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Results for “Rapid Communications in Mass Spectrometry”

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1,602 recordsLinked to original sources
USGS2024

Using stable oxygen isotope dual-inlet isotope-ratio mass spectrometry to elucidate uranium transport and mixed 230Th/U calcite formation ages at the seminal Devils Hole, Nevada, natural laboratory

Rationale Vein calcite in Devils Hole has been precipitating continuously in oxygen-isotope equilibrium at a constant temperature for over 500 000 years, providing an unmatched δ 18 O paleoclimate time series. A substantial issue is that coeval calcite (based on matching δ 18 O values) has uranium-series ages differing by 12 000 years. Methods An unparalleled high-accuracy δ 18 O chronology series from continuously submerged calcite was used to correct the published uranium-series ages of non-continuously formed calcite in two cores, cyclically exposed by water-table decline during glacial–interglacial transitions. This method relies on the premise that the δ 18 O values of coevally precipitated calcite are identical, allowing matching calcite δ 18 O values to establish formation ages. Results Exposed calcite can have apparent ages that are 12 000 years too young due to unrecognized uranium mobility and resulting mixed ages identified in over 50 mixed uranium-series ages from previous studies. Secondary uranium in fluids, sourced from the formation or dissolution of porous carbonate deposits (folia) with high uranium-238 ( 238 U) concentrations, has migrated up to 10 mm into vein calcite. Conclusions The continuously submerged Devils Hole δ 18 O chronology is not explained by orbital forcing. Rather, this chronology represents a regional climate record in the southern Great Basin of sea-surface-temperature (SST) variations off California, variations that preceded the last and penultimate deglaciations by 5000 to approximately 10 000 years. Temporal discrepancies between the continuously submerged Devils Hole chronology and other regional δ 18 O records (e.g., the Leviathan chronology) can be explained by unrecognized cryptic, pernicious uranium mobility, leading to model estimations that may be thousands of years younger than actual ages. Consequently, paleo-moisture availability, water-table, and groundwater recharge models based on these mixed uranium-series ages are too young by as much as 12 000 years. The potential for post-formation uranium addition in subaerial cores and speleothems underscores the need for caution in uranium-series dating, highlighting δ 18 O time-series comparisons as a method for identifying mixed ages.

Nevada↗
USGS2025

lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) data has a wide variety of uses in the geosciences for in-situ chemical analysis of complex natural materials. Improvements to instrument capabilities and operating software have drastically reduced the time required to generate large volumes of data relative to previous methodologies. Raw data from LA-ICP-MS, however, is in counts per unit time (typically counts per second), not elemental concentrations and converting these count ratesto concentrations requires additional processing. For complex materials where the ablated volume may contain a range of material compositions, a moderate amount of user input is also required if appropriate concentrations are to be accurately calculated. In geologic materials such as glasses and minerals that potentially have numerous heterogeneities (e.g., microlites or other inclusions) within them, this is typically determiningwhether the total ablation signal should be filtered to remove these heterogeneities. This necessitates that the LA-ICP-MS data processing pipeline is one that is not automated, but is also designed to enable rapid and efficient processing of large volumes of data. Here we introduce , a Python library for the time resolved analysis of LA-ICP-MS data. We outline its mathematical theory, code structure, and provide an example of how it can be used to provide the time resolved analysis necessitated by LA-ICP-MS data of complex geologic materials. Throughout the pipeline we show how metadata and data are incrementally added to the objects created such that virtually any aspect of an experiment may be interrogated and its quality assessed. We also show, that when combined with other Python libraries for building graphical user interfaces, it can be utilized outside of a pure scripting environment. can be found at https://doi.org/10.5066/P1DZUR3Z

Applied Computing and Geosciences↗
USGS2025

Determination of per- and polyfluoroalkyl substances in water by direct injection of matrix-modified centrifuge supernatant and liquid chromatography/tandem mass spectrometry with isotope dilution

