Abstract Global spread of the pathogenic amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd) may involve dispersal mechanisms not previously explored. Weather systems accompanied by strong wind and rainfall have been known to assist the dispersal of microbes pathogenic to plants and animals, and we considered a similar phenomenon might occur with Bd. We investigated this concept by sampling rainwater from 20 precipitation events for the presence of Bd in Cusuco National Park, Honduras: a site where high Bd prevalence was previously detected in stream-associated amphibians. Quantitative PCR analysis confirmed the presence of Bd in rainwater in one (5 %) of the weather events sampled, although viability cannot be ascertained from molecular presence alone. The source of the Bd and distance that the contaminated rainwater traveled could not be determined; however, this collection site was located approximately 600 m from the nearest observed perennial river by straight-line aerial distance. Although our results suggest atmospheric Bd dispersal is uncommon and unpredictable, even occasional short-distance aerial transport could considerably expand the taxonomic diversity of amphibians vulnerable to exposure and at risk of decline, including terrestrial and arboreal species that are not associated with permanent water bodies.
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Skerratt, 2015, Presence of amphibian chytrid fungus (Batrachochytrium dendrobatidis) in rainwater suggests aerial dispersal is possible: Aerobiologia, v. 31, no. 3, p. 411-419, https://doi.org/10.1007/s10453-015-9374-6.","productDescription":"9 p.","startPage":"411","endPage":"419","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045408","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":298856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-17","publicationStatus":"PW","scienceBaseUri":"5511395be4b02e76d75b50f1","contributors":{"authors":[{"text":"Kolby, Jonathan E.","contributorId":139790,"corporation":false,"usgs":false,"family":"Kolby","given":"Jonathan","email":"","middleInitial":"E.","affiliations":[{"id":12910,"text":"James Cook University, AUS","active":true,"usgs":false}],"preferred":false,"id":543020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramirez, Sara D.","contributorId":139794,"corporation":false,"usgs":false,"family":"Ramirez","given":"Sara","email":"","middleInitial":"D.","affiliations":[{"id":12911,"text":"Operation Wallacea, UK","active":true,"usgs":false}],"preferred":false,"id":543024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berger, Lee","contributorId":139791,"corporation":false,"usgs":false,"family":"Berger","given":"Lee","email":"","affiliations":[{"id":12910,"text":"James Cook University, AUS","active":true,"usgs":false}],"preferred":false,"id":543021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":543019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jocque, Merlijn","contributorId":139793,"corporation":false,"usgs":false,"family":"Jocque","given":"Merlijn","email":"","affiliations":[{"id":12910,"text":"James Cook University, AUS","active":true,"usgs":false}],"preferred":false,"id":543023,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee F. Skerratt","contributorId":139792,"corporation":false,"usgs":false,"family":"Lee F. Skerratt","affiliations":[{"id":12910,"text":"James Cook University, AUS","active":true,"usgs":false}],"preferred":false,"id":543022,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70142045,"text":"sir20155031 - 2015 - Dry season mean monthly flow and harmonic mean flow regression equations for selected ungaged basins in Arkansas","interactions":[],"lastModifiedDate":"2015-07-15T09:03:43","indexId":"sir20155031","displayToPublicDate":"2015-03-17T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5031","title":"Dry season mean monthly flow and harmonic mean flow regression equations for selected ungaged basins in Arkansas","docAbstract":"The U.S. Geological Survey, in cooperation with the Arkansas Department of Environmental Quality, Southwestern Energy, the Arkansas Natural Resources Commission, and the Arkansas Game and Fish Commission, developed regression equations for estimation of dry season mean monthly flows and harmonic mean flows that are representative of natural streamflow conditions at selected ungaged basins in Arkansas. Observed values of dry season mean monthly flow and harmonic mean flow computed from daily-mean flow data were used with basin characteristics to identify significant explanatory variables for multiple-linear-regression equations to estimate predicted values of dry season mean monthly flow and harmonic mean flow. Five dry season mean monthly flow regression equations and two harmonic mean flow regression equations were developed using dry season mean monthly flows and harmonic mean flows established for 91 and 93 U.S. Geological Survey continuous-record streamflow-gaging stations, respectively. The dry season in Arkansas is defined as the months of July through November for this study. For harmonic mean flow calculations and regression equations, the study area is composed of the Springfield-Salem Plateaus (Arkansas and Missouri), Boston Mountains, Arkansas Valley, Ouachita Mountains (Arkansas and Oklahoma), and West Gulf Coastal Plain (Arkansas) physiographic sections. All continuous-record streamflow-gaging stations used to compute dry season mean monthly flows were located within Arkansas.
\nEquations for two regions were found to be statistically significant for developing regression equations for estimating harmonic mean flows at ungaged basins; thus, equations are applicable only to streams in those respective regions in Arkansas. Regression equations for dry season mean monthly flows are applicable only to streams located throughout Arkansas. All regression equations are applicable only to unaltered streams where flows were not significantly affected by regulation, diversion, or urbanization. The median number of years used for dry season mean monthly flow calculation was 43, and the median number of years used for harmonic mean flow calculations was 34 for region 1 and 43 for region 2.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155031","collaboration":"Prepared in cooperation with the Arkansas Department of Environmental Quality","usgsCitation":"Breaker, B.K., 2015, Dry season mean monthly flow and harmonic mean flow regression equations for selected ungaged basins in Arkansas (Version 1: Originally posted March 17, 2015; Version 1.1: June 13, 2015): U.S. Geological Survey Scientific Investigations Report 2015-5031, iv, 24 p., https://doi.org/10.3133/sir20155031.","productDescription":"iv, 24 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062868","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":305737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":298612,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5031/"},{"id":298613,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5031/pdf/sir2015-5031.pdf","text":"Report","size":"2.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"scale":"100000","projection":"USA Contiguous Albers Equal Area Conic USGS version","datum":"North American Datum of 1983","country":"United States","state":"Arkansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.625244140625,\n 36.500805317604794\n ],\n [\n -90.17578124999999,\n 36.5184659896759\n ],\n [\n -90.010986328125,\n 36.359374956015856\n ],\n [\n -90.06591796875,\n 36.1822249804225\n ],\n [\n -90.28564453124999,\n 36.05798104702501\n ],\n [\n -89.637451171875,\n 36.03133177633187\n ],\n [\n -89.615478515625,\n 35.8356283888737\n ],\n [\n -91.07666015625,\n 32.99023555965106\n ],\n [\n -94.053955078125,\n 33.0178760185549\n ],\n [\n -94.06494140625,\n 33.486435450999885\n ],\n [\n -94.482421875,\n 33.55055114384406\n ],\n [\n -94.449462890625,\n 35.44277092585766\n ],\n [\n -94.625244140625,\n 36.500805317604794\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1: Originally posted March 17, 2015; Version 1.1: June 13, 2015","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5509421ee4b02e76d757d911","contributors":{"authors":[{"text":"Breaker, Brian K. 0000-0002-1985-4992 bbreaker@usgs.gov","orcid":"https://orcid.org/0000-0002-1985-4992","contributorId":4331,"corporation":false,"usgs":true,"family":"Breaker","given":"Brian","email":"bbreaker@usgs.gov","middleInitial":"K.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542486,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70142977,"text":"sir20155009 - 2015 - An assessment of two methods for identifying undocumented levees using remotely sensed data","interactions":[],"lastModifiedDate":"2015-03-17T10:32:39","indexId":"sir20155009","displayToPublicDate":"2015-03-17T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5009","title":"An assessment of two methods for identifying undocumented levees using remotely sensed data","docAbstract":"Many undocumented and commonly unmaintained levees exist in the landscape complicating flood forecasting, risk management, and emergency response. This report describes a pilot study completed by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers to assess two methods to identify undocumented levees by using remotely sensed, high-resolution topographic data. For the first method, the U.S. Army Corps of Engineers examined hillshades computed from a digital elevation model that was derived from light detection and ranging (lidar) to visually identify potential levees and then used detailed site visits to assess the validity of the identifications. For the second method, the U.S. Geological Survey applied a wavelet transform to a lidar-derived digital elevation model to identify potential levees. The hillshade method was applied to Delano, Minnesota, and the wavelet-transform method was applied to Delano and Springfield, Minnesota. Both methods were successful in identifying levees but also identified other features that required interpretation to differentiate from levees such as constructed barriers, high banks, and bluffs. Both methods are complementary to each other, and a potential conjunctive method for testing in the future includes (1) use of the wavelet-transform method to rapidly identify slope-break features in high-resolution topographic data, (2) further examination of topographic data using hillshades and aerial photographs to classify features and map potential levees, and (3) a verification check of each identified potential levee with local officials and field visits.