{"pageNumber":"157","pageRowStart":"3900","pageSize":"25","recordCount":11004,"records":[{"id":70043236,"text":"70043236 - 2013 - Geochronologic evidence for a possible MIS-11 emergent barrier/beach-ridge in southeastern Georgia, USA","interactions":[],"lastModifiedDate":"2013-05-29T10:29:19","indexId":"70043236","displayToPublicDate":"2013-05-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Geochronologic evidence for a possible MIS-11 emergent barrier/beach-ridge in southeastern Georgia, USA","docAbstract":"Predominantly clastic, off-lapping, transgressive, near-shore marine sediment packages that are morphologically expressed as subparallel NE-trending barriers, beach ridges, and associated back-barrier areas, characterize the near-surface stratigraphic section between the Savannah and the Ogeechee Rivers in Effingham County, southeastern Georgia. Each barrier/back-barrier (shoreline) complex is lower than and cut into a higher/older complex. Each barrier or shoreline complex overlies Miocene strata. No direct age data are available for these deposits. Previous researchers have disagreed on their age and provenance. Using luminescence and meteoric beryllium-10 (<sup>10</sup>Be) inventory analyses, we estimated a minimum age for the largest, westernmost, morphologically identifiable, and topographically-highest, barrier/beach-ridge (the Wicomico shoreline barrier) and constrained the age of a suite of younger barrier/beach-ridges that lie adjacent and seaward of the Wicomico shoreline barrier.\n\nAt the study site, the near-shore marine/estuarine deposits underlying the Wicomico shoreline barrier are overlain by eolian sand and an intervening zone-of-mixing. Optically stimulated luminescence (OSL) data indicate ages of ≤43 ka for the eolian sand and 116 ka for the zone-of-mixing. Meteoric 10Be and pedostratigraphic data indicate minimum residence times of 33.4 ka for the eolian sand, 80.6 ka for the zone-of-mixing, and 247 ka for the paleosol. The combined OSL and 10Be age data indicate that, at this locality, the barrier/beach ridge has a minimum age of about 360 ka. This age for the Wicomico shoreline-barrier deposit is the first for any Pleistocene near-shore marine/estuarine deposit in southeast Georgia that is conclusively older than 80 ka. The 360-ka minimum age is in agreement with other geochronologic data for near-coastline deposits in Georgia and South Carolina. The geomorphic position of this barrier/beach-ridge is similar to deposits in South Carolina considered to be ~450 ka to >1 Ma. The age and geomorphic data for Georgia and South Carolina possibly suggest the presence of MIS-11 (~420−360 ka) shoreline deposits between 15 m and 28 m above present sea level in the Southeastern Atlantic Coastal Plain.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Quaternary Science Reviews","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2012.10.041","usgsCitation":"Markewich, H.W., Pavich, M., Schultz, A., Mahan, S., Aleman-Gonzalez, W., and Bierman, P., 2013, Geochronologic evidence for a possible MIS-11 emergent barrier/beach-ridge in southeastern Georgia, USA: Quaternary Science Reviews, v. 60, p. 49-75, https://doi.org/10.1016/j.quascirev.2012.10.041.","productDescription":"27 p.","startPage":"49","endPage":"75","ipdsId":"IP-038366","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":272943,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272942,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.quascirev.2012.10.041"}],"country":"United States","state":"Georgia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.6052,30.3556 ], [ -85.6052,35.0 ], [ -80.8408,35.0 ], [ -80.8408,30.3556 ], [ -85.6052,30.3556 ] ] ] } } ] }","volume":"60","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a71566e4b09db86f875c7b","contributors":{"authors":[{"text":"Markewich, H. W.","contributorId":31426,"corporation":false,"usgs":true,"family":"Markewich","given":"H.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":473208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pavich, M.J.","contributorId":70788,"corporation":false,"usgs":true,"family":"Pavich","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":473211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schultz, A. P.","contributorId":106139,"corporation":false,"usgs":true,"family":"Schultz","given":"A. P.","affiliations":[],"preferred":false,"id":473213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mahan, S. A. 0000-0001-5214-7774","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":94333,"corporation":false,"usgs":true,"family":"Mahan","given":"S. A.","affiliations":[],"preferred":false,"id":473212,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aleman-Gonzalez, W. B.","contributorId":36447,"corporation":false,"usgs":true,"family":"Aleman-Gonzalez","given":"W. B.","affiliations":[],"preferred":false,"id":473209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bierman, P.R.","contributorId":49145,"corporation":false,"usgs":true,"family":"Bierman","given":"P.R.","email":"","affiliations":[],"preferred":false,"id":473210,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70046103,"text":"ofr20131120 - 2013 - Survey of bats on Columbia National Wildlife Refuge, Washington, December 2011-April 2012","interactions":[],"lastModifiedDate":"2013-10-30T11:40:29","indexId":"ofr20131120","displayToPublicDate":"2013-05-24T00:00:00","publicationYear":"2013","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":"2013-1120","title":"Survey of bats on Columbia National Wildlife Refuge, Washington, December 2011-April 2012","docAbstract":"Bats are diverse and abundant in many ecosystems worldwide. They perform important ecosystem functions, particularly by consuming large quantities of insects (Cleveland and others, 2006; Jones and others, 2009; Kuhn and others, 2011). The importance of bats to biodiversity and to ecosystem integrity has been overlooked in many regions, largely because the challenges of detecting and studying these small, nocturnal mammals have rendered a paucity of information on matters as basic as species distribution and natural history attributes. Recently, concern for bats has arisen in response to recognition of large-scale threats, such as white-nosed syndrome (WNS; Turner and others, 2009; Frick and others, 2010) and mortality at wind energy facilities (Arnett and others, 2008), factors that are causing unprecedented population declines of bats (Boyles and others, 2011). WNS is a fungal disease that has killed more than 1 million cave-hibernating bats in eastern North America since being discovered in New York State in 2006 (U.S. Fish and Wildlife Service, 2012). WNS has spread rapidly from northeastern U.S., and as of August 2012 has been confirmed as far west as eastern Missouri(U.S. Fish and Wildlife Service, 2013). Given the rapid spread of WNS, there is concern that the disease may soon affect western bat populations.\n\nHibernating bats are particularly vulnerable to the effects of WNS (Blehert and others, 2009). Refuges in eastern Washington, including the Mid-Columbia River National Wildlife Refuge Complex (MCRNWRC) and Little Pend Oreille National Wildlife Refuge, support many potential hibernacula. Sixteen species of bats potentially occur on these refuges, including one federally listed species of concern (Townsend’s big-eared bat [Corynorhinus townsendii]; see table 1 for scientific names of bats), and 12 species that are of conservation concern in Washington and Oregon (table 1). However, little is known about bats on these refuges because few surveys have been done, and none have been done during winter. Refuge biologists are lacking even the most basic information, such as species presence, and location and status of hibernacula. In order to assess vulnerability and develop a strategy for management of WNS, refuge managers need to know where bats are hibernating, and which species are using each hibernaculum. The goal of this project was to provide information on the status of wintering bats to refuge biologists and managers in order to support decision-making that might minimize the threat of WNS in western bat populations. We conducted surveys of bat activity in winter and early spring as an initial step toward identifying bat species that may be over-wintering and locating potential hibernacula on these refuges. Our specific objectives were to identify bat species using the refuges, to identify areas of resident bat activity in autumn, winter, and early spring using acoustic bat detectors, and to try new methods for quick surveys of bat activity.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131120","usgsCitation":"Hagar, J.C., Manning, T., and Barnett, J., 2013, Survey of bats on Columbia National Wildlife Refuge, Washington, December 2011-April 2012: U.S. Geological Survey Open-File Report 2013-1120, iv, 30 p., https://doi.org/10.3133/ofr20131120.","productDescription":"iv, 30 p.","numberOfPages":"38","additionalOnlineFiles":"N","temporalStart":"2011-10-01","temporalEnd":"2012-05-31","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":272800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131120.jpg"},{"id":272798,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1120/"},{"id":272799,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1120/pdf/ofr20131120.pdf"}],"country":"United States","state":"Oregon;Washington","otherGeospatial":"Little Pend Oreille National Wildlife Refuge;Mid-columbia River National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.722585,42.0 ], [ -117.722585,48.544811 ], [ -116.46,48.544811 ], [ -116.46,42.0 ], [ -117.722585,42.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a07dd8e4b0e42455803674","contributors":{"authors":[{"text":"Hagar, Joan C. 0000-0002-3044-6607 joan_hagar@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-6607","contributorId":57034,"corporation":false,"usgs":true,"family":"Hagar","given":"Joan","email":"joan_hagar@usgs.gov","middleInitial":"C.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":478922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manning, Tom","contributorId":47914,"corporation":false,"usgs":true,"family":"Manning","given":"Tom","email":"","affiliations":[],"preferred":false,"id":478921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnett, Jenny","contributorId":67789,"corporation":false,"usgs":true,"family":"Barnett","given":"Jenny","affiliations":[],"preferred":false,"id":478923,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70046080,"text":"ofr20131114 - 2013 - Nahcolite and halite deposition through time during the saline mineral phase of Eocene Lake Uinta, Piceance Basin, western Colorado","interactions":[],"lastModifiedDate":"2013-05-23T14:05:09","indexId":"ofr20131114","displayToPublicDate":"2013-05-23T00:00:00","publicationYear":"2013","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":"2013-1114","title":"Nahcolite and halite deposition through time during the saline mineral phase of Eocene Lake Uinta, Piceance Basin, western Colorado","docAbstract":"Halite and the sodium bicarbonate mineral nahcolite were deposited during the saline phase of Eocene Lake Uinta in the Piceance Basin, western Colorado. Variations in the area of saline mineral deposition through time were interpreted from studies of core and outcrop. Saline minerals were extensively leached by groundwater, so the original extent of saline deposition was estimated from the distribution of empty vugs and collapse breccias. Vugs and breccias strongly influence groundwater movement, so determining where leaching has occurred is an important consideration for in-situ oil shale extraction methods currently being developed.\n\nLake Uinta formed when two smaller fresh water lakes, one in the Uinta Basin of eastern Utah and the other in the Piceance Basin of western Colorado, expanded and coalesced across the Douglas Creek arch, an area of comparatively low subsidence rates. Salinity increased shortly after this expansion, but saline mineral deposition did not begin until later, after a period of prolonged infilling created broad lake-margin shelves and a comparatively small deep central lake area. These shelves probably played a critical role in brine evolution. A progression from disseminated nahcolite and nahcolite aggregates to bedded nahcolite and ultimately to bedded nahcolite and halite was deposited in this deep lake area during the early stages of saline deposition along with rich oil shale that commonly shows signs of slumping and lateral transport. The area of saline mineral and rich oil shale deposition subsequently expanded, in part due to infilling of the compact deep area, and in part because of an increase in water flow into Lake Uinta, possibly due to outflow from Lake Gosiute to the north. Finally, as Lake Uinta in the Piceance Basin was progressively filled from north to south by volcano-clastic sediment, the saline depocenter was pushed progressively southward, eventually covering much of the areas that had previously been marginal shelves. A saline depocenter formed in the eastern Uinta Basin during this progradation, and saline minerals were deposited in both basins for a time. Ultimately, the saline depocenter in the Piceance Basin was completely filled in and saline mineral deposition shifted entirely into the Uinta Basin.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20131114","usgsCitation":"Johnson, R.C., and Brownfield, M.E., 2013, Nahcolite and halite deposition through time during the saline mineral phase of Eocene Lake Uinta, Piceance Basin, western Colorado: U.S. Geological Survey Open-File Report 2013-1114, 71 p., https://doi.org/10.3133/ofr20131114.","productDescription":"71 p.","numberOfPages":"73","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":272754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131114.png"},{"id":272752,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1114/"},{"id":272753,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1114/OF13-1114_508.pdf"}],"country":"United States","state":"Colorado","otherGeospatial":"Lake Uinta;Piceance Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,37.0 ], [ -109.0,41.0 ], [ -102.0,41.0 ], [ -102.0,37.0 ], [ -109.0,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"519f2c5ce4b0687ba0506b62","contributors":{"authors":[{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478847,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046085,"text":"sir20135081 - 2013 - Improved estimates of filtered total mercury loadings and total mercury concentrations of solids from potential sources to Sinclair Inlet, Kitsap County, Washington","interactions":[],"lastModifiedDate":"2013-05-23T15:33:20","indexId":"sir20135081","displayToPublicDate":"2013-05-23T00:00:00","publicationYear":"2013","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":"2013-5081","title":"Improved estimates of filtered total mercury loadings and total mercury concentrations of solids from potential sources to Sinclair Inlet, Kitsap County, Washington","docAbstract":"Previous investigations examined sources and sinks of mercury to Sinclair Inlet based on historic and new data. This included an evaluation of mercury concentrations from various sources and mercury loadings from industrial discharges and groundwater flowing from the Bremerton naval complex to Sinclair Inlet. This report provides new data from four potential sources of mercury to Sinclair Inlet: (1) filtered and particulate total mercury concentrations of creek water during the wet season, (2) filtered and particulate total mercury releases from the Navy steam plant following changes in the water softening process and discharge operations, (3) release of mercury from soils to groundwater in two landfill areas at the Bremerton naval complex, and (4) total mercury concentrations of solids in dry dock sumps that were not affected by bias from sequential sampling.