The Northern High Plains aquifer underlies about 93,000 square miles of Colorado, Kansas, Nebraska, South Dakota, and Wyoming and is the largest subregion of the nationally important High Plains aquifer. Irrigation, primarily using groundwater, has supported agricultural production since before 1940, resulting in nearly $50 billion in sales in 2012. In 2010, the High Plains aquifer had the largest groundwater withdrawals of any major aquifer system in the United States. Nearly one-half of those withdrawals were from the Northern High Plains aquifer, which has little hydrologic interaction with parts of the aquifer farther south. Land-surface elevation ranges from more than 7,400 feet (ft) near the western edge to less than 1,100 ft near the eastern edge. Major stream primarily flow west to east and include the Big Blue River, Elkhorn River, Loup River, Niobrara River, Republican River and Platte River with its two forks—the North Platte River and South Platte River. Population in the Northern High Plain aquifer area is sparse with only 2 cities having a population greater than 30,000.
Droughts across much of the area from 2001 to 2007, combined with recent (2004–18) legislation, have heightened concerns regarding future groundwater availability and highlighted the need for science-based water-resource management. Groundwater models with the capability to provide forecasts of groundwater availability and related stream base flows from the Northern High Plains aquifer were published recently (2016) and were used to analyze groundwater availability. Stream base flows are generally the dominant component of total streamflow in the Northern High Plains aquifer, and total streamflows or shortages thereof define conjunctive management triggers, at least in Nebraska. Groundwater availability was evaluated through comparison of aquifer-scale water budgets compared for periods before and after major groundwater development and across selected future forecasts. Groundwater-level declines and the forecast amount of groundwater in storage in the aquifer also were examined.
Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
This article assesses the ability of regionally specific, frequency‐dependent crustal attenuation (
In addition to its resident Golden Eagles (Aquila chrysaetos), the Southern Great Plains of North America receives an influx of migrant Golden Eagles each winter. However, little current or quantitative information is available regarding eagle presence or the species' land cover associations across the region. During the winters of 2014/2015 and 2015/2016, we surveyed Golden Eagles along 51 approximately 55-km-long road survey transects within a 136,800-km2 area of the Southern Great Plains of eastern New Mexico and the panhandles of Texas and Oklahoma. Our goal was to estimate the winter density of Golden Eagles in the region and to evaluate their land cover associations. Detections were low, with an estimated regional winter density of 0.31 eagles per 100 km2. We found that Golden Eagles were detected in rangeland cover types in greater proportion, and in agricultural and other land cover types in lesser proportion, to their availability. Our results provide regulatory agencies with data that may facilitate better-informed decision making for eagle conservation in the region.
","language":"English","doi":"10.3398/064.080.0402","usgsCitation":"Mitchell, N., Boal, C.W., and Skipper, B., 2020, Distribution, density, and land cover associations of wintering Golden Eagles in the Southern Great Plains: Western North American Naturalist, v. 80, no. 4, p. 452-461, https://doi.org/10.3398/064.080.0402.","productDescription":"10 p.","startPage":"452","endPage":"461","ipdsId":"IP-099428","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Oklahoma, Texas","otherGeospatial":"Southern Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.05078125,\n 33.578014746143985\n ],\n [\n -97.822265625,\n 33.578014746143985\n ],\n [\n -97.822265625,\n 37.09023980307208\n ],\n [\n -107.05078125,\n 37.09023980307208\n ],\n [\n -107.05078125,\n 33.578014746143985\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, N.R.","contributorId":274259,"corporation":false,"usgs":false,"family":"Mitchell","given":"N.R.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":832848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skipper, B.R.","contributorId":270348,"corporation":false,"usgs":false,"family":"Skipper","given":"B.R.","email":"","affiliations":[{"id":56152,"text":"Angelo State University","active":true,"usgs":false}],"preferred":false,"id":832850,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228237,"text":"70228237 - 2020 - Eastern oyster clearance and respiration rates in response to acute and chronic exposure to suspended sediment loads","interactions":[],"lastModifiedDate":"2022-02-08T15:47:02.571742","indexId":"70228237","displayToPublicDate":"2020-02-01T09:31:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2449,"text":"Journal of Sea Research","active":true,"publicationSubtype":{"id":10}},"title":"Eastern oyster clearance and respiration rates in response to acute and chronic exposure to suspended sediment loads","docAbstract":"Coastal Louisiana supports some of the most productive areas for the eastern oyster, Crassostrea virginica. Changing conditions from restoration and climate change alter freshwater and sediment inflows into critical estuarine areas affecting water quality, including salinity and concentrations of suspended sediment. This study examined the effects of acute (1 h) and chronic (8 weeks) exposure of suspended sediment concentrations on the eastern oyster's respiration and clearance rates. Acute exposure at six sediment concentrations (0, 10, 50, 200, 500, 1000 mg L−1) and one salinity (15) indicated that sediment concentration significantly affected oyster clearance rates, with increasing clearance rates as suspended sediment concentrations increased up to 500 mg L−1. Respiration rates were not affected by sediment concentration (p = .12). Chronic exposure at two salinities (6 and 15) and three sediment concentrations (0, 50, 400 mg L−1) found no significant effect of sediment, salinity or their interaction on clearance rates. Respiration rate was reduced at higher sediment concentrations (50 and 400 mg L−1 versus 0 mg L−1) and lower salinity. As clearance and oxygen consumption rates critically inform oyster energetic models, these data provide valuable insight to more accurately predict eastern oyster population dynamics and inform harvest models in the face of changing estuarine conditions. Changes in rates of growth through altered energetic demands ultimately can impact not just the economic viability of the industry, but also the ability for the populations to maintain sustainable reefs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.seares.2019.101831","usgsCitation":"La Peyre, M., Bernasconi, S.K., Lavaud, R., Casas, S.M., and La Peyre, J.F., 2020, Eastern oyster clearance and respiration rates in response to acute and chronic exposure to suspended sediment loads: Journal of Sea Research, v. 157, p. 1-7, https://doi.org/10.1016/j.seares.2019.101831.","productDescription":"101831, 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-109899","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499828,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.lsu.edu/animalsciences_pubs/794","text":"External Repository"},{"id":395621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Bay Gardene","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.68508720397949,\n 29.56188581810685\n ],\n [\n -89.6129035949707,\n 29.56188581810685\n ],\n [\n -89.6129035949707,\n 29.609804580144143\n ],\n [\n -89.68508720397949,\n 29.609804580144143\n ],\n [\n -89.68508720397949,\n 29.56188581810685\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"157","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernasconi, S. K.","contributorId":274906,"corporation":false,"usgs":false,"family":"Bernasconi","given":"S.","email":"","middleInitial":"K.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":833503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lavaud, R.","contributorId":273051,"corporation":false,"usgs":false,"family":"Lavaud","given":"R.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":833504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casas, S. M.","contributorId":272906,"corporation":false,"usgs":false,"family":"Casas","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":833506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, J. F.","contributorId":273052,"corporation":false,"usgs":false,"family":"La Peyre","given":"J.","email":"","middleInitial":"F.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":833505,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70209147,"text":"70209147 - 2020 - Influence of remediation on sediment toxicity within the Grand Calumet River, Indiana, USA","interactions":[],"lastModifiedDate":"2020-03-20T06:47:36","indexId":"70209147","displayToPublicDate":"2020-01-31T18:49:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Influence of remediation on sediment toxicity within the Grand Calumet River, Indiana, USA","docAbstract":"The Grand Calumet River (GCR), located in northern Indiana, is contaminated due to a wide range of historical industrial activities. This study was conducted to determine the influence of sediment remediation within the GCR on concentrations of chemical contaminants and toxicity to sediment-dwelling organisms. Between 2005 and 2016, sediments with high concentrations of metals and toxic organic compounds were remediated through a combination of removal, addition of activated carbon and organoclay amendments, and capping with sand or relatively uncontaminated sediment. Short-term and long-term sediment toxicity tests with the amphipod Hyalella azteca, the midge Chironomus dilutus, and the mussel Lampsilis siliquoidea were conducted with samples collected in 2013, 2015, and 2017, from 29 sites, including both remediated and non-remediated sites. Sediment chemistry and toxicity data for three groups of remediated sites (US Steel, West Branch, and East Branch) were compared to samples from contaminated but unremediated sites and to relatively uncontaminated reference sites. In general, remediated sediments had lower levels of PAHs, PCBs and metals, although sediments from the US Steel area still had elevated levels of PAH, PCB and chromium. Sediments from the three remediated sites and from reference sites showed significantly reduced toxic effects in short-term sediment bioassays, compared to unremediated sites. Variation in the long-term success of remediation may reflect site-specific factors such as the type of remediation and the potential for recontamination from uncontrolled sources.","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2020.126056","usgsCitation":"Steevens, J.A., Besser, J.M., Dorman, R.A., and Sparks, D.W., 2020, Influence of remediation on sediment toxicity within the Grand Calumet River, Indiana, USA: Chemosphere, v. 249, 126056, https://doi.org/10.1016/j.chemosphere.2020.126056.","productDescription":"126056","ipdsId":"IP-113273","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":437131,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XIDHOV","text":"USGS data release","linkHelpText":"Chemical and biological exposure bioassay data from sediment collected within the Grand Calumet River, Indiana, 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Rebecca A. 0000-0002-5748-7046","orcid":"https://orcid.org/0000-0002-5748-7046","contributorId":28522,"corporation":false,"usgs":true,"family":"Dorman","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":785124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sparks, Daniel W.","contributorId":223469,"corporation":false,"usgs":false,"family":"Sparks","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":785125,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208237,"text":"70208237 - 2020 - Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance","interactions":[],"lastModifiedDate":"2020-06-04T16:51:39.984534","indexId":"70208237","displayToPublicDate":"2020-01-31T16:07:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1822,"text":"Geostandards and Geoanalytical Research","active":true,"publicationSubtype":{"id":10}},"title":"Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance","docAbstract":"Waters