In response to a need for information on potential domestic sources of critical minerals, the Earth Mapping Resources Initiative (Earth MRI) was established to identify and prioritize areas for acquisition of new geologic mapping, geophysical data, and elevation data to improve our knowledge of the geologic framework of the United States. Phase 1 of Earth MRI concentrated on those geologic terranes favorable for hosting the rare earth elements (REEs). Phase 2 continued to address the REEs and also identified focus areas for potential domestic sources of 10 more of the 35 critical minerals on the U.S. critical minerals list (aluminum, cobalt, graphite, lithium, niobium, platinum-group elements, tantalum, tin, titanium, tungsten). This report describes the methodology, data sources, and summary results for mineral systems that host these 11 critical minerals in the conterminous United States, Hawaii, and Puerto Rico; Alaska is covered in a separate report. The mineral systems framework adopted for this study links critical mineral commodities to families of genetically related mineral deposit types. The mineral systems approach is an efficient approach, providing a simultaneous evaluation of geologic terranes through aggregation of genetically related mineral deposit types that are much larger than individual ore deposits. Geologic, geochemical, topographic, and geophysical mapping provided by Earth MRI will document geologic features that reflect the extent of individual mineral systems and provide information about critical mineral deposits that may not have been recognized previously.
Each critical mineral commodity is discussed in terms of importance to the Nation’s economy, modes of occurrence, mineral systems, and deposit types along with maps and tables listing examples of focus areas for each critical mineral. Important mineral systems for these critical minerals include chemical weathering systems for aluminum (bauxite); placer systems for titanium and REEs; metamorphic systems for graphite; mafic magmatic systems for platinum-group elements and cobalt; lacustrine evaporite and porphyry tin systems for lithium; and copper-molybdenum-gold (Cu-Mo-Au) systems for tungsten. REEs occur in many different mineral systems. Focus areas were developed by scientists from the U.S. Geological Survey in collaboration with scientists from State geological surveys and other institutions. This first national-scale compilation of focus areas represents an initial step in addressing the Nation’s critical mineral needs by screening areas for acquisition of new data to provide the geologic framework necessary for identifying domestic sources of critical minerals.
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In 2019, total daily tight oil and gas production increased in the United States month over month, with annualized growth of 14% for oil and 12% for gas. Those gains leveled off in the first quarter of 2020 due to aggressive price competition and increases in international production. Then came the pandemic with a substantially larger dose of economic turmoil, driving down demand due in part to shelter in place orders and safety concerns around travel. Between March and May, tight oil and gas production dropped by nearly 2 million bpd and almost 5 Bcf/day before beginning to recover. Production has continued to increase for the most part through the second half of 2020, but drilling remains subdued throughout most of the U.S. and uncertainty around long term demand along with the current price environment and general state of the economy has contributed to layoffs throughout the industry.
Some shale-gas production has declined recently, but a few areas have seen expansion due to construction of LNG facilities along the East Coast of the U.S. (e.g., the Haynesville Formation). Current U.S. shale-gas production is still higher now than in 2019, with daily production of almost 71 Bcf as of October 2020 driven in large part by increased production from the Marcellus Shale in the Appalachian Basin and shales within the Permian Basin. Shale liquids production is down by around a million bpd to approximately 7.1 million (September 2020; U.S. EIA) from pre-pandemic production levels at the end of 2019 and beginning of 2020. Tight oil production remains dominated by plays in the Permian Basin as well as the Bakken and Eagle Ford Formations.
On the development and production front, new enhanced oil recovery approaches for tight shale reservoirs are being more widely implemented. Natural gas or CO2 injection is currently being utilized in the Bakken Formation, Eagle Ford Formation, Anadarko Basin, and the Permian Basin to optimize injection sequences and boost recovery. Refracturing of existing wells to reduce drilling costs, improve production, and prolong well productive life has also begun to occur more widely in developed plays.
International interest in exploiting hydrocarbons from unconventional reservoirs continues to develop, with active exploration projects on most continents. Europe remains relatively underexplored as compared to North America, although a total of 141 exploration and appraisal wells with a possible shale-gas exploration component have been spudded, including horizontal legs from vertical wells. Shale exploration has made a breakthrough in China with shale gas output in 2019 of 10 billion cubic meters (35.3 Bcf), 60% of which was produced from Sinopec’s Fuling Shale Gas field. Lacustrine shale oil exploration has also been successful in the Sichuan and Ordos Basins in central China, Junggar and Tarim Basins in northwest China, and Songliao Basin in north China, and Bohai Bay Basins in northeast China as of 2018.
South America’s potential as an unconventional shale gas and oil province is mainly in Argentina and Brazil, where the production from Neuquen Basin’s tight shale of the Vaca Muerta Formation has been steadily increasing since 2016, but only 4% of the shale resource has been developed thus far. According to International Energy Agency’s report in 2013, Brazil holds the 9th largest unconventional gas reserves. Brazil has shale oil and gas potential in the Parana, Solimoes and Amazon Basins and is actively producing from the oil shale unit of the Irati Formation. In 2019, the Brazil energy ministry launched REATE 2020 to boost onshore investments that include the expectation of drilling an experimental unconventional well in the northeast region.
For this inaugural report, the new AAPG EMD Tight Oil and Gas Committee (TO&G; formerly the Shale Gas & Liquids and Tight Gas Sands committees) has developed new commodity report requirements for contributors. This includes shorter annual reports focused on new developments, play concepts, along with the typical updates on production and new drilling in the play areas they cover. We are also asking contributors to collect background geologic and production related information into a document that summarizes important features of the plays they cover that will be stored on the TO&G webpage along with our commodity reports.
TO&G is currently working to expand the number of contributors to cover more play areas and replace committee and advisory board members that have recently stepped down. Changes to committee leadership occurred in October as recent chairs transition to EMD elected positions.
This report presents potentiometric-surface maps of the Aquia and Magothy aquifers and the Upper Patapsco, Lower Patapsco, and Patuxent aquifer systems using water levels measured during the fall season of 2019. The potentiometric surface maps show water levels ranging from 56 feet above sea level to 163 feet below sea level in the Aquia aquifer, from 87 feet above sea level to 119 feet below sea level in the Magothy aquifer, from 114 feet above sea level to 120 feet below sea level in the Upper Patapsco aquifer system, from 136 feet above sea level to 174 feet below sea level in the Lower Patapsco aquifer system, and from 168 feet above sea level to 184 feet below sea level in the Patuxent aquifer system.
Cones of depression have formed around locations with significant aquifer withdrawals. The Aquia aquifer has depressed water levels around well fields at Lexington Park, Solomons Island, and central Talbot County. Cones of depression have formed in the Magothy aquifer around well fields at Waldorf, Arnold, and Easton. The Upper Patapsco aquifer system has depressed water levels around well fields in the Annapolis-Arnold area, Waldorf, the Lexington Park-Leonardtown area, and at Easton. The Lower Patapsco aquifer system has depressed water levels around well fields at Severndale, Broad Creek, Arnold, and Crofton Meadows as well as in central and western Charles County. Cones of depression have formed in the Patuxent aquifer system around well fields at Dorsey Road, Crofton, Arnold, northwestern Charles County, and at the Chalk Point power plant.
