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NASA NTRS1991

Hydrotropism and its interaction with gravitropism in maize roots

We have partially characterized root hydrotropism and its interaction with gravitropism in maize (Zea mays L.). Roots of Golden Cross Bantam 70, which require light for orthogravitropism, showed positive hydrotropism; bending upward when placed horizontally below a hydrostimulant (moist cheesecloth) in 85% relative humidity (RH) and in total darkness. However, the light-exposed roots of Golden Cross Bantam 70 or roots of a normal maize cultivar, Burpee Snow Cross, showed positive gravitropism under the same conditions; bending downward when placed horizontally below the hydrostimulant in 85% RH. Light-exposed roots of Golden Cross Bantam 70 placed at 70 degrees below the horizontal plane responded positively hydrotropically, but gravitropism overcame the hydrotropism when the roots were placed at 45 degrees below the horizontal. Roots placed vertically with the tip down in 85% RH bent to the side toward the hydrostimulant in both cultivars, and light conditions did not affect the response. Such vertical roots did not respond when the humidity was maintained near saturation. These results suggest that hydrotropic and gravitropic responses interact with one another depending on the intensity of one or both factors. Removal of the approximately 1.5 millimeter root tip blocked both hydrotropic and gravitropic responses in the two cultivars. However, removal of visible root tip mucilage did not affect hydrotropism or gravitropism in either cultivar.

NASA Program Space Biology↗
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 OSTI2020

Super resolution for root imaging

Premise High‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection. An effective super‐resolution (SR) algorithm is therefore needed for overcoming the resolution limitations of sensors, reducing storage space requirements, and boosting the performance of subsequent analyses. Methods We propose an SR framework for enhancing images of plant roots using convolutional neural networks. We compare three alternatives for training the SR model: (i) training with non‐plant‐root images, (ii) training with plant‐root images, and (iii) pretraining the model with non‐plant‐root images and fine‐tuning with plant‐root images. The architectures of the SR models were based on two state‐of‐the‐art deep learning approaches: a fast SR convolutional neural network and an SR generative adversarial network. Results In our experiments, we observed that the SR models improved the quality of low‐resolution images of plant roots in an unseen data set in terms of the signal‐to‐noise ratio. We used a collection of publicly available data sets to demonstrate that the SR models outperform the basic bicubic interpolation, even when trained with non‐root data sets. Discussion The incorporation of a deep learning–based SR model in the imaging process enhances the quality of low‐resolution images of plant roots. We demonstrate that SR preprocessing boosts the performance of a machine learning system trained to separate plant roots from their background. Our segmentation experiments also show that high performance on this task can be achieved independently of the signal‐to‐noise ratio. We therefore conclude that the quality of the image enhancement depends on the desired application.

Ruiz‐Munoz, Jose F.↗
DOE OSTI2010

Dynamics of fine roots in five Chinese temperate forests

Quantifying fine root production and mortality is crucially needed for modeling forest ecosystem carbon cycling, but the fine root dynamics are poorly understood in Chinese temperate forests. We used a minirhizotron method to investigate spatial and temporal dynamics of fine roots (diameter ≤ 2 mm) in five representative temperate forests in northeastern China. Our specific objectives were to: (1) compare standing crop, production and mortality of fine roots among the five stands; (2) examine fine root phenology for the stands; and (3) examine vertical distribution patterns of fine roots for the stands. Fine root dynamics were significantly affected by forest type, soil layer, sampling time and their interactions. The mean values of fine root standing crop varied from 8.0 to 12.8 mm cm-2; those of production varied from 0.027 to 0.046 mm cm-2 d-1; and those of mortality varied from 0.013 to 0.024 mm cm-2 d-1. All stands had a similar seasonal “sinusoidal” pattern of fine root standing crop, and a “unimodal” pattern of production. However, the seasonal dynamics of the mortality was unsynchronized with that of the production. The minimum values of standing crop, production and mortality occurred in March for all stands, while the maximum values and occurring time differed among forest types. The occurrence of the maximum standing crop varied from DOY (day of year) 222 for the oak stand to DOY 271 for the aspen-birch stand; that of the maximum production varied from DOY 188 for the pine and hardwood stands to DOY 239 for the larch stand; and that of the maximum mortality varied from DOY 222 for the oak and aspen-birch stands to DOY 287 for the larch stand. The standing crop, production and mortality of fine roots tended to decrease with soil depths, of which the relative contribution at 0 -10 cm depth averaged 38%, 46%, and 58% of total, respectively. The fact that the production was approximate twice as great as the mortality suggested a net carbon input to the soil of these forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Influence of living grass Roots and endophytic fungal hyphae on soil hydraulic properties