co-produced during petroleum extraction are the largest waste stream from oil and gas development. Reuse or disposal of these waters is difficult due to their high salinities and the sheer volumes generated. Produced waters may also contain valuable mineral commodities. While an understanding of produced water trace element composition is required for evaluating the associated resource and waste potential of these materials, measuring trace elements in brines is challenging due to the dilution requirements of typical methods. Alternatively, inductively coupled plasma-optical emission spectrometry (ICP-OES) has shown promise as being capable of direct measurements of trace elements within produced waters with minimal dilution. Here we evaluate direct ICP-OES trace element quantification in produced waters for 17 trace elements (As, Al, Ba, Be, Cd, Cr, Co, Cu, Hg, Mo, Ni, Pb, Rb, Sb, U, V, and Zn) within 15 produced waters from five U.S. continuous reservoirs. The ICP-OES results are compared against trace element levels determined using inductively coupled plasma-mass spectrometry from the same samples. Our results demonstrate the potential for direct analysis of high salinity waters using ICP-OES with minimal dilution and provide trace element concentrations in waters from several important U.S. petroleum-generating reservoirs where available data is sparse.","language":"English","publisher":"Wiley","doi":"10.1111/GGR.12316","usgsCitation":"Jubb, A., Engle, M., Chenault, J., Blondes, M., Danforth, C.G., Doolan, C., Gallegos, T., Mueller, D., and Shelton, J., 2020, Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance: Geostandards and Geoanalytical Research, v. 44, no. 2, p. 385-397, https://doi.org/10.1111/GGR.12316.","productDescription":"13 p.","startPage":"385","endPage":"397","ipdsId":"IP-111055","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":457922,"rank":0,"type":{"id":40,"text":"Open 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mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":222079,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Danforth, Cloelle G.","contributorId":222080,"corporation":false,"usgs":false,"family":"Danforth","given":"Cloelle","email":"","middleInitial":"G.","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":781219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doolan, Colin 0000-0002-7595-7566 cdoolan@usgs.gov","orcid":"https://orcid.org/0000-0002-7595-7566","contributorId":222081,"corporation":false,"usgs":true,"family":"Doolan","given":"Colin","email":"cdoolan@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781121,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gallegos, Tanya 0000-0003-3350-6473 tgallegos@usgs.gov","orcid":"https://orcid.org/0000-0003-3350-6473","contributorId":222082,"corporation":false,"usgs":true,"family":"Gallegos","given":"Tanya","email":"tgallegos@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781122,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mueller, Dan","contributorId":222083,"corporation":false,"usgs":false,"family":"Mueller","given":"Dan","email":"","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":781220,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shelton, Jenna 0000-0002-1377-0675 jlshelton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-0675","contributorId":222084,"corporation":false,"usgs":true,"family":"Shelton","given":"Jenna","email":"jlshelton@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781124,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70208453,"text":"70208453 - 2020 - Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models","interactions":[],"lastModifiedDate":"2020-02-11T07:40:36","indexId":"70208453","displayToPublicDate":"2020-01-31T07:37:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models","docAbstract":"Determining hydrologic conditions prior to instrumental records is a challenge for restoration of freshwater ecosystems worldwide. Paleoecologic data provide this information on past conditions and when these data are used to adjust hydrologic models, allow conditions to be hindcast that may not be directly estimated from the paleo-data alone. In this context, the paleo-data provide real-world estimates as input to the models. Restoration of the Greater Everglades Ecosystem requires this understanding of the hydrology of the natural system prior to significant alterations due to water management and land use. Large scale models such as the Natural Systems Model (NSM 4.6.2) have been used by the South Florida Water Management District and other agencies responsible for restoration to estimate past hydrologic conditions; however, these models typically portray a drier natural system for the beginning of the 20th century than what is indicated by paleoecologic analyses and historical data. The purpose of this study is to estimate pre-20th century water levels, hydroperiods and flow in the freshwater wetlands of the Everglades by using pollen assemblage data in three sediment cores to adjust the Natural Systems Model. This study is designed to further test estimates of flow through the Everglades derived from analysis of sediment cores collected in Florida Bay. The results demonstrate that the NSM 4.6.2 underestimates water levels and hydroperiods in the Everglades compared to the paleo-adjusted NSM 4.6.2 model outputs. Flow models that use the paleo-adjusted water levels as input indicate flow through Shark River Slough in the late 19th century was approximately two times flow between 1990 and 2000, and flow through Taylor Slough was approximately three times flow between 1990 and 2000. The flow estimates derived from this study agree with the estimates derived from earlier studies using estuarine cores. This integration of paleoecologic information and hydrologic models provides resource managers with the best available estimates of past conditions and allows them to set realistic targets for restoration of freshwater ecosystems.","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2020.00003","usgsCitation":"Marshall, F.E., Bernhardt, C.E., and Wingard, G.L., 2020, Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models: Frontiers in Environmental Science, v. 8, no. 3, 21 p., https://doi.org/10.3389/fenvs.2020.00003.","productDescription":"21 p.","ipdsId":"IP-099728","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":457934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2020.00003","text":"Publisher Index Page"},{"id":372206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.58447265624999,\n 25.110471486223346\n ],\n [\n -80.2716064453125,\n 25.110471486223346\n ],\n [\n -80.2716064453125,\n 25.903703303407667\n ],\n [\n -81.58447265624999,\n 25.903703303407667\n ],\n [\n -81.58447265624999,\n 25.110471486223346\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, Frank E.","contributorId":222355,"corporation":false,"usgs":false,"family":"Marshall","given":"Frank","email":"","middleInitial":"E.","affiliations":[{"id":40533,"text":"Cetacean Logic Foundation","active":true,"usgs":false}],"preferred":false,"id":781946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":781947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":781945,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208331,"text":"70208331 - 2020 - Field observations of wind waves in Upper Delaware Bay with living shorelines","interactions":[],"lastModifiedDate":"2020-05-05T16:46:39.517086","indexId":"70208331","displayToPublicDate":"2020-01-29T17:58:17","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Field observations of wind waves in Upper Delaware Bay with living shorelines","docAbstract":"Constructed oyster reefs (CORs) provide shore protections and habitats for fish and shellfish communities via wave energy attenuation. However, the processes and mechanism of CORs on wave attenuation remain unclear, thus limiting the effective assessment of CORs for shoreline protection. This paper presents results of a field investigation on wave characteristics and wave spectral variations along a shoreline with CORs in an estuary with a large tidal range as well as large wind waves and swell energy. Six pressure transducers were deployed from January 31 to April 2, 2018, in Gandy’s Beach, New Jersey, in upper Delaware Bay. CORs were constructed at the study site in 2016 as living shoreline structures after Hurricane Sandy. The data collected from the study site exhibits the wave variations and spectral characteristics over the span of 2 months, including four winter storms (i.e., nor’easters). The spatial variations of wave heights measured on both sides of CORs show a strong dependence on the ratio between the freeboard of CORs and the offshore wave heights. Due to the large tidal range (> 2 m), the crests of CORs remain submerged over 85% of the time. The submerged CORs only provide partial attenuation of wave energy. The wave environment in the estuary is complex, especially during nor’easters. For instance, winds with rapid changing fetches could lead to bi-modal wind seas. Due to the complex wave spectra, the bulk wave heights such as the significant wave heights cannot be adopted to adequately reveal the capacity of CORs to attenuate wave energy. Spectral analysis is conducted to investigate the spatial and temporal variations of wave energy in targeted frequency bins. The spectral analysis results reveal the energy transfer from the primary waves to the high harmonics after waves propagate over the submerged CORs. Moreover, it is found that swell energy originated from the Atlantic Ocean can penetrate CORs without any dampening even when CORs are emergent. This study could help resource managers for in-depth evaluation of living shoreline effectiveness and improvement of living shoreline structures such as CORs.","language":"English","publisher":"Springer","doi":"10.1007/s12237-019-00670-7","usgsCitation":"Zhu, L., Chen, Q., Wang, H., Capurso, W.D., Niemoczynski, L., Hu, K., and Snedden, G., 2020, Field observations of wind waves in Upper Delaware Bay with living shorelines: Estuaries and Coasts, v. 43, p. 739-755, https://doi.org/10.1007/s12237-019-00670-7.","productDescription":"17 p.","startPage":"739","endPage":"755","ipdsId":"IP-108855","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":437136,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YEUNTM","text":"USGS data release","linkHelpText":"Field observations and spectral evolution of wind waves in Upper Delaware Bay with living shorelines"},{"id":372048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey","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 -75.56396484375,\n 38.34165619279595\n ],\n [\n -74.86358642578125,\n 38.34165619279595\n ],\n [\n -74.86358642578125,\n 39.42346418978382\n ],\n [\n -75.56396484375,\n 39.42346418978382\n ],\n [\n -75.56396484375,\n 38.34165619279595\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhu, Ling 0000-0003-0261-6848","orcid":"https://orcid.org/0000-0003-0261-6848","contributorId":222169,"corporation":false,"usgs":false,"family":"Zhu","given":"Ling","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":781438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":781439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":215079,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":781437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Capurso, William D. 0000-0003-1182-2846 wcapurso@usgs.gov","orcid":"https://orcid.org/0000-0003-1182-2846","contributorId":2113,"corporation":false,"usgs":true,"family":"Capurso","given":"William","email":"wcapurso@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":781440,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Niemoczynski, Lukasz M. 0000-0003-2008-9148","orcid":"https://orcid.org/0000-0003-2008-9148","contributorId":222171,"corporation":false,"usgs":true,"family":"Niemoczynski","given":"Lukasz","middleInitial":"M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781441,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hu, Kelin","contributorId":177218,"corporation":false,"usgs":false,"family":"Hu","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":781442,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Snedden, Gregg 0000-0001-7821-3709 sneddeng@usgs.gov","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":140235,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","email":"sneddeng@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":781443,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208145,"text":"70208145 - 2020 - Simulation modeling of complex climate, wildfire, and vegetation dynamics to address wicked problems in land management","interactions":[],"lastModifiedDate":"2020-07-09T14:32:31.735778","indexId":"70208145","displayToPublicDate":"2020-01-29T17:34:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5860,"text":"Frontiers in Forests and Global Change","active":true,"publicationSubtype":{"id":10}},"title":"Simulation modeling of complex climate, wildfire, and vegetation dynamics to address wicked problems in land management","docAbstract":"Complex, reciprocal interactions among climate, disturbance, and vegetation\ndramatically alter spatial landscape patterns and influence ecosystem dynamics.