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955 records · Page 26Linked to original sources
USGS2026

Stepovers and beyond: Structural control of The Geysers geothermal system and the broader Clear Lake region

Fault geometry exerts a first-order control on geothermal systems by governing stress localization, fracture development, and permeability, yet in complex fault networks or broader shear zones, the relative influence of individual geometric features is often difficult to resolve. In the northern California Coast Ranges, The Geysers geothermal field is commonly interpreted to occur within a releasing stepover, although no single, clearly defined stepover is identified in published studies. To investigate the structural controls on The Geysers and the broader Clear Lake region, a two-dimensional elastic boundary element model is developed to evaluate spatial patterns of dilational strain associated with progressively more complete fault geometries. Model results show that dilation in the region is not controlled by a single structure but instead reflects the combined effects of multiple interacting fault elements. Three primary controls are identified: (1) opposing bends in the regional strike-slip fault system, including a releasing bend along the Maacama fault; (2) the southern fault tip of the Collayomi fault, which generates a prominent dilational lobe beneath the southern Geysers; and (3) a releasing stepover between the Collayomi fault and the Geyser Peak–Mercuryville–Big Sulphur Creek fault system, inferred to collectively behave as a right-lateral shear zone bounding the western margin of The Geysers. Predicted dilational strain magnitudes are sufficient to localize permeability between faults. These results highlight that incorporating complete fault networks and bedrock geological mapping can enhance geothermal assessments and provide a transferable framework for evaluating structurally controlled permeability in tectonically active regions.

California↗
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↗
USGS1996

Technique for estimating magnitude and frequency of peak flows in Maryland

A convenient and reliable technique for estimating flood magnitudes is required for effective flood-plain management and for the efficient design of bridges, culverts, embankments, and flood-protection structures. Methods are presented for estimating peak-flow magnitudes of selected frequencies, ranging from 2 to 500 years, for all nontidal drainage basins in Maryland. The methods were developed by generalized least-squares regression techniques using data from 219 gaged basins in and near Maryland. The State is divided into five hydrologic regions: the Appalachian Plateaus and Allegheny Ridges region, the Blue Ridge and Great Valley region, the Piedmont region, the Western Coastal Plain region, and the Eastern Coastal Plain region. These regions correspond to the physiographic provinces of the State, with the exceptions that (1) the Coastal Plain Province is divided into two hydrologic regions, and (2) there is no distinct hydrologic region corresponding to the Valley and Ridge Province as it is divided into its constituent Allegheny Ridges and Great Valley subdivisions. Sets of equations for calculating peak discharges based on physical basin characteristics are provided for each of the regions. Based on the peak-flow equations, methods for estimating peak flows are presented for ungaged and gaged streams in Maryland. The methods and equations are supported by generalized least-squares analysis of basin and flood-frequency characteristics data from 219 drainage basins in and near Maryland. estimates for each of the five regions are calculated using combinations of the fol-lowing basin characteristics: drainage area, forest cover, basin relief, carbonate rock coverage, storage, and runoff-curve number. Drainage area contributes to the estimate in all five study regions. Carbonate rock coverage is used only in the Blue Ridge and Great Valley region. Storage and runoff-curve number are used solely in the Eastern Coastal Plain region. All other basin characteristics are used in two or more regions. Standard errors of estimate for the regression equations range from 19 to 31 percent in the Appalachian Plateaus and Allegheny Ridges region, 34 to 47 percent in the Blue Ridge and Great Valley region, 33 to 48 percent in the Piedmont region, 45 to 64 percent in the Western Coastal Plain region, and 36 to 42 percent in the Eastern Coastal Plain region.

