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Phytoplankton blooms are dynamic phenomena of great importance to the functioning of estuarine and coastal ecosystems. We analysed a unique (large) collection of phytoplankton monitoring data covering 86 coastal sites distributed over eight regions in North America and Europe, with the aim of investigating common patterns in the seasonal timing and species composition of the blooms. The spring bloom was the most common seasonal pattern across all regions, typically occurring early (February–March) at lower latitudes and later (April–May) at higher latitudes. Bloom frequency, defined as the probability of unusually high biomass, ranged from 5 to 35% between sites and followed no consistent patterns across gradients of latitude, temperature, salinity, water depth, stratification, tidal amplitude or nutrient concentrations. Blooms were mostly dominated by a single species, typically diatoms (58% of the blooms) and dinoflagellates (19%). Diatom-dominated spring blooms were a common feature in most systems, although dinoflagellate spring blooms were also observed in the Baltic Sea. Blooms dominated by chlorophytes and cyanobacteria were only common in low salinity waters and occurred mostly at higher temperatures. Key bloom species across the eight regions included the diatoms Cerataulina pelagica and Dactyliosolen fragilissimus and dinoflagellates Heterocapsa triquetra and Prorocentrum cordatum. Other frequent bloom-forming taxa were diatom genera Chaetoceros, Coscinodiscus, Skeletonema, and Thalassiosira. Our meta-analysis shows that these 86 estuarine-coastal sites function as diatom-producing systems, the timing of that production varies widely, and that bloom frequency is not associated with environmental factors measured in monitoring programs. We end with a perspective on the limitations of conclusions derived from meta-analyses of phytoplankton time series, and the grand challenges remaining to understand the wide range of bloom patterns and processes that select species as bloom dominants in coastal waters.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2015.05.005","usgsCitation":"Carstensen, J., Klais, R., and Cloern, J.E., 2015, Phytoplankton blooms in estuarine and coastal waters: Seasonal patterns and key species: Estuarine, Coastal and Shelf Science, v. 162, p. 98-109, https://doi.org/10.1016/j.ecss.2015.05.005.","productDescription":"12 p.","startPage":"98","endPage":"109","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060088","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":472069,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pure.au.dk/portal/en/publications/be3e563a-d1bf-46c5-8f42-f6dbecef183e","text":"External Repository"},{"id":300917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Baltic Sea, 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Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":547810,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70143863,"text":"sir20155040 - 2015 - Continuous monitoring of sediment and nutrients in the Illinois River at Florence, Illinois, 2012-13","interactions":[],"lastModifiedDate":"2015-05-28T17:07:43","indexId":"sir20155040","displayToPublicDate":"2015-05-28T16:00:00","publicationYear":"2015","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":"2015-5040","title":"Continuous monitoring of sediment and nutrients in the Illinois River at Florence, Illinois, 2012-13","docAbstract":"

The Illinois River is the largest river in Illinois and is the primary contributing watershed for nitrogen, phosphorus, and suspended-sediment loading to the upper Mississippi River from Illinois. In addition to streamflow, the following water-quality constituents were monitored at the Illinois River at Florence, Illinois (U.S. Geological Survey station number 05586300), during May 2012–October 2013: phosphate, nitrate, turbidity, temperature, specific conductance, pH, and dissolved oxygen. The objectives of this monitoring were to (1) determine performance capabilities of the in-situ instruments; (2) collect continuous data that would provide an improved understanding of constituent characteristics during normal, low-, and high-flow periods and during different climatic and land-use seasons; (3) evaluate the ability to use continuous turbidity as a surrogate constituent to determine suspended-sediment concentrations; and (4) evaluate the ability to develop a regression model for total phosphorus using phosphate, turbidity, and other measured parameters. Reliable data collection was achieved, following some initial periods of instrument and data-communication difficulties. The resulting regression models for suspended sediment had coefficient of determination (R2) values of about 0.9. Nitrate plus nitrite loads computed using continuous data were found to be approximately 8 percent larger than loads computed using traditional discrete-sampling based models. A regression model for total phosphorus was developed by using historic orthophosphate data (important during periods of low flow and low concentrations) and historic suspended-sediment data (important during periods of high flow and higher concentrations). The R2of the total phosphorus regression model using orthophosphorus and suspended sediment was 0.8. Data collection and refinement of the regression models is ongoing.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155040","collaboration":"Prepared in cooperation with the Illinois Environmental Protection Agency","usgsCitation":"Terrio, P.J., Straub, T., Domanski, M.M., and Siudyla, N.A., 2015, Continuous monitoring of sediment and nutrients in the Illinois River at Florence, Illinois, 2012-13: U.S. Geological Survey Scientific Investigations Report 2015-5040, vii, 61 p., https://doi.org/10.3133/sir20155040.","productDescription":"vii, 61 p.","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-05-01","temporalEnd":"2013-10-31","ipdsId":"IP-051216","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":300901,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5040/"},{"id":300902,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5040/pdf/sir2015-5040.pdf","text":"Report","size":"4.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155040.jpg"}],"projection":"Albers Equal-Area Conic projection","country":"United States","state":"Illinois","city":"Florence","otherGeospatial":"Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.60956954956055,\n 39.636563184336524\n ],\n [\n -90.6097412109375,\n 39.62783759836399\n ],\n [\n -90.60416221618652,\n 39.627903705425176\n ],\n [\n -90.60502052307129,\n 39.63662928306019\n ],\n [\n -90.60956954956055,\n 39.636563184336524\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55682e1ae4b0d9246a9f60de","contributors":{"authors":[{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Straub, Timothy D. 0000-0002-5896-0851 tdstraub@usgs.gov","orcid":"https://orcid.org/0000-0002-5896-0851","contributorId":2273,"corporation":false,"usgs":true,"family":"Straub","given":"Timothy D.","email":"tdstraub@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":543038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Domanski, Marian M. 0000-0002-0468-314X mdomanski@usgs.gov","orcid":"https://orcid.org/0000-0002-0468-314X","contributorId":5035,"corporation":false,"usgs":true,"family":"Domanski","given":"Marian","email":"mdomanski@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siudyla, Nicholas A. nsiudyla@usgs.gov","contributorId":5420,"corporation":false,"usgs":true,"family":"Siudyla","given":"Nicholas","email":"nsiudyla@usgs.gov","middleInitial":"A.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":543039,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70141032,"text":"fs20153001 - 2015 - Water resources of East Baton Rouge Parish, Louisiana","interactions":[],"lastModifiedDate":"2026-06-25T20:59:41.798043","indexId":"fs20153001","displayToPublicDate":"2015-05-28T15:30:00","publicationYear":"2015","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":"2015-3001","title":"Water resources of East Baton Rouge Parish, Louisiana","docAbstract":"

Information concerning the availability, use, and quality of water in East Baton Rouge Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.

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Ellsworth Air Force Base is an Air Combat Command located approximately 10 miles northeast of Rapid City, South Dakota. Ellsworth Air Force Base occupies about 6,000 acres within Meade and Pennington Counties, and includes runways, airfield operations, industrial areas, housing, and recreational facilities. Fuels Area C within Ellsworth Air Force Base is a fuels storage area that is used to support the mission of the base. In fall of 2013, the U.S. Geological Survey began a study in cooperation with the U.S. Air Force, Ellsworth Air Force Base, to estimate groundwater-flow direction, select locations for permanent monitoring wells, and install and sample monitoring wells for petroleum hydrocarbon compounds within Fuels Area C. Nine monitoring wells were installed for the study within Fuels Area C during November 4–7, 2014. Soil core samples were collected during installation of eight of the monitoring wells and analyzed for benzene, toluene, ethylbenzene, total xylenes, naphthalene,m- and p-xylene, o-xylene, and gasoline- and diesel-range organic compounds. Groundwater samples were collected from seven of the nine wells (two of the monitoring wells did not contain enough water to sample or were dry) during November 19–21, 2014, and analyzed for select physical properties, benzene, toluene, ethylbenzene, total xylenes, naphthalene, m- and p-xylene, o-xylene, and gasoline- and diesel-range organic compounds. This report describes the nine monitoring well locations and presents the soil- and groundwater-quality data collected in 2014 for this study.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds939","collaboration":"Prepared in cooperation with U.S. Air Force, Ellsworth Air Force Base","usgsCitation":"Bender, D.A., and Rowe, B.L., 2015, Soil- and groundwater-quality data for petroleum hydrocarbon compounds within Fuels Area C, Ellsworth Air Force Base, South Dakota, 2014: U.S. Geological Survey Data Series 939, vi, 15 p., https://doi.org/10.3133/ds939.","productDescription":"vi, 15 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064094","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":300892,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds939.jpg"},{"id":300891,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0939/pdf/ds939.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300888,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0939/"}],"projection":"Albers Equal Area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"South Dakota","otherGeospatial":"Ellsworth Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.08327913284302,\n 44.13234155159352\n ],\n [\n -103.08096170425415,\n 44.12996206658891\n ],\n [\n -103.08080077171326,\n 44.132295348913864\n ],\n [\n -103.08190584182739,\n 44.13234155159352\n ],\n [\n -103.08246374130249,\n 44.13274197330301\n ],\n [\n -103.08327913284302,\n 44.13234155159352\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55682e22e4b0d9246a9f60e8","contributors":{"authors":[{"text":"Bender, David A. 0000-0002-1269-0948 dabender@usgs.gov","orcid":"https://orcid.org/0000-0002-1269-0948","contributorId":985,"corporation":false,"usgs":true,"family":"Bender","given":"David","email":"dabender@usgs.gov","middleInitial":"A.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rowe, Barbara L. blrowe@usgs.gov","contributorId":2673,"corporation":false,"usgs":true,"family":"Rowe","given":"Barbara","email":"blrowe@usgs.gov","middleInitial":"L.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547811,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70103075,"text":"70103075 - 2015 - Age, growth rates, and paleoclimate studies of deep sea corals","interactions":[],"lastModifiedDate":"2016-01-26T09:29:06","indexId":"70103075","displayToPublicDate":"2015-05-28T10:34:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Age, growth rates, and paleoclimate studies of deep sea corals","docAbstract":"

Deep-water corals are some of the slowest growing, longest-lived skeletal accreting marine organisms. These habitat-forming species support diverse faunal assemblages that include commercially and ecologically important organisms. Therefore, effective management and conservation strategies for deep-sea corals can be informed by precise and accurate age, growth rate, and lifespan characteristics for proper assessment of vulnerability and recovery from perturbations. This is especially true for the small number of commercially valuable, and potentially endangered, species that are part of the black and precious coral fisheries (Tsounis et al. 2010). In addition to evaluating time scales of recovery from disturbance or exploitation, accurate age and growth estimates are essential for understanding the life history and ecology of these habitat-forming corals. Given that longevity is a key factor for population maintenance and fishery sustainability, partly due to limited and complex genetic flow among coral populations separated by great distances, accurate age structure for these deep-sea coral communities is essential for proper, long-term resource management.