Soil hydraulic properties are often estimated based on laboratory data or pedotransfer functions dependent on soil physical properties, which often do not consider potential impacts of soil roots or fungal hyphae. Here, we first review current knowledge of how these soil biotic components affect hydraulic properties, then we conducted laboratory experiments to specifically test if the presence of roots and mycorrhizal fungi had a significant effect on the hydraulic properties of two soils with contrasting textures: Flint sand and Hamblen silt loam. Soil cores were seeded with (Panicum virgatum) and grown in a greenhouse over three separate growth periods. The endophytic fungus Serendipita indica was injected as liquid inoculant into designated mycorrhizal cores. Saturated hydraulic conductivity (K sat ) measurements were made with a constant head permeameter, and soil water retention curves were obtained by the evaporation method, supplemented at the dry end for Hamblen silt loam with water activity meter data. Retention curve parameters were obtained by fitting the van Genuchten equation to the resulting measurements. Mean root volume ratios were higher in the mycorrhizal inoculated treatment than in the uninoculated treatment for both soils. For Flint sand, analysis of variance revealed that K sat was reduced by the presence of roots as compared to bare soil. This was likely due to roots clogging soil pores. Results also indicated the presence of roots changed the shape of the water retention curve for Flint sand by increasing water content at saturation and by reducing the slope of the curve. These changes suggested roots created additional porosity and broadened the pore-size distribution. The presence of mycorrhizal fungi accentuated the root effects. The influence of roots and mycorrhizal fungi on hydraulic properties was less obvious for the Hamblen silt loam, as none of the treatments differed from each other at p < 0.05. The results highlight the necessity to consider the impact of root and fungal structures on models of soil hydraulic properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Elevated CO2 and plant species diversity interact to slow root decomposition

Changes in plant species diversity can result in synergistic increases in decomposition rates, while elevated atmospheric CO2 can slow the decomposition rates; yet it remains unclear how diversity and changes in atmospheric CO2 may interact to alter root decomposition. To investigate how elevated CO2 interacts with changes in root-litter diversity to alter decomposition rates, we conducted a 120-day laboratory incubation. Roots from three species (Trifolium repens, Lespedeza cuneata, and Festuca pratense) grown under ambient or elevated CO2 were incubated individually or in combination in soils that were exposed to ambient or elevated CO2 for five years. Our experiment resulted in two main findings: (1) Roots from T. repens and L. cuneata, both nitrogen (N) fixers, grown under elevated CO2 treatments had significantly slower decomposition rates than similar roots grown under ambient CO2 treatments; but the decomposition rate of F. pratense roots (a non-N-fixing species) was similar regardless of CO2 treatment. (2) Roots of the three species grown under ambient CO2 and decomposed in combination with each other had faster decomposition rates than when they were decomposed as single species. However, roots of the three species grown under elevated CO2 had similar decomposition rates when they were incubated alone or in combination with other species. These data suggest that if elevated CO2 reduces the root decomposition rate of even a few species in the community, it may slow root decomposition of the entire plant community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Assessing the Effect of a Deep‐Rooted Grass on Belowground Carbon Storage in Cultivated Land: Insights From a Multi‐Site US Study

Agriculture depletes soil organic carbon (SOC), partly due to the exclusion of deep-rooted perennials. Reintroducing deep-rooted perennials to cultivated land may help to mitigate SOC loss. We quantified the effect of deep roots on SOC by comparing 8 to 30 year-old stands of switchgrass ( Panicum virgatum L .) with paired annual row crop fields at 12 sites across the central and eastern USA. We hypothesized that switchgrass would store more root C and SOC than neighboring shallow-rooted annual crops, and that these effects would extend deeper than 30 cm. We also evaluated whether switchgrass stimulates decomposition of SOC at depth using radiocarbon ( 14 C). Finally, we explored whether the effect of switchgrass on SOC is moderated by soil chemical and physical properties. While the effect of switchgrass on SOC in the surface 100 cm was positive at most sites, the average effect was not statistically significant (difference in SOC = 0.6 kg C m −2 [95% CI −0.8 to +1.9 kg C m −2 ]). By contrast, we found that root C was consistently more abundant under switchgrass, yielding an estimated additional 0.6 kg C m −2 in the surface 100 cm of soil [95% CI +0.5 to +0.7 kg C m −2 ]. 14 C measurements suggested that root C inputs were adding to existing SOC without stimulating decomposition. The effect of switchgrass on belowground C was not strongly related to any of the soil properties that we evaluated. Our observations show that root C can contribute substantially to belowground C stocks when deep-rooted perennials replace shallow-rooted crops.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Phloem unloading via the apoplastic pathway is essential for shoot distribution of root-synthesized cytokinins