\n\nThe previous estimate of the loading of filtered total mercury from Sinclair Inlet creeks was based solely on dry season samples. Concentrations of filtered total mercury in creek samples collected during wet weather were significantly higher than dry weather concentrations, which increased the estimated loading of filtered total mercury from creek basins from 27.1 to 78.1 grams per year.\n\nChanges in the concentrations and loading of filtered and particulate total mercury in the effluent of the steam plant were investigated after the water softening process was changed from ion-exchange to reverse osmosis and the discharge of stack blow-down wash began to be diverted to the municipal water-treatment plant. These changes reduced the concentrations of filtered and particulate total mercury from the steam plant of the Bremerton naval complex, which resulted in reduced loadings of filtered total mercury from 5.9 to 0.15 grams per year.\n\nPrevious investigations identified three fill areas on the Bremerton naval complex, of which the western fill area is thought to be the largest source of mercury on the base. Studies of groundwater in the other two fill areas were conducted under worst-case higher high tidal conditions. A December 2011 study found that concentrations of filtered total mercury in the well in the fill area on the eastern boundary of the Bremerton naval complex were less than or equal to 11 nanograms per liter, indicating that releases from the eastern area were unlikely. In addition, concentrations of total mercury of solids were low (<3 milligrams per kilogram). In contrast, data from the November 2011 study indicated that the concentrations of filtered total mercury in the well located in the central fill area had tidally influenced concentrations of up to 500 nanograms per liter and elevated concentrations of total mercury of solids (29–41 milligrams per kilogram). This suggests that releases from this area, which has not been previously studied in detail, may be substantial.\n\nPrevious measurements of total mercury of suspended solids in the dry dock discharges revealed high concentration of total mercury when suspended-solids concentrations were low. However, this result could have been owing to bias from sequential sampling during changing suspended‑solids concentrations. Sampling of two dry dock systems on the complex in a manner that precluded this bias confirmed that suspended-solids concentrations and total mercury concentrations of suspended solids varied considerably during pumping cycles. These new data result in revised estimates of solids loadings from the dry docks. Although most of the solids discharged by the dry docks seem to be recycled Operable Unit B Marine sediment, a total of about 3.2 metric tons of solids per year containing high concentrations of total mercury were estimated to be discharged by the two dry dock systems. A simple calculation, in which solids (from dry docks, the steam plant, and tidal flushing of the largest stormwater drain) are widely dispersed throughout Operable Unit B Marine, suggests that Bremerton naval complex solids would likely have little effect on Operable Unit B Marine sediments because of high concentrations of mercury already present in the sediment.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135081","collaboration":"Prepared in cooperation with Department of the Navy Naval Facilities Engineering Command, Northwest","usgsCitation":"Paulson, A.J., Conn, K., and DeWild, J.F., 2013, Improved estimates of filtered total mercury loadings and total mercury concentrations of solids from potential sources to Sinclair Inlet, Kitsap County, Washington: U.S. Geological Survey Scientific Investigations Report 2013-5081, vi, 35 p., https://doi.org/10.3133/sir20135081.","productDescription":"vi, 35 p.","numberOfPages":"46","additionalOnlineFiles":"N","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":272768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135081.png"},{"id":272766,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5081/"},{"id":272767,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5081/pdf/sir20135081.pdf"}],"country":"United States","state":"Washington","county":"Kitsap County","otherGeospatial":"Sinclair Inlet","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.04,47.4 ], [ -123.04,47.97 ], [ -122.43,47.97 ], [ -122.43,47.4 ], [ -123.04,47.4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"519f2c5ce4b0687ba0506b5e","contributors":{"authors":[{"text":"Paulson, Anthony J. 0000-0002-2358-8834 apaulson@usgs.gov","orcid":"https://orcid.org/0000-0002-2358-8834","contributorId":5236,"corporation":false,"usgs":true,"family":"Paulson","given":"Anthony","email":"apaulson@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":478857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, Kathleen E. 0000-0002-2334-6536 kconn@usgs.gov","orcid":"https://orcid.org/0000-0002-2334-6536","contributorId":3923,"corporation":false,"usgs":true,"family":"Conn","given":"Kathleen E.","email":"kconn@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478856,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeWild, John F. 0000-0003-4097-2798 jfdewild@usgs.gov","orcid":"https://orcid.org/0000-0003-4097-2798","contributorId":2525,"corporation":false,"usgs":true,"family":"DeWild","given":"John","email":"jfdewild@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478855,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70046081,"text":"sir20135007 - 2013 - Relation of watershed setting and stream nutrient yields at selected sites in central and eastern North Carolina, 1997-2008","interactions":[],"lastModifiedDate":"2017-01-17T20:36:54","indexId":"sir20135007","displayToPublicDate":"2013-05-23T00:00:00","publicationYear":"2013","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":"2013-5007","title":"Relation of watershed setting and stream nutrient yields at selected sites in central and eastern North Carolina, 1997-2008","docAbstract":"Data collected between 1997 and 2008 at 48 stream sites were used to characterize relations between watershed settings and stream nutrient yields throughout central and eastern North Carolina. The focus of the investigation was to identify environmental variables in watersheds that influence nutrient export for supporting the development and prioritization of management strategies for restoring nutrient-impaired streams.\n\nNutrient concentration data and streamflow data compiled for the 1997 to 2008 study period were used to compute stream yields of nitrate, total nitrogen (N), and total phosphorus (P) for each study site. Compiled environmental data (including variables for land cover, hydrologic soil groups, base-flow index, streams, wastewater treatment facilities, and concentrated animal feeding operations) were used to characterize the watershed settings for the study sites. Data for the environmental variables were analyzed in combination with the stream nutrient yields to explore relations based on watershed characteristics and to evaluate whether particular variables were useful indicators of watersheds having relatively higher or lower potential for exporting nutrients.\n\nData evaluations included an examination of median annual nutrient yields based on a watershed land-use classification scheme developed as part of the study. An initial examination of the data indicated that the highest median annual nutrient yields occurred at both agricultural and urban sites, especially for urban sites having large percentages of point-source flow contributions to the streams. The results of statistical testing identified significant differences in annual nutrient yields when sites were analyzed on the basis of watershed land-use category. When statistical differences in median annual yields were noted, the results for nitrate, total N, and total P were similar in that highly urbanized watersheds (greater than 30 percent developed land use) and (or) watersheds with greater than 10 percent point-source flow contributions to streamflow had higher yields relative to undeveloped watersheds (having less than 10 and 15 percent developed and agricultural land uses, respectively) and watersheds with relatively low agricultural land use (between 15 and 30 percent). The statistical tests further indicated that the median annual yields for total P were statistically higher for watersheds with high agricultural land use (greater than 30 percent) compared to the undeveloped watersheds and watersheds with low agricultural land use. The total P yields also were higher for watersheds with low urban land use (between 10 and 30 percent developed land) compared to the undeveloped watersheds. The study data indicate that grouping and examining stream nutrient yields based on the land-use classifications used in this report can be useful for characterizing relations between watershed settings and nutrient yields in streams located throughout central and eastern North Carolina.\n\nCompiled study data also were analyzed with four regression tree models as a means of determining which watershed environmental variables or combination of variables result in basins that are likely to have high or low nutrient yields. The regression tree analyses indicated that some of the environmental variables examined in this study were useful for predicting yields of nitrate, total N, and total P. When the median annual nutrient yields for all 48 sites were evaluated as a group (Model 1), annual point-source flow yields had the greatest influence on nitrate and total N yields observed in streams, and annual streamflow yields had the greatest influence on yields of total P. The Model 1 results indicated that watersheds with higher annual point-source flow yields had higher annual yields of nitrate and total N, and watersheds with higher annual streamflow yields had higher annual yields of total P.\n\nWhen sites with high point-source flows (greater than 10 percent of total streamflow) were excluded from the regression tree analyses (Models 2–4), the percentage of forested land in the watersheds was identified as the primary environmental variable influencing stream yields for both total N and total P. Models 2, 3 and 4 did not identify any watershed environmental variables that could adequately explain the observed variability in the nitrate yields among the set of sites examined by each of these models. The results for Models 2, 3, and 4 indicated that watersheds with higher percentages of forested land had lower annual total N and total P yields compared to watersheds with lower percentages of forested land, which had higher median annual total N and total P yields. Additional environmental variables determined to further influence the stream nutrient yields included median annual percentage of point-source flow contributions to the streams, variables of land cover (percentage of forested land, agricultural land, and (or) forested land plus wetlands) in the watershed and (or) in the stream buffer, and drainage area. The regression tree models can serve as a tool for relating differences in select watershed attributes to differences in stream yields of nitrate, total N, and total P, which can provide beneficial information for improving nutrient management in streams throughout North Carolina and for reducing nutrient loads to coastal waters.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135007","collaboration":"Prepared in cooperation with the North Carolina Department of Environment and Natural Resources, Division of Water Quality","usgsCitation":"Harden, S.L., Cuffney, T.F., Terziotti, S., and Kolb, K.R., 2013, Relation of watershed setting and stream nutrient yields at selected sites in central and eastern North Carolina, 1997-2008: U.S. Geological Survey Scientific Investigations Report 2013-5007, vii, 47 p.; 4 Appendixes, https://doi.org/10.3133/sir20135007.","productDescription":"vii, 47 p.; 4 Appendixes","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1997-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":272761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135007.png"},{"id":272757,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5007/Appendixes/Appendix1"},{"id":272755,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5007/"},{"id":272760,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5007/Appendixes/Appendix4"},{"id":272758,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5007/Appendixes/Appendix2"},{"id":272759,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5007/Appendixes/Appendix3"},{"id":272756,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5007/pdf/sir2013-5007.pdf"}],"country":"United States","state":"North Carolina","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.32,33.84 ], [ -84.32,36.59 ], [ -75.46,36.59 ], [ -75.46,33.84 ], [ -84.32,33.84 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"519f2c5de4b0687ba0506b6e","contributors":{"authors":[{"text":"Harden, Stephen L. 0000-0001-6886-0099 slharden@usgs.gov","orcid":"https://orcid.org/0000-0001-6886-0099","contributorId":2212,"corporation":false,"usgs":true,"family":"Harden","given":"Stephen","email":"slharden@usgs.gov","middleInitial":"L.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cuffney, Thomas F. 0000-0003-1164-5560 tcuffney@usgs.gov","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":517,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"tcuffney@usgs.gov","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terziotti, Silvia 0000-0003-3559-5844 seterzio@usgs.gov","orcid":"https://orcid.org/0000-0003-3559-5844","contributorId":1613,"corporation":false,"usgs":true,"family":"Terziotti","given":"Silvia","email":"seterzio@usgs.gov","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolb, Katharine R. 0000-0002-1663-1662 kkolb@usgs.gov","orcid":"https://orcid.org/0000-0002-1663-1662","contributorId":16299,"corporation":false,"usgs":true,"family":"Kolb","given":"Katharine","email":"kkolb@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":478852,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70046072,"text":"70046072 - 2013 - The effect of increasing salinity and forest mortality on soil nitrogen and phosphorus mineralization in tidal freshwater forested wetlands","interactions":[],"lastModifiedDate":"2013-07-01T09:50:57","indexId":"70046072","displayToPublicDate":"2013-05-23T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"The effect of increasing salinity and forest mortality on soil nitrogen and phosphorus mineralization in tidal freshwater forested wetlands","docAbstract":"Tidal freshwater wetlands are sensitive to sea level rise and increased salinity, although little information is known about the impact of salinification on nutrient biogeochemistry in tidal freshwater forested wetlands. We quantified soil nitrogen (N) and phosphorus (P) mineralization using seasonal in situ incubations of modified resin cores along spatial gradients of chronic salinification (from continuously freshwater tidal forest to salt impacted tidal forest to oligohaline marsh) and in hummocks and hollows of the continuously freshwater tidal forest along the blackwater Waccamaw River and alluvial Savannah River. Salinification increased rates of net N and P mineralization fluxes and turnover in tidal freshwater forested wetland soils, most likely through tree stress and senescence (for N) and conversion to oligohaline marsh (for P). Stimulation of N and P mineralization by chronic salinification was apparently unrelated to inputs of sulfate (for N and P) or direct effects of increased soil conductivity (for N). In addition, the tidal wetland soils of the alluvial river mineralized more P relative to N than the blackwater river. Finally, hummocks had much greater nitrification fluxes than hollows at the continuously freshwater tidal forested wetland sites. These findings add to knowledge of the responses of tidal freshwater ecosystems to sea level rise and salinification that is necessary to predict the consequences of state changes in coastal ecosystem structure and function due to global change, including potential impacts on estuarine eutrophication.