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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Development of a Unified Taxonomy for HVAC System Faults

Detecting and diagnosing HVAC faults is critical for maintaining building operation performance, reducing energy waste, and ensuring indoor comfort. An increasing deployment of commercial fault detection and diagnostics (FDD) software tools in commercial buildings in the past decade has significantly increased buildings’ operational reliability and reduced energy consumption. A massive amount of data has been generated by the FDD software tools. However, efficiently utilizing FDD data for ‘big data’ analytics, algorithm improvement, and other data-driven applications is challenging because the format and naming conventions of those data are very customized, unstructured, and hard to interpret. This paper presents the development of a unified taxonomy for HVAC faults. A taxonomy is an orderly classification of HVAC faults according to their characteristics and causal relations. The taxonomy includes fault categorization, physical hierarchy, fault library, relation model, and naming/tagging scheme. The taxonomy employs both a physical hierarchy of HVAC equipment and a cause-effect relationship model to reveal the root causes of faults in HVAC systems. A structured and standardized vocabulary library is developed to increase data representability and interpretability. The developed fault taxonomy can be used for HVAC system ‘big data’ analytics such as HVAC system fault prevalence analysis or the development of an HVAC FDD software standard. A common type of HVAC equipment-packaged rooftop unit (RTU) is used as an example to demonstrate the application of the developed fault taxonomy. Two RTU FDD software tools are used to show that after mapping FDD data according to the taxonomy, the meta-analysis of the multiple FDD reports is possible and efficient.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Stability of a Mixed–Valence Hydrous Iron–Rich Oxide: Implications for Water Storage and Dynamics in the Deep Lower Mantle

Incorporation of water into mantle compositions can have significant effects on the phase relations in the systems. Here, we synthesized an iron-rich hexagonal hydrous phase (referred to as "HH1-phase") under the high pressure-temperature (P-T) conditions of the deep lower mantle and determined the crystal structure of the HH1-phase at 79 GPa using the multigrain crystallography method. The chemical formula obtained was Fe 12.76 O 18 H x (x ~ to 4.5) in the Fe-O-H system. To demonstrate the role of HH1-phase for water storage in multicomponent systems relevant to mantle compositions, we investigated the stability of HH1-phase in both MgO-rich pyrolitic and SiO 2 -rich basaltic compositions. Our results indicate that the HH1-phase serves as major water storage in a pyrolitic composition, whereas the Al-rich CaCl 2 -type δ-phase and SiO 2 phase are major water storage phases in a SiO 2 -rich basaltic composition. Incorporation of considerable amounts of SiO 2 , MgO, and Al 2 O 3 into the HH1-phase expands its stability field from 98 GPa in the Fe-Al-O-H system to at least 108 GPa (corresponding to similar to 2,400 km depth) in the Mg-Si-Al-Fe-O-H system. Plumes of hot upwelling rock rooted at the base of the lower mantle have been proposed as a possible origin of hotspot volcanoes. The hydrous Fe-rich HH1-phase, if included into the material of upwelling plumes, will decompose on its rising to the upper part of the lower mantle and release water. Our results should provide constraints on water storage in the deep lower mantle and have implications for deep mantle dynamics.

58 GEOSCIENCES↗
DOE OSTI2022

AMS Thermal Cooling System (Final Report)

The Alpha Magnetic Spectrometer (AMS) is a U.S. Department of Energy-sponsored particle physics experiment on the International Space Station (ISS). AMS is exploring some of the most fundamental questions in physics such as understanding dark matter, antimatter, the origin of cosmic rays and their characteristics as well as searching for new physics phenomena in the universe. It has recorded more than 200 billion cosmic rays since its launch in May 2011. Over time, anomalies associated with the dedicated cooling system of the AMS Silicon Tracker system were observed, leading to the discovery of progressive deterioration in the functioning of the cooling system's four redundant pumps. The Tracker is crucial to the scientific mission of AMS, as it is the only subdetector that can distinguish matter from antimatter. This report details the successful program of work for the installation of the Upgraded Tracker Thermal Pump System (UTTPS) on AMS. This program included: identifying the root cause of deterioration in the original pumps; design, production, testing, and integration of the new UTTPS cooling system; launch of the UTTPS to ISS; installation of the UTTPS in AMS across a series of four complex extra-vehicular activities (EVAs); and establishment of a dedicated Flight Simulator Laboratory to test the performance of the UTTPS under various thermal conditions. This program was critical to the success of the AMS experiment, and its successful completion will enable AMS to continue taking data through 2030.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Rays for Roots - Integrating Backscatter X-Ray Phenotyping, Modeling and Genetics to Increase Carbon Sequestration and Switchgrass Resource Use (Final Report)

