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USGS2024

Shallow faulting and folding beneath south‐central Seattle, Washington State, from land‐based high‐resolution seismic‐reflection imaging

The geologic framework of the Seattle fault zone (SFZ) has been extensively studied, but the structure and fault strand locations in the central portion of the fault zone through the city of Seattle have remained controversial. Much of what is known about the SFZ has come from light detection and ranging (lidar)‐topographic surveys and paleoseismic investigations of fault scarps primarily west of Puget Sound, regional gravity and aeromagnetic modeling, and multiscale marine seismic imaging in waters both west and east of Seattle. We analyze ∼24 km of land‐based P ‐wave seismic‐reflection data that fill in a critical gap in our understanding of the SFZ beneath the urban areas of West Seattle, south‐central Seattle, and Mercer Island. These data image deformed strata in the upper 1 km, including upwarped Tertiary rock and younger sediments. Collectively, these data provide evidence for multiple Quaternary‐active thrust faults, back thrusts, and sub‐basins within the SFZ beneath the city of Seattle. The results indicate that multiple and potentially active back thrusts in the upper ∼500 m extend across the length of the SFZ and the entire urban corridor that may be analogous to those on Bainbridge Island west of Puget Sound.

Washington↗

USGS2026

Small-volume tephra deposits of the May 1924 explosions from Halemaʻumaʻu, Kīlauea volcano, and their origin

More than 50 explosive eruptions occurred from Halemaʻumaʻu at Kīlauea volcano over 17 days from May 11 to 27, 1924. Ballistics weighing as much as 14,000 kg were ejected and most landed within 2 km of the vent. Fine ash made up a major component of the tephra and was dispersed tens of kilometers downwind. Draining of the Halemaʻumaʻu lava lake occurred in late February 1924, with the crater floor eventually subsiding by a further ∼70 m (to ∼180 m below the crater rim) by the time the first explosions took place during the night of May 10–11. The largest explosions occurred on May 17–18 and smaller explosions continued until May 27, at which point Halemaʻumaʻu had more than doubled in width and depth. The explosions generated plumes reaching up to ∼10 km high with ballistics ejected up to 2 km from the crater. Almost 100 years later, we investigate and characterize the preserved tephra deposits within ∼3 km of the 1924 crater rim. Grain size and shape analyses were performed on 202 samples collected from 34 tephra profiles using dynamic image analysis, with a subset of layers from nine tephra profiles used for componentry (200 grains per layer in the 0.5–1 mm size fraction). Additionally, we characterize the average diameters (using the five largest clasts) at 216 locations and measure the average diameters of 2291 ballistics (largest per ∼100 m 2 area). Physical descriptions from fieldwork and grain size distributions were used to subdivide the tephra layers into five lithofacies: coarse homogeneous, fine homogenous, red ash, accretionary lapilli-bearing, and finely laminated. Grain size versus shape data show a range of values that demonstrate most grains are dense, smooth, and equant, in alignment with lithic clasts dominating the tephra componentry. The fine grained and accretionary lapilli-bearing nature of some of these lithofacies confirms that water influenced the style of the explosions. However, we also note juvenile clasts within many of the tephra layers, indicating that many of the layers were formed during phreatomagmatic explosions (sensu stricto), despite the eruptive mechanism being dominantly phreatic. Juvenile clasts are more abundant higher in the tephra profiles, suggesting that juvenile magma was more involved later in the explosive sequence. Thermal and hydrologic modeling indicate that groundwater inflow into a short-lived, small-diameter volcanic conduit (10-m to 120-m-diameter used for modeling) during the 78–85 days preceding the first explosion provides a physically plausible mechanism for this eruptive sequence.

