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Niobium-rich minerals from the Sheep Creek carbonatite-related deposits, Montana, USA

The Sheep Creek area in southwest Montana contains a number of small, tabular, carbonatite-related deposits that are rich in Nb- and REE-minerals. Two of the “vein-dikes” were mined at a small scale for Nb in the late 1950s. The most abundant Nb-bearing minerals are columbite-(Fe), nioboaeschynite-(Ce), baotite, and two varieties of Ti-Nb-Fe-oxide. An early oxide with Ti/Nb (atomic) near unity later broke down to a mixture of columbite + TiO2 with distinctly lower Nb content. Zircon intergrown with the Nb-REE minerals was dated by U-Pb methods to 116±2 Ma. This age is in agreement with previous dating (Th-Pb on monazite, Re-Os on molybdenite), and indicates that the Sheep Creek deposits are early Cretaceous in age.

Montana

Roadway runoff induced acute mortality in juvenile coho salmon during spring storm events

Extensive mortalities of adult coho salmon ( Oncorhynchus kisutch ), often called “Urban Runoff Mortality Syndrome” (URMS), have been documented during the fall in creeks where water quality has been degraded by roadway runoff. The primary cause of mortality is 6PPD-quinone (6PPDQ; N -(1,3-dimethylbutyl)- N ′-phenyl- p -phenylenediamine quinone)–an ozone transformation product that forms on all vehicle tires. Laboratory studies have shown that juvenile coho salmon are highly sensitive to 6PPDQ exposure. Unlike adults, juveniles reside in impacted watersheds year-round, including during the spring when 6PPDQ concentrations can frequently exceed lethal thresholds during storms. To assess the potential incidence of URMS in springtime rearing habitats for juvenile coho salmon, we conducted a paired water quality and toxicology study at Miller Creek, a runoff-impacted watershed in Normandy Park, WA, USA. Using a small field facility, three naïve groups of juvenile coho salmon ( N = 720) were exposed to either creek water or groundwater ( N = 120 per treatment per storm), across three spring storms while comparing water quality and mortality end points. In creek water during exposures, peak 6PPDQ concentrations reached 73–110 ng/L, exceeding reported median lethal concentrations (LC 50 ) for coho salmon. Over each 24–73 h storm exposure period, ∼80% of Miller Creek-exposed juvenile salmon died. No mortality occurred among control fish exposed to groundwater. These results indicate previously unidentified mortality risks for juvenile life stages of coho salmon during spring storms, suggesting substantial and year-round water quality impediments to coho salmon health and recovery across roadway runoff-impacted spawning, rearing, and migratory habitats.

Washington

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

From landslide susceptibility to risk assessment in the conterminous U.S.

Understanding the spatial distribution of landslide prone-areas and what consequences they may have is important for risk management and land-use planning. In the United States, although landslides occur in every state, a comprehensive landslide risk assessment is still missing. Existing efforts, such as the Federal Emergency Management Agency (FEMA)’s National Risk Index, rely on aggregated products and coarse cartographic units, limiting their geomorphological and practical accuracy. In this study, we present a methodological advance for landslide risk assessment across large areas with incomplete and sparse data. We apply our procedures to the conterminous United States by integrating geomorphologically meaningful partitions and spatial and temporal probability data-driven models. Landslide susceptibility is estimated using a Generalized Additive Mixed Model incorporating a bias capture/correction scheme to account for inventory inaccuracies (reference Area Under the Curve = 0.75). The exceedance probabilities of landslide occurrence are defined for three temporal scenarios (2, 5, and 10 year). Then, we explore the associated potential economic consequences for human settlements and agricultural areas. The findings indicate that the spatial variability of risk is primarily controlled by exposure rather than by susceptibility/hazard alone. The mean risk increases by ∼170% from the 2-year to the 10-year scenario. Beyond its quantitative outcomes, this study offers a blueprint for continental or sub-continental scale landslide risk assessments, demonstrating both the opportunities and current limitations.