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The National Environmental Policy Act and the Endangered Species Act requires Department of Defense land managers to prioritize identification, monitoring, and conservation of Indiana bat day-roost areas, foraging habitat during the maternity season, and pre-hibernation swarming sites during autumn.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bat echolocation research: A handbook for planning and conducting acoustic studies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Bat Conservation International","usgsCitation":"Ford, W., Dobony, C., Jachowski, D., Coleman, L.S., Nocera, T., and Britzke, E.R., 2020, Case study 1: Acoustic Surveys at Fort Drum Military Installation – the Value of Long-term Monitoring, chap. of Bat echolocation research: A handbook for planning and conducting acoustic studies, p. 82-85.","productDescription":"4 p.","startPage":"82","endPage":"85","ipdsId":"IP-090899","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":394588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":393639,"type":{"id":15,"text":"Index Page"},"url":"https://batsurveysolutions.com/pages/batss-covid-19-response"}],"country":"United States","state":"New York","otherGeospatial":"Fort Drum Military Installation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.59349060058594,\n 44.00615076564076\n ],\n [\n -75.40054321289062,\n 44.146246915303635\n ],\n [\n -75.3826904296875,\n 44.19303602884215\n ],\n [\n -75.52894592285156,\n 44.25897020133368\n ],\n [\n -75.64498901367188,\n 44.189097324204134\n ],\n [\n -75.76309204101562,\n 44.086598616569646\n ],\n [\n -75.79124450683594,\n 44.07081379264681\n ],\n [\n -75.80291748046875,\n 44.07969327425713\n ],\n [\n -75.82763671875,\n 44.07525370000069\n ],\n [\n -75.84548950195312,\n 44.02837121279199\n ],\n [\n -75.78849792480469,\n 44.01306468595375\n ],\n [\n -75.69717407226562,\n 44.040712307588414\n ],\n [\n -75.59349060058594,\n 44.00615076564076\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ford, W. 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Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":829730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dobony, Christopher A.","contributorId":264897,"corporation":false,"usgs":false,"family":"Dobony","given":"Christopher A.","affiliations":[{"id":54576,"text":"DoD","active":true,"usgs":false}],"preferred":false,"id":831296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jachowski, David S.","contributorId":228814,"corporation":false,"usgs":false,"family":"Jachowski","given":"David S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":831297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coleman, Laci S.","contributorId":171672,"corporation":false,"usgs":false,"family":"Coleman","given":"Laci","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":831298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nocera, Tomas","contributorId":270948,"corporation":false,"usgs":false,"family":"Nocera","given":"Tomas","email":"","affiliations":[],"preferred":false,"id":831299,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Britzke, Eric R.","contributorId":8327,"corporation":false,"usgs":true,"family":"Britzke","given":"Eric","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":831300,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70215354,"text":"70215354 - 2020 - Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System","interactions":[],"lastModifiedDate":"2021-10-01T15:35:34.106947","indexId":"70215354","displayToPublicDate":"2020-12-31T10:25:19","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9371,"text":"Mississippi River Restoration Program","active":true,"publicationSubtype":{"id":1}},"displayTitle":"Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System","title":"Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System","docAbstract":"Smallmouth buffalo (Ictiobus bubalus) is a common and widely distributed large-bodied species of the family Catostomidae. It inhabits large rivers and reservoirs of the eastern continental United States (east of the continental Divide) and is most abundant and common in the large rivers of the Midwest and Central Plains, though it does occur as far north and east as the Hudson Bay drainage and as far south and west as Arizona (Edwards and Twoney 1982).\n\nHistorically, smallmouth buffalo were an important component of commercial fisheries on both the Mississippi and Illinois Rivers. However, following the introduction of common carp (Cyprinus carpio) in the mid-1800s (Carlander 1954), the construction of a system of navigation dams on Upper Mississippi and Illinois River in the 1930s (USGS 1999), and water quality/pollution issues through the 1980s (Weiner 2010), the role of smallmouth buffalo in the overall UMRS fish community and commercial fishery has generally diminished relative to historical standards. Still, smallmouth buffalo remains an important and valued component of the UMRS commercial fishery.\n\nThe study area is represented by three study reaches on the Illinois River and three study reaches on the Upper Mississippi River (Figure 1). Collectively, these study reaches represent nearly 1200 river km and exist across strong and pronounced ecological and disturbance gradients. For example, habitat composition, water quality, commercial navigation intensity, aquatic plant prominence, and the number and abundance of nonnative fish species vary strongly across the study domain, with northern Mississippi River reaches exhibiting less navigation traffic, better water quality, markedly greater aquatic plant prominence, more diverse habitat composition, and comparably much smaller numbers of nonnative species than the lower Mississippi River study reach and those on the Illinois River (USGS 1999; Johnson and Hagerty [eds] 2008; Irons et al. 2009).\n\nLong term monitoring efforts conducted under the auspices of the Upper Mississippi River Restoration program over the past 27 years have provided tremendous insights into shifts and changes of the overall UMRS fish community (Ickes et al. 2005; Garvey et al. 2010; Schramm and Ickes 2016). However, these monitoring efforts observe only the most basic aspects of the UMRS fish community (i.e., catch, length, weight, distribution, and occurrence). To gain a greater understanding of forces driving community level shifts and changes, more directed study is needed on the functional attributes of fish populations (i.e., growth, mortality, recruitment). Collectively, these functional attributes of populations are termed population dynamics and/or vital rates.\n\nIt is important to note, the population dynamics of fishes in large rivers is generally poorly understood, especially for non-game species (Ickes 2018). The prevailing view is that abiotic factors largely govern inter-annual population dynamics, typically based upon rather short-term observations and correlations with assorted abiotic river attributes that vary on a seasonal or annual basis (for example, Risotto and Turner 1985). However, the role that longer-term abiotic factors play in regulating population abundance, or that biotic factors internal to the population (e.g., spawner-recruit dynamics, growth dynamics) or external to the population (e.g., predator-prey dynamics, sympatric competitors, disease) remain poorly understood. Achieving a greater understanding of these dynamics is important for stock, game, and invasive species management.\n\nIn 2017, as part of a larger study designed to gain vital population rate information for smallmouth buffalo in the Upper Mississippi and Illinois Rivers (“Smallmouth Buffalo population demographics of the Upper Mississippi River System”; UMRR LTRM 2018SOW project items 2018MMBF1-2018MMBF6) annual growth patterns in smallmouth buffalo were determined and evaluated. This was accomplished by measuring growth histories recorded in annual growth increments on hard bony parts (here otoliths), a method known generically as biochronology, and somewhat analogous to dendrochronology practiced by foresters. These methods allow one to generate time-series of annual growth histories that depend upon age, year class (i.e., cohort), and annual environmental conditions experienced by the population over time (Weisberg, 1993).\n\nBiochronology methods were used to develop a 36-year time series of smallmouth buffalo growth in the Upper Mississippi and Illinois Rivers across a 1200 km ecological and human use disturbance gradient. Annual growth intervals were identified and measured from otoliths to determine fish age and growth history. A mixed model that parses the growth increment into age and year effects was fit to these data.\n\nGiven the pronounced ecological and disturbance gradients inherent to the UMRS and the study domain, an a priori expectation of differing patterns in growth is accepted as a null hypothesis to test.\n\nThe goal of this study was to model smallmouth buffalo growth as a function of the age of the fish and the growth year in which the growth was gained. The primary modeling objective was to parse growth observed on each annulus into a portion attributable to the age of the fish and the portion attributable to the year in which the growth was gained. In effect, this modeling approach removes the somewhat trivial age effects on growth so that a non-confounded growth year effect can be gained. Results attributable to growth year provide a time series of growth information that is of the same duration as the oldest fish observed and solely reflects environmental influences on growth. These model responses can then be investigated relative to environmental covariate time-series suspected of influencing growth of smallmouth buffalo in the Upper Mississippi and Illinois Rivers (e.g., temperature, discharge, population density, population mortality, forage availability, sympatric competition, habitat composition, navigation intensity, nonnative fish prominence, etc.). Thus, the primary scientific objective was to investigate if and how smallmouth buffalo growth varies in accordance with innate ecological and disturbance gradients across the study domain.","language":"English","publisher":"US Army Corps of Engineers","usgsCitation":"Ickes, B., 2020, Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System: Mississippi River Restoration Program, 16 p.","productDescription":"16 p.","ipdsId":"IP-111767","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":390126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390125,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://umesc.usgs.gov/reports_publications/ltrmp_rep_list.html"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Illinois river, upper Mississippi River system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.285400390625,\n 40.329795743702064\n ],\n [\n -90.802001953125,\n 41.1290213474951\n ],\n [\n -90.06591796875,\n 41.88592102814744\n ],\n [\n -90.04394531249999,\n 42.13082130188811\n ],\n [\n -90.889892578125,\n 43.052833917627936\n ],\n [\n -91.14257812499999,\n 43.97700467496408\n ],\n [\n -91.900634765625,\n 44.47299117260252\n ],\n [\n -92.757568359375,\n 44.809121700077355\n ],\n [\n -93.71337890625,\n 45.390735154248894\n ],\n [\n -94.141845703125,\n 45.69083283645816\n ],\n [\n -94.15283203125,\n 46.37725420510028\n ],\n [\n -94.7021484375,\n 46.38483322349276\n ],\n [\n -94.39453125,\n 45.583289756006316\n ],\n [\n -93.44970703125,\n 44.92591837128866\n ],\n [\n -92.186279296875,\n 44.37098696297173\n ],\n [\n -91.64794921875,\n 43.98491011404692\n ],\n [\n -91.38427734374999,\n 43.74728909225908\n ],\n [\n -91.34033203125,\n 43.33316939281732\n ],\n [\n -91.2744140625,\n 42.64204079304426\n ],\n [\n -90.582275390625,\n 42.285437007491545\n ],\n [\n -90.3515625,\n 42.00032514831621\n ],\n [\n -91.219482421875,\n 41.36856413680967\n ],\n [\n -91.669921875,\n 40.622291783092706\n ],\n [\n -91.7138671875,\n 39.93501296038254\n ],\n [\n -90.8349609375,\n 38.75408327579141\n ],\n [\n -90.384521484375,\n 38.762650338334154\n ],\n [\n -90.494384765625,\n 38.298559092254344\n ],\n [\n -89.857177734375,\n 37.60552821745789\n ],\n [\n -89.58251953125,\n 37.02886944696474\n ],\n [\n -89.53857421875,\n 36.82687474287728\n ],\n [\n -89.80224609374999,\n 36.30627216957992\n ],\n [\n -89.384765625,\n 36.32397712011264\n ],\n [\n -89.02221679687499,\n 36.76529191711624\n ],\n [\n -89.110107421875,\n 37.28279464911045\n ],\n [\n -89.49462890625,\n 37.92686760148135\n ],\n [\n -90.263671875,\n 38.35027253825765\n ],\n [\n -89.912109375,\n 39.01064750994083\n ],\n [\n -90.50537109375,\n 39.18969082109678\n ],\n [\n -90.362548828125,\n 39.85915479295669\n ],\n [\n -89.593505859375,\n 40.51379915504413\n ],\n [\n -89.154052734375,\n 41.16211393939692\n ],\n [\n -88.4619140625,\n 41.253032440653186\n ],\n [\n -88.05541992187499,\n 41.3850519497068\n ],\n [\n -88.2861328125,\n 41.590796851056005\n ],\n [\n -89.549560546875,\n 41.42625319507269\n ],\n [\n -90.208740234375,\n 40.613952441166596\n ],\n [\n -90.867919921875,\n 39.90130858574735\n ],\n [\n -91.219482421875,\n 39.8928799002948\n ],\n [\n -91.285400390625,\n 40.329795743702064\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ickes, Brian 0000-0001-5622-3842 bickes@usgs.gov","orcid":"https://orcid.org/0000-0001-5622-3842","contributorId":2925,"corporation":false,"usgs":true,"family":"Ickes","given":"Brian","email":"bickes@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":801849,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70218021,"text":"70218021 - 2020 - Geologic map of the Dog River and northern part of the Badger Lake 7.5′ quadrangles, Hood River County, Oregon","interactions":[],"lastModifiedDate":"2021-04-14T14:37:25.364879","indexId":"70218021","displayToPublicDate":"2020-12-31T09:33:36","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":8123,"text":"Geological Map","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"126","title":"Geologic map of the Dog River and northern part of the Badger Lake 7.5′ quadrangles, Hood River County, Oregon","docAbstract":"The Dog River and northern part of the Badger Lake 7.5' quadrangles encompasses an area of ~201 km2 (77.6 mi2) of the High Cascades of north-central Oregon, lying across the eastern slopes of Mount Hood volcano (Figure 1-1; Plate 1; referred to herein as Dog River–Badger Lake area). Mount Hood, known as Wy’east to Native Americans, is Oregon’s tallest peak (3,427 m [11,241 ft]). The volcano has erupted episodically for the past 500,000 years, experiencing two major eruptive periods during the last 1,500 years (Scott and others, 1997a; Scott and others, 2003; Scott and Gardner, 2017). Cascade Range volcanism and structural development in the area dates back longer, with eruptive activity dating from latest Miocene to recent time; part of that volcano-tectonic record is detailed by new high-resolution geologic mapping presented here.
