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Evidence for low effective stress within the crust of the subducted Gorda plate from the 2022 December Mw 6.4 Ferndale earthquake sequence

Stress levels on and adjacent to megathrust faults at seismogenic depths remain a key but difficult to constrain parameter for assessing seismic hazard in subduction zones. Although strong ground motions have been observed to be generated from distinct, high-stress regions on the downdip end of the megathrust rupture areas in many great earthquakes, we lack direct constraints on the stress level in the lower seismogenic portion of the Cascadia megathrust. On 2022 December 20, a M w 6.4 strike-slip earthquake occurred near Ferndale, California in southern Cascadia and likely ruptured the Gorda slab crust in the lower seismogenic portion, providing an opportunity to assess the stress level in this region. Here, we relocate the Ferndale mainshock and the first two weeks of aftershocks using a high-resolution 3-D velocity model and estimate rupture dimensions, directivity, and stress drop for several M w 4-5 aftershocks and recent earthquakes. The aftershocks define a strike-slip fault in the slab crust striking ENE, consistent with the mainshock focal mechanism. The orientation of this fault is about 45 ° off the ideally oriented fault plane given the stress state in the slab. The aftershock zone is extensive and broad in the forward direction of the mainshock rupture but still constrained within the volume of high Vp/Vs within the slab crust. Our stress drop estimates are generally lower for M w 4-5 earthquakes located within the slab crust compared to those a few km deeper in the slab mantle. Combined, our results support a relatively low effective stress level in the vicinity of the megathrust in the lower portion of the seismogenic zone in southern Cascadia, likely due to elevated fluid pressures. Consequently, the ground motion in the onshore region above this low-stress seismogenic portion in southern Cascadia may not be as intense as that observed during great earthquakes in other subduction zones.

California

Wangyanite, PdNi8S8, a new Pd end-member mineral of the pentlandite group from the J-M reef, Stillwater Complex, Montana, USA

Wangyanite (IMA2024-008a), ideally PdNi 8 S 8 , is a Pd end-member mineral of the pentlandite group that was discovered in the J-M reef of the Stillwater Complex, Montana, USA. Wangyanite occurs as anhedral-subhedral granular crystals 200–400 µm in size, associated with isoferroplatinum, braggite, pentlandite, and chalcopyrite interstitial to plagioclase grains within anorthosite. Wangyanite exhibits a yellowish brown color with a black streak and a metallic luster. It is brittle with uneven fractures, and has a calculated density of 5.14 g/cm 3 . The mineral does not show discernible pleochroism, bireflectance, or anisotropy. It has an average composition of 9.95 wt.% Pd, 31.95 wt.% Ni, 25.02 wt.% Fe, 0.57 wt.% Co, 31.74 wt.% S, totaling 99.23 wt.%. The empirical formula, based on eight sulfur atoms per formula unit, is (Pd 0.76 Co 0.08 ) Σ0.84 (Ni 4.39 Fe 3.60 ) Σ7.99 S 8 . Wangyanite has a cubic cell with a space group of Fm -3 m (#225), having lattice parameters of a = 10.1167(12) Å, V = 1035.4(4) Å 3 , and Z = 4. Its crystal structure has been solved by single-crystal three-dimensional electron diffraction study. The strongest X-ray diffraction lines of wangyanite are claculated at [ d in Å ( I %)( hkl )]: 5.841(14.03)(111), 3.050(100)(311), 1.947(29.16)(115,333), 1.264(11.66)(800), 3.577(8.79)(220), 2.920(20.82)(222), and 2.321(9.34)(331). Wangyanite shares the same crystal structure as pentlandite, but the octahedrally coordinated site is mainly occupied by Pd in wangyanite. Based on the textural features and previous experimental Pd-Fe-Ni-S phase system, wangyanite could form by peritectic reaction between braggite, pentlandite and sulfide liquid. These mineral associations are stable in a Ni-Pd-rich sulfide melt system at about 550 °C or even lower temperature. Therefore, wangyanite can potentially serve as an indicator of the presence of Pd-rich residual melts. The mineral is named in honor of Prof. Christina Yan Wang, a well-known researcher on platinum-group element (PGE) occurrences and enrichment mechanisms in mafic-ultramafic intrusions, notably those deposits related to the Emeishan large igneous province in China.

