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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Invasive Plants Rapidly Reshape Soil Properties in a Grassland Ecosystem

In this study, we show how invasive plant species drive rapid shifts in the soil environment from surrounding native communities. Each of the three plant invaders had different but consistent effects on soils. Thus, there does not appear to be a one-size-fits-all strategy for how plant invaders alter grassland soil environments. This work represents a crucial step toward understanding how invaders might be able to prevent or impair native reestablishment by changing soil biotic and abiotic properties. Plant invasions often reduce native plant diversity and increase net primary productivity. Invaded soils appear to differ from surrounding soils in ways that impede restoration of diverse native plant communities. We hypothesize that invader-mediated shifts in edaphic properties reproducibly alter soil microbial community structure and function. Here, we take a holistic approach, characterizing plant, prokaryotic, and fungal communities and soil physicochemical properties in field sites, invasion gradients, and experimental plots for three invasive plant species that cooccur in the Rocky Mountain West. Each invader had a unique impact on soil physicochemical properties. We found that invasions drove shifts in the abundances of specific microbial taxa, while overall belowground community structure and functional potential were fairly constant. Forb invaders were generally enriched in copiotrophic bacteria with higher 16S rRNA gene copy numbers and showed greater microbial carbohydrate and nitrogen metabolic potential. Older invasions had stronger effects on abiotic soil properties, indicative of multiyear successions. Overall, we show that plant invasions are idiosyncratic in their impact on soils and are directly responsible for driving reproducible shifts in the soil environment over multiyear time scales. IMPORTANCE In this study, we show how invasive plant species drive rapid shifts in the soil environment from surrounding native communities. Each of the three plant invaders had different but consistent effects on soils. Thus, there does not appear to be a one-size-fits-all strategy for how plant invaders alter grassland soil environments. This work represents a crucial step toward understanding how invaders might be able to prevent or impair native reestablishment by changing soil biotic and abiotic properties.

Microbiology↗
DOE OSTI2018

Machine Learning Reveals Missing Edges and Putative Interaction Mechanisms in Microbial Ecosystem Networks

Different organisms in a microbial community may drastically affect each other’s growth phenotypes, significantly affecting the community dynamics, with important implications for human and environmental health. Novel culturing methods and the decreasing costs of sequencing will gradually enable high-throughput measurements of pairwise interactions in systematic coculturing studies. However, a thorough characterization of all interactions that occur within a microbial community is greatly limited both by the combinatorial complexity of possible assortments and by the limited biological insight that interaction measurements typically provide without laborious specific follow-ups. Here, we show how a simple and flexible formal representation of microbial pairs can be used for the classification of interactions via machine learning. The approach we propose predicts with high accuracy the outcome of yet-to-be performed experiments and generates testable hypotheses about the mechanisms of specific interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Quantitative Stable-Isotope Probing (qSIP) with Metagenomics Links Microbial Physiology and Activity to Soil Moisture in Mediterranean-Climate Grassland Ecosystems

The growth and physiology of soil microorganisms, which play vital roles in biogeochemical cycling, are shaped by both current and historical soil environmental conditions. Here, we developed and applied a genome-resolved metagenomic implementation of quantitative stable isotope probing (qSIP) with an H 2 18 O labeling experiment to identify actively growing soil microorganisms and their genomic capacities. qSIP enabled measurement of taxon-specific growth because isotopic incorporation into microbial DNA requires production of new genome copies. We studied three Mediterranean grassland soils across a rainfall gradient to evaluate the hypothesis that historic precipitation levels are an important factor controlling trait selection. We used qSIP-informed genome-resolved metagenomics to resolve the active subset of soil community members and identify their characteristic ecophysiological traits. Higher year-round precipitation levels correlated with higher activity and growth rates of flagellar motile microorganisms. In addition to heavily isotopically labeled bacteria, we identified abundant isotope-labeled phages, suggesting phage-induced cell lysis likely contributed to necromass production at all three sites. Further, there was a positive correlation between phage activity and the activity of putative phage hosts. Contrary to our expectations, the capacity to decompose the diverse complex carbohydrates common in soil organic matter or oxidize methanol and carbon monoxide were broadly distributed across active and inactive bacteria in all three soils, implying that these traits are not highly selected for by historical precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Genomic fingerprints of the world’s soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Diverging drivers of fungal diversity: seasonal effects shape aboveground communities, while geographical patterns govern belowground communities in rubber tree ecosystems

