{"pageNumber":"550","pageRowStart":"13725","pageSize":"25","recordCount":46677,"records":[{"id":70048978,"text":"sir20135184 - 2013 - Hydrogeology and water quality in the Snake River alluvial aquifer at Jackson Hole Airport, Jackson, Wyoming, water years 2011 and 2012","interactions":[],"lastModifiedDate":"2014-01-06T13:57:09","indexId":"sir20135184","displayToPublicDate":"2014-01-06T13:41:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5184","title":"Hydrogeology and water quality in the Snake River alluvial aquifer at Jackson Hole Airport, Jackson, Wyoming, water years 2011 and 2012","docAbstract":"<p>The hydrogeology and water quality of the Snake River alluvial aquifer at the Jackson Hole Airport in northwest Wyoming was studied by the U.S. Geological Survey, in cooperation with the Jackson Hole Airport Board, during water years 2011 and 2012 as part of a followup to a previous baseline study during September 2008 through June 2009. Hydrogeologic conditions were characterized using data collected from 19 Jackson Hole Airport wells. Groundwater levels are summarized in this report and the direction of groundwater flow, hydraulic gradients, and estimated groundwater velocity rates in the Snake River alluvial aquifer underlying the study area are presented. Analytical results of groundwater samples collected from 10 wells during water years 2011 and 2012 are presented and summarized.</p>\n<br/>\n<p>The water table at Jackson Hole Airport was lowest in early spring and reached its peak in July or August, with an increase of 12.5 to 15.5 feet between April and July 2011. Groundwater flow was predominantly horizontal but generally had the hydraulic potential for downward flow. Groundwater flow within the Snake River alluvial aquifer at the airport was from the northeast to the west-southwest, with horizontal velocities estimated to be about 25 to 68 feet per day. This range of velocities slightly is broader than the range determined in the previous study and likely is due to variability in the local climate. The travel time from the farthest upgradient well to the farthest downgradient well was approximately 52 to 142 days. This estimate only describes the average movement of groundwater, and some solutes may move at a different rate than groundwater through the aquifer.</p>\n<br/>\n<p>The quality of the water in the alluvial aquifer generally was considered good. Water from the alluvial aquifer was fresh, hard to very hard, and dominated by calcium carbonate. No constituents were detected at concentrations exceeding U.S. Environmental Protection Agency maximum contaminant levels or health advisories; however, reduction and oxidation (redox) measurements indicate oxygen-poor water in many of the wells. Gasoline-range organics, three volatile organic compounds, and triazoles were detected in some groundwater samples. The quality of groundwater in the alluvial aquifer generally was suitable for domestic and other uses; however, dissolved iron and manganese were detected in samples from many of the monitor wells at concentrations exceeding U.S. Environmental Protection Agency secondary maximum contaminant levels. Iron and manganese likely are both natural components of the geologic materials in the area and may have become mobilized in the aquifer because of redox processes. Additionally, measurements of dissolved-oxygen concentrations and analyses of major ions and nutrients indicate reducing conditions exist at 7 of the 10 wells sampled.</p>\n<br/>\n<p>Measurements of dissolved-oxygen concentrations (less than 0.1 to 9 milligrams per liter) indicated some variability in the oxygen content of the aquifer. Dissolved-oxygen concentrations in samples from 3 of the 10 wells indicated oxic conditions in the aquifer, whereas low dissolved-oxygen concentrations (less than 1 milligram per liter) in samples from 7 wells indicated anoxic conditions. Nutrients were present in low concentrations in all samples collected. Nitrate plus nitrite was detected in samples from 6 of the 10 monitored wells, whereas dissolved ammonia was detected in small concentrations in 8 of the 10 monitored wells. Dissolved organic carbon concentrations generally were low. At least one dissolved organic carbon concentration was quantified by the laboratory in samples from all 10 wells; one of the concentrations was an order of magnitude higher than other detected dissolved organic carbon concentrations, and slightly exceeded the estimated range for natural groundwater.</p>\n<br/>\n<p>Samples were collected for analyses of dissolved gases, and field analyses of ferrous iron, hydrogen sulfide, and low-level dissolved oxygen were completed to better understand the redox conditions of the alluvial aquifer. Dissolved gas analyses confirmed low concentrations of dissolved oxygen in samples from wells where reducing conditions exist and indicated the presence of methane gas in samples from several wells. Redox processes in the alluvial aquifer were identified using a model designed to use a multiple-lines-of-evidence approach to distinguish reduction processes. Results of redox analyses indicate iron reduction was the dominant redox process; however, the model indicated manganese reduction and methanogenesis also were taking place in the aquifer.</p>\n<br/>\n<p>Each set of samples collected during this study included analysis of at least two, but often many anthropogenic compounds. During the previous 2008–09 study at Jackson Hole Airport, diesel-range organics were measured in small (estimated) concentrations in several samples. Samples collected from all 10 wells sampled during the 2011–12 study were analyzed for diesel-range organics, and there were no detections; however, several other anthropogenic compounds were detected in groundwater samples during water years 2011—12 that were not detected during the previous 2008–09 study. Gasoline-range organics, benzene, ethylbenzene, and total xylene were each detected (but reported as estimated concentrations) in at least one groundwater sample. These compounds were not detected during the previous study or consistently during this study. Several possible reasons these compounds were not detected consistently include (1) these compounds are present in the aquifer at concentrations near the analytical method detection limit and are difficult to detect, (2) these compounds were not from a persistent source during this study, and (3) these compounds were detected because of contamination introduced during sampling or analysis. During water years 2011–2012, groundwater samples were analyzed for triazoles, specifically benzotriazole, 4-methyl-1H-benzotriazole, and 5-methyl-1H-benzotriazole. Triazoles are anthropogenic compounds often used as an additive in deicing and anti-icing fluids as a corrosion inhibitor, and can be detected at lower laboratory reporting levels than glycols, which previously had not been detected. Two of the three triazoles measured, 4-methyl-1H-benzotriazole and 5-methyl-1H-benzotriazole, were detected at low concentrations in groundwater at 7 of the 10 wells sampled. The detection of triazole compounds in groundwater downgradient from airport operations makes it unlikely there is a natural cause for the high rates of reduction present in many airport monitor wells. It is more likely that aircraft deicers, anti-icers, or pavement deicers have seeped into the groundwater system and caused the reducing conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135184","collaboration":"Prepared in cooperation with the Jackson Hole Airport Board","usgsCitation":"Wright, P., 2013, Hydrogeology and water quality in the Snake River alluvial aquifer at Jackson Hole Airport, Jackson, Wyoming, water years 2011 and 2012: U.S. Geological Survey Scientific Investigations Report 2013-5184, vii, 56 p., https://doi.org/10.3133/sir20135184.","productDescription":"vii, 56 p.","numberOfPages":"68","temporalStart":"2010-10-01","temporalEnd":"2012-09-30","ipdsId":"IP-042348","costCenters":[{"id":684,"text":"Wyoming Water Science Center","active":false,"usgs":true}],"links":[{"id":280625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135184.jpg"},{"id":280624,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5184/pdf/sir2013-5184.pdf"},{"id":280623,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5184/"}],"projection":"Lambert Conformal Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Wyoming","city":"Jackson","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.047058,43.400059 ], [ -111.047058,43.899871 ], [ -110.398865,43.899871 ], [ -110.398865,43.400059 ], [ -111.047058,43.400059 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52cbd082e4b03116c9ddb9fc","contributors":{"authors":[{"text":"Wright, Peter R. prwright@usgs.gov","contributorId":1828,"corporation":false,"usgs":true,"family":"Wright","given":"Peter R.","email":"prwright@usgs.gov","affiliations":[],"preferred":true,"id":485917,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70067332,"text":"70067332 - 2013 - Fluvial rainbow trout contribute to the colonization of steelhead (<i>Oncorhynchus mykiss</i>) in a small stream","interactions":[],"lastModifiedDate":"2016-04-26T11:00:16","indexId":"70067332","displayToPublicDate":"2014-01-06T13:30:56","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Fluvial rainbow trout contribute to the colonization of steelhead (<i>Oncorhynchus mykiss</i>) in a small stream","docAbstract":"<p><span>Life history polymorphisms provide ecological and genetic diversity important to the long term persistence of species responding to stochastic environments.&nbsp;</span><i class=\"EmphasisTypeItalic \">Oncorhynchus mykiss</i><span>&nbsp;have complex and overlapping life history strategies that are also sympatric with hatchery populations. Passive integrated transponder (PIT) tags and parentage analysis were used to identify the life history, origin (hatchery or wild) and reproductive success of migratory rainbow/steelhead for two brood years after barriers were removed from a small stream. The fluvial rainbow trout provided a source of wild genotypes to the colonizing population boosting the number of successful spawners. Significantly more parr offspring were produced by anadromous parents than expected in brood year 2005, whereas significantly more parr offspring were produced by fluvial parents than expected in brood year 2006. Although hatchery steelhead were prevalent in the Methow Basin, they produced only 2&nbsp;parr and no returning adults in Beaver Creek. On average, individual wild steelhead produced more parr offspring than the fluvial or hatchery groups. Yet, the offspring that returned as adult steelhead were from parents that produced few parr offspring, indicating that high production of parr offspring may not be related to greater returns of adult offspring. These data in combination with other studies of sympatric life histories of&nbsp;</span><i class=\"EmphasisTypeItalic \">O. mykiss</i><span>&nbsp;indicate that fluvial rainbow trout are important to the conservation and recovery of steelhead and should be included in the management and recovery efforts.</span></p>","language":"English","publisher":"Kluwer Academic Publishers","doi":"10.1007/s10641-013-0204-9","usgsCitation":"Weigel, D.E., Connolly, P., and Powell, M.S., 2013, Fluvial rainbow trout contribute to the colonization of steelhead (<i>Oncorhynchus mykiss</i>) in a small stream: Environmental Biology of Fishes, v. 97, no. 10, p. 1149-1159, https://doi.org/10.1007/s10641-013-0204-9.","productDescription":"11 p.","startPage":"1149","endPage":"1159","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040005","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":280739,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.21,48.05 ], [ -120.21,48.48 ], [ -119.93,48.48 ], [ -119.93,48.05 ], [ -120.21,48.05 ] ] ] } } ] }","volume":"97","issue":"10","noUsgsAuthors":false,"publicationDate":"2013-11-22","publicationStatus":"PW","scienceBaseUri":"53cd5a0ce4b0b290850f9167","contributors":{"authors":[{"text":"Weigel, Dana E.","contributorId":79389,"corporation":false,"usgs":true,"family":"Weigel","given":"Dana","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":487991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connolly, Patrick J. 0000-0001-7365-7618 pconnolly@usgs.gov","orcid":"https://orcid.org/0000-0001-7365-7618","contributorId":2920,"corporation":false,"usgs":true,"family":"Connolly","given":"Patrick J.","email":"pconnolly@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487989,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Madison S.","contributorId":33609,"corporation":false,"usgs":true,"family":"Powell","given":"Madison","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":487990,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70100728,"text":"70100728 - 2013 - Powassan virus in mammals, Alaska and New Mexico, USA, and Russia, 2004–2007","interactions":[],"lastModifiedDate":"2018-08-20T18:06:21","indexId":"70100728","displayToPublicDate":"2014-01-05T14:03:16","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1493,"text":"Emerging Infectious Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Powassan virus in mammals, Alaska and New Mexico, USA, and Russia, 2004–2007","docAbstract":"Powassan virus is endemic to the United States, Canada, and the Russian Far East. We report serologic evidence of circulation of this virus in Alaska, New Mexico, and Siberia. These data support further studies of viral ecology in rapidly changing Arctic environments.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Emerging Infectious Diseases","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Centers for Disease Control and Prevention","doi":"10.3201/eid1912.130319","usgsCitation":"Deardorff, E.R., Nofchissey, R.A., Cook, J.A., Hope, A.G., Tsvetkova, A., Talbot, S.L., and Ebel, G.D., 2013, Powassan virus in mammals, Alaska and New Mexico, USA, and Russia, 2004–2007: Emerging Infectious Diseases, v. 19, no. 12, Online Article, https://doi.org/10.3201/eid1912.130319.","productDescription":"Online Article","ipdsId":"IP-049225","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":473365,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3201/eid1912.130319","text":"Publisher Index Page"},{"id":285735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285704,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3201/eid1912.130319"},{"id":285705,"type":{"id":15,"text":"Index Page"},"url":"https://wwwnc.cdc.gov/eid/article/19/12/13-0319_article.htm"}],"volume":"19","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535594f8e4b0120853e8c110","contributors":{"authors":[{"text":"Deardorff, Eleanor R.","contributorId":96194,"corporation":false,"usgs":true,"family":"Deardorff","given":"Eleanor","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":492403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nofchissey, Robert A.","contributorId":7620,"corporation":false,"usgs":true,"family":"Nofchissey","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":492398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Joseph A.","contributorId":8323,"corporation":false,"usgs":false,"family":"Cook","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":492399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hope, Andrew G. 0000-0003-3814-2891 ahope@usgs.gov","orcid":"https://orcid.org/0000-0003-3814-2891","contributorId":4309,"corporation":false,"usgs":true,"family":"Hope","given":"Andrew","email":"ahope@usgs.gov","middleInitial":"G.