Engineering Geology

Characterizing changes in postfire debris-flow hazard as burned areas recover

Emergency assessments of postfire debris-flow hazards that are performed by the U.S. Geological Survey (USGS) provide estimates of debris-flow likelihood and rainfall triggering conditions that are used for evaluating and managing runoff-generated debris-flow hazards in recently burned areas throughout the western United States. Although the immediate postfire period, within roughly one year after fire, is typically the most susceptible to runoff-generated debris flows, the hazard evolves in time and space as the burned area recovers. The recovery trajectory a given burned area will take depends on local climate and weather and can be difficult to predict. Some burned areas recover quickly, whereas others experience debris flows for multiple years after fire. As a result, extending our ability to update debris-flow likelihood estimates and rainfall thresholds based on observed recovery of the burned area would be beneficial. We present a method for multi-year runoff-generated debris-flow hazard assessment that leverages the USGS “M1” debris-flow likelihood model and integrates updated, satellite-derived, normalized burn ratio data to estimate vegetation recovery. We predict recovery-aware rainfall thresholds and validate them against a multi-year debris-flow hazard prediction and could be adapted for use with other debris-flow models that incorporate burn severity data.

Arizona, California, Colorado, New Mexico, Washing

Deformed submarine terraces in Puget Sound, Pacific Northwest, indicate only one M >~7.5 earthquake on the Seattle fault zone in the past 11,000 yr

Submerged marine terraces in Puget Sound, deformed across the Seattle fault zone (SFZ), indicate that only one earthquake as large as M~7.5 has occurred in at least the past 11 kyr. Previous paleoseismic studies document a M~7.5 earthquake between 923–4 CE, which uplifted coastal marine terraces by as much as 8 m. We demonstrate that this earthquake was the only such event since ~11 ka by mapping and quantifying deformation of older marine terraces, now submerged in Puget Sound. The submerged terraces, attributed to a late-glacial sea-level lowstand, record both glacial isostatic rebound and tectonic deformation. Vertical offset of the ~11 ka terraces within the SFZ is comparable to that of the marine terraces uplifted in 923 CE, implying no additional large (M>~7.5) earthquake on the SFZ since ~11 ka. This result implies a longer recurrence interval than current hazard estimates, which assumes recurrence of M>7.1 events every 5 kyr. Our mapping of SFZ deformation since ~11 ka also supports fault segmentation and contiguous block uplift between the Seattle and Tacoma fault zones.

Washington

Estimating aftershock risk for entry into earthquake-damaged buildings

We present a simple method to estimate the risk of experiencing strong shaking from aftershocks during entry into earthquake-damaged buildings. We compute wait times until the probability of strong ground shaking from aftershocks reaches a predefined risk threshold; for example, a 0.4 percent probability of experiencing Modified Mercalli Intensity 7 or greater shaking during the planned building entry. We also develop a relation between aftershock probability and the probability of strong shaking, so that users can reference the U.S. Geological Survey aftershock forecast during an ongoing aftershock sequence to determine if the risk threshold has been met. We apply our method to active continental regions (for example, the Western United States), stable continental regions (for example, the Central and Eastern United States), and subduction zones (for example, Cascadia or Alaska).

Open-File Report

Aftershocks in stress shadows are inconsistent with modeled static Coulomb stress changes

Aftershock triggering is commonly attributed to increases in static Coulomb stress. In some areas, termed "stress shadows", a decrease in Coulomb stress is predicted to suppress earthquake occurrence. However, aftershocks are often observed in the modeled stress shadows. We examine several hypotheses that attempt to reconcile these shadow aftershocks with the static Coulomb stress change model: (1) they appear to be in shadows because of inaccuracy in the stress change calculations, (2) they occur on faults of unusual orientation which actually experienced increased Coulomb stress, (3) they occur on faults with different frictional properties, not modeled well by Coulomb stress, and (4) they are secondary aftershocks triggered by prior aftershocks or afterslip. When tested on the 2016 Mw7.0 Kumamoto, Japan, and 2019 Mw7.1 Ridgecrest, California, aftershock sequences, none of these hypotheses can explain the majority of the shadow aftershocks, and taken together these hypotheses can explain only about half of these aftershocks. This implies that Coulomb stress modeling that lacks small-scale fault zone heterogeneity might be inadequate to fully capture the true static stress changes and/or that other physical triggering models are needed, for example transient processes such as delayed triggering by dynamic stress changes from the passing seismic waves.

