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At least 109 records · Page 6

Resistance, Resilience, and Recovery of Dryland Soil Bacterial Communities Across Multiple Disturbances

Dryland ecosystems are sensitive to perturbations and generally slow to recover post disturbance. The microorganisms residing in dryland soils are especially important as they contribute to soil structure and nutrient cycling. Disturbance can have particularly strong effects on dryland soil structure and function, yet the natural resistance and recovery of the microbial components of dryland soils has not been well documented. In this study, the recovery of surface soil bacterial communities from multiple physical and environmental disturbances is assessed. Samples were collected from three field sites in the vicinity of Moab, UT, United States, 6 to 7 years after physical and climate disturbance manipulations had been terminated, allowing for the assessment of community recovery. Additionally, samples were collected in a transect that included three habitat patches: the canopy zone soils under the dominant shrubs, the interspace soils that are colonized by biological soil crusts, and edge soils at the plot borders. Field site and habitat patch were significant factors structuring the bacterial communities, illustrating that sites and habitats harbored unique soil microbiomes. Across the different sites and disturbance treatments, there was evidence of significant bacterial community recovery, as bacterial biomass and diversity were not significantly different than control plots. There was, however, a small number of 16S rRNA gene amplicon sequence variants that distinguished particular treatments, suggesting that legacy effects of the disturbances still remained. Taken together, these data suggest that dryland bacterial communities may possess a previously unappreciated potential to recover within years of the original disturbance.

59 BASIC BIOLOGICAL SCIENCES↗

A shift from inorganic to organic nitrogen-dominance shapes soil microbiome composition and co-occurrence networks

Soil microbiomes are characterized by their composition and networks, which are linked to soil nitrogen (N) availability. In nature, inorganic N dominates at one end and organic N dominates at the other end along soil N gradients; however, little is known about how this shift influences soil microbiome composition and co-occurrence networks, as well as their controls. To this end, we conducted an experiment with the host plant Solidago canadensis , which was subject to three N regimes: inorganic N-dominated, co-dominated by inorganic and organic N (CIO), and organic N-dominated. Organic N dominance exhibited stronger effects on the composition and co-occurrence networks of soil microbiomes than inorganic N dominance. The predominant control was plant traits for bacterial and fungal richness, and soil pH for keystone species. Relative to the CIO regime, inorganic N dominance did not affect fungal richness and increased keystone species; organic N dominance decreased fungal richness and keystone species. Pathogenic fungi and arbuscular mycorrhizal fungi were suppressed by organic N dominance but not by inorganic N dominance. These findings suggest that the shift from soil inorganic N-dominance to soil organic N-dominance could strongly shape soil microbiome composition and co-occurrence networks by altering species diversity and topological properties.

Xin, Yue↗

A new bioenergy model that simulates the impacts of plant‐microbial interactions, soil carbon protection, and mechanistic tillage on soil carbon cycling

Abstract Advancing our predictive understanding of bioenergy systems is critical to design decision tools that can inform which feedstock to plant, where to plant it, and how to manage its production to provide both energy and ecosystem carbon (C) benefits. Here, we lay the foundation for that advancement by integrating recent developments in the science of belowground processes in shaping the C cycle into a new bioenergy model, FUN‐BioCROP (Fixation and Uptake of Nitrogen‐Bioenergy Carbon, Rhizosphere, Organisms, and Protection). We show that FUN‐BioCROP can approximate the historical trajectory of soil C dynamics as natural ecosystems were successively converted into intensive agriculture and bioenergy systems. This ability relies in part on a novel tillage representation that mechanistically models tillage as a process that increases microbial access to C. Importantly, the impacts of tillage and feedstock choice also influence FUN‐BioCROP simulations of warming responses with no‐till perennial feedstocks, miscanthus, and switchgrass, having more C that is unprotected and susceptible to warming than tilled annual feedstocks like corn–corn–soybean. However, this susceptibility to warming is balanced by a greater potential for increases in belowground C allocation to enhance soil C stocks in perennial systems. Collectively, our model results highlight the importance of belowground processes in evaluating the ecosystem C benefits of bioenergy production.