Maryland↗
USGS2026

A three-dimensional geologic framework model of the northern Great Plains region of Montana, North Dakota, South Dakota, and Wyoming, USA

This report presents a new three-dimensional geologic framework model (GFM) of the northern Great Plains region, encompassing parts of Montana, North Dakota, South Dakota, and Wyoming. The model provides a regionally consistent, geographic information system (GIS)-ready representation of Phanerozoic sedimentary strata, major fault systems, and Precambrian basement geometry across two sedimentary basins and adjacent uplifts. More than 300,000 geologic and geophysical data inputs were synthesized to model 41 stratigraphic horizons and 47 faults, yielding an internally coherent, sealed-volume interpretation of the subsurface. The modeling workflow developed for this study demonstrates an efficient and scalable approach for constructing basin-to regional-scale GFMs in geologically complex and data-variable settings. Although model fidelity varies with data density and quality, the resulting geometry is broadly consistent with 1:500,000-scale geologic mapping and highlights areas where additional geologic study is most needed. The three-dimensional GFM provides a foundational framework to support groundwater, energy, and mineral resource assessments, and offers a transferable methodology for potential future U.S. Geological Survey efforts to build large-area subsurface models in underexplored regions of the United States.

Montana, North Dakota, South Dakota, Wyoming↗
USGS2025

Characterization of stream water quality and groundwater levels in the Central Pine Barrens region, Suffolk County, New York, 2017–23

The area locally known as the “Central Pine Barrens” region, located in Suffolk County, New York, contains most of Long Island’s preserved and undeveloped land. This region overlays an aquifer system that provides potable groundwater for residents of Suffolk County. Between 2017 and 2023, the U.S. Geological Survey, in cooperation with the Central Pine Barrens Joint Planning & Policy Commission and the Town of Brookhaven, monitored groundwater levels and stream water quality in this region. Groundwater levels were measured monthly at five wells and continuously (15-minute intervals) at a sixth well. Water quality was monitored at five locations in the Carmans River and at two locations in the Peconic River, and samples were analyzed for major ions, trace elements, nutrients, pharmaceuticals, and pesticides. The major ion compositions at the sites were mainly sodium-chloride type waters, and compositions varied the most at the furthest upstream sites in both streams. Concentrations above aquatic-life criteria thresholds also occurred most frequently at the furthest upstream sites. The seasonal patterns of nutrient loads and concentrations varied between the Carmans and Peconic Rivers. Several organic compounds including pharmaceuticals, domestic use products, and pesticides were detected at low concentrations in both streams. Metformin was the most frequently detected pharmaceutical compound, and herbicides were the most frequently detected pesticide class. Water-quality conditions influenced by anthropogenic contributions are a result of current and historical land use, and these contributions include onsite wastewater disposal systems, commercial or domestic fertilizers and pesticides, and urban or industrial contaminants in road runoff. This study characterizes and improves understanding of the current hydrologic conditions in the Central Pine Barrens region and the study findings can help inform the development of plans to manage, protect, and restore water resources.

New York↗
USGS2025

Assessment of density pattern retention of generalized data for 1:100,000-scale United States topographic maps

Cartographic generalization reduces the complexity of geographic data to produce legible, smaller-scale displays that retain essential information and logical geographic patterns. Generalization is a vital process in topographic map production. An important challenge in this process is managing and evaluating consistency across scale in the density and spatial distribution of map features such as buildings, roads, streams, water bodies, and elevation contours. Density patterns in these features reflect underlying physiographic conditions, which include factors such as bedrock geology, tectonics, climate, and landforms. Assessments of an acceptable level of change in feature density patterns are critical to ensuring the readability, usability, and accuracy of generalized maps and data. Preserving realistic density patterns across mapping scales also supports sustainable development goals in cartography, by helping to prioritize and communicate the relative reliability of geospatial data at specific scales.

