8 Search Results

Understanding microbial community properties is critical to improving the predictions of biogeochemical processes for enhancing soil carbon sequestration. Here, in this observational study, mid-infrared (MIR) spectroscopy and partial least squares regression was used to predict soil microbial and chemical properties from diverse ecosystems across the continental USA. Random calibration and validation demonstrated the prediction potential for soil properties using MIR spectra, with the strongest predictions for microbial respiration, followed by microbial biomass carbon and nitrogen, ß-glucosidase activity, as well as soil chemical properties including organic carbon and total nitrogen. Microbial properties were mainly positively correlated to spectral regions associated withmore » aliphatic C-H groups and C=O stretches of polysaccharides and negatively correlated to quartz and silicate-associated regions. We conclude that MIR spectroscopy can characterize soil microbial functions and be useful for the improvement of continental-scale soil carbon modeling and prediction programs.« less

This paper reviews the current state of high‐resolution remotely sensed soil moisture (SM) and evapotranspiration (ET) products and modeling, and the coupling relationship between SM and ET. SM downscaling approaches for satellite passive microwave products leverage advances in artificial intelligence and high‐resolution remote sensing using visible, near‐infrared, thermal‐infrared, and synthetic aperture radar sensors. Remotely sensed ET continues to advance in spatiotemporal resolutions from MODIS to ECOSTRESS to Hydrosat and beyond. These advances enable a new understanding of bio‐geo‐physical controls and coupled feedback mechanisms between SM and ET reflecting the land cover and land use at field scale (3–30 m, daily).more » Still, the state‐of‐the‐science products have their challenges and limitations, which we detail across data, retrieval algorithms, and applications. We describe the roles of these data in advancing 10 application areas: drought assessment, food security, precision agriculture, soil salinization, wildfire modeling, dust monitoring, flood forecasting, urban water, energy, and ecosystem management, ecohydrology, and biodiversity conservation. We discuss that future scientific advancement should focus on developing open‐access, high‐resolution (3–30 m), sub‐daily SM and ET products, enabling the evaluation of hydrological processes at finer scales and revolutionizing the societal applications in data‐limited regions of the world, especially the Global South for socio‐economic development.« less

Fluids generated from subducted slabs participate in the cycling of deep carbon in the crust and upper mantle. In these fluids, aqueous carbon species vary in oxidation state between +IV and -IV depending on whether the fluids are oxidizing or reducing, respectively. Most studies of subduction-zone fluids have focused on oxidized carbon species. However, recent studies of natural samples have demonstrated the occurrence of deep, reducing fluids, generated in both subducted oceanic upper mantle and crustal rocks. CH₄-H₂-rich fluid inclusions in subducted carbonated serpentinites have demonstrated the existence of abiotic, immiscible, hydrocarbon fluids at upper mantle conditions. To investigate themore » formation of such immiscible hydrocarbon fluids during the evolution of subducted carbonated serpentinites, we used equilibrium constants from the Deep Earth Water model to carry out predictive chemical mass transfer modeling to simulate the alteration reactions. A novel feature of the models was the inclusion of an immiscible hydrocarbon fluid containing six components (CH_4,f, C₂H_6,f, C₃H_8,f, isoC₄H_10,f, CO_2,f, H_2,f). This feature enabled prediction of the formation of a separate immiscible fluid in equilibrium with aqueous species and minerals. We developed a predictive reaction path model of invasive H_2,f reacting with carbonated serpentinites and interstitial aqueous fluids for comparison with the natural samples from the Lanzo Massif, western Italian Alps. Over a range of temperatures and pressures, immiscible hydrocarbon fluids formed in association with altered mineral assemblages. Reaction progress caused the transformation of carbonated serpentinites and the formation of clinopyroxene, brucite, graphite, and hydrocarbon fluids, along with changes of pH, logfO₂, and aqueous species. CH_4,f was the most abundant hydrocarbon species in all the models. The overall results at 2.0 GPa and 400 to 450 °C were consistent with the natural samples from the Lanzo Massif. Interestingly, large amounts of H₂O formed due to oxidation of H₂. More hydrocarbons and H₂O formed in models with lower fluid/rock mass ratios or with more reactant H₂. Models at different pressure and temperature conditions showed similar results with some variation in the relative stabilities of aragonite, graphite and olivine solid solution, and associated differences in mineral sequences, hydrocarbon fluids, values of aqueous species, and the final log fO₂ and pH. As a result, our models strongly support the laboratory and field evidence that reduction of carbonated serpentinites by infiltrating H₂ fluids can cause the formation of immiscible, abiotic hydrocarbon fluids in subduction zones.« less

