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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

The 100-C-7 Remediation Project. An Overview of One of DOE's Largest Remediation Projects - 13260

The U.S. Department of Energy Richland Operations Office (RL), U.S. Environmental Protection Agency (EPA) and Washington Closure Hanford LLC (WCH) completed remediation of one of the largest waste sites in the U.S. Department of Energy complex. The waste site, 100-C-7, covers approximately 15 football fields and was excavated to a depth of 85 feet (groundwater). The project team removed a total of 2.3 million tons of clean and contaminated soil, concrete debris, and scrap metal. 100-C-7 lies in Hanford's 100 B/C Area, home to historic B and C Reactors. The waste site was excavated in two parts as 100-C-7 and 100-C-7:1. The pair of excavations appear like pit mines. Mining engineers were hired to design their tiered sides, with safety benches every 17 feet and service ramps which allowed equipment access to the bottom of the excavations. The overall cleanup project was conducted over a span of almost 10 years. A variety of site characterization, excavation, load-out and sampling methodologies were employed at various stages of remediation. Alternative technologies were screened and evaluated during the project. A new method for cost effectively treating soils was implemented - resulting in significant cost savings. Additional opportunities for minimizing waste streams and recycling were identified and effectively implemented by the project team. During the final phase of cleanup the project team applied lessons learned throughout the entire project to address the final, remaining source of chromium contamination. The C-7 cleanup now serves as a model for remediating extensive deep zone contamination sites at Hanford. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Phenazine‐1‐carboxylic acid and soil moisture influence biofilm development and turnover of rhizobacterial biomass on wheat root surfaces

Summary Phenazine‐1‐carboxylic acid (PCA) is produced by rhizobacteria in dryland but not in irrigated wheat fields of the Pacific Northwest, USA. PCA promotes biofilm development in bacterial cultures and bacterial colonization of wheat rhizospheres. However, its impact upon biofilm development has not been demonstrated in the rhizosphere, where biofilms influence terrestrial carbon and nitrogen cycles with ramifications for crop and soil health. Furthermore, the relationships between soil moisture and the rates of PCA biosynthesis and degradation have not been established. In this study, expression of PCA biosynthesis genes was upregulated relative to background transcription, and persistence of PCA was slightly decreased in dryland relative to irrigated wheat rhizospheres. Biofilms in dryland rhizospheres inoculated with the PCA‐producing (PCA + ) strain Pseudomonas synxantha 2‐79RN 10 were more robust than those in rhizospheres inoculated with an isogenic PCA‐deficient (PCA ‐ ) mutant strain. This trend was reversed in irrigated rhizospheres. In dryland PCA + rhizospheres, the turnover of 15 N‐labelled rhizobacterial biomass was slower than in the PCA ‐ and irrigated PCA + treatments, and incorporation of bacterial 15 N into root cell walls was observed in multiple treatments. These results indicate that PCA promotes biofilm development in dryland rhizospheres, and likely influences crop nutrition and soil health in dryland wheat fields.

LeTourneau, Melissa K.↗
DOE OSTI2020

Modeling the Effects of Global Change on Ecosystem Processes in a Tropical Rainforest

Ongoing land-use change and climate change in wet tropical forests can potentially drive shifts in tree species composition, representing a change in individual species within a functional group, tropical evergreen trees. The impacts on the global carbon cycle are potentially large, but unclear. We explored the differential effects of species within this functional group, in comparison with the effects of climate change, using the Century model as a research tool. Simulating effects of individual tree species on biome-level biogeochemical cycles constituted a novel application for Century. Background and Objectives: A unique, long-term, replicated field experiment containing five evergreen tree species in monodominant stands under similar environmental conditions in a Costa Rican wet forest provided data for model evaluation. Our objectives were to gain insights about this forest’s biogeochemical cycles and effects of tree species within this functional group, in comparison with climate change. Materials and Methods: We calibrated Century, using long-term meteorological, soil, and plant data from the field-based experiment. In modeling experiments, we evaluated effects on forest biogeochemistry of eight plant traits that were both observed and modeled. Climate-change simulation experiments represented two climate-change aspects observed in this region. Results: Model calibration revealed that unmodeled soil processes would be required to sustain observed P budgets. In species-traits experiments, three separate plant traits (leaf death rate, leaf C:N, and allocation to fine roots) resulted in modeled biomass C stock changes of >50%, compared with a maximum 21% change in the climate-change experiments. Conclusions: Modeled ecosystem properties and processes in Century were sensitive to changes in plant traits and nutrient limitations to productivity. Realistic model output was attainable for some species, but unusual plant traits thwarted predictions for one species. Including more plant traits and soil processes could increase realism, but less-complex models provide an accessible means for exploring plant-soil-atmosphere interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Land-Atmosphere Feedback Experiment Field Campaign Report