The geology of the Dog River–Badger Lake area was mapped by the Oregon Department of Geology and Mineral Industries (DOGAMI) between 2017 and 2020, in collaboration with geoscientists from the U. S. Geological Survey Cascade Volcano Observatory (USGS CVO) and Hamilton College, New York. The primary objective of this investigation is to provide an updated and spatially accurate geologic framework for the Dog River–Badger Lake area as part of a multi-year study of the geology of the larger Middle Columbia Basin (Figure 1-1, Figure 1-2). Additional key objectives of this project are to: 1) determine the geologic history of volcanic rocks in this part of the northern Oregon Cascade Range, including lava flows and volcaniclastic deposits erupted from Middle Pleistocene to Holocene Mount Hood volcano; 2) provide significant new details about the structure and fault history along the northern segment of the High Cascades intra-arc graben (Hood River graben); and 3) better understand geologic hazards in the region, related to earthquakes, volcanoes, and landslides. New detailed geologic data presented here also provides a basis for future geologic, geohydrologic, and geohazard studies in the greater Middle Columbia Basin. Detailed geologic mapping in this part of the Middle Columbia Basin is a high priority of the Oregon Geologic Map Advisory Committee (OGMAC), supported in part by grants from the STATEMAP component of the USGS National Cooperative Geologic Mapping Program (G17AC00210, G19AC00160). Additional funds were provided by the State of Oregon.
The core products of this study are this report, an accompanying geologic map and cross sections (Plate 1), an Esri ArcGIS™ geodatabase, and Microsoft Excel® spreadsheets tabulating point data for geochemistry, geochronology, magnetic polarity, orientation points, and well data. The geodatabase presents the new geologic mapping in a digital format consistent with the USGS National Cooperative Geologic Mapping Program Geologic Map Schema (GeMS) (U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020). This geodatabase contains spatial information, including geologic polygons, contacts, structures, geochemistry, geochronology, magnetic observation, orientation points, and well data, as well as data about each geologic unit such as age, lithology, mineralogy, and structure. Digitization at scales of 1:8,000 or better was accomplished using a combination of high-resolution lidar topography and imagery. Surficial and bedrock geologic units contained in the geodatabase are depicted on the Plate 1 at a scale of 1:24,000. Both the geodatabase and geologic map are supported by this report describing the geology in detail.
","language":"English","publisher":"Oregon Department of Geology and Mineral Industries","usgsCitation":"McClaughry, J.D., Scott, W., Duda, C.J., and Conrey, R.M., 2020, Geologic map of the Dog River and northern part of the Badger Lake 7.5′ quadrangles, Hood River County, Oregon: Geological Map 126, Report: 154 p.; 1 Plate 48 x 52 inches; Database; Metadata.","productDescription":"Report: 154 p.; 1 Plate 48 x 52 inches; Database; Metadata","ipdsId":"IP-126371","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":385093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383245,"type":{"id":15,"text":"Index Page"},"url":"https://www.oregongeology.org/pubs/gms/p-GMS-126.htm"}],"scale":"24000","country":"United States","state":"Oregon","county":"Hood River County","otherGeospatial":"Dog River and Northern Part of the Badger Lake 7.5' Quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.87683105468749,\n 44.97839955494438\n ],\n [\n -120.5914306640625,\n 44.97839955494438\n ],\n [\n -120.5914306640625,\n 45.73494252455993\n ],\n [\n -121.87683105468749,\n 45.73494252455993\n ],\n [\n -121.87683105468749,\n 44.97839955494438\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McClaughry, Jason D.","contributorId":194544,"corporation":false,"usgs":false,"family":"McClaughry","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":810242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, William E. 0000-0001-8156-979X","orcid":"https://orcid.org/0000-0001-8156-979X","contributorId":250706,"corporation":false,"usgs":true,"family":"Scott","given":"William E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, Carlie J. M.","contributorId":250707,"corporation":false,"usgs":false,"family":"Duda","given":"Carlie","email":"","middleInitial":"J. M.","affiliations":[{"id":32397,"text":"Oregon Department of Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":810244,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrey, Richard M.","contributorId":194345,"corporation":false,"usgs":false,"family":"Conrey","given":"Richard","email":"","middleInitial":"M.","affiliations":[{"id":13203,"text":"School of the Environment, Washington State University","active":true,"usgs":false}],"preferred":false,"id":810245,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229205,"text":"70229205 - 2020 - Reconnaissance map of the Cenozoic geology in the Carlin basin area, Elko and Eureka counties, Nevada","interactions":[],"lastModifiedDate":"2022-03-03T14:38:55.904902","indexId":"70229205","displayToPublicDate":"2020-12-31T08:27:42","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":10147,"text":"Nevada Bureau of Mines and Geology Open File Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"2020-02","title":"Reconnaissance map of the Cenozoic geology in the Carlin basin area, Elko and Eureka counties, Nevada","docAbstract":"The current map publication was supported by the USGS National Cooperative Geologic Mapping Program under STATEMAP award number G19AC00383.