Hawaii↗

USGS2024

U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33

Executive Summary Earthquakes represent one of our Nation’s most significant and costly natural hazards, with estimated annual loses from earthquakes close to $15 billion in 2023. Over the past two centuries, 37 U.S. States have experienced an earthquake exceeding a magnitude of 5, and 50 percent of States have a significant potential for future damaging shaking; these statistics speak to the need for nationwide interest and investment in earthquake hazard characterization and risk reduction. Authorized under the Earthquake Hazards Reduction Authorization Act, the U.S. Geological Survey (USGS) Earthquake Hazards Program (EHP) provides the scientific information, situational awareness, and knowledge necessary to reduce deaths, injuries, and economic losses from earthquakes and earthquake-induced tsunamis, landslides, and soil liquefaction. The EHP supports activities in three focused topical areas: (1) earthquake monitoring, (2) hazard assessment, and (3) applied research, using the results of each—and the coordination among them—to further support risk translation and communication in regions at risk nationwide. For earthquake monitoring, the Advanced National Seismic System (ANSS), a cooperative effort of USGS networks, university partner regional seismic networks, and real-time geodetic networks, collects and analyzes data on earthquakes; issues timely, reliable notifications of their occurrence and impacts; and provides data for earthquake research, hazard, and risk assessment as a foundation for building an earthquake-resilient Nation. The USGS-operated ShakeAlert Earthquake Early Warning system is a recent addition to EHP’s ANSS infrastructure. In the realm of earthquake hazard assessment, the EHP contributes to earthquake risk mitigation strategies by developing the National Seismic Hazard Model and maps, and other related products, that describe the likelihood and potential effects of earthquakes nationwide, especially in the urban areas of highest risk. The EHP also conducts research on the causes, characteristics, and effects of earthquakes and prioritizes work that directly increases the accuracy and precision of earthquake hazards assessments, earthquake forecasts, and earthquake monitoring and situational-awareness products and that supports the Nation’s earthquake mitigation practices. Bridging the EHP’s efforts across research, hazard assessments, and earthquake monitoring is a broad and comprehensive collection of earthquake information products, including the National Seismic Hazard Model, ShakeAlert, and other products describing impact, such as ShakeMap and PAGER (Prompt Assessment of Global Earthquakes for Response), which have been developed and integrated into EHP’s real-time monitoring systems. EHP funds external partners to carry out many important collaborative activities through an active external grants program—one of the largest in the USGS—and through cooperative agreements with other partners such as the university-operated regional seismic networks, funded as part of the ANSS. To continue its support of earthquake hazard characterization and risk reduction, the EHP aims to strengthen its foundational products and practices while positioning itself to respond to the evolving needs of the Nation and follow best practices of the scientific community. This document describes a strategy for the program to ensure it can meet these demands. The foundational priorities outlined in this strategy represent those activities that remain critical to the core functionality of the program and those that can be supported under current fiscal year 2024-level appropriations. Priorities described as aspirational are important for future growth, and to maintain the program’s position as a leading global resource in earthquake science, but would require increases in appropriated funding to be fully realized. Across the program’s portfolio of activities, several major themes have been identified as the most critical activities to advance EHP science over the coming decade. Together, these activities provide the framework necessary to integrate critical hazard characterization and risk reduction activities across the program. They provide the structure for research to advance the understanding of where, when, and why earthquakes occur and how we can use improved knowledge to drive short-term and actionable forecasts of seismic activity. They expand the usefulness of critical earthquake products and advance the sophistication of those products to keep pace with the rapidly evolving needs of an ever-expanding user base while maintaining the position of the USGS as a global leader in earthquake science. Focus on system-level science. Establish an automated earthquake-processing pipeline. Enhance the accuracy and reliability of the ShakeAlert Earthquake Early Warning system and plan for extension to other regions. Implement time-dependent earthquake forecasting. Develop physically realistic models. Expand computational capacity. This science strategy is organized into three primary sections. The first section provides an overview of the EHP and its budget, governance, and program council. Readers familiar with the program may wish to focus on the second section, which describes the core of the science strategy, including priorities across each of the EHP’s major program activities in monitoring, hazard assessment, and targeted research. The third section outlines science priorities that cut across program activities, including those involving collaborations external to the EHP.