09 BIOMASS FUELS↗

Response of soil nutrient pools and microbiomes to recurrent wildfire disturbance and varying burn severities in a mixed conifer forest

Wildfire is a pervasive disturbance in mixed-conifer forests, yet the relative influence of fire recurrence versus burn severity on soil biogeochemistry and microbial communities remains poorly quantified. We examined a natural gradient of fire history (0–3 prior fires) and burn severity (low–high) spanning 50 yr in a mixed-conifer ecosystem to assess how repeated fire shapes soil carbon (C) and nitrogen (N) pools, their isotopic signatures, mineral and particulate fractions, microbial community composition, carbon-use, CO₂ fluxes, and vegetation cover. Successive fires produced progressively higher bare-ground percentages and lower tree cover, which were tightly linked to declines in microbial diversity and reductions bulk %C, and %N. δ 13 C increased with fire frequency, indicating preferential loss of labile C through combustion or enhanced microbial oxidation, thereby explaining the observed net soil-C decline. Conversely, δ 15 N decreased and pH increased as tree density declined, reflecting altered N cycling and reduced acidification in post-fire soils. Fire recurrence, more than severity, corresponded with a marked shift in the bacterial community: for example, Xanthobacteraceae—key N-fixers and C-cyclers—diminished, while N-fixing Bacillaceae increased, underscoring the tightly coupled nature of soil nutrient dynamics and microbiome composition after repeated burns. Our results demonstrate that fire recurrence appears to be a stronger driver of post-fire soil ecosystem responses in this mixed-conifer forest, influencing both abiotic nutrient pools and the functional potential of the soil microbiome. These findings provide a more enhanced assessment and understanding to date of the biogeochemical consequences of repeated wildfire disturbance that can be used to inform management strategies aimed at preserving soil health in fire-prone landscapes.

54 ENVIRONMENTAL SCIENCES↗

Automated point dendrometer, soil moisture and temperature, and meteorological variables datasets, Oct 2024 – Nov 2025, G.A. Pearson Natural Area, Flagstaff, AZ, USA

This data package includes parsed, cleaned, and calibrated data from 48 TOMST automated point dendrometers, 48 TOMST 15 cm soil moisture sensors, and 12 TOMST 30 cm soil moisture sensors. The point dendrometers were cleaned with the “dendRoAnalyst” package in RStudio. The soil sensors were cleaned and calibrated for volumetric water content (VWC) with the “myClim” package in RStudio using the soil texture of the site (sandy clay loam). Additionally, this data package also includes raw data from 2 METER weather stations. Dendrometers and soil sensors have both their sensor ID, as well as the ID for the specific tree they were instrumented on at the G.A. Pearson Natural Area (GPNA) site and their experimental group. The purpose of these data is to understand how ponderosa pine trees in restored (thinned and burned) vs. unrestored (no treatment) areas are responding to drought and seasonal precipitation. These data use radial growth and soil moisture data to answer the following question: how are active season length, growth on different time scales (weekly, monthly, seasonally, and annually), growth during dry periods and after precipitation events, and environmental and biological drivers of radial growth different between restored versus unrestored areas?

Air temperature↗

Development of Laboratory Testbeds Simulating Real-World Greenhouse Gas Emissions

Climate change leads to drastic variations in the environment that can threaten food security. To protect the security and prosperity of the environment, new agricultural practices that mitigate greenhouse gas emissions need to be developed. Agriculture plays a large role in the emissions of greenhouse gases, thus a need for new practices. At present, testing landscape management practices for carbon sequestration and reduction of greenhouse gas emissions are expensive because such tests often require intricate field experiments. Laboratory tests on landscape management practices often fail to simulate and accurately represent the natural systems researchers intend to study. There are methods that can be used to make these laboratory tests more closely replicate natural systems for the improvement of agricultural lands used in biofuel and food production. The goal of this project is to develop a laboratory testbed replicating field conditions that will mimic field greenhouse gas emissions. To achieve this goal, we used soil cores taken from agricultural and marginal lands, then attached fiberglass wicks to improve the drainage system in the soil core to simulate a more natural hydraulic system. The soil cores with the wicks were used to compared to greenhouse gas emissions observed in the field. Our preliminary results suggest that the soil carbon dioxide and nitrous oxide flux from the agricultural land site were comparable to the soil cores equipped with the drainage wicks. The data suggests that laboratory testbeds can be used to mimic field greenhouse gas emissions if parameters, such as soil water content were in a set range. The laboratory testbed produces similar greenhouse gas emissions to the agricultural site when the soil water content was between 15-25%.