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":492402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tsvetkova, Albina","contributorId":26971,"corporation":false,"usgs":true,"family":"Tsvetkova","given":"Albina","affiliations":[],"preferred":false,"id":492400,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":492397,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ebel, Gregory D.","contributorId":33220,"corporation":false,"usgs":true,"family":"Ebel","given":"Gregory","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":492401,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70111661,"text":"70111661 - 2013 - Next-generation sequencing reveals cryptic mtDNA diversity of Plasmodium relictum in the Hawaiian Islands","interactions":[],"lastModifiedDate":"2014-06-06T08:37:35","indexId":"70111661","displayToPublicDate":"2014-01-05T08:32:23","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3011,"text":"Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Next-generation sequencing reveals cryptic mtDNA diversity of Plasmodium relictum in the Hawaiian Islands","docAbstract":"Next-generation 454 sequencing techniques were used to re-examine diversity of mitochondrial cytochrome b lineages of avian malaria (Plasmodium relictum) in Hawaii. We document a minimum of 23 variant lineages of the parasite based on single nucleotide transitional changes, in addition to the previously reported single lineage (GRW4). A new, publicly available portal (Integroomer) was developed for initial parsing of 454 datasets. Mean variant prevalence and frequency was higher in low elevation Hawaii Amakihi (Hemignathus virens) with Avipoxvirus-like lesions (P = 0·001), suggesting that the variants may be biologically distinct. By contrast, variant prevalence and frequency did not differ significantly among mid-elevation Apapane (Himatione sanguinea) with or without lesions (P = 0·691). The low frequency and the lack of detection of variants independent of GRW4 suggest that multiple independent introductions of P. relictum to Hawaii are unlikely. Multiple variants may have been introduced in heteroplasmy with GRW4 or exist within the tandem repeat structure of the mitochondrial genome. The discovery of multiple mitochondrial lineages of P. relictum in Hawaii provides a measure of genetic diversity within a geographically isolated population of this parasite and suggests the origins and evolution of parasite diversity may be more complicated than previously recognized.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Parasitology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0031182013000905","usgsCitation":"Jarvi, S., Farias, M., Lapointe, D., Belcaid, M., and Atkinson, C., 2013, Next-generation sequencing reveals cryptic mtDNA diversity of Plasmodium relictum in the Hawaiian Islands: Parasitology, v. 140, no. 14, p. 1741-1750, https://doi.org/10.1017/S0031182013000905.","productDescription":"10 p.","startPage":"1741","endPage":"1750","ipdsId":"IP-025078","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":288131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288129,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1017/S0031182013000905"},{"id":288130,"type":{"id":15,"text":"Index Page"},"url":"https://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=9071724"}],"country":"United States","state":"Hawai'i","volume":"140","issue":"14","noUsgsAuthors":false,"publicationDate":"2013-08-19","publicationStatus":"PW","scienceBaseUri":"53ae7786e4b0abf75cf2c170","contributors":{"authors":[{"text":"Jarvi, S.I.","contributorId":60341,"corporation":false,"usgs":true,"family":"Jarvi","given":"S.I.","affiliations":[],"preferred":false,"id":494389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farias, M.E.","contributorId":43675,"corporation":false,"usgs":true,"family":"Farias","given":"M.E.","email":"","affiliations":[],"preferred":false,"id":494388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lapointe, D.A.","contributorId":69691,"corporation":false,"usgs":true,"family":"Lapointe","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":494390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belcaid, M.","contributorId":80193,"corporation":false,"usgs":true,"family":"Belcaid","given":"M.","email":"","affiliations":[],"preferred":false,"id":494391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, C. T.","contributorId":29349,"corporation":false,"usgs":false,"family":"Atkinson","given":"C. T.","affiliations":[],"preferred":false,"id":494387,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70048969,"text":"ds776 - 2013 - Compilation, quality control, analysis, and summary of discrete suspended-sediment and ancillary data in the United States, 1901-2010","interactions":[],"lastModifiedDate":"2014-01-04T14:07:18","indexId":"ds776","displayToPublicDate":"2014-01-04T14:00:00","publicationYear":"2013","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":"776","title":"Compilation, quality control, analysis, and summary of discrete suspended-sediment and ancillary data in the United States, 1901-2010","docAbstract":"<p>Human-induced and natural changes to the transport of sediment and sediment-associated constituents can degrade aquatic ecosystems and limit human uses of streams and rivers. The lack of a dedicated, easily accessible, quality-controlled database of sediment and ancillary data has made it difficult to identify sediment-related water-quality impairments and has limited understanding of how human actions affect suspended-sediment concentrations and transport. The purpose of this report is to describe the creation of a quality-controlled U.S. Geological Survey suspended-sediment database, provide guidance for its use, and summarize characteristics of suspended-sediment data through 2010. The database is provided as an online application at <i>http://cida.usgs.gov/sediment</i> to allow users to view, filter, and retrieve available suspended-sediment and ancillary data.</p>\n<br/>\n<p>A data recovery, filtration, and quality-control process was performed to expand the availability, representativeness, and utility of existing suspended-sediment data collected by the U.S. Geological Survey in the United States before January 1, 2011. Information on streamflow condition, sediment grain size, and upstream landscape condition were matched to sediment data and sediment-sampling sites to place data in context with factors that may influence sediment transport. Suspended-sediment and selected ancillary data are presented from across the United States with respect to time, streamflow, and landscape condition. Examples of potential uses of this database for identifying sediment-related impairments, assessing trends, and designing new data collection activities are provided. This report and database can support local and national-level decision making, project planning, and data mining activities related to the transport of suspended-sediment and sediment-associated constituents.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds776","usgsCitation":"Lee, C., and Glysson, G.D., 2013, Compilation, quality control, analysis, and summary of discrete suspended-sediment and ancillary data in the United States, 1901-2010: U.S. Geological Survey Data Series 776, v, 35 p., https://doi.org/10.3133/ds776.","productDescription":"v, 35 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-040769","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":280609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds776.gif"},{"id":280603,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/776/"},{"id":280608,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/776/pdf/ds776.pdf"}],"scale":"100000","projection":"Universal Transverse Mercator projection","country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 144.616667,13.233333 ], [ 144.616667,71.833333 ], [ -64.566667,71.833333 ], [ -64.566667,13.233333 ], [ 144.616667,13.233333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c92d92e4b03cb62a1b0780","contributors":{"authors":[{"text":"Lee, Casey J. 0000-0002-5753-2038","orcid":"https://orcid.org/0000-0002-5753-2038","contributorId":31062,"corporation":false,"usgs":true,"family":"Lee","given":"Casey J.","affiliations":[],"preferred":false,"id":485899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glysson, G. Douglas","contributorId":13607,"corporation":false,"usgs":true,"family":"Glysson","given":"G.","email":"","middleInitial":"Douglas","affiliations":[],"preferred":false,"id":485898,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70055665,"text":"sir20125267 - 2013 - Analysis of postfire hydrology, water quality, and sediment transport for selected streams in areas of the 2002 Hayman and Hinman fires, Colorado","interactions":[],"lastModifiedDate":"2014-01-04T13:55:43","indexId":"sir20125267","displayToPublicDate":"2014-01-04T13:42:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5267","title":"Analysis of postfire hydrology, water quality, and sediment transport for selected streams in areas of the 2002 Hayman and Hinman fires, Colorado","docAbstract":"<p>The U.S. Geological Survey (USGS) began a 5-year study in 2003 that focused on postfire stream-water quality and postfire sediment load in streams within the Hayman and Hinman fire study areas. This report compares water quality of selected streams receiving runoff from unburned areas and burned areas using concentrations and loads, and trend analysis, from seasonal data (approximately April–November) collected 2003–2007 at the Hayman fire study area, and data collected from 1999–2000 (prefire) and 2003 (postfire) at the Hinman fire study area. The water-quality data collected during this study include onsite measurements of streamflow, specific conductance, and turbidity, laboratory-determined pH, and concentrations of major ions, nutrients, organic carbon, trace elements, and suspended sediment. Postfire floods and effects on water quality of streams, lakes and reservoirs, drinking-water treatment, and the comparison of measured concentrations to applicable water quality standards also are discussed.</p>\n<br/>\n<p>Exceedances of Colorado water-quality standards in streams of both the Hayman and Hinman fire study areas only occurred for concentrations of five trace elements (not all trace-element exceedances occurred in every stream). Selected samples analyzed for total recoverable arsenic (fixed), dissolved copper (acute and chronic), total recoverable iron (chronic), dissolved manganese (acute, chronic, and fixed) and total recoverable mercury (chronic) exceeded Colorado aquatic-life standards.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125267","collaboration":"Prepared in cooperation with Douglas County, U.S. Environmental Protection Agency, the cities of Aurora, Northglenn, Thornton, and Westminster, the Colorado Department of Public Health and Environment, Colorado River Water Conservation District, Colorado Springs Utilities, Denver Water, Federal Emergency Management Agency, North Front Range Water Quality Planning Association, and Routt and Medicine Bow National Forests","usgsCitation":"Stevens, M.R., 2013, Analysis of postfire hydrology, water quality, and sediment transport for selected streams in areas of the 2002 Hayman and Hinman fires, Colorado: U.S. Geological Survey Scientific Investigations Report 2012-5267, Report: ix, 93 p.; Downloads Directory: Appendixes 1-12, https://doi.org/10.3133/sir20125267.","productDescription":"Report: ix, 93 p.; Downloads Directory: Appendixes 1-12","numberOfPages":"106","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-017674","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":280604,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5267/"},{"id":280605,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5267/pdf/sir2012-5267.pdf"},{"id":280606,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2012/5267/downloads/"},{"id":280607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125267.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Fourmile Creek;Lost Dog Creek;Pine Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.99,38.95 ], [ -107.99,41.0 ], [ -104.22,41.0 ], [ -104.22,38.95 ], [ -107.99,38.95 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c92d5fe4b03cb62a1b077c","contributors":{"authors":[{"text":"Stevens, Michael R. 0000-0002-9476-6335 mrsteven@usgs.gov","orcid":"https://orcid.org/0000-0002-9476-6335","contributorId":769,"corporation":false,"usgs":true,"family":"Stevens","given":"Michael","email":"mrsteven@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486197,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70049036,"text":"fs20133095 - 2013 - Mountain pine beetle impacts on vegetation and carbon stocks","interactions":[],"lastModifiedDate":"2014-01-03T12:37:28","indexId":"fs20133095","displayToPublicDate":"2014-01-04T12:31:43","publicationYear":"2013","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":"2013-3095","title":"Mountain pine beetle impacts on vegetation and carbon stocks","docAbstract":"In the Southern Rocky Mountains, an epidemic outbreak of mountain pine beetle (Dendroctonus ponderosae; MPB) has caused levels of tree mortality unprecedented in recorded history. The impacts of this mortality on vegetation composition, forest structure, and carbon stocks have only recently received attention, although the impacts of other disturbances such as fires and land-use/land-cover change are much better known.  This study, initiated in 2010, aims to increase our understanding of MPB outbreaks and their impacts. We have integrated field-collected data with vegetation simulation models to assess and quantify how long-term patterns of vegetation and carbon stocks have and may change in response to MPB outbreaks and other disturbances.