{"pageNumber":"525","pageRowStart":"13100","pageSize":"25","recordCount":46670,"records":[{"id":70104182,"text":"70104182 - 2014 - Phytoplankton primary production in the world's estuarine-coastal ecosystems","interactions":[],"lastModifiedDate":"2014-05-12T14:15:49","indexId":"70104182","displayToPublicDate":"2014-05-12T14:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Phytoplankton primary production in the world's estuarine-coastal ecosystems","docAbstract":"<p>Estuaries are biogeochemical hot spots because they receive large inputs of nutrients and organic carbon from land and oceans to support high rates of metabolism and primary production. We synthesize published rates of annual phytoplankton primary production (APPP) in marine ecosystems influenced by connectivity to land – estuaries, bays, lagoons, fjords and inland seas. Review of the scientific literature produced a compilation of 1148 values of APPP derived from monthly incubation assays to measure carbon assimilation or oxygen production. The median value of median APPP measurements in 131 ecosystems is 185 and the mean is 252 g C m<sup>−2</sup> yr<sup>−1</sup>, but the range is large: from −105 (net pelagic production in the Scheldt Estuary) to 1890 g C m<sup>−2</sup> yr</sup>−1</sup> (net phytoplankton production in Tamagawa Estuary). APPP varies up to 10-fold within ecosystems and 5-fold from year to year (but we only found eight APPP series longer than a decade so our knowledge of decadal-scale variability is limited). We use studies of individual places to build a conceptual model that integrates the mechanisms generating this large variability: nutrient supply, light limitation by turbidity, grazing by consumers, and physical processes (river inflow, ocean exchange, and inputs of heat, light and wind energy). We consider method as another source of variability because the compilation includes values derived from widely differing protocols. A simulation model shows that different methods reported in the literature can yield up to 3-fold variability depending on incubation protocols and methods for integrating measured rates over time and depth. </p>\n<br/>\n<p>Although attempts have been made to upscale measures of estuarine-coastal APPP, the empirical record is inadequate for yielding reliable global estimates. The record is deficient in three ways. First, it is highly biased by the large number of measurements made in northern Europe (particularly the Baltic region) and North America. Of the 1148 reported values of APPP, 958 come from sites between 30 and 60° N; we found only 36 for sites south of 20° N. Second, of the 131 ecosystems where APPP has been reported, 37% are based on measurements at only one location during 1 year. The accuracy of these values is unknown but probably low, given the large interannual and spatial variability within ecosystems. Finally, global assessments are confounded by measurements that are not intercomparable because they were made with different methods. </p>\n<br/>\n<p>Phytoplankton primary production along the continental margins is tightly linked to variability of water quality, biogeochemical processes including ocean–atmosphere CO<sub>2</sub> exchange, and production at higher trophic levels including species we harvest as food. The empirical record has deficiencies that preclude reliable global assessment of this key Earth system process. We face two grand challenges to resolve these deficiencies: (1) organize and fund an international effort to use a common method and measure APPP regularly across a network of coastal sites that are globally representative and sustained over time, and (2) integrate data into a unifying model to explain the wide range of variability across ecosystems and to project responses of APPP to regional manifestations of global change as it continues to unfold.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Copernicus Publications on behalf of the European Geosciences Union","doi":"10.5194/bg-11-2477-2014","usgsCitation":"Cloern, J.E., Foster, S., and Kleckner, A., 2014, Phytoplankton primary production in the world's estuarine-coastal ecosystems: Biogeosciences, v. 11, p. 2477-2501, https://doi.org/10.5194/bg-11-2477-2014.","productDescription":"25 p.","startPage":"2477","endPage":"2501","numberOfPages":"25","ipdsId":"IP-049711","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":472998,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-11-2477-2014","text":"Publisher Index Page"},{"id":287056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287055,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/bg-11-2477-2014"}],"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":"11","noUsgsAuthors":false,"publicationDate":"2014-05-07","publicationStatus":"PW","scienceBaseUri":"5371df52e4b08449547883d9","contributors":{"authors":[{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":493615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, S.Q.","contributorId":103184,"corporation":false,"usgs":true,"family":"Foster","given":"S.Q.","email":"","affiliations":[],"preferred":false,"id":493617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleckner, A.E.","contributorId":33627,"corporation":false,"usgs":true,"family":"Kleckner","given":"A.E.","email":"","affiliations":[],"preferred":false,"id":493616,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70098153,"text":"ds832 - 2014 - A quasi-global precipitation time series for drought monitoring","interactions":[],"lastModifiedDate":"2017-03-27T15:28:17","indexId":"ds832","displayToPublicDate":"2014-05-12T12:46:00","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":"832","title":"A quasi-global precipitation time series for drought monitoring","docAbstract":"Estimating precipitation variations in space and time is an important aspect of drought early warning and environmental monitoring. An evolving drier-than-normal season must be placed in historical context so that the severity of rainfall deficits may quickly be evaluated. To this end, scientists at the U.S. Geological Survey Earth Resources Observation and Science Center, working closely with collaborators at the University of California, Santa Barbara Climate Hazards Group, have developed a quasi-global (50°S–50°N, 180°E–180°W), 0.05° resolution, 1981 to near-present gridded precipitation time series: the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) data archive.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds832","usgsCitation":"Funk, C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, iv, 4 p., https://doi.org/10.3133/ds832.","productDescription":"iv, 4 p.","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-045311","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":287054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds832.jpg"},{"id":287052,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/832/"},{"id":287053,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/832/pdf/ds832.pdf"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-50.0 ], [ -180.0,50.0 ], [ 180.0,50.0 ], [ 180.0,-50.0 ], [ -180.0,-50.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5371df50e4b08449547883ca","contributors":{"authors":[{"text":"Funk, Chris C. 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":62142,"corporation":false,"usgs":true,"family":"Funk","given":"Chris C.","affiliations":[],"preferred":false,"id":491644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Pete J.","contributorId":32453,"corporation":false,"usgs":true,"family":"Peterson","given":"Pete","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":491640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landsfeld, Martin F.","contributorId":89806,"corporation":false,"usgs":true,"family":"Landsfeld","given":"Martin","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":491646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pedreros, Diego H. 0000-0001-9943-7373","orcid":"https://orcid.org/0000-0001-9943-7373","contributorId":76654,"corporation":false,"usgs":true,"family":"Pedreros","given":"Diego","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":491645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":491638,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rowland, James D. 0000-0003-4837-3511","orcid":"https://orcid.org/0000-0003-4837-3511","contributorId":37259,"corporation":false,"usgs":true,"family":"Rowland","given":"James D.","affiliations":[],"preferred":false,"id":491643,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Romero, Bo E.","contributorId":19085,"corporation":false,"usgs":true,"family":"Romero","given":"Bo","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":491639,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Husak, Gregory J.","contributorId":34435,"corporation":false,"usgs":true,"family":"Husak","given":"Gregory","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":491641,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Michaelsen, Joel C.","contributorId":91790,"corporation":false,"usgs":true,"family":"Michaelsen","given":"Joel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":491647,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Verdin, Andrew P.","contributorId":35235,"corporation":false,"usgs":true,"family":"Verdin","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":491642,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70068724,"text":"fs20143002 - 2014 - Long-term soil monitoring at U.S. Geological Survey reference watersheds","interactions":[],"lastModifiedDate":"2014-05-09T15:07:28","indexId":"fs20143002","displayToPublicDate":"2014-05-09T15:05:00","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":"2014-3002","title":"Long-term soil monitoring at U.S. Geological Survey reference watersheds","docAbstract":"Monitoring the environment by making repeated measurements through time is essential to evaluate and track the health of ecosystems (fig. 1). Long-term datasets produced by such monitoring are indispensable for evaluating the effectiveness of environmental legislation and for designing mitigation strategies to address environmental changes in an era when human activities are altering the environment locally and globally.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143002","issn":"2327-6932","usgsCitation":"McHale, M.R., Siemion, J., Lawrence, G.B., and Mast, M.A., 2014, Long-term soil monitoring at U.S. Geological Survey reference watersheds: U.S. Geological Survey Fact Sheet 2014-3002, 2 p., https://doi.org/10.3133/fs20143002.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-045683","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":287032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143002.jpg"},{"id":287031,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3002/pdf/fs2014-3002.pdf"},{"id":287030,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3002/"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173.0,16.916667 ], [ 173.0,71.833333 ], [ -66.95,71.833333 ], [ -66.95,16.916667 ], [ 173.0,16.916667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53771793e4b02eab8669edc3","contributors":{"authors":[{"text":"McHale, Michael R. 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":1735,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siemion, Jason jsiemion@usgs.gov","contributorId":3011,"corporation":false,"usgs":true,"family":"Siemion","given":"Jason","email":"jsiemion@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":488036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488033,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70100782,"text":"fs20143032 - 2014 - Invasive lionfish use a diversity of habitats in Florida","interactions":[],"lastModifiedDate":"2016-11-22T18:43:13","indexId":"fs20143032","displayToPublicDate":"2014-05-09T10:39:00","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":"2014-3032","title":"Invasive lionfish use a diversity of habitats in Florida","docAbstract":"<p>Two species of lionfish (<i>Pterois volitans</i> and <i>Pterois miles</i>) are the first marine fishes known to invade and establish self-sustaining populations along the eastern seaboard of the United States. First documented off the coast of Florida in 1985, lionfish are now found along the Atlantic coast of the United States as well as in the Caribbean Sea and Gulf of Mexico. Although long-term effects of this invasion are not yet fully known, there is early evidence that lionfish are negatively impacting native marine life.</p><p>The lionfish invasion raises questions about which types of habitat the species will occupy in its newly invaded ecosystem. In their native range, lionfish are found primarily on coral reefs but sometimes are found in other habitats such as seagrasses and mangroves. This fact sheet documents the diversity of habitat types in which invasive lionfish have been reported within Florida’s coastal waters, based on lionfish sightings recorded in the U.S. Geological Survey Nonindigenous Aquatic Species database (USGS-NAS).<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143032","issn":"2327-6932","usgsCitation":"Schofield, P., Akins, L., Gregoire-Lucente, D.R., and Pawlitz, R.J., 2014, Invasive lionfish use a diversity of habitats in Florida: U.S. Geological Survey Fact Sheet 2014-3032, 2 p., https://doi.org/10.3133/fs20143032.