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Aninteractive mapshowingPopulus trichocarpaGWAS sub-population structure identified by DBSCAN clustering, which were derived from a UMAP projection of the top 8 PCs of LD-pruned pangenome SNP data. Geographic origins are searchable by genotype or river system using the search bar.
Aninteractive UMAP plotderived from the top 8 PCs of LD-prunedPopulus trichocarpapangenome SNP data. Points are colored by ADMIXTURE population structure (k=3) and geographic origins are searchable by genotype or river system using the search bar.
The composition, integrity, and architecture of the macromolecular matrix of cell walls, collectively referred to as cell wall ultrastructure, exhibits variation across species and organs and among cell types within organs. Indirect approaches have suggested that modifications to cell wall ultrastructure occur in response to abiotic stress; however, modifications have not been directly observed. Glycome profiling was used to study cell wall ultrastructure by examining variation in composition and extractability of non-cellulosic glycans in cell walls of stem wood, roots, and needles of loblolly pine saplings exposed to high and low soil moisture. Soil moisture influenced physiological processes and the overall composition and extractability of cell wall components differed as a function of soil moisture treatments. The strongest response of cell wall ultrastructure to soil moisture was increased extractability of pectic backbone epitopes in the low soil moisture treatment. The higher abundance of these pectic backbone epitopes in the oxalate extract indicate that the loosening of cell wall pectic components could be associated with the release of pectic signals as a stress response. The increased extractability of pectic backbone epitopes in response to low soil moisture availability was more pronounced in stem wood than in roots or needles. Additional responses to low soil moisture availability were observed in lignin associated carbohydrates released in chlorite extracts of stem wood, including an increased abundance of pectic arabinogalactan epitopes. Overall, these results indicate that cell walls of loblolly pine organs undergo changes in their ultrastructural composition and extractability as a response to soil moisture availability and that cell walls of the stem wood are more responsive to low soil moisture availability compared to cell walls of roots and needles. In conclusion, to our knowledge, this is the first direct evidence, delineated by glycomic analyses, that abiotic stress affects cell wall ultrastructure. This study is also unique in that glycome profiling of pine needles has never before been reported.
Snow derived water is a critical component of the US water supply. Measurements of the Snow Water Equivalent (SWE) and associated predictions of peak SWE and snowmelt onset are essential inputs for water management efforts. This paper aims to develop an integrated framework for real-time data ingestion, estimation, prediction and visualization of SWE based on daily snow datasets. In particular, we develop a data-driven approach for estimating and predicting SWE dynamics using the Long Short-Term Memory neural network (LSTM) method. Our approach uses historical datasets (precipitation, air temperature, SWE, and snow thickness) collected at NRCS Snow Telemetry (SNOTEL) stations to train the LSTM network and current year data to predict SWE behavior. The performance of our prediction was compared for different prediction dates and prediction training datasets. Our results suggest that the proposed LSTM network can be an efficient tool for forecasting the SWE timeseries, as well as Peak SWE and snowmelt timing. Results showed that the window size impacts the model performance (where the Nash Sutcliffe efficiency (NSE) ranged from 0.96 to 0.85 and the Rooted Mean Square Error (RMSE) ranged from 0.038 to 0.07) with an optimum number that should be calibrated for different stations and climate conditions. In addition, by implementing the LSTM prediction capability in a cloud based site-monitoring platform, we automate model-data integration. By making the data accessible through a graphical web interface and an underlying API which exposes both training and prediction capabilities. The associated results can be made easily accessible to a broad range of stakeholders.
With the advent of a new Precision Time Protocol specification, new opportunities abound for clock synchronization possibilities within power grid control systems. The third iteration of the Institute of Electrical and Electronics Engineers Standard 1588 specification provides several new features specifically aimed at complex, wide-area deployments in which situational awareness and control require precise time agreement. This paper describes the challenges faced by existing technology, introduces the new time distribution specification, and provides examples to explain how it represents a game-changing innovation.