54 ENVIRONMENTAL SCIENCES↗

Estimating biofuel contaminant concentration from 4D ERT with mixing models

Here, we present the results of a lab-scaled feasibility study to assess the performance of electrical resistivity tomography for detection, characterization, and monitoring of fuel grade ethanol releases to the subsurface. Further, we attempt to determine the concentration distribution of the ethanol from the electrical resistivity tomography data using mixing-models. Ethanol is a renewable fuel source as well as an oxygenate fuel additive currently used to replace the known carcinogen methyl tert-butyl ether; however, ethanol is preferentially biodegraded and a cosolvent. When introduced to areas previously impacted by nonethanol-based fuels, it will facilitate the persistence of carcinogenic fuel compounds like benzene and ethylbenzene, as well as remobilize them to the ground water. These compounds would otherwise be retained in the soil column undergoing active or passive remediation processes such as soil vapor extraction or natural attenuation. Here, we introduce ethanol to a saturated Ottawa sand in a tank instrumented for four-dimensional geoelectrical measurements. Forward model results suggest pure phase ethanol released into a water saturated silica sand should present a detectable target for electrical resistivity tomography relative to a saturated silica sand only. We observe the introduction of ethanol to the closed hydraulic system and subsequent migration over the duration of the experiment. One-dimensional and three–dimensional temporal data are assessed for the detection, characterization, and monitoring of the ethanol release. Results suggest one-dimensional geoelectrical measurements may be useful for monitoring a release, while three-dimensional geoelectrical field imaging would be useful to characterize, monitor, and design effective remediation approaches for an ethanol release, assuming field conditions do not preclude the application of geoelectrical methods. We then attempt to use predictive mixing models to calculate the distribution of ethanol concentration within the measurement domain. For this study we examine four different models: a nested parallel mixing model, a nested cubic mixing model, the complex refractive index model (CRIM), and the Lichtenecker-Rother (L-R) model. The L-R model, modified to include an electrical formation factor geometry term, provided the best agreement with expected EtOH concentrations.

09 BIOMASS FUELS↗

Urban Seismic Site Characterization by Fiber-Optic Seismology

ccurate ground motion prediction requires detailed site effect assessment, but in urban areas where such assessments are most important, geotechnical surveys are difficult to perform, limiting their availability. Distributed acoustic sensing (DAS) offers an appealing alternative by repurposing existing fiber-optic cables, normally employed for telecommunication, as an array of seismic sensors. We present a proof-of-concept demonstration by using DAS to produce high-resolution maps of the shallow subsurface with the Stanford DAS array, California. We describe new methods and their assumptions to assess H/V spectral ratio—a technique widely used to estimate the natural frequency of the soil—and to extract Rayleigh wave dispersion curves from ambient seismic field. These measurements are jointly inverted to provide models of shallow seismic velocities and sediment thicknesses above bedrock in central campus. The good agreement with an independent survey validates the methodology and demonstrates the power of DAS for microzonation.

Geochemistry & Geophysics↗

Bacterial community dynamics as a result of growth-yield trade-off and multispecies metabolic interactions toward understanding the gut biofilm niche

