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Microbial responses to long-term warming differ across soil microenvironments
Soil carbon loss is likely to increase due to climate warming, but microbiomes and microenvironments may dampen this effect. In a 30-year warming experiment, physical protection within soil aggregates affected the thermal responses of soil microbiomes and carbon dynamics. In this study, we combined metagenomic analysis with physical characterization of soil aggregates to explore mechanisms by which microbial communities respond to climate warming across different soil microenvironments. Long-term warming decreased the relative abundances of genes involved in degrading labile compounds (e.g. cellulose), but increased those genes involved in degrading recalcitrant compounds (e.g. lignin) across aggregate sizes. These changes were observed in most phyla of bacteria, especially for Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, and Planctomycetes. Microbial community composition was considerably altered by warming, leading to declined diversity for bacteria and fungi but not for archaea. Microbial functional genes, diversity, and community composition differed between macroaggregates and microaggregates, indicating the essential role of physical protection in controlling microbial community dynamics. Our findings suggest that microbes have the capacity to employ various strategies to acclimate or adapt to climate change (e.g. warming, heat stress) by shifting functional gene abundances and community structures in varying microenvironments, as regulated by soil physical protection.
Cover crops and poultry litter impact on soil structural stability in dryland soybean production in southeastern United States
Abstract This study explored the efficacy of soil aggregate indices in quantifying soil structural development, utilizing 5‐year field experiment data from the Southeastern United States. The experiment utilized a split‐plot design with cover crops (native vegetation as control, cereal rye (Secale cerealeL.), winter wheat (Triticum aestivum), hairy vetch (Vicia villosa), and mustard (Brassica rapa) plus cereal rye as the main factor and fertilizer source (no fertilizer as control, inorganic fertilizer with phosphorus, potassium, and elemental sulfur, and poultry litter) as the secondary factor. Aggregate size fractions were determined using the wet‐sieving method, and aggregate stability index (ASI), mean weight diameter (MWD), geometric mean diameter (GMD), and fractal dimension (FD) were calculated to assess soil structural stability. Main effects results indicated that cereal rye (55.11%) and poultry litter (50.97%) exhibited the highest ASI values. The highest MWD, GMD, and FD were observed under mustard plus cereal rye (1.187 mm), cereal rye (0.462 mm), and hairy vetch (2.573), respectively. Principal component analysis revealed that cover crops significantly improved soil aggregate structure and stability, overcoming limitations of sole fertilization practices. Regression analysis suggested that ASI, MWD, and GWD positively correlated with soil organic carbon, whereas FD negatively correlated with MWD, GMD, and ASI. Principal component analysis exhibited that FD decreased with increasing soil organic carbon, ASI, MWD, and GMD, demonstrating that lower FD values indicate enhanced soil aggregation and structure. Assessed indices, FD included, effectively gauged soil structural stability. These metrics should be prioritized in managerial decisions to support soil productivity and health in agricultural systems.
Aggregating available soil water holding capacity data for crop yield models
The total amount of water available to plants that is held against gravity in a soil is usually estimated as the amount present at -0.03 MPa average water potential minus the amount present at -1.5 MPa water potential. This value, designated available water-holding capacity (AWHC), is a very important soil characteristic that is strongly and positively correlated to the inherent productivity of soils. In various applications, including assessing soil moisture status over large areas, it is necessary to group soil types or series as to their productivity. Current methods to classify AWHC of soils consider only total capacity of soil profiles and thus may group together soils which differ greatly in AWHC as a function of depth in the profile. A general approach for evaluating quantitatively the multidimensional nature of AWHC in soils is described. Data for 902 soil profiles, representing 184 soil series, in Indiana were obtained from the Soil Characterization Laboratory at Purdue University. The AWHC for each of ten 150-mm layers in each soil was established, based on soil texture and parent material. A multivariate clustering procedure was used to classify each soil profile into one of 4, 8, or 12 classes based upon ten-dimensional AWHC values. The optimum number of classes depends on the range of AWHC in the population of oil profiles analyzed and on the sensitivity of a crop to differences in distribution of water within the soil profile.
Observed effects of soil organic matter content on the microwave intensity of soils
In order to determine the significance of organic matter content on the microwave emissivity of soils when estimating soil moisture, field experiments were conducted in which 1.4 GHz microwave emissivity data were collected over test plots of sandy loam soil with different organic matter levels (1.8, 4.0, and 6.1 percent) for a range of soil moisture values. Analyses of the observed data show only minor variation in microwave emissivity due to a change in organic matter content at a given moisture level for soils with similar texture and structure. Predictions of microwave emissivity made using a dielectric model for aggregated soils exhibit the same trends and type of response as the measured data when appropriate values for the input parameters were utilized.