American Samoa, Guam, Northern Marianas Islands, U↗

USGS2024

Classification of lakebed geologic substrate in autonomously collected benthic imagery using machine learning

Mapping benthic habitats with bathymetric, acoustic, and spectral data requires georeferenced ground-truth information about habitat types and characteristics. New technologies like autonomous underwater vehicles (AUVs) collect tens of thousands of images per mission making image-based ground truthing particularly attractive. Two types of machine learning (ML) models, random forest (RF) and deep neural network (DNN), were tested to determine whether ML models could serve as an accurate substitute for manual classification of AUV images for substrate type interpretation. RF models were trained to predict substrate class as a function of texture, edge, and intensity metrics (i.e., features) calculated for each image. Models were tested using a manually classified image dataset with 9-, 6-, and 2-class schemes based on the Coastal and Marine Ecological Classification Standard (CMECS). Results suggest that both RF and DNN models achieve comparable accuracies, with the 9-class models being least accurate (~73–78%) and the 2-class models being the most accurate (~95–96%). However, the DNN models were more efficient to train and apply because they did not require feature estimation before training or classification. Integrating ML models into benthic habitat mapping process can improve our ability to efficiently and accurately ground-truth large areas of benthic habitat using AUV or similar images.

Michigan, Wisconsin↗

USGS2026

Effects of a low-lipid diet on the gut microbiome and head kidney transcriptome of juvenile Chinook Salmon

Objective Pacific salmon Oncorhynchus spp. reared in production hatcheries are typically fed high-lipid, energy-dense diets to achieve large size and high body condition prior to release. In contrast, juveniles in natural environments tend to consume low-lipid, high-protein diets, and fish reared for research or conservation purposes are sometimes fed diets that are formulated to mimic natural diets and promote wild-like phenotypes. Understanding how these alternative diets affect fish health beyond growth and body condition could ultimately contribute to improving hatchery fish fitness. Methods In this work, we evaluated changes in the fecal microbiome and gene expression of juvenile Chinook Salmon O. tshawytscha on a standard high-lipid hatchery diet versus a low-lipid diet formulated to mimic the nutrition profile of natural-origin fish. To evaluate the time scale at which diet alters the fecal microbiome, we collected longitudinal samples over a 12-week period and switched the diets of a subset of fish twice during the experiment. We used 16S ribosomal RNA gene amplicon sequencing to characterize fecal microbiome differences between fish on the two diets as well as hatchery-reared fish at a production hatchery, hatchery fish that had been captured after release into a stream, and natural-origin, stream-reared fish of similar ages. Additionally, we conducted RNA sequencing on head kidney samples from laboratory-reared fish to evaluate changes in gene expression in this important immune organ. Results We found that the low-lipid diet and the hatchery diet resulted in microbiomes that differed from the microbiome of natural-origin fish and from each other and that diet-driven changes to the microbiome could occur in under 14 d. The low-lipid diet did not result in a microbiome that resembled the microbiome of naturally produced fish. Instead, the low-lipid diet resulted in a microbiome community that was distinct from those of fish reared on the hatchery diet and fish sampled from the wild. The RNA sequencing results indicated differential enrichment of pathways related to immunity, metabolism, and hormone synthesis between fish that were fed the two experimental diets. Conclusions The results suggest that additional environmental factors influence the microbiome more strongly than diet formulation or that the low-lipid diet has a smaller effect on the microbiome than a natural, invertebrate-based diet. Given that the gut microbiome and systemic immune function contribute significantly to disease resistance, our findings highlight the importance of understanding how diets fed to fish in captivity may affect fish health beyond growth and body condition metrics.

