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DOE OSTI2022

The weathered bedrock vadose zone: A hidden control on water availability in the western United States (Final Technical Report)

This report summarizes the research completed during the project entitled "The weathered bedrock vadose zone: A hidden control on water availability in the western United States" (Award: DE-SC0018039). The report covers work completed between 9/15/17 and 9/14/20. The objective of the exploratory project work was to evaluate the overarching hypothesis that the subsurface underlying actively eroding landscapes is systematically structured as a result of a balance between weathering and erosion and that this structure leads to dynamic moisture storage within weathered rock. To accomplish project objectives, we characterized hillslope weathering profile structure and conducted subsurface moisture monitoring across four study sites with comparable bedrock types but differing erosion rate and hydroclimate: The Angelo Coast Range Reserve (ACRR), Sagehorn-Russell Ranch (SRR), Antelope Valley Ranch (AVR), and the LBNL Watershed Function Scientific Focus Area (SFA). New characterization and monitoring infrastructure at the AVR and SFA sites was established through this project and enables long-term monitoring of hydrologic and carbon fluxes at the sites for comparison with long-term monitoring in other sites. Deep drilling, downhole logging, and characterization of chemistry and porosity of rock recovered from drilling reveals two weathering fronts across the sites. A shallower front is marked by the extent of pervasive fracturing and oxidation of pyrite and organic carbon. A deeper weathering front is marked by the appearance of open fractures and discoloration. At the AVR site, multiple ridge tops of different hillslope length were investigated to establish the relationship between the weathering front and topography. Drilling reveals that the fraction of the hillslope relief that is weathered scales with hillslope length, consistent with the theoretical framework that guided the project relating groundwater drainage with landscape evolution. With the establishment of new boreholes, we have documented significant water storage in weathered bedrock using low-field borehole nuclear magnetic resonance (NMR) across all four sites. In the upper 4 m of bedrock, the average water contents at ACRR, AVR, SRR, and SFA are approximately 25%, 16%, 25%, 23% respectively. At the ACRR site, where long-term monitoring via neutron probe surveys and time-domain transmission sensors are available, we have demonstrated that NMR reliably records moisture content and importantly, moisture content dynamics in weathered bedrock. Across all sites, our NMR monitoring has also revealed that a considerable fraction of the water storage occurs in fractures or pores that are significantly larger than the fine-grained bedrock matrix of the parent rock. To identify the proportion of water storage occurring in fractures and large pores, we analyzed the NMR signal by evaluating both the sum of echoes and an inversion of the NMR signal for a distribution of T2 relaxation times. Both methods reveal that at least 20% of the water storage occurs in fractures and larger pores across all sites. To constrain the interpretation of the in-situ field-scale NMR measurements, we compare the NMR response in the field to independent pore-structure information obtained via helium pycnometry. Results support the inference that dynamic seasonal water storage is dominantly restricted to the fracture network, which can reach 7% of the total volume. This dynamic range in water content is comparable to that of some soils, underscoring the need to understand how this region of the Earth System is structured, and functions as a hydrologic reservoir.

58 GEOSCIENCES↗

DOE OSTI2025

Hydrogen Transportation and Distributed Energy Systems Seismic Risk Assessment for Cascadia Subduction Zone Airport Facilities

Portland International Airport in Oregon is exploring operating a fleet of 28 fuel cell electric buses to support airport operations and possibly provide backup power during outages. In this report, we evaluate the risk of hydrogen deployment at an airport considering the potential for seismic activity. We present a seismic risk assessment for pressurized piping for a generic hydrogen refueling station at the airport. Only pressurized piping was considered in the risk analysis because of its vulnerability and availability of fragility information unlike the other components. Seismic capacity of other components should be included as more information becomes available. To characterize the seismic hazard, we considered the initiating event frequency of a Cascadia Subduction Zone earthquake event based on data from the literature. Seismic stressors that translate to the site from an earthquake event are expressed as peak ground acceleration. Site disturbance is characterized as a function of soil conditions, represented by different shear wave velocity values, which affect how seismic waves propagate and impact structures. Pipe fragility curves as a function of seismic capacity were used to correlate ground acceleration and failure probability. These fragility characteristics were combined with site-specific soil conditions to calculate the probability of pipe rupture during a seismic event. It should be noted that multiple simultaneous failures due to an earthquake event as a common cause are not considered. Some epistemic uncertainties such as self-exciting shocks, aftershocks, and the time variant nature of the ground motion are not considered either.