Arey Lagoon, located in eastern Arctic Alaska, supports a highly productive ecosystem, where soft substrate and coastal wet sedge fringing the shores are feeding grounds and nurseries for a variety of marine fish and waterfowl. The lagoon is partially protected from the direct onslaught of Arctic Ocean waves by a barrier island chain (Arey Island) which in itself provides important habitat for migratory shorebirds and waterfowl. In this work, numerically modeled waves and water levels are computed under the provision of sea-level rise and changing conditions brought about by 21st century climate variability. Model results, supported by observations, are used to assess the stability of the barrier chain and spatiotemporal changes in flood patterns across fringing coastal wet sedge areas. The results aim to support studies that investigate the possibility of new biological succession trajectories and loss or increase of habitat areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201142","collaboration":"Prepared in cooperation with and funded in part by the Arctic Landscape Conservation Cooperation (ALCC)","usgsCitation":"Erikson, L.H., Gibbs, A.E., Richmond, B.M., Storlazzi, C.D., Jones, B.M., and Ohman, K.A., 2020, Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska: U.S. Geological Survey Open-File Report 2020–1142, 68, p., https://doi.org/10.3133/ofr20201142.","productDescription":"Report: x, 68 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-079323","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":381735,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LGYO2Q","text":"USGS data release","linkHelpText":"Modeled 21st century storm surge, waves, and coastal flood hazards and supporting oceanographic and geological field data (2010 and 2011) for Arey and Barter Islands, Alaska and vicinity"},{"id":381739,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1142/coverthb.jpg"},{"id":381740,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1142/ofr20201142.pdf","text":"Report","size":"8.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1142"}],"country":"United States","state":"Alaska","otherGeospatial":"Arey Island and Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -144.09805297851562,\n 70.03559723423488\n ],\n [\n -143.6407470703125,\n 70.03559723423488\n ],\n [\n -143.6407470703125,\n 70.13476515043729\n ],\n [\n -144.09805297851562,\n 70.13476515043729\n ],\n [\n -144.09805297851562,\n 70.03559723423488\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Stewart B. McKinney National Wildlife Refuge in Connecticut. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of two marsh management units within the refuge and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $1,190,000, but that further expenditures may yield diminishing return on investment. Management actions in optimal portfolios at total costs less than $1,190,000 included controlling avian predators in both management units, managing stormwater on lands adjacent to one marsh management unit, and removing a tide gate and breaching a dike to improve tidal flow in the other marsh management unit. The management benefits were derived from expected increases in the numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds, and an expected decrease in the use of herbicides to control invasive vegetation. The prototype presented here provides a framework for decision making at the Stewart B. McKinney National Wildlife Refuge that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201139","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Low, L.E. , Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Vagos, K., and Potvin, R., 2020, Optimization of salt marsh management at the Stewart B. McKinney National Wildlife Refuge, Connecticut, through use of structured decision making: U.S. Geological Survey Open-File Report 2020–1139, 28 p., https://doi.org/10.3133/ofr20201139.","productDescription":"vi, 28 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120812","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":381645,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1139/ofr20201139.pdf","text":"Report","size":"2.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1139"},{"id":381644,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1139/coverthb.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Stewart B. McKinney National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.17169189453125,\n 41.15022321163024\n ],\n [\n -73.13186645507812,\n 41.13677892209895\n ],\n [\n -73.10028076171875,\n 41.14867208811923\n ],\n [\n -73.15177917480469,\n 41.18537216794189\n ],\n [\n -73.18113327026366,\n 41.17090135180691\n ],\n [\n -73.17169189453125,\n 41.15022321163024\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708–4039
The bedrock geology of the 7.5- by 15-minute Springfield quadrangle consists of highly deformed and metamorphosed Mesoproterozoic through Devonian metasedimentary and meta-igneous rocks. In the west, Mesoproterozoic gneisses of the Mount Holly Complex are the oldest rocks and form the eastern side of the Chester dome. The Moretown slice structurally overlies the Chester dome along the Keyes Mountain thrust fault which represents the Ordovician Taconic suture (Red Indian Line) between Laurentian and Ganderian crust. The allochthonous Cambrian through Ordovician Moretown slice includes the Moretown and Cram Hill Formations and the North River Igneous Suite. Silurian and Devonian metasedimentary and metavolcanic rocks of the Connecticut Valley trough (CVT) unconformably overlie the Moretown slice. Ordovician to Silurian and Devonian metasedimentary and meta-igneous rocks of the New Hampshire sequence structurally overlie the CVT along the Devonian, Acadian Monroe thrust fault. The oldest part of the New Hampshire sequence consists of Ordovician metamorphosed volcanic, plutonic, and sedimentary rocks of the Bronson Hill arc including the Ammonoosuc Volcanics, the Partridge Formation, and the Oliverian Plutonic Suite. The Ammonoosuc Volcanics are the base of the exposed arc section in the map area. The Bronson Hill arc rocks are exposed in fault-bounded structural belts, including the Monroe thrust sheet, the Claremont belt, the Sugar River and Unity domes, and the footwall of the Brennan Hill thrust fault. Silurian to Devonian metasedimentary rocks of the Clough Quartzite, and Fitch and Littleton Formations unconformably overlie the Bronson Hill arc rocks. Devonian granitic and pegmatitic dikes and sills of the New Hampshire Plutonic Suite intruded previously deformed rocks.
Devonian, Acadian F1 fold nappes have a sheath fold geometry and are truncated by multiple generations of faults. The Bronson Hill arc structurally overlies the CVT along the Acadian Monroe fault with preserved tectonic mélange in the footwall. Upright dome-stage F2 folds post-date amphibolite facies metamorphism and locally developed into sheath folds in high-strain zones. F3 folds exhibit sinistral rotation associated with Alleghanian lower-greenschist facies faults. Late Paleozoic Alleghanian to Mesozoic shear zones transpose stratigraphy, early structures, and peak metamorphic isograds. 40Ar/39Ar white-mica growth ages (300–250 million years before present [Ma]) indicate that retrograde deformation continued into the latest Paleozoic and earliest Mesozoic. Apatite fission track data show that brittle faults were active prior to about 100 Ma and experienced Late Cretaceous and even Paleocene re-activation.
The bedrock geology was mapped to study the tectonic history of the area and to provide a framework for ongoing characterization of the bedrock of Vermont and New Hampshire. This Scientific Investigations Map of the Springfield 7.5- x 15-minute quadrangle consists of sheets 1 and 2 as well as a geographic information system (GIS) database that includes bedrock geologic units, faults, outcrops, and structural geologic information. Sheet 1 of the report includes a bedrock geologic map, a correlation of map units, and a description of map units. Sheet 2 includes a discussion of the geology, references cited, two cross sections from the geologic map on sheet 1, a tectonic map showing major structural features, and a structural domain map showing the orientation of brittle features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3462","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey; and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Walsh, G.J., Valley, P.M., Armstrong, T.R., Ratcliffe, N.M., Merschat, A.J., and Gentry, B.J., 2020, Bedrock geologic map of the Springfield 7.5- x 15-minute quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire (ver. 1.1, June 2024): U.S. Geological Survey Scientific Investigations Map 3462, 2 sheets, scale 1:24,000, https://doi.org/10.3133/sim3462.","productDescription":"2 Sheets: 62.78 x 40.79 inches and 48.00 x 41.00 inches; Base Map; Metadata; Database; Read Me; Companion File","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091203","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":499273,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_110835.htm","linkFileType":{"id":5,"text":"html"}},{"id":429409,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3462/versionHist.txt","size":"715 B","linkFileType":{"id":2,"text":"txt"}},{"id":381115,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_openaccess.zip","text":"Open Access","size":"5.06 MB","linkFileType":{"id":6,"text":"zip"}},{"id":381114,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_basemap.zip","text":"Base Map","size":"84.1 MB","linkFileType":{"id":6,"text":"zip"}},{"id":381111,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_readme.txt","size":"11.8 KB","linkFileType":{"id":2,"text":"txt"}},{"id":381110,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_sheet2.pdf","text":"Sheet 2","size":"7.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3462"},{"id":381108,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3462/coverthb.jpg"},{"id":381113,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_metadata.zip","size":"445 KB","linkFileType":{"id":6,"text":"zip"}},{"id":381109,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_sheet1.pdf","text":"Sheet 1","size":"23.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3462"},{"id":381112,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_database.zip","size":"5.38 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"New Hampshire, Vermont","county":"Sullivan County, Windsor County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.5,\n 43.25\n ],\n [\n -72.25,\n 43.25\n ],\n [\n -72.25,\n 43.375\n ],\n [\n -72.5,\n 43.375\n ],\n [\n -72.5,\n 43.25\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 22, 2020; Version 1.1: June 4, 2024","contact":"Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Hanford, Washington (USA) is the construction site of a multi-billion-dollar high-level nuclear waste treatment facility. This site lies 200 kilometers (km) east of Mount St. Helens (MSH), the most active volcano in the contiguous United States. Tephra from a future MSH eruption could pose a hazard to the air intake and filtration systems at this plant. In this report, we present a probabilistic estimate of the amount of tephra that could fall, and the concentrations of airborne ash that could occur at the Hanford Site during a future eruption. Mount St. Helens has produced four large explosive eruptions in approximately the past 500 years, suggesting that its annual probability of eruption (P1) is roughly 4/500=0.008. Assuming that a large eruption occurs, we calculate the probability (P3|1) of a given fall deposit thickness or airborne concentration at Hanford by running about 10,000 simulations of ash-producing eruptions using the atmospheric transport model Ash3d. In each simulation, we calculate the pattern of tephra dispersal, deposit thickness at Hanford, and airborne ash concentration at ground level. As input for each simulation, we choose meteorological conditions from a randomly chosen time in the historical record between 1980 and 2010, using data from the European Centre for Medium-Range Weather Forecasting (ECMWF) Reanalysis (ERA) Interim model. The volume (dense-rock equivalent) of each simulated eruption is randomly chosen from a uniform probability distribution on a log scale from the range of magma volumes (0.008–2.3 cubic kilometers [km3]) estimated for late Holocene eruptions at MSH. Plume heights and durations of each eruption are chosen using empirical correlations between volume, height, and eruption rate, which account for the fact that larger eruptions have higher plumes and last longer. We construct summary tables of final deposit thickness (T), maximum ground-level airborne concentration (Cmax), and average ground-level airborne concentration (Cavg) during tephra-fall for each run. Each table is sorted and ranked by decreasing value of T, Cmax, or Cavg. Conditional probabilities (P3|1) are derived by dividing rank by n+1, where n is the total number of successful runs. For example, a deposit thickness of 5.10 centimeters (cm) from run 446 is ranked 123 of 9,785 successful runs, yielding P3|1=123/9,786=0.01257. Its annual probability is P=P1·P3|1=0.008×0.01257=0.000101. By interpolation, the deposit thickness (T10k) having an annual probability of 1 in 10,000 (P= 0.0001) is 5.11 cm. Analogous concentration values are Cmax,10k=3,819 and Cavg,10k=1,513 milligrams per cubic meter (mg/m3), respectively. Independent calculations using the known mass accumulation rate of the deposit (=0.001–0.006 kilograms per square meter per second [kg/m2/s]), aggregate fall velocities (u=0.3–0.8 meters per second [m/s]), and the simple formula , yield similar results, although highly variable fall velocities add significant uncertainty. This formula implies that deposit accumulation rates of millimeters (mm) to greater than 1 cm per hour, which are not uncommon during heavy ash fall, are associated with airborne concentrations of 102–103 milligrams per cubic meter (mg/m3). These concentrations are much higher than published measurements (10-3–101 mg/m3), which record only suspended particles sampled in sheltered areas. During heavy ashfall, most fine ash falls as aggregates. Whether such aggregates will be ingested into air ducts will depend on the aggregate size and fall rate, the fragility of the aggregates, the air duct geometry, intake velocity, and other factors.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201133","collaboration":"Prepared in cooperation with the U.S. Department of Energy, Office of River Protection","usgsCitation":"Mastin, L.G., Van Eaton, A., and Schwaiger, H.F., 2020, A probabilistic assessment of tephra-fall hazards at Hanford, Washington, from a future eruption of Mount St. Helens: U.S. Geological Survey Open-File Report 2020–1133, 54 p., https://doi.org/10.3133/ofr20201133.","productDescription":"Report: ix, 54 p.; Data Release","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-112179","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":381546,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1133/covrthb.jpg"},{"id":381547,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1133/ofr20201133.pdf","text":"Report","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381548,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VPFXQR","linkHelpText":"Data Used to Develop A Probabilistic Assessment of Tephra-Fall Hazards at Hanford, Washington"}],"country":"United States","state":"Washington","otherGeospatial":"Hanford","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.88281249999999,\n 46.33175800051563\n ],\n [\n -119.2950439453125,\n 46.33175800051563\n ],\n [\n -119.2950439453125,\n 46.81509864599243\n ],\n [\n -119.88281249999999,\n 46.81509864599243\n ],\n [\n -119.88281249999999,\n 46.33175800051563\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, WA, 98683