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155009","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Czuba, C.R., Williams, B.K., Westman, J., and LeClaire, K., 2015, An assessment of two methods for identifying undocumented levees using remotely sensed data: U.S. Geological Survey Scientific Investigations Report 2015-5009, vii, 19 p., https://doi.org/10.3133/sir20155009.","productDescription":"vii, 19 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046266","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":298608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155009.jpg"},{"id":298556,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5009/"},{"id":298607,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5009/pdf/sir2015-5009.pdf","size":"6.04 MB","linkFileType":{"id":1,"text":"pdf"}}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Minnesota","city":"Delano, Springfield","otherGeospatial":"Cottonwood River, South Fork Crow River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.83766174316406,\n 45.00437940337335\n ],\n [\n -93.83766174316406,\n 45.06782265048428\n ],\n [\n -93.75646591186523,\n 45.06782265048428\n ],\n [\n -93.75646591186523,\n 45.00437940337335\n ],\n [\n -93.83766174316406,\n 45.00437940337335\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.01251220703125,\n 44.2075577272807\n ],\n [\n -95.01251220703125,\n 44.25460557622782\n ],\n [\n -94.94685173034668,\n 44.25460557622782\n ],\n [\n -94.94685173034668,\n 44.2075577272807\n ],\n [\n -95.01251220703125,\n 44.2075577272807\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55094218e4b02e76d757d90b","contributors":{"authors":[{"text":"Czuba, Christiana R. cczuba@usgs.gov","contributorId":4555,"corporation":false,"usgs":true,"family":"Czuba","given":"Christiana","email":"cczuba@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":542370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westman, Jack","contributorId":139665,"corporation":false,"usgs":false,"family":"Westman","given":"Jack","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":542372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeClaire, Keith","contributorId":139664,"corporation":false,"usgs":false,"family":"LeClaire","given":"Keith","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":542371,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70141914,"text":"ofr20151035 - 2015 - Monitoring avian productivity and survivorship (MAPS) 5-year summary, Naval Outlying Landing Field, Imperial Beach, southwestern San Diego County, California, 2009-13","interactions":[],"lastModifiedDate":"2015-03-17T09:41:05","indexId":"ofr20151035","displayToPublicDate":"2015-03-17T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1035","title":"Monitoring avian productivity and survivorship (MAPS) 5-year summary, Naval Outlying Landing Field, Imperial Beach, southwestern San Diego County, California, 2009-13","docAbstract":"During 2009–13, a Monitoring Avian Productivity and Survivorship (MAPS) banding station was operated at the Naval Outlying Landing Field (NOLF), Imperial Beach, in southwestern San Diego County, California. The station was established as part of a long-term monitoring program of Neotropical migratory bird populations on NOLF and helps Naval Base Coronado (NOLF is a component) meet the goals and objectives of Department of Defense Partners in Flight program and the Birds and Migratory Birds Management Strategies of the Naval Base Coronado Integrated Natural Resources Management Plan. During 2009–13, captures averaged 644 ±155 per year. Fifty-seven species were captured, of which 44 are Neotropical migratory species and 33 breed at the MAPS station. Twenty-two sensitive species were detected, including Least Bell’s Vireo (Vireo bellii pusillus), Willow Flycatcher (Empidonax traillii), Yellow-breasted Chat (Icteria virens) and Yellow Warbler (Setophaga petechia). Local population trends varied among species and years, as did annual productivity (number of young per adult). We found no significant relationship between productivity and the observed population size in the subsequent year for any species, nor did we find an association between productivity and precipitation for the current bio-year. Similarly, survivorship varied across species and years, and there was no obvious relationship between adult survivorship and observed population size for any species except Wrentit (Chamaea fasciata), for which the relationship was positive. Adult survivorship was unrelated to precipitation at the MAPS station. Additional years of data will be required to generate sample sizes adequate for more rigorous analyses of survivorship and productivity as predictors of population growth.
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The role of habitat contamination in the recent decline of the species has rarely been studied and was the main objective of this effort. A wide range of contaminants (115 analytes) was measured in sediments and tissues at 27 sites across a large geographic area of diverse land use. This is the largest dataset of contaminants in habitats and tissues of Pacific lamprey in North America and the first study to compare contaminant bioburden during the larval life stage and the anadromous, adult portion of the life cycle. Bioaccumulation of pesticides, flame retardants, and mercury was observed at many sites. Based on available data, contaminants are accumulating in larval Pacific lamprey at levels that are likely detrimental to organism health and may be contributing to the decline of the species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2015.03.003","usgsCitation":"Nilsen, E.B., Hapke, W., McIlraith, B., and Markovchick, D.J., 2015, Reconnaissance of contaminants in larval Pacific lamprey (Entosphenus tridentatus) tissues and habitats in the Columbia River Basin, Oregon and Washington, USA: Environmental Pollution, v. 201, p. 121-130, https://doi.org/10.1016/j.envpol.2015.03.003.","productDescription":"10 p.","startPage":"121","endPage":"130","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056929","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":299021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"projection":"Lambert Conformal Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Oregon, Washington","otherGeospatial":"Columbia River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.442138671875,\n 43.51668853502909\n ],\n [\n -124.442138671875,\n 47.73932336136857\n ],\n [\n -116.45507812500001,\n 47.73932336136857\n ],\n [\n -116.45507812500001,\n 43.51668853502909\n ],\n [\n -124.442138671875,\n 43.51668853502909\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"201","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55167f36e4b0323842781b10","contributors":{"authors":[{"text":"Nilsen, Elena B. 0000-0002-0104-6321 enilsen@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-6321","contributorId":923,"corporation":false,"usgs":true,"family":"Nilsen","given":"Elena","email":"enilsen@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hapke, Whitney B. whapke@usgs.gov","contributorId":139936,"corporation":false,"usgs":true,"family":"Hapke","given":"Whitney B.","email":"whapke@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":543500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McIlraith, Brian","contributorId":139919,"corporation":false,"usgs":false,"family":"McIlraith","given":"Brian","affiliations":[{"id":13314,"text":"Columbia River Inter-Tribal Fish Commission","active":true,"usgs":false}],"preferred":false,"id":543452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markovchick, Dennis J. markovch@usgs.gov","contributorId":5960,"corporation":false,"usgs":true,"family":"Markovchick","given":"Dennis","email":"markovch@usgs.gov","middleInitial":"J.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":543453,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159279,"text":"70159279 - 2015 - Priority pollutants and associated constituents in untreated and treated discharges from coal mining or processing facilities in Pennsylvania, USA","interactions":[],"lastModifiedDate":"2015-11-16T13:28:34","indexId":"70159279","displayToPublicDate":"2015-03-17T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Priority pollutants and associated constituents in untreated and treated discharges from coal mining or processing facilities in Pennsylvania, USA","docAbstract":"Clean sampling and analysis procedures were used to quantify more than 70 inorganic constituents, including 35 potentially toxic or hazardous constituents, organic carbon, and other characteristics of untreated (influent) and treated (effluent) coal-mine discharges (CMD) at 38 permitted coal-mining or coal-processing facilities in the bituminous coalfield and 4 facilities in the anthracite coalfield of Pennsylvania. Of the 42 facilities sampled during 2011, 26 were surface mines, 11 were underground mines, and 5 were coal refuse disposal operations. Treatment of CMD with caustic soda (NaOH), lime (CaO or Ca(OH)2), flocculent, or limestone was ongoing at 21%, 40%, 6%, and 4% of the facilities, respectively; no chemicals were added at the remaining facilities. All facilities with CMD treatment incorporated structures for active or passive aeration and settling of metal-rich precipitate.