Journal of Aquatic Animal Health↗

USGS2025

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↗

USGS2024

Aftershock forecasting

Aftershocks can compound the impacts of a major earthquake, disrupting recovery efforts and potentially further damaging weakened buildings and infrastructure. Forecasts of the probability of aftershocks can therefore aid decision-making during earthquake response and recovery. Several countries issue authoritative aftershock forecasts. Most aftershock forecasts are based on simple statistical models that were first developed in the 1980s and remain the best available models. We review these statistical models, and the wide-ranging research to advance aftershock forecasting through better statistical, physical, and machine learning methods. Physics-based forecasts based on mainshock stress changes can sometimes match the statistical models in testing, but don’t yet outperform them. Physical models are also hampered by unsolved problems such as the mechanics of dynamic triggering and the influence of background conditions. Initial work on machine learning forecasts shows promise, and new machine learning earthquake catalogs provide an opportunity to advance all types of aftershock forecasts.

Annual Review of Earth and Planetary Sciences↗

USGS2024

The projected exposure and response of a natural barrier island system to climate-driven coastal hazards

Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (< 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at > 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.

North Carolina↗

USGS2025

Rapid fault healing from cementation controls the dynamics of deep slow slip and tremor

Despite its status as one of the most important discoveries in geophysics, the physical mechanism(s) responsible for slow slip events (SSEs) are not well understood. Here, we synthesize observations of deep SSEs in the Cascadia Subduction Zone and argue that rapid, cohesive fault strengthening may control the dynamics of deep SSEs. Cohesive strength is frequently ignored in constitutive laws used to describe fault rheology in numerical simulations of earthquakes and SSEs alike. To demonstrate its importance, we perform and analyze a suite of petrological experiments that simulate fault healing under representative pressure and temperature conditions. We show that significant cohesive strength recovery caused by dissolution-precipitation processes occurs on timescales of just a few hours. Together, our experimental and observational results support the idea that cohesion is a key component of fault strength under SSE conditions and highlight the need for its inclusion in both future experiments and numerical models of fault slip.

British Columbia, Washington↗

USGS2025

Long-term dynamics of earthquake swarms in the Yellowstone caldera

The factors controlling the spatial distribution and temporal evolution of earthquake swarms in volcanic systems remain unclear. We leverage leading-edge deep learning algorithms and a detailed three-dimensional velocity model to construct a 15-year high-resolution earthquake catalog of the Yellowstone caldera region. More than half of the region’s earthquakes are clustered into swarm-like families characterized by episodes of hypocenter expansion and migration. Adjacent earthquake swarms, separated by long quiescent periods, are found to be a dominant feature. We suggest that these swarms are controlled by the interplay between slowly diffusing aqueous fluids and rapid episodic fluid injections, which may result from the breaking of permeability seals. Our analyses also indicate that clustered seismicity beneath the caldera occurs on relatively immature, rougher fault structures, compared to more planar faults outside. Our results provide additional context for understanding seismicity in hydrothermal systems, highlighting the key role played by long-term fluid diffusion processes in driving the occurrence of earthquake swarms.

Idaho, Montana, Wyoming↗

USGS2024

Hyperspectral (VNIR-SWIR) analysis of roll front uranium host rocks and industrial minerals from Karnes and Live Oak Counties, Texas Coastal Plain

