Continental remobilization is a crucial driver of metallogenesis and the formation of ore deposits. Some of the world’s largest mineral deposits of the economically valuable elements tin (Sn), tungsten (W), gold (Au), copper (Cu), lead (Pb), and zinc (Zn) formed during the Mesozoic Era. Additionally, the chemistry and distribution of the elements Sn and W have been investigated in previous studies to understand planetary formation and differentiation processes. These two elements are largely co-located during certain South China Mesozoic metallogenic events but are not co-located during other time periods in the same regions. Here, we investigated the mineral chemistry network similarities and dissimilarities of Sn and W to understand their mineral formation and distribution during the Mesozoic Era and throughout Earth history. Mineral chemistry network community detection analysis and electronegativity associations among mineral constituent elements of Sn minerals and W minerals indicate that the elements have similar chemistry among their oxide minerals. However, Sn forms a much wider range of minerals that also contain S compared to W, which occurs in a limited number of S-containing minerals. The divergent constituent element interactions among S-containing Sn minerals and W minerals reflect the redox sensitivity and importance of oxygen (O) fugacity in Sn mineral formation. Conversely, extensive W mineral deposits are known to form at both high and low O fugacities. The similarities and differences between the mineral chemistry networks of Sn and W reflect the mineral distribution of the two elements in the Sn-W mineralization event from 160 to 139 Ma vs. the Sn–uranium (U) mineralization event from 125 to 98 million years ago (Ma). The mineral chemistry and distribution of Mesozoic Sn and W deposits illustrate the contrasting importance of redox and O fugacity on the mineral formation of different elements, and the dynamic crustal evolution that took place during this period of Earth history.
","language":"English","publisher":"MDPI","doi":"10.3390/geosciences16040158","usgsCitation":"Moore, E.K., Morrison, S.M., and Hatter, A., 2026, The mineral chemistry networks of tin and tungsten reflect metallogenic eras of the Mesozoic: Geosciences, v. 16, no. 4, 158, 14 p., https://doi.org/10.3390/geosciences16040158.","productDescription":"158, 14 p.","ipdsId":"IP-184681","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":505055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences16040158","text":"Publisher Index Page"},{"id":504994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Elisha Kelly 0000-0002-9750-7769","orcid":"https://orcid.org/0000-0002-9750-7769","contributorId":334043,"corporation":false,"usgs":true,"family":"Moore","given":"Elisha","email":"","middleInitial":"Kelly","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":962330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morrison, Shaunna M.","contributorId":371761,"corporation":false,"usgs":false,"family":"Morrison","given":"Shaunna","middleInitial":"M.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":962331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hatter, Amber","contributorId":352523,"corporation":false,"usgs":false,"family":"Hatter","given":"Amber","affiliations":[{"id":84250,"text":"Department of Environmental Science, School of Earth and the Environment, Rowan University, Glassboro, NJ, United States","active":true,"usgs":false}],"preferred":false,"id":962332,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274159,"text":"sir20265121 - 2026 - Stream sediment sources in Medicine Creek, northern Missouri and southern Iowa","interactions":[],"lastModifiedDate":"2026-03-13T18:29:46.242926","indexId":"sir20265121","displayToPublicDate":"2026-03-02T13:01:12","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-5121","displayTitle":"Stream Sediment Sources in Medicine Creek, Northern Missouri and Southern Iowa","title":"Stream sediment sources in Medicine Creek, northern Missouri and southern Iowa","docAbstract":"This report presents the results of a cooperative study by the U.S. Geological Survey and Missouri Department of Natural Resources to quantify sediment transport source contributions in the Medicine Creek drainage basin. Understanding relative source contributions provides valuable information for selecting the conservation practices that may be most effective in reducing sediment and sediment-associated nutrient transport in the Medicine Creek drainage basin and similar areas of the Lower Grand River drainage basin. Sediment samples were collected from potential contributing areas (source samples) and from fluvial-transported samples (target samples). Source sample types included streambanks, row crop fields, and a combined pastures and forests category. Samples were analyzed for particle size and quantity of carbon, nitrogen, stable isotopes of carbon and nitrogen, and 49 mineral elements as potential tracers. Results for the carbon stable isotope ratio of carbon-13/carbon-12 (δ13C) and concentrations of total carbon, total nitrogen, calcium, potassium, and copper were selected by discriminant function analysis as the best combination of multiple tracers to differentiate each source type. The discriminant function analysis poorly differentiated pastures and forests, so these source types were combined. The sources defined by the discriminant function analysis were then used in an unmixing model to apportion sources for each target sample.
In the study area, transported sediment was predominantly bank sediment, with an overall average of 86.9 percent of suspended-sediment samples and depositional streambed samples attributed to bank material. Suspended-sediment samples from the mainstem of Medicine Creek were dominated by bank sediments (average of 95.8 percent), and depositional streambed samples from throughout the drainage basin had more variable source contributions with an average of 71.1 percent attributed to bank material. The relative importance of upland sources (row crop fields and the combined pastures and forests category) varied seasonally and with streamflow but was not related to land use or drainage basin size. Relative contributions from upland sources were greater in the summer through winter rather than spring and during lower streamflow, though this may be driven by the seasonality of streamflow. These results indicate management practices that reduce bank erosion could be effective strategies for managing the dominant source of sediment and sediment-associated phosphorus.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265121","collaboration":"Prepared in cooperation with Missouri Department of Natural Resources","usgsCitation":"Garrett, J.D., 2026, Stream sediment sources in Medicine Creek, northern Missouri and southern Iowa: U.S. Geological Survey Scientific Investigations Report 2026–5121, 11 p., https://doi.org/10.3133/sir20265121.","productDescription":"Report: vi, 11 p.; Data Release; Dataset","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-164057","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501166,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119303.htm","linkFileType":{"id":5,"text":"html"}},{"id":500681,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":500680,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13EN5TA","text":"USGS data release","linkHelpText":"Chemical and physical data for sediment source and fluvial target samples for fingerprinting of suspended and bed sediment in Medicine Creek, Missouri and Iowa"},{"id":500679,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265121/full"},{"id":500678,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5121/images/"},{"id":500677,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5121/sir20265121.XML"},{"id":500676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5121/sir20265121.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5121"},{"id":500675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5121/coverthb.jpg"}],"country":"United States","state":"Iowa, Missouri","otherGeospatial":"Medicine Creek drainage basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.1667,\n 40.75\n ],\n [\n -93.5,\n 40.75\n ],\n [\n -93.5,\n 40\n ],\n [\n -93.1667,\n 40\n ],\n [\n -93.1667,\n 40.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications.