\nThe untreated influent samples had wide ranges of pH (2.8–7.6), hot acidity (−600 to 8000 mg/L as CaCO3), specific conductance (SC; 253–13,000 μS/cm), total dissolved solids (TDS; 168–18,100 mg/L), and associated dissolved (<0.45-μm pore-size filter) constituents, including SO4 (14.7–10,700 mg/L), Fe (<0.01 to 4100 mg/L), Mn (0.02–136 mg/L), Al (<0.01 to 128 mg/L), and Zn (<0.003 to 18.8 mg/L). Concentrations of Ag (<1 μg/L), Hg (<1 μg/L), Sn (<0.5 μg/L), and CN (<0.01 mg/L) were below detection limits. Only one influent sample met permitted mine effluent (PME) limits plus dissolved-constituent criteria maximum concentration (CMC) thresholds for the protection of freshwater aquatic organisms.
\nThe pH of the treated effluent samples ranged from 5.5 to 11.9 and was greater than or equal to the pH of the corresponding influent at all sites. All the effluent samples met CMC levels for dissolved concentrations of Ag, As, Ba, Cd, Cl, Cr, Pb, Ni, Sb, Se, Tl, V, NH3, NO2, NO3, and CN; however, nine violated one or more of the PME limits for pH (<6,n = 1), net acidity (>0, n = 3), Fe (>7 mg/L, n = 1), or Mn (>5 mg/L, n = 8), plus one or more exceeded CMC levels for Al (>0.75 mg/L, n = 2), Co (>95 μg/L, n = 5), Zn (>307 μg/L,n = 1), Cu (>7.4 μg/L, n = 1), or Se (>12.8 μg/L, n = 3). Although CMC exceedances for Co and Zn were attributed to samples also violating the PME limit for pH or Mn, the samples that exceeded the CMC for Al, Cu, or Se met applicable PME limits for pH, Fe, and Mn. Furthermore, many of the pH-compliant effluents did not meet reference criteria for SO4 and related measures of ionic strength, including TDS, SC, and osmotic pressure.
\nThe Wilcoxon matched-pair signed-ranks statistic was used to test if the overall difference between the effluent and influent pairs was equal to zero. Constituents that statistically were the same for effluent and influent (p > 0.05) included flow rate, SC, osmotic pressure, hardness, alkalinity, total organic carbon (TOC), K, Cl, NO3, PO4, Sb, Sr, Br, Se, Mo, and V. Although temperature, dissolved oxygen, pH, Ca, and Na were greater in the effluent than the influent, most constituents decreased as a result of treatment, including TDS, acidity, SO4, Al, Fe, Mn, Mg, As, Ba, Be, Cd, Cr, Co, Cu, F, Pb, Ni, NH3, Tl, Ti, U, Zn, Zr, total phenols, total inorganic carbon (TIC), biological oxygen demand (BOD), and chemical oxygen demand (COD). Nevertheless, some constituents that decreased, such as SO4, still did not meet reference criteria.
\nFindings from this study suggest that typical chemical or aerobic treatment of CMD to pH > 6 with removal of Fe to <7 mg/L and Mn to <5 mg/L may provide a reasonable measure of protection for aquatic life from priority pollutant metals and other toxic or hazardous constituents in effluent but may not be effective for achieving permissible or background levels for TDS, SC, osmotic pressure, or concentrations of SO4 and some other pollutants, including Se, Br, and Cl, if present.
","language":"English","publisher":"Pergamon","publisherLocation":"Oxford, England; New York, NY","doi":"10.1016/j.apgeochem.2015.03.001","collaboration":"Pennsylvania Department of Environmental Protection","usgsCitation":"Cravotta, I., and Brady, K.B., 2015, Priority pollutants and associated constituents in untreated and treated discharges from coal mining or processing facilities in Pennsylvania, USA: Applied Geochemistry, v. 62, p. 108-130, https://doi.org/10.1016/j.apgeochem.2015.03.001.","productDescription":"23 p.","startPage":"108","endPage":"130","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043932","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":311378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Bituminous and Anthracite Coalfields","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.452880859375,\n 41.51680395810115\n ],\n [\n -77.969970703125,\n 41.48389104267175\n ],\n [\n -78.2666015625,\n 40.79717741518766\n ],\n [\n -78.77197265625,\n 40.069664523297774\n ],\n [\n -79.07958984375,\n 39.740986355883564\n ],\n [\n -80.5078125,\n 39.74943369178247\n ],\n [\n -80.5517578125,\n 41.50034959128928\n ],\n [\n -80.452880859375,\n 41.51680395810115\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.662353515625,\n 41.590796851056005\n ],\n [\n -77.640380859375,\n 41.15384235711447\n ],\n [\n -76.88232421875,\n 41.21172151054787\n ],\n [\n -77.025146484375,\n 41.64007838467894\n ],\n [\n -77.618408203125,\n 41.63186741069748\n ],\n [\n -77.662353515625,\n 41.590796851056005\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.57470703125,\n 40.805493843894155\n ],\n [\n -76.585693359375,\n 40.455307212131494\n ],\n [\n -75.904541015625,\n 40.48038142908172\n ],\n [\n -75.9814453125,\n 40.9218144123785\n ],\n [\n -76.56372070312499,\n 40.9218144123785\n ],\n [\n -76.57470703125,\n 40.805493843894155\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564b0c57e4b0ebfbef0d317b","contributors":{"authors":[{"text":"Cravotta, III cravotta@usgs.gov","contributorId":149319,"corporation":false,"usgs":true,"family":"Cravotta","given":"III","email":"cravotta@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":577955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brady, Keith B.C.","contributorId":149321,"corporation":false,"usgs":false,"family":"Brady","given":"Keith","email":"","middleInitial":"B.C.","affiliations":[{"id":17703,"text":"Pennsylvania Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":577957,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155816,"text":"70155816 - 2015 - Chromosomal damage and EROD induction in tree swallows (Tachycineta bicolor) along the Upper Mississippi River, Minnesota, USA","interactions":[],"lastModifiedDate":"2022-11-15T15:53:44.996779","indexId":"70155816","displayToPublicDate":"2015-03-17T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Chromosomal damage and EROD induction in tree swallows (Tachycineta bicolor) along the Upper Mississippi River, Minnesota, USA","title":"Chromosomal damage and EROD induction in tree swallows (Tachycineta bicolor) along the Upper Mississippi River, Minnesota, USA","docAbstract":"The health of tree swallows, Tachycineta bicolor, on the Upper Mississippi River (UMR) was assessed in 2010 and 2011 using biomarkers at six sites downriver of Minneapolis/St. Paul, MN metropolitan area, a tributary into the UMR, and a nearby lake. Chromosomal damage was evaluated in nestling blood by measuring the coefficient of variation of DNA content (DNA CV) using flow cytometry. Cytochrome P450 1A activity in nestling liver was measured using the ethoxyresorufin-O-dealkylase (EROD) assay, and oxidative stress was estimated in nestling livers via determination of thiobarbituric acid reacting substances (TBARS), reduced glutathione (GSH), oxidized glutathione (GSSG), the ratio GSSG/GSH, total sulfhydryl, and protein bound sulfhydryl (PBSH). A multilevel regression model (DNA CV) and simple regressions (EROD and oxidative stress) were used to evaluate biomarker responses for each location. Chromosomal damage was significantly elevated at two sites on the UMR (Pigs Eye and Pool 2) relative to the Green Mountain Lake reference site, while the induction of EROD activity was only observed at Pigs Eye. No measures of oxidative stress differed among sites. Multivariate analysis confirmed an increased DNA CV at Pigs Eye and Pool 2, and elevated EROD activity at Pigs Eye. These results suggest that the health of tree swallows has been altered at the DNA level at Pigs Eye and Pool 2 sites, and at the physiological level at Pigs Eye site only.
Halite and the sodium bicarbonate mineral nahcolite were deposited in Eocene-age saline Lake Uinta in the Piceance Basin, northwestern Colorado. Variations in the areal extent of saline mineral deposition through time were studied using descriptions of core and outcrop. Saline minerals have been extensively leached by groundwater, and the original extent of saline deposition was determined from the distribution of empty vugs and collapse breccias. Because vugs and breccias strongly influence groundwater movement, determining where leaching has occurred is an important consideration for in-situ oil shale extraction methods currently being developed.