Establishing reliable carbon baselines for landowners desiring to sustain carbon sequestration and identify opportunities to mitigate land management impacts on carbon balance is important; however, national and regional assessments are not designed to support individual landowners. Such baselines become increasingly valuable when landowners convert land use, change management, or when disturbance occurs. We used forest inventories to quantify carbon stocks, estimate annual carbon fluxes, and determine net biome production (NBP) over a 50-year period coinciding with a massive afforestation effort across ~80,000 ha of land in the South Carolina Coastal Plain. Forested land increased from 48,714 ha to 73,824 ha between 1951 and 2001. Total forest biomass increased from 1.73–3.03 Gg to 17.8–18.3 Gg, corresponding to biomass density increases from 35.6–62.2 Mg ha−1 to 231.4–240.0 Mg ha−1. Harvesting removed 1340.3 Gg C between 1955 and 2001, but annual removals were variable. Fire consumed 527.1 Gg C between 1952 and 2001. Carbon exported by streams was <0.5% of total export. Carbon from roots and other harvested material that remained in-use or in landfills comprised 49.3% of total harvested carbon. Mineral soil carbon accounted for 41.6 to 50% of 2001 carbon stocks when considering depths of 1.0 or 1.5 m, respectively, and was disproportionately concentrated in wetlands. Moreover, we identified a soil carbon deficit of 19–20 Mg C ha−1, suggesting opportunities for future soil carbon sequestration in post-agricultural soils. Our results provide a robust baseline for this site that can be used to understand how land conversion, forest management, and disturbance impacts carbon balance of this landscape and highlight the value of these baseline data for other sites. Our work also identifies the need to manage forests for multiple purposes, especially promotion of soil carbon accumulation in low-density pine savannas that are managed for red-cockaded woodpeckers and therefore demand low aboveground carbon stocks.
Microbial communities found in soil ecosystems play important roles in decomposing organic materials and recycling nutrients. A clear understanding on how biotic and abiotic factors influence the microbial community and its functional role in ecosystems is fundamental to terrestrial biogeochemistry and plant production. The purpose of this study was to investigate microbial communities and functional genes involved in nitrogen cycling as a function of groundwater depth (deep and shallow), tree species (pine and eucalypt), and season (spring and fall). Soil fungal, bacterial, and archaeal communities were determined by length heterogeneity polymerase chain reaction (LH-PCR). Soil ammonia oxidation archaeal (AOA) amoA gene, ammonia oxidation bacterial (AOB) amoA gene, nitrite oxidoreductase nrxA gene, and denitrifying bacterial narG, nirK, nirS, and nosZ genes were further studied using PCR and denaturing gradient gel electrophoresis (DGGE). Soil fungal and bacterial communities remained similar between tree species and groundwater depths, respectively, regardless of season. Soil archaeal communities remained similar between tree species but differed between groundwater depths in the spring only. Archaeal amoA for nitrification and bacterial nirK and nosZ genes for denitrification were detected in DGGE, whereas bacterial amoA and nrxA for nitrification and bacterial narG and nirS genes for denitrification were undetectable. The detected nitrification and denitrification communities varied significantly with groundwater depth. There was no significant difference of nitrifying archaeal amoA or denitrifying nirK communities between different tree species regardless of season. The seasonal difference in microbial communities and functional genes involved in nitrogen cycling suggests microorganisms exhibit seasonal dynamics that likely impact relative rates of nitrification and denitrification.
Research linking soil moisture availability to nonstructural carbohydrate (NSC) storage suggests greater NSC reserves promote survival under acute water stress, but little is known about how NSC allocation responds to long-term differences in water availabilty. We hypothesized populations experiencing chronic or frequent water stress shift carbon allocation to build greater NSC reserves for increased survival probability during drought relative to populations rarely experiencing water stress. Over a year, we measured soluble sugar and starch concentrations from branches, stems, and coarse roots of mature Pinus palustris trees at two sites differing in long-term soil moisture availability. Xeric and mesic populations exhibited a cycle of summer depletion-winter accumulation in root starch. Xeric populations reached a maximum root starch concentration approximately 1–2 months later than mesic populations, indicating delayed summer depletion. Xeric and mesic populations reached the same minimum root starch at similar times, suggesting extended winter accumulation for xeric populations. These results suggest seasonal mobilization from root starch is compressed into a shorter interval for xeric populations instead of consistently greater reserves as hypothesized. Seasonal trends differed little between xeric and mesic populations for starch and sugars, suggesting the importance of roots in seasonal carbon dynamics and the primacy of starch for storage. If roots are the primary organ for longterm storage, then our results suggest that whole-plant mobilization and allocation respond to chronic differences in water availability.