VNIR-SWIR (400–2500 nm) reflectance measurements were made on the surfaces of various cores, cuttings and sample splits of sedimentary rocks from the Tertiary Jackson Group, and Catahoula, Oakville and Goliad Formations. These rocks vary in composition and texture from mudstone and claystone to sandstone and are known host rocks for roll front uranium occurrences in Karnes and Live Oak Counties, Texas. Spectral reflectance profiles, 569 in total, were reduced to 125 representative spectral signatures, which were analyzed using the U.S. Geological Survey's (USGS) Material Identification and Characterization Algorithm (MICA). MICA uses an automated continuum-removal procedure together with a least-squares linear regression to determine the fit of observed sample spectral absorption features to those of reference mineral standards in a spectral library. The reference minerals include various clay, mica, carbonate, ferric and ferrous iron minerals and their mixtures. In addition, absorption feature band-depth analysis was done to identify rock surfaces exhibiting absorption features related to uranium and zeolite minerals, which were not included in the command files used to execute MICA. Rocks from each of the four geologic units produced broadly similar spectral signatures as a result of comparable mineral compositions, but there were some notable differences. For example, Ca- and Na-montmorillonite was matched most frequently to the spectral absorption features in 2-μm (∼2000–2500 nm) wavelengths, while goethite occurred often at 1-μm (∼400–1000 nm) wavelengths. The latter is related to limonitic iron-staining in and around oxidized zones of the uranium roll front as described in previous papers. Rocks of the Jackson Group differed from those of the Catahoula, Oakville and Goliad units in that the former exhibited spectral features we interpret as being due to the presence of lignite-bearing mudstone layers. Goliad rocks exhibit spectral features related to dolomite, gypsum, anhydrite, and an unidentified green clay mineral that is possibly glauconite . Jackson Group rocks also exhibit weak but well-resolved absorption features at 964 and 1157 nm related to either or both zeolite minerals clinoptilolite and heulandite. These zeolite minerals and a few spectra exhibiting hydrous silica absorption features are indicative of alteration of volcanic glass in tuffaceous mudstone and claystone layers. A few sample spectra exhibited strong absorption features at around 1135 nm related to the uranium mineral coffinite. Both the 1135 nm coffinite and 1157 nm zeolite absorption features overlap somewhat, potentially making them difficult to distinguish without additional hyperspectral field, laboratory or remote sensing data. The results of this study were compared to mixtures of minerals described for ore, gangue and alteration minerals in deposit models for sandstone-hosted uranium, sedimentary bentonite and sedimentary zeolite. Use of these spectra can help facilitate mapping of both waste materials from the legacy mining of the above commodities, as well as future exploration and resource assessment activities.

Texas↗

USGS2024

Earthquake effects surveyed during the nineteenth century as ecological features of Chinookan tidelands

Lasting effects of a Cascadia earthquake in 1700 were documented during surveys of Chinookan tidelands near the mouth of the Columbia River between 1805 and 1868. The effects resemble estuarine consequences, near Anchorage, of the 1964 Alaska earthquake: fatal drowning of subsided meadows and forests by post-earthquake tides, rebirth of marshes and forests through post-earthquake sedimentation, and uplift. Chinookan remains of killed forests were recorded by James Graham Cooper, John J. Lowell, and Cleveland Rockwell. Cooper, attached to a railroad survey and the Smithsonian Institution, wrote of redcedar stumps and trunks standing dead in tidal marshes of Shoalwater (now Willapa) Bay. Two such snags served as bearing trees for Lowell as he platted a Shoalwater Bay township under contract with the General Land Office. Rockwell, of the US Coast Survey, flecked landward edges of tidal flats west of Astoria with symbols that evoke remains of a bygone spruce forest. The Lewis and Clark Expedition, while in that area in 1805–1806, mapped and puzzled over tideland vegetation that post-1700 succession helps explain.

Alaska, British Columbia, California, Oregon, Wash↗

USGS2024

Oblique contraction along the fastest ocean-continent transform plate boundary focuses rock uplift west of the Fairweather fault, southeast Alaska

Contraction along the Yakutat–North America plate boundary drives 4.6–9.0 mm/year Holocene rock uplift rates along Earth's fastest slipping (≥49 mm/year) ocean–continent transform fault, the Fairweather Fault. Between Icy Point and Lituya Bay, the near-vertical Fairweather fault focuses rock uplift and rapid right-lateral slip by accommodating both vertical and fault-parallel strain during oblique-slip and separate, predominantly strike-slip ruptures. Unusually high uplift rates, indicated by radiocarbon and luminescence dating, result from a 10-km-wide, asymmetric, positive flower structure along a 20°, ∼30-km-long restraining double bend in the Fairweather fault. The principal reverse fault in the flower structure, the offshore, blind Icy Point–Lituya Bay fault, ruptures no more than every 460–1040 years evidenced by uplifted Holocene shorelines. Maximum 3–5 m coseismic uplifts imply 3.1–10 m dip slip per event and earthquake magnitudes of M w 7.0–7.5. The Yakutat block collides obliquely into North America, and our model entails oblique slip on the Fairweather fault with and without corupture on the reverse fault. Oblique slip is evident by vertically offset (>25 m) fluvial and marine terraces and by the primary Fairweather fault strand that strikes >20° to the west of plate-boundary motion.