Abstract Bacterial communities are ubiquitous, found in natural ecosystems, such as soil, and within living organisms, like the human microbiome. The dynamics of these communities in diverse environments depend on factors such as spatial features of the microbial niche, biochemical kinetics, and interactions among bacteria. Moreover, in many systems, bacterial communities are influenced by multiple physical mechanisms, such as mass transport and detachment forces. One example is gut mucosal communities, where dense, closely packed communities develop under the concurrent influence of nutrient transport from the lumen and fluid-mediated detachment of bacteria. In this study, we model a mucosal niche through a coupled agent-based and finite-volume modeling approach. This methodology enables us to model bacterial interactions affected by nutrient release from various sources while adjusting individual bacterial kinetics. We explored how the dispersion and abundance of bacteria are influenced by biochemical kinetics in different types of metabolic interactions, with a particular focus on the trade-off between growth rate and yield. Our findings demonstrate that in competitive scenarios, higher growth rates result in a larger share of the niche space. In contrast, growth yield plays a critical role in neutralism, commensalism, and mutualism interactions. When bacteria are introduced sequentially, they cause distinct spatiotemporal effects, such as deeper niche colonization in commensalism and mutualism scenarios driven by species intermixing effects, which are enhanced by high growth yields. Moreover, sub-ecosystem interactions dictate the dynamics of three-species communities, sometimes yielding unexpected outcomes. Competitive, fast-growing bacteria demonstrate robust colonization abilities, yet they face challenges in displacing established mutualistic systems. Bacteria that develop a cooperative relationship with existing species typically obtain niche residence, regardless of their growth rates, although higher growth yields significantly enhance their abundance. Our results underscore the importance of bacterial niche dynamics in shaping community properties and succession, highlighting a new approach to manipulating microbial systems.

Microbiology↗

Mechanisms of regulation of the rhizosphere, roots and shoots of naive poplars

Trees are associated with a broad range of microorganisms colonising the diverse tissues of their host. However, the early dynamics of the microbiota assembly microbiota from the root to shoot axis and how it is linked to root exudates and metabolite contents of tissues remain unclear. Here, we characterised how fungal and bacterial communities are altering root exudates as well as root and shoot metabolomes in parallel with their establishment in poplar cuttings (Populus tremula x tremuloides clone T89) over 30 days of growth. Sterile poplar cuttings were planted in natural or gamma irradiated soils. Bulk and rhizospheric soils, root and shoot tissues were collected from day 1 to day 30 to track the dynamic changes of fungal and bacterial communities in the different habitats by DNA metabarcoding. Root exudates and root and shoot metabolites were analysed in parallel by gas chromatography-mass spectrometry.

09 BIOMASS FUELS↗

Deep Learning Prediction of Interspecies Interactions from Self-organized Spatiotemporal Patterns of Co-evolving Organisms

Microorganisms colonizing natural habits such as soils co-evolve to form specific spatial patterns through interspecies interactions. These self-organized patterns are a key ecological phenotype, which provides critical information on their interaction mechanisms. However, conventional network inference techniques that analyze species population data in bulk have yet to be extended to account for such spatial heterogeneity. Here we proposed supervised deep learning as a new network inference tool for predicting interspecies interactions from spatiotemporal patterns of microbial evolution. Due to lack of biological imaging data that can be used for training deep learning networks, we used in silico data generated from high-fidelity agent-based models to determine model structure and parameters. Even though networks were trained under simple configurations where interaction coefficients are assumed to be spatially invariant, we demonstrated that the resulting model can be utilized to successfully predict spatial variation of interactions in more complex domains (i.e., configured with a context-dependent mixture of interaction coefficients) as well as in simple domains without further training. In the further test against real biological data obtained through imaging experiments of a binary consortium (Pseudomonas fluorescens and a mutant of Escherichia coli), our model also predicted the dramatic shifts in interactions of the two organisms across different environmental contexts. Through various successful demonstrations in this work, the combined use of the agent-based model and machine learning algorithm provides a means to use new type of data - microscopic images - for extracting microbial interactions, therefore presenting itself as a useful tool for the analysis of more complex microbial community interactions.

