{"pageNumber":"578","pageRowStart":"14425","pageSize":"25","recordCount":40783,"records":[{"id":70125639,"text":"ds885 - 2014 - EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012","interactions":[],"lastModifiedDate":"2014-11-06T10:09:12","indexId":"ds885","displayToPublicDate":"2014-11-04T12:45:00","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":"885","title":"EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012","docAbstract":"<p>These remotely sensed, geographically referenced elevation measurements of lidar-derived submerged topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.</p>\n<p>&nbsp;</p>\n<p>This project provides highly detailed and accurate datasets for part of Barnegat Bay, New Jersey, acquired pre-Hurricane Sandy on October 18, 22, 23, and 26, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys.</p>\n<p>&nbsp;</p>\n<p>Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the \"bare earth\" under vegetation from a point cloud of last return elevations.</p>\n<p>&nbsp;</p>\n<p>For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds885","usgsCitation":"Wright, C.W., Troche, R.J., Klipp, E.S., Kranenburg, C., Fredericks, X., and Nagle, D.B., 2014, EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012: U.S. Geological Survey Data Series 885, Web Page, https://doi.org/10.3133/ds885.","productDescription":"Web Page","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054940","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":295859,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0885/"},{"id":295860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0885/home.html"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f032e4b0bc0bec09f5fe","contributors":{"authors":[{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":2973,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Troche, Rodolfo J. rtroche@usgs.gov","contributorId":4304,"corporation":false,"usgs":true,"family":"Troche","given":"Rodolfo","email":"rtroche@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kranenburg, Christine J. ckranenburg@usgs.gov","contributorId":3924,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine J.","email":"ckranenburg@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredericks, Xan 0000-0001-7186-6555 afredericks@usgs.gov","orcid":"https://orcid.org/0000-0001-7186-6555","contributorId":2972,"corporation":false,"usgs":true,"family":"Fredericks","given":"Xan","email":"afredericks@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagle, David B. 0000-0002-2306-6147 dnagle@usgs.gov","orcid":"https://orcid.org/0000-0002-2306-6147","contributorId":3380,"corporation":false,"usgs":true,"family":"Nagle","given":"David","email":"dnagle@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519515,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70128981,"text":"ds888 - 2014 - EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged)","interactions":[],"lastModifiedDate":"2014-11-06T10:54:55","indexId":"ds888","displayToPublicDate":"2014-11-04T12:15:00","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":"888","title":"EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged)","docAbstract":"<p>These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and submerged) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.</p>\n<p>&nbsp;</p>\n<p>This project provides highly detailed and accurate datasets for part of Fire Island, New York, acquired pre-Hurricane Sandy on October 27, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys.</p>\n<p>&nbsp;</p>\n<p>Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the \"bare earth\" under vegetation from a point cloud of last return elevations.</p>\n<p>&nbsp;</p>\n<p>For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds888","usgsCitation":"Wright, C.W., Kranenburg, C., Klipp, E.S., Troche, R.J., Fredericks, X., Masessa, M.L., and Nagle, D.B., 2014, EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged): U.S. Geological Survey Data Series 888, HTML Document, https://doi.org/10.3133/ds888.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056095","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":295857,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0888/html/home.html"},{"id":295856,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0888/"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f032e4b0bc0bec09f600","contributors":{"authors":[{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":2973,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kranenburg, Christine J. ckranenburg@usgs.gov","contributorId":3924,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine J.","email":"ckranenburg@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Troche, Rodolfo J. rtroche@usgs.gov","contributorId":4304,"corporation":false,"usgs":true,"family":"Troche","given":"Rodolfo","email":"rtroche@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519779,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredericks, Xan 0000-0001-7186-6555 