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USGS2007

Divisions of geologic time—Major chronostratigraphic and geochronologic units

Effective communication in the geosciences requires consistent uses of stratigraphic nomenclature, especially divisions of geologic time. A geologic time scale is composed of standard stratigraphic divisions based on rock sequences and calibrated in years. Over the years, the development of new dating methods and refinement of previous ones have stimulated revisions to geologic time scales. Since the mid-1990s, geologists from the U.S. Geological Survey (USGS), State geological surveys, academia, and other organizations have sought a consistent time scale to be used in communicating ages of geologic units in the United States. Many international debates have occurred over names and boundaries of units, and various time scales have been used by the geoscience community. For consistency purposes, the USGS Geologic Names Committee and the Association of American State Geologists developed Divisions of Geologic Time .

Fact Sheet↗
USGS2026

Top-down targeted network analysis of critical mineral commodities applied to international geochemistry database

The global demand for critical mineral commodities is rapidly increasing, making domestic production an important factor in supporting the economy and national security. Large scale, publicly available geochemical databases allow for the application of data informatics methods to interrogate critical mineral commodities data for correlations in deposit formation and distribution, particularly for identifying enrichment of multiple critical mineral commodities at the same deposit. In this study, we applied network analysis to the Critical Minerals Mapping Initiative (CMMI) ore geochemistry (Critical Minerals in Ores, CMiO) database to identify the high concentration (defined as 10× bulk crustal abundance) co-occurrence of different critical mineral commodities across a mineral system hierarchy from deposit environments to individual deposits. Identifying patterns or unique outliers in enrichment in network communities will allow for the location of secondary critical mineral commodity resources from under-utilized deposits. We find trends in the enrichment of critical mineral commodities in network-communities between the elements praseodymium (Pr), neodymium (Nd), terbium (Tb), and dysprosium (Dy) across multiple CMiO database deposit environments and groups down to specific deposit types and sites. A separate trend in network community deposition is observed as well between iridium (Ir) and platinum (Pt) in deposit environments, groups, types, and sites. Network analysis focused on critical minerals in magmatic-hydrothermal deposits identified multiple deposit sites from different deposit types within the CMiO database with concentrations of Dy, Nd, Tb, Pr, Ir, and Pt that are at least ten times greater than the crustal average. This approach can be applied to any target element(s) or deposit(s) of interest, allowing broad investigation of co-enriched critical mineral commodities.

Journal of Geochemical Exploration↗
USGS2025

Impact of gas/liquid phase change of CO2 during injection for sequestration

CO 2 sequestration in deep saline formations is an effective and important process to control the rapid rise in CO 2 emissions. The process of injecting CO 2 requires reliable predictions of the stress in the formation and the fluid pressure distributions – particularly since monitoring of the CO 2 migration is difficult – to mitigate leakage, prevent induced seismicity, and analyze wellbore stability. A key aspect of CO 2 is the gas–liquid phase transition at the temperatures and pressures of relevance to leakage and sequestration, which has been recognized as being critical for accurate predictions but has been challenging to model without ad hoc empiricisms. This paper presents a robust multiphase thermodynamics-based poromechanics model to capture the complex phase transition behavior of CO 2 and predict the stress and pressure distribution under super- and sub- critical conditions during the injection process. A finite element implementation of the model is applied to analyze the behavior of a multiphase porous system with CO 2 as it displaces the fluid brine phase. We find that if CO 2 undergoes a phase transition in the geologic reservoir, the spatial variation of the density is significantly affected, and the migration mobility of CO 2 decreases in the reservoir. A key feature of our approach is that we do not a priori assume the location of the CO 2 gas/liquid interface – or even if it occurs at all – but rather, this is a prediction of the model, along with the spatial variation of the phase of CO 2 and the change of the saturation profile due to the phase change.