Montana

Key minerals in energy transmission

The electrical grid relies on minerals with unique properties to transform, transmit, and convert electricity. Transmission needs are growing—to support the expansion of data centers and link diverse energy resources into the grid. This expansion will require greater quantities of minerals. Although some minerals are produced in the United States, the United States relies on imports for others. This infographic shows the key minerals that support energy transmission, and how reliant the United States is on imports for these minerals.

General Information Product

SCEC/USGS Community Stress Drop Validation Study: How spectral fitting approaches influence measured source parameters

Spectral source parameters used to estimate an earthquake’s stress drop (Δσ) can vary significantly across measurement approaches. The Statewide California Earthquake Center/U.S. Geological Survey Community Stress-Drop Validation Study was initiated to compare source parameter estimates, focusing initially on a dataset from the 2019 Ridgecrest earthquake sequence. As part of that validation effort, here we focus on one potential source of uncertainty: whether spectral fitting approaches alone, applied to a common set of spectra from the 2019 Ridgecrest sequence result in different source parameter estimates. By using a common set of benchmark spectra analyzed across a consistent frequency band of 1–40 Hz, we eliminate many sources of variability. A subgroup of validation study participants volunteered to estimate the low-frequency displacement (Ω0) and corner frequency ( f c ) by fitting a smooth function to benchmark displacement spectra. Participants used linear- or log-sampled spectra, assumed a Brune or Boatwright spectral model, and applied different misfit criteria. We compare 17 approaches used to estimate Ω0, f c , and Δσ for 54 earthquake spectra. Our results reveal that 35% of events have Δσ estimates within a factor of two, whereas others exhibit variations exceeding an order of magnitude. The variability in Ω0 and f c can largely be attributed to whether a spectrum is consistent with the smooth function of an idealized simple crack model. The trade-off between Ω0 and f c may be more pronounced when using linearly sampled spectra, as higher frequency spectral bumps control the fits. As expected, methods that assumed a Boatwright model tended to have lower Ω0 and somewhat higher f c compared to those assuming a Brune model, although resulting Δσ estimates are similar. When compared to the overall validation study results, the fitting approach alone may account for between 5% and 90% (25% on average) of the total variability in spectral Δσ.

California

Distributed faulting of the northern West Napa Fault Zone in Napa Valley, California

Mapped surface ruptures from the 24 August 2014 M w 6.0 South Napa earthquake in the Napa Valley, California, show a 2‐km‐wide zone of distributed faulting in the southern and central West Napa fault zone (WNFZ). In the northern WNFZ at Hendry Winery (HW), however, the mapped 2014 surface ruptures encompass an ∼100‐m‐wide zone, implying significant narrowing of the near‐surface fault zone to the north. We present a tomographic shear‐wave velocity ( ⁠⁠ V S ) model and guided‐wave data that indicate the northern WNFZ is at least 400‐m wide, with multiple near‐surface fault traces. Our V S model shows that the 2014 surface ruptures are underlain by discrete low‐velocity zones (LVZs), and coincident guided‐wave data show that the LVZs carry fault‐zone guided waves. If nearby (<500 m) mapped faults to the east of HW are part of the WNFZ, the entire WNFZ is more than 1 km wide in the northern Napa Valley. WNFZ guided waves travel up to 38% slower than S body waves, and low‐strain guided‐wave shaking is up to five times stronger than the associated body‐wave shaking. Our data suggest that guided waves, traveling along distributed faults, may result in an increased shaking hazard over a 1‐km‐wide area of the northern Napa Valley during future significant earthquakes. In places, the 2014 surface ruptures were difficult to find one year after the earthquake, and paleoseismic trenching showed only weak evidence for faulting, which may not have been identified in trenches if the locations of the 2014 surface ruptures had not been previously mapped ( Prentice et al. , 2015 ). Guided‐wave and V S tomography data, however, show strong evidence for faulting beneath the 2014 surface ruptures and at locations to the east. Although paleoseismic trenching is the gold standard for identifying near‐surface faulting, methods such as peak ground velocities of guided waves may better identify immature near‐surface fault traces.

