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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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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Impacts of nitrogen addition on switchgrass root-associated diazotrophic community structure and function

ABSTRACT Cellulosic bioenergy crops, like switchgrass (Panicum virgatum), have potential for growth on lands unsuitable for food production coupled with potential for climate mitigation. Sustainability of these systems lies in identifying conditions that promote high biomass yields on marginal lands under low-input agricultural practices. Associative nitrogen fixation (ANF) is a potentially important nitrogen (N) source for these crops, yet ANF contributions to plant N, especially under fertilizer N addition are unclear. In this study, we assess structure (nifH) and function (ANF) of switchgrass root-associated diazotrophic communities to long-term and short-term N additions using soil from three marginal land sites. ANF rates were variable and often unexpectedly high, sometimes 10× greater than reported in the literature, and did not respond in repeatable ways to long-term or short-term N. We found few impacts of N addition on root-associated diazotrophic community structure or membership. Instead, we found a very consistent root-associated diazotrophic community even though switchgrass seeds were germinated in soil from field sites with distinct diazotrophic communities. Ultimately, this work demonstrates that root-associated diazotrophic communities have the potential to contribute to switchgrass N demands, independent of N addition, and this may be driven by selection of the diazotrophic community by switchgrass roots.

Microbiology↗
DOE OSTI2020

Niche Differentiation of Bacterial Versus Archaeal Soil Nitrifiers Induced by Ammonium Inhibition Along a Management Gradient

Soil nitrification, mediated mainly by ammonia oxidizing archaea (AOA) and bacteria (AOB), converts ammonium (NH 4 + ) to nitrite (NO 2 – ) and thence nitrate (NO 3 – ). To better understand ecological differences between AOA and AOB, we investigated the nitrification kinetics of AOA and AOB under eight replicated cropped and unmanaged ecosystems (including two fertilized natural systems) along a long-term management intensity gradient in the upper U.S. Midwest. For five of eight ecosystems, AOB but not AOA exhibited Haldane kinetics (inhibited by high NH 4 + additions), especially in perennial and successional systems. In contrast, AOA predominantly exhibited Michaelis-Menten kinetics, suggesting greater resistance to high nitrogen inputs than AOB. These responses suggest the potential for NH 4 + -induced niche differentiation between AOA and AOB. Additionally, long-term fertilization significantly enhanced maximum nitrification rates (V max ) in the early successional systems for both AOA and AOB, but not in the deciduous forest systems. This was likely due to pH suppression of nitrification in the acidic forest soils, corroborated by a positive correlation of V max with soil pH but not with amoA gene abundance. Results also demonstrated that soil nitrification potentials were relatively stable, as there were no seasonal differences. Overall, results suggest that (1) NH 4 + inhibition of AOB but not AOA could be another factor contributing to niche differentiation between AOA and AOB in soil, and (2) nitrification by both AOA and AOB can be significantly promoted by long-term nitrogen inputs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Predicting soil carbon changes in switchgrass grown on marginal lands under climate change and adaptation strategies

Abstract The United States Great Lakes Region (USGLR) is a critical geographic area for future bioenergy production. Switchgrass ( Panicum virgatum ) is widely considered a carbon (C)‐neutral or C‐negative bioenergy production system, but projected increases in air temperature and precipitation due to climate change might substantially alter soil organic C (SOC) dynamics and storage in soils. This study examined long‐term SOC changes in switchgrass grown on marginal land in the USGLR under current and projected climate, predicted using a process‐based model (Systems Approach to Land‐Use Sustainability) extensively calibrated with a wealth of plant and soil measurements at nine experimental sites. Simulations indicate that these soils are likely a net C sink under switchgrass (average gain 0.87 Mg C ha −1 year −1 ), although substantial variation in the rate of SOC accumulation was predicted (range: 0.2–1.3 Mg C ha −1 year −1 ). Principal component analysis revealed that the predicted intersite variability in SOC sequestration was related in part to differences in climatic characteristics, and to a lesser extent, to heterogeneous soils. Although climate change impacts on switchgrass plant growth were predicted to be small (4%–6% decrease on average), the increased soil respiration was predicted to partially negate SOC accumulations down to 70% below historical rates in the most extreme scenarios. Increasing N fertilizer rate and decreasing harvest intensity both had modest SOC sequestration benefits under projected climate, whereas introducing genotypes better adapted to the longer growing seasons was a much more effective strategy. Best‐performing adaptation scenarios were able to offset >60% of the climate change impacts, leading to SOC sequestration 0.7 Mg C ha −1 year −1 under projected climate. On average, this was 0.3 Mg C ha −1 year −1 more C sequestered than the no adaptation baseline. These findings provide crucial knowledge needed to guide policy and operational management for maximizing SOC sequestration of future bioenergy production on marginal lands in the USGLR.