\nAs climate and disturbance regimes shift, historical analogs and past empirical studies\nmay not be entirely appropriate as templates for future management. The need for a\nbetter understanding of the potential impacts of climate changes on ecosystems is\nreaching a new level of urgency, especially in highly perturbed or vulnerable ecological\nsystems. Simulation models are extremely useful tools for guiding management\ndecisions in an era of rapid change, thus providing potential solutions for wicked\nproblems in land management—those that are difficult to solve and inherently resistant\nto easily definable solutions. We identify three experimental approaches for landscape\nmodeling that address management challenges in the context of uncertain climate\nfutures and complex ecological interactions: (1) an historical comparative approach, (2)\na future comparative approach, and (3) threshold detection. We provide examples of\neach approach from previously published studies of simulated climate, disturbance, and\nlandscape dynamics in forested landscapes of the western United States, modeled with\nthe FireBGCv2 ecosystem process model. Cumulatively, model outcomes indicate that\ntypical land management strategies will likely not be sufficient to counteract the impacts\nof rapid climate change and altered disturbance regimes that threaten the stability\nof ecosystems. Without implementation of new, adaptive management strategies,\nfuture landscapes are very likely to be different than historical or contemporary ones,\nwith significant and sometimes persistent changes triggered by interactions of climate\nand wildfire.","language":"English","publisher":"Frontiers","doi":"10.3389/ffgc.2020.00003","usgsCitation":"Loehman, R.A., Keane, R.E., and Holsinger, L.M., 2020, Simulation modeling of complex climate, wildfire, and vegetation dynamics to address wicked problems in land management: Frontiers in Forests and Global Change, v. 3, 3, 13 p., https://doi.org/10.3389/ffgc.2020.00003.","productDescription":"3, 13 p.","ipdsId":"IP-113393","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":457966,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2020.00003","text":"Publisher Index 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45.95628155285034\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":780709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keane, Robert E.","contributorId":200723,"corporation":false,"usgs":false,"family":"Keane","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":780710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holsinger, Lisa M.","contributorId":187607,"corporation":false,"usgs":false,"family":"Holsinger","given":"Lisa","email":"","middleInitial":"M.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":780711,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210620,"text":"70210620 - 2020 - Does the virus cross the road? Viral phylogeographic patterns among bobcat populations reflect a history of urban development","interactions":[],"lastModifiedDate":"2020-09-10T19:53:51.951009","indexId":"70210620","displayToPublicDate":"2020-01-28T11:42:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Does the virus cross the road? Viral phylogeographic patterns among bobcat populations reflect a history of urban development","docAbstract":"Urban development has major impacts on connectivity among wildlife populations and is thus likely an important factor shaping pathogen transmission in wildlife. However, most investigations of wildlife diseases in urban areas focus on prevalence and infection risk rather than potential effects of urbanization on transmission itself. Feline immunodeficiency virus (FIV) is a directly transmitted retrovirus that infects many felid species and can be used as a model for studying pathogen transmission at landscape scales. We investigated phylogenetic relationships among FIV isolates sampled from five bobcat (Lynx rufus ) populations in coastal southern California that appear isolated due to major highways and dense urban development. Divergence dates among FIV phylogenetic lineages in several cases reflected historical urban growth and construction of major highways. We found strong FIV phylogeographic structure among three host populations north‐west of Los Angeles, largely coincident with host genetic structure. In contrast, relatively little FIV phylogeographic structure existed among two genetically distinct host populations south‐east of Los Angeles. Rates of FIV transfer among host populations did not vary significantly, with the lack of phylogenetic structure south‐east of Los Angeles unlikely to reflect frequent contemporary transmission among populations. Our results indicate that major barriers to host gene flow can also act as barriers to pathogen spread, suggesting potentially reduced susceptibility of fragmented populations to novel directly transmitted pathogens. Infrequent exchange of FIV among host populations suggests that populations would best be managed as distinct units in the event of a severe disease outbreak. Phylogeographic inference of pathogen transmission is useful for estimating the ability of geographic barriers to constrain disease spread and can provide insights into contemporary and historical drivers of host population connectivity.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.12927","usgsCitation":"Kozakiewicz, C.P., Burridge, C.P., Funk, W., Craft, M.E., Crooks, K.R., Fisher, R.N., Fountain-Jones, N.M., Jennings, M.K., Kraberger, S.J., Lee, J.S., Lyren, L.M., Riley, S.P., Serieys, L.E., VandeWoude, S., and Carver, S., 2020, Does the virus cross the road? Viral phylogeographic patterns among bobcat populations reflect a history of urban development: Evolutionary Applications, v. 13, no. 3, p. 1806-1817, https://doi.org/10.1111/eva.12927.","productDescription":"12 p.","startPage":"1806","endPage":"1817","ipdsId":"IP-115355","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":457988,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.12927","text":"Publisher Index Page"},{"id":375558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles, San Diego","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.38818359375,\n 34.07086232376631\n ],\n [\n -117.65258789062499,\n 34.07086232376631\n ],\n [\n -117.65258789062499,\n 35.25907654252574\n ],\n [\n -120.38818359375,\n 35.25907654252574\n ],\n [\n -120.38818359375,\n 34.07086232376631\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.68554687499999,\n 32.55144352864431\n ],\n [\n -114.949951171875,\n 32.55144352864431\n ],\n [\n -114.949951171875,\n 34.25721644329402\n ],\n [\n -117.68554687499999,\n 34.25721644329402\n ],\n [\n -117.68554687499999,\n 32.55144352864431\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kozakiewicz, Christopher P.","contributorId":212126,"corporation":false,"usgs":false,"family":"Kozakiewicz","given":"Christopher","email":"","middleInitial":"P.","affiliations":[{"id":38423,"text":"School of Biological Sciences, University of Tasmania, Hobart, Tasmania, Australia","active":true,"usgs":false}],"preferred":false,"id":790866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burridge, Christopher P.","contributorId":221854,"corporation":false,"usgs":false,"family":"Burridge","given":"Christopher","email":"","middleInitial":"P.","affiliations":[{"id":16141,"text":"University of Tasmania","active":true,"usgs":false}],"preferred":false,"id":790867,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Funk, W. Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":189580,"corporation":false,"usgs":false,"family":"Funk","given":"W. Chris","affiliations":[],"preferred":false,"id":790868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Craft, Meggan E.","contributorId":168372,"corporation":false,"usgs":false,"family":"Craft","given":"Meggan","email":"","middleInitial":"E.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":790869,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crooks, Kevin R.","contributorId":51137,"corporation":false,"usgs":false,"family":"Crooks","given":"Kevin","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":790870,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":790871,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fountain-Jones, Nicholas M. 0000-0001-9248-8493","orcid":"https://orcid.org/0000-0001-9248-8493","contributorId":197452,"corporation":false,"usgs":false,"family":"Fountain-Jones","given":"Nicholas","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":790872,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jennings, Megan K.","contributorId":221856,"corporation":false,"usgs":false,"family":"Jennings","given":"Megan","email":"","middleInitial":"K.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":790873,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kraberger, Simona J","contributorId":225262,"corporation":false,"usgs":false,"family":"Kraberger","given":"Simona","email":"","middleInitial":"J","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":790874,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lee, Justin S.","contributorId":212111,"corporation":false,"usgs":false,"family":"Lee","given":"Justin","email":"","middleInitial":"S.","affiliations":[{"id":38413,"text":"Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA","active":true,"usgs":false}],"preferred":false,"id":790875,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lyren, Lisa M.","contributorId":197457,"corporation":false,"usgs":false,"family":"Lyren","given":"Lisa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":790876,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Riley, Seth P.D.","contributorId":145429,"corporation":false,"usgs":false,"family":"Riley","given":"Seth","middleInitial":"P.D.","affiliations":[{"id":7237,"text":"NPS, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":790877,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Serieys, Laurel E K","contributorId":225263,"corporation":false,"usgs":false,"family":"Serieys","given":"Laurel","email":"","middleInitial":"E K","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":790878,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"VandeWoude, Sue","contributorId":212137,"corporation":false,"usgs":false,"family":"VandeWoude","given":"Sue","email":"","affiliations":[{"id":38434,"text":"College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA","active":true,"usgs":false}],"preferred":false,"id":790879,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Carver, Scott 0000-0002-3579-7588","orcid":"https://orcid.org/0000-0002-3579-7588","contributorId":197456,"corporation":false,"usgs":false,"family":"Carver","given":"Scott","email":"","affiliations":[],"preferred":false,"id":790880,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70208007,"text":"70208007 - 2020 - Dilution and propagation of provenance trends in sand and mud: Geochemistry and detrital zircon geochronology of modern sediment from central California (U.S.A.)","interactions":[],"lastModifiedDate":"2020-01-27T06:24:22","indexId":"70208007","displayToPublicDate":"2020-01-24T06:38:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":732,"text":"American Journal of Science","active":true,"publicationSubtype":{"id":10}},"title":"Dilution and propagation of provenance trends in sand and mud: Geochemistry and detrital zircon geochronology of modern sediment from central California (U.S.A.)","docAbstract":"Integrated, multi-method provenance studies of siliciclastic sedimentary deposits are increasingly used to reconstruct the history of source-to-sink transport, paleogeography, and tectonics. Invariably, analysis of large-scale depositional systems must confront issues regarding how to best sample the system and adequately cope with the details of sediment mixing. Potential biases including variations in grain size, sediment flux, and zircon concentration may cause provenance tracking tools to misrepresent the contributions of source-areas that contribute to large drainage networks. We have acquired U-Pb detrital zircon data from modern sand and whole rock geochemistry from mud sampled from the Sacramento-San Joaquin drainage of central California to elucidate conditions that can skew provenance trends along the course of a major river system. This drainage network is fed by headwaters that tap the Mesozoic pluton-dominated southern Sierra Nevada, the Paleozoic-Mesozoic wallrock and volcanic-dominated northern Sierra Nevada, the ultramafic-dominated eastern Klamath Mountains, and the intermediate to mafic Cascades volcanic arc. Analysis of the results indicates that detrital zircon provenance trends effectively record source variations for the southern, granite-dominated portion of the drainage network where contrasts in lithology and inferred zircon fertility are relatively minor. In these circumstances, mixture modeling of U-Pb detrital zircon data calibrated with a measure of zircon fertility approximates relative sediment flux contributed by individual drainages. Alternatively, in the northern parts of the system, source regions underlain by ultramafic and /or volcanic rocks are poorly represented, or entirely missing, in down-stream detrital zircon records. In some cases, mud geochemistry data more faithfully represents sediment provenance trends.