California

The importance of nodal plane orientation diversity for earthquake focal mechanism stress inversions

Inversions of earthquake focal mechanisms are among the most accessible and reliable methods for determining crustal stress. However, the use of this method varies widely, and assumptions that underpin it are often violated, potentially compromising stress estimates. We investigate the consequences of violating the little-studied assumption that the focal mechanisms have diverse orientations. Our approach is to employ data-informed synthetic mechanisms, with nodal plane orientations defined by recent earthquake lineaments in the Midland Basin, western Texas, and rakes consistent with slip in the mapped stress field. Using both the traditional stress inversion method that assumes constant shear stress magnitudes on the causative faults as well as a recently published variable shear stress method, we show that low fault plane diversity can cause maximum horizontal stress ( S Hmax ) orientation and relative principal stress magnitude (faulting regime) estimates to differ markedly from the true values. This problem is compounded for catalogs with even modest amounts of noise (≤15°) or few (e.g., 20) mechanisms. Significantly, traditional approaches for quantifying uncertainty such as the bootstrap can severely underestimate the true uncertainty under these circumstances. To remedy this, we provide simple tools to quantify nodal plane orientation diversity and stress inversion reliability.

Geological Society of London Special Publications

Analyzing multi-year nitrate concentration evolution in Alabama aquatic systems using a machine learning model

Rising nitrate contamination in water systems poses significant risks to public health and ecosystem stability, necessitating advanced modeling to understand nitrate dynamics more accurately. This study applies the long short-term memory (LSTM) modeling to investigate the hydrologic and environmental factors influencing nitrate concentration dynamics in rivers and aquifers across the state of Alabama in the southeast of the United States. By integrating dynamic data such as streamflow and groundwater levels with static catchment attributes, the machine learning model identifies primary drivers of nitrate fluctuations, offering detailed insights into the complex interactions affecting multi-year nitrate concentrations in natural aquatic systems. In addition, a novel LSTM-based approach utilizes synthetic surface water nitrate data to predict groundwater nitrate levels, helping to address monitoring gaps in aquifers connected to these rivers. This method reveals potential correlations between surface water and groundwater nitrate dynamics, which is particularly meaningful given the lack of water quality observations in many aquifers. Field applications further show that, while the LSTM model effectively captures seasonal trends, limitations in representing extreme nitrate events suggest areas for further refinement. These findings contribute to data-driven water quality management, enhancing understanding of nitrate behavior in interconnected water systems.

Alabama

Submarine avalanche deposits hold clues to past earthquakes

Earthquakes and other natural events sometimes shake the seafloor near coastlines severely enough to cause underwater avalanches that rush down steep slopes, scouring the seabed and carrying sediment to greater depths. These fast-moving sediment-laden flows, called turbidity currents , have at times damaged underwater infrastructure like pipelines and communications cables, as they did, for example, in snapping transatlantic cables off the coast of Newfoundland after the 1929 Grand Banks earthquake.

EOS Transactions

Digitizer Suite: The Albuquerque Seismological Laboratory Digitizer Testing Suite

Laboratory testing of digitizers and seismometers helps ensure that prior to deployment the instrumentation can produce high quality data and is operating within specifications. In this work we detail the software package called: the Albuquerque Seismological Laboratory (ASL) Digitizer Test Suite. This Java software package provides several algorithms to verify various performance parameters of digitizers commonly used for recording analog seismic instruments. The goal of these tests is not to be exhaustive, but to identify common failures that could compromise the integrity of seismic data being recorded on the digitizer. For example, Sandia National Laboratories (e.g., Slad and Merchant, 2018) routinely do comprehensive testing of digitizers for various monitoring missions. While these tests reports are valuable for comprehensively characterizing a recording system, it would be resource intensive to conduct such tests on every seismic recorder used in a network. We focus on tests that include ways to estimate the sensitivity, timing, self-noise, and clip-level of the digitizer, as well as the fidelity of the signal being recorded. The software is publicly available and provides a way for the community to verify the integrity of a digitizer using a minimum amount of outside equipment.