Alaska↗

USGS2024

Slope Unit Maker (SUMak): An efficient and parameter-free algorithm for delineating slope units to improve landslide modeling

Slope units are terrain partitions bounded by drainage and divide lines. In landslide modeling, including susceptibility modeling and event-specific modeling of landslide occurrence, slope units provide several advantages over gridded units, such as better capturing terrain geometry, improved incorporation of geospatial landslide-occurrence data in different formats (e.g., point and polygon), and better accommodating the varying data accuracy and precision in landslide inventories. However, the use of slope units in regional ( > 100 km 2 ) landslide studies remains limited due, in part, to the large computational costs and/or poor reproducibility with current delineation methods. We introduce a computationally efficient algorithm for the parameter-free delineation of slope units that leverages tools from within TauDEM and GRASS, using an R interface. The algorithm uses geomorphic laws to define the appropriate scaling of the slope units representative of hillslope processes, avoiding the often ambiguous determination of slope unit size. We then demonstrate how slope units enable more robust regional-scale landslide susceptibility and event-specific landslide occurrence maps.

Natural Hazards and Earth Systems Sciences (NHESS)↗

USGS2024

Evaluation of the lithium resource in the Smackover Formation brines of southern Arkansas using machine learning

Global demand for lithium, the primary component of lithium-ion batteries, greatly exceeds known supplies, and this imbalance is expected to increase as the world transitions away from fossil fuel energy sources. High concentrations of lithium in brines have been observed in the Smackover Formation in southern Arkansas (>400 milligrams per liter). We used published and newly collected brine lithium concentration data to train a random forest machine-learning model using geologic, geochemical, and temperature explanatory variables and create a map of predicted lithium concentrations in Smackover Formation brines across southern Arkansas. Using these predicted lithium maps with reservoir parameters and geologic information, we calculated that there are 5.1 to 19 million tons of lithium in Smackover Formation brines in southern Arkansas, which represents 35 to 136% of the current US lithium resource estimate. Based on these calculations, in 2022, 5000 tons of dissolved lithium were brought to the surface within brines as waste streams of the oil, gas, and bromine industries.

Arkansas↗

USGS2025

Rapid emplacement of the Keaiwa Lava Flow of 1823 from the Great Crack in the Southwest Rift Zone of Kilauea volcano

The Keaīwa Lava Flow of 1823 in the Southwest Rift Zone of Kīlauea volcano is unusual for its expansive pāhoehoe sheet flow morphology and lack of constructive vent topography, despite having a similar tholeiitic basalt composition to other lavas erupted from Kīlauea. This lava flow issued from a ∼10-km-long continuous fissure now known as the Great Crack, and has an unusually thin sheet flow morphology with margin thicknesses of ∼15–110 cm (average of 42 cm). Based on field observations of the lava flow at its fissure vent (e.g., drain-back features), we propose that the Great Crack formed, or at least significantly widened, just prior to and syn-eruptively with this 1823 eruption. The absence of pyroclastic cones or spatter ramparts indicates that the eruption consisted of a rapid outpouring of relatively degassed lava as the fissure unzipped. The rapidly moving lava flow overtopped pre-existing tumuli and scoria cones (e.g., Lava Plastered Cones) up to ∼10 m tall. Glass and whole-rock chemistry yield homogeneous compositions for the lavas erupted from the Great Crack, with glass compositions of 6.40 ± 0.10 wt% MgO and whole-rock compositions of 7.39 ± 0.07 wt% MgO. Lava pads erupted from a short western fissure system are richer in mafic minerals (e.g., olivine and clinopyroxene), and show slightly more MgO-rich whole-rock compositions (7.79 ± 0.05 wt%). MgO-in-glass thermometry on juvenile spatter yield eruption temperatures of 1153 ± 13°C that are typical of Kīlauea lavas. Thus, the extensive sheet-like lava flow morphology is not a direct consequence of unusual magmatic or rheological conditions (i.e., low viscosity). Instead, the flow morphology is associated with high effusion rates caused by sudden drainage of uprift magma as it erupted from the Great Crack. Lava flow modeling on a 2-m-resolution digital elevation model indicates that a minimum bulk effusion rate of ∼5800 m 3 /s (∼3500 m 3 /s dense rock equivalent) and a minimum flow velocity of ∼11 m/s are required for the lava flow to overcome the topography of the Lava Plastered Cones. This effusion rate is among the highest inferred for eruptions in Hawaiʻi and around the world. This study highlights a less frequent eruption style at Hawaiian volcanoes characterized by a sudden outpouring of lava from an unusual fissure system. Local eyewitness accounts indicate that the 1823 eruption was preceded by seismicity. Given the complex magmatic-volcanic-tectonic relations across Kīlauea, we speculate that the south flank could have slipped over one or more events that ultimately triggered unzipping of the Great Crack and passive release of briefly stored uprift magma. An eruption similar to 1823 at Kīlauea or Mauna Loa, with an eruptive timeframe that could be as short as an hour, with high effusion rates and rapid flow front velocities, would not easily allow for a timely response.

