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Root exudation is one of the primary processes that mediate interactions between plant roots, microorganisms, and the soil matrix, yet the mechanisms by which exudation alters microbial metabolism in soils have been challenging to unravel. Here, utilizing distinct sorghum genotypes, we characterized the chemical heterogeneity between root exudates and the effects of that variability on soil microbial membership and metabolism. Distinct exudate chemical profiles were quantified and used to formulate synthetic root exudate treatments: a high-organic-acid treatment (HOT) and a high-sugar treatment (HST). To parse the response of the soil microbiome to different exudate regimens, laboratory soil reactors were amended with these root exudate treatments as well as a nonexudate control. Amplicon sequencing of the 16S rRNA gene illustrated distinct microbial diversity patterns and membership in response to HST, HOT, or control amendments. Exometabolite changes reflected these microbial community changes, and we observed enrichment of organic and amino acids, as well as possible phytohormones in the HST relative to the HOT and control. Linking the metabolic capacity of metagenome-assembled genomes in the HST to the exometabolite patterns, we identified microorganisms that could produce these phytohormones. Our findings emphasize the tractability of high-resolution multiomics tools to investigate soil microbiomes, opening the possibility of manipulating native microbial communities to improve specific soil microbial functions and enhance crop production.
Phosphorus (P) deficiency in plants creates a variety of metabolic perturbations that decrease photosynthesis and growth. Phosphorus deficiency is especially challenging for the production of bioenergy feedstock plantation species, such as poplars (Populus spp.), where fertilization may not be practically or economically feasible. While the phenotypic effects of P deficiency are well known, the molecular mechanisms underlying whole-plant and tissue-specific responses to P deficiency, and in particular the responses of commercially valuable hardwoods, are less studied. We used a multi-tissue and multi-omics approach using transcriptomic, proteomic, and metabolomic analyses of the leaves and roots of black cottonwood (Populus trichocarpa) seedlings grown under P-deficient (5 µM P) and replete (100 µM P) conditions to assess this knowledge gap and to identify potential gene targets for selection for P efficiency. In comparison to seedlings grown at 100 µM P, P-deficient seedlings exhibited reduced dry biomass, altered chlorophyll fluorescence, and reduced tissue P concentrations. In line with these observations, growth, C metabolism, and photosynthesis pathways were downregulated in the transcriptome of the P-deficient plants. Additionally, we found evidence of strong lipid remodeling in the leaves. Metabolomic data showed that the roots of P-deficient plants had a greater relative abundance of phosphate ion, which may reflect extensive degradation of P-rich metabolites in plants exposed to long-term P-deficiency. With the notable exception of the KEGG pathway for Starch and Sucrose Metabolism (map00500), the responses of the transcriptome and the metabolome to P deficiency were consistent with one another. No significant changes in the proteome were detected in response to P deficiency. Collectively, our multi-omic and multi-tissue approach enabled the identification of important metabolic and regulatory pathways regulated across tissues at the molecular level that will be important avenues to further evaluate for P efficiency. These included stress-mediating systems associated with reactive oxygen species maintenance, lipid remodeling within tissues, and systems involved in P scavenging from the rhizosphere.
Abstract Amino acids (AAs) are modular building blocks which nature uses to synthesize both macromolecules, such as proteins, and small molecule natural products, such as alkaloids and non‐ribosomal peptides. While the 20 main proteinogenic AAs display relatively limited side chain diversity, a wide range of non‐canonical amino acids (ncAAs) exist that are not used by the ribosome for protein synthesis, but contain a broad array of structural features and functional groups. In this communication, we report the discovery of the biosynthetic pathway for a new ncAA, pazamine, which contains a cyclopropane ring formed in two steps. In the first step, a chlorine is added onto the C 4 position of lysine by a radical halogenase, PazA. The cyclopropane ring is then formed in the next step by a pyridoxal‐5′‐phosphate‐dependent enzyme, PazB, via an S N 2‐like attack at C 4 to eliminate chloride. Genetic studies of this pathway in the native host, Pseudomonas azotoformans , show that pazamine potentially inhibits ethylene biosynthesis in growing plants based on alterations in the root phenotype of Arabidopsis thaliana seedlings. We further show that PazB can be utilized to make an alternative cyclobutane‐containing AA. These discoveries may lead to advances in biocatalytic production of specialty chemicals and agricultural biotechnology.