afredericks@usgs.gov","orcid":"https://orcid.org/0000-0001-7186-6555","contributorId":2972,"corporation":false,"usgs":true,"family":"Fredericks","given":"Xan","email":"afredericks@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519775,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Masessa, Melanie L. mmasessa@usgs.gov","contributorId":5903,"corporation":false,"usgs":true,"family":"Masessa","given":"Melanie","email":"mmasessa@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519780,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nagle, David B. 0000-0002-2306-6147 dnagle@usgs.gov","orcid":"https://orcid.org/0000-0002-2306-6147","contributorId":3380,"corporation":false,"usgs":true,"family":"Nagle","given":"David","email":"dnagle@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519777,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70131492,"text":"70131492 - 2014 - Limitations to estimating bacterial cross-speciestransmission using genetic and genomic markers: Inferences from simulation modeling","interactions":[],"lastModifiedDate":"2020-12-29T12:52:06.935036","indexId":"70131492","displayToPublicDate":"2014-11-04T11:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Limitations to estimating bacterial cross-speciestransmission using genetic and genomic markers: Inferences from simulation modeling","docAbstract":"<div class=\"article-section__content en main\"><p>Cross‐species transmission (CST) of bacterial pathogens has major implications for human health, livestock, and wildlife management because it determines whether control actions in one species may have subsequent effects on other potential host species. The study of bacterial transmission has benefitted from methods measuring two types of genetic variation: variable number of tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). However, it is unclear whether these data can distinguish between different epidemiological scenarios. We used a simulation model with two host species and known transmission rates (within and between species) to evaluate the utility of these markers for inferring CST. We found that CST estimates are biased for a wide range of parameters when based on VNTRs and a most parsimonious reconstructed phylogeny. However, estimations of CST rates lower than 5% can be achieved with relatively low bias using as low as 250 SNPs. CST estimates are sensitive to several parameters, including the number of mutations accumulated since introduction, stochasticity, the genetic difference of strains introduced, and the sampling effort. Our results suggest that, even with whole‐genome sequences, unbiased estimates of CST will be difficult when sampling is limited, mutation rates are low, or for pathogens that were recently introduced.</p></div>","language":"English","publisher":"Wiley","doi":"10.1111/eva.12173","usgsCitation":"Benavides, J.A., Cross, P.C., Luikart, G., and Creel, S., 2014, Limitations to estimating bacterial cross-speciestransmission using genetic and genomic markers: Inferences from simulation modeling: Evolutionary Applications, v. 7, no. 7, p. 774-787, https://doi.org/10.1111/eva.12173.","productDescription":"14 p.","startPage":"774","endPage":"787","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052486","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":472654,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.12173","text":"Publisher Index Page"},{"id":295853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"7","noUsgsAuthors":false,"publicationDate":"2014-07-23","publicationStatus":"PW","scienceBaseUri":"5459eaa2e4b009f8aec96ff8","contributors":{"authors":[{"text":"Benavides, Julio Andre","contributorId":124530,"corporation":false,"usgs":false,"family":"Benavides","given":"Julio","email":"","middleInitial":"Andre","affiliations":[{"id":5090,"text":"Department of Ecology, 310 Lewis Hall, Montana State University, Bozeman, Montana 59717 USA","active":true,"usgs":false}],"preferred":false,"id":521270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521269,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luikart, Gordon","contributorId":124531,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":5091,"text":"Flathead Lake Biological Station, Fish and Wildlife Genomics Group, Division of Biological Sciences, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":521271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Creel, Scott","contributorId":124532,"corporation":false,"usgs":false,"family":"Creel","given":"Scott","email":"","affiliations":[{"id":5090,"text":"Department of Ecology, 310 Lewis Hall, Montana State University, Bozeman, Montana 59717 USA","active":true,"usgs":false}],"preferred":false,"id":521272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70127080,"text":"sir20145182 - 2014 - Simulation of hydrologic conditions and suspended-sediment loads in the San Antonio River Basin downstream from San Antonio, Texas, 2000-12","interactions":[],"lastModifiedDate":"2016-08-05T12:08:21","indexId":"sir20145182","displayToPublicDate":"2014-11-04T09:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5182","title":"Simulation