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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Plant responses to rising vapor pressure deficit

Recent decades have been characterized by increasing temperatures worldwide, resulting in an exponential climb in vapor pressure de?cit (VPD). VPD has been identi?ed as an increasingly important driver of plant functioning in terrestrial biomes and has been established as a major contributor in recent drought-induced plant mortality independent of other drivers associated with climate change. Despite this, few studies have isolated the physiological response of plant functioning to high VPD, thus limiting our understanding and ability to predict future impacts on terrestrial ecosystems. An abundance of evidence suggests that stomatal conductance declines under high VPD and transpiration increases in most species up until a given VPD threshold, leading to a cascade of subsequent impacts including reduced photosynthesis and growth, and higher risks of carbon starvation and hydraulic failure. Incorporation of photosynthetic and hydraulic traits in ‘next-generation’ land-surface models has the greatest potential for improved prediction of VPD responses at the plant- and global-scale, and will yield more mechanistic simulations of plant responses to a changing climate. By providing a fully integrated framework and evaluation of the impacts of high VPD on plant function, improvements in forecasting and long-term projections of clNovickimate impacts can be made.

Grossiord, Charlotte↗
DOE OSTI2025

Proximal remote sensing: an essential tool for bridging the gap between high‐resolution ecosystem monitoring and global ecology

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Plant Sciences↗
DOE OSTI2023

Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System

Seasonal variability of the global hydrologic cycle directly impacts human activities, including hazard assessment and mitigation, agricultural decisions, and water resources management. This is particularly true across the High Mountain Asia (HMA) region, where availability of water resources can change depending on local seasonality of the hydrologic cycle. Forecasting the atmospheric states and surface conditions, including hydrometeorologically relevant variables, at subseasonal-to-seasonal (S2S) lead times of weeks to months is an area of active research and development. NASA's Goddard Earth Observing System (GEOS) S2S prediction system has been developed with this research goal in mind. Here, we benchmark the forecast skill of GEOS-S2S (version 2) hydrometeorological forecasts at 1–3-month lead times in the HMA region, including a portion of the Indian subcontinent, during the retrospective forecast period, 1981–2016. To assess forecast skill, we evaluate 2 m air temperature, total precipitation, fractional snow cover, snow water equivalent, surface soil moisture, and terrestrial water storage forecasts against the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and independent reanalysis data, satellite observations, and data fusion products. Anomaly correlation is highest when the forecasts are evaluated against MERRA-2 and particularly in variables with long memory in the climate system, likely due to the similar initial conditions and model architecture used in GEOS-S2S and MERRA-2. When compared to MERRA-2, results for the 1-month forecast skill range from an anomaly correlation of R anom =0.18 for precipitation to R anom =0.62 for soil moisture. Anomaly correlations are consistently lower when forecasts are evaluated against independent observations; results for the 1-month forecast skill range from R anom =0.13 for snow water equivalent to R anom =0.24 for fractional snow cover. We find that, generally, hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system's ability to forecast HMA hydrometeorology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Modeling Aerial Gamma-Ray Backgrounds Using Non-negative Matrix Factorization

Airborne gamma-ray surveys are useful for many applications, ranging from geology and mining to public health and nuclear security. In all these contexts, the ability to decompose a measured spectrum into a linear combination of background source terms can provide useful insights into the data and lead to improvements in the techniques that use spectral energy windows. Multiple methods for the linear decomposition of spectra exist but are subject to various drawbacks, such as allowing negative photon fluxes or requiring detailed Monte Carlo modeling. In this work, we propose using non-negative matrix factorization (NMF) as a data-driven approach to spectral decomposition. Using aerial surveys that include flights over water, we demonstrate that the mathematical approach of NMF finds physically relevant structure in the aerial gamma-ray background, namely, that measured spectra can be expressed as the sum of nearby terrestrial emission, distant terrestrial emission, and radon and cosmic emission. Furthermore, these NMF background components are compared with the background components obtained by noise-adjusted singular value decomposition (NASVD), which contain negative photon fluxes and, thus, do not represent the emission spectra in as straightforward a way. Finally, we comment on the potential areas of research that are enabled by NMF decompositions, such as new approaches to spectral anomaly detection and data fusion.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Impact of the nuclear equation of state on the formation of twin stars

