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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Soil pH Buffering Capacity, Geochemical Characterization, and Soil Water Retention for Arctic Soils of Seward Peninsula and Utqiagvik, Alaska, 2013-2019

This dataset provides pH titration data and soil pH buffering capacities of 21 Arctic soils that were collected between 2013-2019. Geochemical data including soil organic carbon, carbon:nitrogen ratio, initial pH, and gravimetric water content are also reported. Additional measurements of cation exchange capacity and soil water retention (dry range) are presented for selected soils. A script, developed in R, is also included for a simple biogeochemical simulation that incorporates soil pH buffering capacity. This dataset contains 7 csv files and one R script.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 OSTI2025

Dynamic soil columns simulate Arctic redox biogeochemistry and carbon release during changes in water saturation

Thawing Arctic permafrost can induce hydrologic change and alter redox conditions, shifting the balance of soil organic matter (SOM) decomposition. There remains uncertainty about how soil saturation and redox transitions impact dissolved and gas phase carbon fluxes, and efforts to link hydrobiogeochemical processes to ecosystem-scale models are limited. This study evaluates SOM decomposition of Arctic tundra soils using column experiments, water chemistry measurements, microbial community analysis, and a PFLOTRAN reactive transport model. Soil columns from a thermokarst channel (TC) and an upland tundra (UC) were exposed to cycles of saturation and drainage, which controlled carbon emissions. During saturation, an outflow of dissolved organic carbon from the UC soil correlated with elevated reduced iron and decreased pH; during drainage, UC carbon dioxide fluxes were 70% higher than TC fluxes. Intermittent methane release was observed for TC, consistent with higher methanogen abundance. Slower drainage in the TC soil correlated with more subtle biogeochemical changes. PFLOTRAN simulations captured experimental trends in soil carbon fluxes, oxygen concentrations, and water contents. The model was then used to evaluate additional soil water drainage rates. This study emphasizes the importance of considering hydrologic change when evaluating and simulating SOM decomposition in dynamic Arctic tundra environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Temporal patterns of fine‐root dynamics have little influence on seasonal soil CO 2 efflux in a mixed, mesic forest

Among the contributors to soil CO 2 efflux, there remains uncertainty about the contribution of root activity to the overall soil efflux. Soil water and temperature frequently have been used to predict a large portion of the variation in soil CO 2 efflux. We hypothesized that fine-root dynamics explain most of the remaining variability in soil CO 2 efflux that cannot be explained by soil temperature and water content. We anticipated that seasonal increases in root production, mortality via decomposition, and standing crop would result in corresponding increases in soil CO 2 efflux. We tested our hypotheses by collecting and analyzing two years of minirhizotron and soil chamber CO 2 flux data from plots distributed throughout the Shale Hills Catchment of the Susquehanna-Shale Hills Critical Zone Observatory in Central Pennsylvania, USA. Here we showed that: (1) seasonal fluctuations in fine-root dynamics yielded only a very small increase in the predictability of soil CO 2 efflux; (2) fine-root mortality effects on soil CO 2 efflux were strongly tied to soil temperature; (3) fluctuations in fine-root presence or standing mass independent of temperature and moisture had little effect on soil CO 2 efflux; and (4) new fine-root length and root length mortality had limited impacts on soil CO 2 efflux rates. We conclude that, at least in temperate forests on rocky soils, characterizing fine-root dynamics may provide only limited improvement in the estimation of soil CO 2 efflux.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A network of soil moisture, soil temperature, air temperature, net radiation, ground heat flux and ground water for Chicago, Illinois