08 HYDROGEN↗

DOE OSTI2021

Responses of Boreal Forest Ecosystems and Permafrost to Climate Change and Disturbances: A Modeling Perspective

The north circumpolar region contains a large amount of carbon. This carbon storage is vulnerable due to permafrost degradation and wildfire disturbances under ongoing and projected climate change. Climate warming and wildfires change soil organic horizons gradually or abruptly, and modify permafrost thermal-hydrology and biogeochemistry, ecosystem structures, functions, and capability of sequestrating rising atmospheric CO2. Land models do not fully take accounts of these interactions and its complexity in the high latitude. This chapter describes a terrestrial ecosystem model with dynamic organic soil module (DOS-TEM) and its unique freezing-thawing algorithm, and presents key results of its applications mainly in boreal forests of Alaska. The DOS-TEM explicitly considers interactions of soil thermal and hydrological processes, permafrost degradation and the direct and indirect effects of wildfire disturbances, in addition to soil–plant C and N cycles. We first introduce four modules of DOS-TEM, focusing on its disturbance module and coupling with a dynamic organic soil module. Then we describe and validate DOS-TEM’s freezing-thawing algorithm and development based on two-directional Stefan algorithm (TDSA). Finally, we apply the DOS-TEM at site and region scales, with a focus on model ability to dynamically simulate soil organic thickness under warming and wildfires, and consequent impacts on permafrost in the Yukon River Basin. We conclude that land surface model development is urgently needed to include other critical landscape processes, such as thermalkarst and other disturbances, to synchronize thermal-hydrological-biogeochemical processes, and to incorporate an advanced understanding of biospheric feedbacks to atmosphere and ecosystems. Such a complexity of modeling scope is plausible with advancement of high performance computing.

Yi, Shuhua↗

DOE OSTI2023

Structure-Driven Liquid Microjunction Surface-Sampling Probe Mass Spectrometry

The rhizosphere is the narrow region of soil surrounding the roots of plants that is influenced by root exudates, root secretions, and associated microbial communities. This region is crucial to plant growth and development and plays a critical role in nutrient uptake, disease resistance, and soil transformation. Understanding the function of exogenous compounds in the rhizosphere starts with determining the spatiotemporal distribution of these molecular components. Using liquid microjunction surface-sampling probe mass spectrometry (LMJ-SSP-MS) and microfluidic devices with attached microporous membranes enables in situ, nondisruptive, and nondestructive spatiotemporal measurement of exogenous compounds from plant roots. However, long imaging times (>2 h) can negatively affect plant heath and limit temporal studies. Here, we present a novel strategy to optimize the number and location of sampling sites on these microporous membrane-covered microfluidic devices. In conclusion, this novel, “structure-driven” sampling workflow takes into consideration the channel structure of the microfluidic device to maximize sampling from the channels and minimize acquisition time (~4× less time in some cases while providing similar chemical image accuracy), thus reducing stress on plants during in situ LMJ-SSP-MS analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Bayesian chain graph models to characterize microbe-environment dynamics

Microbiome data require statistical models that can simultaneously decode microbes' reaction to the environment and interactions among microbes. While a multiresponse linear regression model seems like a straight-forward solution, we argue that treating it as a graphical model is problematic given that the regression coefficient matrix does not encode the conditional dependence structure between response and predictor nodes. This observation is especially important in biological settings when we have prior knowledge on the edges from specific experimental interventions that can only be properly encoded under a conditional dependence model. Here, we propose a chain graph model with two sets of nodes (predictors and responses) whose solution yields a graph with edges that indeed represent conditional dependence, thus agreeing with the experimenter's intuition on the average behavior of nodes under treatment. The solution to our model is sparse via the Bayesian linear regression (LASSO). In addition, we propose an adaptive extension so that different shrinkages can be applied to different edges to incorporate edge-specific prior knowledge. Our model is computationally inexpensive through an efficient Gibbs sampling algorithm and can account for binary, counting, and compositional responses via an appropriate hierarchical structure. We test the performance of our model in a variety of simulated datasets, thereby showing superior performance to state-of-the-art approaches. We further apply our model to human gut and soil microbial compositional datasets, and we highlight that CG-LASSO can estimate biologically meaningful network structures in the data.

