Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of New York, elevation data are critical for coastal zone management, natural resources conservation, agriculture and precision farming, flood risk management, infrastructure and construction management, water supply and quality, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143006","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for New York: U.S. Geological Survey Fact Sheet 2014-3006, 2 p., https://doi.org/10.3133/fs20143006.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052807","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":282076,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143006.jpg"},{"id":282074,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3006/"},{"id":282075,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3006/pdf/fs2014-3006.pdf","text":"Report","size":"370 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"New 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":489750,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70074056,"text":"fs20143005 - 2014 - The 3D Elevation Program: summary for Maryland","interactions":[],"lastModifiedDate":"2016-08-17T16:25:35","indexId":"fs20143005","displayToPublicDate":"2014-02-06T14:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3005","title":"The 3D Elevation Program: summary for Maryland","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Maryland, elevation data are critical for agriculture and precision farming, natural resources conservation such as the Chesapeake Bay and its watershed, flood risk management, urban and regional planning, infrastructure and construction management, water supply and quality, coastal zone management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143005","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Maryland: U.S. Geological Survey Fact Sheet 2014-3005, 2 p., https://doi.org/10.3133/fs20143005.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051742","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":282077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143005.jpg"},{"id":282072,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3005/"},{"id":282073,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3005/pdf/fs2014-3005.pdf","text":"Report","size":"435 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd76c0e4b0b2908510b18a","contributors":{"authors":[{"text":"Carswell, William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":489354,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70134531,"text":"70134531 - 2014 - Polar bears exhibit genome-wide signatures of bioenergetic adaptation to life in the Arctic environment","interactions":[],"lastModifiedDate":"2014-12-12T15:11:56","indexId":"70134531","displayToPublicDate":"2014-02-06T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3832,"text":"Genome Biology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Polar bears exhibit genome-wide signatures of bioenergetic adaptation to life in the Arctic environment","docAbstract":"Polar bears (Ursus maritimus) face extremely cold temperatures and periods of fasting, which might result in more severe energetic challenges than those experienced by their sister species, the brown bear (U. arctos). We have examined the mitochondrial and nuclear genomes of polar and brown bears to investigate if polar bears demonstrate lineage-specific signals of molecular adaptation in genes associated with cellular respiration/energy production. We observed increased evolutionary rates in the mitochondrial cytochrome c oxidase I gene in polar but not brown bears. An amino acid substitution occurred near the interaction site with a nuclear-encoded subunit of the cytochrome c oxidase complex, and was predicted to lead to a functional change, although the significance of this remains unclear. The nuclear genomes of brown and polar bears demonstrate different adaptations related to cellular respiration. Analyses of the genomes of brown bears exhibited substitutions that may alter the function of proteins that regulate glucose uptake, which could be beneficial when feeding on carbohydrate-dominated diets during hyperphagia, followed by fasting during hibernation. In polar bears, genes demonstrating signatures of functional divergence and those potentially under positive selection were enriched in functions related to production of nitric oxide, which can regulate energy production in several different ways. This suggests that polar bears may be able to fine-tune intracellular levels of nitric oxide as an adaptive response to control trade-offs between energy production in the form of ATP versus generation of heat (thermogenesis).
","language":"English","publisher":"Society for Molecular Biology and Evolution","doi":"10.1093/gbe/evu025","usgsCitation":"Welch, A., Bedoya-Reina, O.C., Carretero-Paulet, L., Miller, W., Rode, K.D., and Lindqvist, C., 2014, Polar bears exhibit genome-wide signatures of bioenergetic adaptation to life in the Arctic environment: Genome Biology and Evolution, v. 6, no. 2, p. 433-450, https://doi.org/10.1093/gbe/evu025.","productDescription":"18 p.","startPage":"433","endPage":"450","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049097","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":473173,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gbe/evu025","text":"Publisher Index Page"},{"id":296453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-06","publicationStatus":"PW","scienceBaseUri":"548193c6e4b0aa6d778520f6","contributors":{"authors":[{"text":"Welch, Andreanna J.","contributorId":79313,"corporation":false,"usgs":false,"family":"Welch","given":"Andreanna J.","affiliations":[],"preferred":false,"id":526446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedoya-Reina, Oscar C.","contributorId":33201,"corporation":false,"usgs":false,"family":"Bedoya-Reina","given":"Oscar","email":"","middleInitial":"C.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":526447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carretero-Paulet, Lorenzo","contributorId":127705,"corporation":false,"usgs":false,"family":"Carretero-Paulet","given":"Lorenzo","email":"","affiliations":[],"preferred":false,"id":526449,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Webb","contributorId":29671,"corporation":false,"usgs":false,"family":"Miller","given":"Webb","email":"","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":526450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":526128,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lindqvist, Charlotte","contributorId":35989,"corporation":false,"usgs":true,"family":"Lindqvist","given":"Charlotte","affiliations":[],"preferred":false,"id":526451,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70074813,"text":"70074813 - 2014 - Market forces and technological substitutes cause fluctuations in the value of bat pest-control services for cotton","interactions":[],"lastModifiedDate":"2017-02-13T14:47:41","indexId":"70074813","displayToPublicDate":"2014-02-05T13:43:00","publicationYear":"2014","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":"Market forces and technological substitutes cause fluctuations in the value of bat pest-control services for cotton","docAbstract":"Critics of the market-based, ecosystem services approach to biodiversity conservation worry that volatile market conditions and technological substitutes will diminish the value of ecosystem services and obviate the “economic benefits” arguments for conservation. To explore the effects of market forces and substitutes on service values, we assessed how the value of the pest-control services provided by Mexican free-tailed bats (Tadarida brasiliensis mexicana) to cotton production in the southwestern U.S. has changed over time. We calculated service values each year from 1990 through 2008 by estimating the value of avoided crop damage and the reduced social and private costs of insecticide use in the presence of bats. Over this period, the ecosystem service value declined by 79% ($19.09 million U.S. dollars) due to the introduction and widespread adoption of Bt (Bacillus thuringiensis) cotton transgenically modified to express its own pesticide, falling global cotton prices and the reduction in the number of hectares in the U.S. planted with cotton. Our results demonstrate that fluctuations in market conditions can cause temporal variation in ecosystem service values even when ecosystem function – in this case bat population numbers – is held constant. Evidence is accumulating, however, of the evolution of pest resistance to Bt cotton, suggesting that the value of bat pest-control services may increase again. This gives rise to an economic option value argument for conserving Mexican free-tailed bat populations. We anticipate that these results will spur discussion about the role of ecosystem services in biodiversity conservation in general, and bat conservation in particular.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0087912","usgsCitation":"López-Hoffman, L., Wiederholt, R., Sansone, C., Bagstad, K.J., Cryan, P.M., Diffendorfer, J., Goldstein, J., LaSharr, K., Loomis, J., McCracken, G., Medellin, R., Russell, A., and Semmens, D.J., 2014, Market forces and technological substitutes cause fluctuations in the value of bat pest-control services for cotton: PLoS ONE, v. 2, no. 9, 7 p., https://doi.org/10.1371/journal.pone.0087912.","productDescription":"7 p.","numberOfPages":"7","onlineOnly":"Y","ipdsId":"IP-049522","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science 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Ruscena","contributorId":69464,"corporation":false,"usgs":true,"family":"Wiederholt","given":"Ruscena","affiliations":[],"preferred":false,"id":489920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sansone, Chris","contributorId":44832,"corporation":false,"usgs":true,"family":"Sansone","given":"Chris","email":"","affiliations":[],"preferred":false,"id":489918,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":489915,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":2356,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":489913,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":489914,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goldstein, Joshua","contributorId":105224,"corporation":false,"usgs":true,"family":"Goldstein","given":"Joshua","affiliations":[],"preferred":false,"id":489923,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LaSharr, Kelsie","contributorId":108397,"corporation":false,"usgs":true,"family":"LaSharr","given":"Kelsie","email":"","affiliations":[],"preferred":false,"id":489924,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Loomis, John","contributorId":60746,"corporation":false,"usgs":true,"family":"Loomis","given":"John","affiliations":[],"preferred":false,"id":489919,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCracken, Gary","contributorId":38885,"corporation":false,"usgs":true,"family":"McCracken","given":"Gary","affiliations":[],"preferred":false,"id":489917,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Medellin, Rodrigo A.","contributorId":77456,"corporation":false,"usgs":true,"family":"Medellin","given":"Rodrigo A.","affiliations":[],"preferred":false,"id":489922,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Russell, Amy","contributorId":38884,"corporation":false,"usgs":true,"family":"Russell","given":"Amy","affiliations":[],"preferred":false,"id":489916,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":489912,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70074744,"text":"70074744 - 2014 - Comparisons of genetic diversity in captive versus wild populations of the federally endangered Quino checkerspot butterfly (Euphydryas editha quino Behr; Lepidoptera: Nymphalidae)","interactions":[],"lastModifiedDate":"2014-02-07T13:01:07","indexId":"70074744","displayToPublicDate":"2014-02-05T12:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3152,"text":"Proceedings of the Entomological Society of Washington","active":true,"publicationSubtype":{"id":10}},"title":"Comparisons of genetic diversity in captive versus wild populations of the federally endangered Quino checkerspot butterfly (Euphydryas editha quino Behr; Lepidoptera: Nymphalidae)","docAbstract":"Captive populations can play a significant role in threatened and endangered species management. An important consideration when developing and managing captive populations, however, is the maintenance of genetic diversity to ensure that adequate variation exists to avoid the negative consequences of inbreeding. In this investigation, we compared genetic diversity patterns within captive and wild populations of the federally endangered Quino checkerspot butterfly (Euphydryas editha quino Behr [Lepidoptera: Nymphalidae]), a taxon with a restricted distribution to chaparral and sage shrublands within Riverside and San Diego counties, California. Our analyses revealed that medium to high-frequency alleles from the wild populations were also present in the captive populations. While there was no significant difference in genetic diversity as quantified by expected heterozygosity, the captive populations showed tendencies toward significantly lower allelic richness than their wild counterparts. Given that alleles from the wild populations were occasionally not detected in captive populations, periodic incorporation of new wild specimens into the captive population would help ensure that allelic diversity is maintained to the extent possible. If performed in advance, genetic surveys of wild populations may provide the clearest insights regarding the number of individuals needed in captivity to adequately reflect wild populations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Proceedings of the Entomological Society of Washington","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Entomological Society of Washington","doi":"10.4289/0013-8797.116.1.80","usgsCitation":"Miller, M.P., Pratt, G.F., Mullins, T., and Haig, S.M., 2014, Comparisons of genetic diversity in captive versus wild populations of the federally endangered Quino checkerspot butterfly (Euphydryas editha quino Behr; Lepidoptera: Nymphalidae): Proceedings of the Entomological Society of Washington, v. 116, no. 1, p. 80-90, https://doi.org/10.4289/0013-8797.116.1.80.","productDescription":"11 p.","startPage":"80","endPage":"90","numberOfPages":"11","ipdsId":"IP-051217","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":282022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281891,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4289/0013-8797.116.1.80"}],"country":"United States","state":"California","otherGeospatial":"Lake Skinner;Marron Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.1708,32.4928 ], [ -117.1708,33.5989 ], [ -116.4802,33.5989 ], [ -116.4802,32.4928 ], [ -117.1708,32.4928 ] ] ] } } ] }","volume":"116","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52f35e25e4b0b03a191c6dc9","contributors":{"authors":[{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":489778,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pratt, Gordon F.","contributorId":99885,"corporation":false,"usgs":true,"family":"Pratt","given":"Gordon","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":489780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullins, Thomas D.","contributorId":12819,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas D.","affiliations":[],"preferred":false,"id":489779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":489777,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70071899,"text":"fs20133041 - 2014 - Arkansas StreamStats: a U.S. Geological Survey web map application for basin characteristics and streamflow statistics","interactions":[],"lastModifiedDate":"2014-02-11T08:33:46","indexId":"fs20133041","displayToPublicDate":"2014-02-05T11:08:00","publicationYear":"2014","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":"2013-3041","title":"Arkansas StreamStats: a U.S. Geological Survey web map application for basin characteristics and streamflow statistics","docAbstract":"The U.S. Geological Survey (USGS) provides streamflow and other related information needed by water-resource managers responsible for protecting people and property from floods, planning and managing water-resource activities, and protecting water quality. Streamflow statistics provided by the USGS, such as the 1-percent annual exceedance probability (100-year flood) and the 7-day 10-year low flow, are frequently used by engineers, flood forecasters, land managers, biologists, and others to guide their everyday decisions. Additionally, resource managers often need to know basin characteristics, the physical and climatic characteristics of a drainage basin, to help understand the mechanisms that control water availability, water quality, and aquatic habitats at various locations.