Lee, Joon-Yong↗

Background Concentrations of Argon-39 in Shallow Soil Gas

While radioisotopes of noble gases are known to be indicators of underground nuclear explosions (UNE), McIntyre et al. (2017) was the first to report the presence of 39Ar in shallow soil gas in association with a decades old UNE. While this finding hinted at the potential application of 39Ar to be used as an indicator of an UNE, doing so would also require an understanding of the natural concentrations of 39Ar present in soil gas. Without knowing the expected range and variability of naturally occurring concentrations of 39Ar, it is difficult to determine what measured concentrations would be indicative of an elevated concentration. This paper presents results from 16 soil gas samples and three atmospheric air samples collected from various locations across the western United States. Shallow soil gas samples were collected into self-contained underwater breathing apparatus (SCUBA) tanks using a custom-built soil gas sampling system and then processed and analyzed for 39Ar. The measured concentrations of 39Ar varied from atmospheric air concentrations to about 3.5 times atmospheric air concentrations. The variation in concentration was primarily attributed to the latitude the sample was collected at, which was consistent with previous work (Johnson et al. 2015). The results presented here represent the first measurements of natural background 39Ar concentrations in shallow soil gas. This data will be necessary if 39Ar is to be used as an indicator of UNE.

Fritz, Brad G.↗

Effect of fluctuating redox conditions on trace metal release from wetland soils from South Carolina and stream sediments from Tennessee

Natural aquatic systems undergo fluctuating redox conditions due to microbial activity, varying water saturation levels, and nutrients dynamics. With fluctuating oxic and anoxic conditions, trace metals can be mobilized or sequestered in response to changes in iron and sulfur speciation and the concentrations and lability of organic carbon. We conducted a systematic laboratory-based microcosm study to examine the effect of redox fluctuations on trace metal mobility in samples collected from two different natural aquatic systems: riparian wetlands and a stream. We incubated water-saturated soils under three cycles of anoxic-oxic conditions (τanoxic:τoxic = 3) spanning 24 days and monitored the change in dissolved and bioavailable metal (copper (Cu), nickel (Ni), zinc (Zn), cobalt (Co), iron (Fe), and manganese (Mn)) concentrations. The dataset includes the results of the variation in metal concentrations due to redox fluctuations in wetland soils and stream sediments. Additionally, the variation in the bioavailable concentration of metals obtained using passive samplers based on diffuse gradient in thin-films technique is included in the dataset. We have also reported the change in the pH values and dissolved oxygen concentrations in the microcosms during the entire study of 24 days. The dataset also contains the dissolved organic carbon and sulfate concentrations, and the data on fractions of metals bound to reducible and oxidizable phases. For materials from both the wetlands and the stream, anoxic conditions favored Co and Zn release, which corresponded with the reductive dissolution of iron oxides. In contrast, dissolved Cu concentrations increased under oxic conditions for both sites and correlated positively with the release of sulfate. In wetland soils, dissolution of Fe (hydr)oxides increased Ni solubility; however, in stream sediments, Ni release occurred when sulfides or organic matter were oxidized. For stream sediments, each subsequent redox cycle increased the bioavailability of trace metals. Upon redox fluctuations in wetland soils, the bioavailability of Zn and Cu increased, whereas bioavailable Ni and Co decreased. This study illustrates that different trace metals display distinct bioavailability patterns during oxic-anoxic fluctuations in natural environments. The biogeochemical cycling of carbon and nitrogen in systems with redox fluctuations may be influenced by these patterns in trace metal availability in addition to the availability of electron donors and acceptors.

54 ENVIRONMENTAL SCIENCES↗

Impact of Grazing Duration and Environment on Soil Carbon in Reclaimed Uranium Mines Tailings: A Region Specific Study

ABSTRACT Grassland ecosystems, which cover over one‐third of the Earth's land area, store 10%–30% of global soil carbon (C). However, these ecosystems face substantial impacts from human activities, including mining. This study investigates the spatial distribution of soil C and related environmental factors in reclaimed grasslands on former uranium mine sites in Wyoming. We hypothesized that grazing duration and environmental factors would influence soil C levels. Interactions between topography, vegetation diversity, soil properties, and soil C in the context of grazing management in both natural and reclaimed grasslands from a wide range of periods from 1 year to 100 years were analyzed using geographically weighted regression models. Data collected from 2022 to 2023 showed that total carbon was consistently higher in natural grasslands (1.2%–4.9%) than in reclaimed grasslands (0.8%–1.3%). Additionally, soil C was significantly higher in natural grasslands grazed for 1 year compared to those grazed for 100 years. In contrast, reclaimed grasslands had lower soil C in areas grazed for 1 year compared to those grazed for 7 or 14 years. The absolute values of coefficients from environmental covariates indicated that areas grazed for a shorter duration (~1 year) were more influenced by biotic and abiotic factors than areas grazed for longer periods (> 7 years). Our findings show moderate grazing increases the resiliency of grassland ecosystems when grazed 7 years or longer and acknowledge the roles of topographic, soil, and vegetative factors in enhancing soil C concentration and developing sustainable land management practices in rangeland conditions.

