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At least 145 records · Page 8

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↗

Which Plant Traits Increase Soil Carbon Sequestration? Empirical Evidence From a Long‐Term Poplar Genetic Diversity Trial

Plants play a key role in mediating soil response to global change, and breeding or engineering crops to increase soil organic carbon (SOC) storage is a potential route to land-based carbon dioxide removal in agricultural systems. However, due to limited observational datasets plus shifting paradigms of SOC stabilization, it is unclear which plant traits are most important for enhancing different types of soil organic matter. Existing long-term common gardens of genetically diverse plant populations may provide an opportunity to evaluate biological controls on SOC, separate from environmental or management variability. Here we report on soil and root chemical data collected for 24 genotypes within a 13-year-old common garden in northwestern Oregon planted with a large natural variant population of Populus trichocarpa. Fractionating surface soil (0–15 cm) revealed substantial variation in stocks of mineral-associated organic matter (MAOM; 18–67 t C/ha) and particulate organic matter (POM; 2–22 t C/ha). Tree genotype explained 24% and 26% of the MAOM and POM stock variability, respectively, after controlling for background variability. We found minimal association between SOC concentration and either aboveground tree productivity or root biomass recalcitrance (C/N ratios and lignin content). In contrast, root elemental content appeared influential for MAOM-C concentration, which showed a strong positive association with root aluminum (Al) and a strong negative association with root boron (B) and magnesium (Mg). Furthermore, root concentrations of these elements were highly heritable (57%–78%) and not simply a reflection of background variation in soil elemental concentrations. We estimate that surface SOC stocks under these 24 genotypes have diverged at rates of up to 1.2–4.3 t C/ha/year. These results suggest that long-term genetic diversity trials have value for elucidating biological controls on soil organic matter dynamics, and that traits associated with root elemental content may be a useful target for enhancing biosequestration.

biomass recalcitrance↗

Feedback and Oscillations: Constructing Feedback Systems for Root Cause Analysis of Oscillations in Power Grids

Dynamic phenomena linked to inverter-based resources (IBRs) have gained global attention. Several IBR-induced dynamics have caused bulk power system-connected wind or solar power plants to trip, and some have even led to widespread outages. In addition, many oscillations have been observed involving IBR power plants. In 2023, the IEEE Power & Energy Society (PES) IBR Subsynchronous Oscillations (SSO) task force published a journal article, “Real-World Subsynchronous Oscillation Events in Power Grids With High Penetrations of Inverter-Based Resources,” in which 19 IBR oscillation events were examined for their causation. Earlier in 2020, another PES task force article, “Definition and Classification of Power System Stability-Revisited & Extended,” authored by prominent academics, introduced converter-driven stability as a new category of stability. The international power grid industry community also took action by publishing the CIGRE Green Book, Power System Dynamic Modelling and Analysis in Evolving Networks (led by Babak Badrzadeh and Zia Emin) in 2024. In August 2024, the Energy Systems Integration Group (ESIG) released a practical guide led by Nick Miller, “Diagnosis and Mitigation of Observed Oscillations in IBR-Dominant Power System: A Practical Guide.” The goal of the guide is to assist practicing engineers in making initial judgments and conducting detailed analyses about oscillations. Finally, when addressing the classification of stability and oscillations, the guide emphasizes a causality-based taxonomy for grouping, such as voltage control-induced oscillations, synchronization-induced oscillations, and frequency or active power control-induced oscillations.

Fan, Lingling [Univ. of South Florida, Tampa, FL (↗

A dynamic growth model of vegetative soya bean plants: model structure and behaviour under varying root temperature and nitrogen concentration

A differential equation model of vegetative growth of the soya bean plant (Glycine max (L.) Merrill cv. Ransom') was developed to account for plant growth in a phytotron system under variation of root temperature and nitrogen concentration in nutrient solution. The model was tested by comparing model outputs with data from four different experiments. Model predictions agreed fairly well with measured plant performance over a wide range of root temperatures and over a range of nitrogen concentrations in nutrient solution between 0.5 and 10.0 mmol NO3- in the phytotron environment. Sensitivity analyses revealed that the model was most sensitive to changes in parameters relating to carbohydrate concentration in the plant and nitrogen uptake rate.

