Corrosive groundwater can cause lead, copper, and other metals to leach from pipes and plumbing fixtures in water distribution systems. Metals, if ingested, could lead to serious health implications to the nearly 2.9 million people in Louisiana who obtain their drinking water from groundwater sources. Four indices—the Langelier Saturation Index (LSI), Ryznar Stability Index (RSI), Puckorius Scaling Index (PSI), and the Potential to Promote Galvanic Corrosion (PPGC)—in addition to an analysis which normalized the results from the existing indices, the Combined Index (CI), were used to assess the corrosivity of groundwater in Louisiana and identify areas within eight major aquifers and aquifer systems with moderate to high corrosivity potential. The purpose of this study is to provide State and local governments, public water system managers, and the nearly 500,000 private well owners in Louisiana with information needed to manage drinking-water supplies and mitigate potential health risks related to leaching of metals from water pipes and fixtures.
The average scores of untreated groundwater samples from approximately 375 wells by index are as follows: LSI, −1.28; RSI, 9.78; PSI, 9.34; and CI, 4.14. The PPGC does not produce a numerical score, but the total percentage of class counts can be used to assign a classification; overall, samples in Louisiana were classified as significant concern. The percentages of groundwater samples from wells classified as potentially corrosive, by index, are as follows: LSI, 53 percent; RSI, 94 percent; PSI, 81 percent; PPGC, 98 percent; and CI, 81 percent. The percentages of samples classified as indeterminate, by index, are as follows: LSI, 46 percent; RSI, 5 percent; PSI, 12 percent; PPGC, 0 percent; and CI, 18 percent.
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"nation\":\"USA \"}}]}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
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","tableOfContents":"Earthquakes have the potential to substantially affect mining operations, potentially leading to supply chain disruptions and adversely affecting the global economy. This study explores the quantification of earthquake risk to copper and rhenium commodity supply by examining the spatial concentration of high earthquake hazard areas and the commodity-specific mining, smelting, and refining operations across the globe. Because many of the largest facilities are concentrated geographically near the highly seismic regions of South America, East Asia, and the Pacific, there is a potential for cascading effects on the entire supply chain. The analysis indicates that the expected annual disruption of global production is 0.3–1.1 percent for copper mines, 1.8–4.0 percent for smelters, and 1.5–3.3 percent for refineries. Expected annual disruption of global rhenium production capacity is 0.32–1.32 percent. The research highlights that the potential lost revenue from earthquake disruptions is from $315 million to $1.29 billion for copper mining, $1.92 billion to $4.33 billion for copper smelting, $2.06 billion to $4.52 billion for copper refining, and $337,000 to $1.40 million for rhenium production capacity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241028","programNote":"Earthquake Hazards Program and Mineral Resources Program","usgsCitation":"Jaiswal, K.S., Luco, N., Schnebele, E.K., Nassar, N.T., and Otarod, D., 2024, Quantitative risk of earthquake disruption to global copper and rhenium supply: U.S. Geological Survey Open-File Report 2024–1028, 19 p., https://doi.org/10.3133/ofr20241028.","productDescription":"iv, 19 p.","onlineOnly":"Y","ipdsId":"IP-155335","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true},{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":499250,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117153.htm","linkFileType":{"id":5,"text":"html"}},{"id":431677,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241028/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1028"},{"id":431623,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1028/ofr20241028.xml"},{"id":431622,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1028/images"},{"id":430730,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1028/coverthb.jpg"},{"id":430732,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1028/ofr20241028.pdf","text":"Report","size":"17.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1028"}],"contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
The low-carbon energy transition requires significant increases in production for many mineral commodities. Understanding demand, technological requirements, and prices associated with this production increase requires understanding the supply chain dynamics of many minerals simultaneously, and via a consistent framework. A generalized economics-informed material flow method, global materials modeling using Bayesian optimization, captures the market dynamics of key mineral commodities. The method relies only on a limited set of widely available historical data as input, enabling quantification of economic relationships (elasticities) for supply chain components where data are sparse, and relationships cannot be obtained via traditional statistical approaches. Building upon established material flow analysis (MFA) and economic modeling techniques, Bayesian optimization was applied to fit an economics-informed MFA model to global historical demand, supply, and price for aluminum, copper, gold, lead, nickel, silver, iron, tin, and zinc. This approach enables estimates for the evolution of ore grades, mine costs, refining charges, sector-specific demand, and scrap collection for each commodity. Economic relationships were quantified and compared with a database compiled from the literature, including 1333 values from 213 analyses across 65 publications. Discrepancies in methods and limited coverage make use of these parameters in modeling efforts difficult. This work provides a single, homogeneous, probabilistic approach to identifying economic relationships across mineral supply chains, with uncertainty quantification, a literature database for comparison, and a modeling framework in which to use them. This article met the requirements for a Gold-Gold JIE data openness badge described at http://jie.click/badges.
","language":"English","publisher":"Wiley","doi":"10.1111/jiec.13517","usgsCitation":"Ryter, J.W., Bhuwalka, K., O’Rourke, M., Montanelli, L., Cohen-Tanugi, D., Roth, R., and Olivetti, E., 2024, Understanding key mineral supply chain dynamics using economics-informed material flow analysis and Bayesian optimization: Journal of Industrial Ecology, v. 28, no. 4, p. 709-726, https://doi.org/10.1111/jiec.13517.","productDescription":"18 p.","startPage":"709","endPage":"726","ipdsId":"IP-157688","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":466986,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jiec.13517","text":"Publisher Index Page"},{"id":463085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-07-08","publicationStatus":"PW","contributors":{"authors":[{"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":916487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bhuwalka, Karan 0000-0002-1963-6717","orcid":"https://orcid.org/0000-0002-1963-6717","contributorId":345417,"corporation":false,"usgs":false,"family":"Bhuwalka","given":"Karan","email":"","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":916488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Rourke, Michelena","contributorId":345418,"corporation":false,"usgs":false,"family":"O’Rourke","given":"Michelena","email":"","affiliations":[{"id":39516,"text":"University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":916489,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Montanelli, Luca 0000-0002-7784-7627","orcid":"https://orcid.org/0000-0002-7784-7627","contributorId":345419,"corporation":false,"usgs":false,"family":"Montanelli","given":"Luca","email":"","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":916490,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cohen-Tanugi, David 0000-0003-2488-4819","orcid":"https://orcid.org/0000-0003-2488-4819","contributorId":345420,"corporation":false,"usgs":false,"family":"Cohen-Tanugi","given":"David","email":"","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":916491,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roth, Richard","contributorId":257597,"corporation":false,"usgs":false,"family":"Roth","given":"Richard","affiliations":[{"id":52064,"text":"Materials Systems Lab, MIT","active":true,"usgs":false}],"preferred":false,"id":916492,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olivetti, Elsa 0009-0005-4190-8319","orcid":"https://orcid.org/0009-0005-4190-8319","contributorId":345421,"corporation":false,"usgs":false,"family":"Olivetti","given":"Elsa","email":"","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":916493,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70255718,"text":"70255718 - 2024 - Metal release from manganese nodules in anoxic seawater and implications for deep-sea mining dewatering operations","interactions":[],"lastModifiedDate":"2024-07-15T16:13:14.868429","indexId":"70255718","displayToPublicDate":"2024-06-27T07:08:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10742,"text":"ACS ES&T Water","active":true,"publicationSubtype":{"id":10}},"title":"Metal release from manganese nodules in anoxic seawater and implications for deep-sea mining dewatering operations","docAbstract":"The potential mining of deep-sea polymetallic nodules has been gaining increasing attention due to their enrichment in metals essential for a low-carbon future. To date, there have been few scientific studies concerning the geochemical consequences of dewatered mining waste discharge into the pelagic water column, which can inform best practices in future mining operations. Here, we report the results of laboratory incubation experiments that simulate mining discharge into anoxic waters such as those that overlie potential mining sites in the North Pacific Ocean. We find that manganese nodules are reductively dissolved, with an apparent activation energy of 42.8 kJ mol–1, leading to the release of associated metals in the order manganese > nickel > copper > cobalt > cadmium > lead. The composition of trace metals released during the incubation allows us to estimate a likely trace metal budget from the simulated dewatering waste plume. These estimates suggest that released cobalt and copper are the most enriched trace metals within the plume, up to ∼15 times more elevated than the background seawater. High copper concentrations can be toxic to marine organisms. Future work on metal toxicity to mesopelagic communities could help us better understand the ecological effects of these fluxes of trace metals.