Conference Paper↗
USGS1990

Preconditioned Conjugate-Gradient 2 (PCG2), a computer program for solving ground-water flow equations

This report documents PCG2: a numerical code to be used with the U.S. Geological Survey modular three-dimensional, finite-difference, ground-water flow model. PCG2 uses the preconditioned conjugate-gradient method to solve the equations produced by the model for hydraulic head. Linear or nonlinear flow conditions may be simulated. PCG2 includes two reconditioning options: modified incomplete Cholesky preconditioning, which is efficient on scalar computers; and polynomial preconditioning, which requires less computer storage and, with modifications that depend on the computer used, is most efficient on vector computers. Convergence of the solver is determined using both head-change and residual criteria. Nonlinear problems are solved using Picard iterations. This documentation provides a description of the preconditioned conjugate gradient method and the two preconditioners, detailed instructions for linking PCG2 to the modular model, sample data inputs, a brief description of PCG2, and a FORTRAN listing.

Water-Resources Investigations Report↗
USGS2026

Widespread landslide activity in an extreme wet season and implications for regional sediment management, eastern San Francisco Bay area, California

Watershed sediment production is expected to increase in a warmer future with more extreme rain, with cascading effects throughout drainage and sediment-transport networks. This study investigated landscape-scale sediment movement in the eastern San Francisco Bay area, California, USA, during the extreme 2016–2017 wet season that brought major rainfall, landslides, and flooding. Mapping 8,928 landslides across a 1,050-km 2 study area revealed new sediment yield of 510–956 t/km 2 , equivalent to denudation of 193–361 mm/ky. These results correspond closely to long-term denudation rates in the northern and central California Coast Ranges, indicating that mass wasting in very wet years dominates long-term sediment mobilization. However, due to long residence times in drainage networks, the 2017 landslides contributed at most ∼1%–2% of the estimated locally derived fluvial sediment transport to San Francisco Bay. Although the amount of sediment mobilized did not threaten municipal water supplies, small rangeland impoundments in this mixed-use landscape lost storage capacity to new sedimentation. Considering regional sediment supply and demand, even the exceptionally large sediment delivery in an extreme wet year cannot meet the need for sediment to accrete tidal wetlands in the bay. To keep pace with rising sea levels, this abnormally high terrestrial sediment input would need to occur in 50 of the next 75 years, an unlikely occurrence due to the prevalence of recent drought years. Shoreline protection and restoration in the bay would need additional sources of sediment, such as through management of dredged sediment through beneficial-reuse programs.

California↗
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↗
USGS2024

Chloride concentrations in groundwater from the western part of the Southern Hills regional aquifer system, Louisiana, 2021–22

Groundwater is heavily used for public supply and industrial uses in the Baton Rouge, Louisiana, area. Lowered water levels resulting from groundwater withdrawals have induced the movement of saltwater towards wells in East Baton Rouge and West Baton Rouge Parishes. Saltwater intrusion has the potential to affect water supply infrastructure, reduce water availability for some uses, and increase treatment costs. To document current conditions, samples were collected from 161 wells screened in 10 aquifers of the Southern Hills regional aquifer system during November 2021 through February 2022. The results were compared with historical data to identify where chloride concentrations are increasing, which could indicate that saltwater intrusion is occurring. Saltwater intrusion, to varying degrees and areal extents, was observed in most of the 10 aquifers. The limited availability of monitoring wells near or within some of the known saltwater plume areas restricts tracking of the movement or delineation of the plumes’ current extents.

Louisiana↗
USGS2026

Revisiting the utility of regional-scale, high-quality geophysical data in mineral exploration - A case study featuring the Mammoth Magnetic Anomaly, Pinal County, Arizona

