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552 records · Page 7Linked to original sources

U.S. Geological Survey geomagnetic variometer data: Capitalizing on seismic infrastructure

The U.S. Geological Survey’s Geomagnetism Program is collaborating with the Earthquake Hazards Program and Global Seismographic Network Program to densify magnetic field observations. This collaboration focuses on the installation of magnetometers, or magnetic variometers, at existing seismic stations. Along with improving the density of space weather observations for hazard monitoring, these data can be used to correct colocated magnetic field induced noise in seismic data. Such corrections are especially useful during time periods of large magnetic storms where the magnetic field‐induced instrument noise can be of similar amplitude to earthquake ground‐motion records.

contiguous United States

Estimating the probability of export restrictions to inform mineral criticality

To assess risks associated with advanced technologies’ supply chain disruptions, governmental agencies and others have developed mineral “criticality” assessments, with criticality described using the economic impact and probability of supply chain disruptions. Previous work developed subjective supply risk indicators to approximate this probability, typically combining several factors such as supply diversity and trading partners’ political stability, where indicator weightings can substantially impact results. This work explicitly quantifies export barrier probability using an ensemble of machine learning classifiers, with probability estimates informed by exogenous variables, including prior barrier implementation and global export dominance. Major differences in high-probability countries and commodities are observed across models, but the ensemble method highlights Indonesia, China, Tanzania, and the United States as particularly high risk. The Supplementary Data File provides export barrier probability estimates for each analyzed country-commodity pair, enabling a direct, quantitative, objective contribution to assessing mineral criticality, enhancing risk identification and prioritization for policymakers.

Resources, Conservation, and Recycling

PFAS sampling activities in the U.S. Geological Survey national networks

Per- and polyfluoroalkyl substances (PFAS), frequently called “forever chemicals,” are used for a wide variety of industrial purposes and are often found in common household and industrial items such as firefighting foams, non-stick cookware, and water-resistant materials. The contamination of water, air, and soil by PFAS is a national and global issue due to their widespread occurrence in multiple applications and resistance to biodegradation and other traditional treatment processes. Research indicates that many PFAS can be emitted to the atmosphere and transported and deposited long distances from the source. The U.S. Geological Survey (USGS) Water Resources Mission Area received funding to implement a national-scale sampling effort to assess PFAS occurrence. To follow agency directives, the National Water Quality Network (NWQN) added PFAS sample monitoring for both surface water and groundwater, and also added PFAS monitoring to selected sites in the National Atmospheric Deposition Program (NADP).

General Information Product

Estimating the probability of export restrictions to inform mineral criticality

As demand for advanced technologies rises, mineral commodities will increase in geopolitical importance. To assess risks associated with mineral commodity supply chain disruptions, governmental agencies and others have developed "criticality" assessments, with criticality described using the economic impact and probability of supply chain disruptions. In previous work, subjective supply risk indicators were developed to approximate this probability, typically combining several factors such as supply diversity and political stability of trading partners, where indicator weightings can substantially impact results. This work explicitly quantifies trade barrier probability using an ensemble of several machine learning classifiers, with probability estimates informed by exogenous variables such as prior trade barrier implementation and global export dominance. Major differences in the high-probability countries and commodities are observed across models, but the ensemble method highlights Indonesia, China, Tanzania, and the United States as particularly high risk. This approach enables a direct, quantitative, objective approach to assessing trade barrier probability, enhancing risk identification and prioritization for policymakers.

SSRN

Rupture process of the Mw7.0 December 5, 2024 Offshore Cape Mendocino earthquake

The Mw7.0 December 5, 2024 Offshore Cape Mendocino earthquake ruptured a km long portion of the east-west trending Mendocino fault zone (MFZ). In order to clarify the rupture process, we assemble three-component seismograms from regional seismic stations, horizontal coseismic displacement vectors derived from Global Navigation Satellite System (GNSS) time series, and a Sentinel-1 ascending interferogram. These data are interpreted with a model of slip distributed on two vertical fault planes representative of the eastern MFZ and spanning the ~70 km length of the aftershock zone. Assuming right-lateral strike slip, we find that the rupture initiates in the oceanic mantle at 20-30 km depth and proceeds unilaterally updip and toward the east. Early aftershocks locate adjacent to the peak slip areas, tracking the coseismic rupture propagation from oceanic mantle to shallower depth and implying a significant role of static stress transfer in driving aftershocks in an ocean plate environment.