This dataset contains environmental monitoring data collected using solar-powered Multi-Function Research (MFR) Long Range Wide Area (LoRaWAN)-enabled nodes at 11 sites in Chicago, Illinois, as part of the DOE Urban Integrated Field Lab CROCUS project. The MFR node system consists of an Input/Output Digital Input Module (IB8) interface box (ICT International) providing wired connections for environmental sensors and an MFR-Node-L data logger that manages power, data processing, and LoRaWAN communication. The wireless data are ingested via Sage network (https://sagecontinuum.org/) nodes that contain LoRaWAN antennae. Measurements were collected from 11 MFR nodes deployed across Chicago State University (CSU), Northeastern Illinois University (NEIU), Northwestern University (NU), University of Illinois Chicago (UIC), West Woodlawn "Blacks in Green" (BIG), and Indian Boundary Prairies (IBP). Each MFR node supports a consistent suite of sensors measuring atmospheric, soil, and hydrological variables. Atmospheric measurements include 2m air temperature (°C), 2m vapor pressure deficit (kPa), and 2m shortwave/longwave radiation (incoming and outgoing, W/m²) measured using ATH-VPD and Apogee SN500 sensors. Soil measurements include volumetric water content (VWC, %) and temperature (°C) at four depths (15, 30, 45, and 60 cm below surface) using Meter Teros54 sensors, and heat flux (W/m²) at 10 cm depth using Huske HFP01-05 sensors. At selected locations, Meter Hydros21 sensors measure groundwater depth (mm), specific conductivity (dS/m), and temperature (°C). The dataset includes timestamps, site identifiers with location names, device IDs, Global Positioning System (GPS) coordinates, variable names with units, measurement depths, values, sensor names, and Sage node identifiers. All timestamps are in local Chicago time (CDT/CST). Quality control flags are provided using a 6-bit binary system indicating physical range violations, step spikes, 24-hour flat-line conditions, 6-hour jitter, 7-day ultra-low variance, and persistent high offset. Data is provided in CSV and CF-compliant NetCDF formats. This dataset is part of a larger collection of CROCUS environmental monitoring data, including linked datasets from Air Quality Transmitter (AQT) sensors, Weather Transmitter (WXT) sensors, and Sap Flow Meter (SFM1x) sensors.

Chicago↗
DOE OSTI2021

Temporal, Spatial, and Temperature Controls on Organic Carbon Mineralization and Methanogenesis in Arctic High-Centered Polygon Soils

Warming temperatures in continuous permafrost zones of the Arctic will alter both hydrological and geochemical soil conditions, which are strongly linked with heterotrophic microbial carbon (C) cycling. Heterogeneous permafrost landscapes are often dominated by polygonal features formed by expanding ice wedges: water accumulates in low centered polygons (LCPs), and water drains outward to surrounding troughs in high centered polygons (HCPs). These geospatial differences in hydrology cause gradients in biogeochemistry, soil C storage potential, and thermal properties. Presently, data quantifying carbon dioxide (CO 2 ) and methane (CH 4 ) release from HCP soils are needed to support modeling and evaluation of warming-induced CO 2 and CH 4 fluxes from tundra soils. This study quantifies the distribution of microbial CO 2 and CH 4 release in HCPs over a range of temperatures and draws comparisons to previous LCP studies. Arctic tundra soils were initially characterized for geochemical and hydraulic properties. Laboratory incubations at −2, +4, and +8°C were used to quantify temporal trends in CO 2 and CH 4 production from homogenized active layer organic and mineral soils in HCP centers and troughs, and methanogen abundance was estimated from mcrA gene measurements. Results showed that soil water availability, organic C, and redox conditions influence temporal dynamics and magnitude of gas production from HCP active layer soils during warming. At early incubation times (2–9 days), higher CO 2 emissions were observed from HCP trough soils than from HCP center soils, but increased CO 2 production occurred in center soils at later times (>20 days). HCP center soils did not support methanogenesis, but CH 4 -producing trough soils did indicate methanogen presence. Consistent with previous LCP studies, HCP organic soils showed increased CO 2 and CH 4 production with elevated water content, but HCP trough mineral soils produced more CH 4 than LCP mineral soils. HCP mineral soils also released substantial CO 2 but did not show a strong trend in CO 2 and CH 4 release with water content. Knowledge of temporal and spatial variability in microbial C mineralization rates of Arctic soils in response to warming are key to constraining uncertainties in predictive climate models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Time-domain reflectometer survey across the East River Watershed, Colorado