\nUsers of streamflow information often require streamflow statistics and basin characteristics at various locations along a stream. The USGS periodically calculates and publishes streamflow statistics and basin characteristics for streamflowgaging stations and partial-record stations, but these data commonly are scattered among many reports that may or may not be readily available to the public. The USGS also provides and periodically updates regional analyses of streamflow statistics that include regression equations and other prediction methods for estimating statistics for ungaged and unregulated streams across the State. Use of these regional predictions for a stream can be complex and often requires the user to determine a number of basin characteristics that may require interpretation. Basin characteristics may include drainage area, classifiers for physical properties, climatic characteristics, and other inputs. Obtaining these input values for gaged and ungaged locations traditionally has been time consuming, subjective, and can lead to inconsistent results.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133041","usgsCitation":"Pugh, A., 2014, Arkansas StreamStats: a U.S. Geological Survey web map application for basin characteristics and streamflow statistics: U.S. Geological Survey Fact Sheet 2013-3041, 2 p., https://doi.org/10.3133/fs20133041.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-046169","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":282009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133041.jpg"},{"id":282008,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3041"},{"id":282011,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3041/pdf/fs2013-3041.pdf"}],"country":"United States","state":"Arkansas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.6179,33.0041 ], [ -94.6179,36.4997 ], [ -89.6468,36.4997 ], [ -89.6468,33.0041 ], [ -94.6179,33.0041 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4debe4b0b290850f1c9b","contributors":{"authors":[{"text":"Pugh, Aaron L. apugh@usgs.gov","contributorId":2480,"corporation":false,"usgs":true,"family":"Pugh","given":"Aaron L.","email":"apugh@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488353,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70049006,"text":"ofr20121024E - 2014 - Geologic framework for the national assessment of carbon dioxide storage resources: Greater Green River Basin, Wyoming, Colorado, and Utah, and Wyoming-Idaho-Utah Thrust Belt","interactions":[{"subject":{"id":70049006,"text":"ofr20121024E - 2014 - Geologic framework for the national assessment of carbon dioxide storage resources: Greater Green River Basin, Wyoming, Colorado, and Utah, and Wyoming-Idaho-Utah Thrust Belt","indexId":"ofr20121024E","publicationYear":"2014","noYear":false,"chapter":"E","title":"Geologic framework for the national assessment of carbon dioxide storage resources: Greater Green River Basin, Wyoming, Colorado, and Utah, and Wyoming-Idaho-Utah Thrust Belt"},"predicate":"IS_PART_OF","object":{"id":70093199,"text":"ofr20121024 - 2012 - Geologic framework for the national assessment of carbon dioxide storage resources","indexId":"ofr20121024","publicationYear":"2012","noYear":false,"title":"Geologic framework for the national assessment of carbon dioxide storage resources"},"id":1}],"isPartOf":{"id":70093199,"text":"ofr20121024 - 2012 - Geologic framework for the national assessment of carbon dioxide storage resources","indexId":"ofr20121024","publicationYear":"2012","noYear":false,"title":"Geologic framework for the national assessment of carbon dioxide storage resources"},"lastModifiedDate":"2019-02-21T11:37:38","indexId":"ofr20121024E","displayToPublicDate":"2014-02-05T08:48:00","publicationYear":"2014","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":"2012-1024","chapter":"E","title":"Geologic framework for the national assessment of carbon dioxide storage resources: Greater Green River Basin, Wyoming, Colorado, and Utah, and Wyoming-Idaho-Utah Thrust Belt","docAbstract":"The 2007 Energy Independence and Security Act (Public Law 110–140) directs the U.S. Geological Survey (USGS) to conduct a national assessment of potential geologic storage resources for carbon dioxide (CO2). The methodology used by the USGS for the national CO2 assessment follows up on previous USGS work. The methodology is non-economic and intended to be used at regional to subbasinal scales. This report identifies and contains geologic descriptions of 14 storage assessment units (SAUs) in Ordovician to Upper Cretaceous sedimentary rocks within the Greater Green River Basin (GGRB) of Wyoming, Colorado, and Utah, and eight SAUs in Ordovician to Upper Cretaceous sedimentary rocks within the Wyoming-Idaho-Utah Thrust Belt (WIUTB). The GGRB and WIUTB are contiguous with nearly identical geologic units; however, the GGRB is larger in size, whereas the WIUTB is more structurally complex. This report focuses on the characteristics, specified in the methodology, that influence the potential CO2 storage resource in the SAUs. Specific descriptions of the SAU boundaries, as well as their sealing and reservoir units, are included. Properties for each SAU, such as depth to top, gross thickness, porosity, permeability, groundwater quality, and structural reservoir traps, are typically provided to illustrate geologic factors critical to the assessment. This geologic information was employed, as specified in the USGS methodology, to calculate a probabilistic distribution of potential storage resources in each SAU. Figures in this report show SAU boundaries and cell maps of well penetrations through sealing units into the top of the storage formations. The cell maps show the number of penetrating wells within one square mile and are derived from interpretations of variably attributed well data and a digital compilation that is known not to include all drilling.
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A key challenge is to improve the predictability of postdisturbance biogeochemical trajectories at the ecosystem level. Ecosystem ecologists and paleoecologists have generated complementary data sets about disturbance (type, severity, frequency) and ecosystem response (net primary productivity, nutrient cycling) spanning decadal to millennial timescales. Here, we take the first steps toward a full integration of these data sets by reviewing how disturbances are reconstructed using dendrochronological and sedimentary archives and by summarizing the conceptual frameworks for carbon, nitrogen, and hydrologic responses to disturbances. Key research priorities include further development of paleoecological techniques that reconstruct both disturbances and terrestrial ecosystem dynamics. In addition, mechanistic detail from disturbance experiments, long-term observations, and chronosequences can help increase the understanding of ecosystem resilience.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"BioScience","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Institute of Biological Sciences","doi":"10.1093/biosci/bit017","usgsCitation":"McLauchlan, K.K., Higuera, P., Gavin, D.G., Perakis, S., Mack, M., Alexander, H., Battles, J., Biondi, F., Buma, B., Colombaroli, D., Enders, S.K., Engstrom, D.R., Hu, F., Marlon, J.R., Marshall, J., McGlone, M., Morris, J.L., Nave, L.E., Shuman, B., Smithwick, E.A., Urrego, D.H., Wardle, D.A., Williams, C.J., and Williams, J.J., 2014, Reconstructing disturbances and their biogeochemical consequences over multiple timescales: BioScience, v. 64, no. 2, p. 105-116, https://doi.org/10.1093/biosci/bit017.","productDescription":"12 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The field-audit program assessed the effects of onsite exposure, sample handling, and shipping on the chemistry of NTN samples; a system-blank program assessed the same effects for MDN. Two interlaboratory-comparison programs assessed the bias and variability of the chemical analysis data from the Central Analytical Laboratory (CAL) and Mercury (Hg) Analytical Laboratory (HAL). The blind-audit program was also implemented for the MDN to evaluate analytical bias in total Hg concentration data produced by the HAL. The co-located-sampler program was used to identify and quantify potential shifts in NADP data resulting from replacement of original network instrumentation with new electronic recording rain gages (E-gages) and precipitation collectors that use optical sensors.