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David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":958567,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272057,"text":"70272057 - 2026 - Widespread anhydrite saturation in Laramide-age arc magmas of southwestern USA","interactions":[],"lastModifiedDate":"2026-01-05T16:46:17.040705","indexId":"70272057","displayToPublicDate":"2025-10-03T09:08:39","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Widespread anhydrite saturation in Laramide-age arc magmas of southwestern USA","docAbstract":"Anhydrite is considered a rare mineral phase in magmas, with only ∼33 documented occurrences worldwide. However, anhydrite readily decomposes in the near-surface environment, making it difficult to recognize its former presence in rocks collected at or near Earth’s surface. In such samples, only small anhydrite inclusions fully shielded within other minerals can have survived. During a recent field trip to the southwestern USA, we sampled 17 Laramide-age (ca. 40−80 Ma) magma systems, most of which are associated with porphyry copper deposits. A systematic search for anhydrite inclusions preserved within apatite, amphibole, plagioclase, and quartz phenocrysts in ∼100 rock samples by optical microscopy and Raman spectroscopy revealed that each of these 17 magma systems was at least temporarily anhydrite-saturated. Also, most previously identified magmatic anhydrite-bearing intrusions are associated with porphyry copper deposits, and both intrusive and volcanic rocks containing magmatic anhydrite show high Sr/Y ratios. These observations suggest that anhydrite saturation and porphyry copper formation are linked via magma fractionation at high pressure. Compared to average arc magmas, anhydrite-bearing magmas are unusually oxidized and sulfur-rich and seem to also be unusually water-rich. Hence, our preferred interpretation is that magma generation and/or fractionation at high pressure promotes the formation of superhydrous and oxidized magmas, which in turn promotes high sulfur contents and ultimately the precipitation of anhydrite. The high mineralization potential of these magmas does not need to result from their high sulfur content but could be caused by other properties of high-pressure magmas.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G53661.1","usgsCitation":"Audétat, A., Chang, J., and Gaynor, S.P., 2026, Widespread anhydrite saturation in Laramide-age arc magmas of southwestern USA: Geology, v. 54, no. 1, p. 19-23, https://doi.org/10.1130/G53661.1.","productDescription":"5 p.","startPage":"19","endPage":"23","ipdsId":"IP-180127","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":496491,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.1850161548798,\n 37.09668430702368\n ],\n [\n -114.17123099542934,\n 36.1314881664468\n ],\n [\n -114.53871291780632,\n 36.149655948885254\n ],\n [\n -114.81618548536994,\n 35.86279700093031\n ],\n [\n -114.72255144506553,\n 32.378354757715044\n ],\n [\n -111.30008643678198,\n 31.339553209100846\n ],\n [\n -109.30561954381162,\n 31.352787834987573\n ],\n [\n -108.17268046973098,\n 31.288413412134357\n ],\n [\n -108.08261646812497,\n 31.7457427678113\n ],\n [\n -103.05693498349231,\n 31.994084642806044\n ],\n [\n -103.05693498349231,\n 37.09668430702368\n ],\n [\n -114.1850161548798,\n 37.09668430702368\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"54","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Audétat, Andreas","contributorId":348171,"corporation":false,"usgs":false,"family":"Audétat","given":"Andreas","affiliations":[{"id":83309,"text":"Bavarian Geoinstitute, University of Bayreuth","active":true,"usgs":false}],"preferred":false,"id":949942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chang, Jia","contributorId":348172,"corporation":false,"usgs":false,"family":"Chang","given":"Jia","affiliations":[{"id":83309,"text":"Bavarian Geoinstitute, University of Bayreuth","active":true,"usgs":false}],"preferred":false,"id":949943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaynor, Sean Patrick 0000-0002-8353-511X","orcid":"https://orcid.org/0000-0002-8353-511X","contributorId":346264,"corporation":false,"usgs":true,"family":"Gaynor","given":"Sean","email":"","middleInitial":"Patrick","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949944,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272681,"text":"70272681 - 2025 - Drone-based radiometric surveys provide high-resolution mine waste characterization","interactions":[],"lastModifiedDate":"2025-12-04T16:04:36.978233","indexId":"70272681","displayToPublicDate":"2025-11-01T09:57:21","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3568,"text":"The Leading Edge","active":true,"publicationSubtype":{"id":10}},"title":"Drone-based radiometric surveys provide high-resolution mine waste characterization","docAbstract":"Airborne radiometric surveys use passive geophysical techniques to characterize geochemical variations at or near earth’s surface. These methods have been used for a variety of mapping applications, including mineral resource evaluation. However, detailed characterization of smaller geologic targets, including mine waste features, requires flying at lower altitudes and with tighter line spacing than is feasible with traditional aircraft. Here, a small uncrewed aircraft system (sUAS) equipped with a radiometric sensor was used to acquire high-resolution gamma-spectrometry over small mine waste features and a low-grade stockpile in southwestern New Mexico. The sUAS radiometric system mapped local variability within each survey area and revealed ~2–10 m wide zones where radioelements K, Th, and U may be elevated 2–10× the surrounding material. Additionally, the sUAS radiometric data revealed radioelement variability across survey sites, which correlated reasonably well with variability seen in geochemical samples at each survey site, even though samples collected from individual sites showed high local variability. The sUAS data characterized local heterogeneity within mine waste and other small geologic targets at scales of a few meters to tens of meters, which is not possible with traditional crewed aircraft, and with continuity of coverage that is not possible with ground surveys, thus filling a key gap in geophysical survey spatial resolution.
","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/tle44110889.1","usgsCitation":"Gustafson, C., Shah, A.K., Burgess, M.A., Adams, J., McLemore, V., and Owen, E.J., 2025, Drone-based radiometric surveys provide high-resolution mine waste characterization: The Leading Edge, v. 44, no. 11, p. 889-900, https://doi.org/10.1190/tle44110889.1.","productDescription":"12 p.","startPage":"889","endPage":"900","ipdsId":"IP-180021","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":497111,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1190/tle44110889.1","text":"Publisher Index Page"},{"id":497057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Blackhawk mining district, Copper Flat Mine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109,\n 33.5\n ],\n [\n -109,\n 31.5\n ],\n [\n -108.22801231819798,\n 31.506679785521342\n ],\n [\n -108.22398985560156,\n 31.79511507151517\n ],\n [\n -106.9946669081999,\n 31.78156997939864\n ],\n [\n -107,\n 33.5\n ],\n [\n -109,\n 33.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gustafson, Chloe Danielle 0000-0001-8323-2568","orcid":"https://orcid.org/0000-0001-8323-2568","contributorId":346924,"corporation":false,"usgs":true,"family":"Gustafson","given":"Chloe Danielle","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951321,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burgess, Matthew Alexander 0000-0003-3487-4972 mburgess@usgs.gov","orcid":"https://orcid.org/0000-0003-3487-4972","contributorId":225090,"corporation":false,"usgs":true,"family":"Burgess","given":"Matthew","email":"mburgess@usgs.gov","middleInitial":"Alexander","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":951322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Josip 0000-0001-8470-4141","orcid":"https://orcid.org/0000-0001-8470-4141","contributorId":217936,"corporation":false,"usgs":true,"family":"Adams","given":"Josip","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":951323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McLemore, Virginia","contributorId":363225,"corporation":false,"usgs":false,"family":"McLemore","given":"Virginia","affiliations":[{"id":86657,"text":"New Mexico Bureau of Geology and Mineral Resources, New Mexico Institute of Mining and Technology","active":true,"usgs":false}],"preferred":false,"id":951324,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Owen, Evan J.","contributorId":363226,"corporation":false,"usgs":false,"family":"Owen","given":"Evan","middleInitial":"J.","affiliations":[{"id":86659,"text":"Mining & Minerals Division, New Mexico Department of Energy, Minerals & Natural Resources Department","active":true,"usgs":false}],"preferred":false,"id":951325,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272061,"text":"70272061 - 2025 - The Mammoth magnetic anomaly, Pinal County, Arizona","interactions":[],"lastModifiedDate":"2025-11-14T15:32:54.822911","indexId":"70272061","displayToPublicDate":"2025-11-01T08:28:30","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3568,"text":"The Leading Edge","active":true,"publicationSubtype":{"id":10}},"title":"The Mammoth magnetic anomaly, Pinal County, Arizona","docAbstract":"A high-resolution Earth Mapping Resources Initiative airborne geophysical survey was flown in the southwest North American porphyry copper province to improve bedrock geologic maps and to identify areas that have unrecognized critical mineral resource potential. During the review of the aeromagnetic data, a distinctly monopolar-shaped, negative magnetic anomaly was observed at a flight elevation of 200 m above the ground with a maximum amplitude of –9500 nT. We have named this the Mammoth magnetic anomaly (MMA) because it is centered 12 km northeast of the town of Mammoth, Arizona, USA. The total field anomaly (TFA) contour of –500 nT enclosing the MMA defines an elongate shape measuring 2.5 km long by 1 km wide that trends northwest–southeast. Given the striking nature of this negative, monopolar-shaped magnetic anomaly, we conducted a ground campaign in May 2025 to determine its authenticity and potential relationship to critical mineral endowment. The MMA was confirmed on the ground with a TFA approaching –46,000 nT. Total magnetic intensity (TMI) observations routinely fell below the 18,000 nT operating floor of an industry-standard cesium-vapor total field magnetometer, and extremely low TMI measurements were corroborated along coincident traverse lines using two high dynamic range, but lower sensitivity, smartphone vector magnetometers. The lowest TMI values recorded by both smartphone magnetometers were 1000 nT and confirmed with multiple adjacent and crossing lines. Field observations suggest that this magnetic feature is caused by strong remanent magnetization within fine-grained magnetite hosted within locally altered Pinal Schist.
