Groundwater quality in the 633-square-mile (1,639-square-kilometer) Northern Coast Ranges (NOCO) study unit was investigated as part of the Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program and the U.S. Geological Survey (USGS) National Water-Quality Assessment Program. The study unit is composed of two study areas (Interior Basins and Coastal Basins) and is located in northern California in Napa, Sonoma, Lake, Colusa, Mendocino, Glenn, Humboldt, and Del Norte Counties. The GAMA-PBP is being conducted by the California State Water Resources Control Board in collaboration with the USGS and the Lawrence Livermore National Laboratory.
\nThe GAMA NOCO study was designed to provide a spatially unbiased assessment of the quality of untreated (ambient) groundwater in the primary aquifer system within the study unit. The assessment is based on water-quality and ancillary data collected in 2009 by the USGS from 58 sites and on water-quality data from the California Department of Public Health (CDPH) database. The primary aquifer system is defined by the perforation intervals of sites listed in the CDPH water-quality database for the NOCO study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallow or deep water-bearing zones.
\nThe first component of this study, the status assessment of the current quality of the groundwater resource, was performed by using data from samples analyzed for inorganic constituents (such as trace elements and major and minor ions), organic constituents (volatile organic compounds and pesticides and pesticide degradates), the special-interest constituent perchlorate, and microbial indicators. This status assessment is intended to characterize the quality of groundwater resources in the primary aquifer system of the NOCO study unit, not the quality of treated drinking water delivered to consumers by water purveyors.
\nRelative-concentrations (sample concentration divided by the health- or aesthetic-based benchmark concentration) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or nonregulatory benchmarks for drinking-water quality. A relative-concentration greater than (>) 1.0 indicates a concentration greater than a benchmark, and a relative-concentration less than or equal to (≤) 1.0 indicates a concentration less than or equal to a benchmark. Relative-concentrations of organic constituents and perchlorate were classified as “high” (relative-concentration >1.0), “moderate” (0.1 < relative-concentration ≤1.0), or “low” (relative-concentration ≤0.1). Relative-concentrations of inorganic constituents were classified as “high” (relative-concentration >1.0), “moderate” (0.5 < relative-concentration ≤1.0), or “low” (relative-concentration ≤0.5).
\nAquifer-scale proportion was used as the primary metric in the status assessment for evaluating regional-scale groundwater quality. High aquifer-scale proportion was defined as the percentage of the area of the primary aquifer system with a relative-concentration >1.0 for a particular constituent or class of constituents; the percentage is based on an aerial rather than a volumetric basis. Moderate and low aquifer-scale proportions were defined as the percentage of the primary aquifer system with moderate and low relative-concentrations, respectively. Two statistical approaches—grid-based and spatially weighted—were used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. Grid-based and spatially weighted estimates were comparable in the NOCO study unit (within 90 percent confidence intervals).
\nInorganic constituents (one or more) with health-based benchmarks were detected at high relative-concentrations in 10.3 percent and at moderate relative-concentrations in 13.8 percent of the primary aquifer system. The high aquifer-scale proportion of inorganic constituents primarily reflected high aquifer-scale proportions of boron (in 8.6 percent of the primary aquifer system), arsenic (in 3.4 percent), and barium (in 1.7 percent). Inorganic constituents with aesthetic-based benchmarks were detected at high relative-concentrations in 39.7 percent and at moderate relative-concentrations in 10.3 percent of the primary aquifer system. The constituents present at high relative-concentrations were iron (25.9 percent) and manganese (39.7 percent).
\nRelative-concentrations of organic constituents with health-based benchmarks (one or more) were high in 0.2 percent, moderate in 1.7 percent, and low in 39.7 percent of the primary aquifer system. Organic constituents were not detected in 58.4 percent of the primary aquifer system. Of the 168 organic constituents analyzed, 11 constituents were detected. Two organic constituents had detection frequencies >10 percent: the trihalomethane chloroform and the herbicide simazine. For the 10 detected organic constituents that had health-based benchmarks, nearly all detections had low relative-concentrations. The special-interest constituent perchlorate was detected at moderate relative-concentrations in 1.7 percent and at low relative-concentrations in 22.4 percent of the primary aquifer system. Perchlorate was not detected in 75.9 percent of the primary aquifer system.
\nThe second component of this study, the understanding assessment, evaluated relations between constituent concentrations and values of selected potential explanatory factors to identify the factors potentially affecting the concentrations and occurrences of constituents found at high relative-concentrations or, for organic constituents, with detection frequencies >10 percent. The potential explanatory factors evaluated were land use (including density of septic tanks and leaking or formerly leaking underground fuel tanks), well construction (well depth and depth to the top of the perforated interval in the well), hydrologic conditions (aridity index, field water temperature, and distance to nearest hot spring and geothermal well), pH, dissolved oxygen concentration, study area, groundwater age distribution, and geochemical conditions.
\nHigh and moderate relative-concentrations of boron primarily occurred in the Interior Basins study area and may be attributed to groundwater interacting with hydrothermal systems. High and moderate relative-concentrations of boron were associated with elevated groundwater temperatures, groundwater chemistry characteristics similar to those of geothermal waters, and distance to known geothermal areas. Boron concentrations generally were higher where low dissolved oxygen concentrations or anoxic conditions exist. High and moderate relative-concentrations of arsenic predominantly occur in the Interior Basins study area under reducing conditions. Arsenic concentrations also may be influenced by hydrothermal systems (when present).
\nChloroform, simazine, and perchlorate were observed in the Interior Basins and Coastal Basins study areas, predominantly at shallow sites with top-of-perforation depths ≤70 feet below land surface, with modern water (post-1950s), and with oxic groundwater conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145215","collaboration":"Prepared in cooperation with the California State Water Resources Control Board and the U.S. Geological Survey National Water-Quality Assessment Program","usgsCitation":"Mathany, T.M., and Belitz, K., 2015, Status and understanding of groundwater quality in the Northern Coast Ranges study unit, 2009: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014-5215, x, 86 p., https://doi.org/10.3133/sir20145215.","productDescription":"x, 86 p.","numberOfPages":"100","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2009-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-030141","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":298170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145215.jpg"},{"id":298169,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5215/pdf/sir2014-5215.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298148,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5215/"}],"country":"United States","state":"California","county":"Colusa County, Del Norte County, Glenn County, Humboldt County, Lake County, Mendocino County, Napa County, Sonoma County","otherGeospatial":"Northern Coast Ranges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.541015625,\n 38.66835610151509\n ],\n [\n -124.541015625,\n 41.96765920367816\n ],\n [\n -121.79443359375,\n 41.96765920367816\n ],\n [\n -121.79443359375,\n 38.66835610151509\n ],\n [\n -124.541015625,\n 38.66835610151509\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043afe4b02419550ce86c","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113 tmathany@usgs.gov","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":1713,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy","email":"tmathany@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":541550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":541551,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70116921,"text":"ofr20141109 - 2015 - GRIDGEN Version 1.0: a computer program for generating unstructured finite-volume grids","interactions":[],"lastModifiedDate":"2015-02-26T10:52:37","indexId":"ofr20141109","displayToPublicDate":"2015-02-26T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1109","title":"GRIDGEN Version 1.0: a computer program for generating unstructured finite-volume grids","docAbstract":"GRIDGEN is a computer program for creating layered quadtree grids for use with numerical models, such as the MODFLOW–USG program for simulation of groundwater flow. The program begins by reading a three-dimensional base grid, which can have variable row and column widths and spatially variable cell top and bottom elevations. From this base grid, GRIDGEN will continuously divide into four any cell intersecting user-provided refinement features (points, lines, and polygons) until the desired level of refinement is reached. GRIDGEN will then smooth, or balance, the grid so that no two adjacent cells, including overlying and underlying cells, differ by more than a user-specified level tolerance. Once these gridding processes are completed, GRIDGEN saves a tree structure file so that the layered quadtree grid can be quickly reconstructed as needed. Once a tree structure file has been created, GRIDGEN can then be used to (1) export the layered quadtree grid as a shapefile, (2) export grid connectivity and cell information as ASCII text files for use with MODFLOW–USG or other numerical models, and (3) intersect the grid with shapefiles of points, lines, or polygons, and save intersection output as ASCII text files and shapefiles. The GRIDGEN program is demonstrated by creating a layered quadtree grid for the Biscayne aquifer in Miami-Dade County, Florida, using hydrologic features to control where refinement is added.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141109","collaboration":"Prepared in cooperation with George Mason University","usgsCitation":"Lien, J., Liu, G., and Langevin, C.D., 2015, GRIDGEN Version 1.0: a computer program for generating unstructured finite-volume grids: U.S. Geological Survey Open-File Report 2014-1109, vi, 26 p., https://doi.org/10.3133/ofr20141109.","productDescription":"vi, 26 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055584","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":298168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141109.jpg"},{"id":298166,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1109/"},{"id":298167,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1109/pdf/ofr2014-1109.pdf","text":"Report","size":"1.93 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043aae4b02419550ce862","contributors":{"authors":[{"text":"Lien, Jyh-Ming","contributorId":139494,"corporation":false,"usgs":true,"family":"Lien","given":"Jyh-Ming","email":"","affiliations":[],"preferred":false,"id":541557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Gaisheng","contributorId":15158,"corporation":false,"usgs":true,"family":"Liu","given":"Gaisheng","email":"","affiliations":[],"preferred":false,"id":541558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":519055,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70133291,"text":"fs20143114 - 2015 - Groundwater quality in the Northern Coast Ranges Basins, California","interactions":[],"lastModifiedDate":"2018-05-24T12:52:45","indexId":"fs20143114","displayToPublicDate":"2015-02-26T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3114","title":"Groundwater quality in the Northern Coast Ranges Basins, California","docAbstract":"The Northern Coast Ranges (NOCO) study unit is 633 square miles and consists of 35 groundwater basins and subbasins (California Department of Water Resources, 2003; Mathany and Belitz, 2015). These basins and subbasins were grouped into two study areas based primarily on locality. The groundwater basins and subbasins located inland, not adjacent to the Pacific Ocean, were aggregated into the Interior Basins (NOCO-IN) study area. The groundwater basins and subbasins adjacent to the Pacific Ocean were aggregated into the Coastal Basins (NOCO-CO) study area (Mathany and others, 2011).