\nThe results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends of chemical constituents in wet deposition across the United States. Results also suggest that retrofit of the NADP networks with the new precipitation collectors could cause –8 to +14 percent shifts in NADP annual precipitation-weighted mean concentrations and total deposition values for ammonium, nitrate, sulfate, and hydrogen ion, and larger shifts (+13 to +74 percent) for calcium, magnesium, sodium, potassium, and chloride. The prototype N-CON Systems bucket collector is more efficient in the catch of precipitation in winter than Aerochem Metrics Model 301 collector, especially for light snowfall.
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Two highly distinctive IgW-encoding loci have been identified that exhibit a unique genomic organization, including a multiplicity of tandemly repeated constant region exons. The overall organization of the IgW loci precludes typical heavy chain class switching. A locus encoding IgM could not be identified either computationally or by using several different experimental strategies. Four distinct sets of genes encoding Ig light chains were identified. This includes a variant sigma-type Ig light chain previously identified only in cartilaginous fishes and which is now provisionally denoted sigma-2. Genes encoding α/β and γ/δ T-cell receptors, and CD3, CD4, and CD8 co-receptors also were characterized. Ig heavy chain variable region genes and TCR components are interspersed within the TCR α/δ locus; this organization previously was reported only in tetrapods and raises questions regarding evolution and functional cooption of genes encoding variable regions. The composition, organization and syntenic conservation of the major histocompatibility complex locus have been characterized. We also identified large numbers of genes encoding cytokines and their receptors, and other genes associated with adaptive immunity. In terms of sequence identity and organization, the adaptive immune genes of the coelacanth more closely resemble orthologous genes in tetrapods than those in teleost fishes, consistent with current phylogenomic interpretations. Overall, the work reported described herein highlights the complexity inherent in the coelacanth genome and provides a rich catalog of immune genes for future investigations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Experimental Zoology Part B: Molecular and Developmental Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley Periodicals, Inc.","doi":"10.1002/jez.b.22558","usgsCitation":"Saha, N.R., Ota, T., Litman, G.W., Hansen, J., Parra, Z., Hsu, E., Buonocore, F., Canapa, A., Cheng, J., and Amemiya, C.T., 2014, Genome complexity in the coelacanth is reflected in its adaptive immune system: Journal of Experimental Zoology Part B: Molecular and Developmental Evolution, v. 322, no. 6, p. 438-463, https://doi.org/10.1002/jez.b.22558.","productDescription":"26 p.","startPage":"438","endPage":"463","numberOfPages":"26","ipdsId":"IP-053194","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":473177,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://ir.soken.ac.jp/records/5424","text":"External Repository"},{"id":281957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281947,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jez.b.22558"}],"volume":"322","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-01-24","publicationStatus":"PW","scienceBaseUri":"52f20c8be4b0a6f0bd498b61","contributors":{"authors":[{"text":"Saha, Nil Ratan","contributorId":85500,"corporation":false,"usgs":true,"family":"Saha","given":"Nil","email":"","middleInitial":"Ratan","affiliations":[],"preferred":false,"id":489935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ota, Tatsuya","contributorId":61336,"corporation":false,"usgs":true,"family":"Ota","given":"Tatsuya","affiliations":[],"preferred":false,"id":489932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Litman, Gary W.","contributorId":101984,"corporation":false,"usgs":true,"family":"Litman","given":"Gary","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":489936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, John","contributorId":21066,"corporation":false,"usgs":true,"family":"Hansen","given":"John","affiliations":[],"preferred":false,"id":489928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parra, Zuly","contributorId":31671,"corporation":false,"usgs":true,"family":"Parra","given":"Zuly","email":"","affiliations":[],"preferred":false,"id":489929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hsu, Ellen","contributorId":63717,"corporation":false,"usgs":true,"family":"Hsu","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":489933,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Buonocore, Francesco","contributorId":39693,"corporation":false,"usgs":true,"family":"Buonocore","given":"Francesco","email":"","affiliations":[],"preferred":false,"id":489930,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Canapa, Adriana","contributorId":64557,"corporation":false,"usgs":true,"family":"Canapa","given":"Adriana","email":"","affiliations":[],"preferred":false,"id":489934,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cheng, Jan-Fang","contributorId":13896,"corporation":false,"usgs":true,"family":"Cheng","given":"Jan-Fang","email":"","affiliations":[],"preferred":false,"id":489927,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Amemiya, Chris T.","contributorId":42869,"corporation":false,"usgs":true,"family":"Amemiya","given":"Chris","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":489931,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70059052,"text":"sir20135233 - 2014 - Estimation of potential scour at bridges on local government roads in South Dakota, 2009-12","interactions":[],"lastModifiedDate":"2017-10-12T20:13:49","indexId":"sir20135233","displayToPublicDate":"2014-02-04T10:38:00","publicationYear":"2014","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":"2013-5233","title":"Estimation of potential scour at bridges on local government roads in South Dakota, 2009-12","docAbstract":"In 2009, the U.S. Geological Survey and South Dakota Department of Transportation (SDDOT) began a study to estimate potential scour at selected bridges on local government (county, township, and municipal) roads in South Dakota. A rapid scour-estimation method (level-1.5) and a more detailed method (level-2) were used to develop estimates of contraction, abutment, and pier scour.
\nData from 41 level-2 analyses completed for this study were combined with data from level-2 analyses completed in previous studies to develop new South Dakota-specific regression equations: four regional equations for main-channel velocity at the bridge contraction to account for the widely varying stream conditions within South Dakota, and one equation for head change. Velocity data from streamgages also were used in the regression for average velocity through the bridge contraction.
\nUsing these new regression equations, scour analyses were completed using the level-1.5 method on 361 bridges on local government roads. Typically, level-1.5 analyses are completed at flows estimated to have annual exceedance probabilities of 1 percent (100-year flood) and 0.2 percent (500-year flood); however, at some sites the bridge would not pass these flows. A level-1.5 analysis was then completed at the flow expected to produce the maximum scour. Data presented for level-1.5 scour analyses at the 361 bridges include contraction, abutment, and pier scour. Estimates of potential contraction scour ranged from 0 to 32.5 feet for the various flows evaluated. Estimated potential abutment scour ranged from 0 to 40.9 feet for left abutments, and from 0 to 37.7 feet for right abutments. Pier scour values ranged from 2.7 to 31.6 feet. The scour depth estimates provided in this report can be used by the SDDOT to compare with foundation depths at each bridge to determine if abutments or piers are at risk of being undermined by scour at the flows evaluated.
\nReplicate analyses were completed at 24 of the 361 bridges to provide quality-assurance/quality-control measures for the level-1.5 scour estimates. An attempt was made to use the same flows among replicate analyses. Scour estimates do not necessarily have to be in numerical agreement to give the same results. For example, if contraction scour replicate analyses are 18.8 and 30.8 feet, both scour depths can indicate susceptibility to scour for which countermeasures may be needed, even though one number is much greater than the other number. Contraction scour has perhaps the greatest potential for being estimated differently in replicate visits. For contraction scour estimates at the various flows analyzed, differences between results ranged from -7.8 to 5.5 feet, with a median difference of 0.4 foot and an average difference of 0.2 foot. Abutment scour appeared to be nearly as reproducible as contraction scour. For abutment scour estimates at the varying flows analyzed, differences between results ranged from -17.4 to 11 feet, with a median difference of 1.4 feet and an average difference of 1.7 feet. Estimates of pier scour tended to be the most consistently reproduced in replicate visits, with differences between results ranging from -0.3 to 0.5 foot, with a median difference of 0.0 foot and an average difference of 0.0 foot.