","language":"English","publisher":"The Society of Exploration Geophysicists","doi":"10.1190/tle44110879.1","usgsCitation":"Walter, C.A., Scheirer, D.S., Beno, C., Borchardt, J.S., and Connell, D., 2025, The Mammoth magnetic anomaly, Pinal County, Arizona: The Leading Edge, v. 44, no. 11, p. 879-888, https://doi.org/10.1190/tle44110879.1.","productDescription":"10 p.","startPage":"879","endPage":"888","ipdsId":"IP-179841","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":496710,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1190/tle44110879.1","text":"Publisher Index Page"},{"id":496913,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13LYAKZ","text":"USGS data release","linkHelpText":"Ground Magnetic Observations of the Mammoth Magnetic Anomaly, Pinal County, Arizona, May 2025"},{"id":496912,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1GGHK8X","text":"USGS data release","linkHelpText":"Airborne magnetic and radiometric data acquired over parts of Cochise, Graham, Greenlee, Pima, Pinal, and Santa Cruz Counties, Arizona"},{"id":496486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","county":"Pinal County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.14609001840401,\n 33.405406351098335\n ],\n [\n -111.14609001840401,\n 31.33976116419477\n ],\n [\n -109.03721319402516,\n 31.33976116419477\n ],\n [\n -109.03721319402516,\n 33.405406351098335\n ],\n [\n -111.14609001840401,\n 33.405406351098335\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walter, Callum Andrew 0000-0001-7955-2016","orcid":"https://orcid.org/0000-0001-7955-2016","contributorId":360911,"corporation":false,"usgs":true,"family":"Walter","given":"Callum","middleInitial":"Andrew","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":949952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scheirer, Daniel S. 0000-0001-8015-7072 dscheirer@usgs.gov","orcid":"https://orcid.org/0000-0001-8015-7072","contributorId":214825,"corporation":false,"usgs":true,"family":"Scheirer","given":"Daniel","email":"dscheirer@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":949953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beno, Carl Joseph 0000-0001-7611-1602","orcid":"https://orcid.org/0000-0001-7611-1602","contributorId":347444,"corporation":false,"usgs":true,"family":"Beno","given":"Carl Joseph","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":949954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borchardt, Jackson Stone 0000-0001-6891-3314","orcid":"https://orcid.org/0000-0001-6891-3314","contributorId":346157,"corporation":false,"usgs":true,"family":"Borchardt","given":"Jackson","email":"","middleInitial":"Stone","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949955,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Connell, Dylan Mark 0000-0001-8678-2776","orcid":"https://orcid.org/0000-0001-8678-2776","contributorId":292570,"corporation":false,"usgs":true,"family":"Connell","given":"Dylan Mark","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949956,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271476,"text":"70271476 - 2025 - Comparing magmatism and hydrothermal alteration using magnetic modelling and stable isotopes at the Clementine porphyry copper prospect, Montana, USA","interactions":[],"lastModifiedDate":"2025-09-17T14:57:28.463629","indexId":"70271476","displayToPublicDate":"2025-09-12T09:49:07","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Comparing magmatism and hydrothermal alteration using magnetic modelling and stable isotopes at the Clementine porphyry copper prospect, Montana, USA","docAbstract":"Recent mapping of the underexplored Clementine prospect in southwestern Montana has revealed evidence of hydrothermal alteration and mineralized breccia vein gossan interpreted to represent the upper expression of a Cretaceous, sediment-hosted copper porphyry system. The prospect is at the nexus of several Cretaceous granites, including the pre-mineralization Butte Granite and Big Hole Canyon plutons and local pre- to post-mineralization granite intrusions. Here, 3D magnetic inversions and stable isotope data are used to evaluate the spatial and genetic relationship of mineralization and Cretaceous magmatism. Magnetic inversions reveal a zone of high magnetic susceptibility beneath the prospect that is related to an exposure of unaltered, likely post-mineralization granite. The granite appears to connect to the Big Hole Canyon pluton at depth, suggesting it is a late-stage differentiate of the cooling, pre-mineralization pluton that may have been one of several potential heat sources for the mineral system at Clementine. This is supported by carbon isotope values of graphite that indicate organic material in shale of the Cretaceous Kootenai Formation was subject to metamorphism. Preliminary light hydrogen isotope values of actinolite hydrothermal orbs suggest formation following magmatic outgassing during thermal advection from an underlying intrusion.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 18th Biennial SGA Meeting","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Magnin, B.P., McIntosh, J.A., and Brimhall, G.H., 2025, Comparing magmatism and hydrothermal alteration using magnetic modelling and stable isotopes at the Clementine porphyry copper prospect, Montana, USA, in Proceedings of the 18th Biennial SGA Meeting, v. 2, p. 471-474.","productDescription":"4 p.","startPage":"471","endPage":"474","ipdsId":"IP-175774","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495608,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.e-sga.org/publications/conference-proceedings"}],"country":"United States","state":"Montana","otherGeospatial":"Clementine prospect","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113,\n 45.9167\n ],\n [\n -113,\n 45.5\n ],\n [\n -112.5,\n 45.5\n ],\n [\n -112.5,\n 45.9167\n ],\n [\n -113,\n 45.9167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Magnin, Benjamin Patrick 0000-0001-9951-4404","orcid":"https://orcid.org/0000-0001-9951-4404","contributorId":300679,"corporation":false,"usgs":true,"family":"Magnin","given":"Benjamin","email":"","middleInitial":"Patrick","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":948882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McIntosh, Julia A. 0000-0003-2819-8664","orcid":"https://orcid.org/0000-0003-2819-8664","contributorId":331662,"corporation":false,"usgs":true,"family":"McIntosh","given":"Julia","email":"","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":948883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brimhall, George H.","contributorId":361483,"corporation":false,"usgs":false,"family":"Brimhall","given":"George","middleInitial":"H.","affiliations":[{"id":86298,"text":"Clementine Exploration LLC","active":true,"usgs":false}],"preferred":false,"id":948884,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271744,"text":"70271744 - 2025 - Formation of the Mount Weld rare earth deposit, Western Australia: Geochronology constraints","interactions":[],"lastModifiedDate":"2025-09-23T14:04:12.768692","indexId":"70271744","displayToPublicDate":"2025-09-12T08:55:51","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Formation of the Mount Weld rare earth deposit, Western Australia: Geochronology constraints","docAbstract":"Constraining the age of protracted chemical weathering in stable cratonic areas that may form thick regoliths and the potential enrichment of various elements is challenging. Economic deposits of aluminium, iron, copper, nickel, cobalt, niobium, and rare earth elements (REEs) form in this manner. Determining the age of formation can provide key information for exploration of similar deposits as well as to better constrain paleoclimatic conditions. This study describes our effort to constrain the age of formation of the Mount Weld deposit, a world-class carbonatite-derived REE laterite deposit. We utilize multiple geochronological techniques on different minerals. The oldest dates, ranging from ca. 100 to 50 Ma, were from laser ablation ICPMS, Lu-Hf dating of churchite, a heavy REE phosphate mineral formed by mineral saturation in groundwater. Growth bands on individual minerals show a younging outwards. 40Ar/39Ar geochronology of cryptomelane, a potassium-bearing manganese oxide mineral, yielded ages ranging from ca. 40 to 26 Ma. Similarly, (U–Th)/He geochronology of goethite yielded ages from ca. 45 to 19 Ma.
