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USGS2025

Magnitude, depth and methodological variations of spectral stress drop within the SCEC/USGS Community Stress Drop Validation Study using the 2019 Ridgecrest Earthquake Sequence

We present the first ensemble analysis of the 56 different sets of results submitted to the ongoing Community Stress Drop Validation Study using the 2019 Ridgecrest, California, earthquake sequence. Different assumptions and methods result in different estimation of the source contribution to recorded seismograms, and hence to the source parameters (principally corner frequency, f c ⁠ , spectral stress drop, Δσ, and seismic moment, M 0 ⁠ ) obtained from modeling calculated source spectra. For earthquakes smaller than magnitude (M) 2.5 there is negligible correlation between the f c values obtained by different studies, implying that no present method is reliable using available data. For larger magnitude events, correlation between f c measurements of different studies, within even a small M range is always higher than spectral ⁠Δσ , because the f c measurements simply reflect the underlying physical decrease in f c with increasing M. We model the observed trends of submitted f c with both magnitude and depth. Most methods report an increase in spectral Δσ with M, although a magnitude‐invariant spectral Δσ is within the confidence limits. The depth dependence is smaller and depends on whether a study allows attenuation to vary with source depth; a combination of depth‐dependent attenuation correction, and depth‐dependent shear‐wave velocity can compensate for reported depth trends. We model the submitted values to remove differing M and depth variation to investigate the relative interevent variability. We find consistent relative variation between individual events, and also lower relative spectral Δσ in the northwest of the aftershock sequence, and higher on the cross fault and in the region of main fault intersection. This large‐scale comparison implies that absolute spectral Δσ estimates are dependent on the methods used; studies of different regions or using different methods should not be directly compared and improved constraints on path and site corrections are needed to resolve these absolute spectral Δσ differences.

California↗
USGS2026

ShakeAlert Earthquake Early Warning System performance during the Mw 7.0 offshore Cape Mendocino earthquake

The 5 December 2024 M w 7.0 Offshore Cape Mendocino earthquake was a challenging test of the U.S. West Coast ShakeAlert earthquake early warning system due to its offshore epicenter and limited near‐source station coverage. We analyzed real‐time performance of all components of the ShakeAlert system, including the seismic algorithms (earthquake point‐source integrated code [EPIC] and Finite‐fault rupture Detector [FinDer]), the geodetic algorithm (Geodetic First Approximation of Size and Time–peak ground displacement [GFAST‐PGD]), and network telemetry during the event. EPIC created the first solution for this earthquake 15 s after origin time with an initial magnitude estimate of M 5.6 and location error of 10 km from the Advanced National Seismic System epicenter. An early spurious trigger from station CE.89101 fortuitously maintained location accuracy and, correspondingly, magnitude accuracy. FinDer contributed its first solution at 18 s with a location estimate closer to the seismic network and produced two distinct rupture geometries, leading to minor fluctuations in estimated intensity contours. GFAST‐PGD did not meet alerting thresholds but otherwise performed as expected. Network latencies were <2 s for most stations, supporting the rapid detection of this earthquake by the system. Roughly five million alerts were delivered to cell phone devices in California and Oregon during this event. This was also the first instance of a school district‐wide ShakeAlert‐powered system being activated. Comparisons to recorded seismograms demonstrate that the maximum warning times before potentially damaging shaking (intensity 6+) were in the range of 5–55 s. Although the ShakeAlert system provided accurate solutions and useful alert delivery, this earthquake raised awareness of potential issues within the system, including the need for improved offshore location estimates, a combination of solutions from ShakeAlert servers, and handling of spurious triggers.