California

A ground-motion model derived using a generalized mean rupture distance for large slab interface earthquakes

Source–station distance is a central input to ground‐motion models (GMMs) for predicting seismic shaking. GMM development uses distance metrics including the Joyner–Boore distance, which is the shortest distance from an observation point to the surface projection of the earthquake rupture, and R rup the shortest distance to the rupture in three dimensions. Thompson and Baltay (2018) proposed the generalized mean rupture distance R p to address observed near‐fault ground‐motion saturation. R p accounts for the contribution to the shaking of all parts of the rupture and provides a simple method for incorporating spatially variable slip. They used R p to develop a GMM for shallow crustal earthquakes, assuming uniform slip. Here, we investigate the improvement offered by an R p ‐based GMM for large subduction interface earthquakes by recalibrating the path term for a published GMM ( Parker et al. , 2022 ) using R p derived from distributed slip models (DSMs). Inspection of within‐event and total residuals indicates that the recalibrated model fits the data at least as well as an alternative in which the path term was recalibrated using R rup and the same dataset. Incorporating slip information in its entirety or trimming the DSM geometry is preferable to assuming uniform moment release on a prescribed model fault that extends beyond the actual ruptured area. R p tuned to minimize model uncertainty is closer to the maximum distance to rupture for peak ground velocity (PGV) than acceleration, possibly reflecting the contribution to high‐frequency shaking of slip on local asperities. However, when the moment is concentrated far from stations, PGV is fit adequately with R p closer to R rup ⁠ . Our results suggest incorporating slip‐derived moment release through R p could improve GMMs for slab interface events, especially if the implementation of R p ‐based models is refined using a larger dataset of earthquakes with greater geographic diversity to account for regional ground‐motion variations.

Seismological Research Letters

Heat-flow data from southeastern Oregon

With the exception of values from two holes drilled within 2 km of Mickey Hot Springs, 17 new heat-flow values in southeastern Oregon are within or somewhat below the range one would normally expect in non-anomalous parts of the North American Cordillera. This is not surprising for a region in which most igneous rocks on the surface are 5 m.y. old or more. There is a suggestion of a thermal anomaly associated with the very young (late Pleistocene or Holocene) Diamond Craters lava field, and the thermal regime on both sides of Steens Mountain seems to be controlled, to some degree, by lateral and vertical movement of water.

Oregon

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

Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas

In the United States, private wells are not federally regulated, and many households do not test for Arsenic (As). Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1 km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10 μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km 2 as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.

Minnesota

Irrigated agriculture influences selenium levels in an endangered marsh bird

Selenium bioaccumulation in aquatic food webs poses risks to wildlife, particularly in wetlands receiving irrigation runoff. The Salton Sea, California’s largest lake, is primarily sustained by agricultural drainage. This drainage creates wetland habitat along the lakeshore that many bird species depend on, including the federally endangered Yuma Ridgway’s rail ( Rallus obsoletus yumanensis ). However, these marshes may pose an ecological trap – attracting rails despite high selenium exposure. We captured rails during the 2020–2023 breeding seasons and compared rail selenium levels within three types of marshes (fed with irrigation runoff, Colorado River water, or groundwater). We collected blood, breast feathers, and head feathers of rails in all three water sources for selenium comparisons. We tagged adult rails with GPS transmitters to locate nests and foraging locations where we collected eggshells, unhatched eggs, and prey. We assessed selenium exposure by collecting multiple prey species commonly eaten by rails in all three water sources. Selenium concentrations varied among sampling locations. Selenium concentrations in most sample types were predominately influenced by water source and marsh inflow velocity (sometimes in combination with marsh size). Distance to inflow, however, did not influence selenium concentrations in any sample type. Selenium concentrations were highest in agricultural-fed marshes compared to river-fed and spring-fed marshes. Increased marsh inflow velocities resulted in lower selenium concentrations. Given the risk of an ecological trap, our results suggest that supplementing wetlands with Colorado River water could mitigate selenium bioaccumulation in Yuma Ridgway’s rails.