09 BIOMASS FUELS↗
DOE OSTI2025

AmeriFlux US-YNS North Star Yedoma

This is the AmeriFlux version of the carbon flux data for the site US-YNS North Star Yedoma. Site Description - Dry hillslope underlain by ice rich permafrost and now covered with native grasses and managed as a rustic golf course. The land clearing performed decades ago has caused permafrost thawing, surface subsidence, and development of thermokarst mounds or baidjarahks. No foreign fill materials, pesticides or fertilizers have been used, and the area is not irrigated. The area outside the flux footprint is second growth deciduous forest with similar soil conditions.

Anthony, Katey Walter [University of Alaska Fairba↗
DOE OSTI2021

Impoverishing Roots Will Improve Wheat Yield and Profitability Through Increased Water and Nitrogen Use Efficiencies

We report that more than a 60% increase in crop production is required by the 2050's to feed a growing world population. Understanding how plant functional traits and field management affect crop yields has the potential to improve agricultural productivity, minimize economic and environmental losses, and maximize food security. We explored the influence of winter wheat root characteristics and management on winter wheat growth, yield, and profit using a mechanistic and well-tested ecosystem and crop model, ecosys. We applied and further tested ecosys at an agricultural farm growing winter wheat in Ardmore, Oklahoma, United States. The model accurately predicted observed shoot carbon (R 2 = 0.95), soil moisture (R 2 = 0.67), soil temperature (R 2 = 0.91), and yield (percent error = 17%). Numerical optimization experiments were conducted to explore potential improvements of winter wheat yield and profit by modifying root characteristics, including root radius and root:shoot carbon transfer conductance, and fertilizer inputs. Our results show the potential for simultaneously improving winter wheat yields and profits. The optimum conditions were found to be in the range of root radius between 0.1 and 0.3 mm, carbon transfer conductance between 0.004 and 0.01 h -1 , and the currently applied fertilizer rate of 112 kg ha -1 . Under these conditions, improvements in yields and profits of up to approximately 25% and 110%, respectively, were modeled compared to those under baseline root traits. These improvements were achieved by impoverishing root structures, thereby increasing nutrient allocation to grains. Our results also demonstrate and motivate model structures that integrate the complex network of plant physiology, soil nutrient biogeochemistry, hydrology, and management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A multi-product landscape life-cycle assessment approach for evaluating local climate mitigation potential

Increasing demand for land-based climate mitigation requires more efficient management of agricultural landscapes for competing objectives. Here we develop methods for assessing trade-offs and synergies between intensification and carbon-sequestering conservation measures in annual crop production landscapes using the DayCent ecosystem model and the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) life-cycle assessment (LCA) model. We compiled county-scaled crop yields, fertilizer application rates, and tillage intensity for a corn–soybean farming case study landscape in the US state of Iowa. Using DayCent, we estimated a baseline soil organic carbon (SOC) accrual rate of 0.29 Mg C ha -1 y -1 driven by historical increases in crop productivity and reductions in tillage intensity. We then simulated the effects of management interventions targeted toward intensification (stover removal) and SOC sequestration (tillage intensity reduction and winter cover crop addition) individually and in combination. We propose a new multi-product landscape–LCA approach that analyzes marginal changes in corn grain, corn stover, and soybean production from the landscape in terms of their value for biofuel production (corn ethanol, soy biodiesel, and cellulosic ethanol from stover) and associated net displacement of conventional fossil-derived fuel use. This enables us to evaluate both intensification and sequestration effects in common CO 2 -equivalent mitigation units. We also used DayCent-simulated yields under the different land management scenarios to estimate farm-level costs and revenues. Our results show that intensification via collecting 30% of corn stover for biofuel production would increase the total greenhouse gas (GHG) mitigation potential of this landscape by 0.93 Mg CO 2 e ha -1 y -1 and provide $49 ha -1 y -1 of additional net revenue from biomass sales, but would reduce the baseline SOC accumulation rate by approximately 40%. In contrast, integrated approaches that include co-adoption of winter cover cropping and/or tillage intensity reduction would result in increased rates of SOC accumulation above the baseline, achieving simultaneous improvements in both farm profits and the overall GHG mitigation potential of the landscape.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Post-flowering Soil Waterlogging Curtails Grain Yield Formation by Restricting Assimilates Supplies to Developing Grains