Lawrence Berkeley National Laboratory (LBNL) collected near-surface point-measurements of soil temperature (file variable TDR_T(C)), volumetric water content (file variable TDR_SM(VWC%)), and soil electrical conductivity (file variable TDR_EC(mS/m)) using a time-domain reflectometer (TDR) at a depth of 25 cm. The survey aimed to characterize the spatial heterogeneity of near-surface hydrological properties at the hillslope scale considering sites with different aspects and elevation within the watershed. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. These data were collected in early July 2019 over four hillslope sites: Pumphouse (north-east facing slope), Bradley (west and east-facing slopes), and Snodgrass (east-facing slope) within the East River watershed. Part of this survey was used to investigate soil-plant interactions at the hillslope scale in Jashvina et al. 2020.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of an Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST by extending the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5,000 annual synthetic storm events in a 2,227 $km^2$ Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.

58 GEOSCIENCES↗
DOE OSTI2025

Remote Sensing of Live Fuel Moisture for Wildfires Using SMAP Satellite Observations

Live Fuel Moisture (LFM) is a critical parameter for wildfire risk assessment, traditionally measured by labor-intensive field sampling. However, sampled LFM data are influenced by site-specific factors, such as local vegetation types and plant traits, and are often collected retrospectively after wildfire events, making it difficult to obtain pre-fire data for predictive applications. Here, we evaluate the relationship between LFM and Vegetation Water Content (VWC) and Soil Moisture (SM) retrieved from SMAP L-band brightness temperature using the Maximum Entropy Production (MEP) approach. The MEP-retrieved VWC exhibited strong correlation with in situ measurements of LFM ( r > 0.6) in the Western U.S. The integration of high-resolution vegetation coverage data enhances the detection of sub-grid vegetation heterogeneity. This study demonstrates the operational potential of remote sensing derived VWC as a scalable proxy of LFM, supporting its application in regional assessment of wildfire risk.

Cho, Kyeungwoo [Georgia Institute of Technology, A↗
DOE OSTI2022

Impact of the numerical solution approach of a plant hydrodynamic model (v0.1) on vegetation dynamics

Abstract. Numerous plant hydrodynamic models have started to be implemented in vegetation dynamics models, reflecting the central role of plant hydraulic traits in driving water, energy, and carbon cycles, as well as plant adaptation to climate change. Different numerical approximations of the governing equations of the hydrodynamic models have been documented, but the numerical accuracy of these models and its subsequent effects on the simulated vegetation function and dynamics have rarely been evaluated. Using different numerical solution methods (including implicit and explicit approaches) and vertical discrete grid resolutions, we evaluated the numerical performance of a plant hydrodynamic module in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES-HYDRO version 0.1) based on single-point and global simulations. Our simulation results showed that when near-surface vertical grid spacing is coarsened (grid size >10 cm), the model significantly overestimates aboveground biomass (AGB) in most of the temperate forest locations and underestimates AGB in the boreal forest locations, as compared to a simulation with finer vertical grid spacing. Grid coarsening has a small effect on AGB in the tropical zones of Asia and South America. In particular, coarse surface grid resolution should not be used when there are large and prolonged water content differences among soil layers at depths due to long dry-season duration and/or well-drained soil or when soil evaporation is a dominant fraction of evapotranspiration. Similarly, coarse surface grid resolution should not be used when there is lithologic discontinuity along the soil depth. This information is useful for uncertainty quantification, sensitivity analysis, or the training of surrogate models to design the simulations when computational cost limits the use of ensemble simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Interpreting the spatial distribution of soil properties with a physically-based distributed hydrological model