\nLake Uinta formed when two much smaller freshwater lakes, one in the Uinta Basin and the other in the Piceance Basin, expanded and coalesced across the Douglas Creek arch. Early Lake Uinta inherited much of the topography in the freshwater lake and surrounding alluvial plains that preceded it, and the deep central lake area of Lake Uinta developed largely over the offshore area of the freshwater lake. A prolonged period of infilling followed the formation of Lake Uinta, creating broad lake-margin shelves prior to the onset of saline mineral deposition. These shelves almost certainly played a critical role in the evolution of the brine layer that accumulated in the deep central lake area. Broad marginal shelves formed as well around the Uinta Basin part of Lake Uinta. Brines that formed on those shelves also probably migrated to the deep central lake area in the Piceance Basin, as no saline minerals were deposited in the Uinta Basin until late in the history of Lake Uinta.
\nOil shale in the deep central lake consists of interbedded laminate oil shale beds that originated within the deep lake area, and blebby and streaked oil shale beds that were transported into the deep lake area by sediment gravity flows. Blebby and streaked oil shale beds contain carbonate clasts and siliciclastic clasts similar to lithologies found on the marginal shelves. It is possible that these clasts and the highly saline brines that evolved on the marginal shelves were incorporated into the same gravity flows.
\nSaline mineral deposition is informally subdivided into early, middle, and late phases. During the early phase, nahcolite and rich oil shale were deposited in the deep central lake area, and carbonate-rich sandstone, siltstone, and mudstone and ostracodal, oolitic, algal limestone were deposited on the marginal shelves. During the middle saline mineral phase, oil shale deposition gradually expanded across the marginal shelves, and by the end of that phase, oil shale deposition covered almost all of the former shelf areas. An increasing flow of water from Lake Gosiute to the north, as it was gradually filled in by volcaniclastics, may have caused this expansion. Saline mineral deposition also expanded during the middle saline mineral phase, reaching to near the former shelf break by the end of that phase. This suggests that the former shelf break remained a topographic feature that confined the deep saline brine layer throughout the middle phase.
\nBy the beginning of the late saline mineral phase, Lake Gosiute had been completely filled in and volcaniclastic debris reached the northern shore of Lake Uinta. This initiated a north-to-south infilling of the Piceance Basin part of Lake Uinta that progressively pushed the saline mineral area southward and ultimately onto the former marginal shelf areas in the southern part of the basin. A saline mineral area formed for the first time in the eastern part of the Uinta Basin during this infilling and, for a time, saline minerals were deposited in both basins. By the end of the late saline phase, the Piceance Basin part of Lake Uinta was filled in and saline mineral deposition shifted entirely into the Uinta Basin.
\nLeaching of saline minerals began sometime after the Green River Formation was lithified enough to allow collapse breccias to form. Leaching is ongoing today, indicated by the discharge of highly saline water from a series of springs in the northern part of the basin. Groundwater invasion and saline mineral dissolution is commonly incomplete in areas that lack fractures, leaving behind pockets of unleached saline minerals in otherwise leached intervals. Today, the base of the leached zone slopes toward the north and toward the area where the brines are being discharged.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135176","usgsCitation":"Johnson, R.C., and Brownfield, M.E., 2015, Development, evolution, and destruction of the saline mineral area of Eocene Lake Uinta, Piceance Basin, western Colorado: U.S. Geological Survey Scientific Investigations Report 2013-5176, Report: vii, 76 p.; 2 Plates: 62.38 x 42.40 inches and 95.69 x 59.99 inches, https://doi.org/10.3133/sir20135176.","productDescription":"Report: vii, 76 p.; 2 Plates: 62.38 x 42.40 inches and 95.69 x 59.99 inches","numberOfPages":"87","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044487","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":298576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135176.jpg"},{"id":298573,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5176/pdf/sir2013-5176.pdf","text":"Report","size":"32.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2013-5176 Report"},{"id":298572,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5176/"},{"id":298574,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5176/downloads/plate_01.pdf","text":"Plate 1","size":"53.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2013-5176 Plate 1"},{"id":298575,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5176/downloads/plate_02.pdf","text":"Plate 2","size":"4.70 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2013-5176 Plate 2"}],"country":"United States","state":"Colorado, Utah, Wyoming","otherGeospatial":"Eocene Lake Uinta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.56640625,\n 43.43696596521823\n ],\n [\n -111.46728515624999,\n 40.51379915504413\n ],\n [\n -111.51123046875,\n 38.151837403006766\n ],\n [\n -106.36962890624999,\n 38.16911413556086\n ],\n [\n -106.36962890624999,\n 42.45588764197166\n ],\n [\n -110.56640625,\n 43.43696596521823\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5507f09de4b02e76d757c124","contributors":{"authors":[{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":518631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":518630,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70140158,"text":"ofr20151016 - 2015 - Bibliography for acid-rock drainage and selected acid-mine drainage issues related to acid-rock drainage from transportation activities","interactions":[],"lastModifiedDate":"2015-03-16T15:22:13","indexId":"ofr20151016","displayToPublicDate":"2015-03-16T15:15:00","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":"2015-1016","title":"Bibliography for acid-rock drainage and selected acid-mine drainage issues related to acid-rock drainage from transportation activities","docAbstract":"Acid-rock drainage occurs through the interaction of rainfall on pyrite-bearing formations. When pyrite (FeS2) is exposed to oxygen and water in mine workings or roadcuts, the mineral decomposes and sulfur may react to form sulfuric acid, which often results in environmental problems and potential damage to the transportation infrastructure. The accelerated oxidation of pyrite and other sulfidic minerals generates low pH water with potentially high concentrations of trace metals. Much attention has been given to contamination arising from acid mine drainage, but studies related to acid-rock drainage from road construction are relatively limited. The U.S. Geological Survey, in cooperation with the Tennessee Department of Transportation, is conducting an investigation to evaluate the occurrence and processes controlling acid-rock drainage and contaminant transport from roadcuts in Tennessee. The basic components of acid-rock drainage resulting from transportation activities are described and a bibliography, organized by relevant categories (remediation, geochemical, microbial, biological impact, and secondary mineralization) is presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151016","collaboration":"Prepared in cooperation with the Tennessee Department of Transportation","usgsCitation":"Bradley, M., and Worland, S.C., 2015, Bibliography for acid-rock drainage and selected acid-mine drainage issues related to acid-rock drainage from transportation activities: U.S. Geological Survey Open-File Report 2015-1016, iii, 16 p., https://doi.org/10.3133/ofr20151016.","productDescription":"iii, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-058759","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":298585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151016.jpg"},{"id":298583,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1016/"},{"id":298584,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1016/pdf/ofr2015-1016.pdf","text":"Report","size":"2.