\nThe U.S. Army Corps of Engineers Hydraulics Engineering Center River Analysis Systems (HEC-RAS) software package was used to model stream hydraulics at the 41 sites with level-2 analyses. Level-1.5 analyses also were completed at these sites, and the performance of the level-1.5 method was assessed by comparing results to those from the more rigorous level-2 method. The envelope curve approach used in the level-1.5 method is designed to overestimate scour relative to the estimate from the level-2 scour analysis. In cases where the level-1.5 method estimated less scour than the level-2 method, the amount of underestimation generally was less than 3 feet. The level-1.5 method generally overestimated contraction, abutment, and pier scour relative to the level-2 method, as intended. Although the level-1.5 method is designed to overestimate scour relative to more involved analysis methods, many assumptions, uncertainties, and estimations are involved. If the envelope curves are adjusted such that the level-1.5 method never underestimates scour relative to the level-2 method, an accompanying result may be excessive overestimation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135233","collaboration":"Prepared in cooperation with the South Dakota Department of Transportation","usgsCitation":"Thompson, R.F., Wattier, C.M., Liggett, R.R., and Truax, R.A., 2014, Estimation of potential scour at bridges on local government roads in South Dakota, 2009-12: U.S. Geological Survey Scientific Investigations Report 2013-5233, Report: vi, 24 p.; 4 Appendixes, https://doi.org/10.3133/sir20135233.","productDescription":"Report: vi, 24 p.; 4 Appendixes","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-044841","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":281954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135233.jpg"},{"id":281953,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5233/downloads/Appendix_4.xls"},{"id":281950,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5233/"},{"id":281951,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5233/downloads/Appendix2"},{"id":281952,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5233/downloads/Appendix_3.xls"},{"id":281955,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5233/pdf/sir2013-5233.pdf"},{"id":281956,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5233/downloads/Appendix_1.xls"}],"projection":"Universal Transverse Mercator projection","country":"United States","state":"South Dakota","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.73,42.24 ], [ -104.73,46.19 ], [ -95.99,46.19 ], [ -95.99,42.24 ], [ -104.73,42.24 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd5825e4b0b290850f7e91","contributors":{"authors":[{"text":"Thompson, Ryan F. 0000-0002-4544-6108 rcthomps@usgs.gov","orcid":"https://orcid.org/0000-0002-4544-6108","contributorId":2702,"corporation":false,"usgs":true,"family":"Thompson","given":"Ryan","email":"rcthomps@usgs.gov","middleInitial":"F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wattier, Chelsea M.","contributorId":7993,"corporation":false,"usgs":true,"family":"Wattier","given":"Chelsea","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":487458,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liggett, Richard R.","contributorId":73105,"corporation":false,"usgs":true,"family":"Liggett","given":"Richard","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":487460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Truax, Ryan A.","contributorId":63305,"corporation":false,"usgs":true,"family":"Truax","given":"Ryan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":487459,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70058742,"text":"fs20133117 - 2014 - Landsat Surface Reflectance Climate Data Records","interactions":[],"lastModifiedDate":"2014-02-04T10:15:03","indexId":"fs20133117","displayToPublicDate":"2014-02-04T10:11:00","publicationYear":"2014","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":"2013-3117","title":"Landsat Surface Reflectance Climate Data Records","docAbstract":"Landsat Surface Reflectance Climate Data Records (CDRs) are high level Landsat data products that support land surface change studies. Climate Data Records, as defined by the National Research Council, are a time series of measurements with sufficient length, consistency, and continuity to identify climate variability and change. The U.S. Geological Survey (USGS) is using the valuable 40-year Landsat archive to create CDRs that can be used to document changes to Earth’s terrestrial environment.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133117","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2014, Landsat Surface Reflectance Climate Data Records: U.S. Geological Survey Fact Sheet 2013-3117, 1 p., https://doi.org/10.3133/fs20133117.","productDescription":"1 p.","numberOfPages":"1","onlineOnly":"Y","ipdsId":"IP-052442","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":281949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133117.jpg"},{"id":281946,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3117/"},{"id":281948,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3117/pdf/fs2013-3117.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd63f8e4b0b290850ff285","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":535611,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70058731,"text":"sir20135221 - 2014 - Water-quality variability and constituent transport and processes in streams of Johnson County, Kansas, using continuous monitoring and regression models, 2003-11","interactions":[],"lastModifiedDate":"2014-02-04T10:08:49","indexId":"sir20135221","displayToPublicDate":"2014-02-04T09:50:00","publicationYear":"2014","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":"2013-5221","title":"Water-quality variability and constituent transport and processes in streams of Johnson County, Kansas, using continuous monitoring and regression models, 2003-11","docAbstract":"The population of Johnson County, Kansas increased by about 24 percent between 2000 and 2012, making it one of the most rapidly developing areas of Kansas. The U.S. Geological Survey, in cooperation with the Johnson County Stormwater Management Program, began a comprehensive study of Johnson County streams in 2002 to evaluate and monitor changes in stream quality. The purpose of this report is to describe water-quality variability and constituent transport for streams representing the five largest watersheds in Johnson County, Kansas during 2003 through 2011. The watersheds ranged in urban development from 98.3 percent urban (Indian Creek) to 16.7 percent urban (Kill Creek). Water-quality conditions are quantified among the watersheds of similar size (50.1 square miles to 65.7 square miles) using continuous, in-stream measurements, and using regression models developed from continuous and discrete data. These data are used to quantify variability in concentrations and loads during changing streamflow and seasonal conditions, describe differences among sites, and assess water quality relative to water-quality standards and stream management goals.
\nWater quality varied relative to streamflow conditions, urbanization in the upstream watershed, and contributions from wastewater treatment facilities and storm runoff. Generally, as percent impervious surface (a measure of urbanization) increased, streamflow yield increased. Water temperature of Indian Creek, the most urban site which is also downstream from wastewater facility discharges, was higher than the other sites about 50 percent of the time, particularly during winter months. Dissolved oxygen concentrations were less than the Kansas Department of Health and Environment minimum criterion of 5 milligrams per liter about 15 percent of the time at the Indian Creek site. Dissolved oxygen concentrations were less than the criterion about 10 percent of the time at the rural Blue River and Kill Creek sites, and less than 5 percent of the time at the other sites. Low dissolved oxygen at all sites generally coincided with lowest streamflow and warmer water temperatures. Hourly dissolved oxygen concentrations less than 5 milligrams per liter were measured at all sites every year, indicating that even under normal climate conditions in non-urban watersheds such as Kill Creek, dissolved oxygen concentrations may not meet State aquatic-life criterion.
\nSpecific conductance was nearly always highest in Indian and Mill Creeks, which were the most urban streams with the largest upstream discharges from wastewater treatment facilities. The largest chloride concentrations and variability were recorded at urban sites and during winter. Each winter during the study period, chloride concentrations in the most urban site, Indian Creek, exceeded the U.S. Environmental Protection Agency-recommended criterion of 230 milligrams per liter for at least 10 consecutive days.
\nThe U.S. Environmental Protection Agency-recommended ecoregion criterion for turbidity was exceeded 30 (Indian Creek) to 50 (Blue River) percent of the time. The highest average annual streamflow-weighted suspendedsediment concentration during the study period was in Mill Creek, which has undergone rapid development that likely contributed to higher sediment concentrations. One of the largest suspended-sediment load events in Indian Creek was recorded in early May 2007 when about 25 percent of the total annual sediment load was transported during a period of about 2.25 days. A simultaneous load event was recorded in Kill Creek, when about 75 percent of the total annual sediment load was transported. Sediment yields generally increased as percent impervious surface increased.
\nComputed hourly total nitrogen and total phosphorus concentrations and yields and streamflow-weighted concentrations generally were largest in Indian and Mill Creeks. Annual percent contribution of total nitrogen in the Blue River from wastewater treatment facility discharges ranged from 19 percent in 2010 to 60 percent in 2006. Annual percent contribution of total nitrogen in Indian Creek from wastewater treatment facility discharges ranged from 35 percent in 2010 to 93 percent in 2006. The largest percent nutrient contributions from wastewater discharges coincided with the smallest annual precipitation and streamflow volume, resulting in less contribution originating from runoff.
\nFecal indicator bacteria Escherichia coli density at the urban Indian Creek site was usually the largest of the five monitoring sites, with an annual median density that consistently exceeded the State primary contact criterion value but was less than the secondary contact criterion. Less than 1 percent of the total annual bacteria load in the Blue River and Indian Creek originated from wastewater discharges, except during 2006 when about 6 percent of the Indian Creek load originated from wastewater.
\nContinuous water-quality monitoring provides a foundation for comprehensive evaluation and understanding of variability and loading characteristics in streams in Johnson County. Because several directly measured parameters are strongly correlated with particular constituents of interest, regression models provide a valuable tool for evaluating variability and loading on the basis of computed continuous data. Continuous data are particularly useful for characterizing nonpoint-source contributions from stormwater runoff. Transmission of continuous data in real-time makes it possible to rapidly detect and respond to potential environmental concerns. As monitoring technologies continue to improve, so does the ability to monitor additional constituents of interest, with smaller measurement error, and at lower operational cost. Continuous water-quality data including model information and computed concentrations and loads during the study period are available at http://nrtwq.usgs.gov/ks/.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135221","collaboration":"Prepared in cooperation with the Johnson County Stormwater Management Program","usgsCitation":"Rasmussen, T., and Gatotho, J., 2014, Water-quality variability and constituent transport and processes in streams of Johnson County, Kansas, using continuous monitoring and regression models, 2003-11: U.S. Geological Survey Scientific Investigations Report 2013-5221, vi, 53 p., https://doi.org/10.3133/sir20135221.","productDescription":"vi, 53 p.","numberOfPages":"64","onlineOnly":"Y","temporalStart":"2003-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-049314","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":281945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135221.jpg"},{"id":281941,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5221/"},{"id":281944,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5221/pdf/sir2013-5221.pdf"}],"projection":"Albers Conic Equal-Area Projection","datum":"NAD 83","country":"United States","state":"Kansas","county":"Johnson County","otherGeospatial":"Blue River;Indian Creek;Kill Creek;Mill Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.1699,38.6994 ], [ -95.1699,39.1002 ], [ -94.4996,39.1002 ], [ -94.4996,38.6994 ], [ -95.1699,38.6994 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7d33e4b0b2908510f3bf","contributors":{"authors":[{"text":"Rasmussen, Teresa","contributorId":101993,"corporation":false,"usgs":true,"family":"Rasmussen","given":"Teresa","email":"","affiliations":[],"preferred":false,"id":487307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gatotho, Jackline","contributorId":103582,"corporation":false,"usgs":true,"family":"Gatotho","given":"Jackline","affiliations":[],"preferred":false,"id":487308,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70058497,"text":"ofr20131168 - 2014 - Evaluation of aerial thermal infrared remote sensing to identify groundwater-discharge zones in the Meduxnekeag River, Houlton, Maine","interactions":[],"lastModifiedDate":"2014-02-04T09:46:16","indexId":"ofr20131168","displayToPublicDate":"2014-02-04T09:30:00","publicationYear":"2014","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":"2013-1168","title":"Evaluation of aerial thermal infrared remote sensing to identify groundwater-discharge zones in the Meduxnekeag River, Houlton, Maine","docAbstract":"Residents of the area near Houlton, Maine, have observed seasonal episodic blooms of algae and documented elevated concentrations of fecal-coliform bacteria and inorganic nutrients and low dissolved oxygen concentrations in the Meduxnekeag River. Although point and nonpoint sources of urban and agricultural runoff likely contribute to water-quality impairment, the role of shallow groundwater inflows in delivering such contaminants to the Meduxnekeag River has not been well understood.