Hawaii↗

USGS2025

Triple-oxygen isotopic evidence of prolonged direct bioleaching of pyrite with O2

Sulfate is often touted as containing atmospheric oxygen whose isotopic signature can constrain redox, environmental conditions, and biological activity. Yet, the amount and isotopic fractionation associated with air-O 2 incorporation during sulfate formation is still debated, making its verification difficult. In this study, we identify a distinct, microbially dominated environment with the potential to preserve maximum signals of air-O 2 in sulfate. We report triple-oxygen isotope data for sulfate produced from pyrite oxidation in microbial and abiotic experiments, and from natural dissolved sulfate from the Rio Tinto, Spain, an acid mine drainage site. The oxygen isotope systematics of sulfate in these environments define a unique kinetic isotope effect associated with initial stage pyrite oxidation by Acidithiobacillus ferrooxidans that preserves >80 % oxygen from air-O 2 in sulfate. Unlike experiments, which evolve toward water-oxygen dominated sulfate on short time scales, Rio Tinto, Spain hosts a microbe rich environment with distinct geochemistry that maintains high O 2 -oxygen in sulfate. Therefore, in addition to containing isotopic records from water and air, sulfates can also contain a biosignature that is promising for understanding conditions on Mars and early Earth.

Earth and Planetary Science Letters↗

USGS2026

Estimating paleotemperature using stable isotopes of soil-formed phyllosilicates from paleosols: A review

Fossilized soils, or paleosols, contain soil-formed phyllosilicates whose stable isotopic compositions may be used to calculate paleotemperature and thus reconstruct ancient terrestrial environments. Though paleosols are common in the geologic record, the use of phyllosilicates as paleotemperature proxies is limited in the literature owing to difficulties with selecting optimal paleosols, isolation from non-clay minerals and organic materials, mixtures of phyllosilicates in natural samples, wide variations of chemical compositions for phyllosilicates, and limited to undefined equilibrium fractionation factors between phyllosilicates-water. Here, we address these challenges by examining and comparing methods used for sample selection, mineral isolation, pretreatments, mineral identification, conventional and developing methods for oxygen and hydrogen isotopic analyses, and determination of phyllosilicate-water equilibrium fractionation factors, concluding with recommendations for best approaches for paleotemperature estimation. Additionally, we discuss how to identify and avoid detrital phyllosilicates, the impacts of diagenesis, comparison of stable isotope and non-isotope paleosol paleotemperature proxies, and challenges and opportunities for broadly using paleosols as paleoclimate archives. With ongoing efforts to refine this multi-faceted paleotemperature approach, the stable isotope geochemistry of soil-formed phyllosilicates continues to be an invaluable proxy system, enhancing our understanding of terrestrial paleoenvironments and paleoclimate.

Kansas↗