California↗
USGS2025

Capturing the uncertainty of seismicity observations in earthquake rate estimates: Implications for probabilistic seismic hazard analysis and the USGS National Seismic Hazard Model

The rate of earthquakes in a region is a fundamental input to Probabilistic Seismic Hazard Analysis. We present a Monte Carlo method for computing that rate from seismicity catalogs while including a range of data and analysis uncertainties. This method is applied to regions for which the b value is assumed to be spatially invariant. Each region is broken down into epochs for which each epoch is estimated to have a uniform magnitude of completeness ( ⁠⁠ M c ). The distribution of earthquake rates for M ≥ M c is determined for each epoch by considering the Poisson likelihood of rates given the number of observed earthquakes with M ≥ M c ⁠ . We use a Monte Carlo process to include the uncertainty in b , ⁠ M c , and individual event magnitudes. The result for each epoch is the joint distribution of the Poisson rate of earthquakes with magnitudes larger than the minimum value used to calculate hazard ( ⁠⁠ M 1 ) and the Gutenberg–Richter b values, which control the extrapolation to other magnitudes. The rate for each region is either the duration‐weighted average over the epochs or, to better capture temporal variations, we also consider mixture models. The mixture models also provide an avenue to allow temporal variations in b values. To implement this joint distribution in a logic tree, we use the mean and 95% confidence branches, each of which is parameterized with an M ≥ M 1 rate and b value. We explore different ways of defining those branches, as well as non‐Gutenberg–Richter branches, and their impact on hazard estimates. The mean hazard, but not the fractiles, is robust with respect to these choices. To illustrate these new methods, we use synthetic data and catalogs from recent U.S. Geological Survey National Seismic Hazard Models for the Central and Eastern United States and for Puerto Rico and the U.S. Virgin Islands.

central and eastern United States, Puerto Rico, U.↗
USGS2024

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↗
USGS2026

Efficient physics‐informed ground‐motion simulations with reduced‐order models: CyberShake implications and high‐resolution site terms for southern San Andreas fault earthquakes

Recent advances in Probabilistic Seismic Hazard Analysis (PSHA) leverage physics‐based ground‐motion simulations to estimate seismic hazard, such as the CyberShake project. However, computational costs quickly escalate when performing PSHA for numerous faults or sites and can become prohibitively expensive. To reduce computational demands, CyberShake uses reciprocity and interpolates physics‐informed corrections from simulations conducted at fewer locations, but the accuracy of these interpolations remains poorly quantified. To quantify the interpolation accuracy, we derive high‐resolution, frequency‐dependent site terms for southern California and compare them with interpolated site terms using the CyberShake approach. We accomplish this by performing a set of earthquake point‐source simulations distributed along the nonplanar fault geometry for the southern San Andreas fault (SSAF) extending from Bombay Beach to Lake Hughes. Using SeisSol, we simulate three minutes of viscoelastic seismic wave propagation for these sources and store the horizontal‐component Green’s functions for 480,000 sites. We then use a scientific machine learning approach based on interpolated proper orthogonal decomposition to construct an accurate reduced‐order model of the Green’s functions to efficiently predict effective amplitude spectra (EAS) for finite‐source rupture models of SSAF earthquakes. Using minimum curvature interpolation with tension, as used in CyberShake, we compare the interpolated site terms against our high‐resolution site terms. We identify local discrepancies with EAS differing by up to a factor of approximately three. Furthermore, we identify locations where unexpectedly high or low ground motions are missed when using the interpolated dataset for these earthquakes. We estimate that our approach may be used within CyberShake to reduce the time‐to‐solution by a factor of 336 for the entire earthquake rupture forecast. Our analysis of physics‐based site terms provides more insight into the seismic hazard due to SSAF ruptures and guides future developments by combining high‐performance computing and reduced‐order modeling techniques for PSHA.

California↗
USGS2025

Near-surface material and topography generate anomalous high-frequency ground motion amplification in Chugiak, Alaska

