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Dating a medieval tsunami with uranium-series techniques on Caribbean corals

Uranium-series dates from coral boulders constrain the timing of a medieval tsunami from the Puerto Rico Trench. Previously reported evidence for this tsunami includes hundreds of coral boulders that came to rest hundreds of meters inland on Anegada, British Virgin Islands. New U-series dates on these coral boulders provide limiting dates for the tsunami. The narrowest limits were by dating interior bands of a coral that retains the hemispherical form of a living coral colony, and which include adjustments for the number of annual density band couplets between the dated samples and the boulder exteriors. By those limits, the tsunami dates between 1381 and 1391 CE, and likely occurred during summer or fall. The tsunami is important as the only reported sign that the eastern Puerto Rico Trench has produced a great earthquake. The dating may aid in defining the earthquake source and in communicating tsunami hazards.

British Virgin Islands, Puerto Rico

Structural evolution of iron coordination in proteins across Earth’s oxygenation history

Protein metal-binding sites support essential biological functions shaped by protein fold, subunit interactions, and cofactor chemistry. Because these sites encode both biochemical function and environmental constraint, they offer a route to connect protein evolution with changes in Earth’s surface environment through time. Of particular interest is iron (Fe), the most widely used metal in biology and a cofactor central to both anaerobic and aerobic metabolism. Here, we systematically compare the immediate chemical environments of functionally essential Fe-binding sites in three-dimensional protein structures to test whether Fe coordination spheres differ across oxygen contexts. Using a curated dataset of experimentally determined structures, we identify a clear shift in the local chemistry of Fe-binding environments from anaerobic to aerobic proteins. Aerobic Fe sites are significantly more hydrophilic than anaerobic ones, and amino-acid composition analyses show reduced cysteine use in aerobic Fe-binding neighborhoods. These patterns suggest that as Earth’s surface environments became more oxygenated, proteins retained Fe as a core redox metal while reconfiguring local coordination chemistry in ways less vulnerable to oxidative damage. More broadly, this study introduces and applies the Coordination Sphere Analysis and Comparison (CSAC) workflow, an open and archived Python workflow for extracting local metal-binding environments from structure datasets, providing a framework for linking metalloprotein structure to evolutionary and geobiological transitions across Earth history.

Discover Life

Formation of the Mount Weld rare earth deposit, Western Australia: Geochronology constraints

Constraining the age of protracted chemical weathering in stable cratonic areas that may form thick regoliths and the potential enrichment of various elements is challenging. Economic deposits of aluminium, iron, copper, nickel, cobalt, niobium, and rare earth elements (REEs) form in this manner. Determining the age of formation can provide key information for exploration of similar deposits as well as to better constrain paleoclimatic conditions. This study describes our effort to constrain the age of formation of the Mount Weld deposit, a world-class carbonatite-derived REE laterite deposit. We utilize multiple geochronological techniques on different minerals. The oldest dates, ranging from ca. 100 to 50 Ma, were from laser ablation ICPMS, Lu-Hf dating of churchite, a heavy REE phosphate mineral formed by mineral saturation in groundwater. Growth bands on individual minerals show a younging outwards. 40 Ar/ 39 Ar geochronology of cryptomelane, a potassium-bearing manganese oxide mineral, yielded ages ranging from ca. 40 to 26 Ma. Similarly, (U–Th)/He geochronology of goethite yielded ages from ca. 45 to 19 Ma.

Mount Weld deposit

Reference 1D seismic velocity models for volcano monitoring and imaging: Methods, models, and applications

Seismic velocity models of the crust are an integral part of earthquake monitoring systems at volcanoes. 1D models that vary only in depth are typically used for real‐time hypocenter determination and serve as critical reference models for detailed 3D imaging studies and geomechanical modeling. Such models are usually computed using seismic tomographic methods that rely on P ‐ and S ‐wave arrival‐time picks from numerous earthquakes recorded at receivers around the volcano. Traditional linearized tomographic methods that jointly invert for source locations, velocity structure, and station corrections depend critically on having reasonable starting values for the unknown parameters, are susceptible to local misfit minima and divergence, and often do not provide adequate uncertainty information. These issues are often exacerbated by sparse seismic networks, inadequate distributions of seismicity, and/or poor data quality common at volcanoes. In contrast, modern probabilistic global search methods avoid these issues only at the cost of increased computation time. In this article, we review both approaches and present example applications and comparisons at several volcanoes in the United States, including Mount Hood (Oregon), Mount St. Helens (Washington), the Island of Hawai’i, and Mount Cleveland (Alaska). We provide guidance on the proper usage of these methods as relevant to challenges specific to volcano monitoring and imaging. Finally, we survey‐published 1D P ‐wave velocity models from around the world and use them to derive a generic stratovolcano velocity model, which serves as a useful reference model for comparison and when local velocity information is sparse.