As awareness of climate change increases, the need for carbon neutral fuel sources is growing. Lignocellulosic biofuel derived from pine trees has been suggested as one potential energy source; however, it requires more research before its efficacy for climate change mitigation can be determined. Due to the large share of forest carbon held in soils and the extensive area of pine plantations in the southeast U.S., a better understanding of plantation soil carbon dynamics is critical for biofuel carbon accounting. This study evaluated the effects of canopy development and productivity on soil CO2 efflux, a proxy for soil respiration (Rs), in an intensively managed loblolly pine (Pinus taeda) stand over a period from May 2015 to December 2019. We found that leaf area index (LAI) and gross ecosystem production (GEP), as well as meteorological variables, had significant effects on Rs, but that both overall Rs and soil carbon pools did not increase over the course of the study. We thus hypothesize that GEP and LAI had intra-annual effects on Rs, and that the lack of change in Rs is the result of an increase in autotrophic respiration (Ra) that offset a decrease in decomposition of the previous stand’s organic matter.
Carbohydrate reserves provide advantages for mature trees experiencing frequent disturbances; however, it is unclear if selective pressures operate on this characteristic at the seedling or mature life history stage. We hypothesized that natural selection has favored carbohydrate reserves in species that have an evolutionary history of frequent disturbance and tested this using three southern pine species that have evolved across a continuum of fire frequencies. Longleaf pine (Pinus palustris) roots exhibited higher maximum starch concentrations than slash (P. elliottii) and loblolly (P. taeda), which were similar. Longleaf also relied on starch reserves in roots more than slash or loblolly, depleting 64, 41, and 23 mg g -1 of starch, respectively, between seasonal maximum and minimum, which represented 52%, 45%, and 26% of reserves, respectively. Starch reserves in stems did not differ among species or exhibit temporal dynamics. Our results suggest that an evolutionary history of disturbance partly explains patterns of carbohydrate reserves observed in southern pines. However, similarities between slash and loblolly indicate that carbohydrate reserves do not strictly follow the continuum of disturbance frequencies among southern pine, but rather reflect the different seedling strategies exhibited by longleaf compared to those shared by slash and loblolly. We propose that the increased carbohydrate reserves in mature longleaf may simply be a relic of selective pressures imposed at the juvenile stage that are maintained through development, thus allowing mature trees to be more resilient and to recover from chronic disturbances such as frequent fire.
The longleaf pine ecosystem is dependent on frequent fire. Climate change is expected to influence moisture availability and it is unclear how drought conditions may interact with prescribed fire to influence management objectives associated with maintaining longleaf pine ecosystems. This study aimed to understand the impacts of drought, fire intensity and their interaction on P. palustris grass-stage seedlings. We used droughted and well-watered P. palustris seedlings burned at two different fire intensity levels at an indoor combustion facility. Needle fuel moisture content of burned seedlings was not different between droughted and well-watered groups. Mortality and resprouting only occurred at fire intensity levels exceeding 3.5 MJ m−2 in combination with drought that resulted in predawn water potentials more negative than −1.7 MPa. Our observations of minimal mortality after exposing P. palustris seedlings to a range of fire intensities in a burn lab contrast the higher mortality observed in field studies for the species. Compared to seedlings and saplings of Western US Pinus species, this study demonstrates that P. palustris is considerably more resistant to the combined effects of high surface fire intensity and drought.
