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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 OSTI2023

Aligning theoretical and empirical representations of soil carbon-to-nitrogen stoichiometry with process-based terrestrial biogeochemistry models

Soil carbon-nitrogen (C:N) stoichiometry acts as a control over decomposition and soil organic matter formation and loss, making it a key soil property for understanding ecosystem dynamics and projected ecosystems responses to global environmental change. However, the controls of soil C:N and how they respond to increasing pressures from global change agents are not fully understood. The “foundational” controls on soil C:N, namely plant and microbial C:N, have been used to predict soil C:N, but fail to accurately simulate all ecosystems and may be insufficient for predictions under global environmental change. Here we present an “emerging” representation of controls of soil C:N that includes plant-microbe-mineral feedbacks that have been shown to regulate soil C:N. We argue that including representation of these emerging drivers in process-based terrestrial biogeochemistry models, which include biological N fixation, mycorrhizae, priming, root exudation of organic acids, and mineralogy (including soil texture, mineral composition, and aggregation), will improve mechanistic representation of soil C:N and associated processes. Such improvements will produce models that will better simulate a variety of ecological states and predict soil C:N when global changes modify plant-microbe-mineral interactions. Here, we align our empirical understanding of controls of soil C:N with those controls represented in models, identifying contexts where emerging drivers might be particularly important to represent (e.g., priming and root exudation in nutrient-limited conditions) and areas of future work. Additionally, we show that implementing emerging drivers of soil C:N results in different simulated outcomes at steady state and in response to elevated atmospheric CO2. Our review and preliminary simulations support the need to incorporate emerging drivers of soil C:N into process-based terrestrial biogeochemistry models, allowing for both theoretical exploration of mechanisms and potentially more accurate predictions of land biogeochemical responses to global change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Alley cropping affects perennial bioenergy crop root distribution, carbon, and nutrient stocks

This study quantified root biomass distribution; root accrual of C, N, P, and K; and changes in soil organic carbon (SOC) associated with alley-cropped switchgrass (Panicum virgatum L.), prairie cordgrass (Spartina pectinata Bosc ex Link), intermediate wheatgrass [Thinopyrum intermedium (Host) Barkworth and Dewey ‘Rush’], and a native polyculture planted between rows of ‘NM6’ poplar (Populus maximowiczii × P. nigra) and ‘Fish Creek’ willow (Salix purpurea) at two Minnesota sites (Empire and Granada). After 4 yr since establishment, SOC declined at each site but was not influenced by species selection. NM6 poplar–prairie cordgrass systems had among the highest root biomass, C, and nutrient accrual, with up to 16.3 Mg root biomass, 7.0 Mg C, 175 kg N, 31 kg P, and 97 kg K ha -1 . Fine roots were the largest fraction of belowground biomass, although course roots were also a large fraction for poplar and prairie cordgrass. Tree roots extended to 6 m into the crop alley, although 85–89% were within 1 m of tree rows, depending on tree species. Crop fine root biomass was reduced up to 67% at 1 m from tree rows and 20% at 3.5 m and was up to 142% greater in willow than in poplar alleys. Total root C was predominated by poplars at Empire regardless of herbaceous crop type, whereas the proportions of tree and crop root C varied by crop at Granada. These results suggest that prairie cordgrass is well suited to alley cropping and that, due to the competitive ability of poplars, productivity, C sequestration, and nutrient accrual may be greater in willow systems in the long term.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Changes in soil pore structure generated by the root systems of maize , sorghum and switchgrass affect in situ N 2 O emissions and bacterial denitrification

Due to the heterogeneous nature of soil pore structure, processes such as nitrification and denitrification can occur simultaneously at microscopic levels, making prediction of small-scale nitrous oxide (N 2 O) emissions in the field notoriously difficult. We assessed N 2 O+N 2 emissions from soils under maize (Zea mays L.), switchgrass (Panicum virgatum L.), and energy sorghum (Sorghum bicolor L.), three potential bioenergy crops in order to identify the importance of different N 2 O sources to microsite production, and relate N 2 O source differences to crop-associated differences in pore structure formation. The combination of isotopic surveys of N 2 O in the field during one growing season and X-ray computed tomography (CT) enabled us to link results from isotopic mappings to soil structural properties. Further, our methodology allowed us to evaluate the potential for in situ N 2 O suppression by biological nitrification inhibition (BNI) in energy sorghum. Our results demonstrated that the fraction of N 2 O originating from bacterial denitrification and reduction of N 2 O to N 2 is largely determined by the volume of particulate organic matter occluded within the soil matrix and the anaerobic soil volume. Bacterial denitrification was greater in switchgrass than in the annual crops, related to changes in pore structure caused by the coarse root system. This led to high N-loses through N 2 emissions in the switchgrass system throughout the season a novel finding given the lack of data in the literature for total denitrification. Isotopic mapping indicated no differences in N 2 O-fluxes or their source processes between maize and energy sorghum that could be associated with the release of BNI by the investigated sorghum variety. The results of this research show how differences in soil pore structures among cropping systems can determine both N 2 O production via denitrification and total denitrification N losses in situ.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Influence of root- vs needle-derived litter on soil C and N stabilization in a California coniferous forest from 2001 to 2011