Seismological Research Letters

Unveiling coseismic deformation from differenced legacy aerial photography and modern lidar topography: The 1983 M6.9 Borah Peak earthquake, Idaho, USA

The 1983 M6.9 Borah Peak, Idaho, earthquake is one of the largest historical normal fault earthquakes in the western United States. We quantified meter-scale vertical change along the 35 km-long rupture using topographic differencing of 1966 aerial imagery and 2019 lidar-derived data. The initial differencing results are largely obscured by horizontal and vertical georeferencing errors and flight-line stripes. Our error corrections are designed to be insensitive to the coseismic deformation and reduced error by 50%. We calculated vertical separation and resolved a maximum of 2.02 ± 0.46 m at Doublespring Pass. Our vertical separation measurements are generally consistent with those from prior studies using field data and post-earthquake topographic data. However, the differencing measurements are a few decimeters lower than these prior measurements, indicating that differencing can isolate historical from prehistoric earthquake deformation. Our study demonstrates that revisiting historical earthquakes can provide new insights into the magnitude and patterns of coseismic deformation.

Idaho

Predictions of anthropogenic background PFAS concentrations in soil and relation to bedrock lithology and groundwater quality

Detectable concentrations of per- and polyfluoroalkyl substances (PFAS) have been observed in soils in remote areas and presumably originate from atmospheric deposition. These anthropogenic background concentrations may enable some PFAS to leach to groundwater at levels that exceed regulatory criteria for drinking water. However, anthropogenic background soil concentrations and their connection to groundwater are not well characterized. We developed a boosted regression tree model to predict perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) concentrations in shallow soils across northern New England. Low soil pH was the most important predictor of elevated anthropogenic PFOS and PFOA concentrations in background soils, rather than potential PFAS sources, land use, or population density. Total organic carbon (TOC) was also an important predictor for PFOS soil concentrations. Model predictions indicate that 73% of the shallow soils within Maine, Vermont, and New Hampshire exceed New Hampshire’s Soil Remediation Standard for PFOS (0.5 ng/g) and 41% exceed the PFOA standard (0.4 ng/g). Analysis of soil model results and groundwater data suggests that areas with high soil pH are associated with higher groundwater detection frequencies, illustrating how areas with less retention in soil are, conversely, also areas with potentially greater groundwater vulnerability. Further analysis indicates that groundwater may be more vulnerable in calcareous lithologies.

Maine, New Hampshire, Vermont

New constraints on northeast Seattle basin structure from converted seismic waves

The Seattle basin is a deep sedimentary basin in the Seattle–Bellevue, Washington metropolitan area within the Puget Lowland of Washington State. We determine the structure of a portion of the basin and the underlying basement using analysis of P waves converted from direct S incident from below. A deep local crustal event beneath Monroe, about 35 km northeast of Seattle, was recorded by a 100‐station nodal array deployed in 2019. The event produced a variety of coherent seismic phases, including converted waves from the sediment—basement boundary, internal structure within the basin, and additional crustal discontinuities. Using observed Sp converted waves, we apply an adjoint‐based full waveform inversion (FWI) method to determine the amplitude and extent of seismic discontinuities at depth. We find the strongest source of converted waves for this event lies ∼6 to 7 km depth below northern Lake Washington, interpreted to be the local depth to basement rock. The newly imaged shallow basement structure may be part of a deformation zone associated with the Siletzia eastern boundary. Our results highlight the utility of converted seismic waves recorded by a dense array, combined with an FWI method, to illuminate crustal structure.

