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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Virus diversity and activity is driven by snowmelt and host dynamics in a high-altitude watershed soil ecosystem

Background: Viruses impact nearly all organisms on Earth, including microbial communities and their associated biogeochemical processes. In soils, highly diverse viral communities have been identified, with a global distribution seemingly driven by multiple biotic and abiotic factors, especially soil temperature and moisture. However, our current understanding of the stability of soil viral communities across time and their response to strong seasonal changes in environmental parameters remains limited. Here, we investigated the diversity and activity of environmental soil DNA and RNA viruses, focusing especially on bacteriophages, across dynamics’ seasonal changes in a snow-dominated mountainous watershed by examining paired metagenomes and metatranscriptomes. Results: We identified a large number of DNA and RNA viruses taxonomically divergent from existing environmental viruses, including a significant proportion of fungal RNA viruses, and a large and unsuspected diversity of positive single-stranded RNA phages ( Leviviricetes ), highlighting the under-characterization of the global soil virosphere. Among these, we were able to distinguish subsets of active DNA and RNA phages that changed across seasons, consistent with a “seed-bank” viral community structure in which new phage activity, for example, replication and host lysis, is sequentially triggered by changes in environmental conditions. At the population level, we further identified virus-host dynamics matching two existing ecological models: “Kill-The-Winner” which proposes that lytic phages are actively infecting abundant bacteria, and “Piggyback-The-Persistent” which argues that when the host is growing slowly, it is more beneficial to remain in a dormant state. The former was associated with summer months of high and rapid microbial activity, and the latter with winter months of limited and slow host growth. Conclusion: Taken together, these results suggest that the high diversity of viruses in soils is likely associated with a broad range of host interaction types each adapted to specific host ecological strategies and environmental conditions. As our understanding of how environmental and host factors drive viral activity in soil ecosystems progresses, integrating these viral impacts in complex natural microbiome models will be key to accurately predict ecosystem biogeochemistry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Modeling and validating tritium transfer in a grassland ecosystem in response to {sup 3}H releases

In this paper a radioecological model (TOCATTA) for tritium transfer in a grassland ecosystem developed on an hourly time-step basis is proposed and compared with the first data set obtained in the vicinity of the AREVA-NC reprocessing plant of La Hague (France). The TOCATTA model aims at simulating dynamics of tritium transfer in agricultural soil and plant ecosystems exposed to time-varying HTO concentrations in air water vapour and possibly in irrigation and rain water. In the present study, gaseous releases of tritium from the AREVA NC nuclear reprocessing plant in normal operation can be intense and intermittent over a period of less than 24 hours. A first comparison of the model predictions with the field data has shown that TOCATTA should be improved in terms of kinetics of tritium transfer.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling

Dormancy is an essential strategy for microorganisms to cope with environmental stress. However, global ecosystem models typically ignore microbial dormancy, resulting in notable model uncertainties. To facilitate the consideration of dormancy in these large-scale models, we propose a new microbial physiology component that works for a wide range of substrate availabilities. This new model is based on microbial physiological states and the major parameters are the maximum specific growth and maintenance rates of active microbes and the ratio of dormant to active maintenance rates. A major improvement of our model over extant models is that it can explain the low active microbial fractions commonly observed in undisturbed soils. Our new model shows that the exponentially-increasing respiration from substrate-induced respiration experiments can only be used to determine the maximum specific growth rate and initial active microbial biomass, while the respiration data representing both exponentially-increasing and non-exponentially-increasing phases can robustly determine a range of key parameters including the initial total live biomass, initial active fraction, the maximum specific growth and maintenance rates, and the half-saturation constant. Our new model can be incorporated into existing ecosystem models to account for dormancy in microbially-driven processes and to provide improved estimates of microbial activities.

Wang, Gangsheng↗
DOE OSTI2016

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Files and scripts to support manuscript Shuman et al 2023 FATES-SPITFIRE ecosystem assembly across tropics