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biogeochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10533-012-9805-1","usgsCitation":"Noe, G., Krauss, K.W., Lockaby, B.G., Conner, W.H., and Hupp, C.R., 2013, The effect of increasing salinity and forest mortality on soil nitrogen and phosphorus mineralization in tidal freshwater forested wetlands: Biogeochemistry, v. 114, no. 1-3, p. 225-244, https://doi.org/10.1007/s10533-012-9805-1.","productDescription":"20 p.","startPage":"225","endPage":"244","ipdsId":"IP-040465","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":272749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272748,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10533-012-9805-1"}],"volume":"114","issue":"1-3","noUsgsAuthors":false,"publicationDate":"2012-11-06","publicationStatus":"PW","scienceBaseUri":"519f2c5ee4b0687ba0506b76","contributors":{"authors":[{"text":"Noe, Gregory B.","contributorId":77805,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory B.","affiliations":[],"preferred":false,"id":478819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":478816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lockaby, B. Graeme","contributorId":28510,"corporation":false,"usgs":true,"family":"Lockaby","given":"B.","email":"","middleInitial":"Graeme","affiliations":[],"preferred":false,"id":478818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conner, William H.","contributorId":79376,"corporation":false,"usgs":false,"family":"Conner","given":"William","email":"","middleInitial":"H.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":478820,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":478817,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70046064,"text":"70046064 - 2013 - Coal resources, reserves and peak coal production in the United States","interactions":[],"lastModifiedDate":"2013-05-23T15:10:11","indexId":"70046064","displayToPublicDate":"2013-05-23T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Coal resources, reserves and peak coal production in the United States","docAbstract":"In spite of its large endowment of coal resources, recent studies have indicated that United States coal production is destined to reach a maximum and begin an irreversible decline sometime during the middle of the current century. However, studies and assessments illustrating coal reserve data essential for making accurate forecasts of United States coal production have not been compiled on a national basis. As a result, there is a great deal of uncertainty in the accuracy of the production forecasts. A very large percentage of the coal mined in the United States comes from a few large-scale mines (mega-mines) in the Powder River Basin of Wyoming and Montana. Reported reserves at these mines do not account for future potential reserves or for future development of technology that may make coal classified currently as resources into reserves in the future. In order to maintain United States coal production at or near current levels for an extended period of time, existing mines will eventually have to increase their recoverable reserves and/or new large-scale mines will have to be opened elsewhere. Accordingly, in order to facilitate energy planning for the United States, this paper suggests that probabilistic assessments of the remaining coal reserves in the country would improve long range forecasts of coal production. As it is in United States coal assessment projects currently being conducted, a major priority of probabilistic assessments would be to identify the numbers and sizes of remaining large blocks of coal capable of supporting large-scale mining operations for extended periods of time and to conduct economic evaluations of those resources.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Coal Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2012.10.002","usgsCitation":"Milici, R.C., Flores, R.M., and Stricker, G.D., 2013, Coal resources, reserves and peak coal production in the United States: International Journal of Coal Geology, v. 113, p. 109-115, https://doi.org/10.1016/j.coal.2012.10.002.","productDescription":"7 p.","startPage":"109","endPage":"115","ipdsId":"IP-027301","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":272765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272764,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.coal.2012.10.002"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,19.0 ], [ 172.5,71.4 ], [ -67.0,71.4 ], [ -67.0,19.0 ], [ 172.5,19.0 ] ] ] } } ] }","volume":"113","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"519f2c5be4b0687ba0506b5a","contributors":{"authors":[{"text":"Milici, Robert C. rmilici@usgs.gov","contributorId":563,"corporation":false,"usgs":true,"family":"Milici","given":"Robert","email":"rmilici@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flores, Romeo M. rflores@usgs.gov","contributorId":71984,"corporation":false,"usgs":true,"family":"Flores","given":"Romeo","email":"rflores@usgs.gov","middleInitial":"M.","affiliations":[{"id":165,"text":"Central Energy Resources Team","active":false,"usgs":true}],"preferred":false,"id":478803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stricker, Gary D. gstricker@usgs.gov","contributorId":87163,"corporation":false,"usgs":true,"family":"Stricker","given":"Gary","email":"gstricker@usgs.gov","middleInitial":"D.","affiliations":[{"id":165,"text":"Central Energy Resources Team","active":false,"usgs":true}],"preferred":false,"id":478804,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70046045,"text":"70046045 - 2013 - A USANS/SANS study of the accessibility of pores in the Barnett Shale to methane and water","interactions":[],"lastModifiedDate":"2013-05-23T12:55:44","indexId":"70046045","displayToPublicDate":"2013-05-23T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1506,"text":"Energy & Fuels","active":true,"publicationSubtype":{"id":10}},"title":"A USANS/SANS study of the accessibility of pores in the Barnett Shale to methane and water","docAbstract":"Shale is an increasingly important source of natural gas in the United States. The gas is held in fine pores that need to be accessed by horizontal drilling and hydrofracturing techniques. Understanding the nature of the pores may provide clues to making gas extraction more efficient. We have investigated two Mississippian Barnett Shale samples, combining small-angle neutron scattering (SANS) and ultrasmall-angle neutron scattering (USANS) to determine the pore size distribution of the shale over the size range 10 nm to 10 μm. By adding deuterated methane (CD<sub>4</sub>) and, separately, deuterated water (D<sub>2</sub>O) to the shale, we have identified the fraction of pores that are accessible to these compounds over this size range. The total pore size distribution is essentially identical for the two samples. At pore sizes >250 nm, >85% of the pores in both samples are accessible to both CD<sub>4</sub> and D<sub>2</sub>O. However, differences in accessibility to CD<sub>4</sub> are observed in the smaller pore sizes (~25 nm). In one sample, CD<sub>4</sub> penetrated the smallest pores as effectively as it did the larger ones. In the other sample, less than 70% of the smallest pores (<25 nm) were accessible to CD<sub>4</sub>, but they were still largely penetrable by water, suggesting that small-scale heterogeneities in methane accessibility occur in the shale samples even though the total porosity does not differ. An additional study investigating the dependence of scattered intensity with pressure of CD<sub>4</sub> allows for an accurate estimation of the pressure at which the scattered intensity is at a minimum. This study provides information about the composition of the material immediately surrounding the pores. Most of the accessible (open) pores in the 25 nm size range can be associated with either mineral matter or high reflectance organic material. However, a complementary scanning electron microscopy investigation shows that most of the pores in these shale samples are contained in the organic components. The neutron scattering results indicate that the pores are not equally proportioned in the different constituents within the shale. There is some indication from the SANS results that the composition of the pore-containing material varies with pore size; the pore size distribution associated with mineral matter is different from that associated with organic phases.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Energy & Fuels","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","doi":"10.1021/ef301859s","usgsCitation":"Ruppert, L.F., Sakurovs, R., Blach, T.P., He, L., Melnichenko, Y., Mildner, D.F., and Alcantar-Lopez, L., 2013, A USANS/SANS study of the accessibility of pores in the Barnett Shale to methane and water: Energy & Fuels, v. 27, no. 2, p. 772-779, https://doi.org/10.1021/ef301859s.","productDescription":"8 p.","startPage":"772","endPage":"779","ipdsId":"IP-042255","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":272751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272750,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/ef301859s"}],"country":"United States","state":"Texas","otherGeospatial":"Barnett Shale","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.65,25.84 ], [ -106.65,36.5 ], [ -93.51,36.5 ], [ -93.51,25.84 ], [ -106.65,25.84 ] ] ] } } ] }","volume":"27","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-02-12","publicationStatus":"PW","scienceBaseUri":"519f2c52e4b0687ba0506b46","contributors":{"authors":[{"text":"Ruppert, Leslie F. 0000-0002-7453-1061 lruppert@usgs.gov","orcid":"https://orcid.org/0000-0002-7453-1061","contributorId":660,"corporation":false,"usgs":true,"family":"Ruppert","given":"Leslie","email":"lruppert@usgs.gov","middleInitial":"F.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sakurovs, Richard","contributorId":68633,"corporation":false,"usgs":true,"family":"Sakurovs","given":"Richard","affiliations":[],"preferred":false,"id":478756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blach, Tomasz P.","contributorId":99866,"corporation":false,"usgs":true,"family":"Blach","given":"Tomasz","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":478758,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"He, Lilin","contributorId":107594,"corporation":false,"usgs":true,"family":"He","given":"Lilin","email":"","affiliations":[],"preferred":false,"id":478759,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Melnichenko, Yuri B.","contributorId":98202,"corporation":false,"usgs":true,"family":"Melnichenko","given":"Yuri B.","affiliations":[],"preferred":false,"id":478757,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mildner, David F.","contributorId":65747,"corporation":false,"usgs":true,"family":"Mildner","given":"David","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":478755,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alcantar-Lopez, Leo","contributorId":8361,"corporation":false,"usgs":true,"family":"Alcantar-Lopez","given":"Leo","email":"","affiliations":[],"preferred":false,"id":478754,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70046051,"text":"ofr20121275 - 2013 - Chronology from sediment cores collected in southwestern Everglades National Park, Florida","interactions":[],"lastModifiedDate":"2013-05-22T13:34:51","indexId":"ofr20121275","displayToPublicDate":"2013-05-22T00:00:00","publicationYear":"2013","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":"2012-1275","title":"Chronology from sediment cores collected in southwestern Everglades National Park, Florida","docAbstract":"Age model data are presented for 10 cores from the southwestern coastal mangrove zone of Everglades National Park, Florida, collected in Common Era (CE) 2004 and 2005 and used for paleoecological analysis. Carbon-14 (<sup>14</sup>C), lead-210 (<sup>210</sup>Pb), cesium-137 (<sup>137</sup>Cs), radium-226 (<sup>226</sup>Ra), and pollen biostratigraphic information is included, and age models were generated for 6 of the 10 cores. Age reversals and sediment disturbance prevented construction of age models on the remaining four cores. Four cores present a continuous record of the last 50 to 100 years, making them useful for analyzing the impacts caused by changes in water management in south Florida. These cores are Harney River 2A and Harney River 1A, Shark River 2A, and Roberts River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121275","usgsCitation":"Bernhardt, C., Wingard, G., Willard, D., Marot, M.E., Landacre, B., and Holmes, C.W., 2013, Chronology from sediment cores collected in southwestern Everglades National Park, Florida: U.S. Geological Survey Open-File Report 2012-1275, vi, 59 p., https://doi.org/10.3133/ofr20121275.","productDescription":"vi, 59 p.","numberOfPages":"65","onlineOnly":"Y","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":272537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121275.gif"},{"id":272535,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1275/"},{"id":272536,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1275/OF2012-1275.pdf"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Everglades","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.0586,25.1621 ], [ -81.0586,25.3402 ], [ -80.5569,25.3402 ], [ -80.5569,25.1621 ], [ -81.0586,25.1621 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"519ddad2e4b0ac3d2125b728","contributors":{"authors":[{"text":"Bernhardt, C.E.","contributorId":65554,"corporation":false,"usgs":true,"family":"Bernhardt","given":"C.E.","email":"","affiliations":[],"preferred":false,"id":478773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wingard, G.L.","contributorId":79981,"corporation":false,"usgs":true,"family":"Wingard","given":"G.L.","email":"","affiliations":[],"preferred":false,"id":478774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Willard, Debra  A. 0000-0003-4878-0942","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":85982,"corporation":false,"usgs":true,"family":"Willard","given":"Debra  A.","affiliations":[],"preferred":false,"id":478775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marot, M. E.","contributorId":7733,"corporation":false,"usgs":true,"family":"Marot","given":"M.