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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Molecular and morphological characterization of Tylenchus zeae n. sp. (Nematoda: Tylenchida) from Corn ( Zea mays ) in South Carolina

Specimens of a tylenchid nematode were recovered in 2019 from soil samples collected from a corn field, located in Pickens County, South Carolina, USA. A moderate number of Tylenchus sp. adults (females and males) were recovered. Extracted nematodes were examined morphologically and molecularly for species identification, which indicated that the specimens of the tylenchid adults were a new species, described herein as Tylenchus zeae n. sp. Morphological examination and the morphometric details of the specimens were very close to the original descriptions of Tylenchus sherianus and T. rex. However, females of the new species can be differentiated from these species by body shape and length, shape of excretory duct, distance between anterior end and esophageal intestinal valve, and a few other characteristics given in the diagnosis. Males of the new species can be differentiated from the two closely related species by tail, spicules, and gubernaculum length. Cryo-scanning electron microscopy confirmed head bearing five or six annules; four to six cephalic sensilla represented by small pits at the rounded corners of the labial plate; a small, round oral plate; and a large, pit-like amphidial opening confined to the labial plate and extending three to four annules beyond it. Phylogenetic analysis of 18S rRNA gene sequences placed Tylenchus zeae n. sp. in a clade with Tylenchus arcuatus and several Filenchus spp., and the mitochondrial cytochrome oxidase c subunit 1 (COI) gene region separated the new species from T. arcuatus and other tylenchid species. In the 28S tree, T. zeae n. sp. showed a high level of sequence divergence and was positioned outside of the main Tylenchus-Filenchus clade.

18S↗
DOE OSTI2021

Computing water flow through complex landscapes – Part 3: Fill–Spill–Merge: flow routing in depression hierarchies

Abstract. Depressions – inwardly draining regions – are common to many landscapes. When there is sufficient moisture, depressions take the form of lakes and wetlands; otherwise, they may be dry. Hydrological flow models used in geomorphology, hydrology, planetary science, soil and water conservation, and other fields often eliminate depressions through filling or breaching; however, this can produce unrealistic results. Models that retain depressions, on the other hand, are often undesirably expensive to run. In previous work we began to address this by developing a depression hierarchy data structure to capture the full topographic complexity of depressions in a region. Here, we extend this work by presenting the Fill–Spill–Merge algorithm that utilizes our depression hierarchy data structure to rapidly process and distribute runoff. Runoff fills depressions, which then overflow and spill into their neighbors. If both a depression and its neighbor fill, they merge. We provide a detailed explanation of the algorithm and results from two sample study areas. In these case studies, the algorithm runs 90–2600 times faster (with a reduction in compute time of 2000–63 000 times) than the commonly used Jacobi iteration and produces a more accurate output. Complete, well-commented, open-source code with 97 % test coverage is available on GitHub and Zenodo.

58 GEOSCIENCES↗
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 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 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 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↗
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↗
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 OSTI2021

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

This dataset contains data used for the paper "Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding". The Related References field will be updated with a full citation when available.Climate change is intensifying the global water cycle, with increased frequency of drought and flood. Water is an important driver of soil carbon dynamics, and it is crucial to understand how moisture disturbances will affect carbon availability and fluxes in soils. Here we investigate the role of water in substrate-microbe connectivity and soil carbon cycling under extreme moisture conditions. We collected soils from Alaska, Florida, and Washington USA, and incubated them under Drought and Flood conditions. Drought had a stronger effect on soil respiration, pore-water carbon, and microbial community composition than flooding. Soil response was not consistent across sites, and was influenced by site-level pedological and environmental factors. Soil texture and porosity can influence microbial access to substrates through the pore network, driving the chemical response. Further, the microbial communities are adapted to the historic stress conditions at their sites and therefore show site-specific responses to drought and flood.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv and .txt format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/TES_3Soils_2021 (DOI: 10.5281/zenodo.4792655).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Carbon flux estimates are sensitive to data source: a comparison of field and lab temperature sensitivity data