An ∼3 km long nodal array oriented approximately east–west was deployed in Chugiak, Alaska, by the U.S. Geological Survey during 2021. The array intersects with the permanent NetQuakes station NP.ARTY, where peak ground acceleration (PGA) value of 1.98 g was recorded during the 2018 M w 7.1 Anchorage, Alaska, earthquake, in sharp contrast to the PGA of ∼0.3 g at a site just 4 km to the west. Seismic data for M w 1.8–4.3 aftershocks from the M w 7.1 event recorded by the nodal array confirm the anomalously large ground motions obtained at NP.ARTY as well as similar amplifications at nodes within ∼1 km to the east. Here, we performed 0–10 Hz 3D finite‐difference simulations, including high‐resolution surface topography, to explore the cause of the unexpectedly large amplification. As expected, the simulations computed with a regional 3D tomography velocity model severely underpredict the 0–10 Hz acceleration records at almost all sites. Adding a near‐surface low‐velocity taper to 300 m depth amplifies the accelerations by up to a factor of 5 and enables a reasonable match between the nodal data and simulations at sites to the west of NP.ARTY. However, this model still underpredicts the spectral energy in the area covered by glacial sediments by up to an order of magnitude. The addition of a till layer using a depth‐dependent shear‐wave velocity ( ⁠⁠ V s ) profile along with a homogeneous, 8 m thick low‐velocity layer with V s = 250 m/s representing the kame terraces improves the fit to data to within a factor of 2 at nodes located on top of the glacial sediments. Our study shows that the anomalously large high‐frequency amplification recorded at and near NP.ARTY can be explained by a combination of topographic effects and near‐surface low‐velocity material with amplification effects on the high‐frequency ground motion by up to about 40% and an order of magnitude, respectively.

Alaska↗
USGS2025

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↗
USGS2026

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE↗
USGS2025

Overview of The SCEC/USGS Community Stress Drop Validation Study using the 2019 Ridgecrest earthquake sequence

We present initial findings from the ongoing Community Stress Drop Validation Study to compare spectral stress‐drop estimates for earthquakes in the 2019 Ridgecrest, California, sequence. This study uses a unified dataset to independently estimate earthquake source parameters through various methods. Stress drop, which denotes the change in average shear stress along a fault during earthquake rupture, is a critical parameter in earthquake science, impacting ground motion, rupture simulation, and source physics. Spectral stress drop is commonly derived by fitting the amplitude‐spectrum shape, but estimates can vary substantially across studies for individual earthquakes. Sponsored jointly by the U.S. Geological Survey and the Statewide (previously, Southern) California Earthquake Center our community study aims to elucidate sources of variability and uncertainty in earthquake spectral stress‐drop estimates through quantitative comparison of submitted results from independent analyses. The dataset includes nearly 13,000 earthquakes ranging from M 1 to 7 during a two‐week period of the 2019 Ridgecrest sequence, recorded within a 1° radius. In this article, we report on 56 unique submissions received from 20 different groups, detailing spectral corner frequencies (or source durations), moment magnitudes, and estimated spectral stress drops. Methods employed encompass spectral ratio analysis, spectral decomposition and inversion, finite‐fault modeling, ground‐motion‐based approaches, and combined methods. Initial analysis reveals significant scatter across submitted spectral stress drops spanning over six orders of magnitude. However, we can identify between‐method trends and offsets within the data to mitigate this variability. Averaging submissions for a prioritized subset of 56 events shows reduced variability of spectral stress drop, indicating overall consistency in recovered spectral stress‐drop values.

California↗
USGS2026

Complex carbonate ore mineralogy in the Mountain Pass carbonatite rare earth element deposit, USA