How plant inputs from above- versus below-ground affect long term carbon (C) and nitrogen (N) retention and stabilization in soils is not well known. We present results of a decade-long field study that traced the decomposition of 13C- and 15N-labeled Pinus ponderosa needle and fine root litter placed in O or A soil horizons of a sandy Alfisol under a coniferous forest. We measured the retention of litter-derived C and N in particulate (>2 mm) and bulk soil (<2 mm) fractions, as well as in density-separated free light and three mineral-associated fractions. After 10 years, the influence of slower initial mineralization of root litter compared to needle litter was still evident: almost twice as much root litter (44% of C) was retained than needle litter (22–28% of C). After 10 years, the O horizon retained more litter in coarse particulate matter implying the crucial comminution step was slower than in the A horizon, while the A horizon retained more litter in the finer bulk soil, where it was recovered in organo-mineral associations. Retention in these A horizon mineral-associated fractions was similar for roots and needles. Nearly 5% of the applied litter C (and almost 15% of the applied N) was in organo-mineral associations, which had centennial residence times and potential for long-term stabilization. Vertical movement of litter-derived C was minimal after a decade, but N was significantly more mobile. Overall, the legacy of initial litter quality influences total SOM retention; however, the potential for and mechanisms of long-term SOM stabilization are influenced not by litter type but by soil horizon.This dataset comprises (1) litter recovery for each of 5 timepoints in >2mm, <2mm, and density fractions, (2) density fractionation results for the 10-year timepoint, and (3) vertical movement of applied litter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Sweet Sorghum Genotypes Tolerant and Sensitive to Nitrogen Stress Select Distinct Root Endosphere and Rhizosphere Bacterial Communities

The belowground microbiomes have many beneficial functions that assist plant growth, including nutrient cycling, acquisition and transport, as well as alleviation of stresses caused by nutrient limitations such as nitrogen (N). Here we analyzed the root endosphere, rhizosphere and soil bacterial communities of seven sweet sorghum genotypes differing in sensitivity to N-stress. Sorghum genotypes were grown in fields with no (low-N) or sufficient (high-N) N. The dry shoot weight ratio (low-N/high-N) was used to determine N-stress sensitivity. Our hypothesis was that genotypes tolerant and sensitive to N-stress select distinct bacterial communities. The endosphere and rhizosphere bacterial community structure were significantly different between the N-stress sensitive and tolerant genotypes in the high-N field, but not in the low-N field. However, significant changes in the relative abundance of specific bacterial taxa were observed in both fields. Streptomyces, a bacterial genus known to alleviate plant abiotic stresses, was enriched in the endosphere and rhizosphere of the tolerant genotypes in the low-N field. Our study indicates that sweet sorghum genotypes tolerant to N-stress select taxa that can potentially mitigate the N-stress, suggesting that the interactions between N-stress tolerant lines and the root-associated microbiome might be vital for coping with N-stress.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Tropical dry forest response to nutrient fertilization: a model validation and sensitivity analysis