\nTo provide information about possible groundwater inflows to the river, airborne thermal infrared videography was evaluated as a means to identify and classify thermal anomalies in a 25-mile reach of the mainstem and tributaries of the Meduxnekeag River near Houlton, Maine. The U.S. Geological Survey, in cooperation with the Houlton Band of Maliseet Indians, collected thermal infrared images from a single-engine, fixed-wing aircraft during flights on December 3–4, 2003, and November 26, 2004.
\nEleven thermal anomalies were identified on the basis of data from the December 2003 flight and 17 from the November 2004 flight, which covered the same reaches of stream. Following image analysis, characterization, and prioritization, the georeferenced infrared images of the thermal anomalies were compared to features on topographic maps of the study area. The mapped anomalies were used to direct observations on the ground to confirm discharge locations and types of inflow. The variations in grayscale patterns on the images were thus confirmed as representing shallow groundwater-discharge zones (seeps), outfalls of treated wastewater, or ditches draining runoff from impervious surfaces.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131168","collaboration":"Prepared in cooperation with the Houlton Band of Maliseet Indians","usgsCitation":"Culbertson, C.W., Huntington, T.G., Caldwell, J.M., and O’Donnell, C., 2014, Evaluation of aerial thermal infrared remote sensing to identify groundwater-discharge zones in the Meduxnekeag River, Houlton, Maine: U.S. Geological Survey Open-File Report 2013-1168, v, 21 p., https://doi.org/10.3133/ofr20131168.","productDescription":"v, 21 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-032616","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":281943,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131168.jpg"},{"id":281940,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1168"},{"id":281942,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1168/pdf/ofr2013-1168.pdf"}],"projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Maine","city":"Houlton","otherGeospatial":"Meduxnekeag River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -68.201752,45.849369 ], [ -68.201752,46.401882 ], [ -67.649002,46.401882 ], [ -67.649002,45.849369 ], [ -68.201752,45.849369 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd5850e4b0b290850f8044","contributors":{"authors":[{"text":"Culbertson, Charles W. cculbert@usgs.gov","contributorId":1607,"corporation":false,"usgs":true,"family":"Culbertson","given":"Charles","email":"cculbert@usgs.gov","middleInitial":"W.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huntington, Thomas G. 0000-0002-9427-3530 thunting@usgs.gov","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":1884,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas","email":"thunting@usgs.gov","middleInitial":"G.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, James M. 0000-0001-5880-443X jmcald@usgs.gov","orcid":"https://orcid.org/0000-0001-5880-443X","contributorId":1882,"corporation":false,"usgs":true,"family":"Caldwell","given":"James","email":"jmcald@usgs.gov","middleInitial":"M.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487113,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Donnell, Cara","contributorId":79800,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Cara","email":"","affiliations":[],"preferred":false,"id":487115,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70074788,"text":"70074788 - 2014 - Marine fog: a review","interactions":[],"lastModifiedDate":"2014-03-14T10:41:04","indexId":"70074788","displayToPublicDate":"2014-02-04T09:14:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":928,"text":"Atmospheric Research","active":true,"publicationSubtype":{"id":10}},"title":"Marine fog: a review","docAbstract":"The objective of this review is to discuss physical processes over a wide range of spatial scales that govern the formation, evolution, and dissipation of marine fog. We consider marine fog as the collective combination of fog over the open sea along with coastal sea fog and coastal land fog. The review includes a history of sea fog research, field programs, forecasting methods, and detection of sea fog via satellite observations where similarity in radiative properties of fog top and the underlying sea induce further complexity. The main thrust of the study is to provide insight into causality of fog including its initiation, maintenance, and destruction. The interplay between the various physical processes behind the several stages of marine fog is among the most challenging aspects of the problem. An effort is made to identify this interplay between processes that include the microphysics of fog formation and maintenance, the influence of large-scale circulation and precipitation/clouds, radiation, turbulence (air-sea interaction), and advection. The environmental impact of marine fog is also addressed. The study concludes with an assessment of our current knowledge of the phenomenon, our principal areas of ignorance, and future lines of research that hold promise for advances in our understanding.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Atmospheric Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosres.2013.12.012","usgsCitation":"Koracin, D., Dorman, C.E., Lewis, J.M., Hudson, J.G., Wilcox, E.M., and Torregrosa, A.A., 2014, Marine fog: a review: Atmospheric Research, v. 143, p. 142-175, https://doi.org/10.1016/j.atmosres.2013.12.012.","productDescription":"34 p.","startPage":"142","endPage":"175","numberOfPages":"34","ipdsId":"IP-049750","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":281938,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281931,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.atmosres.2013.12.012"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","volume":"143","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52f20c8fe4b0a6f0bd498b69","contributors":{"authors":[{"text":"Koracin, Darko","contributorId":16744,"corporation":false,"usgs":true,"family":"Koracin","given":"Darko","email":"","affiliations":[],"preferred":false,"id":489883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dorman, Clive E.","contributorId":13134,"corporation":false,"usgs":true,"family":"Dorman","given":"Clive","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":489882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewis, John M.","contributorId":94970,"corporation":false,"usgs":true,"family":"Lewis","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":489886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hudson, James G.","contributorId":17528,"corporation":false,"usgs":true,"family":"Hudson","given":"James","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":489884,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilcox, Eric M.","contributorId":60533,"corporation":false,"usgs":true,"family":"Wilcox","given":"Eric","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":489885,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Torregrosa, Alicia A. 0000-0001-7361-2241 atorregrosa@usgs.gov","orcid":"https://orcid.org/0000-0001-7361-2241","contributorId":3471,"corporation":false,"usgs":true,"family":"Torregrosa","given":"Alicia","email":"atorregrosa@usgs.gov","middleInitial":"A.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":489881,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70073561,"text":"sir20145009 - 2014 - Effects of land use, stream habitat, and water quality on biological communities of wadeable streams in the Illinois River Basin of Arkansas, 2011 and 2012","interactions":[],"lastModifiedDate":"2014-02-04T09:23:47","indexId":"sir20145009","displayToPublicDate":"2014-02-03T12:38:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5009","title":"Effects of land use, stream habitat, and water quality on biological communities of wadeable streams in the Illinois River Basin of Arkansas, 2011 and 2012","docAbstract":"The Illinois River Basin includes an area of diverse land use in northwestern Arkansas. Land-use data collected in 2006 indicate that most of the land in the basin is agricultural. The agricultural land is used primarily for production of poultry and cattle.
\nEighteen sites were selected from the list of candidate sites based on drainage area, land use, presence or absence of an upstream wastewater-treatment plant, water quality, and other information gathered during the reconnaissance. An important consideration in the process was to select sites along gradients of forest to urban land use and forest to agricultural land use. Water-quality samples were collected for analysis of nutrients, and a multiparameter field meter was used to measure water temperature, specific conductance, pH, and dissolved oxygen. Streamflow was measured immediately following the water-quality sampling. Macroalgae coverage was estimated and periphyton, macroinvertebrate, and fish communities were sampled at each site. Stream habitat also was assessed.
\nMany types of land-use, water-quality, and habitat factors affected one or more aspects of the biological communities. Several macroinvertebrate and fish metrics changed in response to changes in percent forest; sites that would be considered most disturbed, based on these metrics, are sites with the highest percentages of urban land use in their associated basins.
\nThe presence of large mats of macroalgae was one of the most noticeable biological characteristics in several streams within the Illinois River Basin. The highest macroalgae percent cover values were recorded at four sites downstream from wastewater-treatment plants. Macroalgae percent cover was strongly correlated only with bed substrate size, canopy closure, and specific conductance.
\nPeriphyton metrics were most often and most strongly correlated with riparian shading, specific conductance, substrate turbidity, percent agriculture, poultry house density, and unpaved road density; some of these factors were strongly correlated with percent forest, percent urban, or percent agriculture. Total biovolume of periphyton was not strongly correlated with any of the land use, habitat, or water-quality factors assessed in the present study. Although algal growth typically increases with higher nutrient concentrations and less shading, the standing crop of periphyton on rocks can be reduced by herbivorous macroinvertebrates and fish, which may explain why total biovolume in Ozark streams was not strongly affected by water-quality (or other habitat) factors.
\nA macroinvertebrate index and several macroinvertebrate metrics were adversely affected by increasing urban and agricultural land use and associated environmental factors. Factors most commonly affecting the index and metrics included factors associated with water quality, stream geometry, sediment, land-use percentages, and road density. In general, the macroinvertebrate index was higher (indicative of least disturbance) at sites with greater percentages of forest in their basins, lower percentages of urban land in their basins, and lower paved road density. Upstream wastewater-treatment plants affected several metrics. For example, three of the five lowest macroinvertebrate index scores, two of the five lowest percent predator values, and two of the five highest percent gatherer-collector values were at sites downstream from wastewater-treatment plants.
\nThe Ozark Highlands fish index of biotic integrity and several fish metrics were adversely affected by increasing urban and agricultural land use and associated factors. Factors affecting these metrics included factors associated with nutrients, sediment, and shading. In general, the fish index of biotic integrity was higher at sites with higher percentages of forest in their basins, lower percentages of urban land in their basins, higher unpaved road density, and lower paved and total road density. Upstream wastewater-treatment plants seemed to affect some fish community metrics substantially but had little effect on other metrics. For example, three of the five lowest relative abundances of lithophilic spawner minus stonerollers and four of the five highest stoneroller abundances were at sites downstream from wastewater-treatment plants.
\nInterpretations of the results of the study described in this report are limited by a number of factors. These factors individually and collectively add to uncertainty and variability in the responses to various environmental stresses. Notwithstanding the limiting factors, the biological responses of macroalgae cover and periphyton, macroinvertebrate, and fish metrics to environmental variables provide multiple lines of evidence that biological communities of these streams are affected by recent and ongoing land-use practices.