compositional data↗

DOE OSTI2021

Lignin-enhanced reduction of structural Fe(III) in nontronite: Dual roles of lignin as electron shuttle and donor

Lignin is a major component of plant-derived soil organic matter (SOM) in soils and sediments. Fe-bearing clay minerals are widely distributed in these environments and often co-exist with lignin. While previous studies have reported the electron shuttling and donating roles of certain redox-active SOM in the dissimilatory reduction of structural Fe(III) in Fe-bearing clay minerals, the role of lignin in this process remains unknown. Here we studied this role by incubating an Fe-rich smectite (nontronite NAu-2) with two types of lignin (soluble and insoluble) in the absence and presence of an Fe(III)-reducing bacterium Shewanella putrefaciens CN32 under anaerobic condition. Labile carbon source (i.e., lactate) was added in some experiments as an extra electron donor. The results demonstrated that both soluble and insoluble lignins abiotically reduced structural Fe(III) in NAu-2. The reduction extent was proportional to lignin concentration. After abiotic reaction, lignin served as either electron shuttle or electron donor in the presence of CN32: (1) When lactate was present, lignin served as an electron shuttle to enhance the rate of Fe(III) reduction; (2) When lactate was absent, lignin served as an electron donor for Fe(III) reduction. Although the biotic Fe(III) reduction extents were similar in the presence of either soluble or insoluble lignin, the reduction rates with soluble lignin were always higher than those with insoluble lignin, likely owing to their different electron transfer mechanisms. After interaction with NAu-2 and/or CN32, soluble lignin structure largely remained intact, but with some decreases of humic/fulvic acid-like and protein-like compounds, aromatic functional groups (e.g., C-H, C=O, COOH), and aliphatic/aromatic compounds. An increase of semiquinone-like organic radicals was observed after lignin interaction with NAu-2. These chemical changes of lignin were likely coupled with reduction of structural Fe(III) in nontronite. The nontronite structure remained largely unchanged without much dissolution and mineral transformation. The findings of this study provide insights into the role of lignin in promoting mineral-microbe interactions and have significant implications for coupled Fe and C biogeochemical cycles in soils and sediments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Changes in microbial community and network structure precede shrub degradation in a desert ecosystem

Large-scale restoration is intended to promote ecological recovery. Improvements in plant and microbial conditions, however, may slow or even reverse in late succession. To better understand long-term restoration outcomes and underlying drivers of successional pathways, we tracked plant, bacterial and fungal, and soil conditions across a 40-year shrub plantation that was intended to stabilize desertified land in northern China. Here, we found that planted Haloxylon ammodendron shrubs developed and then subsequently became degraded after 30–40 years. Bacterial abundance and α-diversity were much higher than those of fungi, but no significant differences in composition and structure were found in different plantation ages. In contrast, the dominant taxa of fungal communities shifted from symbiotroph and saprotroph species towards pathotroph species with increased soil nutrients in the plantation chronosequence after two decades. The changes in fungal dominant species led to a transition in microbial network structure and function, with an increase in negative linkages among taxa that began in the middle stages of succession. Changes in fungal community structure had direct and indirect negative effects on shrub leaf physiology, root activity, and biomass. Our results highlight the preceding role of a breakdown in soil microbial community composition and network structure on the degradation of shrub performance in long-term desert succession. Our study emphasizes the importance of understanding soil-microbial-plant linkages on restoration outcomes, and mechanisms that can slow or reverse the recovery of ecosystems.