In the U.S., 525,000 horseshoe crabs (Limulus polyphemus) per year have been captured during 2013–2017, brought to biomedical facilities, and bled to produce Limulus amebocyte lysate (LAL), then mostly released to the area of capture. The Atlantic States Marine Fisheries Commission estimates short-term bleeding-induced mortality to be 15% (4% to 30%), resulting in mortality of approximately 78,750 horseshoe crabs annually in recent years comprising a minor portion (<13%) of the up to one million annual coastwide landings dominated by harvest for bait. However, the long-term effect of bleeding for LAL on annual survival and spawning behavior is unknown; thus, results from short-term studies alone might underestimate bleeding effects at the population level. To address this knowledge gap, we analyzed data from the U.S. Fish and Wildlife horseshoe crab tagging database to estimate the differences in survival and recapture rates of bled and not bled horseshoe crabs tagged in the same years and geographic area. Contrary to expectation, survival was not lower for bled crabs compared to unbled crabs. Differences varied, but survival estimates tended to be higher for bled crabs than for unbled crabs. However, biomedical culling and selection for younger or healthier animals could have resulted in biomedically tagged individuals representing a healthier subset of the overall population with subsequent higher survival. Furthermore, the tagging analysis revealed a post-bleeding reduction in capture probability, which could indicate decreased spawning activity, evident in males more than females. Continued tagging of bled and unbled crabs in the same geographic area while recording age class and sex will contribute to the further resolution of LAL production’s effect on horseshoe crab populations.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2020.607668","usgsCitation":"Smith, D.R., Newhard, J., McGowan, C.P., and Butler, C.A., 2020, The Long-term effect of bleeding for Limulus amebocyte lysate on annual survival and recapture of tagged horseshoe crabs: Frontiers in Marine Science, v. 7, 607668, 13 p., https://doi.org/10.3389/fmars.2020.607668.","productDescription":"607668, 13 p.","ipdsId":"IP-115044","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":454627,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2020.607668","text":"Publisher Index Page"},{"id":388481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, Virginia","otherGeospatial":"Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.69580078125,\n 37.09900294387622\n ],\n [\n -75.08056640625,\n 37.97018468810549\n ],\n [\n -74.6630859375,\n 38.496593518947584\n ],\n [\n -74.92675781249999,\n 38.950865400919994\n ],\n [\n -74.8828125,\n 39.172658670429946\n ],\n [\n -75.509033203125,\n 39.46164364205549\n ],\n [\n -75.421142578125,\n 39.257778150283364\n ],\n [\n -75.30029296875,\n 38.89958342598271\n ],\n [\n -75.12451171875,\n 38.685509760012\n ],\n [\n -75.146484375,\n 38.53097889440024\n ],\n [\n -75.135498046875,\n 38.272688535980976\n ],\n [\n -75.30029296875,\n 38.151837403006766\n ],\n [\n -75.7177734375,\n 37.55328764595765\n ],\n [\n -75.89355468749999,\n 37.274052809979054\n ],\n [\n -75.69580078125,\n 37.09900294387622\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":821862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newhard, Joshua","contributorId":264675,"corporation":false,"usgs":false,"family":"Newhard","given":"Joshua","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":821863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":821864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butler, C. Alyssa","contributorId":264748,"corporation":false,"usgs":false,"family":"Butler","given":"C.","email":"","middleInitial":"Alyssa","affiliations":[],"preferred":false,"id":821933,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223486,"text":"70223486 - 2020 - Estimating the invasion extent of Asian swamp eel (Monopterus: Synbranchidae) in an altered river of the south-eastern United States","interactions":[],"lastModifiedDate":"2021-08-30T13:25:27.947909","indexId":"70223486","displayToPublicDate":"2020-12-18T08:21:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2681,"text":"Marine and Freshwater Research","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the invasion extent of Asian swamp eel (Monopterus: Synbranchidae) in an altered river of the south-eastern United States","docAbstract":"The first reported invasion of Asian swamp eels (Monopterus albus, ASE) in the continental United States was in the state of Georgia in 1994. This population was first discovered within several ponds on a private nature centre, but the ponds drained via an outflow pipe into marsh habitats along the Chattahoochee River. Our objective was to delineate the current invasion extent of ASE in the Chattahoochee River, Georgia, by sampling juvenile ASE within an occupancy modelling framework. We sampled 111 and 100 sites in 2015 and 2016 respectively, on 10 occasions, each within a 2-km radius of the purported invasion point to estimate the spatial extent of their invasion in this system. Leaf-litter traps (LLTs) were effective at documenting an increase in the invasion extent of ASE, from within 100 m of the Chattahoochee Nature Center pond outflow to 1.6 km away. Documenting the extent of invasion of this population has proven elusive in the past, but the use of LLTs to target juvenile eels has documented a larger invasion extent than previously known in the study system. The results of this research can be used to develop effective control and management strategies, such as locating potential breeding areas for targeted removal sampling.
Hinkley Valley, in the central to western Mojave Desert of southeastern California, has a long historical record owing to its position as a crossroads for rail and road traffic and its position adjacent to the Mojave River. Subflow in the Mojave River provided groundwater recharge that maintained water consumption and demand by way of shallow wells for local agriculture in the valley. Its crossroads position led to construction of several power-transmission lines, pipeline, and communications cable routes that transect Hinkley Valley. One of these, a natural gas pipeline and its associated compressor station, was the locus of hexavalent chromium, Cr(VI), released into, and consequent contamination of, groundwater. Understanding the movement and fate of the contaminants is a complex hydrologic and geochemical problem. Geologic mapping of the Hinkley Valley area provides framework elements for use in resolving this problem. This report provides new information on surface and subsurface geology to better constrain the origin and geometry of hydrologically important deposits in the Hinkley Valley area and describes youthful faults that may control sediment distribution and groundwater flow. The geologic map (sheet 1) presents substantial new information on surficial geology, including Pliocene deposits, but does not contain significant new work on bedrock. Bedrock investigations were specific to identifying youthful faults and representative outcrops for rocks that were penetrated by boreholes in the valley. Special attention was placed on locating and describing youthful faults. In addition, we analyzed gravity data to (1) map horizontal gradients that we interpret to reflect long-term fault traces and to (2) estimate the depth to bedrock, which is defined as Miocene and older intrusive and metamorphic rocks for the purposes of this report. The subsurface geology of Hinkley Valley was investigated by examining borehole sediment cores and rock encountered at the base of the sediment section. We analyzed the core to determine depositional environments, provenance, and age of the sediment that infilled the valley. Valleys, mountains, and basins in the Hinkley Valley area are topographically complex and incompletely named. The nearly flat floored Hinkley Valley slopes gently northward. It is framed by Mount General and the informally named “Hinkley hills” (southeast of Mount General) on the northeast and by Iron Mountain and Lynx Cat Mountain on the southwest, although breaks in the western mountains allow stream connections between Hinkley Valley and another valley to the west that is herein referred to as Hawes valley. At its south end, Hinkley Valley is traversed by the entrenched Mojave River, which passes east out of the valley past Barstow. North of Hinkley Valley, a few low hills (including Red Hill) separate the valley from a broad west-sloping piedmont that is part of the physiographic Harper Basin (of which the Harper Lake playa is the center). The lower part of this piedmont, however, is referred to as Water Valley, although it is not a distinct valley. The name derives from groundwater sourced from subflow in the Mojave River, which caused shallow water and even artesian flow in Water Valley but not in other parts of the Harper Basin. When water filled the Harper Basin to form Pleistocene Lake Harper it not only submerged Water Valley but also northern Hinkley Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3458","collaboration":"Prepared in cooperation with the Lahontan Regional Water Quality Control Board and the State Water Resources Control Board","usgsCitation":"Miller, D.M., Langenheim, V.E., and Haddon, E.K., 2020, Geologic map and borehole stratigraphy of Hinkley Valley and vicinity, San Bernardino County, California: U.S. Geological Survey Scientific Investigations Map 3458, pamphlet 23 p., 2 sheets, scale 1:24,000, https://doi.org/10.3133/sim3458.","productDescription":"Pamphlet,: iv, 23 p.; 2 Sheets ; 2 Tables; Database; Data Release; Metadata","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102109","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":381271,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_sheet2.pdf","text":"Sheet 2","size":"32 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381270,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_sheet1.pdf","text":"Sheet 1","size":"40 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381269,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_database.zip","text":"Database","size":"7.5 MB","linkFileType":{"id":6,"text":"zip"}},{"id":381268,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_base.zip","text":"Base","size":"1.25 GB","linkFileType":{"id":6,"text":"zip"}},{"id":381267,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_metadata.txt","size":"10 KB","linkFileType":{"id":2,"text":"txt"}},{"id":381266,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_pamphlet.pdf","text":"Pamphlet","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381451,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FV5LG5","linkHelpText":"Gravity data of the Hinkley area, southern California"},{"id":381273,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_table_7.xlsx","text":"Table 7","size":"60 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":381265,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3458/covrthb.jpg"},{"id":381272,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_table_3.xlsx","text":"Table 3","size":"20 KB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","state":"California","county":"San Bernadino County","otherGeospatial":"Hinkley Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.26257324218749,\n 34.80647431931937\n ],\n [\n -117.06619262695312,\n 34.80647431931937\n ],\n [\n -117.06619262695312,\n 35.060352812431496\n ],\n [\n -117.26257324218749,\n 35.060352812431496\n ],\n [\n -117.26257324218749,\n 34.80647431931937\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
A three-dimensional groundwater-flow model was developed for the aquifer system of Long Island, New York, to evaluate (1) responses of the hydrologic system to changes in natural and anthropogenic hydraulic stresses, (2) the subsurface distribution of groundwater age, and (3) the regional-scale distribution of groundwater travel times and the source of water to fresh surface waters and coastal receiving waters. The model also provides the groundwater flow components used to define model boundaries for possible inset models used for local-scale analyses.