A direct-injection liquid chromatography/tandem mass spectrometry method was developed to determine 34 per- and polyfluoroalkyl substances (PFAS), including selected branched isomers, in centrifuge supernatant of matrix-modified (amended with approximately 50 percent methanol) water samples. The method has been validated in reagent water, surface water, groundwater, and wastewater effluent. Other water types (for example, drinking water, untreated wastewater, and landfill leachate) have been analyzed by the method but not systematically validated. Recovery of isotope-dilution standards, added to each sample, may be used to assess method performance in nonvalidated matrices on a sample-by-sample basis. Using this method, PFAS concentrations were determined in the range of 2–2,000 nanograms per liter in water samples. This range can be extended by diluting concentrated samples. At circumneutral pH, most compounds are present in the environment in their ionized form, and data are reported as such (for example, perfluorooctanoic acid is referred to as “perfluorooctanoate” [PFOA], perfluorooctane sulfonic acid is referred to as “perfluorooctane sulfonate” [PFOS]). Sample preparation procedures were designed without the use of filtration and with minimum sample handling steps to mitigate procedural losses of target compounds due to sorption to surfaces. Further, isotope-dilution quantification allowed for the correction of bias that may result from procedural losses, matrix-induced signal suppression or enhancement, and other factors. Validation experiments to characterize bias and variability, method detection level, and holding time were done in four distinct water matrices—reagent water, surface water, treated wastewater effluent, and groundwater—at multiple concentration levels. Mean PFAS recoveries met data quality objectives of bias and variability studies in all four validation matrices except for two compounds with low and variable recovery in the reagent water matrix only. Isotope-dilution standards, treated as surrogate compounds, were analyzed in more than 1,500 customer-submitted environmental samples with aggregate recovery of 102.5±6.5 percent (mean±standard deviation). Maximum holding times for all target compounds in the four validation matrices were 28 days for refrigerated samples and 90 days for frozen samples.

Techniques and Methods↗
USGS2025

Re-Os geochronology of molybdenite by LA-ICP-MS/MS

Re-Os geochronology is a powerful tool to directly date sulphide mineralisation using phases such as molybdenite, pyrite and chalcopyrite. We present a snapshot of a method in development utilizing laser ablation inductively coupled-plasma ‘triple quad’ mass spectrometry (LA-ICP-MS/MS) for Re-Os geochronology of molybdenite. While traditional LA-(MC)-ICP-MS measurements are limited by the >90% isobaric interference correction of parent radioactive 187 Re on radiogenic daughter 187 Os, the MS/MS technology minimizes this correction through careful instrument tuning and use of a (CH 4 + H 2 + He) reaction gas mixture to mass shift 187 Os away from 187 Re. We demonstrate the potential of the MS/MS technique by presenting robust Re-Os dates for three different molybdenite samples ranging in age from ~28 to 1520 Ma.

Conference Paper↗
USGS2022

U-Pb scheelite ages of tungsten and antimony mineralization in the Stibnite-Yellow Pine district, central Idaho

The Stibnite-Yellow Pine district contains the largest antimony resource in the United States, as well as significant gold, and is a historic producer of tungsten. Application of in situ laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) direct dating of scheelite from two Au-Sb-W ore deposits, Yellow Pine and Hangar Flats, yielded an older group of U-Pb ages in the range of 60.0 ± 2.8 to 57.0 ± 1.1 Ma and a younger U-Pb age for scheelite intergrown with stibnite of 47.4 ± 1.1 Ma. These in situ analyses were calibrated by isotope dilution-thermal ionization mass spectrometry (ID-TIMS) U-Pb lower intercept ages of two coarsely crystalline scheelite samples that yielded ages of 57.52 ± 0.22 and 56.62 ± 0.16 Ma. Scheelite of the latter age is of sufficient quality to serve as a primary reference material for LA-ICP-MS scheelite U-Pb geochronology. The group of older U-Pb scheelite ages agrees with 40 Ar/ 39 Ar ages of 56.9 ± 1.2 to 56.38 ± 0.54 Ma on adularia from Yellow Pine and Hangar Flats, whereas the younger U-Pb scheelite age is similar to an 40 Ar/ 39 Ar age of 46.00 ± 0.40 Ma on adularia from an epithermal gold-silver deposit in the adjacent Thunder Mountain caldera. Our results indicate that the main stage of tungsten mineralization occurred at ca. 57 Ma, whereas the main stage of antimony mineralization occurred at ca. 47 Ma—thereby providing first-time age constraints for antimony and tungsten mineralization in the Stibnite-Yellow Pine district.