\nFor several biological metrics there appears to be a threshold of about 40 to 50 percent forest where values of these metrics change in magnitude. However, the four sites with more than 50 percent forest in their basins were the four sites sampled in late May–early June of 2012 (rather than July–August of 2011). The relative influence of season and forest percentage on the biological communities at these sites is unknown.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145009","issn":"2328-032","collaboration":"Prepared in cooperation with the Illinois River Watershed Partnership","usgsCitation":"Petersen, J., Justus, B., and Meredith, B.J., 2014, Effects of land use, stream habitat, and water quality on biological communities of wadeable streams in the Illinois River Basin of Arkansas, 2011 and 2012: U.S. Geological Survey Scientific Investigations Report 2014-5009, viii, 89 p., https://doi.org/10.3133/sir20145009.","productDescription":"viii, 89 p.","numberOfPages":"101","onlineOnly":"Y","temporalStart":"2011-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-052375","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":281886,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5009/"},{"id":281888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145009.jpg"},{"id":281887,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5009/pdf/sir2014-5009.pdf"}],"scale":"24000","datum":"North American Datum of 1983","country":"United States","state":"Arkansas","otherGeospatial":"Illinois River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.666667,35.75 ], [ -94.666667,36.5 ], [ -94.0,36.5 ], [ -94.0,35.75 ], [ -94.666667,35.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd56d7e4b0b290850f72ad","contributors":{"authors":[{"text":"Petersen, James C. petersen@usgs.gov","contributorId":2437,"corporation":false,"usgs":true,"family":"Petersen","given":"James C.","email":"petersen@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":488922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Justus, B. G. 0000-0002-3458-9656 bjustus@usgs.gov","orcid":"https://orcid.org/0000-0002-3458-9656","contributorId":2052,"corporation":false,"usgs":true,"family":"Justus","given":"B. G.","email":"bjustus@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":488921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meredith, Bradley J. bmeredith@usgs.gov","contributorId":5515,"corporation":false,"usgs":true,"family":"Meredith","given":"Bradley","email":"bmeredith@usgs.gov","middleInitial":"J.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488923,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70057875,"text":"sir20135205 - 2014 - Suspended-sediment concentrations, loads, total suspended solids, turbidity, and particle-size fractions for selected rivers in Minnesota, 2007 through 2011","interactions":[],"lastModifiedDate":"2014-02-03T11:49:59","indexId":"sir20135205","displayToPublicDate":"2014-02-03T11:44:00","publicationYear":"2014","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":"2013-5205","title":"Suspended-sediment concentrations, loads, total suspended solids, turbidity, and particle-size fractions for selected rivers in Minnesota, 2007 through 2011","docAbstract":"Sediment-laden rivers and streams pose substantial environmental and economic challenges. Excessive sediment transport in rivers causes problems for flood control, soil conservation, irrigation, aquatic health, and navigation, and transports harmful contaminants like organic chemicals and eutrophication-causing nutrients. In Minnesota, more than 5,800 miles of streams are identified as impaired by the Minnesota Pollution Control Agency (MPCA) due to elevated levels of suspended sediment.\n\nThe U.S. Geological Survey, in cooperation with the MPCA, established a sediment monitoring network in 2007 and began systematic sampling of suspended-sediment concentrations (SSC), total suspended solids (TSS), and turbidity in rivers across Minnesota to improve the understanding of fluvial sediment transport relations. Suspended-sediment samples collected from 14 sites from 2007 through 2011 indicated that the Zumbro River at Kellogg in the driftless region of southeast Minnesota had the highest mean SSC of 226 milligrams per liter (mg/L) followed by the Minnesota River at Mankato with a mean SSC of 193 mg/L. During the 2011 spring runoff, the single highest SSC of 1,250 mg/L was measured at the Zumbro River. The lowest mean SSC of 21 mg/L was measured at Rice Creek in the northern Minneapolis- St. Paul metropolitan area.\n\nTotal suspended solids (TSS) have been used as a measure of fluvial sediment by the MPCA since the early 1970s; however, TSS concentrations have been determined to underrepresent the amount of suspended sediment. Because of this, the MPCA was interested in quantifying the differences between SSC and TSS in different parts of the State. Comparisons between concurrently sampled SSC and TSS indicated significant differences at every site, with SSC on average two times larger than TSS concentrations. The largest percent difference between SSC and TSS was measured at the South Branch Buffalo River at Sabin, and the smallest difference was observed at the Des Moines River at Jackson.\n\nRegression analysis indicated that 7 out of 14 sites had poor or no relation between SSC and streamflow. Only two sites, the Knife River and the Wild Rice River at Twin Valley, had strong correlations between SSC and streamflow, with coefficient of determination (R2) values of 0.82 and 0.80, respectively. In contrast, turbidity had moderate to strong relations with SSC at 10 of 14 sites and was superior to streamflow for estimating SSC at all sites. These results indicate that turbidity may be beneficial as a surrogate for SSC in many of Minnesota’s rivers.\n\nSuspended-sediment loads and annual basin yields indicated that the Minnesota River had the largest average annual sediment load of 1.8 million tons per year and the largest mean annual sediment basin yield of 120 tons of sediment per year per square mile. Annual TSS loads were considerably lower than suspended-sediment loads. Overall, the largest suspended-sediment and TSS loads were transported during spring snowmelt runoff, although loads during the fall and summer seasons occasionally exceeded spring runoff at some sites.\n\nThis study provided data from which to characterize suspended sediment across Minnesota’s diverse geographical settings. The data analysis improves understanding of sediment transport relations, provides information for improving sediment budgets, and documents baseline data to aid in understanding the effects of future land use/land cover on water quality. Additionally, the data provides insight from which to evaluate the effectiveness and efficiency of best management practices at the watershed scale.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135205","issn":"2328-0328","collaboration":"Prepared in cooperation with the Minnesota Pollution Control Agency","usgsCitation":"Ellison, C.A., Savage, B.E., and Johnson, G.D., 2014, Suspended-sediment concentrations, loads, total suspended solids, turbidity, and particle-size fractions for selected rivers in Minnesota, 2007 through 2011: U.S. Geological Survey Scientific Investigations Report 2013-5205, vii, 56 p., https://doi.org/10.3133/sir20135205.","productDescription":"vii, 56 p.","numberOfPages":"68","onlineOnly":"Y","temporalStart":"2007-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-044991","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":281884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135205.jpg"},{"id":281882,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5205/"},{"id":281883,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5205/pdf/sir2013-5205.pdf"}],"datum":"North American Datum of 1983","country":"United States","state":"Minnesota","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.24,43.5 ], [ -97.24,49.38 ], [ -89.49,49.38 ], [ -89.49,43.5 ], [ -97.24,43.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7626e4b0b2908510ab4a","contributors":{"authors":[{"text":"Ellison, Christopher A. 0000-0002-5886-6654 cellison@usgs.gov","orcid":"https://orcid.org/0000-0002-5886-6654","contributorId":4891,"corporation":false,"usgs":true,"family":"Ellison","given":"Christopher","email":"cellison@usgs.gov","middleInitial":"A.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":486902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savage, Brett E. besavage@usgs.gov","contributorId":5188,"corporation":false,"usgs":true,"family":"Savage","given":"Brett","email":"besavage@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Gregory D.","contributorId":46349,"corporation":false,"usgs":true,"family":"Johnson","given":"Gregory","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":486904,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70055725,"text":"sir20135194 - 2014 - Simulation and validation of larval sucker dispersal and retention through the restored Williamson River Delta and Upper Klamath Lake system, Oregon","interactions":[],"lastModifiedDate":"2014-02-03T10:53:34","indexId":"sir20135194","displayToPublicDate":"2014-02-03T10:52:00","publicationYear":"2014","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":"2013-5194","title":"Simulation and validation of larval sucker dispersal and retention through the restored Williamson River Delta and Upper Klamath Lake system, Oregon","docAbstract":"A hydrodynamic model with particle tracking was used to create individual-based simulations to describe larval fish dispersal through the restored Williamson River Delta and into Upper Klamath Lake, Oregon. The model was verified by converting particle ages to larval lengths and comparing these lengths to lengths of larvae in net catches. Correlations of simulated lengths with field data were moderate and suggested a species-specific difference in model performance. Particle trajectories through the delta were affected by wind speed and direction, lake elevation, and shoreline configuration. Once particles entered the lake, transport was a function of current speed and whether behavior enhanced transport (swimming aligned with currents) or countered transport through greater dispersal (faster random swimming). We tested sensitivity to swim speed (higher speeds led to greater dispersal and more retention), shoreline configuration (restoration increased retention relative to pre-restoration conditions), and lake elevation (retention was maximized at an intermediate elevation). The simulations also highlight additional biological questions, such as the extent to which spatially heterogeneous mortality or fish behavior and environmental cues could interact with wind-driven currents and contribute to patterns of dispersal.