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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

Wildfire‐Smoke Aerosols Lead to Increased Light Use Efficiency Among Agricultural and Restored Wetland Land Uses in California's Central Valley

Abstract There are few observational studies measuring the ecosystem‐scale productivity effects of changes in incident diffuse photosynthetically active radiation (PAR diffuse ), especially related to wildfire smoke. Climate change‐induced increases to the duration and intensity of fire conditions have made smoke a common occurrence across western North America, with largely unquantified ecosystem feedbacks. Under equivalent amounts of radiation, increased atmospheric particulate matter could lead to a boost in productivity as scattering redistributes photons throughout multilayer canopies. In this work, we leverage a meso‐network of eddy covariance measurement sites across a unique array of managed and restored C 3 and C 4 canopy types to understand how recent wildfire smoke affected ecosystem productivity during the summer of 2018, an especially smoky year in the agriculturally productive Central Valley. We find that diffuse PAR diffuse increased by more than a third compared to the previous growing season, while total PAR was only slightly diminished. These conditions caused nearly a doubling of light use efficiency over the range of diffuse fraction observed, with the highest sensitivity to diffuse fraction exhibited by corn and alfalfa crops. We utilized an empirical model to assess the trade‐off between enhanced diffuse fraction and reduced total PAR. Under mean radiation conditions, daily integrated gross ecosystem productivity increased by 1.2–4.2% compared to the previous growing season. Finally, we explore the potential negative effect of heightened ozone, a copollutant often associated with wildfire. In addition to the effects of wildfire smoke, the results of this natural experiment can help validate future predictions of aerosol‐productivity feedbacks.

Hemes, Kyle S.↗
DOE OSTI2020

Iron Speciation in PM 2.5 From Urban, Agriculture, and Mixed Environments in Colorado, USA

Atmospheric iron solubility varies depending on whether the particles are collected in rural or urban areas, with urban areas showing increased iron solubility. In this study, we investigate if the iron species present in different environments affects its ultimate solubility. Field data are presented from the Platte River Air Pollution and Photochemistry Experiment (PRAPPE), aimed at understanding the interactions between organic carbon and trace elements in atmospheric particulate matter (PM). 24-hr PM 2.5 samples were collected during the summer and winter (2016–2017), at three different sites on the Eastern Colorado plains: an urban, agricultural, and a mixed site. Downtown Denver had an average total and water-soluble iron air concentration of 181.2 and 7.7 ng m -3 , respectively. Platteville, the mixed site, had an average of total iron of 76.1 ng m -3 , with average water-soluble iron concentration of 9.1 ng m -3 . Jackson State Park (rural/agricultural) had the lowest total iron average of 31.5 ng m -3 and the lowest water-soluble iron average, 1.3 ng m -3 . The iron oxidation state and chemical speciation of 97 samples across all sites and seasons was probed by X-ray absorption near edge structure (XANES) spectroscopy. The most common iron phases observed were almandine (Fe 3 Al 2 Si 3 O 12 ) (Denver 21%, Platteville 16%, Jackson 24%), magnetite (Fe 3 O 4 ) (Denver 9%, Platteville 4%, Jackson 5%) and Fe (III)dextran (Denver 5%, Platteville 13%, Jackson 5%), a surrogate for Fe-organic complexes. Additionally, native iron [Fe(0)] was found in significant amounts at all sites. No correlation was observed between iron solubility and iron oxidation state or chemical speciation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Viromes outperform total metagenomes in revealing the spatiotemporal patterns of agricultural soil viral communities

Abstract Viruses are abundant yet understudied members of soil environments that influence terrestrial biogeochemical cycles. Here, we characterized the dsDNA viral diversity in biochar-amended agricultural soils at the preplanting and harvesting stages of a tomato growing season via paired total metagenomes and viral size fraction metagenomes (viromes). Size fractionation prior to DNA extraction reduced sources of nonviral DNA in viromes, enabling the recovery of a vaster richness of viral populations (vOTUs), greater viral taxonomic diversity, broader range of predicted hosts, and better access to the rare virosphere, relative to total metagenomes, which tended to recover only the most persistent and abundant vOTUs. Of 2961 detected vOTUs, 2684 were recovered exclusively from viromes, while only three were recovered from total metagenomes alone. Both viral and microbial communities differed significantly over time, suggesting a coupled response to rhizosphere recruitment processes and/or nitrogen amendments. Viral communities alone were also structured along an 18 m spatial gradient. Overall, our results highlight the utility of soil viromics and reveal similarities between viral and microbial community dynamics throughout the tomato growing season yet suggest a partial decoupling of the processes driving their spatial distributions, potentially due to differences in dispersal, decay rates, and/or sensitivities to soil heterogeneity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Non-linear relationships between daily temperature extremes and US agricultural yields uncovered by global gridded meteorological datasets

