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USGS2025

Airborne geophysics for geologic mapping of critical mineral systems in the United States southern midcontinent

The increased demand for clean energy technology and a significant reliance on foreign supply chains have given impetus to understanding critical mineral systems and locating potential resources within the United States. At least thirteen critical mineral-bearing systems have been identified throughout the U.S. southern Midcontinent (Hofstra and Kreiner, 2020) but much of the region’s geologic framework is concealed by vegetation and sedimentary cover that hinder traditional geologic mapping efforts. Airborne geophysical data provide an effective way to overcome these obstacles and to provide additional insight into the deeper structures that underlie shallow mineralization. However, legacy airborne magnetic and radiometric data were collected using now-outdated instruments and methods, inconsistent survey parameters, and large flight-line spacings resulting in low-resolution data that present challenges to regional-scale study and interpretation. Over the last decade, the U.S. Geological Survey Earth Mapping Resources Initiative (EMRI) and National Cooperative Geologic Mapping Program have conducted a series of high-resolution airborne magnetic and radiometric surveys across the southern Midcontinent (Fig. 1) as part of an effort to improve understanding of the geophysical framework and natural resource potential in the region. These surveys are designed using modern survey methods and instruments with consistent parameters for flight-line spacing and flight height relative to magnetic sources. The EMRI airborne surveys are planned in collaboration with State geological surveys based on focus areas (Dicken et al., 2022) according to the presence of or potential for critical mineral deposits. High-resolution airborne magnetic and radiometric data cover focus areas such as the southeast Missouri iron metallogenic province and South-Central iron-oxide-apatite (IOA) – iron-oxide-copper-gold (IOCG) province, the Magnet Cove alkaline-carbonatite complex, the Midwest Permian ultramafic dike district, the Illinois-Kentucky fluorspar district, and several Mississippi Valley-type lead-zinc deposits and districts (Fig. 1). These focus areas represent known deposits or prospective host systems of critical minerals including rare earth elements (REEs), platinum-group elements (PGEs), cobalt, lithium, fluorspar, niobium, titanium, vanadium, lead, zinc, gallium, germanium, and many more. Other significant geologic and geophysical features covered include the Reelfoot rift, the New Madrid seismic zone, the Illinois basin, the Arkoma basin, the South-Central magnetic lineament, and the Kentucky-Tennessee magnetic anomaly (Fig. 1). This presentation focuses on new airborne magnetic and radiometric data with continuous coverage across parts of six states, preliminary interpretations, examples of geologic mapping applications, and discussion of newly discovered magnetic anomalies and follow-up investigations.

