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Ti oxides ± orthopyroxene, as well as olivine in lavas with >6 wt% MgO.Kīlauea is a frequently active, open-system volcano on the Island of Hawaiʻi known for erupting olivine-dominated tholeiitic basalt compositions. On rare occasions it erupts more differentiated magmas (<1% of erupted volume), such as basaltic andesites and andesites, from its rift zones. These differentiated magmas offer an opportunity to understand better the petrology, magma storage, magma mixing, and eruptive triggers that occur in Kīlauea's rift zone reservoirs. This study focuses on an eruption from the Southwest Rift Zone of Kīlauea, which is dominantly basaltic andesite with subordinate basalt. This eruption originated at the Kamakaiʻa Hills during the early 19th century and has two eruptive phases: 1) an early ‘a‘ā phase that is primarily exposed in the eastern part of the flow field, with minor western lobes, and 2) a late pāhoehoe phase that makes up most of the western part of the flow field. The early ‘a‘ā phase covers at least 5.8 km2 with an erupted volume of ∼150 × 106 m3 and consists of uniform composition basaltic andesites with 3.72–4.15 wt% MgO over its ∼7 km flow length. The late pāhoehoe phase reached >10 km from its vent, covers an area of ∼7.1 km2, has a volume of ∼100 × 106 m3, and initially erupted basaltic andesite near its vent (4.50–5.64 wt% MgO extending to 3.8 km from vent) with channel and tube-fed basalt (6.21–12.38 wt% MgO sampled at >3.8 km from vent) emplaced during its waning stages. Most Kamakaiʻa Hills lavas are crystal-poor, containing ≤1.5% glomerocrysts and individual phenocrysts of plagioclase + clinopyroxene + FeTi oxides ± orthopyroxene, as well as olivine in lavas with >6 wt% MgO.
Major-oxide and trace-element concentrations throughout the Kamakaiʻa Hills lavas demonstrate the involvement of three distinct magmatic processes. First, the basaltic andesites of the early ‘a‘ā phase are the products of fractionation of plagioclase + clinopyroxene + FeTi oxides ± orthopyroxene, indicative of magmas that have been stored in rift zone reservoirs for decades or longer. Second, the near-vent (within ∼400 m of vent) basaltic andesites of the late pāhoehoe phase yield chemical concentrations that indicate magma mixing with a more differentiated magma (of a similar evolved composition to basaltic andesites at ∼55–56 wt% SiO2 and ∼3.4–4.1 wt% MgO that erupted in the lower East Rift Zone in 2018). Third, the progressively more mafic magma (containing olivine + plagioclase + clinopyroxene) that continued to erupt throughout the waning stages of activity suggests an eruptive triggering process whereby an intruding summit or uprift reservoir basalt overpressurized and forced out the stored, differentiated magma of the Kamakaiʻa Hills rift zone reservoir.
A 21-layer three-dimensional transient groundwater-flow model of the New Jersey Coastal Plain was developed and calibrated by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection to simulate groundwater-flow conditions during 1980–2013, incorporating average annual groundwater withdrawals and average annual groundwater recharge. This model is the third version of the New Jersey Coastal Plain regional groundwater-flow model that was initially developed as part of the USGS Regional Aquifer System Analysis (RASA) program. The model simulates groundwater flow in 11 aquifers and 10 intervening confining units of the New Jersey Coastal Plain to provide a regional overview of groundwater conditions. Averaged groundwater withdrawal data for 1980 to 2013 were used in the model. The 11 aquifers in New Jersey are, from shallowest to deepest, the Holly Beach water-bearing zone and the confined Cohansey aquifer in Cape May County; the Rio Grande water-bearing zone; the Atlantic City 800-foot sand; the Piney Point, Vincentown, and Wenonah-Mount Laurel aquifers; the Englishtown aquifer system; and the upper, middle, and lower aquifers of the Potomac-Raritan-Magothy (PRM) aquifer system.
The model was developed with the MODFLOW–2005 numerical code and the UCODE parameter estimation technique and calibrated using water-level and base-flow observations. A total of 3,453 water-level observations from 392 wells in New Jersey and 48 wells in Delaware from 1983 to 2013 were used in model calibration, which includes historical water-level trends for 29 wells in New Jersey during 1980–2013 presented in time-series hydrographs. In addition, derived observations also were included by calculating the vertical gradient at 33 pairs of nested observation wells in New Jersey, for a total of 210 observations. Changes in water levels over time were calculated for 134 wells in New Jersey and four wells in Delaware where water levels had varied substantially (approximately 10 ft) over the 30-year span of synoptic water-level measurements, for a total of 767 observations. A total of 1,485 base-flow observations in 47 surface-water basins in New Jersey from 1980 to 2013 were used in model calibration.
Updates to the groundwater-flow model include the conversion to a fully three-dimensional model from the previous quasi-three-dimensional model. The new model will allow for potential future uses such as particle tracking or simulation of variable-density groundwater flow that could not be accomplished with earlier versions of the model. Spatially and temporally variable recharge estimated by using a soil-water balance model resulted in a spatially and temporally finer discretization. The Rio Grande water-bearing zone was added to the model as an aquifer layer to refine estimates of simulated flow in Atlantic and Cape May Counties, New Jersey. Hydrogeologic parameters were updated to include the confining units in New Jersey and corresponding hydrogeologic units in Delaware and eastern Maryland.
The simulated water levels for the New Jersey Coastal Plain aquifers were compared to water-level measurements made during 1980–2013. The average residual for 4,243 water-level observations for New Jersey (simulated water levels minus measured water levels) is 1.5 feet. The simulated water-level contours for the confined aquifers for 2013 were compared to potentiometric surfaces produced from water levels measured during 2013. Simulated water levels generally matched the 2013 potentiometric surfaces of the confined aquifers in the areas of large withdrawals. Hydrographs of wells in the confined Coastal Plain aquifers of New Jersey show that simulated water levels generally match the magnitude and seasonal variation of the observed water levels. Hydrographs of base flow for the 47 streamgaging stations in New Jersey indicate that most of the simulated and estimated data match reasonably well.
Groundwater withdrawals are an important resource for water supply, agricultural, industrial, and commercial needs in the New Jersey Coastal Plain. Groundwater withdrawals from the New Jersey Coastal Plain aquifers have resulted in persistent, regionally extensive cones of depression in the Englishtown aquifer system and Wenonah-Mount Laurel aquifer in Ocean and Monmouth Counties; Wenonah-Mount Laurel and upper, middle, and lower PRM aquifers in Camden County; and Atlantic City 800-foot sand in Atlantic County. Because hydrologic stresses and water-management needs change with time, periodic updates to the groundwater-flow model are required to provide current information about hydrologic conditions in the New Jersey Coastal Plain and to maintain its usefulness as a tool to manage water resources and develop water-resource strategies. The current updates will support the continued application of this model as a tool for evaluating the regional effects of changes in groundwater withdrawals and of current and potential future water-management strategies on groundwater levels in the New Jersey Coastal Plain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235066","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Gordon, A.D., and Carleton, G.B., 2023, Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013: U.S. Geological Survey Scientific Investigations Report 2023–5066, 116 p., https://doi.org/10.3133/sir20235066","productDescription":"Report: xii, 116 p.; Data Release","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127396","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":500947,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115639.htm","linkFileType":{"id":5,"text":"html"}},{"id":422695,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5066/images/"},{"id":422693,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235066/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5066"},{"id":422696,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W6RXFC","text":"USGS data release","linkHelpText":"MODFLOW-2005 model used to simulate the regional groundwater flow system in the updated New Jersey Coastal Plain model, 1980-2013"},{"id":422694,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5066/sir20235066.XML"},{"id":422692,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5066/sir20235066.pdf","text":"Report","size":"25.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5066"},{"id":422691,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5066/coverthb.jpg"}],"country":"United States","otherGeospatial":"New Jersey Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.49018324613056,\n 41.03712838002892\n ],\n [\n -75.25922621488034,\n 41.417217443631785\n ],\n [\n -77.41254652738019,\n 39.17183412365296\n ],\n [\n -75.22626723050551,\n 37.8132834585617\n ],\n [\n -72.98505629300531,\n 40.4043207917766\n ],\n [\n -74.49018324613056,\n 41.03712838002892\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
3450 Princeton Pike, Suite 110
Lawrenceville, New Jersey 08648
Coral reefs are iconic ecosystems that support diverse, productive communities in both shallow and deep waters. However, our incomplete knowledge of cold-water coral (CWC) niche space limits our understanding of their distribution and precludes a complete accounting of the ecosystem services they provide. Here, we present the results of recent surveys of the CWC mound province on the Blake Plateau off the U.S. east coast, an area of intense human activity including fisheries and naval operations, and potentially energy and mineral extraction. At one site, CWC mounds are arranged in lines that total over 150 km in length, making this one of the largest reef complexes discovered in the deep ocean. This site experiences rapid and extreme shifts in temperature between 4.3 and 10.7 °C, and currents approaching 1 m s−1. Carbon is transported to depth by mesopelagic micronekton and nutrient cycling on the reef results in some of the highest nitrate concentrations recorded in the region. Predictive models reveal expanded areas of highly suitable habitat that currently remain unexplored. Multidisciplinary exploration of this new site has expanded understanding of the cold-water coral niche, improved our accounting of the ecosystem services of the reef habitat, and emphasizes the importance of properly managing these systems.