Larkinella sp. strain BK230, a heterotrophic bacterium of the phylum Bacteroidetes , was isolated from the roots of a field-grown eastern cottonwood tree ( Populus deltoides ) located in Georgia. The draft 7.27-Mb genome has a G+C content of 53.4% and contains 6,026 coding sequences, including 41 tRNA genes.
Summary In superrosid species, root epidermal cells differentiate into root hair cells and nonhair cells. In some superrosids, the root hair cells and nonhair cells are distributed randomly (Type I pattern), and in others, they are arranged in a position‐dependent manner (Type III pattern). The model plant Arabidopsis ( Arabidopsis thaliana ) adopts the Type III pattern, and the gene regulatory network (GRN) that controls this pattern has been defined. However, it is unclear whether the Type III pattern in other species is controlled by a similar GRN as in Arabidopsis, and it is not known how the different patterns evolved. In this study, we analyzed superrosid species Rhodiola rosea , Boehmeria nivea , and Cucumis sativus for their root epidermal cell patterns. Combining phylogenetics, transcriptomics, and cross‐species complementation, we analyzed homologs of the Arabidopsis patterning genes from these species. We identified R. rosea and B. nivea as Type III species and C. sativus as Type I species. We discovered substantial similarities in structure, expression, and function of Arabidopsis patterning gene homologs in R. rosea and B. nivea , and major changes in C. sativus . We propose that in superrosids, diverse Type III species inherited the patterning GRN from a common ancestor, whereas Type I species arose by mutations in multiple lineages.
Deep learning approaches have been applied to images of C III emission in the lower divertor of DIII-D to develop models for estimating the level of detachment and magnetic configuration (X-point location and strike point radial location). The poloidal distance from the target to the C III emission front is used to represent the level of detachment. The models perform well on a test dataset not used in training, achieving $F_1$ scores as high as 0.99 for detachment state classification and root mean squared error (RMSE) as low as 2cm for front location regression. Predictions for shots with intermittent reattachment are studied, with class activation mapping used to aid in interpretation of the model predictions. Based on the success of these models, a third model was trained to predict the X-point location and strike point radial position from C III images. Though the dataset covers only a small range of possible magnetic configurations, the model shows promising results, achieving RMSE around 1cm for the test data.
Mixed forest stands tend to be more resistant to drought than species-specific stands partially due to complementarity in root ecology and physiology. For this work, we asked whether complementary differences in the drought resistance of soil microbiomes might contribute to this phenomenon. We experimented on the effects of reduced soil moisture on bacterial and fungal community composition in species-specific (single species) and mixed-species root zones of Norway spruce and European beech forests in a 5-year-old throughfall-exclusion experiment and across seasonal (spring-summer-fall) and latitudinal moisture gradients. Bacteria were most responsive to changes in soil moisture, especially members of Rhizobiales, while fungi were largely unaffected, including ectomycorrhizal fungi (EMF). Community resistance was higher in spruce relative to beech root zones, corresponding with the proportions of drought-favored (more in spruce) and drought-sensitive bacterial taxa (more in beech). The spruce soil microbiome also exhibited greater resistance to seasonal changes between spring (wettest) and fall (driest). Mixed-species root zones contained a hybrid of beech- and spruce-associated microbiomes. Several bacterial populations exhibited either enhanced resistance or greater susceptibility to drought in mixed root zones. Overall, patterns in the relative abundances of soil bacteria closely tracked moisture in seasonal and latitudinal precipitation gradients and were more predictive of soil water content than other environmental variables. We conclude that complementary differences in the drought resistance of soil microbiomes can occur and the likeliest form of complementarity in mixed-root zones coincides with the enrichment of drought-tolerant bacteria associated with spruce and the sustenance of EMF by beech.
Abstract Plant-derived phenolic acids are catabolized by soil microorganisms whose activity may enhance the decomposition of soil organic carbon (SOC). We characterized whether phenolic acid-degrading bacteria enhance SOC mineralization in forest soils when primed with 13C-labeled p-hydroxybenzoic acid (pHB). We further tested whether pHB-induced priming could explain differences in SOC content among mono-specific tree plantations in a 70-year-old common garden experiment. pHB addition primed significant losses of SOC (3–13 µmols C g−1 dry wt soil over 7 days) compared to glucose, which reduced mineralization (-3 to -8 µmols C g−1 dry wt soil over 7 days). The principal degraders of pHB were Paraburkholderia and Caballeronia in all plantations regardless of tree species or soil type, with one predominant phylotype (RP11ASV) enriched 23-fold following peak pHB respiration. We isolated and confirmed the phenolic degrading activity of a strain matching this phylotype (RP11T), which encoded numerous oxidative enzymes, including secretion signal-bearing laccase, Dyp-type peroxidase and aryl-alcohol oxidase. Increased relative abundance of RP11ASV corresponded with higher pHB respiration and expression of pHB monooxygenase (pobA), which was inversely proportional to SOC content among plantations. pobA expression proved a responsive measure of priming activity. We found that stimulating phenolic-acid degrading bacteria can prime decomposition and that this activity, corresponding with differences in tree species, is a potential mechanism in SOC cycling in forests. Overall, this study highlights the ecology and function of Paraburkholderia whose associations with plant roots and capacity to degrade phenolics suggest a role for specialized bacteria in the priming effect.