California

Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications

The US Geological Survey’s (USGS) ShakeMap system provides a rapid characterization of strong ground shaking in areas directly affected by an earthquake. This study focuses on studying the aggregate effects of macroseismic shaking estimates from ShakeMap, expressed in terms of modified Mercalli intensity (MMI), when accounting for the uncertainty in forecasted ground motions. We use a Monte Carlo approach to generate numerous spatially correlated realizations of ground motions by utilizing a combination of circulant embedding and kriging techniques for efficiently handling the correlations. We then assessed the aggregate effects of shaking by looking at bin counts across these realizations. We demonstrate that the aggregate shaking regarding the mean macroseismic intensity estimates (from the ShakeMap output) is a biased representation of the aggregate shaking when shaking uncertainty is included. Incorporating shaking uncertainty can help to improve various downstream earthquake impact applications, such as the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) overall earthquake fatality distribution or estimates of shaking-induced ground failure impacts from consequential earthquakes.

Earthquake Spectra Journal

The saline groundwater legacy of a large buried coastal paleo-estuary

Elevated groundwater salinity in coastal regions threatens the beneficial use of fresh groundwater. Coastal groundwater management typically focuses on preventing intrusion from modern sources of seawater; however, past geological processes can also leave a legacy of saline groundwater now hidden in the subsurface. Here, multiple extensive airborne electromagnetic surveys provide detailed evidence of residual salinity from a paleo-estuary filling a late Pleistocene incised valley impacting more than 10,000 km 2 that is now hidden beneath coastal Louisiana’s deltaic plain. Our results show that the three-dimensional pattern of saline groundwater beneath Louisiana mimics that of near-surface aquifers surrounding the modern Delaware Bay estuary, fingerprinting the signature of the past drowning of a large, incised valley of the Mississippi River following post-glacial sea-level rise. These findings demonstrate a new framework for understanding legacy sources of saltwater critical for managing stressed water resources along global coastlines.

Louisiana

The EnMAP spaceborne imaging spectroscopy mission: Initial scientific results two years after launch

Imaging spectroscopy has been a recognized and established remote sensing technology since the 1980s, mainly using airborne and field-based platforms to identify and quantify key bio- and geo-chemical surface and atmospheric compounds, based on characteristic spectral reflectance features in the visible-near infrared (VNIR) and short-wave infrared (SWIR). Spaceborne missions, a leap in technology, were sparse, starting with the CHRIS/PROBA and EO1/Hyperion missions in the early 2000s, and providing spectroscopy data with limited spectral coverage and/or low data quality in the SWIR. Since 2019, several countries and agencies have successfully launched a number of spaceborne imaging spectroscopy systems into orbit or deployed them on the International Space Station (ISS) such as DESIS, PRISMA, HISUI, GF-5, EnMAP and EMIT. Among these recent missions, the German Environmental Mapping and Analysis Program (EnMAP) stands for its long-term development, sophisticated design with on-board calibration, high data quality requirements, and extensive accompanying science program. EnMAP was launched in April 2022 and, following a successful commissioning phase, started its operational activities in November 2022. The EnMAP mission encompasses global coverage from 80° N to 80° S through on-demand data acquisitions. Data are free and open access with 30 m spatial resolution, a high spectral resolution with a spectral sampling distance of 6.5 nm and 10 nm in the VNIR and SWIR regions respectively, and a high signal-to-noise ratio. In this paper, we aim to present the mission's current status, coverage, science capabilities and performance two years after launch. We show the potential of EnMAP for space-based imaging spectroscopy to operate in various environments, including high and low light levels, dense forests, Antarctic glaciers, and arid agricultural areas. EnMAP enables various applications in fields such as agriculture and forestry, soil compositional, raw materials, and methane mapping, as well as water quality assessment, and snow and ice properties. The results show that EnMAP's performance exceeds the mission requirements, and highlights the significant potential for contribution to scientific exploitation in various geo- and biochemical sciences. EnMAP is also expected to serve as a key tool for the development and testing of data processing algorithms for upcoming global operational missions.

Remote Sensing of Environment

Bayesian belief network model to predict human-wildlife conflict in protected areas

Human-wildlife conflict (HWC) poses a pervasive global challenge, affecting livelihoods and threatening biodiversity. To better anticipate and mitigate HWC risk, we developed a large-scale predictive model using a Bayesian Belief Network (BBN). We surveyed 1,011 park rangers across 135 terrestrial protected areas in three Andean countries, documenting recent HWC incidents involving wildlife persecution or killing, livestock depredation, crop damage, or threats to human safety and property. We identified key drivers of HWC risk, including governance, wildlife acceptance, participation, and habitat quality. A sensitivity analysis revealed that enhancing governance and improving wildlife acceptance could reduce HWC risk by > 85%. The BBN model demonstrated scalability, effectively identifying strategies to reduce HWC risk at multiple scales, from individual protected areas to national networks. Our findings highlight the importance of strengthening governance, increasing wildlife acceptance, and enhancing community participation in conservation efforts. BBNs provide a flexible, cost-effective, and data-driven tool to guide protected areas and wildlife managers in monitoring, anticipating, and making informed decisions to mitigate conflict and promote coexistence.