The Land-Atmosphere Feedback Experiment (LAFE; pronounced “la-fey”) deployed several state-of-the-art scanning lidar and remote-sensing systems to the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site. These instruments augmented the ARM instrument suite and collected a data set for studying feedback processes between the land surface and the atmosphere. The novel synergy of remote-sensing systems was applied for simultaneous measurements of land surface fluxes and horizontal and vertical transport processes in the atmospheric convective boundary layer (CBL) (Wulfmeyer et al. 2018). The impact of spatial inhomogeneities of the soil-vegetation continuum on land-atmosphere (L-A) feedback was studied using the scanning capability of the instrumentation. The time period of the observations was August 2017, as large differences in surface fluxes between different fields and bare soil were expected, e.g., pastures versus fields where the wheat has already been harvested. The LAFE strategy involved sampling the surface fluxes over different types of surfaces, and thus the in situ energy balance closure (EBC) stations were placed in fields with different plant covers (e.g., soy bean plants, native grasses, etc.).

Southern Great Plains, convective boundary layer, ↗
DOE OSTI2020

Associative nitrogen fixation linked with three perennial bioenergy grasses in field and greenhouse experiments

Abstract Associative nitrogen (N 2 )‐fixation (ANF) by bacteria in the root‐zone of perennial bioenergy grasses has the potential to replace or supplement N fertilizer and support sustainable production of biomass, but its application in marginal ecosystems requires further evaluation. In this study, we first combined both greenhouse and field experiments, to explore the N 2 fixation effects of three temperate feedstocks Miscanthus × giganteus (giant miscanthus, Freedom), Panicum virgatum (switchgrass, Alamo), and Saccharum sp. (energycane, Ho 02‐147). In field studies across three growing seasons, plant and soil pools of candidate feedstocks were partially composed of N derived from the atmosphere (Ndfa). Energycane, giant miscanthus, and switchgrass were estimated to derive >30%, %Ndfa. Greenhouse studies were also performed to trace isotopically labeled 15 N 2 into plant biomass and soil pools. Evidence for Ndfa was detected in all three feedstock grasses (using reference 15 N of soil, chicory, and sorghum, δ 15 N~+7.0). Isotopically labeled 15 N 2 was traced into biomass (during grass elongation stage) and soil pools. Extrapolation of rates during the 24 hr labeling period to 50 days estimated 30%–55% of plant Ndfa, with the greatest Ndfa for energycane. The findings of the field natural abundance and greenhouse 15 N 2 feeding experiments provided complementary evidence that perennial bioenergy grasses have the potential to support relatively high rates of ANF, and accumulate diazotroph‐derived N into biomass when grown on non‐fertilized soil.