Conference Paper↗
USGS2025

USGS—An Unparalleled Scientific Asset

The U.S. Geological Survey (USGS) delivers information critical to powering our economy, managing our natural resources, and keeping Americans safe and healthy. 1 Mapping the Nation $21B Geologic maps save users an estimated 15% in annual costs: a value of between $14B and $21B. $25.6B in annual value to users of imagery from Landsat satellites, which were codeveloped by NASA and the USGS and operated through their lifespans by the USGS. $13.5B in annual benefits is generated by the USGS's 3D Elevation Program. Securing America’s Energy Independence 44% USGS-identified undiscovered geothermal energy is equal to 44% of current U.S. electricity generation. 29.4B barrels of oil and 391.6 trillion cubic feet of gas in recoverable resources are available on U.S. public lands based on USGS assessments. Protecting Americans’ Health and Safety $424B in recent wildland fire damages highlight the need for USGS fire science, which supports efforts to protect communities and reduce risk. USGS earthquake, volcano, landslide, and coastal hazard monitoring and information save lives and minimize costs; for example, $2.8M can be saved because of USGS enhanced information about a Mauna Loa eruption. $4.5B is the estimated cost of annual flooding. Through a network of over 11,885 streamgages, the USGS supports public safety and enables forecasts, early warning systems, and management actions that protect lives and property. Supporting National Security $3.1B The USGS identified a $3.1B risk to the American economy if China restricts gallium imports. This is one example underscoring the importance of the USGS mapping critical minerals, investigating supply chains, and producing the Nation’s critical minerals list. Enhancing Our Lands and Waters $21B in estimated annual costs results from invasive species. The USGS’s invasive species research informs approaches used to reduce their effects on agriculture, water infrastructure, disease transmission, fisheries, and outdoor recreation. USGS innovations support early warnings for harmful algal blooms—over $2M in yearly benefits are provided to Kansas alone. $45B USGS science informs the management of big game (such as deer and elk). The big-game hunting industry contributes $45B to the U.S. economy. Fostering American Prosperity $4.1T Mineral commodities are necessary for the $4.1T in value added to the GDP by major industries that consume processed mineral materials and employ 1 million workers. Because of this, USGS data on mineral supply, demand, and trade are highly valued. 45,000 metric tons Rare earths power the growing technology economy, including cell phones, electric vehicles, and medical devices. For over 70 years, USGS work has supported the discovery of rare earth resources in California’s Mountain Pass area, which produced 45,000 metric tons of rare earth concentrates in 2024—over 11% of the global supply. Guarding American Food Security $70.2B USGS science informs early warning systems and management strategies to mitigate disease outbreaks in agriculture—critical research on highly pathogenic avian influenza, for example, helps safeguard the $70B value in poultry and egg production. $11.8B USGS groundwater tools are vital for agriculture; for example, in the Mississippi Alluvial Plain, 65% of farming relies on groundwater to support its $11.8B annual industry. 1 Values throughout are given in billions (B), millions (M), and trillions (T) of U.S. dollars. GDP is “Gross Domestic Product.” Percentages are shown as %.

General Information Product↗
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↗
USGS2024

Tungsten skarn quantitative mineral resource assessment and gold, rare earth elements, graphite, and uranium qualitative assessments of the Kuldjuktau and Auminzatau Ranges, in the central Kyzylkum region, Uzbekistan

A new quantitative mineral resource assessment for tungsten skarn was conducted for the Auminzatau and Kuldjuktau mountain ranges in Central Uzbekistan, along with qualitative assessments of orogenic gold, rare earth elements (REEs), amorphous graphite, and uranium. By integrating a variety of geological, geochemical, geophysical, and remote sensing data sets, estimates of undiscovered tungsten skarn deposits in permissive tracts are combined with grade and tonnage distributions of known deposits to generate probabilistic estimates of undiscovered resources. Undiscovered deposits in Auminzatau are estimated to contain median resources of 98 thousand metric tons (kt) of WO 3 with a 70 percent (%) probability of at least 28 kt and a 10% probability of at least 468 kt, of which 16 kt to 293 kt may be economic to extract. In Kuldjuktau, the undiscovered deposits are estimated to contain median resources of 27 kt of WO 3 with a 60% probability of at least 12 kt and a 10% probability of at least 208 kt, of which 5 kt to 132 kt may be economic to extract. Our results suggest that the Auminzatau–Kuldjuktau Mountains area is highly prospective for additional discovery of significant Au and U resources and has low prospectivity for discovery of significant REE and graphite resources.