Aucuba japonica Thunb is an evergreen woody ornamental plant with significant economic and ecological values. It also produces aucubin, showing a variety of biological activities. It is widely planted in the southwest region of China, including karst landscape areas in Guizhou Province. In January 2022, a serious leaf blight disease was observed on the leaves of A. japonica in the outdoor gardens of Guizhou University, Guiyang, Guizhou, China. The causal agent was identified as Colletotrichum aenigma through amplification and sequencing of the internal transcribed spacer (ITS) region, translation of the chitin synthase ( CHS ) and actin ( ACT )more » genes, and morphological characterizations. Koch’s postulates were confirmed by its pathogenicity on healthy leaves, including re-isolation and identification. To our knowledge, this is the first report of C. aenigma causing leaf blight on A. japonica worldwide. To identify pathogen characteristics that could be utilized for future disease management, the effects of temperature and light on mycelial growth, conidia production, and conidial germination, and the effects of humidity on conidial germination were studied. Optimal temperatures for mycelial growth of C. aenigma BY827 were 25–30°C, while 15°C and 35°C were favorable for conidia production. Concurrently, alternating 10-h light and 14-h dark, proved to be beneficial for mycelial growth and conidial germination. Additionally, conidial germination was enhanced at 90% humidity. In vitro screenings of ten chemical pesticides to assess their efficacy in suppressing C. aenigma representative strain BY827. Among them, difenoconazole showed the best inhibition rate, with an EC ₅₀ (concentration for 50% of maximal effect) value of 0.0148 μg/ml. Subsequently, field experiment results showed that difenoconazole had the highest control efficiency on A. japonica leaf blight (the decreasing rate of disease incidence and decreasing rate of disease index were 44.60 and 47.75%, respectively). Interestingly, we discovered that C. aenigma BY827 may develop resistance to mancozeb, which is not reported yet among Colletotrichum spp. strains. In conclusion, our study provided new insights into the causal agent of A. japonica leaf blight, and the effective fungicides evaluated provided an important basis and potential resource for the sustainable control of A. japonica leaf blight caused by C. aenigma in the field.« less

Subduction zones enable carbon transport to the deep Earth. Inorganic and organic carbon in fluids released from the subducted slab are important in water-rock interactions. However, the potential role of reduced carbon species in fluids during subduction is still unclear. In particular, the pressure, temperature, and oxidation state conducive to the formation of fluid hydrocarbons are poorly understood. Here we focused on the role of pressure influencing the formation of hydrocarbons using diamond anvil cell experiments starting with 0.5 M Ca-acetate solutions over a broad range of pressures, from 1.6 to 4.6 GPa at temperatures of 300 and 350°C. Dropletsmore » of immiscible hydrocarbon fluid coexisting with aqueous carbonate or bicarbonate and crystals of calcite or aragonite were formed at peak pressure and temperature conditions in the experiments. Furthermore, greater quantities of hydrocarbons formed at higher pressure as revealed by measuring the in situ volume percent of the droplets. Measurement of the in situ Raman spectra of the co-existing aqueous solutions and analysis of the peak area ratios of acetate to HCO₃^– showed faster decrease at higher pressure, which indicated that the reactions forming hydrocarbons were accelerated by pressure. Compared to previous Na-acetate experiments at 300°C and 3.0 GPa, this study found hydrocarbons that were more methane-rich and had more propane and less isobutane. In experiments at 350°C, isobutane transformed to one or more aromatic hydrocarbons in an immiscible fluid. The air-dried aromatic hydrocarbons were measured using a UV laser, and show peaks of bitumen. Overall, our study supports the hypothesis that high pressures and high temperatures facilitate the possible occurrence of immiscible hydrocarbon fluids in the deep carbon cycle.« less