09 BIOMASS FUELS↗
DOE OSTI2021

Adaptive differentiation and rapid evolution of a soil bacterium along a climate gradient

Significance Increasing evidence suggests that evolutionary processes frequently shape ecological patterns; however, most microbiome studies thus far have focused on only the ecological responses of these communities. By using parallel field experiments and focusing in on a model soil bacterium, we showed that bacterial “species” are differentially adapted to local climates, leading to changes in their composition. Furthermore, we detected strain-level evolution, providing direct evidence that both ecological and evolutionary processes operate on annual timescales. The consideration of eco-evolutionary dynamics may therefore be important to understand the response of soil microbiomes to future environmental change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Genomics of Energy Sorghum's Water Use Efficiency/Drought Resilience

The overall goal of the proposed research is to increase the biomass yield of C4 bioenergy grasses such as sorghum that are often grown in water limited environments by improving the water use efficiency, soil water extraction, and drought resilience of these crops. High biomass yield is strongly correlated with long duration of vegetative growth, however, insufficient rainfall during long growing seasons is a primary factor limiting biomass yield. To minimize this yield constraint, the proposed project will identify sorghum genotypes and traits/QTL that improve water use efficiency, soil water extraction by roots, and drought resilience. The specific objectives of the proposed research are to; (1) Screen diverse energy sorghum accessions and RIL populations for variation in traits that affect soil water extraction, water use efficiency, and drought resilience using lysimeters, aeroponics, and field experiments, (2) identify QTL/alleles and gene regulatory networks that modify expression of traits that impact soil water extraction and water use efficiency, and (3) test the utility of traits/alleles that affect soil water extraction, water use efficiency, and drought resilience in field plots under irrigated and water deficit conditions.

09 BIOMASS FUELS↗
NASA NTRS2003

Mars Redox Chemistry: Atacama Desert Soils as a Terrestrial Analog

The motivation for this work is to perform quantitative site characterizations of soil chemical processes to allow further development and field validation of the Mars Oxidant Instrument (MOI). The MOI is an in situ survey instrument designed to establish the presence of reactive chemical species in the martian soil, dust, or atmosphere, and to provide detailed reaction model system measurements to enable comprehensive Earthbased study. Functioning as a survey instrument, MOI tests the broad range of hypotheses explaining the reactivity of the martian surface material that have been put forth since the Viking experiments. This work is currently being carried out under the NASA ASTEP funded AstroBioLab (Jeffery Bada, PI). A second objective is to use Atacama field and Viking data to perform comparative studies, with the goal of furthering the understanding of the formation mechanisms and properties of martian oxidants.

Quinn, R. C.↗
DOE OSTI2026

Plant-Nitrifier Interactions in Topsoil and Subsoil

Plants can influence soil microbes through resource acquisition and interference competition, with consequences for ecosystem function such as nitrification. However, how plants alter soil conditions to influence nitrifiers and nitrification rates remains poorly understood, especially in the subsoil. Here, coupling the 15N isotopic pool dilution technique, high throughput sequencing and in situ soil O2 monitoring, we investigated how a deep-rooted perennial grass, miscanthus, versus an adjacent shallow-rooted turfgrass reference shapes nitrifier assembly and function along 1 m soil profiles. In topsoil, the suppression of ammonia (NH3) oxidizing archaea (AOA) and gross nitrification rates in miscanthus relative to the reference likely resulted from nitrifiers being outcompeted by plant roots and heterotrophic bacteria for ammonium (NH4+). The stronger tripartite competition under miscanthus may have been caused in part by the lower soil organic matter (SOM) content, which supported lower gross nitrogen (N) mineralization, the major soil process that produces NH4+. In contrast, below 10 cm soil depth, significantly greater gross nitrification rates were observed in miscanthus compared to the reference. This was likely driven by the significantly lower oxygen (O2) in miscanthus than reference subsoil, which selected against aerobic heterotrophic bacteria but in favor of AOA. Overall, we found that plants can regulate AOA community structure and function through different mechanisms in topsoil and subsoil, with suppression of nitrification in topsoil and enhancement of nitrification in subsoil.