Seismological Research Letters

A 10-year continuous daily simulation of chloride flux from a suburban watershed in Fairfax County, Virginia, USA

Increasing levels of chloride in surface water are associated with detrimental effects on water quality, aquatic ecosystems, infrastructure, and human health. Numerous mass-balance studies have inferred watershed transport processes by interpreting chloride inputs and outputs, but few represent internal dynamics explicitly. We constructed a coupled water/chloride mass balance model to gain insights into storage, residence time, and transport processes in a 10-km 2 urban watershed. The model, which operates over a 10-year period at a daily time scale, represents storage in a dynamic soil-moisture reservoir, quick-flow runoff from storm events, and slow-flow runoff that sustains streamflow in dry weather. The calibrated model accurately represented (a)the observed transition from a streamflow enrichment regime in cold months to a dilution regime in warmer months, (b) the observed tendency for late-summer concentrations to be higher after winters with heavy snowfall, and (c) a period-of-record downward trend in chloride concentration likely associated with a downward trend in annual snowfall. Estimated chloride inputs averaged 195 metric tons per year, while the average output was 270 metric tons per year. In contrast, estimated storage was only 107 metric tons. The estimated mean residence time in groundwater was 1.27 years. This short residence time indicates that efforts to reduce inputs will manifest as decreased concentrations in streamflow on a management-relevant time scale of several years. The coupled mass balance model yielded insights into internal watershed dynamics that would not be possible from simple input/output analysis; such models can be useful tools for gaining insight into small watershed hydrology and pollutant transport.

Virginia

Microplastics undergo fragmentation during pressurized membrane filtration

Low-micrometer microplastics (<10 μm) have been detected in drinking water, driving growing interest in using pressure-driven membrane filtration to remove these particles and ensure drinking water safety. However, little attention is paid to the fate of microplastics concentrated in the filtration byproduct. In this study, using well-defined polystyrene (PS) and poly(methyl methacrylate) microspheres as model particles, we observed microplastic fragmentation during nanofiltration and the subsequent release of smaller fragments. After operating for 3 h at 20 bar, 67.9 ± 8.0% of the PS spheres in the concentrate, based on particles counted in selected fields of view, were transformed into fractured particles. The characteristic Raman band signals of microplastics were significantly weakened after fragmentation, leading to detection challenges. To address this, a data processing algorithm was developed to identify PS fragments as small as 1 μm. Preliminary statistical analysis reveals that within the tested pressure range, operation time has a stronger influence on fragmentation than pressure magnitude alone and that fragmentation is further governed by the intrinsic mechanical properties of the tested model polymers. This work provides direct evidence that pressure-driven membrane processes induce microplastic fragmentation and highlights the environmental risks associated with the discharge of fragmented microplastics into the concentrate.

Environmental Science & Technology Letters

Quantifying methane emissions from a rich fen with uncrewed aircraft systems in boreal Alaska

Thawing of permafrost in northern latitudes is accelerating, potentially releasing substantial amounts of methane (CH 4 ) as forested permafrost plateaus transition into wetlands. This ecosystem shift alters the carbon exchange between the soil and atmosphere, influencing the permafrost-carbon feedback. Monitoring these changes may require measurement platforms operating across varied spatial and temporal scales. Recent advancements in small uncrewed aircraft systems (sUAS) enable high resolution CH 4 flux quantification in remote, complex terrains; however, comparisons with established methods such as eddy covariance flux towers remain limited. We used a hexacopter sUAS to quantify CH 4 emissions from the Alaska Peatland Experiment, a wetland within the Bonanza Creek Experimental Forest. Using an ensemble of methods to define the background CH 4 concentration, along with near surface emissions from soil chambers, helped constrain our flux estimates. The sUAS method yielded an average flux of 0.0077 ± 0.0019 mol s −1 CH 4 , within a factor of two concurrent tower-derived total source flux estimates (0.0036 ± 0.00042 mol s −1 CH 4 ). To assess spatial drivers of observed fluxes, we conducted a 2D footprint analysis and overlaid the results with high-resolution hyperspectral land cover classification, quantifying vegetative contributions within each footprint. This revealed higher fen representation in sUAS measurements (73.8%) than in tower footprints (58.8%), and lower tussock meadow representation (15.6% and 30.3%, respectively). These differences were consistent with known variation in vegetation-specific CH 4 emissions. Our results highlight that combining footprint modeling with land cover characterization can enhance interpretations of CH 4 fluxes and guide cross-platform comparisons.