Observed effects of soil organic matter content on the microwave emissivity of soils
In order to determine the significance of organic matter content on the microwave emissivity of soils when estimating soil moisture, field experiments were conducted in which 1.4 GHz microwave emissivity data were collected over test plots of sandy loam soil with different organic matter levels (1.8, 4.0, and 6.1 percent) for a range of soil moisture values. Analyses of the observed data show only minor variation in microwave emissivity due to a change in organic matter content at a given moisture level for soils with similar texture and structure. Predictions of microwave emissivity made using a dielectric model for aggregated soils exhibit the same trends and type of response as the measured data when appropriate values for the input parameters were utilized.
Emerging multiscale insights on microbial carbon use efficiency in the land carbon cycle
Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling.
Getting to the root of the problem: Soil carbon and microbial responses to root inputs within a buried paleosol along an eroding hillslope in southwestern Nebraska, USA
Large quantities of soil carbon (C) can persist within paleosols for millennia due to burial and subsequent isolation from plant-derived inputs, atmospheric conditions, and microbial activity at the modern surface. Erosion exposes buried soils to modern root-derived C influx via root exudation and root turnover, thus stimulating microbial activity leading to SOC decomposition and accumulation through organo-mineral stabilization of modern C. With this study we aim to quantify how modern root-derived C inputs impact paleosol C decomposition and stabilization across varying degrees of isolation from modern surface conditions in southwestern Nebraska, USA, where hillslope erosion is bringing a buried Late-Pleistocene-early Holocene paleosol (the “Brady Soil”) closer to the modern surface. We collected Brady Soil samples from 0.2m, 0.4m, and 1.2m below the modern surface and conducted two lab-based incubations. Soils were amended with either (1) a lab-synthesized mixture of low molecular weight compounds (12 atom% 13 C), or (2) 13 C enriched root residues (92 atom% 13 C), in 30-day and 240-day incubation experiments, respectively. Here we determined microbial responses to synthetic root exudates and residues by partitioning the 13 C label from Brady Soil C, including measurements of total, root, and primed C respiration, microbial biomass C (MBC), microbial C use efficiency (CUE). To assess the capacity of isolated paleosols to accrue modern plant C, we used Nano-scale Secondary Ion Mass Spectrometry imaging. We found that: (1) adding root-derived C inputs primed Brady Soil C across all depths, and was mediated by depth and composition of root additions; (2) root-derived C inputs stimulated microbial biomass C (MBC) growth similarly across depths, but the magnitude of CUE and MBC varied by chemistry of root-derived additions; (3) new particulate organic matter was incorporated into mineral-associated pools over time; (4) material from the added root residues was found in association with bacterial cells and fungal hyphae as well as with soil aggregate and mineral surfaces. Our study shows that paleosols defy expectations of C content and reactivity with depth, and changes in land cover and climate will expose buried paleosols to modern surface conditions, increasing respired C. This work highlights the importance of evaluating the role resurfacing buried soils through landscape change plays in C cycle feedbacks to the climate system.
Extraction of amino acids from soils and sediments with superheated water
A method of extraction for amino acids from soils and sediments involving superheated water has been investigated. About 75-97 per cent of the amino acids contained in four soils of a soil profile from Illinois were extracted by this method. Deep penetration of water into soil aggregates and partial hydrolysis of peptide bonds during this extraction by water at high temperature are likely mechanisms responsible for the release of amino acids from samples. This extraction method does not require subsequent desalting treatments when analyses are carried out with an ion-exchange amino acid analyzer.
1985 International Geoscience and Remote Sensing Symposium (IGARSS '85), University of Massachusetts, Amherst, October 7-9, 1985, Proceedings
Papers are presented on an EM subsurface radar based on the transient field radiated by a wire antenna; the microwave dielectric, structural, and salinity properties of simulated sea ice; the extraction of sea-ice data from satellite SAR imagery, and the probing of thick vegetation canopies with a field microwave scatterometer. Also discussed are the bidirectional reflectance modeling of a conifer forest canopy, a microwave dielectric model for aggregated soils, and the estimation of soil hydraulic parameters with passive microwave data.
How the Emitted Size Distribution and Mixing State of Feldspar Affect Ice Nucleating Particles in a Global Model
The effect of aerosol particles on ice nucleation and, in turn, the formation of ice and mixed phase clouds is recognized as one of the largest sources of uncertainty in climate prediction. We apply an improved dust mineral specific aerosol module in the NASA GISS Earth System ModelE, which takes into account soil aggregates and their fragmentation at emission as well as the emission of large particles. We calculate ice nucleating particle concentrations from K-feldspar abundance for an active site parameterization for a range of activation temperatures and external and internal mixing assumption. We find that the globally averaged INP concentration is reduced by a factor of two to three, compared to a simple assumption on the size distribution of emitted dust minerals. The decrease can amount to a factor of five in some geographical regions. The results vary little between external and internal mixing and different activation temperatures, except for the coldest temperatures. In the sectional size distribution, the size range 24 micrometer contributes the largest INP number.