of hydrologic conditions and suspended-sediment loads in the San Antonio River Basin downstream from San Antonio, Texas, 2000-12","docAbstract":"<p>Suspended sediment in rivers and streams can play an&nbsp;important role in ecological health of rivers and estuaries&nbsp;and consequently is an important issue for water-resource managers. To better understand suspended-sediment loads and transport in a watershed, the U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority, developed a Hydrological Simulation Program&mdash;FORTRAN model to simulate hydrologic conditions and suspended-sediment loads during&nbsp;2000&ndash;12 for four watersheds, which comprise the overall study area in the San Antonio River Basin (hereinafter referred to as the &ldquo;USGS&ndash;2014 model&rdquo;). The study area consists of approximately 2,150 square miles encompassing parts of Bexar, Guadalupe, Wilson, Karnes, DeWitt, Goliad, Victoria, and Refugio Counties. The USGS&ndash;2014 model was calibrated for hydrology and suspended sediment for 2006&ndash;12. Overall, model-fit statistics and graphic evaluations from the calibration and testing periods provided multiple lines of evidence indicating that the USGS&ndash;2014 model simulations of hydrologic and suspended-sediment conditions were mostly&nbsp;&ldquo;good&rdquo; to &ldquo;very good.&rdquo; Model simulation results indicated that approximately 1,230&nbsp;tons per day of suspended sediment exited the study area and were delivered to the Guadalupe River during 2006&ndash;12, of which approximately 62 percent originated upstream from the study area. Sample data and simulated model results indicate that most of the suspended-sediment load in the study area consisted of silt- and clay-sized particles (less than 0.0625&nbsp;millimeters). The Cibolo Creek watershed was the largest contributor of suspended sediment from the study area. For the entire study area, open/developed land and cropland exhibited the highest simulated soil erosion rates; however, the largest contributions of sediment (by land-cover type) were pasture and forest/rangeland/shrubland, which together composed approximately 80&nbsp;percent of the land cover of the study area and generated about 70 percent of the suspended-sediment load from the study area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145182","collaboration":"Prepared in cooperation with the San Antonio River Authority","usgsCitation":"Banta, J., and Ockerman, D.J., 2014, Simulation of hydrologic conditions and suspended-sediment loads in the San Antonio River Basin downstream from San Antonio, Texas, 2000-12: U.S. Geological Survey Scientific Investigations Report 2014-5182, v, 46 p., https://doi.org/10.3133/sir20145182.","productDescription":"v, 46 p.","numberOfPages":"56","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2000-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-056710","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":295842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145182.jpg"},{"id":295821,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5182/"},{"id":295841,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5182/pdf/sir2014-5182.pdf"}],"country":"United States","state":"Texas","city":"San Antonio","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa3e4b009f8aec97016","contributors":{"authors":[{"text":"Banta, J. Ryan 0000-0002-2226-7270 jbanta@usgs.gov","orcid":"https://orcid.org/0000-0002-2226-7270","contributorId":4723,"corporation":false,"usgs":true,"family":"Banta","given":"J. Ryan","email":"jbanta@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":522917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ockerman, Darwin J. 0000-0003-1958-1688 ockerman@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":1579,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","email":"ockerman@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522918,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70127487,"text":"ofr20141206 - 2014 - Low-head hydropower assessment of the Brazilian State of São Paulo","interactions":[],"lastModifiedDate":"2017-01-18T11:27:29","indexId":"ofr20141206","displayToPublicDate":"2014-11-04T09:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1206","title":"Low-head hydropower assessment of the Brazilian State of São Paulo","docAbstract":"<p>This study produced a comprehensive estimate of the magnitude of hydropower potential available in the streams that drain watersheds entirely within the State of S&atilde;o Paulo, Brazil. Because a large part of the contributing area is outside of S&atilde;o Paulo, the main stem of the Paran&aacute; River was excluded from the assessment. Potential head drops were calculated from the Digital Terrain Elevation Data,which has a 1-arc-second resolution (approximately 30-meter resolution at the equator). For the conditioning and validation of synthetic stream channels derived from the Digital Elevation Model datasets, hydrography data (in digital format) supplied