Understanding the spatiotemporal dynamics of microbial communities is essential for predicting their ecological roles and interactions with host plants. In a recent study, Wei and colleagues (Microbiol Spectr 13:e02097-24, 2024) investigated fungal diversity across multiple plant and soil compartments in rubber trees over two seasons and two geographically distinct regions in China. Their findings revealed that alpha diversity was primarily influenced by seasonal changes and physicochemical factors, while beta diversity exhibited a strong geographical pattern, shaped by leaf phosphorus and soil available potassium. These results highlight the role of environmental drivers in shaping within-community diversity, while other factors contribute to the differences between fungal communities across the soil–plant continuum. By distinguishing the effects of temporal and spatial factors, this study provides detailed insights into plant-associated microbiomes and emphasizes the need for further research on the functional implications of microbial diversity in the context of changing environmental and agricultural conditions.

fungal diversity↗
DOE OSTI2017

Millions of targets under attack: a macroscopic characterization of the DoS ecosystem

Denial-of-Service attacks have rapidly increased in terms of frequency and intensity, steadily becoming one of the biggest threats to Internet stability and reliability. However, a rigorous comprehensive characterization of this phenomenon, and of countermeasures to mitigate the associated risks, faces many infrastructure and analytic challenges. We make progress toward this goal, by introducing and applying a new framework to enable a macroscopic characterization of attacks, attack targets, and DDoS Protection Services (DPSs). Our analysis leverages data from four independent global Internet measurement infrastructures over the last two years: backscatter traffic to a large network telescope; logs from amplification honeypots; a DNS measurement platform covering 60% of the current namespace; and a DNS-based data set focusing on DPS adoption. Our results reveal the massive scale of the DoS problem, including an eye-opening statistic that one-third of all / 24 networks recently estimated to be active on the Internet have suffered at least one DoS attack over the last two years. We also discovered that often targets are simultaneously hit by different types of attacks. In our data, Web servers were the most prominent attack target; an average of 3% of the Web sites in .com, .net, and .org were involved with attacks, daily. Finally, we shed light on factors influencing migration to a DPS.

Jonker, Mattijs↗
DOE OSTI2025

FAIR Ecosystems for Science at Scale

High Performance Computing (HPC) centers provide resources to users who require greater scale to “get science done”. They deploy infrastructure with singular hardware architectures, cutting-edge software environments, and stricter security measures as compared with users’ own resources. As a result, users often create and configure digital artifacts in ways that are specialized for the unique infrastructure at a given HPC center. Each user of that center will face similar challenges as they develop specialized solutions to take full advantages of the center’s resources, potentially resulting in significant duplication of effort. Much duplicated effort could be avoided, however, if users of these centers found it easier to discover others’ solutions and artifacts as well as share their own. The FAIR principles address this problem by presenting guidelines focused around metadata practices to be implemented by vaguely defined “communities”; in practice, these tend to gather by domain (e.g. bioinformatics, geosciences, agriculture). Domain-based communities can unfortunately end up functioning as silos that tend both to inhibit sharing of solutions and best practices as well as to encourage fragile and unsustainable improvised solutions in the absence of best-practice guidance. We propose that these communities pursuing “science at scale” be nurtured both individually and collectively by HPC centers so that users can take advantage of shared challenges across disciplines and potentially across HPC centers. We describe an architecture based on the EOSC-Life FAIR Workflows Collaboratory, specialized for use with and inside HPC centers such as the Oak Ridge Leadership Computing Facility (OLCF), and we speculate on user incentives to encourage adoption. We note that a focus on FAIR workflow components rather than FAIR workflows is more likely to benefit the users of HPC centers.

Wilkinson, Sean [ORNL] (ORCID:0000000214437479)↗
DOE OSTI2026

The LCLStream Ecosystem for Multi-Institutional Dataset Exploration

We describe a new end-to-end experimental data streaming framework designed from the ground up to support new types of applications – AI training, extremely high-rate X-ray time-of-flight analysis, crystal structure determination with distributed processing, and custom data science applications and visualizers yet to be created. Throughout, we use design choices merging cloud microservices with traditional HPC batch execution models for security and flexibility. This project makes a unique contribution to the DOE Integrated Research Infrastructure (IRI) landscape. By creating a flexible, API-driven data request service, we address a significant need for high-speed data streaming sources for the X-ray science data analysis community. With the combination of data request API, mutual authentication web security framework, job queue system, high-rate data buffer, and complementary nature to facility infrastructure, the LCLStreamer framework has prototyped and implemented several new paradigms critical for future generation experiments.