California

The U.S. Geological Survey National Water Quality Network—Groundwater—2023

The U.S. Geological Survey (USGS) operates a National Water Quality Network (NWQN) to monitor trends in groundwater quality and assess emerging contaminants of concern. It is a “network of networks” with 81 subnetworks being sampled on a decadal time scale. Each year, eight of the subnetworks are sampled. Subnetworks have 20–30 wells each and include studies of domestic supply wells or shallow groundwater (20–50 feet deep) underlying urban land use or agricultural land use. Currently there are 2,114 wells in the network.

conterminous United States

Integrating habitat suitability and climate constraints to predict nonnative fish invasion risk for U.S. streams and inland lakes

Introduction: Nonnative fishes in streams and inland lakes can substantially alter aquatic ecosystems by degrading habitat conditions, competing with native species, and restructuring food webs. Identifying invasion hotspots can inform proactive management and prevention of nonnative species establishment. Methods: In this study, we identified streams and lakes across the conterminous United States that are vulnerable to invasion by 18 nonnative stream and 28 nonnative lake fish species. Habitat suitability models were developed separately for stream and lake species across nine ecoregions using natural and anthropogenic predictors, and species occurrences were predicted by integrating model results with climate match scores based on comparisons between environmental conditions in species’ native and potential nonnative ranges. We classified areas with both high habitat suitability and strong climate similarity as having high invasion potential and generated hotspot maps by stacking species-level predictions. Results: Florida exhibits the highest invasion risk for both habitat types. Stream hotspots were concentrated near major metropolitan areas, whereas lake hotspots were more widely distributed across the Great Lakes basin and the northeastern U.S. Twelve species were predicted to invade both habitat types, with goldfish ( Carassius auratus ) and pirapitinga ( Piaractus brachypomus ) showing particularly high invasion potential. Discussion: These findings provide a comprehensive assessment of nonnative freshwater fish invasion risk and support targeted monitoring and management strategies.

conterminous United States

pySATSI: A Python package for computing focal mechanism stress inversions

We introduce pySATSI, a Python package for computing earthquake focal mechanism stress inversions. This algorithm can handle a wide variety of types of stress inversion problems with a single script and can duplicate many capabilities of preceding methodologies. We also add new capabilities that include spatiotemporally variable inversion grids, damped stress estimates for clusters with few or no focal mechanisms, and variable fault‐plane ambiguities that the user can assign to individual events. In addition, we added the ability to use damped stress inversions with fault‐plane ambiguity probabilities that are weighted by fault instabilities. Our algorithm is computationally efficient with faster runtimes than previous algorithms, scales well for large datasets, and can be easily parallelized.

Seismological Research Letters

Satellite imagery of the north-central Gulf of Mexico, June 1993-May 1997

This CD contains imagery collected by the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA polar-orbiting weather satellites. The AVHRR provides almost daily coverage of a site at a resolution of approximately 1 km. The data types included are sea surface temperature (SST), water reflectance (REF), and a false-color infrared overview (FCI).

Alabama, Florida, Louisiana, Mississippi

Water table rise sustains carbon release from soils in wetland-dominated landscapes: An intact soil core study

Wetland-dominated landscapes influence carbon cycling through their potential to act as both carbon sinks and sources. Wetlands in low-relief landscapes have dynamic terrestrial-aquatic interfaces that change seasonally with variable surface water and groundwater levels. However, few studies have directly quantified dissolved organic matter (DOM) release and greenhouse gas (CO 2 , CH 4 ) fluxes from wetland soils along terrestrial-aquatic interfaces as they are seasonally re-saturated by groundwater. To estimate groundwater-mediated soil DOM and gas fluxes, we performed laboratory simulations of vertical groundwater rise on intact soil cores collected from four Delmarva bay wetlands located in the Mid-Atlantic United States. At each wetland, one core was collected from within the wetland basin and the other from the transitional zone at the basin edge. Cores were re-saturated with groundwater over 15 days and then kept fully saturated for an additional 25 days. Source groundwater, soil porewater, and exfiltrated surface water samples were collected and analyzed for pH, ORP, DOM concentration, and DOM optical indices. In both the wetland and transition zone cores, porewater DOM concentrations increased over the wet up and were sustained during prolonged saturation. Optical indices shifted from recently produced, microbial-like signatures towards aromatic, terrestrial-like signatures. Fluxes of CO 2 decreased as the duration of soil saturation increased and soil cores switched from CH 4 sinks to sources upon full soil core saturation. Results indicate that groundwater rise sustains carbon mobilization from soils in wetland-dominated landscapes, emphasizing the need to understand how climate-driven changes to groundwater dynamics may affect carbon fluxes along terrestrial-aquatic interfaces.

Delaware, Maryland