Field Data↗
DOE OSTI2015

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

Abstract Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial‐based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial‐enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal‐spatial scales. The dormancy model consistently produced better match with field‐observed heterotrophic soil CO 2 efflux ( R H ) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 Pg C yr −1 ). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon‐to‐nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale‐dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial‐based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

He, Yujie↗
DOE OSTI2016

Dynamics of microbial community composition and soil organic carbon mineralization in soil following addition of pyrogenic and fresh organic matter

Pyrogenic organic matter (PyOM) additions to soils can have large impacts on soil organic carbon (SOC) cycling. As the soil microbial community drives SOC fluxes, understanding how PyOM additions affect soil microbes is essential to understanding how PyOM affects SOC. We studied SOC dynamics and surveyed soil bacterial communities after OM additions in a field experiment. We produced and mixed in either 350 °C corn stover PyOM or an equivalent initial amount of dried corn stover to a Typic Fragiudept soil. Stover increased SOC-derived and total CO 2 fluxes (up to 6x), and caused rapid and persistent changes in bacterial community composition over 82 days. In contrast, PyOM only temporarily increased total soil CO 2 fluxes (up to 2x) and caused fewer changes in bacterial community composition. Of the operational taxonomic units (OTUs) that increased in response to PyOM additions, 70% also responded to stover additions. These OTUs likely thrive on easily mineralizable carbon (C) that is found both in stover and, to a lesser extent, in PyOM. In contrast, we also identified unique PyOM responders, which may respond to substrates such as polyaromatic C. In particular, members of Gemmatimonadetes tended to increase in relative abundance in response to PyOM but not to fresh organic matter. As a result, we identify taxa to target for future investigations of the mechanistic underpinnings of ecological phenomena associated with PyOM additions to soil.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A data-driven global soil heterotrophic respiration dataset and the drivers of its inter-annual variability

Soil heterotrophic respiration (SHR), one of the primary carbon fluxes from terrestrial ecosystems to the atmosphere, is important for carbon-climate feedbacks because of its sensitivity to available litter and soil carbon, climatic conditions, and nutrient availability. However, until recently limited SHR data were available, and most published global SHR estimates have either a short time span, coarse spatial resolution, or reply on overly-simple model formulations. To better understand and quantify the global distribution of SHR and its sensitivity to climate variability, we produced a new global SHR dataset using Random Forest algorithms, up-scaling 455 point data from the Global Soil Respiration Database (SRDB 4.0) with gridded fields of climatic, edaphic and productivity as explanatory variables. We estimated a global total SHR of 46.8 Pg C yr-1 over 1985-2013 (95% confidence interval: 38.6-56.3 Pg C yr-1), with a significant increasing trend of 0.03 Pg C yr-2 during this period. We found that the choice of soil moisture datasets contributes more to the difference among these data-driven SHR members rather than that of productivity, temperature and precipitation data sources. We also analyzed the influence of climatic variables on the inter-annual variability (IAV) of our SHR product. Water availability was the dominant driver of IAV at global scales, although the inferred sensitivity depends on the choice of the soil moisture gridded dataset. At the ecosystem scale, temperature strongly controls the IAV of SHR in tropical forests, while water availability dominates in extra-tropical forest and semi-arid regions. Our machine-learning gridded SHR dataset and outputs from process-based land surface models (TRENDYv6) show agreement for a strong association between water variability and SHR IAV at the global scale, but the two approaches lead to different temporal trend globally and different controlling variables for IAV at the ecosystem scale. Our study provides evidence for the pervasive and important role of water availability in driving SHR, indicating both a direct effect limiting decomposition rates and an indirect effect through the amount of fresh organic matter made available to SHR from productivity. In consideration of potential limitations and uncertainties remaining in our data-driven SHR datasets, we call for a more scientifically designed observation network for SHR, more observation data compilation, and increased use of deep learning methods making maximum use of observation data in hand. This will benefit process-based models, and improve our understanding of SHR response to future anomalous environmental conditions.

