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1,659 records · Page 10Linked to original sources
USGS2026

Seismic characteristics of the April 2024 eruption of Ruang Volcano, North Sulawesi, Indonesia

The two most recent eruptions of Ruang volcano, in 2002 and 2024, have been large (VEI 4) with very short precursory periods, 3 and 6 days, respectively. Background seismicity at Ruang volcano is generally low with 0–2 volcano-tectonic (VT) earthquakes per day. The 2024 eruptions were preceded by a notable increase in VT earthquakes from 11 to 15 April with a rapid escalation from 16 to 17 April in the form of increased VT swarms, and the appearance of low frequency earthquakes and short bursts of VT drumbeats shortly before the eruption. Similar VT seismic unrest was recorded in March 2015, May 2016, and April 2022, although none of these episodes culminated in an eruption. A comparison of seismic energy release between April 2022 and April 2024 shows distinct differences. In 2024, cumulative seismic energy reached its peak within 5 days, just before the onset of eruption on 17 April. In contrast, during the 2022-episode, energy release followed a more gradual increase over 8 days peaking on 16 April, then declining gradually without leading to eruption. Notably, low frequency (LF) and drumbeat earthquakes were absent in non-eruptive unrest episodes. The transition to proximal LFs in 2024 likely signals pressure fluctuations, intensified magma degassing, and conduit formation, acting as an important precursor to eruption. Additionally, the occurrence of short bursts of drumbeat seismicity likely reflects the onset of the shallow magma ascent and was an important short-term precursor to the eruption. Finally, we examine the potential influence of regional tectonic earthquakes on the escalation of precursory unrest in 2024.

North Sulawesi, Ruang volcano↗
USGS2025

Meet the people where they are: Assessing user needs for aftershock forecast products in El Salvador, Mexico and the United States

Aftershock forecasts can help communities reduce their seismic risk by conveying how many aftershocks can be expected following a large earthquake, and how the expected number of aftershocks and their corresponding ground shaking evolves over time and space. Prior work finds that graphical forecast products may communicate such information better than only text or numbers. To identify which visual products can serve multiple user groups, we held workshops with members of several professions, including emergency managers, engineers, critical infrastructure operators, public health specialists, science communicators, and more. We conducted these workshops in El Salvador, Mexico and the United States to understand which forecast products may be effective across different countries. In these workshops, users performed small-group activities to elicit the types of aftershock forecast information that would support decisions in their respective roles and how this information would optimally be displayed. Maps of shaking hazards were frequently requested across all professions and countries, even for dissimilar forecast uses. The design of these maps, and other product needs, were differentiated by profession, country and other factors. Other forecast products, including those showing forecasts about the magnitudes and time periods of future aftershocks, also served a variety of users, but for different types of decisions. We found a greater variation in user needs by profession than by country, and that user needs also vary with time, communication channel and other contextual factors. We discuss practical implications for user-centered visual communication of operational aftershock forecasts.

International Journal for Disaster Risk Reduction↗
USGS2025

Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems

Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWS) have relied solely on rainfall event information. In previous decades, several studies demonstrated the value of integrating proxies for subsurface hydrologic information to improve rainfall-based forecasting of shallow landslides. More recently, broader access to commercial sensors and telemetry for real-time data transmission has invigorated new research into hydrometeorological thresholds for LEWS. Given the increasing number of studies across the globe using hydrologic monitoring, mathematical modeling, or both in combination, it is now possible to make some insights into the advantages versus limitations of this approach. The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms, through the ability to characterize infiltration during, as well as the drainage and drying processes between major storm events. There are also some areas for caution surrounding the long-term sustainability of subsurface monitoring in landslide-prone terrain, as well as unresolved questions in hillslope hydrologic modeling, which relies heavily on the assumptions of diffuse flow and vertical infiltration but often ignores preferential flow and lateral drainage. Here, we share a collective perspective based on our previous collaborative work across Europe, North America, Africa, and Asia to discuss these challenges and provide some guidelines for integrating knowledge of hydrology and climate into the next generation of LEWS. We propose that the greatest opportunity for improvement is through a measure-and-model approach to develop an understanding of landslide hydro-climatology that accounts for local controls on subsurface storage dynamics. Additionally, new efforts focused on the subsurface hydrology are complementary to existing rainfall-based methods, so leveraging these with near-term precipitation forecasts is a priority for increasing lead times.