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":478770,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landacre, B.","contributorId":11037,"corporation":false,"usgs":true,"family":"Landacre","given":"B.","affiliations":[],"preferred":false,"id":478771,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holmes, C. W.","contributorId":36076,"corporation":false,"usgs":true,"family":"Holmes","given":"C.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":478772,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70046048,"text":"ofr20061260I - 2013 - Surficial geologic map of the Mount Grace-Ashburnham-Monson-Webster 24-quadrangle area in central Massachusetts","interactions":[],"lastModifiedDate":"2013-05-21T16:02:05","indexId":"ofr20061260I","displayToPublicDate":"2013-05-21T00:00:00","publicationYear":"2013","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":"2006-1260","chapter":"I","title":"Surficial geologic map of the Mount Grace-Ashburnham-Monson-Webster 24-quadrangle area in central Massachusetts","docAbstract":"The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction-aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20061260I","collaboration":"Prepared in cooperation with the Commonwealth of Massachusetts, Massachusetts Geological Survey and Office of Geographic Information (MassGIS), Information Technology Division","usgsCitation":"Stone, J.R., 2013, Surficial geologic map of the Mount Grace-Ashburnham-Monson-Webster 24-quadrangle area in central Massachusetts: U.S. Geological Survey Open-File Report 2006-1260, Report: iv, 19 p.; Downloads Directory; 24K_GRAPHICS Directory; Zip File, https://doi.org/10.3133/ofr20061260I.","productDescription":"Report: iv, 19 p.; Downloads Directory; 24K_GRAPHICS Directory; Zip File","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":272534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20061260i.png"},{"id":272531,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2006/1260/I/Downloads"},{"id":272529,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2006/1260/I/OFR2006-1260-I.pdf"},{"id":272532,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2006/1260/I/24k_GRAPHICS"},{"id":272533,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2006/1260/I/OFR2006-1260I.zip"},{"id":272530,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2006/1260/I/"}],"country":"United States","state":"Massachusetts","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -72.6855,42.5854 ], [ -72.6855,41.9595 ], [ 71.8835,41.9595 ], [ 71.8835,42.5854 ], [ -72.6855,42.5854 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"519c8958e4b0ce6c26df4312","contributors":{"authors":[{"text":"Stone, Janet Radway jrstone@usgs.gov","contributorId":1695,"corporation":false,"usgs":true,"family":"Stone","given":"Janet","email":"jrstone@usgs.gov","middleInitial":"Radway","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":478764,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046030,"text":"70046030 - 2013 - The northwest trending north Boquerón Bay-Punta Montalva Fault Zone; A through going active fault system in southwestern Puerto Rico","interactions":[],"lastModifiedDate":"2020-09-21T17:08:16.215541","indexId":"70046030","displayToPublicDate":"2013-05-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"The northwest trending north Boquerón Bay-Punta Montalva Fault Zone; A through going active fault system in southwestern Puerto Rico","docAbstract":"The North Boquerón Bay–Punta Montalva fault zone has been mapped crossing the Lajas Valley in southwest Puerto Rico. Identification of the fault was based upon detailed analysis of geophysical data, satellite images, and field mapping. The fault zone consists of a series of Cretaceous bedrock faults that reactivated and deformed Miocene limestone and Quaternary alluvial fan sediments. The fault zone is seismically active (local magnitude greater than 5.0) with numerous locally felt earthquakes. Focal mechanism solutions suggest strain partitioning with predominantly east–west left-lateral displacements with small normal faults striking mostly toward the northeast. Northeast-trending fractures and normal faults can be found in intermittent streams that cut through the Quaternary alluvial fan deposits along the southern margin of the Lajas Valley, an east–west-trending 30-km-long fault-controlled depression. Areas of preferred erosion within the alluvial fan trend toward the west-northwest parallel to the onland projection of the North Boquerón Bay fault. The North Boquerón Bay fault aligns with the Punta Montalva fault southeast of the Lajas Valley. Both faults show strong southward tilting of Miocene strata. On the western end, the Northern Boquerón Bay fault is covered with flat-lying Holocene sediments, whereas at the southern end the Punta Montalva fault shows left-lateral displacement of stream drainage on the order of a few hundred meters.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220120115","usgsCitation":"Howe, C.M., Asencio, E., and Joyce, J., 2013, The northwest trending north Boquerón Bay-Punta Montalva Fault Zone; A through going active fault system in southwestern Puerto Rico: Seismological Research Letters, v. 84, no. 3, p. 538-550, https://doi.org/10.1785/0220120115.","productDescription":"13 p.","startPage":"538","endPage":"550","numberOfPages":"13","additionalOnlineFiles":"N","ipdsId":"IP-027345","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":272517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -67.41,17.75 ], [ -67.41,19.03 ], [ -65.53,19.03 ], [ -65.53,17.75 ], [ -67.41,17.75 ] ] ] } } ] }","volume":"84","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-05-03","publicationStatus":"PW","scienceBaseUri":"519c8958e4b0ce6c26df4316","contributors":{"authors":[{"text":"Howe, Coral Marie 0000-0002-3040-719X","orcid":"https://orcid.org/0000-0002-3040-719X","contributorId":21847,"corporation":false,"usgs":true,"family":"Howe","given":"Coral","middleInitial":"Marie","affiliations":[],"preferred":false,"id":478723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asencio, Eugenio","contributorId":44182,"corporation":false,"usgs":true,"family":"Asencio","given":"Eugenio","email":"","affiliations":[],"preferred":false,"id":478724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joyce, James","contributorId":72426,"corporation":false,"usgs":true,"family":"Joyce","given":"James","affiliations":[],"preferred":false,"id":478725,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042145,"text":"70042145 - 2013 - White-nose syndrome in bats: Illuminating the darkness","interactions":[],"lastModifiedDate":"2017-10-26T09:54:02","indexId":"70042145","displayToPublicDate":"2013-05-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":953,"text":"BMC Biology","active":true,"publicationSubtype":{"id":10}},"title":"White-nose syndrome in bats: Illuminating the darkness","docAbstract":"<p>Happy ten-year anniversary to BMC Biology! We can attest to the effectiveness of the journal in reaching a great diversity of scientists based on reader responses to our commentary [1] about bat white-nose syndrome (WNS) two years ago. WNS is still on course to rank among the most destructive wildlife diseases to emerge in recent history, and it has continued to have unprecedented effects on populations of hibernating bats in eastern North America. At the time of our last writing in November 2010, the cold-adapted fungus then presumed to cause WNS (<i>Geomyces destructans</i>) had spread about 1,300 km from an index site in New York (Figure 1). In those early years of the epizootic, WNS caused a staggering wave of mass mortality among all six species of hibernating bats that occur in north-eastern North America. Since November 2010, WNS has spread into eight additional US states and two more Canadian provinces (Figure 1), and has continued to cause mortality in those six species most affected during the early years of the epizootic. Although part of a mostly tragic story has continued to unfold as new areas are affected, anecdotal signs are emerging that all may not be lost when it comes to hibernating bats and WNS. Amid the continued large-scale population declines of certain species, we have yet to see mass mortality in some of the more westerly areas where the fungus was detected two winters ago (Figure 1). Also, recently disease without obvious mortality was diagnosed in gray bats (<i>Myotis grisescens</i>) - an endangered species thought by many two years ago to be at high risk of extinction from WNS. Clearly, large gaps in our understanding of WNS remain, but some have been filled since we last communicated with readers of BMC Biology.</p>","language":"English","publisher":"BioMed Central Ltd","doi":"10.1186/1741-7007-11-47","usgsCitation":"Cryan, P., Meteyer, C.U., Boyles, J.G., and Blehert, D., 2013, White-nose syndrome in bats: Illuminating the darkness: BMC Biology, v. 11, no. 1, Article 47; 4 p., https://doi.org/10.1186/1741-7007-11-47.","productDescription":"Article 47; 4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042912","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":473820,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1186/1741-7007-11-47","text":"External 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Center","active":true,"usgs":true}],"preferred":false,"id":470851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meteyer, Carol U. 0000-0002-4007-3410 cmeteyer@usgs.gov","orcid":"https://orcid.org/0000-0002-4007-3410","contributorId":111,"corporation":false,"usgs":true,"family":"Meteyer","given":"Carol","email":"cmeteyer@usgs.gov","middleInitial":"U.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":470848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyles, Justin G.","contributorId":26810,"corporation":false,"usgs":true,"family":"Boyles","given":"Justin","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":470850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":1816,"corporation":false,"usgs":true,"family":"Blehert","given":"David S.","email":"dblehert@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":470849,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70046019,"text":"sim3255 - 2013 - Flood-inundation maps for the East Fork White River at Columbus, Indiana","interactions":[],"lastModifiedDate":"2013-05-20T13:25:17","indexId":"sim3255","displayToPublicDate":"2013-05-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3255","title":"Flood-inundation maps for the East Fork White River at Columbus, Indiana","docAbstract":"Digital flood-inundation maps for a 5.4-mile reach of the East Fork White River at Columbus, Indiana, from where the Flatrock and Driftwood Rivers combine to make up East Fork White River to just upstream of the confluence of Clifty Creek with the East Fork White River, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at USGS streamgage 03364000, East Fork White River at Columbus, Indiana. Current conditions at the USGS streamgage may be obtained on the Internet from the USGS National Water Information System (http://waterdata.usgs.gov/in/nwis/uv/?site_no=03364000&agency_cd=USGS&). The National Weather Service (NWS) forecasts flood hydrographs for the East Fork White River at Columbus, Indiana at their Advanced Hydrologic Prediction Service (AHPS) flood warning system Website (http://water.weather.gov/ahps/), that may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relation at USGS streamgage 03364000, East Fork White River at Columbus, Indiana. The calibrated hydraulic model was then used to determine 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from Light Detection and Ranging (LiDAR) data), having a 0.37-ft vertical accuracy and a 1.02 ft horizontal accuracy), in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage at Columbus, Indiana, and forecasted stream stages from the NWS will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3255","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Lombard, P., 2013, Flood-inundation maps for the East Fork White River at Columbus, Indiana: U.S. Geological Survey Scientific Investigations Map 3255, Pamphlet: vi, 7 p.; Map Sheets: 15 JPEGs, 15 PDFs 17 x 22 inches; Downloads Directory; Readme; Metadata, https://doi.org/10.3133/sim3255.","productDescription":"Pamphlet: vi, 7 p.; Map Sheets: 15 JPEGs, 15 PDFs 17 x 22 inches; Downloads Directory; Readme; Metadata","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":272456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3255.gif"},{"id":272440,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet11_617.7_SIM3255.pdf"},{"id":272444,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet12_618.7_SIM3255.pdf"},{"id":272413,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet03_609.7_SIM3255.pdf"},{"id":272445,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet13_619.7_SIM3255.pdf"},{"id":272453,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3255/Downloads/metadata"},{"id":272451,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3255/Downloads"},{"id":272452,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3255/Downloads/Readme.txt"},{"id":272447,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet14_620.7_SIM3255.pdf"},{"id":272425,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet06_612.7_SIM3255.pdf"},{"id":272428,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet07_613.7_SIM3255.pdf"},{"id":272449,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet15_621.7_SIM3255.pdf"},{"id":272437,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet10_616.7_SIM3255.pdf"},{"id":272434,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet09_615.7_SIM3255.pdf"},{"id":272388,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3255/"},{"id":272389,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3255/pdf/sim3255.pdf"},{"id":272405,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet01_607.7_SIM3255.pdf"},{"id":272418,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet04_610.7_SIM3255.pdf"},{"id":272421,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet05_611.7_SIM3255.pdf"},{"id":272432,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet08_614.7_SIM3255.pdf"},{"id":272409,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3255/pdf/pdf-mapsheets/sheet02_608.7_SIM3255.pdf"}],"projection":"Indiana State Plane Eastern Zone","datum":"North American Datum of 1983","country":"United States","state":"Indiana","city":"Columbus","otherGeospatial":"White River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.99617,39.149898 ], [ -85.99617,39.210643 ], [ -85.884247,39.210643 ], [ -85.884247,39.149898 ], [ -85.99617,39.149898 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"519b37dbe4b0e4e151ef5cba","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":23899,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela J.","affiliations":[],"preferred":false,"id":478707,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045984,"text":"sir20135066 - 2013 - Estimating irrigation water use in the humid eastern United States","interactions":[],"lastModifiedDate":"2013-05-16T13:41:25","indexId":"sir20135066","displayToPublicDate":"2013-05-16T00:00:00","publicationYear":"2013","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":"2013-5066","title":"Estimating irrigation water use in the humid eastern United States","docAbstract":"Accurate accounting of irrigation water use is an important part of the U.S. Geological Survey National Water-Use Information Program and the WaterSMART initiative to help maintain sustainable water resources in the Nation. Irrigation water use in the humid eastern United States is not well characterized because of inadequate reporting and wide variability associated with climate, soils, crops, and farming practices. To better understand irrigation water use in the eastern United States, two types of predictive models were developed and compared by using metered irrigation water-use data for corn, cotton, peanut, and soybean crops in Georgia and turf farms in Rhode Island. Reliable metered irrigation data were limited to these areas.  