This work evaluates glacial dust as a source of sediment, and associated iron (Fe), to the Fe-limited Gulf of Alaska (GoA). A reanalysis of GoA sediment data, using rare earth elements and thorium as provenance tracers, suggests a flux to the ocean surface of Copper River (AK) glacial dust, and associated Fe, that is comparable to the flux of dust from Asia, at least 1,000 km from the narrow mountain valley glacial dust source area. This work suggests dust from Asia may not be the largest source of Fe to the GoA. Dust models fail to accurately simulate this glacial dust transport because their coarse resolution underestimates wind speeds, and the dust flux. This work suggests that glacial dust fluxes may have been important in the geologic past (e.g., the last glacial maximum) from locations where there was more extensive coverage by glaciers than at present.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GL106778","usgsCitation":"Crusius, J., Lao, C., Holmes, T.M., and Murray, J.W., 2024, Alaskan glacial dust is an important iron source to surface waters of the Gulf of Alaska: Geophysical Research Letters, v. 51, no. 12, e2023GL106778, 10 p., https://doi.org/10.1029/2023GL106778.","productDescription":"e2023GL106778, 10 p.","ipdsId":"IP-144402","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":498678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gl106778","text":"Publisher Index Page"},{"id":498516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -166,\n 61\n ],\n [\n -166,\n 48\n ],\n [\n -136,\n 48\n ],\n [\n -136,\n 61\n ],\n [\n -166,\n 61\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":953433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lao, Carsten","contributorId":364912,"corporation":false,"usgs":false,"family":"Lao","given":"Carsten","affiliations":[{"id":87012,"text":"UW Dept of Chemistry","active":true,"usgs":false}],"preferred":false,"id":953434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmes, Thomas M. 0000-0001-8061-4325","orcid":"https://orcid.org/0000-0001-8061-4325","contributorId":364913,"corporation":false,"usgs":false,"family":"Holmes","given":"Thomas","middleInitial":"M.","affiliations":[{"id":87014,"text":"U. Tasmania","active":true,"usgs":false}],"preferred":false,"id":953435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murray, J. W. 0000-0002-8577-7964","orcid":"https://orcid.org/0000-0002-8577-7964","contributorId":364914,"corporation":false,"usgs":false,"family":"Murray","given":"J.","middleInitial":"W.","affiliations":[{"id":87015,"text":"UW School of Oceanography","active":true,"usgs":false}],"preferred":false,"id":953436,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255527,"text":"sir20245029 - 2024 - Dissolved arsenic concentrations in surface waters within the upper portions of the Klamath River Basin, Oregon and California","interactions":[],"lastModifiedDate":"2024-06-21T16:00:45.438369","indexId":"sir20245029","displayToPublicDate":"2024-06-21T06:46:09","publicationYear":"2024","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":"2024-5029","displayTitle":"Dissolved Arsenic Concentrations in Surface Waters Within the Upper Portions of the Klamath River Basin, Oregon and California","title":"Dissolved arsenic concentrations in surface waters within the upper portions of the Klamath River Basin, Oregon and California","docAbstract":"Arsenic toxicity is an environmental health problem. Levels of arsenic in surface waters at some locations in the Klamath River Basin in southern Oregon and northern California can exceed the U.S. Environmental Protection Agency (EPA) standard for drinking water. There are both anthropogenic and natural sources of arsenic. The Klamath River Basin consists primarily of volcanic deposits and contains an underground geothermal system with hot springs and warm water wells, all known natural sources of arsenic. Anthropogenic sources of arsenic are related to the agricultural use of herbicides, fungicides, and insecticides. Surface water arsenic levels can also be affected by fertilizer amendments, evaporative concentration, oxygen-level depletion, and various geochemical transformations that can increase arsenic mobilization.
In this study by the U.S. Geological Survey and the Bureau of Reclamation, dissolved concentrations of arsenic, copper, and lead were measured in surface waters at 39 unique sites within the upper portions of the Klamath River Basin between 2018 and 2022. In every year, except 2022, sites were sampled four times between April and November. Surface-water arsenic concentrations varied up to four-orders of magnitude among sites. Median arsenic concentration was lowest at Cherry Creek (0.03 micrograms per liter [μg/L]) and highest at Wood Kimball Spring (36.7 μg/L), two sites located north of Upper Klamath Lake. The highest arsenic concentrations (17.4±4.9 μg/L, n=3) were found in drain sites (defined here as a waterbody returning used irrigation water) while the lowest arsenic concentrations were found in an artesian well (0.8 μg/L, n=1). The elevated arsenic concentrations of the drain sites suggest that arsenic might be concentrated or mobilized by agricultural activities, water re-use practices, and (or) by geochemical processes occurring around water stored in drains (that is, in the water column and across sediment water boundaries). A source of arsenic in drain water in the Klamath Strait Drain area includes water used for irrigation originating from Ady Canal. Other potential sources include groundwater, geothermal water, and local soils and sediments.
Seasonal differences in surface-water arsenic concentrations were detected at 13 sites, 10 of which had higher arsenic concentrations in summer than in either spring or fall. The sites sampled around Upper Klamath Lake, the impounded rivers, one of the two canal sites, and 5 of the 14 river sites had higher surface-water arsenic concentrations in the summer than in either spring or fall. Surface-water arsenic concentrations from groundwater sources (that is, springs and in the artesian well) did not vary significantly among seasons (p-values greater than 0.1).