\nThe primary aquifer system in the NOCO-IN study area occurs in alluvial basins made up of sand, silt, gravel, clay, and thin volcanic ash layers or lenses. Groundwater movement in the NOCO-IN study area follows the topography and direction of surface-water features. In the NOCO-CO study area, groundwater is present in alluvial fan, floodplain, and terrace deposits. Groundwater movement in the NOCO-CO study area is from east to west towards the Pacific Ocean.
\nThe primary aquifer system in the study unit generally is defined as those parts of the aquifer system corresponding to the perforated intervals of sites listed in the California Department of Public Health (CDPH) database of public drinking-water supply sources. Well depths in the NOCO-IN study area ranged from 36 to 400 feet below land surface (ft bls), and depths to top-of-perforations ranged from 15 to 148 ft bls. In the NOCO-CO study area, well depths ranged from 15 to 400 ft bls, and depths to top-of-perforations ranged from 10 to 356 ft bls. Water quality in the primary aquifer system may differ from that in the shallower and deeper parts of the aquifer system.
\nAverage annual rainfall in the NOCO study unit ranges from 22 to 79 inches. In the NOCO-IN study area, the climate is classified as Mediterranean, with warm to hot, dry summers and cold, wet winters. In the NOCO-CO study area, the climate is influenced by the Pacific Ocean and is characterized by cool to mild summers and cold, wet winters. The study unit is drained by several rivers and their principal tributaries: the Eel, Russian, Mad, Navarro, Smith, Klamath, Noyo, and Big Rivers.
\nLand use in the study unit is about 60 percent (%) natural (mostly grassland and forest), 29% agricultural, and 11% urban. The primary uses of agricultural lands are pasture, row crops, hay, vineyards, and timberlands. The largest urban areas are the cities of Crescent City, Arcata, Eureka, Fort Bragg, Willits, Ukiah, and Lakeport.
\nRecharge to the groundwater system is primarily from mixture of ambient sources, including direct percolation of precipitation and irrigation waters, infiltration of runoff from surrounding hills/areas, seepage from rivers and creeks, and subsurface inflow (from non-alluvial geologic units that bound the alluvial basins). The primary sources of discharge are evaporation, discharge to streams, and water pumped for municipal supply and irrigation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143114","collaboration":"U.S. Geological Survey and the California State Water Resources Control Board","usgsCitation":"Mathany, T.M., and Belitz, K., 2015, Groundwater quality in the Northern Coast Ranges Basins, California: U.S. Geological Survey Fact Sheet 2014-3114, 4 p., https://doi.org/10.3133/fs20143114.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-044056","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":298165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143114.JPG"},{"id":298163,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3114/pdf/fs2014-3114.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298164,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sir/2014/5215/","text":"Scientific Investigations Report 2014-5215","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Report 2014-5215"},{"id":298147,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3114/"}],"country":"United States","state":"California","otherGeospatial":"Northern Coast Ranges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.541015625,\n 38.66835610151509\n ],\n [\n -124.541015625,\n 41.96765920367816\n ],\n [\n -121.79443359375,\n 41.96765920367816\n ],\n [\n -121.79443359375,\n 38.66835610151509\n ],\n [\n -124.541015625,\n 38.66835610151509\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043ace4b02419550ce864","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113 tmathany@usgs.gov","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":1713,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy","email":"tmathany@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":541548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":541549,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70141633,"text":"pp1650G - 2015 - Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: Revisions for all taxa from the United States and Canada and new taxa from the western United States","interactions":[],"lastModifiedDate":"2023-08-29T14:10:23.523993","indexId":"pp1650G","displayToPublicDate":"2015-02-26T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1650","chapter":"G","title":"Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: Revisions for all taxa from the United States and Canada and new taxa from the western United States","docAbstract":"This is the seventh volume in an atlas series that explores the relations between the geographic distributions of woody plant species and climatic variables in North America. A 25-kilometer (km) equal-area grid of modern climatic and bioclimatic variables was constructed from weather data. The geographic distributions of selected tree and shrub species were digitized, and the presence or absence of each species was determined for each point on the 25-km grid, thus providing a basis for comparing climatic data and species' distributions. The relations between climate and plant distributions are presented in graphical and tabular form. The results of this effort are intended primarily for use in biogeographic, ecologic, paleoclimatic, and global-change research.
\nThis volume of the atlas provides numerous changes, updates, and enhancements from previous volumes. Its geographic coverage is now restricted to Canada and the continental United States, and the source and time period of the climatic data have changed. New variables were added, including monthly values for temperature and precipitation, and measures of interannual variability. The distribution maps for all previously published species were redigitized, some distribution maps were revised, and 148 new species were added from the arid and semiarid western United States. The graphical displays were expanded to illustrate the new climatic variables, and the data tables were modified to provide more detail on the population distributions of plant taxa relative to climatic variables.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1650G","usgsCitation":"Thompson, R.S., Anderson, K.H., Pelltier, R.T., Strickland, L.E., Shafer, S.L., Bartlein, P.J., and McFadden, A., 2015, Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: Revisions for all taxa from the United States and Canada and new taxa from the western United States: U.S. Geological Survey Professional Paper 1650, HTML Document; Downloads Directory, https://doi.org/10.3133/pp1650G.","productDescription":"HTML Document; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-048941","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":419975,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FPD80E","text":"USGS data release","linkHelpText":"A gridded database of the modern distributions of climate, woody plant taxa, and ecoregions for the continental United States and Canada"},{"id":298161,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/pp/p1650-g/downloads/pp1650-g.zip","text":"Downloads Directory","linkHelpText":"Contains: PP1650-G.zip"},{"id":298162,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp1650g.JPG"},{"id":298146,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/p1650-g/"}],"country":"Canada, United States","otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.328125,\n 24.846565348219734\n ],\n [\n -141.328125,\n 70.0205873017406\n ],\n [\n -55.1953125,\n 70.0205873017406\n ],\n [\n -55.1953125,\n 24.846565348219734\n ],\n [\n -141.328125,\n 24.846565348219734\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043a8e4b02419550ce860","contributors":{"authors":[{"text":"Thompson, Robert S. 0000-0001-9287-2954 rthompson@usgs.gov","orcid":"https://orcid.org/0000-0001-9287-2954","contributorId":891,"corporation":false,"usgs":true,"family":"Thompson","given":"Robert","email":"rthompson@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":541541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Katherine H. 0000-0003-2677-6109","orcid":"https://orcid.org/0000-0003-2677-6109","contributorId":52556,"corporation":false,"usgs":true,"family":"Anderson","given":"Katherine","email":"","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":541542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pelltier, Richard T. 0000-0001-8322-7961 rtpelltier@usgs.gov","orcid":"https://orcid.org/0000-0001-8322-7961","contributorId":4683,"corporation":false,"usgs":true,"family":"Pelltier","given":"Richard","email":"rtpelltier@usgs.gov","middleInitial":"T.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":541543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strickland, Laura E. 0000-0002-1958-7273 lstrickland@usgs.gov","orcid":"https://orcid.org/0000-0002-1958-7273","contributorId":4682,"corporation":false,"usgs":true,"family":"Strickland","given":"Laura","email":"lstrickland@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":541544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shafer, Sarah L. 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":1684,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":541545,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bartlein, Patrick J.","contributorId":106879,"corporation":false,"usgs":true,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":541546,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McFadden, Andrew K.","contributorId":139367,"corporation":false,"usgs":false,"family":"McFadden","given":"Andrew K.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":541547,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70138825,"text":"fs20153005 - 2015 - In-place oil shale resources of the Mahogany zone sorted by grade, overburden thickness and stripping ratio, Green River Formation, Piceance Basin, Colorado and Uinta Basin, Utah","interactions":[],"lastModifiedDate":"2015-02-26T11:45:42","indexId":"fs20153005","displayToPublicDate":"2015-02-26T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3005","title":"In-place oil shale resources of the Mahogany zone sorted by grade, overburden thickness and stripping ratio, Green River Formation, Piceance Basin, Colorado and Uinta Basin, Utah","docAbstract":"A range of geological parameters relevant to mining oil shale have been examined for the Mahogany zone of the Green River Formation in the Piceance Basin, Colorado, and Uinta Basin, Utah, using information available in the U.S. Geological Survey Oil Shale Assessment database. Basinwide discrete and cumulative distributions of resource in-place as a function of (1) oil shale grade, (2) Mahogany zone thickness, (3) overburden thickness, and (4) stripping ratio (overburden divided by zone thickness) were determined for both basins on a per-acre basis, and a resource map showing the areal distribution of these properties was generated. Estimates of how much of the Mahogany zone resource meets various combinations of these parameters were also determined. Of the 191.7 billion barrels of Mahogany zone oil in-place in the Piceance Basin, 32.3 percent (61.8 billion barrels) is associated with oil shale yielding at least 25 gallons of oil per ton (GPT) of rock processed, is covered by overburden 1,000 feet thick or less, and has a stripping ratio of less than 10. In the Uinta Basin, 14.0 percent (29.9 billion barrels) of the 214.5 billion barrels of Mahogany zone oil in-place meets the same overburden and stripping ratio criteria but only for the lower grade cutoff of 15 GPT.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153005","usgsCitation":"Birdwell, J.E., Mercier, T.J., Johnson, R.C., and Brownfield, M.E., 2015, In-place oil shale resources of the Mahogany zone sorted by grade, overburden thickness and stripping ratio, Green River Formation, Piceance Basin, Colorado and Uinta Basin, Utah: U.S. Geological Survey Fact Sheet 2015-3005, 6 p., https://doi.org/10.3133/fs20153005.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060005","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":298159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153005.jpg"},{"id":298157,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3005/"},{"id":298158,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3005/pdf/fs2015-3005.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Colorado, Utah","otherGeospatial":"Piceance Basin, Uinta Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.08203125,\n 37.00255267215955\n ],\n [\n -114.08203125,\n 41.983994270935625\n ],\n [\n -102.041015625,\n 41.983994270935625\n ],\n [\n -102.041015625,\n 37.00255267215955\n ],\n [\n -114.08203125,\n 37.00255267215955\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043aee4b02419550ce866","contributors":{"authors":[{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":541537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":541539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":541540,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70141913,"text":"fs20153014 - 2015 - Maine StreamStats: a water-resources web application","interactions":[],"lastModifiedDate":"2015-02-26T10:56:46","indexId":"fs20153014","displayToPublicDate":"2015-02-26T09:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3014","title":"Maine StreamStats: a water-resources web application","docAbstract":"Maine StreamStats is a tool that any user with Internet access can use to delineate a basin on the fly and estimate a wide variety of streamflow statistics for ungaged sites on rivers and streams in Maine. Estimates are based on regression equations or are from data from similar gaged locations on the stream. Maine StreamStats is based on a national StreamStats application that can be used for streamflow estimates in many other states across the country.
