Predicting the decomposability of arctic tundra soil organic matter with mid infrared spectroscopy
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Soil microbial respiration is one of the largest sources of carbon (C) emissions to the atmosphere in terrestrial ecosystems, which is strongly dependent on multiple environmental variables including soil moisture. Soil moisture content is strongly dependent on soil texture, and the combined effects of texture and moisture on microbial respiration are complex and less explored. Therefore, this study examines the effects of soil moisture on the mineralization of soil organic C Soil organic carbon in three different soils, Ultisol, Alfisol and Vertisol, collected from mixed forests of Georgia, Missouri, and Texas, United States , respectively. A laboratory microcosm experiment was conducted for 90 days under different moisture regimes. Soil respiration was measured weekly, and destructive harvests were conducted at 1, 15, 60, and 90 days after incubation to determine extractable organic C (EOC), phospholipid fatty acid based microbial community, and C-acquiring hydrolytic extracellular enzyme activities (EEA). The highest cumulative respiration in Ultisol was observed at 50% water holding capacity (WHC), in Alfisol at 100% water holding capacity, and in Vertisol at 175% WHC. The trends in Extractable Organic Carbon were opposite to that of cumulative microbial respiration as the moisture levels showing the highest respiration showed the lowest EOC concentration in all soil types. Also, extracellular enzyme activities increased with increase in soil moisture in all soils, however, respiration and EEA showed a decoupled relationship in Ultisol and Alfisol soils. Soil moisture differences did not influence microbial community composition.
Microbial decomposition drives the transformation of plant-derived substrates into microbial products that form stable soil organic matter (SOM). Recent theories have posited that decomposition depends on an interaction between SOM chemistry with microbial diversity and resulting function. Here, we explicitly test these theories by coupling quantitative stable isotope probing and metabolomics to track the fate of 13C enriched substrates that vary in chemical composition as they are assimilated by microbes and transformed into new metabolic products in soil. We found that mycorrhizal-driven differences in forest nutrient economies (e.g., nutrient cycling, microbial competition) led to arbuscular mycorrhizal (AM) soils harboring greater micro8ial diversity than ectomycorrhizal (ECM) soils. When incubated with 13C enriched substrates, substrate type drove shifts in the identity of active decomposers and their metabolic products in the highly diverse AM soils. The decomposition pathways were more static in the less diverse, ECM soil. Importantly, the majority of these shifts were driven by taxa only present in the AM soil suggesting a strong link between microbial identity and specialized function. Collectively, these results highlight an important interaction between ecosystem-level processes and microbial diversity; whereby the identity and function of active decomposers impacts the composition of decomposition products that can form stable SOM.
Chemical oxidations are routinely employed in soil science to study soil organic matter (SOM), and their interpretation could be improved by characterizing oxidation effects on SOM composition with spectroscopy. We investigated the effects of routinely employed oxidants on SOM composition in a Mollic Xerofluvent representative of intensively managed agricultural soils in the California Central Valley. Soil samples were subjected to oxidation by potassium permanganate (KMnO4), sodium hypochlorite (NaOCl), and hydrogen peroxide (H2O2). Additionally, non-oxidized and oxidized soils were treated with hydrofluoric acid (HF) to evaluate reduction of the mineral component to improve spectroscopy of oxidation effects. Oxidized non-HF and HF-treated soils were characterized by diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), 13C cross polarization magic angle spinning (CP-MAS) nuclear magnetic resonance (NMR) spectroscopy, and pyrolysis molecular beam mass spectrometry (py-MBMS), and for particle size distribution (PSD) using laser diffractometry (LD). Across the range of soil organic carbon (OC) removed by oxidations (14-72%), aliphatic C-H stretch at 3000-2800 cm-1 (DRIFTS) decreased with OC removal, and this trend was enhanced by HF treatment due to significant demineralization in this soil (70%). Analysis by NMR spectroscopy was feasible only after HF treatment, and did not reveal trends between OC removal and C functional groups. Pyrolysis-MBMS did not detect differences among oxidations, even after HF treatment of soils. Hydrofluoric acid entailed OC loss (13-39%), and for H2O2 oxidized soils increased C:N and substantially decreased mean particle size. This study demonstrates the feasibility of using HF to improve characterizations of SOM composition following oxidations as practiced in soil science, in particular for DRIFTS. Since OC removal by oxidants, mineral removal by HF, and the interaction of oxidants and HF observed for this soil may differ for soils with different mineralogies, future work should examine additional soil and land use types to optimize characterizations of oxidation effects on SOM composition.