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In managing fish populations, especially at-risk species, realistic mathematical models are needed to help predict population response to potential management actions in the context of environmental conditions and changing climate while effectively incorporating the stochastic nature of real world conditions. We provide a key component of such a model for the endangered pallid sturgeon (Scaphirhynchus albus) in the form of an individual-based bioenergetics model influenced not only by temperature but also by flow. This component is based on modification of a known individual-based bioenergetics model through incorporation of: the observed ontogenetic shift in pallid sturgeon diet from marcroinvertebrates to fish; the energetic costs of swimming under flowing-water conditions; and stochasticity. We provide an assessment of how differences in environmental conditions could potentially alter pallid sturgeon growth estimates, using observed temperature and velocity from channelized portions of the Lower Missouri River mainstem. We do this using separate relationships between the proportion of maximum consumption and fork length and swimming cost standard error estimates for fish captured above and below the Kansas River in the Lower Missouri River. Critical to our matching observed growth in the field with predicted growth based on observed environmental conditions was a two-step shift in diet from macroinvertebrates to fish.

","language":"English","publisher":"The Geological Society of London","doi":"10.1144/SP408.10","usgsCitation":"Wildhaber, M.L., Dey, R., Wikle, C.K., Moran, E.H., Anderson, C.J., and Franz, K.J., 2015, A stochastic bioenergetics model based approach to translating large river flow and temperature in to fish population responses: The pallid sturgeon example: Geological Society of London Special Publications, v. 408, p. 1-17, https://doi.org/10.1144/SP408.10.","productDescription":"18 p. 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In 2012, the National Oceanic and Atmospheric Administration (NOAA) declared Atlantic Sturgeon Acipenser oxyrinchus oxyrinchus to be threatened or endangered throughout its range in U.S. waters. Restoration of the subspecies will require much new information, particularly on the location and timing of spawning. We used a combination of acoustic telemetry and sampling with anchored artificial substrates (spawning pads) to detect fall (September–November) spawning in the Roanoke River in North Carolina. This population is included in the Carolina Distinct Population Segment, which was classified by NOAA as endangered. Sampling was done immediately below the first shoals encountered by anadromous fishes, near Weldon. Our collection of 38 eggs during the 21 d that spawning pads were deployed appears to be the first such collection (spring or fall) for wild-spawned Atlantic Sturgeon eggs. Based on egg development stages, estimated spawning dates were September 17–18 and 18–19 at water temperatures from 25.3°C to 24.3°C and river discharge from 55 to 297 m3/s. These observations about fall spawning and habitat use should aid in protecting critical habitats and planning research on Atlantic Sturgeon spawning in other rivers.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2014.965344","usgsCitation":"Smith, J.A., Hightower, J.E., and Flowers, H.J., 2015, Fall spawning of Atlantic sturgeon in the Roanoke River, North Carolina: Transactions of the American Fisheries Society, v. 144, no. 1, p. 48-54, https://doi.org/10.1080/00028487.2014.965344.","productDescription":"7 p.","startPage":"48","endPage":"54","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055820","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":300862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Roanoke River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.59171485900879,\n 36.4214896403675\n ],\n [\n -77.59171485900879,\n 36.42967346850678\n ],\n [\n -77.57493495941162,\n 36.42967346850678\n ],\n [\n -77.57493495941162,\n 36.4214896403675\n ],\n [\n -77.59171485900879,\n 36.4214896403675\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"144","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-02","publicationStatus":"PW","scienceBaseUri":"5566dca4e4b0d9246a9ec289","contributors":{"authors":[{"text":"Smith, Joseph A.","contributorId":140973,"corporation":false,"usgs":false,"family":"Smith","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":547773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hightower, Joseph E. jhightower@usgs.gov","contributorId":835,"corporation":false,"usgs":true,"family":"Hightower","given":"Joseph","email":"jhightower@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flowers, H. Jared","contributorId":140974,"corporation":false,"usgs":false,"family":"Flowers","given":"H.","email":"","middleInitial":"Jared","affiliations":[],"preferred":false,"id":547774,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148271,"text":"70148271 - 2015 - Depositional conditions for the Kuna Formation, Red Dog Zn-PB-Ag-Barite District, Alaska, inferred from isotopic and chemical proxies","interactions":[],"lastModifiedDate":"2018-11-19T11:29:28","indexId":"70148271","displayToPublicDate":"2015-05-27T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Depositional conditions for the Kuna Formation, Red Dog Zn-PB-Ag-Barite District, Alaska, inferred from isotopic and chemical proxies","docAbstract":"

Water column redox conditions, degree of restriction of the depositional basin, and other paleoenvironmental parameters have been determined for the Mississippian Kuna Formation of northwestern Alaska from stratigraphic profiles of Mo, Fe/Al, and S isotopes in pyrite, C isotopes in organic matter, and N isotopes in bulk rock. This unit is important because it hosts the Red Dog and Anarraaq Zn-Pb-Ag ± barite deposits, which together constitute one of the largest zinc resources in the world. The isotopic and chemical proxies record a deep basin environment that became isolated from the open ocean, became increasingly reducing, and ultimately became euxinic. The basin was ventilated briefly and then became isolated again just prior to its demise as a discrete depocenter with the transition to the overlying Siksikpuk Formation. Ventilation corresponded approximately to the initiation of bedded barite deposition in the district, whereas the demise of the basin corresponded approximately to the formation of the massive sulfide deposits. The changes in basin circulation during deposition of the upper Kuna Formation may have had multiple immediate causes, but the underlying driver was probably extensional tectonic activity that also facilitated fluid flow beneath the basin floor. Although the formation of sediment-hosted sulfide deposits is generally favored by highly reducing conditions, the Zn-Pb deposits of the Red Dog district are not found in the major euxinic facies of the Kuna basin, nor did they form during the main period of euxinia. Rather, the deposits occur where strata were permeable to migrating fluids and where excess H2S was available beyond what was produced in situ by decomposition of local sedimentary organic matter. The known deposits formed mainly by replacement of calcareous strata that gained H2S from nearby highly carbonaceous beds (Anarraaq deposit) or by fracturing and vein formation in strata that produced excess H2S by reductive dissolution of preexisting barite (Red Dog deposits).

","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.110.5.1143","usgsCitation":"Johnson, C.A., Dumoulin, J.A., Burruss, R.A., and Slack, J.F., 2015, Depositional conditions for the Kuna Formation, Red Dog Zn-PB-Ag-Barite District, Alaska, inferred from isotopic and chemical proxies: Economic Geology, v. 110, no. 5, p. 1143-1156, https://doi.org/10.2113/econgeo.110.5.1143.","productDescription":"14 p.","startPage":"1143","endPage":"1156","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044384","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":300846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kuna Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.201171875,\n 68.60852084639889\n ],\n [\n -162.20214843749997,\n 68.57644086491786\n ],\n [\n -162.20214843749997,\n 67.75939813204413\n ],\n [\n -164.443359375,\n 67.7094454829218\n ],\n [\n -165.76171875,\n 68.10610151896537\n ],\n [\n -166.640625,\n 68.31814602144938\n ],\n [\n -166.201171875,\n 68.60852084639889\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"110","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-22","publicationStatus":"PW","scienceBaseUri":"5566dca1e4b0d9246a9ec285","contributors":{"authors":[{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":547642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":547643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burruss, Robert A. 0000-0001-6827-804X burruss@usgs.gov","orcid":"https://orcid.org/0000-0001-6827-804X","contributorId":558,"corporation":false,"usgs":true,"family":"Burruss","given":"Robert","email":"burruss@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":547641,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":547644,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70136357,"text":"sir20145236 - 2015 - Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line","interactions":[],"lastModifiedDate":"2015-11-04T12:07:21","indexId":"sir20145236","displayToPublicDate":"2015-05-27T09:30:00","publicationYear":"2015","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":"2014-5236","title":"Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line","docAbstract":"

A series of nine digital flood-inundation maps were developed for an 8-mile reach of the Hoosic River in North Adams and Williamstown, Massachusetts, by the U.S. Geological Survey (USGS) in cooperation with the Federal Emergency Management Agency. The coverage of the maps extends from the confluence with the North Branch Hoosic River to the Vermont State line. Peak flows with 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations, and to place the tropical storm Irene flood of August 28, 2011 into historical context. The hydraulic model was calibrated by using the current (2014) stage-discharge relation at the USGS streamgage Hoosic River near Williamstown, Massachusetts (01332500), and from documented high-water marks from the tropical storm Irene flood, which had approximately a 1-percent annual exceedance probability.

\n

The hydraulic model was used to compute water-surface profiles for flood stages referenced to the streamgage and ranging from 9 feet (ft; 624.45 ft North American Vertical Datum of 1988 [NAVD 1988]), which is near bankfull, to 16.1 ft (631.59 ft NAVD 1988), which exceeds the maximum recorded water level at the streamgage and the National Weather Service major flood stage of 13.0 ft. The mapped stages, 10.9 to 16.1 ft, were selected to match the stages of flows with annual exceedance probabilities between 20 and 0.2 percent, and thus do not fall at exact 1-ft increments. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 0.5-ft vertical accuracy to create a set of flood-inundation maps.

\n

The availability of the flood-inundation maps, combined with information regarding current (near real-time) stage from USGS streamgage Hoosic River near Williamstown, and forecasted flood stages from the National Weather Service Advanced Hydrologic Prediction Service will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, and post-flood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145236","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Lombard, P., and Bent, G.C., 2015, Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line: U.S. Geological Survey Scientific Investigations Report 2014-5236, Report: vi, 15 p.; Downloads Directory, https://doi.org/10.3133/sir20145236.","productDescription":"Report: vi, 15 p.; Downloads Directory","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059673","costCenters":[{"id":371,"text":"Maine Water Science 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5566dca7e4b0d9246a9ec28b","contributors":{"authors":[{"text":"Lombard, Pamela J. plombard@usgs.gov","contributorId":140923,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela J.","email":"plombard@usgs.gov","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":false,"id":547600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bent, Gardner C. 0000-0002-5085-3146 gbent@usgs.gov","orcid":"https://orcid.org/0000-0002-5085-3146","contributorId":1864,"corporation":false,"usgs":true,"family":"Bent","given":"Gardner","email":"gbent@usgs.gov","middleInitial":"C.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547601,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70173890,"text":"70173890 - 2015 - Effectiveness of two commercial rotenone formulations in the eradication of virile crayfish Orconectes virillis","interactions":[],"lastModifiedDate":"2016-06-22T13:39:50","indexId":"70173890","displayToPublicDate":"2015-05-27T06:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Effectiveness of two commercial rotenone formulations in the eradication of virile crayfish Orconectes virillis","docAbstract":"

The virile or northern crayfish Orconectes virilis is an invasive species throughout much of the USA, damaging aquatic communities where it is introduced. Therefore, identification of effective methods for its eradication from areas in which it is unwanted is important. We studied the effectiveness of two commercial formulations of rotenone, Chem Fish Regular and CFT Legumine, for virile crayfish control. Although both formulations were effective for fish eradication, earlier observations by fisheries managers suggested that the relative effectiveness of the two formulations differs for crayfish. The only noteworthy difference between the formulations is that the former contains a synergist. In our first experiment, we tested each toxicant at the maximum labeled dosage (5 ppm) and found CFT Legumine to be 100% ineffective (0% mortality), while the Chem Fish Regular treatment resulted in 12.5% mortality. After we deemed Chem Fish Regular to be the only toxicant with any effectiveness against virile crayfish, we tested concentrations from 5 to 50 ppm and found 10 times the maximum labeled dosage (50 ppm rotenone) was needed to kill all virile crayfish. Because crayfish burrow and can leave water, and because 100% eradication is usually desired, rotenone applied at the labeled rates will not be effective for crayfish control. However, treating a body of water with CFT Legumine to eradicate invasive fish while leaving desirable crayfish unharmed is possible.