Non-NASA Center↗

New method for propagating the square root covariance matrix in triangular form

A method proposed by Potter of applying the Kalman-Bucy filter to the problem of estimating the state of a dynamic system is described, in which the square root of the state error covariance matrix is used to process the observations. A new technique which propagates the covariance square root matrix in lower triangular form is given for the discrete observation case. The technique is faster than previously proposed algorithms and is well-adapted for use with the Carlson square root measurement algorithm.

Choe, C. Y.↗

From 2D to 4D: a containerized workflow and browser to explore dynamic chromatin architecture

Background Characterizing the physical organization of the genome is essential for understanding long-range gene regulation, chromatin compartmentalization, and epigenetic accessibility. Hi-C experiments generate two-dimensional (2D) genome-wide contact maps of chromatin interactions by capturing the spatial proximity between genomic loci, which reveal interaction frequencies but lack the spatial resolution needed to interpret the three-dimensional (3D) genome structure(s). Emerging evidence suggests that epigenetic regulation is closely linked to 3D genome architecture, and that structural changes over time (4D) drive key biological processes in development, disease, and environmental response. Thus, integrating 3D structure with functional data is critical for a more complete understanding of genome regulation. Previous work, most notably the 4DHiC chromosome modeling framework, has shown that physical multi-dimensional modeling approaches rooted in polymer physics and molecular dynamics can resolve these structures at biologically meaningful resolutions by integrating temporal Hi-C data with physical constraints to uncover dynamic chromosome reorganization. Thus, molecular dynamics simulations, constrained by Hi-C contact matrices, can resolve fine-scale structural changes and reveal functionally significant transitions in chromatin conformation. Results Herein, we present the 4D Genome Browser Workflow (4DGBWorkflow) and the 4D Genome Browser (4DGB). The algorithm is based on the 4DHiC method, and the containerized tool is an end-to-end workflow that can transform, filter, and view 4D epigenomics and chromatin datasets, allowing non-specialists to apply three-dimensional modeling principles to diverse datasets and experimental conditions. The software executes on a laptop running macOS, Linux or Windows. From input Hi-C files (.hic), the 4DGBWorkflow produces 3D reconstructions of chromosomes, integrates the reconstruction with track data (e.g., epigenetic marks, transcriptome profiles), and provides comparative visualization of the results in a single workflow. Conclusions The 4DGBWorkflow and 4D Genome Browser are open-source tools for comparative analysis and visualization of 4D chromosome datasets, including chromatin architecture and epigenomic signals. Automatic integration of Hi-C data with molecular dynamics democratizes the construction of time resolved 3D genome structures, simplifying complex simulations and data integration schemes.

3D Genome Browser↗

Mechanochemical Synthesis of Sustainable Ternary and Quaternary Nanostructured Cu2SnS3, Cu2ZnSnS4, and Cu2ZnSnSe4 Chalcogenides for Thermoelectric Applications

Copper-based chalcogenides have emerged as promising thermoelectric materials due to their high thermoelectric performance, tunable transport properties, earth abundance and low toxicity. We have presented an overview of experimental results and first-principal calculations investigating the thermoelectric properties of various polymorphs of Cu2SnS3 (CTS), Cu2ZnSnS4 (CZTS), and Cu2ZnSnSe4 (CZTSe) synthesized by high-energy reactive mechanical alloying (ball milling). Of particular interest are the disordered polymorphs of these materials, which exhibit phonon-glass–electron-crystal behavior—a decoupling of electron and phonon transport properties. The interplay of cationic disorder and nanostructuring leads to ultra-low thermal conductivities while enhancing electronic transport. These beneficial transport properties are the consequence of a plethora of features, including trap states, anharmonicity, rattling, and conductive surface states, both topologically trivial and non-trivial. Based on experimental results and computational methods, this report aims to elucidate the details of the electronic and lattice transport properties, thereby confirming that the higher thermoelectric (TE) performance of disordered polymorphs is essentially due to their complex crystallographic structures. In addition, we have presented synchrotron X-ray diffraction (SR-XRD) measurements and ab initio molecular dynamics (AIMD) simulations of the root-mean-square displacement (RMSD) in these materials, confirming anharmonicity and bond inhomogeneity for disordered polymorphs.