The dataset includes the parameter and domain files, relevant output files, and scripts to generate simulations and perform analysis with Jupyter notebooks that support the manuscript Shuman, JK et al 2023 “Dynamic ecosystem assembly and escaping the “fire-trap” in the tropics: Insights from FATES_15.0.0”. We have adapted the fire-behavior and effects module, SPITFIRE, for use with the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a size-structured vegetation demographic model. We test how climate, fire regime and fire-tolerance plant traits interact to determine the biogeography of tropical forests and grasslands. We assign different fire-tolerance strategies based on crown, leaf and bark characteristics, which are key observed fire-tolerance traits across woody plants. For these simulations, three types of vegetation compete for resources: a fire-vulnerable tree with thin bark, a vulnerable deep crown and fire-intolerant foliage; a fire-tolerant tree with thick bark, a thin crown and fire-tolerant foliage; and a fire-promoting C4 grass. We explore the model sensitivity to a critical parameter governing fuel moisture, and show that drier fuels promote increased burning, an expansion of area for grass and fire-tolerant trees and a reduction of area for fire-vulnerable trees. This conversion to lower biomass or grass areas with increased fuel drying results in increased fire burned area and its effects, which could fee back to local climate variables. Simulated size-based fire mortality for trees less than 20 cm in diameter and those with fire-vulnerable traits is higher than that for larger and/or fire-tolerant trees, in agreement with observations. Fire-disturbed forests demonstrate reasonable productivity and capture observed patterns of aboveground biomass in areas dominated by natural vegetation for the recent historical period, but have a large bias in less disturbed areas. Though the model predicts a greater extent of burned fraction than observed in areas with grass dominance, the resulting biogeography of fire-tolerant, thick-bark trees and fire-vulnerable, thin-bark trees corresponds to observations across the tropics. In areas with more than 2500 mm of precipitation, simulated fire frequency and burned area are low, with fire intensities below 150 kW m-1, consistent with observed understory fire behavior across the Amazon. Areas drier than this demonstrate fire intensities consistent with those measured in savannas and grasslands, with high values up to 4000 kW m-1. The results support a positive grass-fire feedback across the region, and suggest that forests which have existed without frequent burning may be vulnerable at higher fire intensities, which is of greater concern under intensifying climate and land use pressures. The ability of FATES to capture the connection between fire disturbance and plant fire-tolerance strategies in determining biogeography provides a useful tool for assessing the vulnerability and resilience of these critical carbon storage areas under changing conditions across the tropics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A data ecosystem to support machine learning in materials science

Facilitating the application of machine learning to materials science problems requires enhancing the data ecosystem to enable discovery and collection of data from many sources, automated dissemination of new data across the ecosystem, and the connecting of data with materialsspecific machine learning models. Here, we present two projects, the Materials Data Facility (MDF) and the Data and Learning Hub for Science (DLHub), that address these needs. We use examples to show how MDF and DLHub capabilities can be leveraged to link data with machine learning models and how users can access those capabilities through web and programmatic interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Business Models for Scaling Demand Flexibility Volume III – Stakeholder ecosystem management challenges, and lessons learned from U.S. programs

Load growth at the grid edge is driving increased attention to the distribution system and its ability to enable customer technology adoption in an affordable and timely manner. Key industry stakeholders, including electric utilities and regulators, can benefit from strategies to manage and balance customer needs with infrastructure investments, such as demand flexibility. This report focuses on demand flexibility—the ability to reduce, shift, shed, generate, or modulate loads in response to building and grid needs—to reduce the need for costly grid upgrades by deferring investment needs and increase system reliability by shifting electricity usage during periods of high risk. Specifically, we focus on the emerging characteristics of business models for demand flexibility as a framework to understand how demand flexibility programs generate value. In this report, we focus on demand flexibility program stakeholder ecosystem management strategies, which provide information on value delivery and describe how program implementers leverage partner capabilities and collaborate to deliver customer and grid benefits. This report discusses the role of stakeholder ecosystem management in demand flexibility programs, identifies existing challenges to effective stakeholder management, and describes lessons learned. This report is part of a series that includes reports on value propositions, customer relationship management strategies, and program life cycle.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Soil Carbon Accumulation and Nutrient Availability in Managed and Unmanaged Ecosystems of East Tennessee

In the last two decades, urban and suburban lands grew by 34% in the United States, with 16 to 20 million ha maintained under turfgrass systems. Side-by-side comparison of turfgrass systems with other managed and unmanaged ecosystems have not been comprehensively conducted in the climate transition zone of the United States, despite the environmental significance of land use changes. Our objective was to determine the relative effects of C 3 and C 4 turfgrasses on soil organic carbon (SOC) accumulation and nutrient availability, in comparison with managed row crop and unmanaged woodlot and grassland systems. Soil samples from depths of 0 to 5, 5 to 15, and 15 to 30 cm were collected during March 2017 at the University of Tennessee’s East Tennessee Research and Education Center from seven ecosystems: (i) corn ( Zea mays L.)–soybean ( Glycine max L.) rotation, (ii) continuous soybean, (iii) tall fescue ( Festuca arundinacea L.), (iv) Kentucky bluegrass ( Poa pratensis L.), (v) bermudagrass ( Cynodon dactylon L.), (vi) unmanaged grassland, and (vii) unmanaged woodlot. All turfgrass species were established in 2012 and were managed like low-input residential lawns. Within the 30-cm soil profile, turfgrass systems contained 4.2 kg m –2 SOC at the time of sampling, which was 33% more than croplands and 34% less than unmanaged systems, and the C 4 turfgrass system contained 2.3 kg m –2 SOC and 0.4 mg kg –1 inorganic N, which were 56 and 57% lower than C 3 systems, respectively. Here, the results from this study highlight that low-input lawns with suitable grass species can offer higher SOC stock and nutrient availability than conventional cropland systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Next-Generation Ecosystem Experiment Arctic Rainfall Simulator: a tool to understand the effects of changing rainfall patterns in the Arctic