\nReports referenced in this fact sheet present the regression equations used to estimate the flow statistics, describe the errors associated with the estimates, and describe the methods used to develop the equations and to measure the basin characteristics used in the equations. Limitations of the methods are also described in the reports; for example, all of the equations are appropriate only for ungaged, unregulated, rural streams in Maine.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153014","collaboration":"Prepared in cooperation with Maine Department of Transportation","usgsCitation":"Lombard, P., 2015, Maine StreamStats: a water-resources web application: U.S. Geological Survey Fact Sheet 2015-3014, 2 p., https://doi.org/10.3133/fs20153014.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063510","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":298152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153014.jpg"},{"id":298150,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3014/pdf/fs2015-3014.pdf","text":"Report","size":"739 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298151,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://streamstats.usgs.gov/","text":"Maine StreamStats","linkHelpText":"a geographic information system-based Web application of the U.S. Geological Survey, is a tool for calculating basin characteristics and streamflow statistics for user-selected sites on streams in Maine."},{"id":298149,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3014/"}],"country":"United States","state":"Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.927734375,\n 43.068887774169625\n ],\n [\n -70.927734375,\n 47.517200697839414\n ],\n [\n -66.884765625,\n 47.517200697839414\n ],\n [\n -66.884765625,\n 43.068887774169625\n ],\n [\n -70.927734375,\n 43.068887774169625\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043aee4b02419550ce868","contributors":{"authors":[{"text":"Lombard, Pamela J. plombard@usgs.gov","contributorId":871,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela J.","email":"plombard@usgs.gov","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":false,"id":541536,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70141966,"text":"70141966 - 2015 - Wildlife, urban inputs, and landscape configuration are responsible for degraded swimming water quality at an embayed beach","interactions":[],"lastModifiedDate":"2015-02-25T12:49:21","indexId":"70141966","displayToPublicDate":"2015-02-25T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Wildlife, urban inputs, and landscape configuration are responsible for degraded swimming water quality at an embayed beach","docAbstract":"Jeorse Park Beach, on southern Lake Michigan, experiences frequent closures due to high Escherichia coli (E. coli) levels since regular monitoring was implemented in 2005. During the summer of 2010, contaminant source tracking techniques, such as the conventional microbial and physical surveys and hydrodynamic models, were used to determine the reasons for poor water quality at Jeorse Park. Fecal indicator bacteria (E. coli, enterococci) were high throughout the season, with densities ranging from 12–2419 (culturable E. coli) and 1–2550 and < 1–5831 (culturable and qPCR enterococci, respectively). Genetic markers for human (Bacteroides HF183) and gull (Catellicoccus marimammalium) fecal contamination were found in 15% and 37% of the samples indicating multiple sources contributing to poor water quality. Nesting colonies of double-crested cormorants (Phalacrocorax auritus) have steadily increased since 2005, coinciding with high E. colilevels. A hydrodynamic model indicated that limited circulation allows bacteria entering the embayed area to be retained in nearshore areas; and bacterial resuspension from sand and stranded beach wrack during storm events compounds the problem. The integration of hydrodynamics, expanded use of chemical and biological markers, as well as more complex statistical multivariate techniques can improve microbial source tracking, informing management actions to improve recreational water quality. Alterations to embayed structures to improve circulation and reduce nuisance algae as well as growing native plants to retain sand to improve beach morphometry are among some of the restoration strategies under consideration in ongoing multi-agency collaborations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2014.11.027","usgsCitation":"Byappanahalli, M.N., Nevers, M., Whitman, R.L., Ge, Z., Shively, D.A., Spoljaric, A., and Przybyla-Kelly, K., 2015, Wildlife, urban inputs, and landscape configuration are responsible for degraded swimming water quality at an embayed beach: Journal of Great Lakes Research, v. 41, no. 1, p. 156-163, https://doi.org/10.1016/j.jglr.2014.11.027.","productDescription":"8 p.","startPage":"156","endPage":"163","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056382","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":298142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.4563217163086,\n 41.631995715210444\n ],\n [\n -87.4563217163086,\n 41.6916296425077\n ],\n [\n -87.39160537719727,\n 41.6916296425077\n ],\n [\n -87.39160537719727,\n 41.631995715210444\n ],\n [\n -87.4563217163086,\n 41.631995715210444\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54eef22ae4b02d776a684b0b","contributors":{"authors":[{"text":"Byappanahalli, Muruleedhara N. byappan@usgs.gov","contributorId":139462,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","middleInitial":"N.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":541525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nevers, Meredith 0000-0001-6963-6734 mnevers@usgs.gov","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":2013,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"mnevers@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ge, Zhongfu","contributorId":139463,"corporation":false,"usgs":false,"family":"Ge","given":"Zhongfu","email":"","affiliations":[{"id":12773,"text":"American Bureau of Shipping, Corporate Marine Technology","active":true,"usgs":false}],"preferred":false,"id":541528,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shively, Dawn A. dshively@usgs.gov","contributorId":2051,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541529,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spoljaric, Ashley 0000-0001-6262-030X aspoljaric@usgs.gov","orcid":"https://orcid.org/0000-0001-6262-030X","contributorId":139464,"corporation":false,"usgs":true,"family":"Spoljaric","given":"Ashley","email":"aspoljaric@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541530,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Przybyla-Kelly, Katarzyna kprzybyla-kelly@usgs.gov","contributorId":3613,"corporation":false,"usgs":true,"family":"Przybyla-Kelly","given":"Katarzyna","email":"kprzybyla-kelly@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541531,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70141967,"text":"70141967 - 2015 - The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes","interactions":[],"lastModifiedDate":"2018-04-02T15:24:19","indexId":"70141967","displayToPublicDate":"2015-02-25T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes","docAbstract":"Zero-order drainage basins, and their constituent hillslopes, are the fundamental geomorphic unit comprising much of Earth's uplands. The convergent topography of these landscapes generates spatially variable substrate and moisture content, facilitating biological diversity and influencing how the landscape filters precipitation and sequesters atmospheric carbon dioxide. In light of these significant ecosystem services, refining our understanding of how these functions are affected by landscape evolution, weather variability, and long-term climate change is imperative. In this paper we introduce the Landscape Evolution Observatory (LEO): a large-scale controllable infrastructure consisting of three replicated artificial landscapes (each 330 m2 surface area) within the climate-controlled Biosphere 2 facility in Arizona, USA. At LEO, experimental manipulation of rainfall, air temperature, relative humidity, and wind speed are possible at unprecedented scale. The Landscape Evolution Observatory was designed as a community resource to advance understanding of how topography, physical and chemical properties of soil, and biological communities coevolve, and how this coevolution affects water, carbon, and energy cycles at multiple spatial scales. With well-defined boundary conditions and an extensive network of sensors and samplers, LEO enables an iterative scientific approach that includes numerical model development and virtual experimentation, physical experimentation, data analysis, and model refinement. We plan to engage the broader scientific community through public dissemination of data from LEO, collaborative experimental design, and community-based model development.