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133095","usgsCitation":"Hawbaker, T., Briggs, J., Caldwell, M.K., and Stitt, S., 2013, Mountain pine beetle impacts on vegetation and carbon stocks: U.S. Geological Survey Fact Sheet 2013-3095, 2 p., https://doi.org/10.3133/fs20133095.","productDescription":"2 p.","ipdsId":"IP-049649","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":280602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133095.jpg"},{"id":280600,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3095/pdf/fs2013-3095.pdf"},{"id":280601,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3095/"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.06,36.99 ], [ -109.06,41.0 ], [ -102.04,41.0 ], [ -102.04,36.99 ], [ -109.06,36.99 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c92d93e4b03cb62a1b0784","contributors":{"authors":[{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":486061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Jennifer S.","contributorId":101167,"corporation":false,"usgs":true,"family":"Briggs","given":"Jennifer S.","affiliations":[],"preferred":false,"id":486064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Megan K. mcaldwell@usgs.gov","contributorId":4243,"corporation":false,"usgs":true,"family":"Caldwell","given":"Megan","email":"mcaldwell@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":486063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stitt, Susan susan_stitt@usgs.gov","contributorId":1410,"corporation":false,"usgs":true,"family":"Stitt","given":"Susan","email":"susan_stitt@usgs.gov","affiliations":[],"preferred":true,"id":486062,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70049005,"text":"sim3278 - 2013 - Flood-inundation maps for a 6.5-mile reach of the Kentucky River at Frankfort, Kentucky","interactions":[],"lastModifiedDate":"2014-01-03T10:44:30","indexId":"sim3278","displayToPublicDate":"2014-01-03T10:27:48","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3278","title":"Flood-inundation maps for a 6.5-mile reach of the Kentucky River at Frankfort, Kentucky","docAbstract":"Digital flood-inundation maps for a 6.5-mile reach of Kentucky River at Frankfort, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Frankfort Office of Emergency Management. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage Kentucky River at Lock 4 at Frankfort, Kentucky (station no. 03287500). Current conditions for the USGS streamgage may be obtained online at the USGS National Water Information System site (http://waterdata.usgs.gov/nwis/inventory?agency_code=USGS&site_no=03287500). In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http:/water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated at USGS streamgages. The forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.  In this study, flood profiles were computed for the Kentucky River reach by using HEC–RAS, a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current (2013) stage-discharge relation for the Kentucky River at Lock 4 at Frankfort, Kentucky, in combination with streamgage and high-water-mark measurements collected for a flood event in May 2010. The calibrated model was then used to calculate 26 water-surface profiles for a sequence of flood stages, at 1-foot intervals, referenced to the streamgage datum and ranging from a stage near bankfull to the elevation that breached the levees protecting the City of Frankfort. To delineate the flooded area at each interval flood stage, the simulated water-surface profiles were combined with a digital elevation model (DEM) of the study area by using geographic information system software. The DEM consisted of bare-earth elevations within the study area and was derived from a Light Detection And Ranging (LiDAR) dataset having a 5.0-foot horizontal resolution and an accuracy of 0.229 foot.  The availability of these maps, along with Internet information regarding current stages from USGS streamgages and forecasted stages from the NWS, provides emergency management personnel and local residents with critical information for flood response activities such as evacuations, road closures, and postflood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3278","collaboration":"Prepared in cooperation with City of Frankfort, Kentucky, Office of Emergency Management","usgsCitation":"Lant, J.G., 2013, Flood-inundation maps for a 6.5-mile reach of the Kentucky River at Frankfort, Kentucky: U.S. Geological Survey Scientific Investigations Map 3278, Report: vi, 10 p.; Low Resolution and High Resolution Map Sheets; Downloads Directory, https://doi.org/10.3133/sim3278.","productDescription":"Report: vi, 10 p.; Low Resolution and High Resolution Map Sheets; Downloads Directory","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-045182","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":280591,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3278/"},{"id":280592,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3278/pdf/sim3278.pdf"},{"id":280593,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3278/PDF-mapSheets/"},{"id":280594,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3278/downloads/"},{"id":280595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3278.jpg"}],"projection":"Lambert Conformal Conic","datum":"North American Datum of 1983","country":"United States","state":"Kentucky","city":"Fankfort","otherGeospatial":"Kentucky River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.916,38.15 ], [ -84.916,38.233 ], [ -84.816,38.233 ], [ -84.816,38.15 ], [ -84.916,38.15 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c7dbe1e4b0a753c7d3e375","contributors":{"authors":[{"text":"Lant, Jeremiah G. 0000-0001-6688-4820 jlant@usgs.gov","orcid":"https://orcid.org/0000-0001-6688-4820","contributorId":4912,"corporation":false,"usgs":true,"family":"Lant","given":"Jeremiah","email":"jlant@usgs.gov","middleInitial":"G.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485986,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70055737,"text":"ofr20131255 - 2013 - seawaveQ: an R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables","interactions":[],"lastModifiedDate":"2017-10-12T20:16:54","indexId":"ofr20131255","displayToPublicDate":"2014-01-03T09:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1255","title":"seawaveQ: an R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables","docAbstract":"The seawaveQ R package fits a parametric regression model (seawaveQ) to pesticide concentration data from streamwater samples to assess variability and trends. The model incorporates the strong seasonality and high degree of censoring common in pesticide data and users can incorporate numerous ancillary variables, such as streamflow anomalies. The model is fitted to pesticide data using maximum likelihood methods for censored data and is robust in terms of pesticide, stream location, and degree of censoring of the concentration data. This R package standardizes this methodology for trend analysis, documents the code, and provides help and tutorial information, as well as providing additional utility functions for plotting pesticide and other chemical concentration data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131255","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Ryberg, K.R., and Vecchia, A.V., 2013, seawaveQ: an R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables: U.S. Geological Survey Open-File Report 2013-1255, Report: iv, 13 p.; Downloads Directory, https://doi.org/10.3133/ofr20131255.","productDescription":"Report: iv, 13 p.; Downloads Directory","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-049192","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":280584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131255.jpg"},{"id":280570,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1255/"},{"id":280582,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1255/pdf/ofr13-1255.pdf.pdf"},{"id":280583,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1255/Downloads/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c7dc0ee4b0a753c7d3e47d","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":41810,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":486258,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70056151,"text":"sir20135214 - 2013 - An update of hydrologic conditions and distribution of selected constituents in water, eastern Snake River Plain aquifer and perched groundwater zones, Idaho National Laboratory, Idaho, emphasis 2009–11","interactions":[],"lastModifiedDate":"2014-01-02T13:21:37","indexId":"sir20135214","displayToPublicDate":"2014-01-02T12:49:29","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5214","title":"An update of hydrologic conditions and distribution of selected constituents in water, eastern Snake River Plain aquifer and perched groundwater zones, Idaho National Laboratory, Idaho, emphasis 2009–11","docAbstract":"Since 1952, wastewater discharged to infiltration ponds (also called percolation ponds) and disposal wells at the Idaho National Laboratory (INL) has affected water quality in the eastern Snake River Plain (ESRP) aquifer and perched groundwater zones underlying the INL. The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, maintains groundwater monitoring networks at the INL to determine hydrologic trends, and to delineate the movement of radiochemical and chemical wastes in the aquifer and in perched groundwater zones. This report presents an analysis of water-level and water-quality data collected from aquifer, multilevel monitoring system (MLMS), and perched groundwater wells in the USGS groundwater monitoring networks during 2009–11.  Water in the ESRP aquifer primarily moves through fractures and interflow zones in basalt, generally flows southwestward, and eventually discharges at springs along the Snake River. The aquifer primarily is recharged from infiltration of irrigation water, infiltration of streamflow, groundwater inflow from adjoining mountain drainage basins, and infiltration of precipitation.  From March–May 2009 to March–May 2011, water levels in wells generally declined in the northern part of the INL. Water levels generally rose in the central and eastern parts of the INL.  Detectable concentrations of radiochemical constituents in water samples from aquifer wells or MLMS equipped wells in the ESRP aquifer at the INL generally decreased or remained constant during 2009–11. Decreases in concentrations were attributed to radioactive decay, changes in waste-disposal methods, and dilution from recharge and underflow.  In 2011, concentrations of tritium in groundwater from 50 of 127 aquifer wells were greater than or equal to the reporting level and ranged from 200±60 to 7,000±260 picocuries per liter. Tritium concentrations from one or more discrete zones from four wells equipped with MLMS were greater than or equal to reporting levels in water samples collected at various depths. Tritium concentrations in water from wells completed in shallow perched groundwater at the Advanced Test Reactor Complex (ATR Complex) were less than the reporting levels. Tritium concentrations in deep perched groundwater at the ATR Complex equaled or exceeded the reporting level in 12 wells during at least one sampling event during 2009–11 at the ATR Complex.  Concentrations of strontium-90 in water from 20 of 76 aquifer wells sampled during April or October 2011 exceeded the reporting level. Strontium-90 was not detected within the ESRP aquifer beneath the ATR Complex. During at least one sampling event during 2009–11, concentrations of strontium-90 in water from 10 wells completed in deep perched groundwater at the ATR Complex equaled or exceeded the reporting levels.  During 2009–11, concentrations of plutonium-238, and plutonium-239, -240 (undivided), and americium-241 were less than the reporting level in water samples from all aquifer wells and in all wells equipped with MLMS. Concentrations of cesium-137 were equal to or slightly above the reporting level in 8 aquifer wells and from 2 wells equipped with MLMS.  The concentration of chromium in water from one well south of the ATR Complex was 97 micrograms per liter (μg/L) in April 2011, just less than the maximum contaminant level (MCL) of 100 μg/L. Concentrations of chromium in water samples from 69 other wells sampled ranged from 0.8 μg/L to 25 μg/L. During 2009–11, dissolved chromium was detected in water from 15 wells completed in perched groundwater at the ATR Complex.  In 2011, concentrations of sodium in water from most wells in the southern part of the INL were greater than the background concentration of 10 milligrams per liter (mg/L); the highest concentrations were at or near the Idaho Nuclear Engineering and Technology Center (INTEC). After the newpercolation ponds were put into service in 2002 southwest of the INTEC, concentrations of sodium in water samples from the Rifle Range well rose steadily until 2008, when the concentrations generally began decreasing. The increases and decreases were attributed to disposal variability in the new percolation ponds. Concentrations of sodium in most wells equipped with MLMS generally were consistent with depth. During 2011, dissolved sodium concentrations in water from 17 wells completed in deep perched groundwater at the ATR Complex ranged from 6 to 146 mg/L.  In 2011, concentrations of chloride in most water samples from aquifer wells south of the INTEC and at the Central Facilities Area exceeded the background concentrations of 15 mg/L, but were less than the secondary MCL of 250 mg/L. Chloride concentrations in water from wells south of the INTEC have generally increased because of increased chloride disposal to the old percolation ponds since 1984 when discharge of wastewater to the INTEC disposal well was discontinued. After the new percolation ponds were put into service in 2002 southwest of the INTEC, concentrations of chloride in water samples from one well rose steadily until 2008 then began decreasing. Chloride concentrations in water from all but one well completed in the ESRP aquifer at or near the ATR Complex were less than background and ranged between 10 and 14 mg/L during 2011, similar to concentrations detected during the 2006–08 reporting period. During 2011, chloride concentrations in water from two aquifer wells at the Radioactive Waste Management Complex (RWMC) were slightly greater than concentrations detected during the 2006–08 reporting period. The vertical distribution of chloride concentrations in wells equipped with MLMS were generally consistent within zones during 2009–11 and ranged from about 8 to 20 mg/L. During April 2011, dissolved chloride concentrations in shallow perched groundwater at the ATR Complex ranged from 7 to 13 mg/L in water from three wells. Dissolved chloride concentrations in deep perched groundwater at the ATR Complex during 2011 ranged from 4 to 54 mg/L.  In 2011, sulfate concentrations in water samples from 11 aquifer wells in the south-central part of the INL equaled or exceeded the background concentration of sulfate and ranged from 40 to 167 mg/L. The greater-than-background concentrations in water from these wells probably resulted from sulfate disposal at the ATR Complex infiltration ponds or the old INTEC percolation ponds. In 2011, sulfate concentrations in water samples from two wells near the RWMC were greater than background levels and could have resulted from well construction techniques and (or) waste disposal at the RWMC. The vertical distribution of sulfate concentrations in three wells near the southern boundary of the INL was generally consistent with depth, and ranged between 19 and 25 mg/L. The maximum dissolved sulfate concentration in shallow perched groundwater near the ATR Complex was 400 mg/L in well CWP 1 in April 2011. During 2009–11, the maximum concentration of dissolved sulfate in deep perched groundwater at the ATR Complex was 1,550 mg/L in a well located west of the chemical-waste pond.  