36 MATERIALS SCIENCE↗

Tree root nutrient uptake kinetics vary with nutrient availability, environmental conditions, and root traits: a global analysis

Summary: Root nutrient uptake by trees is a critical process that couples carbon and nutrient cycling in forest ecosystems. Yet, root nutrient uptake traits are poorly constrained, and the dynamics of this process are often not represented in models reflecting sparse measurements and understanding of root nutrient uptake physiology that lags those of aboveground physiology in forest ecosystems. Here, we present a global dataset of published nutrient uptake capacity and affinity values for tree species, with the goal of describing global patterns and evaluating responses to environmental drivers and associations with root traits. Furthermore, the dataset contains observations for ammonium, nitrate, and phosphate uptake spanning 77 tree species. Nutrient uptake capacity and affinity varied by more than an order of magnitude for each nutrient. Notably, tropical forests are underrepresented in these observations. Nutrient uptake capacity was generally diminished under nutrient enrichment but enhanced with soil warming and root–mycorrhizal colonization. The magnitude and direction of these effects can depend on the duration of exposure to a given treatment. Species with thinner roots had a tendency toward greater uptake capacity and affinity. Overall, root nutrient uptake traits are highly variable across tree species, yet they depend on environmental drivers and life-history strategies.

Km↗

Rewritable Surface‐Grafted Polymer Brushes with Dynamic Covalent Linkages

Abstract Surface grafting of polymer brushes drastically modifies surface properties, including wettability, compatibility, responsiveness, etc. A broad variety of functionalities can be introduced to the surface via different types of polymers. Bringing together properties of two or more types of polymer brushes to one surface opens up even more possibilities in brush‐modified materials. However, while it is generally feasible to introduce several chemical compositions along the brushes via copolymerization, it is challenging to vary the types of polymer brushes along a surface. Although previous studies have demonstrated binary brushes via orthogonal polymerization techniques or partial deactivation/regrafting, they commonly limit the number of polymer types to two. Here, we propose a strategy to introduce dynamic covalent diketoenamine linkages at the root of polymer brushes. The grafting density could be precisely tuned during surface functionalization. The surface‐anchored polymer brushes were cleaved by the addition of small molecule amines. New polymer brushes can be regrafted from the surface following refunctionalization of exposed sites. The maneuverability allows tuning of the types and densities of the polymer brushes, pointing the way to the preparation of a new generation of well‐defined brush‐modified materials with mixed grafts, with potential applications in the design of smart materials and surfaces.

Cui, Feichen↗

Functional variability in specific root respiration translates to autotrophic differences in soil respiration in a temperate deciduous forest

CO 2 release from forest soils (R s ) is a prominent flux in the global carbon cycle. Rs is derived from roots (autotrophic respiration, R a ) and microbial (heterotrophic) respiration and is highly dynamic, as it depends on edaphic and environmental conditions as well as root functional traits and microbial community composition. It is unclear how root functional traits affect root and microbial respiration rates; however, their consideration may help parse out the relative contributions of root and microbial respiration to R s . At a temperate forest site, root systems of 3–4 functional root orders and their surrounding surface soil were carefully excavated and placed into custom trays designed to repeatedly measure R s in situ on eight temperate tree species that varied in their root functional strategies and mycorrhizal affinity. R s was measured bi-weekly to monthly for nearly one year using a custom chamber attached to a gas exchange system. R s varied over time, ranging from 0.3 to 12 µmol m -2 s -1 . Comparable root systems of the same species were excised from the soil and specific root respiration rates (R r ) were measured. Rr ranged from 2.5 to 9.0 nmol g -1 s -1 and was negatively correlated with root tissue density and positively related to root tissue nitrogen concentration. Using R r to estimate R a , we estimate that R a accounts for <10%, on average 2–3%, of R s for individual root systems (averaging 1.2 g dry biomass) housed in surrounding soil (average 1.3 kg dry mass) in situ; thus, Ra was roughly 20 times greater than Rh per unit mass. The contribution of R a peaked in the fall and coincided with leaf senescence of the forest canopy. A soil-sterilizing experimental treatment designed to help isolate R a in situ reduced bacterial biomass and shifted fungal community composition, but there was no reduction in Rs of the in-situ root-soil tray systems. The relative R a to R s ratio increased with root functional strategies characterized by greater specific root length and tip abundance, but also to greater root tissue density. The ratio of R a to R s also increased with warmer soil temperatures and decreased slightly with increasing soil moisture. We discuss how incorporating root functional traits as modulators of the autotrophic contribution to R s could be considered when modeling total soil CO 2 efflux from forests.