Economic concentrations of rare earth element (REE) minerals are uncommon in the Earth’s crust, with most occurring in carbonatites. Unlike most igneous rocks composed of silicate minerals, carbonatites are dominated by carbonate minerals, some of which can incorporate significant light REEs (LREEs; La, Ce, Pr, Nd). Technological applications of REEs are numerous and they have been identified as some of the most critical mineral commodities to the global economy. The Mountain Pass carbonatite stock in the Mojave Desert of California is the most economically significant REE deposit in the USA and contains a few to tens of percent (by volume) of the carbonate REE ore mineral bastnäsite. Despite the economic significance of the Mountain Pass deposit, studies of its ore mineralogy are limited. Here we present new carbonate ore mineralogy data for a compositionally diverse suite of carbonatitic rocks from the Mountain Pass stock and related dikes. Whole-rock geochemical data are integrated with mineral-scale textural and chemical data obtained by scanning electron microscopy (SEM), electron probe microanalysis (EPMA), and microRaman spectroscopy. Our results document a complex spectrum of REE-bearing carbonate minerals and intermediate mixed-layer structures. Mineral species include bastnäsite [REE(CO 3 )F], hydroxylbastnäsite [REE(CO 3 )OH], parisite [Ca(REE) 2 (CO 3 ) 3 F 2 ], synchysite [Ca(REE)(CO 3 ) 2 F], röntgenite [Ca 2 (Ce,La) 3 (CO 3 ) 5 F 3 ], and sahamalite [(Mg,Fe 2+ )(REE) 2 (CO 3 ) 4 ]. Carbonate ore mineralogy is heterogeneous within and between samples, including at the intracrystal scale. Complexly zoned crystals exhibit as many as five to six different compositional domains and syntaxial intergrowths, commonly with the more Ca-rich varieties (parisite, synchysite) forming crystal rims that surround relict bastnäsite cores. We attribute the phenocryst variability to changes in the chemistry and temperature of primary carbonatite magmas and evolved/exsolved fluids. Cross-cutting vein textures of calcite, celestine and various REE carbonate minerals, interstitial bastnäsite crystallization, breccia blocks lined by fine-grained bastnäsite, and the presence of hydroxylbastnäsite and partially hydroxylated bastnäsite point to the role of secondary hydrothermal processes in REE mineralization. Fluorcarbonate mineral compositions demonstrate that La and Ce are more structurally abundant in bastnäsite, whereas the more Ca-rich species (parisite, synchysite) contain a greater proportion of REE heavier than Pr (Nd, Sm, Eu, Gd) and Y. Atomic ratios of Pr/(Nd + Pr) are likewise variable, with the highest average value for bastnäsite (0.25) compared to parisite (0.22) and sychysite (0.21). This finding has geometallurgical implications, given that current mining operations are focused on recovery of Nd and Pr for high field strength permanent magnets and the Nd/Pr ratios are a critical factor in ore processing and magnet manufacture.

California↗
USGS2025

Pre-eruptive characteristics of “suspect” silicic magmas in Carlin-type Au-forming systems

World-class Carlin-type Au deposits hosted in sedimentary rock were formed when profuse Eocene silicic magmatism swept across northern Nevada in response to arc migration. Carlin-type Au deposits formed along with porphyry/skarn Cu-Mo-W-Au deposits, epithermal Ag-Au deposits, and distal disseminated Ag-Au deposits. But unlike these other Au-bearing deposits that have clear associations with igneous intrusions, Carlin-type ore deposits appear to have formed distant from concealed plutons, and their origin remains controversial. Despite decades of abundant geophysical, geochronological, and geochemical studies suggesting the involvement of magmas, concrete evidence for magmatic involvement is still lacking. Consequently, the involvement of contemporaneous igneous systems remains inferred based on age, proximity, and variable isotopic, geochemical, and geophysical clues. A recent synthesis of deposit models postulates that Carlin-type Au deposits are intrusion-related, but that the causative magmas reside deeper (∼6–12 km) than in typical porphyry and peripheral systems (∼3–5 km), meaning that Carlin-type deposits are perhaps more distal expressions of igneous intrusions. We investigate a collection of “suspect” magmatic systems over a ∼7 m.y. timespan (∼41–34 Ma) that are contemporaneous with and near known Carlin-type ore deposits. We report results of a multifaceted array of in situ geochemical analyses (FTIR, EMP, SHRIMP-RG, LA-ICP-MS) of quartz-hosted melt inclusions, biotite, and quartz to better characterize the pre-eruptive characteristics of these magmas. We also report results of thermobarometry and thermodynamic phase equilibria modeling to help place constraints on magmatic reservoir depths and processes. Rather than a single “flavor” of silicic magma, we observe a surprisingly broad compositional spectrum of rhyolites, with one end of the spectrum exhibiting more arc-like (I-type) characteristics and the other end displaying more post-subduction, thick-crust extensional (A-type) characteristics. This broad compositional spectrum suggests a more complex picture of silicic crustal magmatism operating over a narrow span of time during slab rollback. Despite this spectrum, magmatic systems in this study are consistently ferroan and generally peraluminous, which we interpret as an expression of the relatively elevated geotherm at the time and incorporation of variable amounts of highly peraluminous metasedimentary crustal components. The silicic magma spectrum encompasses a range of mineralization associations, including subduction-related Cu-Mo-W-Au-Ag and post-subduction, thick-crust extensional rare-metal Mo-Sn-W-F-Be-Ag-Au, consistent with the prolific and diverse array of ore deposits that formed during this time. Carlin-type Au deposition appears to be associated with nearly the entire magmatic spectrum. This apparent indifference to silicic magma “flavor” would seem to imply that if magmas are involved in Carlin-type Au deposit genesis, they perhaps do not need to be compositionally specialized and/or possibly are only relevant as heat sources driving circulation to remobilize and redistribute metals.