In 2011, concentrations of nitrate in water from most wells at and near the INTEC exceeded the regional background concentrations of 1 mg/L and ranged from 1.6 to 5.95 mg/L. Concentrations of nitrate in wells south of INTEC and farther away from the influence of disposal areas and the Big Lost River show a general decrease in nitrate concentrations through time.  During 2009–11, water samples from 30 wells were collected and analyzed for volatile organic compounds (VOCs). Six VOCs were detected. At least one and up to five VOCs were detected in water samples from 10 wells. The primary VOCs detected include carbon tetrachloride, chloroform, tetrachloroethylene, 1,1,1-trichloroethane, and trichloroethylene. In 2011, concentrations for all VOCs were less than their respective MCL for drinking water, except carbon tetrachloride in water from two wells.  During 2009–11, variability and bias were evaluated from 56 replicate and 16 blank quality-assurance samples. Results from replicate analyses were investigated to evaluate sample variability. Constituents with acceptable reproducibility were stable isotope ratios, major ions, nutrients, and VOCs. All radiochemical constituents and trace metals had acceptable reproducibility except for gross beta-particle radioactivity, aluminum, antimony, and cobalt. Bias from sample contamination was evaluated from equipment, field, container, and source-solution blanks. No detectable constituent concentrations were reported for equipment blanks of the thief samplers and sampling pipes or for the source-solution and field blanks. Equipment blanks of bailers had detectable concentrations of strontium-90, sodium, chloride, and sulfate, and the container blank had a detectable concentration of dichloromethane.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135214","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Davis, L.C., Bartholomay, R.C., and Rattray, G.W., 2013, An update of hydrologic conditions and distribution of selected constituents in water, eastern Snake River Plain aquifer and perched groundwater zones, Idaho National Laboratory, Idaho, emphasis 2009–11: U.S. Geological Survey Scientific Investigations Report 2013-5214, x, 89 p., https://doi.org/10.3133/sir20135214.","productDescription":"x, 89 p.","numberOfPages":"206","onlineOnly":"Y","ipdsId":"IP-045208","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":280581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":280580,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5214/pdf/sir20135214.pdf"},{"id":280574,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5214/"}],"projection":"Universal Transverse Mercator projection, Zone 12","datum":"North American Datum of 1927","country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.75,43.25 ], [ -113.75,44.5 ], [ -112.25,44.5 ], [ -112.25,43.25 ], [ -113.75,43.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c68a5ee4b06d2ed1226481","contributors":{"authors":[{"text":"Davis, Linda C. lcdavis@usgs.gov","contributorId":2539,"corporation":false,"usgs":true,"family":"Davis","given":"Linda","email":"lcdavis@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486351,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70154884,"text":"70154884 - 2013 - What happens in an estuary doesn't stay there: patterns of biotic connectivity resulting from long term ecological research","interactions":[],"lastModifiedDate":"2015-07-15T14:08:36","indexId":"70154884","displayToPublicDate":"2014-01-01T12:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2929,"text":"Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"What happens in an estuary doesn't stay there: patterns of biotic connectivity resulting from long term ecological research","docAbstract":"<p>The paucity of data on migratory connections and an incomplete understanding of how mobile organisms use geographically separate areas have been obstacles to understanding coastal dynamics. Research on acoustically tagged striped bass (Morone saxatilis) at the Plum Island Ecosystems (PIE) Long Term Ecological Research site, Massachusetts, documents intriguing patterns of biotic connectivity (i.e., long-distance migration between geographically distinct areas). First, the striped bass tagged at PIE migrated southward along the coast using different routes. Second, these tagged fish exhibited strong fidelity and specificity to PIE. For example, across multiple years, tagged striped bass resided in PIE waters for an average of 1.5-2.5 months per year (means: 51-72 days; range 2-122 days), left this estuary in fall, then returned in subsequent years. Third, this specificity and fidelity connected PIE to other locations. The fish exported nutrients and energy to at least three other coastal locations through biomass added as growth. These results demonstrate that what happens in an individual estuary can affect other estuaries. Striped bass that use tightly connected routes to feed in specific estuaries should have greater across-system impacts than fish that are equally likely to go anywhere. Consequently, variations in when, where, and how fish migrate can alter across-estuary impacts.</p>","language":"English","publisher":"The Oceanography Society","publisherLocation":"Rockville, MD","doi":"10.5670/oceanog.2013.60","usgsCitation":"Mather, M.E., Finn, J.T., Kennedy, C., Deegan, L.A., and Smith, J.M., 2013, What happens in an estuary doesn't stay there: patterns of biotic connectivity resulting from long term ecological research: Oceanography, v. 26, no. 3, p. 168-179, https://doi.org/10.5670/oceanog.2013.60.","productDescription":"12 p.","startPage":"168","endPage":"179","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-045506","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473370,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5670/oceanog.2013.60","text":"Publisher Index Page"},{"id":305767,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Plum Island Ecosystems Long Term Ecological Research site","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.543212890625,\n              42.01665183556825\n            ],\n            [\n              -70.1806640625,\n              42.17154633452751\n            ],\n            [\n              -69.521484375,\n              41.549700145132725\n            ],\n            [\n              -69.90600585937499,\n              41.15384235711447\n            ],\n            [\n              -74.915771484375,\n              38.75408327579141\n            ],\n            [\n              -75.11352539062499,\n              39.33429742980725\n            ],\n            [\n              -74.20166015624999,\n              40.84706035607122\n            ],\n            [\n              -73.026123046875,\n              41.45919537950706\n            ],\n            [\n              -70.543212890625,\n              42.01665183556825\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"26","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55a7843ae4b0183d66e45e9a","contributors":{"authors":[{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":564311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, John T.","contributorId":78302,"corporation":false,"usgs":true,"family":"Finn","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":564876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Christina G.","contributorId":145646,"corporation":false,"usgs":false,"family":"Kennedy","given":"Christina G.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":564877,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deegan, Linda A.","contributorId":34094,"corporation":false,"usgs":false,"family":"Deegan","given":"Linda","email":"","middleInitial":"A.","affiliations":[{"id":27818,"text":"The Ecosystems Center, Marine Biological Laboratory. Woods Hole, MA 02543.","active":true,"usgs":false}],"preferred":false,"id":564878,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Joseph M.","contributorId":106712,"corporation":false,"usgs":false,"family":"Smith","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":17855,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA","active":true,"usgs":false},{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":564879,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70093890,"text":"70093890 - 2013 - Blind test of methods for obtaining 2-D near-surface seismic velocity models from first-arrival traveltimes","interactions":[],"lastModifiedDate":"2017-11-07T10:30:12","indexId":"70093890","displayToPublicDate":"2014-01-01T08:43:07","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Blind test of methods for obtaining 2-D near-surface seismic velocity models from first-arrival traveltimes","docAbstract":"Seismic refraction methods are used in environmental and engineering studies to image the shallow subsurface. We present a blind test of inversion and tomographic refraction analysis methods using a synthetic first-arrival-time dataset that was made available to the community in 2010. The data are realistic in terms of the near-surface velocity model, shot-receiver geometry and the data's frequency and added noise. Fourteen estimated models were determined by ten participants using eight different inversion algorithms, with the true model unknown to the participants until it was revealed at a session at the 2011 SAGEEP meeting. The estimated models are generally consistent in terms of their large-scale features, demonstrating the robustness of refraction data inversion in general, and the eight inversion algorithms in particular. When compared to the true model, all of the estimated models contain a smooth expression of its two main features: a large offset in the bedrock and the top of a steeply dipping low-velocity fault zone. The estimated models do not contain a subtle low-velocity zone and other fine-scale features, in accord with conventional wisdom. Together, the results support confidence in the reliability and robustness of modern refraction inversion and tomographic methods.","language":"English","publisher":"Journal of Environmental and Engineering Geophysics","doi":"10.2113/JEEG18.3.183","usgsCitation":"Zelt, C.A., Haines, S., Powers, M.H., Sheehan, J., Rohdewald, S., Link, C., Hayashi, K., Zhao, D., Zhou, H., Burton, B., Petersen, U.K., Bonal, N.D., and Doll, W.E., 2013, Blind test of methods for obtaining 2-D near-surface seismic velocity models from first-arrival traveltimes: Journal of Environmental & Engineering Geophysics, v. 18, no. 3, p. 183-194, https://doi.org/10.2113/JEEG18.3.183.","productDescription":"12 p.","startPage":"183","endPage":"194","ipdsId":"IP-043837","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":282370,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2113/JEEG18.3.183"},{"id":282371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4fa1e4b0b290850f2d42","contributors":{"authors":[{"text":"Zelt, Colin A.","contributorId":99461,"corporation":false,"usgs":true,"family":"Zelt","given":"Colin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":490258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haines, Seth 0000-0003-2611-8165","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":97814,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","affiliations":[],"preferred":false,"id":490257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sheehan, Jacob","contributorId":75059,"corporation":false,"usgs":true,"family":"Sheehan","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":490256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohdewald, Siegfried","contributorId":64554,"corporation":false,"usgs":true,"family":"Rohdewald","given":"Siegfried","email":"","affiliations":[],"preferred":false,"id":490255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Link, Curtis","contributorId":6368,"corporation":false,"usgs":true,"family":"Link","given":"Curtis","email":"","affiliations":[],"preferred":false,"id":490248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hayashi, Koichi","contributorId":22675,"corporation":false,"usgs":true,"family":"Hayashi","given":"Koichi","email":"","affiliations":[],"preferred":false,"id":490251,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhao, Don","contributorId":58182,"corporation":false,"usgs":true,"family":"Zhao","given":"Don","email":"","affiliations":[],"preferred":false,"id":490254,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zhou, Hua-wei","contributorId":11504,"corporation":false,"usgs":true,"family":"Zhou","given":"Hua-wei","email":"","affiliations":[],"preferred":false,"id":490249,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Burton, Bethany L. 0000-0001-5011-7862 blburton@usgs.gov","orcid":"https://orcid.org/0000-0001-5011-7862","contributorId":1341,"corporation":false,"usgs":true,"family":"Burton","given":"Bethany L.","email":"blburton@usgs.gov","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":490247,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Petersen, Uni K.","contributorId":34037,"corporation":false,"usgs":true,"family":"Petersen","given":"Uni","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":490253,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bonal, Nedra D.","contributorId":26620,"corporation":false,"usgs":true,"family":"Bonal","given":"Nedra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":490252,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Doll, William E.","contributorId":20249,"corporation":false,"usgs":true,"family":"Doll","given":"William","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":490250,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70155070,"text":"70155070 - 2013 - Quantitative and qualitative approaches to identifying migration chronology in a continental migrant","interactions":[],"lastModifiedDate":"2015-08-05T13:01:35","indexId":"70155070","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative and qualitative approaches to identifying migration chronology in a continental migrant","docAbstract":"<p>The degree to which extrinsic factors influence migration chronology in North American waterfowl has not been quantified, particularly for dabbling ducks. Previous studies have examined waterfowl migration using various methods, however, quantitative approaches to define avian migration chronology over broad spatio-temporal scales are limited, and the implications for using different approaches have not been assessed. We used movement data from 19 female adult mallards (Anas platyrhynchos) equipped with solar-powered global positioning system satellite transmitters to evaluate two individual level approaches for quantifying migration chronology. The first approach defined migration based on individual movements among geopolitical boundaries (state, provincial, international), whereas the second method modeled net displacement as a function of time using nonlinear models. Differences in migration chronologies identified by each of the approaches were examined with analysis of variance. The geopolitical method identified mean autumn migration midpoints at 15 November 2010 and 13 November 2011, whereas the net displacement method identified midpoints at 15 November 2010 and 14 November 2011. The mean midpoints for spring migration were 3 April 2011 and 20 March 2012 using the geopolitical method and 31 March 2011 and 22 March 2012 using the net displacement method. The duration, initiation date, midpoint, and termination date for both autumn and spring migration did not differ between the two individual level approaches. Although we did not detect differences in migration parameters between the different approaches, the net displacement metric offers broad potential to address questions in movement ecology for migrating species. Ultimately, an objective definition of migration chronology will allow researchers to obtain a comprehensive understanding of the extrinsic factors that drive migration at the individual and population levels. As a result, targeted conservation plans can be developed to support planning for habitat management and evaluation of long-term climate effects.