Scientific Reports

Airborne geophysical efforts for critical mineral systems mapping in the southern Midcontinent, USA

The increasing global demand for critical minerals to support energy and technological advancement has accelerated exploration and research efforts for these essential resources. Since 2019, the United States Geological Survey (USGS) Earth Mapping Resources Initiative (EMRI) has worked to modernize geologic mapping of the Nation to better understand its critical mineral resources. To further this initiative, the USGS has flown a series of high-resolution airborne magnetic and radiometric surveys over large areas of the southern Midcontinent. The surveys cover known critical mineral deposits and areas with the potential to host additional critical minerals based on the presence of one or more overlapping mineral systems. One aspect of EMRI emphasizes close collaboration between the USGS and the Association of American State Geologists, as well as other government and industry partners to leverage geophysical, geological, and geochemical expertise on both regional and local scales. The EMRI high-resolution airborne survey data provide new insights into the geophysical framework of the southern Midcontinent and its critical mineral endowment. Additionally, discoveries made from the data have directed new studies for critical mineral exploration.

southern Midcontinent

The influence of nodule versus crust morphology on the composition of seamount-hosted ferromanganese minerals

Ferromanganese mineral precipitation in the global oceans is ubiquitous, occurring in the form of both crusts and nodules at a broad range of depths and seafloor terrains. Although ferromanganese crusts and nodules are both composed of ferromanganese minerals, mineralogy and mean element concentrations compiled for regional crust versus nodule occurrences differ. Notably, most published compilations compare nodules from abyssal plain sediments to crusts forming on seamounts, and do not address the question as to whether mineral morphology may affect the composition of crusts and nodules in addition to environmental factors. To address this, we have compiled a dataset of co-located hydrogenetic (seawater sourced) open-ocean ferromanganese crusts and seamount-hosted nodules. The preliminary data presented here support our hypothesis that co-located crusts and nodules exhibit similar compositions, both in terms of their mineralogy and mean element concentrations, as well as overall variance in concentrations for any given element. These data indicate that local processes influence sample-to-sample variation in both crusts and nodules, in contrast to broader ferromanganese variation reported between open-ocean seamounts- hosted crusts and abyssal plain-hosted nodules.

Conference Paper

Observing northern high-latitude river systems to understand changes in a warming Arctic

Purpose of Review Streams and rivers are undergoing rapid change as the Arctic warms and thaws. We review recent observations in Arctic stream systems to identify ubiquitous changes and the most useful tools for observing change and exploring the underlying processes. Recent Findings Recent literature indicates increasingly significant trends in river hydrology and chemistry due to persistent warming in the Arctic and longer observational records for analysis. However, regional differences in the magnitude and direction of these trends persist. We also observe thresholds in ground thaw and surface–groundwater interactions that can impact river hydrology and chemistry. Summary Warming and thaw are occurring rapidly at high latitudes, resulting in increasing, yet variable responses in stream systems across regions and scales. These differences highlight the need for long-term records and an interdisciplinary approach to explain trends and predict future states. Stream systems respond to multiple landscape changes related to hydrology (changing precipitation and subsurface flow), geology (ground thaw dynamics), and ecology (vegetation change).

Current Climate Change Reports

Development of USGS NSHMs: Do small changes in hazard imply small changes in risk?

One of the flagship products from the U.S. Geological Survey (USGS) is the National Seismic Hazard Model (NSHM). Since 1976, the NSHM has been periodically updated to reflect newly published earthquake science and provide probabilistic estimates of seismic hazard for the United States. During each update cycle, alternative models are deliberated, analyzed, and documented through logic trees and their corresponding logic tree branch weights. For example, the decision to modify a logic tree branch weight may be influenced by sensitivity analyses of the logic tree branches in their effects on the mean hazard. However, do small changes in traditional measures of hazard imply small changes in risk? In this study, we make use of two update cycles of the USGS NSHMs and a National Bridge Inventory (NBI) from the Federal Highway Administration (FHWA) to explore the preceding question. Specifically, we first identify geographic locations in the conterminous United States in which the change in hazard from one cycle to another is relatively small. Next, we model the seismic risk to highway bridges for these locations and for each update cycle, while simultaneously distinguishing low hazard environments from high hazard environments. These data enable quantitative analysis of how much changes in risk can be expected given small changes in hazard, investigating the importance of risk models in decision-making during development of the USGS NSHMs.