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-050728","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":287024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143032.jpg"},{"id":287022,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3032/"},{"id":287023,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3032/pdf/fs2014-3032.pdf","text":"Report","size":"2.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.63,24.52 ], [ -87.63,31.0 ], [ -80.03,31.0 ], [ -80.03,24.52 ], [ -87.63,24.52 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5371ed75e4b0844954788432","contributors":{"authors":[{"text":"Schofield, Pamela J. 0000-0002-8752-2797","orcid":"https://orcid.org/0000-0002-8752-2797","contributorId":30306,"corporation":false,"usgs":true,"family":"Schofield","given":"Pamela J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":492439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Akins, Lad","contributorId":6573,"corporation":false,"usgs":true,"family":"Akins","given":"Lad","affiliations":[],"preferred":false,"id":492438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gregoire-Lucente, Denise R. dgregoire-lucente@usgs.gov","contributorId":4027,"corporation":false,"usgs":true,"family":"Gregoire-Lucente","given":"Denise","email":"dgregoire-lucente@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":492436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pawlitz, Rachel J. rpawlitz@usgs.gov","contributorId":4251,"corporation":false,"usgs":true,"family":"Pawlitz","given":"Rachel","email":"rpawlitz@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":492437,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70103833,"text":"70103833 - 2014 - Investigating the importance of sediment resuspension in <i>Alexandrium fundyense</i> cyst population dynamics in the Gulf of Maine","interactions":[],"lastModifiedDate":"2014-05-29T15:09:13","indexId":"70103833","displayToPublicDate":"2014-05-08T09:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1371,"text":"Deep-Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Investigating the importance of sediment resuspension in <i>Alexandrium fundyense</i> cyst population dynamics in the Gulf of Maine","docAbstract":"Cysts of <i>Alexandrium fundyense</i>, a dinoflagellate that causes toxic algal blooms in the Gulf of Maine, spend the winter as dormant cells in the upper layer of bottom sediment or the bottom nepheloid layer and germinate in spring to initiate new blooms. Erosion measurements were made on sediment cores collected at seven stations in the Gulf of Maine in the autumn of 2011 to explore if resuspension (by waves and currents) could change the distribution of over-wintering cysts from patterns observed in the previous autumn; or if resuspension could contribute cysts to the water column during spring when cysts are viable. The mass of sediment eroded from the core surface at 0.4 Pa ranged from 0.05 kg m<sup>−2</sup> near Grand Manan Island, to 0.35 kg m<sup>−2</sup> in northern Wilkinson Basin. The depth of sediment eroded ranged from about 0.05 mm at a station with sandy sediment at 70 m water depth on the western Maine shelf, to about 1.2 mm in clayey–silt sediment at 250 m water depth in northern Wilkinson Basin. The sediment erodibility measurements were used in a sediment-transport model forced with modeled waves and currents for the period October 1, 2010 to May 31, 2011 to predict resuspension and bed erosion. The simulated spatial distribution and variation of bottom shear stress was controlled by the strength of the semi-diurnal tidal currents, which decrease from east to west along the Maine coast, and oscillatory wave-induced currents, which are strongest in shallow water. Simulations showed occasional sediment resuspension along the central and western Maine coast associated with storms, steady resuspension on the eastern Maine shelf and in the Bay of Fundy associated with tidal currents, no resuspension in northern Wilkinson Basin, and very small resuspension in western Jordan Basin. The sediment response in the model depended primarily on the profile of sediment erodibility, strength and time history of bottom stress, consolidation time scale, and the current in the water column. Based on analysis of wave data from offshore buoys from 1996 to 2012, the number of wave events inducing a bottom shear stress large enough to resuspend sediment at 80 m ranged from 0 to 2 in spring (April and May) and 0 to 10 in winter (October through March). Wave-induced resuspension is unlikely in water greater than about 100 m deep. The observations and model results suggest that a millimeter or so of sediment and associated cysts may be mobilized in both winter and spring, and that the frequency of resuspension will vary interannually. Depending on cyst concentration in the sediment and the vertical distribution in the water column, these events could result in a concentration in the water column of at least 10<sup>4</sup> cysts m<sup>−3</sup>. In some years, resuspension events could episodically introduce cysts into the water column in spring, where germination is likely to be facilitated at the time of bloom formation. An assessment of the quantitative effects of cyst resuspension on bloom dynamics in any particular year requires more detailed investigation.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Deep-Sea Research Part II: Topical Studies in Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2013.10.011","usgsCitation":"Butman, B., Aretxabaleta, A., Dickhudt, P., Dalyander, P., Sherwood, C.R., Anderson, D.M., Keafer, B.A., and Signell, R.P., 2014, Investigating the importance of sediment resuspension in <i>Alexandrium fundyense</i> cyst population dynamics in the Gulf of Maine: Deep-Sea Research Part II: Topical Studies in Oceanography, v. 103, p. 79-95, https://doi.org/10.1016/j.dsr2.2013.10.011.","productDescription":"17 p.","startPage":"79","endPage":"95","numberOfPages":"17","ipdsId":"IP-044852","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dsr2.2013.10.011","text":"Publisher Index Page"},{"id":286986,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.dsr2.2013.10.011"},{"id":286987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada;United States","otherGeospatial":"Bay Of Fundy;Grand Manan Island;Gulf Of Maine;Jordan Basin;Wilkinson Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.488,41.5003 ], [ -71.488,45.1549 ], [ -64.4678,45.1549 ], [ -64.4678,41.5003 ], [ -71.488,41.5003 ] ] ] } } ] }","volume":"103","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536c9950e4b060efff280d88","contributors":{"authors":[{"text":"Butman, Bradford 0000-0002-4174-2073 bbutman@usgs.gov","orcid":"https://orcid.org/0000-0002-4174-2073","contributorId":943,"corporation":false,"usgs":true,"family":"Butman","given":"Bradford","email":"bbutman@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aretxabaleta, Alfredo L.","contributorId":41311,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo L.","affiliations":[],"preferred":false,"id":493447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickhudt, Patrick J.","contributorId":48302,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick J.","affiliations":[],"preferred":false,"id":493448,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":65177,"corporation":false,"usgs":true,"family":"Dalyander","given":"P. Soupy","affiliations":[],"preferred":false,"id":493449,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493446,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Donald M.","contributorId":79801,"corporation":false,"usgs":true,"family":"Anderson","given":"Donald","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493450,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keafer, Bruce A.","contributorId":102795,"corporation":false,"usgs":true,"family":"Keafer","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":493451,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Signell, Richard P. rsignell@usgs.gov","contributorId":1435,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":493445,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70148490,"text":"70148490 - 2014 - Mechanisms of aquatic species invasions across the SALCC - an update","interactions":[],"lastModifiedDate":"2016-12-19T16:44:36","indexId":"70148490","displayToPublicDate":"2014-05-08T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Mechanisms of aquatic species invasions across the SALCC - an update","docAbstract":"The USGS Nonindigenous Aquatic Species Database (NAS; nas.er.usgs.gov) is a comprehensive tool for demonstrating where and when nonindigenous species have been sighted across the U.S. Information in the database is used for state-level invasive species management plans, to focus monitoring efforts, for public education, predictive modeling, and for avoiding unintentional introductions during inter-basin water transfers.\nOur project represents the first attempt to utilize the NAS Database within the context of a Landscape Conservation Cooperative conservation blueprint. A significant amount of effort during the past year was dedicated to determining the most appropriate use of these data for the purposes of identifying the mechanisms and patterns of aquatic species invasions. Descriptive analyses were first undertaken to characterize the spatial and temporal characteristics of the SALCC subset of NAS data.","language":"English","publisher":"Southeast Atlantic Landscape Conservation Cooperative","collaboration":"Robert Doarzio; Fred Johnson; Mike Turtora; Vic Engel; Pam Fuller","usgsCitation":"Benson, A.J., 2014, Mechanisms of aquatic species invasions across the SALCC - an update, HTML.","productDescription":"HTML","ipdsId":"IP-056360","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":332298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":301092,"type":{"id":15,"text":"Index Page"},"url":"https://www.southatlanticlcc.org/profiles/blogs/mechanisms-of-aquatic-species-invasions-across-the-salcc-an"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5859000ae4b03639a6025e35","contributors":{"authors":[{"text":"Benson, Amy J. 0000-0002-4517-1466 abenson@usgs.gov","orcid":"https://orcid.org/0000-0002-4517-1466","contributorId":3836,"corporation":false,"usgs":true,"family":"Benson","given":"Amy","email":"abenson@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":548407,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70101719,"text":"ds709FF - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan","interactions":[{"subject":{"id":70101719,"text":"ds709FF - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan","indexId":"ds709FF","publicationYear":"2014","noYear":false,"chapter":"FF","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan"},"predicate":"IS_PART_OF","object":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"id":1}],"isPartOf":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"lastModifiedDate":"2022-12-09T20:57:06.961314","indexId":"ds709FF","displayToPublicDate":"2014-05-07T12:42:20","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":"709","chapter":"FF","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits.</p>\n\n<br>\n\n<p>ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement.</p>\n\n<br>\n\n<p>The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands).</p>\n\n<br>\n\n<p>All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Farah) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Farah area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Farah study area, five subareas were designated for detailed field investigations (that is, the FarahA through FarahE subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (Data Series 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709FF","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=\" http://tfbso.defense.gov/\" target=\"_blank\"> Task Force for Business and Stability Operations</a> and the <a href=\"http://www.bgs.ac.uk/AfghanMinerals/\" target=\"_blank\">Afghanistan Geological Survey</a>","usgsCitation":"Davis, P.A., 2014, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme Text; Index Maps; Image Files; Metadata Files;  Shapefiles, https://doi.org/10.3133/ds709FF.","productDescription":"HTML Document; Readme Text; Index Maps; Image Files; Metadata Files;  Shapefiles","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055960","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":286977,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709ff.jpg"},{"id":286974,"rank":11,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/ff/image_files/image_files.html","text":"Image Files"},{"id":286972,"rank":2,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/ff/1_readme.doc"},{"id":286975,"rank":1,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/ff/metadata/metadata.html"},{"id":286971,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/ff/"},{"id":286973,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/ff/index_maps/index_maps.html","text":"Index Maps"},{"id":286976,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/ff/shapefiles/shapefiles.html"}],"country":"Afghanistan","otherGeospatial":"Farah Mineral District","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              62.73978191168703,\n              32.9985359214848\n            ],\n            [\n              60.74259795471943,\n              32.9985359214848\n            ],\n            [\n              60.74259795471943,\n              31.463985777157987\n            ],\n            [\n              62.73978191168703,\n              31.463985777157987\n            ],\n            [\n              62.73978191168703,\n              32.9985359214848\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536b47d1e4b0a51a87c4b125","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":492735,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70101718,"text":"ds709EE - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan","interactions":[{"subject":{"id":70101718,"text":"ds709EE - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan","indexId":"ds709EE","publicationYear":"2014","noYear":false,"chapter":"EE","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan"},"predicate":"IS_PART_OF","object":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"id":1}],"isPartOf":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"lastModifiedDate":"2022-12-09T20:57:48.473565","indexId":"ds709EE","displayToPublicDate":"2014-05-07T12:17:00","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":"709","chapter":"EE","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits.</p>\n\n<br>\n\n<p>ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement.</p>\n\n<br>\n\n<p>The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands).</p>\n\n<br>\n\n<p>All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni2) and the WGS84 datum. The images for the Ghazni2 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (Data Series 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709EE","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=\" http://tfbso.defense.gov/\" target=\"_blank\"> Task Force for Business and Stability Operations</a> and the <a href=\"http://www.bgs.ac.uk/AfghanMinerals/\" target=\"_blank\">Afghanistan Geological Survey</a>","usgsCitation":"Davis, P.A., 2014, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme Text; Index Maps; Image Files; Metadata Files; Shapefiles, https://doi.org/10.3133/ds709EE.","productDescription":"HTML Document; Readme Text; Index Maps; Image Files; Metadata Files; Shapefiles","onlineOnly":"Y","ipdsId":"IP-054394","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":286970,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709ee.jpg"},{"id":286964,"rank":11,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/ee/","linkFileType":{"id":5,"text":"html"}},{"id":286967,"rank":4,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/ee/image_files/image_files.html","text":"Image Files","linkFileType":{"id":5,"text":"html"}},{"id":286965,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/ee/1_readme.doc"},{"id":286968,"rank":1,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/ee/metadata/metadata.html","linkFileType":{"id":5,"text":"html"}},{"id":286969,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/ee/shapefiles/shapefiles.html"},{"id":286966,"rank":1,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/ee/index_maps/index_maps.html","text":"Index Maps","linkFileType":{"id":5,"text":"html"}}],"country":"Afghanistan","otherGeospatial":"Ghazni2 Mineral District","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              68.87252342306118,\n              33.400794951645565\n            ],\n            [\n              68.5382513185329,\n              33.71681758841511\n            ],\n            [\n              68.30727405623549,\n              33.72224478024398\n            ],\n            [\n              68.08601269164748,\n              34.1414227946527\n            ],\n            [\n              67.2638552357352,\n              34.07256923954678\n            ],\n            [\n              67.23635530353977,\n              33.52157172943353\n            ],\n            [\n              66.91878464275106,\n              33.262493443111566\n            ],\n            [\n              67.42957551466375,\n              32.86586167317263\n            ],\n            [\n              67.7125922483599,\n              32.561357509486314\n            ],\n            [\n              68.87252342306118,\n              33.400794951645565\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536b47d3e4b0a51a87c4b12f","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":492734,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70101717,"text":"ds709DD - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan","interactions":[{"subject":{"id":70101717,"text":"ds709DD - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan","indexId":"ds709DD","publicationYear":"2014","noYear":false,"chapter":"DD","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan"},"predicate":"IS_PART_OF","object":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"id":1}],"isPartOf":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"lastModifiedDate":"2022-12-09T20:58:26.596731","indexId":"ds709DD","displayToPublicDate":"2014-05-07T12:01:00","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":"709","chapter":"DD","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits.</p>\n<br>\n<p>ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement.</p>\n<br>\n<p>The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands).</p>\n<br>\n<p>All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni1) and the WGS84 datum. The images for the Ghazni1 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (Data Series 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709DD","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey","usgsCitation":"Davis, P.A., 2014, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan: U.S. Geological Survey Data Series 709, Readme Text; Index Maps; Image Files; Metadata Files; Shapefiles, https://doi.org/10.3133/ds709DD.","productDescription":"Readme Text; Index Maps; Image Files; Metadata Files; Shapefiles","onlineOnly":"Y","ipdsId":"IP-054392","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":286957,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709dd.jpg"},{"id":286960,"rank":11,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/dd/image_files/image_files.html","text":"Image Files","linkFileType":{"id":5,"text":"html"}},{"id":286958,"rank":2,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/dd/1_readme.doc"},{"id":286961,"rank":1,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/dd/metadata/metadata.html","linkFileType":{"id":5,"text":"html"}},{"id":286963,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/dd/"},{"id":286959,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/dd/index_maps/index_maps.html","text":"Index Maps","linkFileType":{"id":5,"text":"html"}},{"id":286962,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/dd/shapefiles/shapefiles.html"}],"scale":"7000000","country":"Afghanistan","otherGeospatial":"Ghazni1 Mineral District","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              68.87252342306118,\n              33.400794951645565\n            ],\n            [\n              68.5382513185329,\n              33.71681758841511\n            ],\n            [\n              68.30727405623549,\n              33.72224478024398\n            ],\n            [\n              68.08601269164748,\n              34.1414227946527\n            ],\n            [\n              67.2638552357352,\n              34.07256923954678\n            ],\n            [\n              67.23635530353977,\n              33.52157172943353\n            ],\n            [\n              66.91878464275106,\n              33.262493443111566\n            ],\n            [\n              67.42957551466375,\n              32.86586167317263\n            ],\n            [\n              67.7125922483599,\n              32.561357509486314\n            ],\n            [\n              68.87252342306118,\n              33.400794951645565\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536b47d2e4b0a51a87c4b12a","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":492733,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70099230,"text":"fs20143017 - 2014 - Water resources of Orleans Parish, Louisiana","interactions":[],"lastModifiedDate":"2014-05-07T11:55:36","indexId":"fs20143017","displayToPublicDate":"2014-05-07T11:49:00","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":"2014-3017","title":"Water resources of Orleans Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in Orleans Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (<a href=\"http://waterdata.usgs.gov/nwis\">http://waterdata.usgs.gov/nwis</a>) are the primary sources of the information presented here.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143017","issn":"2327-6932","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., White, V.E., and Lovelace, J.K., 2014, Water resources of Orleans Parish, Louisiana: U.S. Geological Survey Fact Sheet 2014-3017, 6 p., https://doi.org/10.3133/fs20143017.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-052184","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":286956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143017.jpg"},{"id":286954,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3017/"},{"id":286955,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3017/pdf/fs2014-3017.pdf"}],"projection":"Albers Equal-Area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Louisiana","otherGeospatial":"Orleans Parish","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.166667,30.0 ], [ -90.166667,30.166667 ], [ -89.666667,30.166667 ], [ -89.666667,30.0 ], [ -90.166667,30.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536b47d4e4b0a51a87c4b139","contributors":{"authors":[{"text":"Prakken, Lawrence B.","contributorId":73978,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","affiliations":[],"preferred":false,"id":491878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovelace, John K. 0000-0002-8532-2599 jlovelac@usgs.gov","orcid":"https://orcid.org/0000-0002-8532-2599","contributorId":999,"corporation":false,"usgs":true,"family":"Lovelace","given":"John","email":"jlovelac@usgs.gov","middleInitial":"K.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491876,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70099231,"text":"fs20143016 - 2014 - Water resources of Terrebonne Parish, Louisiana","interactions":[],"lastModifiedDate":"2014-05-07T11:54:19","indexId":"fs20143016","displayToPublicDate":"2014-05-07T11:48:07","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":"2014-3016","title":"Water resources of Terrebonne Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in Terrebonne Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends,and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System <a href=\" http://waterdata.usgs.gov/nwis \" target=\"_blank\"> http://waterdata.usgs.gov/nwis </a> are the primary sources of the information presented here.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143016","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., Lovelace, J.K., and White, V.E., 2014, Water resources of Terrebonne Parish, Louisiana: U.S. Geological Survey Fact Sheet 2014-3016, 6 p., https://doi.org/10.3133/fs20143016.","productDescription":"6 p.","ipdsId":"IP-052292","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":286953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143016.jpg"},{"id":286951,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3016/"},{"id":286952,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3016/pdf/fs2014-3016.pdf"}],"country":"United States","state":"Louisiana","city":"Terrebonne Parish","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.353,29.041 ], [ -91.353,29.778 ], [ -90.377,29.778 ], [ -90.377,29.041 ], [ -91.353,29.041 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536b47d6e4b0a51a87c4b13e","contributors":{"authors":[{"text":"Prakken, Lawrence B.","contributorId":73978,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","affiliations":[],"preferred":false,"id":491881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lovelace, John K. 0000-0002-8532-2599 jlovelac@usgs.gov","orcid":"https://orcid.org/0000-0002-8532-2599","contributorId":999,"corporation":false,"usgs":true,"family":"Lovelace","given":"John","email":"jlovelac@usgs.gov","middleInitial":"K.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491880,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70100415,"text":"ofr20141031 - 2014 - Nutrient budgets, marsh inundation under sea-level rise scenarios, and sediment chronologies for the Bass Harbor Marsh estuary at Acadia National Park","interactions":[],"lastModifiedDate":"2014-05-07T09:15:10","indexId":"ofr20141031","displayToPublicDate":"2014-05-07T09:04:00","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":"2014-1031","title":"Nutrient budgets, marsh inundation under sea-level rise scenarios, and sediment chronologies for the Bass Harbor Marsh estuary at Acadia National Park","docAbstract":"<p>Eutrophication in the Bass Harbor Marsh estuary on Mount Desert Island, Maine, is an ongoing problem manifested by recurring annual blooms of green macroalgae species, principally Enteromorpha prolifera and Enteromorpha flexuosa, blooms that appear in the spring and summer. These blooms are unsightly and impair the otherwise natural beauty of this estuarine ecosystem. The macroalgae also threaten the integrity of the estuary and its inherent functions. The U.S. Geological Survey and Acadia National Park have collaborated for several years to better understand the factors related to this eutrophication problem with support from the U.S. Geological Survey and National Park Service Water Quality Assessment and Monitoring Program. The current study involved the collection of hydrologic and water-quality data necessary to investigate the relative contribution of nutrients from oceanic and terrestrial sources during summer 2011 and summer 2012. This report provides data on nutrient budgets for this estuary, sedimentation chronologies for the estuary and fringing marsh, and estuary bathymetry. The report also includes data, based on aerial photographs, on historical changes from 1944 to 2010 in estuary surface area and data, based on surface-elevation details, on changes in marsh area that may accompany sea-level rise.