","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2015.1017127","usgsCitation":"Recsetar, M.S., and Bonar, S.A., 2015, Effectiveness of two commercial rotenone formulations in the eradication of virile crayfish Orconectes virillis: North American Journal of Fisheries Management, v. 35, no. 3, p. 616-620, https://doi.org/10.1080/02755947.2015.1017127.","productDescription":"5 p.","startPage":"616","endPage":"620","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057198","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":324228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-27","publicationStatus":"PW","scienceBaseUri":"576bb6b2e4b07657d1a22896","contributors":{"authors":[{"text":"Recsetar, Matthew S.","contributorId":67395,"corporation":false,"usgs":true,"family":"Recsetar","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":640357,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":638894,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70135042,"text":"70135042 - 2015 - Estimates of hydraulic fracturing (Frac) sand production, consumption, and reserves in the United States","interactions":[],"lastModifiedDate":"2016-11-09T11:59:32","indexId":"70135042","displayToPublicDate":"2015-05-26T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5225,"text":"Rock Products","active":true,"publicationSubtype":{"id":10}},"title":"Estimates of hydraulic fracturing (Frac) sand production, consumption, and reserves in the United States","docAbstract":"

The practice of fracturing reservoir rock in the United States as a method to increase the flow of oil and gas from wells has a relatively long history and can be traced back to 1858 in Fredonia, New York, when a gas well situated in shale of the Marcellus Formation was successfully fractured using black powder as a blasting agent. Nearly all domestic hydraulic fracturing, often referred to as hydrofracking or fracking, is a process where fluids are injected under high pressure through perforations in the horizontal portion of a well casing in order to generate fractures in reservoir rock with low permeability (“tight”). Because the fractures are in contact with the well bore they can serve as pathways for the recovery of gas and oil. To prevent the fractures generated by the fracking process from closing or becoming obstructed with debris, material termed “proppant,” most commonly high-silica sand, is injected along with water-rich fluids to maintain or “prop” open the fractures. The first commercial application of fracking in the oil and gas industry took place in Oklahoma and Texas during the 1940s. In 1949, over 300 wells, mostly vertical, were fracked (ALL Consulting, LLC, 2012; McGee, 2012; Veil, 2012) and used silica sand as a proppant (Fracline, 2011). The resulting increase in well productivity demonstrated the significant potential that fracking might have for the oil and gas industry.

","language":"English","publisher":"Rock Products","usgsCitation":"Bleiwas, D.I., 2015, Estimates of hydraulic fracturing (Frac) sand production, consumption, and reserves in the United States: Rock Products, v. 118, no. 5, p. 60-60.","productDescription":"1 p.","startPage":"60","endPage":"60","ipdsId":"IP-061248","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":330887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":330886,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://connection.ebscohost.com/c/articles/103170641/estimates-hydraulic-fracturing-frac-sand-production-consumption-reserves-united-states"}],"volume":"118","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"582443f6e4b09065cdf30542","contributors":{"authors":[{"text":"Bleiwas, Donald I. bleiwas@usgs.gov","contributorId":1434,"corporation":false,"usgs":true,"family":"Bleiwas","given":"Donald","email":"bleiwas@usgs.gov","middleInitial":"I.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":526711,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70171170,"text":"70171170 - 2015 - Initiation of migration and movement rates of Atlantic salmon smolts in fresh water","interactions":[],"lastModifiedDate":"2016-05-25T16:18:28","indexId":"70171170","displayToPublicDate":"2015-05-25T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Initiation of migration and movement rates of Atlantic salmon smolts in fresh water","docAbstract":"

Timing of ocean entry is critical for marine survival of both hatchery and wild Atlantic salmon (Salmo salar) smolts. Management practices and barriers to migration such as dams may constrain timing of smolt migrations resulting in suboptimal performance at saltwater entry. We modeled influences of stocking location, smolt development, and environmental conditions on (i) initiation of migration by hatchery-reared smolts and (ii) movement rate of hatchery- and wild-reared Atlantic salmon smolts in the Penobscot River, Maine, USA, from 2005 through 2014 using acoustic telemetry data. We also compared movement rates in free-flowing reaches with rates in reaches with hydropower dams and head ponds. We compared movement rates before and after (1) removal of two mainstem dams and (2) construction of new powerhouses. Initiation of movement by hatchery fish was influenced by smolt development, stocking location, and environmental conditions. Smolts with the greatest gill Na+, K+-ATPase (NKA) activity initiated migration 24 h sooner than fish with the lowest gill NKA activity. Fish with the greatest cumulative thermal experience initiated migration 5 days earlier than those with lowest cumulative thermal experience. Smolts released furthest from the ocean initiated migration earlier than those released downstream, but movement rate increased by fivefold closer to the ocean, indicating behavioral trade-offs between initiation and movement rate. Dams had a strong effect on movement rate. Movement rate increased from 2.8 to 5.4 km·h−1 in reaches where dams were removed, but decreased from 2.1 to 0.1 km·h−1 in reaches where new powerhouses were constructed. Movement rate varied throughout the migratory period and was inversely related to temperature. Fish moved slower at extreme high or low discharge. Responses in fish movement rates to dam removal indicate the potential scope of recovery for these activities.

","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2014-0570","usgsCitation":"Stich, D.S., Kinnison, M.T., Kocik, J.F., and Zydlewski, J.D., 2015, Initiation of migration and movement rates of Atlantic salmon smolts in fresh water: Canadian Journal of Fisheries and Aquatic Sciences, v. 72, no. 9, p. 1339-1351, https://doi.org/10.1139/cjfas-2014-0570.","productDescription":"13 p.","startPage":"1339","endPage":"1351","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060916","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":321685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.5,\n 44.7\n ],\n [\n -68.5,\n 45.1\n ],\n [\n -68.8,\n 45.1\n ],\n [\n -68.8,\n 44.7\n ],\n [\n -68.5,\n 44.7\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"72","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5746ccbde4b07e28b662dce6","contributors":{"authors":[{"text":"Stich, Daniel S.","contributorId":139212,"corporation":false,"usgs":false,"family":"Stich","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":12606,"text":"University of Maine, Dept of Plant, Soil, & Envir Sciences","active":true,"usgs":false}],"preferred":false,"id":630301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinnison, Michael T.","contributorId":169617,"corporation":false,"usgs":false,"family":"Kinnison","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":630302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kocik, John F.","contributorId":103162,"corporation":false,"usgs":true,"family":"Kocik","given":"John","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":630303,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":630304,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148195,"text":"ofr20151106 - 2015 - Estimating exposure of piscivorous birds and sport fish to mercury in California lakes using prey fish monitoring: a predictive tool for managers","interactions":[],"lastModifiedDate":"2017-11-27T14:27:39","indexId":"ofr20151106","displayToPublicDate":"2015-05-25T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1106","title":"Estimating exposure of piscivorous birds and sport fish to mercury in California lakes using prey fish monitoring: a predictive tool for managers","docAbstract":"

Numerous water bodies in California are listed under the Clean Water Act as being impaired due to mercury (Hg) contamination. The Surface Water Ambient Monitoring Program (SWAMP), via the Bioaccumulation Oversight Group (BOG), has recently completed statewide surveys of contaminants in sport fish tissue from more than 250 lakes and rivers in California and throughout coastal waters. This effort focused on human health issues but did not include beneficial uses by wildlife. Many piscivorous birds such as grebes, terns, cormorants, and mergansers eat fish smaller than those that were sampled by BOG, and sport fish Hg concentrations are not always indicative of wildlife exposure to Hg; therefore, the BOG surveys could not address whether wildlife were at risk due to Hg-induced reproductive impairment in these lakes.

\n

We used western grebes (Aechmophorus occidentalis) and Clark’s grebes (Aechmophorus clarkii) as our index of wildlife exposure to Hg in California lakes. Grebes are widely distributed in lakes throughout California and, as piscivorous waterbirds, are near the top of the food chain in lakes. Additionally, grebes become flightless after they arrive at their summer locations. Thus, grebes are useful representatives for wildlife risk from local, lake-specific contaminant exposure. Grebes also breed at many lakes throughout California, making them susceptible to impaired reproduction due to local Hg contamination.

\n

We developed a tool for estimating wildlife and sport fish risk from Hg exposure based on Hg concentrations in prey fish. This quantitative tool can be used to predict Hg concentrations in grebe blood, grebe eggs, and sport fish, thus facilitating a feasible alternative for adequately estimating wildlife exposure when more comprehensive wildlife sampling is not possible. Specifically, we sampled grebes, prey fish, and sport fish simultaneously at 25 lakes throughout California during the spring and summer of 2012 and 2013 when breeding birds are particularly vulnerable to Hg-induced reproductive impairment. We selected lakes based on a combination of factors, including lakes

\n
    \n
  1. from southern and northern California,
    2. \n
  2. of various sizes, shapes, and elevations,
    3. \n
  3. with a range of sport fish Hg exposure levels ,
    4. \n
  4. where largemouth bass (Micropterus salmoides) was the primary sport fish, and
    5. \n
  5. with a history of use by grebes.
    6. \n
\n

Using these factors ensured that our results are representative of a broad range of lakes and reservoirs in California and are comparable to prior BOG studies.

\n

Specifically, we addressed three management questions:

\n
    \n
  1. Does methylmercury pose significant risks to aquatic life in a representative sample of California lakes and reservoirs?
    2. \n
  2. Can a correlational approach be applied on a statewide basis to estimate risks to birds?
    3. \n
  3. What are appropriate water-quality monitoring requirements to address methylmercury exposure in wildlife?
    4. \n
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151106","collaboration":"USFWS, CA State Water Resources Control Board","usgsCitation":"Ackerman, J., Hartman, C.A., Eagles-Smith, C.A., Herzog, M., Davison, J., Ichikawa, G., and Bonnema, A., 2015, Estimating exposure of piscivorous birds and sport fish to mercury in California lakes using prey fish monitoring: a predictive tool for managers: U.S. Geological Survey Open-File Report 2015-1106, Report: vii, 48 p.; Risk Estimator Tool, https://doi.org/10.3133/ofr20151106.","productDescription":"Report: vii, 48 p.; Risk Estimator Tool","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065497","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":300763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151106.jpg"},{"id":300757,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1106/"},{"id":300761,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1106/pdf/ofr2015-1106.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300762,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1106/downloads/ofr2015-1106_USGS_Wildlife_and_Sport_Fish_Risk_Estimator_Tool_Final.xlsx","text":"USGS Wildlife and Sport Fish Risk Estimator Tool Final","size":"472 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"USGS Wildlife and Sport Fish Risk Estimator Tool Final"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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32.63937487360669\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5564399be4b0afeb70725816","contributors":{"authors":[{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":547554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131109,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":547567,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547568,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herzog, Mark P. mherzog@usgs.gov","contributorId":3965,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark P.","email":"mherzog@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":547569,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davison, Jay","contributorId":92353,"corporation":false,"usgs":true,"family":"Davison","given":"Jay","email":"","affiliations":[],"preferred":false,"id":547570,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ichikawa, Gary","contributorId":140920,"corporation":false,"usgs":false,"family":"Ichikawa","given":"Gary","email":"","affiliations":[],"preferred":false,"id":547571,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bonnema, Autumn","contributorId":140921,"corporation":false,"usgs":false,"family":"Bonnema","given":"Autumn","email":"","affiliations":[],"preferred":false,"id":547572,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70243861,"text":"70243861 - 2015 - End-of-winter snow depth variability on glaciers in Alaska","interactions":[],"lastModifiedDate":"2023-05-24T15:05:42.814122","indexId":"70243861","displayToPublicDate":"2015-05-23T15:56:20","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"End-of-winter snow depth variability on glaciers in Alaska","docAbstract":"