Regional aeromagnetic surveys passively measure the total magnetic intensity (TMI) and are a foundational tool used in mineral exploration (Airo, 2015). With the increased global demand and the number of critical mineral resources required for manufacturing high-tech devices, developing high-quality, regional-scale geophysical surveys could aid critical mineral exploration efforts and geologic mapping. In 2019, the U. S. Geological Survey launched the Earth Mapping Resources Initiative (Earth MRI) to modernize the geologic and geophysical mapping of regions that have the potential to contain critical mineral resources within the United States. In support of planning Earth MRI geophysical surveys, Drenth and Grauch (2019) defined five aeromagnetic data quality rankings (rank 1 through rank 5) applying them to the airborne geophysical survey inventory of the United States (Johnson et al., 2021). Rank 1 aeromagnetic surveys are of the highest quality, meeting modern standards and allowing best practices for qualitative and quantitative interpretation; whereas rank 5 aeromagnetic surveys are of the lowest quality, being useful only for qualitative interpretation of broad features. Through the Earth MRI effort, 48 high-quality, regional-scale rank 1 and 2 airborne magnetic and radiometric geophysical surveys have been planned, collected, or publicly release through May 2025 (U. S. Geological Survey, 2025). Here, a portion of a rank 1 Earth MRI aeromagnetic survey in southeast Arizona is presented and compared to a legacy rank 5 aeromagnetic survey over the Mammoth Magnetic Anomaly (MMA), demonstrating how modern, high-quality aeromagnetic data improves our view of crustal geology, aiding mineral exploration.

Arizona↗
USGS2024

Prediction of regional broadband strong ground motions using a teleseismic source model of the 18 April 2014 Mw 7.3 Papanoa, Mexico, earthquake

To estimate predicted ground motion from a teleseismic slip model, we use a low‐ and high‐frequency hybrid method to simulate the regional, strong ground motions observed following the 18 April 2014 moment magnitude ( ⁠M w ⁠ ) 7.3 Papanoa, Mexico, earthquake. To generate the regional ground motion at low frequencies (<1 Hz), a teleseismically derived, finite‐fault, kinematic model is used to define the earthquake source, taking into account slip‐model variations identified with a parameter sampling approach that considers possible errors in the fault geometry, the hypocenter depth, and the rupture velocity. A 3D crustal model is used to calculate the low‐frequency ground motions using a finite‐element calculation that includes topography and considers variations in the source model to estimate the uncertainty in the calculations. High frequencies (>1 Hz) are added using a 1D full‐wave propagation code that estimates uncertainties by considering multiple random distributions of slip with different spatial correlation lengths. The synthetic, broadband (0.05–10.0 Hz) ground motions are obtained by combining the low‐ and high‐frequency portions match filtered at 1 Hz. These synthetic ground motions are compared with the regional observations using velocity records, peak ground acceleration, and medians of the orientation‐independent response spectra of the horizontal components (RotD50) calculated at periods of 0.2, 0.3, 0.5, 1.0, 2.0, 3.0, 5.0, 7.5, and 10.0 s. The results indicate that ground motions estimated at these periods using our hybrid approach based primarily on a teleseismically derived source model are comparable to the values observed for the 2014 Papanoa earthquake at regional distances. The approach could be used to estimate strong‐motion spectral levels expected for regions with limited local and regional recordings and could also fill in magnitude or distance gaps in ground‐motion prediction relations utilized in the assessment of seismic hazard.

Papanoa↗
USGS2025

Estimating agricultural irrigation water consumption for the High Plains aquifer region with integrated energy- and water-balance evapotranspiration modeling approaches

Estimation of irrigation water use provides essential information for the management and conservation of agricultural water resources. Conventionally, water use data are created based on reports and surveys from water users, whereas manual records may not be complete due to lacking flow meters, measurement gaps, inconsistent methods across regions, and time- and cost-consuming data processing. Alternatively, spatially explicit estimation of irrigation water use can be conducted efficiently using remote sensing evapotranspiration (ET) modeling approaches. In this study, we created a gridded blue water evapotranspiration (BWET) dataset to estimate historical irrigation water consumption (1986 – 2020) in the croplands across the United States High Plains aquifer region. The BWET data were generated by integrating an energy-balance ET model [Operational Simplified Surface Energy Balance model (SSEBop)] and a water-balance ET model [Vegetation ET model (VegET)]. BWET in croplands indicates crop consumptive use of irrigation water extracted from surface water and groundwater resources. The BWET estimates were compared with reported irrigation water use data for all counties within the aquifer region. The results revealed high agreement between growing season (May – September) BWET and annual water withdrawal at county level. Specifically, correlation coefficients of volumetric BWET and water withdrawal were 0.90 and 0.96, respectively, for the entire aquifer region and western Kansas. The timeseries of BWET and water withdrawal showed similar temporal trends and high covariations. The BWET estimates were systematically lower than the water withdrawal measurements, which was primarily attributed to blue water losses in the irrigation system. The irrigation efficiency, calculated as the ratio of BWET to water withdrawal depth, was 0.57 and 0.74 for the entire aquifer region and western Kansas, respectively. This study demonstrates the capability of using satellite-based ET models (e.g., SSEBop and VegET) to efficiently estimate crop water consumption and evaluate irrigation efficiency at landscape, county, and regional scales.