Migratory waterfowl are an important resource for consumptive and non-consumptive users alike and provide tremendous economic value in North America. These birds rely on a complex matrix of public and private land for forage and roosting during migration and wintering periods, and substantial conservation effort focuses on increasing the amount and quality of target habitat. Yet, the value of habitat is a function not only of a site's resources but also of its geographic position and weather. To quantify this value, we used a continental-scale energetics-based model of daily dabbling duck movement to assess the marginal value of lands across the contiguous United States during the non-breeding period (September to May). We examined effects of eliminating each habitat node (32 × 32 km) in both a particularly cold and a particularly warm winter, asking which nodes had the largest effect on survival. The marginal value of habitat nodes for migrating dabbling ducks was a function of forage and roosting habitat but, more importantly, of geography (especially latitude and region). Irrespective of weather, nodes in the Southeast, central East Coast, and California made the largest positive contributions to survival. Conversely, nodes in the Midwest, Northeast, Florida, and the Pacific Northwest had consistent negative effects. Effects (positive and negative) of more northerly nodes occurred in late fall or early spring when climate was often severe and was most variable. Importance and effects of many nodes varied considerably between a cold and a warm winter. Much of the Midwest and central Great Plains benefited duck survival in a warm winter, and projected future warming may improve the value of lands in these regions, including many National Wildlife Refuges, for migrating dabbling ducks. Our results highlight the geographic variability in habitat value, as well as shifts that may occur in these values due to climate change.
Three-dimensional inversion of regional long-period magnetotelluric (MT) data reveals the presence of two distinct sets of high-conductivity belts in the Precambrian basement of the eastern U.S. Midcontinent. One set, beneath Missouri, Illinois, Indiana, and western Ohio, is defined by northwest–southeast-oriented conductivity structures; the other set, beneath Kentucky, West Virginia, western Virginia, and eastern Ohio, includes structures that are generally oriented northeast–southwest. The northwest-trending belts occur mainly in Paleoproterozoic crust, and we suggest that their high conductivity values are due to graphite precipitated within trans-crustal shear zones from intrusion-related CO2-rich fluids. Our MT inversion results indicate that some of these structures dip steeply through the crust and intersect the Moho, which supports an interpretation that the shear zones originated as “leaky” transcurrent faults or transforms during the late Paleoproterozoic or the early Mesoproterozoic. The northeast-trending belts are associated with Grenvillian orogenesis and also potentially with Iapetan rifting, although further work is needed to verify the latter possibility. We interpret the different geographic positions of these two sets of conductivity belts as reflecting differences in origin and/or crustal rheology, with the northwest-trending belts largely confined to older, stable, pre-Grenville cratonic Laurentia, and the northeast-trending belts largely having formed in younger, weaker marginal crust. Notably, these high-conductivity zones spatially correlate with Midcontinent fault-and-fold zones that affect Phanerozoic strata. Stratigraphic evidence indicates that Midcontinent fault-and-fold zones were particularly active during Phanerozoic orogenic events, and some remain seismically active today, so the associated high-conductivity belts likely represent long-lived weaknesses that transect the crust.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B37099.1","usgsCitation":"Murphy, B.S., DeLucia, M.S., Marshak, S., Ravat, D., and Bedrosian, P.A., 2023, Magnetotelluric insights into the formation and reactivation of trans-crustal shear zones in Precambrian basement of the eastern U.S. Midcontinent: Geological Society of America Bulletin, v. 136, no. 7-8, p. 2661-2675, https://doi.org/10.1130/B37099.1.","productDescription":"15 p.","startPage":"2661","endPage":"2675","ipdsId":"IP-156454","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":501615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b37099.1","text":"Publisher Index Page"},{"id":501591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Kentucky, Michigan, Missouri, Ohio, Tennessee, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.56385155199473,\n 43.58838657273898\n ],\n [\n -94.89342352797115,\n 36.665741391167515\n ],\n [\n -90.1632867900763,\n 36.40918959165568\n ],\n [\n -90.1822818596265,\n 35.19325938384543\n ],\n [\n -82.50702489905923,\n 35.09029830465867\n ],\n [\n -81.72015275766472,\n 36.414903288152516\n ],\n [\n -75.94724335361846,\n 36.6343891406775\n ],\n [\n -78.22364477580007,\n 39.341914933866796\n ],\n [\n -83.87679948786644,\n 45.80918107937691\n ],\n [\n -86.49918682600257,\n 44.950592730464656\n ],\n [\n -87.74442475620134,\n 42.792743875212764\n ],\n [\n -90.2357236948469,\n 42.584968113049044\n ],\n [\n -91.44396187965609,\n 43.610837609280644\n ],\n [\n -96.56385155199473,\n 43.58838657273898\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"136","issue":"7-8","noUsgsAuthors":false,"publicationDate":"2023-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Benjamin Scott 0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":242928,"corporation":false,"usgs":true,"family":"Murphy","given":"Benjamin","email":"","middleInitial":"Scott","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":957907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeLucia, Michael S.","contributorId":367930,"corporation":false,"usgs":false,"family":"DeLucia","given":"Michael","middleInitial":"S.","affiliations":[{"id":87645,"text":"Department of Geology and Environmental Geoscience, College of Charleston","active":true,"usgs":false}],"preferred":false,"id":957908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marshak, Stephen","contributorId":367931,"corporation":false,"usgs":false,"family":"Marshak","given":"Stephen","affiliations":[{"id":40647,"text":"Department of Geology, University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":957909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ravat, Dhananjay","contributorId":367932,"corporation":false,"usgs":false,"family":"Ravat","given":"Dhananjay","affiliations":[{"id":87646,"text":"Department of Earth and Environmental Sciences, University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":957910,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":957911,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70249877,"text":"70249877 - 2023 - Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast","interactions":[],"lastModifiedDate":"2024-01-04T14:49:45.971708","indexId":"70249877","displayToPublicDate":"2023-11-03T06:35:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast","docAbstract":"Context Tidal saline wetlands (TSWs) are highly threatened from climate-change effects of sea-level rise. Studies of TSWs along the East Coast U.S. and elsewhere suggest significant likely losses over coming decades but needed are analytic tools gauged to Pacific Coast U.S. wetlands.
Objectives We predict the impacts of sea-level rise (SLR) on the elevation capital (vertical) and migration potential (lateral) resilience of TSWs along the Pacific Coast U.S. over the period 2020 to 2150 under a 1.5-m SLR scenario, and identified TSWs at risk of most rapid loss of resilience. Here, we define vertical resilience as the amount of elevation capital and lateral resilience as the amount of TSW displacement area relative to existing area.
Methods We used Bayesian network (BN) modeling to predict changes in resilience of TSWs as probabilities which can be useful in risk analysis and risk management. We developed the model using a database sample of 26 TSWs with 147 sediment core samples, among 16 estuary drainage areas along coastal California, Oregon, and Washington.
Results We found that all TSW sites would lose at least 50% of their elevation capital resilience by 2060 to just before 2100, and 100% by 2070 to 2130, depending on the site. Under a 1.5-m sea-level rise scenario, nearly all sites in California will lose most or all of their lateral migration resilience. Resilience losses generally accelerated over time. In the BN model, elevation capital resilience is most sensitive to elevation capital at time t, mean tide level at time t, and change in sea level from time 0 to time t.