Journal of the Mechanics and Physics of Solids↗
USGS2025

Land application of drill waste: A scope analysis

Drilling fluid waste land application, a process where drilling wastes are spread and tilled into the land surface, has become common in some petroleum-producing states, however, the potential benefits and risks of this practice are not well studied. Drilling fluids can be water- or oil-based and can have high concentrations of total soluble salts and total petroleum hydrocarbons. Comprehensive chemical characterization of these fluids is not well documented in the literature, and the extent of land application is largely unknown. We hypothesized that the land application of drill waste would fluctuate over time due to economic factors. To begin to understand the extent of historical and potential future land application, we analyzed data from over 5,800 drilling fluid land application permits collected by the Oklahoma Corporation Commission for years 2000, 2005, 2010, and 2015–2020. During the years studied, drilling fluid wastes were applied to more than 250,000 acres in Oklahoma, with over 54,000 thousand barrels (Mbbl) of liquids and nearly 21,000 Mbbl of solids applied. Land application is widespread (occurring in 59/77 counties), however recent drilling activity, land availability, and the economics of transportation have created conditions favorable for land application specifically in the Anadarko Basin. Land application can co-occur with sensitive areas, such as important groundwater and surface-water drinking sources and agricultural fields used for subsistence or feed crop production. Our approach for quantifying the extent of land application, along with further chemical characterization studies, can aid operators and land managers who are considering this practice in assessing the associated benefits and risks.

Oklahoma↗
USGS2026

Satellite tracking of Galapagos Petrel Pterodroma phaeopygia reveals distribution and movements during chick rearing

We tracked 19 adult Galapagos Petrels Pterodroma phaeopygia during the chick-rearing seasons in 2009 and 2010 (Santa Cruz Island [ n = 16] and Floreana Island [ n = 3]) in the Galápagos Islands, Ecuador. Eight petrels performed 27 complete foraging trips lasting 0.6 to 18.8 days. Short trips (3.2 ± 2.1 days; 785 km; max displacement 671 km) and long trips (10.8 ± 3.9 days; 2,856 km; max displacement 1,034 km) resulted in concentrated use of waters off southern and western Isabela Island and within the Galápagos Marine Reserve (GMR). Less concentrated time extended farther southwest and eastward, in that case toward mainland Ecuador. Total distance covered among all completed trips, independent of duration, was strongly correlated with trip duration ( R ² = 0.92), indicating a strategy favoring active searching and foraging over commuting. Petrels ranged across Ecuador's exclusive economic zone (EEZ), as well as other countries' (Colombia, Costa Rica, Perú), and waters beyond; they spent 46%, 27%, and 34% of their time in the GMR during short, long, and apparent (incomplete) trips, respectively. However, overlap with EEZs or marine protected areas (MPAs) does not necessarily confer protection, because commercial tuna fishing, including legal fishing historically permitted inside the GMR, occurs within these waters. Including all complete and incomplete trips, petrels spent 37% of their time in high-seas waters without formal protection, outside both MPAs and EEZs. While some hot spots overlapped Galápagos MPAs, the far-ranging nature of chick-provisioning petrels underscores the importance for this species of also having coordinated, multinational protection of the high seas.

Floreana Island, Galápagos Islands, Santa Cruz Isl↗
USGS2026

Competition between invasive round goby and native slimy sculpin in a coldwater laboratory setting

Slimy sculpin ( Cottus cognatus ) abundance has substantially declined in many regions of the Laurentian Great Lakes coincident with the arrival and range expansions of invasive round goby ( Neogobius melanostomus ). Previous studies have shown that round goby can outcompete native mottled sculpin ( C. bairdii ) for shelter and negatively affect native spoonhead sculpin ( C. ricei ) growth, but direct behavioral interactions of slimy sculpin and round goby have not been observed. We conducted a laboratory experiment in which a pair of slimy sculpin were placed in an aquarium that contained an artificial spawning shelter and one round goby (treatment, n = 10) or no other fish (control, n = 10) for at least 30 days at temperatures reflective of their potential offshore overlap. We measured slimy sculpin egg deposition, aggressive interactions, artificial shelter occupancy, growth, and survival. Slimy sculpin were less likely to occupy shelters and experienced increased intraspecific competition when a round goby was present. In contrast, round goby rarely chased slimy sculpin, slimy sculpin were more likely to chase round goby, and slimy sculpin growth, egg deposition, and survival were not significantly different between groups. Differences in density between treatments and the relative size of fish could confound our observations. However, the dominant slimy sculpin occupied the shelter at similar rates between experimental groups if the round goby was smaller. Our results indicate that larger round goby overlapping with slimy sculpin could affect slimy sculpin shelter and space use, but the Great Lakes environment may create more stress for slimy sculpin than we observed.