The three-dimensional, groundwater flow model developed for this investigation uses the numerical code MODFLOW–NWT to represent steady-state conditions for average groundwater pumping and aquifer recharge for 2005–15. The particle-tracking algorithm MODPATH, which simulates advective transport in the aquifer, was used to estimate groundwater age, delineate the areas at the water table that contribute recharge to coastal and freshwater bodies, and estimate total travel times of water from the water table to discharge locations.
A three-dimensional, 1-meter (3.3-foot) topobathymetric model was used to determine land-surface altitudes for the island and seabed altitudes for the surrounding coastal waters. The mapped extents and surface altitudes of major geologic units were compiled and used to develop a three-dimensional hydrogeologic framework of the aquifer system, including aquifers and confining units. Lithologic data from deep boreholes and previous aquifer-test results were used to estimate the three-dimensional distribution of hydraulic conductivity in principal aquifers. Natural recharge from precipitation was estimated for 2005–15 using a modified Thornthwaite-Mather methodology as implemented in a soil-water balance model. Components of anthropogenic recharge—wastewater return flow, storm water inflow, and inflow from leaky infrastructure—also were estimated for 2005–15. Groundwater withdrawals for various sources, including public water supply, industrial, remediation, and agricultural, were compiled or estimated for the same period.
These data were incorporated into the model development to represent the aquifer system geometry, boundaries, and initial hydraulic properties of the regional aquifers and confining units within the Long Island aquifer system. Average hydraulic conditions—water levels and streamflows—for 2005–15 were estimated using existing data from the U.S. Geological Survey National Water Information System database. Model inputs were adjusted to best match average hydrologic conditions using inverse methods as implemented in the parameter-estimating software PEST. The calibrated model was used to simulate average hydrologic conditions in the aquifer system for 2005–15.
About 656 cubic feet per second of water was withdrawn on average annually for 2005–15 for water supply and an average of about 349 cubic feet per second of water recharged the aquifer annually from return flow and leaky infrastructure. Parts of New York City have drawdowns exceeding 25 feet, mostly because of urbanization and associated large decreases in recharge rates. Large areas in the western part of the island have drawdowns exceeding 10 feet, mostly from large groundwater withdrawals and sewering, which largely eliminates wastewater return flow. Water-table altitudes in eastern parts of the island increased by more than 2 feet in some areas as a result of wastewater return flow in unsewered areas and changes in land use. Changes in streamflows show a similar pattern as water-table altitudes. Streamflows generally decrease in western parts of the island where there are large drawdowns and increase in eastern parts of the island where water-table altitudes increase.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205091","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Walter, D.A., Masterson, J.P., Finkelstein, J.S., Monti, J., Jr., Misut, P.E., and Fienen, M.N., 2020, Simulation of groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15: U.S. Geological Survey Scientific Investigations Report 2020–5091, 75 p., https://doi.org/10.3133/sir20205091.","productDescription":"Report: ix, 75 p.; 3 Data Releases","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-112206","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":381521,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5091/images/"},{"id":381195,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5091/sir20205091.pdf","text":"Report","size":"35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5091"},{"id":381194,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5091/coverthb2.jpg"},{"id":381192,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P954DLLC","text":"USGS data release","linkHelpText":"Aquifer texture data describing the Long Island aquifer system"},{"id":381191,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KWQSEJ","text":"USGS data release","linkHelpText":"MODFLOW–NWT and MODPATH6 used to simulate groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15"},{"id":381190,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90B6OTX","text":"USGS data release","linkHelpText":"Time domain electromagnetic surveys collected to estimate the extent of saltwater intrusion in Nassau and Queens Counties, New York, October-November 2017"},{"id":381520,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5091/sir20205091.XML"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.102783203125,\n 40.55554790286311\n ],\n [\n -73.7017822265625,\n 40.49709237269567\n ],\n [\n -72.8778076171875,\n 40.65147128144057\n ],\n [\n -72.037353515625,\n 40.91351257612758\n ],\n [\n -71.6143798828125,\n 41.16211393939692\n ],\n [\n -71.9384765625,\n 41.178653972331674\n ],\n [\n -72.191162109375,\n 41.236511201246216\n ],\n [\n -72.65808105468749,\n 41.11660732012896\n ],\n [\n -73.4490966796875,\n 40.967455873296714\n ],\n [\n -73.751220703125,\n 40.89275342420696\n ],\n [\n -74.0203857421875,\n 40.718119379753446\n ],\n [\n -74.102783203125,\n 40.55554790286311\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Subduction zones drive plate tectonics on Earth, yet subduction initiation and the related upper plate depositional and structural kinematics remain poorly understood because upper plate records are rare and often strongly overprinted by magmatism and deformation. During the late Paleozoic time, Laurentia’s western margin was truncated by a sinistral strike-slip fault that transformed into a subduction zone. Thick Permian strata in the Inyo Mountains of central-eastern California record this transition. Two basins that were separated by a transpressional antiform contain sedimentary lithofacies that record distinct patterns of shoaling and deepening conditions before and during tectonism associated with subduction initiation. Sandstone petrography and lithofacies analysis show that rocks in a southeastern basin are dominated by carbonate grains derived from adjacent carbonate shelves, whereas sandstones in a northwestern basin are predominantly quartzose with likely derivation from distant ergs or underlying strata. Detrital zircon spectra from all but the youngest strata in both basins are typical of Laurentian continent spectra with prominent peaks that indicate ultimate sources in Appalachia, Grenville, Yavapai/Mazatzal, and the Wyoming or Superior cratons. The first Cordilleran arc-derived detrital zircon grains appear in the uppermost strata of the northwestern basin and record Late Permian (ca. 260 Ma) Cordilleran arc magmatism at this approximate latitude, and a possible source area is suggested by geochemical similarities between these detrital zircons and broadly coeval magmatic zircons in the El Paso Mountains to the southwest. Deformation responsible for basin partitioning is consistent with sinistrally oblique contraction in the earliest Permian time. The data presented from the Inyo Mountains shed more light on the nature of Cordilleran subduction initiation and the upper-crustal response to this transition.
Biological conservation is a fundamental purpose of the National Park system, and Catoctin Mountain Park (CATO) supports high-quality habitat for native fishes in the headwaters of the Chesapeake Bay watershed in eastern North America. However, native Blue Ridge sculpin (Cottus caeruleomentum) have been extirpated in Big Hunting Creek above Cunningham Falls in CATO. Prior research indicates that infection by the fungal-like protist Dermocystidium is a likely cause for the extirpation, but elevated stream temperatures also have been observed in the study area, and it remains unknown whether thermal stress may exacerbate infections or otherwise limit habitat suitability for fishes in CATO.
The purpose of this study was to quantify spatial variation in summer stream temperatures and to evaluate the effects of temperature on sculpin growth rates and susceptibility to Dermocystidium infection. We used observational and experimental methods to address these objectives. First, we deployed stream temperature gages at 10 sites throughout the study area to assess hourly and daily temperatures during the summer of 2019. Second, we conducted an in situ fish enclosure experiment at five of the temperature sites to assess fish growth and susceptibility to Dermocystidium infection over a 45-day exposure period. For this experiment we collected sculpin from a stream in CATO that supports a robust population of Blue Ridge sculpin (Owens Creek) and held them in quarantine for 50 days in the Experimental Stream Laboratory at the U.S. Geological Survey (USGS) Leetown Science Center. Pre-exposure histopathology confirmed the absence of Dermocystidium infection prior to the introduction of fish into experimental enclosures.