","conferenceTitle":"18th SGA Biennial Meeting","conferenceDate":"August 3-7, 2025","conferenceLocation":"Golden, CO","language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Verplanck, P., Mercer, C.M., Thompson, J.M., Danišík, M., Bhat, G., and Lowers, H.A., 2025, Formation of the Mount Weld rare earth deposit, Western Australia: Geochronology constraints, 18th SGA Biennial Meeting, v. 2, Golden, CO, August 3-7, 2025, p. 695-699.","productDescription":"5 p.","startPage":"695","endPage":"699","ipdsId":"IP-175872","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495892,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.e-sga.org/publications/conference-proceedings"}],"country":"Australia","otherGeospatial":"Mount Weld deposit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 122.50129211245445,\n -28.838271184659284\n ],\n [\n 122.50129211245445,\n -28.899390507112095\n ],\n [\n 122.59126576645451,\n -28.899390507112095\n ],\n [\n 122.59126576645451,\n -28.838271184659284\n ],\n [\n 122.50129211245445,\n -28.838271184659284\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Verplanck, Philip L. 0000-0002-3653-6419","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":212813,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","middleInitial":"L.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":949269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercer, Cameron Mark 0000-0003-0534-848X","orcid":"https://orcid.org/0000-0003-0534-848X","contributorId":301880,"corporation":false,"usgs":true,"family":"Mercer","given":"Cameron","email":"","middleInitial":"Mark","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Jay M. 0000-0003-3322-0870","orcid":"https://orcid.org/0000-0003-3322-0870","contributorId":329664,"corporation":false,"usgs":true,"family":"Thompson","given":"Jay","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danišík, Martin 0000-0003-3909-6102","orcid":"https://orcid.org/0000-0003-3909-6102","contributorId":361709,"corporation":false,"usgs":false,"family":"Danišík","given":"Martin","affiliations":[{"id":86336,"text":"Curtin University, Perth, Australia","active":true,"usgs":false}],"preferred":false,"id":949272,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bhat, Ganesh","contributorId":329666,"corporation":false,"usgs":false,"family":"Bhat","given":"Ganesh","email":"","affiliations":[{"id":78683,"text":"Lynas Rare Earths Ltd","active":true,"usgs":false}],"preferred":false,"id":949273,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":949274,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271704,"text":"70271704 - 2025 - Airborne radiometric data map alteration of porphyry copper systems in the Elkhorn district, MT","interactions":[],"lastModifiedDate":"2025-09-19T13:42:47.938711","indexId":"70271704","displayToPublicDate":"2025-09-12T08:24:03","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Airborne radiometric data map alteration of porphyry copper systems in the Elkhorn district, MT","docAbstract":"The Elkhorn district in southwestern Montana is known for past production of high-grade base and precious metals from skarn and carbonate replacement deposits. The district also hosts a porphyry Cu-Mo deposit. A radiometric survey flown over the district and surrounds provides maps of surficial concentrations of potassium, thorium, and uranium. Handheld gamma ray spectrometer measurements on altered and unaltered rocks in the district and surrounding region provide a means to ground truth the airborne data. We demonstrate that the airborne and ground-based measurements show similar map patterns. We calculate ratios of the radioelement concentrations and present a potassium enhancement map that combines potassium and ratios of potassium to thorium and uranium. The results highlight the rocks previously mapped as having K-feldspar-biotite and quartz-sericite alteration assemblages in the Elkhorn district and map additional hydrothermal systems in the region, including known alteration in the Radersburg district. The data enhancement techniques can be used as a screening tool for mapping additional porphyry copper systems.
","conferenceTitle":"18th SGA Biennial Meeting","conferenceDate":"August 3-7, 2025","conferenceLocation":"Golden, CO","language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Anderson, E., Scarberry, K., Eastman, K., Funk, J.A., Magnin, B.P., Clevenger, J., Dilles, J., Zimmerman, J.L., Attia, S., and Cosca, M., 2025, Airborne radiometric data map alteration of porphyry copper systems in the Elkhorn district, MT, 18th SGA Biennial Meeting, v. 3, Golden, CO, August 3-7, 2025, p. 1200-1203.","productDescription":"4 p.","startPage":"1200","endPage":"1203","ipdsId":"IP-177511","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495774,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.e-sga.org/publications/conference-proceedings#c345"},{"id":495778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Elkhorn district","volume":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Eric D. 0000-0002-0138-6166 ericanderson@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":172766,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric","email":"ericanderson@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scarberry, Kaleb","contributorId":361605,"corporation":false,"usgs":false,"family":"Scarberry","given":"Kaleb","affiliations":[{"id":32397,"text":"Oregon Department of Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":949069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eastman, Kyle","contributorId":361606,"corporation":false,"usgs":false,"family":"Eastman","given":"Kyle","affiliations":[{"id":36941,"text":"Montana Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":949070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, Jonathan Andrew 0000-0001-7897-687X","orcid":"https://orcid.org/0000-0001-7897-687X","contributorId":297164,"corporation":false,"usgs":true,"family":"Funk","given":"Jonathan","email":"","middleInitial":"Andrew","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magnin, Benjamin Patrick 0000-0001-9951-4404","orcid":"https://orcid.org/0000-0001-9951-4404","contributorId":300679,"corporation":false,"usgs":true,"family":"Magnin","given":"Benjamin","email":"","middleInitial":"Patrick","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":949072,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clevenger, Joseph","contributorId":361607,"corporation":false,"usgs":false,"family":"Clevenger","given":"Joseph","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":949073,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dilles, John","contributorId":361675,"corporation":false,"usgs":false,"family":"Dilles","given":"John","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":949133,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zimmerman, Jarred L. 0000-0003-3423-7711","orcid":"https://orcid.org/0000-0003-3423-7711","contributorId":359591,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Jarred","middleInitial":"L.","affiliations":[{"id":85873,"text":"Montana Buteau of Mines and Geology, Montana Technological University, Butte, Montana, USA","active":true,"usgs":false}],"preferred":false,"id":949134,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Attia, Snir 0000-0001-8582-8197","orcid":"https://orcid.org/0000-0001-8582-8197","contributorId":344165,"corporation":false,"usgs":true,"family":"Attia","given":"Snir","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949135,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cosca, Michael 0000-0002-0600-7663","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":33043,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949136,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70270258,"text":"ofr20251047 - 2025 - 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","interactions":[],"lastModifiedDate":"2026-04-16T13:59:07.528586","indexId":"ofr20251047","displayToPublicDate":"2025-08-25T10:58:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1047","displayTitle":"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","title":"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","docAbstract":"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.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251047","usgsCitation":"Nassar, N.T., Pineault, D., Allen, S.M., McCaffrey, D.M., Padilla, A.J., Brainard, J.L., Bayani, M., Shojaeddini, E., Ryter, J.W., Lincoln, S., and Alonso, E., 2025, 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 (ver. 2.0, 2026): U.S. Geological Survey Open-File Report 2025–1047, 215 p., https://doi.org/10.3133/ofr20251047.","productDescription":"Report: vi, 215 p.; Data Release","numberOfPages":"215","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-180772","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":494012,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1047/ofr20251047.pdf","text":"Report","size":"3.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1047 PDF"},{"id":494011,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1047/coverthb3.jpg"},{"id":494013,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251047/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1047 HTML"},{"id":494014,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1047/ofr20251047.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1047 XML"},{"id":494015,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1047/images/"},{"id":499034,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118752.htm","linkFileType":{"id":5,"text":"html"}},{"id":502425,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2025/1047/versionHist.txt","size":"3.01 KB","linkFileType":{"id":2,"text":"txt"}},{"id":494403,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14BRF29","text":"USGS data release","linkHelpText":"U.S. Geological Survey Minerals Yearbook data for select mineral commodities referenced in “U.S. Geological Survey 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”"}],"edition":"Version 1.0: August 2025; Version 2.0: April 2026","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
","tableOfContents":"To quantify the risks associated with potential disruptions and to recommend mineral commodities for inclusion on the updated U.S. List of Critical Minerals, as required by the Energy Act of 2020, the U.S. Geological Survey developed an economic model to estimate the potential effects of foreign trade disruptions of mineral commodities on the U.S. economy. The results of the study recommend 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 List of Critical Minerals. The analysis also provides a prioritization based on the results. The economic model has several advantages over previous assessments including the ability to directly compare the results against other economic risks and the costs of initiatives aimed at reducing the risks.