by the S&atilde;o Paulo State Department of Energy and the Ag&ecirc;ncia Nacional de &Aacute;guas were used. Within the study area there were 1,424&nbsp;rain gages and 123 streamgages with long-term data records. To estimate average yearly streamflow, a hydrologic regionalization system that divides the State into 21 homogeneous basins was used. Stream segments, upstream areas, and mean annual rainfall were estimated using geographic information systems techniques. The accuracy of the flows estimated with the regionalization models was validated. Overall, simulated streamflows were significantly correlated with the observed flows but with a consistent underestimation bias. When the annual mean flows from the regionalization models were adjusted upward by 10 percent, average streamflow estimation bias was reduced from -13 percent to -4 percent. The sum of all the validated stream reach mean annual hydropower potentials in the 21 basins is 7,000 megawatts (MW). Hydropower potential is mainly concentrated near the Serra do Mar mountain range and along the Tiet&ecirc; River. The power potential along the Tiet&ecirc; River is mainly at sites with medium and high potentials, sites where hydropower has already been harnessed. In addition to the annual mean hydropower estimates, potential hydropower estimates with flow rates with exceedance probabilities of 40 percent, 60 percent, and 90&nbsp;percent were made.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141206","usgsCitation":"Artan, G.A., Cushing, W.M., Mathis, M.L., and Tieszen, L.L., 2014, Low-head hydropower assessment of the Brazilian State of São Paulo: U.S. Geological Survey Open-File Report 2014-1206, v, 15 p., https://doi.org/10.3133/ofr20141206.","productDescription":"v, 15 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051675","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":295835,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141206.jpg"},{"id":295834,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1206/pdf/ofr2014-1206.pdf","text":"Report","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":295766,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1206/"}],"country":"Brazil","city":"São Paulo","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa2e4b009f8aec96ffe","contributors":{"authors":[{"text":"Artan, Guleid A. 0000-0001-8409-6182 gartan@usgs.gov","orcid":"https://orcid.org/0000-0001-8409-6182","contributorId":2938,"corporation":false,"usgs":true,"family":"Artan","given":"Guleid","email":"gartan@usgs.gov","middleInitial":"A.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cushing, W. Matthew 0000-0001-5209-6006 mcushing@usgs.gov","orcid":"https://orcid.org/0000-0001-5209-6006","contributorId":2980,"corporation":false,"usgs":true,"family":"Cushing","given":"W.","email":"mcushing@usgs.gov","middleInitial":"Matthew","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mathis, Melissa L. 0000-0003-4967-4770 mlmathis@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-4770","contributorId":5461,"corporation":false,"usgs":true,"family":"Mathis","given":"Melissa","email":"mlmathis@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tieszen, Larry L. tieszen@usgs.gov","contributorId":2831,"corporation":false,"usgs":true,"family":"Tieszen","given":"Larry","email":"tieszen@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":521222,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70121352,"text":"sir20145164 - 2014 - Estimates of growth and mortality of under-yearling smallmouth bass in Spednic Lake, from 1970 through 2008","interactions":[],"lastModifiedDate":"2014-11-04T08:55:49","indexId":"sir20145164","displayToPublicDate":"2014-11-04T09:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5164","title":"Estimates of growth and mortality of under-yearling smallmouth bass in Spednic Lake, from 1970 through 2008","docAbstract":"<p>This report is the product of a 2013 cooperative agreement between the U.S. Geological Survey, the International Joint Commission, and the Maine Bureau of Sea Run Fisheries and Habitat to quantify the effects of meteorological conditions (from 1970 through 2008) on the survival of smallmouth bass (<em>Micropterus dolomieu</em>) in the first year of life in Spednic Lake. This report documents the data and methods used to estimate historical daily mean lake surface-water temperatures from early spring through late autumn, which were used to estimate the dates of smallmouth bass spawning, young-of-the-year growth, and probable strength of each year class. Mortality of eggs and fry in nests was modeled and estimated to exceed 10 percent in 17 of 39 years; during those years, cold temperatures in the early part of the spawning period resulted in mortality to fish that were estimated to have had the longest growing season and attain the greatest length. Modeled length-dependent overwinter survival combined with early mortality identified 1986, 1994, 1996, and 2004 as the years in which temperature was likely to have presented the greatest challenge to year-class strength in the Spednic Lake fishery. Age distribution of bass in fisheries on lakes in the St. Croix and surrounding watersheds confirmed that conditions in 1986 and 1996 resulted in weak smallmouth bass year classes (age-four or age-five bass representing less than 15 percent of a 100-fish sample).