Abstract. Soil nutrients, especially nitrogen (N) and phosphorus (P), regulate plant growth and hence influence carbon fluxes between the land surface and atmosphere. However, how forests adjust biomass partitioning to leaves, wood, and fine roots in response to N and/or P fertilization remains puzzling. Recent work in tropical forests suggests that trees increase fine root production under P fertilization, but it is unclear whether mechanistic models can reproduce this dynamic. In order to better understand mechanisms governing nutrient effects on plant allocation and improve models, we used the nutrient-enabled ED2 model to simulate a fertilization experiment being conducted in a secondary tropical dry forest in Costa Rica. We evaluated how different allocation parameterizations affected model performance. These parameterizations prescribed a linear relationship between relative allocation to fine roots and soil P concentrations. The slope of the linear relationship was allowed to be positive, negative, or zero. Some parameterizations realistically simulated leaf, wood, and fine root production, and these parameterizations all assumed a positive relationship between relative allocation to fine roots and soil P concentration. Model simulations of a 30-year timeframe indicated strong sensitivity to parameterization and fertilization treatment. Without P fertilization, the simulated aboveground biomass (AGB) accumulation was insensitive to the parameterization. With P fertilization, the model was highly sensitive to the parameterization and the greatest AGB accumulation occurred when relative allocation to fine roots was independent of soil P. Our study demonstrates the need for simultaneous measurements of leaf, wood, and fine root production in nutrient fertilization experiments and for longer-term experiments. Models that do not accurately represent allocation to fine roots may be highly biased in their simulations of AGB, especially on multi-decadal timescales.

Environmental Sciences & Ecology↗
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 OSTI2020

Switchgrass Rhizosphere Metabolite Chemistry Driven by Nitrogen Availability

Plants and soil microorganisms interact closely in the rhizosphere where plants may exchange carbon (C) for functional benefits from the microbial community. For example, the bioenergy crop, switchgrass (Panicum virgatum) is thought to exchange root-exuded C for nitrogen (N) fixed by diazotrophs (free-living N-fixers). However, this interaction is not well characterized and it is not known how or if switchgrass responds to diazotrophs or their activity. To explore this question, we assessed rhizosphere metabolite chemistry of switchgrass grown in a hydroponic system under two N levels and under inoculated or uninoculated conditions. Plants were grown with the inoculum Azotobacter vinelandii DJ for 3 days before harvest. We found switchgrass root exudate chemistry to be driven by N availability. Total metabolite concentrations were generally greater under high N versus low N and unaffected by inoculation. Examination of rhizosphere chemical fingerprints indicates metabolite chemistry was also driven strongly by N availability with a greater relative abundance of carbohydrates under high N and greater relative abundance of organic acids under low N. We also found evidence of changes in rhizosphere chemical fingerprints by inoculation treatment. However, we found little evidence of N treatment and inoculation interaction effects that suggests this response is not directly mediated by N availability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Data from: Switchgrass rhizosphere metabolite chemistry driven by nitrogen availability

Plants and soil microorganisms interact closely in the rhizosphere where plants may exchange carbon (C) for functional benefits from the microbial community. For example, the bioenergy crop, switchgrass (Panicum virgatum) is thought to exchange root-exuded C for nitrogen (N) fixed by diazotrophs (free-living N-fixers). However, this interaction is not well characterized and it is not known how or if switchgrass responds to diazotrophs or their activity. To explore this question, we assessed rhizosphere metabolite chemistry of switchgrass grown in a hydroponic system under two N levels and under inoculated or uninoculated conditions. Plants were grown with the inoculum Azotobacter vinelandii DJ for three days before harvest. We found switchgrass root exudate chemistry to be driven by N availability. Total metabolite concentrations were generally greater under high N versus low N and unaffected by inoculation. Examination of rhizosphere chemical fingerprints indicates metabolite chemistry was also driven strongly by N availability with a greater relative abundance of carbohydrates under high N and greater relative abundance of organic acids under low N. We also found evidence of changes in rhizosphere chemical fingerprints by inoculation treatment. However, we found little evidence of N treatment and inoculation interaction effects which suggests this response is not directly mediated by N availability.

09 BIOMASS FUELS↗
DOE OSTI2021

Dynamics of N 2 O in vicinity of plant residues: a microsensor approach

Plant residues decomposing within the soil matrix are known to serve as hotspots of N 2 O production. However, the lack of technical tools for microscale in-situ N 2 O measurements limits understanding of hotspot functioning. Our aim was to assess performance of microsensor technology for evaluating the temporal patterns of N 2 O production in immediate vicinity to decomposing plant residues. We incorporated intact switchgrass leaves and roots into soil matrix and monitored O 2 depletion and N 2 O production using electrochemical microsensors along with N 2 O emission from the soil. We also measured residue’s water absorption and b-glucosidase activity on the surface of the residue - the characteristics related to microenvironmental conditions and biological activity near the residue. N 2 O production in the vicinity of switchgrass residues began within 0–12 h after the wetting, reached peak at ~0.6 day and decreased by day 2. N 2 O was higher near leaf than near root residues due to greater leaf N contents and water absorption by the leaves. However, N 2 O production near the roots started sooner than near the leaves, in part due to high initial enzyme levels on root surfaces. Electrochemical microsensor is a useful tool for in-situ micro-scale N 2 O monitoring in immediate vicinity of soil incorporated plant residues. Monitoring provided valuable information on N 2 O production near leaves and roots, its temporal dynamic, and the factors affecting it. The N 2 O production from residues measured by microsensors was consistent with the N 2 O emission from the whole soil, demonstrating the validity of the microsensors for N 2 O hotspot studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Vadose zone flushing of fertilizer tracked by isotopes of water and nitrate