Insights Into the Size-Resolved Dust Emission From Field Measurements in the Moroccan Sahara
The particle size distribution (PSD) of mineral dust has a strong effect on the impacts of dust on climate. However, our understanding of the emitted dust PSD, including its variability and the fraction of super-coarse dust (diameter >10 µm), remains limited. Here, we provide new insights into the size-resolved dust emission process based on a field campaign performed in the Moroccan Sahara in September 2019 in the context of the FRontiers in dust minerAloGical coMposition and its Effects upoN climaTe (FRAGMENT) project. The obtained dust concentration and diffusive flux PSDs show significant dependencies upon the friction velocity (u*), wind direction and type of event (regular events versus haboob events). For instance, the number fraction of sub-micrometre particles increases with u*, along with a large decrease in the mass fraction of super-coarse dust. We identify dry deposition, which is modulated by u* and fetch length, as a potential cause for this PSD variability. Using a resistance model constrained with field observations to estimate the dry deposition flux and thereby also the emitted dust flux, we show that deposition could represent up to ∼90 % of the emission of super-coarse particles (>10 µm) and up to ∼65 % of the emission of particles as small as ∼5 µm in diameter. Importantly, removing the deposition component significantly reduces the variability with u* in the PSD of the emitted dust flux compared with the diffusive flux, particularly for super-coarse dust. The differences between regular and haboob event concentration and diffusive flux PSDs are suspected to result from a smaller and variable dust source fetch during the haboob events, and/or an increased resistance of soil aggregates to fragmentation associated with the observed increase in relative humidity along the haboob outflow. Finally, compared to the invariant emitted dust flux PSD estimated based on brittle fragmentation theory, we obtain a substantially higher proportion of super-micrometre particles in the dust flux. Overall, our results suggest that dry deposition needs to be adequately considered to estimate the emitted PSD, even in studies limited to the fine and coarse size ranges (<10 µm).
Predicting the Mineral Composition of Dust Aerosols: Representing Key Processes - Part 1
Soil dust aerosols created by wind erosion are typically assigned globally uniform physical and chemical properties within Earth system models, despite known regional variations in the mineral content of the parent soil. Mineral composition of the aerosol particles is important to their interaction with climate, including shortwave absorption and radiative forcing, nucleation of cloud droplets and ice crystals, heterogeneous formation of sulfates and nitrates, and atmospheric processing of iron into bioavailable forms that increase the productivity of marine phytoplankton. Here, aerosol mineral composition is derived by extending a method that provides the composition of a wet-sieved soil. The extension accounts for measurements showing significant differences between the mineral fractions of the wetsieved soil and the emitted aerosol concentration. For example, some phyllosilicate aerosols are more prevalent at silt sizes, even though they are nearly absent at these diameters in a soil whose aggregates are dispersed by wet sieving. We calculate the emitted mass of each mineral with respect to size by accounting for the disintegration of soil aggregates during wet sieving. These aggregates are emitted during mobilization and fragmentation of the original undispersed soil that is subject to wind erosion. The emitted aggregates are carried far downwind from their parent soil. The soil mineral fractions used to calculate the aggregates also include larger particles that are suspended only in the vicinity of the source. We calculate the emitted size distribution of these particles using a normalized distribution derived from aerosol measurements. In addition, a method is proposed for mixing minerals with small impurities composed of iron oxides. These mixtures are important for transporting iron far from the dust source, because pure iron oxides are more dense and vulnerable to gravitational removal than most minerals comprising dust aerosols. A limited comparison to measurements from North Africa shows that the model extensions result in better agreement, consistent with a more extensive comparison to global observations as well as measurements of elemental composition downwind of the Sahara, as described in companion articles.