Alaska↗
USGS2025

ARCHI: A new R package for automated imputation of regionally correlated hydrologic records

Missing data in hydrological records can limit resource assessment, process understanding, and predictive modeling. Here, we present ARCHI (Automated Regional Correlation Analysis for Hydrologic Record Imputation), a new, open-source software package in R designed to aggregate, impute, cluster, and visualize regionally correlated hydrologic records. ARCHI imputes missing data in “target” records by linear regression using more complete “reference” records as predictors. Automated imputation is implemented using a novel, iterative algorithm that allows each site to be considered a target or reference for regression, growing the pool of complete references with each imputed record until viable gap-filling ceases. Users can limit artifacts from spurious correlations by specifying model-acceptance criteria and applying geospatial, correlation, and group-based filters to control reference selection. ARCHI provides additional functions for visualizing results, clustering records with similar correlation structures, evaluating holdout data, and interactive parameterization with an accessible and intuitive graphical user interface (GUI). This methods brief provides an overview of the ARCHI package, modeling guidelines, and benchmarking on two regional groundwater-level datasets from the Central Valley, CA and Long Island, NY. We evaluate ARCHI alongside widely used multivariate imputation software to highlight and contextualize its computational efficiency, imputation accuracy, and model transparency when applied to large, groundwater-level datasets.

California, New York↗
USGS2026

Re-examining the growing degree day minimum for grass carp spawning initiation in Lake Erie: Have we missed the mark?

Understanding the timing of life history processes of invasive fish species, such as adult aggregations during spawning, allows natural resource managers to optimize targeted population control efforts. Temperature-based estimates of the timing of spawning initiation for grass carp ( Ctenopharyngodon idella ) exist from its native range, but have not previously been developed for grass carp reproduction in its invaded range in the Laurentian Great Lakes of North America. We accounted for differences among methods across studies and calculated cumulative growing degree days (GDD) for the dates of grass carp egg capture in Lake Erie tributaries (Sandusky, Maumee, and Huron rivers) during 2015–2024 and compared these values to the existing GDD base 15°C requirement estimate from the native range (633 GDD–15°C). The earliest egg detection in Lake Erie (Sandusky River) was 19 GDD–15°C or 361 GDD–5°C (latest egg detection was 2285 GDD–5°C from the Sandusky River), indicating that spawning was initiated up to 25 days earlier than would be predicted by the native range GDD. Moreover, spawning in Lake Erie tributaries occurred earlier than predicted for 58% of spawning events examined based on the native range GDD. The GDD values for spawning initiation in Lake Erie tributaries can be used to refine the timing of control efforts targeting pre-spawn and spawning adult fish, inform the timing of egg sampling, and provide linkages to existing early life stage models to infer the length of the growing season available for age-0 fish to reassess tributary suitability.

Lake Erie, Maumee, River, Sandusky river↗
USGS2025

Gas emissions from the Sulphur Bank Mercury Mine hydrothermal system, Clear Lake volcanic field, California

The Sulphur Bank Mercury Mine (SBMM) hydrothermal system offers insights into active degassing processes in the Clear Lake volcanic field (CLVF), a high-threat region based on its record of Holocene eruptions and proximity to populated areas. Here we present chemical and isotopic analyses of gas samples collected between 2015 and 2023, along with the first comprehensive CO 2 flux survey of the SBMM area conducted in 2023. Sampled gases are CO 2 - and CH 4 -rich (≥84 and 6 mol% in dry gas, respectively) with high mantle-derived helium contributions ( 3 He/ 4 He = 6.54–7.86 R C /R A ). Carbon isotopic compositions of CO 2 (δ 13 C = −10.0 to −9.5 ‰) and CH 4 (δ 13 C = −35.8 ‰) indicate mixed sources, with significant contributions from metamorphism of organic-rich Franciscan Complex rocks hosting the hydrothermal system. Modeling of gas compositions shows that scrubbing by interaction with air-saturated groundwater strongly influences observed compositional variability. From our CO₂ flux measurements, we estimate the deeply derived CO 2 emission rate from the SBMM hydrothermal area (0.2 km 2 ) at 240 t d −1 , comparable to many quiescently degassing volcanoes worldwide. We also provide a first-order estimate of CH 4 emissions at approximately 0.5 t d −1 . Our findings establish crucial baseline data for future volcanic monitoring efforts, enhancing detection capabilities for potential changes in this active hydrothermal system. This work contributes to the broader understanding of volatile contributions from volcanic and metamorphic sources to the global carbon budget, while highlighting the strong influence of bedrock geology on gas compositions in the CLVF.