</p>","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0075673","usgsCitation":"Beatty, W.S., Kesler, D.C., Webb, E.B., Raedeke, A.H., Naylor, L.W., and Humburg, D.D., 2013, Quantitative and qualitative approaches to identifying migration chronology in a continental migrant: PLoS ONE, p. 1-9, https://doi.org/10.1371/journal.pone.0075673.","productDescription":"e75673; 9 p.","startPage":"1","endPage":"9","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-09-01","temporalEnd":"2012-12-31","ipdsId":"IP-045956","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473373,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0075673","text":"Publisher Index Page"},{"id":306440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-10-09","publicationStatus":"PW","scienceBaseUri":"57f7f1d6e4b0bc0bec0a0024","contributors":{"authors":[{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":146301,"corporation":false,"usgs":false,"family":"Beatty","given":"William","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":567383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kesler, Dylan C.","contributorId":14358,"corporation":false,"usgs":false,"family":"Kesler","given":"Dylan","email":"","middleInitial":"C.","affiliations":[{"id":6769,"text":"University of Missouri, Columbia, MO","active":true,"usgs":false}],"preferred":false,"id":567384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":564764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raedeke, Andrew H.","contributorId":94083,"corporation":false,"usgs":true,"family":"Raedeke","given":"Andrew","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":567385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Naylor, Luke W.","contributorId":145840,"corporation":false,"usgs":false,"family":"Naylor","given":"Luke","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":567386,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":567387,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192303,"text":"70192303 - 2013 - Fifty years after Welles and Welles: Distribution and genetic structure of Desert Bighorn Sheep in Death Valley National Park","interactions":[],"lastModifiedDate":"2018-02-27T11:20:41","indexId":"70192303","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Fifty years after Welles and Welles: Distribution and genetic structure of Desert Bighorn Sheep in Death Valley National Park","docAbstract":"The status of desert bighorn sheep (Ovis canadensis nelsoni) populations in the mountains around Death Valley was first evaluated in 1938, shortly after designation of Death Valley National Monument. However, the most comprehensive evaluation of bighorn sheep in the region was conducted by Ralph and Florence Welles during 1955-1961. They documented patterns of use at water sources and other focal areas around Death Valley and roughly estimated numbers of bighorn sheep from observational data. Data collection on bighorn sheep in the area since that time has\nlacked a regional approach needed to address metapopulation questions.From 2011-2013, we evaluated bighorn activity at important water sources and other likely locations around Death Valley using remote cameras and observations of tracks, beds, sign, and bighorn sheep, and non-invasively collected genetic samples (fecal pellets and bones).\nWhere possible, we revisited many of the water sources and other locations originally investigated by Welles and Welles (1961) and earlier researchers. We extracted DNA from fecal pellets, carcass tissue samples, and blood samples archived from earlier captures and genotyped them using highly variable genetic markers (15 microsatellite loci) with sufficient power to distinguish individuals and characterize gene flow and genetic structure. We also analyzed DNA samples collected from other bighorn sheep populations extending north to the White Mountains, west to the Inyo Mountains, south to the Avawatz Mountains, and southeast to the Clark Mountain Range, Kingston Range, and Spring Mountains of Nevada. We estimated genetic structure and recent gene flow among nearly all known populations of bighorn sheep in and around Death Valley National Park (DEVA), and used assignment tests to evaluate individual and population-level genetic structure to infer connectivity across the region. We found that bighorn sheep are still widely distributed in mountain ranges throughout DEVA, including many of the areas described by Welles and Welles (1961), although some use patterns appear to have changed and other areas still require resurvey. Gene flow was relatively high through some sections of fairly continuous habitat, such as the Grapevine and Funeral Mountains along the eastern side of Death Valley, but other populations were more isolated. Genetic diversity was relatively high throughout the park. Although southern Death Valley populations were genetically distinct from populations to the southeast, population assignment tests and recent gene flow estimates suggested that individuals occasionally migrate between those regions, indicating the potential for the recent outbreak of respiratory disease in the southern Mojave Desert to spread into the Death Valley system. We recommend careful monitoring of bighorn sheep using remote cameras to check for signs of respiratory disease in southeastern DEVA and ground surveys in the still-understudied southwestern part of DEVA.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"1st Death Valley Natural History Conference Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Death Valley National History Association","usgsCitation":"Epps, C.W., Wehausen, J.D., Sloan, W.B., Holt, S., Creech, T.G., Crowhurst, R.S., Jaeger, J.R., Longshore, K.M., and Monello, R.J., 2013, Fifty years after Welles and Welles: Distribution and genetic structure of Desert Bighorn Sheep in Death Valley National Park, <i>in</i> 1st Death Valley Natural History Conference Proceedings.","ipdsId":"IP-056088","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":352068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347251,"type":{"id":15,"text":"Index Page"},"url":"https://dvnha.org/opencart/index.php?route=product/product&product_id=768&search=proceedings+Death+Valley+Natural+History+Conference"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeefd7e4b0da30c1bfc798","contributors":{"authors":[{"text":"Epps, Clinton W.","contributorId":198148,"corporation":false,"usgs":false,"family":"Epps","given":"Clinton","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":715207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wehausen, John D.","contributorId":198149,"corporation":false,"usgs":false,"family":"Wehausen","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":715208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sloan, William B.","contributorId":198150,"corporation":false,"usgs":false,"family":"Sloan","given":"William","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":715209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holt, Stacy","contributorId":198151,"corporation":false,"usgs":false,"family":"Holt","given":"Stacy","email":"","affiliations":[],"preferred":false,"id":715210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Creech, Tyler G.","contributorId":198152,"corporation":false,"usgs":false,"family":"Creech","given":"Tyler","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":715211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crowhurst, Rachel S.","contributorId":198153,"corporation":false,"usgs":false,"family":"Crowhurst","given":"Rachel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":715212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jaeger, Jef R.","contributorId":198154,"corporation":false,"usgs":false,"family":"Jaeger","given":"Jef","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":715213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Longshore, Kathleen M. 0000-0001-6621-1271 longshore@usgs.gov","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":2677,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"longshore@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":715206,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Monello, Ryan J.","contributorId":184143,"corporation":false,"usgs":false,"family":"Monello","given":"Ryan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":715214,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70171458,"text":"70171458 - 2013 - Emulating natural disturbances for declining late-successional species: A case study of the consequences for Cerulean Warblers (<i>Setophaga cerulea</i>)","interactions":[],"lastModifiedDate":"2016-05-31T15:39:54","indexId":"70171458","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Emulating natural disturbances for declining late-successional species: A case study of the consequences for Cerulean Warblers (<i>Setophaga cerulea</i>)","docAbstract":"<p><span>Forest cover in the eastern United States has increased over the past century and while some late-successional species have benefited from this process as expected, others have experienced population declines. These declines may be in part related to contemporary reductions in small-scale forest interior disturbances such as fire, windthrow, and treefalls. To mitigate the negative impacts of disturbance alteration and suppression on some late-successional species, strategies that emulate natural disturbance regimes are often advocated, but large-scale evaluations of these practices are rare. Here, we assessed the consequences of experimental disturbance (using partial timber harvest) on a severely declining late-successional species, the cerulean warbler (</span><i>Setophaga cerulea</i><span>), across the core of its breeding range in the Appalachian Mountains. We measured numerical (density), physiological (body condition), and demographic (age structure and reproduction) responses to three levels of disturbance and explored the potential impacts of disturbance on source-sink dynamics. Breeding densities of warblers increased one to four years after all canopy disturbances (vs. controls) and males occupying territories on treatment plots were in better condition than those on control plots. However, these beneficial effects of disturbance did not correspond to improvements in reproduction; nest success was lower on all treatment plots than on control plots in the southern region and marginally lower on light disturbance plots in the northern region. Our data suggest that only habitats in the southern region acted as sources, and interior disturbances in this region have the potential to create ecological traps at a local scale, but sources when viewed at broader scales. Thus, cerulean warblers would likely benefit from management that strikes a landscape-level balance between emulating natural disturbances in order to attract individuals into areas where current structure is inappropriate, and limiting anthropogenic disturbance in forests that already possess appropriate structural attributes in order to maintain maximum productivity.</span></p>","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0052107","usgsCitation":"Boves, T.J., Buehler, D.A., Sheehan, J., Wood, P.B., Rodewald, A.D., Larkin, J.L., Keyser, P.D., Newell, F.L., George, G.A., Bakermans, M.H., Evans, A., Beachy, T.A., McDermott, M., Perkins, K.A., White, M., and Wigley, T.B., 2013, Emulating natural disturbances for declining late-successional species: A case study of the consequences for Cerulean Warblers (<i>Setophaga cerulea</i>): PLoS ONE, v. 8, no. 1, p. 1-13, https://doi.org/10.1371/journal.pone.0052107.","productDescription":"e52107; 13 p.","startPage":"1","endPage":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037905","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0052107","text":"Publisher Index Page"},{"id":321945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-01-04","publicationStatus":"PW","scienceBaseUri":"574eb5c4e4b0ee97d51a83b2","contributors":{"authors":[{"text":"Boves, Than J.","contributorId":169750,"corporation":false,"usgs":false,"family":"Boves","given":"Than","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":631075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buehler, David A.","contributorId":169746,"corporation":false,"usgs":false,"family":"Buehler","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":631072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheehan, James","contributorId":169745,"corporation":false,"usgs":false,"family":"Sheehan","given":"James","email":"","affiliations":[],"preferred":false,"id":631073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Petra Bohall pbwood@usgs.gov","contributorId":1791,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"Bohall","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":631070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodewald, Amanda D.","contributorId":169748,"corporation":false,"usgs":false,"family":"Rodewald","given":"Amanda","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":631071,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Larkin, Jeffrey L.","contributorId":169747,"corporation":false,"usgs":false,"family":"Larkin","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":34542,"text":"Department of Biology. Indiana University of Pennsylvania","active":true,"usgs":false},{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":631074,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keyser, Patrick D.","contributorId":146945,"corporation":false,"usgs":false,"family":"Keyser","given":"Patrick","email":"","middleInitial":"D.