Idaho↗
USGS2026

Evidence for a biological origin of uranium-rich carbon masses within the Ediacaran Salt Range Formation of Pakistan

Thucholites are unique organic structures found in igneous and sedimentary rocks composed of a U-C-rich interior enclosed by an organic outer shell. Their formation and occurrence have perplexed scientists for over 100 years. Typically, thucholites are sparse in sedimentary rocks but where found in abundance, they may be the result of rapid paleoecological disruptions, e.g., volcanic ashfall. Here, we evaluated thucholites from the Ediacaran Salt Range Formation of the Indus Basin in Pakistan using field emission scanning electron microscopy (FESEM) and nanoscale secondary ion mass spectroscopy (NanoSIMS) to propose a two-stage mechanism for thucholite development. NanoSIMS results suggest organic matter in thucholite cores formed by biological fractionation (represented by the presence of lighter 13 C/ 12 C and 34 S/ 32 S) while the outer organic mantle formed via radiolysis-induced polymerization. FESEM elemental analysis confirms compositional differences between the two thucholite components (core and mantle), further implying their contrasting origins. Dimensional comparison of thucholite cores and their U-bearing mineral morphologies to ancient and modern U-biomineralized microbes suggests that the thucholite cores formed from metal-biological interactions. The presence of volcanogenic biotite, alkali feldspar, and clay spherules (interpreted as devitrified volcanic glass) with thucholite suggests that the thucholite cores in the Salt Range Formation are biological responses to rapid paleoenvironmental change from volcanic eruption which preserved the fossilized morphologies of Proterozoic microorganisms.

Salt Range↗
USGS2024

The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters

Rare earth elements (REEs) are a class of critical minerals, all of which can have supply chain vulnerability that impacts economic security. These elements are widely measured in environmental matrices via inductively coupled plasma mass spectrometry (ICP-MS); however, successful quantification can require time-consuming, sample-specific optimization. While a sample-by-sample approach is appropriate for targeted quantification studies, this approach is not suitable for mineral exploration efforts where rapidly screening thousands of samples for the presence of REEs is desired. Here, we demonstrated the use of a Quick Screening Tool for Approximating REEs (Q-STAR) to detect REEs in surface water and groundwater matrices, collected as part of existing environmental studies. A mass-to-charge ratio of 144 ( m / z = 144) was added to an ICP-MS method to screen for REEs in filtered water samples submitted for metals analyses to the U.S. Geological Survey (USGS) National Water Quality Laboratory. We detected the presence of REEs above a reference threshold of 1200 counts per second in 18 % of pre-selected 6626 samples. Using this screened dataset, we mapped estimated dissolved REE concentrations across the United States in relation to ecoregions and underlying geology. Data are constrained to where sample collection took place but nevertheless show estimated aqueous dissolved REE concentrations on a geographic scale that has not yet been studied. To validate Q-STAR, REEs were measured in a USGS standard reference sample, a subset of 88 archived filtered water samples, and in fresh filtered surface water samples. Our targeted analyses demonstrated a strong linear relationship between Q-STAR predicted and measured values in all archived samples for Nd (r 2 = 0.94), and light REEs (LREEs) such as lanthanum (La) (r 2 = 0.93), praseodymium (Pr) (r 2 = 0.94) and samarium (Sm) (r 2 = 0.94). Using Q-STAR screen values, nine field sites were identified and surface water samples recollected to confirm the continued presence of Nd and LREEs. Q-STAR can be used to screen an unlimited number of water samples for the presence of REEs prior to time-intensive and costly quantitative analyses and to generate large REE datasets for further investigation.

Journal of Geochemical Exploration↗
USGS2026

Landslide volume estimation from seismic waveform features using a global catalog of seismogenic events

Seismic waves generated by large, rapid landslides encode information about the source and can be analyzed rapidly following an event. Even remote landslides can pose hazards to downstream communities, so rapid detection and characterization using existing seismic monitoring networks could be beneficial. In this study, we expand on past regionally limited work by presenting a globally applicable method for estimating landslide volume from seismic features that could be integrated into future landslide seismic monitoring frameworks. We train the model using multivariable linear regression and five seismic features derived from recordings of 129 landslide events of a range of styles and locations with independently estimated volumes. We present two preferred models, one that combines long‐period (LP) and high‐frequency (HF) features and one for use on smaller landslides without observed long‐period signals. We find that our best‐performing model, applicable to landslides larger than 100,000 m 3 with signals containing observable long‐period energy, requires only two features: LP (20–100 s) absolute maximum amplitude and HF (1–5 Hz) rise time (time between the signal start and the maximum envelope amplitude) and has an R 2 score of 0.79. This model predicted volumes within one order of magnitude for 55 out of 58 events. We find that this combination mitigates the trade‐off between mass and acceleration and other variations of landslide style that limit methods based on amplitude alone.

