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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

MOFLUX Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: Modeling Archive

This Modeling Archive is in support the publication “Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: A Mechanistic Modeling Analysis” (Liang et al., 2021). Here we provide model code, inputs, outputs and evaluation datasets for the Microbial ENzyme Decomposition (MEND) model for the Missouri Ozarks AmeriFlux eddy covariance measurement site (MOFLUX) near Ashland, Missouri USA. The MEND model was developed with explicit representation of microbial and enzyme pools to mechanistically simulate the role of microbial organisms and extracellular enzymes in soil organic carbon (SOC) decomposition. Long-term SOC dynamics under intensified moisture extremes are studied using the MEND model that is parameterized with 11 years of measurements from the MOFLUX forest. The model explicitly represents microbial dormancy and resuscitation, different types of SOC-degrading enzymes, and how they vary with changes in soil moisture (Wang et al. 2015, 2019). A combination of two levels of frequency and severity of soil moisture, as well as a control with normal interannual variability, are used to simulate a range of moisture scenarios over 100 years. The code of Microbial-ENzyme Decomposition (MEND) as well as the input and output data are included in the archive. A user’s manual (MEND_Readme.pdf) is included with instructions for compiling and running the model to simulate soil organic carbon decomposition under various moisture scenarios. This dataset contains the modelling archive contained within a compressed (*.zip) file, a file-level metadata file in comma separate (*.csv) format, and two instructional files in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Soil physical and thermal properties from soil samples at multiple locations at Teller Road Site, Seward Peninsula, Alaska, 2019

This dataset contains results of the laboratory analysis of soil samples collected across the watershed located at miles #27 along the Teller road, near Nome, AK. The dataset includes 124 soil samples retrieved from 52 locations during the first week of August 2019. The soil samples were collected in the top 1.2 m of soil with volume known samples, analyzed with a thermal analyser to infer thermal parameters (thermal conductivity, volumetric heat capacity and thermal diffusivity), and then processed in a lab for estimation of their bulk density, water content, carbon and nitrogen content, soil texture, and elemental fractions. This dataset has one csv file and one pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Spatial variation in soil microbial processes as a result of woody encroachment depends on shrub size in tallgrass prairie

Aims: As woody plants encroach into grassland ecosystems, we expect that altered plant-soil interactions will lead to changes in the microbial processes that affect carbon storage and nutrient cycling. Specifically, this research aimed to address how (1) soil chemistry, (2) microbial nutrient demand, and (3) the rate and source of potential soil C mineralization vary spatially under individual woody shrubs of varying size within a mesic grassland. Methods: Here, we collected soil samples from the center, the midpoint between the center and edge, the edge, and the shrub-grass ecotone of multiple Cornus drummondii shrubs across a shrub-size gradient in infrequently burned tallgrass prairie. Results: We found total soil carbon and total soil nitrogen increased with shrub size in every location but the edge. Microbial demand for nitrogen also increased as shrubs increased in size. Across all shrub sizes and sampling locations, potential soil carbon mineralization rates were higher when microbes broke down proportionally more shrub-derived (C 3 ) organic matter than grass-derived (C 4 ) organic matter. Conclusions: Our results suggest that the spatio-temporal context of woody encroachment is critical for understanding its impact on belowground microbial processes. In this ecosystem, a longer period of occupancy by woody plants increases potentially mineralizable carbon.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Soil oxidoreductase zymography: Visualizing spatial distributions of peroxidase and phenol oxidase activities at the root-soil interface

Decomposition of organic material in the rhizosphere – the most dynamic microbial habitat in soil – involves arrays of oxidoreductase and hydrolytic enzymes. Spatial distributions of various hydrolytic activities in soil have already been explored by zymographic techniques. However, the distribution of oxidative activity in the rhizosphere remains to be studied. Thus, we extended a Time-Lapse Zymography technique, using Amplex Red® reagent, to visualize and quantify distributions of phenol oxidase and peroxidase activities in the rhizosphere of Zea mays L. growing in a Haplic Phaeozem and the non-rhizospheric soil. The gross oxidative activity was greatest at the root surfaces, and fell to background soil levels 1.26 and 0.73 mm from seminal (>1 mm diameter) and lateral (<0.5 mm diameter) roots, respectively. The rhizosphere extent relative to the root radius was 59% broader around lateral than around seminal roots. The greatest activities, up to 30 nmol cm –2 min –1 , were peroxidase-dominated and closely associated with roots. Here, the results confirm the utility of the approach for studying spatio-temporal distributions of oxidative activities in soil. However, actual activity of oxidoreductases in the field will be strongly controlled by fluctuating environmental conditions such as soil aeration and the gradient of reactive oxygen species, which need to be considered especially in anoxic soils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Spatial scale drives patterns in soil bacterial diversity: Spatial scale drives soil diversity