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":631109,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Newell, Felicity L.","contributorId":169755,"corporation":false,"usgs":false,"family":"Newell","given":"Felicity","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":631110,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"George, Gregory A.","contributorId":169751,"corporation":false,"usgs":false,"family":"George","given":"Gregory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631111,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bakermans, Marja H.","contributorId":169752,"corporation":false,"usgs":false,"family":"Bakermans","given":"Marja","email":"","middleInitial":"H.","affiliations":[{"id":33354,"text":"Worcester Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":631112,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Evans, Andrea","contributorId":169754,"corporation":false,"usgs":false,"family":"Evans","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":631113,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Beachy, Tiffany A.","contributorId":169753,"corporation":false,"usgs":false,"family":"Beachy","given":"Tiffany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631114,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McDermott, Molly E. 0000-0002-0000-0831","orcid":"https://orcid.org/0000-0002-0000-0831","contributorId":169743,"corporation":false,"usgs":false,"family":"McDermott","given":"Molly E.","affiliations":[],"preferred":false,"id":631115,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Perkins, Kelly A.","contributorId":169756,"corporation":false,"usgs":false,"family":"Perkins","given":"Kelly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631116,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"White, Matthew","contributorId":169757,"corporation":false,"usgs":false,"family":"White","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":631117,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wigley, T. Bently","contributorId":169749,"corporation":false,"usgs":false,"family":"Wigley","given":"T.","email":"","middleInitial":"Bently","affiliations":[],"preferred":false,"id":631118,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70173625,"text":"70173625 - 2013 - Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010","interactions":[],"lastModifiedDate":"2016-06-09T15:10:12","indexId":"70173625","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010","docAbstract":"<p><span>Water clarity is a strong indicator of regional water quality. Unlike other common water-quality metrics, such as chlorophyll&nbsp;</span><i>a</i><span>, total P, or trophic status, clarity can be accurately and efficiently estimated remotely on a regional scale. Satellite-based remote sensing is useful in regions with many lakes where traditional field-sampling techniques may be prohibitively expensive. Repeated sampling of easily accessed lakes can lead to spatially irregular, nonrandom samples of a region. Remote sensing remedies this problem. We applied a remote monitoring protocol we had previously developed for Maine lakes &gt;8&nbsp;ha based on Landsat satellite data recorded during 1995&ndash;2010 to identify spatial and temporal patterns in Maine lake clarity. We focused on the overlapping region of Landsat paths 11 and 12 to increase availability of cloud-free images in August and early September, a period of relative lake stability and seasonal poor-clarity conditions well suited for annual monitoring. We divided Maine into 3 regions (northeastern, south-central, western) based on morphometric and chemical lake features. We found a general decrease in average statewide lake clarity from 4.94 to 4.38&nbsp;m during 1995&ndash;2010. Water clarity ranged from 4 to 6&nbsp;m during 1995&ndash;2010, but it decreased consistently during 2005&ndash;2010. Clarity in both the northeastern and western lake regions has decreased from 5.22&nbsp;m in 1995 to 4.36 and 4.21&nbsp;m, respectively, in 2010, whereas lake clarity in the south-central lake region (4.50&nbsp;m) has not changed since 1995. Climate change, timber harvesting, or watershed morphometry may be responsible for regional water-clarity decline. Remote sensing of regional water clarity provides a more complete spatial perspective of lake water quality than existing, interest-based sampling. However, field sampling done under existing monitoring programs can be used to calibrate accurate models designed to estimate water clarity remotely.</span></p>","language":"English","publisher":"The University of Chicago Press","doi":"10.1899/12-070.1","usgsCitation":"McCullough, I.M., Loftin, C., and Sader, S., 2013, Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010: Freshwater Science, v. 32, no. 3, p. 741-752, https://doi.org/10.1899/12-070.1.","productDescription":"12 p.","startPage":"741","endPage":"752","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1995-01-01","ipdsId":"IP-036854","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"32","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575a9333e4b04f417c275162","contributors":{"authors":[{"text":"McCullough, Ian M.","contributorId":149952,"corporation":false,"usgs":false,"family":"McCullough","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":638297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cynthia S. 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":2167,"corporation":false,"usgs":true,"family":"Loftin","given":"Cynthia S.","email":"cyndy_loftin@usgs.gov","affiliations":[],"preferred":true,"id":637416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sader, Steven A.","contributorId":112282,"corporation":false,"usgs":true,"family":"Sader","given":"Steven A.","affiliations":[],"preferred":false,"id":638298,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70173432,"text":"70173432 - 2013 - Accuracy of stream habitat interpolations across spatial scales","interactions":[],"lastModifiedDate":"2016-06-21T16:13:26","indexId":"70173432","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5095,"text":"Journal of Geographic Information System","active":true,"publicationSubtype":{"id":10}},"title":"Accuracy of stream habitat interpolations across spatial scales","docAbstract":"<p>Stream habitat data are often collected across spatial scales because relationships among habitat, species occurrence, and management plans are linked at multiple spatial scales. Unfortunately, scale is often a factor limiting insight gained from spatial analysis of stream habitat data. Considerable cost is often expended to collect data at several spatial scales to provide accurate evaluation of spatial relationships in streams. To address utility of single scale set of stream habitat data used at varying scales, we examined the influence that data scaling had on accuracy of natural neighbor predictions of depth, flow, and benthic substrate. To achieve this goal, we measured two streams at gridded resolution of 0.33 &times; 0.33 meter cell size over a combined area of 934 m2 to create a baseline for natural neighbor interpolated maps at 12 incremental scales ranging from a raster cell size of 0.11 m2 to 16 m2 . Analysis of predictive maps showed a logarithmic linear decay pattern in RMSE values in interpolation accuracy for variables as resolution of data used to interpolate study areas became coarser. Proportional accuracy of interpolated models (r2 ) decreased, but it was maintained up to 78% as interpolation scale moved from 0.11 m2 to 16 m2 . Results indicated that accuracy retention was suitable for assessment and management purposes at various scales different from the data collection scale. Our study is relevant to spatial modeling, fish habitat assessment, and stream habitat management because it highlights the potential of using a single dataset to fulfill analysis needs rather than investing considerable cost to develop several scaled datasets.</p>","language":"English","publisher":"Scientific Research","doi":"10.4236/jgis.2013.56057","usgsCitation":"Sheehan, K.R., and Welsh, S., 2013, Accuracy of stream habitat interpolations across spatial scales: Journal of Geographic Information System, v. 5, p. 606-612, https://doi.org/10.4236/jgis.2013.56057.","productDescription":"7 p.","startPage":"606","endPage":"612","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033558","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473384,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/jgis.2013.56057","text":"Publisher Index Page"},{"id":324171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a652fe4b07657d1a11cee","contributors":{"authors":[{"text":"Sheehan, Kenneth R.","contributorId":146541,"corporation":false,"usgs":false,"family":"Sheehan","given":"Kenneth","email":"","middleInitial":"R.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":637126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":637125,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70171457,"text":"70171457 - 2013 - Comparison of point counts and territory mapping for detecting effects of forest management on songbirds","interactions":[],"lastModifiedDate":"2016-05-31T15:45:42","indexId":"70171457","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of point counts and territory mapping for detecting effects of forest management on songbirds","docAbstract":"<p><span>Point counts are commonly used to assess changes in bird abundance, including analytical approaches such as distance sampling that estimate density. Point-count methods have come under increasing scrutiny because effects of detection probability and field error are difficult to quantify. For seven forest songbirds, we compared fixed-radii counts (50 m and 100 m) and density estimates obtained from distance sampling to known numbers of birds determined by territory mapping. We applied point-count analytic approaches to a typical forest management question and compared results to those obtained by territory mapping. We used a before&ndash;after control impact (BACI) analysis with a data set collected across seven study areas in the central Appalachians from 2006 to 2010. Using a 50-m fixed radius, variance in error was at least 1.5 times that of the other methods, whereas a 100-m fixed radius underestimated actual density by &gt;3 territories per 10 ha for the most abundant species. Distance sampling improved accuracy and precision compared to fixed-radius counts, although estimates were affected by birds counted outside 10-ha units. In the BACI analysis, territory mapping detected an overall treatment effect for five of the seven species, and effects were generally consistent each year. In contrast, all point-count methods failed to detect two treatment effects due to variance and error in annual estimates. Overall, our results highlight the need for adequate sample sizes to reduce variance, and skilled observers to reduce the level of error in point-count data. Ultimately, the advantages and disadvantages of different survey methods should be considered in the context of overall study design and objectives, allowing for trade-offs among effort, accuracy, and power to detect treatment effects.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12026","usgsCitation":"Newell, F.L., Sheehan, J., Wood, P.B., Rodewald, A.D., Buehler, D.A., Keyser, P.D., Larkin, J.L., Beachy, T.A., Bakermans, M.H., Boves, T.J., Evans, A., George, G.A., McDermott, M., Perkins, K.A., White, M., and Wigley, T.B., 2013, Comparison of point counts and territory mapping for detecting effects of forest management on songbirds: Journal of Field Ornithology, v. 84, no. 3, p. 270-286, https://doi.org/10.1111/jofo.12026.","productDescription":"17 p.","startPage":"270","endPage":"286","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038461","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":321946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-08-23","publicationStatus":"PW","scienceBaseUri":"574eb5bae4b0ee97d51a83a2","contributors":{"authors":[{"text":"Newell, Felicity L.","contributorId":169755,"corporation":false,"usgs":false,"family":"Newell","given":"Felicity","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":631121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheehan, James","contributorId":169745,"corporation":false,"usgs":false,"family":"Sheehan","given":"James","email":"","affiliations":[],"preferred":false,"id":631122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Petra Bohall pbwood@usgs.gov","contributorId":1791,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"Bohall","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":631123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodewald, Amanda D.","contributorId":169748,"corporation":false,"usgs":false,"family":"Rodewald","given":"Amanda","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":631124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buehler, David A.","contributorId":169746,"corporation":false,"usgs":false,"family":"Buehler","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":631125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keyser, Patrick D.","contributorId":146945,"corporation":false,"usgs":false,"family":"Keyser","given":"Patrick","email":"","middleInitial":"D.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":631126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Larkin, Jeffrey L.","contributorId":169747,"corporation":false,"usgs":false,"family":"Larkin","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false},{"id":34542,"text":"Department of Biology. Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":631127,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Beachy, Tiffany A.","contributorId":169753,"corporation":false,"usgs":false,"family":"Beachy","given":"Tiffany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631128,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bakermans, Marja H.","contributorId":169752,"corporation":false,"usgs":false,"family":"Bakermans","given":"Marja","email":"","middleInitial":"H.","affiliations":[{"id":33354,"text":"Worcester Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":631129,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Boves, Than J.","contributorId":169750,"corporation":false,"usgs":false,"family":"Boves","given":"Than","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":631130,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Evans, Andrea","contributorId":169754,"corporation":false,"usgs":false,"family":"Evans","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":631131,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"George, Gregory A.","contributorId":169751,"corporation":false,"usgs":false,"family":"George","given":"Gregory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631132,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McDermott, Molly E. 0000-0002-0000-0831","orcid":"https://orcid.org/0000-0002-0000-0831","contributorId":169743,"corporation":false,"usgs":false,"family":"McDermott","given":"Molly E.","affiliations":[],"preferred":false,"id":631133,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Perkins, Kelly A.","contributorId":169756,"corporation":false,"usgs":false,"family":"Perkins","given":"Kelly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631134,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"White, Matthew","contributorId":169757,"corporation":false,"usgs":false,"family":"White","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":631135,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wigley, T. Bently","contributorId":169749,"corporation":false,"usgs":false,"family":"Wigley","given":"T.","email":"","middleInitial":"Bently","affiliations":[],"preferred":false,"id":631136,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70192414,"text":"70192414 - 2013 - Rapid chemical evolution of tropospheric volcanic emissions from Redoubt Volcano, Alaska, based on observations of ozone and halogen-containing gases","interactions":[],"lastModifiedDate":"2017-10-25T15:11:01","indexId":"70192414","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Rapid chemical evolution of tropospheric volcanic emissions from Redoubt Volcano, Alaska, based on observations of ozone and halogen-containing gases","docAbstract":"<p><span>We report results from an observational and modeling study of reactive chemistry in the tropospheric plume emitted by Redoubt Volcano, Alaska. Our measurements include the first observations of Br and I degassing from an Alaskan volcano, the first study of O</span><sub>3</sub><span><span>&nbsp;</span>evolution in a volcanic plume, as well as the first detection of BrO in the plume of a passively degassing Alaskan volcano. This study also represents the first detailed spatially-resolved comparison of measured and modeled O</span><sub>3</sub><span><span>&nbsp;</span>depletion in a volcanic plume. The composition of the plume was measured on June 20, 2010 using base-treated filter packs (for F, Cl, Br, I, and S) at the crater rim and by an instrumented fixed-wing aircraft on June 21 and August 19, 2010. The aircraft was used to track the chemical evolution of the plume up to ~</span><span>&nbsp;</span><span>30</span><span>&nbsp;</span><span>km downwind (2</span><span>&nbsp;</span><span>h plume travel time) from the volcano and was equipped to make in situ observations of O</span><sub>3</sub><span>, water vapor, CO</span><sub>2</sub><span>, SO</span><sub>2</sub><span>, and H</span><sub>2</sub><span>S during both flights plus remote spectroscopic observations of SO</span><sub>2</sub><span><span>&nbsp;</span>and BrO on the August 19th flight. The airborne data from June 21 reveal rapid chemical O</span><sub>3</sub><span><span>&nbsp;</span>destruction in the plume as well as the strong influence chemical heterogeneity in background air had on plume composition. Spectroscopic retrievals from airborne traverses made under the plume on August 19 show that BrO was present ~</span><span>&nbsp;</span><span>6</span><span>&nbsp;</span><span>km downwind (20</span><span>&nbsp;</span><span>min plume travel time) and in situ measurements revealed several ppbv of O</span><sub>3</sub><span><span>&nbsp;</span>loss near the center of the plume at a similar location downwind. Simulations with the<span>&nbsp;</span></span><i>PlumeChem</i><span><span>&nbsp;</span>model reproduce the timing and magnitude of the observed O</span><sub>3</sub><span><span>&nbsp;</span>deficits and suggest that autocatalytic release of reactive bromine and in-plume formation of BrO were primarily responsible for the observed O</span><sub>3</sub><span><span>&nbsp;</span>destruction in the plume. The measurements are therefore in general agreement with recent model studies of reactive halogen formation in volcanic plumes, but also show that field studies must pay close attention to variations in the composition of ambient air entrained into volcanic plumes in order to unambiguously attribute observed O</span><sub>3</sub><span><span>&nbsp;</span>anomalies to specific chemical or dynamic processes. Our results suggest that volcanic eruptions in Alaska are sources of reactive halogen species to the subarctic troposphere.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2012.04.023","usgsCitation":"Werner, C.A., Kelly, P.J., Kern, C., Roberts, T., and Aluppe, A., 2013, Rapid chemical evolution of tropospheric volcanic emissions from Redoubt Volcano, Alaska, based on observations of ozone and halogen-containing gases: Journal of Volcanology and Geothermal Research, v. 259, p. 317-333, https://doi.org/10.1016/j.jvolgeores.2012.04.023.","productDescription":"17 p.","startPage":"317","endPage":"333","ipdsId":"IP-035796","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473392,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10447/99077","text":"External Repository"},{"id":347388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Redoubt Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -154,\n              59\n            ],\n            [\n              -149,\n              59\n            ],\n            [\n              -149,\n              62\n            ],\n            [\n              -154,\n              62\n            ],\n            [\n              -154,\n              59\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"259","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a9e4b0220bbd9d9fa8","contributors":{"authors":[{"text":"Werner, Cynthia A. cwerner@usgs.gov","contributorId":2540,"corporation":false,"usgs":true,"family":"Werner","given":"Cynthia","email":"cwerner@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":715744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":715747,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":715746,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Roberts, T.J.","contributorId":198344,"corporation":false,"usgs":false,"family":"Roberts","given":"T.J.","email":"","affiliations":[],"preferred":false,"id":715748,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Aluppe, A.","contributorId":198341,"corporation":false,"usgs":false,"family":"Aluppe","given":"A.","email":"","affiliations":[],"preferred":false,"id":715745,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70192301,"text":"70192301 - 2013 - Black bear density in Glacier National Park, Montana","interactions":[],"lastModifiedDate":"2017-10-26T09:57:40","indexId":"70192301","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Black bear density in Glacier National Park, Montana","docAbstract":"<p>We report the first abundance and density estimates for American black bears (<i>Ursus americanus</i>) in Glacier National Park (NP),Montana, USA.We used data from 2 independent and concurrent noninvasive genetic sampling methods—hair traps and bear rubs—collected during 2004 to generate individual black bear encounter histories for use in closed population mark–recapture models. We improved the precision of our abundance estimate by using noninvasive genetic detection events to develop individual-level covariates of sampling effort within the full and one-half mean maximum distance moved (MMDM) from each bear’s estimated activity center to explain capture probability heterogeneity and inform our estimate of the effective sampling area.Models including the one-halfMMDMcovariate received overwhelming Akaike’s Information Criterion support suggesting that buffering our study area by this distance would be more appropriate than no buffer or the full MMDM buffer for estimating the effectively sampled area and thereby density. Our modelaveraged super-population abundance estimate was 603 (95% CI¼522–684) black bears for Glacier NP. Our black bear density estimate (11.4 bears/100 km2, 95% CI¼9.9–13.0) was consistent with published estimates for populations that are sympatric with grizzly bears (U. arctos) and without access to spawning salmonids. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.</p>","language":"English","publisher":"Wiley","doi":"10.1002/wsb.356","usgsCitation":"Stetz, J.B., Kendall, K.C., and Macleod, A.C., 2013, Black bear density in Glacier National Park, Montana: Wildlife Society Bulletin, v. 38, no. 1, p. 60-70, https://doi.org/10.1002/wsb.356.","productDescription":"11 p.","startPage":"60","endPage":"70","ipdsId":"IP-045361","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":500011,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/bbe229248951484a85366b0798f527ef","text":"External Repository"},{"id":347347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.0543212890625,\n              49.001843917978526\n            ],\n            [\n              -114.993896484375,\n              48.929717630629554\n            ],\n            [\n              -114.884033203125,\n              48.89722676235673\n            ],\n            [\n              -114.72473144531251,\n              48.8936153614802\n            ],\n            [\n              -114.72473144531251,\n              48.79600890414036\n            ],\n            [\n              -114.697265625,\n              48.72358515157852\n            ],\n            [\n              -114.47753906249999,\n              48.56024979174329\n            ],\n            [\n              -114.3182373046875,\n              48.46199462233164\n            ],\n            [\n              -114.1644287109375,\n              48.46563710044979\n            ],\n            [\n              -114.0216064453125,\n              48.50932644976633\n            ],\n            [\n              -113.93920898437499,\n              48.50932644976633\n            ],\n            [\n              -113.8128662109375,\n              48.44013426398058\n            ],\n            [\n              -113.7744140625,\n              48.40367941865281\n            ],\n            [\n              -113.69750976562499,\n              48.334343174592014\n            ],\n            [\n              -113.65905761718749,\n              48.26491251331118\n            ],\n            [\n              -113.521728515625,\n              48.25759852914997\n            ],\n            [\n              -113.31298828125,\n              48.29781249243716\n            ],\n            [\n              -113.258056640625,\n              48.425555463221066\n            ],\n            [\n              -113.41735839843749,\n              48.69096039092549\n            ],\n            [\n              -113.4283447265625,\n              48.73807825631017\n            ],\n            [\n              -113.48876953125,\n              48.76343113791796\n            ],\n            [\n              -113.62060546875,\n              48.94415123418794\n            ],\n            [\n              -113.609619140625,\n              48.99463598353405\n            ],\n            [\n              -115.0543212890625,\n              49.001843917978526\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"38","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-08","publicationStatus":"PW","scienceBaseUri":"59f1a2a9e4b0220bbd9d9fb9","contributors":{"authors":[{"text":"Stetz, Jeff B.","contributorId":198142,"corporation":false,"usgs":false,"family":"Stetz","given":"Jeff","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":715190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, Katherine C. 0000-0002-4831-2287 kkendall@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-2287","contributorId":3081,"corporation":false,"usgs":true,"family":"Kendall","given":"Katherine","email":"kkendall@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":715188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macleod, Amy C.","contributorId":198141,"corporation":false,"usgs":false,"family":"Macleod","given":"Amy","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":715189,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70059790,"text":"70059790 - 2013 - Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA","interactions":[],"lastModifiedDate":"2018-09-18T16:29:07","indexId":"70059790","displayToPublicDate":"2013-12-30T14:56:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":836,"text":"Applied Geography","active":true,"publicationSubtype":{"id":10}},"title":"Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA","docAbstract":"Riparian vegetation provides important wildlife habitat in the Southwestern United States, but limited distributions and spatial complexity often leads to inaccurate representation in maps used to guide conservation. We test the use of data conflation and aggregation on multiple vegetation/land-cover maps to improve the accuracy of habitat models for the threatened western yellow-billed cuckoo (Coccyzus americanus occidentalis). We used species observations (n = 479) from a state-wide survey to develop habitat models from 1) three vegetation/land-cover maps produced at different geographic scales ranging from state to national, and 2) new aggregate maps defined by the spatial agreement of cover types, which were defined as high (agreement = all data sets), moderate (agreement ≥ 2), and low (no agreement required). Model accuracies, predicted habitat locations, and total area of predicted habitat varied considerably, illustrating the effects of input data quality on habitat predictions and resulting potential impacts on conservation planning. Habitat models based on aggregated and conflated data were more accurate and had higher model sensitivity than original vegetation/land-cover, but this accuracy came at the cost of reduced geographic extent of predicted habitat. Using the highest performing models, we assessed cuckoo habitat preference and distribution in Arizona and found that major watersheds containing high-probably habitat are fragmented by a wide swath of low-probability habitat. Focus on riparian restoration in these areas could provide more breeding habitat for the threatened cuckoo, offset potential future habitat losses in adjacent watershed, and increase regional connectivity for other threatened vertebrates that also use riparian corridors.