Lake Michigan, Lake Superior↗
USGS2025

Collaborative drought science planning in the Colorado River Basin

The U.S. Geological Survey (USGS) is using collaborative, interdisciplinary planning to develop data and tools needed to optimize the management of water resources and land use by resource management agencies during an ongoing, multidecadal drought in the Colorado River Basin. The USGS Actionable and Strategic Integrated Science and Technology team works to build relationships with resource management agencies and other stakeholders who can benefit from the use of USGS data and products. In 2023, the Actionable and Strategic Integrated Science and Technology team hosted a series of collaborative workshops to bring together representatives of resource management agencies and other stakeholders (any person or entity with interests in a resource or location) with USGS program managers, scientists, and multidisciplinary subject matter experts to codevelop concepts for interdisciplinary drought science and technology projects to address pressing needs related to drought in the Colorado River Basin. Workshop participants identified current and recent scientific data that could be shared through a centralized online data portal. Workshop participants also identified drought science and technology needs and developed project concepts to address those science needs. Participants categorized project concepts based on their potential to develop short-, mid-, and long-term drought science data and tools, provide for the spatial or temporal expansion of ongoing USGS science projects, and address high-priority science needs. Participants developed nine project concepts: (1) understanding shifting ecohydrologic baselines, (2) San Juan River Basin synthesis, (3) incorporating dynamic land cover into hydrologic models, (4) aridification compared to drought, (5) surface water-groundwater interactions, (6) cascading effects of drought on dust, (7) cascading effects of drought on water availability, (8) cascading effects of drought on socioeconomic factors, and (9) the value of water in the Colorado River Basin. This report provides an overview of the 2023 Codesign Workshop Series, synthesized outcomes from workshop materials and discussions, and science project concepts that emerged from the collaborative meetings that will continue to be refined into science project proposals through codevelopment processes. This report also highlights lessons learned and next steps needed to receive feedback and testing of the USGS Science Collaboration Portal, continue collaboration to develop detailed specifics and steps for short-term wins, develop interdisciplinary project proposals, and implement science planning and studies.

Arizona, California, Colorado, Nevada, New Mexico,↗
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↗
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↗
USGS2026

Distinguishing natural from mining-related metal sources by including streambank groundwater data in a stream mass loading study

Distinguishing stream metal loading caused by mine features from that caused by natural background sources remains challenging, yet this distinction is essential for making effective remedial decisions at many legacy mine sites. We combine a stream tracer injection and synoptic sampling study with data from shallow near-stream groundwater wells to estimate left-bank versus right-bank metal loading contributions at the 100-m spatial scale. The study was performed in the East Mancos River, a mountain headwater stream in Colorado, USA. The dominant source of elevated stream metal concentrations could be either groundwater infiltration through right-bank Doyle Mine waste piles or natural acid rock drainage from hydrothermally altered bedrock located mainly on the left bank. For the five metals of concern (Cu, Al, Zn, Cd, and Mn), we find that 15 % of the load contributed by diffuse groundwater inputs in the section potentially influenced by Doyle mine waste originates from the right bank. This right-bank potential mine contribution equates to only 3 % of the total watershed instream load for these metals. Furthermore, apparent 3 H/ 3 He groundwater ages in segments contributing most of the right-bank metal loading are sufficiently old (9–12 yr) to suggest that infiltration through the waste piles, located only 140–180 m from the stream, is unlikely. Estimated potential Doyle mine loading contributions can therefore be considered maximum values. Study results thus indicate that Doyle mine waste piles are a minor source of metal loading under low-flow conditions, and streambank groundwater data can provide valuable additional information in stream mass loading studies.