Abstract Root-synthesized cytokinins are transported to the shoot and regulate the growth, development, and stress responses of aerial tissues. Previous studies have demonstrated that Arabidopsis (Arabidopsis thaliana) ATP binding cassette (ABC) transporter G family member 14 (AtABCG14) participates in xylem loading of root-synthesized cytokinins. However, the mechanism by which these root-derived cytokinins are distributed in the shoot remains unclear. Here, we revealed that AtABCG14-mediated phloem unloading through the apoplastic pathway is required for the appropriate shoot distribution of root-synthesized cytokinins in Arabidopsis. Wild-type rootstocks grafted to atabcg14 scions successfully restored trans-zeatin xylem loading. However, only low levels of root-synthesized cytokinins and induced shoot signaling were rescued. Reciprocal grafting and tissue-specific genetic complementation demonstrated that AtABCG14 disruption in the shoot considerably increased the retention of root-synthesized cytokinins in the phloem and substantially impaired their distribution in the leaf apoplast. The translocation of root-synthesized cytokinins from the xylem to the phloem and the subsequent unloading from the phloem is required for the shoot distribution and long-distance shootward transport of root-synthesized cytokinins. This study revealed a mechanism by which the phloem regulates systemic signaling of xylem-mediated transport of root-synthesized cytokinins from the root to the shoot.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

DIRT/3D: 3D root phenotyping for field-grown maize ( Zea mays )

The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs, and to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major bottleneck to achieving these improvements is high-throughput phenotyping to quantify root phenotypes of field-grown roots. We address this bottleneck with Digital Imaging of Root Traits (DIRT)/3D, an image-based 3D root phenotyping platform, which measures 18 architecture traits from mature field-grown maize (Zea mays) root crowns (RCs) excavated with the Shovelomics technique. DIRT/3D reliably computed all 18 traits, including distance between whorls and the number, angles, and diameters of nodal roots, on a test panel of 12 contrasting maize genotypes. The computed results were validated through comparison with manual measurements. Overall, we observed a coefficient of determination of r 2 > 0.84 and a high broad-sense heritability of H$_{mean}^{2}$ < 0.6 for all but one trait. The average values of the 18 traits and a developed descriptor to characterize complete root architecture distinguished all genotypes. DIRT/3D is a step toward automated quantification of highly occluded maize RCs. Therefore, DIRT/3D supports breeders and root biologists in improving carbon sequestration and food security in the face of the adverse effects of climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Development of an Experimental Approach to Achieve Spatially Resolved Plant Root-Associated Metaproteomics Using an Agar-Plate System

Plant–microbe interactions in the rhizosphere play a vital role in plant health and productivity. The composition and function of root-associated microbiomes is strongly influenced by their surrounding environment, which is often customized by their host. How microbiomes change with respect to space and time across plant roots remains poorly understood, and methodologies that facilitate spatiotemporal metaproteomic studies of root-associated microbiomes are yet to be realized. Here, we developed a method that provides spatially resolved metaproteome measurements along plant roots embedded in agar-plate culture systems, which have long been used to study plants. Spatially defined agar “plugs” of interest were excised and subsequently processed using a novel peptide extraction method prior to metaproteomics, which was used to infer both microbial community composition and function. As a proof-of-principle, a previously studied 10-member community constructed from a Populus root system was grown in an agar plate with a 3-week-old Populus trichocarpa plant. Metaproteomics was performed across two time points (24 and 48 h) for three distinct locations (root base, root tip, and a region distant from the root). The spatial resolution of these measurements provides evidence that microbiome composition and expression changes across the plant root interface. Interrogation of the individual microbial proteomes revealed functional profiles related to their behavioral associations with the plant root, in which chemotaxis and augmented metabolism likely supported predominance of the most abundant member. This study demonstrated a novel peptide extraction method for studying plant agar-plate culture systems, which was previously unsuitable for (meta)proteomic measurements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Transgenic Mixed‐Linkage‐Glucan Enhancement Affects Root Characteristics and Decomposition in Soils of Contrasting Vegetation History