Minerals↗
USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

Indiana↗
USGS2026

Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution

Hydrologic variation is a primary driver of stream ecosystems. Changing hydrology can lead to assemblage shifts and alterations in suitable habitat for freshwater species. As climate change is predicted to alter flow patterns in addition to increasing water temperatures, insight into relationships between species occupancy, hydrology, and temperature is critical for understanding current and future distributions. We examined how hydrologic variability, temperature, and other environmental variables interact to influence Micropterus dolomieu (Smallmouth Bass) occurrence. We used Spatial Stream Network models, allowing for the incorporation of spatial autocorrelation along streams' unique dendritic network, to examine Smallmouth Bass occupancy across a range of hydrologic variation in the Ozark-Ouachita Interior Highlands, USA. Hydrologic variation was the main driver of Smallmouth Bass occurrence, with occurrence more likely in groundwater streams with low hydrologic variation and high flow permanence. For groundwater streams, occurrence was positively associated with summer stream temperature and negatively associated with annual stream temperature. As variation increased, more variables showed significant relationships with occurrence. Distance metrics were important for all models, however as hydrologic disturbance increased, flow connected distance played a lesser role and stream distance played a greater role. Hydrologic variability was the overarching determinant of Smallmouth Bass occurrence and strongly influenced the predictive importance of environmental variables and geospatial relationships. Greater hydrologic variability resulted in stronger statistical relationships between occurrence and environmental variables and an increased importance of system connectivity. As climate change alters hydrologic processes and streams become more variable, understanding and accounting for these shifting relationships is essential.

Arkansas, Kansas, Missouri, Oklahoma↗
USGS2025

Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California

The Mountain Pass carbonatite stock is the largest rare earth element (REE) deposit and only active REE mine in the United States. The carbonatite intrusion and spatially associated alkaline silicate intrusions constitute the Mountain Pass Intrusive Suite, which is located within the Mojave Province in California. Both the carbonatite and the alkaline silicate rocks are enriched in large ion lithophile elements and light REEs, and less enriched to depleted in high field strength elements, indicating the mantle source region was metasomatically enriched in incompatible trace elements. The cause of this metasomatic mantle enrichment and the genetic relationship between the carbonatite and the alkaline silicate stocks are poorly understood. In this study, major and trace element geochemical data and isotopic (Rb-Sr, Sm-Nd, and Lu-Hf) data are presented to constrain genesis of the Mountain Pass Intrusive Suite, from mantle source region to the intrusion of the stocks. Our geochemical data are consistent with derivation of the alkaline silicate and carbonatite melts through partial melting from a shared mantle source region rather than through liquid immiscibility or fractional crystallization and separation of a carbothermal fluid. Although the Rb-Sr isotopic system in the Mountain Pass Intrusive Suite is disturbed at the whole-rock scale, the isotopic systems for whole-rock Sm-Nd (εNd i = ‐2.2 ± 0.8) and zircon Lu-Hf (εHf i = 0.1 ± 1.1) are robust and support mantle derivation of the magmas. Geochemical modeling using experimentally derived partition coefficients was used to identify possible causes of enrichment in incompatible elements through metasomatism in the mantle source region. Modeling of metasomatism by melts derived by partial melting of deeply subducted carbonated sediments approximates observed Mountain Pass Intrusive Suite trace element chemistry. Scattered εHf i in inherited zircon (2.8 ± 2.6) is consistent with derivation from an arc-related environment with substantial crustal contamination. Paleotectonic studies in the Mojave Province indicate that regional subduction preceded emplacement of the Mountain Pass Intrusive Suite by ∼300 Ma. Melting of the Mountain Pass source region may have been caused by post-collisional thermal relaxation and extension.

California↗
USGS2026

Utilization of multiple geochronology techniques to constrain the age of laterization and mineralization of the world-class Mount Weld rare earth element deposit, Western Australia