Abstract A substantial fraction of nitrogen (N) fertilizer applied in agricultural systems is not incorporated into crops and moves below the rooting zone as nitrate (NO 3 − ). Understanding mechanisms for soil N retention below the rooting zone and leaching to groundwater is essential for our ability to track the fate of added N. We used dual stable isotopes of nitrate (δ 15 N–NO 3 − and δ 18 O–NO 3 − ) and water (δ 18 O–H 2 O and δ 2 H–H 2 O) to understand the mechanisms driving nitrate leaching at three depths (0.8, 1.5, and 3.0 m) of an irrigated corn field sampled every 2 weeks from 2016 to 2020 in the southern Willamette Valley, Oregon, USA. Distinct periods of high nitrate concentrations with lower δ 15 N–NO 3 − values indicated that a portion of that nitrate was from recent fertilizer applications. We used a mixing model to quantify nitrate fluxes associated with recently added fertilizer N versus older, legacy soil N during these “fertilizer signal periods.” Nitrate leached below 3.0 m in these periods made up a larger proportion of the total N leached at that depth (∼52%) versus the two shallower depths (∼13%–16%), indicating preferential movement of recently applied fertilizer N through the deep soil into groundwater. Further, N associated with recent fertilizer additions leached more easily when compared to remobilized legacy N. A high volume of fall and winter precipitation may push residual fertilizer N to depth, potentially posing a larger threat to groundwater than legacy N. Optimizing fertilizer N additions could minimize fertilizer losses and reduce nitrate leaching to groundwater.

Agriculture↗
DOE OSTI2024

Mycorrhizal associations of temperate forest seedlings mediate rhizodeposition, but not soil carbon storage, under elevated nitrogen availability

Abstract Tree‐mycorrhizal associations are associated with patterns in nitrogen (N) availability and soil organic matter storage; however, we still lack a mechanistic understanding of what tree and fungal traits drive these patterns and how they will respond to global changes in soil N availability. To address this knowledge gap, we investigated how arbuscular mycorrhizal (AM)‐ and ectomycorrhizal (EcM)‐associated seedlings alter rhizodeposition in response to increased seedling inorganic N acquisition. We grew four species each of EcM and AM seedlings from forests of the eastern United States in a continuously 13 C‐labeled atmosphere within an environmentally controlled chamber and subjected to three levels of 15 N‐labeled fertilizer. We traced seedling 15 N uptake from, and 13 C‐labeled inputs (net rhizodeposition) into, root‐excluded or ‐included soil over a 5‐month growing season. N uptake by seedlings was positively related to rhizodeposition for EcM‐ but not AM‐associated seedlings in root‐included soils. Despite this contrast in rhizodeposition, there was no difference in soil C storage between mycorrhizal types over the course of the experiment. Instead root‐inclusive soils lost C, while root‐exclusive soils gained C. Our findings suggest that mycorrhizal associations mediate tree belowground C investment in response to inorganic N availability, but these differences do not affect C storage. Continued soil warming and N deposition under global change will increase soil inorganic N availability and our seedling results indicate this could lead to greater belowground C investment by EcM‐associated trees. This potential for less efficient N uptake by EcM‐trees could contribute to AM‐tree success and a shift toward more AM‐dominated temperate forests.