</p>\n<br/>\n<p>The LOADEST regression model was used to calculate nutrient loads into and out of the estuary during summer 2011 and summer 2012. During these summers, tidal inputs of ammonium to the estuary were more than seven times greater than the combined inputs in watershed runoff and precipitation. In 2011 tidal inputs of nitrate were about four times greater than watershed plus precipitation inputs, and in 2012 tidal inputs were only slightly larger than watershed plus precipitation inputs. In 2011, tidal inputs of total organic nitrogen were larger than watershed input by a factor of 1.6. By contrast, in 2012 inputs of total organic nitrogen in watershed runoff were much larger than tidal inputs, by a factor of 3.6. During the 2011 and 2012 summers, tidal inputs of total dissolved phosphorus to the estuary were more than seven times greater than inputs in watershed runoff. It is evident that during the summer tidal inputs of inorganic nitrogen and total dissolved phosphorus to the estuary exceed inputs from watershed runoff and precipitation.</p>\n<br/>\n<p>Projected sea-level rise associated with ongoing climate warming will affect the area of land within the Bass Harbor Marsh estuary watershed that is inundated during conditions of mean higher high water and during mean lower low water and hence will affect the vegetation and marsh area. Given 100-centimeter sea-level rise, the inundated area would increase from 25.7 hectares at the current condition to 77.5 hectares at mean higher high water and from 21.6 hectares to 26.7 hectares at mean lower low water. Given 50-centimeter sea-level rise, flooding of the entire marsh surface, which currently occurs only under the highest spring tides, would occur on average every other day.</p>\n<br/>\n<p>Radioisotope analysis of sediment cores from the estuary indicates that the sediment accumulation rate increased markedly from 1930 to 1980 and was relatively constant (0.4 to 0.5 centimeter per year) from 1980 to 2009. Similarly, from 1980 to 2009 there was a consistently high mass accumulation rate of 0.09 to 0.11 grams per square centimeter per year. The sediment accretion rates determined for the five cores collected from the marsh surface (east and west sides of the estuary) in 2011 show generally higher rates of 0.20 to 0.29 centimeter per year for the period between 1980 to 2011 than for the period before 1980, when sediment accretion rates were 0.06 to 0.25 centimeter per year.</p>\n<br/>\n<p>The data in this report provide resource managers at Acadia National Park with a baseline that can be used to evaluate future conditions within the estuary. Climate change, sea-level rise, and land-use change within the estuary’s watershed may influence nutrient dynamics, sedimentation, and eutrophication, and these potential effects can be studied in relation to the baseline data provided in this report. The Route 102 Bridge in Tremont, Maine is constructed over a sill that controls the amount of tidal flushing by restricting the duration of the flood tide, and structural changes to the bridge could alter tidal nutrient inputs and residence times for watershed and ocean-derived nutrients in the estuary. Ongoing sea-level rise is likely increasing ocean-derived nutrients and their residence time in the estuary on the one hand and decreasing the residence time of watershed-derived nutrients on the other.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141031","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Huntington, T.G., Culbertson, C.W., Fuller, C.C., Glibert, P., and Sturtevant, L., 2014, Nutrient budgets, marsh inundation under sea-level rise scenarios, and sediment chronologies for the Bass Harbor Marsh estuary at Acadia National Park: U.S. Geological Survey Open-File Report 2014-1031, xii, 108 p., https://doi.org/10.3133/ofr20141031.","productDescription":"xii, 108 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-049630","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":286945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141031.jpg"},{"id":285165,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1031"},{"id":286944,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1031/pdf/ofr2014-1031.pdf"}],"scale":"24000","country":"United States","state":"Maine","otherGeospatial":"Acadia National Park;Bass Harbor Marsh;Mount Desert Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -68.375,44.25 ], [ -68.375,44.291667 ], [ -68.333333,44.291667 ], [ -68.333333,44.25 ], [ -68.375,44.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536b47d3e4b0a51a87c4b134","contributors":{"authors":[{"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":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":492189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":492190,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glibert, Patricia","contributorId":94593,"corporation":false,"usgs":true,"family":"Glibert","given":"Patricia","email":"","affiliations":[],"preferred":false,"id":492192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sturtevant, Luke","contributorId":99893,"corporation":false,"usgs":true,"family":"Sturtevant","given":"Luke","affiliations":[],"preferred":false,"id":492193,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70103569,"text":"70103569 - 2014 - Lack of sex-biased dispersal promotes fine-scale genetic structure in alpine ungulates","interactions":[],"lastModifiedDate":"2018-08-20T18:15:29","indexId":"70103569","displayToPublicDate":"2014-05-06T14:50:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Lack of sex-biased dispersal promotes fine-scale genetic structure in alpine ungulates","docAbstract":"Identifying patterns of fine-scale genetic structure in natural populations can advance understanding of critical ecological processes such as dispersal and gene flow across heterogeneous landscapes. Alpine ungulates generally exhibit high levels of genetic structure due to female philopatry and patchy configuration of mountain habitats. We assessed the spatial scale of genetic structure and the amount of gene flow in 301 Dall’s sheep (<i>Ovis dalli dalli</i>) at the landscape level using 15 nuclear microsatellites and 473 base pairs of the mitochondrial (mtDNA) control region. Dall’s sheep exhibited significant genetic structure within contiguous mountain ranges, but mtDNA structure occurred at a broader geographic scale than nuclear DNA within the study area, and mtDNA structure for other North American mountain sheep populations. No evidence of male-mediated gene flow or greater philopatry of females was observed; there was little difference between markers with different modes of inheritance (pairwise nuclear DNA F <sub>ST</sub> = 0.004–0.325; mtDNA F <sub>ST</sub> = 0.009–0.544), and males were no more likely than females to be recent immigrants. Historical patterns based on mtDNA indicate separate northern and southern lineages and a pattern of expansion following regional glacial retreat. Boundaries of genetic clusters aligned geographically with prominent mountain ranges, icefields, and major river valleys based on Bayesian and hierarchical modeling of microsatellite and mtDNA data. Our results suggest that fine-scale genetic structure in Dall’s sheep is influenced by limited dispersal, and structure may be weaker in populations occurring near ancestral levels of density and distribution in continuous habitats compared to other alpine ungulates that have experienced declines and marked habitat fragmentation.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Conservation Genetics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10592-014-0583-2","usgsCitation":"Roffler, G.H., Talbot, S.L., Luikart, G., Sage, G.K., Pilgrim, K.L., Adams, L., and Schwartz, M.K., 2014, Lack of sex-biased dispersal promotes fine-scale genetic structure in alpine ungulates: Conservation Genetics, v. 15, no. 4, p. 837-851, https://doi.org/10.1007/s10592-014-0583-2.","productDescription":"15 p.","startPage":"837","endPage":"851","numberOfPages":"15","ipdsId":"IP-049059","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":286931,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10592-014-0583-2"},{"id":286936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -146.0,60.5 ], [ -146.0,63.0 ], [ -140.0,63.0 ], [ -140.0,60.5 ], [ -146.0,60.5 ] ] ] } } ] }","volume":"15","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-02-17","publicationStatus":"PW","scienceBaseUri":"5369f650e4b063fb73c0a9d3","contributors":{"authors":[{"text":"Roffler, Gretchen H. groffler@usgs.gov","contributorId":1946,"corporation":false,"usgs":true,"family":"Roffler","given":"Gretchen","email":"groffler@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":493394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":493393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":493398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":493397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pilgrim, Kristy L.","contributorId":45222,"corporation":false,"usgs":true,"family":"Pilgrim","given":"Kristy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":493396,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":493395,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schwartz, Michael K.","contributorId":102326,"corporation":false,"usgs":true,"family":"Schwartz","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":493399,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70059074,"text":"ds811 - 2014 - Occurrence of pesticides in groundwater and sediments and mineralogy of sediments and grain coatings underlying the Rutgers Agricultural Research and Extension Center, Upper Deerfield, New Jersey, 2007","interactions":[],"lastModifiedDate":"2021-05-27T13:59:50.478121","indexId":"ds811","displayToPublicDate":"2014-05-06T14:15:00","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":"811","title":"Occurrence of pesticides in groundwater and sediments and mineralogy of sediments and grain coatings underlying the Rutgers Agricultural Research and Extension Center, Upper Deerfield, New Jersey, 2007","docAbstract":"Water and sediment samples were collected from June through October 2007 from seven plots at the Rutgers Agricultural Research and Extension Center in Upper Deerfield, New Jersey, and analyzed for a suite of pesticides (including fungicides) and other physical and chemical parameters (including sediment mineralogy) by the U.S. Geological Survey. Plots were selected for inclusion in this study on the basis of the crops grown and the pesticides used. Forty-one pesticides were detected in 14 water samples; these include 5 fungicides, 13 herbicides, 1 insecticide, and 22 pesticide degradates. The following pesticides and pesticide degradates were detected in 50 percent or more of the groundwater samples: 1-amide-4-hydroxy-chorothalonil, alachlor sulfonic acid, metolachlor oxanilic acid, metolachlor sulfonic acid, metalaxyl, and simazine. Dissolved-pesticide concentrations ranged from below their instrumental limit of detection to 36 micrograms per liter (for metolachlor sulfonic acid, a degradate of the herbicide metolachlor). The total number of pesticides found in groundwater samples ranged from 0 to 29. Fourteen pesticides were detected in sediment samples from continuous cores collected within each of the seven sampled plots; these include 4 fungicides, 2 herbicides, and 7 pesticide degradates. Pesticide concentrations in sediment samples ranged from below their instrumental limit of detection to 34.2 nanograms per gram (for azoxystrobin). The total number of pesticides found in sediment samples ranged from 0 to 8. Quantitative whole-rock and grain-coating mineralogy of sediment samples were determined by x-ray diffraction. Whole-rock analysis indicated that sediments were predominantly composed of quartz. The materials coating the quartz grains were removed to allow quantification of the trace mineral phases present.