Median surface-water concentrations of copper and lead ranged from 0.03 to 3.7 μg/L, and from 0.013 to 0.175 μg/L (n=2–18), respectively. Dissolved concentrations of both metals were below acute toxicity endpoints reported by the EPA for freshwater animals. Surface-water arsenic concentrations varied independently from corresponding changes in surface-water lead or copper concentrations. However, arsenic concentrations measured in bed-sediment samples collected from a subset of sites located north of Upper Klamath Lake correlated strongly and significantly with the corresponding sedimentary lead concentrations (p=0.015).
Aqueous arsenic speciation measured in a subset of sites in 2019 and 2022 showed that all the arsenic existed as arsenic (V), the most oxidized arsenic species, and presumably, the least toxic. The highest proportions of arsenite (As(III)), the presumably most toxic arsenic species, relative to total arsenic concentrations were found at drain sites.
Our assessment of dissolved arsenic concentrations in various surface-water bodies in the Upper Klamath River Basin reveals geographical areas of consistently low (below 2.1 μg/L), moderate (below 10 μg/L) and high (above 10 μg/L) surface-water arsenic concentrations. South of Upper Klamath Lake, surface-water arsenic concentrations were consistently higher than 20 μg/L at two drain sites located in an area of predominant agricultural land use with extensive water re-use practices. North of Upper Klamath Lake, surface-water arsenic concentrations greater than 20 μg/L were consistently measured at sites with limited nearby agricultural activities, suggesting a geogenic source. The consistently high arsenic levels from the Wood River at Jackson F. Kimball State Park, Fort Creek, and Crooked Creek, which are sites located at or near headwater spring sources, suggest a natural background source of arsenic. Water flowing downstream from this area could be a potential source of arsenic to Upper Klamath Lake and the Upper Klamath River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20245029","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Croteau, M.N., Topping, B.R., and Carlson, R.A., 2024, Dissolved arsenic concentrations in surface waters within the upper portions of the Klamath River Basin, Oregon and California: U.S. Geological Survey Scientific Investigations Report 2024–5029, 42 p., https://doi.org/10.3133/sir20245029.","productDescription":"Report: viii, 38 p.; Data Release","ipdsId":"IP-149938","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":430399,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P943CWH1","text":"USGS Data Release","description":"Hill, K.L., Croteau, M.N., Topping, B.R., Caro, D.A., Parris, J.L., Zierdt Smith, E.L., and Baesman, S.M., 2021, Dissolved arsenic, copper and lead concentrations in surface water within the Klamath Basin (ver 4.0, April 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P943CWH1.","linkHelpText":"Dissolved arsenic, copper and lead concentrations in surface water within the Klamath Basin (ver 4.0, April 2023)"},{"id":430404,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245029/full"},{"id":430403,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5029/images"},{"id":430402,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5029/sir20245029.xml"},{"id":430401,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5029/sir20245029.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":430400,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5029/covrthb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.44639737545533,\n 43\n ],\n [\n -122.44639737545533,\n 41.66727944834608\n ],\n [\n -120.85711312398831,\n 41.66727944834608\n ],\n [\n -120.85711312398831,\n 43\n ],\n [\n -122.44639737545533,\n 43\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
Increasing stream metal concentrations apparently caused by climate warming have been reported for a small number of mountain watersheds containing hydrothermally altered bedrock with abundant sulfide minerals (mineralized watersheds). Such increases are concerning and could negatively impact downstream ecosystem health, water resources, and mine-site remediation efforts. However, the pervasiveness and typical magnitude of these trends remain uncertain. We aggregated available streamwater chemistry data collected from late summer and fall over the past 40 years for 22 mineralized watersheds throughout the Colorado Rocky Mountains. Temporal trend analysis performed using the Regional Kendall Test indicates significant regional upward trends of ∼2% of the site median per year for sulfate, zinc, and copper concentrations in the 17 streams affected by acid rock drainage (ARD; median pH ≤ 5.5), equivalent to concentrations roughly doubling over the past 30 years. An examination of potential load trends utilizing streamflow data from eight “index gages” located near the sample sites provides strong support for regionally increasing sulfate and metal loads in ARD-affected streams, particularly at higher elevations. Declining streamflows are likely contributing to regionally increasing concentrations, but increasing loads appear to be on average an equal or greater contributor. Comparison of selected site characteristics with site concentration trend magnitudes shows the highest correlation for mean annual air temperature and mean elevation (R2 of 0.42 and 0.35, respectively, with all others being ≤0.14). Future research on climate-driven controlling mechanisms should therefore focus on processes such as melting of frozen ground directly linked to site mean temperature and elevation.
The Pecos National Historical Park protects 2.9 miles of the Pecos River and part of Glorieta Creek within the park boundaries. Updated water-quality data can assist resource managers in determining if effluent from two nearby wastewater treatment plants (WWTPs) is affecting the quality of the water in the Pecos River and Glorieta Creek within the park. Water samples were collected four times in 2022 at two WWTP outfalls, two locations on Glorieta Creek, and two locations on the Pecos River. Water quality parameters (dissolved oxygen, water temperature, pH, turbidity, specific conductance) were measured in the field, and samples were collected and analyzed for major ions, trace elements, rare earth elements, nutrients, bacteria, and per- and polyfluoroalkyl substances (PFAS).
Specific conductance values in all samples collected from Glorieta Creek exceeded the New Mexico Surface Water Quality Standard (NMWQS) of 300 microsiemens per centimeter at 25 degrees Celsius. Concentrations of dissolved oxygen in three samples collected from Glorieta Creek and one sample for the Pecos WWTP did not meet the standard for high-quality cold-water use. Concentrations of Escherichia coli in samples from the Pecos WWTP exceeded the NMWQS of 235 colony-forming units per 100 milliliters during every sampling event. Concentrations of E. coli in samples collected from two sites on Glorieta Creek in August exceeded the NMWQS.
The chemical signature of water from Glorieta Creek indicated groundwater and (or) septic system contributions. Water samples collected from the Pecos River all had similar chemical signatures of calcium-bicarbonate type. Although concentrations of several trace elements were higher in samples from Glorieta Creek than in samples from the Pecos River, no concentrations exceeded the drinking-water standards. No concentrations exceeded aquatic life standards except for copper concentrations in two samples from the downstream location on Glorieta Creek. The trace element signature and the gadolinium anomalies in the WWTP samples indicate anthropogenic contributions.