Washington

Characterizing sedimentary organic carbon in a hydrothermal spreading center, the Escanaba Trough

Sediments in critical marine mineral environments are of wide importance due to their preservation of both marine minerals and organic carbon (OC) stocks. However, OC storage and cycling is often overlooked in mineral system studies. This work characterizes sedimentary OC within the Escanaba Trough, a hydrothermal sulfide system off the coast of northern California. By utilizing ROV-based push coring, we collected sediments near and far from high temperature, low temperature, and inactive vents. We applied a multipronged organic geochemical approach, measuring bulk sediment, OC fractions of varying labilities, and biomarkers to tease apart the storage, source, and cycling of OC within this complex system. In contrast to past work indicating a primarily terrestrial source to deeper, Pleistocene sediments, our results suggest a primarily marine source in surface sediments at least 50 m away from active venting. Near active venting, we see evidence of locally produced chemosynthetic OC in addition to the background marine source. This chemosynthetic OC appears to be rapidly remineralized and supports more complex deep-sea food webs compared to hemipelagic sites. Still, the greatest contribution of labile OC was observed at inactive vent sites, which we suggest is due to hydrothermal fluid alteration of more labile OC at actively venting sites. Depending on fluid temperature, hydrothermally altered OC is either preserved in the sediments as petroleum or migrated with fluid flow. Considering inactive sites are those most likely to be targeted by potential mining, we suggest additional studies could verify if these results apply at other sedimented seafloor massive sulfide systems.

California

Persistent deep long-period seismicity near the Lassen Volcanic Center

Deep long-period (DLP) earthquakes have been observed at many volcanic settings around the world and linked to the magmatic processes that drive volcanic unrest. At the Lassen Volcanic Center (LVC) of the Cascade arc, limited detection of DLP activity hinders classification of anomalous seismic behavior and its relationship to the LVC magmatic system. This study uses a template matching approach with seismic data from temporary nodal and permanent stations to detect and locate DLP earthquakes near the LVC between 2017 and 2024. Within the DLP catalog of 611 events, a transition occurs from scattered (2017–2020) to oscillatory (2021–2024) occurrence rates. During the oscillatory period, regional earthquakes with large amplitude velocity waveforms observed near the LVC are associated with abrupt changes in DLP occurrence rates. Continued monitoring of DLP activity has the potential to better define the processes that drive volcanic unrest at the LVC in the future.

California

Geoelectric evidence for a wide spatial footprint of active extension in central Colorado

Three-dimensional magnetotelluric (MT) imaging in central Colorado reveals a set of north-striking high-conductivity tracks at lower-crustal (50–20 km) depths, with conductive finger-like structures rising off these tracks into the middle crust (20–5 km depth). We interpret these features to represent saline aqueous fluids and partial melt that are products of active extensional tectonomagmatism. These conductors are distributed over a wider region than the narrow corridor along which Rio Grande rift structures are traditionally mapped at the surface, and they consequently demarcate regions of the lower crust where accommodation of bulk extensional strain has concentrated conductive phases. Our observations reveal limitations in existing models of Rio Grande rift activity and may reflect unrecognized spatiotemporal variations in rift system evolution globally.

Colorado

A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping

Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD. LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics. Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved 72.1 ± 1.60% overall agreement, compared to 71.1 ± 1.7% agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved 83.4 ± 1.22% agreement, compared to 84.6 ± 1.11% agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.

Remote Sensing of Environment

Increased flood exposure in the Pacific Northwest following earthquake-driven subsidence and sea-level rise

Climate-driven sea-level rise is increasing the frequency of coastal flooding worldwide, exacerbated locally by factors like land subsidence from groundwater and resource extraction. However, a process rarely considered in future sea-level rise scenarios is sudden (over minutes) land subsidence associated with great (>M8) earthquakes, which can exceed 1 m. Along the Washington, Oregon, and northern California coasts, the next great Cascadia subduction zone earthquake could cause up to 2 m of sudden coastal subsidence, dramatically raising sea level, expanding floodplains, and increasing the flood risk to local communities. Here, we quantify the potential expansion of the 1% floodplain (i.e., the area with an annual flood risk of 1%) under low (~0.5 m), medium (~1 m), and high (~2 m) earthquake-driven subsidence scenarios at 24 Cascadia estuaries. If a great earthquake occurred today, floodplains could expand by 90 km 2 (low), 160 km 2 (medium), or 300 km 2 (high subsidence), more than doubling the flooding exposure of residents, structures, and roads under the high subsidence scenario. By 2100, when climate-driven sea-level rise will compound the hazard, a great earthquake could expand floodplains by 170 km 2 (low), 240 km 2 (medium), or 370 km 2 (high subsidence), more than tripling the flooding exposure of residents, structures, and roads under the high subsidence scenario compared to the 2023 floodplain. Our findings can support decision-makers and coastal communities along the Cascadia subduction zone as they prepare for compound hazards from the earthquake cycle and climate-driven sea-level rise and provide critical insights for tectonically active coastlines globally.