54 ENVIRONMENTAL SCIENCES↗

Hourly PM 2.5 Estimates across California from 2018 to 2023

This study presents a new data set of hourly PM 2.5 concentrations across California from 2018 to 2023 at a three-kilometer resolution. This data set was developed by assimilating observations from PurpleAir and the U.S. EPA Air Quality System monitors into wildfire smoke forecasts from the High-Resolution Rapid Refresh Smoke (HRRR-Smoke) model using the Gridpoint Statistical Interpolation (GSI) three-dimensional variational data assimilation framework. Archived forecasts of modeled wildfire smoke PM 2.5 from HRRR-Smoke create the background field for assimilation, which is then corrected using surface observations of total PM 2.5 . The resulting reanalysis from GSI provides an estimate of total PM 2.5 that minimizes error from both the observational and the model data. Validation results indicate strong performance, with monthly R 2 values ranging from 0.73 to 0.91 across the six-year data set, comparable to other PM 2.5 data sets. Case studies are presented for three major fire events, the 2018 Camp Fire, 2019 Kincade Fire, and 2020 Lightning Complex Fires to demonstrate the data set’s fidelity in resolving plume dynamics and local exposure patterns. Root-mean-squared error averaged over each month scales with average PM 2.5 concentrations, resulting in a low error under typical conditions but higher absolute errors during extreme smoke events. This is the first long-term, hourly PM 2.5 data set of its kind for California and enables the generation of subdaily exposure metrics, such as peak hourly concentrations, exceedance durations, and time-of-day exposure peaks. The novelty and strong validation of this data set make it a compelling resource for future studies on the impact and significance of subdaily PM 2.5 exposure.

PM2.5↗

Random heteropolymers as enzyme mimics

Despite successes in replicating the primary–secondary–tertiary structure hierarchy of protein, it remains elusive to synthetically materialize protein functions that are deeply rooted in their chemical, structural and dynamic heterogeneities. We propose that for polymers with backbone chemistries different from that of proteins, programming spatial and temporal projections of sidechains at the segmental level can be effective in replicating protein behaviours; and leveraging the rotational freedom of polymer can mitigate deficiencies in monomeric sequence specificity and achieve behaviour uniformity at the ensemble level. Here, guided by the active site analysis of about 1,300 metalloproteins, we design random heteropolymers (RHPs) as enzyme mimics based on one-pot synthesis. We introduce key monomers as the equivalents of the functional residues of protein and statistically modulate the chemical characteristics of key monomer-containing segments, such as segmental hydrophobicity. The resultant RHPs form pseudo-active sites that provide key monomers with protein-like microenvironments, co-localize substrates with catalytic or cofactor-binding sidechains and catalyse reactions such as oxidation and cyclization of citronellal with isopulegol/menthoglycol selectivity. This RHP design led to enzyme-like materials that can retain catalytic activity under non-biological conditions, are compatible with scalable processing and have expanded substrate scope, including environmentally long-lasting antibiotic tetracycline.

36 MATERIALS SCIENCE↗

Elevated Temperature Effects on Protein Turnover Dynamics in Arabidopsis thaliana Seedlings Revealed by 15 N-Stable Isotope Labeling and ProteinTurnover Algorithm

Global warming poses a threat to plant survival, impacting growth and agricultural yield. Protein turnover, a critical regulatory mechanism balancing protein synthesis and degradation, is crucial for the cellular response to environmental changes. We investigated the effects of elevated temperature on proteome dynamics in Arabidopsis thaliana seedlings using 15 N-stable isotope labeling and ultra-performance liquid chromatography-high resolution mass spectrometry, coupled with the ProteinTurnover algorithm. Analyzing different cellular fractions from plants grown under 22 °C and 30 °C growth conditions, we found significant changes in the turnover rates of 571 proteins, with a median 1.4-fold increase, indicating accelerated protein dynamics under thermal stress. Notably, soluble root fraction proteins exhibited smaller turnover changes, suggesting tissue-specific adaptations. Significant turnover alterations occurred with redox signaling, stress response, protein folding, secondary metabolism, and photorespiration, indicating complex responses enhancing plant thermal resilience. Conversely, proteins involved in carbohydrate metabolism and mitochondrial ATP synthesis showed minimal changes, highlighting their stability. This analysis highlights the intricate balance between proteome stability and adaptability, advancing our understanding of plant responses to heat stress and supporting the development of improved thermotolerant crops.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flight characteristics of a manned, low-speed, controlled deep stall vehicle

A successful manned, low speed, controlled deep stall flight research program was conducted at NASA Ames Research Center's Dryden Flight Research Facility. Piloting techniques were established that enabled the pilot to attain and stabilize on an angle of attack in the 30 deg to 72 deg range. A flight determined aerodynamic data base was established for angles of attack as high as 72 deg. Poor lateral directional flying qualities were encountered at angles of attack above 60 deg. Insight into the high angle of attack lateral directional dynamics was gained through a basic root locus analysis.