Shilpakar, Chandan [Department of Plant Sciences U↗

Microbial sensitivity to temperature and sulfate deposition modulates greenhouse gas emissions from peat soils

Abstract Peatlands are among the largest natural sources of atmospheric methane (CH 4 ) worldwide. Microbial processes play a key role in regulating CH 4 emissions from peatland ecosystems, yet the complex interplay between soil substrates and microbial communities in controlling CH 4 emissions as a function of global change remains unclear. Herein, we performed an integrated analysis of multi‐omics data sets to provide a comprehensive understanding of the molecular processes driving changes in greenhouse gas (GHG) emissions in peatland ecosystems with increasing temperature and sulfate deposition in a laboratory incubation study. We sought to first investigate how increasing temperatures (4, 21, and 35°C) impact soil microbiome–metabolome interactions; then explore the competition between methanogens and sulfate‐reducing bacteria (SRBs) with increasing sulfate concentrations at the optimum temperature for methanogenesis. Our results revealed that peat soil organic matter degradation, mediated by biotic and potentially abiotic processes, is the main driver of the increase in CO 2 production with temperature. In contrast, the decrease in CH 4 production at 35°C was linked to the absence of syntrophic communities and the potential inhibitory effect of phenols on methanogens. Elevated temperatures further induced the microbial communities to develop high growth yield and stress tolerator trait‐based strategies leading to a shift in their composition and function. On the other hand, SRBs were able to outcompete methanogens in the presence of non‐limiting sulfate concentrations at 21°C, thereby reducing CH 4 emissions. At higher sulfate concentrations, however, the prevalence of communities capable of producing sufficient low‐molecular‐weight carbon substrates for the coexistence of SRBs and methanogens was translated into elevated CH 4 emissions. The use of omics in this study enhanced our understanding of the structure and interactions among microbes with the abiotic components of the system that can be useful for mitigating GHG emissions from peatland ecosystems in the face of global change.

AminiTabrizi, Roya↗

Lipid–enhanced Oilcane does not impact soil carbon dynamics compared with wild–type Sugarcane

The carbon neutral potential of bioenergy relies in part on the ability of feedstocks to sequester carbon (C) in the soil. Sugarcane is one of the most widely used bioenergy crops, yet there remain unknowns about how it impacts soil C dynamics. In addition, Oilcane, a genetically modified version of Sugarcane has been produced to accumulate more energy-dense oils and less soluble lignin, which enhances conversion efficiency but may also impact soil C cycling. Thus, our objectives were to examine the impact of Sugarcane litter decomposition on soil C formation and losses and determine if the genetic modifications to produce Oilcane alter these dynamics. To do this, we incubated bagasse (processed stem litter) and leaf litter from Sugarcane and Oilcane in microcosms with forest soil for 11 weeks. We used differences in natural abundance δ 13 C between C 3 forest soil and C 4 litter to trace the fate of the litter into respiratory losses as well as stable and unstable soil C pools. Our results show that genetic modifications to Oilcane did not substantially alter soil C dynamics. Sugarcane and Oilcane litter both led to net soil C gains dominated by an accumulation of the added litter as unstable, particulate organic C (POC). Oilcane litter led to small but significantly greater net soil C gains than Sugarcane litter due to greater POC formation, but the formation of stable, mineral associated organic matter (MAOC) did not differ between crop types. Sugarcane and Oilcane had opposing effects on tissue type where Sugarcane bagasse formed more MAOC, while Oilcane leaves preferentially remained as POC which may have important management implications. These results suggest that genetic modifications to Sugarcane will not significantly impact soil C dynamics; however, this may not be universal to other crops particularly if modifications lead to greater differences in litter chemistry.