Pervasive chemical weathering on stable cratons may form thick regoliths and elemental enrichment, but constraining the age of regolith formation is challenging. In this study we utilize multiple geochronological techniques on different minerals from the world-class Mount Weld rare earth element (REE) deposit, formed by lateritic weathering of a carbonatite, to constrain the age of formation and provide insight into landscape evolution. The oldest dates, ca. 100 to 38 Ma, are from Lu-Hf dating of churchite [HREE(PO 4 )·2(H 2 O)], a heavy REE phosphate mineral. Growth bands on individual minerals show a younging outwards. 40 Ar/ 39 Ar geochronology of cryptomelane [K(Mn 4+ ,Mn 2+ )₈O₁₆] yielded dates from ca. 40 to 27 Ma. Similarly, (U-Th)/He geochronology of goethite [FeO(OH)] yielded dates ranging from ca. 45 to 19 Ma. Integrating results into regional constraints, suggests 1) churchite formed by mineral saturation in a karst-like setting below the water table from ca. 100 to 40 Ma, 2) with minor uplift and erosion, cryptomelane and goethite formed at or near the water table between ca. 45 and 19 Ma, 3) after ca. 15 to 10 Ma chemical weathering within the profile had ended. Other studies document that the region experienced minimal uplift and a wet, warm climate from ca. 100 Ma to 15 Ma. These conditions and the high carbonate content of the carbonatite promote extensive chemical weathering, a deep weathering profile, and the preservation of the weathered section. This study highlights the use of multiple geochronological techniques utilizing different minerals to provide insight into how laterites form and to constrain the timing and history of the formation of this important mineral deposit.

Western Australia↗
USGS2026

Legacy of the fumigant 1,2-dibromo-3-chloropropane (DBCP) in California groundwater

The fumigant pesticide 1,2-dibromo-3-chloropropane (DBCP) was widely used in California agriculture during the 1960s and 1970s before being banned in 1979. Despite this ban, DBCP continues to contaminate groundwater due to its persistence and mobility. This study evaluates the distribution, historical trends, and projected persistence of DBCP in California using data from over 13,000 public supply wells and additional domestic, irrigation, and observation wells (1980-2022). Since 2010, DBCP has been detected in 9% of public supply wells statewide, with higher frequencies in the San Joaquin Valley (21%) and upper Santa Ana River watershed (13%), where DBCP use was most prevalent. Approximately 70% of wells had decreasing concentration trends, whereas increases were more common in deeper wells, indicating downward vertical migration of the DBCP front. Groundwater age estimates show that recharge timing aligns with the 1960s–1970s loading period, enabling reconstruction of peak inputs and providing a basis for age based modeling. To estimate future persistence, we applied a one dimensional advection–dispersion model that simulates long term declines in peak concentrations based on groundwater age, historical loading, and a 38 year degradation half life. Model projections suggest that concentrations above the maximum contaminant level may persist in a declining number of wells until approximately 2080 (range: 2048–2109), with longer persistence in the San Joaquin Valley. The simplified modeling framework, based on age distributions typical of wells capturing peak concentrations, can provide practical regional scale assessment of non-point source contaminants where long-term monitoring exists. This study highlights how the legacy of DBCP contamination will likely affect California's groundwater resources throughout the 21st century.

California↗
USGS2025

Summary of selenium in the lower Gunnison River Basin, Colorado—Information and data gaps

The Cretaceous Mancos Shale is a geologic source of selenium in the lower Gunnison River Basin. Natural weathering processes and human activity mobilize selenium from the Mancos Shale and derived materials, and surface water, groundwater, and sediment all affect the transport of selenium from source areas to receiving streams and biota. Selenium accumulates through the aquatic food chain, and its toxic effects can result in invertebrate mortality and mortality, decreased reproduction, and deformities to fish and birds. The Bureau of Reclamation, in cooperation with the State of Colorado and Gunnison River Basin water users, is implementing a Selenium Management Program to reduce selenium concentrations in the lower Gunnison River Basin of Colorado. Goals of the Selenium Management Program are to (1) achieve compliance with the State of Colorado chronic aquatic-life standard for dissolved selenium (4.6 micrograms per liter) in the Gunnison River near Grand Junction, Colorado; (2) sufficiently improve water-quality conditions to assist in the recovery of endangered species in the Gunnison and Colorado Rivers by reducing selenium concentrations; and (3) support continued water uses in the basin. Many previous studies have contributed to the understanding of selenium in the environment; however, monitoring and research data gaps exist in the lower Gunnison River Basin. The purpose of this report is to summarize information regarding selenium in the lower Gunnison River Basin and describe strategies for scientific research and monitoring to potentially improve understanding of selenium sources; processes affecting the mobilization, transport, and fate of selenium; and the effects of selenium-mitigation projects in the lower Gunnison River Basin. Monitoring and research data gaps discussed in this report include geologic mapping and geochemical source characterization, long-term and ongoing monitoring of the surface-water and groundwater networks, developing and refining statistical models, characterizing selenium on suspended sediment, modeling selenium in the food web, evaluating best management practices, and more.