Sim, A. G.↗

Issues in Developing a Normative Descriptive Model for Dyadic Decision Making

Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.

Serfaty, D.↗

Development of Unsteady Aerodynamic and Aeroelastic Reduced-Order Models Using the FUN3D Code

Recent significant improvements to the development of CFD-based unsteady aerodynamic reduced-order models (ROMs) are implemented into the FUN3D unstructured flow solver. These improvements include the simultaneous excitation of the structural modes of the CFD-based unsteady aerodynamic system via a single CFD solution, minimization of the error between the full CFD and the ROM unsteady aero- dynamic solution, and computation of a root locus plot of the aeroelastic ROM. Results are presented for a viscous version of the two-dimensional Benchmark Active Controls Technology (BACT) model and an inviscid version of the AGARD 445.6 aeroelastic wing using the FUN3D code.

Silva, Walter A.↗

A Study of the 20 Day Superorbital Modulation in the High-Mass X-Ray Binary IGR J16493-4348

We report on Nuclear Spectroscopic Telescope Array (NuSTAR), Neil Gehrels Swift Observatory(Swift) X-ray Telescope (XRT), and Swift Burst Alert Telescope (BAT) observations of IGR J16493-4348, a wind-fed supergiant X-ray binary showing significant superorbital variability. From a discrete Fourier transform of the BAT light curve,we refine its superorbital period to be 20.058±0.007 days. The BAT dynamic power spectrum and a fractional root mean square analysis both show strong variations in the amplitude of the superorbital modulation, but no observed changes in the period are found. The superorbital modulation is significantly weaker between MJD 55,700 and MJD 56,300. The joint NuSTAR and XRT observations, which were performed near the minimum and maximum of one cycle of the 20 day superorbital modulation, show that the flux increases by more than a factor of two between superorbital minimum and maximum. We find no significant changes in the 3-50 keV pulse profiles between superorbital minimum and maximum, which suggests a similar accretion regime. Modeling the pulse-phase-averaged spectra we find a possible Fe Kα emission line at 6.4 keV at superorbital maximum. This feature is not significant at superorbital minimum. While we do not observe any significant differences between the pulse-phase-averaged spectral continua apart from the overall flux change, we find that the hardness ratio near the broad main peak of the pulse profile increases from superorbital minimum to maximum. This suggests the spectral shape hardens with increasing luminosity. We discuss different mechanisms that might drive the observed superorbital modulation.

Coley, Joel B.↗

Auxin‐induced actin cytoskeleton rearrangements require AUX1

Summary The actin cytoskeleton is required for cell expansion and implicated in cellular responses to the phytohormone auxin. However, the mechanisms that coordinate auxin signaling, cytoskeletal remodeling and cell expansion are poorly understood. Previous studies examined long‐term actin cytoskeleton responses to auxin, but plants respond to auxin within minutes. Before this work, an extracellular auxin receptor – rather than the auxin transporter AUXIN RESISTANT 1 (AUX1) – was considered to precede auxin‐induced cytoskeleton reorganization. In order to correlate actin array organization and dynamics with degree of cell expansion, quantitative imaging tools established baseline actin organization and illuminated individual filament behaviors in root epidermal cells under control conditions and after indole‐3‐acetic acid (IAA) application. We evaluated aux1 mutant actin organization responses to IAA and the membrane‐permeable auxin 1‐naphthylacetic acid (NAA). Cell length predicted actin organization and dynamics in control roots; short‐term IAA treatments stimulated denser and more parallel, longitudinal arrays by inducing filament unbundling within minutes. Although AUX1 is necessary for full actin rearrangements in response to auxin, cytoplasmic auxin (i.e. NAA) stimulated a lesser response. Actin filaments became more ‘organized’ after IAA stopped elongation, refuting the hypothesis that ‘more organized’ actin arrays universally correlate with rapid growth. Short‐term actin cytoskeleton response to auxin requires AUX1 and/or cytoplasmic auxin.

AUX1↗