Soil waterlogging is among the major factors limiting the grain yield of winter wheat crops in many parts of the world, including the middle and lower reaches of the Yangtze River China. In a field study, we investigated the relationship between leaf physiology and grain development under a varying duration of post-flowering waterlogging. A winter wheat cultivar Ningmai 13 was exposed to soil waterlogging for 0 (W0), 3 (W3), 6 (W6), and 9 d (W9) at anthesis. Increasing waterlogging duration significantly reduced flag leaf SPAD (soil plant analysis development) values and net photosynthetic rate (Pn). There was a linear reduction in flag leaf Pn and SPAD as plant growth progressed under all treatments; however, the speed of damage was greater in the waterlogged leaves. For example, compared with their respective control (W0), flag leaves of W9 treatment have experienced 46% more reduction in Pn at 21 d after anthesis (DAA) than at 7 DAA. Increasing waterlogging duration also induced oxidative damage in flag leaves, measured as malondialdehyde (MDA) contents. The capacity to overcome this oxidative damage was limited by the poor performance of antioxidant enzymes in wheat leaves. Inhibited leaf Pn and capacity to sustain assimilate synthesis under waterlogged environments reduced grain development. Compared with W0, W6 and W9 plants experienced a 20 and 22% reduction in thousand grain weight (TGW) in response to W6 and W9, respectively at 7 DAA and 11 and 19%, respectively at 28 DAA. Sustained waterlogging also significantly reduced grain number per spike and final grain yield. Averaged across two years of study, W9 plants produced 28% lesser final grain yield than W0 plants. Our study suggested that wheat crops are highly sensitive to soil waterlogging during reproductive and grain filling phases due to their poor capacity to recover from oxidative injury to photosynthesis. Management strategies such as planting time, fertilization and genotype selection should be considered for the areas experiencing frequent waterlogging problems.

Ma, Shangyu↗
DOE OSTI2021

Agricultural Impacts on Nitrogen Cycling: Climate and Air Pollution (Final Technical Report)

We have successfully added a parameterization of ammonia emissions from synthetic fertilizer and manure from agriculture to Earth System Models. We have evaluated how emissions change in the future and the processes driving these changes. We have examined the impact of agricultural ammonia emissions on present-day air quality and have evaluated the impact of resolving the emissions with high temporal resolution. We have also examined the impact of how Earth System Models treat the cycling of emissions in soils. Our code, the Flows of Agricultural Nitrogen – version 2 – model (FANv2) has been run in both the CLM framework and the ELM framework. To my knowledge the code has not yet been fully implemented into ELM. Volatilization of ammonia (NH3) from fertilizers and livestock wastes forms a significant pathway of nitrogen losses in agricultural ecosystems and constitutes the largest source of atmospheric emissions of NH3. We have provided a major update to the process model FAN (Flow of Agricultural Nitrogen), which evaluates NH3 emissions interactively within an Earth system model; in this work, the Community Earth System Model (CESM) is used. The updated version (FANv2) includes a more detailed treatment of both physical and agricultural processes, which allows the model to differentiate between the volatilization losses from animal housings, manure storage, grazed pastures, and the application of manure and different types of mineral fertilizers. The modeled ammonia emissions are first evaluated at a local scale against experimental data for various types of fertilizers and manure, and they are subsequently run globally to evaluate NH3 emissions for 2010–2015 based on gridded datasets of fertilizer use and livestock populations. Comparison of regional emissions shows that FANv2 agrees with previous inventories for North America and Europe and is within the range of previous inventories for China. However, due to higher NH3 emissions in Africa, India, and Latin America, the global emissions simulated by FANv2(48 Tg N) are 30 %–40 % higher than in the existing inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

FUN-BioCROP model with litter decomposition parameters derived from the LIDET dataset