California↗
USGS2025

Over, under, and through: Hydrologic connectivity and the future of coastal landscape salinization

Seawater intrusion (SWI) affects coastal landscapes worldwide. Here we describe the hydrologic pathways through which SWI occurs - over land via storm surge or tidal flooding, under land via groundwater transport, and through watersheds via natural and artificial surface water channels—and how human modifications to those pathways alter patterns of SWI. We present an approach to advance understanding of spatiotemporal patterns of salinization that integrates these hydrologic pathways, their interactions, and how humans modify them. We use examples across the East Coast of the United States that exemplify mechanisms of salinization that have been reported around the planet to illustrate how hydrologic connectivity and human modifications alter patterns of SWI. Finally, we suggest a path for advancing SWI science that includes (a) deploying standardized and well-distributed sensor networks at local to global scales that intentionally track SWI fronts, (b) employing remote sensing and geospatial imaging techniques targeted at integrating above and belowground patterns of SWI, and (c) continuing to develop data analysis and model-data fusion techniques to measure the extent, understand the effects, and predict the future of coastal salinization.

Water Resources Research↗
USGS2025

VIPER site analysis

We needed to evaluate available orbital data of NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) mission area in order to derive a variety of maps to help the science team identify scientifically interesting places for the rover to visit and to provide scientific context for our mission. Some of these maps also fulfilled engineering and mission design needs to enable safe and efficient landing and roving. We incorporated data from the Lunar Reconnaissance Orbiter Camera, the Lunar Orbital Laser Altimeter, the Mini-RF instrument, the Chandrayaan-2 Orbital High Resolution Camera, the Korean Pathfinder Lunar Orbiter’s Shadowcam, the Kaguya Spectral Profiler and Multiband Imager, and the Chandrayaan-1 Moon Mineralogy Mapper. We used a variety of techniques to build these maps, including stereogrammetry, shape-from-shading, ice stability depth and surface temperature calculations, and the horizon method for solar illumination and direct-to-Earth communications maps. Altogether, these maps allowed us to survey for boulders, evaluate features in permanently shadowed regions that VIPER might explore, provide mineralogic context for what VIPER’s instruments may learn, estimate the ages and radar properties of craters in the VIPER mission area, and evaluate the potential for gravity traverses with the rover. These data and techniques provided a rich set of information from which both the VIPER science team and engineering teams were able to draw in order to plan a safe landing and to plan a VIPER surface mission that will be both scientifically valuable and robust from an operational perspective.

The Planetary Science Journal↗
USGS2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

Comptes Rendus. Géoscience↗
USGS1998

Continuous hydrologic simulation of runoff for the Middle Fork and South Fork of the Beargrass Creek basin in Jefferson County, Kentucky

The Hydrological Simulation Pro-gram-FORTRAN (HSPF) was applied to an urban drainage basin in Jefferson County, Ky to integrate the large amounts of information being collected on water quantity and quality into an analytical framework that could be used as a management and planning tool. Hydrologic response units were developed using geographic data and a K-means analysis to characterize important hydrologic and physical factors in the basin. The Hydrological Simulation Program FORTRAN Expert System (HSPEXP) was used to calibrate the model parameters for the Middle Fork Beargrass Creek Basin for 3 years (June 1, 1991, to May 31, 1994) of 5-minute streamflow and precipitation time series, and 3 years of hourly pan-evaporation time series. The calibrated model parameters were applied to the South Fork Beargrass Creek Basin for confirmation. The model confirmation results indicated that the model simulated the system within acceptable tolerances. The coefficient of determination and coefficient of model-fit efficiency between simulated and observed daily flows were 0.91 and 0.82, respectively, for model calibration and 0.88 and 0.77, respectively, for model confirmation. The model is most sensitive to estimates of the area of effective impervious land in the basin; the spatial distribution of rain-fall; and the lower-zone evapotranspiration, lower-zone nominal storage, and infiltration-capacity parameters during recession and low-flow periods. The error contribution from these sources varies with season and antecedent conditions.