Conclusions All TSW sites were projected with declines in resilience. Our model can further aid decision-making such as prioritizing sites for potential management adaptation strategies. We also identified variables most influencing resilience predictions and thus those potentially prioritized for monitoring or development of strategies to prevent loss regionally.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-023-01762-3","usgsCitation":"Marcot, B.G., Thorne, K., Carr, J., and Guntenspergen, G.R., 2023, Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast: Landscape Ecology, v. 38, p. 3061-3080, https://doi.org/10.1007/s10980-023-01762-3.","productDescription":"20 p.","startPage":"3061","endPage":"3080","ipdsId":"IP-148063","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441704,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-023-01762-3","text":"Publisher Index Page"},{"id":422365,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Pacific Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.79508376826595,\n 32.6394986015149\n ],\n [\n -117.38046175678818,\n 33.634263181198776\n ],\n [\n -119.04924372825178,\n 34.47903231583611\n ],\n [\n -120.38379894663998,\n 34.68829360587419\n ],\n [\n -120.39855065841579,\n 35.33926414301449\n ],\n [\n -121.79626050797515,\n 36.460712237169574\n ],\n [\n -121.69218260053856,\n 36.794964571410546\n ],\n [\n -121.93473143542474,\n 37.099336500561904\n ],\n [\n -121.67841132759617,\n 37.4046675213457\n ],\n [\n -122.29904672509281,\n 38.299945698864775\n ],\n [\n -122.73038676825749,\n 38.20384318696074\n ],\n [\n -123.43481358189254,\n 39.0731465550509\n ],\n [\n -124.04491152385293,\n 40.344784634590496\n ],\n [\n -123.71975903545354,\n 41.393830664494715\n ],\n [\n -124.30182241974398,\n 42.756208502734836\n ],\n [\n -123.72352270756943,\n 43.87384063633678\n ],\n [\n -123.69957609415667,\n 46.20564287869419\n ],\n [\n -123.73190708914615,\n 47.01614568390107\n ],\n [\n -124.52407464804097,\n 48.44687072153897\n ],\n [\n -125.07770960477518,\n 48.56365821581798\n ],\n [\n -124.81324633275776,\n 47.69849413178119\n ],\n [\n -124.24511492723724,\n 46.407052517711605\n ],\n [\n -124.64743081974362,\n 43.59326210341467\n ],\n [\n -124.85817977876286,\n 42.61603559520387\n ],\n [\n -124.46177432494142,\n 41.15906667493712\n ],\n [\n -124.73844702893035,\n 40.16919745978089\n ],\n [\n -124.14464449468676,\n 39.63763990789823\n ],\n [\n -124.08963171928053,\n 38.73318027566873\n ],\n [\n -123.05064665424416,\n 37.68717586937068\n ],\n [\n -121.75049102805497,\n 35.902294376643596\n ],\n [\n -120.98156553638233,\n 35.198466337951686\n ],\n [\n -120.87397110810903,\n 34.31747679968289\n ],\n [\n -119.36572913414489,\n 34.05126341484619\n ],\n [\n -117.64709261279006,\n 33.1121239333127\n ],\n [\n -117.2603048744129,\n 32.509262003906\n ],\n [\n -116.79508376826595,\n 32.6394986015149\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"38","noUsgsAuthors":false,"publicationDate":"2023-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Marcot, Bruce G.","contributorId":140456,"corporation":false,"usgs":false,"family":"Marcot","given":"Bruce","email":"","middleInitial":"G.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":887494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":887495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":887496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":887497,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250196,"text":"70250196 - 2023 - Geology of the Mount Rogers area, revisited: Evidence of Neoproterozoic continental rifting, glaciation, and the opening and closing of the Iapetus Ocean, Blue Ridge, VA–NC–TN","interactions":[],"lastModifiedDate":"2023-11-28T17:43:17.27309","indexId":"70250196","displayToPublicDate":"2023-11-01T11:42:39","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geology of the Mount Rogers area, revisited: Evidence of Neoproterozoic continental rifting, glaciation, and the opening and closing of the Iapetus Ocean, Blue Ridge, VA–NC–TN","docAbstract":"Recent field and geochronological studies in eight 7.5-minute quadrangles near Mount Rogers in Virginia, North Carolina and Tennessee recognize (1) important stratigraphic and structural relationships for the Neoproterozoic Mount Rogers and Konnarock Formations, and the northeast end of the Mountain City window; (2) the separation of Mesoproterozoic rocks of the Blue Ridge into three age groups; and (3) the timing and emplacement of the Blue Ridge thrust sheet. The study area includes folded and faulted Paleozoic strata of the Valley and Ridge in the northwest juxtaposed by metamorphic and igneous rocks of the Blue Ridge to the southeast. In the Valley and Ridge, Cambrian to Middle Ordovician carbonate and clastic rocks are exposed in a syncline in the Pulaski thrust sheet; these rocks are overridden by the Blue Ridge thrust sheet. The northeast end of the Mountain City window is interpreted as a simple window; the Stone Mountain fault is folded and continues as the Iron Mountain fault on the NW-side of the window. The Stone Mountain fault does not exist at the surface to the NE near the Razor Ridge volcanic center. Instead, a continuous section of Proterozoic gneisses, Mount Rogers Formation, Konnarock Formation and Chilhowee Group is now recognized.
Rhyolites of the Mount Rogers Formation range from 760–749Ma, with detrital zircon age populations from associated volcaniclastic rocks indicating magmatism and rifting began by ~780 Ma. Rhyolite outliers in the Konnarock Formation and a change from rift-related clastic rocks of the Mount Rogers Formation transitioning to maroon laminites, mudstones and laminites with dropstones, suggest that the Konnarock Formation may be as old as ~751 Ma.
Mesoproterozoic crystalline rocks of the Blue Ridge, previously referred to as the Cranberry Gneiss, are distinguished based on field relationships and SHRIMP U–Pb zircon geochronology: (1) ~1.33 Ga pre-Grenvillian crust; (2) 1190–1140 Ma granitoids (early magmatic suite); and (3) 1075–1030 Ma granitoids (late magmatic suite).
Multiple greenschist-facies high-strain zones, including the 2–11 km wide Fries high-strain zone, occur in the Blue Ridge thrust sheet. Fabrics across the Fries and Gossan Lead faults have similar orientations and NW–directed contractional deformation. 40Ar/39Ar hornblende, muscovite, and K-feldspar ages indicate the western and eastern Blue Ridge had different thermal histories. The eastern Blue Ridge (Gossan Lead thrust sheet) experienced a 360–340 Ma amphibolite facies event prior to juxtaposition with the western Blue Ridge. 40Ar/39Ar muscovite ages in western Blue Ridge rocks document greenschist facies metamorphism and deformation and emplacement of the Blue Ridge thrust sheet at ~340 Ma; the Catface and Fries faults are tentatively interpreted to be contemporaneous. After initial emplacement of the Blue Ridge thrust sheet at ~340 Ma, shortening was accommodated by westward translation along the basal decollement, which carried the Blue Ridge thrust sheet to its current position.
","conferenceTitle":"Geology of the Mount Rogers area, revisited, Blue Ridge, VA–NC–TN: Virginia Geological Field Conference","conferenceDate":"October 27-29, 2023","conferenceLocation":"Troutdale, VA","language":"English","publisher":"Virginia Geological Field Conference","usgsCitation":"Merschat, A.J., McAleer, R.J., Holm-Denoma, C., and Southworth, C.S., 2023, Geology of the Mount Rogers area, revisited: Evidence of Neoproterozoic continental rifting, glaciation, and the opening and closing of the Iapetus Ocean, Blue Ridge, VA–NC–TN, Geology of the Mount Rogers area, revisited, Blue Ridge, VA–NC–TN: Virginia Geological Field Conference, Troutdale, VA, October 27-29, 2023, p. 1-28.","productDescription":"28 p.","startPage":"1","endPage":"28","ipdsId":"IP-158912","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":423016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":422996,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://vgfc.blogs.wm.edu/past-conferences/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"North Carolina, Tennessee, Virginia","otherGeospatial":"Mount Rogers area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.37532149916849,\n 36.95542282359787\n ],\n [\n -82.37532149916849,\n 36.22133694740798\n ],\n [\n -80.84600971858332,\n 36.22133694740798\n ],\n [\n -80.84600971858332,\n 36.95542282359787\n ],\n [\n -82.37532149916849,\n 36.95542282359787\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Merschat, Arthur J. 0000-0002-9314-4067 amerschat@usgs.gov","orcid":"https://orcid.org/0000-0002-9314-4067","contributorId":4556,"corporation":false,"usgs":true,"family":"Merschat","given":"Arthur","email":"amerschat@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":888788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":888789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":219763,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher S.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":888790,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Southworth, C. Scott 0000-0002-7976-7807 ssouthwo@usgs.gov","orcid":"https://orcid.org/0000-0002-7976-7807","contributorId":1608,"corporation":false,"usgs":true,"family":"Southworth","given":"C.","email":"ssouthwo@usgs.gov","middleInitial":"Scott","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":888791,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70243910,"text":"70243910 - 2023 - Resistivity imaging over porphyry copper systems in the Red Mountain district, southwest Colorado, USA","interactions":[],"lastModifiedDate":"2024-01-26T17:34:45.358484","indexId":"70243910","displayToPublicDate":"2023-11-01T11:25:05","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Resistivity imaging over porphyry copper systems in the Red Mountain district, southwest Colorado, USA","docAbstract":"The Red Mountain district in southwestern Colorado produced base and precious metals hosted in breccia pipes and vein structures related to an extensive lithocap that overlies pervasive quartz-sericite-pyrite alteration. A helicopter-borne time-domain electromagnetic survey flown over the district yielded resistivity values that range from tens to thousand or more ohm-m, with lesser resistivity values in the lithocap and greater resistivity values in the rocks with propylitic alteration. A 60 m-thick, low resistivity zone subparallel to topography characterizes the magmatic-hydrothermal breccia pipes. A broad zone of low resistivity that may envelope epithermal deposits spans multiple flight lines and occurs beneath rocks with argillic alteration. A 50 m-thick low resistivity zone occurs beneath quartz-sericite-pyrite alteration and may indicate porphyry deposit at depth.