Soil microbial communities are essential for ecosystem function, but linking community composition to biogeochemical processes is challenging because of high microbial diversity and large spatial variability of most soil characteristics. We investigated soil bacterial community structure in a switchgrass stand planted on soil with a history of grassland vegetation at high spatial resolution to determine whether biogeographic trends occurred at the centimeter scale. Moreover, we tested whether such heterogeneity, if present, influenced community structure within or among ecosystems. Pronounced heterogeneity was observed at centimeter scales, with abrupt changes in relative abundance of phyla from sample to sample. At the ecosystem scale (> 10 m), however, bacterial community composition and structure were subtly, but significantly, altered by fertilization, with higher alpha diversity in fertilized plots. Moreover, by comparing these data with data from 1772 soils from the Earth Microbiome Project, it was found that 20% diverse globally sourced soil samples, while grassland soils shared approximately 40% of their operational taxonomic units with the current study. By spanning several orders of magnitude, the analysis suggested that extreme patchiness characterized community structure at smaller scales but that coherent patterns emerged at larger length scales.

16S rRNA↗
DOE OSTI2021

Soil enzymes as indicators of soil function: A step toward greater realism in microbial ecological modeling

Soil carbon (C) and nitrogen (N) cycles and their complex responses to environmental changes have received increasing attention. However, large uncertainties in model predictions remain, partially due to the lack of explicit representation and parameterization of microbial processes. One great challenge is to effectively integrate rich microbial functional traits into ecosystem modeling for better predictions. Here, using soil enzymes as indicators of soil function, we developed a competitive dynamic enzyme allocation scheme and detailed enzyme-mediated soil inorganic N processes in the Microbial-ENzyme Decomposition (MEND) model. We conducted a rigorous calibration and validation of MEND with diverse soil C-N fluxes, microbial C:N ratios, and functional gene abundances from a 12-year CO 2 × N grassland experiment (BioCON) in Minnesota, USA. In addition to accurately simulating soil CO 2 fluxes and multiple N variables, the model correctly predicted microbial C:N ratios and their negative response to enriched N supply. Model validation further showed that, compared to the changes in simulated enzyme concentrations and decomposition rates, the changes in simulated activities of eight C-N-associated enzymes were better explained by the measured gene abundances in responses to elevated atmospheric CO 2 concentration. In conclusion, our results demonstrated that using enzymes as indicators of soil function and validating model predictions with functional gene abundances in ecosystem modeling can provide a basis for testing hypotheses about microbially mediated biogeochemical processes in response to environmental changes. Further development and applications of the modeling framework presented here will enable microbial ecologists to address ecosystem-level questions beyond empirical observations, toward more predictive understanding, an ultimate goal of microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

The response of soil carbon storage and microbially mediated carbon turnover to simulated climatic disturbance in a northern peatland forest. Revisiting the concept of soil organic matter recalcitrance