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145164","collaboration":"Prepared in cooperation with the International Joint Commission St. Croix River Watershed Board and the Maine Bureau of Sea Run Fisheries and Habitat","usgsCitation":"Dudley, R.W., and Trial, J.G., 2014, Estimates of growth and mortality of under-yearling smallmouth bass in Spednic Lake, from 1970 through 2008: U.S. Geological Survey Scientific Investigations Report 2014-5164, v, 15 p., https://doi.org/10.3133/sir20145164.","productDescription":"v, 15 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1970-01-01","temporalEnd":"2008-12-31","ipdsId":"IP-057932","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":295830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145164.jpg"},{"id":295761,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5164/"},{"id":295762,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5164/pdf/sir2014-5164.pdf","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"}}],"scale":"24000","projection":"Universal Transverse Mercator projection","country":"Canada, United States","state":"Maine","otherGeospatial":"Spednic Lake","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa1e4b009f8aec96fda","contributors":{"authors":[{"text":"Dudley, Robert W. 0000-0002-0934-0568 rwdudley@usgs.gov","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":2223,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert","email":"rwdudley@usgs.gov","middleInitial":"W.","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":519251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trial, Joan G.","contributorId":91156,"corporation":false,"usgs":true,"family":"Trial","given":"Joan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":519252,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70157371,"text":"70157371 - 2014 - Using mark-recapture distance sampling methods on line transect surveys","interactions":[],"lastModifiedDate":"2017-11-24T17:47:57","indexId":"70157371","displayToPublicDate":"2014-11-01T12:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Using mark-recapture distance sampling methods on line transect surveys","docAbstract":"<ol id=\"mee312294-list-0001\" class=\"numbered\">\n<li>Mark&ndash;recapture distance sampling (MRDS) methods are widely used for density and abundance estimation when the conventional DS assumption of certain detection at distance zero fails, as they allow detection at distance zero to be estimated and incorporated into the overall probability of detection to better estimate density and abundance. However, incorporating MR data in DS models raises survey and analysis issues not present in conventional DS. Conversely, incorporating DS assumptions in MR models raises issues not present in conventional MR. As a result, being familiar with either conventional DS methods or conventional MR methods does not on its own put practitioners in good a position to apply MRDS methods appropriately. This study explains the sometimes subtly different varieties of MRDS survey methods and the associated concepts underlying MRDS models. This is done as far as possible without giving mathematical details &ndash; in the hope that this will make the key concepts underlying the methods accessible to a wider audience than if we were to present the concepts via equations.</li>\n<li>We illustrate use of the two main types of MRDS model by using data collected on two different types of survey: a survey of ungulate faecal pellets where two observers searched independently of each other; and a cetacean survey that used a search protocol that could accommodate responsive movement, with only one observer searching independently and the other being aware of all detections.</li>\n<li><i>Synthesis and applications</i>. Mark&ndash;recapture DS is a widely used method for estimating animal density and abundance when detection of animals at distance zero is not certain. Two observer configurations and three statistical models are described, and it is important to choose the most appropriate model for the observer configuration and target species in question. By way of making the methods more accessible to practicing ecologists, we describe the key ideas underlying MRDS methods, the sometimes subtle differences between them, and we illustrate these by applying different kinds of MRDS method to surveys of two different target species using different survey configurations.