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds811","usgsCitation":"Reilly, T.J., Smalling, K., Meyer, M.T., Sandstrom, M.W., Hladik, M., Boehlke, A., Fishman, N.S., Battaglin, W.A., and Kuivila, K., 2014, Occurrence of pesticides in groundwater and sediments and mineralogy of sediments and grain coatings underlying the Rutgers Agricultural Research and Extension Center, Upper Deerfield, New Jersey, 2007: U.S. Geological Survey Data Series 811, x, 53 p., https://doi.org/10.3133/ds811.","productDescription":"x, 53 p.","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-043852","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":286934,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0811/pdf/ds811.pdf"},{"id":286933,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0811/"},{"id":286939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds811.jpg"}],"country":"United States","state":"New Jersey","city":"Upper Deerfield","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.240104,39.499658 ], [ -75.240104,39.53987 ], [ -75.17473,39.53987 ], [ -75.17473,39.499658 ], [ -75.240104,39.499658 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5369f652e4b063fb73c0a9f1","contributors":{"authors":[{"text":"Reilly, Timothy J. 0000-0002-2939-3050 tjreilly@usgs.gov","orcid":"https://orcid.org/0000-0002-2939-3050","contributorId":1858,"corporation":false,"usgs":true,"family":"Reilly","given":"Timothy","email":"tjreilly@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"preferred":true,"id":487466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smalling, Kelly L.","contributorId":16105,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[],"preferred":false,"id":487467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":487463,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sandstrom, Mark W. 0000-0003-0006-5675 sandstro@usgs.gov","orcid":"https://orcid.org/0000-0003-0006-5675","contributorId":706,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Mark","email":"sandstro@usgs.gov","middleInitial":"W.","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":487461,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hladik, Michelle 0000-0002-0891-2712 mhladik@usgs.gov","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":784,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","email":"mhladik@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":487462,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boehlke, Adam R. 0000-0003-4980-431X","orcid":"https://orcid.org/0000-0003-4980-431X","contributorId":23835,"corporation":false,"usgs":true,"family":"Boehlke","given":"Adam R.","affiliations":[],"preferred":false,"id":487468,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fishman, Neil S.","contributorId":106464,"corporation":false,"usgs":true,"family":"Fishman","given":"Neil","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":487469,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Battaglin, William A. 0000-0001-7287-7096 wbattagl@usgs.gov","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":1527,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","email":"wbattagl@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487465,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kuivila, Kathryn  0000-0001-7940-489X kkuivila@usgs.gov","orcid":"https://orcid.org/0000-0001-7940-489X","contributorId":1367,"corporation":false,"usgs":true,"family":"Kuivila","given":"Kathryn ","email":"kkuivila@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":487464,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70101481,"text":"ofr20141074 - 2014 - Sediment-hosted gold deposits of the world: Database and grade and tonnage models","interactions":[],"lastModifiedDate":"2023-05-26T15:29:00.030413","indexId":"ofr20141074","displayToPublicDate":"2014-05-06T10:06:00","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":"2014-1074","title":"Sediment-hosted gold deposits of the world: Database and grade and tonnage models","docAbstract":"All sediment-hosted gold deposits (as a single population) share one characteristic—they all have disseminated micron-sized invisible gold in sedimentary rocks. Sediment-hosted gold deposits are recognized in the Great Basin province of the western United States and in China along with a few recognized deposits in Indonesia, Iran, and Malaysia. Three new grade and tonnage models for sediment-hosted gold deposits are presented in this paper: (1) a general sediment-hosted gold type model, (2) a Carlin subtype model, and (3) a Chinese subtype model. These models are based on grade and tonnage data from a database compilation of 118 sediment-hosted gold deposits including a total of 123 global deposits. The new general grade and tonnage model for sediment-hosted gold deposits (n=118) has a median tonnage of 5.7 million metric tonnes (Mt) and a gold grade of 2.9 grams per tonne (g/t). This new grade and tonnage model is remarkable in that the estimated parameters of the resulting grade and tonnage distributions are comparable to the previous model of Mosier and others (1992). A notable change is in the reporting of silver in more than 10 percent of deposits; moreover, the previous model had not considered deposits in China. From this general grade and tonnage model, two significantly different subtypes of sediment-hosted gold deposits are differentiated: Carlin and Chinese. The Carlin subtype includes 88 deposits in the western United States, Indonesia, Iran, and Malaysia, with median tonnage and grade of 7.1 Mt and 2.0 g/t Au, respectively. The silver grade is 0.78 g/t Ag for the 10th percentile of deposits. The Chinese subtype represents 30 deposits in China, with a median tonnage of 3.9 Mt and medium grade of 4.6 g/t Au. Important differences are recognized in the mineralogy and alteration of the two sediment-hosted gold subtypes such as: increased sulfide minerals in the Chinese subtype and decalcification alteration dominant in the Carlin type. We therefore recommend using the appropriate grade and tonnage model presented in this study for mineral resource assessments depending on the geologic and mineralogical data available for a region. Tonnage and contained gold within the general sediment-hosted gold model are analyzed based on major geologic features such as tectonic setting and magmatic (dikes, sills, and stocks) or amagmatic environment. The results show a significant difference in tonnage and contained gold, with higher median values in deposits spatially associated with igneous rocks, regardless of structural style of the deposit. These results suggest that magmatic environments control mineralization intensity—an important consideration in the regional assessment of prospective areas for sediment-hosted gold deposits.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141074","usgsCitation":"Berger, V.I., Mosier, D.L., Bliss, J.D., and Moring, B.C., 2014, Sediment-hosted gold deposits of the world: Database and grade and tonnage models (Originally posted May 5, 2014; Version 1.1 June 19, 2014): U.S. Geological Survey Open-File Report 2014-1074, Report: v, 46 p.; Appendixes 1-6, https://doi.org/10.3133/ofr20141074.","productDescription":"Report: v, 46 p.; Appendixes 1-6","numberOfPages":"51","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-046320","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":417504,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_100014.htm","linkFileType":{"id":5,"text":"html"}},{"id":286923,"rank":1,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1074/downloads/ofr2014-1074_appendixes.zip"},{"id":286228,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1074/"},{"id":286924,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141074.GIF"},{"id":286922,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1074/pdf/ofr2014-1074.pdf"}],"edition":"Originally posted May 5, 2014; Version 1.1 June 19, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5369f652e4b063fb73c0a9f6","contributors":{"authors":[{"text":"Berger, Vladimir I.","contributorId":15246,"corporation":false,"usgs":true,"family":"Berger","given":"Vladimir","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":492718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mosier, Dan L.","contributorId":42593,"corporation":false,"usgs":true,"family":"Mosier","given":"Dan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":492719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bliss, James D. jbliss@usgs.gov","contributorId":2790,"corporation":false,"usgs":true,"family":"Bliss","given":"James","email":"jbliss@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":492716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moring, Barry C. 0000-0001-6797-9258 moring@usgs.gov","orcid":"https://orcid.org/0000-0001-6797-9258","contributorId":2794,"corporation":false,"usgs":true,"family":"Moring","given":"Barry","email":"moring@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":492717,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70173908,"text":"70173908 - 2014 - Estimating habitat carrying capacity for migrating and wintering waterfowl: Considerations, pitfalls and improvements","interactions":[],"lastModifiedDate":"2016-06-22T13:35:54","indexId":"70173908","displayToPublicDate":"2014-05-06T05:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3764,"text":"Wildfowl","onlineIssn":"2052-6458","printIssn":"0954-6324","active":true,"publicationSubtype":{"id":10}},"title":"Estimating habitat carrying capacity for migrating and wintering waterfowl: Considerations, pitfalls and improvements","docAbstract":"<p>Population-based habitat conservation planning for migrating and wintering waterfowl&nbsp;in North America is carried out by habitat Joint Venture (JV) initiatives and is based on&nbsp;the premise that food can limit demography (i.e. food limitation hypothesis).&nbsp;Consequently, planners use bioenergetic models to estimate food (energy) availability&nbsp;and population-level energy demands at appropriate spatial and temporal scales, and&nbsp;translate these values into regional habitat objectives. While simple in principle, there&nbsp;are both empirical and theoretical challenges associated with calculating energy supply&nbsp;and demand including: 1) estimating food availability, 2) estimating the energy content&nbsp;of specific foods, 3) extrapolating site-specific estimates of food availability to&nbsp;landscapes for focal species, 4) applicability of estimates from a single species to other&nbsp;species, 5) estimating resting metabolic rate, 6) estimating cost of daily behaviours, and&nbsp;7) estimating costs of thermoregulation or tissue synthesis. Most models being used are&nbsp;daily ration models (DRMs) whose set of simplifying assumptions are well established&nbsp;and whose use is widely accepted and feasible given the empirical data available to&nbsp;populate such models. However, DRMs do not link habitat objectives to metrics of&nbsp;ultimate ecological importance such as individual body condition or survival, and&nbsp;largely only consider food-producing habitats. Agent-based models (ABMs) provide a&nbsp;possible alternative for creating more biologically realistic models under some&nbsp;conditions; however, ABMs require different types of empirical inputs, many of which&nbsp;have yet to be estimated for key North American waterfowl. Decisions about how JVs&nbsp;can best proceed with habitat conservation would benefit from the use of sensitivity&nbsp;analyses that could identify the empirical and theoretical uncertainties that have the&nbsp;greatest influence on efforts to estimate habitat carrying capacity. Development of&nbsp;ABMs at restricted, yet biologically relevant spatial scales, followed by comparisons of&nbsp;their outputs to those generated from more simplistic, deterministic models can&nbsp;provide a means of assessing degrees of dissimilarity in how alternative models&nbsp;describe desired landscape conditions for migrating and wintering waterfowl.</p>","language":"English","publisher":"InterMedia Outdoors","usgsCitation":"Williams, C., Dugger, B., Brasher, M., Coluccy, J.M., Cramer, D.M., Eadie, J.M., Gray, M., Hagy, H.M., Livolsi, M., McWilliams, S.R., Petrie, M., Soulliere, G.J., Tirpak, J.M., and Webb, E.B., 2014, Estimating habitat carrying capacity for migrating and wintering waterfowl: Considerations, pitfalls and improvements: Wildfowl, no. 4, p. 407-435.","productDescription":"29 p.","startPage":"407","endPage":"435","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055427","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":324226,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324227,"type":{"id":15,"text":"Index Page"},"url":"https://wildfowl.wwt.org.uk/index.php/wildfowl/article/view/2614"}],"issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576bb6b3e4b07657d1a2289f","contributors":{"authors":[{"text":"Williams, Christopher","contributorId":36592,"corporation":false,"usgs":true,"family":"Williams","given":"Christopher","affiliations":[],"preferred":false,"id":640344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dugger, Bruce D.","contributorId":81236,"corporation":false,"usgs":true,"family":"Dugger","given":"Bruce D.","affiliations":[],"preferred":false,"id":640345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brasher, Michael G.","contributorId":17139,"corporation":false,"usgs":true,"family":"Brasher","given":"Michael G.","affiliations":[],"preferred":false,"id":640346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coluccy, John M.","contributorId":111382,"corporation":false,"usgs":true,"family":"Coluccy","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cramer, Dane M.","contributorId":172325,"corporation":false,"usgs":false,"family":"Cramer","given":"Dane","email":"","middleInitial":"M.