JGR Atmospheres

Earthquake ground-motion model adjustments for the San Francisco Bay area

We develop adjustments to ergodic ground‐motion models (GMMs) to improve their performance in the San Francisco Bay Area (SFBA). GMMs are widely used in hazard assessments to estimate characteristics of ground shaking based on known properties of the source, path, and site. Such models are often developed using datasets containing records from various regions, resulting in models that represent median ground‐motion behavior, which may not adequately represent ground motions within subregions. This is true for the SFBA, where ground motions attenuate more rapidly with distance than in many other parts of California that dominate GMM databases. To support improved seismic hazard estimates in the SFBA, we calculate regional constants and anelastic attenuation coefficient adjustments relative to two commonly used ergodic GMMs: BSSA14 ( Boore et al. , 2014 ) and ASK14 ( Abrahamson et al. , 2014 ). These adjustments are obtained for a suite of ground‐motion intensity measures (peak ground acceleration, peak ground velocity, and 5%‐damped pseudospectral acceleration at oscillator periods ranging from 0.075 to 10 s) using mixed‐effects regression. Use of the regionally adjusted models reduces the overall bias by up to 0.5 natural log units for BSSA14 and up to 0.6 natural log units for ASK14. We demonstrate one application of our attenuation adjustments and their implications in an earthquake early warning case study of the 2014 M 6.0 South Napa earthquake. The predicted extent of shaking using the adjusted models better matches observed shaking at large source‐to‐site distances, especially for lower shaking intensities, thus potentially reducing overalerting. We encourage the use of our model adjustments when ergodic models are considered for seismic hazard studies in the SFBA.

California

To heal or not to heal?: 2. The moment-recurrence time behavior of repeating earthquakes in the 2011 Prague, Oklahoma aftershock sequence is consistent with laboratory healing rates

The timing and failure conditions of an earthquake are governed by the interplay between fault reloading and restrengthening. The moment-recurrence time behavior of repeating earthquakes can give observational estimates of fault healing rates; however, it is difficult to link these observed healing rates to laboratory studies of frictional healing in part because of uncertainty in lithology. Here, we study the 2011 Prague earthquake sequence, which includes repeating earthquakes in the Arbuckle group and the granitic basement, and compare them to laboratory experiments on samples of the Arbuckle and Troy granite (representative of the basement rock) (Okamoto et al., 2025, https://doi.org/10.1029/2024JB030573 ). We find three spatially distinct groups of repeating earthquakes with different moment-recurrence behavior: (a) constant moment-recurrence time in the Arbuckle group, (b) scattered moment-recurrence time at the intersection of the foreshock-mainshock fault in the granitic basement, and (c) moment-predictable behavior outside of the foreshock-mainshock fault intersection also in the granitic basement. Our observation of stagnant healing for repeating sequences in the Arbuckle group is consistent with laboratory observations of low healing rates for moderately high pore fluid pressures in Arbuckle samples. For the moment-predictable group, the source radius that is required in order to match healing rates is consistent with source radius estimations when taking into account reasonable attenuation of the P- pulse width. Overall, we observe diverse healing behaviors in the seismic families that are consistent with laboratory healing rates, providing seismic evidence that contact-scale frictional mechanisms are relevant to large-scale earthquake dynamics.