Seismological Research Letters↗
USGS2026

Rapid earthquake magnitude classification via P-wave strains from borehole strainmeters and Distributed Acoustic Sensing

Distributed Acoustic Sensing (DAS) offers a promising approach for earthquake early warning (EEW) in settings where seismic networks are costly to maintain. By repurposing fiber-optic cables as dense strainmeter arrays, DAS enables real-time earthquake detection wherever those fibers are accessible. However, poor azimuthal coverage and challenges in estimating magnitude from strain measurements remain key hurdles in applying for earthquake monitoring. Here, we develop a machine learning method to distinguish large (M≥5.4) earthquakes from smaller ones within the first 4 seconds of a strain waveform after a P-wave arrival without determining location. Using ensemble decision tree models trained on borehole strainmeter data (3.5≤M≤7.1) and tested on onshore DAS waveforms (including the 2024 M7 Offshore Cape Mendocino earthquake), we find that low-frequency (0.2–0.5 Hz) continuous wavelet transform coefficients are the strongest predictors of magnitude, in addition to strain amplitude. Both DAS and borehole strainmeters effectively capture long-period strain signals, making these findings valuable for EEW systems. Our method shows high precision compared to the real-time EEW system, ShakeAlert®, supporting the position that DAS is a viable technology for earthquake monitoring and magnitude classification.

California↗
USGS2025

Timing of hydrothermal alteration and Au-Sb-W mineralization, Stibnite-Yellow Pine district, Idaho

The Stibnite-Yellow Pine district of central Idaho was mined from the early 1900s until the 1990s, extracting gold, antimony, tungsten, and mercury from veins and disseminated and replacement ores in mountainous terrain along the headwaters of the Salmon River. Mining during the two World Wars supplied critical antimony and tungsten to the war efforts. Recent exploration has delineated mineral resources of over 187 metric tons Au, 274 metric tons Ag, and 93,000 metric tons Sb. Mineralization is hosted in Cretaceous Idaho batholith granitic rocks and a sequence of Neoproterozoic to Paleozoic metasedimentary strata of carbonate and siliciclastic compositions. Historical studies outlined some of the complex paragenesis but debated the absolute age of mineralization. New petrographic and geochronologic work documents a sequence of five hydrothermal events in the Stibnite-Yellow Pine district. Event 1 is related to Cretaceous magmatic and hydrothermal activity and includes events ranging in age from 86 to 75 Ma, including sparse quartz-molybdenite veins dated at 86 Ma. Disseminated gold mineralization of event 2 is associated with sericitic alteration and sulfidation of igneous biotite and replacement of plagioclase by potassium feldspar, largely in granodiorite. Gold is present in zoned arsenian pyrite in both disseminated ores and in crosscutting carbonate-quartz veins containing pyrite and arsenopyrite. The large Yellow Pine deposit, localized at a dilatant bend in the Meadow Creek fault, hosts such disseminated and vein gold. Event 2 is interpreted as the major gold-forming event; 40 Ar/ 39 Ar ages of sericite and potassium feldspar alteration range, respectively, from 70 to 59 and 66 to 56 Ma. The long span is interpreted to reflect the age of gold mineralization and local overprinting by event 3. A narrower range from 66 to 61 Ma is interpreted to date the peak of gold mineralization and alteration. Event 3, tungsten mineralization with scheelite, is texturally later than event 2 gold and localized along the Meadow Creek structure. Event 3 scheelite has been dated by isotope dilution-thermal ionization mass spectrometry (ID-TIMS) and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) U-Pb methods at 57 Ma. Event 4, best developed in the West End area, includes gold-silver–bearing quartz-carbonate-pyrite veins and breccias with epithermal textures and potassium feldspar alteration envelopes. Adularia from event 4 yields 40 Ar/ 39 Ar plateau ages of 52 to 51 Ma. Event 5 antimony and mercury mineralization consists of stibnite veins and breccia cements at the Yellow Pine and Hangar Flat deposits as well as cinnabar veins and replacements at the peripheral Fern and Hermes deposits; it is constrained by an LA-ICP-MS U-Pb date on scheelite (ca. 47 Ma) intergrown with stibnite. Minor propylitic and argillic alteration is evident in 47 Ma igneous dikes, which do not contain economic mineralization. The Au-Sb-W ores in the Stibnite-Yellow Pine mining district formed over an extended time period from about 70 to 45 Ma in multiple pulses that were localized along the Meadow Creek fault zone. Each event corresponds to episodes of magmatism and/or hydrothermal activity in the region. Insignificant event 1 skarn and molybdenum mineralization is similar in age to the Thompson Creek porphyry molybdenum deposit in central Idaho. Event 2 gold mineralization occurred during a magmatic gap in central Idaho but was synchronous with magmatism in the Bitterroot lobe further north; event 2 is similar in age to orogenic gold-arsenic mineralization at the Beartrack mine in eastern Idaho. Event 3 scheelite mineralization coincides with tungsten mineralization at the Quartz Creek deposit, late magmatism in the Bitterroot lobe, and rapid exhumation of the Atlanta lobe of the Idaho batholith. Event 4 gold mineralization is coincident with the onset of regional Challis magmatism and extension. Event 5 antimony and mercury mineralization is time-equivalent to epithermal gold mineralization in the nearby Thunder Mountain volcanic field and the peak of Challis magmatism.