Kentucky↗
USGS2024

Detrital zircons and the magmatic history of Viti Levu, Fiji

We integrate the existing detrital zircon data from multiple modern river sediment samples on Viti Levu, Fiji, with the most current available geological and topographic mapping of the respective river drainage basins to compare detrital populations with potential bedrock sources. The temporal and spatial variations in zircon geochemistry supplement what is known from igneous rocks and confirm the petrological differences between plutonic and volcanic rocks from the Eocene to early Oligocene (Yavuna age, >30 Ma), middle Oligocene to middle Miocene (Wainimala age, 30–12.5 Ma), late Miocene (Colo age, 12.5–6.5 Ma) and latest Miocene (Namosi age, 6.5–5 Ma). The >30 Ma Yavuna-age zircons are restricted to areas that drain the previously mapped Yavuna Group. The 30–12.5 Ma zircons are found across central Viti Levu from west to east, and the 30–15 Ma zircons have distinctively low U/Yb and high Dy/Yb ratios. They are the best radiometric evidence of widespread early to middle Miocene arc magmatism in Fiji that was relatively U-poor. Peak deconvolution of the Colo age zircons from individual basins suggests the following ages for undated or poorly dated plutons from central Viti Levu. The large Mavuvu pluton is probably composed of multiple intrusions in the 12–10 Ma range, the Waiqa pluton is probably ca 10 Ma, and the Noikoro pluton is probably ca 9 Ma. There are zircons from unknown plutonic or volcanic sources between 8 and 7 Ma in western Viti Levu that have distinct Eu/Eu* ratios. We attribute the highest U/Yb ratios in some Colo age zircons to crustal anatexis. Namosi-age zircons are abundant in the Medrausucu Group and can be found scattered across Viti Levu.

Viti Levu↗
USGS2025

Identification of representative earthquakes for probabilistic tsunami hazard analysis (PTHA) using earthquake rupture forecasts and machine learning

As probabilistic tsunami hazard analysis (PTHA) focuses more on assessments for localized, populous regions, techniques are needed to identify a subsample of representative earthquake ruptures to make the computational requirements for producing high-resolution hazard maps tractable. Moreover, the greatest epistemic uncertainty in seismic PTHA is related to source characterization, which is often poorly defined and subjective. We address these two salient issues by applying streamlined earthquake rupture forecasts (ERFs), based on combinatorial optimization methods, to an unsupervised machine learning workflow for identifying representative ruptures. ERFs determine the optimal distribution of a millennia-scale sample of earthquakes by inverting the observed slip rate on major faults. We use two previously developed combinatorial optimization ERFs, integer programming and greedy sequential, to produce the optimal location of ruptures with seismic moments sampled from a regional Gutenberg–Richter magnitude–frequency distribution. These ruptures in turn are used to calculate peak nearshore tsunami amplitude, using computationally efficient tsunami Green's functions. An unsupervised machine learning workflow is then used to identify a small subsample of the earthquakes input to ERFs for onshore PTHA analysis. We eliminate epistemic uncertainty related to source distribution under traditional PTHA analysis; in its place, a quantifiable, less subjective and generally smaller uncertainty related to the input to ERFs is included. The Nankai subduction zone is used as a test case, where previous ERFs have been conducted. Results indicate that the locations of representative earthquakes are sensitive to choice of magnitude–area relation and to whether a minimum cumulative stress objective is imposed on the fault. In general, incorporating ERFs into PTHA provide a physically self-consistent method to incorporate fault slip information in determining representative earthquakes for onshore PTHA, eliminating a major source of epistemic uncertainty.