Colorado, Kansas, Nebraska, New Mexico, Oklahoma, ↗
USGS2024

Uncertainty in ground-motion-to-intensity conversions significantly affects earthquake early warning alert regions

We examine how the choice of ground‐motion‐to‐intensity conversion equations (GMICEs) in earthquake early warning (EEW) systems affects resulting alert regions. We find that existing GMICEs can underestimate observed shaking at short rupture distances or overestimate the extent of low‐intensity shaking. Updated GMICEs that remove these biases would improve the accuracy of alert regions for the ShakeAlert EEW system for the West Coast of the United States. ShakeAlert uses ground‐motion prediction equations (GMPEs), which calculate spatial distributions of peak ground acceleration (PGA) and peak ground velocity (PGV) from earthquake source estimates, combined with GMICEs to translate GMPE output into modified Mercalli intensity (MMI). We find significant epistemic uncertainty in alert distances; near‐source MMI estimates from different GMICEs can differ by over 1 MMI unit, and MMI extents used for public EEW alerts can differ by hundreds of kilometers for larger magnitude earthquakes ( M ∼6.5+). We use a catalog of “Did You Feel It?” shaking reports to evaluate how well GMICEs predict observed shaking. Our preferred GMICE is the one that computes MMI using PGV for high intensities and transitions to using PGA for nondamaging intensities. These results motivate updating GMICE relationships more generally, including in ShakeMap applications.

The Seismic Record↗
USGS2024

Site response in the Walnut Creek–Concord region of the San Francisco Bay, California: Ground motion amplification in a fault-bounded basin

Thirty‐seven portable accelerometers were deployed in the eastern San Francisco Bay communities of Walnut Creek and Concord to study site response in a fault‐bounded, urban, sedimentary basin. Local earthquakes were recorded for a period of two years from 2017 to 2019 resulting in 101 well‐recorded events. Site response is estimated by two methods: the reference site spectral ratio method and a source‐site spectral inversion method. The reference site spectral ratio method allows investigation of the variability of site amplification with source azimuth and frequency. The source‐site spectral inversion method yields the best least‐squares fit to site response for a database of ground‐motion records. Both methods show substantial amplification in the Walnut Creek–Concord basin below 2 Hz indicating strong surface‐wave development. Greater amplification is seen for sources aligned along the long axis of the basin. Inversion using close‐in sources at short distances yields lower amplification at longer periods than the entire data set due to reduced surface‐wave generation for steeper angles of incidence. Inversion of site response spectra for shallow shear‐wave velocity using a global search algorithm yields V S30 values consistent with generalized mapping results based on geology and topography but with greater variability due to local site variations. 3D finite‐element modeling shows greater amplification in the Walnut Creek–Concord basin with a basin‐edge effect likely contributing to higher ground motions. Topography is also seen to lead to increased scattering and shadowing effects.