","conferenceTitle":"46th Annual Binghamton Geomorphology Symposium","conferenceDate":"September 18-20, 2015","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2015.01.020","usgsCitation":"Pangle, L.A., DeLong, S.B., Abramson, N., Adams, J., Barron-Gafford, G.A., Breshears, D.D., Brooks, P.D., Chorover, J., Dietrich, W., Dontsova, K., Durcik, M., Espeleta, J., Ferre, T., Ferriere, R., Henderson, W., Hunt, E.A., Huxman, T.E., Millar, D., Murphy, B., Niu, G., Pavao-Zuckerman, M., Pelletier, J.D., Rasmussen, C., Ruiz, J., Saleska, S., Schaap, M., Sibayan, M., Troch, P.A., Tuller, M., van Haren, J., and Zeng, X., 2015, The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes: Geomorphology, v. 244, p. 190-203, https://doi.org/10.1016/j.geomorph.2015.01.020.","productDescription":"14 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Although sedimentary and geomorphic responses to sediment pulses are a fundamental part of landscape evolution, few opportunities exist to quantify those processes over field scales. We investigated the downstream effects of sediment released during the largest dam removal in history, on the Elwha River, Washington, USA, by measuring changes in riverbed elevation and topography, bed sediment grain size, and channel planform as two dams were removed in stages over two years.
\nAs 10.5 million t (7.1 million m3) of sediment was released from two former reservoirs, downstream dispersion of a sediment wave caused widespread bed aggradation of ~ 1 m (greater where pools filled), changed the river from pool–riffle to braided morphology, and decreased the slope of the lowermost river. The newly deposited sediment, which was finer than most of the pre-dam-removal bed, formed new bars (largely pebble, granule, and sand material), prompting aggradational channel avulsion that increased the channel braiding index by almost 50%. As a result of mainstem bed aggradation, floodplain channels received flow and accumulated new sediment even during low to moderate flow conditions. The river system showed a two- to tenfold greater geomorphic response to dam removal (in terms of bed elevation change magnitude) than it had to a 40-year flood event four years before dam removal. Two years after dam removal began, as the river had started to incise through deposits of the initial sediment wave, ~ 1.2 million t of new sediment (~ 10% of the amount released from the two reservoirs) was stored along 18 river km of the mainstem channel and 25 km of floodplain channels. The Elwha River thus was able to transport most of the released sediment to the river mouth. The geomorphic alterations and changing bed sediment grain size along the Elwha River have important ecological implications, affecting aquatic habitat structure, benthic fauna, salmonid fish spawning and rearing potential, and riparian vegetation. The response of the river to dam removal represents a unique opportunity to observe and quantify fundamental geomorphic processes associated with a massive sediment influx, and also provides important lessons for future river-restoration endeavors.
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Chironomus dilutus)—in sediments from 2 lead–zinc mining areas: the Tri-State Mining District and Southeast Missouri Mining District. Mussel tests were conducted in sediments sieved to <0.25 mm to facilitate recovery of juvenile mussels (2–4 mo old). Sediments were contaminated primarily with lead, zinc, and cadmium, with greater zinc and cadmium concentrations in Tri-State sediments and greater lead concentrations in southeast Missouri sediments. The frequency of highly toxic responses (reduced 10% or more relative to reference sites) in Tri-State sediments was greatest for amphipod survival (25% of samples), midge biomass (20%), and mussel survival (14%). In southeast Missouri sediments, the frequency of highly toxic samples was greatest for mussel biomass (25%) and amphipod biomass (13%). Thresholds for metal toxicity to mussels, expressed as hazard quotients based on probable effect concentrations, were lower for southeast Missouri sediments than for Tri-State sediments. Southeast Missouri sites with toxic sediments had 2 or fewer live mussel taxa in a concurrent mussel population survey, compared with 7 to 26 taxa at reference sites. These results demonstrate that sediment toxicity tests with juvenile mussels can be conducted reliably by modifying existing standard methods; that the sensitivity of mussels to metals can be similar to or greater than standard test organisms; and that responses of mussels in laboratory toxicity tests are consistent with effects on wild mussel populations.
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But the cause of a cyclic snowshoe hare population's reduced reproduction during the low phase of the cycle, when predator density collapses, is not completely understood. We propose that moderate-severe browsing by snowshoe hares upon preferred winter-foods could increase the toxicity of some of the hare's best winter-foods during the following hare low, with the result being a decline in hare nutrition that could reduce hare reproduction. We used a combination of modeling and experiments to explore this hypothesis. Using the shrub birch Betula glandulosa as the plant of interest, the model predicted that browsing by hares during a hare cycle peak, by increasing the toxicity B. glandulosa twigs during the following hare low, could cause a hare population to cycle. The model's assumptions were verified with assays of dammarane triterpenes in segments of B. glandulosa twigs and captive hare feeding experiments conducted in Alaska during February and March 1986. The model's predictions were tested with estimates of hare density and measurements of B. glandulosa twig growth made at Kluane, Yukon from 1988–2008. The empirical tests supported the model's predictions. Thus, we have concluded that a browsing-caused increase in twig toxicity that occurs during the hare cycle's low phase could reduce hare reproduction during the low phase of the hare cycle.
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It marks the plate boundary between the subducting Nazca plate and the South America plate, where the oceanic crust and lithosphere of the Nazca plate begin their descent into the mantle beneath South America. The convergence associated with this subduction process is responsible for the uplift of the Andes Mountains, and for the active volcanic chain present along much of this deformation front. Relative to a fixed South America plate, the Nazca plate moves slightly north of eastwards at a rate varying from approximately 80 millimeters/year (mm/yr) in the south, to approximately 65 mm/yr in the north. Although the rate of subduction varies little along the entire arc, there are complex changes in the geologic processes along the subduction zone that dramatically influence volcanic activity, crustal deformation, earthquake generation and occurrence all along the western edge of South America.
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2015 - Ecosystem consequences of changing inputs of terrestrial dissolved organic matter to lakes: current knowledge and future challenges","interactions":[],"lastModifiedDate":"2015-04-01T09:50:16","indexId":"70142976","displayToPublicDate":"2015-02-24T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem consequences of changing inputs of terrestrial dissolved organic matter to lakes: current knowledge and future challenges","docAbstract":"Lake ecosystems and the services that they provide to people are profoundly influenced by dissolved organic matter derived from terrestrial plant tissues. These terrestrial dissolved organic matter (tDOM) inputs to lakes have changed substantially in recent decades, and will likely continue to change. In this paper, we first briefly review the substantial literature describing tDOM effects on lakes and ongoing changes in tDOM inputs. We then identify and provide examples of four major challenges which limit predictions about the implications of tDOM change for lakes, as follows: First, it is currently difficult to forecast future tDOM inputs for particular lakes or lake regions. Second, tDOM influences ecosystems via complex, interacting, physical-chemical-biological effects and our holistic understanding of those effects is still rudimentary. Third, non-linearities and thresholds in relationships between tDOM inputs and ecosystem processes have not been well described. Fourth, much understanding of tDOM effects is built on comparative studies across space that may not capture likely responses through time. We conclude by identifying research approaches that may be important for overcoming those challenges in order to provide policy- and management-relevant predictions about the implications of changing tDOM inputs for lakes.
","language":"English","publisher":"Springer-Verlag","publisherLocation":"New York, NY","doi":"10.1007/s10021-015-9848-y","usgsCitation":"Solomon, C.T., Jones, S., Weidel, B., Buffam, I., Fork, M.L., Karlsson, J., Larsen, S., Lennon, J.T., Read, J.S., Sadro, S., and Saros, J.E., 2015, Ecosystem consequences of changing inputs of terrestrial dissolved organic matter to lakes: current knowledge and future challenges: Ecosystems, v. 18, no. 3, p. 376-389, https://doi.org/10.1007/s10021-015-9848-y.","productDescription":"14 p.","startPage":"376","endPage":"389","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053306","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":298554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus 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To assess the potential for decreased water levels and discharge to streams in the Pine Ridge Indian Reservation, conceptual and numerical models of groundwater flow in the Ogallala and Arikaree aquifers in southwestern South Dakota were developed by the U.S. Geological Survey in cooperation with the Oglala Sioux Tribe. The study area includes most of the Pine Ridge Reservation in Jackson and Shannon Counties and Indian trust lands in Bennett County in southwestern South Dakota.
\nThe High Plains aquifer, which includes the Ogallala and Arikaree aquifers, generally is less developed in South Dakota compared with other areas underlain by this aquifer; therefore, water levels in the High Plains aquifer in South Dakota generally fluctuated by less than 5 feet (ft) from 1980 to 1999. Despite minimal water-level changes in the High Plains aquifer in South Dakota, extensive withdrawals of groundwater for irrigation have caused water-level declines in many areas and increased concerns about the long-term sustainability of the aquifer; therefore, continued or increased withdrawals from the aquifer or prolonged drought may have the potential to affect water levels within the aquifer and discharge to important streams in the area.