A quantitative understanding of snow thickness and snow water equivalent (SWE) on glaciers is essential to a wide range of scientific and resource management topics. However, robust SWE estimates are observationally challenging, in part because SWE can vary abruptly over short distances in complex terrain due to interactions between topography and meteorological processes. In spring 2013, we measured snow accumulation on several glaciers around the Gulf of Alaska using both ground- and helicopter-based ground-penetrating radar surveys, complemented by extensive ground truth observations. We found that SWE can be highly variable (40% difference) over short spatial scales (tens to hundreds of meters), especially in the ablation zone where the underlying ice surfaces are typically rough. Elevation provides the dominant basin-scale influence on SWE, with gradients ranging from 115 to 400 mm/100 m. Regionally, total accumulation and the accumulation gradient are strongly controlled by a glacier's distance from the coastal moisture source. Multiple linear regressions, used to calculate distributed SWE fields, show that robust results require adequate sampling of the true distribution of multiple terrain parameters. Final SWE estimates (comparable to winter balances) show reasonable agreement with both the Parameter-elevation Relationships on Independent Slopes Model climate data set (9–36% difference) and the U.S. Geological Survey Alaska Benchmark Glaciers (6–36% difference). All the glaciers in our study exhibit substantial sensitivity to changing snow-rain fractions, regardless of their location in a coastal or continental climate. While process-based SWE projections remain elusive, the collection of ground-penetrating radar (GPR)-derived data sets provides a greatly enhanced perspective on the spatial distribution of SWE and will pave the way for future work that may eventually allow such projections.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JF003539","usgsCitation":"Mcgrath, D., Sass, L., O’Neel, S., Arendt, A., Wolken, G., Gusmeroli, A., Kienholz, C., and McNeil, C., 2015, End-of-winter snow depth variability on glaciers in Alaska: Journal of Geophysical Research: Earth Surface, v. 120, no. 8, p. 1530-1550, https://doi.org/10.1002/2015JF003539.","productDescription":"21 p.","startPage":"1530","endPage":"1550","ipdsId":"IP-064450","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":472080,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jf003539","text":"Publisher Index Page"},{"id":438700,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K072BV","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Valdez Glacier, Alaska; 2013"},{"id":438699,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F769M4","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Eklutna Glacier, Alaska; 2013"},{"id":438698,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z60M35","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Eureka Glacier, Alaska; 2013"},{"id":438697,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TH8JRR","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Gulkana Glacier, Alaska; 2013"},{"id":438696,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BG2M16","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data,Taku Glacier, Alaska; 2013"},{"id":438695,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G73BRH","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Wolverine Glacier, Alaska; 2013"},{"id":438694,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76Q1V81","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Scott Glacier, Alaska; 2013"},{"id":417368,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -151.14517565646327,\n 62.938908091713984\n ],\n [\n -151.14517565646327,\n 57.55690540490215\n ],\n [\n -137.04945194161488,\n 57.55690540490215\n ],\n [\n -137.04945194161488,\n 62.938908091713984\n ],\n [\n -151.14517565646327,\n 62.938908091713984\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"120","issue":"8","noUsgsAuthors":false,"publicationDate":"2015-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Mcgrath, Daniel 0000-0002-9462-6842","orcid":"https://orcid.org/0000-0002-9462-6842","contributorId":220417,"corporation":false,"usgs":true,"family":"Mcgrath","given":"Daniel","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":873543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sass, Louis C. 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":873544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":873545,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arendt, Anthony 0000-0003-0429-6905","orcid":"https://orcid.org/0000-0003-0429-6905","contributorId":220394,"corporation":false,"usgs":false,"family":"Arendt","given":"Anthony","email":"","affiliations":[{"id":40162,"text":"U. of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":873546,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolken, Gabriel","contributorId":305685,"corporation":false,"usgs":false,"family":"Wolken","given":"Gabriel","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":873547,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gusmeroli, Alessio 0000-0002-8355-5591","orcid":"https://orcid.org/0000-0002-8355-5591","contributorId":220395,"corporation":false,"usgs":false,"family":"Gusmeroli","given":"Alessio","email":"","affiliations":[{"id":40163,"text":"U of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":873548,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kienholz, Christian 0000-0001-7962-4446","orcid":"https://orcid.org/0000-0001-7962-4446","contributorId":220396,"corporation":false,"usgs":false,"family":"Kienholz","given":"Christian","email":"","affiliations":[{"id":40162,"text":"U. of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":873549,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McNeil, Christopher J. 0000-0003-4170-0428 cmcneil@usgs.gov","orcid":"https://orcid.org/0000-0003-4170-0428","contributorId":5803,"corporation":false,"usgs":true,"family":"McNeil","given":"Christopher J.","email":"cmcneil@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":873550,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70147415,"text":"sir20155061 - 2015 - Groundwater flow in the Brunswick/Glynn County area, Georgia, 2000-04","interactions":[],"lastModifiedDate":"2017-01-18T13:19:32","indexId":"sir20155061","displayToPublicDate":"2015-05-22T15:00:00","publicationYear":"2015","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":"2015-5061","title":"Groundwater flow in the Brunswick/Glynn County area, Georgia, 2000-04","docAbstract":"

An existing regional steady-state model for coastal Georgia, and parts of South Carolina and Florida, was revised to evaluate the local effects of pumping on the migration of high chloride (saline) water in the Upper Floridan aquifer located in the Brunswick/Glynn County, Georgia (Ga.) area. Revisions were focused on enhancing the horizontal and vertical resolution of the regional model grid in the vicinity of saline water. Modifications to the regional model consisted of (1) limiting grid size to a maximum of 500 feet (ft) per side in the vicinity of chloride contamination; (2) representing the upper and lower Brunswick aquifers with distinct model layers; (3) similarly, representing upper and lower water-bearing zones of the Upper Floridan aquifer with distinct model layers in Glynn and Camden Counties, Ga.; and (4) establishing new hydraulic-property zones in the Upper Floridan aquifer. The revised model simulated steady-state conditions that were assumed to exist during 2000 and 2004.

\n

Calibration of the revised steady-state model using pumping rates from 2000 indicates a \"good\" match (±10 ft) based on 181 observations, with median residuals (simulated minus observed water levels) in each of the active model layers ranging from -8.62 to 4.67 ft, and root mean square error (RMSE) ranging from 10.9 to 11.4 ft. In the Brunswick/Glynn County area, groundwater-level residuals in the upper water-bearing zone of the Upper Floridan aquifer (layer 7) indicate an \"excellent\" match (±5 ft) based on 41 observations with a median residual of -0.35 ft and RMSE of 4.32 ft.

\n

Calibration of the revised steady-state model using 2004 pumping rates and adjusted specified-head input values in the Floridan aquifer system indicates a \"good\" match (-10 ft) based on 88 observations, with median residuals in each of the active model layers ranging from -6.31 to -2.05 ft, and RMSE ranging from -6.95 to 14.5 ft. In the Brunswick/Glynn County area, groundwater-level residuals in the upper water-bearing zone of the Upper Floridan aquifer (layer 7) indicate an \"excellent\" match (±5 ft) based on 32 observations with a median residual of -1.50 ft and RMSE of 5.34 ft.

\n

Simulated potentiometric surfaces for 2000 and 2004 indicate coastward groundwater flow in the Upper and Lower Floridan aquifers influenced by pumping centers at Savannah, Jesup, and Brunswick, Ga., and indicate steep potentiometric gradients to the west and north of the Gulf Trough. In the Brunswick/Glynn County area, simulated industrial production wells located north of downtown Brunswick intercept local groundwater flow in the upper and lower water-bearing zones of the Upper Floridan aquifer and have created a cone of depression that locally alters the regional coastward flow direction.

\n

Maps of simulated water-level change during the 2000-04 period show differences in groundwater levels in the Upper Floridan aquifer that range from -2.5 ft to more than 5 ft in areas of coastal Georgia, and more than 20 ft near the Georgia-Florida State Line. Positive values indicate higher simulated water levels during 2004 than during 2000, which were caused by reduced pumping in the Upper Floridan aquifer prompted by the shutdown of a paper mill near the southern model boundary in 2002 and increased recharge following a prolonged drought during 1998-2002.

\n

Simulated potentiometric profiles for 2000 and 2004 were used to evaluate the potentiometric gradients in the upper water-bearing zone of the Upper Floridan aquifer (layer 7) near the chloride plume in the downtown Brunswick area. Four potentiometric profiles were constructed for 2000 to compare the simulated and observed water levels in 13 wells and were oriented outward from a primary well field. The simulated potentiometric gradients from the four profiles for 2000 ranged from 3.6 to 5.2 feet per mile (ft/mi) compared to observed values ranging from 4.1 to 5.6 ft/mi. The five potentiometric profiles constructed for 2004 allowed for a similar comparison using simulated and observed water levels in 18 wells. The simulated potentiometric gradients from the five profiles for 2000 ranged from 3.6 to 11.1 ft/mi compared to observed values ranging from 3.8 to 10.2 ft/mi. Simulated potentiometric gradients were higher for 2004 than for 2000 because of the inclusion of a well located within the cone of depression near downtown Brunswick.

\n

Composite-scaled sensitivities of the model parameters indicate the revised model is most sensitive to pumping rates, followed by the horizontal hydraulic conductivity in the Upper Floridan aquifer for zones along coastal Georgia. The revised model is least sensitive to the horizontal hydraulic conductivity of the confining units and vertical hydraulic conductivity of the aquifers. For parameters defined by hydraulic-property zones in the upper and lower water-bearing zones of the Upper Floridan aquifer, such as horizontal hydraulic conductivity, model sensitivity was not as great in the Brunswick/Glynn County area as other areas along coastal Georgia. The model exhibited more sensitivity to these parameters however, than to parameters representing the majority of zones defining the vertical hydraulic conductivity of the confining units, which originally were assumed to govern upward migration of chloride contamination into this aquifer.