Nevada↗
USGS2026

Cambrian and Ordovician stratigraphy, conodont biostratigraphy, and microfacies analysis to support 1:24,000-scale geologic mapping of the southern Lake Champlain valley, New York and Vermont

Introduction Geologic mapping in the southern Lake Champlain valley of New York and Vermont (fig. 1) has required evaluation of stratigraphic nomenclature used since the early 1900s. The paleogeography of the Cambrian and Ordovician adjacent to the Adirondack Highlands, the high-relief mountains of Proterozoic igneous and metamorphic rocks of northern New York, has impacted the lithostratigraphic succession, facies changes, and several hiatuses that occur within the package of clastic and carbonate rocks that demonstrates overall deepening consistent from the southern to northern Appalachians. The stratigraphic nomenclature used for the geologic mapping of the Cambrian and Ordovician strata of the study area is derived from evaluation of names put forth by previous workers from areas of northern New York and western Vermont. Descriptions of type localities or type sections and other criteria set forth by the North American Stratigraphic Code (North American Commission on Stratigraphic Nomenclature [NACSN], 2021) were consulted. The North American Stratigraphic Code states that lithostratigraphic units, such as the fundamental unit, the formation, be defined by lithic character and be mappable (NACSN, 2021, Article 24). However, some early workers (Walcott, 1912; Kay, 1937; Fisher and Hanson, 1951; Oxley and Kay, 1959) have defined stratigraphic units based on fossil content, which may or may not be facies dependent, and hence may not be mappable as lithostratigraphic units. Although preservation of older names takes priority in stratigraphic nomenclature (NACSN, 2021, Article 7), some do not have adequately defined stratotypes or are located a distance away with different lithologies than that in the study area. Biostratigraphy can be a helpful tool for understanding correlations and facies changes. Herein, conodont biostratigraphy is utilized to date and correlate separate lithologic units. Further, microfacies analyses of units through inspection of petrographic thin sections provide paleogeographic information that helps in understanding the genesis of geologic units.

New York, Vermont↗
USGS2025

ShakeAlert® version 3: Expected performance in large earthquakes

The ShakeAlert earthquake early warning (EEW) system partners along with U.S. Geological Survey (USGS) licensed operators deliver EEW alerts to the public and trigger automated systems when a significant earthquake is expected to impact California, Oregon, or Washington. ShakeAlert’s primary goal is to provide usable warning times before the arrival of damaging shaking. EEW is most likely to achieve this goal in large‐magnitude earthquakes. In recent years, ShakeAlert has gone through a series of upgrades to its underlying scientific algorithms aimed at improved performance during large earthquakes. Version 3 of this software recently went live in the production system and includes improvements to all algorithms. The main seismic algorithms that detect an earthquake and characterize its location, magnitude, and fault rupture orientation are faster than older versions. Other key changes include: using real‐time geodetic data to characterize the magnitude growth in large earthquakes; the introduction of an alert pause procedure to compromise between speed near the epicenter and improved accuracy at larger distances; and the inclusion of a nonergodic site‐response model in the ground‐motion predictions. ShakeAlert has achieved its primary goal of usable warning times before strong shaking at some locations in real‐time operations in recent M 6 earthquakes. Using offline tests, we demonstrate usable warning times are possible for many sites with peak shaking values of modified Mercalli intensity (MMI) 7–8 in M 7+ earthquakes and also for many MMI 8–9 sites in M 8+ earthquakes. ShakeAlert partners use a variety of MMI and magnitude thresholds in deciding when to alert their users within bounds set by the USGS. Our study shows that there is room to raise the magnitude thresholds up to about M 5.5 without adversely affecting performance in large earthquakes. The ground‐motion criteria are more complex owing to a significant drop‐off in warning times between the MMI 4 and 5 levels of predicted shaking. However, widely used ShakeAlert products, such as the MMI 3 and 4 contour products, can provide sufficiently long warning times before strong shaking in moderate‐to‐great earthquakes to enable a range of protective actions.