\nSampling performed at the confluence of the Sacramento, American, Mokolumne, and San Joaquin rivers within the Sacramento Delta region yields a detrital zircon age distribution that is indistinguishable from that of an independently established database of Sierra Nevada batholith crystallization ages. However, when the combined river flows along a recently established passage to the Pacific through the San Francisco Bay region, dredged sediment is found to be significantly contaminated by locally eroded material from the Franciscan Complex and other rocks that crop out within the Coast Ranges. Large variation of Zr concentrations measured throughout the Bay area document that significant hydrodynamic fractionation impacts sediment delivery through this segment of the system. The more Sierra Nevada-like detrital zircon age distribution yielded by a piston-core sample from the continental slope may be explained by either early-stage unroofing of the Coast Ranges or more efficient sand delivery from the delta to the Pacific by a free flowing river driven by a low stand in sea level.","language":"English","publisher":"AJS","doi":"10.2475/10.2019.02","usgsCitation":"Malkowski, M., Sharman, G.R., Johnstone, S., Grove, M.J., Kimbrough, D.L., and Graham, S.A., 2020, Dilution and propagation of provenance trends in sand and mud: Geochemistry and detrital zircon geochronology of modern sediment from central California (U.S.A.): American Journal of Science, v. 319, p. 846-902, https://doi.org/10.2475/10.2019.02.","productDescription":"57 p.","startPage":"846","endPage":"902","ipdsId":"IP-101193","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":371511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.34374999999999,\n 41.31082388091818\n ],\n [\n -123.0908203125,\n 41.21172151054787\n ],\n [\n -123.26660156249999,\n 39.9434364619742\n ],\n [\n -122.431640625,\n 38.71980474264237\n ],\n [\n -121.86035156249999,\n 37.64903402157866\n ],\n [\n -121.11328124999999,\n 36.38591277287651\n ],\n [\n -119.92675781249999,\n 35.17380831799959\n ],\n [\n -119.00390625,\n 34.56085936708384\n ],\n [\n -118.21289062499999,\n 34.56085936708384\n ],\n [\n -118.65234374999999,\n 36.38591277287651\n ],\n [\n -119.970703125,\n 38.09998264736481\n ],\n [\n -121.46484375,\n 40.1452892956766\n ],\n [\n -122.34374999999999,\n 41.31082388091818\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"319","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Malkowski, Matthew A.","contributorId":221753,"corporation":false,"usgs":false,"family":"Malkowski","given":"Matthew A.","affiliations":[{"id":40415,"text":". Department of Geological Sciences, Stanford University, Stanford CA 94305","active":true,"usgs":false}],"preferred":false,"id":780126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sharman, Glenn R.","contributorId":196537,"corporation":false,"usgs":false,"family":"Sharman","given":"Glenn","email":"","middleInitial":"R.","affiliations":[{"id":34621,"text":"Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA","active":true,"usgs":false}],"preferred":false,"id":780127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":780310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grove, Marty J.","contributorId":221754,"corporation":false,"usgs":false,"family":"Grove","given":"Marty","email":"","middleInitial":"J.","affiliations":[{"id":40416,"text":"Department of Geological Sciences, Stanford University, Stanford CA 94305","active":true,"usgs":false}],"preferred":false,"id":780128,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kimbrough, Dave L.","contributorId":221755,"corporation":false,"usgs":false,"family":"Kimbrough","given":"Dave","email":"","middleInitial":"L.","affiliations":[{"id":40417,"text":"Department of Geological Sciences, San Diego State University, San Diego, CA 92182","active":true,"usgs":false}],"preferred":false,"id":780129,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graham, Stephen A.","contributorId":221756,"corporation":false,"usgs":false,"family":"Graham","given":"Stephen","email":"","middleInitial":"A.","affiliations":[{"id":40416,"text":"Department of Geological Sciences, Stanford University, Stanford CA 94305","active":true,"usgs":false}],"preferred":false,"id":780130,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70207972,"text":"fs20203001 - 2020 - Assessment of undiscovered oil and gas resources in the Central North Slope of Alaska, 2020","interactions":[],"lastModifiedDate":"2022-04-19T21:56:41.792192","indexId":"fs20203001","displayToPublicDate":"2020-01-23T10:25:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3001","displayTitle":"Assessment of Undiscovered Oil and Gas Resources in the Central North Slope of Alaska, 2020","title":"Assessment of undiscovered oil and gas resources in the Central North Slope of Alaska, 2020","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 3.6 billion barrels of oil and 8.9 trillion cubic feet of natural gas (associated and nonassociated) in conventional accumulations in Mississippian through Paleogene strata in the central North Slope of Alaska.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20203001","usgsCitation":"Houseknecht, D.W., Whidden, K.J., Connors, C.D., Lease, R.O., Schenk, C.J., Mercier, T.J., Rouse, W.A., Botterell, P.J., Smith, R.A., Sanders, M.M., Craddock, W.H., DeVera, C.A., Garrity, C.P., Buursink, M.L., Karacan, C.O., Heller, S.J., Moore, T.E., Dumoulin, J.A., Tennyson, M.E., French, K.L., Woodall, C.A., Drake, R.M., II, Marra, K.R., Finn, T.M., Kinney, S.A., and Shorten, C.M., 2020, Assessment of undiscovered oil and gas resources in the central North Slope of Alaska, 2020: U.S. Geological Survey Fact Sheet 2020–3001, 4 p., https://doi.org/10.3133/fs20203001.","productDescription":"Report: 4 p.; Data release","onlineOnly":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":371465,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91SK721","text":"USGS data release","linkHelpText":"USGS Alaska Petroleum Systems Project - Northern Alaska Province, Central North Slope Assessment Unit Boundaries and Assessment Input Forms, 2020"},{"id":399145,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109608.htm"},{"id":371441,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3001/fs20203001.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3001"},{"id":371440,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3001/coverthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"central North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158,\n 68\n ],\n [\n -148,\n 68\n ],\n [\n -148,\n 70.9417\n ],\n [\n -158,\n 70.9417\n ],\n [\n -158,\n 68\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Energy Resources Science Center
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12201 Sunrise Valley Drive, MS-954
Reston, VA 20192
The three sets of ground‐motion predictions (GMPs) of Boore (2018; hereafter, B18) are compared with a much larger dataset than was used in deriving the predictions. The B18 GMPs work well for response spectra at periods between
The predictions of B18, developed for very‐hard‐rock sites (
An additional finding is that the
The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers (USACE), analyzed streamflow trends and streamflow-related variables through 2017 in seven important water-supply basins to provide information that can help water managers with the USACE and river authorities make future water management decisions. The primary purpose of this report is to document trends in long-term streamflow data at 114 selected USGS streamflow-gaging stations and 36 simulated reservoir-inflow stations in 7 river basins primarily in Texas: Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity. In this report, trends were considered statistically significant if their p-values were less than or equal to 0.05 (p-value ≤0.05). Streamflow data selected for temporal trend analyses included annual minimum streamflow, annual peak streamflow, and streamflow volume. Precipitation, air temperature, and groundwater-level-elevation data were analyzed for trends that may help to explain changes observed in the streamflow statistics. Basins were divided into sections along county lines for precipitation analyses. Streamflow volumes were analyzed for associations with potential flood storage. The potential flood storage, defined as the difference between maximum storage and normal storage, was computed for each dam from the National Inventory of Dams database and accumulated over time based on the completion date of the dam.
Precipitation and air temperature trends were analyzed for each of the eight climate divisions (High Plains, Trans-Pecos, Low Rolling Hills, Edwards Plateau, North Central Texas, South Central Texas, East Texas, and Upper Coast). Results of precipitation trend analyses indicated moderate upward trends in the Upper Coast and East Texas Climate Divisions analyzed on an annual time step from 1900 through 2017. These two climate divisions are in the eastern and southeastern parts of the State, and they receive more mean annual precipitation (45.88 and 46.09 inches, respectively) than the other climate divisions. The results of air temperature analyses indicated upward trends in annual mean air temperature within all climate divisions, with a mean slope of 0.02 degree Fahrenheit per year, or 1 degree every 50 years.
Within the Brazos River Basin, results of precipitation trend analyses on an annual time step indicated that precipitation amounts are most likely increasing in the lower and middle sections of the basin. Downward trends in annual streamflow and in the ratio of streamflow volume to precipitation volume were indicated at 7 of the 15 stations in the upper sections of the basin. The lower sections of the basin had mostly downward trends in annual minimum streamflow, whereas upward trends in annual minimum streamflow were indicated in the upper sections of the basin. Downward trends in annual peak streamflow were indicated at many of the stations in the upper sections of the basin. At the same seven stations in the upper sections of the basin where there were downward trends in annual streamflow, there were also downward trends in the ratio of streamflow volume to precipitation volume. The data from the same seven stations indicated negative associations between potential flood storage volume and annual streamflow volume and downward trends in the ratio of annual streamflow volume to potential flood storage volume. With the known addition of 13,006,394 acre-feet of potential flood storage between 1900 and 2010 in the subbasins analyzed, streamflow volumes have decreased in the upper sections of the Brazos River Basin.