Rainfall frequency and intensity are expected to increase in the Arctic, with potential detrimental impacts on permafrost, leading to enhanced thawing and carbon release to the atmosphere. However, there have been very few studies on the effect of discrete rain events on permafrost in the Arctic and sub-Arctic. Conducting controlled rainfall experiments within permafrost landscapes can provide an improved understanding of the effect of changing intensity, duration, and timing of rain events on permafrost tundra ecosystems. Here, we describe the design and implementation of the Next-Generation Ecosystem Experiment Arctic Rainfall Simulator (NARS), a variable intensity (4–82 mm/h) rainfall simulator that can be used to study the effects of rainfall on permafrost stability. The NARS design includes a 3D-printed 4 cm H-flume and uses an eTape resistivity sensor that was calibrated (R 2 = 0.9–0.96) to measure discharge from the system. NARS is designed to be lightweight, simple to construct, and can be easily deployed in remote locations. As a field validation of updated rainfall simulator design and modernized controls, NARS was tested on the Seward Peninsula, AK. Because of its portability, versatility in deployment, dimensions, and rainfall intensity, NARS represents a methodological innovation for researching the impacts of rainfall on permafrost environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

The Effects of Iron Complexing Ligands on the Long Term Ecosystem Response to Iron Enrichment of HNLC waters (Final Activity Report)

Substantial increases in the concentrations of the stronger of two Fe(III) complexing organic ligand classes measured during the mesoscale Fe enrichment studies IronEx II and SOIREE appeared to sharply curtailed Fe availability to diatoms and thus limited the efficiency of carbon sequestration to the deep. Detailed observations during IronEx II (equatorial Pacific Ocean) and SOIREE (Southern Ocean –Pacific sector) indicate that the diatoms began re-experiencing Fe stress even though dissolved Fe concentrations remained elevated in the patch. This surprising outcome likely is related to the observed increased concentrations of strong Fe(III)-complexing ligands in seawater. Preliminary findings from other studies indicate that diatoms may not readily obtain Fe from these chemical species whereas Fe bound by strong ligands appears to support growth of cyanobacteria and nanoflagellates. The difficulty in assessing the likelihood of these changes with in-situ mesoscale experiments is the extended monitoring period needed to capture the long-term trajectory of the carbon cycle. A more detailed understanding of Fe complexing ligand effects on long-term ecosystem structure and carbon cycling is essential to ascertain not only the effect of Fe enrichment on short-term carbon sequestration in the oceans, but also the potential effect of Fe enrichment in modifying ecosystem structure and trajectory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

The Oncor Geodatabase for the Columbia Estuary Ecosystem Restoration Program: Handbook of Data Reduction Procedures, Workbooks, and Exchange Templates

This Handbook of Data Reduction Procedures, Workbooks, and Exchange Templates is designed to support the Oncor geodatabase for the Columbia Estuary Ecosystem Restoration Program (CEERP). The following data categories are covered: water-surface elevation and temperature, sediment accretion rate, photo points, herbaceous wetland vegetation cover, tree plots and site summaries, fish catch and density, fish size, fish diet, fish prey, and Chinook salmon genetic stock identification. The handbook is intended for use by scientists collecting monitoring and research data for the CEERP. The ultimate goal of Oncor is to provide quality, easily accessible, geospatial data for synthesis and evaluation of the collective performance of CEERP ecosystem restoration actions at a program scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

The Oncor Geodatabase for the Columbia Estuary Ecosystem Restoration Program (Annual Report, 2012)

The study reported herein was conducted by researchers at the Pacific Northwest National Laboratory (PNNL) for the U.S. Army Corps of Engineers, Portland District (Corps). The purpose of the project is to develop a geospatial, web-accessible database (called Oncor) for action effectiveness and related data from monitoring and research efforts for the Columbia Estuary Ecosystem Restoration Program (CEERP). The intent is for the Oncor database to enable synthesis and evaluation, the results of which can then be applied in subsequent CEERP decision-making. This is the first annual report in what is expected to be a 3- to 4-year project, which commenced on February 14, 2012. This report covers project activities conducted from February 2012 through February 2013. The specific objectives and tasks for the 2012 study year were as enumerated here. 1) Coordination - Coordinate with CEERP funding agencies and regional stakeholders to finalize key analysis questions and database needs for research, monitoring, and evaluation (RME) and ecosystem restoration in the lower Columbia River and estuary (LCRE) within CEERP’s adaptive management framework. 2) Database Development - Develop and demonstrate a web-based proof-of-concept geospatial database management system and analysis system for CEERP. 3) Analysis and Synthesis - Draft the CEERP 2012 Strategy Report, 2012 Action Plan, and 2013 Synthesis and Evaluation Memorandum, and provide other analytical and programmatic support. Work products for Objective 3 were reported separately.