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Tennessee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.05541992187499,\n 36.66841891894786\n ],\n [\n -88.05541992187499,\n 36.491973470593685\n ],\n [\n -88.35205078124999,\n 36.491973470593685\n ],\n [\n -88.428955078125,\n 34.96699890670367\n ],\n [\n -83.73779296875,\n 35.0120020431607\n ],\n [\n -81.309814453125,\n 36.20882309283712\n ],\n [\n -81.2548828125,\n 36.5978891330702\n ],\n [\n -88.05541992187499,\n 36.66841891894786\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5507f098e4b02e76d757c122","contributors":{"authors":[{"text":"Bradley, Mike 0000-0002-2979-265X mbradley@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-265X","contributorId":582,"corporation":false,"usgs":true,"family":"Bradley","given":"Mike","email":"mbradley@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539836,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70142164,"text":"ofr20141224 - 2015 - Sea-floor morphology and sedimentary environments in western Block Island Sound, offshore of Fishers Island, New York","interactions":[],"lastModifiedDate":"2015-03-18T08:42:24","indexId":"ofr20141224","displayToPublicDate":"2015-03-16T13:30:00","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":"2014-1224","title":"Sea-floor morphology and sedimentary environments in western Block Island Sound, offshore of Fishers Island, New York","docAbstract":"Multibeam-bathymetric and sidescan-sonar data, collected by the National Oceanic and Atmospheric Administration in a 114-square-kilometer area of Block Island Sound, southeast of Fishers Island, New York, are combined with sediment samples and bottom photography collected by the U.S. Geological Survey from 36 stations in this area in order to interpret sea-floor features and sedimentary environments. These interpretations and datasets provide base maps for studies on benthic ecology and resource management. The geologic features and sedimentary environments on the sea floor are products of the area’s glacial history and modern processes. These features include bedrock, drumlins, boulders, cobbles, large current-scoured bathymetric depressions, obstacle marks, and glaciolacustrine sediments found in high-energy sedimentary environments of erosion or nondeposition; and sand waves and megaripples in sedimentary environments characterized by coarse-grained bedload transport. Trawl marks are preserved in lower energy environments of sorting and reworking. This report releases the multibeam-bathymetric, sidescan-sonar, sediment, and photographic data and interpretations of the features and sedimentary environments in Block Island Sound, offshore Fishers Island.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141224","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","usgsCitation":"McMullen, K.Y., Poppe, L.J., Danforth, W.W., Blackwood, D.S., Winner, W.G., and Parker, C.E., 2015, Sea-floor morphology and sedimentary environments in western Block Island Sound, offshore of Fishers Island, New York: U.S. Geological Survey Open-File Report 2014-1224, HTML Document; DVD-ROM, https://doi.org/10.3133/ofr20141224.","productDescription":"HTML Document; DVD-ROM","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060422","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":298568,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1224/"},{"id":298569,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1224/ofr2014-1224-title_page.html","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":298570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141224.jpg"}],"datum":"World Geodetic System 1984","country":"United States","state":"New York","otherGeospatial":"Block Island Sound, Fishers Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.0047378540039,\n 41.193381423508484\n ],\n [\n -72.00576782226562,\n 41.25458109268851\n ],\n [\n -71.97452545166016,\n 41.27393614529453\n ],\n [\n -71.92955017089844,\n 41.287094304074884\n ],\n [\n -71.85745239257812,\n 41.28761025624326\n ],\n [\n -71.85745239257812,\n 41.194156460760546\n ],\n [\n -72.0047378540039,\n 41.193381423508484\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5507f09fe4b02e76d757c126","contributors":{"authors":[{"text":"McMullen, Katherine Y. kmcmullen@usgs.gov","contributorId":2148,"corporation":false,"usgs":true,"family":"McMullen","given":"Katherine","email":"kmcmullen@usgs.gov","middleInitial":"Y.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":541646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poppe, Lawrence J. lpoppe@usgs.gov","contributorId":139521,"corporation":false,"usgs":true,"family":"Poppe","given":"Lawrence","email":"lpoppe@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":541647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danforth, William W. 0000-0002-6382-9487 bdanforth@usgs.gov","orcid":"https://orcid.org/0000-0002-6382-9487","contributorId":3292,"corporation":false,"usgs":true,"family":"Danforth","given":"William","email":"bdanforth@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":541648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blackwood, Dann S. dblackwood@usgs.gov","contributorId":2457,"corporation":false,"usgs":true,"family":"Blackwood","given":"Dann","email":"dblackwood@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":541649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winner, William G.","contributorId":139522,"corporation":false,"usgs":false,"family":"Winner","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":541650,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parker, Castle E.","contributorId":28684,"corporation":false,"usgs":false,"family":"Parker","given":"Castle","email":"","middleInitial":"E.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":541651,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70136356,"text":"ofr20141259 - 2015 - The distribution of submersed aquatic vegetation and water lettuce in the fresh and oligohaline tidal Potomac River, 2007","interactions":[],"lastModifiedDate":"2015-03-16T08:44:15","indexId":"ofr20141259","displayToPublicDate":"2015-03-16T08:15:00","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":"2014-1259","title":"The distribution of submersed aquatic vegetation and water lettuce in the fresh and oligohaline tidal Potomac River, 2007","docAbstract":"Surveys documenting the composition of species of submersed aquatic vegetation (SAV) have been conducted in the Potomac River for decades. These surveys can help managers assess the proportion of native and exotic plants in the river or can be used to determine relationships between native and exotic plants, environmental conditions, and wildlife. SAV coverage increased from 2005 to 2007 throughout the fresh and oligohaline study area. The 2007 survey documented here determined that eleven species of SAV were present. The abundance of the exotic species Hydrilla verticillata (hydrilla) was relatively low, and species diversity was relatively high compared to previous years. The survey also revealed a new population of the invasive, floating aquatic plant Pistia stratiotes (water lettuce). In 2007, water lettuce, the latest exotic aquatic plant to be found in the fresh to oligohaline portion of the Potomac River, was most abundant in Mattawoman Creek, Charles County, Maryland. However, it was not observed in the fresh to oligohaline portion of the Potomac River in the summer of 2008. An understanding of the distribution of SAV species and factors governing the abundance of native and invasive aquatic species is enhanced by long-term surveys.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141259","usgsCitation":"Campbell, S.H., Rybicki, N.B., and Schenk, E.R., 2015, The distribution of submersed aquatic vegetation and water lettuce in the fresh and oligohaline tidal Potomac River, 2007: U.S. Geological Survey Open-File Report 2014-1259, vi, 33 p., https://doi.org/10.3133/ofr20141259.","productDescription":"vi, 33 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-011359","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":298553,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141259.jpg"},{"id":298551,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1259/"},{"id":298552,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1259/pdf/ofr2014-1259.pdf","text":"Report","size":"3.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Potomac River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.00523376464844,\n 38.74819282375652\n ],\n [\n -77.00660705566406,\n 38.6897975322717\n ],\n [\n -77.12745666503906,\n 38.66781998344701\n ],\n [\n -77.10960388183592,\n 38.69247725944551\n ],\n [\n -77.02583312988281,\n 38.74765730401543\n ],\n [\n -77.00523376464844,\n 38.74819282375652\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.2998046875,\n 38.53527591154413\n ],\n [\n -77.22084045410156,\n 38.54870243589558\n ],\n [\n -77.26547241210936,\n 38.4632670276956\n ],\n [\n -77.28744506835938,\n 38.34057907754285\n ],\n [\n -77.33345031738281,\n 38.3384247989913\n ],\n [\n -77.33139038085938,\n 38.40302528453207\n ],\n [\n -77.32933044433594,\n 38.4514377951069\n ],\n [\n -77.2998046875,\n 38.53527591154413\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.92558288574219,\n 38.301792263441016\n ],\n [\n -76.92558288574219,\n 38.31903340948611\n ],\n [\n -76.90292358398438,\n 38.31903340948611\n ],\n [\n -76.90292358398438,\n 38.301792263441016\n ],\n [\n -76.92558288574219,\n 38.301792263441016\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5507f0a0e4b02e76d757c128","contributors":{"authors":[{"text":"Campbell, Sarah Hunter","contributorId":139663,"corporation":false,"usgs":false,"family":"Campbell","given":"Sarah","email":"","middleInitial":"Hunter","affiliations":[],"preferred":false,"id":542368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rybicki, Nancy