This repository contains the code and data necessary to run the FUN-BioCROP (Fixation and Uptake of Nitrogen-Bioenergy Carbon, Rhizosphere, Organisms, and Protection) model with litter decomposition parameters derived from a modified Monte Carlo simulation that used the Long-term Intersite Decomposition Experiment Team dataset. Related publication:Juice, S.M., Ridgeway, J.R., Hartman, M.D., Parton, W.J., Berardi, D.M., Sulman, B.N., Allen, K.E., & Brzostek, E.R. Reparameterizing litter decomposition using a simplified Monte Carlo method improves litter decay simulated by a microbial model and alters bioenergy soil carbon estimates. Description of Files: FUNBioCROP_LIDET Study.Rmd R code with FUN-BioCROP model that can be run with 10 different sets of parameters for litter decomposition (Baseline, LIDET, or eight other best parameter sets identified in the modified Monte Carlo simulation. CORPSE Functions_Bioenergy_V2.R Code with CORPSE model functions, called by FUNBioCROP_LIDET Study.Rmd Model Input Data: bulk.csv, bulk_till.csv, rhizo.csv, rhizo_till.csv, litter.csv Initial C and N (kg C or N/m2) pool values for each soil compartment, final values from spin up. All five files have the same columns: (Column - Description - Units) uFastC - Unprotected fast decomposing carbon - kg carbon/m2 uSlowC - Unprotected slow decomposing carbon - kg carbon/m2 uNecroC - Unprotected necromass carbon - kg carbon/m2 pFastC - Protected fast decomposing carbon - kg carbon/m2 pSlowC - Protected slow decomposing carbon - kg carbon/m2 pNecroC - Protected necromass carbon - kg carbon/m2 livingMicrobeC - Carbon in living microbial biomass - kg carbon/m2 uFastN - Unprotected fast decomposing nitrogen - kg nitrogen/m2 uSlowN - Unprotected slow decomposing nitrogen - kg nitrogen/m2 uNecroN - Unprotected necromass nitrogen - kg nitrogen/m2 pFastN - Protected fast decomposing nitrogen - kg nitrogen/m2 pSlowN - Protected slow decomposing nitrogen - kg nitrogen/m2 pNecroN - Protected necromass nitrogen - kg nitrogen/m2 inorganicN - Inorganic nitrogen - kg nitrogen/m2 CO2 - Carbon in carbon dioxide - kg carbon/m2 livingMicrobeN - Nitrogen in living microbial biomass - kg nitrogen/m2 Model Input Data: FluxTower_AvgSoilT.csv: Average daily soil temperature (oC) at 10 cm depth at University of Illinois Urbana-Champaign (UIUC) Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: FluxTower_AvgSoilVWC.csv: Average daily soil volumetric water content (VWC) at 10 cm depth at UIUC Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: input_CCS_LIDET Study.csv: This file has daily data to run FUN-BioCROP (Column - Description - Units): yr - calendar year - year doy - day of year (1 to 365) (no leap year) - day anpp - aboveground NPP (DayCent) - kg C/m2/day bnpp - belowground NPP (DayCent) - kg C/m2/day aglivc - live aboveground biomass carbon (DayCent) - kg C/m2 bglivcj - live juvenile fine root biomass carbon (DayCent) - kg C/m2 bglivcm - live mature fine root biomass carbon (DayCent) - kg C/m2 aglivn - live aboveground biomass nitrogen (DayCent) - kg N/m2 bglivnj - live juvenile fine root biomass nitrogen (DayCent) - kg N/m2 bglivnm - live mature fine root biomass nitrogen (DayCent) - kg N/m2 nyr - simulation year - year cult - indicates a cultivation event (0 or 1) crop - indicates a new crop (0 or 1) fert - indicates a fertilizer event (0 or 1) frst - indicates the first day of the growing season (0 or 1) harv - indicates a harvest event (0 or 1) last - indicates the end of the growing season (0 or 1) croptype - crop type (0=none; 1=alfalfa; 2=corn; 3=grass clover pasture; 4=soybean; 5=wheat) cropsrl - crop specific root length - mm/g root cultrhizmix - fraction of rhizosphere mixed with bulk soil during cultivation (0.0-1.0) - fraction cultlitmix - fraction of litter mixed with bulk soil during cultivation (0.0-1.0) - fraction harvremov - fraction of above ground biomass removed during harvest (0.0-1.0) - fraction fertamt - fertilization amount - g N/m2 lifehist - plant life history (0 = annual, 1 = perennial) froot_turnover_c - amount of C in fine root turnover - kg C/m2 froot_turnover_n - amount of N in fine root turnover - kg N/m2 agrd_turnover_c - amount of C in aboveground biomass turnover - kg C/m2 agrd_turnover_n - amount of N in aboveground biomass turnover - kg N/m2 leaf_litter_fastfrac - Fast decomposing fraction of leaf litter (0.0-1.0) - fraction root_litter_fastfrac - Fast decomposing fraction of root litter (0.0-1.0) - fraction root_diameter - root diameter - mm root_length - root length - mm root/m2 rhizo_frac - fraction of total soil volume that is rhizosphere (0.0 - 1.0) - fraction date - date in format YYYY-MM-DD Instructions: Save the model code ("FUN-BioCROP_LIDET Study.Rmd") and accompanything files (data streams and CORPSE function code) in the same folder. In model code "Chunk 3: Load CORPSE Data Streams" set the working directory (setwd) to the folder with the files saved in step #1. In "Chunk 5: Define LIDET parameter sets" select the litter decomposition parameter set to be used in the run, and comment out all other sets. If changing any parameter values, edit them in "Chunk 6: Load parameters." Run all chunks up to and including "Chunk 10: Prepare Data for Export." In "Chunk 11: Export Output Data" edit data frames for export and filenames, as necessary. "Chunk 12: Graph Total Soil C" makes a figure of C remaining over the model run period. Description of each model chunk (in file FUN-BioCROP_LIDET Study.Rmd): Chunk 1: Remove all functions, clear memory. Removes all functions from R environment, clears the memory. Chunk 2: Load Packages. Loads packages necessary to run the code. Chunk 3: Load CORPSE Data Streams. Sets the working directory and loads the data files necessary to run CORPSE. Chunk 4: Load CORPSE Functions. Loads the R script with CORPSE functions from the working directory, "CORPSE Functions_Bioenergy_V2.R". Chunk 5: Define LIDET parameter sets. Has ten different parameter sets for litter decomposition tested in this study: Baseline parameters, LIDET parameters, and the other 8 best performing parameter sets identified in the modified Monte Carlo. To run the model, all but one parameter set must be commented out. Chunk 6: Load Parameters. Loads all fixed parameters to run the model. Data frame with definitions of parameters is in the CORPSE function script "CORPSE Functions_Bioenergy_V2.R" Chunk 7: Prepare Data Streams. Takes data streams loaded in Chunk 3 and puts them in the format necessary to run the model. The model is coded to run at least two sites at a time, so if only one site is being run it must be run in duplicate. Individual data tables of daily values are created in this chunk from the input data file. Chunk 8: Set Initial Conditions. Creates data tables of soil C and N pools for each soil compartment (rhizo_till, rhizo, bulk_till, bulk, litter) and loads initial values into the data tables. Creates lists for each soil compartment to hold model output. Chunk 9: Load FUN Data and Set Up Matrices. Uses DayCent data to calculate FUN input data: root and leaf N demand, total N demand, plant CN, leaf N available for retranslocation, and litter production. Creates matrices for FUN model outputs. Chunk 10: Run Model. Runs the model. Chunk 11: Prepare Data for Export. Combines data from each day saved as lists into data frames for each soil compartment. Adds values from all soil compartments together to calculate total soil values, creates separate data frames for each soil C and N pool (e.g., protected slow C) for the total soil value. Adds different C and N pools together to calculate total soil C and N for all layers. Creates data frame of ratio of protected to unprotected SOC. Organizes FUN data for export. Chunk 12: Export Results. Exports CSV files of model results to the working directory. Chunk 13: Graph Total Soil C. Makes figure of C remaining over time. Related Links: Original FUN-BioCROP model: https://github.com/BrzostekEcologyLab/FUN-BioCROP LIDET dataset: https://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023