We found that stream temperatures were warmer where sculpin have been extirpated than elsewhere in CATO where sculpin persist. However, the fish enclosure experiment revealed a positive effect of temperature on fish growth, suggesting that increased food availability and foraging rates compensated for increased metabolic demands in the warmest sites. Moreover, fish held in enclosures did not develop Dermocystidium infection. Our results therefore suggest that current environmental conditions in upper Big Hunting Creek may be suitable for Blue Ridge sculpin reintroduction, and this could ultimately lead to sportfishing opportunities by increasing the forage base for native brook trout (Salvelinus fontinalis).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201137","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Hitt, N.P., Kessler, K.G., Kelly, Z.A., Rogers, K.M., Macmillan, H.E., and Walsh, H.L., 2020, Assessing native fish restoration potential in Catoctin Mountain Park: U.S. Geological Survey Open-File Report 2020–1137, 17 p., https://doi.org/10.3133/ofr20201137.","productDescription":"Report: vii, 17 p.; Data Release","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-122955","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":381222,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P950A13P","text":"USGS data release","linkHelpText":"Stream temperature and sculpin growth data collected from Catoctin Mountain Park in 2019"},{"id":381221,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1137/ofr20201137.pdf","text":"Report","size":"4.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1137"},{"id":381220,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1137/coverthb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Catoctin Mountain Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.51781463623047,\n 39.60621720230201\n ],\n [\n -77.38151550292969,\n 39.60621720230201\n ],\n [\n -77.38151550292969,\n 39.70137566512028\n ],\n [\n -77.51781463623047,\n 39.70137566512028\n ],\n [\n -77.51781463623047,\n 39.60621720230201\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
White-nose syndrome (WNS) is an emerging infectious disease of hibernating bats caused by a fungus previously known as Geomyces destructans and reclassified as Pseudogymnoascus destructans. The disease was first documented in 2006 in New York, has since spread across much of eastern North America, and as of January 2012, had caused the death of at least 5.7 to 6.7 million bats. Previous studies have suggested that environmental conditions play a strong role in WNS mortality. However, to predict where and when the disease will spread to new sites is difficult because detailed site information and associated environmental data are notably sparse. This paper presents a chronology of where and when WNS was detected in North America before October 2011 and indicates who reported the infections. This paper also presents available data on WNS-infected site elevation, geology, sediment chemistry and biota, air temperature, and relative humidity.
By the end of September 2011, at least 241 known WNS-infected sites were in North America and the number of infected sites per winter season had increased each year since 2006. The progressive increase in the number of infected sites per winter season suggests that the number of WNS infections had not peaked as of the 2010–11 winter season. WNS-infected sites include caves and mines, but the sites are not restricted by elevation, lithology, or strata age. Available data on site sediment chemistry are sparse but present a wide range of values, suggesting that caves and mines may contain a great range of microenvironments that are still poorly understood. The distribution of WNS may be restricted by air temperature and relative humidity. Published air temperature values from WNS-infected sites range from −15 to 33 degrees Celsius (but most temperature values are less than 20 degrees Celsius), and relative humidity values range from 50 to 100 percent. The spread of WNS may be restricted by a cave or mine temperature threshold of 20 degrees Celsius (which is likely to be south of most of the continental United States) and by some yet to be determined threshold of low relative humidity. These results indicate that WNS may not spread south into Mexico or to Puerto Rico.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201117","usgsCitation":"Swezey, C.S., and Garrity, C.P., 2020, Environmental data associated with sites infected with white-nose syndrome (WNS) before October 2011 in North America: U.S. Geological Survey Open-File Report 2020–1117, 67 p., https://doi.org/10.3133/ofr20201117.","productDescription":"x, 67 p.","numberOfPages":"67","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-117667","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":381184,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1117/coverthb.jpg"},{"id":381185,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1117/ofr20201117.pdf","text":"Report","size":"19.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1117"}],"country":"Canada, United States","state":"Connecticut, Delaware, Indiana, Kentucky, Maine, Maryland, Massachsetts, Missouri, New Brunswick, New Hampshire, New Jersey, New York, North Carolina, Nova Scotia, Ohio, Oklahoma, Ontario, Pennsylvania, Quebec, Tennessee, Vermont, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.95898437499999,\n 33.797408767572485\n ],\n [\n -75.673828125,\n 35.88905007936091\n ],\n [\n -74.53125,\n 39.436192999314095\n ],\n [\n -73.65234375,\n 40.78054143186033\n ],\n [\n -70.13671875,\n 42.16340342422401\n ],\n [\n -64.775390625,\n 43.389081939117496\n ],\n [\n -59.4140625,\n 46.31658418182218\n ],\n [\n -65.390625,\n 49.724479188712984\n ],\n [\n -66.0498046875,\n 54.521081495443596\n ],\n [\n -79.4970703125,\n 54.62297813269033\n ],\n [\n -89.296875,\n 56.77680831656842\n ],\n [\n -95.44921875,\n 52.669720383688166\n ],\n [\n -95.2294921875,\n 49.03786794532644\n ],\n [\n -89.7802734375,\n 48.37084770238366\n ],\n [\n -83.935546875,\n 46.9502622421856\n ],\n [\n -81.9580078125,\n 43.70759350405294\n ],\n [\n -83.5400390625,\n 41.64007838467894\n ],\n [\n -86.8798828125,\n 41.83682786072714\n ],\n [\n -87.451171875,\n 41.57436130598913\n ],\n [\n -88.24218749999999,\n 37.47485808497102\n ],\n [\n -89.2529296875,\n 36.56260003738545\n ],\n [\n -90.04394531249999,\n 35.24561909420681\n ],\n [\n -85.5615234375,\n 34.95799531086792\n ],\n [\n -82.880859375,\n 34.994003757575776\n ],\n [\n -82.265625,\n 35.15584570226544\n ],\n [\n -81.01318359375,\n 35.08395557927643\n ],\n [\n -79.716796875,\n 34.77771580360469\n ],\n [\n -78.486328125,\n 33.815666308702774\n ],\n [\n -77.95898437499999,\n 33.797408767572485\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
New U-Pb and 40Ar/39Ar ages integrated with geologic mapping and observations across the western Alaska Range constrain the distribution and tectonic setting of Cretaceous to Oligocene magmatism along an evolving accretionary plate margin in south-central Alaska. These rocks were emplaced across basement domains that include Neoproterozoic to Jurassic carbonate and siliciclastic strata of the Farewell terrane, Triassic and Jurassic plutonic and volcanic rocks of the Peninsular terrane, and Jurassic and Cretaceous siliciclastic strata of the Kahiltna assemblage. Plutonic rocks of different ages also host economic mineralization including intrusion-related Au, porphyry Cu-Mo-Au, polymetallic veins and skarns, and peralkaline intrusion-related rare-earth elements. The oldest intrusive suites were emplaced ca. 104–80 Ma into the Peninsular terrane only prior to final accretion. Deformation of the northern Kahiltna succession and underlying Farewell terrane occurred at ca. 97 Ma, and more widespread deformation ca. 80 Ma involved south-vergent folding and thrusting of the Kahiltna assemblage that records collisional accretion of the Peninsular-Wrangellia terrane and juxtaposition of sediment wedges formed on the inboard and outboard terranes. More widespread magmatism ca. 75–55 Ma occurred in two general pulses, each having distinct styles of localized deformation. Circa 75–65 Ma plutons were emplaced in a transpressional setting and stitch the accreted Peninsular and Wrangellia terranes to the Farewell terrane. Circa 65–55 Ma magmatism occurred across the entire range and extends for more than 200 km inboard from the inferred position of the continental margin. The Paleocene plutonic suite generally reflects shallower emplacement depths relative to older suites and is associated with more abundant andesitic to rhyolitic volcanic rocks. Deformation ca. 58–56 Ma was concentrated along two high-strain zones, the most prominent of which is 1 km wide, strikes east-northeast, and accommodated dextral oblique motion. Emplacement of widespread intermediate to mafic dikes ca. 59–51 Ma occurred before a notable magmatic lull from ca. 51–44 Ma reflecting a late Paleocene to early Eocene slab window. Magmatism resumed ca. 44 Ma, recording the transition from slab window to renewed subduction that formed the Aleutian-Meshik arc to the southwest. In the western Alaska Range, Eocene magmatism included emplacement of the elongate north-south Merrill Pass pluton and large volumes of ca. 44–37 Ma andesitic flows, tuffs, and lahar deposits. Finally, a latest Eocene to Oligocene magmatic pulse involved emplacement of a compositionally variable but spatially concentrated suite of magmas ranging from gabbro to peralkaline granite ca. 35–26 Ma, followed by waning magmatism that coincided with initiation of Yakutat shallow-slab subduction. Cretaceous to Oligocene magmatism throughout the western Alaska Range collectively records terrane accretion, translation, and integration together with evolving subduction dynamics that have shaped the southern Alaska margin since the middle Mesozoic.