Rogers, David [ORNL] (ORCID:0000000251871768)↗
DOE OSTI2022

Framework For Optimization Of Resources And Economics Ecosystem

The Framework for Optimization of ResourCes and Economics is a collection of software tools, models, and datasets acquired and developed under the Integrated Energy Systems (IES) program to enable analysis of technical and economic viability of myriad IES configurations. FORCE is the consolidating interface and data repository for all the IES toolsets ranging from macro technoeconomic analysis to transient process modeling and experimental validation for integrated energy systems.

Frick, KonorL↗
DOE OSTI2023

Multiscale Ecosystem for solving Maxwell-Schrodinger equations of open quantum systems (OpenMS)

Light-matter interactions play an important role in many branches of physics, chemistry, energy, and materials science. In the strong coupling regime, light-matter interactions are able to tune the materials properties via the formation of new quasiparticles, such as plasmons and polaritons. However, theoretical and numerical modeling of the light-matter interaction-mediated processes remain a big challenge because light-matter interactions are fundamentally multiscale and multiphysics problems involving multiple interactions between electrons, nuclei, and photons at different time/length scales. In the current community, light-matter interactions were treated at different levels of theoretical complexity in quantum chemistry and quantum optics. In quantum optics or quantum photonics, the matter is usually simplified as a few-level system, and the light is treated quantum-mechanically. On the other hand, quantum chemistry explores first-principles methods, including both single-particle and many-body-based techniques, to describe the electronic properties of matter in detail. However, light is usually prescribed as a classical electromagnetic field, and the light-matter interaction is taken into account as an external potential via classical approximations. This software is designed to fill current modeling shortcomings by delivering a first-ever scalable multiscale platform for simulating light-matter interactions in realistic electromagnetic environments. The software solves Maxwell and Schrodinger equations self-consistent on the heterogeneous platforms. It implements HF/DFT, TDDFT, and coupled-cluster counterparts for light-matter interactions and adopts modular programming to offload massively parallel algorithms on a large number of CPU/GPUs.

Zhang, Yu↗
DOE OSTI2022

LungMAP Portal Ecosystem: Systems-level Exploration of the Lung

An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging, and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a new gateway portal. This portal connects a broad spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development, and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease, and drug treatment. These atlases are provided as independent and integrated queryable datasets, with an emphasis on dynamic visualization, figure generation, re-analysis, cell-type curation, and automated reference-based classification of user-provided single-cell genomics datasets (Azimuth). Finally, as this resource grows, we intend to increase the breadth of available interactive interfaces, supported data types, data portals and datasets from LungMAP and external research efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model

Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated here using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportant forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Biogeography of the ecosystems of the healthy human body

Characterizing the biogeography of the microbiome of healthy humans is essential for understanding microbial associated diseases. Previous studies mainly focused on a single body habitat from a limited set of subjects. Here, we analyzed one of the largest microbiome datasets to date and generated a biogeographical map that annotates the biodiversity, spatial relationships, and temporal stability of 22 habitats from 279 healthy humans. We identified 929 genera from more than 24 million 16S rRNA gene sequences of 22 habitats, and we provide a baseline of inter-subject variation for healthy adults. The oral habitat has the most stable microbiota with the highest alpha diversity, while the skin and vaginal microbiota are less stable and show lower alpha diversity. The level of biodiversity in one habitat is independent of the biodiversity of other habitats in the same individual. The abundances of a given genus at a body site in which it dominates do not correlate with the abundances at body sites where it is not dominant. Additionally, we observed the human microbiota exhibit both cosmopolitan and endemic features. Finally, comparing datasets of different projects revealed a project-based clustering pattern, emphasizing the significance of standardization of metagenomic studies. The data presented here extend the definition of the human microbiome by providing a more complete and accurate picture of human microbiome biogeography, addressing questions best answered by a large dataset of subjects and body sites that are deeply sampled by sequencing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Terrestrial Subsurface Ecosystem