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeog.2013.12.003","usgsCitation":"Villarreal, M., van Riper, C., and Petrakis, R., 2013, Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA: Applied Geography, v. 47, p. 57-69, https://doi.org/10.1016/j.apgeog.2013.12.003.","productDescription":"13 p.","startPage":"57","endPage":"69","numberOfPages":"13","ipdsId":"IP-048880","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":280568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280567,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeog.2013.12.003"}],"country":"United States","state":"Arizona","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.8184,31.3322 ], [ -114.8184,37.0043 ], [ -109.0452,37.0043 ], [ -109.0452,31.3322 ], [ -114.8184,31.3322 ] ] ] } } ] }","volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c29607e4b040b25da903da","contributors":{"authors":[{"text":"Villarreal, Miguel L.","contributorId":107012,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel L.","affiliations":[],"preferred":false,"id":487828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":487826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petrakis, Roy E.","contributorId":46868,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy E.","affiliations":[],"preferred":false,"id":487827,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70056564,"text":"sir20105070G - 2013 - Descriptive and geoenvironmental model for Co-Cu-Au deposits in metasedimentary rocks","interactions":[],"lastModifiedDate":"2022-12-12T23:19:59.000786","indexId":"sir20105070G","displayToPublicDate":"2013-12-30T13:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5070","chapter":"G","title":"Descriptive and geoenvironmental model for Co-Cu-Au deposits in metasedimentary rocks","docAbstract":"<h1>Introduction</h1><p>This report is a revised model for a specific type of cobalt-copper-gold (Co-Cu-Au) deposit that will be evaluated in the next U.S. Geological Survey (USGS) assessment of undiscovered mineral resources in the United States (see Ferrero and others, 2012). Emphasis is on providing an up-to-date deposit model that includes both geologic and geoenvironmental aspects. The new model presented here supersedes previous USGS models by Earhart (1986) and Evans and others (1995), which are based solely on deposits in the Blackbird mining district of central Idaho. This report is a broader synthesis of information on 19 Co-Cu-Au deposits occurring in predominantly metasedimentary successions worldwide (table 1–1) that generally share common geologic, mineralogical, and geochemical features; preliminary summary versions were presented in Slack and others (2010) and Slack and others (2011), which are superseded by this report. As defined herein, the individual Co-Cu-Au deposits are located more than 500 meters from similar deposits and contain 0.1 percent or more by weight of Co in ore or mineralized rock; some deposits included in the database lack reported average Co grades, but they contain high Co concentrations, at least locally. Most of the deposits also have high As contents, present in Co arsenide and sulfarsenide minerals. Type examples of the Co-Cu-Au deposits are those in the Blackbird district, Skuterud in Norway, and Kouvervarra and Juomasuo in Finland. Some deposits in the database have low grades for Cu (for example, NICO in Canada) or Au (for example, Lemmonlampi in Finland), but these deposits are included because their geological, mineralogical, and alteration features are similar to those of the type examples. Several deposits included in the model are partly hosted by metavolcanic or metaigneous rocks (including granite), but regionally these deposits are within metasedimentary successions; no deposits are wholly within granite or other plutonic igneous intrusions.</p><p>Despite having a lower average Co grade, the Mt. Cobalt deposit in Australia is included here because it has past Co production from higher-grade ore zones (Nisbet and others, 1983). The Black Pine deposit in the Idaho cobalt belt is included because it contains mineable Co- and Au-rich lenses within Cu-rich mineralized zones (Formation Metals, Inc., 2012). Six deposits that lack data for average Co grades are also included because each reportedly contains abundant Co (&gt;0.1 weight percent Co), at least locally. Many of the deposits are noteworthy as possible resources of Ag, Bi, W, Ni, Y, REE, and (or) U. Detailed data on the deposits listed in table 1–1, including references, are available in appendix 1. Significantly, the grouping in this report of Co-Cu-Au deposits in metasedimentary rocks into a single model includes deposits that other workers have previously classified in different ways. For background information, a global overview of different types of Co deposits worldwide is given in Smith (2001).</p><p>Additional geologically and compositionally similar deposits are known, but have average Co grades less than 0.1 percent. Most of these deposits contain cobalt-rich pyrite and lack appreciable amounts of distinct Co sulfide and (or) sulfarsenide minerals. Such deposits are not discussed in detail in the following sections, but these deposits may be relevant to the descriptive and genetic models presented below. Examples include the Scadding Au-Co-Cu deposit in Ontario, Canada; the Vähäjoki Co-Cu-Au deposit in Finland; the Tuolugou Co-Au deposit in Qinghai Province, China; the Lala Co-Cu-UREE deposit in Sichuan Province, China; the Guelb Moghrein Cu-Au-Co deposit in Mauritania; and the Great Australia Co-Cu, Greenmount Cu-Au-Co, and Monakoff Cu-Au-Co-UAg deposits in Queensland, Australia. Detailed information on these deposits is presented in appendix 2.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Mineral deposit models for resource assessment (Scientific Investigations Report 2010-5070)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070G","usgsCitation":"Slack, J.F., Johnson, C.A., Causey, J.D., Lund, K., Schulz, K.J., Gray, J.E., and Eppinger, R.G., 2013, Descriptive and geoenvironmental model for Co-Cu-Au deposits in metasedimentary rocks: U.S. Geological Survey Scientific Investigations Report 2010-5070, xii, 218 p., https://doi.org/10.3133/sir20105070G.","productDescription":"xii, 218 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040230","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":280564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105070G.jpg"},{"id":280563,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/g/pdf/sir2010-5070-G.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":280562,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5070/g/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c29608e4b040b25da903e1","contributors":{"editors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":580212,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":580205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":580206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Causey, J. 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,{"id":70044629,"text":"ofr20121208 - 2013 - Water-quality data of lakes and wetlands in the Yukon Flats, Alaska, 2007–2009","interactions":[],"lastModifiedDate":"2014-02-19T13:09:09","indexId":"ofr20121208","displayToPublicDate":"2013-12-30T13:02:43","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1208","title":"Water-quality data of lakes and wetlands in the Yukon Flats, Alaska, 2007–2009","docAbstract":"Over a three-year period (2007–2009), in-situ measurements were taken and water-quality samples were collected from 111 lakes and wetlands located in the Yukon Flats, Alaska, during a U.S. Fish and Wildlife Service wetlands inventory. The U.S. Geological Survey performed the chemical analyses on the retrieved water-quality samples. Results from the analyses of water samples for dissolved carbon gases and carbon isotopes, hydrogen and oxygen stable isotopes, dissolved organic carbon, and major cations and anions, along with supporting site data, are presented in this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121208","usgsCitation":"Halm, D.R., and Guldager, N., 2013, Water-quality data of lakes and wetlands in the Yukon Flats, Alaska, 2007–2009: U.S. Geological Survey Open-File Report 2012-1208, Report: v, 8 p.; Excel Table, https://doi.org/10.3133/ofr20121208.","productDescription":"Report: v, 8 p.; Excel Table","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-037333","costCenters":[{"id":435,"text":"National Research Program - Central Region","active":false,"usgs":true}],"links":[{"id":282535,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1208/pdf/of2012-1208.pdf"},{"id":282536,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1208/tables.xlsx"},{"id":282537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121208.gif"},{"id":282534,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1208/"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -149.553,65.4692 ], [ -149.553,67.4718 ], [ -142.4346,67.4718 ], [ -142.4346,65.4692 ], [ -149.553,65.4692 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7d2ce4b0b2908510f36e","contributors":{"authors":[{"text":"Halm, Douglas R. drhalm@usgs.gov","contributorId":1635,"corporation":false,"usgs":true,"family":"Halm","given":"Douglas","email":"drhalm@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":476040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guldager, Nikki","contributorId":101981,"corporation":false,"usgs":true,"family":"Guldager","given":"Nikki","email":"","affiliations":[],"preferred":false,"id":476041,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70058107,"text":"ds809 - 2013 - Water column and bed-sediment core samples collected from Brownlee Reservoir near Oxbow, Oregon, 2012","interactions":[],"lastModifiedDate":"2013-12-30T13:19:07","indexId":"ds809","displayToPublicDate":"2013-12-30T12:42:00","publicationYear":"2013","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":"809","title":"Water column and bed-sediment core samples collected from Brownlee Reservoir near Oxbow, Oregon, 2012","docAbstract":"The U.S. Geological Survey, in cooperation with Idaho Power Company, collected water-column and bed-sediment core samples from eight sites in Brownlee Reservoir near Oxbow, Oregon, during May 5–7, 2012. Water-column and bed-sediment core samples were collected at each of the eight sites and analyzed for total mercury and methylmercury. Additional bed-sediment core samples, collected from three of the eight sites, were analyzed for pesticides and other organic compounds, trace metals, and physical characteristics, such as particle size.\n\nTotal mercury and methylmercury were detected in each of the water column and bed-sediment core samples. Only 17 of the 417 unique pesticide and organic compounds were detected in bed-sediment core samples. Concentrations of most organic wastewater compounds detected in bed sediment were less than the reporting level. Trace metals detected were greater than the reporting level in all the bed-sediment core samples submitted for analysis. The particle size distribution of bed-sediment core samples was predominantly clay mixed with silt.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds809","collaboration":"Prepared in cooperation with Idaho Power Company","usgsCitation":"Fosness, R.L., Naymik, J., Hopkins, C.B., and DeWild, J.F., 2013, Water column and bed-sediment core samples collected from Brownlee Reservoir near Oxbow, Oregon, 2012: U.S. Geological Survey Data Series 809, vi, 44 p., https://doi.org/10.3133/ds809.","productDescription":"vi, 44 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-042203","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":280560,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/809/"},{"id":280561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds809.JPG"},{"id":280559,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/809/pdf/ds809.pdf"}],"projection":"Transverse Mercator","datum":"North American Datum of 1983","country":"United States","state":"Idaho;Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.268066,44.403618 ], [ -117.268066,44.832257 ], [ -116.906204,44.832257 ], [ -116.906204,44.403618 ], [ -117.268066,44.403618 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c2960be4b040b25da90416","contributors":{"authors":[{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Naymik, Jesse","contributorId":58936,"corporation":false,"usgs":true,"family":"Naymik","given":"Jesse","affiliations":[],"preferred":false,"id":487009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hopkins, Candice B. 0000-0003-3207-7267 chopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-3207-7267","contributorId":1379,"corporation":false,"usgs":true,"family":"Hopkins","given":"Candice","email":"chopkins@usgs.gov","middleInitial":"B.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeWild, John F. 0000-0003-4097-2798 jfdewild@usgs.gov","orcid":"https://orcid.org/0000-0003-4097-2798","contributorId":2525,"corporation":false,"usgs":true,"family":"DeWild","given":"John","email":"jfdewild@usgs.gov","middleInitial":"F.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487007,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70048988,"text":"tm7D1 - 2013 - Digital-image processing and image analysis of glacier ice","interactions":[],"lastModifiedDate":"2013-12-30T11:32:45","indexId":"tm7D1","displayToPublicDate":"2013-12-30T11:19:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-D1","title":"Digital-image processing and image analysis of glacier ice","docAbstract":"This document provides a methodology for extracting grain statistics from 8-bit color and grayscale images of thin sections of glacier ice—a subset of physical properties measurements typically performed on ice cores. This type of analysis is most commonly used to characterize the evolution of ice-crystal size, shape, and intercrystalline spatial relations within a large body of ice sampled by deep ice-coring projects from which paleoclimate records will be developed. However, such information is equally useful for investigating the stress state and physical responses of ice to stresses within a glacier. The methods of analysis presented here go hand-in-hand with the analysis of ice fabrics (aggregate crystal orientations) and, when combined with fabric analysis, provide a powerful method for investigating the dynamic recrystallization and deformation behaviors of bodies of ice in motion.\n\nThe procedures described in this document compose a step-by-step handbook for a specific image acquisition and data reduction system built in support of U.S. Geological Survey ice analysis projects, but the general methodology can be used with any combination of image processing and analysis software. The specific approaches in this document use the FoveaPro 4 plug-in toolset to Adobe Photoshop CS5 Extended but it can be carried out equally well, though somewhat less conveniently, with software such as the image processing toolbox in MATLAB, Image-Pro Plus, or ImageJ.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section D: Digital-image processing in Book 7 <i>Automated Data Processing and Computations</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7D1","collaboration":"This report is Chapter 1 of Section D: Digital-image processing in Book 7 <i>Automated Data Processing and Computations</i>","usgsCitation":"Fitzpatrick, J.J., 2013, Digital-image processing and image analysis of glacier ice: U.S. Geological Survey Techniques and Methods 7-D1, iv, 21 p., https://doi.org/10.3133/tm7D1.","productDescription":"iv, 21 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-042842","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":280555,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/7d1"},{"id":280557,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm7D1.jpg"},{"id":280556,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/7d1/pdf/tm7-d1.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c29609e4b040b25da903ec","contributors":{"authors":[{"text":"Fitzpatrick, Joan J. jfitz@usgs.gov","contributorId":1416,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Joan","email":"jfitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":485939,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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