\n

Analysis of simulated water-budget components for 2000 and 2004 indicate that specified-head boundaries in the Floridan aquifer system to the south and southwest of the regional model area control about 70 percent of inflows and nearly 50 percent of outflows to the model region. Other water-budget components indicate an 80-million-gallon-per-day decrease in pumping from the Floridan aquifer system during this period.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155061","usgsCitation":"Cherry, G.S., 2015, Groundwater flow in the Brunswick/Glynn County area, Georgia, 2000-04: U.S. Geological Survey Scientific Investigations Report 2015-5061, viii, 88 p., https://doi.org/10.3133/sir20155061.","productDescription":"viii, 88 p.","numberOfPages":"100","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2000-01-01","temporalEnd":"2004-12-31","ipdsId":"IP-015105","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":300754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155061.jpg"},{"id":300753,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5061/pdf/sir2015-5061.pdf","text":"Report","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5061 Report"},{"id":300752,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5061/"}],"country":"United States","state":"Georgia","county":"Brunswick County, Glynn County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.52284622192383,\n 31.121439619206097\n ],\n [\n -81.52284622192383,\n 31.178147212117395\n ],\n [\n -81.4577865600586,\n 31.178147212117395\n ],\n [\n -81.4577865600586,\n 31.121439619206097\n ],\n [\n -81.52284622192383,\n 31.121439619206097\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5560452be4b0afeb70724149","contributors":{"authors":[{"text":"Cherry, Gregory S. 0000-0002-5567-1587 gccherry@usgs.gov","orcid":"https://orcid.org/0000-0002-5567-1587","contributorId":1567,"corporation":false,"usgs":true,"family":"Cherry","given":"Gregory","email":"gccherry@usgs.gov","middleInitial":"S.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545930,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148122,"text":"ofr20151104 - 2015 - Exposure-related effects of Pseudomonas fluorescens, strain CL145A, on coldwater, coolwater, and warmwater fish","interactions":[],"lastModifiedDate":"2015-05-22T13:38:15","indexId":"ofr20151104","displayToPublicDate":"2015-05-22T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1104","title":"Exposure-related effects of Pseudomonas fluorescens, strain CL145A, on coldwater, coolwater, and warmwater fish","docAbstract":"

The exposure-related effects of a commercially prepared spray-dried powder (SDP) formulation of Pseudomonas fluorescens, strain CL145A, were evaluated on coldwater, coolwater, and warmwater fish endemic to the Great Lakes and Upper Mississippi River Basins. Nine species of young-of-the-year fish were exposed to SDP for 24 hours by using continuous-flow, serial-dilution exposure systems at temperatures of 12 degrees Celsius (°C; 2 species; Oncorhynchus mykiss [rainbow trout] and Salvelinus fontinalis [brook trout]), 17 °C (3 species; Perca flavescens [yellow perch], Sander vitreus [walleye], and Acipenser fulvescens [lake sturgeon]), or 22 °C (4 species; Micropterus salmoides [largemouth bass], Micropterus dolomieu [smallmouth bass], Lepomis macrochirus [bluegill sunfish], and Ictalurus punctatus [channel catfish]).

\n

Treatments, which were nominal target concentrations of SDP (as active ingredient) of 50, 100, 200, and 300 milligrams per liter (mg/L), were continuously applied for 24 hours by the addition of a test article stock solution into the main water inflow of each exposure system's dilution box. The SDP-treated water was then serially diluted through a series of dilution cells before delivery to the test chambers. The exposure concentrations measured were 61.5 to 81.4 percent of the target concentration. After exposure, fish were monitored for 22 days to assess exposure-related latent effects.

\n

Analyses of test animal condition factors and survival revealed that a 24-hour continuous dose of SDP affected all species. Calculated concentrations of SDP that would be lethal to 50 percent of the test animals (LC50) for the coldwater species were 19.2 and 104.6 mg/L for rainbow and brook trout, respectively. The LC50's for the coolwater species were 185.4, 176.9 and 8.9 mg/L for yellow perch, walleye, and lake sturgeon, respectively. The LC50's for the warmwater species were 173.6, 139.4, and 63.1 for the largemouth bass, smallmouth bass, and channel catfish, respectively. A reliable LC50 for bluegill sunfish could not be calculated because mortality in the SDP-treated groups did not exceed 20 percent.

\n

Further investigations to evaluate the SDP-exposure related effects on freshwater fish at the maximum approved open-water label concentration and exposure duration (100 mg/L for 8 hours) and using the expected lentic application technique (static application) are warranted. The variation in tolerance to P. fluorescens, strain CL145A, exposure observed in this study indicates that fish species community composition should be considered before SDP is applied in open-water environments.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151104","usgsCitation":"Luoma, J.A., Weber, K.L., and Denise A. Mayer, 2015, Exposure-related effects of Pseudomonas fluorescens, strain CL145A, on coldwater, coolwater, and warmwater fish: U.S. Geological Survey Open-File Report 2015-1104, viii, 1632 p., https://doi.org/10.3133/ofr20151104.","productDescription":"viii, 1632 p.","numberOfPages":"1641","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064984","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":300743,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1104/pdf/ofr2015-1104.pdf","text":"Report","size":"56.6 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"OF 2015-1104 Report"},{"id":300744,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1050/","text":"Open-File Report 2015-1050","description":"Companion Report - Efficacy of Pseudomonas fluorescens (Pf-CL145A) Spray Dried Powder for Controlling Zebra Mussels Adhering to Test Substrates"},{"id":300745,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1051/","text":"Open-File Report 2015-1051","description":"Companion Report - Efficacy of Pseudomonas fluorescens Strain CL145A Spray Dried Powder for Controlling Zebra Mussels Adhering to Native Unionid Mussels Within Field Enclosures"},{"id":300746,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1064/","text":"Open-File Report 2015-1064","description":"Companion Report - Safety of Spray-Dried Powder Formulated Pseudomonas fluorescens Strain CL145A Exposure to Subadult/Adult Unionid Mussels During Simulated Open-Water Treatments"},{"id":300742,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1104/"},{"id":300747,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1066/","text":"Open-File Report 2015-1066","description":"Companion Report - Exposure-Related Effects of Pseudomonas fluorescens (Pf-CL145A) on Juvenile Unionid Mussels"},{"id":300748,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1094","text":"Open-File Report 2015-1094","description":"Companion Report - Exposure-Related Effects of Formulated Pseudomonas fluorescens Strain CL145A to Glochidia from Seven Unionid Mussel Species"},{"id":300749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151104.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55604527e4b0afeb70724145","contributors":{"authors":[{"text":"Luoma, James A. 0000-0003-3556-0190 jluoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3556-0190","contributorId":4449,"corporation":false,"usgs":true,"family":"Luoma","given":"James","email":"jluoma@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":547449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weber, Kerry L. klweber@usgs.gov","contributorId":4750,"corporation":false,"usgs":true,"family":"Weber","given":"Kerry","email":"klweber@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":547450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Denise A. Mayer","contributorId":140891,"corporation":false,"usgs":false,"family":"Denise A. Mayer","affiliations":[{"id":13605,"text":"New York State Department of Education, Cambridge Field Laboratory","active":true,"usgs":false}],"preferred":false,"id":547451,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70146512,"text":"sir20155055 - 2015 - Comparisons of estimates of annual exceedance-probability discharges for small drainage basins in Iowa, based on data through water year 2013","interactions":[],"lastModifiedDate":"2015-05-22T13:13:31","indexId":"sir20155055","displayToPublicDate":"2015-05-22T14:15:00","publicationYear":"2015","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":"2015-5055","title":"Comparisons of estimates of annual exceedance-probability discharges for small drainage basins in Iowa, based on data through water year 2013","docAbstract":"

Traditionally, the Iowa Department of Transportation has used the Iowa Runoff Chart and single-variable regional-regression equations (RREs) from a U.S. Geological Survey report (published in 1987) as the primary methods to estimate annual exceedance-probability discharge (AEPD) for small (20 square miles or less) drainage basins in Iowa. With the publication of new multi- and single-variable RREs by the U.S. Geological Survey (published in 2013), the Iowa Department of Transportation needs to determine which methods of AEPD estimation provide the best accuracy and the least bias for small drainage basins in Iowa.

\n

Twenty five streamgages with drainage areas less than 2 square miles (mi2) and 55 streamgages with drainage areas between 2 and 20 mi2 were selected for the comparisons that used two evaluation metrics. Estimates of AEPDs calculated for the streamgages using the expected moments algorithm/multiple Grubbs-Beck test analysis method were compared to estimates of AEPDs calculated from the 2013 multivariable RREs; the 2013 single-variable RREs; the 1987 single-variable RREs; the TR-55 rainfall-runoff model; and the Iowa Runoff Chart.

\n

For the 25 streamgages with drainage areas less than 2 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the TR-55 method for flood regions 1 and 3 (published in 2013) and by using the 1987 single-variable RREs for flood region 2 (published in 2013).

\n

For drainage basins with areas between 2 and 20 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the 1987 single-variable RREs for the Southern Iowa Drift Plain landform region and for flood region 3 (published in 2013), by using the 2013 multivariable RREs for the Iowan Surface landform region, and by using the 2013 or 1987 single-variable RREs for flood region 2 (published in 2013). For all other landform or flood regions in Iowa, use of the 2013 single-variable RREs may provide the best overall accuracy and the least bias.

\n

An examination was conducted to understand why the 1987 single-variable RREs seem to provide better accuracy and less bias than either of the 2013 multi- or single-variable RREs. A comparison of 1-percent annual exceedance-probability regression lines for hydrologic regions 1-4 from the 1987 single-variable RREs and for flood regions 1-3 from the 2013 single-variable RREs indicates that the 1987 single-variable regional-regression lines generally have steeper slopes and lower discharges when compared to 2013 single-variable regional-regression lines for corresponding areas of Iowa. The combination of the definition of hydrologic regions, the lower discharges, and the steeper slopes of regression lines associated with the 1987 single-variable RREs seem to provide better accuracy and less bias when compared to the 2013 multi- or single-variable RREs; better accuracy and less bias was determined particularly for drainage areas less than 2 mi2, and also for some drainage areas between 2 and 20 mi2. The 2013 multi- and single-variable RREs are considered to provide better accuracy and less bias for larger drainage areas. Results of this study indicate that additional research is needed to address the curvilinear relation between drainage area and AEPDs for areas of Iowa.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155055","collaboration":"Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project TR-678)","usgsCitation":"Eash, D.A., 2015, Comparisons of estimates of annual exceedance-probability discharges for small drainage basins in Iowa, based on data through water year 2013: U.S. Geological Survey Scientific Investigations Report 2015-5055, viii, 37 p., https://doi.org/10.3133/sir20155055.","productDescription":"viii, 37 p.","numberOfPages":"50","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058580","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":300734,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155055.jpg"},{"id":300732,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5055/pdf/sir2015-5055.pdf","text":"Report","size":"2.06 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5055"},{"id":300731,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5055/"},{"id":300733,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5055/downloads/","text":"Downloads Directory","linkFileType":{"id":3,"text":"xlsx"},"description":"Contains: Table 3, 4, 8, 9, and 10 in XLSX format","linkHelpText":"SIR 2015-5055 Downloads Directory"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.7236328125,\n 43.51668853502906\n ],\n [\n -91.2744140625,\n 43.51668853502906\n ],\n [\n -91.01074218749999,\n 43.29320031385282\n ],\n [\n -91.20849609375,\n 43.11702412135048\n ],\n [\n -91.01074218749999,\n 42.79540065303723\n ],\n [\n -90.703125,\n 42.65012181368022\n ],\n [\n -90.06591796875,\n 42.08191667830631\n ],\n [\n -90.32958984375,\n 41.508577297439324\n ],\n [\n -91.01074218749999,\n 41.37680856570233\n ],\n [\n -90.85693359375,\n 40.896905775860006\n ],\n [\n -91.47216796875,\n 40.29628651711716\n ],\n [\n -91.8017578125,\n 40.58058466412761\n ],\n [\n -95.73486328124999,\n 40.54720023441049\n ],\n [\n -95.97656249999999,\n 40.713955826286046\n ],\n [\n -96.70166015624999,\n 42.73087427928485\n ],\n [\n -96.70166015624999,\n 43.14909399920127\n ],\n [\n -96.7236328125,\n 43.51668853502906\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5560451be4b0afeb70724141","contributors":{"authors":[{"text":"Eash, David A. 0000-0002-2749-8959 daeash@usgs.gov","orcid":"https://orcid.org/0000-0002-2749-8959","contributorId":1887,"corporation":false,"usgs":true,"family":"Eash","given":"David","email":"daeash@usgs.gov","middleInitial":"A.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544976,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70141461,"text":"sir20155015 - 2015 - Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels","interactions":[],"lastModifiedDate":"2015-05-28T09:27:59","indexId":"sir20155015","displayToPublicDate":"2015-05-22T12:30:00","publicationYear":"2015","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":"2015-5015","title":"Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels","docAbstract":"