Bacterial and fungal community composition↗

DOE OSTI2024

New Opportunities for Neutrons in Environmental and Biological Sciences

The use of neutron methods in environmental and biological sciences is rapidly emerging and accelerating with the development of new instruments at neutron user facilities. This article, based on a workshop held at Oak Ridge National Laboratory (ORNL), offers insights into the application of neutron techniques in environmental and biological sciences. Here we highlight recent advances and identify key challenges and potential future research areas. These include soil and rhizosphere processes, root water dynamics, plant-microbe interactions, structure and dynamics of biological systems, applications in synthetic biology and enzyme engineering, next-generation bioproducts, biomaterials and bioenergy, nanoscale structure, and fluid dynamics of porous materials in geochemistry. We provide an outlook on emerging opportunities with an emphasis on new capabilities that will be enabled at the Spallation Neutron Source Second Target Station currently under design at ORNL. The mission of scientific neutron user facilities worldwide is to enable science using state-of-the-art neutron capabilities. We aim to encourage researchers in the environmental and biological research community to explore the unique capability afforded by neutrons at these facilities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Porous carbon from lignocellulosic biomass with emphasis on corn plant waste residue for energy storage

The rising global demand for sustainable energy storage materials has driven the search for environmentally friendly and cost-effective electrode options. Hydrothermal conversion of lignocellulosic biomass has gained attention due to its low energy requirements and operation at relatively low temperatures, presenting a green alternative to traditional thermochemical methods. The resulting solid product, hydrochar, has been used as an adsorbent and soil amendment; however, chemical/thermal treatment significantly enhances its physical properties. These structural modifications transform hydrochar into an effective porous carbon electrode, offering abundant sites for electrolyte ion transport, critical for high-performance devices like supercapacitors and batteries. This review first discusses various waste biomass and sustainable feedstocks available globally. It compares two primary thermochemical conversion techniques, pyrolysis and hydrothermal carbonization/liquefaction, and examines their respective solid products, biochar and hydrochar, analyzing differences in their physical and chemical characteristics. The focus is placed on hydrochar, summarizing activation methods to produce porous carbon suitable for energy storage applications. Additionally, this review will include a dedicated section on the application of porous carbon derived from corn plant waste residue, considering that corn is one of the most abundant crops grown worldwide, which makes it an important and promising source for sustainable porous carbon production. The role of machine learning models in optimizing hydrothermal processes to produce high-quality hydrochar is also discussed, emphasizing how data-driven approaches can streamline process development. Finally, the review identifies the current challenges and prospects for lignocellulosic biomass-derived porous carbon as a sustainable electrode material in next-generation energy storage technologies.

25 ENERGY STORAGE↗

DOE OSTI2024

Abiotic Stress Reorganizes Rhizosphere and Endosphere Network Structure of Sorghum bicolor

Sorghum bicolor is a promising bioenergy feedstock with high biomass production and unusual tolerance for stresses, such as water and nutrient limitation. Although the membership of the sorghum microbiome in response to stress has been explored, relatively little is known about how microbe–microbe networks change under water- or nutrient-limited conditions. This is important because network changes can indicate impacts on the functionality and stability of microbial communities. We performed network-based analysis on the core bacterial and archaeal community of an agronomically promising high biomass bioenergy genotype, Grassl, grown under nitrogen and water stress. Stress caused relatively minor changes in bacterial abundances within soil, rhizosphere, and endosphere communities but led to significant changes in bacterial network structure and modularity. We found a complete reorganization of network roles in all plant compartments, as well as an increase in the modularity and proportion of positive associations, which potentially could represent coexistence and cooperation in the sorghum bacterial/archaeal community under stress. Although stressors are often believed to be destabilizing, we found stressed networks were as or more stable than non-stressed networks, likely due to their redundancy and compartmentalization. Together, these findings support the idea that both sorghum and its bacterial/archaeal community can be resilient to future environmental stressors.

09 BIOMASS FUELS↗

DOE OSTI2020

Lessons Learned from Hanford's Purex Tunnel 2 Structural Stabilization Project - 20509