ABSTRACT Development of transgenic bioenergy sorghum [ Sorghum bicolor (L.) Moench] with increased contents of mixed‐linkage (1,3;1,4)‐β‐glucan (MLG) is an important step towards enhancing quality of bioenergy feedstocks. Since MLG‐enhancement leads to greater biomass digestibility, our overarching hypothesis is that root residues of MLG‐enhanced plants may be more readily decomposed in the soil, potentially creating new opportunities for optimizing soil carbon (C) sequestration, nutrient cycling, and overall agricultural sustainability. The study examined morphological, chemical, and enzymatic characteristics of fine and coarse roots of four bioenergy sorghum genotypes. Then, we incubated the roots within soils with contrasting vegetation histories while measuring C mineralization, microbial biomass C (MBC), and activity of hydrolytic enzymes and calculating vector length and vector angle enzymatic stoichiometry parameters. The results indicated that MLG‐enhancing transformations increased root total nitrogen (N) contents, decreased C/N ratios, and were associated with higher MLG concentrations in fine than in coarse roots. Incubations with transgenic roots led to 16%–38% higher MBC and 19%–41% lower microbial metabolic quotient (qCO 2 ). While enzyme activity differed markedly among the studied genotypes, it did not directly respond to MLG levels in root tissues. The increase in MBC without concurrent increases in C mineralization or hydrolytic enzyme activities in transgenic genotypes suggests that MLG enhancement promoted microbial anabolic retention of root‐derived C rather than stimulating catabolic decomposition. Enzymatic vector results indicated that these parameters reflect a variety of drivers behind microbial enzyme production, including availability of specific substrates, such as MLG here, and/or deficiency in specific nutrients, such as phosphorus (P). The study confirms the positive impacts from the roots of engineered MLG‐enhanced bioenergy plants on soil microbial activity and highlights the interactive influences on the MLG‐enhancement effects from root size and inherent soil properties.

Mahmoodabadi, Majid [Department of Plant, Soil, an↗
DOE OSTI2020

Conifers depend on established roots during drought: results from a coupled model of carbon allocation and hydraulics

Trees may survive prolonged droughts by shifting water uptake to reliable water sources, but it is unknown if the dominant mechanism involves activating existing roots or growing new roots during drought, or some combination of the two. To gain mechanistic insights on this unknown, a dynamic root-hydraulic modeling framework was developed that set up a feedback between hydraulic controls over carbon allocation and the role of root growth on soil–plant hydraulics. The new model was tested using a 5 yr drought/heat field experiment on an established pi~non-juniper stand with root access to bedrock groundwater. Owing to the high carbon cost per unit root area, modeled trees initialized without adequate bedrock groundwater access experienced potentially lethal declines in water potential, while all of the experimental trees maintained nonlethal water potentials. Simulated trees were unable to grow roots rapidly enough to mediate the hydraulic stress, particularly during warm droughts. Alternatively, modeled trees initiated with root access to bedrock groundwater matched the hydraulics of the experimental trees by increasing their water uptake from bedrock groundwater when soil layers dried out. Therefore, the modeling framework identified a critical mechanism for drought response that required trees to shift water uptake among existing roots rather than growing new roots.

Mackay, D. Scott↗
DOE OSTI2023

The soil pore structure encountered by roots affects plant‐derived carbon inputs and fate

Summary Plant roots are the main supplier of carbon (C) to the soil, the largest terrestrial C reservoir. Soil pore structure drives root growth, yet how it affects belowground C inputs remains a critical knowledge gap. By combining X‐ray computed tomography with 14 C plant labelling, we identified root–soil contact as a previously unrecognised influence on belowground plant C allocations and on the fate of plant‐derived C in the soil. Greater contact with the surrounding soil, when the growing root encounters a pore structure dominated by small (< 40 μm Ø) pores, results in strong rhizodeposition but in areas of high microbial activity. The root system of Rudbeckia hirta revealed high plasticity and thus maintained high root–soil contact. This led to greater C inputs across a wide range of soil pore structures. The root–soil contact Panicum virgatum , a promising bioenergy feedstock crop, was sensitive to the encountered structure. Pore structure built by a polyculture, for example, restored prairie, can be particularly effective in promoting lateral root growth and thus root–soil contact and associated C benefits. The findings suggest that the interaction of pore structure with roots is an important, previously unrecognised, stimulus of soil C gains.