Shallow bore ground heat exchangers have been investigated in recent years because they have the potential to reduce the initial cost of the ground source heat pump system. Correctly modeling the transient heat transfer between the ground heat exchanger and the surrounding soil is essential for predicting a ground heat exchanger's performance. Simplification of the soil model could increase computation speed but sacrifice accuracy. This study investigates the impact of the soil model complexity on the annual performance prediction of a new shallow bore ground heat exchanger, the underground thermal battery (UTB). A simple 1D soil model and a more detailed 2D soil model were implemented, and they were validated against a 3D soil model. Overall, the resulting predictions of the UTB’s response from the 1D and 2D models to a given thermal load in different climates were compared. The results show that the root mean square differences between the hourly temperatures of the UTB during a year predicted using the two soil models range from 1.17°C to 3.39°C. As a result, the difference in the annual power consumption of the heat pump was between 0.7% and 3.4%. Furthermore, the dimensions of the UTB affected its performance, and a longer UTB was less sensitive to the soil models.
This report presents machine learning (ML) analysis of temperature-strain relationships for structural health monitoring of nuclear reactor stainless steel (SS) pipes with the strain gauge sensor directly printed on the pipe with a 3D conformal aerosol jet printer. We investigate correlations for two sensor pairs installed on the same SS304 pipe: commercial K-type thermocouple with a printed gold strain gauge (TC3-SG3), and commercial K-type thermocouple with commercial Kyowa strain gauge (TC0-SG0). The temperature ranges for the sensor pairs TC0-SG0 and TC3-SG3 are 20.00°C to 266.37°C and 39.95°C to 219.28°C respectively. ML algorithms in this study include Linear Regression (baseline method), Ridge Regression, Lasso Regression, and Gradient Boosting. Performance evaluation metrics include Root Mean Square Error (RMSE), Mean Square Error (MSE), Mean Absolute Error (MAE), R 2 Score, and Explained Variance. Using advanced feature engineering techniques, we extracted 27 temperature-based features and 30 strategic inclusion features. The best performance was obtained with the Gradient Boosting method, which achieves prediction accuracy of R 2 = 0.9999 and RMSE = 7.69 μStrain for TC0-SG0, and R 2 = 0.9998 and RMSE = 18.03 μStrain for TC3-SG3. While the temperature-strain correlations are weaker for the gauge directly printed on the pipe than for the commercial strain gauge, deployment-ready performance exceeding industry standards is achieved for both sensor pairs.
BACKGROUND: As the population and range of wild pigs (Sus scrofa) continue to grow across North America, there has been an increase in environmental and economic damages caused by this invasive species, and control efforts to reduce damages have increased concomitantly. Despite the expanding impacts and costs associated with population control of wild pigs, the extent to which wild pig control reduces populations and diminishes environmental and agricultural damages are rarely quantified. The goal of this study is to quantify changes in wild pig relative abundance and subsequent changes in damages caused by invasive wild pigs in response to control. RESULTS: Using a combination of wild pig population surveys, agricultural damage assessments, and environmental rooting surveys across 19 mixed forest-agricultural properties in South Carolina, USA, we quantified changes in wild pig relative abundance and associated damages over a 3-year period following implementation of a professional control program. Following implementation of control efforts, both the number of wild pig detections and estimated abundance decreased markedly. Within 24 months relative abundance was reduced by an average of ~70%, which resulted in a corresponding decline in environmental rooting damage by ~99%. CONCLUSION: Our findings suggest that sustained wild pig control efforts can substantially reduce wild pig relative abundance, which in turn resulted in a reduction in environmental rooting damage by wild pigs. Ultimately this study will help fill critical knowledge gaps regarding the efficacy of wild pig control programs and the effort needed to reduce impacts to native ecosystems, livestock, and crops. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Nickel-based Alloy 690 and the associated weld Alloys 52 and 152 are typically used for nozzle penetrations in replacement heads for pressurized water reactor (PWR) vessels, because of their excellent overall resistance to general corrosion and environmental degradation, primarily stress corrosion cracking (SCC). However, many of the existing PWRs are expected to operate for 40-80 years. Likewise, water-cooled small modular reactors (SMRs) will use Ni-Cr alloys and are expected to receive initial operating licenses for 60 years. Hence, the thermal stability of Ni-Cr alloys is a potential concern for the long-term performance of both existing and advanced nuclear power plants, and possibly spent fuel storage containers. The objective of this research is to understand the microstructural changes occurring in high-Cr, Ni-based Alloy 152 weldments during long time exposure to the reactor operating temperatures, and the effect of these changes on the service performance. One area of particular concern is the potential for long range ordering (LRO), i.e. formation of the intermetallic Ni2Cr phase under prolonged exposure to reactor temperatures and/or irradiation, which can increase strength, decrease ductility, and cause dimensional changes or lead to in-service embrittlement of components made with these alloys. Hence, this research focused on the microstructural evolution and the SCC response of Alloy 152 under accelerated thermal aging. The materials studied involved three heats of Alloy 152 used to produce a dissimilar metal weld (DMW) joining an Alloy 690 plate to an Alloy 533 low alloy steel (LAS) plate, thermally aged at three different temperatures (370°C, 400°C and 450°C) for up to 75,000h (equivalent to 60 years of service). The microstructural characterization by means of synchrotron X-ray conducted in small, 0.2 mm - step line scans in the high-deformation regions of the weld root – covering areas spanning from the weld heat affected zone (HAZ) in Alloy 690 to the weld and weld butter on LAS - did not show evidence of LRO in any of the three Alloy 152 heats aged to an equivalent of 60 years of service. Testing in a primary water environment of two heats of Alloy 152 aged at 370°C to a 60-year service equivalent revealed a fatigue and corrosion fatigue crack growth responses similar to those measured on the un-aged alloys. However, the SCC CGR response of the aged samples appears to show a deterioration in performance, confirming our previous observation.
The Energy Exascale Earth System Model (E3SM) simulates fully coupled processes and interactions among water, energy, carbon and nutrient cycles. E3SM connects vegetation and soil dynamics through nutrient uptake, plant production, litterfall and decomposition as a function of abiotic parameters (e.g. temperature and moisture). However, E3SM is designed to characterize terrestrial ecosystems and connects land and open ocean systems using a single streamflow transport term, ignoring the complex dynamics of energy, water, carbon, and nutrients in coastal systems. The goals of our project were to: (1) Parameterize a point version of E3SM to capture coastal wetland habitats and (2) Determine marsh community responses to increased temperature and elevated CO 2 . We adapted a version of the E3SM land model, previously configured to represent forested bog hydrology to a coastal ecosystem using datasets from field experiments conducted at the Smithsonian Environmental Research Center's Global Change Research Wetland (GCReW). Tidal forcing in a marsh environment was simulated using a two-column system in which the columns are connected by lateral hydrologic flows. One column simulates interactions between vegetation and soil while a second column simulates variation in water level (both tidal and sea level rise). The updated model captures many aspects of the field experiments, showing that plant community responses to environmental change are non-linear, non-additive and different between plant types. Elevated CO 2 treatments increased C 3 plant biomass more than C 4 (33% vs 17%). Temperature exacerbated CO 2 responses in C 3 plants (0 °C: 26%, 5.1 °C: 56%). We were more successful at characterizing C 3 than C 4 responses and simulating above rather than belowground biomass production. Furthermore, the next steps will include updates to key physiological parameters such as root:shoot carbon allocation and the addition of mechanistic feedbacks between vegetation and biogeochemical processes.