Abstract A large literature exists on mechanisms driving soil production of the greenhouse gases CO 2 and CH 4 . Although it is common knowledge that measurements obtained through field studies vs. laboratory incubations can diverge because of the vastly different conditions of these environments, few studies have systematically examined these patterns. These data are used to parameterize and benchmark ecosystem- to global-scale models, which are then susceptible to the biases of the source data. Here, we examine how greenhouse gas measurements may be influenced by whether the measurement/incubation was conducted in the field vs. laboratory, focusing on CO 2 and CH 4 measurements. We use Q 10 of greenhouse gas flux (temperature sensitivity) for our analyses because this metric is commonly used in biological and Earth system sciences and is an important parameter in many modeling frameworks. We predicted that laboratory measurements would be less variable, but also less representative of true field conditions. However, there was greater variability in the Q 10 values calculated from lab-based measurements of CO 2 fluxes, because lab experiments explore extremes rarely seen in situ , and reflect the physical and chemical disturbances occurring during sampling, transport, and incubation. Overall, respiration Q 10 values were significantly greater in laboratory incubations (mean = 4.19) than field measurements (mean = 3.05), with strong influences of incubation temperature and climate region/biome. However, this was in part because field measurements typically represent total respiration (Rs), whereas lab incubations typically represent heterotrophic respiration (Rh), making direct comparisons difficult to interpret. Focusing only on Rh-derived Q 10 , these values showed almost identical distributions across laboratory ( n = 1110) and field ( n = 581) experiments, providing strong support for using the former as an experimental proxy for the latter, although we caution that geographic biases in the extant data make this conclusion tentative. Due to a smaller sample size of CH 4 Q 10 data, we were unable to perform a comparable robust analysis, but we expect similar interactions with soil temperature, moisture, and environmental/climatic variables. Our results here suggest the need for more concerted efforts to document and standardize these data, including sample and site metadata.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Microbiome Aggregated Traits and Assembly Are More Sensitive to Soil Management than Diversity

How soil is managed, particularly for agriculture, exerts stresses upon soil microbiomes, resulting in altered community structures and functional states. Understanding how soil microbiomes respond to combined stresses is important for predicting system performance under different land use scenarios, aids in identification of the most environmentally benign managements, and provides insight into how system function can be recovered in degraded soils. We use a long-established field experiment to study the effects of combined chronic (press) disturbance of the magnitude of organic carbon inputs with acute (pulse) effects of physical disturbance by tillage and chemical disturbance due to inorganic fertilization and pesticide application. We show that because of the variety of ways it can be assessed, biodiversity—here based on microbial small subunit rRNA gene phylotypes—does not provide a consistent view of community change. In contrast, aggregated traits associated with soil microbiomes indicate general loss of function, measured as a reduction of average genome lengths, associated with chronic reduction of organic inputs in arable or bare fallow soils and altered growth strategies associated with rRNA operon copy number in prokaryotes, as well as a switch to pathogenicity in fungal communities. In addition, pulse disturbance by soil tillage is associated with an increased influence of stochastic processes upon prokaryote community assembly, but fungicide used in arable soils results in niche assembly of fungal communities compared to untilled grassland. Overall, bacteria, archaea, and fungi do not share a common response to land management change, and estimates of biodiversity do not capture important facets of community adaptation to stresses adequately.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Understanding Soil Microbial Sources of Nitrous Acid and their Effect on Carbon-Nitrogen Cycle Interactions