Plant Sciences↗
DOE OSTI2024

Variation in forest root image annotation by experts, novices, and AI

Abstract Background The manual study of root dynamics using images requires huge investments of time and resources and is prone to previously poorly quantified annotator bias. Artificial intelligence (AI) image-processing tools have been successful in overcoming limitations of manual annotation in homogeneous soils, but their efficiency and accuracy is yet to be widely tested on less homogenous, non-agricultural soil profiles, e.g., that of forests, from which data on root dynamics are key to understanding the carbon cycle. Here, we quantify variance in root length measured by human annotators with varying experience levels. We evaluate the application of a convolutional neural network (CNN) model, trained on a software accessible to researchers without a machine learning background, on a heterogeneous minirhizotron image dataset taken in a multispecies, mature, deciduous temperate forest. Results Less experienced annotators consistently identified more root length than experienced annotators. Root length annotation also varied between experienced annotators. The CNN root length results were neither precise nor accurate, taking ~ 10% of the time but significantly overestimating root length compared to expert manual annotation ( p = 0.01). The CNN net root length change results were closer to manual ( p = 0.08) but there remained substantial variation. Conclusions Manual root length annotation is contingent on the individual annotator. The only accessible CNN model cannot yet produce root data of sufficient accuracy and precision for ecological applications when applied to a complex, heterogeneous forest image dataset. A continuing evaluation and development of accessible CNNs for natural ecosystems is required.

Handy, Grace↗
DOE OSTI2024

In-vivo Raman microspectroscopy reveals differential nitrate concentration in different developmental zones in Arabidopsis roots

Abstract Background Nitrate (NO 3 − ) is one of the two major forms of inorganic nitrogen absorbed by plant roots, and the tissue nitrate concentration in roots is considered important for optimizing developmental programs. Technologies to quantify the expression levels of nitrate transporters and assimilating enzymes at the cellular level have improved drastically in the past decade. However, a technological gap remains for detecting nitrate at a high spatial resolution. Using extraction-based methods, it is challenging to reliably estimate nitrate concentration from a small volume of cells (i.e., with high spatial resolution), since targeting a small or specific group of cells is physically difficult. Alternatively, nitrate detection with microelectrodes offers subcellular resolution with high cell specificity, but this method has some limitations on cell accessibility and detection speed. Finally, optical nitrate biosensors have very good ( in-vivo ) sensitivity (below 1 mM) and cellular-level spatial resolution, but require plant transformation, limiting their applicability. In this work, we apply Raman microspectroscopy for high-dynamic range in-vivo mapping of nitrate in different developmental zones of Arabidopsis thaliana roots in-situ . Results As a proof of concept, we have used Raman microspectroscopy for in-vivo mapping of nitrate content in roots of Arabidopsis seedlings grown on agar media with different nitrate concentrations. Our results revealed that the root nitrate concentration increases gradually from the meristematic zone (~ 250 µm from the root cap) to the maturation zone (~ 3 mm from the root cap) in roots grown under typical growth conditions used for Arabidopsis, a trend that has not been previously reported. This trend was observed for plants grown in agar media with different nitrate concentrations (0.5–10 mM). These results were validated through destructive measurement of nitrate concentration. Conclusions We present a methodology based on Raman microspectroscopy for in-vivo label-free mapping of nitrate within small root tissue volumes in Arabidopsis. Measurements are done in-situ without additional sample preparation. Our measurements revealed nitrate concentration changes from lower to higher concentration from tip to mature root tissue. Accumulation of nitrate in the maturation zone tissue shows a saturation behavior. The presented Raman-based approach allows for in-situ non-destructive measurements of Raman-active compounds.

Fernández González, Alma↗
DOE OSTI2021

Fine-root traits from common tree species in Puerto Rico before and after Hurricane María (2017-2018)