Within the Colorado River Basin, results of precipitation trend analyses on an annual time step indicated no trends in the basin. Downward trends in annual streamflow were indicated at 16 stations in the upper sections of the basin, whereas no trends in annual streamflow were indicated in the lower section of the basin. In the lower section of the basin, one station that was operated as a continuous streamflow-gaging station through 2017 had a downward trend in annual minimum streamflow, and another station (operated through 2007) had an upward trend in annual minimum streamflow. In the upper sections of the basin, data from seven stations indicated upward trends in annual minimum streamflow, and data from six stations indicated downward trends. Data from 18 stations in the upper sections of the basin indicated downward trends in annual peak streamflow. Thirteen of the 16 stations in the upper sections of the basin with data that indicated downward trends in annual streamflow also have data that indicated downward trends in the ratio of streamflow volume to precipitation volume. Data from the same 13 stations indicated negative associations between potential flood storage volume and annual streamflow volume and downward trends in the ratio of annual streamflow volume to potential flood storage volume. With the known addition of 7,193,147 acre-feet of potential flood storage between 1891 and 2014 in the subbasins analyzed, streamflow volumes have decreased in the upper sections of the Colorado River Basin.
Within the Big Cypress Basin, results of precipitation trend analyses on annual, seasonal, and monthly time steps indicated almost no trends in the basin as defined in this report. However, the annual precipitation p-value only slightly exceeded the p-value threshold for a statistically significant trend. Given the upward trend in precipitation in the East Texas Climate Division, which includes the Big Cypress Basin, and the low p-value for annual precipitation within the basin, precipitation in the basin may be increasing over time. Two annual streamflow trends, one upward and one downward, were in the upper parts of the basin. Data from USGS streamflow-gaging station 07346000 Big Cypress Bayou near Jefferson, Texas, indicated an upward trend in annual minimum streamflow and a downward trend in annual peak streamflow. The station is immediately downstream from Lake O’ the Pines; presumably, minimums have increased because of regulated releases, and annual peaks have decreased because of storage from the lake for flood control. Despite the known addition of 2,737,154 acre-feet of potential flood storage between 1898 and 2011 in the subbasins analyzed, there have not been widespread reductions in streamflow volumes in the Big Cypress Basin, except for within the drainage area for the farthest upstream station on the main stem downstream from Mount Pleasant, Texas.
Within the Guadalupe River Basin, results of precipitation trend analyses on an annual time step indicated an upward trend in the lower section of the basin, but no trends in annual streamflow were indicated in the lower section of the basin. In the upper section of the basin, data from 1 of the 13 stations indicated an upward trend in annual streamflow. Data from 6 of the 13 stations in the upper section of the basin indicated a trend in annual minimum streamflow with 4 upward and 2 downward trends. Data from 2 of the 13 stations in the upper section of the basin indicated downward trends in annual peak streamflow. Despite the known addition of 2,016,534 acre-feet of potential flood storage between 1849 and 2013 in the subbasins analyzed, streamflow volumes have not decreased in the Guadalupe River Basin.
Within the Neches River Basin, results of precipitation trend analyses on an annual time step indicated upward trends in the basin. None of the data from stations analyzed in the Neches River Basin indicated annual trends in streamflow despite upward trends in annual precipitation within the basin. Data from 9 of the 19 stations analyzed in the basin indicated upward trends in annual minimum streamflow. Data from one of the simulated-inflow stations indicated a downward trend in annual minimum streamflow into Sam Rayburn Reservoir. Data from two stations indicated downward trends in annual peak streamflow, and data from one small subbasin indicated an upward trend in annual peak streamflow. Despite the known addition of 4,839,609 acre-feet of potential flood storage between 1888 and 2008 in the subbasins analyzed, there have not been widespread reductions in streamflow volumes in the Neches River Basin.
Within the Sulphur River Basin, results of precipitation trend analyses on an annual time step indicated a moderate upward trend within the basin. Data from only one of the stations, the simulated inflow to Jim Chapman Lake, indicated an annual upward trend in streamflow despite an upward trend in annual precipitation throughout the basin. Data from three of the six stations in the Sulphur River Basin indicated upward trends in annual minimum streamflow, and data from one of the six stations indicated a downward trend in annual peak streamflow. Despite the known addition of 6,933,361 acre-feet of potential flood storage between 1904 and 2006 in the subbasins analyzed, streamflow volumes have not decreased in the Sulphur River Basin.
Within the Trinity River Basin, results of precipitation trend analyses on an annual time step indicated upward trends in most sections of the basin. Data from 8 of the 36 stations analyzed for trends in annual streamflow indicated upward trends, and all 8 stations are in the upper sections of the basin. None of the data from stations in the lower sections of the basin indicated trends in annual streamflow. Data from 16 of the 36 stations indicated upward trends in annual minimum streamflow. Upward trends in annual minimum streamflow could be the result of managed reservoir releases in combination with wastewater treatment plant releases in the large Dallas-Fort Worth metroplex in the upper sections of the basin. All the trends in annual peak streamflow were in the sections of the basin that include the Dallas-Fort Worth metroplex. Data from two stations, one USGS streamflow-gaging station and one simulated-inflow station, indicated upward trends in annual peak streamflow, and data from one streamflow-gaging station indicated a downward trend in annual peak streamflow. Of the basins included in this study, the Trinity River Basin has the second largest amount of potential flood storage of 8,947,349 acre-feet from dams added between 1890 and 2013. Eleven stations in the Trinity River Basin had positive associations between potential flood storage volume and annual streamflow volume, indicating that annual streamflow increases as potential flood storage increases. Data from 7 of the 11 stations also indicated upward trends in annual streamflow. The positive associations may be the result of increases in minimum streamflow, which could be the result of any combination of managed reservoir releases, wastewater treatment plant releases, or increased runoff from urbanized areas, particularly in the urbanized area of the Dallas-Fort Worth metroplex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195137","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Fort Worth District","usgsCitation":"Harwell, G.R., McDowell, J.S., Gunn, C.L., and Garrett, B.S., 2020, Precipitation, temperature, groundwater-level elevation, streamflow, and potential flood storage trends within the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River basins in Texas through 2017 (ver. 1.1, April 2020): U.S. Geological Survey Scientific Investigations Report 2019–5137, 94 p., https://doi.org/10.3133/sir20195137.","productDescription":"Report: x, 94 p.; 5 Tables; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102896","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":399613,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109606.htm"},{"id":374071,"rank":9,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5137/coverthb2.jpg"},{"id":373986,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5137/versionHist.txt","text":"Version History","size":"1.35 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2019–5137 Version History"},{"id":371261,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table9.xlsx","text":"Table 9—","size":"120 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 9","linkHelpText":"Summary of annual, seasonal, and monthly trends in the ratio of streamflow volume to precipitation volume in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371258,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table7.xlsx","text":"Table 7—","size":"64 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 7","linkHelpText":"Summary of precipitation temporal trends around the time of annual peak streamflow in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371255,"rank":2,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table5.xlsx","text":"Table 5—","size":"80 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 5","linkHelpText":"Summary of annual, seasonal, and monthly associations between precipitation volume and streamflow volume in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371252,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L1F7PT","text":"USGS data release","description":"USGS data release","linkHelpText":"Data used to assess precipitation, temperature, groundwater-level elevation, streamflow, and potential flood storage trends within the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins in Texas through 2017"},{"id":373985,"rank":7,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_v1.1.pdf","text":"Report","size":"20.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5137"},{"id":371259,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table8.xlsx","text":"Table 8—","size":"144 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 8","linkHelpText":"Summary of annual, seasonal, and monthly streamflow volume trends in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371262,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table10.xlsx","text":"Table 10—","size":"48 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 10","linkHelpText":"Summary of trends in annual minimum streamflow and annual peak streamflow and relations between streamflow volume and potential flood storage volume in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"}],"country":"United States","state":"Texas","otherGeospatial":"Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.4667,\n 28.4167\n ],\n [\n -93.0619,\n 28.4167\n ],\n [\n -93.0619,\n 33.6667\n ],\n [\n -101.4667,\n 33.6667\n ],\n [\n -101.4667,\n 28.4167\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: January 2020; Version 1.1: April 2020","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