Twin stars-two stable neutron stars (NSs) with the same mass but different radii have long been proposed to appear as a consequence of a possible first-order phase transition in NS matter. Within a meta-model for the EOS of hybrid stars, we revisit the viability of twin stars and its dependence on numerous parameters characterizing the EOS of nuclear matter, quark matter, and the phase transition between them. While essentially no experimental constraint exists for the last two, parameters characterizing the EOS of neutron-rich nucleonic matter have been constrained within various ranges by terrestrial experiments and astrophysical observations. Within these ranges, the impact of nuclear EOS and crust-core transition density on the formation of twin stars is studied. Here, it is found that the symmetry energy of neutron-rich nucleonic matter notably influences the formation of twin stars, particularly through its slope L and curvature K sym . Conversely, varying the EOS of symmetric nuclear matter within their currently known uncertainty ranges shows minimal influence on the formation of twin stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Shock equation of state experiments in MgO up to 1.5 TPa and the effects of optical depth on temperature determination

Laser-driven shock compression enables an experimental study of phase transitions at unprecedented pressures and temperatures. One example is the shock Hugoniot of magnesium oxide (MgO), which crosses the B1–B2-liquid triple point at 400–600 GPa, 10 000–13 000 K (0.86–1.12 eV). MgO is a major component within the mantles of terrestrial planets and has long been a focus of high-pressure research. Here, we combine time-resolved velocimetry and pyrometry measurements with a decaying shock platform to obtain pressure–temperature data on MgO from 300 to 1500 GPa and 9000 to 50 000 K. Pressure–temperature–density Hugoniot data are reported at 1500 GPa. These data represent the near-instantaneous response of an MgO [100] single crystal to shock compression. We report on a prominent temperature anomaly between 400 and 460 GPa, in general agreement with previous shock studies, and draw comparison with equation-of-state models. We provide a detailed analysis of the decaying shock compression platform, including a treatment of a pressure-dependent optical depth near the shock front. We show that if the optical depth of the shocked material is larger than 1 μm, treating the shock front as an optically thick gray body will lead to a noticeable overestimation of the shock temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Spatial Study 2022: Water Column, Sediment, and Total Ecosystem Respiration Rates across the Yakima River Basin, Washington, USA (v2)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin and is associated with the manuscript “Sediment-associated processes account for most of the spatial variation in ecosystem respiration in the Yakima River basin” submitted to Nature Communications Earth & Environment (Garayburu-Caruso et al., in review). The dataset provides ecosystem metabolism estimates generated from streamMetabolizer (Appling et al.; 2018) using data collected during the same five-week period at 48 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. Additionally, it includes the scripts used for the analysis and producing the figures in the manuscript. The contents include streamMetabolizer inputs and outputs and additional relevant data needed to generate the main manuscript results. The data included are: total ecosystem respiration, water respiration, calculated sediment-associated respiration, gross primary production outputs from the river corridor model for the Yakima River Basin, median grain size (d50), depth, dissolved oxygen, water temperature, pressure, and annual oxygen consumption. The associated GitHub repository can be found at https://github.com/river-corridors-sfa/SSS_metabolism. Samples collected during this study were labeled as “Second Spatial Study” or “SSS.” Raw time series sensor data, total suspended solids, and depth data from SSS were published at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1969566. A subset of data from the SSS samples were published in the contiguous United States (CONUS)-Scale Model-Sample (CM) study data package available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689 that presents data from across the CONUS. They include dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), total nitrogen (TN), grain size, aerobic sediment respiration, dissolved oxygen (DO), and temperature. Parent IDs and Site IDs are consistent between the SSS and CM data packages, and they can be mapped directly so data across packages can be used together. Field metadata for the samples in this da This dataset is comprised of one main data folder with four subfolders. The main data folder contains of (1) file-level metadata; (2) data dictionary; (3) total/water column/sediment respiration; (4) gross primary production (GPP); (5) median grain size (d50); and (6) annual oxygen consumption. The “Figures” subfolder contains the figures used in the paper and all intermediate files (including geospatial files). The “Published_Data” contains a readme directing the user to download the public data to reproduce analyses and figures. The “Scripts” folder contains all scripts used in the analyses that were not part of running StreamMetabolizer. Lastly, the “Stream_Metabolizer” folder contains all files associated with running StreamMetabolizer including (1) model input files, (2) model output files, (3) processing scripts, (4) histogram plots of the outputs, and (5) an R project. All files are .csv, .pdf, .R, .Rmd, .Rproj, .html, .png, .txt, .qgz, .cpg, .dbf, .prj, .shp, .shp.ea.iso.xml, .shp.iso.xml, .shx, .sbn. ta package can be found at either link. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Microbes and Climate Change: a Research Prospectus for the Future