Fitch, Amelia A.↗
DOE OSTI2021

Theoretical evidence that root penetration ability interacts with soil compaction regimes to affect nitrate capture

Abstract Background and Aims Although root penetration of strong soils has been intensively studied at the scale of individual root axes, interactions between soil physical properties and soil foraging by whole plants are less clear. Here we investigate how variation in the penetration ability of distinct root classes and bulk density profiles common to real-world soils interact to affect soil foraging strategies. Methods We utilize the functional–structural plant model ‘OpenSimRoot’ to simulate the growth of maize (Zea mays) root systems with variable penetration ability of axial and lateral roots in soils with (1) uniform bulk density, (2) plow pans and (3) increasing bulk density with depth. We also modify the availability and leaching of nitrate to uncover reciprocal interactions between these factors and the capture of mobile resources. Key Results Soils with plow pans and bulk density gradients affected overall size, distribution and carbon costs of the root system. Soils with high bulk density at depth impeded rooting depth and reduced leaching of nitrate, thereby improving the coincidence of nitrogen and root length. While increasing penetration ability of either axial or lateral root classes produced root systems of comparable net length, improved penetration of axial roots increased allocation of root length in deeper soil, thereby amplifying N acquisition and shoot biomass. Although enhanced penetration ability of both root classes was associated with greater root system carbon costs, the benefit to plant fitness from improved soil exploration and resource capture offset these. Conclusions While lateral roots comprise the bulk of root length, axial roots function as a scaffold determining the distribution of these laterals. In soils with high soil strength and leaching, root systems with enhanced penetration ability of axial roots have greater distribution of root length at depth, thereby improving capture of mobile resources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Impacts of Arctic Shrubs on Root Traits and Belowground Nutrient Cycles Across a Northern Alaskan Climate Gradient

Deciduous shrubs are expanding across the graminoid-dominated nutrient-poor arctic tundra. Absorptive root traits of shrubs are key determinants of nutrient acquisition strategy from tundra soils, but the variations of shrub root traits within and among common shrub genera across the arctic climatic gradient are not well resolved. Consequently, the impacts of arctic shrub expansion on belowground nutrient cycling remain largely unclear. Here, we collected roots from 170 plots of three commonly distributed shrub genera ( Alnus , Betula , and Salix ) and a widespread sedge ( Eriophorum vaginatum ) along a climatic gradient in northern Alaska. Absorptive root traits that are relevant to the strategy of plant nutrient acquisition were determined. The influence of aboveground dominant vegetation cover on the standing root biomass, root productivity, vertical rooting profile, as well as the soil nitrogen (N) pool in the active soil layer was examined. We found consistent root trait variation among arctic plant genera along the sampling transect. Alnus and Betula had relatively thicker and less branched, but more frequently ectomycorrhizal colonized absorptive roots than Salix , suggesting complementarity between root efficiency and ectomycorrhizal dependence among the co-existing shrubs. Shrub-dominated plots tended to have more productive absorptive roots than sedge-dominated plots. At the northern sites, deep absorptive roots (>20 cm depth) were more frequent in birch-dominated plots. We also found shrub roots extensively proliferated into the adjacent sedge-dominated plots. The soil N pool in the active layer generally decreased from south to north but did not vary among plots dominated by different shrub or sedge genera. Our results reveal diverse nutrient acquisition strategies and belowground impacts among different arctic shrubs, suggesting that further identifying the specific shrub genera in the tundra landscape will ultimately provide better predictions of belowground dynamics across the changing arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Root-derived inputs are major contributors to soil carbon in temperate forests, but vary by mycorrhizal type

Roots promote the formation of slow-cycling soil carbon (C), yet we have a limited understanding of the magnitude and controls on this flux. We hypothesised arbuscular mycorrhizal (AM)- and ectomycorrhizal (ECM)-associated trees would exhibit differences in root-derived C accumulation in the soil, and that much of this C would be transferred into mineral-associated pools. We installed δ 13 C-enriched ingrowth cores across mycorrhizal gradients in six Eastern U.S. forests (n = 54 plots). Overall, root-derived C was 54% greater in AM versus ECM-dominated plots. This resulted in nearly twice as much root-derived C in putatively slow-cycling mineral-associated pools in AM compared to ECM plots. Finally, given that our estimates of root-derived inputs were often equal to or greater than leaf litter inputs, our results suggest that variation in root-derived soil C accumulation due to tree mycorrhizal dominance may be a key control of soil C dynamics in forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Stronger fertilization effects on aboveground versus belowground plant properties across nine U.S. grasslands