California, Oregon, Washington

The Mammoth magnetic anomaly, Pinal County, Arizona

A high-resolution Earth Mapping Resources Initiative airborne geophysical survey was flown in the southwest North American porphyry copper province to improve bedrock geologic maps and to identify areas that have unrecognized critical mineral resource potential. During the review of the aeromagnetic data, a distinctly monopolar-shaped, negative magnetic anomaly was observed at a flight elevation of 200 m above the ground with a maximum amplitude of –9500 nT. We have named this the Mammoth magnetic anomaly (MMA) because it is centered 12 km northeast of the town of Mammoth, Arizona, USA. The total field anomaly (TFA) contour of –500 nT enclosing the MMA defines an elongate shape measuring 2.5 km long by 1 km wide that trends northwest–southeast. Given the striking nature of this negative, monopolar-shaped magnetic anomaly, we conducted a ground campaign in May 2025 to determine its authenticity and potential relationship to critical mineral endowment. The MMA was confirmed on the ground with a TFA approaching –46,000 nT. Total magnetic intensity (TMI) observations routinely fell below the 18,000 nT operating floor of an industry-standard cesium-vapor total field magnetometer, and extremely low TMI measurements were corroborated along coincident traverse lines using two high dynamic range, but lower sensitivity, smartphone vector magnetometers. The lowest TMI values recorded by both smartphone magnetometers were 1000 nT and confirmed with multiple adjacent and crossing lines. Field observations suggest that this magnetic feature is caused by strong remanent magnetization within fine-grained magnetite hosted within locally altered Pinal Schist.

Arizona

The 2023 Alaska National Seismic Hazard Model

US Geological Survey (USGS) National Seismic Hazard Models (NSHMs) are used extensively for seismic design regulations in the United States and earthquake scenario development, as well as risk assessment and mitigation for both buildings and infrastructure. This 2023 update of the long-term, time-independent Alaska NSHM includes substantial changes to both the earthquake rupture forecast (ERF) and ground motion models (GMMs). The ERF includes numerous additions to the finite-fault model, considers two deformation models, and introduces updated declustering and smoothing algorithms in the gridded background seismicity model. For the Alaska–Aleutian subduction zone, megathrust earthquakes occur on an updated structural and segmentation model, and the moment magnitude (M) 8+ rupture and rate model include a logic tree branch that considers slip rates derived from geodetic models of interface coupling. The megathrust model considers multiple models of down-dip width, and magnitudes are computed using newly developed scaling relations. For subduction intraslab events and subduction interface events with M < 7, the 2023 update uses a smoothed seismicity model with rupture depths derived from Slab2. The 2023 model updates GMMs in all tectonic settings using the recently published Next Generation Attenuation Subduction (NGA-Sub) GMMs for subduction interface and intraslab events, and the NGA-West2 GMMs for active crustal settings. Collectively, additions and updates to the Alaska NSHM result in hazard increases across most of south-central Alaska relative to the previous model, published in 2007. These changes are primarily due to the adoption of updated rate models for the large-magnitude interface events and the NGA-Sub GMMs that have much higher aleatory variability (sigma), consistent with global observations, and that include models of epistemic uncertainty.

Alaska

Groundwater-level elevations in the Denver Basin bedrock aquifers and Upper Black Squirrel Creek alluvial aquifer, El Paso County, Colorado, 2021–24