Among various components commonly used in redox flow batteries (RFBs), the separator plays a significant role, influencing resistance to current as well as capacity decay via unintended crossover. It is well-established that the ohmic overpotential is dominated by the membrane and interfacial resistance in most aqueous RFBs. The ultimate goal of engineering membranes is to improve the ionic conductivity while keeping crossover at a minimum. One of the major issues yet to be addressed is the contribution of interfacial phenomena in the influence of ionic and water transport through the membrane. In this work, we have utilized a novel experimental system capable of measuring the ionic crossover in real-time to quantify the permeability of ionic species. Specifically, we have focused on quantifying the contributions from the interfacial resistance to ionic crossover. The trade-off between the mass and ionic transport impedance caused by the interface of the membranes has been addressed. The MacMullin number has been quantified for a series of electrolyte configurations and a correlation between the ionic conductivity of the contacting electrolyte and the Nafion® membrane has been established. The performance of individual ion-exchange membranes along with a stack of various separators have been explored. We have found that utilizing a stack of membranes is significantly beneficial in reducing the electroactive species crossover in redox flow batteries compared to a single membrane of the same fold thickness. For example, we have demonstrated that the utilization of five layers of Nafion ® 211 membrane reduces the crossover by 37% while only increasing the area-specific resistance (ASR) by 15% compared to a single layer Nafion ® 115 membrane. Therefore, the influence of interfacial impedance in reducing the vanadium ion crossover is substantially higher compared to a corresponding increase in ASR, indicating that mass and ohmic interfacial resistances are dissimilar. We have expanded our analysis to a combination of commercially available ion-exchange membranes and provided a design chart for membrane selection based on the application of interest (short duration/high-performance vs. long-term durability). The results of this study provide a deeper insight into the optimization of all-vanadium redox flow batteries (VRFBs).
The study objective was to field-validate the technical feasibility of a membrane- and adsorption-enhanced water gas shift reaction process employing a carbon molecular sieve membrane (CMSM)-based membrane reactor (MR) followed by an adsorptive reactor (AR) for pre-combustion CO2 capture. The project was carried out in two different phases. In Phase I, the field-scale experimental MR-AR system was designed and constructed, the membranes, and adsorbents were prepared, and the unit was tested with simulated syngas to validate functionality. In Phase II, the unit was installed at the test site, field-tested using real syngas, and a technoeconomic analysis (TEA) of the technology was completed. All project milestones were met. Specifically, (i) high-performance CMSMs were prepared meeting the target H2 permeance (>1 m3/(m2.hbar) and H2/CO selectivity of >80 at temperatures of up to 300 °C and pressures of up to 25 bar with a <10% performance decline over the testing period; (ii) pelletized adsorbents were prepared for use in relevant conditions (250 °C < T < 450 °C, pressures up to 25 bar) with a working capacity of >2.5 wt.% and an attrition rate of <0.2; (iii) TEA showed that the MR-AR technology met the CO2 capture goals of 95% CO2 purity at a cost of electricity (COE) 30% less than baseline approaches.
One of the major sources of lost capacity in all-vanadium redox flow batteries (VRFBs) is the undesired transport (usually called crossover) of water and vanadium ions through the ion-exchange membrane. In this work, an experimental assessment of the impact of ion-exchange membrane properties on vanadium ion crossover and capacity decay of VRFBs has been performed. Two types of cationic membranes (non-reinforced and reinforced) with three equivalent weights of 800, 950 and 1100 g·mol -1 were investigated via a series of in situ performance and capacity decay tests along with ex situ vanadium crossover measurement and membrane characterization. For non-reinforced membranes, increasing the equivalent weight (EW) from 950 to 1100 g·mol -1 decreases the V(IV) permeability by ~30%, but increases the area-specific resistance (ASR) by ~16%. This increase in ASR and decrease in V(IV) permeability was accompanied by increased through-plane membrane swelling. Comparing the non-reinforced with reinforced membranes, membrane reinforcement increases ASR, but V(IV) permeability decreases. It was also shown that there exists a monotonic correlation between the discharge capacity decay over long-term cycling and V(IV) permeability values. Thus, V(IV) permeability is considered a representative diagnostic for assessing the overall performance of a particular ion-exchange membrane with respect to capacity fade in a VRFB.
The combination of 13C-isotopic labeling and mass spectrometry imaging (MSI) offers an approach to analyze metabolic flux in situ. However, combining isotopic labeling and MSI presents technical challenges ranging from sample preparation, label incorporation, data collection, and analysis. Isotopic labeling and MSI individually create large, complex data sets, and this is compounded when both methods are combined. Therefore, analyzing isotopically labeled MSI data requires streamlined procedures to support biologically meaningful interpretations. Using currently available software and techniques, here we describe a workflow to analyze 13C-labeled isotopologues of the membrane lipid and storage oil lipid intermediate―phosphatidylcholine (PC). Our results with embryos of the oilseed crops, Camelina sativa and Thlaspi arvense (pennycress), demonstrated greater 13C-isotopic labeling in the cotyledons of developing embryos compared with the embryonic axis. Greater isotopic enrichment in PC molecular species with more saturated and longer chain fatty acids suggest different flux patterns related to fatty acid desaturation and elongation pathways. The ability to evaluate MSI data of isotopically labeled plant embryos will facilitate the potential to investigate spatial aspects of metabolic flux in situ.