In 2019, U.S. Department of Energy (DOE) contractor CH2M Hill Plateau Remediation Company (CHPRC) completed structurally stabilizing the Plutonium Uranium Extraction Plant (Purex) waste storage Tunnel 2 with engineered grout. This action significantly reduced risk to Hanford workers, the surrounding community and environment by preventing future collapse of the tunnel and possible release of radioactive materials. Decades of plutonium production at the Purex facility required construction of two large underground tunnels for storage of highly contaminated plutonium processing equipment that had failed during the operation of Purex and other facilities across the Hanford Site. Following the partial collapse of Purex Tunnel 1 on May 9, 2017, DOE and CHPRC took immediate action to safely stabilize the collapsed section of the tunnel. The hole in the tunnel was filled the next day as a temporary stabilization measure, and no contamination was detected as a result of the partial collapse of the tunnel. Workers then stabilized Tunnel 1 in its entirety by filling with engineered grout, which also encapsulated the radioactive equipment and railcars within the tunnel. Grouting eliminated the risk of further collapse and stabilized the tunnel contents, all while not precluding future remedial actions or final closure decisions. While conducting an integrity analysis of Tunnel 1 by using construction drawings, photos and other historical documents, project teams also analyzed the much larger Purex Tunnel 2. The analysis found Tunnel 2 did not meet current codes for structural integrity, and it may not be able to bear the weight of the soil above the tunnel. Therefore, it was determined that Tunnel 2 was also at risk of collapse. DoE's independent panel of experts determined grouting to be the best choice for stabilizing Tunnel 2 because it provides the highest level of stability and protection, and does not preclude future remedial actions. DOE authorized CHPRC to commence work and the Purex Tunnel 2 Structural Stabilization Project was launched in December of 2017. The paper will discuss the process of recognizing the following critical aspects and risks associated with stabilizing Tunnel 2, and the actions taken by the project team to mitigate these risks, including: - Tunnel investigation and data collection to assist with future remediation; - On-site batching and mock-ups to provide the large quantity of grout required for stabilizing the tunnel; - Workforce involvement and innovative actions that mitigated the project's most significant potential hazards, including traffic control; - Project team high level of execution translated into successful project execution. Sharing lessons learned from this critical risk-reduction effort can enhance the safety and efficiency of other complex and hazardous projects across the DOE complex. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Data for Microbial-Explicit Processes and Refined Perennial Plant Traits Improve Modeled Ecosystem Carbon Dynamics

Globally, soils hold approximately half of ecosystem carbon and can serve as a source or sink depending on climate, vegetation, management, and disturbance regimes. Understanding how soil carbon dynamics are influenced by these factors is essential to evaluate proposed natural climate solutions and policy regarding net ecosystem carbon balance. Soil microbes play a key role in both carbon fluxes and stabilization. However, biogeochemical models often do not specifically address microbial-explicit processes. Here, we incorporated microbial-explicit processes into the DayCent biogeochemical model to better represent large perennial grasses and mechanisms of soil carbon formation and stabilization. We also take advantage of recent model improvements to better represent perennial grass structural complexity and life-history traits. Specifically, this study focuses on: 1) a plant sub-model that represents perennial phenology and more refined plant chemistry with downstream implications for soil organic matter (SOM) cycling though litter inputs, 2) live and dead soil microbe pools that influence routing of carbon to physically protected and unprotected pools, 3) Michaelis-Menten kinetics rather than first-order kinetics in the soil decomposition calculations, and 4) feedbacks between decomposition and live microbial pools. We evaluated the performance of the plant sub-model and two SOM cycling sub-models, Michaelis-Menten (MM) and first-order (FO), using observations of net ecosystem production, ecosystem respiration, soil respiration, microbial biomass, and soil carbon from long-term bioenergy research plots in the mid-western United States. The MM sub-model represented seasonal dynamics of soil carbon fluxes better than the FO sub-model which consistently overestimated winter soil respiration. While both SOM sub-models were similarly calibrated to total, physically protected, and physically unprotected soil carbon measurements, the models differed in future soil carbon response to disturbance and climate, most notably in the protected pools. Adding microbial-explicit mechanisms of soil processes to ecosystem models will improve model predictions of ecosystem carbon balances but more data and research are necessary to validate disturbance and climate change responses and soil pool allocation.