Former operations in the 100-KE Area at the Hanford Site resulted in vadose zone hexavalent chromium that provides a source of groundwater contamination. Previous efforts to remediate vadose zone chromium involved excavation and offsite treatment of contaminated soils. Although much of the chromium was removed, contamination still exists in native soil between the water table and the bottom of the pit, which has since been backfilled. In-situ soil flushing was tested at the 100-KE Area to accelerate the removal of the remaining hexavalent chromium in the vadose zone. Soil flushing works by applying clean flush water at the surface, which mobilizes and transports chromium as it migrates downward to the water table. Once the chromium reaches the water table, it is hydraulically contained, extracted, and treated through pump and treat operations. The efficacy of soil flushing is directly related to the volume of clean water that infiltrates through contaminated soils. Therefore, performance monitoring requires and understanding of flush water migration through the vadose zone. It is challenging to comprehensively assess soil flushing performance via borehole access due to the limited volume of investigation afforded by a given wellbore. As an alternative, 3D time-lapse electrical resistivity tomography (ERT) was tested as a method of monitoring the distribution of flush water over time within the vadose zone. ERT is a method of imaging the bulk electrical conductivity of the subsurface, which is highly dependent on water saturation levels in unconsolidated and unsaturated sediments. Thus, the timing and location of changes in bulk conductivity caused by soil flushing can be used to infer flush water migration pathways. In this report we present results of 3D time-lapse ERT imaging during two separate soil flushing campaigns conducted during the spring and summer months of 2022 and 2023. Results show generally that: 1) Pit backfill materials appear to nominally have larger permeability than native soils. Consequently, the boundary between pit backfill and native soil had a significant impact on flush water migration, causing some flush water to migrate along the pit boundary to the bottom of the pit. 2) Non-uniform flows, likely caused by variations in hydrogeologic properties, developed in the pit backfill materials, resulting in uneven flush water distribution on the southern margin of the soil flushing zone. 3) Redistribution of water at the interface between backfill materials and Hanford formation materials likely facilitated elevated and uniform distribution of flush water within native soils beneath the deeper parts of the pit boundary beneath the center of the flush zone, which presumably overlie soils with elevated chromium contamination. These areas appear to have been infiltrated by higher volumes of flush water than the northern and southern margins of the flush zone. 4) In comparison to 2022, high flush water application rates significantly improved flush water distribution throughout the target flushing zone. 5) Imaging resolution was limited to a depth of approximate 20 meters below the land surface, due primarily to limitations on the lateral extent of the surface ERT array. The ~10 m region of the vadose zone between approximately 130 meters elevation and the water table at approximately 120 meters elevation was unresolved.
Most agricultural soils have experienced substantial soil organic carbon losses in time. These losses motivate recent calls to restore organic carbon in agricultural lands to improve biogeochemical cycling and for climate change mitigation. Declines in organic carbon also reduce soil infiltration and water holding capacity, which may have important effects on regional hydrology and climate. To explore the regional hydroclimate impacts of soil organic carbon changes, we conduct new global climate model experiments with NASA Goddard Institute for Space Studies ModelE that include spatially explicit soil organic carbon concentrations associated with different human land management scenarios. Compared to a “no land use” case, a year 2010 soil degradation scenario, in which organic carbon content (OCC; weight %) is reduced by a factor of ∼0.12 on average across agricultural soils, resulted in soil moisture losses between 0.5 and 1 temporal standard deviations over eastern Asia, northern Europe, and the eastern United States. In a more extreme idealized scenario where OCC is reduced uniformly by 0.66 across agricultural soils, soil moisture losses exceed one standard deviation in both hemispheres. Within the model, these soil moisture declines occur primarily due to reductions in porosity (and to a lesser extent infiltration) that overall soil water holding capacity. These results demonstrate that changes in soil organic carbon can have meaningful, large-scale effects on regional hydroclimate and should be considered in climate model evaluations and developments. Further, this also suggests that soil restoration efforts targeting the carbon cycle are likely to have additional benefits for improving drought resilience.