Predicting the Mineral Composition of Dust Aerosols: Model Evaluation and Identification of Key Processes with Observations - Part 2
A global compilation of nearly sixty measurement studies is used to evaluate two methods of simulating the mineral composition of dust aerosols in an Earth system model. Both methods are based upon a Mean Mineralogical Table (MMT) that relates the soil mineral fractions to a global atlas of arid soil type. The Soil Mineral Fraction (SMF) method assumes that the aerosol mineral fractions match the fractions of the soil. The MMT is based upon soil measurements after wet sieving, a process that destroys aggregates of soil particles that would have been emitted from the original, undisturbed soil. The second method approximately reconstructs the emitted aggregates. This model is referred to as the Aerosol Mineral Fraction (AMF) method because the mineral fractions of the aerosols differ from those of the wet-sieved parent soil, partly due to reaggregation. The AMF method remedies some of the deficiencies of the SMF method in comparison to observations. Only the AMF method exhibits phyllosilicate mass at silt sizes, where they are abundant according to observations. In addition, the AMF quartz fraction of silt particles is in better agreement with measured values, in contrast to the overestimated SMF fraction. Measurements at distinct clay and silt particle sizes are shown to be more useful for evaluation of the models, in contrast to the sum over all particles sizes that is susceptible to compensating errors, as illustrated by the SMF experiment. Model errors suggest that allocation of the emitted silt fraction of each mineral into the corresponding transported size categories is an important remaining source of uncertainty. Evaluation of both models and the MMT is hindered by the limited number of size-resolved measurements of mineral content that sparsely sample aerosols from the major dust sources. The importance of climate processes dependent upon aerosol mineral composition shows the need for global and routine mineral measurements.
Data for: Miscanthus × giganteus changes soil structure and increases maximum water holding capacity
The data provided include results from a comparative study evaluating the impact of Miscanthus × giganteus (miscanthus) versus maize on soil structural properties and maximum water holding capacity (MWHC) across two Iowa sites. The dataset includes MWHC values determined using the Funnel Filter Paper Drainage (FFPD) method, as well as additional measurements of MWHC following structural disruption of the soil to isolate the effect of aggregation. It also contains three-dimensional micro-computed tomography (microCT) data used to quantify total porosity and pore size distribution (PSD) of soil aggregates at a 5 µm resolution. All data are provided as raw replicate-level measurements, organized by site, crop, and depth, along with processed summary files in table form in CSV (.csv) format to support reproducibility and downstream analysis.
Remote spectral identification of surface aggregates by thermal imaging techniques - Progress report
The NASA Thermal Infrared Multispectral Scanner (TIMS) has been successfully used for the remote identification of a variety of soil and aggregate deposits in vegetated areas of two states. Over three million cubic meters of gravel deposits were identified from the imagery during a two year period. Verification was accomplished by ground reconnaissance using drilling machinery and by ground instrumentation. The method has been used to differentiate between fine and coarse grained soils, and gravel deposits. The deposits were found to have been naturally sorted according to grain size by depositional processes, providing each deposit with distinct spectral qualities. It was found that the masking effects of relatively dense vegetation were largely overcome by using imagery acquired at higher altitudes above terrain than 9000 meters, due to loss of resolution of the finer detail. The mechanics of image resolution are discussed, a method of data analysis used is described, and sample spectral signatures are illustrated.
Aspects of spatial and temporal aggregation in estimating regional carbon dioxide fluxes from temperate forest soils
We examine the influence of aggregation errors on developing estimates of regional soil-CO2 flux from temperate forests. We find daily soil-CO2 fluxes to be more sensitive to changes in soil temperatures (Q(sub 10) = 3.08) than air temperatures (Q(sub 10) = 1.99). The direct use of mean monthly air temperatures with a daily flux model underestimates regional fluxes by approximately 4%. Temporal aggregation error varies with spatial resolution. Overall, our calibrated modeling approach reduces spatial aggregation error by 9.3% and temporal aggregation error by 15.5%. After minimizing spatial and temporal aggregation errors, mature temperate forest soils are estimated to contribute 12.9 Pg C/yr to the atmosphere as carbon dioxide. Georeferenced model estimates agree well with annual soil-CO2 fluxes measured during chamber studies in mature temperate forest stands around the globe.
WHONDRS laboratory time series moisture manipulative experiment from soil core layers across eastern contiguous US: time series aerobic respiration, geochemistry, and aggregates
This dataset supports a broader study examining the effects of wetting and drying on soil layers across the eastern contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata. Samples were collected as part of a collaboration between WHONDRS (Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems; https://whondrs.pnnl.gov) and MONet (Molecular Observation Network; https://www.emsl.pnnl.gov/monet). The field samples (soil cores) were labeled as MEL_##_COR and subsequent subsamples begin with MEL_##. Additional subsamples were taken for the laboratory experiment and were labeled as EL_##. The labels from the MEL field samples and the EL subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EL_01 is a subsample from MEL_01). See the critical details section below for more details on sample naming and experimental design.For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) a subfolder with soil sample data from field samples and the incubation experiment. The sample data subfolder contains (1) effect size; (2) gravimetric moisture from field samples and incubation experiment; (3) respiration rates, raw dissolved oxygen values, and plots; (4) specific conductance, pH, and temperature from the incubation; (5) soil aggregates; (6) a summary containing median values of each data type for each treatment (wet and dry) in the incubation; (7) a summary containing averages for each data type of each soil layer; and (8) methods codes. All files are .csv, .pdf, .jpeg, or .jpg.