","publicationDate":"2025-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945905,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pineault, David 0009-0001-6801-4711","orcid":"https://orcid.org/0009-0001-6801-4711","contributorId":352217,"corporation":false,"usgs":true,"family":"Pineault","given":"David","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945906,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Sydney M. 0000-0001-6560-3548","orcid":"https://orcid.org/0000-0001-6560-3548","contributorId":359608,"corporation":false,"usgs":true,"family":"Allen","given":"Sydney","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCaffrey, Dalton M. 0000-0002-2539-4865","orcid":"https://orcid.org/0000-0002-2539-4865","contributorId":298840,"corporation":false,"usgs":true,"family":"McCaffrey","given":"Dalton","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945908,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Padilla, Abraham J. 0000-0002-8371-533X","orcid":"https://orcid.org/0000-0002-8371-533X","contributorId":290608,"corporation":false,"usgs":true,"family":"Padilla","given":"Abraham","email":"","middleInitial":"J.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945909,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brainard, Jamie L. 0000-0002-1712-0821","orcid":"https://orcid.org/0000-0002-1712-0821","contributorId":201465,"corporation":false,"usgs":true,"family":"Brainard","given":"Jamie","middleInitial":"L.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945910,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bayani, Mani 0000-0003-4730-3140","orcid":"https://orcid.org/0000-0003-4730-3140","contributorId":359609,"corporation":false,"usgs":true,"family":"Bayani","given":"Mani","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945911,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shojaeddini, Ensieh 0000-0001-9584-6399","orcid":"https://orcid.org/0000-0001-9584-6399","contributorId":346849,"corporation":false,"usgs":true,"family":"Shojaeddini","given":"Ensieh","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945912,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ryter, John W. 0000-0002-0343-7553","orcid":"https://orcid.org/0000-0002-0343-7553","contributorId":345416,"corporation":false,"usgs":true,"family":"Ryter","given":"John","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945913,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lincoln, Sara 0000-0002-0162-3563","orcid":"https://orcid.org/0000-0002-0162-3563","contributorId":359610,"corporation":false,"usgs":false,"family":"Lincoln","given":"Sara","affiliations":[{"id":85881,"text":"Contractor to the U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":945914,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Alonso, Elisa 0000-0002-0090-8284","orcid":"https://orcid.org/0000-0002-0090-8284","contributorId":223015,"corporation":false,"usgs":true,"family":"Alonso","given":"Elisa","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945915,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70267829,"text":"70267829 - 2025 - Airborne geophysics for geologic mapping of critical mineral systems in the United States southern midcontinent","interactions":[],"lastModifiedDate":"2026-01-16T16:33:30.622156","indexId":"70267829","displayToPublicDate":"2025-08-19T10:30:56","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Airborne geophysics for geologic mapping of critical mineral systems in the United States southern midcontinent","docAbstract":"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.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic Mapping Forum 24/24 abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"University of Minnesota Twin Cities","usgsCitation":"Amaral, C.M., McCafferty, A.E., and Connell, D., 2025, Airborne geophysics for geologic mapping of critical mineral systems in the United States southern midcontinent, in Geologic Mapping Forum 24/24 abstracts, p. 15-16.","productDescription":"2 p.","startPage":"15","endPage":"16","ipdsId":"IP-173917","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":489447,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/11299/275433"},{"id":498748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.25384608464034,\n 38.46574935812839\n ],\n [\n -93.61302912846105,\n 38.46574935812839\n ],\n [\n -93.61302912846105,\n 34.021659839091996\n ],\n [\n -86.25384608464034,\n 34.021659839091996\n ],\n [\n -86.25384608464034,\n 38.46574935812839\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2025-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Amaral, Chelsea Morgan 0000-0003-4632-4097","orcid":"https://orcid.org/0000-0003-4632-4097","contributorId":313539,"corporation":false,"usgs":true,"family":"Amaral","given":"Chelsea","email":"","middleInitial":"Morgan","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":939061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCafferty, Anne E. 0000-0001-5574-9201 anne@usgs.gov","orcid":"https://orcid.org/0000-0001-5574-9201","contributorId":1120,"corporation":false,"usgs":true,"family":"McCafferty","given":"Anne","email":"anne@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":939062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connell, Dylan Mark 0000-0001-8678-2776","orcid":"https://orcid.org/0000-0001-8678-2776","contributorId":292570,"corporation":false,"usgs":true,"family":"Connell","given":"Dylan Mark","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":939063,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70270862,"text":"70270862 - 2025 - Estimating the hypothetical endowment of critical minerals and other commodities in porphyry copper mine waste in the Four Corners states, USA","interactions":[],"lastModifiedDate":"2025-08-26T14:17:35.326171","indexId":"70270862","displayToPublicDate":"2025-08-19T09:14:15","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Estimating the hypothetical endowment of critical minerals and other commodities in porphyry copper mine waste in the Four Corners states, USA","docAbstract":"Society is fundamentally dependent upon commodities that are used in end-use products for the aerospace, defense, energy, telecommunication, and transportation sectors, resulting in centuries of mining to supply these commodities and materials. Waste from these mining operations can remain on the landscape indefinitely, but there is a lack of national understanding of the distribution and scale of such waste features. The renewable energy transition will continue to increase demand for critical minerals and will result in increasing volumes of mine waste on the Earth’s surface. Reprocessing mine waste can reduce environmental risks and recover needed commodities to match growing demand for societal growth. Therefore, understanding the approximate abundance of commodities that may be available for recovery within mine waste features can be an important piece of domestic critical mineral supply.
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0000-0002-8288-7236","orcid":"https://orcid.org/0000-0002-8288-7236","contributorId":351072,"corporation":false,"usgs":true,"family":"Helfrich","given":"Autumn Lynne","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":947233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Andrew Francis 0000-0002-7908-6091","orcid":"https://orcid.org/0000-0002-7908-6091","contributorId":360587,"corporation":false,"usgs":true,"family":"Smith","given":"Andrew","middleInitial":"Francis","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":947234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mauk, Jeffrey L. 0000-0002-6244-2774 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benthic community of a copper treatment to eradicate invasive mussels in a large western river, USA","docAbstract":"Copper-based chemical treatments are commonly used to eradicate invasive mussels in small ponds and lakes, but their use in large rivers has been limited. In 2023, in response to a detection of invasive quagga mussels, a 10-km reach of the Snake River (Idaho, USA), was treated with an unprecedented 19,300 kg of chelated copper molluscicide to a target concentration of 1,000 µg/L for 10 days. We assessed the transport and fate of the copper and its exposure and effects on the nontarget benthic community downstream. Water samples were collected at seven locations throughout the treatment period, and sediment, periphyton, and benthic macroinvertebrates were collected pre- and posttreatment. Nearly half of the original mass of copper was removed from the water column via sedimentation, sorption to algae, or biological uptake within the 10-km treatment reach and the first 15 km downstream. Even so, dissolved copper concentrations exceeded the acute toxicity threshold at least as far as 28 km downstream for more than 2 weeks. Sediment copper increased by up to 8.3-fold, exceeding the consensus-based sediment quality threshold effect concentration at several sites. Effects on benthic macroinvertebrates varied by taxa. From 0–28 km downstream, invertebrate abundances decreased 52%–94%, with gastropods among the most affected. Of the unique taxa present at these sites pretreatment, 52%–64% were not found posttreatment but were replaced by other taxa, indicating a reorganization of the base of the food web. Additionally, from 0–15 km downstream, the percentage of individuals from tolerant taxa increased two to15-fold. Findings from this study can help watershed managers plan future invasive mussel responses while protecting culturally, economically, and ecologically important nontarget species in large rivers.