\nThe Ogallala and Arikaree aquifers generally consist of poorly consolidated claystones, siltstones, sandstones, and shale deposited in fluvial and lacustrine environments. Saturated thicknesses ranged from 10 to 314 ft for the Ogllala aquifer and from 10 to 862 ft for the Arikaree aquifer. Previous hydraulic conductivity estimates ranged from less than 1 to 180 feet per day (ft/d) for the Ogallala aquifer and from less than 1 to 13 ft/d for the Arikaree aquifer.
\nRecharge to the Ogallala and Arikaree aquifers is from precipitation on the outcrop areas, and discharge occurs through evapotranspiration, discharge to streams, and well withdrawals. Evapotranspiration generally occurs in topographically low areas along streams, and maximum evapotranspiration occurs when the water level is at the land surface.
\nThe generalized groundwater-flow direction is to the northeast with local flow towards streams. Precipitation for water years 1980–2009 ranged from about 11 to 39 inches per year (in/yr) and averaged about 19 in/yr. Estimated mean recharge for water years 1980–2009 was about 17.3 percent of precipitation for the Ogallala aquifer and 7.9 percent of precipitation for the Arikaree aquifer. The estimated mean maximum evapotranspiration for water years 1980–2009 was about 35 in/yr. Estimated mean base flow for gaged streams was about 0.06 cubic foot per second (ft3/s) per square mile of drainage area. Estimated mean total water use for water years 1980–2009 was 5.4 ft3/s from the Ogallala aquifer and 7.1 ft3/s from the Arikaree aquifer.
\nA two-layer numerical groundwater-flow model was constructed using MODFLOW–NWT with a uniformly spaced grid consisting of 166 rows and 288 columns with cells 1,640 ft on a side. The numerical model of the Ogallala and Arikaree aquifers was used to simulate steady-state and transient conditions for water years 1980–2009. Model calibration was accomplished using the Parameter ESTimation (PEST) program that adjusted individual model input parameters and assessed the difference between estimated and model-simulated values of hydraulic head and base flow. Aquifer boundaries were no-flow on the northern and western sides and constant-head on the southern and eastern sides. The mean arithmetic difference was 1.4 ft between the 731 simulated and observed hydraulic heads in the Ogallala aquifer and 9.8 ft between the 2,754 simulated and observed hydraulic heads in the Arikaree aquifer. Simulated mean discharge from the Ogallala and Arikaree aquifers to selected stream reaches was 92.1 ft3/s compared to estimated discharge of 88.7 ft3/s.
\nCalibrated recharge for the transient simulation averaged 3.3 in/yr for the Ogallala aquifer and 1.1 in/yr for the Arikaree aquifer. The mean maximum potential evapotranspiration rate was 35.4 in/yr. Streambed conductance for perennial stream reaches averaged 530 feet squared per day. Horizontal hydraulic conductivity averaged 27 ft/d for the Ogallala aquifer and 1.0 ft/d for the Arikaree aquifer. The vertical hydraulic conductivity averaged 1.4 ft/d for the Ogallala aquifer and 0.004 ft/d for the Arikaree aquifer. Specific yield for the Ogallala aquifer was 0.15 (dimensionless) and averaged 0.02 for the Arikaree aquifer. Specific storage for the Arikaree aquifer was 1.7x10-6 per foot. Simulated steady-state model inflow and outflow was 459 ft3/s. The percentages of inflows were 17 percent from constant-head boundaries, 9 percent from streams, and 74 percent from recharge. Percentages of outflow were 8 percent to constant-head boundaries, 1 percent to wells, 31 percent to streams, and 59 percent to evapotranspiration. Simulated net inflow from the Ogallala aquifer to the Arikaree aquifer ranged from about 22 ft3/s in dry years to about 37 ft3/s in wet years.
\nTwo hypothetical future stress scenarios were simulated using input from the 30-year calibrated simulation of water years 1980–2009. The first hypothetical scenario represented an increase in groundwater withdrawals from 50 hypothetical production wells completed in the Arikaree aquifer. At the end of the 30-year hypothetical increased pumping simulation, water levels declined as much as 66 ft in the Arikaree aquifer, decreased discharge to streams accounted for about 26 percent (2.6 ft3/s) of increased withdrawals, and decreased evapotranspiration accounted for about 53 (5.3 ft3/s) percent of increased withdrawals.
\nThe second hypothetical scenario represented a 30-year period of decreased recharge (drought) by decreasing recharge 0.2 inch (24 ft3/s) for each water year. At the end of the hypothetical drought simulation, water levels declined as much as 10.9 ft in the Arikaree aquifer, decreased discharge to streams accounted for about 23 percent (5.5 ft3/s) of decreased recharge, and decreased evapotranspiration accounted for about 72 percent (17.3 ft3/s) of decreased recharge.
\nThe numerical model is a tool that could be used to better understand the flow system of the Ogallala and Arikaree aquifers, to approximate hydraulic heads in the aquifer, and to estimate discharge to rivers, springs, and seeps in the Pine Ridge Reservation area in Bennett, Jackson, and Shannon Counties. The model also is useful to help assess the response of the aquifer to additional stress, including potential increased well withdrawals and potential drought conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145241","collaboration":"Prepared in cooperation with the Oglala Sioux Tribe","usgsCitation":"Davis, K.W., Putnam, L.D., and LaBelle, A.R., 2015, Conceptual and numerical models of groundwater flow in the Ogallala and Arikaree aquifers, Pine Ridge Indian Reservation area, South Dakota, water years 1980-2009: U.S. Geological Survey Scientific Investigations Report 2014-5241, x, 68 p., https://doi.org/10.3133/sir20145241.","productDescription":"x, 68 p.","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1979-10-01","temporalEnd":"2009-09-30","ipdsId":"IP-045449","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":298106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145241.jpg"},{"id":298103,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5241/pdf/sir2014-5241.pdf","text":"Report","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298101,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5241/"}],"projection":"Universal Transverse Mercator projection, Zone 14","country":"United States","state":"South Dakota","otherGeospatial":"Arikaree Aquifer, Ogallala Aquifer, Pine Ridge Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.98858642578125,\n 42.99862111927107\n ],\n [\n -102.98858642578125,\n 43.7294293330051\n ],\n [\n -101.19781494140625,\n 43.7294293330051\n ],\n [\n -101.19781494140625,\n 42.99862111927107\n ],\n [\n -102.98858642578125,\n 42.99862111927107\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54ec4f2de4b02d776a67da93","contributors":{"authors":[{"text":"Davis, Kyle W. 0000-0002-8723-0110 kyledavis@usgs.gov","orcid":"https://orcid.org/0000-0002-8723-0110","contributorId":3987,"corporation":false,"usgs":true,"family":"Davis","given":"Kyle","email":"kyledavis@usgs.gov","middleInitial":"W.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":541126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Putnam, Larry D. ldputnam@usgs.gov","contributorId":990,"corporation":false,"usgs":true,"family":"Putnam","given":"Larry","email":"ldputnam@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":541124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaBelle, Anneka R.","contributorId":139410,"corporation":false,"usgs":false,"family":"LaBelle","given":"Anneka","email":"","middleInitial":"R.","affiliations":[{"id":12443,"text":"U.S. Geological Survey (retired)","active":true,"usgs":false}],"preferred":false,"id":541125,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155505,"text":"70155505 - 2015 - A comparison of hydrologic models for ecological flows and water availability","interactions":[],"lastModifiedDate":"2015-12-07T10:24:59","indexId":"70155505","displayToPublicDate":"2015-02-23T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of hydrologic models for ecological flows and water availability","docAbstract":"Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine-scale models and two regional-scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/−30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over-predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional-scale models have comparable performance to the more complex, fine-scale models at a monthly time step.