Accurate modelling and mapping soil organic carbon are crucial for supporting soil health restoration and climate change mitigation at both regional and global scales. However, regional soil predictions often suffer from data scarcity and high prediction uncertainty. Utilizing a pre-trained global-to-regional soil carbon predictive model can be a potential solution to address this challenge. Despite its promise, how to construct and apply the global-scale model to enhance regional-scale soil carbon mapping remains largely unexplored. Here, we propose the Global Soil Carbon Pre-trained Model (GSoilCPM), a deep-learning-based domain adaptative model, to enhance regional-scale soil carbon predictions. Based on large amount of environmental covariate data and 106,167 soil samples across the globe, we verify our hypothesis of the effectiveness of this 'global-to-regional' modelling strategy. The pre-trained model can be then transferred and fine-tuned to bridge the regional- and global-scale soil–environment relationships. We applied and validated this modelling strategy in four regional-scale study areas, three in the Northern Hemisphere and one in the Southern Hemisphere, each with distinct environmental background. Compared to traditional modelling approaches as a baseline, four case studies all demonstrated significant improvement in prediction accuracy across diverse environments and varying data availabilities. The average percentage improvement across all regions is 10.93% (absolute values decreased by 1.20 g kg−1 averagely) in MAE and 29.04% (absolute values increased by 0.10 averagely) in CCC. The applicability and future horizons of using GSoilCPM were further discussed. We further reveal that regions with fewer soil samples or lower baseline accuracy benefit more from the pre-trained global model. Our findings highlight the advantages of leveraging the generalized knowledge from global models to enhance specifically localized soil modelling, positioning a potential paradigm shift in digital soil mapping, and far-reaching implications for soil monitoring and land management.
Boreal forests cover vast areas of land in the northern hemisphere and store large amounts of carbon (C) both aboveground and belowground. Wildfires, which are a primary ecosystem disturbance of boreal forests, affect soil C via combustion and transformation of organic matter during the fire itself and via changes in plant growth and microbial activity post-fire. Wildfire regimes in many areas of the boreal forests of North America are shifting towards more frequent and severe fires driven by changing climate. As wildfire regimes shift and the effects of fire on belowground microbial community composition are becoming clearer, there is a need to link fire-induced changes in soil properties to changes in microbial functions, such as respiration, in order to better predict the impact of future fires on C cycling. We used laboratory burns to simulate boreal crown fires on both organic-rich and sandy soil cores collected from Wood Buffalo National Park, Alberta, Canada, to measure the effects of burning on soil properties including pH, total C, and total nitrogen (N). We used 70-day soil incubations and two-pool exponential decay models to characterize the impacts of burning and its resulting changes in soil properties on soil respiration. Laboratory burns successfully captured a range of soil temperatures that were realistic for natural wildfire events. We found that burning increased pH and caused small decreases in C:N in organic soil. Overall, respiration per gram total (post-burn) C in burned soil cores was 16% lower than in corresponding unburned control cores, indicating that soil C lost during a burn may be partially offset by burn-induced decreases in respiration rates. Simultaneously, burning altered how remaining C cycled, causing an increase in the proportion of C represented in the modeled slow-cycling vs. fast-cycling C pool as well as an increase in fast-cycling C decomposition rates. Together, our findings imply that C storage in boreal forests following wildfires will be driven by the combination of C losses during the fire itself as well as fire-induced changes to the soil C pool that modulate post-fire respiration rates. Moving forward, we will pair these results with soil microbial community data to understand how fire-induced changes in microbial community composition may influence respiration.