Global agricultural commodity markets are highly integrated among major producers. Prices are driven by aggregate supply rather than what happens in individual countries in isolation. Furthermore, estimating the effects of weather-induced shocks on production, trade patterns and prices hence requires a globally representative weather data set. Recently, two data sets that provide daily or hourly records, GMFD and ERA5-Land, became available. Starting with the US, a data rich region, we formally test whether these global data sets are as good as more fine-scaled country-specific data in explaining yields and whether they estimate similar response functions. While GMFD and ERA5-Land have lower predictive skill for US corn and soybeans yields than the fine-scaled PRISM data, they still correctly uncover the underlying non-linear temperature relationship. All specifications using daily temperature extremes under any of the weather data sets outperform models that use a quadratic in average temperature. Correctly capturing the effect of daily extremes has a larger effect than the choice of weather data. In a second step, focusing on Sub Saharan Africa, a data sparse region, we confirm that GMFD and ERA5-Land have superior predictive power to CRU, a global weather data set previously employed for modeling climate effects in the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Phenogenomics reveals the ecology and evolution of Trichoderma fungi for sustainable agriculture

Trichoderma fungi support sustainable agriculture by suppressing plant diseases and improving crop performance. However, emerging pathogenicity of Trichoderma warrants further ecological and genetic characterization. Here we used machine learning to correlate genomic data from 37 Trichoderma strains with over 140 phenotypic traits, spanning metabolic versatility, biotic interactions, stress tolerance and reproductive strategies. We determined Trichoderma to be an ancient, genetically cohesive and physiologically diverse genus with spores capable of germination in water and dispersal via air and water droplets. Metabolic preferences indicate universal adaptation to mycoparasitism and to niches like arboreal microbial mats, alongside broader saprotrophic versatility. Our analyses are consistent with character displacement among close relatives and convergent evolution in distant lineages, with both processes shaping ecological plasticity and traits including dispersal modes, terrestrialization or endophytism. Our findings reveal that while some Trichoderma species show traits of biosafety concern, its vast ecophysiological diversity enables the development of safe, targeted bioeffectors.

Steindorff, Andrei S. [USDOE Joint Genome Institut↗
DOE OSTI2026

Enamel nanocrystal misorientation increased with meat-eating and agriculture

Enamel covers teeth, is the hardest tissue in the vertebrate body and has a complex multiscale structure from nanometres to millimetres. The structure comprises thin, long hydroxyapatite (Ca 5 (PO 4 ) 3 OH) nanocrystals, 50–70 nm wide, many micrometres long, parallel and bundled into approximately 5-µm-wide rods. The rods undulate and cross into a microscale ‘decussation pattern’ that toughens enamel by deflecting cracks. However, the crystallographic orientation of enamel nanocrystals is poorly understood. Here we show that the misorientation angle of adjacent nanocrystals varies markedly across 12 primate teeth spanning 9 species, 17.8 million years of evolution and diverse diets. Using a method called Polarization Enabled Large Input of Crystal Angles at the Nanoscale (PELICAN), we compare nanocrystals in the same (pre)molar locations and show that misorientation increases with food hardness in extant and fossil non-human apes and monkeys. We compare misorientation across three major dietary shifts in human evolution: the transition to meat-eating about 2.0–1.5 million years before present, to agriculture (about 12,000 years before present), and the Industrial Revolution (about 250 years before present). We show that over the past 1.6 million years, in the human lineage misorientation increased with time, especially when meat and stone-ground grains were introduced into human diets, but not with the Industrial Revolution. Thus, besides macro-changes, teeth adapted to dietary change at the nanoscale and crystallographically. This observation suggests that misorientation may contribute to enamel’s resilience; thus, bioinspired materials may consider small misorientation angles for added resilience.