Colorado↗
USGS2025

Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin

Future water availability depends on understanding the responses of constituent concentrations to hydrologic change. Projecting future water quality remains a methodological challenge, particularly when using discrete observations with limited temporal resolution. This study introduces Weighted Regression on Time, Discharge, and Season for Projection (WRTDS-P), a novel, computationally efficient method that enables the projection of daily stream water quality under varying hydrologic conditions using commonly available discrete monitoring data. WRTDS-P model performance was validated using 39 sites in the Delaware River Basin (DRB) and four key constituents: specific conductance (SC), nitrate (NO 3 − ), magnesium (Mg 2+ ) and calcium (Ca 2+ ). Projections were tested against holdout data from the final 1 to 5 years of each time series, demonstrating robust predictive capability, with median Nash-Sutcliffe efficiencies of 0.67 for SC, 0.56 for NO 3 − , 0.65 for Ca 2+ , and 0.79 for Mg 2+ . Model uncertainty was correlated with indicators of hydrologic or geochemical mass-sinks, such as groundwater storage and adsorption in wetland soils. Drought scenario analyses for SC used ranges of reduced discharge including flows from the 1965 drought of record. Scenarios predicted widespread increases of SC, especially in southern DRB streams where baseline SC levels are already elevated. Fractional increases of SC were more uniformly distributed, indicating potential risk to sensitive ecosystems. Notably, drought-induced SC increases were positively correlated with interannual SC trends, indicating that hydrologic extremes could exacerbate ongoing salinization. This work provides a transferable and interpretable framework for projecting future water quality and assessing hydrologic risk to water resources and aquatic ecosystems.

Delaware, New Jersey, New York, Pennsylvania↗
USGS2026

Comparative crop yield forecasting using satellite-derived biophysical and agro-climatic predictors in Sub-Saharan Africa

Timely and accurate crop yield forecasting is central to food security early warning systems, particularly in climate-vulnerable regions. While operational forecasting frameworks commonly rely on precipitation and vegetation indices such as NDVI, their ability to provide actionable lead time remains limited. Here, we evaluate the added value of satellite-derived biophysical Essential Climate Variables (ECVs): Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FAPAR), for forecasting millet yield in Burkina Faso (BF) and maize yield in South Africa (ZA) and Malawi (MW). Using Random Forest models, we quantify forecast skill across the growing season at both national and sub-national scales. Results show that LAI and FAPAR provide effective forecast lead times of approximately 4 months in BF, 2 months in ZA, and up to 6 months in MW relative to harvest. At peak performance, Mean Absolute Percentage Error (MAPE) reaches 19.8% (LAI) and 23.8% (FAPAR) in BF, 12.0% and 9.8% in ZA, and 21.8% and 20.8% in MW, respectively. Across countries, biophysical parameters often outperform NDVI and precipitation, particularly in arid and semi-arid regions. At the sub-national level, LAI and FAPAR enable classification of administrative units into high and moderate-skill forecast units, revealing strong spatial heterogeneity linked to crop dominance. However, forecast skill declines where the target crop is not the dominant type, highlighting an important limitation for operational deployment. Overall, the findings suggest that satellite-derived biophysical parameters can provide earlier and more spatially resolved yield signals than commonly used predictors, with potential to improve the timeliness and effectiveness of food security early warning systems.