Idaho↗
USGS2025

Using peak geometry and shifts in the x-ray spectrum of carbon from electron probe microanalysis to determine thermal maturity of organic matter

During the burial of mudstones, the associated organic matter undergoes gradual thermal maturation, a key process that can influence the reactivity of organic matter during catagenesis, the formation of hydrocarbon deposits and the chemical weathering of mudstones. Conventional methods for assessing the thermal maturity of organic matter often fail to reflect the geochemical heterogeneity between individual organic phases in mudstone samples. Here, we report an alternative, non-destructive, surficial and micro-scale (analytical spot size of ~ 300 nm with about 4 μm diffusion depth for micrometre-size organic grains) method to evaluate the thermal maturity of organic matter in mudstones using the carbon K α X-ray spectrum measured by field emission-electron probe microanalyser (FE-EPMA). Using this method, we observed correlations between parameter values derived from FE-EPMA spectra, including the peak position, the peak area and the intra-sample heterogeneity of these measurements, and independently measured vitrinite/solid bitumen reflectance for a suite of mudstones, representing different age, geological context and burial depth. With the increased values in peak area and position, we identified an increase in the carbon mass fraction of organic matter and the mean nominal oxidation state of carbon approaching zero. These trends, which are consistent with aromatisation and graphitisation, provide the rationale for using FE-EPMA to estimate the thermal maturity of organic matter. To explore some of these trends in more detail, we employed time-of-flight secondary ionisation mass spectrometry, X-ray photoelectron spectroscopy and optical reflectance measurements on a subset of samples.

Geostandards and Geoanalytical Research↗
USGS2025

Examining the compositional selectivity of hydrocarbon oxidation products using liquid–liquid extraction and solid-phase extraction techniques

The effect of extraction methods on detecting hydrocarbon oxidation products (HOPs) in groundwater remains unclear. HOPs are polar, water-soluble byproducts of petroleum biodegradation. Our previous work showed that liquid–liquid extraction (LLE), a method commonly used in regulatory monitoring, has a significantly lower extraction efficiency for HOPs compared to solid-phase extraction (SPE). In this study, we evaluate the analytical limitations and compositional selectivity of LLE and SPE using groundwater samples from the Bemidji, MN, crude oil spill site. Optical properties were characterized using excitation–emission matrix spectroscopy (EEMs), and a three-component PARAFAC model was validated, showing consistent trends across both extracts and whole water samples. Ultrahigh-resolution mass spectrometry (UHR-MS) revealed that LLE selectively recovered aliphatic-like compounds but underrepresented more polar oxygenated HOPs. In contrast, SPE methods were more effective at isolating highly oxidized compound classes. These differences were consistent across a gradient of contamination. Overall, the LLE was less precise and less representative of polar HOPs, introducing bias in the characterization of HOPs. This study is the first to quantitatively demonstrate the compositional selectivity and analytical bias of LLE versus SPE for HOPs using combined EEM-PARAFAC and UHR-MS techniques, with implications for long-term monitoring and site assessment protocols.