Juice, Stephanie↗
DOE OSTI2022

Energy Exascale Earth System Model v2.0.1

First patch release of v2.0.0 Changes since v2.0.0 [Important change] Fix ocean threading bug seen in debug cases on Chrysalis with Intel 20.0.4. Was introduced around time of v2.0.0 tag. Does not change v2.0.0 answers on Chrysalis because those didn't use threading or debugging. [EAM] Add semi-lagrangian tracer transport for theta-l (F90 and C++), add new algorithm for finding tropopause, add DSCREAM to allow v2 and SCREAM settings in same code such as adjust_ps [EAM-MMF] 60L default, allow C++ back end of RRTMGP (EAM too). [EAMxx] add nu-top functionality, fix forcing functor, add ttype9 and dcmip2012 tests 2.1, 2.2, and 3 HOMME: remove obsolete remap algs, option to specify dynamics alg indep of tracer, new sponge layer, add imex tests [ELM] Add topography-based subgrid (topounits), add FATES-ELM Nitro., Phos. and CH4 coupling, add land-use ts for NARRM, add lulc for SSP3 RCP7, Fix nutrient fertilization exp test and carbon isotope flux, Fix xactive lnd dry deposition, add lake water storage option, fix plant hydraulics 2d params, fix carbon budget calc, fix soil nutrient conc. bug, fix mosart dam bug, add test for new ELM, MOSART features, fix bug in O3 dry dep stomatal resistances, fix plant hydraulics restart BFB error, update mkmapdata. [MOSART] fix bug for reading the latitude from an unstructured input file, fix oversat in bubble test. [MPAS-ocean] Add CFC11, CFC12 tracers, add 2D spherical transport tests, fix del4 tracer mixing, add MARBL ocean tracer mixing, modify harmonic analysis options, add GPU port of vmix routines, fix calc of ML-averaged BV freq. [MPAS-seaice] Change extents of initial polar disks for oRRS18to6v3 grid, fix ice BGC with MARBL, update spherical test cases, fix DON coupling, Remove Cf from sea ice constants. [MPAS-landice] add CRYO1850-4xCO2 compset [CIME] add GCP, ANL GCE, Spock, Perlmutter, deprecate config_compilers.xml, fix and clean-up cmake macros, fix slurm bindings, refactor CIME internal testing, cleanup SCORPIO perf data, allow position independent compset naming, [also] update v2 benchmarking suite, extend e3sm_prod with throughput and memory checks

E3SM Project, DOE↗
DOE OSTI2025

Adaptive responses of Trichlorobacter lovleyi to nitrite detoxification reveal overlooked contributions of Geobacterales to nitrate ammonification

Abstract Poorly understood microorganisms “short-circuit” the nitrogen cycle via the dissimilatory nitrate reduction to ammonium to retain the element in agricultural lands and stimulate crop productivity. The prevalence of Geobacterales closely related to Trichlorobacter lovleyi in nitrate ammonification hotspots motivated us to investigate adaptive responses contributing to ammonification rates in the laboratory type strain T. lovleyi SZ. Here, we describe the identification of tightly regulated pathways for efficient nitrate foraging and respiration with acetate, an important intermediate of organic matter degradation that Geobacterales efficiently assimilate and oxidize. Challenging the established dogma that high carbon/nitrate ratios stimulate the reduction of nitrate to ammonium, T. lovleyi doubled rapidly across a wide range of ratios provided nitrate concentrations were low enough to prevent the accumulation of the toxic nitrite intermediate. Yet, excess electrons during hydrogenotrophic growth alleviated nitrite toxicity and stimulated the reduction of nitrate to ammonium even under conditions of severe acetate limitation. These findings underscore the importance of nitrite toxicity in the ammonification of nitrate by Geobacterales and provide much needed mechanistic understanding of microbial adaptations contributing to soil nitrogen conservation. This information is critical to enhance the predictive value of genomic-based traits in environmental surveys and to guide strategies for sustainable management of nitrogen fertilization as well as mitigation of green-house emissions and agrochemical leaching from agricultural lands.

Environmental Sciences & Ecology↗
DOE OSTI2021

Microbial Community Field Surveys Reveal Abundant Pseudomonas Population in Sorghum Rhizosphere Composed of Many Closely Related Phylotypes