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":640348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eadie, John M.","contributorId":65219,"corporation":false,"usgs":false,"family":"Eadie","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":640349,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gray, Matthew J.","contributorId":101343,"corporation":false,"usgs":true,"family":"Gray","given":"Matthew J.","affiliations":[],"preferred":false,"id":640350,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hagy, Heath M.","contributorId":172326,"corporation":false,"usgs":false,"family":"Hagy","given":"Heath","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640351,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Livolsi, Mark","contributorId":172327,"corporation":false,"usgs":false,"family":"Livolsi","given":"Mark","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":640352,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McWilliams, Scott R.","contributorId":172328,"corporation":false,"usgs":false,"family":"McWilliams","given":"Scott","email":"","middleInitial":"R.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":640353,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Petrie, Matthew mpetrie@usgs.gov","contributorId":167013,"corporation":false,"usgs":true,"family":"Petrie","given":"Matthew","email":"mpetrie@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":640354,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Soulliere, Gregory J.","contributorId":172329,"corporation":false,"usgs":false,"family":"Soulliere","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":640355,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tirpak, John M.","contributorId":85704,"corporation":false,"usgs":true,"family":"Tirpak","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640356,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":638956,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70156135,"text":"70156135 - 2014 - Using nuclear magnetic resonance and transient electromagnetics to characterise water distribution beneath an ice covered volcanic crater: The case of Sherman Crater Mt. Baker Washington.","interactions":[],"lastModifiedDate":"2019-03-11T14:03:42","indexId":"70156135","displayToPublicDate":"2014-05-06T01:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2850,"text":"Near Surface Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Using nuclear magnetic resonance and transient electromagnetics to characterise water distribution beneath an ice covered volcanic crater: The case of Sherman Crater Mt. Baker Washington.","docAbstract":"<p>Surface and laboratory Nuclear Magnetic Resonance (NMR) measurements combined with transient electromagnetic (TEM) data are powerful tools for subsurface water detection. Surface NMR (sNMR) and TEM soundings, laboratory NMR, complex resistivity, and X-Ray Diffraction (XRD) analysis were all conducted to characterise the distribution of water within Sherman Crater on Mt. Baker, WA. Clay rich rocks, particularly if water saturated, can weaken volcanoes, thereby increasing the potential for catastrophic sector collapses that can lead to far-travelled, destructive debris flows. Detecting the presence and volume of shallow groundwater is critical for evaluating these landslide hazards. The TEM data identified a low resistivity layer (&lt;10 ohm-m), under 60 m of glacial ice related to water saturated clays. The TEM struggles to resolve the presence or absence of a plausible thin layer of bulk liquid water on top of the clay. The sNMR measurements did not produce any observable signal, indicating the lack of substantial accumulated bulk water below the ice. Laboratory analysis on a sample from the crater wall that likely represented the clays beneath the ice confirmed that the controlling factor for the lack of sNMR signal was the fine-grained nature of the media. The laboratory measurements further indicated that small pores in clays detected by the XRD contain as much as 50% water, establishing an upper bound on the water content in the clay layer. Forward modelling of geologic scenarios revealed that bulk water layers as thin as &frac12; m between the ice and clay layer would have been detectable using sNMR. The instrumentation conditions which would allow for sNMR detection of the clay layer are investigated. Using current instrumentation the combined analysis of the TEM and sNMR data allow for valuable characterisation of the groundwater system in the crater. The sNMR is able to reduce the uncertainty of the TEM in regards to the presence of a bulk water layer, a valuable piece of information in hazard assessment.</p>","language":"English","publisher":"European Association of Geoscientists & Engineers","doi":"10.3997/1873-0604.2014009","usgsCitation":"Irons, T.P., Martin, K., Finn, C.A., Bloss, B.R., and Horton, R., 2014, Using nuclear magnetic resonance and transient electromagnetics to characterise water distribution beneath an ice covered volcanic crater: The case of Sherman Crater Mt. Baker Washington.: Near Surface Geophysics, v. 12, no. 2, p. 285-296, https://doi.org/10.3997/1873-0604.2014009.","productDescription":"12 p.","startPage":"285","endPage":"296","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053051","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":306810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Baker, Sherman Crater","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.05947875976562,\n              48.62110864256238\n            ],\n            [\n              -122.05947875976562,\n              48.89722676235673\n            ],\n            [\n              -121.55548095703125,\n              48.89722676235673\n            ],\n            [\n              -121.55548095703125,\n              48.62110864256238\n            ],\n            [\n              -122.05947875976562,\n              48.62110864256238\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d305bce4b0518e35468d35","contributors":{"authors":[{"text":"Irons, Trevor P. tirons@usgs.gov","contributorId":4851,"corporation":false,"usgs":true,"family":"Irons","given":"Trevor","email":"tirons@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":567909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Kathryn","contributorId":146449,"corporation":false,"usgs":false,"family":"Martin","given":"Kathryn","email":"","affiliations":[{"id":16695,"text":"Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":567910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finn, Carol A. 0000-0002-6178-0405 cfinn@usgs.gov","orcid":"https://orcid.org/0000-0002-6178-0405","contributorId":1326,"corporation":false,"usgs":true,"family":"Finn","given":"Carol","email":"cfinn@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":567908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bloss, Benjamin R. 0000-0002-1678-8571 bbloss@usgs.gov","orcid":"https://orcid.org/0000-0002-1678-8571","contributorId":139981,"corporation":false,"usgs":true,"family":"Bloss","given":"Benjamin","email":"bbloss@usgs.gov","middleInitial":"R.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":567911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Horton, Robert 0000-0001-5578-3733 rhorton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-3733","contributorId":612,"corporation":false,"usgs":true,"family":"Horton","given":"Robert","email":"rhorton@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":567912,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70056060,"text":"70056060 - 2014 - Lipid and moisture content modeling of amphidromous Dolly Varden using bioelectrical impedance analysis","interactions":[],"lastModifiedDate":"2014-05-06T09:49:15","indexId":"70056060","displayToPublicDate":"2014-05-05T16:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Lipid and moisture content modeling of amphidromous Dolly Varden using bioelectrical impedance analysis","docAbstract":"The physiological well-being or condition of fish is most commonly estimated from aspects of individual morphology. However, these metrics may be only weakly correlated with nutritional reserves stored as lipid, the primary form of accumulated energy in fish. We constructed and evaluated bioelectrical impedance analysis (BIA) models as an alternative method of assessing condition in amphidromous Dolly Varden Salvelinus malma collected from nearshore estuarine and lotic habitats of the Alaskan Arctic. Data on electrical resistance and reactance were collected from the lateral and ventral surfaces of 192 fish, and whole-body percent lipid and moisture content were determined using standard laboratory methods. Significant inverse relationships between temperature and resistance and reactance prompted the standardization of these data to a constant temperature using corrective equations developed herein. No significant differences in resistance or reactance were detected among spawning and nonspawning females after accounting for covariates, suggesting that electrical pathways do not intersect the gonads. Best-fit BIA models incorporating electrical variables calculated from the lateral and ventral surfaces produced the strongest associations between observed and model-predicted estimates of proximate content. These models explained between 6% and 20% more of the variability in laboratory-derived estimates of proximate content than models developed from single-surface BIA data and 32% more than models containing only length and weight data. While additional research is required to address the potential effects of methodological variation, bioelectrical impedance analysis shows promise as a way to provide high-quality, minimally invasive estimates of Dolly Varden lipid or moisture content in the field with only small increases in handling time.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"North American Journal of Fisheries Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2014.880764","usgsCitation":"Stolarski, J., Margraf, F., Carlson, J., and Sutton, T., 2014, Lipid and moisture content modeling of amphidromous Dolly Varden using bioelectrical impedance analysis: North American Journal of Fisheries Management, v. 34, no. 3, p. 471-481, https://doi.org/10.1080/02755947.2014.880764.","productDescription":"11 p.","startPage":"471","endPage":"481","numberOfPages":"11","ipdsId":"IP-044095","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":286920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286919,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02755947.2014.880764"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -145.1541,69.6619 ], [ -145.1541,70.1599 ], [ -141.6989,70.1599 ], [ -141.6989,69.6619 ], [ -145.1541,69.6619 ] ] ] } } ] }","volume":"34","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-04-15","publicationStatus":"PW","scienceBaseUri":"536a0463e4b063fb73c0aa10","contributors":{"authors":[{"text":"Stolarski, J.T.","contributorId":96487,"corporation":false,"usgs":true,"family":"Stolarski","given":"J.T.","affiliations":[],"preferred":false,"id":486315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Margraf, F.J.","contributorId":47738,"corporation":false,"usgs":true,"family":"Margraf","given":"F.J.","email":"","affiliations":[],"preferred":false,"id":486312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson, J.G.","contributorId":74681,"corporation":false,"usgs":true,"family":"Carlson","given":"J.G.","email":"","affiliations":[],"preferred":false,"id":486314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sutton, T.M.","contributorId":72193,"corporation":false,"usgs":true,"family":"Sutton","given":"T.M.","email":"","affiliations":[],"preferred":false,"id":486313,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70103370,"text":"ofr20141087 - 2014 - Characterization of potential transport pathways and implications for groundwater management near an anticline in the Central Basin area, Los Angeles County, California","interactions":[],"lastModifiedDate":"2014-05-05T15:36:05","indexId":"ofr20141087","displayToPublicDate":"2014-05-05T15:11:14","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":"2014-1087","title":"Characterization of potential transport pathways and implications for groundwater management near an anticline in the Central Basin area, Los Angeles County, California","docAbstract":"The Central Groundwater Basin (Central Basin) of southern Los Angeles County includes ~280 mi<sup>2</sup> of the Los Angeles Coastal Plain and serves as the primary source of water for more than two million residents. In the Santa Fe Springs–Whittier–Norwalk area, located in the northeastern part of the basin, several sources of volatile organic compounds have been identified. The volatile organic compunds are thought to have contributed to a large, commingled contaminant plume in groundwater that extends south-southwest downgradient from the Omega Chemical Corporation Superfund Site across folded geologic strata, known as the Santa Fe Springs Anticline. A multifaceted study—that incorporated a three-dimensional sequence-stratigraphic geologic model, two-dimensional groundwater particle-tracking simulations, and new groundwater chemistry data—was conducted to gain insight into the geologic and hydrologic controls on contaminant migration in the study area and to assess the potential for this shallow groundwater contamination to migrate into producing aquifer zones. Conceptual flow models were developed along a flow-parallel cross section based on the modeled stratigraphic architecture, observed geochemistry, and numerical model simulations that generally agree with observed water levels and contaminant distributions. These models predict that contaminants introduced into groundwater at shallow depths near the Omega Chemical Corporation Superfund Site and along the study cross section will likely migrate downgradient to depths intercepted by public supply wells. These conclusions, however, are subject to limitations and simplifications inherent in the modeling approaches used, as well as a significant scarcity of available geologic and hydrogeochemical information at depth and in the downgradient parts of the study area.