The concept of soil health has evolved over the past several decades, recognizing that dynamic soil property response to management and land use is highly dependent on site-specific factors that must be considered when interpreting soil health measurements. Initially, the Soil Management Assessment Framework (SMAF) and Comprehensive Assessment of Soil Health (CASH) were developed and used globally for scoring soil health indicators. However, both SMAF and CASH frameworks were developed using a relatively small dataset and their interpretation curves were not validated at the nationwide scale. Expanding upon these concepts, we propose the Soil Health Assessment Protocol and Evaluation (SHAPE) tool. The SHAPE was developed using 14,680 soil organic C (SOC) observations from across the United States, and accounts for edaphic and climate factors at the continental scale. Data were compiled from the literature, the Cornell Soil Health Laboratory, and the Kellogg Soil Survey Laboratory. In this approach, scoring curves are Bayesian model-based estimates of the conditional cumulative distribution function (CDF) for defined soil peer groups reflecting five soil texture and five soil suborder classes adjusted for mean annual temperature and precipitation. Specifically, SHAPE produces scores between 0 and 1 (0–100%) for measured SOC values that reflect the quantile or position within the conditional CDF along with measures of uncertainty. Herein, we focus on development of the SHAPE scoring curve for SOC with our case studies. SHAPE is a flexible, quantitative tool that provides a regionally relevant interpretation of this key soil health indicator.
Lead (Pb) contaminated soils are a potential exposure hazard to the public. Amending soils with phosphorus (P) may reduce Pb soil hazards. Soil from Cleveland, OH containing 726 ± 14 mg Pb kg -1 was amended in a laboratory study with bone meal and triple super phosphate (TSP) at 5:1 P:Pb molar ratios. Soil was acidified, neturalized and re-acidified to encourage Pb phosphate formation. PRSTM-probes were used to evaluate changes in soil solution chemistry. Soil acidification did not decrease in vitro bioaccessible (IVBA) Pb using either a pH 1.5, 0.4 M glycine solution or a pH 2.5 solution with organic acids. PRSTM-probe data found soluble Pb increased 10-fold in acidic conditions compared to circumnetural pH conditions. In acidic conditions (p = 3-4), TSP treated soils increased detected P 10-fold over untreated soils. Bone meal application did not increase PRSTM-probe detected P, indicating there may have been insufficient P to react with Pb. X-ray absorption spectroscopy suggested a 10% increase in pyromorphite formation for the TSP treated soil only. Treatments increased soil electrical conductivity above 16 mS cm -1 , potentially causing a new salinity hazard. This study used a novel approach by combining the human ingestion endpoint, PRSTM-probes, and X-ray absorption spectroscopy to evaluate treatment efficacy. PRSTM-probe data indicated potentially excess Ca relative to P across incubation steps that could have competed with Pb for soluble P. More research is needed to characterize soil solutions in Pb contaminated urban soils to identify where P treatments might be effective and when competing cations, such as Ca, Fe, and Zn may limit low rate P applications for treating Pb soils.
Rewetting dry soils is associated with a burst of microbial activity and mineralization, which manifests itself as a pulse in soil CO 2 emissions, long-known as the Birch effect. In arid and semi-arid systems, soil CO 2 losses upon rewetting at the end of extended dry periods can contribute a significant fraction to the overall carbon (C) budget. Microbial biomass is one of the sources of mineralized C, as was demonstrated over 30 years ago (Kieft et al., 1987). The present paper offers a perspective on how the field has progressed since the 1987 paper was published in Soil Biology & Biochemistry, what it means in terms of current concerns about global climate change, and the needs and potential emphases of future research. Many studies since 1987 have addressed the origin of this CO 2 pulse, finding multiple possible C sources involving both biotic and abiotic processes. We propose that the magnitude of the rewetting event (Δψ) determines the relative contribution from the array of substrates that contribute to the soil CO 2 pulse upon rewetting. The magnitude of the CO 2 pulse is likely related to soil physical characteristics and to the size of the available C pool, which is partly controlled by plants. Further, the relative contributions of the mechanisms generating soil CO 2 pulses upon rewetting are likely to be modified by climate change. To understand and predict the magnitude of soil CO 2 pulses upon rewetting, we advocate continued cross-disciplinary research involving soil microbial ecology, soil physics, soil chemistry, as well as increased integration and recognition of the importance of plant-soil interactions in controlling the soil C pools contributing to soil CO 2 pulses.
The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). In this study, to assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. We show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. Lastly, these results support projections of strong carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.