Bulletin of the Seismological Society of America↗
USGS2024

The 3D Elevation Program—Supporting New Hampshire’s economy

Introduction The topography of New Hampshire ranges from the Coastal Lowlands to the Eastern New England Upland to the White Mountains region. High-quality statewide elevation data are useful in managing this very diverse landscape. For example, the short coastline, including the Great Bay estuary and the Hampton-Seabrook marshes, is of disproportionately high value to New Hampshire’s tourist economy. The vulnerability of the coast to the effects of sea-level rise underscores the need for accurate, high-quality nearshore topographic elevation data and offshore bathymetric data to effectively manage the coast’s valuable resources, which include important fisheries, habitat, and infrastructure. Another important use for accurate elevation data in New Hampshire is in the evaluation of flood hazards and their potential environmental and infrastructure effects. This evaluation includes mapping of inundation and sediment transport, and assessing the associated costs of flooding. Addressing this challenge requires detailed knowledge of both surface topography and inland bathymetry. Other important activities having a substantial economic element and needing accurate elevation data include geologic resource assessment and hazard mitigation, urban and regional planning, infrastructure and construction management, and cultural resources preservation and management. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional model of the Earth’s surface and aboveground features.

New Hampshire↗
USGS2026

Spatially referenced watershed models for the binational Red–Assiniboine River Basin: Bayesian vs frequentist comparison

Excess nutrient loading remains a leading cause of declining water quality in lakes, estuaries, and coastal waters worldwide, with global economic costs of US$200 billion – US$2 trillion annually from impacts on fisheries, tourism, freshwater resources, and water treatment. Our study focuses on total phosphorus (TP) in Lake Winnipeg and its binational Red-Assiniboine River Basin, where nutrient inputs have degraded water quality and increased cyanobacterial blooms. These changes pose ecological, public health, and economic risks. We applied a spatially referenced watershed model with a hybrid statistical-mechanistic structure partitioning annual nutrient loads into land-use export, land-to-water delivery, and in-reservoir decay. Bayesian and traditional frequentist model calibrations were compared. In the frequentist model, coefficients for agricultural inputs, forests /wetlands, stream channels, precipitation, and reservoir losses were statistically significant, whereas coefficient for wastewater was not. In contrast, all variables were successfully calibrated using the Bayesian approach. Model results delineate TP-export hotspots across the basin, showing that 54–62% of TP originates from the U.S., with agricultural sources ranging 62–72%—highlighting the importance of agriculture-focused Best Management Practices. Given the global relevance of nutrient-driven water-quality challenges, our results highlight Bayesian calibration for robust risk assessment and adaptive nutrient management.

Red–Assiniboine River Basin↗
USGS2025

Origin and evolution of mafic volcanism associated with 3 m.y. of andesite production at the Goat Rocks volcanic cluster, southern Washington Cascade Range