To increase carbon (C) deposition in the soil and enhance crop resource use efficiency, characterizing root form and function is essential. Several root and soil traits have been linked to increased root-to-soil C transfer. Technology that could provide high-resolution characterization of many of these traits in field conditions would revolutionize our ability to study and understand how to increase C sequestration. In this effort, we developed an initial early prototype backscatter X-ray system for non-destructive imaging of root traits. We collected initial backscatter X-ray data in field and lab settings and carried out early analysis of these data. Along with this prototype, we also developed a suite of root phenotyping approaches including advanced minirhizotron image analysis, soil core imaging, and mesocosm imaging. Minirhizotron (MR) tubes are clear tubes inserted into the soil in the field and used to image roots and the surrounding soil. Our team has developed deep learning-based methods that can segment roots from soil that can learn from imprecise image-level labels. The ability to learn or fine-tune our deep learning algorithms from image-level labels allows easier and faster application of these approaches to new locations and new plant species. We have successfully implemented and applied our MR analysis approaches to thousands of switchgrass MR images collected across geographical regions. An advantage of MR imaging is the ability to collect root and soil images over time. Our soil core analysis included collecting hundreds of soil core samples from harvested switchgrass fields and imaging these cores with both X-ray CT and backscatter X-ray imaging. Initial segmentation approaches for the X-ray CT images of these cores have been developed and applied. An advantage of soil core analysis is that it preserves the three-dimensional structures of the roots and soil in the core collected. Our group also developed photogrammetry-based mesocosm root imaging and phenotyping approaches. In this approach, a plant was grown in a large mesocosm with a three-dimensional grid of thin supporting lines inserted throughout the mesocosm. After the plant (and, correspondingly, the root architecture is grown and established) the soil media was removed and the supporting lines approximately preserved the three-dimensional root architecture. Then, we applied photogrammetry techniques to create a three-dimensional digital representation of the root architecture for which we developed analysis algorithms including skeletonization. We carried out our phenotyping development with powerful switchgrass resources and physiological and agroecosystem modeling to deliver novel technology. This project contributes to multiple ARPA-E missions including reduction of foreign imports of energy, reduction of energy-related emissions including greenhouse gases, and ensuring that the United States maintains a technological lead in developing and deploying advanced energy technology. Furthermore, the developed tools could transform public and private plant breeding and could be broadly applicable to other crops and, potentially, other application areas. Our team of engineers, plant and soil scientists, and modelers i) developed an early prototype backscatter X-ray platform that can operate in field conditions; ii) developed a suite of root phenotyping and characterization approaches as described above; iii) developed and carried out plant biology and physiology roots studies and; iv) developed and implemented mechanistic physiological modeling.

42 ENGINEERING↗
DOE OSTI2022

Important Roles of Thiols in Methylmercury Uptake and Translocation by Rice Plants

We report the bioaccumulation of the neurotoxin methylmercury (MeHg) in rice is a significant concern due to its potential risk to humans. Thiols have been known to affect MeHg bioavailability in microorganisms, but how thiols influence MeHg accumulation in rice plants remains unknown. Here, we investigated effects of common low-molecular-weight thiols, including cysteine (Cys), glutathione (GSH), and penicillamine (PEN), on MeHg uptake and translocation by rice plants. Results show that rice roots can rapidly take up MeHg, and this process is influenced by the types and concentrations of thiols in the system. The presence of Cys facilitated MeHg uptake by roots and translocation to shoots, while GSH could only promote MeHg uptake, but not translocation, by roots. Conversely, PEN significantly inhibited MeHg uptake and translocation to shoots. Using labeled 13 Cys assays, we also found that MeHg uptake was coupled with Cys accumulation in rice roots. Moreover, analyses of comparative transcriptomics revealed that key genes associated with metallothionein and SULTR transporter families may be involved in MeHg uptake. These findings provide new insights into the uptake and translocation of MeHg in rice plants and suggest potential roles of thiol attributes in affecting MeHg bioavailability and bioaccumulation in rice.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