Abstract Increased nutrient inputs due to anthropogenic activity are expected to increase primary productivity across terrestrial ecosystems, but changes in allocation aboveground versus belowground with nutrient addition have different implications for soil carbon (C) storage. Thus, given that roots are major contributors to soil C storage, understanding belowground net primary productivity (BNPP) and biomass responses to changes in nutrient availability is essential to predicting carbon–climate feedbacks in the context of interacting global environmental changes. To address this knowledge gap, we tested whether a decade of nitrogen (N) and phosphorus (P) fertilization consistently influenced aboveground and belowground biomass and productivity at nine grassland sites spanning a wide range of climatic and edaphic conditions in the continental United States. Fertilization effects were strong aboveground, with both N and P addition stimulating aboveground biomass at nearly all sites (by 30% and 36%, respectively, on average). P addition consistently increased root production (by 15% on average), whereas other belowground responses to fertilization were more variable, ranging from positive to negative across sites. Site‐specific responses to P were not predicted by the measured covariates. Atmospheric N deposition mediated the effect of N fertilization on root biomass and turnover. Specifically, atmospheric N deposition was positively correlated with root turnover rates, and this relationship was amplified with N addition. Nitrogen addition increased root biomass at sites with low N deposition but decreased it at sites with high N deposition. Overall, these results suggest that the effects of nutrient supply on belowground plant properties are context dependent, particularly with regard to background N supply rates, demonstrating that site conditions must be considered when predicting how grassland ecosystems will respond to increased nutrient loading from anthropogenic activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Geostrophic to magnetically-damped turbulence in liquid metal rotating magnetoconvection

Understanding planetary core convection dynamics requires the study of convective flows in which the Coriolis and Lorentz forces attain a leading-order, so-called magnetostrophic balance. Experimental investigations of rotating magnetoconvection (RMC) in the magnetostrophic regime are therefore essential to broadly characterize the properties of local-scale planetary core flow. Toward this end, we present here the first thermovelocimetric measurements of magnetostrophic, liquid metal convection, which are made using liquid gallium as the working fluid, at moderate rotation rates (Ekman numbers 10 -4 ≤ Ek ≤ 10 -5 ) and in the presence of dynamically strong magnetic fields (Elsasser number Λ = 1). Complementary rotating convection (RC) experiments are performed at the same rotation rates to serve as reference cases. Our RMC velocity measurements adequately follow a geostrophic turbulent scaling for cases in which local-scale convective inertial forces exceed the Lorentz forces in the fluid bulk. In cases where Lorentz forces exceed local-scale inertia (local or convective interaction parameter N ℓ or N C ≳ 3), the root-mean-square RMC velocities are magnetically damped, yielding values below the geostrophic turbulent RC scaling prediction. An enhancement in heat transfer is observed, which we attribute to the increased coherence of vertically aligned magnetostrophic convective flow. Finally, our results and comparisons to dynamo simulations suggest that the system is in the strong-field regime, where convection-scale flows are magnetically damped with N C ≳ 3).

Convective turbulence↗
DOE OSTI2024

Nitrogen addition alters the relative importance of roots and mycorrhizal hyphae in regulating soil organic carbon accumulation in a karst forest

Plant belowground carbon (C) inputs from roots and associated mycorrhizal hyphae are increasingly recognized as critical drivers impacting soil organic C (SOC) pool. However, whether roots and mycorrhizal hyphae differentially regulate SOC formation and accumulation under elevated nitrogen (N) deposition remains to be addressed. Using an ingrowth-core technique, the relative contributions of roots and mycorrhizal hyphae to SOC accumulation were distinguished and quantified in a karst forest receiving three levels of N additions (control (0 kg N ha -1 yr -1 ), low N (150 kg N ha -1 yr -1 ) and high N (300 kg N ha -1 yr -1 )). Here our results showed that N addition stimulated SOC accumulation (indicated by the increase of both bulk SOC and mineral associated organic C fraction) influenced by both roots and hyphae, especially for higher N doses. Moreover, N addition increased the contribution of the root effect relative to the hyphal effect in the SOC accrual. The correlation analysis showed that, for the hyphal effect, the change in SOC content was solely and positively correlated with the change in protective mineral phases of SOC, but not with the microbial necromass. In contrast, for the root effect, the change in SOC content was significantly and positively correlated with the changes in both soil microbial C pump efficacy and protective mineral phases of SOC. These results suggest that roots and mycorrhizal hyphae may influence the accumulation of microbial necromass and the formation of mineral-organic associations in a different magnitude under enhanced N supply. These findings advance our understanding of the root-mycorrhizal interactions in mediating SOC dynamics in forests under future N deposition scenarios.

54 ENVIRONMENTAL SCIENCES↗