Yao, Yitong↗
NASA NTRS2005

Satellite-Derived Management Zones

The term "satellite-derived management zones" (SAMZ) denotes agricultural management zones that are subdivisions of large fields and that are derived from images of the fields acquired by instruments aboard Earth-orbiting satellites during approximately the past 15 years. "SAMZ" also denotes the methodology and the software that implements the methodology for creating such zones. The SAMZ approach is one of several products of continuing efforts to realize a concept of precision agriculture, which involves optimal variations in seeding, in application of chemicals, and in irrigation, plus decisions to farm or not to farm certain portions of fields, all in an effort to maximize profitability in view of spatial and temporal variations in the growth and health of crops, and in the chemical and physical conditions of soils. As used here, "management zone" signifies, more precisely, a subdivision of a field within which the crop-production behavior is regarded as homogeneous. From the perspective of precision agriculture, management zones are the smallest subdivisions between which the seeding, application of chemicals, and other management parameters are to be varied. In the SAMZ approach, the main sources of data are the archives of satellite imagery that have been collected over the years for diverse purposes. One of the main advantages afforded by the SAMZ approach is that the data in these archives can be reused for purposes of precision agriculture at low cost. De facto, these archives contain information on all sources of variability within a field, including weather, crop types, crop management, soil types, and water drainage patterns. The SAMZ methodology involves the establishment of a Web-based interface based on an algorithm that generates management zones automatically and quickly from archival satellite image data in response to requests from farmers. A farmer can make a request by either uploading data describing a field boundary to the Web site or else drawing the boundary on a reference image. Hence, a farmer can start to engage in precision farming shortly after gaining access to the Web site, without the need for incurring the high costs of conventional precision-agriculture data-collection practices that include collecting soil samples, mapping electrical conductivity of soil, and compiling multiyear crop-yield data. Given the boundary of a field, a SAMZ server computes the zones within the field in a three-stage process. In the first stage, a vector-valued image of the field is constructed by assembling, from the archives, the equivalent of a stack of the available images of the field (see figure). In the second stage, the vector-valued image is analyzed by use of a wavelet transform that detects spatial variations considered significant for precision farming while suppressing small-scale heterogeneities that are regarded as insignificant. In the third stage, a segmentation algorithm assembles the zones from smaller regions that have been identified in the wavelet analysis.

Lepoutre, Damien↗
DOE OSTI2021

NGEE Arctic Plant Traits: Fine Roots, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016

Soil cores were collected from twelve vegetation biomass plots at the Kougarok hillslope in late July of 2016. The sampled plots were located across six ecotypes present at this site (n=2 replicates per ecotype). Soil cores were separated into depth intervals in the field and frozen for transport to Oak Ridge National Laboratory. Data package contains one *.csv and one *.pdf.Laboratory sample processing of these soils generated depth-specific data on soil properties as well as fine root biomass, length, %C, %N, delta13C, and delta15N. Only live fine roots were analyzed. Fine roots were not separated by species or plant functional type.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), 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↗
NASA NTRS2004

SAMZ: Satellite-Derived Management Zones

The term "satellite-derived management zones" (SAMZ) denotes agricultural management zones that are subdivisions of large fields and that are derived from images of the fields acquired by instruments aboard Earth orbiting satellites during approximately the past 15 years. "SAMZ" also denotes the methodology and the software that implements the methodology for creating such zones. The SAMZ approach is one of several products of continuing efforts to realize a concept of precision agriculture, which involves optimal variations in seeding, in application of chemicals, and in irrigation, plus decisions to farm or not to farm certain portions of fields, all in an effort to maximize profitability in view of spatial and temporal variations in the growth and health of crops and in the chemical and physical conditions of soils. As used here, "management zone" signifies, more precisely, a subdivision of a field within which the crop production behavior is regarded as homogeneous. From the perspective of precision agriculture, management zones are the smallest subdivisions between which the seeding, application of chemicals, and other management parameters are to be varied. In the SAMZ approach, the main sources of data are the archives of satellite imagery that have been collected over the years for diverse purposes. One of the main advantages afforded by the SAMZ approach is that the data in these archives can be reused for purposes of precision agriculture at low cost. De facto, these archives contain information on all sources of variability within a field, including weather, crop types, crop management, soil types, and water drainage patterns. The SAMZ methodology involves the establishment of a Web-based interface based on an algorithm that generates management zones automatically and quickly from archival satellite image data in response to requests from farmers. A farmer can make a request by either uploading data describing a field boundary to the Web site or else drawing the boundary on a reference image. Hence, a farmer can start to engage in precision farming shortly after gaining access to the Web site, without need for incurring the high costs of conventional precision-agriculture data-collection practices that include collecting soil samples, mapping electrical conductivity of soil, and compiling multi-year crop-yield data. Given the boundary of a field, a SAMZ server computes the zones within the field in a three-stage process. In the first stage, a vector-valued image of the field is constructed by assembling, from the archives, the equivalent of a stack of the available images of the field (see figure). In the second stage, the vector-valued image is analyzed by use of a wavelet transform that detects spatial variations considered significant for precision farming while suppressing small-scale heterogeneities that are regarded as insignificant. In the third stage, a segmentation algorithm assembles the zones from smaller regions that have been identified in the wavelet analysis.