09 BIOMASS FUELS↗

Opportunistic Short‐Term Water Uptake Dynamics by Subalpine Trees Observed via In Situ Water Isotope Measurements

Abstract Variations in tree water sources are important to understand in semi‐arid ecosystems because climatic shifts towards lower snowpack and increased drought affect water availability in subalpine forests of the western US. Here, we use daily in situ measurements of stable isotopes ( 2 H & 18 O) in soil and tree stem water, soil matric potential and sap flow to study tree water uptake dynamics. We instrumented three soil profiles down to 90 cm, as well as three aspen and engelmann spruce trees near Gothic, Colorado, in the East River watershed. We observed the fate of natural isotopic variations in rainfall, soil, and plants from June to October 2022, and in August 2023 we conducted a 2 H labeled irrigation experiment. Our observations showed that all studied aspen trees compensated for water scarcity in the shallow soil by shifting the dominant water source at 60(±20) cm to ⅔ of uptake from 90 cm within a few days of a dry period. Both species relied on snowmelt stored in the subsoil to sustain transpiration. Intense rainfall caused the plant water uptake to shift partially to top soil layers within 2 days. Spruce transpiration was lower and relied more on snowmelt, because rainfall infiltration was low in the spruce stand due to high canopy interception. Our findings highlight the important role of snowmelt stored in the deep soil layers for subalpine forest drought response and the dominant fate of monsoonal rainfall to become transpiration rather than recharging groundwater and streams in the Upper Colorado River. Plain Language Summary There is a need to understand how trees in mountainous regions respond to dry conditions that lead to water scarcity, because climate projections suggest that such conditions will become more frequent in the future. Here we present a novel data set of measurements of daily stable isotopes of water across soil profiles and in tree stems of aspen and spruce. Our data show that when the upper soil dried out, aspen trees shifted to using water from deeper layers (beneath 60 cm) to keep transpiring. For spruce trees the uptake pattern is less clear, but both types of trees mainly used snowmelt stored in the deeper soil layers to survive the dry summer. After heavy rain, aspen and spruce trees switched to using water from the top 20 cm of soil. However, for spruce, only some rain reached the soil because the dense tree canopy intercepted it, so spruce trees stayed more dependent on snowmelt and used less water overall. This study shows how important deep snowmelt water is for helping forests survive dry periods and suggests that most summer rain is quickly used by trees rather than replenishing streams and groundwater in the headwaters of the Colorado River. Key Points Tree water resources changed within a few days from snow dominated to higher share of rainfall as soils wetted up after a dry period Compensatory plant water uptake by aspen from the deep layer (90 cm), while uptake from soil depths that became drier (60 cm) declined Strong differences between water sources and availability beneath aspen and spruce, respectively

Sprenger, Matthias↗

Characterization of Oil and Gas Drill Cuttings for Critical Mineral Recovery and Reuse Potential as Soil Supplements

Expansion of unconventional oil and natural gas production over the last decade in the United States has resulted in record production of natural gas and oil in 2024. Millions of tons of drill cuttings generated from shale gas development are currently disposed of in landfills. Converting these cuttings into value product(s) such as critical minerals (CMs) and soil supplements, has the potential of reducing environmental impact of fossil fuel exploration. In this study we characterize the CM distribution and extractability from collected drill cuttings and core samples from major U.S. shale formations. A four-step sequential extraction, consisting of a sonicated soap step, sonicated EDTA step , mildly reducing agent, and a oxidizing agent, was developed to simultaneously extract CMs and convert the drill cuttings into soil supplements. Viability of converted drill cuttings as soil supplement was determined with a seedling growth experiment. Results show high concentrations of vanadium (V) (up to 1575 ppm, barite (up to 5 wt. %), and rare earth elements (REE) concentrations (up to 253 ppm). High extractability of selected critical minerals such as REE (19-50%) and Ba (10-58%) show promising results. Preliminary results show seedling growth in a mixture of converted drill cuttings with soil. These results show the potential for recovery of CMs from drill cuttings as an alternative domestic and the reduction of the environmental impact of fossil fuel production.

Barczok, Maximilian↗