Climate change is the most serious challenge facing humanity. Microbes produce and consume three major greenhouse gases—carbon dioxide, methane, and nitrous oxide—and some microbes cause human, animal, and plant diseases that can be exacerbated by climate change. Hence, microbial research is needed to help ameliorate the warming trajectory and cascading effects resulting from heat, drought, and severe storms. We present a brief summary of what is known about microbial responses to climate change in three major ecosystems: terrestrial, ocean, and urban. We also offer suggestions for new research directions to reduce microbial greenhouse gases and mitigate the pathogenic impacts of microbes. These include performing more controlled studies on the climate impact on microbial processes, system interdependencies, and responses to human interventions, using microbes and their carbon and nitrogen transformations for useful stable products, improving microbial process data for climate models, and taking the One Health approach to study microbes and climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Direct astrophysical tests of chiral effective field theory at supranuclear densities

Recent observations of neutron stars with gravitational waves and X-ray timing provide unprecedented access to the equation of state (EoS) of cold dense matter at densities difficult to realize in terrestrial experiments. At the same time, predictions for the EoS equipped with reliable uncertainty estimates from chiral effective field theory ( x EFT) allow us to bound our theoretical ignorance. In this work, we analyze astrophysical data using a nonparametric representation of the neutron-star EoS conditioned on x EFT to directly constrain the underlying physical properties of the compact objects without introducing modeling systematics. We discuss how the data alone constrain the EoS at high densities when we condition on x EFT at low densities. Here, we also demonstrate how to exploit astrophysical data to directly test the predictions of x EFT for the EoS up to twice nuclear saturation density, in order to estimate the density at which these predictions might break down. We nd that the existence of massive pulsars, gravitational waves from GW170817, and NICER observations of PSR J0030+0451 favor x EFT predictions for the EoS up to nuclear saturation density over a more agnostic analysis by as much as a factor of 7 for the quantum Monte Carlo (QMC) calculations used in this work. While x EFT predictions using QMC are fully consistent with gravitational-wave data up to twice nuclear saturation density, NICER observations suggest that the EoS stiffens relative to these predictions at or slightly above nuclear saturation density. Additionally, for these QMC calculations, we marginalize over the uncertainty in the density at which x EFT begins to break down, constraining the radius of a 1.4M $\bigodot$ neutron star to R 1.4 = $11.40^{+1.38}_{–1.04}$ ($12.54^{+0.71}_{–0.63}$) km and the pressure at twice nuclear saturation density to p(2n sat ) = $14.2^{+18.1}_{–8.4}$ ($28.7^{+15.3}_{–15.0}$) MeV=fm 3 with massive pulsar and gravitational-wave (and NICER) data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Predictive Modeling and Operational Monitoring of Starlink Leo Satellite Network Performance in Maritime Environments

This thesis investigates short-term performance prediction for maritime LEO operational planning and application performance cannot anticipate available bandwidth or communication delay, which complicates variation alter signal conditions over short time scales. As a result, maritime users often fluctuations in link quality. In addition, Frequent satellite handoffs and Doppler-induced rapid satellite movement and changing atmospheric conditions cause substantial unavailable. Despite their availability, reliable operation at sea remains difficult because broadband connectivity in maritime regions where terrestrial infrastructure in