B. 0000-0002-2205-7927 nrybicki@usgs.gov","orcid":"https://orcid.org/0000-0002-2205-7927","contributorId":2142,"corporation":false,"usgs":true,"family":"Rybicki","given":"Nancy","email":"nrybicki@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":537343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schenk, Edward R. 0000-0001-6886-5754 eschenk@usgs.gov","orcid":"https://orcid.org/0000-0001-6886-5754","contributorId":2183,"corporation":false,"usgs":true,"family":"Schenk","given":"Edward","email":"eschenk@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":537342,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175295,"text":"70175295 - 2015 - Modeling climate change, urbanization, and fire effects on Pinus palustris ecosystems of the southeastern U.S.","interactions":[],"lastModifiedDate":"2018-12-20T12:59:26","indexId":"70175295","displayToPublicDate":"2015-03-15T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Modeling climate change, urbanization, and fire effects on Pinus palustris ecosystems of the southeastern U.S.","docAbstract":"Managing ecosystems for resilience and sustainability requires understanding how they will respond to future anthropogenic drivers such as climate change and urbanization. In fire-dependent ecosystems, predicting this response requires a focus on how these drivers will impact fire regimes. Here, we use scenarios of climate change, urbanization and management to simulate the future dynamics of the critically endangered and fire-dependent longleaf pine (Pinus palustris) ecosystem. We investigated how climate change and urbanization will affect the ecosystem, and whether the two conservation goals of a 135% increase in total longleaf area and a doubling of fire-maintained open-canopy habitat can be achieved in the face of these drivers. Our results show that while climatic warming had little effect on the wildfire regime, and thus on longleaf pine dynamics, urban growth led to an 8% reduction in annual wildfire area. The management scenarios we tested increase the ecosystem's total extent by up to 62% and result in expansion of open-canopy longleaf by as much as 216%, meeting one of the two conservation goals for the ecosystem. We find that both conservation goals for this ecosystem, which is climate-resilient but vulnerable to urbanization, are only attainable if a greater focus is placed on restoration of non-longleaf areas as opposed to maintaining existing longleaf stands. Our approach demonstrates the importance of accounting for multiple relevant anthropogenic threats in an ecosystem-specific context in order to facilitate more effective management actions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2014.12.032","usgsCitation":"Costanza, J., Terando, A.J., McKerrow, A., and Collazo, J., 2015, Modeling climate change, urbanization, and fire effects on Pinus palustris ecosystems of the southeastern U.S.: Journal of Environmental Management, v. 151, p. 186-199, https://doi.org/10.1016/j.jenvman.2014.12.032.","startPage":"186","endPage":"199","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056277","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":326103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"151","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a46749e4b0ebae89b63cd4","contributors":{"authors":[{"text":"Costanza, Jennifer","contributorId":74689,"corporation":false,"usgs":true,"family":"Costanza","given":"Jennifer","affiliations":[],"preferred":false,"id":644718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terando, Adam J. 0000-0002-9280-043X aterando@usgs.gov","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":173447,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":644717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":644719,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":644720,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70139954,"text":"70139954 - 2015 - Nine microsatellite loci developed from the octocoral, Paragorgia arborea","interactions":[],"lastModifiedDate":"2015-08-17T15:05:21","indexId":"70139954","displayToPublicDate":"2015-03-13T00:00:00","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":"Nine microsatellite loci developed from the octocoral, Paragorgia arborea","docAbstract":"Paragorgia arborea, or bubblegum coral, occurs in continental slope habitats worldwide, which are increasingly threatened by human activities such as energy development and fisheries practices. From 101 putative loci screened, nine microsatellite markers were developed from samples taken from Baltimore canyon in the western North Atlantic Ocean. The number of alleles ranged from two to thirteen per locus and each displayed equilibrium. These nuclear resources will help further research on population connectivity in threatened coral species where mitochondrial markers are known to lack fine-scale genetic diversity.
","language":"English","publisher":"Springer","doi":"10.1007/s12686-015-0457-z","usgsCitation":"Coykendall, D.K., and Morrison, C., 2015, Nine microsatellite loci developed from the octocoral, Paragorgia arborea: Conservation Genetics Resources, v. 7, no. 3, p. 771-772, https://doi.org/10.1007/s12686-015-0457-z.","productDescription":"2 p.","startPage":"771","endPage":"772","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062510","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":299452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Baltimore Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.816650390625,\n 34.397844946449865\n ],\n [\n -75.816650390625,\n 41.20345619205129\n ],\n [\n -68.609619140625,\n 41.20345619205129\n ],\n [\n -68.609619140625,\n 34.397844946449865\n ],\n [\n -75.816650390625,\n 34.397844946449865\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-13","publicationStatus":"PW","scienceBaseUri":"5524ffb0e4b027f0aee3d47d","contributors":{"authors":[{"text":"Coykendall, D. Katharine 0000-0002-1148-2397 dcoykendall@usgs.gov","orcid":"https://orcid.org/0000-0002-1148-2397","contributorId":5472,"corporation":false,"usgs":true,"family":"Coykendall","given":"D.","email":"dcoykendall@usgs.gov","middleInitial":"Katharine","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":539715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morrison, Cheryl L. cmorrison@usgs.gov","contributorId":3355,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl L.","email":"cmorrison@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":539716,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70138818,"text":"ds915 - 2015 - Hydrological, water-quality, and ecological data for streams in Independence, Missouri, June 2005 through September 2013","interactions":[],"lastModifiedDate":"2015-03-12T16:36:48","indexId":"ds915","displayToPublicDate":"2015-03-12T17:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"915","title":"Hydrological, water-quality, and ecological data for streams in Independence, Missouri, June 2005 through September 2013","docAbstract":"Water-quality, hydrological, and ecological data collected from June 2005 through September 2013 from the Little Blue River and smaller streams within the City of Independence, Missouri, are presented in this report. These data were collected as a part of an ongoing cooperative study between the U.S. Geological Survey and the City of Independence Water Pollution Control Department to characterize the water quality and ecological condition of Independence streams. The quantities, sources of selected constituents, and processes affecting water quality and aquatic life were evaluated to determine the resulting ecological condition of streams within Independence. Data collected for this study fulfill the municipal separate sewer system permit requirements for the City of Independence and can be used to provide a baseline with which city managers can determine the effectiveness of current (2014) and future best management practices within Independence. Continuous streamflow and water-quality data, collected during base flow and stormflow, included physical and chemical properties, inorganic constituents, common organic micro-constituents, pesticides in streambed sediment and surface water, fecal indicator bacteria and microbial source tracking data, and suspended sediment. Dissolved oxygen, pH, specific conductance, water temperature, and turbidity data were measured continuously at seven sites within Independence. Base-flow and stormflow samples were collected at eight gaged and two ungaged sites. Fecal sources samples were collected for reference for microbial source tracking, and sewage influent samples were collected as additional source samples. Dry-weather screening was done on 11 basins within Independence to identify potential contaminant sources to the streams. Benthic macroinvertebrate community surveys and habitat assessments were done on 10 stream sites and 2 comparison sites outside the city. Sampling and laboratory procedures and quality-assurance and quality-control methods used in data collection for this study are described in this report.