This dataset is a compilation of root trait measurements from common tree species in the Luquillo Experimental Forest in Puerto Rico taken in February 2017 (before Hurricane María), and in February 2018 (after the hurricane). This dataset is being used on a publication called "Tradeoffs in phosphorus acquisition strategies of five tree species in a tropical forest of Puerto Rico", where we describe belowground P-acquisition strategies of five common tree species (two pioneers and three non-pioneers) growing in the lowland tropical wet forests of Puerto Rico. Additionally, we used the unique opportunity of two consecutive hurricanes that passed over the island (Irma and Maria) to compare root traits before and after the hurricanes to determine which traits were the most responsive and whether such disturbance affected root trait relationships and trade-offs. For this, we sampled trees from EV1, SB2, and NGEE Tropics' plots EVV and EVR in 2017 (before hurricanes) and 2018 (after hurricanes). Morphological fine-root traits include root length, diameter, and SRL. Root architectural traits includes root branching ratio and intensity. Root physiological trait measured includes phosphatase activity, and root microbial association trait measured includes percentage mycorrhizal colonization. Chemistry data includes root phosphorus concentration, soil available, and organic phosphorus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Impacts of Nitrogen Rate and Landscape Position on Soils and Switchgrass Root Growth Parameters

Core Ideas Nitrogen rate did not affect soil properties for Oklahoma, South Dakota, and Virginia. Landscape position affected soil properties under higher slope. Nitrogen rate affected root N, surface area, and weight for the total profile. Landscape position affected the root C and N. Switchgrass roots can increase C accumulation and reduce risk of N loss in soils. ABSTRACT Switchgrass ( Panicum virgatum L.) has been recognized as a potential bioenergy feedstock, and can positively impact soils and the environment. The experimental sites were established in 2008 at three locations with each in Oklahoma (OK), South Dakota (SD), and Virginia (VA) to assess the impacts of N fertilization rate (N rate; low, 0 kg ha −1 ; high, 112 kg ha −1 ) and landscape position (shoulder, backslope, and footslope) on select soil properties and root growth parameters. Data indicate that N rate did not affect soil bulk density (BD), pH, electrical conductivity (EC), soil organic carbon (SOC), and total nitrogen (TN) for any of five depths. Landscape position impacted some of these properties by depth, depending on location. The N rate influenced root weight (RW), root surface area (RSA), and root total nitrogen (RTN) for the total profile (0–100‐cm depth) depending on local site conditions. The landscape position impacted RW, root total carbon (RTC), and RTN for total profile according to different site conditions. The interactions of landscape position by N rate on switchgrass root parameters were significant. The findings in this study indicate that the root system of switchgrass could improve soils and increase C accumulation and reduce the risk of N loss to benefit the environment.

09 BIOMASS FUELS↗
DOE OSTI2016

Assessment of potential greenhouse gas mitigation from changes to crop root mass and architecture

Reducing (and eventually reversing) the increase in greenhouse gases (GHGs) in the atmosphere due to human activities, and thus reducing the extent and severity of anthropogenic climate change, is one of the great challenges facing humanity. While most of the man-caused increase in GHGs has been due to fossil fuel use, land use (including agriculture) currently accounts for about 25% of total GHG emissions and thus there is a need to include emission reductions from the land use sector as part of an effective climate change mitigation strategy. In addition, analyses included in the recent IPCC 5th Climate Change Assessment report suggests that it may not be possible to achieve large enough emissions reductions in the energy, transport and industrial sectors alone to stabilize GHG concentrations at a level commensurate with a less than 2°C global average temperature increase, without the help of a substantial CO 2 sink (i.e., atmospheric CO 2 removal) from the land use sector. One of the potential carbon sinks that could contribute to this goal is increasing C storage in soil organic matter on managed lands. This report details a preliminary scoping analysis, to assess the potential agricultural area in the US – where appropriate soil, climate and land use conditions exist – to determine the land area on which ‘improved root phenotype’ crops could be deployed and to evaluate the potential long-term soil C storage, given a set of ‘bounding scenarios’ of increased crop root input and/or rooting depth for major crop species (e.g., row crops (corn, sorghum, soybeans), small grains (wheat, barley, oats), and hay and pasture perennial forages). The enhanced root phenotype scenarios assumed 25, 50 and 100% increase in total root C inputs, in combination with five levels of modifying crop root distributions (i.e., no change and four scenarios with increasing downward shift in root distributions). We also analyzed impacts of greater root production on the soil-crop nitrogen balance, from the standpoint of increased need for additional N inputs and consequences for increased N 2 O flux, as well as potential impacts if more and deeper roots contributed to reduced N leaching. In the enhanced root phenotype scenarios, the implicit assumption was that increases in overall plant production could be achieved (e.g., through increased CO 2 assimilation, greater growth efficiency) without reducing the harvested yield – that is, we did not include potential leakage and land substitution effects from potential decreased crop yield in the analysis.

54 ENVIRONMENTAL SCIENCES↗