The first predictive model that was developed uses logistic regression to predict the occurrence of irrigation on the basis of antecedent climate conditions. Logistic regression equations were developed for corn, cotton, peanut, and soybean crops by using weekly irrigation water-use data from 36 metered sites in Georgia in 2009 and 2010 and turf farms in Rhode Island from 2000 to 2004. For the weeks when irrigation was predicted to take place, the irrigation water-use volume was estimated by multiplying the average metered irrigation application rate by the irrigated acreage for a given crop.  The second predictive model that was developed is a crop-water-demand model that uses a daily soil water balance to estimate the water needs of a crop on a given day based on climate, soil, and plant properties. Crop-water-demand models were developed independently of reported irrigation water-use practices and relied on knowledge of plant properties that are available in the literature. Both modeling approaches require accurate accounting of irrigated area and crop type to estimate total irrigation water use.  Water-use estimates from both modeling methods were compared to the metered irrigation data from Rhode Island and Georgia that were used to develop the models as well as two independent validation datasets from Georgia and Virginia that were not used in model development. Irrigation water-use estimates from the logistic regression method more closely matched mean reported irrigation rates than estimates from the crop-water-demand model when compared to the irrigation data used to develop the equations. The root mean squared errors (RMSEs) for the logistic regression estimates of mean annual irrigation ranged from 0.3 to 2.0 inches (in.) for the five crop types; RMSEs for the crop-water-demand models ranged from 1.4 to 3.9 in. However, when the models were applied and compared to the independent validation datasets from southwest Georgia from 2010, and from Virginia from 1999 to 2007, the crop-water-demand model estimates were as good as or better at predicting the mean irrigation volume than the logistic regression models for most crop types. RMSEs for logistic regression estimates of mean annual irrigation ranged from 1.0 to 7.0 in. for validation data from Georgia and from 1.8 to 4.9 in. for validation data from Virginia; RMSEs for crop-water-demand model estimates ranged from 2.1 to 5.8 in. for Georgia data and from 2.0 to 3.9 in. for Virginia data. In general, regression-based models performed better in areas that had quality daily or weekly irrigation data from which the regression equations were developed; however, the regression models were less reliable than the crop-water-demand models when applied outside the area for which they were developed. In most eastern coastal states that do not have quality irrigation data, the crop-water-demand model can be used more reliably.  The development of predictive models of irrigation water use in this study was hindered by a lack of quality irrigation data. Many mid-Atlantic and New England states do not require irrigation water use to be reported. A survey of irrigation data from 14 eastern coastal states from Maine to Georgia indicated that, with the exception of the data in Georgia, irrigation data in the states that do require reporting commonly did not contain requisite ancillary information such as irrigated area or crop type, lacked precision, or were at an aggregated temporal scale making them unsuitable for use in the development of predictive models. Confidence in the reliability of either modeling method is affected by uncertainty in the reported data from which the models were developed or validated. Only through additional collection of quality data and further study can the accuracy and uncertainty of irrigation water-use estimates be improved in the humid eastern United States.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135066","collaboration":"Prepared in cooperation with the WaterSMART Initiative","usgsCitation":"Levin, S.B., and Zarriello, P.J., 2013, Estimating irrigation water use in the humid eastern United States: U.S. Geological Survey Scientific Investigations Report 2013-5066, viii, 34 p., https://doi.org/10.3133/sir20135066.","productDescription":"viii, 34 p.","numberOfPages":"44","onlineOnly":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":272329,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135066.gif"},{"id":272328,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5066/pdf/sir2013-5066_report_508.pdf"},{"id":272327,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5066/"}],"country":"United States","otherGeospatial":"Eastern United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85,30 ], [ -85,33.08 ], [ -81,33.08 ], [ -81,30 ], [ -85,30 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51955815e4b0a933d82c4c81","contributors":{"authors":[{"text":"Levin, Sara B. 0000-0002-2448-3129 slevin@usgs.gov","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":1870,"corporation":false,"usgs":true,"family":"Levin","given":"Sara","email":"slevin@usgs.gov","middleInitial":"B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zarriello, Phillip J. 0000-0001-9598-9904 pzarriel@usgs.gov","orcid":"https://orcid.org/0000-0001-9598-9904","contributorId":1868,"corporation":false,"usgs":true,"family":"Zarriello","given":"Phillip","email":"pzarriel@usgs.gov","middleInitial":"J.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478645,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045817,"text":"70045817 - 2013 - Newly documented host fishes for the eastern elliptio mussel (Elliptio complanata)","interactions":[],"lastModifiedDate":"2020-09-23T13:19:07.809685","indexId":"70045817","displayToPublicDate":"2013-05-14T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Newly documented host fishes for the eastern elliptio mussel (<i>Elliptio complanata</i>)","title":"Newly documented host fishes for the eastern elliptio mussel (Elliptio complanata)","docAbstract":"<p><span>The eastern elliptio&nbsp;</span><i>Elliptio complanata</i><span>&nbsp;is a common, abundant, and ecologically important freshwater mussel that occurs throughout the Atlantic Slope drainage in the United States and Canada. Previous research has shown&nbsp;</span><i>E. complanata</i><span>&nbsp;glochidia to be host fish generalists, parasitizing yellow perch&nbsp;</span><i>Perca flavescens</i><span>, banded killifish&nbsp;</span><i>Fundulus diaphanus</i><span>, banded sculpin&nbsp;</span><i>Cottus carolinae</i><span>, and seven centrarchid species. Past laboratory studies have been conducted in the Midwest; however, glochidia used in these studies were obtained from adult mussels in the Great Lakes or St. Lawrence River basins, or glochidia sources were not reported. The objective of this study was to identify host fishes for&nbsp;</span><i>E. complanata</i><span>&nbsp;from streams in the Mid-Atlantic region. We used artificial laboratory infections to test host suitability of 38 fish and 2 amphibian species with&nbsp;</span><i>E. complanata</i><span>&nbsp;glochidia from the Chesapeake Bay drainage. Glochidia successfully metamorphosed into juvenile mussels on five fish species: American eel&nbsp;</span><i>Anguilla rostrata</i><span>, brook trout&nbsp;</span><i>Salvelinus fontinalis</i><span>, lake trout&nbsp;</span><i>Salvelinus namaycush</i><span>, mottled sculpin&nbsp;</span><i>Cottus bairdii</i><span>, and slimy sculpin&nbsp;</span><i>Cottus cognatus</i><span>. American eel was the most effective host, yielding the highest overall metamorphosis success (percentage of attached glochidia that transformed into juvenile mussels; ≥0.90) and producing 13.2 juveniles per fish overall. No juvenile&nbsp;</span><i>E. complanata</i><span>&nbsp;metamorphosed on other fish or amphibian species tested, including many previously identified host fishes that appear in the literature. Reasons for discrepancies in published host fish could include geographic variation in host use across the species' range, differences in host use between lentic and lotic populations, or poorly resolved taxonomy within the genus&nbsp;</span><i>Elliptio</i><span>.</span></p>","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/102012-JFWM-094","usgsCitation":"Lellis, W.A., St. John White, B., Cole, J.C., Johnson, C.S., Devers, J.L., van Snik-Gray, E., and Galbraith, H.S., 2013, Newly documented host fishes for the eastern elliptio mussel (Elliptio complanata): Journal of Fish and Wildlife Management, v. 4, no. 1, p. 75-85, https://doi.org/10.3996/102012-JFWM-094.","productDescription":"11 p.","startPage":"75","endPage":"85","ipdsId":"IP-044908","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473830,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/102012-jfwm-094","text":"Publisher Index Page"},{"id":272264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c02ff3e4b0ee1529ed3d30","contributors":{"authors":[{"text":"Lellis, William A. 0000-0001-7806-2904 wlellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7806-2904","contributorId":2369,"corporation":false,"usgs":true,"family":"Lellis","given":"William","email":"wlellis@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":799448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"St. John White, Barbara 0000-0001-8131-0534 bwhite@usgs.gov","orcid":"https://orcid.org/0000-0001-8131-0534","contributorId":141183,"corporation":false,"usgs":false,"family":"St. John White","given":"Barbara","email":"bwhite@usgs.gov","affiliations":[],"preferred":false,"id":799447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cole, Jeffrey C. 0000-0002-2477-7231 jccole@usgs.gov","orcid":"https://orcid.org/0000-0002-2477-7231","contributorId":5585,"corporation":false,"usgs":true,"family":"Cole","given":"Jeffrey","email":"jccole@usgs.gov","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":799449,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Connie S.","contributorId":241063,"corporation":false,"usgs":false,"family":"Johnson","given":"Connie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":799450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Devers, Julie L.","contributorId":218866,"corporation":false,"usgs":false,"family":"Devers","given":"Julie","email":"","middleInitial":"L.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":799451,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Snik-Gray, Ellen","contributorId":241064,"corporation":false,"usgs":false,"family":"van Snik-Gray","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":799452,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Galbraith, Heather S. 0000-0003-3704-3517 hgalbraith@usgs.gov","orcid":"https://orcid.org/0000-0003-3704-3517","contributorId":4519,"corporation":false,"usgs":true,"family":"Galbraith","given":"Heather","email":"hgalbraith@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":478386,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70045935,"text":"sir20135079 - 2013 - Groundwater depletion in the United States (1900−2008)","interactions":[],"lastModifiedDate":"2018-05-22T09:57:25","indexId":"sir20135079","displayToPublicDate":"2013-05-10T00:00:00","publicationYear":"2013","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":"2013-5079","title":"Groundwater depletion in the United States (1900−2008)","docAbstract":"A natural consequence of groundwater withdrawals is the removal of water from subsurface storage, but the overall rates and magnitude of groundwater depletion in the United States are not well characterized. This study evaluates long-term cumulative depletion volumes in 40 separate aquifers or areas and one land use category in the United States, bringing together information from the literature and from new analyses. Depletion is directly calculated using calibrated groundwater models, analytical approaches, or volumetric budget analyses for multiple aquifer systems. Estimated groundwater depletion in the United States during 1900–2008 totals approximately 1,000 cubic kilometers (km<sup>3</sup>). Furthermore, the rate of groundwater depletion has increased markedly since about 1950, with maximum rates occurring during the most recent period (2000–2008) when the depletion rate averaged almost 25 km<sup>3</sup> per year (compared to 9.2 km<sup>3</sup> per year averaged over the 1900–2008 timeframe).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135079","usgsCitation":"Konikow, L.F., 2013, Groundwater depletion in the United States (1900−2008): U.S. Geological Survey Scientific Investigations Report 2013-5079, viii, 65 p., https://doi.org/10.3133/sir20135079.","productDescription":"viii, 65 p.","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1900-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":272180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135079.gif"},{"id":272178,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5079/"},{"id":272179,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5079/SIR2013-5079.pdf"},{"id":354382,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sir2013-5079_Groundwater_Depletion.xml"}],"country":"United 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States\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518e08f6e4b05ebc8f7cc2d6","contributors":{"authors":[{"text":"Konikow, Leonard F. 0000-0002-0940-3856 lkonikow@usgs.gov","orcid":"https://orcid.org/0000-0002-0940-3856","contributorId":158,"corporation":false,"usgs":true,"family":"Konikow","given":"Leonard","email":"lkonikow@usgs.gov","middleInitial":"F.