifying diazotroph diversity across a long-term management gradient during and after the growing season. In addition to field observations, we leveraged the same management gradient to manipulate diversity in soil microcosms via chloroform fumigation exposure. In the field, diazotroph diversity was significantly higher after the growing season, and the biologically-based annual cropping system harbored the highest diazotroph diversity. However, perennial cropping systems maintained the highest FLNF despite lower diazotroph diversity, and both soil moisture and temperature were stronger predictors of FLNF. Based on these results, integrating diverse perennial crops into agricultural landscape could result in greater N from FLNF, particularly at the end of the growing season. When we reduced biodiversity in a manipulation experiment, the diversity-FLNF association was stronger than in the field experiment, suggesting that FLNF communities are not as functionally redundant as taxonomically ‘broad’ ecosystem functions. Here, the strength of diversity-FLNF correlation varied by previous land management. Diazotroph diversity better predicted FLNF in annual and forest soil microcosms, and microbial biomass carbon better predicted FLNF in perennial soil microcosms. Taken together, our results show that while diazotroph diversity influences FLNF, especially under extreme environmental disturbances, abiotic factors like soil moisture and temperature are stronger constraints on FLNF in the field.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1988

Alpha, beta, or gamma: where does all the diversity go?

Global taxonomic richness is affected by variation in three components: within-community, or alpha, diversity, between-community, or beta, diversity; and between-region, or gamma, diversity. A data set consisting of 505 faunal lists distributed among 40 stratigraphic intervals and six environmental zones was used to investigate how variation of alpha and beta diversity influenced global diversity through the Paleozoic, and especially during the Ordovician radiations. As first shown by Bambach (1977), alpha diversity increased by 50 to 70 percent in offshore marine environments during the Ordovician and then remained essentially constant of the remainder of the Paleozoic. The increase is insufficient, however, to account for the 300 percent rise observed in global generic diversity. It is shown that beta diversity among level, soft-bottom communities also increased significantly during the early Paleozoic. This change is related to enhanced habitat selection, and presumably increased overall specialization, among diversifying taxa during the Ordovician radiations. Combined with alpha diversity, the measured change in beta diversity still accounts for only about half of the increase in global diversity. Other sources of increase are probably not related to variation in gamma diversity but rather to appearance and/or expansion of organic reefs, hardground communities, bryozoan thickets, and crinoid gardens during the Ordovician.

NASA Discipline Exobiology↗
DOE OSTI2023

Getting Technical: Introducing Students to Technical Concepts for Nuclear Science and Policy to Create and Encourage Diversity in the Nuclear Field

When discussing diversity, it is important to consider the many of the types of diversity: gender diversity, racial diversity, religious diversity, cultural diversity, and diversity in abilities. The nuclear field has recently seen a surge in the diversity within the entire industry, but there is still room for the industry to grow in those areas. Where does that begin? How does that develop? When is the right time to engage the next generation of nuclear professionals? What topics should be introduced to encourage and foster excitement in the nuclear field? These questions are all certainly important but narrowing in on the topics that should be introduced might prove to be a very effective way to grow excitement in and, then, diversity in the nuclear field. Students at all socioeconomic levels should be introduced to various technical concepts that correspond to the stage and level of education that is appropriate for those students. Oftentimes there may be a speaker at a school for certain ages that will provide an overview of the nuclear industry as a whole, or perhaps even specifics on what that person does, but rarely is the interaction carried on over a long period of time and rarely do presentations for these students introduce technical concepts. Creating new, effective volunteer programs in a wide range of schools in local areas where nuclear sciences are supported would allow professionals in the nuclear field to identify and focus on students whose aptitude might lean them towards future careers in the nuclear field. This paper will focus on potential, effective ways to start these programs, and it will identify a range of technical concepts that might be considered as age-appropriate or that can be molded to fit individual schools and would, in turn, begin to develop a diverse base of students to grow and enter the nuclear field.

Loftin, Bradley↗