Environmental Science and Technology↗
USGS2025

Rainfall thresholds for postfire debris-flow initiation vary with short-duration rainfall climatology

The size, frequency, and geographic scope of severe wildfires are expanding across the globe, including in the Western United States. Recently burned steeplands have an increased likelihood of debris flows, which pose hazards to downstream communities. The conditions for postfire debris-flow initiation are commonly expressed as rainfall intensity-duration thresholds, which can be estimated given sufficient observational history. However, the spread of wildfire across diverse climates poses a challenge for accurate threshold prediction in areas with limited observations. Studies of mass-movement processes in unburned areas indicate that thresholds vary with local climate, such that higher rainfall rates are required for initiation in climates characterized by frequent intense rainfall. Here, we use three independent methods to test whether initiation of postfire runoff-generated debris flows across the Western United States varies similarly with climate. Through the compilation of observed thresholds at various fires, analysis of the spatial density of observed debris flows, and quantification of feature importance at different spatial scales, we show that postfire debris-flow initiation thresholds vary systematically with short-duration rainfall-intensity climatology. The predictive power of climatological data sets that are readily available before a fire occurs offers a much-needed tool for hazard management in regions that are facing increased wildfire activity, have sparse observational history, and/or have limited resources for field-based hazard assessment. Furthermore, if the observed variation in thresholds reflects long-term adjustment of the landscape to local climate, rapid shifts in rainfall intensity related to climate change will likely induce spatially variable shifts in postfire debris-flow likelihood.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2024

Compositional and structural mapping of Northwest Africa 15507 angrite

Angrite meteorites represent interesting sampling of planetary crustal environments. Quench-textured angrites with strong crystal zoning originated from the shallow surface region, with evidence of reducing conditions during solidification. Plutonic angrites have more coarse-grained igneous and metamorphic textures with comparatively less zoning and are interpreted as having equilibrated at greater depth. Plutonic angrites contain the minerals magnetite Fe 3 O 4 comprised of Fe 2+ and Fe 3+ , and rhönite, where Fe 3+ is required by inspection of mineral stoichiometry. NWA 15507 is a plutonic angrite with a microgabbroic texture (mean grainsize ∼1.4 mm) composed of zoned Al-Ti-augite, Ca-bearing olivine, anorthite, with accessory kirschsteinite, rhönite, hercynite, low-Ni kamacite, merrillite, Ti-free magnetite and troilite [ 1 ]. Rhönite analyzed by electron-probe microanalysis (EPMA) has the formula Ca 2.04 (Mg 0.32 Fe 2+ 4.25 Fe 3+ 0.47 Ti 0.33 Al 0.61 )(Si 3.74 Al 2.26 )O 20 , where Fe 3+ was estimated by stoichiometric analysis. During preliminary cathodoluminescence (CL) analysis, complex subgrain and oscillatory zoning was observed in the anorthite. In this study we use a combined approach of electron probe microanalysis (EPMA), cathodoluminescence (CL), electron-backscatter diffraction (EBSD), and laser ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS) to further investigate the anorthite and distribution of Fe 3+ in NWA 15507.

Microscopy and Microanalysis↗
USGS2025

Do bighorn sheep use desert tortoise burrow spoil piles as mineral licks in southern California?

In a previous study, bighorn sheep ( Ovis canadensis ) were periodically photographed by trail cameras when they visited desert tortoise ( Gopherus agassizii ) burrows in the San Bernardino Mountains near Palm Springs, California, USA. The authors suggested that bighorn sheep may utilize the excavated spoil material from burrows as a mineral lick. To test that supposition, we collected soil samples from the spoil piles and undisturbed surface soil up to 1 m away at two desert tortoise study sites with bighorn sheep at the aforementioned site and another nearby site. We hypothesized that sodium concentrations would be greater in spoil than in nearby surface soil samples. Common major cations were quantified in soil samples using inductively coupled plasma-mass spectrometry following microwave-assisted digestion to solubilize the fraction of elements that could become biologically or environmentally available. Mean sodium concentrations were greater in burrow spoil samples than in undisturbed soil samples at both sites, likely due to aqueous leaching of sodium from surface to subsurface soil horizons. Although we did not collect evidence of geophagy by bighorn sheep, the behavior is well known. However, trail camera photographs of bighorn sheep with their head next to the entrance of tortoise burrows suggests that they may periodically utilize sodium and other elements brought to the surface by desert tortoises that are otherwise unavailable to bighorn sheep on the surface.