While the root-associated microbiome is typically less diverse than the surrounding soil due to both plant selection and microbial competition for plant derived resources, it typically retains considerable complexity, harboring many hundreds of distinct bacterial species. Here, we report a time-dependent deviation from this trend in the rhizospheres of field grown sorghum. In this study, 16S rRNA amplicon sequencing was used to determine the impact of nitrogen fertilization on the development of the root-associated microbiomes of 10 sorghum genotypes grown in eastern Nebraska. We observed that early rhizosphere samples exhibit a significant reduction in overall diversity due to a high abundance of the bacterial genus Pseudomonas that occurred independent of host genotype in both high and low nitrogen fields and was not observed in the surrounding soil or associated root endosphere samples. When clustered at 97% identity, nearly all the Pseudomonas reads in this dataset were assigned to a single operational taxonomic unit (OTU); however, exact sequence variant (ESV)-level resolution demonstrated that this population comprised a large number of distinct Pseudomonas lineages. Furthermore, single-molecule long-read sequencing enabled high-resolution taxonomic profiling revealing further heterogeneity in the Pseudomonas lineages that was further confirmed using shotgun metagenomic sequencing. Finally, field soil enriched with specific carbon compounds recapitulated the increase in Pseudomonas, suggesting a possible connection between the enrichment of these Pseudomonas species and a plant-driven exudate profile.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Community Structure of Arbuscular Mycorrhizal Fungi in Soils of Switchgrass Harvested for Bioenergy

We assessed the different species of beneficial fungi living in agricultural fields of switchgrass, a large grass grown for biofuels, using high-resolution DNA sequencing. Contrary to our expectations, the fungi were not greatly affected by fertilization. However, we found a positive relationship between plant productivity and the number of families of beneficial fungi at one site. Furthermore, we sequenced many species that could not be identified with existing reference databases. One group of fungi was highlighted in an earlier study for being widely distributed but of unknown taxonomy. We discovered that this group belonged to a family called Pervetustaceae , which may benefit switchgrass in stressful environments. To produce higher-yielding switchgrass in a more sustainable manner, it could help to study these undescribed fungi and the ways in which they may contribute to greater switchgrass yield in the absence of fertilization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Managing Plant Microbiomes for Sustainable Biofuel Production

The development of environmentally sustainable, economical, and reliable sources of energy is one of the great challenges of the 21st century. Large-scale cultivation of cellulosic feedstock crops (henceforth, bioenergy crops) is considered one of the most promising renewable sources for liquid transportation fuels. However, the mandate to develop a viable cellulosic bioenergy industry is accompanied by an equally urgent mandate to deliver not only cheap reliable biomass but also ecosystem benefits, including efficient use of water, nitrogen, and phosphorous; restored soil health; and net negative carbon emissions. Thus, sustainable bioenergy crop production may involve new agricultural practices or feedstocks and should be reliable, cost effective, and minimal input, without displacing crops currently grown for food production on fertile land. In this editorial perspective for the Phytobiomes Journal Focus Issue on Phytobiomes of Bioenergy Crops and Agroecosystems, we consider the microbiomes associated with bioenergy crops, the effects beneficial microbes have on their hosts, and potential ecosystem impacts of these interactions. We also address outstanding questions, major advances, and emerging biotechnological strategies to design and manipulate bioenergy crop microbiomes. This approach could simultaneously increase crop yields and provide important ecosystem services for a sustainable energy future.

09 BIOMASS FUELS↗
DOE OSTI2023

Quantifying direct yield benefits of soil carbon increases from cover cropping

Cropland management practices that restore soil organic carbon (SOC) are increasingly presented as climate solutions that also enhance yields. But how often these benefits align at the farm level—the scale of farmers’ decision making—remains uncertain. Here we examined concurrent SOC and yield responses to cover cropping, including their direct connection, with a global meta-analysis. Cover cropping simultaneously increased yields and SOC in 59.7% of 434 paired observations. Increases in SOC directly increased crop yields in soils with initial SOC concentrations below 11.6 g kg-1; for example, a change from 5 g kg -1 to 6 g kg -1 increased yields by +2.4%. These yield benefits of SOC did not decline as nitrogen inputs increased or when legume cover crops were used, suggesting fertility inputs cannot substitute for SOC effects. Regardless of direct effects of SOC increases on yields, integrating legume cover crops into systems with simplified rotations or with nitrogen inputs < 157 kg ha -1 season -1 N led to the largest yield increases (up to +24.3%), with legumes also increasing SOC more than non-legumes (up to +1.5 g kg -1 ). By simultaneously increasing yields and SOC, cover cropping provides an opportunity to benefit both food security and climate, including via direct yield benefits from SOC increases on low carbon soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Bear Brook Watershed in Maine: Multi-Decadal Whole-Watershed Experimental Acidification

The Bear Brook Watershed in Maine (BBWM) is a long-term research site established to study the response of forest ecosystem function to environmental disturbances of chronic acidic deposition and ecosystem nitrogen enrichment. Starting in 1989, the West Bear (treated) watershed received bimonthly applications of ammonium sulfate [(NH4)2SO4] fertilizer from above the canopy, whereas East Bear (reference) received ambient deposition. The treatments were stopped in 2016, marking the beginning of the recovery phase. Research at the site has focused on soils, streams, and vegetation. Here, we describe data collected over three decades at the BBWM—input and stream output nutrient fluxes, quantitative soil pits and soil chemistry, and soil temperature and moisture.