Eleven of the 28 PFAS compounds analyzed were detected in samples during this study, with the treated wastewater effluent samples having the highest total PFAS concentrations. The total PFAS concentrations in samples from Glorieta Creek decreased by an order of magnitude as the creek flowed downstream. At the downstream site on the Pecos River, there was only one sample that had a detection of PFAS.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Hydropsyche and Arctopsyche are filter-feeding caddisflies (Order: Trichoptera; Family: Hydropsychidae) that are commonly used to monitor metal exposures in rivers. While tissue residue concentrations provide important bioaccumulation data regarding metal bioavailability, they do not provide information regarding the mechanisms of uptake and loss, or exposure history. This study examined the physiological processes that control Cu and Cd uptake and loss using a biokinetic bioaccumulation model. Larvae of each taxon were experimentally exposed to either water or food enriched with stable isotopes (65Cu and 106Cd). Dissolved Cu uptake (ku) was similar between species (2.6–3.4 L-1g 1d-1), but Cd uptake was 3-fold higher in Hydropsyche than Arctopsyche (1.85 L-1g 1d-1 and 0.60 L-1g 1d-1, respectively). Cu and Cd efflux rates (ke) were relatively fast (0.14 d-1–0.24 d-1) in both species, and may explain, in part, their metal tolerance to mine-impacted rivers. Food ingestion rates (IR), assimilation efficiency (AE) of 65Cu and 106Cd from laboratory diets were also derived and used in a biodynamic model to quantify the relative contribution of dissolved and dietary exposure routes. Results from the biodynamic model were compared to tissue concentrations observed in a long-term field study and indicated that because dissolved Cu and Cd exposures accounted for less than 20% of body concentrations of either taxon, dietary exposure was the predominant metal pathway. An estimation of exposure history was determined using the model to predict steady state concentrations. Under constant exposure conditions (dissolved plus diet), steady state concentrations were reached in less than 30 days, an outcome largely influenced by rapid efflux (ke).
The Pinto Mountain Fault Zone (PMFZ) marks a major structural boundary between east-oriented sinistral faults of the eastern Transverse Ranges (to the south) and northwest-oriented dextral faults of the south-central Mojave Desert (to the north). These structural fault systems comprise sinistral and dextral deformational domains of the Eastern California Shear Zone (ECSZ) that intersect one another in the Copper Mountain and Twentynine Palms areas. The U.S. Geological Survey (USGS) is conducting detailed geologic mapping and geochronologic investigations designed to clarify geometric, kinematic, and temporal relations among the two domains, that are focused on the central portion of the left-lateral PMFZ near its intersection with the right-lateral Copper Mountain Fault (CMF) and Mesquite Lake Fault Zone (MLFZ).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic Mapping Forum 23/24 abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"University of Minnesota","usgsCitation":"Menges, C., Dudash, S.L., and Mahan, S.A., 2024, Using geologic mapping to understand temporal and spatial relations of closely clustered to concurrent latest Holocene surface ruptures on two intersecting faults, south-central Mojave Desert, California, in Geologic Mapping Forum 23/24 abstracts, p. 16-17.","productDescription":"2 p.","startPage":"16","endPage":"17","ipdsId":"IP-160493","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":464812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":464783,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://conservancy.umn.edu/items/f2deba60-7ac2-49ac-b63f-b7422a85065d","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"south-central Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.1167,\n 34.2333\n ],\n [\n -116.1167,\n 34.125\n ],\n [\n -116,\n 34.125\n ],\n [\n -116,\n 34.2333\n ],\n [\n -116.1167,\n 34.2333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Menges, Christopher M. 0000-0002-8045-2933","orcid":"https://orcid.org/0000-0002-8045-2933","contributorId":204511,"corporation":false,"usgs":true,"family":"Menges","given":"Christopher M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":920288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudash, Stephanie L. 0000-0001-8728-5915 sdudash@usgs.gov","orcid":"https://orcid.org/0000-0001-8728-5915","contributorId":5911,"corporation":false,"usgs":true,"family":"Dudash","given":"Stephanie","email":"sdudash@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":920289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":920290,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250088,"text":"70250088 - 2024 - Using multiple metal mixture models to predict toxicity of riverine sediment porewater to the benthic life stage of juvenile white sturgeon (Acipenser transmontanus)","interactions":[],"lastModifiedDate":"2024-01-04T14:52:22.03027","indexId":"70250088","displayToPublicDate":"2023-09-26T06:35:14","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17090,"text":"Environmental Toxicology & Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Using multiple metal mixture models to predict toxicity of riverine sediment porewater to the benthic life stage of juvenile white sturgeon (Acipenser transmontanus)","docAbstract":"Five metal mixture dose–response models were used to predict the toxicity of porewater to young sturgeon at areas of interest in the Upper Columbia River (WA, USA/BC, Canada) and to evaluate these models as tools for risk assessments. Dose components of metal mixture models included exposure to free metal ion activities or metal accumulation by biotic ligands or humic acid, and links of dose to response used logistic equations, independent joint action equations, or additive toxicity functions. Laboratory bioassay studies of single metal exposures to juvenile sturgeon, porewater collected in situ in the fast-flowing Upper Columbia River, and metal mixture models were used to evaluate toxicity. The five metal mixture models were very similar in their predictions of adverse response of juvenile sturgeon and in identifying copper (Cu) as the metal responsible for the most toxic conditions. Although the modes of toxic action and the 20% effective concentration values were different among the dose models, predictions of adverse response were consistent among models because all doses were tied to the same biological responses. All models indicated that 56% ± 5% of 122 porewater samples were predicted to have <20% adverse response, 25% ± 5% of samples were predicted to have 20% to 80% adverse response, and 20% ± 4% were predicted to have >80% adverse response in juvenile sturgeon. The approach of combining bioassay toxicity data, compositions of field porewater, and metal mixture models to predict lack of growth and survival of aquatic organisms due to metal toxicity is an important tool that can be integrated with other information (e.g., survey studies of organism populations, life cycle and behavior characteristics, sediment geochemistry, and food sources) to assess risks to aquatic organisms in metal-enriched ecosystems. Environ Toxicol Chem 2023;00:1–12. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.