Digital soil maps are commonly data-driven as the development of physically-based models for soil mapping is difficult due to the complexity of soils. However, physically-based hydrologic models have been successful in simulating water dynamics. Since water movement is a major driver of pedogenesis, the physical rules that govern water movement might help explain and predict the spatial variation of soil properties. Here, we demonstrate the novel use of a physically-based, distributed hydrologic model to inform the spatial distribution of soil properties. The Distributed Hydrology Soil Vegetation Model (DHSVM) was utilized to simulate soil moisture content (SM) and water table depth (WTD) in two hillslope catchments under pasture and forest management wherein hydrologic model outputs were then compared with soil properties measured in situ. SM sensors and wells were installed in both catchments to validate simulations of soil water movement via Nash-Sutcliffe Efficiency (E). In-situ observations were made at 87 sites within both catchments to study the connection between simulated water movement (SM and WTD) and observed soil properties, namely the depth and thickness of the argillic (Bt), fragic (Btx), and C horizons, and the depth of redoximorphic features. The simulated time series of SM and WTD were also clustered per season using Dynamic Time Warping (DTW), which identified similarity among time series at varying timescales. Model validation suggested that simulations of surficial SM (0–20 cm) were reasonable (E = 0.45), however, simulated subsurface SM (45–60 cm) and WTD were not sufficiently accurate. The thickness of Btx horizons were spatially grouped into different populations by SM clusters from every season except spring. For the other properties, only SM dynamics of specific seasons grouped into significantly different populations, suggesting that the explanatory power of simulated water movement varies seasonally and was greater during winter. Here, we show clusters of simulated SM separated soil properties into statistically different populations, showing that hydrologic models could inform areas that followed different water dynamics related to pedogenic trajectories and related biogeochemical processes not necessarily simulated by the model. As such, physically-based modeling of water dynamics can, therefore, inform and advance digital soil mapping by linking water movement patterns stemming from hydrologic model outputs to spatial patterns of soil properties and pedogenesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Influence of plateau, slope, and valley on soil hydrology during the dry season in a Central Amazon old‐growth forest

Soil moisture regulates plant water supply and drought sensitivity in tropical forests, yet its vertical and topographic variation remains poorly characterized. We combined high-frequency time-domain reflectometry measurements from 5 to 100 cm across plateau, slope, and valley landforms at the Zona Florestal 2 research site north of Manaus, Central Amazonia, to quantify how soil moisture memory, timing of responses to rainfall, dry-down rates (τ), and soil–water depletion vary across these contrasting landforms. Landform-specific soil moisture calibration curves ensured accurate volumetric water content estimates in these highly weathered soils. During the 2023 dry-to-wet transition (August–November), soil moisture memory showed strong topographic contrasts, with valley profiles increasing from ∼47 h at 5 cm to ∼154 h at 100 cm, while plateaus exhibited higher near-surface persistence (∼124 h at 5 cm) but weaker memory at depth. Dry-down behavior reinforced these differences as valley soils exhibited τ values exceeding ∼200 h, more than double the characteristic τ of plateau soils (∼90 h). Rainfall–soil moisture correlations indicated immediate responses at shallow depths in valleys and progressively longer lags with depth on plateaus and slopes. These hydrologic patterns were mirrored in depletion profiles, which declined sharply below 30 cm on plateaus but remained high and sustained throughout the upper meter in slopes and valleys. Together, these findings provide the first depth-resolved field measurements of soil moisture memory, rainfall coupling, dry-down constants, and depletion dynamics across major upland landforms in Central Amazonia and offer clear observational benchmarks for improving land-surface and ecosystem model representations of soil–water processes.

Hillslope↗
DOE OSTI2020

Manganese: The overlooked contaminant in the world largest mine tailings dam collapse