Descriptions of soil emissions of reactive nitrogen (NO y ) in climate models are underdeveloped or non-existent, due to the fact that details of the mechanisms leading to nitrous acid (HONO) and nitrogen di-oxide (NO 2 ) formation in soil are lacking. This represents a major gap in our understanding of a significant land-atmosphere interaction that prevents us from scaling these processes from the laboratory scale to the ecosystem and global scales. There is a critical need to include these mechanisms into climate models since NO y controls the oxidative capacity of the atmosphere and the lifetime of greenhouse gases and the rate of secondary aerosol formation that directly and indirectly affect climate. The first objective of this proposal is to conduct laboratory and field measurements of NO y fluxes from diverse soil types and determine the mechanism of biogenic NO y formation. The working hypothesis based on preliminary data is that soil HONO and NO 2 is ultimately derived from ammonia-oxidizing archaea (AOA) and bacteria (AOB) that are widespread, but whose abundance varies across ecosystems. In the case of NO 2 , reactive oxygen species derived from iron-containing minerals and heterotrophic bacteria drive NO-to-NO 2 conversion. The approach is to link soil fluxes of HONO and NO 2 to AOA, AOB, and other heterotrophs using a combination of laboratory and field experiments, isotopic analysis, and molecular techniques to address how variability in land surfaces and edaphic properties impact emissions. In addition, we will determine the effect of HONO and NO 2 on nitrogen immobilization and the photo-oxidative capacity of soil. The working hypothesis is that HONO uptake in soil will be a source of nitrosonium and hydroxyl radical that will lead to thermal- and photodegradation of soil organic matter to CO 2 and CO, and the incorporation of N in soil organic matter. We will use surface-sensitive mass spectrometry techniques and gas phase detection to study N-immobilization in soil and subsequent enhancements in reactivity that lead to decomposition of organic matter. The results will be used to reduce the uncertainty in projections from the Community Earth System Model (CESM) stemming from inaccurate representations of soil NO y emissions. The proposed research is significant because, in addition to demonstrating new mechanisms of NO y formation and loss, it will be a crucial first step towards modeling the land-atmosphere exchange of HONO and NO 2 in the CESM. Improved model treatment of land-air exchange of NO y is key for understanding feedbacks between human activity and climate, and addressing societal concerns about the fate of N and C emitted to the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dredged sediments contain potentially beneficial microorganisms for agriculture and little harmful cyanobacteria

Soils worldwide are degrading, raising concerns about our ability to feed the growing global population. Soil amendments that can alleviate degradation are gaining attention. The application of sediments dredged from waterways to agricultural fields has increasing promise as a means for improving degraded soils. However, herbaceous plant species may have difficulty establishing on dredged material because of low nutrient availability, inhibitory levels of toxins, unsuitable moisture conditions and lack of microorganisms capable of ameliorating these characteristics. To counteract these issues, we sought to understand if the use of a cover crop would increase the abundance, diversity and function of beneficial soil microorganisms compared to harmful microorganisms in dredged sediments. We collected soil samples from two 100% dredged sediment plots, one where winter cereal rye (Secale cereal) was grown as a winter cover crop and one left fallow over the winter, followed by traditional corn (Zea mays) planting. We sampled both plots three times during the growing season: before cover crop application, following cover crop application but before corn planting and following final corn harvest. We then used high-throughput sequencing to identify the bacterial and fungal communities present in the samples. Our data show that cover crop application did not alter the microbial community in these plots. However, sampling time decreased species diversity and altered the composition of both fungal and bacterial communities recovered from these plots. Across both plots, microorganisms associated with carbon cycling were more abundant than those associated with harmful effects, including microcystin-producing cyanobacteria, which were an extremely small portion of the overall community. Our work suggests that dredged sediments have the potential to improve soil function through the addition of microorganisms associated with nutrient cycling, but a cover crop is not necessary to incur these benefits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Field-Deployable Magnetic Resonance Imaging Rhizotron for Modeling and Enhancing Root Growth and Biogeochemical Function

A collaborative team from Texas A&M AgriLife Research, ABQMR Inc., the Soil Health Institute, the Athinoula A. Martinos Center for Biomedical Imaging, and NIST developed low-field magnetic resonance imaging (LF-MRI) instrumentation capable of imaging intact soil-root systems. The system measured root biomass, architecture, 3D mass distribution, and growth rates, providing a non-destructive means to evaluate ideal plant characteristics based on root metrics. It also successfully generated three-dimensional images of soil water content, a key property influencing root growth and exploration. Operating much like an MRI used in a medical setting, the system functioned in field conditions without damaging plants, overcoming the limitations of traditional methods such as trenching, soil coring, and root excavation. Over the course of the project, the team designed and built three functional prototype systems. These prototypes provided new insights into root–water–soil interactions that drive processes such as nutrient uptake, water use, and carbon management. This information contributed to efforts to optimize plants for carbon sequestration without sacrificing economic yield. The project also supported the identification of desirable traits for energy sorghum, including high root growth rates, more vertical root angles, and enhanced drought resilience under water-limiting conditions.