One of the North American bat species most impacted by white-nose syndrome (WNS) is the northern long-eared bat Myotis septentrionalis, which as a result has been listed under the Endangered Species Act. WNS was first detected in Wisconsin in 2014. Unfortunately, little is known regarding the ecology of M. septentrionalis in this state pre-WNS to guide management supporting post-WNS recovery efforts. The objectives of our research were to (1) assess characteristics of trees that are associated with roost tree selection and (2) investigate how characteristics of maternity colony networks compare to colonies in the eastern USA. We mist-netted at 3 sites in Wisconsin in 2015 and 2016, and affixed radio transmitters to 39 female M. septentrionalis. We tracked bats to 53 confirmed day roosts. We found that roost trees were larger, more decayed, and more likely to be in dominant canopy closure areas than random trees. Oaks Quercus spp. were used most frequently and in proportion to their availability in the landscape at 2 field sites, whereas invasive black locust Robinia pseudoacacia was used more than expected based on availability at another site. Overall, minimum convex polygon sizes for maternity roosts were variable (5.2 to 8.9 ha) but similar to values reported for other regions. However, network centrality was low, indicating equitable use of day roosts and more frequent roost switching compared to other regions. Our findings provide information that increasing availability of potential day roosts in the landscape during the reproductive period may improve recruitment, which may in turn mitigate some of the detrimental population effects from WNS.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01004","usgsCitation":"Hyzy, B.A., Russell, R.E., Silvis, A., Ford, W., Riddle, J., and Russell, K., 2020, Investigating maternity roost selection by northern long-eared bats at three sites in Wisconsin: Endangered Species Research, v. 41, p. 55-65, https://doi.org/10.3354/esr01004.","productDescription":"11 p., Data release","startPage":"55","endPage":"65","ipdsId":"IP-106190","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":458110,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01004","text":"Publisher Index Page"},{"id":418323,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YH1668","text":"USGS data release","description":"USGS data release","linkHelpText":"Roost selection for Northern Long-eared Bats (Myotis septentrionalis) in Wisconsin"},{"id":391798,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Black River State Forest, Governor Dodge State Park, Sandhill Wildlife Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.1479721069336,\n 42.996110107947956\n ],\n [\n -90.07038116455078,\n 42.996110107947956\n ],\n [\n -90.07038116455078,\n 43.05785119934999\n ],\n [\n -90.1479721069336,\n 43.05785119934999\n ],\n [\n -90.1479721069336,\n 42.996110107947956\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.89813232421875,\n 44.049102784014536\n ],\n [\n -90.52871704101562,\n 44.049102784014536\n ],\n [\n -90.52871704101562,\n 44.50825885600572\n ],\n [\n -90.89813232421875,\n 44.50825885600572\n ],\n [\n -90.89813232421875,\n 44.049102784014536\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.20736694335936,\n 44.295349956045804\n ],\n [\n -90.11398315429686,\n 44.295349956045804\n ],\n [\n -90.11398315429686,\n 44.39257961837961\n ],\n [\n -90.20736694335936,\n 44.39257961837961\n ],\n [\n -90.20736694335936,\n 44.295349956045804\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","noUsgsAuthors":false,"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":826915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":826916,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvis, Alex","contributorId":269007,"corporation":false,"usgs":false,"family":"Silvis","given":"Alex","affiliations":[],"preferred":false,"id":826917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":826918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riddle, Jason","contributorId":269008,"corporation":false,"usgs":false,"family":"Riddle","given":"Jason","affiliations":[],"preferred":false,"id":826919,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Russell, Kevin","contributorId":269009,"corporation":false,"usgs":false,"family":"Russell","given":"Kevin","affiliations":[],"preferred":false,"id":826920,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209223,"text":"70209223 - 2020 - A 100-year geoelectric hazard analysis for the U.S. high-voltage power grid","interactions":[],"lastModifiedDate":"2020-03-25T06:19:56","indexId":"70209223","displayToPublicDate":"2020-01-15T13:47:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"A 100-year geoelectric hazard analysis for the U.S. high-voltage power grid","docAbstract":"A once-per-century geoelectric hazard map is created for the United States high-voltage\n\tpower grid. A statistical extrapolation from 31 years of magnetic field measurements is\n\tmade by identifying 84 geomagnetic storms with the Kp and Dst indices. Data from 24\n\tgeomagnetic observatories, 1079 magnetotelluric survey sites, and 17,258 transmission\n\tlines are utilized to perform a geoelectric hazard analysis with the most comprehensive\n\tdata publicly available. With this data we estimate once-per-century geoelectric fields at\n\tthe magnetotelluric survey sites and calculate the theoretical voltages within transmission\n\tlines in the United States power grid. Once-per-century geoelectric field strengths span\n\tmore than three orders of magnitude from a minimum of 0.02 V/km at a site in Idaho to a\n\tmaximum of 26.8 V/km at a site in Maine, with nearly 30% of the surveyed land area ex-\n\tceeding 1 V/km. We show the influence that geoelectric field polarization has on geoelec-\n\ttric hazards when viewed on a power transmission network. The calculated transmission\n\tline voltages can exceed 1000 V in some transmission lines. Four regions in the United\n\tStates with particularly notable geoelectric hazards are identified and discussed: the East\n\tcoast, Pacific Northwest, upper Midwest, and the Denver metropolitan area.","language":"English","publisher":"Wiley","doi":"10.1029/2019SW002329","usgsCitation":"Lucas, G., Love, J.J., Kelbert, A., Bedrosian, P.A., and Rigler, E.J., 2020, A 100-year geoelectric hazard analysis for the U.S. high-voltage power grid: Space Weather, v. 18, no. 2, e2019SW002329, https://doi.org/10.1029/2019SW002329.","productDescription":"e2019SW002329","ipdsId":"IP-113155","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":458123,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019sw002329","text":"Publisher Index Page"},{"id":373484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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-67.67578124999999,\n 47.21956811231547\n ],\n [\n -68.994140625,\n 47.45780853075031\n ],\n [\n -71.3671875,\n 45.213003555993964\n ],\n [\n -74.70703125,\n 45.1510532655634\n ],\n [\n -77.080078125,\n 43.58039085560784\n ],\n [\n -78.92578124999999,\n 43.70759350405294\n ],\n [\n -79.1015625,\n 42.74701217318067\n ],\n [\n -82.08984375,\n 41.96765920367816\n ],\n [\n -83.14453125,\n 42.09822241118974\n ],\n [\n -81.650390625,\n 43.51668853502906\n ],\n [\n -82.705078125,\n 45.644768217751924\n ],\n [\n -88.330078125,\n 48.3416461723746\n ],\n [\n -89.56054687499999,\n 47.989921667414194\n ],\n [\n -95.09765625,\n 49.095452162534826\n ],\n [\n -114.697265625,\n 49.210420445650286\n ],\n [\n -123.134765625,\n 49.095452162534826\n ],\n [\n -122.958984375,\n 48.16608541901253\n ],\n [\n -124.98046874999999,\n 48.10743118848039\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Lucas, Greg M. 0000-0003-1331-1863","orcid":"https://orcid.org/0000-0003-1331-1863","contributorId":223556,"corporation":false,"usgs":false,"family":"Lucas","given":"Greg M.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":785448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":785449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":785450,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":785451,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":785452,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207244,"text":"sir20195141 - 2020 - Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17","interactions":[],"lastModifiedDate":"2022-04-25T20:16:09.086144","indexId":"sir20195141","displayToPublicDate":"2020-01-08T16:45:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5141","displayTitle":"Water-Balance Techniques for Determining Available Soil-Water Storage for Selected Sandy and Clay Soil Study Sites in Cass County, North Dakota, 2016–17","title":"Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service, collected field and remotely sensed data on precipitation, evapotranspiration (ET), and soil-water content to determine available soil-water storage (AWS) at six study sites on sandy and clay soils in Cass County, North Dakota. Data were collected at all the study sites from May 1–October 31, 2016, and from May 1–October 24, 2017. Estimated daily AWS was determined using daily meteorological and potential evapotranspiration (PET) data obtained from various climate stations, and estimated monthly AWS was determined using monthly meteorological and PET data and monthly ET data determined using the Operational Simplified Surface Energy Balance model. AWS during 2016 and 2017 was determined at daily and monthly time steps because of data availability and to assess results using varying time steps. Comparisons of measured and estimated daily values of AWS at the Brewer Lake site indicated poor agreement during May–October 2016 and May–October 2017. Comparisons of measured and estimated daily values of AWS at the Embden East and Embden West sites indicated poor and fair agreement respectively. At the Lynchburg Crop and Lynchburg Grass sites, comparisons of measured and estimated daily values of AWS indicated fair and good relations, respectively, even with the possible effects of soil cracks. Mean estimated values of daily runoff plus soil percolation for the four sandy soil sites indicated that a maximum of about 19 percent of the estimated runoff plus soil percolation could be considered runoff and that the remaining 81 percent could be considered soil percolation, and for the two clay soil sites about 13 percent of the runoff plus soil percolation could have been considered runoff and about 87 percent could have been considered soil percolation. Results indicated little difference between using monthly PET or monthly ET in water-balance equations to estimate monthly AWS for the grouped sandy soil sites, and only slightly better results were obtained using monthly PET than monthly ET to estimate monthly AWS for the grouped clay soil study sites. Overall, the monthly water-balance models did not perform as well as the daily water-balance models for determining AWS at the six study sites. Additional data collection from a longer-period study and adjustments to the models may improve results from the monthly water-balance techniques.
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Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
The Atlantic, or American, horseshoe crab (Limulus polyphemus) has existed largely unchanged for over 100 million years. Millions of individuals are commonly observed ashore in spring and summer months during spawning events along the entire North American coastline expanding from the East to the Gulf coasts of the United States and Mexico. Other species can be found in the Indian and Pacific Ocean. The massive deposit of eggs in nearshore sand provides a critical source of food for endangered migrating birds, especially the Red Knot (Calidruis canutus rufa) in the Delaware Bay. Horseshoe crabs are also an important component of the sea turtle diet. In addition to the ecological importance, horseshoe crabs are used commercially for bait in eel and conch fisheries and for biomedical purposes in the production of Limulus Amebocyte Lysate (LAL) to detect bacterial toxins in injectable drugs and implantable devices. Commercial demands have led to population declines in some regions. Fisheries are regulated by state and the current International Union for Conservation of Nature (IUCN) listing for L. polyphemus is vulnerable.
A small number of individuals are housed in public aquaria for educational purposes. With growing interest in animal welfare, the health and stability of populations, and potential stressors that can contribute to decline , it is important to have clear and detailed descriptions of horseshoe crab anatomy and necropsy techniques. The purpose of this guide is to illustrate the normal anatomy and the step-by-step technique for dissection of horseshoe crabs. The contents are largely excerpts of the master’s thesis of artist, Katie (Bergdale) Roorda, which was based on photographs from C. Meteyer documenting the sequence and procedure used for necropsy dissection.