The South Platte River and underlying alluvial aquifer form an important hydrologic resource in northeastern Colorado that provides water to population centers along the Front Range and to agricultural communities across the rural plains. Water is regulated based on seniority of water rights and delivered using a network of administration structures that includes ditches, reservoirs, wells, impacted river sections, and engineered recharge areas. A recent addendum to Colorado water law enacted during 2002-2003 curtailed pumping from thousands of wells that lacked authorized augmentation plans. The restrictions in pumping were hypothesized to increase water storage in the aquifer, causing groundwater to rise near the land surface at some locations. The U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board and the Colorado Water Institute, completed an assessment of 60 years (yr) of historical groundwater-level records collected from 1953 to 2012 from 1,669 wells. Relations of \"high\" groundwater levels, defined as depth to water from 0 to 10 feet (ft) below land surface, were compared to precipitation, river discharge, and 36 geographic and administrative attributes to identify natural and human controls in areas with shallow groundwater.

\n

Averaged per decade and over the entire aquifer, depths to groundwater varied between 24 and 32 ft over the 60-yr record. The shallowest average depth to water was identified during 1983-1992, which also recorded the highest levels of decadal precipitation. Average depth to water was greatest (32 ft) during 1953-1962 and intermediate (30 ft) in the recent decade (2003-2012) following curtailment of pumping. Between the decades 1993-2002 and 2003-2012, groundwater levels declined about 2 ft across the aquifer. In comparison, in areas where groundwater levels were within 20 ft of the land surface, observed groundwater levels rose about 0.6 ft, on average, during the same period, which demonstrated preferential rise in areas with shallow groundwater.

\n

Approximately 29 percent of water-level observations were identified as high groundwater in the South Platte River alluvial aquifer over the 60-yr record. High groundwater levels were found in 17 to 33 percent of wells examined by decade, with the largest percentages occurring over three decades from 1963 to 1992. The recent decade (2003-2012) exhibited an intermediate percentage (25 percent) of wells with high groundwater levels but also had the highest percentage (30 percent) of high groundwater observations, although results by observations were similar (26-29 percent) over three decades prior, from 1963 to 1992. Major sections of the aquifer from north of Sterling to Julesburg and areas near Greeley, La Salle, and Gilcrest were identified with the highest frequencies of high groundwater levels.

\n

Changes in groundwater levels were evaluated using Kendal line and least trimmed squares regression methods using a significance level of 0.01 and statistical power of 0.8. During 2003-2012, following curtailment of pumping, 88 percent of wells and 81 percent of subwatershed areas with significant trends in groundwater levels exhibited rising water levels. Over the complete 60-yr record, however, 66 percent of wells and 57 percent of subwatersheds with significant groundwater-level trends still showed declining water levels; rates of groundwater-level change were typically less than 0.125 ft/yr in areas near the South Platte River, with greater declines along the southern tributaries. In agreement, 58 percent of subwatersheds evaluated between 1963-1972 and 2003-2012 showed net declines in average decadal groundwater levels. More areas had groundwater decline in upgradient sections to the west and rise in downgradient sections to the east, implying a redistribution of water has occurred in some areas of the aquifer.

\n

Precipitation was identified as having the strongest statistically significant correlations to river discharge over annual and decadal periods (Pearson correlation coefficients of 0.5 and 0.8, respectively, and statistical significance defined by p-values less than 0.05). Correlation coefficients between river discharge and frequency of high groundwater levels were statistically significant at 0.4 annually and 0.6 over decadal periods, indicating that periods of high river flow were often coincident with high groundwater conditions. Over seasonal periods in five of the six decades examined, peak high groundwater levels occurred after spring runoff from July to September when administrative structures were most active. Between 1993-2002 and 2003-2012, groundwater levels rose while river discharge decreased, in part from greater reliance on surface water and curtailed pumping from wells without augmentation plans.

\n

Geographic attributes of elevation and proximity to streams and rivers showed moderate correlations to high groundwater levels in wells used for observing groundwater levels (correlation coefficients of 0.3 to 0.4). Local depressions and regional lows within the aquifer were identified as areas of potential shallow groundwater. Wells close to the river regularly indicated high groundwater levels, while those within depleted tributaries tended to have low frequencies of high groundwater levels. Some attributes of administrative structures were spatially correlated to high groundwater levels at moderate to high magnitudes (correlation coefficients of 0.3 to 0.7). The number of affected river reaches or recharge areas that surround a well where groundwater levels were observed and its distance from the nearest well field showed the strongest controls on high groundwater levels. Influences of administrative structures on groundwater levels were in some cases local over a mile or less but could extend to several miles, often manifesting as diffuse effects from multiple surrounding structures.

\n

A network of candidate monitoring wells was proposed to initiate a regional monitoring program. Consistent monitoring and analysis of groundwater levels will be needed for informed decisions to optimize beneficial use of water and to limit high groundwater levels in susceptible areas. Finalization of the network will require future field reconnaissance to assess local site conditions and discussions with State authorities.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155015","collaboration":"Prepared in cooperation with the Colorado Water Institute and Colorado Water Conservation Board","usgsCitation":"Wellman, T., 2015, Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels: U.S. Geological Survey Scientific Investigations Report 2015-5015, viii, 68 p., https://doi.org/10.3133/sir20155015.","productDescription":"viii, 68 p.","numberOfPages":"79","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1953-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-057966","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":300710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155015.jpg"},{"id":300708,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5015/pdf/sir2015-5015.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5015 Report"},{"id":300709,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5015/"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.13818359375,\n 36.98500309285596\n ],\n [\n -109.13818359375,\n 41.04621681452063\n ],\n [\n -101.9970703125,\n 41.04621681452063\n ],\n [\n -101.9970703125,\n 36.98500309285596\n ],\n [\n -109.13818359375,\n 36.98500309285596\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55604523e4b0afeb70724143","contributors":{"authors":[{"text":"Wellman, Tristan 0000-0003-3049-6214 twellman@usgs.gov","orcid":"https://orcid.org/0000-0003-3049-6214","contributorId":2166,"corporation":false,"usgs":true,"family":"Wellman","given":"Tristan","email":"twellman@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547513,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70147635,"text":"ofr20151089 - 2015 - Geotechnical soil characterization of intact Quaternary deposits forming the March 22, 2014 SR-530 (Oso) landslide, Snohomish County, Washington","interactions":[],"lastModifiedDate":"2015-05-22T09:39:22","indexId":"ofr20151089","displayToPublicDate":"2015-05-22T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1089","title":"Geotechnical soil characterization of intact Quaternary deposits forming the March 22, 2014 SR-530 (Oso) landslide, Snohomish County, Washington","docAbstract":"

During the late morning of March 22, 2014, a devastating landslide occurred near the town of Oso, Washington. The landslide with an estimated volume of 10.9 million cubic yards (8.3 x 106 m3) of both intact glacially deposited and previously disturbed landslide sediments, reached speeds averaging 40 miles per hour (64 kilometers per hour) and crossed the entire 2/3-mile (~1100 m) width of the adjacent North Fork Stillaguamish River floodplain in approximately 60 seconds, resulting in the complete destruction of an entire neighborhood (Iverson and others, 2015). More than 40 homes were destroyed as the debris overran the neighborhood, resulting in the deaths of 43 people.

\n

Landslides in glacial deposits are common in the Pacific Northwest (for example, Baum and others, 2008), and in fact, the site of the March 22, 2014 SR-530 landslide had experienced significant reactivation several times in past decades, with the most recent event occurring in 2006 (for example, Miller and Sias, 1998). However, these previous landslides were of considerably less volume and mobility (Iverson and others, 2015), and debris had never reached the Steelhead Haven neighborhood. Further, no landslides with the type of mobility that the March 22, 2014 landslide underwent have been recorded in historic times within the North Fork Stillaguamish River valley. However, mapping performed immediately following the landslide indicates that several other slopes in the North Fork Stillaguamish River valley have experienced large-volume landslides exhibiting high mobility in prehistoric times (Haugerud, 2014). The presence of previous high-mobility landslides in the valley, and the now well-documented occurrence of one involving many fatalities, underscores both the hazard and risk for those that live and travel in this and other river valleys in the Pacific Northwest with similar glacial deposits and precipitation patterns.

\n

To understand the hazards posed by highly mobile landslides in the Pacific Northwest, the U.S. Geological Survey (USGS), together with its project partners, the University of California, Berkeley Department of Civil and Environmental Engineering (UCB), and the Washington State Department of Transportation (WSDOT), is undertaking a critically needed study to identify the geologic, hydrogeologic, and geotechnical conditions in which these large landslides initiate, as well as the processes responsible for the exceptional mobility of this, and potentially other, landslides in the region. One of the first study activities involves characterizing the stratigraphy and materials from which the landslide deposits are derived, so that the fundamental geotechnical nature of the soils can be understood. This understanding is required to begin identifying possible conditions leading to slope failure and their relation to the landslide's high mobility. In addition, detailed characterization of each stratigraphic unit encountered in initial geotechnical borings is needed to relate stratigraphy between borings for this study and as a part of ongoing investigations by WSDOT and other project partners.