California↗
USGS2025

ShakeAlert®—Communication, education, outreach and technical engagement strategic vision

Executive Summary In 2006, the U.S. Geological Survey (USGS) began directly supporting ShakeAlert ® research and in 2012 the ShakeAlert demonstration system began testing ( Given and others, 2018 ). The ShakeAlert earthquake early warning (EEW) system is a partnership between the U.S. Geological Survey (USGS) and the three West Coast States (Washington, Oregon, and California) served by the ShakeAlert System, which is part of the larger Advanced National Seismic System (ANSS). With more than 143 million people exposed to potentially damaging shaking in the United States ( Jaiswal and others, 2015 ), earthquakes are a national hazard. Most of our Nation’s earthquake risk is concentrated in the highly populated areas on the active plate tectonic boundaries on the West Coast of the conterminous United States. ShakeAlert is the first public alert system in the United States to provide rapid mass notification of earthquake detection, potentially offering seconds of warning before strong shaking arrives. A few seconds may not seem like much time, but the information in ShakeAlert Messages can be used to trigger automated actions that can prevent injury or death, reduce immediate damage, and speed recovery from earthquakes. The information product issued by the ShakeAlert system is called a ShakeAlert Message and is one of the information products and tools of the ANSS. The ShakeAlert System includes the USGS component, plus the pathways by which ShakeAlert-powered products and (or) services are delivered to end users. Alerts can be delivered to cell phones or be used to trigger automated systems to protect equipment, facilities, and infrastructure, such as slowing or stopping a train. ShakeAlert-powered automated actions can include fire house doors that can be opened to prevent jamming, heavy equipment (for example, trains, elevators, and cranes) that can be automatically stopped or parked in safe positions, and pipeline valves that can be closed to prevent surges and spills. A few seconds of warning also may be sufficient for people to take protective actions, such as drop, cover, and hold on or modified protective actions for a broad range of populations. Advance training may increase the benefit of a speedy response to an alert. Outreach and education about EEW may raise awareness of the overall earthquake threat and how people can best react when they receive an alert or feel shaking. ShakeAlert communication, education, outreach, and technical engagement (CEO&TE) efforts are highly collaborative and essential for the success of the ShakeAlert System. This strategic vision informs how the vast ShakeAlert CEO&TE Community operates and works together. The CEO&TE Community delineates a strategic framework that is intended to set the path for a long-term, sustainable approach to CEO&TE through three focus areas and five priorities. Focus Areas Technical engagement.— The objective of this focus area is to expand and broaden ShakeAlert technical engagement and implementation. External engagement.— This focus area targets engagement in long-term communication, education, and outreach planning, implementation, and evaluation. Internal engagement.— The purpose of this focus area is to build and sustain a robust infrastructure to optimize collaboration, information sharing, and project planning among the community of stakeholders charged with implementing ShakeAlert CEO&TE. Priorities The enumeration of the five priorities listed below does not suggest priority ranking. Public safety, preparedness, and resilience; Technical implementation and engagement; Consistent messaging and communication; Integration with other Federal and State earthquake hazards products; and Educational resources development and dissemination. This strategic vision is a tangible outcome of collaboration among many stakeholders beginning in July 2016. Since then, the work of the ShakeAlert CEO&TE Community has grown into an international effort. The USGS has developed, tested, and implemented a broad spectrum of communication, education, and outreach tools and resources—all of which recognize that seconds matter when it comes to safety and mitigating harm from earthquake hazards. The CEO&TE social science research effort has provided invaluable insights into the ShakeAlert System’s human interface. USGS-licensed technical partners develop, test, and implement real-world applications using ShakeAlert Messages. The success of ShakeAlert CEO&TE efforts is predicated on robust collaboration across numerous agencies, organizations, and groups. As such, this strategic vision outlines a “partnership model” that delineates roles and responsibilities to ensure alignment with focus areas and priorities. The partnership model includes the CEO&TE lead agency (USGS); its principal partners (State agencies and university partners); its implementation partners (for example, technical partners who build systems to deliver ShakeAlert-powered products and (or) services [focus area one]), earthquake education partners who work to increase public preparedness for seismic events (focus area two); and other organizations that work together to enhance the adoption and effectiveness of the ShakeAlert System. These partners collaborate and convene through a variety of working groups and forums, which are also described in this strategic vision and align with focus area three (internal engagement). The CEO&TE Community collaboratively developed its operating principles and a consensus-based, decision-making strategic framework to guide its collective work. Performance metrics are used to continually measure success. Ultimately, the USGS and ShakeAlert CEO&TE Community are advancing the ShakeAlert System that as of the publication of this strategic vision to “provide earthquake early warning for all” serves more than 50 million people.