</li>\n</ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.12294","usgsCitation":"Burt, L.M., Borchers, D., Jenkins, K.J., and Marques, T.A., 2014, Using mark-recapture distance sampling methods on line transect surveys: Methods in Ecology and Evolution, v. 5, no. 11, p. 1180-1191, https://doi.org/10.1111/2041-210X.12294.","productDescription":"12 p.","startPage":"1180","endPage":"1191","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059999","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":472656,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12294","text":"Publisher Index Page"},{"id":308436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-12","publicationStatus":"PW","scienceBaseUri":"5603cd5de4b03bc34f544b49","chorus":{"doi":"10.1111/2041-210x.12294","url":"http://dx.doi.org/10.1111/2041-210x.12294","publisher":"Wiley-Blackwell","authors":"Burt Mary Louise, Borchers David L., Jenkins Kurt J., Marques Tiago A.","journalName":"Methods in Ecology and Evolution","publicationDate":"11/2014"},"contributors":{"authors":[{"text":"Burt, Louise M.","contributorId":147848,"corporation":false,"usgs":false,"family":"Burt","given":"Louise","email":"","middleInitial":"M.","affiliations":[{"id":16945,"text":"St. Andrews University, UK","active":true,"usgs":false}],"preferred":false,"id":572899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borchers, David L.","contributorId":31106,"corporation":false,"usgs":true,"family":"Borchers","given":"David L.","affiliations":[],"preferred":false,"id":572900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenkins, Kurt J. 0000-0003-1415-6607 kurt_jenkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":3415,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","email":"kurt_jenkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":572898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marques, Tigao A","contributorId":147849,"corporation":false,"usgs":false,"family":"Marques","given":"Tigao","email":"","middleInitial":"A","affiliations":[{"id":16945,"text":"St. Andrews University, UK","active":true,"usgs":false}],"preferred":false,"id":572901,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70157379,"text":"70157379 - 2014 - Attenuation and scattering tomography of the deep plumbing system of Mount St. Helens","interactions":[],"lastModifiedDate":"2019-03-05T09:51:38","indexId":"70157379","displayToPublicDate":"2014-11-01T12:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Attenuation and scattering tomography of the deep plumbing system of Mount St. Helens","docAbstract":"<p><span>We present a combined 3-D&nbsp;</span><i>P</i><span>&nbsp;wave attenuation, 2-D&nbsp;</span><i>S</i><span>&nbsp;coda attenuation, and 3-D&nbsp;</span><i>S</i><span>&nbsp;coda scattering tomography model of fluid pathways, feeding systems, and sediments below Mount St. Helens (MSH) volcano between depths of 0 and 18 km. High-scattering and high-attenuation shallow anomalies are indicative of magma and fluid-rich zones within and below the volcanic edifice down to 6 km depth, where a high-scattering body outlines the top of deeper aseismic velocity anomalies. Both the volcanic edifice and these structures induce a combination of strong scattering and attenuation on any seismic wavefield, particularly those recorded on the northern and eastern flanks of the volcanic cone. North of the cone between depths of 0 and 10 km, a low-velocity, high-scattering, and high-attenuation north-south trending trough is attributed to thick piles of Tertiary marine sediments within the St. Helens Seismic Zone. A laterally extended 3-D scattering contrast at depths of 10 to 14 km is related to the boundary between upper and lower crust and caused in our interpretation by the large-scale interaction of the Siletz terrane with the Cascade arc crust. This contrast presents a low-scattering, 4&ndash;6 km</span><span>2</span><span>&nbsp;&ldquo;hole&rdquo; under the northeastern flank of the volcano. We infer that this section represents the main path of magma ascent from depths greater than 6 km at MSH, with a small north-east shift in the lower plumbing system of the volcano. We conclude that combinations of different nonstandard tomographic methods, leading toward full-waveform tomography, represent the future of seismic volcano imaging.</span></p>","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2014JB011372","usgsCitation":"De Siena, L., Thomas, C., Waite, G., Moran, S.C., and Klemme, S., 2014, Attenuation and scattering tomography of the deep plumbing system of Mount St. Helens: Journal of Geophysical Research B: Solid Earth, v. 119, no. 11, p. 8223-8238, https://doi.org/10.1002/2014JB011372.","productDescription":"16 p.","startPage":"8223","endPage":"8238","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054945","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014jb011372","text":"Publisher Index Page"},{"id":308432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","county":"Skamania","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.35,\n              46.0833\n            ],\n            [\n              -122,\n              46.0833\n            ],\n            [\n              -122,\n              46.3\n            ],\n            [\n              -122.35,\n              46.3\n            ],\n            [\n              -122.35,\n              