\n

This report provides a description of the methods used to obtain and test the intact soil stratigraphy behind the headscarp of the March 22 landslide. Detailed geotechnical index testing results are presented for 24 soil samples representing the stratigraphy at 19 different depths along a 650 ft (198 m) soil profile. The results include (1) the soil's in situ water content and unit weight (where applicable); (2) specific gravity of soil solids; and (3) each sample's grain-size distribution, critical limits for fine-grain water content states (that is, the Atterberg limits), and official Unified Soil Classification System (USCS) designation. In addition, preliminary stratigraphy and geotechnical relations within and between soil units are presented.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151089","collaboration":"Prepared in cooperation with the University of California, Berkeley and the Washington State Department of Transportation","usgsCitation":"Riemer, M.F., Collins, B.D., Badger, T.C., Toth, C., and Yu, Y.C., 2015, Geotechnical soil characterization of intact Quaternary deposits forming the March 22, 2014 SR-530 (Oso) landslide, Snohomish County, Washington: U.S. Geological Survey Open-File Report 2015-1089, vi, 17 p., https://doi.org/10.3133/ofr20151089.","productDescription":"vi, 17 p.","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064901","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":300694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151089.jpg"},{"id":300692,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1089/"},{"id":300693,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1089/pdf/ofr20151089.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"OF 2015-1089 Report"}],"country":"United States","state":"Washington","county":"Snohomish County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.55273437499999,\n 47.010225655683485\n ],\n [\n -121.55273437499999,\n 48.21003212234042\n ],\n [\n -119.5751953125,\n 48.21003212234042\n ],\n [\n -119.5751953125,\n 47.010225655683485\n ],\n [\n -121.55273437499999,\n 47.010225655683485\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55604529e4b0afeb70724147","contributors":{"authors":[{"text":"Riemer, Michael F.","contributorId":140577,"corporation":false,"usgs":false,"family":"Riemer","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":13533,"text":"Univ. of California, Berkeley, Dept. of Civil and Envir. Engineeering","active":true,"usgs":false}],"preferred":false,"id":546217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collins, Brian D. bcollins@usgs.gov","contributorId":2406,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":546216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Badger, Thomas C.","contributorId":140578,"corporation":false,"usgs":false,"family":"Badger","given":"Thomas","email":"","middleInitial":"C.","affiliations":[{"id":13534,"text":"Washington State Dept. of Transporation, Geotechnical Office","active":true,"usgs":false}],"preferred":false,"id":546218,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Toth, Csilla","contributorId":140579,"corporation":false,"usgs":false,"family":"Toth","given":"Csilla","email":"","affiliations":[{"id":13535,"text":"Univ. of California, Berkeley, Dept. of Civil and Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":546219,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yu, Yat Chun","contributorId":140580,"corporation":false,"usgs":false,"family":"Yu","given":"Yat","email":"","middleInitial":"Chun","affiliations":[{"id":13535,"text":"Univ. of California, Berkeley, Dept. of Civil and Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":546220,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148004,"text":"sir20155072 - 2015 - Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Rincon, Effingham County, Georgia","interactions":[],"lastModifiedDate":"2017-01-18T13:21:04","indexId":"sir20155072","displayToPublicDate":"2015-05-22T10:00:00","publicationYear":"2015","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":"2015-5072","title":"Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Rincon, Effingham County, Georgia","docAbstract":"

Steady-state simulations using a revised regional groundwater-flow model based on MODFLOW were run to assess the potential long-term effects on the Upper Floridan aquifer (UFA) of pumping the Lower Floridan aquifer (LFA) at well (36S048) near the City of Rincon in coastal Georgia near Savannah. Simulated pumping of well 36S048 at a rate of 1,000 gallons per minute (gal/min; or 1.44 million gallons per day [Mgal/d]) indicated a maximum drawdown of about 6.8 feet (ft) in the UFA directly above the pumped well and at least 1 ft of drawdown within a nearly 400-square-mile area (scenario A). Induced vertical leakage from the UFA provided about 99 percent of the water to the pumped well. Simulated pumping of well 36S048 indicated increased downward leakage in all layers above the LFA, decreased upward leakage in all layers above the LFA, increased inflow to and decreased outflow from lateral specified-head boundaries in the UFA and LFA, and an increase in the volume of induced inflow from the general-head boundary representing outcrop units. Water budgets for scenario A indicated that changes in inflows and outflows through general-head boundaries would compose about 72 percent of the simulated pumpage from well 36S048, with the remaining 28 percent of the pumped water derived from flow across lateral specified-head boundaries.

\n

Additional steady-state simulations were run to evaluate a pumping rate in the UFA of 292 gal/min (0.42 Mgal/d), which would produce the equivalent maximum drawdown in the UFA as pumping from well 36S048 in the LFA at a rate of 1,000 gal/min (called the drawdown offset; scenario B). Simulated pumping in the UFA for the drawdown offset produced about 6.7 ft of drawdown, comparable to 6.8 ft of drawdown in the UFA simulated in scenario A. Water budgets for scenario B also provided favorable comparisons with scenario A, indicating that 69 percent of the drawdown-offset pumpage (0.42 Mgal/d) in the UFA originates as increased inflow and decreased outflow across general-head boundaries from overlying units in the surficial and Brunswick aquifer systems and that the remaining simulated pumpage originates as flow across general- and specified-head boundaries within the UFA.

\n

A steady-state simulation representing implementation of drawdown-offset-pumping reductions totaling 292 gal/min at Rincon UFA production wells 36S034 and 36S035 and pumping from the new LFA well 36S048 at 1,000 gal/min (scenario C) resulted in decreased magnitude and areal extent of drawdown in the UFA compared with scenario A. In the latter scenario, the LFA well was pumped without UFA drawdown-offset-pumping reductions. Water budgets for scenario C yielded percentage contributions from flow components that were consistent with those from scenario B. Specifically, 69 percent of the increased pumping in scenario C originated from general-head boundaries from overlying units of the surficial and Brunswick aquifer systems and the balance of flow was derived from general- and specified-head boundaries in the UFA. In all scenarios, the placement of model boundaries and type of boundary exerted the greatest control on overall groundwater flow and interaquifer leakage in the system.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155072","collaboration":"Prepared in cooperation with the City of Rincon, Georgia","usgsCitation":"Cherry, G.S., and Clarke, J.S., 2015, Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Rincon, Effingham County, Georgia: U.S. Geological Survey Scientific Investigations Report 2015-5072, viii, 36 p., https://doi.org/10.3133/sir20155072.","productDescription":"viii, 36 p.","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054209","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":300691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155072.jpg"},{"id":300690,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5072/pdf/sir2015-5072.pdf","text":"Report","size":"5.16 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5072 Report"},{"id":300689,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5072/"}],"country":"United States","state":"Georgia","county":"Effingham County","otherGeospatial":"Rincon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.4251708984375,\n 31.785384226419566\n ],\n [\n -81.4251708984375,\n 32.21396296653795\n ],\n [\n -80.80307006835938,\n 32.21396296653795\n ],\n [\n -80.80307006835938,\n 31.785384226419566\n ],\n [\n -81.4251708984375,\n 31.785384226419566\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5560452ce4b0afeb7072414b","contributors":{"authors":[{"text":"Cherry, Gregory S. 0000-0002-5567-1587 gccherry@usgs.gov","orcid":"https://orcid.org/0000-0002-5567-1587","contributorId":1567,"corporation":false,"usgs":true,"family":"Cherry","given":"Gregory","email":"gccherry@usgs.gov","middleInitial":"S.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clarke, John S. jsclarke@usgs.gov","contributorId":400,"corporation":false,"usgs":true,"family":"Clarke","given":"John","email":"jsclarke@usgs.gov","middleInitial":"S.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546736,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156183,"text":"70156183 - 2015 - Modeling apple snail population dynamics on the Everglades landscape","interactions":[],"lastModifiedDate":"2019-07-25T15:01:35","indexId":"70156183","displayToPublicDate":"2015-05-22T01:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling apple snail population dynamics on the Everglades landscape","docAbstract":"

Context

\n

The Florida Everglades has diminished in size and its existing wetland hydrology has been altered. The endangered snail kite (Rostrhamus sociabilis) has nearly abandoned the Everglades, and its prey, the apple snail (Pomacea paludosa), has declined.

\n

Objective

\n

We developed a population model (EverSnail) to understand apple snail response to inter- and intra-annual fluctuations in water depths over the Everglades landscape. EverSnail was developed as a tool to understand how apple snails respond to different hydrologic scenarios.

\n

Methods

\n

EverSnail is an age- and size-structured, spatially-explicit landscape model of P. paludosa in the Everglades. Landscape-level inputs are water depth and air temperature. We conducted sensitivity analyses by running EverSnail with ± 20 % the baseline value of eight parameters.

\n

Results

\n

EverSnail was sensitive to changes in survival and water depth associated with reproduction. The EverSnail population varied with changes and/or differences in depth generally consistent with empirical data; site-specific comparisons to field data proved less reliable. A simulated 3-year wet period resulted in a shift in apple snail distribution, but little change in total abundance over the landscape. In contrast, a simulated 3-year succession of relatively dry years resulted in overall lower snail abundances.

\n

Conclusions

\n

Comparisons of model output to empirical data indicate the need for more data to better understand, and eventually parameterize, several aspects of snail ecology in support of EverSnail. A primary value of EverSnail is its capacity to describe the relative response of snail abundance to alternative hydrologic scenarios considered for Everglades water management and restoration.

","language":"English","publisher":"Springer Netherlands","doi":"10.1007/s10980-015-0205-5","usgsCitation":"Darby, P., DeAngelis, D., Romanach, S.S., Suir, K.J., and Bridevaux, J.L., 2015, Modeling apple snail population dynamics on the Everglades landscape: Landscape Ecology, v. 30, no. 8, p. 1497-1510, https://doi.org/10.1007/s10980-015-0205-5.","productDescription":"14 p.","startPage":"1497","endPage":"1510","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056099","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":306812,"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 -83.1060791015625,\n 25.199970890386023\n ],\n [\n -83.1060791015625,\n 28.338230147025865\n ],\n [\n -79.8486328125,\n 28.338230147025865\n ],\n [\n -79.8486328125,\n 25.199970890386023\n ],\n [\n -83.1060791015625,\n 25.199970890386023\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"8","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-22","publicationStatus":"PW","scienceBaseUri":"560bb6d5e4b058f706e53d8b","contributors":{"authors":[{"text":"Darby, Phil","contributorId":146459,"corporation":false,"usgs":false,"family":"Darby","given":"Phil","email":"","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":567951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":138934,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","email":"don_deangelis@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":567949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":567950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suir, Kevin J. 0000-0003-1570-9648 suirk@usgs.gov","orcid":"https://orcid.org/0000-0003-1570-9648","contributorId":4894,"corporation":false,"usgs":true,"family":"Suir","given":"Kevin","email":"suirk@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":567952,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bridevaux, Joshua L.","contributorId":103567,"corporation":false,"usgs":true,"family":"Bridevaux","given":"Joshua","email":"","middleInitial":"L.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":567953,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159970,"text":"70159970 - 2015 - Automated calculation of surface energy fluxes with high-frequency lake buoy data","interactions":[],"lastModifiedDate":"2015-12-04T16:47:25","indexId":"70159970","displayToPublicDate":"2015-05-22T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Automated calculation of surface energy fluxes with high-frequency lake buoy data","docAbstract":"

Lake Heat Flux Analyzer is a program used for calculating the surface energy fluxes in lakes according to established literature methodologies. The program was developed in MATLAB for the rapid analysis of high-frequency data from instrumented lake buoys in support of the emerging field of aquatic sensor network science. To calculate the surface energy fluxes, the program requires a number of input variables, such as air and water temperature, relative humidity, wind speed, and short-wave radiation. Available outputs for Lake Heat Flux Analyzer include the surface fluxes of momentum, sensible heat and latent heat and their corresponding transfer coefficients, incoming and outgoing long-wave radiation. Lake Heat Flux Analyzer is open source and can be used to process data from multiple lakes rapidly. It provides a means of calculating the surface fluxes using a consistent method, thereby facilitating global comparisons of high-frequency data from lake buoys.