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2015 - The 3D Elevation Program: summary for Pennsylvania","interactions":[],"lastModifiedDate":"2016-08-10T21:04:52","indexId":"fs20153019","displayToPublicDate":"2015-03-12T15:15:00","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":"2015-3019","title":"The 3D Elevation Program: summary for Pennsylvania","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the Commonwealth of Pennsylvania, elevation data are critical for natural resources conservation (including the effects of drilling for oil and natural gas), agriculture and precision farming, flood risk management, infrastructure and construction management, water supply and quality, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, and local agencies work in partnership to replace data that are older and of lower quality. A joint goal of Commonwealth and Federal partners is to provide a temporal and density refresh of the current statewide coverage in order to support existing and emerging applications enabled by improved lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
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Jr. carswell@usgs.gov","contributorId":127609,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":541907,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70142446,"text":"fs20153018 - 2015 - The 3D Elevation Program: summary for Iowa","interactions":[],"lastModifiedDate":"2016-08-17T15:06:20","indexId":"fs20153018","displayToPublicDate":"2015-03-12T15:00:00","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":"2015-3018","title":"The 3D Elevation Program: summary for Iowa","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Iowa, elevation data are critical for agriculture and precision farming, infrastructure and construction management, natural resources conservation, flood risk management, water supply and quality, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153018","usgsCitation":"Carswell, W., 2015, The 3D Elevation Program: summary for Iowa (Version 1.0: Originally posted March 12, 2015; Version 1.1: June 25, 2015): U.S. Geological Survey Fact Sheet 2015-3018, 2 p., https://doi.org/10.3133/fs20153018.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060453","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":298459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153018.jpg"},{"id":298458,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3018/pdf/fs2015-3018.pdf","text":"Report","size":"260 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298457,"rank":1,"type":{"id":15,"text":"Index 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\"}}]}","edition":"Version 1.0: Originally posted March 12, 2015; Version 1.1: June 25, 2015","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5502aa9ce4b02e76d7564e98","contributors":{"authors":[{"text":"Carswell, William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":541906,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70137387,"text":"sir20155001 - 2015 - Low-flow characteristics and flow-duration statistics for selected USGS continuous-record streamgaging stations in North Carolina through 2012","interactions":[],"lastModifiedDate":"2017-01-18T13:18:37","indexId":"sir20155001","displayToPublicDate":"2015-03-12T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5001","title":"Low-flow characteristics and flow-duration statistics for selected USGS continuous-record streamgaging stations in North Carolina through 2012","docAbstract":"In 2013, the U.S. Geological Survey, in cooperation with the North Carolina Division of Water Resources, compiled updated low-flow characteristics and flow-duration statistics for selected continuous-record streamgages in North Carolina. The compilation of updated streamflow statistics provides regulators and planners with relevant hydrologic information reflective of the recent droughts, which can be used to better manage the quantity and quality of streams in North Carolina. Streamflow records available through the 2012 water year1 were used to determine the annual (based on climatic year2) and winter 7-day, 10-year (7Q10, W7Q10) low-flow discharges, the 30-day, 2-year (30Q2) low-flow discharge, and the 7-day, 2-year (7Q2) low-flow discharge. Consequently, streamflow records available through March 31, 2012 (or the 2011 climatic year) were used to determine the updated low-flow characteristics. Low-flow characteristics were published for 177 unregulated sites, 56 regulated sites, and 33 sites known or considered to be affected by varying degrees of minor regulation and (or) diversions upstream from the streamgages (266 sites total). The updated 7Q10 discharges were compared for 63 streamgages across North Carolina where (1) long-term streamflow record consisted of 30 or more climatic years of data available as of the 1998 climatic year, and (2) streamflows were not known to be regulated. The 7Q10 discharges did not change for 3 sites, whereas increases and decreases were noted at 5 and 55 sites, respectively. Positive changes (increases) ranged from 4.3 percent (site 362) to 34.1 percent (site 112) with a median of 13.2 percent. Negative percentage changes (decreases) ranged from –3.3 percent (site 514) to –80.0 percent (site 308) with a median of –22.2 percent. The median percentage change for all 63 streamgages was –18.4 percent. Streamflow statistics determined as a part of this compilation included minimum, mean, maximum, and flow-duration statistics of daily mean discharges for categorical periods. Flow-duration statistics based on the daily mean discharge records were compiled in this study for the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles. Flow-duration statistics were determined for each complete water year of record at a streamgage as well as the available period of record (or selected periods if flows were regulated) and selected seasonal, monthly, and calendar day periods. In addition to the streamflow statistics compiled for each of the water years, the number of days the daily mean discharge was at or below the 10th percentile was summed for each water year as well as the number of events during the water year when streamflow was consistently at or below the 10th percentile. All low-flow characteristics for the streamgages were added into the StreamStatsDB, which is a database accessible to users through the recently released USGS StreamStats application for North Carolina. The minimum, mean, maximum, and flow-duration statistics of daily mean discharges based on the available (or selected if regulated flows) period of record were updated in the North Carolina StreamStatsDB. However, for the selected seasonal, monthly, calendar day, and annual water year periods, tab-delimited American Standard Code for Information Interchange (ASCII) tables of the streamflow statistics are available online to users from a link provided in the StreamStats application. 1The annual period from October 1 through September 30, designated by the year in which the period ends. 2The annual period from April 1 through March 31, designated by the year in which the period begins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155001","collaboration":"Prepared in cooperation with North Carolina Department of Environment and Natural Resources, Division of Water Resources","usgsCitation":"Weaver, J.C., 2016, Low-flow characteristics and flow-duration statistics for selected USGS continuous-record streamgaging stations in North Carolina through 2012 (ver. 1.1, March 2016): U.S. Geological Survey Scientific Investigations Report 2015–5001, 89 p., https://dx.doi.org/10.3133/sir20155001.","productDescription":"vii, 89 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051713","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":318509,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2015/5001/versionHist.txt","size":"3.96 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2015-5001"},{"id":318636,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5001/downloads/","text":"Downloads Directory","linkFileType":{"id":5,"text":"html"},"linkHelpText":"An alternative method to accessing the streamflow statistcs not provided in the report outside of the StreamStats application http://water.usgs.gov/osw/streamstats/north_carolina.html is through the Downloads Directory link above. Tables 3 and 5 in the report provide the low-flow characteristics and flow-duration statistics, respectively, for the available (or selected if regulated flows) period of records at the streamages. The Downloads directory contains the minimum, mean, maximum, and flow-duration statistics of daily mean discharges based on the available (or selected if regulated flows) period of record, each complete water year of record, each calendar day, each month, and selected seasonal periods."},{"id":318508,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5001/pdf/sir20155001.pdf","text":"Report","size":"4.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5001"},{"id":318510,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5001/images/coverthb2.jpg"},{"id":298463,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5001/index.html"}],"country":"United States","state":"North 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U.S. Geological Survey
3916 Sunset Ridge Road
Raleigh, NC 27607
http://nc.water.usgs.gov/
The authors documented gross and microscopic morphology of lesions in corals on 7 islands spanning western, southern, and eastern Micronesia, sampling 76 colonies comprising 30 species of corals among 18 genera, with Acropora, Porites, and Montipora dominating. Tissue loss comprised the majority of gross lesions sampled (41%), followed by discoloration (30%) and growth anomaly (29%). Of 31 cases of tissue loss, most lesions were subacute (48%), followed by acute and chronic (26% each). Of 23 samples with discoloration, most were dark discoloration (40%), with bleaching and other discoloration each constituting 30%. Of 22 growth anomalies, umbonate growth anomalies composed half, with exophytic, nodular, and rugose growth anomalies composing the remainder. On histopathology, for 9 cases of dark discoloration, fungal infections predominated (77%); for 7 bleached corals, depletion of zooxanthellae from the gastrodermis made up a majority of microscopic diagnoses (57%); and for growth anomalies other than umbonate, hyperplasia of the basal body wall was the most common microscopic finding (63%). For the remainder of the gross lesions, no single microscopic finding constituted >50% of the total. Host response varied with the agent present on histology. Fragmentation of tissues was most often associated with algae (60%), whereas necrosis dominated (53%) for fungi. Two newly documented potentially symbiotic tissue-associated metazoans were seen in Porites and Montipora. Findings of multiple potential etiologies for a given gross lesion highlight the importance of incorporating histopathology in coral disease surveys. This study also expands the range of corals infected with cell-associated microbial aggregates.
","language":"English","publisher":"European College of Veterinary Pathologists","publisherLocation":"New York, NY","doi":"10.1177/0300985815571669","usgsCitation":"Work, T.M., Aeby, G.S., and Hughen, K.A., 2015, Gross and microscopic lesions in corals from Micronesia: Veterinary Pathology, v. 53, no. 1, p. 153-162, https://doi.org/10.1177/0300985815571669.","productDescription":"10 p.","startPage":"153","endPage":"162","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056418","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":472211,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/7939","text":"External Repository"},{"id":298559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-12","publicationStatus":"PW","scienceBaseUri":"5507fec0e4b02e76d757c148","contributors":{"authors":[{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":542376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aeby, Greta S.","contributorId":64783,"corporation":false,"usgs":false,"family":"Aeby","given":"Greta","email":"","middleInitial":"S.","affiliations":[{"id":13394,"text":"Hawai‘i Institute of Marine Biology","active":true,"usgs":false}],"preferred":false,"id":542377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hughen, Konrad A.","contributorId":52490,"corporation":false,"usgs":true,"family":"Hughen","given":"Konrad","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":542378,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70139403,"text":"cir1406 - 2015 - Understanding nutrients in the Chesapeake Bay watershed and implications for management and restoration: The Eastern Shore","interactions":[],"lastModifiedDate":"2021-07-02T13:53:08.712418","indexId":"cir1406","displayToPublicDate":"2015-03-12T09:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1406","title":"Understanding nutrients in the Chesapeake Bay watershed and implications for management and restoration: The Eastern Shore","docAbstract":"The Eastern Shore includes only a small part of the Chesapeake Bay watershed, but contributes disproportionately large loads of the excess nitrogen and phosphorus that have contributed to ecological and economic degradation of the bay in recent decades. Chesapeake Bay is the largest estuary in the United States and a vital ecological and economic resource. The bay and its tributaries have been degraded in recent decades by excessive nitrogen and phosphorus in the water column, however, which cause harmful algal blooms and decreased water clarity, submerged aquatic vegetation, and dissolved oxygen. The disproportionately large nitrogen and phosphorus yields from the Eastern Shore to Chesapeake Bay are attributable to human land-use practices as well as natural hydrogeologic and soil conditions. Applications of nitrogen and phosphorus compounds to the Eastern Shore from human activities are intensive. More than 90 percent of nitrogen and phosphorus reaching the land in the Eastern Shore is applied as part of inorganic fertilizers or manure, or (for nitrogen) fixed directly from the atmosphere in cropland. Also, hydrogeologic and soil conditions promote the movement of these compounds from application areas on the landscape to groundwater and (or) surface waters, and the proximity of much of the Eastern Shore to tidal waters limits opportunities for natural removal of these compounds in the landscape. The Eastern Shore only includes 7 percent of the Chesapeake Bay watershed, but receives nearly twice as much nitrogen and phosphorus applications (per area) as the remainder of the watershed and yields greater nitrogen and phosphorus, on average, to the bay. Nitrogen and phosphorus commonly occur in streams at concentrations that may adversely affect aquatic ecosystems and have increased in recent decades.