Remote Sensing Applications: Society and Environme↗
USGS2025

Alteration mapping in granitic gneiss using handheld geophysical and geochemical instruments: Implications for iron oxide-apatite and rare earth elements exploration

The Adirondack Mountains of New York, U.S.A. contain iron oxide-apatite (IOA) mineral deposits with variable concentrations of rare earth elements (REE). The IOA mineral deposits are typically hosted in the Lyon Mountain Granite Gneiss and are spatially correlated with extensive Na metasomatism (albitization) of the surrounding country rocks, although some mineral deposits also occur in metagabbro, paragneiss, and anorthosite hosts. The location of albitization zones is key to finding new IOA mineral deposits and better understanding the mineralization processes associated with their genesis. However, the Na alteration zones are generally not visibly identifiable in outcrop or hand specimens because the color and textural changes are subtle and are thus difficult to map. Here, we discuss the results from testing two spectroscopic techniques (handheld, field gamma-ray spectroscopy, and portable X-ray fluorescence (pXRF)) to characterize albitization zones surrounding IOA mineral deposits. The gamma-ray and pXRF spectrometers successfully distinguished the relative intensity of alteration in the Lyon Mountain Granite Gneiss based on the K abundance. The measured K content decreases towards the IOA mineral deposits, and the magnitude and width of the gradient are similar along the strike of each mineral deposit. Elevated Th and U values are present in host rocks adjacent to REE-bearing IOA mineral deposits. The pXRF and gamma-ray spectrometer K values are remarkably consistent with laboratory-based, whole-rock XRF compositional data and, therefore, useful for semi-quantitative analysis. Notably, albitization aureoles are consistent around REE-rich and REE-poor mineral deposits, suggesting that saline fluids are essential for the petrogenesis of IOA mineral deposits but may not be critical to REE mineralization. Ultimately, this study demonstrates the utility of handheld gamma-ray and pXRF spectrometry for identifying otherwise cryptic albitization gradients associated with IOA mineral deposits in granitic gneiss.

New York↗
USGS2025

Methodology and technical input for the 2025 U.S. List of Critical Minerals—Assessing the potential effects of mineral commodity supply chain disruptions on the U.S. economy

The Secretary of the Interior, acting through the Director of the U.S. Geological Survey, is tasked by section 7002 (“Mineral Security”) of title VII (“Critical Minerals”) of the Energy Act of 2020 (Public Law 116–260, December 27, 2020, 116th Congress) with reviewing and revising the methodology used to evaluate mineral commodity supply risk and the U.S. List of Critical Minerals (LCM) no less than every 3 years. Following two previous LCM assessments, this analysis represents the latest technical input for evaluating each mineral commodity’s supply risk and determining their recommended status on the LCM. We evaluated mineral commodity supply risk using two criteria: (1) an economic effects assessment that quantified the potential effects of various trade disruption scenarios on the U.S. economy, and (2) an examination of whether the mineral commodity’s U.S. supply chain relied on a sole domestic producer that represented a single point of failure. For the first criterion, postdisruption equilibrium quantities and prices for each mineral commodity were calculated based on their price elasticities of supply and demand and the availability of excess production capacity for each yearlong foreign trade disruption scenario. Subsequently, a nonlinear optimization routine was used with detailed economic input-output tables to estimate the potential economic effects on the U.S. economy of over 1,200 scenarios for 84 mineral commodities. After accounting for the probability of each scenario’s occurrence, the overall results are presented in terms of changes in U.S. gross domestic product (GDP) by individual industry and the economy overall. The results, which ranged from a net decrease in U.S. GDP of nearly $4.5 billion to a net increase of $33 million, largely reflect U.S. import dependency and world production concentration. Using the Jenks natural breaks optimization method, a statistical classification technique, we categorized the mineral commodities into several classes based on this overall risk quantification. Mineral commodities with annualized probability-weighted net decreases in U.S. GDP greater than $2 million were recommended for inclusion on the LCM. If a mineral commodity did not meet the threshold for inclusion on the LCM under the first criterion, its domestic supply chain was examined under the second criterion, which recommended a mineral commodity for inclusion on the LCM if there was only a single domestic producer. Ultimately, the two criteria resulted in the recommendation of the addition of six mineral commodities (in descending risk order, potash, silicon, copper, silver, rhenium, and lead) to and the removal of two mineral commodities (arsenic and tellurium) from the LCM. By using an economic effects assessment, the results of this analysis provide a prioritization that can also be compared directly against other risk analyses and the cost of various risk mitigation strategies.