Oklahoma

Indications of preferential groundwater seepage feeding northern peatland pools

Groundwater seepage from underlying permeable glacial sedimentary structures, such as eskers, has been hypothesized to directly feed pools in northern peat bogs. These hypotheses directly contradict classical peat bog models for ombrogenous systems, wherein meteoric water is the sole water input to these systems. Variations in the underlying mineral sediment in contact with the peat imply that unrecognized hydrogeologic connectivity may exist with pools in northern peat bogs, particularly where high permeability materials are in contact with the peat. Seepage dynamics originating from these structural variations were investigated using a suite of thermal and hydrogeophysical methods deployed around pools in a peat bog of northeastern Maine, USA. Thermal characterization methods mapped anomalies that were confirmed as matrix seepage or preferential flow pathways (PFPs). Geochemical methods were employed at identified thermal anomalies to confirm upwelling of solute-rich groundwater. Conduits around pools were associated with surficial terminations of suspected peat pipes, based on the inference of pathways extending down into the peat, that focus flow through PFPs in the peat matrix. Discharge also occurred through the peat matrix adjacent to suspected pipe structures and matrix seepage rates were quantified using analysis of diurnal temperature signals recorded at multiple depths. Seepage rates, with a maximum of nearly 0.4 m/d, were measured at localized points around pools. Periods of synchronized temperatures paired with highly muted diurnal temperature signals, recorded in diurnal temperature with depth data, were interpreted qualitatively as activation of strong upward discharge rates through suspected peat pipes. These time periods correlated strongly with local precipitation events around the peatland. Ground-penetrating radar surveys revealed discontinuities in the low permeability glacio-marine clay at the mineral sediment-peat interface, interpreted to be regional glacial esker deposits, which were located beneath and around pools. Heat tracing, specific conductance contrasts, seepage rates, and trace metal concentrations all imply groundwater seepage originating from underlying permeable glacial esker deposits and directly sourcing pools. Preferential groundwater inputs into northern peat bogs may play a key role in developing and maintaining pool systems, with enhanced solute transport impacting peatland ecology, water resources, and carbon cycling.

Maine

Beaver dam analogs as nature-based solutions to mitigate snowpack loss in northern New Mexico

Reductions in snow have left many streams in northern New Mexico dry or with very low flows during the summer. Base flow, defined as the contribution of groundwater to streamflow, can sustain streamflow during the summer and during drought conditions. Beaver dam analogs can be used to “slow the flow,” or increase the infiltration of rain-based runoff to replenish shallow groundwater reservoirs and increase base flow and potentially increase summertime streamflow.

New Mexico

Overcoming the data limitations in landslide susceptibility modelling

Data-driven models widely used for assessing landslide susceptibility are severely limited by the landslide and environmental data needed to create them. They rely on inventories of past landslide locations, which are difficult to collect and often nonrepresentative. Furthermore, susceptibility maps are most needed in regions without the means to assemble an inventory. To overcome these challenges, we develop a method for assessing shallow landslide susceptibility based on a probabilistic morphometric analysis of the landscape’s topography, rather than the characteristics of landslides. The model assumes that hillslopes with higher relief and gradient compared to the surrounding landscape are more prone to landslides. We demonstrate the superior performance of this approach over contrasting data-driven models across the northwestern United States. As our morphometric model only requires elevation data, it overcomes the major limitations of data-driven models and facilitates the creation of effective susceptibility models in areas where it was previously unfeasible.

Oregon, Washington

Predicted exposure of communities in southeastern United States to climate-related coastal hazards

A rigorous analysis of 21st Century multi-hazard exposure for U.S. Southeast Atlantic coastal communities indicates that up to 70% of residents will be exposed daily to shallow and emerging groundwater by ~2100, 15 times higher than from surficial flooding alone. This threat further exacerbates other coastal stressors, such as flooding, subsidence, and beach erosion, that impact these vulnerable coastal communities and ecosystems under expected future climate change scenarios.

Florida, Georgia, North Carolina, South Carolina,