","language":"English","publisher":"John Wiley & Sons","publisherLocation":"Chichester, West Sussex, UK","doi":"10.1002/eco.1602","usgsCitation":"Caldwell, P.V., Kennen, J., Sun, G., Kiang, J.E., Butcher, J.B., Eddy, M.C., Hay, L.E., LaFontaine, J.H., Hain, E.F., Nelson, S.C., and McNulty, S., 2015, A comparison of hydrologic models for ecological flows and water availability: Ecohydrology, v. 8, no. 8, p. 1525-1546, https://doi.org/10.1002/eco.1602.","productDescription":"22 p.","startPage":"1525","endPage":"1546","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062207","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":306514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-23","publicationStatus":"PW","scienceBaseUri":"55c9cb2ee4b08400b1fdb6e1","contributors":{"authors":[{"text":"Caldwell, Peter V","contributorId":145892,"corporation":false,"usgs":false,"family":"Caldwell","given":"Peter","email":"","middleInitial":"V","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":565591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565590,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sun, Ge","contributorId":145893,"corporation":false,"usgs":false,"family":"Sun","given":"Ge","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":565592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":565593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Butcher, John B","contributorId":145894,"corporation":false,"usgs":false,"family":"Butcher","given":"John","email":"","middleInitial":"B","affiliations":[{"id":16286,"text":"Tetra Tech","active":true,"usgs":false}],"preferred":false,"id":565594,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eddy, Michelle C","contributorId":145895,"corporation":false,"usgs":false,"family":"Eddy","given":"Michelle","email":"","middleInitial":"C","affiliations":[{"id":7151,"text":"RTI International","active":true,"usgs":false}],"preferred":false,"id":565595,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":565596,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565597,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hain, Ernie F.","contributorId":141247,"corporation":false,"usgs":false,"family":"Hain","given":"Ernie","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":565598,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nelson, Stacy C","contributorId":145896,"corporation":false,"usgs":false,"family":"Nelson","given":"Stacy","email":"","middleInitial":"C","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":565599,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McNulty, Steve G","contributorId":145897,"corporation":false,"usgs":false,"family":"McNulty","given":"Steve G","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":567588,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70141774,"text":"70141774 - 2015 - Development of 13 microsatellites for Gunnison Sage-grouse (Centrocercus minimus) using next-generation shotgun sequencing and their utility in Greater Sage-grouse (Centrocercus urophasianus)","interactions":[],"lastModifiedDate":"2015-02-25T08:23:41","indexId":"70141774","displayToPublicDate":"2015-02-23T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"title":"Development of 13 microsatellites for Gunnison Sage-grouse (Centrocercus minimus) using next-generation shotgun sequencing and their utility in Greater Sage-grouse (Centrocercus urophasianus)","docAbstract":"Gunnison Sage-grouse are an obligate sagebrush species that has experienced significant population declines and has been proposed for listing under the U.S. Endangered Species Act. In order to examine levels of connectivity among Gunnison Sage-grouse leks, we identified 13 novel microsatellite loci though next-generation shotgun sequencing, and tested them on the closely related Greater Sage-grouse. The number of alleles per locus ranged from 2 to 12. No loci were found to be linked, although 2 loci revealed significant departures from Hardy–Weinberg equilibrium or evidence of null alleles. While these microsatellites were designed for Gunnison Sage-grouse, they also work well for Greater Sage-grouse and could be used for numerous genetic questions including landscape and population genetics.
","language":"English","publisher":"Springer","publisherLocation":"Netherlands","doi":"10.1007/s12686-014-0336-z","usgsCitation":"Fike, J.A., Oyler-McCance, S.J., Zimmerman, S., and Castoe, T.A., 2015, Development of 13 microsatellites for Gunnison Sage-grouse (Centrocercus minimus) using next-generation shotgun sequencing and their utility in Greater Sage-grouse (Centrocercus urophasianus): Conservation Genetics Resources, v. 7, no. 1, p. 211-214, https://doi.org/10.1007/s12686-014-0336-z.","productDescription":"4 p.","startPage":"211","endPage":"214","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059564","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":298092,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-24","publicationStatus":"PW","scienceBaseUri":"54ec4f2ee4b02d776a67da95","contributors":{"authors":[{"text":"Fike, Jennifer A. fikej@usgs.gov","contributorId":4564,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer","email":"fikej@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":541065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":541066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zimmerman, Shawna J","contributorId":139402,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Shawna J","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":541067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Castoe, Todd A.","contributorId":23819,"corporation":false,"usgs":true,"family":"Castoe","given":"Todd","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":541068,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70136504,"text":"ofr20141261 - 2015 - Analysis of historic agricultural irrigation data from the Natural Resources Conservation Service monitoring and evaluation for Grand Valley, Lower Gunnison Basin, and McElmo Creek Basin, western Colorado, 1985 to 2003","interactions":[],"lastModifiedDate":"2015-02-23T09:13:09","indexId":"ofr20141261","displayToPublicDate":"2015-02-23T08:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1261","title":"Analysis of historic agricultural irrigation data from the Natural Resources Conservation Service monitoring and evaluation for Grand Valley, Lower Gunnison Basin, and McElmo Creek Basin, western Colorado, 1985 to 2003","docAbstract":"The Natural Resources Conservation Service Monitoring and Evaluation for three salinity control units in western Colorado—Grand Valley, Lower Gunnison, and McElmo Creek—from 1985 to 2003 was a response to the Colorado River Basin Salinity Control Act, Public Law 93–320, July 24, 1974, and its amendments. The Natural Resources Conservation Service evaluated the effects on seasonal irrigation efficiency and deep percolation of irrigation water of various on-farm irrigation system improvements in the three salinity control units, and reported the results in a series of internal Natural Resources Conservation Service annual reports. Because of the large amount of effort and expense that went into the Natural Resources Conservation Service Monitoring and Evaluation and the importance of the data to help quantify the changes to deep percolation, the Natural Resources Conservation Service has determined that having the evaluation results made public through a characterization and analysis of the results by the U.S. Geological Survey could be of use to a wider audience of water managers and the general public.
\nIn 2011, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation and the Colorado River Basin Salinity Control Forum, began a study to evaluate the Natural Resources Conservation Service evaluation data to (1) document the methods of the evaluation, and (2) analyze and summarize the data collected during the evaluation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141261","collaboration":"Prepared in cooperation with the Bureau of Reclamation and Colorado River Basin Salinity Control Forum","usgsCitation":"Mayo, J.W., 2015, Analysis of historic agricultural irrigation data from the Natural Resources Conservation Service monitoring and evaluation for Grand Valley, Lower Gunnison Basin, and McElmo Creek Basin, western Colorado, 1985 to 2003: U.S. Geological Survey Open-File Report 2014-1261, xii, 176 p., https://doi.org/10.3133/ofr20141261.","productDescription":"xii, 176 p.","numberOfPages":"191","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1985-01-01","temporalEnd":"2003-12-31","ipdsId":"IP-055814","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":298090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141261.jpg"},{"id":298081,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1261/"},{"id":298083,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1261/pdf/ofr2014-1261.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Colorado","otherGeospatial":"Grand Valley, Lower Gunnison Basin, McElmo Creek Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.00634765625,\n 37.09023980307208\n ],\n [\n -109.00634765625,\n 39.32579941789298\n ],\n [\n -107.2979736328125,\n 39.32579941789298\n ],\n [\n -107.2979736328125,\n 37.09023980307208\n ],\n [\n -109.00634765625,\n 37.09023980307208\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54ec4f29e4b02d776a67da91","contributors":{"authors":[{"text":"Mayo, John W. jwmayo@usgs.gov","contributorId":993,"corporation":false,"usgs":true,"family":"Mayo","given":"John","email":"jwmayo@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":541109,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70155981,"text":"70155981 - 2015 - The U.S. Geological Survey’s nonindigenous aquatic species database: over thirty years of tracking introduced aquatic species in the United States (and counting)","interactions":[],"lastModifiedDate":"2019-07-25T15:06:52","indexId":"70155981","displayToPublicDate":"2015-02-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"The U.S. Geological Survey’s nonindigenous aquatic species database: over thirty years of tracking introduced aquatic species in the United States (and counting)","docAbstract":"The U.S. Geological Survey’s Nonindigenous Aquatic Species (NAS) Database has tracked introductions of freshwater aquatic organisms in the United States for the past four decades. A website provides access to occurrence reports, distribution maps, and fact sheets for more than 1,000 species. The site also includes an on-line reporting system and an alert system for new occurrences. We provide an historical overview of the database, a description of its current capabilities and functionality, and a basic characterization of the data contained within the database.
","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2015.6.2.06","usgsCitation":"Fuller, P.L., and Neilson, M., 2015, The U.S. Geological Survey’s nonindigenous aquatic species database: over thirty years of tracking introduced aquatic species in the United States (and counting): Management of Biological Invasions, v. 6, no. 2, p. 159-170, https://doi.org/10.3391/mbi.2015.6.2.06.","productDescription":"12 p.","startPage":"159","endPage":"170","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060621","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472263,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2015.6.2.06","text":"Publisher Index Page"},{"id":306674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cdbfbde4b08400b1fe1441","contributors":{"authors":[{"text":"Fuller, Pamela L. 0000-0002-9389-9144 pfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9389-9144","contributorId":3217,"corporation":false,"usgs":true,"family":"Fuller","given":"Pamela","email":"pfuller@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":567532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neilson, Matthew E. 0000-0002-5139-5677","orcid":"https://orcid.org/0000-0002-5139-5677","contributorId":146352,"corporation":false,"usgs":false,"family":"Neilson","given":"Matthew E.","affiliations":[{"id":16681,"text":"Cherokee Nation Technical Solutions","active":true,"usgs":false}],"preferred":false,"id":567533,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70125445,"text":"ofr20141200 - 2015 - Modeling elk and bison carrying capacity for Great Sand Dunes National Park, Baca National Wildlife Refuge, and The Nature Conservancy's Medano Ranch, Colorado","interactions":[],"lastModifiedDate":"2015-02-20T15:25:16","indexId":"ofr20141200","displayToPublicDate":"2015-02-20T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1200","title":"Modeling elk and bison carrying capacity for Great Sand Dunes National Park, Baca National Wildlife Refuge, and The Nature Conservancy's Medano Ranch, Colorado","docAbstract":"Great Sand Dunes National Park and Preserve and the neighboring Baca National Wildlife Refuge constitute an extraordinary setting that offers a variety of opportunities for outdoor recreation and natural resource preservation in the San Luis Valley of Colorado. Adjacent to these federal lands, the Nature Conservancy (TNC) manages the historic Medano Ranch. The total land area of these three conservation properties is roughly 121,500 hectares (ha). It is a remote and rugged area in which resource managers must balance the protection of natural resources with recreation and neighboring land uses. The management of wild ungulates in this setting presents challenges, as wild ungulates move freely across public and private landscapes.