biomaterials↗
DOE OSTI2025

Depth-dependent Metagenome-Assembled Genomes of Agricultural Soils under Managed Aquifer Recharge

Abstract Managed Aquifer Recharge (MAR) systems, which intentionally replenish groundwater aquifers with excess water, are critical for addressing water scarcity exacerbated by demographic shifts and climate variability. To date, little is known about the functional diversity of the soil microbiome at different soil depth inhabiting agricultural soils used for MAR. Knowing the functional diversity is pivotal in regulating nutrient cycling and maintaining soil health. Metagenomics, particularly Metagenome-Assembled Genomes (MAGs), provide a powerful tool to explore the diversity of uncultivated soil microbes, facilitating in-depth investigations into microbial functions. In a field experiment conducted in a California vineyard, we sequenced soil DNA before and after water application of MAR. Through this process, we assembled 146 medium and 14 high-quality MAGs, uncovering a wide array of archaeal and bacterial taxa across different soil depths. These findings advance our understanding of the microbial ecology and functional diversity of soils used for MAR, contributing to the development of more informed and sustainable land management strategies.

Science & Technology - Other Topics↗
DOE OSTI2021

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project’s Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)—explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts consistently occurs earlier in the new projections—before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

Jagermeyr, Jonas↗
DOE OSTI2023

Ecological insights into soil health according to the genomic traits and environment-wide associations of bacteria in agricultural soils

Abstract Soil microbiomes are sensitive to current and previous soil conditions, and bacterial ‘bioindicators’ of biological, physical, and chemical soil properties have considerable potential for soil health assessment. However, the lack of ecological or physiological information for most soil microorganisms limits our ability to interpret the associations of bioindicators and, thus, their utility for guiding management. We identified bioindicators of tillage intensity and twelve soil properties used to rate soil health using a 16S rRNA gene-based survey of farmland across North America. We then inferred the genomic traits of bioindicators and evaluated their environment-wide associations (EWAS) with respect to agricultural management practice, disturbance, and plant associations with 89 studies from agroecosystems. Most bioindicators were either positively correlated with biological properties (e.g., organic matter) or negatively correlated with physical and chemical properties. Higher soil health ratings corresponded with smaller genome size and higher coding density, while lower ratings corresponded with larger genomes and higher rrn copy number. Community-weighted genome size explained most variation in health ratings. EWAS linked prominent bioindicators with the impacts of environmental disturbances. Our findings provide ecological insights into bioindicators of soil properties relevant to soil health management, illustrating the tight coupling of microbiome and soil function.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Reductive catalytic fractionation of agricultural residue and energy crop lignin and application of lignin oil as antimicrobials

Cheap and abundant waste from bioethanol and agricultural processing industries are an alluring alternative feedstock for biorefineries. In this work, we employ reductive catalytic fractionation (RCF) to depolymerize, over Ru/C powder and Ru/Al 2 O 3 pellets, five herbaceous biomass feedstocks, namely corn stover, miscanthus, switchgrass, sugarcane bagasse, and wheat straw into phenolic monomers with high yields (~40 wt.% based on total (Klason + acid soluble) lignin and > 50 wt.% when stabilized using aldehydes), leaving behind a carbohydrate pulp residue. Interestingly, a polar solvent is sufficient to solubilize and fragment the lignin polymer into monomers without any catalyst. Here, contrary to woody biomass, where the monomer yields are positively correlated with the S-content of lignin, principal component analysis indicates that the monomer yields from herbaceous biomass depend on the content of lignin crosslinker – ferulate. Using NMR, we further identify α – 6 C-C linked oligomers formed from condensation reactions, explaining the unexpected low monomer yields of high β-O-4 herbaceous biomass. Recyclability experiments indicate that catalyst deactivation occurs through sintering, leaching, and fouling. Lignin oil from herbaceous biomass exhibits bacteriostatic effects against Staphylococcus aureus, highlighting a potential application in functional food development and as food or feed preservative.