Patel, Kaizad F.↗
DOE OSTI2023

Root phenotypes for improved nitrogen capture

Abstract Background Suboptimal nitrogen availability is a primary constraint for crop production in low-input agroecosystems, while nitrogen fertilization is a primary contributor to the energy, economic, and environmental costs of crop production in high-input agroecosystems. In this article we consider avenues to develop crops with improved nitrogen capture and reduced requirement for nitrogen fertilizer. Scope Intraspecific variation for an array of root phenotypes has been associated with improved nitrogen capture in cereal crops, including architectural phenotypes that colocalize root foraging with nitrogen availability in the soil; anatomical phenotypes that reduce the metabolic costs of soil exploration, improve penetration of hard soil, and exploit the rhizosphere; subcellular phenotypes that reduce the nitrogen requirement of plant tissue; molecular phenotypes exhibiting optimized nitrate uptake kinetics; and rhizosphere phenotypes that optimize associations with the rhizosphere microbiome. For each of these topics we provide examples of root phenotypes which merit attention as potential selection targets for crop improvement. Several cross-cutting issues are addressed including the importance of soil hydrology and impedance, phenotypic plasticity, integrated phenotypes, in silico modeling, and breeding strategies using high throughput phenotyping for co-optimization of multiple phenes. Conclusions Substantial phenotypic variation exists in crop germplasm for an array of root phenotypes that improve nitrogen capture. Although this topic merits greater research attention than it currently receives, we have adequate understanding and tools to develop crops with improved nitrogen capture. Root phenotypes are underutilized yet attractive breeding targets for the development of the nitrogen efficient crops urgently needed in global agriculture.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

The climate change mitigation potential of annual grasslands under future climates

Abstract Composted manure and green waste amendments have been shown to increase net carbon (C) sequestration in rangeland soils and have been proposed as a means to help lower atmospheric CO 2 concentrations. However, the effect of climate change on soil organic C (SOC) stocks and greenhouse gas emissions in rangelands is not well understood, and the viability of climate change mitigation strategies under future conditions is even less certain. We used a process‐based biogeochemical model (DayCent) at a daily time step to explore the long‐term effects of potential future climate changes on C and greenhouse gas dynamics in annual grassland ecosystems. We then used the model to explore how the same ecosystems might respond to climate change following compost amendments to soils and determined the long‐term viability of net SOC sequestration under changing climates. We simulated net primary productivity (NPP), SOC, and greenhouse gas fluxes across seven California annual grasslands with and without compost amendments. We drove the DayCent simulations with field data and with site‐specific daily climate data from two Earth system models (CanESM2 and HadGEM‐ES) and two representative concentration pathways (RCP4.5 and RCP8.5) through 2100. NPP and SOC stocks in unamended and amended ecosystems were surprisingly insensitive to projected climate changes. A one‐time amendment of compost to rangeland acted as a slow‐release organic fertilizer and increased NPP by up to 390–814 kg C ha −1 year −1 across sites. The amendment effect on NPP was not sensitive to Earth system model or emissions scenario and endured through the end of the century. Net SOC sequestration amounted to 1.96 ± 0.02 Mg C ha −1 relative to unamended soils at the maximum amendment effect. Averaged across sites and scenarios, SOC sequestration peaked 22 ± 1 years after amendment and declined but remained positive throughout the century. Though compost stimulated nitrous oxide (N 2 O) emissions, the cumulative net emissions (in CO 2 equivalents) due to compost were far less than the amount of SOC sequestered. Compost amendments resulted in a net climate benefit of 69.6 ± 0.5 Tg CO 2 e 20 ± 1 years after amendment if applied to similar ecosystems across the state, amounting to 39% of California's rangeland. These results suggest that the biogeochemical benefits of a single amendment of compost to rangelands in California are insensitive to climate change and could contribute to decadal‐scale climate change mitigation goals alongside emissions reductions.

Mayer, Allegra↗