The complexity of processes and interactions that drive soil C dynamics necessitate the use of proxy variables to represent soil characteristics that cannot be directly measured (correlative proxies), or that aggregate information about multiple soil characteristics into one variable (integrative proxies). These proxies have proven useful for understanding the soil C cycle, which is highly variable in both space and time, and are now being used to make predictions of the C fate and persistence under future climate scenarios. As these proxies are used at increasingly larger scales, the C pools and processes that proxies represent must be thoughtfully considered in order to minimize uncertainties in empirical understanding, as well as in model parameters and in model outcomes. The importance of these uncertainties is further amplified by the current need to make predictions of the C cycle for the non steady state environmental conditions resulting from global climate change. To clarify the appropriate uses of proxy variables, we provide specific examples of proxy variables that could improve decision making, adaptation choices, and modeling skill, while not foreclosing on – and also encouraging – continued work on their mechanistic underpinnings. We explore the use of three common soil proxies used to study soil organic matter: metabolic quotient, clay content, and physical fractionation. We also consider emerging data types, specifically genome-sequence data, and how these serve as proxies for microbial community activities. We opine that the demand for increasing mechanistic detail, and the flood of data from new imaging and genetic techniques, does not replace the value of correlative and integrative proxies--variables that are simpler, easier, or cheaper to measure. By closely examining the current knowledge gaps and broad assumptions in soil C cycling with the proxies already in use, we can develop new hypotheses and specify criteria for new and needed proxies.
Abstract Warming temperatures are likely to accelerate permafrost thaw in the Arctic, potentially leading to the release of old carbon previously stored in deep frozen soil layers. Deeper thaw depths in combination with geomorphological changes due to the loss of ice structures in permafrost, may modify soil water distribution, creating wetter or drier soil conditions. Previous studies revealed higher ecosystem respiration rates under drier conditions, and this study investigated the cause of the increased ecosystem respiration rates using radiocarbon signatures of respired CO 2 from two drying manipulation experiments: one in moist and the other in wet tundra. We demonstrate that higher contributions of CO 2 from shallow soil layers (0–15 cm; modern soil carbon) drive the increased ecosystem respiration rates, while contributions from deeper soil (below 15 cm from surface and down to the permafrost table; old soil carbon) decreased. These changes can be attributed to more aerobic conditions in shallow soil layers, but also the soil temperature increases in shallow layers but decreases in deep layers, due to the altered thermal properties of organic soils. Decreased abundance of aerenchymatous plant species following drainage in wet tundra reduced old carbon release but increased aboveground plant biomass elevated contributions of autotrophic respiration to ecosystem respiration. The results of this study suggest that drier soils following drainage may accelerate decomposition of modern soil carbon in shallow layers but slow down decomposition of old soil carbon in deep layers, which may offset some of the old soil carbon loss from thawing permafrost.
The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.
We report that Glacier forelands provide an excellent opportunity to investigate vegetation succession and soil development along the chronosequence; however, there are few studies on soil biogeochemical changes from environmental factors, aside from time. This study aimed to investigate soil development and biogeochemical changes in the glacier foreland of Midtre Lovenbreen, Svalbard, by considering various factors, including time. Eighteen vegetation and soil variables were measured at 38 different sampling sites of varying soil age, depth, and glacio-fluvial activity. Soil organic matter (SOM) was quantitatively measured, and the compositional changes in SOM were determined following size-density fractionation. In the topsoil, the soil organic carbon (SOC) and total nitrogen (N) content was found to increase along the soil chronosequence and were highly correlated with vegetation-associated variables. These findings suggest that plant-derived material was the main driver of the light fraction of SOM accumulation in the topsoil. The heavy fractions of SOM were composed of microbially transformed organic compounds, eventually contributing to SOM stabilization within short 90-yr deglaciation under harsh climatic conditions. In addition to time, the soil vertical profiles showed that other environmental parameters, also affected the soil biogeochemical properties. The high total phosphorous (P) content and electrical conductivity in the topsoil were attributed to unweathered subglacial materials and a considerable amount of inorganic ions from subglacial meltwater. The high P and magnesium content in the subsoil were attributed to parent materials, while the high sodium and potassium content in the surface soil were a result of sea-salt deposition. Glacio-fluvial runoff hampered ecosystem development by inhibiting vegetation development and SOM accumulation. This study emphasizes the importance of considering various soil-forming factors, including parent/subglacial materials, aeolian deposition, and glacio-fluvial runoff, as well as soil age, to obtain a comprehensive understanding of the ecosystem development in glacier forelands.