Field Data↗

DOE OSTI2023

Bridging Time-series Image Phenotyping and Functional–Structural Plant Modeling to Predict Adventitious Root System Architecture

Root system architecture (RSA) is an important measure of how plants navigate and interact with the soil environment. However, current methods in studying RSA must make tradeoffs between precision of data and proximity to natural conditions, with root growth in germination papers providing accessibility and high data resolution. Functional–structural plant models (FSPMs) can overcome this tradeoff, though parameterization and evaluation of FSPMs are traditionally based in manual measurements and visual comparison. Here, we applied a germination paper system to study the adventitious RSA and root phenology of Populus trichocarpa stem cuttings using time-series image-based phenotyping augmented by FSPM. We found a significant correlation between timing of root initiation and thermal time at cutting collection (P value = 0.0061, R 2 = 0.875), but little correlation with RSA. We also present a use of RhizoVision [1] for automatically extracting FSPM parameters from time series images and evaluating FSPM simulations. A high accuracy of the parameterization was achieved in predicting 2D growth with a sensitivity rate of 83.5%. This accuracy was lost when predicting 3D growth with sensitivity rates of 38.5% to 48.7%, while overall accuracy varied with phenotyping methods. Despite this loss in accuracy, the new method is amenable to high throughput FSPM parameterization and bridges the gap between advances in time-series phenotyping and FSPMs.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Impacts of nitrogen addition on switchgrass root-associated diazotrophic community structure and function

ABSTRACT Cellulosic bioenergy crops, like switchgrass (Panicum virgatum), have potential for growth on lands unsuitable for food production coupled with potential for climate mitigation. Sustainability of these systems lies in identifying conditions that promote high biomass yields on marginal lands under low-input agricultural practices. Associative nitrogen fixation (ANF) is a potentially important nitrogen (N) source for these crops, yet ANF contributions to plant N, especially under fertilizer N addition are unclear. In this study, we assess structure (nifH) and function (ANF) of switchgrass root-associated diazotrophic communities to long-term and short-term N additions using soil from three marginal land sites. ANF rates were variable and often unexpectedly high, sometimes 10× greater than reported in the literature, and did not respond in repeatable ways to long-term or short-term N. We found few impacts of N addition on root-associated diazotrophic community structure or membership. Instead, we found a very consistent root-associated diazotrophic community even though switchgrass seeds were germinated in soil from field sites with distinct diazotrophic communities. Ultimately, this work demonstrates that root-associated diazotrophic communities have the potential to contribute to switchgrass N demands, independent of N addition, and this may be driven by selection of the diazotrophic community by switchgrass roots.

Microbiology↗

DOE OSTI2025

Community‐Level Metabolic Shifts Following Land Use Change in the Amazon Rainforest Identified by a Supervised Machine Leaning Approach

ABSTRACT The Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. This change in plant cover is known to alter the soil microbiome and the functions it mediates, but the genomic changes underlying this response are still unresolved. In this study, we used a combination of deep shotgun metagenomics complemented by a supervised machine learning approach to compare the metabolic strategies of tropical soil microbial communities in pristine forests and long‐term established pastures in the Amazon. Machine learning‐derived metagenome analysis indicated that microbial community structures (bacteria, archaea and viruses) and the composition of protein‐coding genes were distinct in each plant cover type environment. Forest and pasture soils had different genomic diversities for the above three taxonomic groups, characterised by their protein‐coding genes. These differences in metagenome profiles in soils under forests and pastures suggest that metabolic strategies related to carbohydrate and energy metabolisms were altered at community level. Changes were also consistent with known modifications to the C and N cycles caused by long‐term shifts in aboveground vegetation and were also associated with several soil physicochemical properties known to change with land use, such as the C/N ratio, soil temperature and exchangeable acidity. In addition, our analysis reveals that these alterations in land use can also result in changes to the composition and diversity of the soil DNA virome. Collectively, our study indicates that soil microbial communities shift their overall metabolic strategies, driven by genomic alterations observed in pristine forests and long‐term established pastures with implications for the C and N cycles.

carbon and nitrogen cycles↗

DOE OSTI2020

Linear two-pool models are insufficient to infer soil organic matter decomposition temperature sensitivity from incubations