The goal of this project was to investigate changes in the structure of dissolved and solid phase organic matter, the production of CO 2 and CH 4 , and the composition of decomposer microbial communities in response to the climatic forcing of environmental processes that determine the balance between carbon gas production versus storage and sequestration in peatlands. Cutting-edge analytical chemistry and next generation sequencing of microbial genes were been applied to habitats at the Marcell Experimental Forest (MEF), where the US DOE’s Oak Ridge National Laboratory and the USDA Forest Service are constructing a large-scale ecosystem study entitled, “Spruce and Peatland Responses Under Climatic and Environmental Change”(SPRUCE). Our study represented a comprehensive characterization of the sources, transformation, and decomposition of organic matter in the S1 bog at MEF. Multiple lines of evidence point to distinct, vertical zones of organic matter transformation: 1) the acrotelm consisting of living mosses, root material, and newly formed litter (0-30 cm), 2) the mesotelm, a mid-depth transition zone (30-75 cm) characterized by labile organic C compounds and intense decomposition, and 3) the underlying catotelm (below 75cm) characterized by refractory organic compounds as well as relatively low decomposition rates. These zones are in part defined by physical changes in hydraulic conductivity and water table depth. O-alkyl-C, which represents the carbohydrate fraction in the peat, was shown to be an excellent proxy for soil decomposition rates. The carbon cycle in deep peat was shown to be fueled by modern carbon sources further indicating that hydrology and surface vegetation play a role in belowground carbon cycling. We provide the first metagenomic study of an ombrotrophic peat bog, with novel insights into microbial specialization and functions in this unique terrestrial ecosystem. Vertical structuring of microbial communities closely paralleled the chemical evolution of peat, with large shifts in microbial populations occurring in the biogeochemical hotspot, the mesotelm, where the highest rates of decomposition were detected. Stable isotope geochemistry and potential rates of methane production paralleled vertical changes in methanogen community composition to indicate a predominance of acetoclastic methanogenesis mediated by the Methanosarcinales in the mesotelm, while hydrogen-utilizing methanogens dominated in the deeper catotelm. Evidence pointed to the availability of phosphorus as well as nitrogen limiting the microbially-mediated turnover of organic carbon at MEF. Prior to initiation of the experimental treatments, our study provided key baseline data for the SPRUCE site on the vertical stratification of peat decomposition, key enzymatic pathways, and microbial taxa containing these pathways. The sensitivity of soil carbon turnover to climate change is strongly linked to recalcitrant carbon stocks and the temperature sensitivity of decomposition is thought to increase with increasing molecular complexity of carbon substrates. This project delivered results on how climate change perturbations impact the microbially-mediated turnover of recalcitrant organic matter in peatland forest soils, both under controlled conditions in the laboratory and at the ecosystem-scale in the field. This project revisited the concept of “recalcitrance” in the regulation of soil carbon turnover using a combination of natural abundance radiocarbon and optical spectroscopic measurements on bulk DOM, and high resolution molecular characterization of DOM. The project elucidated how organic matter reactivity and decomposition will respond to climate change in a both a qualitative (organic matter lability) and quantitiative (increased rates) manner. An Aromaticity Index was developed to represent a more direct and accurate parameter for modeling of DOM reactivity in peatlands. The abundance and community composition of soil microorganisms that mediate C cycling were interrogated with depth in the peat, with season, and in manipulated climate enclosures at unprecedented resolution. Therefore this project delivered strategic new insights on the functioning of peatland ecosystems that collectively store approximately one-third of the world's soil carbon. Furthermore, results from the detailed characterization of DOM lability and microbial community structure/ function will be employed to further develop biogeochemical models to include microbial respiration pathways as well as to track carbon flow with a term that incorporates relative reactivity based on aromaticity index. As it stands now, detailed soil organic matter structure and microbial parameters are not included in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Remote Sensing and GIS data at 1km-grid over Chesapeake Bay used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”

The package contains the data layers used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”. The study aims to use multi-source remote sensing and GIS datasets to investigate the spatial heterogeneity and identify spatial zones with similar environmental characteristics and understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. We employed unsupervised hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, then determined the main driving factors using Random Forest regression and SHapley Additive exPlanations (SHAP). Spatial data layers include soil respiration, kernel Normalized Difference Vegetation Index (kNDVI) computed from Harmonized Landsat 8 and Sentinel-2 time series, climate variables from the Daymet dataset, land cover, biodiversity, topographical metrics, soil property, and tidal elevation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Explicitly representing soil microbial processes in Earth system models: Soil microbes in earth system models

Microbes influence soil organic matter (SOM) decomposition and the long-term stabilization of carbon (C) in soils. Herein, we contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) may make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here, we review the diversity, advantages, and pitfalls of simulating soil biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models we suggest: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding

Abstract Climate change is intensifying the global water cycle, with increased frequency of drought and flood. Water is an important driver of soil carbon dynamics, and it is crucial to understand how moisture disturbances will affect carbon availability and fluxes in soils. Here we investigate the role of water in substrate-microbe connectivity and soil carbon cycling under extreme moisture conditions. We collected soils from Alaska, Florida, and Washington USA, and incubated them under Drought and Flood conditions. Drought had a stronger effect on soil respiration, pore-water carbon, and microbial community composition than flooding. Soil response was not consistent across sites, and was influenced by site-level pedological and environmental factors. Soil texture and porosity can influence microbial access to substrates through the pore network, driving the chemical response. Further, the microbial communities are adapted to the historic stress conditions at their sites and therefore show site-specific responses to drought and flood.