09 BIOMASS FUELS↗
DOE OSTI2020

Iowa’s agriculture is losing its Goldilocks climate

The Iowa landscape is endowed with rich, deep, dark soils that have high water-holding capacity. Because most of the state’s land is flat or gently rolling, agriculture can be practiced with large, efficient machinery. Historically, Iowa’s average climate is characterized by a growing season of about five to six months with favorable sunshine and warm temperatures. Its crop-dormant season has low enough temperatures to prevent overwintering of detrimental pests and pathogens. The seasonal cycle of precipitation has a spring–summer maximum and a winter minimum that generally provide a sufficient and timely supply of water to support high crop densities without the need for irrigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Where old meets new: An ecosystem study of methanogenesis in a reflooded agricultural peatland

Reflooding formerly drained peatlands has been proposed as a means to reduce losses of organic matter and sequester soil carbon for climate change mitigation, but a renewal of high methane emissions has been reported for these ecosystems, offsetting mitigation potential. Our ability to interpret observed methane fluxes in reflooded peatlands and make predictions about future flux trends is limited due to a lack of detailed studies of methanogenic processes. In this study we investigate methanogenesis in a reflooded agricultural peatland in the Sacramento Delta, California. Furthermore, we use the stable-and radio-carbon isotopic signatures of wetland sediment methane, ecosystem-scale eddy covariance flux observations, and laboratory incubation experiments, to identify which carbon sources and methanogenic production pathways fuel methanogenesis and how these processes are affected by vegetation and seasonality. We found that the old peat contribution to annual methane emissions was large (~30%) compared to intact wetlands, indicating a biogeochemical legacy of drainage. However, fresh carbon and the acetoclastic pathway still accounted for the majority of methanogenesis throughout the year. Although temperature sensitivities for bulk peat methanogenesis were similar between open-water (Q 10 = 2.1) and vegetated (Q 10 = 2.3) soils, methane production from both fresh and old carbon sources showed pronounced seasonality in vegetated zones. We conclude that high methane emissions in restored wetlands constitute a biogeochemical trade-off with contemporary carbon uptake, given that methane efflux is fueled primarily by fresh carbon inputs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Agricultural Management Legacy Effects on Switchgrass Growth and Soil Carbon Gains

Switchgrass ( Panicum virgatum L.) is a native North American grass currently considered a high-potential bioenergy feedstock crop. However, previous reports questioned its effectiveness in generating soil organic carbon (SOC) gains, with resultant uncertainty regarding the monoculture switchgrass's impact on the environmental sustainability of bioenergy agriculture. We hypothesize that the inconsistencies in past SOC accrual results might be due, in part, to differences in prior land management among the systems subsequently planted to switchgrass. To test this hypothesis, we measured SOC and other soil properties, root biomass, and switchgrass growth in an experimental site with a 30-year history of contrasting tillage and N-fertilization treatments, 7 years after switchgrass establishment. We determined switchgrass' monthly gross primary production (GPP) for six consecutive years and conducted deep soil sampling. Nitrogen fertilization expectedly stimulated switchgrass growth; however, a tendency for better plant growth was also observed under unfertilized settings in the former no-till soil. In topsoil, SOC significantly increased from 2007 to 2023 in fertilized treatments of both tillage histories, with the greatest increase observed in fertilized no-till. Fertilized no-till also had the highest particulate organic matter content in the topsoil, with no differences among the treatments observed in deeper soil layers. However, regardless of fertilization, the tillage history had a strong effect on stratification with depth of SOC, total N, and microbial biomass C. Results suggested that historic and ongoing N fertilization had a substantial impact on switchgrass growth and soil characteristics, while tillage legacy had a much weaker, but still discernible, effect.

bioenergy crop production system↗
DOE OSTI2023

Butterfly biodiversity increases with prairie strips and conservation management in row crop agriculture