A forest bed of tree stumps currently in the intertidal zone at Girdwood, south-central Alaska, records coseismic submergence during the penultimate great earthquake. Tree-ring samples from ten spruce stumps were crossdated to develop a 149-year-long ring-width chronology. Radiocarbon wiggle-matching found that single-ring ages from the chronology were offset 28 ± 7 years older than the IntCal20 calibration curve and that the last ring of the chronology dated as 1169 to 1189 CE (781–761 cal. yr. BP) at the 95% confidence level. Bark was observed on some stumps, six samples had the same year for the last growth ring, and so this wiggle-match date is also the best estimate of the date of the penultimate great earthquake. This date is in good agreement with a date for this event in a seismo-turbidite record from Skilak Lake but not with previous dates from Bayesian models of maximum- and minimum-limiting ages from coastal salt marshes. Reanalysis of the coastal salt marsh ages with the data grouped by area, context and material found that outer wood samples from stumps at coseismic submergence sites and a Bayesian limiting age model based on just herbaceous plant ages from Turnagain Arm and the Copper River area are both consistent with our wiggle-match date. Furthermore, coseismic emergence ages from Cape Suckling and Yakataga are older than the penultimate earthquake and so likely relate to an earlier uplift event in this eastern area. The rupture extent during the penultimate great earthquake appears to have been less than in the 1964 great earthquake and the interseismic interval between these two events was 785 ± 10 years.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.qsa.2023.100142","usgsCitation":"Barclay, D.J., Haeussler, P., and Witter, R.C., 2023, Dating the penultimate great earthquake in south-central Alaska using tree-ring crossdating and radiocarbon wiggle-matching: Quaternary Science Advances, v. 13, 100142, 13 p., https://doi.org/10.1016/j.qsa.2023.100142.","productDescription":"100142, 13 p.","ipdsId":"IP-158222","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":498704,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.qsa.2023.100142","text":"Publisher Index Page"},{"id":498618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.97392172569602,\n 60.587785877878815\n ],\n [\n -156.97392172569602,\n 56.48596044935496\n ],\n [\n -140.95577716118677,\n 56.48596044935496\n ],\n [\n -140.95577716118677,\n 60.587785877878815\n ],\n [\n -156.97392172569602,\n 60.587785877878815\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barclay, David J 0009-0007-9629-3731","orcid":"https://orcid.org/0009-0007-9629-3731","contributorId":365136,"corporation":false,"usgs":false,"family":"Barclay","given":"David","middleInitial":"J","affiliations":[{"id":87054,"text":"SUNY Cortland, Cortland, NY","active":true,"usgs":false}],"preferred":false,"id":953743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":953744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":219962,"corporation":false,"usgs":true,"family":"Witter","given":"Robert","email":"rwitter@usgs.gov","middleInitial":"C.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":953745,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249935,"text":"70249935 - 2023 - Bioavailability and toxicity models of copper to freshwater life: The state of regulatory science","interactions":[],"lastModifiedDate":"2023-12-04T17:25:25.241762","indexId":"70249935","displayToPublicDate":"2023-10-11T06:43:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Bioavailability and toxicity models of copper to freshwater life: The state of regulatory science","docAbstract":"Efforts to incorporate bioavailability adjustments into regulatory water quality criteria in the United States have included four major procedures: hardness-based single-linear regression equations, water-effect ratios (WERs), biotic ligand models (BLMs), and multiple-linear regression models (MLRs) that use dissolved organic carbon, hardness, and pH. The performance of each with copper (Cu) is evaluated, emphasizing the relative performance of hardness-based versus MLR-based criteria equations. The WER approach was shown to be inherently highly biased. The hardness-based model is in widest use, and the MLR approach is the US Environmental Protection Agency's (USEPA's) present recommended approach for developing aquatic life criteria for metals. The performance of criteria versions was evaluated with numerous toxicity datasets that were independent of those used to develop the MLR models, including olfactory and behavioral toxicity, and field and ecosystem studies. Within the range of water conditions used to develop the Cu MLR criteria equations, the MLR performed well in terms of predicting toxicity and protecting sensitive species and ecosystems. In soft waters, the MLR outperformed both the BLM and hardness models. In atypical waters with pH <5.5 or >9, neither the MLR nor BLM predictions were reliable, suggesting that site-specific testing would be needed to determine reliable Cu criteria for such settings. The hardness-based criteria performed poorly with all toxicity datasets, showing no or weak ability to predict observed toxicity. In natural waters, MLR and BLM criteria versions were strongly correlated. In contrast, the hardness-criteria version was often out of phase with the MLR and, depending on waterbody and season, could be either strongly overprotective or underprotective. The MLR-based USEPA-style chronic criterion appears to be more generally protective of ecosystems than other models.
During the World War and Cold War eras (1910s–1990s), domestic consumption of numerous mineral commodities relied increasingly on imported supplies. Consumption reliance has since expanded to include 50 “critical minerals” (elements and mineral commodities) that are mostly to entirely imported and subject to curtailment by suppliers or supply chain disruption. New domestic supplies of critical minerals are being pursued by mining companies and by several federal departments and agencies. Information on domestic deposits and resources of critical minerals is being compiled by the U.S. Geological Survey Mineral Resources Program, which has organized investigations by mineral system, deposit type, and commodity.
Production, reserves, resources, and inventories of 21 critical minerals in domestic magmatic-hydrothermal deposits related to subduction-generated magmatism, and in tailings, slag, slimes, and electrolyte from copper concentrators, smelters, and refineries that processed some deposits, are largely restricted to Western States and Alaska. The critical mineral commodities Al, Sb, As, Bi, Co, fluorite, Ga, Ge, In, Mn, Ni, Nb, Pd, Pt, potash, Re, Ta, Te, Sn, W, and V are variably concentrated in porphyry/skarn copper-(molybdenum), skarn-replacement-vein (S-R-V) tungsten, polymetallic sulfide S-R-V intermediate sulfidation (IS), high-sulfidation gold-silver, low-sulfidation gold-silver, and lithocap alunite deposit types. These deposit types occur in porphyry copper-molybdenum-gold, alkalic porphyry, porphyry tin (granite related), and reduced intrusion-related mineral systems.
Production, reserves, and resources of Co, Ni, Nb, Pd, Pt, Ta, Sn, and V in subduction-related deposits in Western States are insignificant to small, mostly equivalent to months to a few years of recent annual domestic consumption (2016–2020). Significant inventories, equivalent to 2 or more years of consumption of aluminum, antimony, potash, and tungsten in unmined S-R-V tungsten, polymetallic sulfide S-R-V-IS, and lithocap alunite deposits vary from approximately 2 to 8 years. Several decades of consumption of arsenic, bismuth, fluorite, gallium, germanium, and indium exist in some polymetallic sulfide S-R-V-IS and lithocap alunite deposit types.
Based on concentrations of critical minerals in reserves, resources, drill holes, and deposit domains (ore types), and in captive refinery records, the largest domestic inventories of Sb, As, Bi, Re, and Te, and possibly Ga, Ge, In, Sn, and W, are in porphyry copper-molybdenum (Cu-Mo) deposits in Alaska, Idaho, Utah, and Arizona, and in interim products of processing porphyry Cu-Mo deposit ores for recovery of copper and molybdenum. Concentrations of critical minerals in archival specimens and sample collections, although somewhat biased by collection and conservation decisions and categorization, are broadly proportionate to those in reserves, resources, and drill holes. These concentrations imply significant inventories of some critical minerals in deposits for which production, resources, and refinery records are unavailable or incomplete.
Because of the large masses of ores mined and processed annually (hundreds of millions of metric tons) and in reserves and resources (hundreds of millions of metric tons to billions of metric tons), calculated inventories of critical minerals in porphyry Cu-Mo deposits are equivalent to decades and centuries of recent consumption. However, these inventories should not be considered consumable supplies without reserve definition and development of economically viable mining plans and recovery techniques. An expeditious strategy for elimination or reduction of import reliance is recovery, and improved recovery efficiency, of Sb, As, Bi, Re, and Te, and possibly Ga, Ge, In, Ni, Sn, Ti, and W; during concentration and refining of copper and molybdenum minerals in ores of operating porphyry Cu-Mo mines; and in unmined porphyry Cu-Mo resources. These chalcophile, siderophile, and lithophile critical minerals, often undetectable in ore, are concentrated (hundreds of parts per million to percents) in slimes and electrolyte during copper electrorefining or could be recovered, in part, during sulfide concentration and smelting. Other than rhenium (recovered during molybdenum refining) and tellurium, all have been routinely discarded.