Manganese (Mn) is an abundant element in terrestrial and coastal ecosystems and an essential micronutrient in the metabolic processes of plants and animals. Mn is generally not considered a potentially toxic element due to its low content in both soil and water. However, in coastal ecosystems, the Mn dynamic (commonly associated with the Fe cycle) is mostly controlled by redox processes. Here, we assessed the potential contamination of the Rio Doce estuary (SE Brazil) by Mn after the world’s largest mine tailings dam collapse, potentially resulting in chronic exposure to local wildlife and humans. Estuarine soils, water, and fish were collected and analyzed seven days after the arrival of the tailings in 2015 and again two years after the dam collapse in 2017. Using a suite of solid-phase analyses including X-ray absorption spectroscopy and sequential extractions, our results indicated that a large quantity of Mn II arrived in the estuary in 2015 bound to Fe oxyhydroxides. Over time, dissolved Mn and Fe were released from soils when Fe III oxyhydroxides underwent reductive dissolution. Due to seasonal redox oscillations, both Fe and Mn were then re-oxidized to Fe III , Mn III , and Mn IV and re-precipitated as poorly crystalline Fe oxyhydroxides and poorly crystalline Mn oxides. In 2017, redox conditions (Eh: -47 ± 83 mV; pH: 6.7 ± 0.5) favorable to both Fe and Mn reduction led to an increase (~880%) of dissolved Mn (average for 2015: 66 ± 130 μg L -1 ; 2017: 582 ± 626 μg L -1 ) in water and a decrease (~75%, 2015: 547 ± 498 mg kg -1 ; 2017: 135 ± 80 mg kg -1 ) in the total Mn content in soils. The crystalline Fe oxyhydroxides content significantly decreased while the fraction of poorly ordered Fe oxides increased in the soils limiting the role of Fe in Mn retention. The high concentration of dissolved Mn found within the estuary two years after the arrival of mine tailings indicates a possible chronic contamination scenario, which is supported by the high levels of Mn in two species of fish living in the estuary. Our work suggests a high risk to estuarine biota and human health due to the rapid Fe and Mn biogeochemical dynamic within the impacted estuary.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Microbial community data from throughfall exclusion experiment: Metadata, SI, community composition, LefSe, and FunGuilR data tables from PARCHED Panama tropical forest soils, 2024-2025

Soil contains more carbon (C) than terrestrial vegetation and the atmosphere combined, with some of the largest terrestrial C stocks in tropical rainforests. Soil microbes decompose organic matter, playing a vital role in the storage or loss of soil C. With climate change, drought conditions are predicted to increase in many tropical regions, including both chronic drying and extended drought, potentially influencing these processes. This project explored the effects of chronic and seasonal drying on soil microbial communities across four distinct tropical forests in a long-term drying experiment. We investigated the effects of a chronic drying manipulation on soil microbial community abundance and variation across different forests and seasons. We also compared findings with previously published data from these forests after short-term drying. This project used soils from a long-term drying experiment established in 2018 across four seasonal lowland forests in Panama. Soils were collected from 0 – 10 cm depths during three seasonal periods in control and drying plots in 2024 and 2025 from a total of 32 plots (n = 4 per forest per treatment). The forests varied in baseline rainfall and soil fertility. We calculated alpha and beta diversity indices and compared taxonomic community composition. We found significant biogeographic variation in microbial diversity and taxonomy, with significant differences across the forests and significant effects of the drying treatment. Metadata and sample IDs are within Metadata_16S.csv and Metadata_ITS.csv. Relative abundance tables of every sample at every season are shown in the Excel workbooks 16S Relative Abundance.xlsx and ITS Relative Abundance.xlsx. They are then also shown in CSV files by each taxonomic level. Linear discriminant analysis effect size (LefSe) tables are shown for the full 16S and ITS datasets (n = 96), subsets for every site at every season (n = 8), and then for the forests with each plot merged by season (n = 8). FunGuildR data table of ITS data is uploaded.

Bacteria↗
DOE OSTI2024

AmeriFlux Measurement Component Instrument Handbook

An AMC system was installed at the Atmospheric Radiation Measurement (ARM) Climate Research Facility’s North Slope Alaska (NSA) Barrow site, also known as NSA C1 at the ARM Data Archive, in August 2012. A second AMC system was installed at the third ARM Mobile Facility deployment at Oliktok Point, also known as NSA M1. This in situ system consists of 12 combination soil temperature and volumetric water content (VWC) reflectometers and one set of upwelling and downwelling PAR sensors, all deployed within the fetch of the Eddy Correlation Flux Measurement System. Soil temperature and VWC sensors placed at two depths (10 and 30 cm below the vegetation layer) at six locations (or microsites) allow soil property inhomogeneity to be monitored across a landscape. The soil VWC and temperature sensors used at NSA C1 are the Campbell Scientific CS650L and the sensors at NSA M1 use the Campbell Scientific CS655. The two sensors are nearly identical in function, and vendor specifications are based on the CS650 unless otherwise stated.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Geophysical survey associated with NEON AOP survey, East River, CO 2018