Colorado↗
USGS2025

Bayesian mapping of regionally grouped, sparse, univariate earth science data

Some earth science data are naturally grouped by region, and it is often desirable to map these data by region. However, if there are only a few samples within each region, then the map should be smoothed in an appropriate way to mitigate the problems that arise from having only a few samples. A smoothing algorithm based on a Bayesian hierarchical model is developed and presented in this report. This algorithm has several features that make it especially suitable for mapping earth science data: it can account for measurements that are censored, it can process multiple datasets with different measurement errors and different censoring thresholds, and it can calculate the uncertainty in any statistic that is mapped. The algorithm is demonstrated by mapping gold concentrations that are measured in streambed sediments in the Taylor Mountains quadrangle in southwestern Alaska.

Alaska↗
USGS2025

A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed

Seasonal shifts from runoff to groundwater dominance influence daily headwater stream temperatures, especially where local groundwater input is strong. This input buffers temperature during hot periods, supporting cold-water habitats. Recent studies use air–water temperature signal metrics to identify zones of strong stream–groundwater connectivity. While Previous studies used air–water signal ratios as proxies for groundwater influence but were limited to specific sites and periods, without dynamic forecasting. This study is the first to forecast daily A r as a spatiotemporal signal using a Graph Convolutional Network–Long Short-Term Memory (GCN-LSTM) model. The model was trained using hydroclimate data (air temperature, precipitation, shortwave radiation, streamflow) and watershed physical features (e.g., sand content, slope). Results showed high predictive skill, achieving R 2 (NSE, RMSE) of 0.86 (0.73, 0.0004) for one-day-ahead to 0.52 (0.50, 0.0009) for seven-days ahead forecasts. Prior studies often have not explicitly incorporated spatial hydrogeologic drivers, but this model explicitly incorporates them to assess their impact on A r forecasting and stream-groundwater connectivity. Feature analysis identified mean sand, elevation, slope, clay, and TWI as key predictors of A r . Stronger groundwater signals appeared in hillslopes, elevations, and tributaries, highlighting watershed influence on streamflow. However, limitations include reliance on historical air–water temperature patterns for training and limited representation of extreme climate conditions. Despite these limitations, unlike previous studies relying on measured in-situ stream and air temperature, this study forecasts A r directly from climate and physiographic features after training, avoiding in-situ data requirements. Findings aiding predictions of stream ecosystem resilience.

New York↗
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↗
USGS2025

Engineering and risk research—A strategic vision for extending USGS earthquake science to risk assessment and mitigation

As a part of the U.S. Geological Survey (USGS) Natural Hazards Mission Area, the Engineering and Risk Project (ERP) of the Geologic Hazards Science Center conducts civil engineering research to extend natural hazards science to risk assessments. The ERP includes predominantly, but not exclusively, staff funded by the USGS Earthquake Hazards Program. A major focus of the ERP is to deliver actionable information to decisionmakers that helps promote the safety, security, and economic well-being of the Nation. The report discusses briefly the ERP’s evolution and scope, its organization structure, describes key products and deliverables, their efforts to engage with external partners, and its strategy and vision in conducting range of engineering and risk research. The research topics outlined in this report, as developed by the ERP, may be used to facilitate project planning activities during the next 10 years and serve as a longer-term planning resource for the USGS Earthquake Hazards Program and Geologic Hazards Science Center.

Circular↗
USGS2025

U.S. Geological Survey—Department of the Interior, Region 11, Alaska—2023–24 biennial science report

Introduction U.S. Geological Survey (USGS) Mission—The USGS national mission is to monitor, analyze, and predict the current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable information at scales and timeframes relevant to decision makers. Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five interconnected focus areas: Energy and Minerals; Geospatial Mapping; Natural Hazards; Water Quality, Streamflow, and Ice Dynamics; and Ecosystems. The USGS in Alaska consists of approximately 350 scientists and support staff working in 3 Alaska-based science centers. USGS science activities are also initiated by the Cooperative Research Unit and USGS centers outside Alaska. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 900 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.usgs.gov/.

Alaska↗
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↗
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↗