The northern long‐eared bat (Myotis septentrionalis) is one of the bat species most affected by white‐nose syndrome. Population declines attributed to white‐nose syndrome contributed to the species’ listing as federally threatened under the 1973 Endangered Species Act. Although one of the most abundant Myotine bats in eastern North America prior to white‐nose syndrome, little is known about northern long‐eared bats in the upper Midwest, USA. We assessed the habitat associations of the northern long‐eared bats on a regional scale using occupancy models that accounted for uncertainty in nightly detection to provide needed information on the distribution as white‐nose syndrome has recently arrived in this area. We monitored bat activity using zero‐crossing frequency‐division bat detectors for 10–15 nights at 20 detector sites at each of 3 sampling areas in Michigan, USA, and 6 sampling areas in Wisconsin, USA, stratified by mesic and xeric habitat types. We constructed northern long‐eared bat nightly detection histories for our occupancy analysis using maximum likelihood estimates from 2 commercially‐available automated identification programs: Kaleidoscope and Echoclass. We sampled for a total of 2,174 detector‐nights. Both Kaleidoscope and Echoclass identified northern long‐eared bat passes on 110 detector‐nights, whereas on 1,968 detector‐nights neither program identified a northern long‐eared bat call. Only one program or the other identified northern long‐eared bat calls on 206 detector‐nights, indicating an overall agreement rate of 35% on nights when calls were detected. We analyzed these data using an occupancy analysis accounting for the potential for false positives to assess the relationship between northern long‐eared bat presence and habitat characteristics. Our analyses indicated that the probability of a false positive at a site was low (0.015; 95% CI 0.009–0.021), and detection probability, but not occupancy, declined from 2015 to 2016 for sites in Wisconsin sampled in both years. Occupancy was positively associated with distance into the forest interior (distance from nearest road).
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1138","usgsCitation":"Hyzy, B.A., Russell, R., Silvis, A., Ford, W., Riddle, J.D., and Russell, K.R., 2020, Occupancy and detectability of northern long-eared bats in the Lake States Region: Wildlife Society Bulletin, v. 44, no. 4, p. 732-740, https://doi.org/10.1002/wsb.1138.","productDescription":"9 p.","startPage":"732","endPage":"740","ipdsId":"IP-095702","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":503728,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://zotero.org/groups/5435545/items/AGGCIIRI","text":"External Repository"},{"id":381445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.52734374999999,\n 42.53689200787315\n ],\n [\n -87.802734375,\n 42.601619944327965\n ],\n [\n -87.6708984375,\n 44.574817404670306\n ],\n [\n -87.802734375,\n 45.042478050891546\n ],\n [\n -87.03369140625,\n 45.73685954736049\n ],\n [\n -85.4736328125,\n 46.07323062540835\n ],\n [\n -85.869140625,\n 46.649436163350245\n ],\n [\n -86.7041015625,\n 46.45299704748289\n ],\n [\n -88.00048828124999,\n 46.9502622421856\n ],\n [\n -88.9453125,\n 46.965259400349275\n ],\n [\n -90.37353515625,\n 46.63435070293566\n ],\n [\n -90.98876953125,\n 46.63435070293566\n ],\n [\n -90.76904296874999,\n 46.9052455464292\n ],\n [\n -91.97753906249999,\n 46.7248003746672\n ],\n [\n -92.28515625,\n 45.321254361171476\n ],\n [\n -91.0546875,\n 44.071800467511565\n ],\n [\n -90.52734374999999,\n 42.53689200787315\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Hyzy, Brenna A.","contributorId":171457,"corporation":false,"usgs":false,"family":"Hyzy","given":"Brenna","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":806603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":806604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvis, Alexander","contributorId":171585,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","email":"","affiliations":[{"id":26923,"text":"Virginia Polytechnic Institute, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":806605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. 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Importantly distinct from the abundant and widespread eastern subspecies (Progne subis subis), the western subspecies is of particular concern to Federal forest managers. Whereas the eastern subspecies is almost entirely dependent on artificial human-provided housing, the western subspecies continues to rely on natural cavities for nesting habitat (Bettinger, 2003). Accurate estimates of the regional abundance of the western purple martin are difficult to obtain; the most recent statewide census for Oregon, conducted in 2005, estimated the population at 1,100 pairs (Western Purple Martin Working Group, 2010). Several factors, including a small population size, loss of breeding habitat, and reductions in the number of suitable nesting sites have put populations of the western purple martin at risk throughout much of the Pacific Northwest region (Rockwell, 2019).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201130","usgsCitation":"Hagar, J.C., and Branch, E.C., 2020, Western purple martin (Progne subis arboricola) occurrence on the Siuslaw National Forest, summer 2019: U.S. Geological Survey Open-File Report 2020-1130, 25 p., https://doi.org/10.3133/ofr20201130.","productDescription":"iv, 25 p.","onlineOnly":"Y","ipdsId":"IP-117452","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":380937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1130/coverthb.jpg"},{"id":380938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1130/ofr20201130.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1130"}],"country":"United States","state":"Oregon","otherGeospatial":"Siuslaw National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.14001464843749,\n 43.691707903073805\n ],\n [\n -123.42041015624999,\n 43.691707903073805\n ],\n [\n -123.42041015624999,\n 44.66865287227321\n ],\n [\n -124.14001464843749,\n 44.66865287227321\n ],\n [\n -124.14001464843749,\n 43.691707903073805\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Mercury is an environmentally ubiquitous neurotoxin, and its methylated form presents health risks to humans and other biota, primarily through dietary intake. Because methylmercury bioaccumulates and biomagnifies in living tissue, concentrations progressively increase at higher trophic positions in ecosystem food webs. Therefore, the greatest health risks are for organisms at the highest trophic positions and for humans who consume organisms such as fish from these high trophic positions. Data on environmental mercury concentrations in various media and biota provide a basis for comparison among sites and regions and for evaluating ecosystem health risks. The U.S. Geological Survey, in cooperation with the Natural Resources Department, Bad River Band of Lake Superior Chippewa, have compiled a dataset from analyses of mercury concentrations in surface water, bed sediment, fish tissue, Rana clamitans (green frog) tissue, Haliaeetus leucocephalus (bald eagle) feathers, Lontra canadensis (North American river otter) hair, Zizania palustris (northern wild rice), and litterfall from samples collected in the Bad River watershed, Wisconsin during 2004–18. These data originated from either the Natural Resources Department or another agency based on samples collected within or near to Bad River Tribal lands before transfer to the U.S. Geological Survey for compilation and analysis at the onset of the project. This report describes the compiled mercury dataset, provides comparisons to similar measurements in the region and elsewhere, and evaluates health risks to humans and to the sampled biota. Except for litterfall, data were not collected on a consistent, regular basis over a sufficient period to evaluate temporal patterns. The reported mercury concentrations are generally similar to those reported elsewhere in the upper Great Lakes region. Reported values are consistent with atmospheric deposition as the principal source and reflect a favorable environment for mercury methylation. Fish mercury concentrations increased at higher food web positions and generally increased with length in most species measured. Sander vitreus (walleye) present the greatest risk to humans among fishes considered here because of their high trophic position and associated elevated mercury concentrations in combination with relatively high walleye consumption rates by the Native American community. Methylmercury concentrations in wild rice are generally low and likely pose little health risk. Despite reports of declining atmospheric mercury deposition across eastern North America during the past decade, a downward trend in litterfall mercury deposition was not evident in samples collected during 2012–18. Limitations in this data compilation and analysis were noted due to missing information such as collection dates and site locations for some samples. Regular monitoring of mercury in litterfall and surface waters along with periodic collection of fish would enable evaluation of temporal change in the mercury cycle that might affect future risk to humans and aquatic ecosystem inhabitants.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201095","collaboration":"Prepared in cooperation with the Natural Resources Department, Bad River Band of Lake Superior Chippewa","usgsCitation":"Burns, D.A., 2020, Compilation of mercury data and associated risk to human and ecosystem health, Bad River Band of Lake Superior Chippewa, Wisconsin (ver 1.1, December 2020): U.S. Geological Survey Open-File Report 2020–1095, 19 p., https://doi.org/10.3133/ofr20201095.","productDescription":"Report: vii, 19 p.; Database; Data Release","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-110861","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":377882,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- USGS water data for the Nation"},{"id":377880,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1095/ofr20201095.pdf","text":"Report","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1095"},{"id":377879,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1095/coverthb2.jpg"},{"id":377881,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HRS2C3","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Mercury data from the Bad River Watershed, Wisconsin, 2004–2018"},{"id":380931,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1095/versionHist.txt","size":"448 B","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"Wisconsin","otherGeospatial":"Bad River Tribal Lands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.48751831054686,\n 46.54658317951774\n ],\n [\n -90.4779052734375,\n 46.57868671298067\n ],\n [\n -90.51223754882812,\n 46.599449464868584\n ],\n [\n -90.59600830078125,\n 46.63057868059483\n ],\n [\n -90.69488525390625,\n 46.69184147024343\n ],\n [\n -90.78140258789062,\n 46.71632714994794\n ],\n [\n -90.7855224609375,\n 46.66734468444288\n ],\n [\n -90.83221435546875,\n 46.62020426357956\n ],\n [\n -90.8294677734375,\n 46.57774276255591\n ],\n [\n -90.83770751953125,\n 46.39619977845332\n ],\n [\n -90.55343627929688,\n 46.409457767475764\n ],\n [\n -90.54931640625,\n 46.54280504427768\n ],\n [\n -90.48751831054686,\n 46.54658317951774\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: August 2020; Version 1.1: December 2020","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349