Conference Paper

The use of fluorite geochemistry and machine learning to identify critical mineral systems

Fluorite (CaF 2 ) is a potential pathfinder to critical mineral and rare earth element (REE) deposits but its application has been limited to a narrow range of mineralization types. I show that fluorite is a robust recorder of mineralization fertility by applying statistical and machine-learning methods to a new global fluorite geochemical database. Distinct median rare earth and trace element patterns are observed among deposit types and genetic environments. Fluorite associated with carbonatites and REE deposits are relatively enriched in Sr and have minimal Eu anomalies. These characteristics define new bivariate discrimination diagrams that correctly identify 78% of carbonatite-related fluorite and 88% of fluorite from REE deposits. Random forest classifiers were developed for a wide range of mineralization types and genetic settings. Trained solely on rare earth element patterns, these models achieve accuracies of 77–79%. Higher classification accuracies (up to 88–96%) are obtained when including elements such as Sr, highlighting the significance of trace elements for optimal fluorite classification. The recognition of diagnostic fluorite compositional fingerprints, particularly in REE-fertile systems, underscores its potential as a pathfinder and indicator for critical mineral exploration in F-bearing environments.

Mineralium Deposita

Characterization of change in tree cover state and condition over the conterminous United States

Variability in the effects of disturbances and extreme climate events can lead to changes in tree cover over time, including partial or complete loss, with diverse ecological consequences. It is therefore critical to identify in space and time the change processes that lead to tree cover change. Studies of change are often hampered by the lack of data capable of consistently detecting different types of change. Using the Landsat satellite record to create a long time-series of land cover and land cover change, the U.S. Geological Survey Land Change Monitoring Assessment and Projection (LCMAP) project has made an annual time series of land cover across the conterminous United States for the period 1985 to 2018. Multiple LCMAP products analyzed together with map validation reference plots provide a robust basis for understanding tree cover change. In LCMAP (Collection 1.2), annual change detection is based on harmonic model breaks calculated at each Landsat pixel from the Continuous Change Detection and Classification (CCDC) algorithm. The results showed that the majority of CCDC harmonic model breaks (signifying change) indicated partial tree cover loss (associated with management practices such as tree cover thinning) as compared to complete tree cover loss (associated with practices like clearcut harvest or fire disturbance). Substantially fewer occurrences of complete tree cover loss were associated with change in land cover state. The area of annual tree cover change increased after the late 1990s and stayed high for the rest of the study period. The reference data showed that tree harvest dominated across the conterminous United States. The majority of tree cover change occurred in evergreen forests. Large estimates of disturbance-related tree cover change indicated that tree cover loss may have previously been underreported due to omission of partial tree cover loss in prior studies. This has considerable implications for forest carbon accounting along with tracking ecosystem goods and services.

Forests

Mine waste as a potential source of critical minerals and other commodities: Examples from the Four Corners states, USA

The growing demand for critical minerals and other mineral resources has raised concerns about possible supplies of these essential commodities. Mine waste is a potential source of these essential commodities. We compiled a geospatial database of publicly available data of the largest non-fuel mine waste features (>200,000 m 2 in areal extent) in the Four Corners states of the United States, where most of those features are from porphyry Cu deposits. The combined volume of those large porphyry Cu mine waste features is approximately 17 cubic kilometers, 60% of which is ore-related material such as tailings. Using publicly available data on density, grade, and previous recovery values, we estimate the contained endowments of Ag, As, Au, Bi, Cu, Mo, Re, S, Sb, Se, Te, and W. These estimates indicate endowments within ore-related mine wastes are collectively comparable to endowments of giant to supergiant deposits. If fully recovered, these commodities could meet current global demand from less than 1 year (Sb) to more than 200 years (Re), underscoring the enormous untapped resource potential of mine waste.

Arizona, Colorado, New Mexico, Utah

Stable isotope composition and geochemistry of calcite and dolomite in the Mountain Pass carbonatite: A lens into petrogenesis

Carbonatites host most of the global rare earth element (REE) deposits. The petrogenesis of these rocks, including magmatic and post-magmatic processes, are poorly understood but critical in forming and upgrading these deposits. The Mountain Pass carbonatite, which hosts the only active REE mine in North America, is lithologically variable but consistently contains >50% calcite and/or dolomite. Multiple generations of carbonates are evident, suggesting bulk analysis of carbonate minerals would generate a mixed isotopic and geochemical signature. In-situ stable carbon and oxygen isotopes, combined with geochemical analysis and petrography, distinguish carbonate generations, trace the source region of the carbonatite magma, and link carbonate genesis to REE mineralization throughout the intrusion. Primary carbon and oxygen isotope values outside the accepted mantle range may suggest a subduction-related carbon and oxygen source in the mantle. Deformation textures in primary calcite indicate syn- or post-crystallization ductile flow. Carbonates with secondary textures and heavy δ 13 C and δ 18 O values are associated with ore mineralization, suggesting fluid mobilization was important in concentrating REE and upgrading of the Mountain Pass deposit.

California