Subsidization (for example, commodity price guarantees, tax credits, recovery technology development), political initiative, and (or) sustained market favorability could support new production of critical mineral commodities from subduction-related magmatic-hydrothermal deposits in Western States. In addition, insufficient domestic refining capacity could relegate the large inventories of critical minerals in porphyry Cu-Mo reserves and resources (for example, Pebble, Alaska; Resolution and Copper World [Rosemont], Arizona) to exportation in concentrates and importation insecurity, fortifying their present status.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235082","usgsCitation":"Vikre, P., John, D., Wintzer, N.E., Koutz, F., Graybeal, F., Dail, C., and Annis, D.C., 2023, Critical minerals in subduction-related magmatic-hydrothermal systems of the United States: U.S. Geological Survey Scientific Investigations Report 2023–5082, 110 p., https://doi.org/10.3133/sir20235082.","productDescription":"x, 110 p.","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-137402","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":501045,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115449.htm","linkFileType":{"id":5,"text":"html"}},{"id":421606,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5082/images"},{"id":421605,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235082/full"},{"id":421604,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5082/sir20235082.xml"},{"id":421603,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5082/sir20235082.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":421602,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5082/covrthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -126.97828338393356,\n 50.4388592678921\n ],\n [\n -126.97828338393356,\n 27.657631239110117\n ],\n [\n -95.77838522885939,\n 27.657631239110117\n ],\n [\n -95.77838522885939,\n 50.4388592678921\n ],\n [\n -126.97828338393356,\n 50.4388592678921\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
The central Idaho metallogenic province hosts numerous mineral deposit types. These include Late Cretaceous precious-polymetallic vein deposits, amagmatic Paleocene–Eocene breccia-hosted gold-tungsten-antimony deposits, and Eocene mercury deposits in metasedimentary roof pendants and in Late Cretaceous granitoids. Hot-springs gold deposits in Eocene volcanic rocks are also included in the central Idaho province. New sensitive high mass-resolution ion microprobe (SHRIMP) uranium-lead (U-Pb) ages for igneous rocks and for detrital zircon analyses of metasedimentary rocks along with geologic mapping clarify the geologic framework of the mineral deposits. This framework includes (1) structural controls for regional distribution of mining districts, (2) progressive structural development of individual districts, (3) regional sedimentary facies and their control of metals associations resulting in regional belts, and (4) influences of the several regional magmatic events.
In central Idaho, 15 mining districts form two clusters that are grouped about a 200-kilometer (km) long system of normal faults. The northwestern cluster is in the regional hanging wall west of large, west-side-down faults, and the mineral deposits are located along smaller faults and fractures that cut the regional hanging wall. The southeastern cluster is in the regional hanging wall east of a linked large east-side-down fault and along and controlled by related hanging wall faults. At the southern extent of the regional fault system, the Yellow Pine-Thunder Mountain districts span a nearly 24-km-wide, east-tilted crustal block of normal-fault dominoes, exposing original crustal depths from 5 to 10 km deep on the west in the Late Cretaceous to shallow-surface depths on the east in the Eocene.
Ore deposition in the northwestern district cluster was primarily Late Cretaceous and related to Idaho batholith plutons with only a single deposit related to a small Eocene intrusion; in the southeastern cluster, most deposits were initiated in the Late Cretaceous but with varying manifestations of overprinted Eocene mineralization activity. In the Yellow Pine-Thunder Mountain districts at the southern extent of the southern cluster, several mineralizing pulses occurred during hanging-wall collapse, such that (1) early deposits were multiply overprinted and (2) deposit depths, ages, and structural characteristics change progressively eastward. Originally deep-seated western Yellow Pine district deposits are Late Cretaceous viscoplastic mesothermal veins overprinted by Paleocene and Eocene breccia-hosted epithermal deposits. Central Yellow Pine district deposits contain early deeper vein systems but are primarily Paleocene and Eocene breccia-hosted epithermal deposits in Late Cretaceous plutonic rocks and Proterozoic–Paleozoic roof pendant rocks. Eastern district deposits are Eocene hot-springs-related deposits in the roof pendant. Thunder Mountain deposits farthest east are near-surface hot-springs deposits in Eocene volcanic and volcaniclastic rocks that overlie buried Cretaceous igneous and older roof pendant rocks.
The mining district clusters are sited across several northwest-striking paleostratigraphic belts that are exposed in roof pendants and are offset by the regional normal fault system. A northeastern belt is Mesoproterozoic strata associated with gold-silver-copper±cobalt deposits. A central belt of Neoproterozoic rocks is not associated with mineral deposits in the central Idaho mineral province. A southwestern belt composed of probable Paleozoic deep-water miogeoclinal slope rocks and late Paleozoic epicratonic basinal rocks is thin and narrowly exposed but associated with gold-silver-antimony-tungsten±mercury deposits. These metasedimentary rocks (and their metal associations) are parts of regional mineral belts in which metal endowments are related to particular sedimentary facies belts and their Cretaceous thrust-fault juxtaposition and where these features have proximity to Late Cretaceous or Eocene igneous rocks. Offset and preservation or erosional stripping of these facies belts, thrust plates, igneous settings, and the associated regional mineral belts were controlled by the sense and magnitude of displacements across the regional normal-fault system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1884","programNote":"Mineral Resources Program","usgsCitation":"Lund, K., Aleinikoff, J.N., and Holm-Denoma, C., 2023, Roles of regional structures and country-rock facies in defining mineral belts in central Idaho mineral province with detail for Yellow Pine and Thunder Mountain mining districts (ver. 1.1, September 2023): U.S. Geological Survey Professional Paper 1884, 53 p., https://doi.org/10.3133/pp1884.","productDescription":"Report: vii, 53 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-108495","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":422432,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/pp/1884/pp1884.xml"},{"id":422431,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/pp/1884/images"},{"id":420574,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/pp/1884/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":500195,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115237.htm","linkFileType":{"id":5,"text":"html"}},{"id":420149,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P931I3A3","text":"USGS data release","linkHelpText":"SHRIMP U-Pb and LA-ICPMS U-Pb geochronologic data for igneous and metasedimentary rocks in central Idaho mineral province, U.S.A., 2023"},{"id":420146,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1884/pp1884.pdf","text":"Report","size":"19.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1884"},{"id":420145,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1884/coverthb2.jpg"},{"id":422433,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/pp1884/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"PP 1884"}],"country":"United States","state":"Idaho","otherGeospatial":"Yellow Pine and Thunder Mountain Mining Districts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.00,\n 47.00\n ],\n [\n -117.00,\n 43.00\n ],\n [\n -112.00,\n 43.00\n ],\n [\n -112.00,\n 47.00\n ],\n [\n -117.00,\n 47.00\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: August 29, 2023; Version 1.1: September 6, 2023","contact":"Center Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