09 BIOMASS FUELS↗
DOE OSTI2020

Predicting Water Cycle Characteristics from Percolation Theory and Observational Data

The fate of water and water-soluble toxic wastes in the subsurface is of high importance for many scientific and practical applications. Although solute transport is proportional to water flow rates, theoretical and experimental studies show that heavy-tailed (power-law) solute transport distribution can cause chemical transport retardation, prolonging clean-up time-scales greatly. However, no consensus exists as to the physical basis of such transport laws. In percolation theory, the scaling behavior of such transport rarely relates to specific medium characteristics, but strongly to the dimensionality of the connectivity of the flow paths (for example, two- or three-dimensional, as in fractured-porous media or heterogeneous sediments), as well as to the saturation characteristics (i.e., wetting, drying, and entrapped air). In accordance with the proposed relevance of percolation models of solute transport to environmental clean-up, these predictions also prove relevant to transport-limited chemical weathering and soil formation, where the heavy-tailed distributions slow chemical weathering over time. The predictions of percolation theory have been tested in laboratory and field experiments on reactive solute transport, chemical weathering, and soil formation and found accurate. Recently, this theoretical framework has also been applied to the water partitioning at the Earth’s surface between evapotranspiration, ET, and run-off, Q, known as the water balance. A well-known phenomenological model by Budyko addressed the relationship between the ratio of the actual evapotranspiration (ET) and precipitation, ET/P, versus the aridity index, ET 0 /P, with P being the precipitation and ET 0 being the potential evapotranspiration. Existing work was able to predict the global fractions of P represented by Q and ET through an optimization of plant productivity, in which downward water fluxes affect soil depth, and upward fluxes plant growth. In the present work, based likewise on the concepts of percolation theory, we extend Budyko’s model, and address the partitioning of run-off Q into its surface and subsurface components, as well as the contribution of interception to ET. Using various published data sources on the magnitudes of interception and information regarding the partitioning of Q, we address the variability in ET resulting from these processes. The global success of this prediction demonstrated here provides additional support for the universal applicability of percolation theory for solute transport as well as guidance in predicting the component of subsurface run-off, important for predicting natural flow rates through contaminated aquifers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Modeling Plant Nutrient Acquisition Strategies Alters Projections of Carbon and Nitrogen Dynamics in Bioenergy Agroecosystems

Plant strategies to acquire nutrients from limited environments help shape ecosystem carbon (C) and nitrogen (N) cycling and response to environmental change. The effects of plant strategies on ecosystem dynamics are largely uncharacterized in bioenergy agroecosystems, where the impacts could determine bioenergy's ability to meet its sustainability goals of storing C and reducing N loss. We used FUN-BioCROP (Fixation and Uptake of Nitrogen-Bioenergy Carbon, Rhizosphere, Organisms and Protection), a plant–microbe interaction model of coupled plant nutrient uptake and soil organic matter decomposition, to simulate the effects of nutrient acquisition strategies on soil microbial activity and ecosystem nutrient cycling in bioenergy feedstocks miscanthus (Miscanthus × giganteus) and sorghum (Sorghum bicolor (L.) Moench). We examined the model's ability to reproduce the relative effects of belowground nutrient uptake on microbial activity using a reanalysis of empirical data showing that miscanthus root exudation provoked a larger soil microbial response than sorghum. From baseline model simulations, we found that the ability of miscanthus to retranslocate N resulted in higher N uptake at a lower C cost than the sorghum/soybean rotation and that soil C and N pools increased under perennial (miscanthus) and decreased under annual (sorghum/soybean) cultivation. The model also predicted that greater root exudation increased soil C accumulation, highlighting the role of roots in forming stable soil C. Overall, the baseline model was unable to reproduce field observations of miscanthus root exudation stimulating microbial activity more than sorghum. To improve the model, we updated the soil microbial parameters in miscanthus to have faster decomposition, a higher C/N ratio, and greater carbon use efficiency. These changes improved the simulated soil microbial response to miscanthus root exudation, supporting the hypothesis that miscanthus soils foster a microbial community that is more responsive to root exudation than that of sorghum.

09 BIOMASS FUELS↗