","language":"English","publisher":"Wildlife Disease Association","usgsCitation":"Roorda, K., Arnold, J., Meteyer, C., and Whitaker, B., 2020, Standardized guide to the examination and necropsy of the horseshoe crab using Limulus polyphemus as Limulidae prototype: Cooperator Report, 31 p.","productDescription":"31 p.","ipdsId":"IP-108910","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":375778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":375770,"type":{"id":15,"text":"Index Page"},"url":"https://zooquaticlab.com/file?filename=Limulus%20Necropsy%20Guide_%20July%202019.pdf&type=reference"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roorda, Katie","contributorId":225415,"corporation":false,"usgs":false,"family":"Roorda","given":"Katie","email":"","affiliations":[{"id":41102,"text":"John Hopkins University.","active":true,"usgs":false}],"preferred":false,"id":791116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arnold, Jill","contributorId":225416,"corporation":false,"usgs":false,"family":"Arnold","given":"Jill","email":"","affiliations":[{"id":41103,"text":"ZooQuatic Laboratory LLC1","active":true,"usgs":false}],"preferred":false,"id":791117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meteyer, Carol 0000-0002-4007-3410","orcid":"https://orcid.org/0000-0002-4007-3410","contributorId":207215,"corporation":false,"usgs":true,"family":"Meteyer","given":"Carol","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"preferred":true,"id":791118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitaker, Brent","contributorId":225417,"corporation":false,"usgs":false,"family":"Whitaker","given":"Brent","email":"","affiliations":[{"id":41104,"text":"National Aquarium of Baltimore","active":true,"usgs":false}],"preferred":false,"id":791119,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70244010,"text":"70244010 - 2020 - Using advanced population genomics to better understand the relationship between offshore and spawning habitat use for Atlantic Sturgeon","interactions":[],"lastModifiedDate":"2023-05-31T14:05:38.468729","indexId":"70244010","displayToPublicDate":"2020-01-01T08:58:09","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5709,"text":"OCS Study","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"2020-062","title":"Using advanced population genomics to better understand the relationship between offshore and spawning habitat use for Atlantic Sturgeon","docAbstract":"Atlantic Sturgeon (Acipenser oxyrinchus oxyrinchus) are a large-bodied anadromous fish that historically supported important fisheries along the east coast of the United States. Following years of overharvest and habitat degradation, populations experienced severe declines. In 2012, the National Marine Fisheries Service listed Atlantic Sturgeon under the Endangered Species Act (ESA; 61 FR 4722). Their listing named five Distinct Population Segments (DPSs), predicated on genetic groups composed of geographically proximate populations.
Federal management of Atlantic Sturgeon presents challenges, as sturgeon from each of the five DPSs mix extensively in coastal and marine habitats yet take and recovery progress must be evaluated separately for each unit. Genetic assignment testing based on mitochondrial and microsatellite markers allows individuals to be assigned back to their natal river and DPS. However, this approach is not perfect and some individuals may be incorrectly assigned. Recent advances in genomics offer the potential of a higher resolution approach to genetic assignment testing, and thus may reduce uncertainty associated with assignment testing. In addition, genomics allows a greater number of markers to be examined from across a broader portion of the sturgeon genome, thus may provide an enhanced perspective of population structure for the species, and potentially allow other previously intractable questions to be addressed (Bernatchez et al. 2017, Supple and Shapiro 2018).
We used next-generation sequencing to develop a draft genome for Atlantic Sturgeon and identify single nucleotide polymorphisms (SNPs) that could be used to resolve the natal river and DPS of individual Atlantic Sturgeon. We identified 1,210 candidate SNPs within the nuclear genome as well as 49 SNPs within the mitochondrial genome. After filtering and review, we selected 161 nuclear SNPs and 39 mitochondrial SNPs for further testing and evaluation. We used genotyping-in-thousands by sequencing (GT-seq) to simultaneously sequence nuclear SNP loci, mitochondrial SNP loci, and the existing panel of twelve microsatellite loci. This effort required a pilot sequencing run on a single sturgeon sample to test marker amplification and refine primer strengths, followed by a series of sequencing runs to generate baseline data for 288 individuals representing nine populations of Atlantic Sturgeon in four DPSs.
Using baseline data from the nine populations, we ran a series of genomic analyses to characterize diversity within and among populations, providing a benchmark for this species using the new SNP markers. Allelic richness was similar for all populations, although there was a general trend of more northern population containing greater levels of allelic richness. Interestingly, we observed linkage disequilibrium among many pairs of loci within many populations. This might be the result of physical linkage but could also suggest these populations are recovering from genetic bottlenecks and/or are effectively small, leading to specific haplotypes to be favored by chance. Pairwise differentiation among populations varied among the populations (FST range: 0.010-0.098) and was significantly correlated (r = 0.771; P < 0.001) to pairwise FST observed using microsatellite markers). Population clustering and ordination techniques using the new genomic data both support an overall population structure that is similar to the current DPS management units (which were developed primarily based on microsatellite genetic data). Overall, this suggests that existing microsatellite markers and the panel of SNP markers developed in this study provide similar information about the populations structure and ecology of Atlantic Sturgeon. Given the observed differences in allele frequencies among populations, our genomic baseline supports previous assertations that Atlantic Sturgeon show natal homing, despite mixing extensively in marine waters during non-breeding periods. Lower levels of differentiation between populations in the South Atlantic DPS suggest that populations in this region may have greater levels of gene flow relative to their more northerly conspecifics, which has also previously been suggested based on microsatellite data. The observed differentiation among populations provides the necessary foundation for determining the natal river and DPS of Atlantic Sturgeon using assignment testing.
We tested the utility of our new genomic baseline for resolving the population and DPS of Atlantic Sturgeon. Our nuclear SNP markers showed utility for identifying the origin of unknown Atlantic Sturgeon samples, as 86.5% were assigned to the correct DPS and 66.3% were assigned to the correct natal river. However, since this study was funded the Conservation Genetics and Genomics Laboratory at Leetown Science Center has made significant improvements to their microsatellite genetic baseline, which now performs more effectively than our new genomic approach (the genetic baseline includes 12 populations and 5 DPSs, and correctly assigns 95.8% of individuals to DPS and 84.9% of individuals to their natal population using 12 microsatellite loci). We conducted an ad hoc exploration of how additional microsatellite or nuclear SNP loci may further improve the accuracy of assignment testing. We found that additional microsatellite markers are likely to result in greater improvements in assignment efficiency than additional nuclear SNPs. However, a much larger number of SNP loci (which if identified could be sequenced using other methods that are now available; e.g., the RAD-capture approach published by Ali et al. 2016) could produce assignment efficiencies that are greater than what is currently feasible using microsatellites. In the absence of further research and development of additional SNP markers for Atlantic Sturgeon (possibly using an approach other than GT-seq), the existing microsatellite loci are the most effective means available to determine the natal river and DPS of Atlantic Sturgeon encountered in offshore waters.
Because our new genomic markers were less effective than the existing panel of 12 microsatellite markers, we chose to use the existing microsatellite markers to assign Atlantic Sturgeon captured in another BOEM-funded study (cooperative agreement M16AC00003; Monitoring endangered Atlantic Sturgeon and commercial finfish habitat use offshore New York) following consultation with our project officer. Using this approach, we genotyped and assigned 186 Atlantic Sturgeon captured in coastal waters off the Rockaway Peninsula, New York. The vast majority of these sturgeon were assigned to the New York Bight DPS (94.62%), and most appear to belong to the Hudson River population (87.10%) with smaller contributions from the Delaware River population (7.53%). Smaller contributions (2.15%) were observed from six other populations, including those from the James, York, Kennebec, Ogeechee, and Edisto rivers. Although most of the fish we assigned were assigned to the nearest spawning rivers (Hudson and Delaware), the contributions from distant rivers is consistent with the propensity of this species to move long distances and form mixed stock aggregations along the continental shelf. This finding indicates that spawning populations (and their corresponding DPS) from distant locations may potentially be impacted by offshore activities. In fact, activities in this region of the New York Bight could negatively impact Atlantic Sturgeon population from at least four different DPSs. Genetic or genomic assignment testing remains an essential tool to characterize potential impacts to Atlantic Sturgeon populations and should be applied more broadly to better characterize potential impacts of activities in other locations.
","language":"English","publisher":"Bureau of Ocean Energy Management","usgsCitation":"Kazyak, D.C., Aunins, A.W., Johnson, R.L., Lubinski, B.A., Eackles, M.S., and King, T.L., 2020, Using advanced population genomics to better understand the relationship between offshore and spawning habitat use for Atlantic Sturgeon: OCS Study 2020-062, vi, 70 p.","productDescription":"vi, 70 p.","ipdsId":"IP-106640","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":417577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417553,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://espis.boem.gov/final%20reports/BOEM_2020-062.pdf"}],"country":"United States","otherGeospatial":"Atlantic Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.78806562180561,\n 30.580780235117913\n ],\n [\n -77.30336432135029,\n 29.69193789019691\n ],\n [\n -64.22711779996946,\n 41.900389189548946\n ],\n [\n -67.3512701866663,\n 45.015746962117504\n ],\n [\n -69.19972084180974,\n 45.07365899620572\n ],\n [\n -71.17441845739293,\n 43.73099181927631\n ],\n [\n -71.83104405363528,\n 41.84410310133748\n ],\n [\n -74.31268565149895,\n 41.0826339553866\n ],\n [\n -77.28914013501216,\n 39.074309300310176\n ],\n [\n -76.84797677722777,\n 36.18896372481389\n ],\n [\n -80.79266974786641,\n 32.79868499554179\n ],\n [\n -82.1343310450048,\n 31.38292965735748\n ],\n [\n -81.78806562180561,\n 30.580780235117913\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aunins, Aaron W. 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","middleInitial":"W.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Robin L. 0000-0003-4314-3792 rjohnson1@usgs.gov","orcid":"https://orcid.org/0000-0003-4314-3792","contributorId":224717,"corporation":false,"usgs":true,"family":"Johnson","given":"Robin","email":"rjohnson1@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eackles, Michael S. 0000-0001-5624-5769 meackles@usgs.gov","orcid":"https://orcid.org/0000-0001-5624-5769","contributorId":218936,"corporation":false,"usgs":true,"family":"Eackles","given":"Michael","email":"meackles@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874145,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"King, Tim L. tlking@usgs.gov","contributorId":3520,"corporation":false,"usgs":true,"family":"King","given":"Tim","email":"tlking@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874258,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208625,"text":"70208625 - 2020 - Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change","interactions":[],"lastModifiedDate":"2020-12-15T20:16:16.059853","indexId":"70208625","displayToPublicDate":"2019-12-31T14:44:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2785,"text":"Monographs of the Western North American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change","docAbstract":"Over 80% of the Mid-Continent Sandhill Crane (Antigone canadensis) Population (MCP), estimated at over 660,000 individuals, stops in the Central Platte River Valley (CPRV) during spring migration from mid-February through mid-April. Research suggests that the MCP may be shifting its distribution spatially and temporally within the CPRV. From 2002 to 2017, we conducted weekly aerial surveys of Sandhill Cranes staging in the CPRV to examine temporal and spatial trends in their abundance and distribution. Then, we used winter temperature and drought severity measures from key wintering and early migratory stopover locations to assess the impacts of weather patterns on annual migration chronology in the CPRV. We also evaluated channel width and land cover characteristics using aerial imagery from 1938, 1998, and 2016 to assess the relationship between habitat change and the spatial distribution of the MCP in the CPRV. We used generalized linear models, cumulative link models, and Akaike’s information criterion corrected for small sample sizes (AICc) to compare temporal and spatial models. Temperatures and drought conditions at wintering and migration locations that are heavily used by Greater Sandhill Cranes (A. c. tabida) best predicted migration chronology of the MCP to the CPRV. The spatial distribution of roosting Sandhill Cranes from 2015 to 2017 was best predicted by the proportion of width reduction in the main channel since 1938 (rather than its width in 2016) and the proportion of land cover as prairie-meadow habitat within 800 m of the Platte River. Our data suggest that Sandhill Cranes advanced their migration by an average of just over 1 day per year from 2002 to 2017, and that they continued to shift eastward, concentrating at eastern reaches of the CPRV. Climate change, land use change, and habitat loss have all likely contributed to Sandhill Cranes coming earlier and staying longer in fewer reaches of the CPRV, increasing their site use intensity. These historically unprecedented densities may present a disease risk to Sandhill Cranes and other waterbirds, including Whooping Cranes (Grus americana). Our models suggest that conservation actions may be maintaining Sandhill Crane densities in areas that would otherwise be declining in use. We suggest that management actions intended to mitigate trends in the distribution of Sandhill Cranes, including wet meadow restoration, may similarly benefit prairie- and braided river–endemic species of concern.