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The Brachiopod δ 11 B Record Across the Carboniferous-Permian Climate Transition

In this work, we present the δ 11 B of well-preserved brachiopod fossils coupled with geochemical modeling to examine how seawater boron responded to abrupt and dynamic climate changes in the Late Paleozoic. The Late Carboniferous, a time of major coal formation and glacioeustatic sea level changes, is characterized by relatively stable brachiopod δ11B of 15–17‰, similar to values seen in modern brachiopods. Brachiopod δ 11 B dropped by ~5‰ in the early Permian and then restabilized at a new value of 10‰ within a few million years. Mass balance models of seawater δ 11 B reproduced the overall trends in our brachiopod data but failed to capture the large drop in δ11B in the early Permian. Published seawater 87 Sr/ 86 Sr and δ 44 / 40 Ca data based on brachiopod shells also shift to lower values in the early Permian, suggesting a common control on all three seawater isotope systems. The Permian terrestrial record of evaporites and eolian deposits suggests a prolonged reduced delivery of dissolved weathering products to the ocean, accounting for the change in seawater 87 Sr/ 86 Sr. This reduced weathering, in turn, led to increased atmospheric CO 2 and lowered seawater pH, which may have significantly decreased major removal mechanisms for seawater calcium and boron leading to declines in both isotope systems. We propose that boron removal via coprecipitation in carbonates and adsorption onto clay minerals was significantly diminished due to a reduction in the availability of the borate aqueous species caused by lowered seawater pH.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tropical forests and global change: biogeochemical responses and opportunities for cross-site comparisons, an organized INSPIRE session at the 108th Annual Meeting, Ecological Society of America, Portland, Oregon, USA, August 2023

In this study, tropical forests play a critical role in the global carbon (C) cycle. These ecosystems maintain the highest rates of net primary production (NPP) on Earth, contain c. 30% of terrestrial C stocks, and have some of the largest stores of fine-root biomass globally, as well as higher fine-root production and turnover rates compared with other biomes. Tropical forest responses to projected warming, altered rainfall regimes, and elevated CO 2 concentrations are likely to be different from other ecosystems because of their unique characteristics (Box 1), making targeted research and model development important for understanding tropical forest–climate feedbacks. There is now a critical mass of long-term global change field experiments and modeling efforts in tropical forests, yet thus far there has been little synthesis, cross-site comparison, or multi-site standardized experimentation among tropical forests to help us understand how these biomes are changing. An organized INSPIRE session at the 108th Annual Meeting of the Ecological Society of America set out to tackle just this. Speakers covered large-scale tropical forest field experiments and modeling efforts, with an emphasis on changes in ecosystem biogeochemistry under warming, drying, elevated atmospheric CO 2 , and changing nutrient status. In this Meeting report, we provide an overview of the large-scale global change experiments presented and highlight the main objectives and opportunities for tropical forest research that emerged, including cross-site comparisons and integration with ecosystem-scale models (Fig. 1).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Multilevel analysis between Physcomitrium patens and Mortierellaceae endophytes explores potential long‐standing interaction among land plants and fungi