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":478556,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70042766,"text":"70042766 - 2013 - Ecosystem services from keystone species: diversionary seeding and seed-caching desert rodents can enhance Indian ricegrass seedling establishment","interactions":[],"lastModifiedDate":"2013-05-09T09:16:39","indexId":"70042766","displayToPublicDate":"2013-05-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem services from keystone species: diversionary seeding and seed-caching desert rodents can enhance Indian ricegrass seedling establishment","docAbstract":"Seeds of Indian ricegrass (Achnatherum hymenoides), a native bunchgrass common to sandy soils on arid western rangelands, are naturally dispersed by seed-caching rodent species, particularly Dipodomys spp. (kangaroo rats). These animals cache large quantities of seeds when mature seeds are available on or beneath plants and recover most of their caches for consumption during the remainder of the year. Unrecovered seeds in caches account for the vast majority of Indian ricegrass seedling recruitment. We applied three different densities of white millet (Panicum miliaceum) seeds as “diversionary foods” to plots at three Great Basin study sites in an attempt to reduce rodents' over-winter cache recovery so that more Indian ricegrass seeds would remain in soil seedbanks and potentially establish new seedlings. One year after diversionary seed application, a moderate level of Indian ricegrass seedling recruitment occurred at two of our study sites in western Nevada, although there was no recruitment at the third site in eastern California. At both Nevada sites, the number of Indian ricegrass seedlings sampled along transects was significantly greater on all plots treated with diversionary seeds than on non-seeded control plots. However, the density of diversionary seeds applied to plots had a marginally non-significant effect on seedling recruitment, and it was not correlated with recruitment patterns among plots. Results suggest that application of a diversionary seed type that is preferred by seed-caching rodents provides a promising passive restoration strategy for target plant species that are dispersed by these rodents.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Restoration Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1526-100X.2012.00895.x","usgsCitation":"Longland, W., and Ostoja, S.M., 2013, Ecosystem services from keystone species: diversionary seeding and seed-caching desert rodents can enhance Indian ricegrass seedling establishment: Restoration Ecology, v. 21, no. 2, p. 285-291, https://doi.org/10.1111/j.1526-100X.2012.00895.x.","productDescription":"7 p.","startPage":"285","endPage":"291","ipdsId":"IP-032558","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":272121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272120,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1526-100X.2012.00895.x"}],"country":"United States","state":"California;Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.0 ], [ -114.0,42.0 ], [ -114.0,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","volume":"21","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-07-06","publicationStatus":"PW","scienceBaseUri":"518cb759e4b05ebc8f7cc0dc","contributors":{"authors":[{"text":"Longland, William","contributorId":73899,"corporation":false,"usgs":true,"family":"Longland","given":"William","affiliations":[],"preferred":false,"id":472211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ostoja, Steven M. sostoja@usgs.gov","contributorId":3039,"corporation":false,"usgs":true,"family":"Ostoja","given":"Steven","email":"sostoja@usgs.gov","middleInitial":"M.","affiliations":[{"id":33665,"text":"USDA California Climate Hub, UC Davis","active":true,"usgs":false},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":472210,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045771,"text":"ofr20121051 - 2013 - Benthic substrate classification map: Gulf Islands National Seashore","interactions":[],"lastModifiedDate":"2013-05-03T15:17:16","indexId":"ofr20121051","displayToPublicDate":"2013-05-03T00:00:00","publicationYear":"2013","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":"2012-1051","title":"Benthic substrate classification map: Gulf Islands National Seashore","docAbstract":"The 2005 hurricane season was devastating for the Mississippi Gulf Coast. Hurricane Katrina caused significant degradation of the barrier islands that compose the Gulf Islands National Seashore (GUIS). Because of the ability of coastal barrier islands to help mitigate hurricane damage to the mainland, restoring these habitats prior to the onset of future storms will help protect the islands themselves and the surrounding habitats.  During Hurricane Katrina, coastal barrier islands reduced storm surge by approximately 10 percent and moderated wave heights (Wamsley and others, 2009). Islands protected the mainland by preventing ocean waves from maintaining their size as they approached the mainland. In addition to storm protection, it is advantageous to restore these islands to preserve the cultural heritage present there (for example, Fort Massachusetts) and because of the influence that these islands have on marine ecology. For example, these islands help maintain a salinity regime favorable to oysters in the Mississippi Sound and provide critical habitats for many migratory birds and endangered species such as sea turtles (Chelonia mydas, Caretta caretta, and Dermochelys coriacea), Gulf sturgeon (Acipenser oxyrinchus desotoi), and piping plovers (Charadrius melodus) (U.S. Army Corps of Engineers, 2009a).  As land manager for the GUIS, the National Park Service (NPS) has been working with the State of Mississippi and the Mobile District of the U.S. Army Corps of Engineers to provide a set of recommendations to the Mississippi Coastal Improvements Program (MsCIP) that will guide restoration planning. The final set of recommendations includes directly renourishing both West Ship Island (to protect Fort Massachusetts) and East Ship Island (to restore the French Warehouse archaeological site); filling Camille Cut to recreate a continuous Ship Island; and restoring natural regional sediment transport processes by placing sand in the littoral zone just east of Petit Bois Island. Prevailing sediment transport processes will provide natural renourishment of the westward islands in the barrier system (U.S. Army Corps of Engineers, 2009b).  One difficulty in developing the final recommendations is that few data are available to incorporate into restoration plans related to bathymetry, sediment type, and biota. For example, the most recent bathymetry available dates to when East and West Ship Islands were a single continuous island (1917). As a result, the MsCIP program has encouraged post-hurricane bathymetric data collection for future reference. Furthermore, managing a complex environment such as this barrier island system for habitat conservation and best resource usage requires significant knowledge about those habitats and resources. To effectively address these issues, a complete and comprehensive understanding of the type, geographic extent, and condition of marine resources included within the GUIS is required. However, the data related to the GUIS marine resources are limited either spatially or temporally. Specifically, there is limited knowledge and information about the distribution of benthic habitats and the characteristics of the offshore region of the GUIS, even though these are the habitats that will be most affected by habitat restoration. The goal of this project is to develop a comprehensive map of the benthic marine habitats within the GUIS to give park managers the ability to develop strategies for coastal and ocean-resource management and to aid decisionmakers in evaluating conservation priorities.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121051","collaboration":"Prepared as part of the U.S. Geological Survey Northern Gulf of Mexico Progam","usgsCitation":"Lavoie, D., Flocks, J., Twichell, D., and Rose, K., 2013, Benthic substrate classification map: Gulf Islands National Seashore: U.S. Geological Survey Open-File Report 2012-1051, vi, 14 p., https://doi.org/10.3133/ofr20121051.","productDescription":"vi, 14 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":271804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121051.gif"},{"id":271802,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1051/"},{"id":271803,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1051/pdf/ofr2012-1051.pdf"}],"country":"United States","state":"Mississippi","otherGeospatial":"Mississippi Gulf Coast","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.74,28.49 ], [ -88.74,30.4 ], [ -85.8,30.4 ], [ -85.8,28.49 ], [ -88.74,28.49 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5184ce51e4b04d6ec94d6295","contributors":{"authors":[{"text":"Lavoie, Dawn","contributorId":43881,"corporation":false,"usgs":true,"family":"Lavoie","given":"Dawn","affiliations":[],"preferred":false,"id":478333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flocks, James","contributorId":62266,"corporation":false,"usgs":true,"family":"Flocks","given":"James","affiliations":[],"preferred":false,"id":478334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Twichell, Dave","contributorId":23421,"corporation":false,"usgs":true,"family":"Twichell","given":"Dave","affiliations":[],"preferred":false,"id":478332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rose, Kate","contributorId":66154,"corporation":false,"usgs":true,"family":"Rose","given":"Kate","email":"","affiliations":[],"preferred":false,"id":478335,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047837,"text":"70047837 - 2013 - Vascular plant and vertebrate species richness in national parks of the eastern United States","interactions":[],"lastModifiedDate":"2013-11-15T09:49:42","indexId":"70047837","displayToPublicDate":"2013-05-01T09:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":56,"text":"Natural Resource Technical Report NPS/NCR/NCRO/NRTR","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"2013/002","title":"Vascular plant and vertebrate species richness in national parks of the eastern United States","docAbstract":"Given the estimates that species diversity is diminishing at 50-100 times the normal rate, it is critical that we be able to evaluate changes in species richness in order to make informed decisions for conserving species diversity.  In this study, we examined the potential of vascular plant species richness to be used as a surrogate for vertebrate species richness in the classes of amphibians, reptiles, birds, and mammals.  Vascular plants, as primary producers, represent the biotic starting point for ecological community structure and are the logical place to start for understanding vertebrate species associations.  We used data collected by the United States (US) National Park Service (NPS) on species presence within parks in the eastern US to estimate simple linear regressions between plant species richness and vertebrate richness. Because environmental factors may also influence species diversity, we performed simple linear regressions of species richness versus natural logarithm of park area, park latitude, mean annual precipitation, mean annual temperature, and human population density surrounding the parks.  We then combined plant species richness and environmental variables in multiple regressions to determine the variables that remained as significant predictors of vertebrate species richness.  As expected, we detected significant relationships between plant species richness and amphibian, bird, and mammal species richness.  In some cases, plant species richness was predicted by park area alone.  Species richness of mammals was only related to plant species richness.  Reptile species richness, on the other hand, was related to plant species richness, park latitude and annual precipitation, while amphibian species richness was related to park latitude, park area, and plant species richness.  Thus, plant species richness predicted species richness of different vertebrate groups to varying degrees and should not be used exclusively as a surrogate for vertebrate species richness.  Plant species richness should be included with other variables such as area and climate when considering strategies to manage and conserve species in US National Parks.  It is not always appropriate to draw conclusions about analyses of taxonomic surrogates from one area to another. Two patterns evident from the linear regressions were the increase in species richness with the increase of park area and with increase of vascular plant species richness.  To test whether there were differences in these patterns among networks, we used analysis of covariance (ANCOVA).  Differences among networks were detected only in bird species richness versus plant species richness and for all taxa except mammals for vertebrate species richness versus park area.  Some of these results may be due to small sample size among networks, and therefore, low statistical power.  Other factors that could have contributed to these results were differences in average park area and habitat heterogeneity among networks, latitudinal gradients, low variation in mean annual precipitation, and different use of vegetation by migratory species.  Based on these results we recommend that management of biodiversity be approached from local and site specific criteria rather than applying management directives derived from other regions of the US.  It is also recommended that analyses similar to those presented here be conducted for all national parks, once data become available for all networks in the US, to gain a better understanding of how vascular plant species richness, area, and vertebrate species richness are related in the US.","language":"English","publisher":"National Park Service","publisherLocation":"Washington, D.C.","usgsCitation":"Hatfield, J., Myrick, K.E., Huston, M.A., Weckerly, F.W., and Green, M.C., 2013, Vascular plant and vertebrate species richness in national parks of the eastern United States: Natural Resource Technical Report NPS/NCR/NCRO/NRTR 2013/002, v. 002, no. 2013, vi, 50 p.","productDescription":"vi, 50 p.","numberOfPages":"60","ipdsId":"IP-050677","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":279101,"type":{"id":11,"text":"Document"},"url":"https://www.pwrc.usgs.gov/prodabs/pubpdfs/7906_Hatfield.pdf"},{"id":279102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"projection":"Albers equal-area conic projection","country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.55,32.1 ], [ -100.55,50.68 ], [ -66.4,50.68 ], [ -66.4,32.1 ], [ -100.55,32.1 ] ] ] } } ] }","volume":"002","issue":"2013","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5287509fe4b03b89f6f155ea","contributors":{"authors":[{"text":"Hatfield, Jeffrey S. jhatfield@usgs.gov","contributorId":151,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeffrey S.","email":"jhatfield@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":483103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myrick, Kaci E.","contributorId":18667,"corporation":false,"usgs":true,"family":"Myrick","given":"Kaci","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":483105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huston, Michael A.","contributorId":57351,"corporation":false,"usgs":true,"family":"Huston","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":483107,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weckerly, Floyd W.","contributorId":10298,"corporation":false,"usgs":false,"family":"Weckerly","given":"Floyd","email":"","middleInitial":"W.","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":483104,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Green, M. Clay","contributorId":55325,"corporation":false,"usgs":true,"family":"Green","given":"M.","email":"","middleInitial":"Clay","affiliations":[],"preferred":false,"id":483106,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70043407,"text":"70043407 - 2013 - Reevaluation of the Piermont-Frontenac allochthon in the