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 17th SGA biennial meeting","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"17th Biennial SGA Meeting","conferenceDate":"August 28 - September 1, 2023","conferenceLocation":"Zurich, Switzerland","language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Anderson, E., Deszcz-Pan, M., Yager, D., Eastman, K., and Hoogenboom, B.E., 2023, Resistivity imaging over porphyry copper systems in the Red Mountain district, southwest Colorado, USA, in Proceedings of the 17th SGA biennial meeting, v. 3, Zurich, Switzerland, August 28 - September 1, 2023, p. 343-346.","productDescription":"4 p.","startPage":"343","endPage":"346","ipdsId":"IP-151353","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":425027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":425026,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://sga2023.ch/programme/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","otherGeospatial":"Red Mountain district, Silverton caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.7348537741502,\n 37.95951050781375\n ],\n [\n -107.7348537741502,\n 37.80819889981343\n ],\n [\n -107.54924524249871,\n 37.80819889981343\n ],\n [\n -107.54924524249871,\n 37.95951050781375\n ],\n [\n -107.7348537741502,\n 37.95951050781375\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Eric D. 0000-0002-0138-6166","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":202072,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":873711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deszcz-Pan, Maryla 0000-0002-6298-5314","orcid":"https://orcid.org/0000-0002-6298-5314","contributorId":305724,"corporation":false,"usgs":false,"family":"Deszcz-Pan","given":"Maryla","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":873712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yager, Douglas 0000-0001-5074-4022","orcid":"https://orcid.org/0000-0001-5074-4022","contributorId":305726,"corporation":false,"usgs":false,"family":"Yager","given":"Douglas","affiliations":[],"preferred":false,"id":873713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eastman, Kyle","contributorId":305728,"corporation":false,"usgs":false,"family":"Eastman","given":"Kyle","email":"","affiliations":[{"id":36941,"text":"Montana Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":873714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoogenboom, Bennett Eugene 0000-0001-8096-3533","orcid":"https://orcid.org/0000-0001-8096-3533","contributorId":239871,"corporation":false,"usgs":true,"family":"Hoogenboom","given":"Bennett","email":"","middleInitial":"Eugene","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":873715,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245198,"text":"70245198 - 2023 - Reconnaissance mineral and cathodoluminescence studies of gold occurrences in the Pogo-Black Mountain area, eastern interior Alaska, USA","interactions":[],"lastModifiedDate":"2024-01-26T17:23:09.372104","indexId":"70245198","displayToPublicDate":"2023-11-01T11:17:57","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Reconnaissance mineral and cathodoluminescence studies of gold occurrences in the Pogo-Black Mountain area, eastern interior Alaska, USA","docAbstract":"The Pogo Au deposit is the largest of a number of gold occurrences in eastern interior Alaska, that occur along a broad trend from west of Pogo to Black Mountain. Some of these occurrences are hosted in amphibolite facies gneisses and others in mid-Cretaceous igneous rocks that intruded the older metamorphic rocks. All occurrences contain arsenopyrite and pyrite. Whole rock geochemical trends distinguish most metamorphic rock-hosted vein prospects (strong Bi-Te-Au correlations) and intrusion-hosted occurrences (weak As-Au correlations). Brecciated quartz veins in metamorphic rocks have paragentically late Bi-Te (±S) + Au that post-dates Fe-As sulphide deposition. High grade vein samples from the Tibbs Creek intrusion-hosted deposits contain pyrite and arsenopyrite, generally lack Bi-Te minerals, but can contain paragentically younger euhedral quartz, stibnite and carbonate. Cathodoluminescence studies of gold-rich samples indicate that quartz dissolution occurred during the syn- to post-tectonic Bi-Te-Au deposition, and the later stibnite event. In the case of metamorphic rock-hosted deposits (e.g., Pogo, Gray Lead), Bi-Te and gold deposition commonly occurs in microfractures within quartz veins; the limited quartz in these fractures have distinctive CL response. We propose that gold deposition is related to changes in P-T conditions rather than fluid-rock chemical reactions. Similar quartz dissolution textures affect the void-filling euhedral quartz before or during stibnite and carbonate mineralization in the high-grade Au samples from Blue Lead.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 17th SGA biennial meeting","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"17th Biennial SGA Meeting","conferenceDate":"August 28 - September 1, 2023","conferenceLocation":"Zurich, Switzerland","language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Graham, G.E., Marsh, E.E., Lowers, H.A., and Taylor, R., 2023, Reconnaissance mineral and cathodoluminescence studies of gold occurrences in the Pogo-Black Mountain area, eastern interior Alaska, USA, in Proceedings of the 17th SGA biennial meeting, v. 2, Zurich, Switzerland, August 28 - September 1, 2023, p. 142-145.","productDescription":"4 p.","startPage":"142","endPage":"145","ipdsId":"IP-151250","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":425025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":425024,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://sga2023.ch/programme/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","otherGeospatial":"Pogo-Black Mountains area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -145,\n 64.5\n ],\n [\n -145,\n 64.33\n ],\n [\n -144.5,\n 64.33\n ],\n [\n -144.5,\n 64.5\n ],\n [\n -145,\n 64.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","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":875825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marsh, Erin E. 0000-0001-5245-9532 emarsh@usgs.gov","orcid":"https://orcid.org/0000-0001-5245-9532","contributorId":1250,"corporation":false,"usgs":true,"family":"Marsh","given":"Erin","email":"emarsh@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":875826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":875827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Ryan D. 0000-0002-8845-5290","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":201948,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":875828,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249788,"text":"sim3511 - 2023 - Stratigraphic cross sections of the Lewis Shale in the eastern part of the southwestern Wyoming Province, Wyoming and Colorado","interactions":[],"lastModifiedDate":"2026-02-23T18:14:31.201823","indexId":"sim3511","displayToPublicDate":"2023-10-30T16:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3511","title":"Stratigraphic cross sections of the Lewis Shale in the eastern part of the southwestern Wyoming Province, Wyoming and Colorado","docAbstract":"Three stratigraphic cross sections A–A', B–B', and C–C' were created for the Lewis Shale and associated strata in the eastern part of the Southwestern Wyoming Province of Wyoming and Colorado. The cross sections highlight 15 clinothems within the Lewis Shale, Fox Hills Sandstone, and Lance Formation progradational system (also referred to as the Lewis Shale system). Additionally, the cross sections indicate that multiple source areas were active at the same time during deposition of the Lewis Shale. Specifically, the north-to-southeast cross section A–A' demonstrates that the northern, sand-rich source was being deposited and onlapping onto an older, southern, mud-rich source.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3511","usgsCitation":"Hearon, J.S., 2023, Stratigraphic cross sections of the Lewis Shale in the eastern part of the Southwestern Wyoming Province, Wyoming and Colorado: U.S. Geological Survey Scientific Investigations Map 3511, 1 sheet, 5-p. pamphlet, https://doi.org/10.3133/sim3511.","productDescription":"Report: iv, 5 p.; 1 Sheet: 55.68 × 45.43 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-140606","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":422191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3511/coverthb.jpg"},{"id":422257,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3511/sim3511_pamphlet.pdf","text":"Report","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3511 Pamphlet"},{"id":422258,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3511/sim3511.pdf","text":"Sheet","size":"14.