California↗
USGS2024

Paleoseismology of the Sawtooth fault and implications for fault behavior in the epicentral region of the 2020 Mw 6.5 Stanley, Idaho, earthquake

The 2020 moment magnitude ( M w ⁠⁠ ) 6.5 Stanley, Idaho, earthquake raised questions about the history and extent of complex faulting in the northwestern Centennial Tectonic Belt (CTB) and its relation to the Sawtooth normal fault and Eocene Trans‐Challis fault system (TCFS). To explore faulting in this area, we excavated a paleoseismic trench across the Sawtooth fault along the western margin of the CTB, and compared an early Holocene (9.1 ± 2.1 ka, 1δ ⁠ ) rupture at the site with lacustrine paleoseismic data and fault mapping in the 2020 epicentral region. We find: (1) a history of partial to full rupture of the Sawtooth fault ( M w ⁠ 6.8–7.4), (2) that shorter ruptures ( M w ≤ ⁠⁠6.9 ) are likely along distributed and discontinuous faults in the epicentral region, (3) that this complex system that hosted the 2020 earthquake is not directly linked to the Sawtooth fault, (4) that the northeast‐trending TCFS likely plays a role in controlling fault length and rupture continuity for adjacent faults, and (5) that parts of the TCFS may facilitate displacement transfer between normal faults that accommodate crustal extension and rotation. Our results help unravel complex faulting in the CTB and imply that relict structures can help inform regional seismic hazard assessments.

Idaho↗
USGS2025

Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California

The Mountain Pass carbonatite stock is the largest rare earth element (REE) deposit and only active REE mine in the United States. The carbonatite intrusion and spatially associated alkaline silicate intrusions constitute the Mountain Pass Intrusive Suite, which is located within the Mojave Province in California. Both the carbonatite and the alkaline silicate rocks are enriched in large ion lithophile elements and light REEs, and less enriched to depleted in high field strength elements, indicating the mantle source region was metasomatically enriched in incompatible trace elements. The cause of this metasomatic mantle enrichment and the genetic relationship between the carbonatite and the alkaline silicate stocks are poorly understood. In this study, major and trace element geochemical data and isotopic (Rb-Sr, Sm-Nd, and Lu-Hf) data are presented to constrain genesis of the Mountain Pass Intrusive Suite, from mantle source region to the intrusion of the stocks. Our geochemical data are consistent with derivation of the alkaline silicate and carbonatite melts through partial melting from a shared mantle source region rather than through liquid immiscibility or fractional crystallization and separation of a carbothermal fluid. Although the Rb-Sr isotopic system in the Mountain Pass Intrusive Suite is disturbed at the whole-rock scale, the isotopic systems for whole-rock Sm-Nd (εNd i = ‐2.2 ± 0.8) and zircon Lu-Hf (εHf i = 0.1 ± 1.1) are robust and support mantle derivation of the magmas. Geochemical modeling using experimentally derived partition coefficients was used to identify possible causes of enrichment in incompatible elements through metasomatism in the mantle source region. Modeling of metasomatism by melts derived by partial melting of deeply subducted carbonated sediments approximates observed Mountain Pass Intrusive Suite trace element chemistry. Scattered εHf i in inherited zircon (2.8 ± 2.6) is consistent with derivation from an arc-related environment with substantial crustal contamination. Paleotectonic studies in the Mojave Province indicate that regional subduction preceded emplacement of the Mountain Pass Intrusive Suite by ∼300 Ma. Melting of the Mountain Pass source region may have been caused by post-collisional thermal relaxation and extension.

California↗
USGS2025

Cooling perspectives on the risk of pathogenic viruses from thawing permafrost

Climate change is inducing wide-scale permafrost thaw in the Arctic and subarctic, triggering concerns that long-dormant pathogens could reemerge from the thawing ground and initiate epidemics or pandemics. Viruses, as opposed to bacterial pathogens, garner particular interest because outbreaks cannot be controlled with antibiotics, though the effects can be mitigated by vaccines and newer antiviral drugs. To evaluate the potential hazards posed by viral pathogens emerging from thawing permafrost, we review information from a diverse range of disciplines. This includes efforts to recover infectious virus from human remains, studies on disease occurrence in polar animal populations, investigations into viral persistence and infectivity in permafrost, and assessments of human exposure to the enormous viral diversity present in the environment. Based on currently available knowledge, we conclude that the risk posed by viruses from thawing permafrost is no greater than viruses in other environments such as temperate soils and aquatic systems.

mSystems↗