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141087","collaboration":"Prepared in cooperation with the Water Replenishment District of Southern California","usgsCitation":"Ponti, D.J., Wagner, B.J., Land, M., and Landon, M.K., 2014, Characterization of potential transport pathways and implications for groundwater management near an anticline in the Central Basin area, Los Angeles County, California: U.S. Geological Survey Open-File Report 2014-1087, Report: vii, 75 p.; Appendix A: 49 p.; 1 Plate: 28.00 x 19.50 inches; Tables 1,4,7; High resolution figures, https://doi.org/10.3133/ofr20141087.","productDescription":"Report: vii, 75 p.; Appendix A: 49 p.; 1 Plate: 28.00 x 19.50 inches; Tables 1,4,7; High resolution figures","numberOfPages":"84","onlineOnly":"Y","ipdsId":"IP-037058","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":286913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141087.jpg"},{"id":286906,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1087/pdf/ofr2014-1087.pdf"},{"id":286907,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1087/pdf/ofr2014-1087_appendixA.pdf"},{"id":286905,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1087/"},{"id":286909,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1087/downloads/ofr2014-1087_table4.xlsx"},{"id":286908,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1087/downloads/ofr2014-1087_table1.xlsx"},{"id":286910,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1087/downloads/ofr2014-1087_table7.xlsx"},{"id":286911,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1087/downloads/figures/"},{"id":286912,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2014/1087/pdf/ofr2014-1087_plate1.pdf"}],"country":"United States","state":"California","county":"Los Angeles County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.5,33.583 ], [ -118.5,34.25 ], [ -117.66,34.25 ], [ -117.66,33.583 ], [ -118.5,33.583 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5368a4d0e4b059f7e82882f5","contributors":{"authors":[{"text":"Ponti, Daniel J. 0000-0002-2437-5144 dponti@usgs.gov","orcid":"https://orcid.org/0000-0002-2437-5144","contributorId":1020,"corporation":false,"usgs":true,"family":"Ponti","given":"Daniel","email":"dponti@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":493274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Brian J. bjwagner@usgs.gov","contributorId":427,"corporation":false,"usgs":true,"family":"Wagner","given":"Brian","email":"bjwagner@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":493273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Land, Michael 0000-0001-5141-0307","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":56613,"corporation":false,"usgs":true,"family":"Land","given":"Michael","affiliations":[],"preferred":false,"id":493275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70103489,"text":"70103489 - 2014 - Seasonal thaw settlement at drained thermokarst lake basins, Arctic Alaska","interactions":[],"lastModifiedDate":"2018-06-16T18:00:26","indexId":"70103489","displayToPublicDate":"2014-05-05T14:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3554,"text":"The Cryosphere","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal thaw settlement at drained thermokarst lake basins, Arctic Alaska","docAbstract":"Drained thermokarst lake basins (DTLBs) are ubiquitous landforms on Arctic tundra lowland. Their dynamic states are seldom investigated, despite their importance for landscape stability, hydrology, nutrient fluxes, and carbon cycling. Here we report results based on high-resolution Interferometric Synthetic Aperture Radar (InSAR) measurements using space-borne data for a study area located on the North Slope of Alaska near Prudhoe Bay, where we focus on the seasonal thaw settlement within DTLBs, averaged between 2006 and 2010. The majority (14) of the 18 DTLBs in the study area exhibited seasonal thaw settlement of 3–4 cm. However, four of the DTLBs examined exceeded 4 cm of thaw settlement, with one basin experiencing up to 12 cm. Combining the InSAR observations with the in situ active layer thickness measured using ground penetrating radar and mechanical probing, we calculated thaw strain, an index of thaw settlement strength along a transect across the basin that underwent large thaw settlement. We found thaw strains of 10–35% at the basin center, suggesting the seasonal melting of ground ice as a possible mechanism for the large settlement. These findings emphasize the dynamic nature of permafrost landforms, demonstrate the capability of the InSAR technique to remotely monitor surface deformation of individual DTLBs, and illustrate the combination of ground-based and remote sensing observations to estimate thaw strain. Our study highlights the need for better description of the spatial heterogeneity of landscape-scale processes for regional assessment of surface dynamics on Arctic coastal lowlands.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Cryosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"European Geosciences Union","doi":"10.5194/tc-8-815-2014","usgsCitation":"Liu, L., Schaefer, K., Gusmeroli, A., Grosse, G., Jones, B.M., Zhang, T., Parsekian, A., and Zebker, H., 2014, Seasonal thaw settlement at drained thermokarst lake basins, Arctic Alaska: The Cryosphere, v. 8, p. 815-826, https://doi.org/10.5194/tc-8-815-2014.","productDescription":"12 p.","startPage":"815","endPage":"826","ipdsId":"IP-051116","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":473003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-8-815-2014","text":"Publisher Index Page"},{"id":286890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286886,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/tc-8-815-2014"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -149.9132,70.0825 ], [ -149.9132,70.5707 ], [ -147.7664,70.5707 ], [ -147.7664,70.0825 ], [ -149.9132,70.0825 ] ] ] } } ] }","volume":"8","noUsgsAuthors":false,"publicationDate":"2014-05-05","publicationStatus":"PW","scienceBaseUri":"5368a4d3e4b059f7e828830e","contributors":{"authors":[{"text":"Liu, Lin","contributorId":92950,"corporation":false,"usgs":false,"family":"Liu","given":"Lin","email":"","affiliations":[{"id":36342,"text":"Earth System Science Programme, Faculty of Science, Chinese University of Hong Kong, Hong Kong, China","active":true,"usgs":false}],"preferred":false,"id":493369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaefer, Kevin","contributorId":63323,"corporation":false,"usgs":true,"family":"Schaefer","given":"Kevin","affiliations":[],"preferred":false,"id":493367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gusmeroli, Alessio","contributorId":106003,"corporation":false,"usgs":true,"family":"Gusmeroli","given":"Alessio","affiliations":[],"preferred":false,"id":493371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":493370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":493366,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhang, Tinjun","contributorId":14742,"corporation":false,"usgs":true,"family":"Zhang","given":"Tinjun","email":"","affiliations":[],"preferred":false,"id":493364,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Parsekian, Andrew","contributorId":21466,"corporation":false,"usgs":true,"family":"Parsekian","given":"Andrew","affiliations":[],"preferred":false,"id":493365,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zebker, Howard","contributorId":88072,"corporation":false,"usgs":true,"family":"Zebker","given":"Howard","affiliations":[],"preferred":false,"id":493368,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70100414,"text":"70100414 - 2014 - Mineral commodity summaries 2014","interactions":[],"lastModifiedDate":"2014-05-05T14:08:57","indexId":"70100414","displayToPublicDate":"2014-05-05T12:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"seriesTitle":{"id":368,"text":"Mineral Commodity Summaries","active":false,"publicationSubtype":{"id":6}},"title":"Mineral commodity summaries 2014","docAbstract":"<p>Each chapter of the 2014 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS)  includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular  presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world  production and resources. The MCS is the earliest comprehensive source of 2013 mineral production data for the  world. More than 90 individual minerals and materials are covered by two-page synopses.</p>\n\n<br> \n \n<p>For mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the two-page synopsis.</p>\n\n<br> \n \n<p>Abbreviations and units of measure, and definitions of selected terms used in the report, are in Appendix A and Appendix B, respectively. “Appendix C—Reserves and Resources” includes “Part A—Resource/Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is Appendix D. </p>\n\n<br> \n \n<p>The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2014 are welcomed.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70100414","collaboration":"This summary is available online, in print and CD-ROM format. Please see the verso of the title page in this summary for ordering information.","usgsCitation":"Mineral commodity summaries 2014; 2014; USGS Unnumbered Series; MINERAL; U.S. Geological Survey","productDescription":"Report: 196 p.; Appendixes A-D","numberOfPages":"199","onlineOnly":"Y","ipdsId":"IP-055293","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":286884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70100414.GIF"},{"id":286875,"type":{"id":15,"text":"Index Page"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/"},{"id":286876,"type":{"id":11,"text":"Document"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/2014/mcs2014.pdf"},{"id":286877,"type":{"id":3,"text":"Appendix"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/2014/mcsapp2014.pdf"}],"otherGeospatial":"Earth","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 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5368a4d2e4b059f7e8288309","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":535647,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70103395,"text":"70103395 - 2014 - Habitat used by juvenile lake sturgeon (<i>Acipenser fulvescens</i>) in the North Channel of the St. Clair River (Michigan, USA)","interactions":[],"lastModifiedDate":"2014-06-19T09:29:15","indexId":"70103395","displayToPublicDate":"2014-05-05T11:21:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Habitat used by juvenile lake sturgeon (<i>Acipenser fulvescens</i>) in the North Channel of the St. Clair River (Michigan, USA)","docAbstract":"Lake sturgeon (<i>Acipenser fulvescens</i>) occupy the St. Clair River, part of a channel connecting lakes Huron and Erie in the Laurentian Great Lakes. In the North Channel of the St. Clair River, juvenile lake sturgeon (3–7 years old and 582–793 mm in length) were studied to determine movement patterns and habitat usage. Fourteen juveniles were implanted with ultrasonic transmitters and tracked June–August of 2004, 2005 and 2006. Telemetry data, Geographic Information System software, side-scan sonar, video images of the river bottom, scuba diving, and benthic substrate samples were used to determine the extent and composition of habitats they occupied. Juvenile lake sturgeon habitat selection was strongly related to water depth. No fish were found in <6 m of water and over 97% of the relocations were found at depths greater than 9 m. Available water depths exceeding 18 m only represented 3.5% of the available habitat, however 34.9% of the relocations were found at depths exceeding 18 m. Juvenile lake sturgeon did not use most areas in proportion to their availability. Sturgeon avoided clay ledges and shallow areas with silt or soft clay, which comprised approximately 39% of the benthic habitat in the North Channel. A total of 300 out of 351 documented locations were on sand and gravel habitat types mixed with clay. Lake sturgeon > 700 mm in length selected sand and gravel areas mixed with zebra mussels and areas dominated by zebra mussels, while fish < 700 mm used these habitat types in proportion to their availability.