SUMMARY The model moss species Physcomitrium patens has long been used for studying divergence of land plants spanning from bryophytes to angiosperms. In addition to its phylogenetic relationships, the limited number of differential tissues, and comparable morphology to the earliest embryophytes provide a system to represent basic plant architecture. Based on plant–fungal interactions today, it is hypothesized these kingdoms have a long‐standing relationship, predating plant terrestrialization. Mortierellaceae have origins diverging from other land fungi paralleling bryophyte divergence, are related to arbuscular mycorrhizal fungi but are free‐living, observed to interact with plants, and can be found in moss microbiomes globally. Due to their parallel origins, we assess here how two Mortierellaceae species, Linnemannia elongata and Benniella erionia , interact with P. patens in coculture. We also assess how Mollicute ‐related or Burkholderia ‐related endobacterial symbionts (MRE or BRE) of these fungi impact plant response. Coculture interactions are investigated through high‐throughput phenomics, microscopy, RNA‐sequencing, differential expression profiling, gene ontology enrichment, and comparisons among 99 other P. patens transcriptomic studies. Here we present new high‐throughput approaches for measuring P. patens growth, identify novel expression of over 800 genes that are not expressed on traditional agar media, identify subtle interactions between P. patens and Mortierellaceae, and observe changes to plant–fungal interactions dependent on whether MRE or BRE are present. Our study provides insights into how plants and fungal partners may have interacted based on their communications observed today as well as identifying L. elongata and B. erionia as modern fungal endophytes with P. patens .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Genomic selection in algae with biphasic lifecycles: A Saccharina latissima (sugar kelp) case study

Introduction Sugar kelp ( Saccharina latissima ) has a biphasic life cycle, allowing selection on both thediploid sporophytes (SPs) and haploid gametophytes (GPs). Methods We trained a genomic selection (GS) model from farm-tested SP phenotypic data and used a mixed-ploidy additive relationship matrix to predict GP breeding values. Topranked GPs were used to make crosses for further farm evaluation. The relationship matrix included 866 individuals: a) founder SPs sampled from the wild; b) progeny GPs from founders; c) Farm-tested SPs crossed from b); and d) progeny GPs from farm-tested SPs. The complete pedigree-based relationship matrix was estimated for all individuals. A subset of founder SPs ( n = 58) and GPs ( n = 276) were genotyped with Diversity Array Technology and whole genome sequencing, respectively. We evaluated GS prediction accuracy via cross validation for SPs tested on farm in 2019 and 2020 using a basic GBLUP model. We also estimated the general combining ability (GCA) and specific combining ability (SCA) variances of parental GPs. A total of 11 yield-related and morphology traits were evaluated. Results The cross validation accuracies for dry weight per meter ( r ranged from 0.16 to 0.35) and wet weight per meter ( r ranged 0.19 to 0.35) were comparable to GS accuracy for yield traits in terrestrial crops. For morphology traits, cross validation accuracy exceeded 0.18 in all scenarios except for blade thickness in the second year. Accuracy in a third validation year (2021) was 0.31 for dry weight per meter over a confirmation set of 87 individuals. Discussion Our findings indicate that progress can be made in sugar kelp breeding by using genomic selection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Degradation Science from Nanometers to Kilometers: A Pathway to Rapid Detection for Reliable Photovoltaics

Photovoltaics reliability for terrestrial applications has more than four decades of history and experience. International standards development has prevented many early life failures and must be continued in the future. Yet, as the module product development cycle is measured in mere months, additional investment in the fundamental degradation science and rapid detection should be developed. In this article, a brief strategy is provided addressing indoor accelerated, outdoor testing, and modeling efforts required to retain high reliability in the following decade.

14 SOLAR ENERGY↗
DOE OSTI2022

Quantifying the drivers of ecosystem fluxes and water potential across the soil-plant-atmosphere continuum in an arid woodland

Dryland ecosystems occupy a vast swath of the terrestrial land surface and exert a sizeable impact on the cycling of carbon and water globally. These biomes are characterized by tightly coupled carbon and water cycles that respond rapidly to transient pulses in water availability. However, there exist many mechanistic uncertainties regarding the environmental drivers of, and linkages between, plant and ecosystem processes. Thus, drylands are often poorly represented in many vegetation and land surface models. An enhanced understanding of dryland ecosystem function is limited by the lack of long-term, co-located, and frequent measurements of plant and ecosystem processes. At a piñon-juniper woodland in southeastern Utah, USA, we collected a continuous dataset of meteorological conditions, soil water potential from surface to bedrock, tree water potential, and ecosystem carbon and water fluxes from eddy covariance. We found that predawn and midday tree water potential and daily ecosystem fluxes were highly sensitive to fluctuations in soil water availability, particularly in shallower layers, and that daytime variability in atmospheric drivers only loosely controlled these processes. The strong connections between shallow soil water potential, tree water potential, and ecosystem fluxes occurred because of the dominant role of precipitation pulses in driving vegetation activity, as even small pulses of moisture stimulated shallow soil water potential, tree water potential, and evapotranspiration for between 1 and 2 weeks. Carbon fluxes (net ecosystem exchange and gross primary productivity) were sensitive to precipitation pulses for longer, up to 3 weeks. Our results highlight that improved monitoring and sensing of shallow soil moisture can greatly enhance our understanding of dryland ecosystem function. Here, a better mechanistic understanding of the impacts of precipitation pulses is also needed to improve vegetation modeling of dryland ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Drivers of stability and transience in composition-functioning links during serial propagation of litter-decomposing microbial communities