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The depth-differentiation hypothesis proposes that the bathyal region is a source of genetic diversity and an area where there is a high rate of species formation. Genetic differentiation should thus occur over relatively small vertical distances, particularly along the upper continental slope (200–1000 m) where oceanography varies greatly over small differences in depth. To test whether genetic differentiation within deepwater octocorals is greater over vertical rather than geographical distances, Callogorgia delta was targeted. This species commonly occurs throughout the northern Gulf of Mexico at depths ranging from 400 to 900 m. We found significant genetic differentiation (FST = 0.042) across seven sites spanning 400 km of distance and 400 m of depth. A pattern of isolation by depth emerged, but geographical distance between sites may further limit gene flow. Water mass boundaries may serve to isolate populations across depth; however, adaptive divergence with depth is also a possible scenario. Microsatellite markers also revealed significant genetic differentiation (FST = 0.434) between C. delta and a closely related species, Callogorgia americana, demonstrating the utility of microsatellites in species delimitation of octocorals. Results provided support for the depth-differentiation hypothesis, strengthening the notion that factors covarying with depth serve as isolation mechanisms in deep-sea populations.

","language":"English","publisher":"The Royal Society","doi":"10.1098/rspb.2015.0008","usgsCitation":"Quattrini, A., Baums, I.B., Shank, T.M., Morrison, C., and Cordes, E.E., 2015, Testing the depth-differentiation hypothesis in a deepwater octocoral: Proceedings of the Royal Society B: Biological Sciences, v. 282, no. 1807, p. 1-9, https://doi.org/10.1098/rspb.2015.0008.","productDescription":"Article 20150008; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-062076","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":472082,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2015.0008","text":"Publisher Index Page"},{"id":339269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"282","issue":"1807","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-22","publicationStatus":"PW","scienceBaseUri":"58e60273e4b09da6799ac687","contributors":{"authors":[{"text":"Quattrini, Andrea aquattrini@usgs.gov","contributorId":149599,"corporation":false,"usgs":true,"family":"Quattrini","given":"Andrea","email":"aquattrini@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":689599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baums, Iliana B. 0000-0001-6463-7308","orcid":"https://orcid.org/0000-0001-6463-7308","contributorId":190566,"corporation":false,"usgs":false,"family":"Baums","given":"Iliana","email":"","middleInitial":"B.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":689600,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shank, Timothy M.","contributorId":190567,"corporation":false,"usgs":false,"family":"Shank","given":"Timothy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":689601,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morrison, Cheryl L. cmorrison@usgs.gov","contributorId":3355,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl L.","email":"cmorrison@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":689598,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":689602,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148109,"text":"fs20153040 - 2015 - Tools for discovering and accessing Great Lakes scientific data","interactions":[],"lastModifiedDate":"2015-06-19T14:52:12","indexId":"fs20153040","displayToPublicDate":"2015-05-21T13:15:00","publicationYear":"2015","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":"2015-3040","title":"Tools for discovering and accessing Great Lakes scientific data","docAbstract":"

The Great Lakes Restoration Initiative (GLRI) is a multidisciplinary and interagency effort focused on the protection and restoration of the Great Lakes (GL) using the best available science and applying lessons learned from previous studies. The U.S. Geological Survey (USGS) contributes to the GLRI effort by providing resource managers with information and tools needed to meet restoration goals. This includes contributing scientific expertise and delivering findings to the GL community through meaningful information products.

\n

One of the strengths of the GLRI is its interagency approach; however, this can create challenges when coordinating the large number of restoration activities being performed by GL governments, tribes, academics, nonprofits, and industry. There is a vast array of data being produced by both the USGS and its partners, and it is crucial that scientists, managers, policymakers, and the public can easily locate the biological, geological, geospatial, and water-resources data being generated.

\n

The USGS strives to develop data products that are easy to find, easy to understand, and easy to use through Web-accessible tools that allow users to learn about the breadth and scope of GLRI activities being undertaken by the USGS and its partners. By creating tools that enable data to be shared and reused more easily, the USGS can encourage collaboration and assist the GL community in finding, interpreting, and understanding the information created during GLRI science activities.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153040","usgsCitation":"Lucido, J., and Bruce, J.L., 2015, Tools for discovering and accessing Great Lakes scientific data: U.S. Geological Survey Fact Sheet 2015-3040, 2 p., https://doi.org/10.3133/fs20153040.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065137","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":300655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153040.jpg"},{"id":300653,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3040/"},{"id":300654,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3040/pdf/fs2015-3040.pdf","text":"Report","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.6376953125,\n 50.45750402042058\n ],\n [\n -90.68115234375,\n 49.52520834197442\n ],\n [\n -93.31787109374999,\n 47.234489635299184\n ],\n [\n -92.8564453125,\n 46.34692761055676\n ],\n [\n -89.23095703125,\n 46.437856895024204\n ],\n [\n -89.36279296875,\n 43.29320031385282\n ],\n [\n -88.3740234375,\n 42.439674178149424\n ],\n [\n -88.13232421875,\n 41.19518982948959\n ],\n [\n -85.53955078125,\n 41.261291493919884\n ],\n [\n -84.55078125,\n 40.49709237269567\n ],\n [\n -82.28759765625,\n 40.59727063442024\n ],\n [\n -79.013671875,\n 42.16340342422401\n ],\n [\n -76.31103515625,\n 42.08191667830631\n ],\n [\n -74.50927734375,\n 43.691707903073805\n ],\n [\n -74.72900390625,\n 44.29240108529005\n ],\n [\n -76.26708984375,\n 44.5278427984555\n ],\n [\n -80.44189453125,\n 47.87214396888731\n ],\n [\n -83.8037109375,\n 48.60385760823255\n ],\n [\n -87.451171875,\n 50.41551870402678\n ],\n [\n -88.6376953125,\n 50.45750402042058\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555ef3a1e4b0a92fa7eb9664","contributors":{"authors":[{"text":"Lucido, Jessica M. jlucido@usgs.gov","contributorId":4695,"corporation":false,"usgs":true,"family":"Lucido","given":"Jessica M.","email":"jlucido@usgs.gov","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":547431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bruce, Jennifer L. 0000-0003-4915-5567 jlbruce@usgs.gov","orcid":"https://orcid.org/0000-0003-4915-5567","contributorId":132,"corporation":false,"usgs":true,"family":"Bruce","given":"Jennifer","email":"jlbruce@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547432,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70144908,"text":"pp1813 - 2015 - Mercury and methylmercury in reservoirs in Indiana","interactions":[],"lastModifiedDate":"2015-05-20T15:39:27","indexId":"pp1813","displayToPublicDate":"2015-05-20T16:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1813","title":"Mercury and methylmercury in reservoirs in Indiana","docAbstract":"

Mercury (Hg) is an element that occurs naturally, but evidence suggests that human activities have resulted in increased amounts being released to the atmosphere and land surface. When Hg is converted to methylmercury (MeHg) in aquatic ecosystems, MeHg accumulates and increases in the food web so that some fish contain levels which pose a health risk to humans and wildlife that consume these fish. Reservoirs unlike natural lakes, are a part of river systems that are managed for flood control. Data compiled and interpreted for six flood-control reservoirs in Indiana showed a relation between Hg transport, MeHg formation in water, and MeHg in fish that was influenced by physical, chemical, and biological differences among the reservoirs. Existing information precludes a uniform comparison of Hg and MeHg in all reservoirs in the State, but factors and conditions were identified that can indicate where and when Hg and MeHg levels in reservoirs could be highest.

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As part of a statewide monitoring network for Hg and MeHg in Indiana streams, 66 water samples were collected from four reservoir tailwater sites (downstream near the dams) on a quarterly schedule for 5 years. The reservoirs were Brookville Lake, Cagles Mill Lake, J. Edward Roush Lake, and Mississinewa Lake. Particulate-bound Hg concentrations were significantly lower in tailwater samples than in samples from free-flowing streams in the statewide network. (Free-flowing streams were not affected by dams and were not upstream from these reservoirs.) These data indicated the reduced flow velocity of water upstream from dams was allowing particulate-bound Hg to settle out of the water in the reservoir pools. The concentration ratios of MeHg to Hg were significantly higher in the tailwater samples than in samples from free-flowing streams, and the MeHg to Hg ratios were significantly higher in summer than in other seasons.

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To evaluate the conditions related to MeHg formation, pools of three reservoirs (Brookville Lake, Monroe Lake, and Patoka Lake) were investigated during summer hydrologic conditions. Water temperature and dissolved oxygen were measured from the water surface to the lake bottom at 10 to 17 transects across each reservoir to identify three thermal strata, defined by water temperature, dissolved oxygen concentration, and depth. Depth-specific water samples were collected from these thermal strata throughout each reservoir, from the headwaters to the dam and from the tailwater. Mercury concentrations higher than 0.04 nanogram per liter (ng/L) were detected in all 53 samples, and MeHg concentrations higher than 0.04 ng/L were detected in 53 percent of the samples.

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The investigation found a zone of water below 8 or 9 meters, with temperatures less than 18 degrees Celsius and dissolved oxygen less than 3.5 milligrams per liter, extending through nearly half the reservoir area in Monroe Lake and Patoka Lake. This zone had abundant dissolved MeHg and concentration ratios of dissolved MeHg to Hg that ranged from 25 to 82 percent. This zone also had water with pH less than 7 and decreased dissolved sulfate, conditions indicating sulfate reduction by microorganisms that promoted a high potential for the conversion of Hg to MeHg. Reservoir outflow came from this zone at Monroe Lake and contributed to a tailwater concentration ratio for dissolved MeHg to Hg of 56 percent. Reservoir outflow at Patoka Lake was not from this zone, and dissolved MeHg was not detected in the tailwater. In contrast, samples from the summer pool at Brookville Lake had no MeHg detections even though Hg was detected, probably because the water pH higher than 7 inhibited sulfate reduction and did not promote the conversion of Hg to MeHg.

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Mercury and MeHg concentrations and the concentration ratios of MeHg to Hg in water varied among the six reservoirs in Indiana, and the differences were related to a combination of factors that could apply to other reservoirs. In areas with moderate to high rates of atmospheric Hg wet and dry deposition, Hg runoff and transport to streams and reservoirs was potentially highest for reservoirs with heavily forested watersheds in steep terrains of near-surface bedrock. Methylmercury concentrations and concentration ratios of MeHg to Hg were highest for reservoirs with the longest summer pools and highest inflow-to-outflow retention times, where water-chemistry conditions favoring sulfate reduction promoted conversion of Hg to MeHg.

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Methylmercury (reported as Hg) in fish-tissue samples collected for the State fish consumption advisory program was used to describe MeHg food-web accumulation and magnification in the reservoirs. The highest percentages of fish-tissue samples with Hg concentrations that exceeded the criterion of 0.30 milligram per kilogram for protection of human health were from Monroe Lake (38 percent) and Patoka Lake (33 percent). A review of the number and size of fish species caught from these two reservoirs resulted in two implications for fish consumption by humans. First, the highest numbers of fish harvested for potential human consumption were species more likely to have MeHg concentrations lower than the human-health criterion (crappie, bluegill, and catfish). Second, although largemouth bass were likely to have MeHg concentrations higher than the human-health criterion, they were caught and released more often than they were harvested. However, the average size largemouth bass (in both reservoirs) and above-average size walleye (in Monroe Lake) that were harvested for potential human consumption were likely to have MeHg concentrations higher than the human-health criterion.

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