The U.S. Geological Survey (USGS) provides a wide range of streamflow, groundwater, and water-quality data to Government, commercial, academic, and public users. The USGS has a record of success with using optical turbidity sensors to predict suspended-sediment concentrations in rivers and streams. Turbidity sensors collect backscatter signals from suspended particles in water, which can be accurately measured and linked closely to hazardous contaminants that travel on the surfaces of suspended particles. Contaminant concentrations derived from the statistical relations between turbidity and contaminants like copper and lead can then be measured in real-time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233032","usgsCitation":"Ellison, C.A., 2023, Predicting water quality in the Clark Fork near Grant-Kohrs Ranch National Historic Site, southwestern Montana: U.S. Geological Survey Fact Sheet 2023–3032, 4 p., https://doi.org/10.3133/fs20233032.","productDescription":"Report: 4 p.; Data Release","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-149634","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":499691,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115178.htm","linkFileType":{"id":5,"text":"html"}},{"id":419659,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233032/full"},{"id":419605,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3032/fs20233032.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023–3032"},{"id":419604,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3032/coverthb.jpg"},{"id":419606,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3032/fs20233032.XML"},{"id":419607,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3032/images"},{"id":419608,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9330BXM","text":"USGS data release","linkHelpText":"Water quality and streamflow data for the Clark Fork near Grant-Kohrs Ranch National Historic Site in southwestern Montana, water years 2019–2020"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork, Grant-Kohrs Ranch National Historic Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.8301717989599,\n 46.5276604287545\n ],\n [\n -112.8301717989599,\n 46.38873569479347\n ],\n [\n -112.66374787281434,\n 46.38873569479347\n ],\n [\n -112.66374787281434,\n 46.5276604287545\n ],\n [\n -112.8301717989599,\n 46.5276604287545\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Over the past decade, an abundance of 16S rRNA gene surveys have provided microbiologists with data regarding the prokaryotes present in a coral-associated microbial community. Functional gene studies that provide information regarding what those microbes might do are fewer, particularly for non-tropical corals. Using the GeoChip 5.0S microarray, we present a functional gene study of microbiomes from five species of cold-water corals collected from depths of 296–1567 m. These species included two octocorals, Acanthogorgia aspera and Acanthogorgia spissa, and three stony corals: Desmophyllum dianthus, Desmophyllum pertusum (formerly Lophelia pertusa), and Enallopsammia profunda. A total of 24,281 gene sequences (representing different microbial taxa) encoding for 383 functional gene families and representing 9 metabolic gene categories were identified. Gene categories included metabolism of carbon, nitrogen, phosphorus, and sulfur, as well as virulence, organic remediation, metal homeostasis, secondary metabolism and phylogeny. We found that microbiomes from Acanthogorgia spp. were the most functionally distinct but also least diverse compared against those from stony corals. Desmophyllum spp. microbiomes were more similar to each other than to E. profunda. Of 383 total gene families detected in this study, less than 20% were significantly different among these deep-water coral species. Similarly, out of 59 metabolic sub-categories for which we were able to make a direct comparison to microbiomes of tropical corals, only 7 were notably different: anaerobic ammonium oxidation (anammox), chitin degradation, and dimethylsulfoniopropionate (DMSP) degradation, all of which had higher representations in deep-water corals; and chromium homeostasis/resistance, copper homeostasis/resistance, antibiotic resistance, and methanogenesis, all of which had higher representation in tropical corals. This implies a broad-scale convergence of the microbial functional genes present within the coral holobiont, independent of coral species, depth, symbiont status, and morphology.
Breccia pipe deposits of the Grand Canyon region contain ore grade copper and uranium. Horn Creek is located near the Orphan Mine mineralized breccia pipe deposit and groundwater emerging from the bedrock in the headwaters of Horn Creek has the highest uranium concentrations in the region. Uranium decreases an order of magnitude between the groundwater at the top of the watershed and the groundwater emerging from the alluvial material lower in the watershed. Horn Creek water has low sulfur and uranium isotopic ratios which may suggest interaction with sulfide and uranium minerals found in mineralized breccia pipe deposits. Per- and polyfluoroalkyl substances (PFBA and PFBS) were found in low concentrations in groundwater from the bedrock and may be related to mining process materials or other anthropogenic activities. PHREEQC modeling suggests that water that is elevated in uranium emerging from the bedrock in the upper watershed may mix with other groundwater and atmospheric precipitation infiltrated into the alluvial material in the lower watershed. Tritium is elevated in Horn Creek groundwaters suggesting a component of modern water, some of which may have interacted with Orphan Mine workings. Additional studies could build on this understanding of chemistry changes in waters of Horn Creek to provide more direct evidence of contribution of water moving through the Orphan Mine.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/geochem2023-007","usgsCitation":"Beisner, K.R., Davidson, C., and Tillman, F.D., 2023, Anthropogenic influence on groundwater geochemistry in Horn Creek Watershed near the Orphan Mine in Grand Canyon National Park, Arizona, USA: Geochemistry: Exploration, Environment, Analysis, v. 23, no. 3, geochem2023-007, 14 p., https://doi.org/10.1144/geochem2023-007.","productDescription":"geochem2023-007, 14 p.","ipdsId":"IP-148025","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":442670,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/geochem2023-007","text":"Publisher Index Page"},{"id":435245,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X17FKG","text":"USGS data release","linkHelpText":"PHREEQC files for geochemical simulations in Horn Creek, Grand Canyon, AZ"},{"id":419348,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park, Horn Creek Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.20894969063656,\n 36.094735674145454\n ],\n [\n -112.21000073958996,\n 36.06653388307063\n ],\n [\n -112.13348437577403,\n 36.06653388307063\n ],\n [\n -112.13768857158801,\n 36.110530696949866\n ],\n [\n -112.20894969063656,\n 36.094735674145454\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Beisner, Kimberly R. 0000-0002-2077-6899 kbeisner@usgs.gov","orcid":"https://orcid.org/0000-0002-2077-6899","contributorId":2733,"corporation":false,"usgs":true,"family":"Beisner","given":"Kimberly","email":"kbeisner@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davidson, Collin","contributorId":317722,"corporation":false,"usgs":false,"family":"Davidson","given":"Collin","email":"","affiliations":[{"id":40182,"text":"University of Nevada Las Vegas","active":true,"usgs":false}],"preferred":false,"id":879134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879135,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70246656,"text":"sir20235070 - 2023 - Spatiotemporal variations in copper, arsenic, cadmium, and zinc concentrations in surface water, fine-grained bed sediment, and aquatic macroinvertebrates in the upper Clark Fork Basin, western Montana—A 20-year synthesis, 1996–2016","interactions":[],"lastModifiedDate":"2026-03-09T17:10:18.876972","indexId":"sir20235070","displayToPublicDate":"2023-07-12T15:04:42","publicationYear":"2023","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":"2023-5070","displayTitle":"Spatiotemporal Variations in Copper, Arsenic, Cadmium, and Zinc Concentrations in Surface Water, Fine-Grained Bed Sediment, and Aquatic Macroinvertebrates in the Upper Clark Fork Basin, Western Montana—A 20-Year Synthesis, 1996–2016","title":"Spatiotemporal variations in copper, arsenic, cadmium, and zinc concentrations in surface water, fine-grained bed sediment, and aquatic macroinvertebrates in the upper Clark Fork Basin, western Montana—A 20-year synthesis, 1996–2016","docAbstract":"The legacy of mining-related contamination in the upper Clark Fork Basin created an extensive longitudinal gradient in metal concentrations, extending from Silver Bow Creek to Lake Pend Oreille, Idaho. Downstream metal concentrations continue to decline, but, despite such improvements, the ecological health of much of the river remains uncertain. Understanding the long-term consequences of the Clark Fork River mining legacy may be supported by environmental monitoring techniques that include a holistic assessment of biological health or response to define organism exposure to complex contaminant mixtures and the consequences of such exposures. This report presents the spatiotemporal patterns of mining-related contaminants, copper, arsenic, cadmium, and zinc, in surface water, fine-grained bed sediment, and macroinvertebrate (aquatic insect) tissue in the upper Clark Fork from near Butte to Missoula, Montana. Overall, the patterns in water column sample concentrations observed in this study were consistent with previously observed trends, but bed sediment concentrations and concentrations of copper and arsenic varied more in tissue samples among sites. Trace element concentrations, especially copper, often exceeded the chronic aquatic life criteria and consistently exceeded the sediment probable effects level PEL for copper, particularly in the upper and middle river segments. The 20 years considered here were the wettest period since remediation started, and this increase in precipitation may have affected patterns in contaminant concentrations.