Coastal forests worldwide are vulnerable to a dramatic transition from upland to wetland as sea-level rise accelerates and regimes of precipitation and storms change. However, the biogeochemical impacts of shifting salinity and inundation disturbance that foreshadow forest to wetland state transitions are largely unknown. This experiment used a natural salinity gradient in a tidal creek in eastern Maryland, U.S.A., to examine how soil respiration and chemistry may change under novel salinity and inundation disturbance regimes. Soil monoliths were transplanted in a reciprocal design among plots varying in seawater exposure and elevation above the creek. We monitored the monoliths’ carbon dioxide (CO 2 ) flux for two years and performed soil chemical analyses at the end of the experiment. Soil CO 2 flux was affected by changing disturbance regimes and responses were dependent upon the salinity and inundation legacies associated with each study location. Lowland soil CO 2 flux was resistant to changing salinity and inundation disturbance, with transplanted soil monolith chemistry composition in between that of its origin and destination. Conversely, upland soil CO 2 flux was sensitive to changing salinity and inundation disturbance and remained suppressed throughout the 2-year study when exposed to wetter, saline conditions. Additionally, transplanted upland soil chemistry composition was like that of its destination, rather than origin, with upland soils displaying higher pH, base saturation, and nutrient availability relative to lowland soils. Here, we hypothesize that reductions in soil respiration rates were driven by loss of soil nutrients and osmotic and redox stress on microbial communities following exposure to seawater. Together, our results suggest that disturbance legacies shape coastal forest soil responses to changing salinity and inundation disturbance regimes. However, fully understanding the dependence of system responses on disturbance legacies requires future study across a variety of systems and spatial and temporal scales.
Currently the Department of Energy (DOE) and the nuclear industry perform seismic soil-structure interaction (SSI) analysis using equivalent linear numerical analysis tools. For lower levels of ground motion, these tools should produce reasonable in-structure response values for evaluation of existing and new facilities. For larger levels of ground motion these tools likely overestimate the in-structure response (and therefore structural demand) since they do not consider geometric nonlinearities (such as gaping and sliding between the soil and structure) and are limited in the ability to model nonlinear soil behavior. The current equivalent linear SSI (SASSI) analysis approach either joins the soil and structure together in both tension and compression or releases the soil from the structure for both tension and compression. It also makes linear approximations for material nonlinearities and generalizes energy absorption with viscous damping. This produces the potential for inaccurately establishing where the structural concerns exist and/or inaccurately establishing the amplitude of the in-structure responses. Seismic hazard curves at nuclear facilities have continued to increase over the years as more information has been developed on seismic sources (i.e. faults), additional information gathered on seismic events, and additional research performed to determine local site effects. Seismic hazard curves are used to develop design basis earthquakes (DBE) that are used to evaluate nuclear facility response. As the seismic hazard curves increase, the input ground motions (DBE’s) used to numerically evaluation nuclear facility response increase causing larger in-structure response. As ground motions increase so does the importance of including nonlinear effects in numerical SSI models. To include material nonlinearity in the soil and geometric nonlinearity using contact (gaping and sliding) it is necessary to develop a nonlinear time domain methodology. This methodology will be known as, NonLinear Soil-Structure Interaction (NLSSI). In general NLSSI analysis should provide a more accurate representation of the seismic demands on nuclear facilities their systems and components. INL, in collaboration with a Nuclear Power Plant Vender (NPP-V), will develop a generic Nuclear Power Plant (NPP) structural design to be used in development of the methodology and for comparison with SASSI. This generic NPP design has been evaluated for the INL soil site because of the ease of access and quality of the site specific data. It is now being evaluated for a second site at Vogtle which is located approximately 15 miles East-Northeast of Waynesboro, Georgia and adjacent to Savanna River. The Vogtle site consists of many soil layers spanning down to a depth of 1058 feet. The reason that two soil sites are chosen is to demonstrate the methodology across multiple soil sites. The project will drive the models (soil and structure) using successively increasing acceleration time histories with amplitudes. The models will be run in time domain codes such as ABAQUS, LS-DYNA, and/or ESSI and compared with the same models run in SASSI. The project is focused on developing and documenting a method for performing time domain, non-linear seismic soil structure interaction (SSI) analysis. Development of this method will provide the Department of Energy (DOE) and industry with another tool to perform seismic SSI analysis.