El Paso County is the second-most populous county in Colorado and is projected to grow another 15 percent by 2030. Within El Paso County is the Upper Black Squirrel Creek Designated Groundwater Basin (Black Squirrel Basin), an area where surface water is scarce and water users rely primarily on groundwater from five different aquifers (the Upper Black Squirrel Creek alluvial aquifer and four bedrock aquifers within the Denver Basin aquifer system: the lower Dawson, Denver, Arapahoe, and Laramie-Fox Hills aquifers) to meet their needs. Currently (2024), land within the Upper Black Squirrel Creek Basin is primarily used for rural grazing and agriculture; however, municipal development is ongoing. In 2021, the U.S. Geological Survey, in cooperation with the Upper Black Squirrel Creek Ground Water Management District, began a study to establish a baseline dataset and assess the groundwater resources of the aquifers within the Black Squirrel Basin. A network of 39 wells was established in 2021; discrete groundwater-level measurements were made bimonthly. Nine of the 39 wells were equipped with pressure transducers to record hourly groundwater-level data. Seven wells had statistically significant seasonal trends, and trends at 3 wells were negative. For the discrete data, 16 wells had a significant trend for the study period, and 4 wells had negative trends. For the time-series data, 8 wells had significant trends, and 3 wells had negative trends. Potentiometric surface maps were created for this study using discrete, static groundwater levels measured in April 2023. These maps showed the estimated groundwater flow direction from the north-northwest to the south-southeast in the alluvial aquifer and from the northwest to the east-southeast for the lower Dawson and Denver aquifer wells. This study indicates the potential benefit of monitoring wells in the areas near municipal pumping. Additional monitoring could lead to a better understanding of connectivity between aquifers and be an important tool for assessing long-term sustainability of groundwater use.

Colorado

A method to obtain remotely sensed grain size distributions from nonplanar granular deposits

Constraining the grain size distribution of granular deposits with complex surfaces is difficult with existing approaches. Field and laboratory techniques are time consuming and limited by the maximum grain size that laboratories can accommodate. In this study, we present a new method to identify the coarse fraction of the grain size distribution at a debris-flow fan deposit surveyed with terrestrial laser scanning (TLS) in Glenwood Canyon, Colorado, USA. This method is a novel grain segmentation algorithm developed for application to point cloud data of deposits with complex surfaces and angular grains ranging in size from centimeters to a meter. This approach combines an existing random forest machine learning method with a novel iterative clustering algorithm. We compared the grain size distribution from our algorithm with a Wolman pebble count conducted in the field, and found a root mean squared error of less than 2 cm from the 5th to 95th percentile of the grain size distribution of grains ranging from cobble to boulder sized (6.3–78 cm in our application). Finally, we compared our new algorithm with an existing open-source grain segregation algorithm, and our method outperformed the selected alternative when applied to the debris-flow deposit point cloud.

Colorado

Uncertainty and spatial correlation in station measurements for mb magnitude estimation

The body‐wave magnitude (⁠⁠) is a long‐standing network‐averaged, amplitude‐based magnitude used to estimate the magnitude of seismic sources from teleseismic observations. The U.S. Geological Survey National Earthquake Information Center (NEIC) relies on in its global real‐time earthquake monitoring mission. Although waveform modeling‐based moment magnitudes are the modern standard to characterize earthquake size, is important because (1) in many cases, waveform modeling is not possible (e.g., low signal‐to‐noise events), (2) is applicable over a broad range of magnitudes, ∼M 4–7, and (3) there is a many decades‐long history of estimating magnitudes. We use the NEIC Preliminary Determination of Epicenters earthquake catalog to investigate the uncertainty in NEIC station measurements. We show that measurements are spatially correlated, which can bias event ⁠, and we describe an empirical relation between this spatial correlation and station‐to‐station distance. We further describe an approach to mitigate bias from the spatial correlation. Accounting for the spatial covariance of observations can change the event from −0.15 to 0.07 units (10th to 90th percentile) for smaller events (⁠⁠). These smaller events have the largest standard deviations ranging from 0.05 to 0.15 units (10th to 90th percentile).

The Seismic Record

Cruise summary—Samoa Basin abyssal mapping—Box coring leg, Pago Pago, Territory of American Samoa to Pago Pago, American Samoa, April 11– May 1, 2026

Expedition Summary U.S. Geological Survey scientists led a box coring effort to the Samoa Basin to characterize minerals and the surrounding abyssal sediments and fauna. Thirty-eight box cores were deployed between April 13, 2026, and April 28, 2026. Thirty-six box cores recovered sufficient material to determine nodule density, and 35 recovered sufficient material for subcores to be collected. The purpose of this Data Report is to provide a summary of samples collected, initial results that were obtained shipboard, and briefly mention planned future analyses from this expedition.

Data Report