Coleman, Andre M.↗
DOE OSTI2015

Threshold responses to interacting global changes in a California grassland ecosystem

Building on the history and infrastructure of the Jasper Ridge Global Change Experiment, we conducted experiments to explore the potential for single and combined global changes to stimulate fundamental type changes in ecosystems that start the experiment as California annual grassland. Using a carefully orchestrated set of seedling introductions, followed by careful study and later removal, the grassland was poised to enable two major kinds of transitions that occur in real life and that have major implications for ecosystem structure, function, and services. These are transitions from grassland to shrubland/forest and grassland to thistle patch. The experiment took place in the context of 4 global change factors – warming, elevated CO 2 , N deposition, and increased precipitation – in a full-factorial array, present as all possible 1, 2, 3, and 4-factor combinations, with each combination replicated 8 times.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem (Mid-year report FY15 Q2)

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

An open source platform for multi-scale spatially distributed simulations of microbial ecosystems

The goal of this project was to develop a tool for facilitating simulation, validation and discovery of multiscale dynamical processes in microbial ecosystems. This led to the development of an open-source software platform for Computation Of Microbial Ecosystems in Time and Space (COMETS). COMETS performs spatially distributed time-dependent flux balance based simulations of microbial metabolism. Our plan involved building the software platform itself, calibrating and testing it through comparison with experimental data, and integrating simulations and experiments to address important open questions on the evolution and dynamics of cross-feeding interactions between microbial species.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) Science Plan

Cumulus convection is an important component in the atmospheric radiation budget and hydrologic cycle over the Southern Great Plains and over many regions of the world, particularly during the summertime growing season when intense turbulence induced by surface radiation couples the land surface to clouds. Current convective cloud parameterizations contain uncertainties resulting in part from insufficient coincident data that couples cloud macrophysical and microphysical properties to inhomogeneities in boundary layer and aerosol properties. The Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign is designed to provide a detailed set of measurements that are needed to obtain a more complete understanding of the life cycle of shallow clouds by coupling cloud macrophysical and microphysical properties to land surface properties, ecosystems, and aerosols. HI-SCALE consists of 2, 4-week intensive observational periods, one in the spring and the other in the late summer, to take advantage of different stages and distribution of “greenness” for various types of vegetation in the vicinity of the Atmospheric Radiation and Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) site as well as aerosol properties that vary during the growing season. Most of the proposed instrumentation will be deployed on the ARM Aerial Facility (AAF) Gulfstream 1 (G-1) aircraft, including those that measure atmospheric turbulence, cloud water content and drop size distributions, aerosol precursor gases, aerosol chemical composition and size distributions, and cloud condensation nuclei concentrations. Routine ARM aerosol measurements made at the surface will be supplemented with aerosol microphysical properties measurements. The G-1 aircraft will complete transects over the SGP Central Facility at multiple altitudes within the boundary layer, within clouds, and above clouds.

Fast, JD↗
DOE OSTI2015

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY15 Q4.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Cryptic Methane Emissions from Upland Forest Ecosystems

This exploratory research on Cryptic Methane Emissions from Upland Forest Ecosystems was motivated by evidence that upland ecosystems emit 36% as much methane to the atmosphere as global wetlands, yet we knew almost nothing about this source. The long-term objective was to refine Earth system models by quantifying methane emissions from upland forests, and elucidate the biogeochemical processes that govern upland methane emissions. The immediate objectives of the grant were to: (i) test the emerging paradigm that upland trees unexpectedly transpire methane, (ii) test the basic biogeochemical assumptions of an existing global model of upland methane emissions, and (iii) develop the suite of biogeochemical approaches that will be needed to advance research on upland methane emissions. We instrumented a temperate forest system in order to explore the processes that govern upland methane emissions. We demonstrated that methane is emitted from the stems of dominant tree species in temperate upland forests. Tree emissions occurred throughout the growing season, while soils adjacent to the trees consumed methane simultaneously, challenging the concept that forests are uniform sinks of methane. High frequency measurements revealed diurnal cycling in the rate of methane emissions, pointing to soils as the methane source and transpiration as the most likely pathway for methane transport. We propose the forests are smaller methane sinks than previously estimated due to stem emissions. Stem emissions may be particularly important in upland tropical forests characterized by high rainfall and transpiration, resolving differences between models and measurements. The methods we used can be effectively implemented in order to determine if the phenomenon is widespread.

54 ENVIRONMENTAL SCIENCES↗