Abstract Terrestrial carbon (C)-climate feedbacks depend strongly on how soil organic matter (SOM) decomposition responds to temperature. This dependency is often represented in land models by the parameter Q 10 , which quantifies the relative increase of microbial soil respiration per 10 °C temperature increase. Many studies have conducted paired laboratory soil incubations and inferred “active” and “slow” pool Q 10 values by fitting linear two-pool models to measured respiration time series. Using a recently published incubation study (Qin et al. in Sci Adv 5(7):eaau1218, 2019) as an example, here we first show that the very high parametric equifinality of the linear two-pool models may render such incubation-based Q 10 estimates unreliable. In particular, we show that, accompanied by the uncertain initial active pool size, the slow pool Q 10 can span a very wide range, including values as high as 100, although all parameter combinations are producing almost equally good model fit with respect to the observations. This result is robust whether or not interactions between the active and slow pools are considered (typically these interactions are not considered when interpreting incubation data, but are part of the predictive soil carbon models). This very large parametric equifinality in the context of interpreting incubation data is consistent with the poor temporal extrapolation capability of linear multi-pool models identified in recent studies. Next, using a microbe-explicit SOM model (RESOM), we show that the inferred two pools and their associated parameters (e.g., Q 10 ) could be artificial constructs and are therefore unreliable concepts for integration into predictive models. We finally discuss uncertainties in applying linear two-pool (or more generally multiple-pool) models to estimate SOM decomposition parameters such as temperature sensitivities from laboratory incubations. We also propose new observations and model structures that could enable better process understanding and more robust predictive capabilities of soil carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

N-induced soil acidification triggers metal stimulation of soil methane oxidation in a temperate steppe ecosystem

Methane (CH 4 ) is a potent greenhouse gas, and it is well established that low nitrogen (N) stimulates- and high N suppresses CH 4 oxidation in grassland ecosystems. Here, in this study, we examined the response of CH 4 uptake to long-term (>10 years) multi-level N additions in a temperate steppe of northern China. The N impacts on CH 4 uptake transitioned from positive to negative at the N addition rate of 4 g N m -2 y -1 . However, the high-N suppression on CH 4 uptake was partially relieved when the continuous (>10 years) high N inputs (16 g N m -2 y -1 to 64 g N m -2 y -1 ) caused soil pH drop to < 5.7. Further experiments revealed that continuous high-N inputs acidified soil to pH < 5.7 that released metal ions to stimulate monooxygenase enzyme activity; therefore, the CH 4 oxidation suppression was partially relieved under continuous N loading. Structural equation model results confirmed that metal ions, such as Iron (Fe 3+ ), Manganese (Mn 4+ ), and Copper (Cu) desorbed by soil particles, were negatively correlated with soil pH while positively correlated with CH 4 oxidation under high N inputs. These analyses suggested that continuous high N inputs-induced soil acidification can release previously bounded metal elements that partially alleviated the N suppression on CH 4 uptake. The N-induced soil acidification impacts on CH 4 uptake might play a critical role in global CH 4 cycling and deserve further investigation as external N inputs continue climbing.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Warming effects on grassland soil microbial communities are amplified in cool months

Abstract Global warming modulates soil respiration (RS) via microbial decomposition, which is seasonally dependent. Yet, the magnitude and direction of this modulation remain unclear, partly owing to the lack of knowledge on how microorganisms respond to seasonal changes. Here, we investigated the temporal dynamics of soil microbial communities over 12 consecutive months under experimental warming in a tallgrass prairie ecosystem. The interplay between warming and time altered (P < 0.05) the taxonomic and functional compositions of microbial communities. During the cool months (January to February and October to December), warming induced a soil microbiome with a higher genomic potential for carbon decomposition, community-level ribosomal RNA operon (rrn) copy numbers, and microbial metabolic quotients, suggesting that warming stimulated fast-growing microorganisms that enhanced carbon decomposition. Modeling analyses further showed that warming reduced the temperature sensitivity of microbial carbon use efficiency (CUE) by 28.7% when monthly average temperature was low, resulting in lower microbial CUE and higher heterotrophic respiration (Rh) potentials. Structural equation modeling showed that warming modulated both Rh and RS directly by altering soil temperature and indirectly by influencing microbial community traits, soil moisture, nitrate content, soil pH, and gross primary productivity. The modulation of Rh by warming was more pronounced in cooler months compared to warmer ones. Together, our findings reveal distinct warming-induced effects on microbial functional traits in cool months, challenging the norm of soil sampling only in the peak growing season, and advancing our mechanistic understanding of the seasonal pattern of RS and Rh sensitivity to warming.

54 ENVIRONMENTAL SCIENCES↗