ABSTRACT Biotic factors that influence the temporal stability of microbial community functioning are an emerging research focus for the control of natural and engineered systems. The discovery of common features within community ensembles that differ in functional stability over time is a starting point to explore biotic factors. We serially propagated a suite of soil microbial communities through five generations of 28-day microcosm incubations to examine microbial community compositional and functional stability during plant litter decomposition. Using dissolved organic carbon (DOC) abundance as a target function, we hypothesized that microbial diversity, compositional stability, and associated changes in interactions would explain the relative stability of the ecosystem function between generations. Communities with initially high DOC abundance tended to converge towards a “low DOC” phenotype within two generations, but across all microcosms, functional stability between generations was highly variable. By splitting communities into two cohorts based on their relative DOC functional stability, we found that compositional shifts, diversity, and interaction network complexity were associated with the stability of DOC abundance between generations. Further, our results showed that legacy effects were important in determining compositional and functional outcomes, and we identified taxa associated with high DOC abundance. In the context of litter decomposition, achieving functionally stable communities is required to utilize soil microbiomes to increase DOC abundance and long-term terrestrial DOC sequestration as one solution to reduce atmospheric carbon dioxide concentrations. Identifying factors that stabilize function for a community of interest may improve the success of microbiome engineering applications. IMPORTANCE Microbial community functioning can be highly dynamic over time. Identifying and understanding biotic factors that control functional stability is of significant interest for natural and engineered communities alike. Using plant litter–decomposing communities as a model system, this study examined the stability of ecosystem function over time following repeated community transfers. By identifying microbial community features that are associated with stable ecosystem functions, microbial communities can be manipulated in ways that promote the consistency and reliability of the desired function, improving outcomes and increasing the utility of microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Vegetation Warming Experiment: 15N Uptake Experiment Water-Extractable Soil Nutrients, Utqiagvik (Barrow), Alaska, 2018

This dataset consists of measured water-extractable carbon and nutrients measured on soils collected from warming experiment enclosures and paired control plots. Harvest types include both natural abundance and enriched soils. Vegetation warming chambers (Zero Power) were deployed on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. These chambers (Figure 1) consistently elevated air temperatures by approximately 4°C using a self-venting system described by Lewin et al (2017). Five chambers were deployed from June 17, 2018 to September 24, 2018 on the BEO within a 1 km2 area centered on 71.275N, -156.641W. Each chamber was co-located with an ambient plot where temperatures were not manipulated on patches of tundra containing the target species Arctagrostis latifolia. An intensive field campaign in late July investigated the impact of warming had on A. latifolia biomass, chemistry, and uptake of 15N labeled ammonia that was injected into the surface soils for one week. Initial measurements were taken on July 21, 2018. Harvest occurred on July 27, 2018. Water-extractable nutrients in soils were measured in July following harvests of A. latifolia plants and underlying soils. Availability of ammonia, nitrate, and phosphate throughout the growing season was measured by extracting nutrients bound to anion and cation binding resins deployed from July through September. Environmental variables (thaw depth, surface soil temperatures, surface soil moisture) were measured. Leaf traits and root traits of A. latifolia were also measured. The data package includes one *.csv data file and one *.pdf user guide. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