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2013.11.002","usgsCitation":"Boase, J., Manny, B.A., Donald, K.A., Kennedy, G.W., Diana, J., Thomas, M.V., and Chiotti, J., 2014, Habitat used by juvenile lake sturgeon (<i>Acipenser fulvescens</i>) in the North Channel of the St. Clair River (Michigan, USA): Journal of Great Lakes Research, v. 40, p. 81-88, https://doi.org/10.1016/j.jglr.2013.11.002.","productDescription":"8 p.","startPage":"81","endPage":"88","numberOfPages":"8","ipdsId":"IP-055169","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":286873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286872,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2013.11.002"}],"country":"United States","state":"Michigan","otherGeospatial":"St. Clair River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.4285,41.9625 ], [ -83.4285,43.0146 ], [ -82.2876,43.0146 ], [ -82.2876,41.9625 ], [ -83.4285,41.9625 ] ] ] } } ] }","volume":"40","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5368a4d1e4b059f7e82882fa","contributors":{"authors":[{"text":"Boase, James C.","contributorId":72713,"corporation":false,"usgs":true,"family":"Boase","given":"James C.","affiliations":[],"preferred":false,"id":493311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manny, Bruce A. 0000-0002-4074-9329 bmanny@usgs.gov","orcid":"https://orcid.org/0000-0002-4074-9329","contributorId":3699,"corporation":false,"usgs":true,"family":"Manny","given":"Bruce","email":"bmanny@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":493305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donald, Katherine A.L.","contributorId":56978,"corporation":false,"usgs":true,"family":"Donald","given":"Katherine","email":"","middleInitial":"A.L.","affiliations":[],"preferred":false,"id":493310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, Gregory W. 0000-0003-1686-6960 gkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-1686-6960","contributorId":3700,"corporation":false,"usgs":true,"family":"Kennedy","given":"Gregory","email":"gkennedy@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":493306,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diana, James S.","contributorId":52137,"corporation":false,"usgs":true,"family":"Diana","given":"James S.","affiliations":[],"preferred":false,"id":493309,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thomas, Michael V.","contributorId":47629,"corporation":false,"usgs":true,"family":"Thomas","given":"Michael","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":493308,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chiotti, Justin A.","contributorId":26629,"corporation":false,"usgs":false,"family":"Chiotti","given":"Justin A.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":493307,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70078397,"text":"ofr20141019 - 2014 - Seismic profile analysis of sediment deposits in Brownlee and Hells Canyon Reservoirs near Cambridge, Idaho","interactions":[],"lastModifiedDate":"2014-05-05T10:30:23","indexId":"ofr20141019","displayToPublicDate":"2014-05-05T09:51:29","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":"2014-1019","title":"Seismic profile analysis of sediment deposits in Brownlee and Hells Canyon Reservoirs near Cambridge, Idaho","docAbstract":"The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center, in cooperation with the USGS Idaho Water Science Center and the Idaho Power Company, collected high-resolution seismic reflection data in the Brownlee and Hells Canyon Reservoirs, in March of 2013.These reservoirs are located along the Snake River, and were constructed in 1958 (Brownlee) and 1967 (Hells Canyon). The purpose of the survey was to gain a better understanding of sediment accumulation within the reservoirs since their construction. The chirp system used in the survey was an EdgeTech Geo-Star Full Spectrum Sub-Bottom (FSSB) system coupled with an SB-424 towfish with a frequency range of 4 to 24 kHz. Approximately 325 kilometers of chirp data were collected, with water depths ranging from 0-90 meters. These reservoirs are characterized by very steep rock valley walls, very low flow rates, and minimal sediment input into the system. Sediments deposited in the reservoirs are characterized as highly fluid clays. Since the acoustic signal was not able to penetrate the rock substrate, only the thin veneer of these recent deposits were imaged. Results from the seismic survey indicate that throughout both of the Brownlee and Hells Canyon reservoirs the accumulation of sediments ranged from 0 to 2.5 m, with an average of 0.5 m. Areas of above average sediment accumulation may be related to lower slope, longer flooding history, and proximity to fluvial sources.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141019","usgsCitation":"Flocks, J., Kelso, K., Fosness, R., and Welcker, C., 2014, Seismic profile analysis of sediment deposits in Brownlee and Hells Canyon Reservoirs near Cambridge, Idaho: U.S. Geological Survey Open-File Report 2014-1019, v, 14 p., https://doi.org/10.3133/ofr20141019.","productDescription":"v, 14 p.","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-052989","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":286861,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1019/"},{"id":286862,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1019/pdf/ofr2014-1019.pdf"},{"id":286863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141019.jpg"}],"country":"United States","state":"Idaho;Oregon","otherGeospatial":"Brownlee Reservoirs;Hells Canyon Reservoirs","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.25,44.33 ], [ -117.25,45.25 ], [ -116.66,45.25 ], [ -116.66,44.33 ], [ -117.25,44.33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5368a4d3e4b059f7e8288313","contributors":{"authors":[{"text":"Flocks, James","contributorId":62266,"corporation":false,"usgs":true,"family":"Flocks","given":"James","affiliations":[],"preferred":false,"id":489940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelso, Kyle","contributorId":68017,"corporation":false,"usgs":true,"family":"Kelso","given":"Kyle","affiliations":[],"preferred":false,"id":489942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fosness, Ryan","contributorId":76229,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","affiliations":[],"preferred":false,"id":489943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Welcker, Chris","contributorId":63314,"corporation":false,"usgs":true,"family":"Welcker","given":"Chris","email":"","affiliations":[],"preferred":false,"id":489941,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70057889,"text":"70057889 - 2014 - Reducing bias in survival under non-random temporary emigration","interactions":[],"lastModifiedDate":"2014-06-27T13:46:08","indexId":"70057889","displayToPublicDate":"2014-05-01T15:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Reducing bias in survival under non-random temporary emigration","docAbstract":"Despite intensive monitoring, temporary emigration from the sampling area can induce bias severe enough for managers to discard life-history parameter estimates toward the terminus of the times series (terminal bias). Under random temporary emigration unbiased parameters can be estimated with CJS models. However, unmodeled Markovian temporary emigration causes bias in parameter estimates and an unobservable state is required to model this type of emigration. The robust design is most flexible when modeling temporary emigration, and partial solutions to mitigate bias have been identified, nonetheless there are conditions were terminal bias prevails. Long-lived species with high adult survival and highly variable non-random temporary emigration present terminal bias in survival estimates, despite being modeled with the robust design and suggested constraints. Because this bias is due to uncertainty about the fate of individuals that are undetected toward the end of the time series, solutions should involve using additional information on survival status or location of these individuals at that time. Using simulation, we evaluated the performance of models that jointly analyze robust design data and an additional source of ancillary data (predictive covariate on temporary emigration, telemetry, dead recovery, or auxiliary resightings) in reducing terminal bias in survival estimates. The auxiliary resighting and predictive covariate models reduced terminal bias the most. Additional telemetry data was effective at reducing terminal bias only when individuals were tracked for a minimum of two years. High adult survival of long-lived species made the joint model with recovery data ineffective at reducing terminal bias because of small-sample bias. The naïve constraint model (last and penultimate temporary emigration parameters made equal), was the least efficient, though still able to reduce terminal bias when compared to an unconstrained model. Joint analysis of several sources of data improved parameter estimates and reduced terminal bias. Efforts to incorporate or acquire such data should be considered by researchers and wildlife managers, especially in the years leading up to status assessments of species of interest. Simulation modeling is a very cost effective method to explore the potential impacts of using different sources of data to produce high quality demographic data to inform management.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/13-0558.1","usgsCitation":"Peñaloza, C., Kendall, W.L., and Langtimm, C.A., 2014, Reducing bias in survival under non-random temporary emigration: Ecological Applications, v. 24, no. 5, p. 1155-1166, https://doi.org/10.1890/13-0558.1.","productDescription":"12 p.","startPage":"1155","endPage":"1166","numberOfPages":"12","ipdsId":"IP-044788","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":287158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287157,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/13-0558.1"}],"volume":"24","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53749074e4b0870f4d23cfe2","contributors":{"authors":[{"text":"Peñaloza, Claudia L.","contributorId":107201,"corporation":false,"usgs":true,"family":"Peñaloza","given":"Claudia L.","affiliations":[],"preferred":false,"id":486921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. wkendall@usgs.gov","contributorId":406,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"wkendall@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":486919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langtimm, Catherine Ann 0000-0001-8499-5743","orcid":"https://orcid.org/0000-0001-8499-5743","contributorId":33223,"corporation":false,"usgs":true,"family":"Langtimm","given":"Catherine","email":"","middleInitial":"Ann","affiliations":[],"preferred":false,"id":486920,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70112938,"text":"70112938 - 2014 - BatTool: an R package with GUI for assessing the effect of White-nose syndrome and other take events on <i>Myotis</i> spp. of bats","interactions":[],"lastModifiedDate":"2014-06-18T14:17:51","indexId":"70112938","displayToPublicDate":"2014-05-01T14:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3433,"text":"Source Code for Biology and Medicine","active":true,"publicationSubtype":{"id":10}},"title":"BatTool: an R package with GUI for assessing the effect of White-nose syndrome and other take events on <i>Myotis</i> spp. of bats","docAbstract":"<p>Background:</p> \n<p>Myotis species of bats such as the Indiana Bat and Little Brown Bat are facing population declines because of White-nose syndrome (WNS). These species also face threats from anthropogenic activities such as wind energy development. Population models may be used to provide insights into threats facing these species. We developed a population model, BatTool, as an R package to help decision makers and natural resource managers examine factors influencing the dynamics of these species. The R package includes two components: 1) a deterministic and stochastic model that are accessible from the command line and 2) a graphical user interface (GUI).</p>\n<br>\n<p>Results:</p> \n<p>BatTool is an R package allowing natural resource managers and decision makers to understand Myotis spp. population dynamics. Through the use of a GUI, the model allows users to understand how WNS and other take events may affect the population. The results are saved both graphically and as data files. Additionally, R-savvy users may access the population functions through the command line and reuse the code as part of future research. This R package could also be used as part of a population dynamics or wildlife management course.</p>\n<br>\n<p>Conclusions:</p> \n<p>BatTool provides access to a Myotis spp. population model. This tool can help natural resource managers and decision makers with the Endangered Species Act deliberations for these species and with issuing take permits as part of regulatory decision making. The tool is available online as part of this publication.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Source Code for Biology and Medicine","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"BioMed Central","doi":"10.1186/1751-0473-9-9","usgsCitation":"Erickson, R.A., Thogmartin, W.E., and Szymanski, J.A., 2014, BatTool: an R package with GUI for assessing the effect of White-nose syndrome and other take events on <i>Myotis</i> spp. of bats: Source Code for Biology and Medicine, v. 9, no. 9, 10 p., https://doi.org/10.1186/1751-0473-9-9.","productDescription":"10 p.","numberOfPages":"10","onlineOnly":"Y","ipdsId":"IP-055439","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":473009,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/1751-0473-9-9","text":"Publisher Index Page"},{"id":288829,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288820,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1186/1751-0473-9-9"}],"volume":"9","issue":"9","noUsgsAuthors":false,"publicationDate":"2014-05-06","publicationStatus":"PW","scienceBaseUri":"53ae7644e4b0abf75cf2beef","contributors":{"authors":[{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":494958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":494957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Szymanski, Jennifer A.","contributorId":51593,"corporation":false,"usgs":true,"family":"Szymanski","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494959,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}