The Earth’s crust is a solid cool layer that overlays the mantle, with a varying thickness of between 30-50 km on continental plates, and 5-10 km on oceanic plates. Continental crust is composed of a variety of igneous, metamorphic, and sedimentary rocks that weather and re-form over geologic cycles lasting millions to billions of years. At the crust surface, these weathered minerals and organic material combine to produce a variety of soils types that provide suitable habitats and niches for abundant microbial diversity (see Chapter 4). Beneath this soil zone is the subsurface. Once thought to be relatively free of microorganisms, recent estimates have calculated that between 1016-1017 g C biomass (2-19% of Earth’s total biomass) may be present in this environment (Whitman et al., 1998;McMahon and Parnell, 2014). Microbial life in the subsurface exists across a wide range of habitats: in pores associated with relatively shallow unconsolidated aquifer sediments to fractures in bedrock formations that are more than a kilometer deep, where extreme lithostatic pressures and temperatures are encountered. While these different environments contain varying physical and chemical conditions, the absence of light is a constant. Despite this, diverse physiologies and metabolisms enable microorganisms to harness energy and carbon for growth in water-filled pore spaces and fractures. Carbon and other element cycles are driven by microbial activity, which has implications for both natural processes and human activities in the subsurface, e.g., bacteria play key roles in both hydrocarbon formation and degradation. Hydrocarbons are a major focus for human utilization of the subsurface, via oil and gas extraction and potential geologic CO2 sequestration. The subsurface is also utilized or being considered for sequestered storage of high-level radioactive waste from nuclear power generation and residual waste from past production of weapons grade nuclear materials. While our understanding of the subsurface is continually improving, it is clear that only a small fraction of microbial habitats have been sampled and studied. In this chapter, we will discuss these studies in the context of the distribution of microbial life in the subsurface, the stresses that microorganisms must overcome to survive in these environments, and the metabolic strategies that are employed to harness energy in a region of the planet far-removed from sunlight. Finally, we will consider both beneficial and deleterious effects of microbial activity in the subsurface on human activities in this environment.

Wilkins, Michael J.↗
DOE OSTI2015

Can the Results of Biodiversity-Ecosystem Productivity Studies Be Translated to Bioenergy Production?

Biodiversity experiments show that increases in plant diversity can lead to greater biomass production, and some researchers suggest that high diversity plantings should be used for bioenergy production. However, many methods used in past biodiversity experiments are impractical for bioenergy plantings. For example, biodiversity experiments often use intensive management such as hand weeding to maintain low diversity plantings and exclude unplanted species, but this would not be done for bioenergy plantings. Also, biodiversity experiments generally use high seeding densities that would be too expensive for bioenergy plantings. Here we report the effects of biodiversity on biomass production from two studies of more realistic bioenergy crop plantings in southern Michigan, USA. One study involved comparing production between switchgrass (Panicum virgatum) monocultures and species-rich prairie plantings on private farm fields that were managed similarly to bioenergy plantings. The other study was an experiment where switchgrass was planted in monoculture and in combination with increasingly species-rich native prairie mixtures. Overall, we found that bioenergy plantings with higher species richness did not produce more biomass than switchgrass monocultures. The lack of a positive relationship between planted species richness and production in our studies may be due to several factors. Non-planted species (weeds) were not removed from our studies and these non-planted species may have competed with planted species and also prevented realized species richness from equaling planted species richness. Also, we found that low seeding density of individual species limited the biomass production of these individual species. Finally, production in future bioenergy plantings with high species richness may be increased by using a high density of inexpensive seed from switchgrass and other highly productive species, and future efforts to translate the results of biodiversity experiments to bioenergy plantings should consider the role of seeding density.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Higher Trophic Levels Overwhelm Climate Change Impacts on Terrestrial Ecosystem Functioning

Forest floor food webs play pivotal roles in carbon cycling, but they are rarely considered in models of carbon fluxes, including soil carbon dioxide emissions (respiration), under climatic warming. The indirect effects of invertebrates on heterotrophic (microbial and invertebrate) respiration through interactions with microbial communities are significant and will be altered by warming. However, the interactive effects of invertebrates and warming on heterotrophic respiration in the field are poorly understood. In this study we combined field and common garden laboratory approaches to examine relationships between warming, forest floor food web structure, and heterotrophic respiration. We found that soil animals can overwhelm the effects of warming (to 5 degrees Celsius above ambient) on heterotrophic respiration. In particular, the presence of higher trophic levels and burrowing detritivores strongly determined heterotrophic respiration rates in temperate forest soils. These effects were, however, context-dependent, with greater effects in a lower-latitude site. Without isolating and including the significant impact of invertebrates, climate models will be incomplete, hindering well-informed policy decisions.

59 BASIC BIOLOGICAL SCIENCES↗