PIPER: Performance Insight for Programmers and Exascale Runtimes (Final Technical Report)

This project concentrated on the development of novel performance tools and analysis techniques for large scale parallel systems and applications, eventually targeting exascale platforms. Activities conducted included work to novel root cause detection approaches and an auto-tuning framework for parallel systems. The work has led to several software solutions, which are available as open source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Mesorhizobium japonicum quorum sensing circuit that involves three linked genes and an unusual acyl-homoserine lactone signal

ABSTRACT Members of the genus Mesorhizobium, which are core components of the rhizosphere and specific symbionts of legume plants, possess genes for acyl-homoserine lactone (AHL) quorum sensing (QS). Here we show Mesorhizobium japonicum MAFF 303099 (formerly M. loti ) synthesizes and responds to N -[(2 E , 4 E )-2,4-dodecadienoyl] homoserine lactone (2 E, 4 E- C 12:2 -HSL). We show that the 2 E, 4 E- C 12:2 -HSL QS circuit involves one of four luxR-luxI -type genes found in the sequenced genome of MAFF 303099. We refer to this circuit, which appears to be conserved among Mesorhizobium species, as R1-I1. We show that two other Mesorhizobium strains also produce 2 E, 4 E- C 12:2 -HSL. The 2 E, 4 E- C 12:2 -HSL is unique among known AHLs in its arrangement of two trans double bonds. The R1 response to 2 E, 4 E- C 12:2 -HSL is extremely selective in comparison with other LuxR homologs, and the trans double bonds appear critical for R1 signal recognition. Most well-studied LuxI-like proteins use S -adenosylmethionine and an acyl-acyl carrier protein as substrates for synthesis of AHLs. Others that form a subgroup of LuxI-type proteins use acyl-coenzyme A substrates rather than acyl-acyl carrier proteins. I1 clusters with the acyl-coenzyme A-type AHL synthases. We show that a gene linked to the I1 AHL synthase is involved in the production of the QS signal. The discovery of the unique I1 product enforces the view that further study of acyl-coenzyme A-dependent LuxI homologs will expand our knowledge of AHL diversity. The involvement of an additional enzyme in AHL generation leads us to consider this system a three-component QS circuit. IMPORTANCE We report a Mesorhizobium japonicum quorum sensing (QS) system involving a novel acyl-homoserine lactone (AHL) signal. This system is known to be involved in root nodule symbiosis with host plants. The chemistry of the newly described QS signal indicated that there may be a dedicated cellular enzyme involved in its synthesis in addition to the types known for production of other AHLs. Indeed, we report that an additional gene is required for synthesis of the unique signal, and we propose that this is a three-component QS circuit as opposed to the canonical two-component AHL QS circuits. The signaling system is exquisitely selective. The selectivity may be important when this species resides in the complex microbial communities around host plants and may make this system useful in various synthetic biology applications of QS circuits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

RhizoNet segments plant roots to assess biomass and growth for enabling self-driving labs