Abstract Butterfly abundances are declining globally, with meta‐analysis showing a rate of −2% per year. Agriculture contributes to butterfly decline through habitat loss and degradation. Prairie strips—strips of farmland actively restored to native perennial vegetation—are a conservation practice with the potential to mitigate biodiversity loss, but their impact on butterfly biodiversity is not known. Working within a 30‐year‐old experiment that varied land use intensity, from natural areas to croplands (maize–soy–wheat rotation), we introduced prairie strips to less intensely managed crop treatments. Treatments included conservation land, biologically based (organic) row crops with prairie strips, reduced input row crops with prairie strips, no‐till row crops and conventional row crops. We measured butterfly abundance and richness: (1) within prairie strips and (2) across the gradient of land use intensity at the plot level. Butterfly abundance was higher within prairie strips than in all other treatments. Across the land use intensity gradient at the plot level, the conservation land treatment had the highest abundance, treatments with prairie strips had intermediate levels and no‐till and conventional treatments had the lowest abundances. Also across entire plots, butterfly richness increased as land use intensity decreased. Treatments with prairie strips, which also had reduced land use intensity, had distinct butterfly communities as they harboured several butterfly species that were not found in other row crop treatments. In addition to the known effects of prairie strips on ecosystem services including erosion control and increased water quality, prairie strips can increase biodiversity in multifunctional landscapes.

Kemmerling, Lindsey R.↗
DOE OSTI2024

The mycorrhizal symbiosis: research frontiers in genomics, ecology, and agricultural application

Summary Mycorrhizal symbioses between plants and fungi are vital for the soil structure, nutrient cycling, plant diversity, and ecosystem sustainability. More than 250 000 plant species are associated with mycorrhizal fungi. Recent advances in genomics and related approaches have revolutionized our understanding of the biology and ecology of mycorrhizal associations. The genomes of 250+ mycorrhizal fungi have been released and hundreds of genes that play pivotal roles in regulating symbiosis development and metabolism have been characterized. rDNA metabarcoding and metatranscriptomics provide novel insights into the ecological cues driving mycorrhizal communities and functions expressed by these associations, linking genes to ecological traits such as nutrient acquisition and soil organic matter decomposition. Here, we review genomic studies that have revealed genes involved in nutrient uptake and symbiosis development, and discuss adaptations that are fundamental to the evolution of mycorrhizal lifestyles. We also evaluated the ecosystem services provided by mycorrhizal networks and discuss how mycorrhizal symbioses hold promise for sustainable agriculture and forestry by enhancing nutrient acquisition and stress tolerance. Overall, unraveling the intricate dynamics of mycorrhizal symbioses is paramount for promoting ecological sustainability and addressing current pressing environmental concerns. This review ends with major frontiers for further research.

Plant Sciences↗
DOE OSTI2022

Food And Agriculture Supply Chain Model

This model is part of an LDRD effort to investigate the connection of food and agriculture supply chain and the critical infrastructure. The model was built for a small number of farmers, shippers, processing companies and retailers as proof of concept to illustrate supply chain impacts. In this model, the emphasis is on understanding the climate change impacts on the food supply chain. The model uses agent-based modeling method in combination with machine learning. It also connects logistic simulation with economic principles such as price change caused by supply and demand, and consumer substitution effect based on price comparisons of two substitutable commodities.

Nguyen, Thuy↗
DOE OSTI2024

Field To Farm Aggregation For Agricultural Systems

The Fields to Farms methodology illustrates the generation of farm parcels from the Crop Data Layer (CDL), a raster dataset containing 133 categories representing various crop types and land uses. This methodology involves two primary steps: Field Delineation and Farm Aggregation. The code specifically addresses the aggregation of pre-delineated fields within a county to form farms, adhering to predefined criteria for farm size categories. It is assumed that the field delineation process, which involves creating vector polygons from CDL raster, has been completed beforehand, possibly through external tools or methods. Upon initialization, the script processes county-level fields, preparing them for farm aggregation. In the Farm Aggregation phase, the code iteratively combines delineated fields into farms based on specified criteria, continuing until the aggregated farm size meets predefined thresholds derived from data from the 2017 National Agricultural Statistics Service (NASS) census. Throughout this iterative process, the script dynamically adjusts the aggregation to ensure alignment with the desired distribution reported by NASS. The resulting output of the script is a GeoDataFrame containing classified farms, which are subsequently saved as GeoPackage files. These files enable further analysis and visualization, facilitating comprehensive exploration of the farm landscape generated through the methodology.

Paudel, Rajiv [Idaho National Laboratory (INL), Id↗