\nThe San Luis Valley was historically used for irrigated agriculture and ranching. Historically, livestock, including sheep (Ovis aries) and cattle (Bos taurus), were grazed throughout the valley. The former Luis Marie “Baca” Ranch, which makes up the northern part of Great Sand Dunes National Park (hereafter “Park”) and all of the Baca National Wildlife Refuge (hereafter “Refuge”), was actively grazed by cattle until 2004. Bison (Bison bison), elk (Cervus elaphus), mule deer (Odocoileus hemionus), and pronghorn (Antilocapra americana) were native to the area until about the 1840s, when bison, elk, and pronghorn were extirpated.
\nElk and pronghorn likely moved back into the area from surrounding populations to the north and south, and mule deer populations have varied through time. A population of 4,400 elk currently inhabits the area. The current bison population was established in 1986 for meat production. In 1999 TNC purchased the ranch and established a bison conservation herd, and eventually subcontracted management to a private rancher in 2005. A population of bison ranging in size from 1,200–2,000 ranges freely within the 16,100 ha Medano Ranch. Ungulate populations in the valley are regulated by hunting, with the exception of bison, which are rounded up and culled annually to maintain population levels.
\nIn an effort to create and form the basis of a multi-agency ungulate management plan for the region, the Park sought the development of an elk and bison ecological carrying capacity model to provide guidance to resource managers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141200","collaboration":"In cooperation with the National Park Service","usgsCitation":"Wockner, G., Boone, R., Schoenecker, K.A., and Zeigenfuss, L., 2015, Modeling elk and bison carrying capacity for Great Sand Dunes National Park, Baca National Wildlife Refuge, and The Nature Conservancy's Medano Ranch, Colorado: U.S. Geological Survey Open-File Report 2014-1200, iv, 23 p., https://doi.org/10.3133/ofr20141200.","productDescription":"iv, 23 p.","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056689","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":298075,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141200.jpg"},{"id":298073,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1200/"},{"id":298074,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1200/pdf/ofr2014-1200.pdf","text":"Report","size":"7.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Colorado","otherGeospatial":"Baca National Wildlife Refuge, Great Sand Dunes National Park, San Luis Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.15264892578125,\n 37.477037796698056\n ],\n [\n -106.15264892578125,\n 38.52023522875919\n ],\n [\n -105.018310546875,\n 38.52023522875919\n ],\n [\n -105.018310546875,\n 37.477037796698056\n ],\n [\n -106.15264892578125,\n 37.477037796698056\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e85aade4b02d776a67c5b7","contributors":{"authors":[{"text":"Wockner, Gary","contributorId":118967,"corporation":false,"usgs":true,"family":"Wockner","given":"Gary","email":"","affiliations":[],"preferred":false,"id":541072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boone, Randall","contributorId":121404,"corporation":false,"usgs":true,"family":"Boone","given":"Randall","email":"","affiliations":[],"preferred":false,"id":541073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X schoeneckerk@usgs.gov","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":2001,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn","email":"schoeneckerk@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":541070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zeigenfuss, Linda 0000-0002-6700-8563 linda_zeigenfuss@usgs.gov","orcid":"https://orcid.org/0000-0002-6700-8563","contributorId":2079,"corporation":false,"usgs":true,"family":"Zeigenfuss","given":"Linda","email":"linda_zeigenfuss@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":541071,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198398,"text":"70198398 - 2015 - Pre-fieldwork surveys ","interactions":[],"lastModifiedDate":"2018-09-04T14:44:36","indexId":"70198398","displayToPublicDate":"2015-02-20T14:35:29","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"Pre-fieldwork surveys ","docAbstract":"In sea-level studies, initial surveys at the office or library can increase a project’s likelihood of success. Pre-fieldwork surveys should begin with a thorough review of prior research literature that appraises available data, identifies data gaps, and places the project objectives into a broader scientific context. Whereas peer reviewed journal articles may contain a wealth of research findings, often the most useful maps, historical documents, images, and other data critical for sea-level research are discovered by searching government files, libraries, museums, unpublished reports, or, increasingly, online digital data collections.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Handbook of sea-level research","largerWorkSubtype":{"id":13,"text":"Handbook"},"language":"English","publisher":"Wiley","doi":"10.1002/9781118452547","usgsCitation":"Witter, R., 2015, Pre-fieldwork surveys , chap. 3 of Handbook of sea-level research, https://doi.org/10.1002/9781118452547.","productDescription":"20 p.","startPage":"27","numberOfPages":"46","ipdsId":"IP-055158","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":488779,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/output/1659707","text":"External Repository"},{"id":357049,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-20","publicationStatus":"PW","scienceBaseUri":"5b98a8a8e4b0702d0e843106","contributors":{"editors":[{"text":"Shennan, Ian","contributorId":54883,"corporation":false,"usgs":true,"family":"Shennan","given":"Ian","email":"","affiliations":[],"preferred":false,"id":744125,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Long, Antony J.","contributorId":191198,"corporation":false,"usgs":false,"family":"Long","given":"Antony","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":744126,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Horton, Benajamin P.","contributorId":192918,"corporation":false,"usgs":false,"family":"Horton","given":"Benajamin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":744127,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":741348,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70141759,"text":"70141759 - 2015 - Chilled frogs are hot: hibernation and reproduction of the Endangered mountain yellow-legged frog Rana muscosa","interactions":[],"lastModifiedDate":"2015-02-20T13:38:56","indexId":"70141759","displayToPublicDate":"2015-02-20T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Chilled frogs are hot: hibernation and reproduction of the Endangered mountain yellow-legged frog Rana muscosa","docAbstract":"In the face of the sixth great extinction crisis, it is imperative to establish effective breeding protocols for amphibian conservation breeding programs. Captive efforts should not proceed by trial and error, nor should they jump prematurely to assisted reproduction techniques, which can be invasive, difficult, costly, and, at times, counterproductive. Instead, conservation practitioners should first look to nature for guidance, and replicate key conditions found in nature in the captive environment, according to the ecological and behavioral requirements of the species. We tested the effect of a natural hibernation regime on reproductive behaviors and body condition in the Endangered mountain yellow-legged frog Rana muscosa. Hibernation had a clear positive effect on reproductive behavior, manifesting in vocal advertisement signaling, female receptivity, amplexus, and oviposition. These behaviors are critical components of courtship that lead to successful reproduction. Our main finding was that captive R. muscosa require a hibernation period for successful reproduction, as only hibernated females produced eggs and only hibernated males successfully fertilized eggs. Although hibernation also resulted in a reduced body condition, the reduction appeared to be minimal with no associated mortality. The importance of hibernation for reproduction is not surprising, since it is a major component of the conditions that R. muscosa experiences in the wild. Other amphibian conservation breeding programs can also benefit from a scientific approach that tests the effect of natural ecological conditions on reproduction. This will ensure that captive colonies maximize their role in providing genetic reservoirs for assurance and reintroduction efforts.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr00648","usgsCitation":"Santana, F.E., Swaisgood, R.R., Lemm, J.M., Fisher, R.N., and Clark, R.W., 2015, Chilled frogs are hot: hibernation and reproduction of the Endangered mountain yellow-legged frog Rana muscosa: Endangered Species Research, v. 27, no. 1, p. 43-51, https://doi.org/10.3354/esr00648.","productDescription":"9 p.","startPage":"43","endPage":"51","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053809","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472264,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00648","text":"Publisher Index Page"},{"id":298072,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e85aa9e4b02d776a67c5b1","contributors":{"authors":[{"text":"Santana, Frank E.","contributorId":139391,"corporation":false,"usgs":false,"family":"Santana","given":"Frank","email":"","middleInitial":"E.","affiliations":[{"id":12761,"text":"San Diego Zoo Institute for Conservation Resarch and San Diego State University","active":true,"usgs":false}],"preferred":false,"id":541014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swaisgood, Ronald R.","contributorId":69490,"corporation":false,"usgs":false,"family":"Swaisgood","given":"Ronald","email":"","middleInitial":"R.","affiliations":[{"id":12762,"text":"San Diego Zoo Institure for Conservation Research","active":true,"usgs":false}],"preferred":false,"id":541015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lemm, Jeffrey M.","contributorId":139392,"corporation":false,"usgs":false,"family":"Lemm","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[{"id":12762,"text":"San Diego Zoo Institure for Conservation Research","active":true,"usgs":false}],"preferred":false,"id":541016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541013,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Rulon W.","contributorId":139393,"corporation":false,"usgs":false,"family":"Clark","given":"Rulon","email":"","middleInitial":"W.