Diffuse reflectance spectroscopy has been extensively employed to deliver timely and cost-effective predictions of a number of soil properties. However, although several soil spectral laboratories have been established worldwide, the distinct characteristics of instruments and operations still hamper further integration and interoperability across mid-infrared (MIR) soil spectral libraries. In this study, we conducted a large-scale ring trial experiment to understand the lab-to-lab variability of multiple MIR instruments. By developing a systematic evaluation of different mathematical treatments with modeling algorithms, including regular preprocessing and spectral standardization, we quantified and evaluated instruments' dissimilarity and how this impacts internal and shared model performance.more » We found that all instruments delivered good predictions when calibrated internally using the same instruments' characteristics and standard operating procedures by solely relying on regular spectral preprocessing that accounts for light scattering and multiplicative/additive effects, e.g., using standard normal variate (SNV). When performing model transfer from a large public library (the USDA NSSCKSSL MIR library) to secondary instruments, good performance was also achieved by regular preprocessing (e. g., SNV) if both instruments shared the same manufacturer. However, significant differences between the KSSL MIR library and contrasting ring trial instruments responses were evident and confirmed by a semi-unsupervised spectral clustering. For heavily contrasting setups, spectral standardization was necessary before transferring prediction models. Non-linear model types like Cubist and memory-based learning delivered more precise estimates because they seemed to be less sensitive to spectral variations than global partial least square regression. In summary, the results from this study can assist new laboratories in building spectroscopy capacity utilizing existing MIR spectral libraries and support the recent global efforts to make soil spectroscopy universally accessible with centralized or shared operating procedures.« less

Current carbon cycle models focus on the effects of climate and land-use change on primary productivity and microbial-mineral dependent carbon turnover in the topsoil, while less attention has been paid to vertical soil processes and soil-dependent response to land-use change along the profile. In this study, a spatial-temporal analysis was used to estimate soil organic carbon (SOC) change in topsoil/A horizon and subsoil/B horizon at National Ecological Observatory Network (NEON) sites, USA over 30 years. To separate the effects of land-use, environmental, and edaphic factors on SOC change, space-for-time substitution was used in combination with the Continuous Change Detection andmore » Classification algorithm and Structural Equation Modeling. Results showed that (a) under natural vegetation, Spodosols and Inceptisols found in the eastern NEON sites had substantial topsoil SOC accumulation (+0.4 to +1.2 Mg C ha^–1 year^–1), while Inceptisols and Andisols in the west had a comparable magnitude of topsoil SOC loss (–0.5 to –1.8 Mg C ha^–1 year^–1); (b) Mollisols and Alfisols in the Central Plains sites were susceptible to significant SOC loss under farming and grazing; (c) Runoff/erosion and leaching potential, vertical translocation, and mineral sorption were the most important factors controlling SOC variation across the NEON sites. Our work could be used to parameterize ecosystem models simulating SOC change.« less

Core Ideas A Bayesian inference approach (INLA‐SPDE) was used to map topsoil and subsoil CEC. DEM, gamma‐ray spectrometer and EM induction data were combined to map CEC. Posterior marginal distributions of the model parameters and responses were estimated. Gamma‐ray data performed best in the topsoil, followed by DUALEM421S and elevation. Elevation data performed best in the subsoil, followed by gamma‐ray and DUALEM421S. Cation exchange capacity (CEC) affects soil fertility, acidity, and structural resilience. This is particularly the case in sugarcane growing areas of Australia because the soil there is sandy (>60%), strongly acidic (pH < 5.5), and strongly sodic (exchangeablemore » sodium percentage [ESP] > 15%). Unfortunately, obtaining information on CEC at the field extent is time‐consuming and expensive. Here, we used a digital soil mapping approach to add value to limited (40) topsoil (0–0.3 m) and subsoil (0.6–0.9 m) CEC information. We first collected proximally sensed ancillary data from three sources, including a digital elevation model (DEM), γ‐ray (γ‐ray) spectrometer (RS700) and electromagnetic (EM) induction instruments. We then use a Bayesian inference approach (Integrated Nested Laplace Approximation with Stochastic Partial Differential Equation, INLA‐SPDE) implemented in R software to model the CEC and ancillary data. Accuracy (RMSE), bias (ME), and concordance (Lin's) of models were also generated from the different sources of ancillary data, either in combination or alone. We concluded, overall, that the INLA–SPDE approach could provide estimations of the posterior marginal distributions of the model parameters as well as the model responses as reported by other researchers. We also concluded that using the ancillary data sources in combination was most accurate (e.g., RMSE = 0.72) to predict CEC, least biased (e.g., ME = 0.07) and had the highest concordance (e.g., Lin's = 0.69) in both the topsoil and subsoil than using the ancillary data alone. The best ancillary data, when used alone for mapping CEC in the topsoil, was γ‐ray spectrometry, followed by EM data and elevation. For subsoil CEC, it was elevation, followed by γ‐ray spectrometry and then soil electrical conductivity (EC _a ) data. The maps of the credibility interval (CI) indicated that better predictions were achieved in the topsoil and indicated where improvements in prediction could be achieved in the subsoil.« less