Abstract Flatbed scanners are commonly used for root analysis, but typical manual segmentation methods are time-consuming and prone to errors, especially in large-scale, multi-plant studies. Furthermore, the complex nature of root structures combined with noisy backgrounds in images complicates automated analysis. Addressing these challenges, this article introduces RhizoNet, a deep learning-based workflow to semantically segment plant root scans. Utilizing a sophisticated Residual U-Net architecture, RhizoNet enhances prediction accuracy and employs a convex hull operation for delineation of the primary root component. Its main objective is to accurately segment root biomass and monitor its growth over time. RhizoNet processes color scans of plants grown in a hydroponic system known as EcoFAB, subjected to specific nutritional treatments. The root detection model using RhizoNet demonstrates strong generalization in the validation tests of all experiments despite variable treatments. The main contributions are the standardization of root segmentation and phenotyping, systematic and accelerated analysis of thousands of images, significantly aiding in the precise assessment of root growth dynamics under varying plant conditions, and offering a path toward self-driving labs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for understanding these methods generated. Existing Python programming packages for implementing each algorithm are acknowledged, and the model equations necessary for prediction are presented. A case study on a coal-fired power plant’s NO x emission rates is performed, directly comparing each modeling method’s performance on a mutual system. Each model is evaluated by its root mean squared error (RMSE) on out-of-sample future horizon predictions. Optimal hyperparameters are identified using either an exhaustive search or genetic algorithm. The top five model structures of each method are used to recursively predict future NO x emission rates over a 60-step time horizon. The RMSE at each future timestep is determined, and the recursive output prediction trends compared against measurements in time. The GRU neural network is identified as the best candidate for representing the system, demonstrating accurate and stable predictions across the future horizon by all considered models, while satisfactory performance was observed in several of the ARX/NARX formulations. Finally, these efforts have contributed 1) a concise resource of multiple proven dynamic machine learning methods, 2) a practical guide explaining the use of these methods, effectively lowering the “barrier-to-entry” of deploying such models in control systems, 3) a comparison study evaluating each method’s performance on a mutual system, 4) demonstration of accurate multi-timestep emissions modeling suitable for systems-level control, and 5) generalizable results demonstrating the suitability of each method for prediction over a multi-step future horizon to other complex dynamic systems.

42 ENGINEERING↗
DOE OSTI2023

Drought Shifts Sorghum Root Metabolite and Microbiome Profiles and Enriches for Pipecolic Acid

Plant-associated microbial communities shift in composition as a result of environmental perturbations, such as drought. It has been shown that Actinobacteria are enriched in plant roots and rhizospheres during drought stress. However, the correlations between microbiome dynamics and plant response to drought are poorly understood. Here we apply a combination of bacterial community composition analysis and plant metabolite profiling in Sorghum bicolor roots, rhizospheres, and soil during drought and drought recovery to investigate potential contributions of host metabolism to shifts in bacterial composition. Our results provide a detailed view of metabolic shifts across the plant root during drought and show that the response to rewatering differs between root and soil; additionally, we identify drought-responsive metabolites that are highly correlated with the observed changes in Actinobacteria abundance. Furthermore, we find that pipecolic acid is a drought-enriched metabolite in sorghum roots, and that exogenous application of pipecolic acid inhibits root growth. Finally, we show that this activity functions independent of the systemic acquired resistance pathway and has the potential to impact Actinobacterial taxa within the root microbiome.

165 RRNA↗
DOE OSTI2022

N-dependent dynamics of root growth and nitrate and ammonium uptake are altered by the bacterium Herbaspirillum seropedicae in the cereal model Brachypodium distachyon

Nitrogen (N) fixation in cereals by root-associated bacteria is a promising solution for reducing use of chemical N fertilizers in agriculture. However, plant and bacterial responses are unpredictable across environments. We hypothesized that cereal responses to N-fixing bacteria are dynamic, depending on N supply and time. To quantify the dynamics, a gnotobiotic, fabricated ecosystem (EcoFAB) was adapted to analyse N mass balance, to image shoot and root growth, and to measure gene expression of Brachypodium distachyon inoculated with the N-fixing bacterium Herbaspirillum seropedicae. Phenotyping throughput of EcoFAB-N was 25–30 plants h -1 with open software and imaging systems. Herbaspirillum seropedicae inoculation of B. distachyon shifted root and shoot growth, nitrate versus ammonium uptake, and gene expression with time; directions and magnitude depended on N availability. Primary roots were longer and root hairs shorter regardless of N, with stronger changes at low N. At higher N, H. seropedicae provided 11% of the total plant N that came from sources other than the seed or the nutrient solution. The time-resolved phenotypic and molecular data point to distinct modes of action: at 5 mM NH 4 NO 3 the benefit appears through N fixation, while at 0.5 mM NH 4 NO 3 the mechanism appears to be plant physiological, with H. seropedicae promoting uptake of N from the root medium.Future work could fine-tune plant and root-associated microorganisms to growth and nutrient dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hypothetical Sodium-Cooled Fast Reactor Fuel Transport Using the Existing ES-3100