ABSTRACT Through their roots, trees interact with a highly complex community of microorganisms belonging to various trophic guilds and contributing to tree nutrition, development, and protection against stresses. Tree roots select for specific microbial species from the bulk soil communities. The root microbiome formation is a dynamic process, but little is known on how the different microorganisms colonize the roots and how the selection occurs. To decipher whether the final composition of the root microbiome is the product of several waves of colonization by different guilds of microorganisms, we planted sterile rooted cuttings of gray poplar obtained from plantlets propagated in axenic conditions in natural poplar stand soil. We analyzed the root microbiome at different time points between 2 and 50 days of culture by combining high-throughput Illumina MiSeq sequencing of the fungal ribosomal DNA internal transcribed spacer and bacterial 16S rRNA amplicons with confocal laser scanning microscopy observations. The microbial colonization of poplar roots took place in three stages, but bacteria and fungi had different dynamics. Root bacterial communities were clearly different from those in the soil after 2 days of culture. In contrast, if fungi were also already colonizing roots after 2 days, the initial communities were very close to that in the soil and were dominated by saprotrophs. They were slowly replaced by endophytes and ectomycorhizal fungi. The replacement of the most abundant fungal and bacterial community members observed in poplar roots over time suggest potential competition effect between microorganisms and/or a selection by the host. IMPORTANCE The tree root microbiome is composed of a very diverse set of bacterial and fungal communities. These microorganisms have a profound impact on tree growth, development, and protection against different types of stress. They mainly originate from the bulk soil and colonize the root system, which provides a unique nutrient-rich environment for a diverse assemblage of microbial communities. In order to better understand how the tree root microbiome is shaped over time, we observed the composition of root-associated microbial communities of naive plantlets of poplar transferred in natural soil. The composition of the final root microbiome relies on a series of colonization stages characterized by the dominance of different fungal guilds and bacterial community members over time. Our observations suggest an early stabilization of bacterial communities, whereas fungal communities are established following a more gradual pattern.
This dataset contains vegetation survey measurements from root ingrowth core plots (Määttä et al. 2025) inside SPRUCE Experiment plots at the Marcell Experimental Forest in northern Minnesota. Vegetation surveys were conducted in 0.25 meter2 plots containing root ingrowth cores on August 8th and 9th, 2022 (2022-08-08 to 2022-08-09). The warming and elevated carbon dioxide (CO2) treatments in the dataset include the full treatment gradient: +0 degrees Celsius (C) (+0 and +500 parts per million (ppm) elevated CO2), +2.25 degrees C (+0 and +500 ppm), +4.5 degrees C (+0 and +500 ppm elevated CO2), +6.75 degrees C (+0 and +500 ppm) and +9 degrees C (+0 and +500 ppm elevated CO2) for both hummocks and hollows. This dataset includes measurements of the height and absolute coverage (%) for each vascular plant and moss species, as well as organic litter and dead overstory vascular plants, and the distance from the grid center to the nearest tree and the species of the nearest tree. These data were used as species-specific aboveground plant metadata for assessing the warming and elevated CO2 response of fine roots across different peatland microtopographical features (hummocks and hollows) and plant functional types (shrub, spruce and larch). This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.
Abstract Quantitative constraints on past mean ocean temperature (MOT) critically inform our historical understanding of Earth's energy balance. A recently developed MOT proxy based on paleoatmospheric Xe, Kr, and N 2 ratios in ice core air bubbles is a promising tool rooted in the temperature dependences of gas solubilities. However, these inert gases are systematically undersaturated in the modern ocean interior, and it remains unclear how air‐sea disequilibrium may have changed in the past. Here, we carry out 30 tracer‐enabled model simulations under varying circulation, sea ice cover, and wind stress regimes to evaluate air‐sea disequilibrium in the Last Glacial Maximum (LGM) ocean. We find that undersaturation of all three gases was likely reduced, primarily due to strengthened high‐latitude winds, biasing reconstructed MOT by −0.38 ± 0.37°C (1σ). Accounting for air‐sea disequilibrium, paleoatmospheric inert gases indicate that LGM MOT was 2.27 ± 0.46°C (1σ) colder than the pre‐industrial era.
Summary Relative sea level rise (SLR) increasingly impacts coastal ecosystems through the formation of ghost forests. To predict the future of coastal ecosystems under SLR and changing climate, it is important to understand the physiological mechanisms underlying coastal tree mortality and to integrate this knowledge into dynamic vegetation models. We incorporate the physiological effect of salinity and hypoxia in a dynamic vegetation model in the Earth system land model, and used the model to investigate the mechanisms of mortality of conifer forests on the west and east coast sites of USA, where trees experience different form of sea water exposure. Simulations suggest similar physiological mechanisms can result in different mortality patterns. At the east coast site that experienced severe increases in seawater exposure, trees loose photosynthetic capacity and roots rapidly, and both storage carbon and hydraulic conductance decrease significantly within a year. Over time, further consumption of storage carbon that leads to carbon starvation dominates mortality. At the west coast site that gradually exposed to seawater through SLR, hydraulic failure dominates mortality because root loss impacts on conductance are greater than the degree of storage carbon depletion. Measurements and modeling focused on understanding the physiological mechanisms of mortality is critical to reducing predictive uncertainty.