Open-File Report↗
USGS2026

The Sedimentary Geochemistry and Paleoenvironments Project Phase 2 data release: An open data resource for the study of Earth's environmental history

Geochemical data from sedimentary rocks are the primary source of information regarding Earth's surface evolution through time, including its air and water envelopes and interactions with life and deep Earth processes. The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is a scientific consortium centered around open data and community-driven development of cyberinfrastructure tools and resources for sedimentary geochemistry and Earth history. Here we describe the SGP Phase 2 data release, which focused on incorporating Paleoproterozoic and Mesoproterozoic (2500–1000 million years ago) data and better accommodating carbonate data. This data release was built through the involvement of >200 researchers worldwide in academia, government, and industry, and provides the largest available public data resource for our user community in the academic fields of geochemistry, sedimentology, tectonics, paleontology, Earth history, and paleoclimate, as well as the petroleum and minerals industries. The dataset now encompasses 126,006 samples and 4,132,371 geochemical analyses. In addition to direct entry by SGP Team Members, we have ingested and incorporated datasets from the Geoscience Australia OZCHEM database, the Alberta Geological Survey, and the Deep-Time Marine Sedimentary Element Database (DM-SED) compilation. This paper details sampling in the Phase 2 dataset with respect to age, geography, lithology, and other geological characteristics, documents access via our search website and API, discusses possible issues and/or biases in the dataset that could impact analyses, describes plans for governance and stewardship of data from Indigenous lands, and serves as the citable reference paper for the data release.

Chemical Geology↗
USGS2024

Factors contributing to pesticide contamination in riverine systems: The role of wastewater and landscape sources

Wastewater treatment plant (WWTP) discharges can be a source of organic contaminants, including pesticides, to rivers. An integrated model was developed for the Potomac River watershed (PRW) to determine the amount of accumulated wastewater percentage of streamflow (ACCWW) and calculate predicted environmental concentrations (PECs) for 14 pesticides in non-tidal National Hydrography Dataset Plus Version 2.1 stream segments. Predicted environmental concentrations were compared to measured environmental concentrations (MECs) from 32 stream sites that represented a range of ACCWW and land use to evaluate model performance and to assess possible non-WWTP loading sources. Statistical agreement between PECs and MECs was strongest for insecticides, followed by fungicides and herbicides. Principal component analysis utilizing optical fluorescence and ancillary water quality data identified wastewater and urban runoff sources. Pesticides that indicated relatively larger sources from WWTPs included dinotefuran, fipronil, carbendazim, thiabendazole, and prometon whereas imidacloprid, azoxystrobin, propiconazole, tebuconazole, and diuron were more related to urban runoff. In addition, PECs generally comprised a low proportion of MECs, which indicates possible dominant loading sources beyond WWTP discharges. Cumulative potential toxicity was higher for sites with greater ACCWW and/or located in developed areas. Imidacloprid, fipronil, and carbendazim accounted for the largest portion of predicted potential toxicity across sites. The chronic aquatic life toxicity benchmarks for freshwater invertebrates were exceeded for 82 % of the imidacloprid detections ( n = 28) and 47 % of the fipronil detections ( n = 19). These results highlight the ecological implications of pesticide contamination from WWTP discharges and also the potential legacy effects from accumulated soil and groundwater sources. Pesticide management strategies that mitigate both current and historical impacts may improve the health of aquatic ecosystems.