Increased industry interest in increased enrichment fuels is associated with a heightened interest in high-assay low-enriched uranium (HALEU)-based systems, as novel designs look to take root as alternatives to traditional LWRs. Increased enrichment with novel reactors can produce designs that, in theory and in some historical experience, are capable of operation at increased burnups, higher energy density, and other unique features compared to conventional LWRs. As part of a Department of Energy (DOE) initiative to increase the availability of HALEU fuel, initial funding sourced from the Inflation Reduction Act of 2022 (H.R. 5376) [1] resulted in the DOE/NRC Criticality Safety for Commercial-Scale HALEU Fuel Cycle and Transportation (DNCSH) project, part of the HALEU Availability Program. The project aims to support the Nuclear Regulatory Commission (NRC) in providing data for criticality safety validation of reactor designs that, while perhaps demonstrated in limited capacity, represent more exotic systems than those that regulators are accustomed to reviewing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Symmetry-Based Classification of Exact Flat Bands in Single and Bilayer Moiré Systems

Landau levels have been central to the discovery of exotic quantum phases and their unprecedentedly deep roots in geometry and topology. A powerful concept called “vortexability” extends this framework to moiré systems. In this Letter, we show that vortexable systems support not only Landau-level-like flat bands but also entirely new types with distinct topological properties. Notably, while 𝑛𝑏 Landau levels have total Chern number 𝐶 = 𝑛 𝑏 , vortexable moiré systems can host 𝑛 𝑏 flat bands with 𝐶 = 1 ≠ 𝑛 𝑏 . Here, we provide a complete classification of such exact flat bands in single and bilayer systems with Dirac or quadratic band crossings, identifying the symmetry conditions that govern their number and topology. Up to six flat bands can be symmetry protected. We construct explicit wave functions, showing that sublattice-polarized states always sum to Chern number ±1 and satisfy ideal non-Abelian quantum geometry. When the Berry curvature is sharply peaked, we show that a topological heavy-fermion description remains valid—even for bands with high degeneracy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A framework for calibrating and validating an air loop dynamic model in an HVAC system in Modelica

The use of Modelica for simulating the dynamic behaviors of building heating, ventilation, and air conditioning (HVAC) systems has gained popularity. Calibration of a model that represents large and complex HVAC systems in Modelica involves the determination of hundreds of parameters using real-world operation data. Considering the coupling effects among various components, such a calibration process is complex and time-consuming. In this study, we propose a systematic framework to efficiently calibrate and validate a complex HVAC system model in Modelica. The framework includes strategies to solicit real-system operation data and to decouple the model. The goal of this calibration framework is to accurately and efficiently determine a set of Modelica model parameters that provide a good match between the simulated and real system behaviors. To demonstrate the validity of the framework, it was applied to calibrate the parameters of a Modelica model of the air loop subsystem of a real AHU-VAV system. The results show that the calibrated model can generate simulated results, including VAV air flow rate, outdoor air flow, and fan power consumption, that match well with the operational data of the real system. The coefficient of the variation of the root mean square error, CV(RMSE), of the air flow rate and power consumption are 14.6 % and 11.5 %, respectively. The results prove that the framework is valid and effective, and it can be used to calibrate other complex HVAC system Modelica models in the future.

Li, Yicheng↗
DOE OSTI2021

Potassium isotopic fractionation in a humid and an arid soil–plant system in Hawai‘i