58 GEOSCIENCES↗
DOE OSTI2018

Temperature sensitivity of soil organic carbon decomposition increased with mean carbon residence time: Field incubation and data assimilation

Abstract Temperature sensitivity of soil organic carbon ( SOC ) decomposition is one of the major uncertainties in predicting climate‐carbon (C) cycle feedback. Results from previous studies are highly contradictory with old soil C decomposition being more, similarly, or less sensitive to temperature than decomposition of young fractions. The contradictory results are partly from difficulties in distinguishing old from young SOC and their changes over time in the experiments with or without isotopic techniques. In this study, we have conducted a long‐term field incubation experiment with deep soil collars (0–70 cm in depth, 10 cm in diameter of PVC tubes) for excluding root C input to examine apparent temperature sensitivity of SOC decomposition under ambient and warming treatments from 2002 to 2008. The data from the experiment were infused into a multi‐pool soil C model to estimate intrinsic temperature sensitivity of SOC decomposition and C residence times of three SOC fractions (i.e., active, slow, and passive) using a data assimilation ( DA ) technique. As active SOC with the short C residence time was progressively depleted in the deep soil collars under both ambient and warming treatments, the residences times of the whole SOC became longer over time. Concomitantly, the estimated apparent and intrinsic temperature sensitivity of SOC decomposition also became gradually higher over time as more than 50% of active SOC was depleted. Thus, the temperature sensitivity of soil C decomposition in deep soil collars was positively correlated with the mean C residence times. However, the regression slope of the temperature sensitivity against the residence time was lower under the warming treatment than under ambient temperature, indicating that other processes also regulated temperature sensitivity of SOC decomposition. These results indicate that old SOC decomposition is more sensitive to temperature than young components, making the old C more vulnerable to future warmer climate.

Zhou, Xuhui↗
DOE OSTI2018

Effect of land use and soil organic matter quality on the structure and function of microbial communities in pastoral soils: Implications for disease suppression

Cropping soils vary in extent of natural suppression of soil-borne plant diseases. However, it is unknown whether similar variation occurs across pastoral agricultural systems. We examined soil microbial community properties known to be associated with disease suppression across 50 pastoral fields varying in management intensity. The composition and abundance of the disease-suppressive community were assessed from both taxonomic and functional perspectives. Pseudomonas bacteria were selected as a general taxonomic indicator of disease suppressive potential, while genes associated with the biosynthesis of a suite of secondary metabolites provided functional markers (GeoChip 5.0 microarray analysis). The composition of both the Pseudomonas communities and disease suppressive functional genes were responsive to land use. Underlying soil properties explained 37% of the variation in Pseudomonas community structure and up to 61% of the variation in the abundance of disease suppressive functional genes. Notably, measures of soil organic matter quality, C:P ratio, and aromaticity of the dissolved organic matter content (carbon recalcitrance), influenced both the taxonomic and functional disease suppressive potential of the pasture soils. Our results suggest that key components of the soil microbial community may be managed on-farm to enhance disease suppression and plant productivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

The Variable Saturation Hydraulic Conductivity Method for Improving Soil Water Content Simulation in EPIC and APEX Models

Core Ideas We propose VSHC for calculating soil water percolation in continuous models. VSHC relates permeability to daily hydraulic properties to estimate hydraulic conductivity. VSHC performed well at field scale and improved estimates of peak streamflows. Soil water percolation is a key process in the life cycle of water in fields, watersheds, and river basins. The Environmental Policy Integrated Climate (EPIC) and the Agricultural Policy/Environmental eXtender (APEX) are continuous models developed for evaluating the environmental effects of agricultural management. Traditionally, these models have simulated soil water percolation processes using a tipping‐bucket approach, with the rate of flow limited by the saturated hydraulic conductivity. This simple approach often leads to inaccuracy in simulating elevated soil water conditions where soil water content (SWC) levels may remain above field capacity under prolonged wet weather periods or limited drainage. To overcome this deficiency, a new submodel, the variable saturation hydraulic conductivity (VSHC) method, was developed for simulating soil water percolation processes using a nonlinear equation to estimate the effective hydraulic conductivity as a function of the SWC and soil properties. The VSHC method was evaluated at three sites in the United States and two sites in Europe. In addition, a numerical solution of the Richards equation was used as a benchmark for SWC comparison. Results show that the VSHC method substantially improves the accuracy of the SWC simulation in long‐term simulations, particularly during wet periods. At the watershed scale, results on the Riesel Y2 watershed indicate that the VSHC method enhances model performance in the high‐flow regime of channel peak flows because of the improved estimation of SWC, which implies that the improved SWC simulation at the field scale is beneficial to hydrologic modeling at the watershed scale.