Results of this study demonstrated the utility of a continued, comprehensive biomonitoring program to help guide and evaluate future environmental cleanup activities in the Clark Fork. Despite variation in defining complete restoration in these watersheds, using multiple lines of evidence in this study provided quantifiable measures of the timing and completeness of recovery relative to reference conditions. Successful recovery in the Clark Fork may benefit from an adaptive management strategy to continue collecting a comprehensive, multivariate dataset to evaluate whether established goals are being met and for subsequent adjustments and management, as needed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235070","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Caldwell Eldridge, S.L., and Hornberger, M.I., 2023, Spatiotemporal variations in copper, arsenic, cadmium, and zinc concentrations in surface water, fine-grained bed sediment, and aquatic macroinvertebrates in the upper Clark Fork Basin, western Montana—A 20-year synthesis, 1996–2016: U.S. Geological Survey Scientific Investigations Report 2023–5070, 55 p., https://doi.org/10.3133/sir20235070.","productDescription":"Report: viii, 55 p.; Dataset","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-124462","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":500950,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114966.htm","linkFileType":{"id":5,"text":"html"}},{"id":418908,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235070/full"},{"id":418905,"rank":5,"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":418904,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5070/images/"},{"id":418903,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5070/sir20235070.XML"},{"id":418902,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5070/sir20235070.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5070"},{"id":418901,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5070/coverthb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Upper Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.19960466889883,\n 47.19600162794333\n ],\n [\n -114.19960466889883,\n 45.651910037647326\n ],\n [\n -110.76235872576048,\n 45.651910037647326\n ],\n [\n -110.76235872576048,\n 47.19600162794333\n ],\n [\n -114.19960466889883,\n 47.19600162794333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
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Macrophage aggregate (MA) abundance in fish is a useful general biomarker of contaminant exposures and environmental stress. Hepatic and splenic MAs were evaluated in semi-anadromous white perch Morone americana (Gmelin, 1789) from the urbanized Severn River (S) and the more rural Choptank River (C), Chesapeake Bay. Fish were collected from different sites in the annual migratory circuit in each river that corresponded to active spawning in late winter-early spring, summer regenerating, autumn developing, and winter spawning-capable phases. An age-associated progressive increase in the total volume of MAs (MAV) was evident in the liver and spleen. Mean hepatic MAV (range in seasonal means, C: 6.4-23.1 mm3; S: 15.7-48.7 mm3) and mean splenic MAV (C: 7.3-12.6 mm3; S: 16.0-33.0 mm3) differed significantly among seasons and were significantly greater in females and in Severn River fish. Age and river were the most influential factors, suggesting that increased MAV in Severn River fish resulted from chronic exposures to higher concentrations of environmental contaminants. Hepatic MAV was directly related to the relative volume of copper granules in the liver. Less influential factors on splenic MAV included fish condition, trematode infections, and granulomas, indicating possible functional differences in MAs by organ. While organ volumes were strongly linked to gonadosomatic index (GSI) and reproductive phase, the reason for seasonal differences in MAV was less clear. Water temperature, salinity, and dissolved oxygen were not significantly related to MAV, and indicators of reproductive phase (hepatosomatic index and GSI) were significant but less important in explaining variation in MAV.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/dao03734","usgsCitation":"Blazer, V., Matsche, M.A., and Pulster, E.L., 2023, White perch health relative to urbanization and habitat degradation in Chesapeake Bay tributaries. II. 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I. Biliary neoplasms and hepatic lesions","interactions":[],"lastModifiedDate":"2023-07-19T11:43:15.216964","indexId":"70246797","displayToPublicDate":"2023-07-06T06:38:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"title":"White perch health relative to urbanization and habitat degradation in Chesapeake Bay tributaries. I. Biliary neoplasms and hepatic lesions","docAbstract":"White perch Morone americana (Gmelin, 1789) from the Chesapeake Bay (USA) watershed have a high incidence of liver disease, including neoplasms of bile duct origin. Fish collected seasonally from spring 2019 to winter 2020 from the urban Severn River and the more rural Choptank River were evaluated for hepatic lesions. Biliary hyperplasia (64.1%), neoplasms (cholangioma and cholangiocarcinoma, 27%), and dysplasia (24.9%) were significantly higher in Severn River fish compared to Choptank River fish (52.9, 16.2, and 15.8%, respectively). Hepatocellular lesions were less common, including foci of hepatocellular alteration (FHA, 13.3%) and hepatocellular neoplasms (1%). There was also a progressive age-related increase in copper-laden granules in hepatocytes, which was a significant risk factor for FHA and could be a source of oxidative stress in the liver. Significant risk factors for biliary neoplasms included age, bile duct fibrosis, and infections by the myxozoan parasite Myxidium murchelanoi, but the prevalence and relative intensity of M. murchelanoi infections did not differ significantly between fish populations. Hepatic disease in this species appears to be chronic and may stem from an age-related accumulation of damage, possibly from parasitic infections and contaminants such as polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), and copper. Watershed development and exposures to PCBs and PAHs were generally higher for white perch in the Severn River, but similar suites of chemical contaminants were detected in the Choptank River. A broader survey of white perch within and outside Chesapeake Bay may allow determination of the extent of biliary neoplasia in this species.
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