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgaf119","usgsCitation":"Baldwin, A.K., Murray, E., Zinsser, L.M., King, T.V., Ducar, S.D., Southern, I., Thom, T., and Mebane, C.A., 2025, Fate and effects to the benthic community of a copper treatment to eradicate invasive mussels in a large western river, USA: Environmental Toxicology and Chemistry, v. 44, no. 8, p. 2166-2180, https://doi.org/10.1093/etojnl/vgaf119.","productDescription":"15 p.","startPage":"2166","endPage":"2180","ipdsId":"IP-173841","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":494190,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgaf119","text":"Publisher Index Page"},{"id":493934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.19538272232973,\n 43.32567469741488\n ],\n [\n -116.19538272232973,\n 42.22650789070423\n ],\n [\n -113.5905787354007,\n 42.22650789070423\n ],\n [\n -113.5905787354007,\n 43.32567469741488\n ],\n [\n -116.19538272232973,\n 43.32567469741488\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murray, Erin 0000-0002-5007-3449","orcid":"https://orcid.org/0000-0002-5007-3449","contributorId":205705,"corporation":false,"usgs":true,"family":"Murray","given":"Erin","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zinsser, Lauren M. 0000-0002-8582-066X","orcid":"https://orcid.org/0000-0002-8582-066X","contributorId":205756,"corporation":false,"usgs":true,"family":"Zinsser","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, Tyler V. 0000-0002-5785-3077","orcid":"https://orcid.org/0000-0002-5785-3077","contributorId":292424,"corporation":false,"usgs":true,"family":"King","given":"Tyler","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ducar, Scott D. 0000-0003-0781-5598","orcid":"https://orcid.org/0000-0003-0781-5598","contributorId":297547,"corporation":false,"usgs":true,"family":"Ducar","given":"Scott","email":"","middleInitial":"D.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945509,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Southern, India","contributorId":359460,"corporation":false,"usgs":false,"family":"Southern","given":"India","affiliations":[{"id":6912,"text":"Idaho Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":945510,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thom, Theresa","contributorId":224436,"corporation":false,"usgs":false,"family":"Thom","given":"Theresa","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":945511,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945512,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70268358,"text":"ofr20251033 - 2025 - Select elements of concern in surface water of three hydrologic basins (Delaware River, Illinois River, and Upper Colorado River)—Data screening for the development of spatial and temporal models","interactions":[],"lastModifiedDate":"2025-06-24T13:43:22.987262","indexId":"ofr20251033","displayToPublicDate":"2025-06-23T14:10:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1033","displayTitle":"Select Elements of Concern in Surface Water of Three Hydrologic Basins (Delaware River, Illinois River, and Upper Colorado River)—Data Screening for the Development of Spatial and Temporal Models","title":"Select elements of concern in surface water of three hydrologic basins (Delaware River, Illinois River, and Upper Colorado River)—Data screening for the development of spatial and temporal models","docAbstract":"The report focuses on the screening of previously published concentration data associated with 12 elements of concern (aluminum, arsenic, cadmium, chromium, copper, iron, mercury, manganese, lead, selenium, uranium, and zinc) measured in stream surface waters of three hydrologic basins (Delaware River Basin, Illinois River Basin, and the Upper Colorado River Basin). The purpose of this analysis is to determine what subsets of the original dataset (containing more than 1,500,000 observations) may be most suitable for each of two types of modeling efforts. The first type of modeling envisions a machine learning approach to determine which geospatial attributes are most significant in describing the spatial distribution of elemental concentrations within a basin. The second type of modeling envisions a stepwise regression approach to develop multivariable models that can be used to determine high resolution time-series estimates of elemental concentrations or loads at discrete U.S. Geological Survey real-time stream surface water sites. These site-specific temporal models are based on continuous measurements of available discharge and (or) in situ sensor data (temperature, pH, turbidity, dissolved oxygen, specific conductance, and (or) fluorescent dissolved organic matter) as the explanatory variables. The data screening for both model types considered historical trends in analytical methods and detection quantitation limits, the extent of censored data, data density, and environmental relevance with respect to three U.S. Environmental Protection Agency water quality thresholds (drinking water guidelines, human health criteria, and aquatic life criteria). The result of this analysis was the production of a final list of potential models deemed suitable for further development based upon the data exclusion (or inclusion) scheme developed herein for each model type. In both cases, the final models included mostly the three crustal elements (iron, manganese, and aluminum) that are found at comparatively high concentrations in surface water, whereas most of the more pernicious elements were excluded from the final model lists owing to various data limitations. The one exception to this was arsenic, for which the existing data were sufficient at three U.S. Geological Survey real-time sites for potential further development of time-series models.
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Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Ave, Suite 1950
Portland, OR 97204
Small leisure boat harbours have important aesthetic and recreational values in any country with a coastline. In Sweden, there are about 860 000 leisure boats, which is one of the world's highest numbers in relation to the country's population. However, small boat harbours also present a wide range of environmental problems, including the introduction of alien species and high pollution. In this study, we investigated the ecological quality status (EcoQS) of the Hinsholmskilen small boat harbour, located southwest of the city of Gothenburg (Sweden). We performed a reconnaissance survey of the harbour's previously unstudied benthic foraminiferal communities and analysed surface sediment (0–2 cm) samples for potentially toxic elements: copper (Cu), zinc (Zn), lead (Pb), cobalt (Co), nickel (Ni), chromium (Cr), mercury (Hg), and arsenic (As). The results show that, based on the total benthic foraminiferal distribution (dead and live specimens), the assemblages in Hinsholmskilen harbour represent a typical European estuarine community with highly abundant Ammonia and Elphidium species. Based on molecular and morphological data, we report the presence of two alien and putatively invasive species likely originating from Asia: Trochammina hadai and Ammonia confertitesta (phylotype T6). Both species have recently been identified elsewhere on the Swedish west coast based on molecular and morphological data but do not have a well-known distribution. The sediment analysis for potentially toxic elements showed that the harbour has good to high EcoQS corresponding to no or little deviation from reference conditions for Cd, Co, Ni, and Pb distribution. Some of the contaminants (Pb, As, Zn, and Cr) showed poor to bad EcoQS in the innermost harbour in proximity to high-pressure cleaning plants, where boats are usually lifted, cleaned, and prepared for winter storage on land. Finally, Cu and Hg showed consistently bad and poor EcoQS all over the harbour, reflecting the use of both metals as biocides in antifouling boat paints.