Doro, Luca↗
DOE OSTI2019

Incorporating rhizosphere interactions and soil physical properties into a soil carbon degradation model through experimenting across ecotypes (Final Report)

Soil properties and biological communities contribute to carbon loss and gain, which vary significantly by ecosystem, but current carbon cycling models fail to incorporate interactions among these groups. We experimentally manipulated and modeled how mycorrhizal fungi and roots alter carbon dynamics in temperate, tropical, and boreal forests (see Jiang et al. 2017, Moore et al. 2015a, 2015b, in review, Zak et al. 2019, Rewcastle et al. in review). To date, we find that the influence of fungi on carbon dynamics varies by the nutrient constraints of that ecosystem. For example, in temperate forests mycorrhizal fungi compete with the free-living community to reduce carbon degradation - a pattern not seen in a boreal forest. We established a site in Costa Rica to explore the impact of fungi and roots on tropical forest carbon cycling and again found that the results were context dependent. Building on this, I held a workshop with soil carbon modelers and soil ecologists to explore how experiments and models predict carbon dynamics. We conducted a meta-analysis and ran model simulation with 5 soil carbon models. Surprisingly, we found that the spread in the models and experiments were similar - they predicted responses equally well (Sulman et al. 2018). However, the area we seemed to know little about and that produced the most spread in the models, and thus the underlying model assumptions, was the response of protected and unprotected carbon pools. These seem like exciting areas to follow-up on in the future. In addition, data from these experiments spurred numerous other studies across ecosystems and with a variety of modeling groups focusing on how plant-soil interactions alter carbon and nutrient cycling. For example, Classen wrote an Ecological Society of America invited centennial review paper on this topic in 2015. Our group hosted several workshops that resulted in the Sulman et al. (2018) paper in Biogeoscience and Classen recently attended a workshop at the University of Michigan on mycorrhizal influence on the carbon cycle that resulted in another thought piece (Zak et al. 2019) in New Phytologist and she has an invited review paper at Functional Ecology (Bennett & Classen in review) on this topic. Overall, there were >25 papers published on this topic over the grant period with 15 more papers in revision/review that were related to this project – we have at least two more papers in preparation. We trained >27 students and postdocs and participated in numerous talks, workshops, and community events promoting the importance of soils, soil diversity, and global change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Introduction to Carbon Sensing in Soil. A surface-level review of traditional and alternative methods of soil carbon measurement

Soil carbon can be divided into two categories: organic and inorganic. Soil inorganic carbon (SIC) is present in carbonate minerals in the soil and is often found in dry, arid regions. Examples of SIC include calcium carbonate (CaCO 3 ) and magnesium carbonate (MgCO 3 ), both of which play important roles in soil health. Soil organic carbon (SOC) is found in fresh plant matter (available SOC) and as humus or charcoal (inert SOC). Both types of carbon act as storage in the global carbon cycle. As a carbon sink, soil carbon has the potential to store carbon that would otherwise remain in the atmosphere as CO 2 , one of the primary greenhouse emissions. As such, soil is under increasing attention and research to be used as a sequestration (i.e., isolation) method to reduce the amount of carbon in the atmosphere. This type of carbon sequestration is called biological sequestration. SOC typically stores carbon for several decades (depending on decomposition rates) while SIC can store carbon for more than 70,000 years. Common sequestration techniques for SOC usually fall under the category of land management: planting perennials, keeping plant residue and composting, reducing tilling, and other agricultural practices that vary by region. SIC sequestration through carbonates naturally takes thousands of years but there have been studies to increase SIC sequestration through the addition of silicates.

47 OTHER INSTRUMENTATION↗