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3511 Sheet"},{"id":422288,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3511/images"},{"id":500440,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115585.htm","linkFileType":{"id":5,"text":"html"}},{"id":422289,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3511/sim3511_pamphlet.xml","linkFileType":{"id":8,"text":"xml"}},{"id":422290,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3511/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIM 3511 Pamphlet"},{"id":422306,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/P9NAFL9H","text":"USGS data release—","linkHelpText":"Digital Stratigraphic and Structural Grids of the Cretaceous Lewis Shale in the Eastern Part of the Southwestern Wyoming Province, Wyoming and Colorado"},{"id":435135,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NAFL9H","text":"USGS data release","linkHelpText":"Digital Stratigraphic and Structural Grids of the Cretaceous Lewis Shale in the Eastern Part of the Southwestern Wyoming Province, Wyoming and Colorado"},{"id":422196,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XRPCSC","text":"USGS data release","linkHelpText":"Formation tops data from the stratigraphic cross sections of the Lewis Shale in the eastern part of the Southwestern Wyoming Province, Wyoming and Colorado"}],"country":"United States","state":"Colorado, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.31087420580677,\n 40.14874874835829\n ],\n [\n -106.31087420580677,\n 42.49163925065031\n ],\n [\n -109.82649920580654,\n 42.49163925065031\n ],\n [\n -109.82649920580654,\n 40.14874874835829\n ],\n [\n -106.31087420580677,\n 40.14874874835829\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Mercury (Hg) is a toxic contaminant that has been mobilized and distributed worldwide and is a threat to many wildlife species. Amphibians are facing unprecedented global declines due to many threats including contaminants. While the biphasic life history of many amphibians creates a potential nexus for methylmercury (MeHg) exposure in aquatic habitats and subsequent health effects, the broad-scale distribution of MeHg exposure in amphibians remains unknown. We used nonlethal sampling to assess MeHg bioaccumulation in 3,241 juvenile and adult amphibians during 2017–2021. We sampled 26 populations (14 species) across 11 states in the United States, including several imperiled species that could not have been sampled by traditional lethal methods. We examined whether life history traits of species and whether the concentration of total mercury in sediment or dragonflies could be used as indicators of MeHg bioaccumulation in amphibians. Methylmercury contamination was widespread, with a 33-fold difference in concentrations across sites. Variation among years and clustered subsites was less than variation across sites. Life history characteristics such as size, sex, and whether the amphibian was a frog, toad, newt, or other salamander were the factors most strongly associated with bioaccumulation. Total Hg in dragonflies was a reliable indicator of bioaccumulation of MeHg in amphibians (R2 ≥ 0.67), whereas total Hg in sediment was not (R2 ≤ 0.04). Our study, the largest broad-scale assessment of MeHg bioaccumulation in amphibians, highlights methodological advances that allow for nonlethal sampling of rare species and reveals immense variation among species, life histories, and sites. Our findings can help identify sensitive populations and provide environmentally relevant concentrations for future studies to better quantify the potential threats of MeHg to amphibians.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.3c05549","usgsCitation":"Tornabene, B.J., Hossack, B., Halstead, B., Eagles-Smith, C., Adams, M.J., Backlin, A.R., Brand, A., Emery, C., Fisher, R., Fleming, J.E., Glorioso, B., Grear, D.A., Campbell Grant, E.H., Kleeman, P.M., Miller, D., Muths, E., Pearl, C., Rowe, J., Rumrill, C.T., Waddle, J.H., Winzeler, M., and Smalling, K., 2023, Broad-scale assessment of methylmercury in adult amphibians: Environmental Science and Technology, v. 57, no. 45, p. 17511-17521, https://doi.org/10.1021/acs.est.3c05549.","productDescription":"11 p.","startPage":"17511","endPage":"17521","ipdsId":"IP-151126","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science 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From 2018 - 2022, the U.S. Geological Survey acquired over 82,000 line-kilometres of airborne electromagnetic, radiometric, and magnetic data over this region to provide comprehensive and systematic information about subsurface geologic and hydrologic properties that support multiple scientific and societal interests. Most of the data were acquired on a regional grid of west-east flight lines separated by 3 - 6 kilometres; however, several high-resolution inset grids with line spacing as close as 200 m were acquired in targeted areas of interest. Approximately 8,000 line-kilometres were acquired along streams and rivers to characterise the potential for surface water-groundwater connection, and another 6,000 line-kilometres were acquired along the Mississippi and Arkansas River levees to characterise this critical infrastructure. Here, we present a summary of the data along with several examples of how they are being used to inform regional groundwater model development, inferences of groundwater salinity, identification of faults in the New Madrid seismic zone, and levee infrastructure.
","conferenceTitle":"AEM2023 8th International Airborne Electromagnetics Workshop","conferenceDate":"September 3-7, 2023","conferenceLocation":"Fitzroy Island, Queensland, Australia","language":"English","publisher":"Australian Society of Exploration Geophysicists","doi":"10.5281/zenodo.10052667","usgsCitation":"Minsley, B.J., Adams, R.F., Asquith, W.H., Burton, B.L., Hoogenboom, B.E., James, S.R., Killian, C.D., Knierim, K.J., Kress, W.H., Lindaman, M., Leaf, A.T., Rigby, J.R., and Traylor, J.P., 2023, System-scale airborne electromagnetic surveys in the lower Mississippi River Valley support multidisciplinary applications, AEM2023 8th International Airborne Electromagnetics Workshop, Fitzroy Island, Queensland, Australia, September 3-7, 2023, 5 p., https://doi.org/10.5281/zenodo.10052667.","productDescription":"5 p.","ipdsId":"IP-150848","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science 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wkress@usgs.gov","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":1576,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","email":"wkress@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886135,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lindaman, Maxwell A. 0000-0003-1786-1272","orcid":"https://orcid.org/0000-0003-1786-1272","contributorId":219064,"corporation":false,"usgs":true,"family":"Lindaman","given":"Maxwell A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886136,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886137,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rigby, James R. 0000-0002-5611-6307","orcid":"https://orcid.org/0000-0002-5611-6307","contributorId":260894,"corporation":false,"usgs":true,"family":"Rigby","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886138,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Traylor, Jonathan P. 0000-0002-2008-1923 jtraylor@usgs.gov","orcid":"https://orcid.org/0000-0002-2008-1923","contributorId":5322,"corporation":false,"usgs":true,"family":"Traylor","given":"Jonathan","email":"jtraylor@usgs.gov","middleInitial":"P.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886139,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70273450,"text":"70273450 - 2023 - Dating the penultimate great earthquake in south-central Alaska using tree-ring crossdating and radiocarbon wiggle-matching","interactions":[],"lastModifiedDate":"2026-01-14T15:59:24.616609","indexId":"70273450","displayToPublicDate":"2023-10-30T08:53:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7169,"text":"Quaternary Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Dating the penultimate great earthquake in south-central Alaska using tree-ring crossdating and radiocarbon wiggle-matching","docAbstract":"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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","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":70249899,"text":"70249899 - 2023 - Monitoring population-level foraging distribution of a marine migratory species from land: Strengths and weaknesses of the isotopic approach on the Northwest Atlantic loggerhead turtle aggregation","interactions":[],"lastModifiedDate":"2023-11-04T13:36:45.459948","indexId":"70249899","displayToPublicDate":"2023-10-27T08:35:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring population-level foraging distribution of a marine migratory species from land: Strengths and weaknesses of the isotopic approach on the Northwest Atlantic loggerhead turtle aggregation","docAbstract":"Assessing the linkage between breeding and non-breeding areas has important implications for understanding the fundamental biology of and conserving animal species. This is a challenging task for marine species, and in sea turtles a combination of stable isotope analysis (SIA) and satellite telemetry has been increasingly used. The Northwest Atlantic (NWA) loggerhead (Caretta caretta) Regional Management Unit, one of the largest sea turtle populations in the world, provides an excellent opportunity to investigate key biological patterns as well as methodological aspects related to the use of stable isotopes to infer spatial distribution of turtles in foraging areas. We provide the first comprehensive assessment of the annual distribution of NWA adult female loggerheads among foraging areas and investigate the efficacy of various analytical approaches as well as the effect of sample size in these types of studies. A total of 5168 individual females were sampled from seven Management Units (MUs) between 2013-2018. We provide the first estimate of the proportion of females originating from each MU that uses each foraging area and show how this proportion varies over time. We also estimate the relative importance (in terms of number of turtles) of each foraging area to the overall loggerhead breeding aggregation nesting in Florida and in the NWA for each year of the study. The foraging area used by reproductively active females differs considerably across MUs. One of these, the Subtropical NWA, is by far the most important foraging area in terms of both number of individuals and genetic diversity, and therefore this region may be considered as a conservation priority. Through simulations, we show that limited sizes of sample groups (unknowns; training; priors) may result in false geographic differentiation and consequently mislead interpretations. We provide thresholds and methodological recommendations for future studies. This study establishes a fundamental baseline for monitoring the annual contribution of foraging area to a terrestrial-based breeding aggregation of a marine animal in a cost-effective way. This type of monitoring allows for early detection of changes in foraging distributions—a possible effect of climate change on marine ecosystems or of area-specific anthropogenic threats.