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2025 - Effects of chronic metal exposure and metamorphosis on the microbiomes of larval and adult insects and riparian spiders through the aquatic-riparian food web","interactions":[],"lastModifiedDate":"2025-03-11T15:16:09.842235","indexId":"70264304","displayToPublicDate":"2025-04-15T08:10:25","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Effects of chronic metal exposure and metamorphosis on the microbiomes of larval and adult insects and riparian spiders through the aquatic-riparian food web","docAbstract":"The macroinvertebrate microbiome controls various aspects of the host's physiology, from regulation of environmental contaminants to reproductive output. Aquatic insects provide critical nutritional subsidies linking aquatic and riparian food webs while simultaneously serving as a contaminant pathway for riparian insectivores in polluted ecosystems. Previous studies have characterized the transport and transfer of contaminants from aquatic to riparian ecosystems through insect metamorphosis, but both contaminant exposure and metamorphosis are energetically intensive processes that may cause host microbiomes to undergo radical transformation in structure and function, potentially affecting the host's physiology. We collected arthropods from three sites within Torch Lake, a historical copper mine in the Keweenaw Peninsula, Michigan, USA, and three sites within a nearby reference lake. Our objectives were to: 1) characterize the variation in microbiome communities and predicted metagenomic functions with legacy copper mining activity across space, among host types and family-level host taxonomy, 2) characterize how insect metamorphosis alters the microbiome community, including the degree of endosymbiotic infection, and predicted metagenomic function. We field-collected organisms, extracted their DNA, and sequenced the 16S region of the rRNA gene to characterize microbiome communities, then predicted metagenomic function. Site, lake, and host taxonomy affected the host microbiome community composition. Copper exposure increased the abundance of xenobiotic and lipid metabolism pathways in the Araneidae spider microbiome. Insect metamorphosis reduced the alpha diversity, altered the community composition, and predicted metagenomic function. We observed a bioconcentration of endosymbiotic bacteria in adult insects, especially holometabolous insects. Through metamorphosis, we observed a transition in function from xenobiotic degradation pathways to carbohydrate metabolism. Overall, contaminant exposure alters the microbiome composition in aquatic insects and riparian spiders and alters the function of the microbiome across the aquatic-riparian interface. Furthermore, metamorphosis is a critical element in shaping the aquatic insect microbiome across its life history.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2025.125867","usgsCitation":"Perrotta, B.G., Kidd, K.A., Marcarelli, A., Paterson, G., and Walters, D., 2025, Effects of chronic metal exposure and metamorphosis on the microbiomes of larval and adult insects and riparian spiders through the aquatic-riparian food web: Environmental Pollution, v. 371, 125867, 9 p., https://doi.org/10.1016/j.envpol.2025.125867.","productDescription":"125867, 9 p.","ipdsId":"IP-169288","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":489130,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2025.125867","text":"Publisher Index Page"},{"id":483200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","county":"Houghton County","otherGeospatial":"Torch Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.46640849263272,\n 47.14649980228603\n ],\n [\n -88.4605085402806,\n 47.1315363557228\n ],\n [\n -88.4065837887026,\n 47.14806456116506\n ],\n [\n -88.38858688945557,\n 47.17549829654733\n ],\n [\n -88.39397591964818,\n 47.195600580412474\n ],\n [\n -88.43333972210017,\n 47.175319195702855\n ],\n [\n -88.46640849263272,\n 47.14649980228603\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"371","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Perrotta, Brittany G. 0000-0003-2669-3047","orcid":"https://orcid.org/0000-0003-2669-3047","contributorId":301929,"corporation":false,"usgs":true,"family":"Perrotta","given":"Brittany","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":930366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kidd, Karen A.","contributorId":201554,"corporation":false,"usgs":false,"family":"Kidd","given":"Karen","email":"","middleInitial":"A.","affiliations":[{"id":25502,"text":"McMaster University","active":true,"usgs":false}],"preferred":false,"id":930367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marcarelli, Amy M.","contributorId":272244,"corporation":false,"usgs":false,"family":"Marcarelli","given":"Amy M.","affiliations":[{"id":56375,"text":"isu","active":true,"usgs":false}],"preferred":false,"id":930368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paterson, Gordon","contributorId":347134,"corporation":false,"usgs":false,"family":"Paterson","given":"Gordon","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":930369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":205921,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":930370,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264757,"text":"fs20253002 - 2025 - Critical Minerals in Ores (CMiO) database","interactions":[],"lastModifiedDate":"2026-01-23T21:37:38.090764","indexId":"fs20253002","displayToPublicDate":"2025-03-26T16:15:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3002","displayTitle":"Critical Minerals in Ores (CMiO) Database","title":"Critical Minerals in Ores (CMiO) database","docAbstract":"Critical minerals are commodities essential to modern industrial and strategic technologies and are highly vulnerable to supply chain disruption. 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Importantly, it uses a novel consensus deposit environment, group, and type classification scheme developed by the agencies that allows comparisons among ore deposits from different regions. The CMiO database contains geochemical data for more than 20,000 samples from more than 100 deposit types comprising 10 deposit environments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20253002","collaboration":"Prepared in collaboration with the Geological Survey of Canada and Geoscience Australia","programNote":"Mineral Resources Program","usgsCitation":"Case, G.N.D., Graham, G.E., Lawley, C.J.M., Bastrakov, E., Huston, D.L., Hofstra, A.H., Lisitsin, V., Hawkins, S.G., and Wang, B., 2025, Critical Minerals in Ores (CMiO) database (ver. 1.2, May 2025): U.S. Geological Survey Fact Sheet 2025–3002, 2 p., https://doi.org/10.3133/fs20253002.","productDescription":"Report: 2 p.; Dataset","onlineOnly":"N","ipdsId":"IP-172113","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":493736,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118563.htm","text":"Version 1.1","linkFileType":{"id":5,"text":"html"}},{"id":485219,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2025/3002/versionHist.txt","size":"4.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"FS 2025-3002 version history"},{"id":483999,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253002/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3002"},{"id":483900,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3002/fs20253002.xml"},{"id":483899,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3002/images"},{"id":483682,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pid.geoscience.gov.au/dataset/ga/145496","text":"Critical Minerals in Ores - geochemistry database"},{"id":483671,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3002/fs20253002.pdf","text":"Report","size":"5.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3002"},{"id":483670,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3002/coverthb3.jpg"},{"id":498997,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118502.htm","text":"Version 1.0","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0: March 26, 2025; Version 1.1: April 30, 2025; Version 1.2: May 22, 2025","contact":"Program Coordinator, Mineral Resources Program
U.S. Geological Survey
913 National Center
Reston, VA 20192
Across the United States, rural residents rely on unregulated and generally unmonitored private wells for drinking water, which may pose serious health risks due to unrecognized contaminants. We assessed the nature, degree, and spatial distribution of cumulative health risks from inorganic contaminants in groundwater. Our analysis included nearly 84,000 data points from 6500+ wells, across 51 of Montana's 98 watersheds, using a public groundwater database. We compared a drinking water screening level cumulative risk assessment (CRA) for inorganics based on the U.S. Environmental Protection Agency (EPA) protective health thresholds (Maximum Contaminant Level Goals, Health Advisories [MCLG-HAs]) to a CRA based on EPA public supply enforceable Maximum Contaminant Levels (MCLs). Based on median concentrations of 19 inorganics (antimony, arsenic, barium, beryllium, boron, cadmium, chromium, copper, fluoride, manganese, molybdenum, nickel, nitrate, lead, selenium, strontium, thallium, uranium, zinc), 75% of watersheds had MCLG-HA-based cumulative risk values > 1.0; arsenic and uranium contributed the most risk, followed by strontium, fluoride, manganese and boron. Hence, this screening level (Tier I) CRA indicated widespread potential for unrecognized human health risk to private well users from inorganic contaminants considering both carcinogenic and non-carcinogenic risks. Sensitivity analysis showed that benchmarks applied (MCLG-HAs versus MCLs) exerted the largest control on results. Our findings identify priority regions for Tier 2 risk assessments to elucidate local sources and distributions of geogenic versus anthropomorphic contaminants. Our study is the first statewide assessment of cumulative health risk from groundwater that we are aware of, and results support increased statewide drinking water education and testing to reduce human health risks from contaminated private well water.