Upper Connecticut Valley: Restoration of a coherent Boundary Mountains–Bronson Hill stratigraphic sequence","interactions":[],"lastModifiedDate":"2013-06-07T15:09:37","indexId":"70043407","displayToPublicDate":"2013-05-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Reevaluation of the Piermont-Frontenac allochthon in the Upper Connecticut Valley: Restoration of a coherent Boundary Mountains–Bronson Hill stratigraphic sequence","docAbstract":"The regional extent and mode and time of emplacement of the Piermont-Frontenac allochthon in the Boundary Mountains–Bronson Hill anticlinorium of the Upper Connecticut Valley, New Hampshire–Vermont, are controversial. Moench and coworkers beginning in the 1980s proposed that much of the autochthonous pre–Middle Ordovician section of the anticlinorium was a large allochthon of Silurian to Early Devonian rocks correlated to those near Rangeley, Maine. This ∼200-km-long allochthon was postulated to have been transported westward in the latest Silurian to Early Devonian as a soft-sediment gravity slide on a hypothesized Foster Hill fault. New mapping and U-Pb geochronology do not support this interpretation. The undisputed Rangeley sequence in the Bean Brook slice is different from the disputed sequence in the proposed larger Piermont-Frontenac allochthon, and field evidence for the Foster Hill fault is lacking. At the type locality on Foster Hill, the postulated “fault” is a stratigraphic contact within the Ordovician Ammonoosuc Volcanics. The proposed Foster Hill fault would place the Piermont-Frontenac allochthon over the inverted limb of the Cornish(?) nappe, which includes the Emsian Littleton Formation, thus limiting the alleged submarine slide to post-Emsian time. Mafic dikes of the 419 Ma Comerford Intrusive Complex intrude previously folded strata attributed to the larger Piermont-Frontenac allochthon as well as the autochthonous Albee Formation and Ammonoosuc Volcanics. The Lost Nation pluton intruded and produced hornfels in previously deformed Albee strata. Zircons from an apophysis of the pluton in the hornfels have a thermal ionization mass spectrometry <sup>207</sup>Pb/<sup>206</sup>Pb age of 444.1 ± 2.1 Ma. Tonalite near Bath, New Hampshire, has a zircon sensitive high-resolution ion microprobe <sup>206</sup>Pb/<sup>238</sup>U age of 492.5 ± 7.8 Ma. The tonalite intrudes the Albee Formation, formerly interpreted as the Silurian Perry Mountain Formation of the proposed allochthon. Collectively, these features indicate that the large Piermont-Frontenac allochthon gravity slide of Silurian-Devonian strata, as previously proposed, cannot exist. Allochthonous rocks are restricted to a 25 km<sup>2</sup> klippe, the Bean Brook slice, emplaced by hard-rock thrusting in the post-Emsian Devonian. The Albee Formation, the oldest unit in the study area, is older than the Late Cambrian tonalite at Bath. The correlation and apparent continuity along strike to the northeast of the Albee Formation with the Dead River Formation suggest that the Albee Formation, like the Dead River Formation, is of Ganderian affinity and that the Bronson Hill magmatic arc in the Upper Connecticut Valley was built on Ganderian crust. The Dead River Formation is unconformably overlain by Middle and Upper Ordovician volcanic units; the unconformity is attributed to the pre-Arenig Penobscottian orogeny. Some of the pre-Silurian deformation in the Upper Connecticut Valley may be Penobscottian rather than Taconian. New stratigraphic units defined herein include the pelitic Scarritt Member of the Albee Formation, the Ordovician Washburn Brook Formation consisting of synsedimentary breccia and coticule, chert, and ironstone, and the Devonian–Silurian Sawyer Mountain Formation, probably correlative with the Frontenac Formation. The Partridge Formation is partially coeval with the Ammonoosuc Volcanics.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geological Society of America Bulletin","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Geological Society of America","doi":"10.1130/B30590.1","usgsCitation":"Rankin, D., Tucker, R.D., and Amelin, Y., 2013, Reevaluation of the Piermont-Frontenac allochthon in the Upper Connecticut Valley: Restoration of a coherent Boundary Mountains–Bronson Hill stratigraphic sequence: Geological Society of America Bulletin, v. 125, no. 5-6, p. 998-1024, https://doi.org/10.1130/B30590.1.","productDescription":"27 p.","startPage":"998","endPage":"1024","ipdsId":"IP-035967","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":273462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273461,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/B30590.1"}],"country":"United States","state":"New Hampshire;Vermont","volume":"125","issue":"5-6","noUsgsAuthors":false,"publicationDate":"2012-11-21","publicationStatus":"PW","scienceBaseUri":"51b300e6e4b01368e589e3f8","contributors":{"authors":[{"text":"Rankin, Douglas W. dwrankin@usgs.gov","contributorId":1770,"corporation":false,"usgs":true,"family":"Rankin","given":"Douglas W.","email":"dwrankin@usgs.gov","affiliations":[],"preferred":true,"id":473536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Robert D. 0000-0001-8463-4358 rtucker@usgs.gov","orcid":"https://orcid.org/0000-0001-8463-4358","contributorId":2007,"corporation":false,"usgs":true,"family":"Tucker","given":"Robert","email":"rtucker@usgs.gov","middleInitial":"D.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":473537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amelin, Yuri","contributorId":94955,"corporation":false,"usgs":true,"family":"Amelin","given":"Yuri","affiliations":[],"preferred":false,"id":473538,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70045702,"text":"ofr20131099 - 2013 - Differential expression profiles of microRNA in the little brown bat (Myotis lucifugus) associated with white nose syndrome affected and unaffected individuals","interactions":[],"lastModifiedDate":"2024-03-04T18:46:56.883032","indexId":"ofr20131099","displayToPublicDate":"2013-04-30T00:00:00","publicationYear":"2013","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":"2013-1099","title":"Differential expression profiles of microRNA in the little brown bat (Myotis lucifugus) associated with white nose syndrome affected and unaffected individuals","docAbstract":"First documented in New York State in 2006, white nose syndrome (WNS) quickly became the leading cause of mortality in hibernating bat species in the United States. WNS is caused by a psychrophilic fungus, Geomyces destructans. Clinical signs of this pathogen are expressed as a dusty white fungus predominately around the nose and on the wings of affected bats. Relatively new biomarkers, such as microRNAs (miRNAs) are being targeted as markers to predict the syndrome prior to the clinical manifestation. The primary objective of this study was to identify miRNAs that could serve as biomarkers and proxies of little brown bat health. Bats were collected from hibernacula that had tested positive and negative for WNS. Genetic sequencing was completed using the Ion Torrent platform. A number of miRNAs were identified from the liver as putative biomarkers of WNS. However, given the small sample size for each treatment, this data set has only coarsely identified miRNAs indicative of WNS, and further validation is required.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131099","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Iwanowicz, D., Iwanowicz, L., Hitt, N., and King, T., 2013, Differential expression profiles of microRNA in the little brown bat (Myotis lucifugus) associated with white nose syndrome affected and unaffected individuals: U.S. Geological Survey Open-File Report 2013-1099, iv, 11 p., https://doi.org/10.3133/ofr20131099.","productDescription":"iv, 11 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":271636,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131099.png"},{"id":271635,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1099/pdf/ofr2013-1099.pdf"},{"id":271634,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1099/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5180d9dae4b0df838b924d2d","contributors":{"authors":[{"text":"Iwanowicz, D.D.","contributorId":97706,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"D.D.","email":"","affiliations":[],"preferred":false,"id":478098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, L. R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":43864,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"L. R.","affiliations":[],"preferred":false,"id":478096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hitt, N.P. 0000-0002-1046-4568","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":101466,"corporation":false,"usgs":true,"family":"Hitt","given":"N.P.","affiliations":[],"preferred":false,"id":478099,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, T.L.","contributorId":93416,"corporation":false,"usgs":true,"family":"King","given":"T.L.","email":"","affiliations":[],"preferred":false,"id":478097,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043334,"text":"70043334 - 2013 - Developing a new stream metric for comparing stream function using a bank-floodplain sediment budget: a case study of three Piedmont streams","interactions":[],"lastModifiedDate":"2013-06-17T09:15:16","indexId":"70043334","displayToPublicDate":"2013-04-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Developing a new stream metric for comparing stream function using a bank-floodplain sediment budget: a case study of three Piedmont streams","docAbstract":"A bank and floodplain sediment budget was created for three Piedmont streams tributary to the Chesapeake Bay. The watersheds of each stream varied in land use from urban (Difficult Run) to urbanizing (Little Conestoga Creek) to agricultural (Linganore Creek). The purpose of the study was to determine the relation between geomorphic parameters and sediment dynamics and to develop a floodplain trapping metric for comparing streams with variable characteristics. Net site sediment budgets were best explained by gradient at Difficult Run, floodplain width at Little Conestoga Creek, and the relation of channel cross-sectional area to floodplain width at Linganore Creek. A correlation for all streams indicated that net site sediment budget was best explained by relative floodplain width (ratio of channel width to floodplain width). A new geomorphic metric, the floodplain trapping factor, was used to compare sediment budgets between streams with differing suspended sediment yields. Site sediment budgets were normalized by floodplain area and divided by the stream's sediment yield to provide a unitless measure of floodplain sediment trapping. A floodplain trapping factor represents the amount of upland sediment that a particular floodplain site can trap (e.g. a factor of 5 would indicate that a particular floodplain site traps the equivalent of 5 times that area in upland erosional source area). Using this factor we determined that Linganore Creek had the highest gross and net (floodplain deposition minus bank erosion) floodplain trapping factor (107 and 46, respectively) that Difficult Run the lowest gross floodplain trapping factor (29) and Little Conestoga Creek had the lowest net floodplain trapping factor (–14, indicating that study sites were net contributors to the suspended sediment load). The trapping factor is a robust metric for comparing three streams of varied watershed and geomorphic character, it promises to be a useful tool for future stream assessments.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth Surface Processes and Landforms","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/esp.3314","usgsCitation":"Schenk, E.R., Hupp, C.R., Gellis, A., and Noe, G., 2013, Developing a new stream metric for comparing stream function using a bank-floodplain sediment budget: a case study of three Piedmont streams: Earth Surface Processes and Landforms, v. 38, no. 8, p. 771-784, https://doi.org/10.1002/esp.3314.","productDescription":"14 p.","startPage":"771","endPage":"784","ipdsId":"IP-039185","costCenters":[{"id":146,"text":"Branch of Regional Research-Eastern Region","active":false,"usgs":true}],"links":[{"id":271433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271428,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/esp.3314"}],"country":"United States","otherGeospatial":"Piedmont;Difficult Run;Little Conestoga Creek;Linganore Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -78.18,36.91 ], [ -78.18,38.71 ], [ -75.64,38.71 ], [ -75.64,36.91 ], [ -78.18,36.91 ] ] ] } } ] }","volume":"38","issue":"8","noUsgsAuthors":false,"publicationDate":"2012-09-23","publicationStatus":"PW","scienceBaseUri":"5178f0dce4b0d842c705f6ac","contributors":{"authors":[{"text":"Schenk, Edward R. 0000-0001-6886-5754 eschenk@usgs.gov","orcid":"https://orcid.org/0000-0001-6886-5754","contributorId":2183,"corporation":false,"usgs":true,"family":"Schenk","given":"Edward","email":"eschenk@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":473407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":473408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gellis, Allen","contributorId":37051,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","affiliations":[],"preferred":false,"id":473410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noe, Greg","contributorId":18650,"corporation":false,"usgs":true,"family":"Noe","given":"Greg","email":"","affiliations":[],"preferred":false,"id":473409,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70045595,"text":"70045595 - 2013 - Comparative susceptibility among three stocks of yellow perch, <i>Perca flavescens</i> (Mitchill), to viral haemorrhagic septicaemia virus strain IVb from the Great Lakes","interactions":[],"lastModifiedDate":"2016-05-17T09:01:02","indexId":"70045595","displayToPublicDate":"2013-04-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2286,"text":"Journal of Fish Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Comparative susceptibility among three stocks of yellow perch, <i>Perca flavescens</i> (Mitchill), to viral haemorrhagic septicaemia virus strain IVb from the Great Lakes","docAbstract":"<p><span>The Great Lakes strain of viral haemorrhagic septicaemia virus IVb (VHSV-IVb) is capable of infecting a wide number of naive species and has been associated with large fish kills in the Midwestern United States since its discovery in 2005. The yellow perch,&nbsp;</span><i>Perca flavescens&nbsp;</i><span>(Mitchill), a freshwater species commonly found throughout inland waters of the United States and prized for its high value in sport and commercial fisheries, is a species documented in several fish kills affiliated with VHS. In the present study, differences in survival after infection with VHSV IVb were observed among juvenile fish from three yellow perch broodstocks that were originally derived from distinct wild populations, suggesting innate differences in susceptibility due to genetic variance. While all three stocks were susceptible upon waterborne exposure to VHS virus infection, fish derived from the Midwest (Lake Winnebago, WI) showed significantly lower cumulative % survival compared with two perch stocks derived from the East Coast (Perquimans River, NC and Choptank River, MD) of the United States. However, despite differences in apparent susceptibility, clinical signs did not vary between stocks and included moderate-to-severe haemorrhages at the pelvic and pectoral fin bases and exophthalmia. After the 28-day challenge was complete, VHS virus was analysed in subsets of whole fish that had either survived or succumbed to the infection using both plaque assay and quantitative PCR methodologies. A direct correlation was identified between the two methods, suggesting the potential for both methods to be used to detect virus in a research setting.