The package contains data layers developed and used in Falco et al. 2024: “EcoImaging: Advanced Sensing to Investigate Plant and Abiotic Hierarchical Spatial Patterns in Mountainous Watersheds". The package is part of the DOE Watershed Function Science Focus Area (SFA) project and includes geophysical measurements collected at the East River, Colorado, in conjunction with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey conducted in June 2018. This dataset provide soil geophysical information and were used to investigate soil-plant relationships. The dataset consists of: - NEON_2018_EMI_survey.zip: the electromagnetic induction (EMI) survey as shape-file; - NEON_plot_TDR.csv: plot‑level data from Time‑Domain Reflectometry (TDR) measurements, providing: * volumetric water content (VWC) in percent (%); * soil temperature in degrees Celsius (°C); - file level metadata (flmd.csv) - data dictionary (dd.csv) file This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2022

Quantifying pH buffering capacity in acidic, organic-rich Arctic soils: Measurable proxies and implications for soil carbon degradation

Dynamic pH change promoted by biogeochemical reactions in Arctic tundra soils can be a major control on the production and release of CO 2 and CH 4 , which contribute to rising global temperatures. Large quantities of soil organic matter (SOM) in these soils are susceptible to microbial decomposition, leading to pH changes during permafrost thaw. Soil pH buffering capacity (β) modulates the extent of pH change but has not been thoroughly studied and represented in predictive ecosystem scale biogeochemical models in Arctic tundra soils. In this study, we generated titration curves for 21 acidic tundra soils from three Arctic sites across northern Alaska, United States of America. Geochemical and hydrological soil properties were evaluated, and correlations with β were developed. Strong correlations between β and both gravimetric water content (Θ g ) (R 2 = 0.847, p < 0.001) and soil water retention (SWR) (R 2 = 0.849, p = 0.001) indicate that the ability of soil to retain water could be associated with its buffering properties. Correlations between β and soil organic carbon (SOC) and cation exchange capacity (CEC) were also explored, and relationships to SWR are discussed. These correlations were then used with existing soil databases reporting SOC, CEC, and SWR to estimate β across Alaska soils. We further demonstrated the quantitative relationships between β and the simulated rates of biogeochemical reactions and show that lower β leads to higher soil pH and more CH 4 production. Overall, our study provides simple proxies for β in Arctic soils and highlights the importance and implications of representing soil buffering in predictive models, thereby enabling quantitative coupling between pH dynamics associated with biogeochemical reactions. Integrating β into predictive models of Arctic biogeochemical cycling may reduce model uncertainty and further our understanding of permafrost SOM degradation accelerated by warming.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Integrating fine root diameter and watershed mapping to characterize rhizosphere hydrology

Root morphology and soil hydraulic characteristics were integrated using watershed distance mapping to show water distribution and uptake across the plant-soil interface. Poplar (Populus deltoides, P. trichocarpa), maize (Zea mays), juniper (Juniperus virginiana), grape (Vitis rotundifolia) and maple (Acer saccharum) seedlings were grown in sand, after which root diameter and soil water dynamics were assessed via sequential neutron radiography. Three local soil regions (root-soil interface or edge, rhizosphere, bulk soil) were classified based on both radial distance from the root surface and diameter of the nearest root, from which changes in water content and distribution were characterized using digital image processing. Water content dynamics across the rhizosphere showed two different species-independent processes: a consistently elevated water content at the root-soil edge interface which increased with root diameter, and hysteresis as the rhizosphere transitioned to bulk soil (~0.5 cm from the root), independent of root diameter. Water uptake per unit root surface area declined exponentially with root diameter, independent of species. Results highlight the species-independent hydrologic characteristics of the rhizosphere and the potential for evaluating them in a local spatially connected soil context. Avenues for improved integration of soil and root characteristics are discussed.

59 BASIC BIOLOGICAL 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↗