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135194","issn":"2328-0328","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Wood, T.M., Hendrixson, H.A., Markle, D.F., Erdman, C.S., Burdick, S.M., and Ellsworth, C.M., 2014, Simulation and validation of larval sucker dispersal and retention through the restored Williamson River Delta and Upper Klamath Lake system, Oregon: U.S. Geological Survey Scientific Investigations Report 2013-5194, Report: v, 33 p.; Appendix A, https://doi.org/10.3133/sir20135194.","productDescription":"Report: v, 33 p.; Appendix A","numberOfPages":"41","onlineOnly":"Y","ipdsId":"IP-045337","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":281864,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5194/section9.html"},{"id":281862,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5194/"},{"id":281863,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5194/pdf/sir2013-5194.pdf"},{"id":281865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135194.PNG"}],"country":"United States","state":"Oregon","otherGeospatial":"Klamath Lake;Williamson River Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.166667,42.166667 ], [ -122.166667,42.583333 ], [ -121.666667,42.583333 ], [ -121.666667,42.166667 ], [ -122.166667,42.166667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd72d5e4b0b290851088ff","contributors":{"authors":[{"text":"Wood, Tamara M. 0000-0001-6057-8080 tmwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6057-8080","contributorId":1164,"corporation":false,"usgs":true,"family":"Wood","given":"Tamara","email":"tmwood@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hendrixson, Heather A.","contributorId":43602,"corporation":false,"usgs":true,"family":"Hendrixson","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":486242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Markle, Douglas F.","contributorId":14530,"corporation":false,"usgs":true,"family":"Markle","given":"Douglas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":486240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erdman, Charles S.","contributorId":66102,"corporation":false,"usgs":true,"family":"Erdman","given":"Charles","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":486243,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burdick, Summer M. 0000-0002-3480-5793 sburdick@usgs.gov","orcid":"https://orcid.org/0000-0002-3480-5793","contributorId":3448,"corporation":false,"usgs":true,"family":"Burdick","given":"Summer","email":"sburdick@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":486239,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellsworth, Craig M.","contributorId":14913,"corporation":false,"usgs":true,"family":"Ellsworth","given":"Craig","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":486241,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70048917,"text":"ds69CC - 2014 - National Assessment of Oil and Gas Project: geologic assessment of undiscovered gas hydrate resources on the North Slope, Alaska","interactions":[],"lastModifiedDate":"2024-07-23T17:45:51.242","indexId":"ds69CC","displayToPublicDate":"2014-02-03T10:22:00","publicationYear":"2014","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":"69","chapter":"CC","title":"National Assessment of Oil and Gas Project: geologic assessment of undiscovered gas hydrate resources on the North Slope, Alaska","docAbstract":"Scientists with the U.S. Geological Survey have completed the first assessment of the undiscovered, technically recoverable gas hydrate resources beneath the North Slope of Alaska. This assessment indicates the existence of technically recoverable gas hydrate resources—that is, resources that can be discovered, developed, and produced using current technology.\n\nThe approach used in this assessment followed standard geology-based USGS methodologies developed to assess conventional oil and gas resources. In order to use the USGS conventional assessment approach on gas hydrate resources, three-dimensional industry-acquired seismic data were analyzed. The analyses indicated that the gas hydrates on the North Slope occupy limited, discrete volumes of rock bounded by faults and downdip water contacts. This assessment approach also assumes that the resource can be produced by existing conventional technology, on the basis of limited field testing and numerical production models of gas hydrate-bearing reservoirs.\n\nThe area assessed in northern Alaska extends from the National Petroleum Reserve in Alaska on the west through the Arctic National Wildlife Refuge on the east and from the Brooks Range northward to the State-Federal offshore boundary (located 3 miles north of the coastline). This area consists mostly of Federal, State, and Native lands covering 55,894 square miles. Using the standard geology-based assessment methodology, the USGS estimated that the total undiscovered technically recoverable natural-gas resources in gas hydrates in northern Alaska range between 25.2 and 157.8 trillion cubic feet, representing 95 percent and 5 percent probabilities of greater than these amounts, respectively, with a mean estimate of 85.4 trillion cubic feet.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds69CC","collaboration":"Available on CD-ROM contact Energy Team CD Distribution","usgsCitation":"USGS AK Gas Hydrate Assessment Team: Collett, T.S., Agena, W.F., Lee, M.W., Lewis, K.A., Zyrianova, M.V., Bird, K.J., Charpentier, R., Cook, T.A., Houseknecht, D.W., Klett, T., and Pollastro, R.M., 2014, National Assessment of Oil and Gas Project: geologic assessment of undiscovered gas hydrate resources on the North Slope, Alaska: U.S. Geological Survey Data Series 69, Report: vii, 101 p.; ReadMe; Executive Summary; CD-ROM .zip, https://doi.org/10.3133/ds69CC.","productDescription":"Report: vii, 101 p.; ReadMe; Executive Summary; CD-ROM .zip","numberOfPages":"111","ipdsId":"IP-039154","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":431363,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IOB90O","text":"USGS data release","linkHelpText":"Limits of the Gas Hydrate stability zone contour lines"},{"id":431362,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P962NZTI","text":"USGS data release","linkHelpText":"Total Petroleum Systems"},{"id":431361,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IQPTP7","text":"USGS data release","linkHelpText":"Assessment Units"},{"id":281872,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-cc/CD-ROM/REPORTS/DDS-69-CC.pdf"},{"id":281867,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-cc/"},{"id":281874,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-cc/CD-ROM/REPORTS/DDS-69_CC_EXECUTIVE_SUMMARY.pdf","text":"Executive Summary","linkFileType":{"id":1,"text":"pdf"}},{"id":281875,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-cc/CD-ROM.zip","text":"CD-ROM","linkFileType":{"id":6,"text":"zip"}},{"id":281873,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-cc/CD-ROM/READ_ME/READ_ME.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":281876,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds69cc.jpg"}],"projection":"Albers Conical Equal area projection","datum":"North American Datum of 1983","country":"United States","state":"Alaska","otherGeospatial":"North Slope","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -168.0,68.0 ], [ -168.0,72.0 ], [ -140.0,72.0 ], [ -140.0,68.0 ], [ -168.0,68.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517057e4b05569d805a33d","contributors":{"authors":[{"text":"USGS AK Gas Hydrate Assessment Team: Collett, Timothy S.","contributorId":25465,"corporation":false,"usgs":true,"family":"USGS AK Gas Hydrate Assessment Team: Collett","given":"Timothy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":485809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agena, Warren F. wagena@usgs.gov","contributorId":3181,"corporation":false,"usgs":true,"family":"Agena","given":"Warren","email":"wagena@usgs.gov","middleInitial":"F.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":485805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Myung Woong","contributorId":15114,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"","middleInitial":"Woong","affiliations":[],"preferred":false,"id":485807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, Kristen A. 0000-0003-4991-3399 klewis@usgs.gov","orcid":"https://orcid.org/0000-0003-4991-3399","contributorId":4120,"corporation":false,"usgs":true,"family":"Lewis","given":"Kristen","email":"klewis@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":485806,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zyrianova, Margarita V. 0000-0002-3669-1320 rita@usgs.gov","orcid":"https://orcid.org/0000-0002-3669-1320","contributorId":1203,"corporation":false,"usgs":true,"family":"Zyrianova","given":"Margarita","email":"rita@usgs.gov","middleInitial":"V.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":485804,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bird, Kenneth J. kbird@usgs.gov","contributorId":1015,"corporation":false,"usgs":true,"family":"Bird","given":"Kenneth","email":"kbird@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":485803,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Charpentier, Ronald R. charpentier@usgs.gov","contributorId":934,"corporation":false,"usgs":true,"family":"Charpentier","given":"Ronald R.","email":"charpentier@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":485802,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cook, Troy A.","contributorId":52519,"corporation":false,"usgs":true,"family":"Cook","given":"Troy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":485810,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":485800,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Klett, Timothy R. 0000-0001-9779-1168 tklett@usgs.gov","orcid":"https://orcid.org/0000-0001-9779-1168","contributorId":709,"corporation":false,"usgs":true,"family":"Klett","given":"Timothy R.","email":"tklett@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":485801,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pollastro, Richard M.","contributorId":25100,"corporation":false,"usgs":true,"family":"Pollastro","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":485808,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70058700,"text":"70058700 - 2014 - Variables that affect agricultural chemicals in groundwater in Nebraska","interactions":[],"lastModifiedDate":"2014-02-05T10:05:21","indexId":"70058700","displayToPublicDate":"2014-02-02T13:20:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Variables that affect agricultural chemicals in groundwater in Nebraska","docAbstract":"Agricultural chemicals from nonpoint\nsources in groundwater are present in the major provinces\nof the High Plains aquifer in Nebraska. Nitrate and\ntriazine-herbicide concentrations in groundwater were\nassessed to establish preliminary relations between these\nconstituents and selected hydrogeologic, climatic, and\nland-use variables. Also, macropore flow paths were\nmeasured in an attempt to delineate their contribution\nto non-point source pollution from the study areas.\nWater from 82 wells in six study areas was analyzed\nfor nitrate; water from 57 of the 82 wells was analyzed\nfor triazine herbicides. Twenty-one independent variables\nwere identified that could potentially affect chemical\nconcentrations in groundwater. Data for 9 of 21\nindependent variables suspected of affecting concentrations\nof nitrate and triazine herbicides in groundwater\nwere collected from the well sites. The nine variables\nand their measured ranges were hydraulic gradient,\n0.0006–0.0053; hydraulic conductivity, 1.5–45.4 m\n(5–149 ft) per day; specific discharge, 0.004–0.091 m\n(0.0128–0.2998 ft) per day; depth to water, 0.91–76 m\n(3–250 ft); well depth, 12–168 m (40–550 ft); annual\nprecipitation, 30–100 cm (12.0–39.3 in.); soil permeability,\n1.9–23 cm (0.76–9.0 in.); irrigation-well density,\n0–8 irrigation wells per 2.59 km2 (1 square mile); and\nannual nitrogen fertilizer use, 0–118 kg (0–260 lb) of\nnitrogen per acre. Macropore flow is listed in percent,\naverage per study area based on determinations from\ndye studies. In this instance, macropore flow is used to\nalso entail preferential flow paths. Nitrate concentrations\nranged from 0.1 to 45 mgL−1. Triazine-herbicide concentrations\nwere detected in samples from five of the six\nstudy areas in concentrations ranging from 0.1 to\n2.3 μL−1. Analysis indicated that there were significant\ndifferences in nitrate concentrations (averages-at 95 %\nconfidence level using Kendall Test) among the six\nstudy areas; no significant differences in triazineherbicide\nconcentrations were found. Concentrations\nof nitrate and triazine herbicide were determined (using\ncontingency-table analysis), to be significantly larger in\nmore intensively irrigated areas compared to less intensively\nirrigated areas. Preliminary correlations with the\nindependent variables and nitrate concentrations indicated\nsignificant relations at the 95%confidence level with\nvariables hydraulic conductivity, well depth, and irrigation\nwell density. Correlations with triazine-herbicide\nconcentrations indicated significant relations with hydraulic\nconductivity, specific discharge, well depth, annual\nprecipitation, and irrigation well density, as well as\nnitrate concentrations. Simple multiple-regression technique\nindicated that well depth and density and fertilizer\nuse explained about 51 % of the variation in nitrate\nconcentrations. Specific discharge and well depth explained\nabout 60 % of the variation in triazine-herbicide\nconcentrations. Macropore flow paths and specific discharge\nexplained 84 % of the total variation in triazineherbicide\nconcentrations. The use of trade names in this\nreport is for identification purposes only and does not\nconstitute endorsement by the U.S. Geological Survey.