</span></p>","language":"English","publisher":"Blackwell Science","doi":"10.1111/jfd.12068","usgsCitation":"Olson, W., Emmenegger, E., Glenn, J., Winton, J., and Goetz, F., 2013, Comparative susceptibility among three stocks of yellow perch, <i>Perca flavescens</i> (Mitchill), to viral haemorrhagic septicaemia virus strain IVb from the Great Lakes: Journal of Fish Diseases, v. 36, no. 8, p. 711-719, https://doi.org/10.1111/jfd.12068.","productDescription":"9 p.","startPage":"711","endPage":"719","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042613","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":271432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.11,41.4 ], [ -92.11,48.85 ], [ -76.3,48.85 ], [ -76.3,41.4 ], [ -92.11,41.4 ] ] ] } } ] }","volume":"36","issue":"8","noUsgsAuthors":false,"publicationDate":"2013-01-11","publicationStatus":"PW","scienceBaseUri":"5178f0dbe4b0d842c705f6a4","contributors":{"authors":[{"text":"Olson, W.","contributorId":95357,"corporation":false,"usgs":true,"family":"Olson","given":"W.","email":"","affiliations":[],"preferred":false,"id":477922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Emmenegger, E.","contributorId":34324,"corporation":false,"usgs":true,"family":"Emmenegger","given":"E.","email":"","affiliations":[],"preferred":false,"id":477919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, J.","contributorId":71086,"corporation":false,"usgs":true,"family":"Glenn","given":"J.","email":"","affiliations":[],"preferred":false,"id":477921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winton, J.","contributorId":55627,"corporation":false,"usgs":true,"family":"Winton","given":"J.","email":"","affiliations":[],"preferred":false,"id":477920,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goetz, F.","contributorId":33203,"corporation":false,"usgs":true,"family":"Goetz","given":"F.","email":"","affiliations":[],"preferred":false,"id":477918,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70045559,"text":"sim3240 - 2013 - Map Showing Principal Coal Beds and Bedrock Geology of the Ucross-Arvada Area, Central Powder River Basin, Wyoming","interactions":[],"lastModifiedDate":"2013-04-23T10:10:01","indexId":"sim3240","displayToPublicDate":"2013-04-23T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3240","title":"Map Showing Principal Coal Beds and Bedrock Geology of the Ucross-Arvada Area, Central Powder River Basin, Wyoming","docAbstract":"The Ucross-Arvada area is part of the Powder River Basin, a large, north-trending structural depression between the Black Hills on the east and the Bighorn Mountains on the west. Almost all of the study area is within Sheridan and Johnson Counties, Wyoming. \n\nMost of the Ucross-Arvada area lies within the outcrop of the Wasatch Formation of Eocene age; the extreme northeast corner falls within the outcrop of the Tongue River Member of the Fort Union Formation of Paleocene age. Within the Powder River Basin, both the Wasatch Formation and the Tongue River Member of the Fort Union Formation contain significant coal resources. \n\nThe map includes locations and elevations of coal beds at 1:50,000 scale for an area that includes ten 7½-minute quadrangles covering some 500 square miles. The Wasatch Formation coal beds shown (in descending order) are Monument Peak, Walters (also called Ulm 1), Healy (also called Ulm 2), Truman, Felix, and Arvada. The Fort Union Formation coal beds shown (in descending order) are Roland (of Baker, 1929) and Smith.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3240","usgsCitation":"Molnia, C.L., 2013, Map Showing Principal Coal Beds and Bedrock Geology of the Ucross-Arvada Area, Central Powder River Basin, Wyoming: U.S. Geological Survey Scientific Investigations Map 3240, Pamphlet: iv, 11 p.; Map: 1 Sheet: 50 x 27 inches, https://doi.org/10.3133/sim3240.","productDescription":"Pamphlet: iv, 11 p.; Map: 1 Sheet: 50 x 27 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-038168","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":271392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3240.gif"},{"id":271391,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3240/SIM3240_map_508.pdf"},{"id":271389,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3240/"},{"id":271390,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3240/SIM3240_pamphlet_508.pdf"}],"country":"United States","state":"Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.0,41.0 ], [ -111.0,45.0 ], [ -104.0,45.0 ], [ -104.0,41.0 ], [ -111.0,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51779f5ae4b095699adf272e","contributors":{"authors":[{"text":"Molnia, Carol L.","contributorId":62238,"corporation":false,"usgs":true,"family":"Molnia","given":"Carol","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":477848,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045552,"text":"sir20135044 - 2013 - Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011","interactions":[],"lastModifiedDate":"2015-10-16T13:47:34","indexId":"sir20135044","displayToPublicDate":"2013-04-23T00:00:00","publicationYear":"2013","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":"2013-5044","title":"Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the White Bear Lake Conservation District, the Minnesota Pollution Control Agency, the Minnesota Department of Natural Resources, and other State, county, municipal, and regional planning agencies, watershed organizations, and private organizations, conducted a study to characterize groundwater and surface-water interactions near White Bear Lake through 2011. During 2010 and 2011, White Bear Lake and other lakes in the northeastern part of the Twin Cities Metropolitan Area were at historically low levels. Previous periods of lower water levels in White Bear Lake correlate with periods of lower precipitation; however, recent urban expansion and increased pumping from the Prairie du Chien-Jordan aquifer have raised the question of whether a decline in precipitation is the primary cause for the recent water-level decline in White Bear Lake. Understanding and quantifying the amount of groundwater inflow to a lake and water discharge from a lake to aquifers is commonly difficult but is important in the management of lake levels. Three methods were used in the study to assess groundwater and surface-water interactions on White Bear Lake: (1)&nbsp;a historical assessment (1978-2011) of levels in White Bear Lake, local groundwater levels, and their relation to historical precipitation and groundwater withdrawals in the White Bear Lake area; (2) recent (2010-11) hydrologic and water-quality data collected from White Bear Lake, other lakes, and wells; and (3) water-balance assessments for White Bear Lake in March and August 2011. An analysis of covariance between average annual lake-level change and annual precipitation indicated the relation between the two variables was significantly different from 2003 through 2011 compared with 1978 through 2002, requiring an average of 4 more inches of precipitation per year to maintain the lake level. This shift in the linear relation between annual lake-level change and annual precipitation indicated the net effect of the non-precipitation terms on the water balance has changed relative to precipitation. The average amount of precipitation required each year to maintain the lake level has increased from 33 inches per year during 1978-2002 to 37 inches per year during 2003-11. The combination of lower precipitation and an increase in groundwater withdrawals can explain the change in the lake-level response to precipitation. Annual and summer groundwater withdrawals from the Prairie du Chien-Jordan aquifer have more than doubled from 1980 through 2010. Results from a regression model constructed with annual lake-level change, annual precipitation minus evaporation, and annual volume of groundwater withdrawn from the Prairie du Chien-Jordan aquifer indicated groundwater withdrawals had a greater effect than precipitation minus evaporation on water levels in the White Bear Lake area for all years since 2003. The recent (2003-11) decline in White Bear Lake reflects the declining water levels in the Prairie du Chien-Jordan aquifer; increases in groundwater withdrawals from this aquifer are a likely cause for declines in groundwater levels and lake levels. Synoptic, static groundwater-level and lake-level measurements in March/April and August 2011 indicated groundwater was potentially flowing into White Bear Lake from glacial aquifers to the northeast and south, and lake water was potentially discharging from White Bear Lake to the underlying glacial and Prairie du Chien-Jordan aquifers and glacial aquifers to the northwest. Groundwater levels in the Prairie du Chien-Jordan aquifer below White Bear Lake are approximately 0 to 19 feet lower than surface-water levels in the lake, indicating groundwater from the aquifer likely does not flow into White Bear Lake, but lake water may discharge into the aquifer. Groundwater levels from March/April to August 2011 declined more than 10 feet in the Prairie du Chien-Jordan aquifer south of White Bear Lake and to the north in Hugo, Minnesota. Water-quality analyses of pore water from nearshore lake-sediment and well-water samples, seepage-meter measurements, and hydraulic-head differences measured in White Bear Lake also indicated groundwater was potentially flowing into White Bear Lake from shallow glacial aquifers to the east and south. Negative temperature anomalies determined in shallow waters in the water-quality survey conducted in White Bear Lake indicated several shallow-water areas where groundwater may be flowing into the lake from glacial aquifers below the lake. Cool lake-sediment temperatures (less than 18 degrees Celsius) were measured in eight areas along the northeast, east, south, and southwest shores of White Bear Lake, indicating potential areas where groundwater may flow into the lake. Stable isotope analyses of well-water, precipitation, and lake-water samples indicated wells downgradient from White Bear Lake screened in the glacial buried aquifer or open to the Prairie du Chien-Jordan aquifer receive a mixture of surface water and groundwater; the largest surface-water contributions are in wells closer to White Bear Lake. A wide range in oxygen-18/oxygen-16 and deuterium/protium ratios was measured in well-water samples, indicating different sources of water are supplying water to the wells. Well water with oxygen-18/oxygen-16 and deuterium/protium ratios that plot close to the meteoric water line consisted mostly of groundwater because deuterium/protium ratios for most groundwater usually are similar to ratios for rainwater and snow, plotting close to meteoric water lines. Well water with oxygen-18/oxygen-16 and deuterium/protium ratios that plot between the meteoric water line and ratios for the surface-water samples from White Bear Lake consists of a mixture of surface water and groundwater; the percentage of each source varies relative to its ratios. White Bear Lake is the likely source of the surface water to the wells that have a mixture of surface water and groundwater because (1) it is the only large, deep lake near these wells; (2)&nbsp;these wells are near and downgradient from White Bear Lake; and (3) these wells obtain their water from relatively deep depths, and White Bear Lake is the deepest lake in that area. The percentages of surface-water contribution to the three wells screened in the glacial buried aquifer receiving surface water were 16, 48, and 83 percent. The percentages of surface-water contribution ranged from 5 to 79 percent for the five wells open to the Prairie du Chien-Jordan aquifer receiving surface water; wells closest to White Bear Lake had the largest percentages of surface-water contribution. Water-balance analysis of White Bear Lake in March and August 2011 indicated a potential discharge of 2.8 and 4.5 inches per month, respectively, over the area of the lake from the lake to local aquifers. Most of the sediments from a 12.4-foot lake core collected at the deepest part of White Bear Lake consisted of silts, sands, and gravels likely slumped from shallower waters, with a very low amount of low-permeability, organic material.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135044","collaboration":"Prepared in cooperation with the White Bear Lake Conservation District, Minnesota Pollution Control Agency, Minnesota Department of Natural Resources, Minnesota Board of Water and Soil Resources, Twin Cities Metropolitan Council, and the Groundwater/Surface-Water Interaction Partners","usgsCitation":"Jones, P.M., Trost, J.J., Rosenberry, D.O., Jackson, P., Bode, J.A., and O’Grady, R.M., 2013, Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011: U.S. Geological Survey Scientific Investigations Report 2013-5044, ix, 73 p.; Downloads Directory, https://doi.org/10.3133/sir20135044.","productDescription":"ix, 73 p.; Downloads Directory","numberOfPages":"88","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-030440","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":271388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135044.gif"},{"id":271385,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5044/"},{"id":271387,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5044/downloads/"},{"id":271386,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5044/sir2013-5044.pdf"}],"country":"United States","state":"Minnesota","county":"Anoka County, Ramsey County, Washington County","city":"Minneapolis","otherGeospatial":"White Bear Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.2080078125,\n              44.92883525162427\n            ],\n            [\n              -93.2080078125,\n              45.2004253589021\n            ],\n            [\n              -92.80357360839842,\n              45.2004253589021\n            ],\n            [\n              -92.80357360839842,\n              44.92883525162427\n            ],\n            [\n              -93.2080078125,\n              44.92883525162427\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51779f59e4b095699adf272a","contributors":{"authors":[{"text":"Jones, Perry M. 0000-0002-6569-5144 pmjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6569-5144","contributorId":2231,"corporation":false,"usgs":true,"family":"Jones","given":"Perry","email":"pmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trost, Jared J. 0000-0003-0431-2151 jtrost@usgs.gov","orcid":"https://orcid.org/0000-0003-0431-2151","contributorId":3749,"corporation":false,"usgs":true,"family":"Trost","given":"Jared","email":"jtrost@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477837,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":477835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, P. 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