Plant phenotyping is typically a time-consuming and expensive endeavor, requiring large groups of researchers to meticulously measure biologically relevant plant traits, and is the main bottleneck in understanding plant adaptation and the genetic architecture underlying complex traits at population scale. In this work, we address these challenges by leveraging few-shot learning with convolutional neural networks to segment the leaf body and visible venation of 2,906 Populus trichocarpa leaf images obtained in the field. In contrast to previous methods, our approach (a) does not require experimental or image preprocessing, (b) uses the raw RGB images at full resolution, and (c) requires very few samples for training (e.g., just 8 images for vein segmentation). Traits relating to leaf morphology and vein topology are extracted from the resulting segmentations using traditional open-source image-processing tools, validated using real-world physical measurements, and used to conduct a genome-wide association study to identify genes controlling the traits. In this way, the current work is designed to provide the plant phenotyping community with (a) methods for fast and accurate image-based feature extraction that require minimal training data and (b) a new population-scale dataset, including 68 different leaf phenotypes, for domain scientists and machine learning researchers. All of the few-shot learning code, data, and results are made publicly available.
We present initial results from the “Ponos” zoom-in numerical simulations of dark matter substructures in massive ellipticals. Two very highly resolved dark matter halos with M {sub vir} = 1.2 × 10{sup 13} M{sub ⊙} and M {sub vir} = 6.5 × 10{sup 12} M{sub ⊙} and different (“violent” versus “quiescent”) assembly histories have been simulated down to z = 0 in a ΛCDM cosmology with a total of 921,651,914 and 408,377,544 particles, respectively. Within the virial radius, the total mass fraction in self-bound M {sub sub} > 10{sup 6} M{sub ⊙} subhalos at the present epoch is 15% for the violent host and 16.5% for the quiescent one. At z = 0.7, these fractions increase to 19% and 33%, respectively, as more recently accreted satellites are less prone to tidal destruction. In projection, the average fraction of surface mass density in substructure at a distance of R/R {sub vir} = 0.02 (∼5–10 kpc) from the two halo centers ranges from 0.6% to ≳2%, significantly higher than that measured in simulations of Milky Way-sized halos. The contribution of subhalos with M {sub sub} < 10{sup 9} M{sub ⊙} to the projected mass fraction is between one-fifth and one-third of the total, with the smallest share found in the quiescent host. We assess the impact of baryonic effects via twin, lower-resolution hydrodynamical simulations that include metallicity-dependent gas cooling, star formation, and a delayed-radiative-cooling scheme for supernova feedback. Baryonic contraction produces a super-isothermal total density profile and increases the number of massive subhalos in the inner regions of the main host. The host density profiles and projected subhalo mass fractions appear to be broadly consistent with observations of gravitational lenses.
We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of molecular line emission from d216-0939, one of the largest and most massive protoplanetary disks in the Orion Nebula Cluster. We model the spectrally resolved HCO{sup +} (4–3), CO (3–2), and HCN (4–3) lines observed at 0.′5 resolution to fit the temperature and density structure of the disk. We also weakly detect and spectrally resolve the CS (7–6) line but do not model it. The abundances we derive for CO and HCO{sup +} are generally consistent with expected values from chemical modeling of protoplanetary disks, while the HCN abundance is higher than expected. We dynamically measure the mass of the central star to be 2.17±0.07 M{sub ⊙}, which is inconsistent with the previously determined spectral type of K5. We also report the detection of a spatially unresolved high-velocity blueshifted excess emission feature with a measurable positional offset from the central star, consistent with a Keplerian orbit at 60 ± 20 au. Using the integrated flux of the feature in HCO{sup +} (4–3), we estimate the total H{sub 2} gas mass of this feature to be at least 1.8--8 M{sub Jupiter}, depending on the assumed temperature. The feature is due to a local temperature and/or density enhancement consistent with either a hydrodynamic vortex or the expected signature of the envelope of a forming protoplanet within the disk.