Source record↗
DOE OSTI2023

Pollen and Bio-Soiling in the Southeast U.S.

Typical PV soiling models presume that soiling follows a sawtooth pattern: linear soiling during dry periods followed by abrupt recovery or cleaning during rainfall events. Due to frequency of rainfall in the in the eastern U.S. sawtooth soiling models report near zero soiling losses in this region. Alternatively, through work with system owner/operators per NREL's PVfleet project it has become clear that there are systems in the Southeast that have soiled as high as 10% which are not recovering with regular rainfall. The current hypothesis is that sticky soiling due to pollen or other biological sources is persistent to rainfall removal. Field data and the latest progress towards de-risking bio-soiling will be presented.

photovoltaic↗
DOE OSTI2023

Forest Soil Carbon Efflux Evaluation Across China: A New Estimate With Machine Learning

Forest soil respiration (Rs) plays an important role in the carbon balance of terrestrial ecosystems. China's forest occupies a large part of the world's forest. However, due to the lack of integrated observation data and appropriate upscaling methodologies, substantial uncertainties exist in the Rs evaluation, which limits our understanding of the carbon balance. Here, we re-evaluated the total soil carbon effluxes across China by combining field observations from 634 published annual Rs with a machine learning technique (i.e., Random Forest (RF)). Our results revealed that the combination of systematic measurements with the RF model allowed a definite estimate. The average annual Rs was 773.6 g C m -2 yr -1 , ranging from 404.6 to 1,772.3 g C m -2 yr -1 . Total forest soil carbon effluxes amounted to 1.17 Pg C yr -1 in China. Geographically, annual Rs showed a clear spatially increasing trend from northeast to southwest. Forest type is an important factor in determining the soil respiration rate. Bamboo and Evergreen broadleaf forests were higher than other types of forests. In conclusion, these results provide a unique insight into the magnitudes and mechanisms of soil CO 2 emissions in China's forest ecosystems.

58 GEOSCIENCES↗
DOE OSTI2019

Selenium (Se) Does Not Reduce Cadmium (Cd) Uptake and Translocation in Rice (Oryza sativa L.) in Naturally Occurred Se-Rich Paddy Fields with a High Geological Background of Cd

This study examined the selenium (Se) and cadmium (Cd) uptake by rice from soil and analyzed the relationship between Se and Cd in naturally occurred Se-rich paddy fields with a high geological background of Cd. Significant correlations were observed between soil Se and plant biomass Se, but not between soil Cd and plant biomass Cd. High concentrations of Cd were detected in rice plants and particularly in rice grains, suggesting potential health risks to human. Contrary to results from other previous studies, our results showed that high soil Se did not reduce Cd uptake by rice, although it decreased the availability of Cd in soil. Rather, soil Se and internal Se pool in rice were positively correlated to the transfer of Cd from root to straw. The effect of Se on the uptake and translocation of Cd in rice in field is therefore different from those in pot experiments.

54 ENVIRONMENTAL SCIENCES↗