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2025.125810","usgsCitation":"Eggers, M., Sigler, W., Kiekover, N., Bradley, P., Smalling, K., Parker, A., Peterson, R., and LaFave, J., 2025, Statewide cumulative human health risk assessment of inorganics-contaminated groundwater wells, Montana, USA: Environmental Pollution, v. 369, 125810, 17 p., https://doi.org/10.1016/j.envpol.2025.125810.","productDescription":"125810, 17 p.","ipdsId":"IP-167347","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":489772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2025.125810","text":"Publisher Index Page"},{"id":482274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Biological responses in single metal exposures are used to parameterize toxicity functions, which include accumulations of hydrogen and selected metals on biological receptors, intrinsic potencies of hydrogen and metals, sensitivities of organisms, and times of exposure. The model then is used to predict responses in multiple metal laboratory exposures and field-collected porewater. The following sensitivity sequence in porewater was determined based on endpoints of survival or total abundance: juvenile white sturgeon greater than (>) Ephemerellidae family > Hyalella azteca > Heptageniidae family about equal to (~) benthic macroinvertebrate community > Brachycentridae family. The fraction of porewater samples that are predicted to have adverse impacts on benthic biota (20-percent or greater negative response) depends on organism sensitivities and metal toxicities, and ranges from 44 to 48 percent for juvenile white sturgeon, 23 to 26 percent for the Ephemerellidae family, 16 to 22 percent for Hyalella azteca, 5 to 8 percent for the Heptageniidae family and BMI community, and 0 percent for the caddisfly family. The most toxic porewater in the upper Columbia River Basin (UCR) is at the backwater bar site at Deadmans Eddy and China Bend. The model also indicates that the element responsible for the most toxic conditions in UCR porewater is copper for all organisms, except Hyalella azteca and the metal-insensitive Brachycentridae family. Copper and lead result in the most toxic conditions for Hyalella azteca. This approach and results can aid in assessing metal toxicity and its potential risk to aquatic biota in ecosystems impacted by historical mining activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255001","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Balistrieri, L.S., 2025, Sensitivity of benthic biota and toxicity of cadmium, cobalt, copper, nickel, lead, and zinc mixtures in Washington, United States, and British Columbia, Canada: U.S. Geological Survey Scientific Investigations Report 2025–5001, 19 p., https://doi.org/10.3133/sir20255001.","productDescription":"v, 19 p.","onlineOnly":"Y","ipdsId":"IP-168170","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":492689,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118446.htm","linkFileType":{"id":5,"text":"html"}},{"id":482001,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5001/images"},{"id":482002,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5001/sir20255001.XML"},{"id":482000,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255001/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5001"},{"id":481999,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5001/sir20255001.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5001"},{"id":481998,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5001/coverthb.jpg"}],"country":"Canada, United States","state":"British Columbia, Washington","otherGeospatial":"Upper Columbia River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.333,\n 49.5\n ],\n [\n -118.333,\n 49.5\n ],\n [\n -118.333,\n 48.6\n ],\n [\n -117.333,\n 48.6\n ],\n [\n -117.333,\n 49.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The demand for metals and raw materials, such as nickel and copper, has been projected to expand in the coming decades, driven by the global energy transition, the need for green technologies, and expanding infrastructure. Consequently, the increasing extraction and production of mining waste can have adverse impacts on surrounding environments and human health. The aim of this thematic collection is to fill critical knowledge gaps in the present-day cycles of metal(loid)s from source to larger sinks, and the effect of environmental management, anthropogenic development, and climate change. Altogether, the studies have been conducted in different natural settings around the world and comprise investigations in laterites, a soil-medicinal plant system, watersheds, and banded iron formations, among others. The geochemical applications in tracing mineralization, its secondary products, and/or potential impact on the immediate environment are highly diverse with applied tools ranging from isotope tracers to major and trace element systematics. Particularly the use of rare earth elements, their patterns and anomalies are methods employed by several studies in this collection. We summarize the findings to offer a potential future direction for the use of geochemical tracing techniques in resource exploration in the context of climate change and environmental challenges.
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Given the toxicity of copper to invertebrates, this study assessed the influence of this legacy on present day nearshore aquatic and terrestrial ecosystems. We measured the metal (Co, Cu, Ni, Zn, Cd) and metalloid (As) concentrations in sediment, pore water, surface water, larval and adult insects, and two riparian spider taxa collected from Torch Lake and a nearby reference lake. Overall, elevated metal and metalloid concentrations, particularly Cu, were measured in all sediment samples and some surface and pore water samples collected from Torch Lake. For instance, Cu concentrations in the Torch Lake sediment were ∼200% higher than the reference lake and all measured concentrations exceeded predicted effects concentrations by at least ninefold. Within larval insect tissues, we observed 160% higher Cu concentrations than measured in the reference lake, and Cu was the only measured element above predicted effects concentrations in Torch Lake. Adult insects collected at both lakes had similar metal concentrations irrespective of exposure levels. Yet we found 100% higher copper concentrations in Torch Lake riparian spiders, demonstrating elevated exposure risk to insectivores across the aquatic-terrestrial boundary. Our results highlight that other metals in the mixture may not be as concerning to adjacent riparian ecosystems, but copper remains a contaminant of concern in Torch Lake 60 years after mining ceased.
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Because copper’s toxicity changes with water chemistry, using the same copper concentration in different waterbodies could yield different outcomes. We demonstrate how measuring water chemistry parameters and using the Biotic Ligand Model (BLM) and multiple linear regression (MLR) models can predict a suitable, site-specific copper concentration for management. We exposed zebra mussel adults and non-target organisms to varying concentrations of copper over 10 d in a mobile laboratory. We found that one non-target species, Daphnia magna, had a 50% chance of survival at 9.50 µg Cu/L (i.e., the 50% lethal concentration, LC50), within our BLM-predicted range of 3.38–16.95 µg Cu/L LC50 values. In the future, managers could make similar predictions and tailor their copper concentrations to their management goals. We also measured zebra mussel larvae mortality at copper concentrations ranging from 0 to 191 µg Cu/L. While those results were inconclusive, we present the results of this work as a foundation for future projects. Our study underscores the importance of developing site-specific copper concentration recommendations and demonstrates the potential utility of the BLM and MLR approaches for informing those recommendations.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-025-09231-4","usgsCitation":"Dahlberg, A.D., Waller, D.L., Severson, T.J., Barbour, M.T., Meulemans, M., Wise, J.K., Bajcz, A.W., Jankowski, M., and Phelps, N.B., 2025, Using bioavailability modeling to refine copper treatments for zebra mussel control and better understanding risks to non-target species: Scientific Reports, v. 15, 29333, 16 p., https://doi.org/10.1038/s41598-025-09231-4.","productDescription":"29333, 16 p.","ipdsId":"IP-158934","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":503431,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-09231-4","text":"Publisher Index Page"},{"id":503214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Pelican 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The post-Carr Fire data were compared to available pre-Carr Fire data to help determine if there have been wildfire-induced changes in the aquatic communities within the Whiskeytown National Recreational Area. Benthic sediment results for metals of biological concern were compared with consensus-based probable effect concentrations from previously published sediment-quality guidelines. Results from 2020 sampling indicated exceedances of these guidelines at one site for cadmium, chromium, copper, and zinc; there were exceedances of the guidelines at three sites for nickel. Concentrations of metals of biological concern in fish and invertebrate tissue samples generally varied among sites and years, with no pattern with specific reference to the Carr Fire. Average zinc and lead concentrations in composite invertebrate samples were slightly higher in 2020 than in previous years, and arsenic levels were lower in 2020 for invertebrate and fish tissues. Post-Carr Fire stream-habitat and sediment-size characterization values did not change substantially when compared to pre-Carr Fire values, or had high variation among all sites and years. Fish and amphibian inventories demonstrated that fewer total fish and amphibians were collected post-Carr Fire, but higher numbers of native Sacramento Sucker (Catostomus occidentalis) and Sacramento Pikeminnow (Ptychocheilus grandis) were collected than in previous years. The combined histories of mining and frequent wildfires in the area pose an increased risk for metal contamination throughout the aquatic system. Continued monitoring for multilevel trophic effects of contaminants can provide information about the overall health of the Whiskeytown National Recreation Area and surrounding region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1201","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Wulff, M.L., Brown, L.R., and Violette, V.L., 2024, Post Carr Fire bioassessment data report, Whiskeytown National Recreation Area, Shasta County, California: U.S. Geological Survey Data Report 1201, 26 p., https://doi.org/10.3133/dr1201.","productDescription":"Report: viii, 26 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-125210","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":463558,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90WGKWI","text":"USGS Data Release","description":"Wulff, M.L., Brown, L.R., and Violette, V.L., 2023, Post Carr Fire Bioassessment Data, Whiskeytown National Recreation Area, Shasta County, California, 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P90WGKWI.","linkHelpText":"Post Carr Fire Bioassessment Data, Whiskeytown National Recreation Area, Shasta County, California, 2020"},{"id":463557,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1201/full"},{"id":463556,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1201/images"},{"id":463555,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1201/dr1201.XML"},{"id":463554,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1201/dr1201.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1201/coverthb.jpg"}],"country":"United States","state":"California","county":"Shasta County","otherGeospatial":"Whiskeytown National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.7971714207388,\n 41.04817475780641\n ],\n [\n -122.7971714207388,\n 40.53716575964799\n ],\n [\n -122.2801689286946,\n 40.53716575964799\n ],\n [\n -122.2801689286946,\n 41.04817475780641\n ],\n [\n -122.7971714207388,\n 41.04817475780641\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819