Circular↗
USGS2026

High-resolution transboundary vegetation community maps of the Sonoran and Mojave Desert ecoregion to support critical landscape conservation planning and habitat management needs

We produced a 30-m resolution binational land cover map of Bird Conservation Region 33 (BCR 33) for the U.S. North American Bird Conservation Initiative. The region covers large portions of the Sonoran and Mojave Deserts. The map can support the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program’s recovery planning efforts and constitutes the first known binational land cover dataset spanning sections of the United States–Mexico border and using a consistent classification system for both countries. The mapped region includes 152 distinct land cover classes, covering a total area of 38,421,453 ha (148,345 mi 2 ), of which 13,148,345 ha (52,706 mi 2 ) are located in Mexico and 24,770,640 ha (95,639 mi 2 ) in the United States. We primarily used Landsat 8 (OLI) imagery, supplemented by limited ground surveys from two field campaigns, drone-based aerial data, and existing vegetation classification frameworks from both countries. The classification applied a data-fusion approach integrating 30-m Landsat 8 imagery, decadal phenology metrics from vegetation indices, and a random forest model trained mainly with datasets from a comprehensive national mapping project from the U.S. Geological Survey (USGS) GAP Analysis Project (GAP) and federal wildland fire agencies’ Landscape Fire and Resource Management Planning Tools (LANDFIRE) (GAP/LANDFIRE) [United States side] and the National Institute of Statistics and Geography (INEGI) [Mexico side] as well as land cover maps and opportunistic open-access and field observations. Mapping of the full BCR 33 region was carried out in two phases: 1) Phase I, the prototype map, covered a smaller portion of the transboundary area and identified 31 land cover classes, and 2) Phase II, the full BCR 33 map (refer to Figure 1), which resulted in 152 land cover classes. Using a Random Forest classifier, we achieved an overall prediction accuracy of 92% for the Phase I map and 87% for the Phase II full region map. This slight decrease can be attributed to working on a larger, more complex area with a greater number of land cover classes. No formal validation was conducted, aside from using a subset of the collected field observations and training data to assess model performance during and after training. The training sites were further verified using Google Earth (Google, 2026) imagery. Two undergraduate students who worked for over a year visually inspected imagery and open access public images to confirm each training site during model training using in-house developed, online, visual tools. A portion of this field training data was reserved for model validation, and the corresponding results are to be presented in later sections. The project developed an end-to-end, medium- and fine-resolution remote sensing–based data fusion mapping approach. This effort produced a map (Nagler et al., 2025) and the online tools to support a dynamic, live, online map for visualizing the transboundary vegetation communities in BCR 33. The toolset is currently hosted by the University of Arizona (UofA) Vegetation Index and Phenology (VIP) Lab to support FWS partners (https://vip.arizona.edu/viplab_data_explorer?LCM_BCR33). The online map is designed to allow rapid updates using new training, validation, or correction data, making it dynamic and maintainable. The approach we took established a framework for rapid updating and correction of land cover maps, as the model can be quickly retrained with new field observations, updated training data, or other sources. This enables dynamic mapping and change detection of the region’s vegetation. This framework is an advance in data fusion and crowdsourced mapping of complex, vulnerable regions, providing support to regional stakeholders and the wider user community. This transboundary map can inform the protection, conservation, and restoration of vegetation, habitat, and ecosystems, particularly for threatened and endangered species across the two nations using consistent and harmonized binational mapping systems. Beyond supporting land management decisions and stakeholders in the transboundary desert ecoregions, this BCR 33 mapping effort establishes a foundation for future rapid, low-cost, cross-border land cover mapping that can benefit and advance ecosystem management.

Arizona, Baja California, California, Nevada, Sina↗
USGS2026

Controls on natural hydrogen generation during serpentinization of mantle rocks

Mantle rocks undergoing serpentinization can generate significant amounts of natural hydrogen, yet the rates and controlling processes remain poorly understood. Here, we constrain the possible hydrogen generation rates in two distinct mantle rock types, the fertile lherzolites of the Western Pyrenees and the depleted harzburgites of Northern California, to relatively low rates of ~0.1 to ~0.5 tonnes H₂ yr⁻¹ km⁻³ of reactive rock. When integrated over the full reactive volumes, this corresponds to total production rates of ~300 to ~600 tonnes H₂ yr⁻¹. By combining three-dimensional geophysical inversion with numerical modelling of fluid-rock processes, we show that hydrogen generation rates are mainly limited by H₂ saturation in the fluid and reaction kinetics. Under these constraints, hydrogen generation in mantle-derived serpentinization systems proceeds slowly, making rapid large-scale replenishment unlikely and suggesting that large, economically relevant accumulations, would require timescales of thousands to tens of thousands of years to develop.

northern California, western Pyrenees↗