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":541017,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70177028,"text":"70177028 - 2015 - Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches","interactions":[],"lastModifiedDate":"2016-10-19T15:22:25","indexId":"70177028","displayToPublicDate":"2015-02-20T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches","docAbstract":"As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the U.S. Geological Survey (USA), HDR⎪HydroQual, Inc. (USA), and the Centre for Ecology and Hydrology (UK) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME Workshop in Brussels, Belgium (May 2012), is provided herein. Overall, the models were found to be similar in structure (free ion activities computed by WHAM; specific or non-specific binding of metals/cations in or on the organism; specification of metal potency factors and/or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single versus multiple types of binding site on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong inter-relationships among the model parameters (log KM values, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed.","language":"English","publisher":"Society of Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/etc.2820","usgsCitation":"Farley, K.J., Meyer, J., Balistrieri, L.S., DeSchamphelaere, K., Iwasaki, Y., Janssen, C., Kamo, M., Lofts, S., Mebane, C.A., Naito, W., Ryan, A.C., Santore, R.C., and Tipping, E., 2015, Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches: Environmental Toxicology and Chemistry, v. 34, no. 4, p. 741-753, https://doi.org/10.1002/etc.2820.","productDescription":"13 p.","startPage":"741","endPage":"753","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056635","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":472265,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/etc.2820","text":"External Repository"},{"id":329768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-24","publicationStatus":"PW","scienceBaseUri":"58088688e4b0f497e78e24d3","contributors":{"authors":[{"text":"Farley, Kevin J.","contributorId":175407,"corporation":false,"usgs":false,"family":"Farley","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":27565,"text":"Manhattan College","active":true,"usgs":false}],"preferred":false,"id":651038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Joe","contributorId":175408,"corporation":false,"usgs":false,"family":"Meyer","given":"Joe","email":"","affiliations":[{"id":27566,"text":"ARCADIS US","active":true,"usgs":false}],"preferred":false,"id":651039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balistrieri, Laurie S. 0000-0002-6359-3849 balistri@usgs.gov","orcid":"https://orcid.org/0000-0002-6359-3849","contributorId":1406,"corporation":false,"usgs":true,"family":"Balistrieri","given":"Laurie","email":"balistri@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":651037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeSchamphelaere, Karl","contributorId":175409,"corporation":false,"usgs":false,"family":"DeSchamphelaere","given":"Karl","email":"","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":651040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iwasaki, Yuichi","contributorId":175410,"corporation":false,"usgs":false,"family":"Iwasaki","given":"Yuichi","email":"","affiliations":[{"id":27568,"text":"Tokyo Institute of Tecnology","active":true,"usgs":false}],"preferred":false,"id":651041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Janssen, Colin","contributorId":175411,"corporation":false,"usgs":false,"family":"Janssen","given":"Colin","email":"","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":651042,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kamo, Masashi","contributorId":175412,"corporation":false,"usgs":false,"family":"Kamo","given":"Masashi","email":"","affiliations":[],"preferred":false,"id":651043,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lofts, Steve","contributorId":175413,"corporation":false,"usgs":false,"family":"Lofts","given":"Steve","affiliations":[],"preferred":false,"id":651044,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":651045,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Naito, Wataru","contributorId":175563,"corporation":false,"usgs":false,"family":"Naito","given":"Wataru","email":"","affiliations":[],"preferred":false,"id":651433,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ryan, Adam C.","contributorId":175564,"corporation":false,"usgs":false,"family":"Ryan","given":"Adam","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":651434,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Santore, Robert C.","contributorId":53206,"corporation":false,"usgs":true,"family":"Santore","given":"Robert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":651435,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tipping, Edward","contributorId":36405,"corporation":false,"usgs":true,"family":"Tipping","given":"Edward","email":"","affiliations":[],"preferred":false,"id":651436,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70140264,"text":"ofr20151013 - 2015 - Occurrence and distribution of fecal indicator bacteria and gene markers of pathogenic bacteria in Great Lakes tributaries, March-October 2011","interactions":[],"lastModifiedDate":"2018-09-12T17:12:19","indexId":"ofr20151013","displayToPublicDate":"2015-02-20T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1013","title":"Occurrence and distribution of fecal indicator bacteria and gene markers of pathogenic bacteria in Great Lakes tributaries, March-October 2011","docAbstract":"From March through October 2011, the U.S. Geological Survey (USGS), conducted a study to determine the frequency of occurrence of pathogen gene markers and densities of fecal indicator bacteria (FIB) in 22 tributaries to the Great Lakes. This project was funded as part of the Great Lakes Restoration Initiative (GLRI) and included sampling at 22 locations throughout 6 states that border the Great Lakes.
\nA total of 177 environmental samples were collected at USGS streamgaging stations during both normal-flow and high-flow conditions and were analyzed by the Michigan Bacteriological Research Laboratory at the USGS Water Science Center in Lansing, Michigan.
\nWater samples were analyzed for the presence of FIB concentrations (FIB; fecal coliform bacteria, Escherichia coli [E. coli], and enterococci) by using membrane filtration and serial dilution methods. The resulting enrichments from standard culturing of the samples were then analyzed by using polymerase chain reaction (PCR) to determine the occurrence of pathogen gene markers for Shigella species, Campylobacter jejuni and coli, Salmonellaspecies, and pathogenic E. coli, including Shiga toxin-producing E. coli (STEC).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151013","collaboration":"Prepared in cooperation with the Great Lakes Restoration Initiative","usgsCitation":"Brennan, A.K., Johnson, H., Totten, A.R., and Duris, J.W., 2015, Occurrence and distribution of fecal indicator bacteria and gene markers of pathogenic bacteria in Great Lakes tributaries, March-October 2011: U.S. Geological Survey Open-File Report 2015-1013, v, 29 p., https://doi.org/10.3133/ofr20151013.","productDescription":"v, 29 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-03-01","temporalEnd":"2011-10-31","ipdsId":"IP-039000","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":298071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151013.jpg"},{"id":298069,"type":{"id":15,"text":"Index 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on-orbit","interactions":[],"lastModifiedDate":"2017-01-18T10:05:02","indexId":"70141305","displayToPublicDate":"2015-02-20T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Landsat-8 Operational Land Imager (OLI) radiometric performance on-orbit","docAbstract":"Expectations of the Operational Land Imager (OLI) radiometric performance onboard Landsat-8 have been met or exceeded. The calibration activities that occurred prior to launch provided calibration parameters that enabled ground processing to produce imagery that met most requirements when data were transmitted to the ground. Since launch, calibration updates have improved the image quality even more, so that all requirements are met. These updates range from detector gain coefficients to reduce striping and banding to alignment parameters to improve the geometric accuracy. This paper concentrates on the on-orbit radiometric performance of the OLI, excepting the radiometric calibration performance. Topics discussed in this paper include: signal-to-noise ratios that are an order of magnitude higher than previous Landsat missions; radiometric uniformity that shows little residual banding and striping, and continues to improve; a dynamic range that limits saturation to extremely high radiance levels; extremely stable detectors; slight nonlinearity that is corrected in ground processing; detectors that are stable and 100% operable; and few image artifacts.
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However, while arid and semiarid ecosystems commonly experience extremely hot and dry conditions, our understanding of how further temperature increases or altered precipitation will affect dryland plant communities remains poor. To address this question, we assessed plant physiology and growth at a long-term (7-year) climate experiment on the Colorado Plateau, USA, where the community is a mix of shallow-rooted C3 and C4 grasses and deep-rooted C4 shrubs. The experiment maintained elevated-temperature treatments (+2 or +4 °C) in combination with altered summer monsoonal precipitation (+small frequent precipitation events or +large infrequent events). Increased temperature negatively affected photosynthesis and growth of the C3 and C4 grasses, but effects varied in their timing: +4 °C treatments negatively affected the C3 grass early in the growing season of both years, while the negative effects of temperature on the C4 grass were seen in the +2 and +4 °C treatments, but only during the late growing season of the drier year. Increased summer precipitation did not affect photosynthesis or biomass for any species, either in the year the precipitation was applied or the following year. Although previous research suggests dryland plants, and C4 grasses in particular, may respond positively to elevated temperature, our findings from a cool desert show marked declines in C3 and C4 photosynthesis and growth, with temperature effects dependent on the degree of warming and growing-season precipitation.
","language":"English","publisher":"Springer","doi":"10.1007/s00442-015-3235-4","usgsCitation":"Wertin, T., Reed, S.C., and Belnap, J., 2015, C3 and C4 plant responses to increased temperatures and altered monsoonal precipitation in a cool desert on the Colorado Plateau, USA: Oecologia, v. 177, no. 4, p. 997-1013, https://doi.org/10.1007/s00442-015-3235-4.","productDescription":"17 p.","startPage":"997","endPage":"1013","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058148","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":298066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.50048828124999,\n 38.20365531807149\n ],\n [\n -110.50048828124999,\n 39.01491572891582\n ],\n [\n -109.149169921875,\n 39.01491572891582\n ],\n [\n -109.149169921875,\n 38.20365531807149\n ],\n [\n -110.50048828124999,\n 38.20365531807149\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"177","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-13","publicationStatus":"PW","scienceBaseUri":"54e85aa7e4b02d776a67c5af","contributors":{"authors":[{"text":"Wertin, Timothy M.","contributorId":20642,"corporation":false,"usgs":true,"family":"Wertin","given":"Timothy M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":540733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":540732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":540734,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}