The Elk Hills Oil Field is one of the many fields selected for regional groundwater mapping and monitoring by the California State Water Resources Control Board as part of the Oil and Gas Regional Monitoring Program (California State Water Resources Control Board, 2015, 2022b; U.S. Geological Survey, 2022a). The U.S. Geological Survey (USGS), in cooperation with the California State Water Resources Control Board, is evaluating groundwater resources near areas of oil and gas development in California, including (1) the location of groundwater resources near oil fields; (2) the proximity of oil and gas operations to groundwater, and the geologic materials between them; (3) evidence (or lack of evidence) of fluids from oil and gas sources in groundwater; and (4) the pathways or processes responsible when fluids from oil and gas sources are present in groundwater (U.S. Geological Survey, 2022a). As part of this evaluation, the USGS installed a multiple-well monitoring site near the administrative boundary of the Elk Hills Oil Field in the southern San Joaquin Valley about 6 miles northeast of Taft, California (California Department of Water Resources, 2020; fig. 1). Data collected at the Elk Hills multiple-well monitoring site (ELKH) provide information about the geology, hydrology, geophysical properties, and water quality of the aquifer system, thus enhancing the understanding of relations between adjacent groundwater and the Elk Hills Oil Field in an area where groundwater data are limited, particularly at different depths in the aquifer. This report presents construction information for the ELKH and initial geohydrologic data collected from the site. Similar sites installed on the east side of the Lost Hills Oil Field, on the east side of the North and South Belridge Oil Fields, and within the Poso Creek Oil Field were described by Everett and others (2020a, b, 2023).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231073","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Everett, R.R., Gillespie J.M., Shepherd, M.M., Morita, A.Y., Bobbitt, M., Kohel, C.A., and Warden, J.G., 2023, Multiple-well monitoring site adjacent to the Elk Hills Oil Field, Kern County, California: U.S. Geological Survey Open-File Report 2023–1073, 11 p., https://doi.org/10.3133/ofr20231073.","productDescription":"11 p.","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-148290","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499485,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115583.htm","linkFileType":{"id":5,"text":"html"}},{"id":422144,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231073/full"},{"id":422143,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1073/images"},{"id":422141,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1073/ofr20231073.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":422140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1073/covrthb.jpg"},{"id":422142,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1073/ofr20231073.xml"}],"country":"United States","state":"California","county":"Kern County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.35,\n 35.2\n ],\n [\n -119.35,\n 35.1\n ],\n [\n -119.1,\n 35.1\n ],\n [\n -119.1,\n 35.2\n ],\n [\n -119.35,\n 35.2\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
Excess sediment is a common reason water bodies in the USA become listed as impaired resulting in total maximum daily loads (TMDL) that require municipalities to invest millions of dollars annually on management practices aimed at reducing suspended-sediment loads (SSLs), yet monitoring data are rarely used to quantify SSLs and track TMDL progress. A monitoring network was created to quantify the SSL from the City of Roanoke, Virginia, USA (CoR), to the Roanoke River and Tinker Creek and help guide TMDL assessment and implementation. Suspended-sediment concentrations were estimated between 2020 and 2022 from high-frequency turbidity data using surrogate linear-regression models. Sixty-one percent of the total three-year SSL resulted from five large storm events. The average suspended-sediment yield from the CoR (58.1 metric tons/km2/year) was similar to other urban watersheds in the Eastern United States; however, the yield was nearly five times larger than the TMDL allocation (12.2 metric tons/km2/year). The TMDL allocated load was modeled based on a predominantly forested reference watershed and may not be a practical target for highly impervious watersheds within the CoR. The TMDL model used daily input data which likely does not capture the full range of SSLs during storm events, particularly from flashy urban streams. The average SSL following the five large storm events doubled that of the CoR’s annual allocated load from the TMDL. The results of this study highlight the importance of using high-frequency monitoring data to accurately estimate SSLs and evaluate TMDLs in urban areas.
The summer of 2023 is a notable time for water-resource management in the western United States: Glen Canyon Dam, on the Colorado River, turns 60 years old while the largest dam-removal project in history is beginning on the Klamath River. This commentary discusses these events in the context of a changing paradigm for dam and reservoir management in this region. Since the era of large dam building began to wane six decades ago, new challenges have arisen for dam and reservoir management owing to climate change, population increase, reservoir sedimentation, declining safety of aging dams, and more environmentally focused management objectives. Today we also better understand dams' benefits, costs, and environmental impacts, including some that were unforeseen and took decades to become apparent. Where dams have become unsafe, obsolete (e.g., due to excessive reservoir sedimentation), and uneconomical beyond saving, dam removal has become common. The science and practice of dam removal are accelerating rapidly, and some long-term physical and biological response studies are now available. Removal of four hydroelectric dams on the Klamath River will be a larger and more complex project than any previous dam removal. The imminency of this project reflects a very different situation for dam and reservoir management than 60 years ago. Looking forward, dam and reservoir management in the western United States and worldwide will require continued collaboration and innovative thinking to meet a wide range of objectives and to manage water resources sustainably for future generations.
Trace elements within groundwater that originate from aquifer materials and pose potential public-health hazards if consumed are known as geogenic contaminants. The geogenic contaminants arsenic, chromium, and vanadium can form negatively charged ions with oxygen known as oxyanions. Uranium complexes with bicarbonate and carbonate to form negatively charged ions having aqueous chemistry similar to oxyanions. The concentrations of arsenic, chromium, uranium, and vanadium in groundwater result from the combined effects of (1) geologic abundance within aquifer materials; (2) the fraction of these elements that have weathered from and sorbed to the surfaces of mineral grains and are potentially available to groundwater; and (3) the aqueous chemistry of dissolved oxyanions in groundwater during different redox conditions and pH, both of which are affected by hydrogeology, including the length of time groundwater has been in contact with aquifer materials. Concentrations of arsenic, chromium, uranium, and vanadium were measured in samples of (1) rock, surficial alluvium, and drill cuttings using portable (handheld) X-ray fluorescence (pXRF); (2) operationally defined fractions extractable from these materials; and (3) water from wells sampled between 2000 and 2018 within the 3,500 square mile Mojave River area and Morongo area of the western Mojave Desert, southern California.
Regionally, rock and surficial alluvium in the Mojave River and Morongo areas are high in arsenic, low in chromium and uranium, and near the average bulk continental crust concentration for vanadium. Locally, high chromium concentrations are present in mafic rock within the San Gabriel Mountains; high uranium concentrations are present in felsic rock within the San Bernardino Mountains; and high arsenic, uranium, and vanadium concentrations are present in extrusive (volcanic) felsic rock within uplands surrounding groundwater basins along the Mojave River downstream from Barstow, California. Elemental assemblages identified using principal component analyses (PCA) of pXRF data were used to characterize felsic, mafic, and felsic volcanic source terranes in rock, surficial alluvium, and in geologic material penetrated by selected monitoring wells drilled between 1994 and 2018. Highly felsic alluvium associated with recent deposition from the Mojave River was identified along the 90-mile length of the floodplain aquifer along the river. The thickness of these highly felsic alluvial deposits ranged from 200 feet (ft) near Victorville and near Barstow to a thin veneer about 30 ft thick downstream from Victorville and downstream portions of the floodplain aquifer within the Mojave Valley.
Groundwater in the Mojave River and Morongo areas was generally oxic and alkaline (pH≥7.5). Maximum concentrations of arsenic, hexavalent chromium [Cr(VI)], uranium, and vanadium in water from as many as 498 wells sampled between 2000 and 2018 were 360, 140, 1,470, and 690 micrograms per liter (μg/L), respectively. Water from 22 percent of sampled wells exceeded the U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL) for arsenic of 10 μg/L, with arsenic concentrations commonly exceeding the MCL in water from wells east of Barstow, deep wells in the Victorville fan, and in suboxic or reduced groundwater within the floodplain aquifer. Water from about 1 percent of sampled wells had Cr(VI) concentrations greater than the California MCL for total chromium of 50 μg/L, whereas 13 percent of sampled wells had Cr(VI) concentrations greater than the former California MCL of 10 μg/L. Hexavalent chromium concentrations were highest in water from wells in the Sheep Creek alluvial fan, eroded from mafic rock in the San Gabriel Mountains, although Cr(VI) concentrations greater than the former California MCL also were present elsewhere in the study area where mafic materials or older groundwater were present. Water from about 9 percent of sampled wells exceeded the EPA MCL for uranium of 30 μg/L, with concentrations exceeding the MCL commonly associated with irrigation return from agricultural land overlying the floodplain aquifer. Water from about 7 percent of sampled wells had vanadium concentrations greater than the California notification level of 50 μg/L; most of these wells were in the Victorville fan within the Mojave River area. In general, arsenic concentrations were higher in suboxic or reduced water; chromium concentrations were higher in oxic, alkaline (pH≥7.5) water; uranium concentrations were higher in circumneutral to slightly alkaline water (pH≤7.4); and vanadium concentrations were higher in highly alkaline (pH≥8.0) water, independent of redox status.
Concentrations within geologic source terranes are not the sole factor controlling the concentrations of geogenic elements in groundwater. Differences in mineral weathering, pH-dependent sorption to surface-exchange sites on mineral grains, and aqueous geochemistry (especially redox status and pH) affect geogenic element concentrations in groundwater. Consequently, the relative abundances of arsenic, Cr(VI), uranium, and vanadium in groundwater differ from their relative abundances in the average bulk continental crust and their regional abundances in rock and surficial alluvium within groundwater basins of the western Mojave Desert. Processes that control the concentrations of arsenic, chromium, uranium, and vanadium in groundwater operate at the mineral-grain and aquifer scale.
At the mineral-grain scale, sequential chemical extraction data show arsenic and uranium are more available to groundwater (under specific geochemical conditions) than chromium or vanadium, which largely are unavailable within unweathered mineral grains. Additionally, chromium and vanadium form few aqueous complexes and bind tightly with iron minerals within surface coatings on mineral grains making them less available to groundwater, whereas complexation with other dissolved ions enhances the solubility of uranium and, to a lesser extent, arsenic. Complexation also increases the valence (less negative charge) and increases the size of dissolved oxyanions and uranium complexes with bicarbonate and carbonate making them less readily sorbed to aquifer materials.