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Center","active":false,"usgs":true}],"preferred":false,"id":539385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Denver, Judith M. jmdenver@usgs.gov","contributorId":780,"corporation":false,"usgs":true,"family":"Denver","given":"Judith M.","email":"jmdenver@usgs.gov","affiliations":[{"id":375,"text":"Maryland, Delaware, and the District of Columbia Water Science Center","active":false,"usgs":true}],"preferred":false,"id":539386,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178147,"text":"70178147 - 2015 - A comparison of methods to estimate seismic phase delays--Numerical examples for coda wave interferometry","interactions":[],"lastModifiedDate":"2016-11-04T11:05:23","indexId":"70178147","displayToPublicDate":"2015-03-12T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of methods to estimate seismic phase delays--Numerical examples for coda wave interferometry","docAbstract":"Time-shift estimation between arrivals in two seismic traces before and after a velocity perturbation is a crucial step in many seismic methods. The accuracy of the estimated velocity perturbation location and amplitude depend on this time shift. Windowed cross correlation and trace stretching are two techniques commonly used to estimate local time shifts in seismic signals. In the work presented here, we implement Dynamic Time Warping (DTW) to estimate the warping function – a vector of local time shifts that globally minimizes the misfit between two seismic traces. We illustrate the differences of all three methods compared to one another using acoustic numerical experiments. We show that DTW is comparable to or better than the other two methods when the velocity perturbation is homogeneous and the signal-to-noise ratio is high. When the signal-to-noise ratio is low, we find that DTW and windowed cross correlation are more accurate than the stretching method. Finally, we show that the DTW algorithm has better time resolution when identifying small differences in the seismic traces for a model with an isolated velocity perturbation. These results impact current methods that utilize not only time shifts between (multiply) scattered waves, but also amplitude and decoherence measurements. DTW is a new tool that may find new applications in seismology and other geophysical methods (e.g., as a waveform inversion misfit function).","language":"English","publisher":"Oxford University Press on behalf of The Royal Astronomical Society","doi":"10.1093/gji/ggv138","usgsCitation":"Mikesell, T.D., Malcolm, A.E., Yang, D., and Haney, M., 2015, A comparison of methods to estimate seismic phase delays--Numerical examples for coda wave interferometry: Geophysical Journal International, v. 202, no. 1, p. 347-360, https://doi.org/10.1093/gji/ggv138.","productDescription":"13 p.","startPage":"347","endPage":"360","ipdsId":"IP-062686","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472212,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggv138","text":"Publisher Index Page"},{"id":330749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"202","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-30","publicationStatus":"PW","scienceBaseUri":"581d9e2be4b0dee4cc90cbc5","contributors":{"authors":[{"text":"Mikesell, T. Dylan","contributorId":52856,"corporation":false,"usgs":true,"family":"Mikesell","given":"T.","email":"","middleInitial":"Dylan","affiliations":[],"preferred":false,"id":653075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malcolm, Alison E.","contributorId":176672,"corporation":false,"usgs":false,"family":"Malcolm","given":"Alison","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":653076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yang, Di","contributorId":176675,"corporation":false,"usgs":false,"family":"Yang","given":"Di","email":"","affiliations":[],"preferred":false,"id":653077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M.","contributorId":61356,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew M.","affiliations":[],"preferred":false,"id":653078,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70137274,"text":"sir20145231 - 2015 - A comparison of methods to predict historical daily streamflow time series in the southeastern United States","interactions":[],"lastModifiedDate":"2015-03-11T15:26:27","indexId":"sir20145231","displayToPublicDate":"2015-03-11T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5231","title":"A comparison of methods to predict historical daily streamflow time series in the southeastern United States","docAbstract":"Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB). Additional metrics of comparison can easily be incorporated into this type of analysis. By considering such a multifaceted approach, the top-performing models can easily be identified and considered for further research. The top-performing models can then provide a basis for future applications and explorations by scientists, engineers, managers, and practitioners to suit their own needs.
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Central Branch","active":true,"usgs":true}],"preferred":true,"id":542166,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LaFontaine, Jacob H. jlafonta@usgs.gov","contributorId":138508,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob H.","email":"jlafonta@usgs.gov","affiliations":[],"preferred":false,"id":542167,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":542168,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70137613,"text":"ds891 - 2015 - Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools","interactions":[],"lastModifiedDate":"2017-12-27T15:13:45","indexId":"ds891","displayToPublicDate":"2015-03-11T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"891","title":"Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools","docAbstract":"With rapidly changing landscape conditions within Wyoming and the potential effects of landscape changes on sage-grouse habitat, land managers and conservation planners, among others, need procedures to assess the location and juxtaposition of important habitats, land-cover, and land-use patterns to balance wildlife requirements with multiple human land uses. Biologists frequently develop habitat-selection studies to identify prioritization efforts for species of conservation concern to increase understanding and help guide habitat-conservation efforts. Recently, the authors undertook a large-scale collaborative effort that developed habitat-selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes in Wyoming, USA and for multiple life-stages (nesting, late brood-rearing, and winter). We developed these habitat models using resource selection functions, based upon sage-grouse telemetry data collected for localized studies and within each life-stage. The models allowed us to characterize and spatially predict seasonal sage-grouse habitat use in Wyoming. Due to the quantity of models, the diversity of model predictors (in the form of geographic information system data) produced by analyses, and the variety of potential applications for these data, we present here a resource that complements our published modeling effort, which will further support land managers.
\nWe deliver all products described herein as online geographic information system data for visualization and downloading. We outline the data properties for each model and their data inputs, describe the process of selecting appropriate data products for multifarious applications, describe all data products and software, provide newly derived model composites, and discuss how land managers may use the models to inform future sage-grouse studies and potentially refine conservation efforts. The models, software tools, and associated opportunities for novel applications of these products should provide a suite of additional, but not exclusive, tools for assessing Wyoming Greater Sage-grouse habitats, which land managers, conservationists, and scientists can apply to myriad applications.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds891","usgsCitation":"O’Donnell, M.S., Aldridge, C.L., Doherty, K., and Fedy, B., 2015, Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools: U.S. Geological Survey Data Series 891, Report: iv, 27 p.; Downloads Directory, https://doi.org/10.3133/ds891.","productDescription":"Report: iv, 27 p.; Downloads Directory","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052571","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":298435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds891.jpg"},{"id":298434,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/ds/0891/downloads/","text":"Downloads Directory","description":"Downloads Directory","linkHelpText":"Contains: geospatial database."},{"id":298433,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0891/pdf/ds891.pdf","text":"Report","size":"8.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298425,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0891/"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.060791015625,\n 40.9964840143779\n ],\n [\n -111.060791015625,\n 45.00365115687189\n ],\n [\n -104.051513671875,\n 45.00365115687189\n ],\n [\n -104.051513671875,\n 40.9964840143779\n ],\n [\n -111.060791015625,\n 40.9964840143779\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551a65bee4b0323842783480","contributors":{"authors":[{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":3351,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":542119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":542120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, Kevin E.","contributorId":62452,"corporation":false,"usgs":true,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":542122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fedy, Bradley C.","contributorId":40536,"corporation":false,"usgs":true,"family":"Fedy","given":"Bradley C.","affiliations":[],"preferred":false,"id":542121,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}