Nankai subduction zone↗
USGS2026

Assessment of extreme subsurface hydrologic conditions captured during atmospheric river storms in the San Francisco Bay area (California, USA) with applications to shallow landslide early warning

An increase in soil pore water pressure is the typical trigger for the majority of landslides caused by rainfall. Atmospheric river storms, common to the west coast of North America during the winter season, can deliver landslide triggering rainfall resulting in severe impacts to coastal communities. Using a network of hydrologic monitoring stations situated within landslide-prone terrain in the San Francisco Bay area of California (USA), we assess the meteorologic conditions and resulting hydrologic and landslide response resulting from eight consecutive storm events that caused thousands of shallow landslides during the winter of 2022–2023. We find disparate hydrological responses and resultant degrees of observed landsliding ranging from < 1 landslide/km2 to 18 landslides/km2 at the monitoring sites that reflect the interplay and differences between rainfall delivery, subsurface hydrological characteristics, and geotechnical properties at each site. Antecedent soil moisture from both early season rainfall and the first storm in the sequence played a critical role in setting up some hillslopes for failure. Subsequent storms then generated elevated pore water pressures for several hours with associated landsliding. However, we find that the occurrence of widespread landsliding required not only sufficient pore water pressure magnitude in susceptible hillslopes, but also full and prolonged effective soil saturation throughout hillslope profiles. Landslides may still occur at lower values and durations of effective saturation but are likely to be less extensive regionally. We present these findings within the context of research directions and improvements to landslide early warning systems first suggested by researchers 40 years ago.

California↗
USGS2024

Thermo-hydrologic processes governing supra-permafrost talik dynamics in discontinuous permafrost near Umiujaq (Québec, Canada)

Widespread supra-permafrost talik formation is currently recognized as a critical mechanism that could accelerate permafrost thaw in the Arctic (e.g., Connon et al. 2018; Farquharson et al. 2022). However, the trajectory of permafrost dynamics following talik formation may prove difficult to predict. Physically-based cryohydrogeologic models provide a powerful tool for understanding processes and factors controlling talik dynamics and, ultimately, how permafrost will respond to climate change. Such models are typically used to represent multiple non-linear processes relevant for groundwater systems in cold regions, such as coupled heat and groundwater movement, including freeze-thaw dynamics and the effects on the surface energy balance and the subsurface thermal and hydraulic properties (Lamontagne-Hallé et al. 2020). Though cryohydrogeologic modeling advances have been made in simulating talik dynamics, few applications have been tested against robust long-term hydrometeorological and subsurface observations.

Quebec↗
USGS2026

Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)

Large, rapid landslides are a global hazard that can occur in remote, mountainous areas. Eyewitness reports of landslides and satellite imagery can often be limited or delayed, particularly during inclement weather. However, landslide-generated seismic and infrasound (low-frequency atmospheric sound) waves can be remotely detected in near real-time. This information can significantly expedite characterization and possible landslide response activities. Here, we highlight these capabilities using a > 4 million m³ ice–rock avalanche in Denali National Park and Preserve (Alaska). This event was detected via a landslide-specific seismic location and volume estimation algorithm deployed in Alaska, and — notably — by standard earthquake monitoring systems. Following rapid detection of this event, we combined its seismic and infrasound dataset with optical, synthetic aperture radar, and oblique aerial imagery, multitemporal digital elevation models, and a numerical flow model to reconstruct its failure timeline and dynamics. We apply array processing to infrasound signals traveling > 250 km and find that two precursory events occurred minutes prior to the main failure. We use long-period seismic signals to infer the force exerted by the landslide on the Earth and constrain the rheological parameters of our numerical flow simulation with this result and deposit morphology. The main failure produced a steeply-dipping impulsive initial downward force and reached speeds exceeding 60 m/s. This impulsive force generated relatively strong seismic body waves, which contributed to the earthquake system detection. This large, remote Alaska landslide underscores the key value of seismic and infrasound analysis for rapid landslide assessment and motivates efforts to further operationalize these approaches.

Alaska↗
USGS1976

Effect of deicing chemicals on the hydrologic environment in Massachusetts; evaluation of surface-water data collection

The objective of this study is to develop predictive relationships that can be used to describe the impact of highway deicing salts on the hydrologic environment. A method, presented in an earlier report, for estimating yearly mean chloride concentrations from estimated or actual runoff and salt-application data was applied to the period 1971 through1974 and the results compared with yearly mean chloride concentrations computed from records of specific conductance. Estimates were found to be from minus 63 percent to plus 56 percent in error when the error was expressed as the difference between estimated and computed values as a percentage of the computed values. Chloride concentrations used in this study are computed from specific conductance/chloride concentration relationships and records of specific conductance. Preliminary results from graphic analyses and least-squares regression analysis show that relationships between measured values of specific conductance and chloride concentration have correlation coefficients ranging from 0.30 to 0.97. Analysis of streamflow for all major dissolved constituents is recommended with the purpose of attempting to describe the variations in the specific conductance/chloride concentration relationships.