At the aquifer scale, hydrogeology (including isolation of water in aquifers from surface sources of recharge, older groundwater age, and long contact times between groundwater and aquifer materials) combined with geochemical processes (such as silicate weathering) to produce alkaline groundwater. Desorption from sorption sites on the surfaces of mineral grains with increasing pH increases arsenic, chromium, and vanadium concentrations in water from wells and increases Cr(VI) concentrations as long as water remains oxic.
Aqueous geochemistry and concentrations of geogenic contaminants also are affected by anthropogenic activities including (1) discharge of treated municipal wastewater, which may change the redox status of groundwater; (2) return from irrigated agriculture, which may alter the chemistry of groundwater and increase the solubility of trace elements such as uranium; and (3) groundwater pumping and subsequent water-level declines, which may change the source of water yielded by wells. The quality of water imported from northern California and infiltrated from ponds for groundwater recharge may be altered by naturally present trace elements, especially uranium in areas of agricultural land use or chromium within mafic alluvium.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235089","collaboration":"Prepared in cooperation with the Mojave Water Agency","programNote":"U.S. Geological Survey Cooperative Water Program","usgsCitation":"Izbicki, J.A., Groover, K.D., and Seymour, W.A., 2023, Arsenic, chromium, uranium, and vanadium in rock, alluvium, and groundwater, western Mojave Desert, southern California: U.S. Geological Survey Scientific Investigations Report 2023–5089, 96 p., https://doi.org/10.3133/sir20235089.","productDescription":"Report: xiii, 96 p., 3 Data Releases; 2 Tables","numberOfPages":"96","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101005","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501053,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115509.htm","linkFileType":{"id":5,"text":"html"}},{"id":421873,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir20235089_table2.1.csv","text":"Table 2.1","size":"3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Well Identification and National Water Information System Record Numbers for Wells Sampled in the Mojave River and Morongo Groundwater Basins as Part of This Study July 2016 to October 2016 and for Wells Sampled as Part of the Groundwater Ambient Monitoring Assessment Program Priority Basin Project Mojave Basin Domestic-Supply Aquifer Study January to May 2018 western Mojave Desert southern California"},{"id":421877,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C7U6DW","text":"USGS Data Release","description":"Groover, K.D., Goldrath, D.A., Bennett, G.L., Johnson, T.D., and Watson, E.E., 2019, Groundwater-quality data in the Mojave Basin Shallow Aquifer Study Unit, 2018—Results from the California GAMA Priority Basin Project: U.S. Geological Survey data release, https://doi.org/10.5066/P9C7U6DW.","linkHelpText":"Groundwater-quality data in the Mojave Basin Shallow Aquifer Study Unit, 2018—Results from the California GAMA Priority Basin Project"},{"id":421878,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://ca.water.usgs.gov/mojave/mojave-water-quality.html","text":"USGS Data Release","description":"Metzger, L.F., Landon, M.K., House, S.F., and Olsen, L.D., 2015, Mapping selected trace elements and major ions, 2000–2012, Mojave River and Morongo Groundwater Basins, Southwestern Mojave Desert, San Bernardino County, California: U.S. Geological Survey data release, https://ca.water.usgs.gov/mojave/mojave-water-quality.html.","linkHelpText":"Mapping selected trace elements and major ions, 2000–2012, Mojave River and Morongo Groundwater Basins, Southwestern Mojave Desert, San Bernardino County, California"},{"id":421923,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235089/full"},{"id":421973,"rank":10,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir_20235089.pdf","text":"Report","size":"30 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":421869,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5089/covrthb.jpg"},{"id":421871,"rank":2,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir20235089.xml"},{"id":421872,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir20235089_table1.1.csv","text":"Table 1.1","size":"3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Boreholes having portable (handheld) X-ray fluoresence (pXRF) data from drill cuttings, Mojave River and Morongo groundwater basins, western Mojave Desert, southern California"},{"id":421874,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5089/images"},{"id":421876,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CU0EH3","text":"USGS Data Release","description":"Groover, K.D., and Izbicki, J.A., 2018, Field portable X-ray fluorescence and associated quality control data for the western Mojave Desert, San Bernardino County, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9CU0EH3.","linkHelpText":"Field portable X-ray fluorescence and associated quality control data for the western Mojave Desert, San Bernardino County, California"}],"country":"United States","state":"California","otherGeospatial":"Western Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.4,\n 35.2\n ],\n [\n -117.4,\n 34.00\n ],\n [\n -116.0,\n 34\n ],\n [\n -116,\n 35.2\n ],\n [\n -117.4,\n 35.2\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
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This publication is a preliminary map and geodatabase of the coseismic surface rupture and other coseismic features generated from the August 9, 2020, Mw 5.1 earthquake near Sparta, North Carolina. Geologic mapping facilitated by analysis of post-earthquake quality level 0 to 1 lidar, document the coseismic surface rupture, named the Little River fault, and other coseismic features. The Little River fault is traced for approximately 4 kilometers and cuts the regional Paleozoic fabric (mean foliation, 063°/57°), and the dominant strike of joint sets are 0°–10°, 130°–150°, and 320°–340°. Individual fault strands occur in an en echelon pattern within an approximately 10-meter-wide zone. Trenches across the Little River fault document a thrust fault oriented 110°/45° with at least 10 centimeters (cm) of displacement. The Little River fault is marked by a flexure or scarp with a height of 5–30 cm and a local maximum height of 50 cm. Southwest-side-up displacement is consistent along the fault and indicates thrust kinematics. The strike of the Little River fault changes from 110° to 130° near Duncan Farm where it crosses Chestnut Grove Church Road (NC Rt. 1426). Although the surface expression of the fault terminates and (or) is imperceptible at both ends, deformation is still clear in residual surface maps showing the change between pre- and post-earthquake lidar elevations. Other coseismic features documented are rockfalls, ground cracks, fissures, lateral spreading on a sandbar, and mass-wasting scarps; several possible faults that were identified from lidar analyses strike E-W and oblique to the Little River fault.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231074","usgsCitation":"Merschat, A.J., and Carter, M.W., 2023, Preliminary map of the surface rupture from the August 9, 2020, Mw 5.1 earthquake near Sparta, North Carolina—The Little River fault and other possible coseismic features: U.S. Geological Survey Open-File Report 2023–1074, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20231074.","productDescription":"Sheet: 47.89 x 19.47 inches; Data Release","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-144102","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":421654,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S5PGIH","text":"USGS data release","linkHelpText":"Database for the preliminary map of the surface rupture from the August 9, 2020, Mw 5.1 earthquake near Sparta, North Carolina—The Little River fault and other possible coseismic features"},{"id":421652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1074/coverthb.jpg"},{"id":421653,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1074/ofr20231074.pdf","text":"Report","size":"106 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1074"},{"id":499788,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115507.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"North Carolina","city":"Sparta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.18690346012897,\n 36.54364449287644\n ],\n [\n -81.18690346012897,\n 36.472458202284926\n ],\n [\n -81.09177792830289,\n 36.472458202284926\n ],\n [\n -81.09177792830289,\n 36.54364449287644\n ],\n [\n -81.18690346012897,\n 36.54364449287644\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
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Rattlesnake Knoll is a small, 30-meter-high mound of igneous breccia in the center of Spring Valley, east-central Nevada. In the past, researchers have disagreed as to whether the unusual-looking outcrop is intrusive or volcanic. The breccia possesses a normal magnetic polarity, but this is not apparent in aeromagnetic survey data. These data instead show that the knoll lies within a small aeromagnetic low that partially overlaps the extent of a small gravity high. The small gravity anomaly associated with the knoll, combined with an initial, limited ground magnetic survey taken at the knoll, indicates that the knoll rocks extend northward in the subsurface. A second, more extensive ground magnetic traverse was also done north of the knoll. Taking into consideration these new survey data and preexisting data, a two and one-half dimensional modeling program based on Webring (1985) was used to produce a geophysical model that accounts for gravity and magnetic properties, satisfies available geologic information, and conforms to current estimates of basin thickness. This model and the field observations support the interpretation that the knoll consists of gently west-dipping beds of Tertiary volcanic flow breccia, mudflow breccia, and conglomerate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231002","usgsCitation":"Mankinen, E.A., Rowley, P.D., and McKee, E.H., 2023, The enigmatic Rattlesnake Knoll, Spring Valley, east-central Nevada—A geophysical perspective: U.S. Geological Survey Open-File Report 2023–1002, 13 p., https://doi.org/10.3133/ofr20231002.","productDescription":"Report: vi, 13 p.; Data Release","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-133281","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":435149,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WL97XY","text":"USGS data release","linkHelpText":"Ground magnetic data, Spring Valley, White Pine County, Nevada"},{"id":421859,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1002/covrthb_.jpg"},{"id":421860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1002/ofr20231002.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":499729,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115506.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nevada","otherGeospatial":"Spring Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.36,\n 39.06\n ],\n [\n -114.36,\n 39.00\n ],\n [\n -114.24,\n 39.00\n ],\n [\n -114.24,\n 39.06\n ],\n [\n -114.36,\n 39.06\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