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water, Air, and Soil Pollution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s11270-013-1862-0","usgsCitation":"Tindall, J.A., and Chen, A., 2014, Variables that affect agricultural chemicals in groundwater in Nebraska: Water, Air, & Soil Pollution, v. 255, no. 1862, 18 p., https://doi.org/10.1007/s11270-013-1862-0.","productDescription":"18 p.","ipdsId":"IP-051590","costCenters":[{"id":435,"text":"National Research Program - Central Region","active":false,"usgs":true}],"links":[{"id":281991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281990,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11270-013-1862-0"}],"country":"United States","state":"Nebraska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.0535,39.9999 ], [ -104.0535,43.0017 ], [ -95.3083,43.0017 ], [ -95.3083,39.9999 ], [ -104.0535,39.9999 ] ] ] } } ] }","volume":"255","issue":"1862","noUsgsAuthors":false,"publicationDate":"2014-02-02","publicationStatus":"PW","scienceBaseUri":"5351706de4b05569d805a439","contributors":{"authors":[{"text":"Tindall, James A. 0000-0002-0940-1586 jtindall@usgs.gov","orcid":"https://orcid.org/0000-0002-0940-1586","contributorId":2529,"corporation":false,"usgs":true,"family":"Tindall","given":"James","email":"jtindall@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":487249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Abraham","contributorId":73918,"corporation":false,"usgs":true,"family":"Chen","given":"Abraham","affiliations":[],"preferred":false,"id":487250,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70126396,"text":"70126396 - 2014 - Evaluation of a combined macrophyte–epiphyte bioassay for assessing nutrient enrichment in the Portneuf River, Idaho, USA","interactions":[],"lastModifiedDate":"2017-01-11T15:44:36","indexId":"70126396","displayToPublicDate":"2014-02-02T10:01:50","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a combined macrophyte–epiphyte bioassay for assessing nutrient enrichment in the Portneuf River, Idaho, USA","docAbstract":"We describe and evaluate a laboratory bioassay that uses Lemna minor L. and attached epiphytes to characterize the status of ambient and nutrient-enriched water from the Portneuf River, Idaho. Specifically, we measured morphological (number of fronds, longest surface axis, and root length) and population-level (number of plants and dry mass) responses of L. minor and community-level (ash-free dry mass [AFDM] and chlorophyll a [Chl a]) responses of epiphytes to nutrient enrichment. Overall, measures of macrophyte biomass and abundance increased with increasing concentrations of dissolved phosphorus (P) and responded more predictably to nutrient enrichment than morphological measures. Epiphyte AFDM and Chl a were also greatest in P-enriched water; enrichments of N alone produced no measurable epiphytic response. The epiphyte biomass response did not directly mirror macrophyte biomass responses, illustrating the value of a combined macrophyte–epiphyte assay to more fully evaluate nutrient management strategies. Finally, the most P-enriched waters not only supported greater standing stocks of macrophyte and epiphytes but also had significantly higher water column dissolved oxygen and dissolved organic carbon concentrations and a lower pH. Advantages of this macrophyte–epiphyte bioassay over more traditional single-species assays include the use of a more realistic level of biological organization, a relatively short assay schedule (~10 days), and the inclusion of multiple biological response and water-quality measures.
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Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":627,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":583576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castiglione, Chris","contributorId":150899,"corporation":false,"usgs":false,"family":"Castiglione","given":"Chris","email":"","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":583577,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70108143,"text":"70108143 - 2014 - Snow conditions as an estimator of the breeding output in high-Arctic pink-footed geese Anser brachyrhynchus","interactions":[],"lastModifiedDate":"2014-05-22T15:46:23","indexId":"70108143","displayToPublicDate":"2014-02-01T15:40:29","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3093,"text":"Polar Biology","active":true,"publicationSubtype":{"id":10}},"title":"Snow conditions as an estimator of the breeding output in high-Arctic pink-footed geese Anser brachyrhynchus","docAbstract":"The Svalbard-breeding population of pink-footed geese Anser brachyrhynchus has increased during the last decades and is giving rise to agricultural conflicts along their migration route, as well as causing grazing impacts on tundra vegetation. An adaptive flyway management plan has been implemented, which will be based on predictive population models including environmental variables expected to affect goose population development, such as weather conditions on the breeding grounds. A local study in Svalbard showed that snow cover prior to egg laying is a crucial factor for the reproductive output of pink-footed geese, and MODIS satellite images provided a useful estimator of snow cover. In this study, we up-scaled the analysis to the population level by examining various measures of snow conditions and compared them with the overall breeding success of the population as indexed by the proportion of juveniles in the autumn population. As explanatory variables, we explored MODIS images, satellite-based radar measures of onset of snow melt, winter NAO index, and the May temperature sum and May thaw days. To test for the presence of density dependence, we included the number of adults in the population. For 2000–2011, MODIS-derived snow cover (available since 2000) was the strongest indicator of breeding conditions. For 1981–2011, winter NAO and May thaw days had equal weight. Interestingly, there appears to have been a phase shift from density-dependent to density-independent reproduction, which is consistent with a hypothesis of released breeding potential due to the recent advancement of spring in Svalbard.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Polar Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00300-013-1404-7","usgsCitation":"Jensen, G.H., Madsen, J., Johnson, F.A., and Tamstorf, M.P., 2014, Snow conditions as an estimator of the breeding output in high-Arctic pink-footed geese Anser brachyrhynchus: Polar Biology, v. 37, no. 1, p. 1-14, https://doi.org/10.1007/s00300-013-1404-7.","productDescription":"14 p.","startPage":"1","endPage":"14","numberOfPages":"14","ipdsId":"IP-038881","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":473178,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00300-013-1404-7","text":"Publisher Index Page"},{"id":287543,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00300-013-1404-7"},{"id":287544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Norway","otherGeospatial":"Svalbard","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 10.08,75.96 ], [ 10.08,80.89 ], [ 33.98,80.89 ], [ 33.98,75.96 ], [ 10.08,75.96 ] ] ] } } ] }","volume":"37","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-11-16","publicationStatus":"PW","scienceBaseUri":"537f1c64e4b021317a86e301","contributors":{"authors":[{"text":"Jensen, Gitte Hoj","contributorId":99472,"corporation":false,"usgs":true,"family":"Jensen","given":"Gitte","email":"","middleInitial":"Hoj","affiliations":[],"preferred":false,"id":493969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madsen, Jesper","contributorId":9950,"corporation":false,"usgs":true,"family":"Madsen","given":"Jesper","affiliations":[],"preferred":false,"id":493967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":493966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tamstorf, Mikkel P.","contributorId":43674,"corporation":false,"usgs":true,"family":"Tamstorf","given":"Mikkel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":493968,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70115921,"text":"70115921 - 2014 - Performance of several low-cost accelerometers","interactions":[],"lastModifiedDate":"2014-07-08T15:38:14","indexId":"70115921","displayToPublicDate":"2014-02-01T15:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Performance of several low-cost accelerometers","docAbstract":"Several groups are implementing low‐cost host‐operated systems of strong‐motion accelerographs to support the somewhat divergent needs of seismologists and earthquake engineers. The Advanced National Seismic System Technical Implementation Committee (ANSS TIC, 2002), managed by the U.S. Geological Survey (USGS) in cooperation with other network operators, is exploring the efficacy of such systems if used in ANSS networks. To this end, ANSS convened a working group to explore available Class C strong‐motion accelerometers (defined later), and to consider operational and quality control issues, and the means of annotating, storing, and using such data in ANSS networks. The working group members are largely coincident with our author list, and this report informs instrument‐performance matters in the working group’s report to ANSS. Present examples of operational networks of such devices are the Community Seismic Network (CSN; csn.caltech.edu), operated by the California Institute of Technology, and Quake‐Catcher Network (QCN; Cochran et al., 2009; qcn.stanford.edu; November 2013), jointly operated by Stanford University and the USGS. Several similar efforts are in development at other institutions. The overarching goals of such efforts are to add spatial density to existing Class‐A and Class‐B (see next paragraph) networks at low cost, and to include many additional people so they become invested in the issues of earthquakes, their measurement, and the damage they cause.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Seismological Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220130091","usgsCitation":"Evans, J., Allen, R.M., Chung, A.I., Cochran, E., Guy, R., Hellweg, M., and Lawrence, J.F., 2014, Performance of several low-cost accelerometers: Seismological Research Letters, v. 85, no. 1, p. 147-158, https://doi.org/10.1785/0220130091.","productDescription":"12 p.","startPage":"147","endPage":"158","numberOfPages":"12","ipdsId":"IP-049369","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":473179,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.caltech.edu/CaltechAUTHORS:20140206-094054383","text":"External Repository"},{"id":289566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289538,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0220130091"}],"volume":"85","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-01-02","publicationStatus":"PW","scienceBaseUri":"53bd12efe4b00cbf31f72357","contributors":{"authors":[{"text":"Evans, J.R.","contributorId":50526,"corporation":false,"usgs":true,"family":"Evans","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":495685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, R. 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