More than 3 m.y. of mafic volcanism near the Goat Rocks volcanic cluster in the southern Washington Cascade Range, USA, lends insight into the evolution of basalts and the subarc mantle at a long-lived, major arc volcanic locus. We contribute field observations, 40 Ar/ 39 Ar dates, paleomagnetic directions, and bulk rock and mineral compositions to characterize nine mafic units that erupted in association with the Goat Rocks volcanic cluster. The time frame of mafic volcanism, ca. 3.6 Ma to 60 ka, encompasses the lifespan of the central volcanic cluster (3.1 Ma to 115 ka), with a lull from ca. 2.7 Ma to 1.4 Ma. A climactic period of voluminous mafic activity and far-traveled lava flows, including construction of the Hogback Mountain shield volcano, coincided with voluminous andesite eruptions from the central volcanic cluster. The basaltic rocks in the Goat Rocks area are calc-alkaline to barely tholeiitic and have high field strength element depletion relative to large-ion lithophile elements characteristic of calc-alkaline basalts (CAB) of the Cascade volcanic arc. Unlike at neighboring andesitic volcanic centers (Mounts Adams, St. Helens, and Rainier), no other mafic end members such as high-aluminum olivine tholeiite (HAOT) or intraplate-type basalt (IPB) are present at or near the Goat Rocks volcanic cluster, although some of the calc-alkaline basalts in this study have IPB-like affinities. The Goat Rocks mafic units exhibit two main temporal trends in composition: (1) the most primitive basalts erupted earlier, compared to less primitive and more evolved compositions later, and (2) high field strength element concentrations are higher in the younger basalt units relative to the oldest two. In contrast to these temporal trends, the mafic units define two compositional groups that recur through time, a low-Sr and a high-Sr group, each with distinct trace element and Sr and Nd isotope ratios. Although radiogenic isotope ratios are generally aligned with High Cascades CAB and HAOT, some extend toward IPB of Mount Adams and Simcoe Mountains volcanic field. Olivine-dominated crystal fractionation at shallow pressure from a small range of parent magma compositions accounts for much of the variation among the basalts and basaltic andesites. A high-pressure fractionation model is plausible for only one of the youngest basalt units (basalt of Walupt Lake volcano). Mafic recharge and crustal assimilation accounts for the incompatible-element enriched composition of basaltic andesites erupted during construction of the largest andesitic centers, further supporting sustained basalt mass flux and thermal energy driving andesite genesis. We model the most primitive members of the Goat Rocks mafic units as partial melts of successively less depleted mantle in time. Variable degrees of fluxing with fluids and melts from subduction explain the distinction between high-Sr and low-Sr groups. We propose that mantle metasomatism by ancestral subduction and fluid-flux melting is heterogeneously distributed through the local subarc mantle and played a greater role in the genesis of the high-Sr basalt group. The limited range of primitive basalt types around the Goat Rocks volcanic cluster contrasts with the much greater diversity of basalts throughout the southern Washington to northern Oregon Cascade arc. On the other hand, the central volcanic cluster encompasses nearly the entire diversity observed at neighboring composite volcanoes. In the case of the Goat Rocks area at least, and perhaps attributable to the entire region, this means that the genesis of diverse intermediate magmas is independent from and does not require vastly different parental basalt compositions.

California, Oregon, Washington↗
USGS2026

Design and function of the Autonomous Benthic Imaging and Surveying System (ABISS) for remote sensing of lake and seabed environments

Lake and seabed environments are home to fisheries and other biota that are important to ecosystems and economies, yet these environments and the species that use them are difficult to accurately assess and monitor. Traditional benthic survey techniques, like bottom trawling used by the U.S. Geological Survey, are limited by substrate constraints, poor spatial resolution and precision, and operational depth limits, hindering accurate assessment of benthic species and habitats. In response to these limitations, the U.S. Geological Survey developed the Autonomous Benthic Imaging and Surveying System, a camera system integrated into underwater vehicles, to capture high-resolution images of the lakebed. The system uses color and stereo cameras to collect imagery, which can be analyzed using computational methods to detect organisms and (or) characterize habitat features, such as geologic substrate types. The system has been integrated into autonomous underwater vehicles and into an underwater housing used by self-contained underwater breathing apparatus (SCUBA) divers. Although the engineering of the system was motivated by the need for data collection in the Great Lakes, it has potential to collect high quality data in any aqueous setting with sufficient water clarity and safe operating conditions. The Autonomous Benthic Imaging and Surveying System can operate across diverse depths and light conditions to map and quantify ecological patterns that were difficult or impossible to assess using traditional methods. The Autonomous Benthic Imaging and Surveying System offers the potential for accurate and precise monitoring and assessment of native benthic biota, invasive species, and habitat, potentially providing natural resource managers with improved information to support decision making about benthic resource management.

Great Lakes↗
USGS2025

The U.S. Geological Survey, the U.S. Department of Defense, and the U.S. Intelligence Community—100 years of mapping and remote sensing collaboration, 1879–1979

Introduction The U.S. Geological Survey (USGS)—a Federal civilian agency—and U.S. military and intelligence agencies collaborate on mapping and remote sensing and have since the establishment of the USGS. The organizations exchange data and information and share technology to further their respective missions in service to the American people. Often referred to as examples of “good government” or “whole of government,” the collaboration avoids costly duplication and maximizes time and effort for the government sectors. Collaboration between these sectors started with the original mapping of the United States and evolved to include remote sensing after the advent of aerial photography and satellite imagery.

Circular↗