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Due to Idaho’s inland location approximately 350 miles from the Pacific Ocean and its 80 recognized mountain ranges, the State’s climate varies widely, with maritime influence in the northern and western parts of Idaho and continental influence on the eastern side. The weather in the abundant mountains is unpredictable and often associated with natural hazards such as severe thunder and lightning storms leading to flooding, landslides, and wildfires. Issues important to Idaho’s economy include river, stream, and forest resource management, and infrastructure and construction management. Idaho participated in the U.S. Geological Survey 3D Elevation Program (3DEP) in 2016, the State’s first 3DEP project. The success of this project led to development of the Idaho Statewide Lidar Plan. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233035","usgsCitation":"Carlson, T., 2023, The 3D Elevation Program—Supporting Idaho’s economy: U.S. Geological Survey Fact Sheet 2023–3035, 2 p., https://doi.org/10.3133/fs20233035.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-146166","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":421592,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3035/fs20233035.XML"},{"id":421591,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3035/images/"},{"id":421590,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233035/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 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\"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, Mail Stop 511
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Waterfowl with more body mass and a greater body condition during the non-breeding season are thought to be more likely to survive and have increased productivity during the following breeding season. Body mass and body condition in waterfowl should reflect the resources available to them locally. We analyzed the relationship of landscape composition on mallard (Anas platyrhynchos) body mass and body condition (mass-wing length index) among age and sex groups. We calculated these variables from hunter-harvested mallards during the 2019–2020 and 2020–2021 duck hunting seasons in the Lower Mississippi Alluvial Valley of Arkansas, USA. We used linear mixed-effects models to analyze changes in body mass and body condition with changes in the percent landscape composition of water cover, woody wetlands, herbaceous wetlands, rice, soybeans, and disturbance. We found that body mass and condition of harvested mallards were positively associated with greater proportions of water cover and woody wetlands but negatively associated with greater proportions of herbaceous wetlands and human disturbance from human infrastructure. Management actions focused on providing flooded and woody wetland areas on the landscape that allow waterfowl to access food resources, while decreasing the disturbance around wetlands in the form of road density and human infrastructure, should increase body mass and body condition in mallards spending the non-breeding season in the Lower Mississippi Alluvial Valley.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22509","usgsCitation":"Veon, J., Krementz, D., Naylor, L., and DeGregorio, B.A., 2023, Influences of landscape composition on hunter-harvested mallard body mass and condition in eastern Arkansas: The Journal of Wildlife Management, v. 88, no. 1, e22509, 22 p., https://doi.org/10.1002/jwmg.22509.","productDescription":"e22509, 22 p.","ipdsId":"IP-139908","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":490090,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22509","text":"Publisher Index Page"},{"id":482266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"eastern 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\"}}]}","volume":"88","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-10-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Veon, John T.","contributorId":351068,"corporation":false,"usgs":false,"family":"Veon","given":"John T.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":927830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krementz, David G.","contributorId":351069,"corporation":false,"usgs":false,"family":"Krementz","given":"David G.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":927831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Naylor, Luke W.","contributorId":351070,"corporation":false,"usgs":false,"family":"Naylor","given":"Luke W.","affiliations":[{"id":37007,"text":"Arkansas Game and Fish Commission","active":true,"usgs":false}],"preferred":false,"id":927832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":927833,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70256477,"text":"70256477 - 2023 - Striped bass exploitation in tailwater habitats of east-central Oklahoma","interactions":[],"lastModifiedDate":"2024-09-09T15:47:17.424251","indexId":"70256477","displayToPublicDate":"2023-10-03T10:41:23","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-152-2023","title":"Striped bass exploitation in tailwater habitats of east-central Oklahoma","docAbstract":"Striped Bass (Morone saxatilis) is naturally anadromous, but a few land-locked populations have been documented that are self-sustaining, including fish in the Arkansas River, Oklahoma. This rare population is the source of brood stock for the Oklahoma Department of Wildlife Conservation hatcheries and is an important sportfish stock. Striped Bass often congregate in tailwater habitats, where anecdotal observations indicate anglers can harvest numerous fish daily. This suggests the need to evaluate the sustainability of harvest in these locations. It is unknown what portion of fish from the Arkansas River population use tailwater habitats or the timing and duration of use. The objectives of this study were to: 1) determine size structure , abundance, and total mortality rate of Striped Bass in the tailwaters of Tenkiller Lake and Lake Eufaula; 2) determine the extent and timing of immigration and emigration of Striped Bass in tailwater habitats to determine the potential for overharvest when they congregate in tailwater areas; 3) estimate delayed hooking mortality of Striped Bass in spring and summer; and 4) using the above data and modeling simulations, determine the potential for growth overfishing of Striped Bass in the tailwater reaches. We sampled 2,730 Striped Bass using boat electrofishing and tagged with passive integrated transponder (PIT) tags to estimate demographic data using a capture-recapture model. A subset of these Striped Bass was tagged with angler reward tags (internal anchor tags, n = 681) and dual technology acoustic-radio telemetry tags (n = 111) to estimate exploitation and track movements, respectively. Anglers returned 116 tags from 2020 to 2022; and our angler reporting rate was estimated to be 14.3%. Annual harvest mortality is minimally 7% (unadjusted for reporting rate) but could be as high as 42% (i.e., adjusting for compliance; but this exceeds the measured total mortality rate (34.3%) so true exploitation is probably 7–34.3%). Our abundance estimates for Striped Bass varied seasonally (ranging from 782 to 38,597 seasonally) and had a high level of uncertainty likely due to relatively low recapture rates. Additionally, our results indicated that Striped Bass exhibited a strong fidelity to their respective habitats within seasons, with fidelity probabilities ranging from 0.98 to 1.00. Movement among segments was common among seasons, indicating these localized populations mix with a larger population annually. Striped Bass were primarily in tailwater habitats during summer. Delayed hooking mortality data were collected in summer 2022. Due to habitat conditions that year, angling catch rates were low. Twenty-nine Striped Bass were tagged, and only eight Striped Bass remained tagged long enough to be tracked at least one day. The total time tracked for these eight fish was between one and three days. There were no confirmed mortalities, treatment, or control. Because of the low sample size, literature values for delayed hooking mortality were also used to supplement field data in the models. The yield-per-recruit model indicated exploitation at 30% or higher leads to recruitment overfishing. A 600 mm minimum TL regulation and 25–30% exploitation rate achieve maximum yield (954 kg/1,000 recruits). Maximum yield related to an average size at harvest of 718-mm TL; thus, growth overfishing occurs for any regulation where average size of harvest is smaller than 718 mm (which the model predicted would occur for any minimum length < 600, and for minimum length = 600 if exploitation was > 30%, it never occurred with minimum length requirements > 650). Increasing the minimum length regulation improves size structure, but a maximum length regulation had minimal effect unless it was implemented at a sufficiently small size (i.e., < 700 mm). Although catch-and-release mortality can be relatively high at times in the literature, according to our model, it appears to have a small effect on size structure, except when exploitation rates are > 50% and a restrictive maximum size regulation (< 800 mm) is used. The current population appears sustainable, especially considering the annual mixing dynamics and apparently large population (though we see a lot of uncertainty in the population estimates). However, modeling indicates that if enhancing size structure is an agency priority, then implementing more restrictive regulations could be advantageous.
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We combined the data of four long-term sampling programs, adding several years of data (post and prior) to previously published analyses to offer a longer-term, cross-basin analysis of M. diluviana populations in the Great Lakes from 1997 to 2019. Densities were high in lakes Superior and Ontario (summer values 100–300/m2), high and variable but declining (from 200–300/m2 in 1997–2004 to less than 100/m2 in 2017–2019) in Lake Michigan, low (∼20–50/m2 since 2005) in Lake Huron, and very low in shallower eastern Lake Erie (<1/m2). Biomass showed similar trends. Life history parameters (mortality, fecundity, and growth) were consistently highest in eastern Lake Erie, followed by lakes Ontario, Michigan, Huron, and Superior. Generation time was 1 year in Lake Erie and 2 years in the other lakes. Cross-basin relationships between annual M. diluviana areal densities and food indices (chlorophyll-a concentration and zooplankton biomass) were non-linear, increasing with food levels up to about 250 mysids/m2 and about 650 mg dry wt/m2. Annual growth rates were also positively correlated to both food indices in the four deep lakes, but fecundity and mortality rates were not. Our results suggest food availability is a primary factor predicting M. diluviana density and biomass. Density-dependent mortality and fish predation could explain some of the inter-lake differences, but these relationships could benefit from further investigations.
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