","language":"English","publisher":"BioOne","doi":"10.3398/042.011.0104","usgsCitation":"Caven, A.J., Brinley Buckley, E.M., King, K.C., Wiese, J.D., Baasch, D.M., Wright, G.D., Harner, M.J., Pearse, A.T., Rabbe, M., Varner, D., Krohn, B., Arcilla, N., Schroeder, K.D., and Dinan, K.F., 2020, Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change: Monographs of the Western North American Naturalist, v. 11, p. 33-76, https://doi.org/10.3398/042.011.0104.","productDescription":"44 p.","startPage":"33","endPage":"76","ipdsId":"IP-102357","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458279,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3398/042.011.0104","text":"Publisher Index Page"},{"id":372957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.03237915039062,\n 41.024981358869915\n ],\n [\n -98.06465148925781,\n 41.055537533528636\n ],\n [\n -98.27957153320312,\n 40.954492756949186\n ],\n [\n -98.40934753417967,\n 40.88029480552824\n ],\n [\n -98.81515502929688,\n 40.73112880602221\n ],\n [\n -98.99642944335938,\n 40.69938133866613\n ],\n [\n -99.55535888671874,\n 40.73321007823572\n ],\n [\n -99.60548400878906,\n 40.66293116628907\n ],\n [\n -99.1845703125,\n 40.63740418690266\n ],\n [\n -98.86459350585938,\n 40.64469860601899\n ],\n [\n -98.55491638183594,\n 40.72540497175607\n ],\n [\n -98.28781127929688,\n 40.805493843894155\n 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Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiese, Joshua D","contributorId":222651,"corporation":false,"usgs":false,"family":"Wiese","given":"Joshua","email":"","middleInitial":"D","affiliations":[{"id":40581,"text":"Platte River Whooping Crane Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baasch, David M.","contributorId":147145,"corporation":false,"usgs":false,"family":"Baasch","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":16795,"text":"Headwaters Corp, Kearney, NE","active":true,"usgs":false}],"preferred":false,"id":782802,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wright, Greg D.","contributorId":177585,"corporation":false,"usgs":false,"family":"Wright","given":"Greg","email":"","middleInitial":"D.","affiliations":[{"id":12957,"text":"Chippewa Ottawa Resource Authority","active":true,"usgs":false}],"preferred":false,"id":782803,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harner, Mary J.","contributorId":177584,"corporation":false,"usgs":false,"family":"Harner","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":782804,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":782797,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rabbe, Matt","contributorId":202597,"corporation":false,"usgs":false,"family":"Rabbe","given":"Matt","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":782805,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Varner, Dana","contributorId":222652,"corporation":false,"usgs":false,"family":"Varner","given":"Dana","affiliations":[{"id":40582,"text":"Rainwater Basin Joint Venture","active":true,"usgs":false}],"preferred":false,"id":782806,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Krohn, Brice","contributorId":222653,"corporation":false,"usgs":false,"family":"Krohn","given":"Brice","email":"","affiliations":[{"id":40581,"text":"Platte River Whooping Crane Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782807,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Arcilla, Nicole","contributorId":223085,"corporation":false,"usgs":false,"family":"Arcilla","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":782808,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Schroeder, Kirk D","contributorId":222655,"corporation":false,"usgs":false,"family":"Schroeder","given":"Kirk","email":"","middleInitial":"D","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":782809,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dinan, Kenneth F","contributorId":222656,"corporation":false,"usgs":false,"family":"Dinan","given":"Kenneth","email":"","middleInitial":"F","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":782810,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70216997,"text":"70216997 - 2020 - A transect through Vermont's most famous volcano - Mount Ascutney","interactions":[],"lastModifiedDate":"2023-03-23T16:18:22.745397","indexId":"70216997","displayToPublicDate":"2019-12-31T09:57:15","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A transect through Vermont's most famous volcano - Mount Ascutney","docAbstract":"The Cretaceous Ascutney Mountain igneous complex affords a classic exposure of the White Mountain Igneous Suite. Often called Vermont’s most famous volcano, Mount Ascutney (elev. 3,144 feet, 958 m) stands as a prominent monadnock in the Connecticut River Valley. The mountain often serves as an inspirational landmark, as it does when viewed from locations throughout the valley including the Saint-Gaudens National Historic Site (Walsh, 2017). The Ascutney Mountain igneous complex (Ratcliffe and others, 2011) consists of several mafic to felsic nested plutons including gabbro-diorite exposed at Little Ascutney to the west, and the Ascutney Mountain stock composed of syenite, granite, and related volcanic rocks underlying the main summit to the east (Fig. 1) (Schneiderman, 1989, 1991). Foland and Faul (1977) and Foland and others (1985) dated the gabbro-diorite complex at 125.5 to 122.2 Ma by K-Ar on biotite and by whole rock Rb/Sr, and dated the syenite-granite complex at 123.2 to 121.4 Ma by K-Ar on biotite. During the field trip we will visit the host rocks south of the mountain and the main rocks types of the Ascutney Mountain stock exposed near the summit and along the Mount Ascutney toll road. \n \n Mount Ascutney is the classic location where Daly (1903) discussed the evidence for piecemeal stoping as a pluton emplacement mechanism. This theory was later modified to favor cauldron subsidence, or ring-fracture stoping, as an alternative mode of emplacement (Chapman and Chapman, 1940). Our new mapping (Walsh and others, in press), which supersedes an earlier provisional study (Walsh and others, 1996a, b), supports the cauldron subsidence model, and shows that the main Ascutney Mountain stock is a funnel shaped composite pluton in agreement with geophysical data (Daniels, 1990). This field guide will primarily highlight the results of the new geologic mapping.\n\n This field guide is modified from a field trip presented in 2017 (Walsh, 2017). Additional stops have been added to examine the host rocks in the region south of the Ascutney Mountain stock. Two hikes are planned as part of this trip. Other NEIGC field trip guides to Mount Ascutney include Stoiber (1954) and Schneiderman (1988).","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"111th New England Intercollegiate Geological Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"111th New England Intercollegiate Geological Conference","conferenceDate":"October 1-13, 2019","conferenceLocation":"Barre, VT","language":"English","publisher":"New England Intercollegiate Geological Conference","usgsCitation":"Walsh, G.J., Proctor, B., Sicard, K.R., and Valley, P.M., 2020, A transect through Vermont's most famous volcano - Mount Ascutney, in 111th New England Intercollegiate Geological Conference, v. 111, Barre, VT, October 1-13, 2019, p. 1-6.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-109653","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":381650,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":414625,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://neigc.info/guidebooks/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Vermont","otherGeospatial":"Mount Ascutney","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.48590469360352,\n 43.4175176458317\n ],\n [\n -72.40299224853516,\n 43.4175176458317\n ],\n [\n -72.40299224853516,\n 43.466002139041116\n ],\n [\n -72.48590469360352,\n 43.466002139041116\n ],\n [\n -72.48590469360352,\n 43.4175176458317\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"111","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Gregory J. 0000-0003-4264-8836 gwalsh@usgs.gov","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":873,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory","email":"gwalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":807199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Proctor, Brooks P. 0000-0002-4878-8728 bproctor@usgs.gov","orcid":"https://orcid.org/0000-0002-4878-8728","contributorId":178527,"corporation":false,"usgs":true,"family":"Proctor","given":"Brooks P.","email":"bproctor@usgs.gov","affiliations":[],"preferred":true,"id":807200,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sicard, Karri R. 0000-0003-4062-8030","orcid":"https://orcid.org/0000-0003-4062-8030","contributorId":219210,"corporation":false,"usgs":false,"family":"Sicard","given":"Karri","email":"","middleInitial":"R.","affiliations":[],"preferred":true,"id":807201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valley, Peter M. 0000-0002-9957-0403 pvalley@usgs.gov","orcid":"https://orcid.org/0000-0002-9957-0403","contributorId":4809,"corporation":false,"usgs":true,"family":"Valley","given":"Peter","email":"pvalley@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":807202,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}