Massachusetts↗
USGS2026

Upper Triassic igneous rocks of the southern Kenai Peninsula, Alaska – Prelude to Early Jurassic subduction along the western Wrangellia composite terrane margin

New U–Pb zircon geochronology identifies a latest Triassic (ca 214–201 Ma) igneous suite of tuff, hypabyssal dikes, and a pluton on the southern Kenai Peninsula, Alaska. The igneous suite was emplaced within Upper Triassic sedimentary rocks along the southern margin of Western Wrangellia, the western-most fragment of the Wrangellia composite terrane. The igneous rocks range from mafic (50.6% SiO 2 ) to felsic (78.3% SiO 2 ), characteristically have less than 1.55% K 2 O, and generally have low trace element abundances. The tonalitic and trondhjemitic magmas were largely sourced in mafic-rich lower crust and incompletely assimilated quartz and other mineral xenocrysts are common. Fractionation involving plagioclase and amphibole is indicated for some magmas and composite intrusions and igneous xenoliths indicate magma mixing was possible. Paleozoic and Precambrian inherited zircons and initial 87 Sr/ 86 Sr (0.704103–0.705609) and 143 Nd/ 144 Nd (0.512396–0.512777) ratios indicate that the Western Wrangellia crustal sources are heterogeneous and contain sialic components. The latest Triassic magmatism reflects processes that preceded Early Jurassic subduction along the Wrangellia composite terrane and Pacific Ocean plate boundary. These processes involved heating and melting of mantle lithosphere and lower crust as mantle instabilities accompanied the breaking of the plate boundary linkages. The Late Triassic transition to subduction along the Wrangellia composite terrane margin coincided with the transition to subduction cessation in the Late Triassic arcs of the western Intermontane terranes of Canada. The shift to subduction along the outboard Wrangellia composite terrane margin marks the beginning of the Pacific Ocean–Cordillera plate interactions that came to dominate the tectonic evolution of the northern Cordillera from the Early Jurassic to today.

Alaska↗
USGS2026

Deep subsurface organic-rich shale supports abundant, diverse, and novel fungi

As Earth’s principal reservoir of organic carbon and microbial biomass, the deep subsurface hosts microorganisms capable of mobilizing this once-sequestered carbon. Contrary to standard assumptions of eukaryotic scarcity, this study documents abundant fungal communities, ranging from 4.2 × 10 3 to 6.8 × 10 3 fungal cells mL −1 , across a methane-producing organic-rich shale 247–556 meters below the surface. Although fungal:bacterial cell ratios ranged from 1:7028 to 1:713, application of biomass conversion factors developed for oceanic systems yielded a median fungal:bacterial biomass ratio of 1:4.7. 16S rRNA gene amplicons revealed bacterial and archaeal communities mirroring those found in well-characterized extremophilic, carbon-degrading environments, while sequencing of 18S rRNA gene and ITS rRNA spacer amplicons collectively identified a eukaryotic hotspot with 689 fungal OTUs across six phyla. The dominant fungal classes, Agaricomycetes and Dothideomycetes, are well-established degraders of recalcitrant carbon compounds at the surface, suggesting they may similarly contribute to organic matter degradation and ecosystem maintenance in the subsurface. Cultivation and isolation efforts yielded 205 fungal strains, including 13 candidate novel taxa, underscoring the deep subsurface as an underexplored eukaryotic habitat. Stable carbon isotopes indicate methane is predominantly generated via microbial conversion of the fossil carbon, while water isotopes suggest in situ geochemical conditions have been relatively stable since the Late Pleistocene, with subglacial recharge as a plausible mechanism for microbial introduction. Collectively, these findings suggest that fungi are underrecognized contributors to organic matter transformation and functional diversity in the deep biosphere, revealing a critical gap in our understanding of deep subsurface ecosystem processes.

Indiana, Michigan, Ohio↗