Potomac River watershed↗
USGS2025

Special issue "Effects of surface geology on seismic motion (ESG): General state-of-research"

To understand and predict the behaviors of strong ground motions incurred during devastating earthquakes, studies focused on the “effects of surface geology (ESG) on seismic motions” (following tradition, herein contracted as: “ESG”) have progressed steadily in the last three decades. These ESG studies typically involve in situ measurements of the wavefield and commonly apply both analytical and computational approaches. Concurrently, improvements in ESG related research can be readily attributed to the proliferation of openly accessible strong motion data, as well as advances in computational power. Nevertheless, there remain significant shortfalls in our understanding of the epistemic and aleatory uncertainties associated with the ESG as demonstrated by phenomena from recent deadly earthquake-related site effects. Thus, investigations toward addressing these deficiencies should be underscored in future earthquake related disaster mitigation efforts. This special issue of Earth, Planets, and Space (EPS) is dedicated to the ongoing efforts by the International Association of Seismology and Physics of the Earth’s Interior (IASPEI) and the International Association of Earthquake Engineering (IAEE) that champion activities promoting studies related to the ESG.

Earth, Planets and Space↗
USGS2025

Rare earth element-mineralized carbonatite in the Bear Lodge Alkaline Complex, USA—Ore genesis implications from fluid inclusion characterization

Rare earth element (REE) resources of the Bear Lodge Alkaline Complex, Wyoming, are hosted in variably leached carbonatite spatially related to diatreme breccia pipes. We investigated the genesis of REE and lesser-known gold resources through fluid inclusion analysis of carbonatite, fluorite breccia, and smoky quartz vein samples. Physicochemical characteristics of inclusion-trapped fluids were evaluated using petrography, microthermometry, Raman spectroscopy, decrepitate mound analysis, energy-dispersive spectroscopy, laser ablation inductively coupled plasma mass spectrometry, and noble gas isotope analysis. Microthermometry results reveal three fluid types that affected carbonatite dikes within deeper zones that escaped near-surface, ore-grade REE enrichment: (1) high-temperature (330–432°C) magmatic fluid captured in fine-grained calcite; (2) REE-enriched alkali bicarbonate-sulfate brine; and (3) low-temperature (117–182°C) diluted magmatic or meteoric water. Multiphase brine-like inclusions contain burbankite, nahcolite, strontianite, celestine and alkali sulfate daughter crystals, linking them to early burbankite mineralization. Peripheral smoky quartz and fluorite occurrences at Smith Ridge, 1.5 km from the central carbonatite dike swarm, contain primary inclusions that are Cl-poor and rich in Na-HCO 3 -SO 4 , similar to secondary and pseudosecondary inclusions in carbonatites. Helium isotopes reveal a MORB-like source for carbonatite samples and an older crust signature at Smith Ridge, consistent with the proximal ridge-top exposures of Archean granite. Results from this fluid inclusion study coupled with previous studies of carbonatite mineral paragenesis, show that light REEs (LREEs) were not mobilized great distances. Instead, burbankite crystallized within carbonatite from alkali bicarbonate fluids. With sodium retained in early burbankite, outward-emanating fluids enriched in potassium relative to sodium (higher K:Na) resulted in potassium–ferric iron metasomatism of silicate host rocks. This alkali fractionation was accompanied by fractionation of LREEs and heavy REEs (HREEs), with LREEs dominating the central carbonatite resources. In contrast, areas of peripheral REE mineralization at Bear Lodge are commonly characterized by higher HREE:LREE ratios. The K:Na ratio of associated fenites or alteration assemblages could be indicative of early crystallized burbankite in carbonatites and REE fractionation processes potentially leading to areas of concentrated HREEs with greater supply vulnerabilities.

South Dakota, Wyoming↗