Plants play a critical role in the cycling of potassium (K) and the fractionation of its isotopes. However, little is known about K stable isotopic compositions in natural soil–plant systems and possible fractionation during intra-plant transport and root-soil uptake of K. Herein this study focuses on K isotopic fractionation within a humid and an arid soil–plant system sampled on the windward and leeward sides of Kohala Mountain, Hawai‘i. We determined the K isotopic compositions of < 2-mm bulk soil, soil saturation extraction, and selected plant tissues by multi-collector inductively coupled plasma mass spectrometry and X-ray absorption spectroscopy. We studied soils and individual tissue samples such as roots, stems, barks, shoots (a sum of stems and fresh leaves), leaves (fresh and dead), seeds, and flowers of trees and grasses. The results demonstrated that: (i) tissue δ 41 K values ranged from –1.06 ± 0.06 to 1.15 ± 0.09‰; (ii) within the same plant, stems (barks), dead leaves, and reproductive tissues (flowers and seeds) were isotopically lighter compared to fresh leaves, and to a lesser extent, roots; (iii) δ 41 K values of the humid soil (-0.54 ± 0.07 to –0.49 ± 0.06‰) were lower than those of the arid soil (-0.24 ± 0.07 to –0.14 ± 0.06‰); and (iv) soil bioavailable pool δ 41 K (saturation extracts) ranged from –0.63 ± 0.08 to 0.34 ± 0.08‰ and 0.48 ± 0.08 to 0.54 ± 0.10‰ in the humid and arid soils, respectively. From synchrotron-based analysis of K atoms, we identified two major K-bearing phases co-existing as ionic K + and K-pectate association of different fractions. Based on K isotopic and synchrotron data, we conclude that two dominant processes are responsible for plant-mediated K isotopic fractionation, including (1) K redistribution during intra-plant circulation and (2) uptake at the root-soil interface. For intra-plant circulation of K, there is a high affinity of isotopically lighter K to organic complexes as K-pectate, and K-pectate is particularly enriched in roots and fresh leaves. For K uptake at root-soil interface, isotopically lighter K is preferentially taken by roots from soil bioavailable pools following a low-affinity (passive) transport path. Soil K budget in two sites reflects strong source mixing effects with limited plant imprints. This work provides exploratory data on the biogeochemical fractionation of K isotopes in the soil–plant system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Ectomycorrhizal effects on decomposition are highly dependent on fungal traits, climate, and litter properties: A model-based assessment

It has been proposed that competition between ectomycorrhizal (ECM) fungi and free-living saprotrophs for resources like nitrogen (N) slows decomposition and increases the soil carbon storage in ECM ecosystems compared to arbuscular (AM) ecosystems. However, empirical evidence for the generality of such ECM effects is equivocal, and confounding mechanisms have been proposed that affect the magnitude and direction of ECM effects on soil carbon. Here, for this work, we conduct a theoretical modeling experiment, where we explicitly incorporate mycorrhizal processes into the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model. We use the model to explore the conditions under which ECM N acquisition processes can induce stronger saprotrophic N limitation and result in slower decomposition rates and greater soil organic carbon accumulation compared to AM processes. We found that the ECM fungi more strongly inhibited decomposition when litter inputs were N-depleted and relatively recalcitrant and when ECM fungi possessed a strong capacity to mine N from both recalcitrant soil organic matter and microbial necromass. Climate and seasonality also played a role as the ECM competition effect was strongest at low mean annual temperatures and when litterfall peaked seasonally. Priming effects driven by high root exudation rates in ECM-dominated systems could overwhelm the competition effect and reduce soil carbon under some circumstances. The ECM effect on decomposition in our simulations was highly context dependent. Based on our model results, we expect to see a strong ECM competition effect in temperate deciduous and boreal forests with relatively recalcitrant litter inputs, and with ECM fungi that produce oxidases and necromass-degrading enzymes. However, even a relatively strong ECM competition effect on decomposition only increased soil organic carbon accumulation by ~10%.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Stochastic and deterministic processes shape bioenergy crop microbiomes along a vertical soil niche

Abstract Sustainable biofuel cropping systems aim to address climate change while meeting energy needs. Understanding how soil and plant‐associated microbes respond to these different cropping systems is key to promoting agriculture sustainability and evaluating changes in ecosystem functions. Here, we leverage a long‐term biofuel cropping system field experiment to dissect soil and root microbiome changes across a soil‐depth gradient in poplar, restored prairie and switchgrass to understand their effects on the microbial communities. High throughput amplicon sequencing of the fungal internal transcribed spacer (ITS) and prokaryotic 16S DNA regions showed a common trend of root and soil microbial community richness decreasing and evenness increasing with depth. Ecological niche (root vs. soil) had the strongest effect on community structure, followed by depth, then crop. Stochastic processes dominated the structuring of fungal communities in deeper soil layers while operational taxonomic units (OTUs) in surface soil layers were more likely to co‐occur and to be enriched by plant hosts. Prokaryotic communities were dispersal limited at deeper depths. Microbial networks showed a higher density, connectedness, average degree and module size in deeper soils. We observed a decrease in fungal‐fungal links and an increase of bacteria–bacteria links with increasing depth in all crops, particularly in the root microbiome.

59 BASIC BIOLOGICAL SCIENCES↗