46.0833\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"119","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-07","publicationStatus":"PW","scienceBaseUri":"5603cd32e4b03bc34f544aee","contributors":{"authors":[{"text":"De Siena, Luca","contributorId":147853,"corporation":false,"usgs":false,"family":"De Siena","given":"Luca","email":"","affiliations":[{"id":16948,"text":"Institut fur Geophysik, University of Munster, Germany","active":true,"usgs":false}],"preferred":false,"id":572924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Christine","contributorId":84988,"corporation":false,"usgs":true,"family":"Thomas","given":"Christine","affiliations":[],"preferred":false,"id":572925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waite, Greg P.","contributorId":147854,"corporation":false,"usgs":false,"family":"Waite","given":"Greg P.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":572926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moran, Seth C. 0000-0001-7308-9649 smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":548,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":572923,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klemme, Stefan","contributorId":147855,"corporation":false,"usgs":false,"family":"Klemme","given":"Stefan","email":"","affiliations":[{"id":16949,"text":"Institut fur Mineralogie, University of Munster, Germany","active":true,"usgs":false}],"preferred":false,"id":572927,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70156785,"text":"70156785 - 2014 - Development of the Coastal Storm Modeling System (CoSMoS) for predicting the impact of storms on high-energy, active-margin coasts","interactions":[],"lastModifiedDate":"2015-08-31T10:51:57","indexId":"70156785","displayToPublicDate":"2014-11-01T12:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Development of the Coastal Storm Modeling System (CoSMoS) for predicting the impact of storms on high-energy, active-margin coasts","docAbstract":"<p><span>The Coastal Storm Modeling System (CoSMoS) applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers). CoSMoS was developed for hindcast studies, operational applications (i.e., nowcasts and multiday forecasts), and future climate scenarios (i.e., sea-level rise&nbsp;+&nbsp;storms) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. The prototype system, developed for the California coast, uses the global WAVEWATCH III wave model, the TOPEX/Poseidon satellite altimetry-based global tide model, and atmospheric-forcing data from either the US National Weather Service (operational mode) or Global Climate Models (future climate mode), to determine regional wave and water-level boundary conditions. These physical processes are dynamically downscaled using a series of nested Delft3D-WAVE (SWAN) and Delft3D-FLOW (FLOW) models and linked at the coast to tightly spaced XBeach (eXtreme Beach) cross-shore profile models and a Bayesian probabilistic cliff failure model. Hindcast testing demonstrates that, despite uncertainties in preexisting beach morphology over the ~500&nbsp;km alongshore extent of the pilot study area, CoSMoS effectively identifies discrete sections of the coast (100s of meters) that are vulnerable to coastal hazards under a range of current and future oceanographic forcing conditions, and is therefore an effective tool for operational and future climate scenario planning.</span></p>","language":"English","publisher":"International Society for the Prevention and Mitigation of Natural Hazards","publisherLocation":"Dordrecht","doi":"10.1007/s11069-014-1236-y","usgsCitation":"Barnard, P., van Ormondt, M., Erikson, L., Eshleman, J., Hapke, C.J., Peter Ruggiero, Adams, P., and Foxgrover, A.C., 2014, Development of the Coastal Storm Modeling System (CoSMoS) for predicting the impact of storms on high-energy, active-margin coasts: Natural Hazards, v. 74, no. 2, p. 1095-1125, https://doi.org/10.1007/s11069-014-1236-y.","productDescription":"31 p.","startPage":"1095","endPage":"1125","numberOfPages":"31","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054533","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":307716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-21","publicationStatus":"PW","scienceBaseUri":"55e57aace4b05561fa20868b","contributors":{"authors":[{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":570535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Ormondt, Maarten","contributorId":147148,"corporation":false,"usgs":false,"family":"van Ormondt","given":"Maarten","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":570536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":147149,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":570537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eshleman, Jodi","contributorId":147150,"corporation":false,"usgs":false,"family":"Eshleman","given":"Jodi","email":"","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":570538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":570539,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peter Ruggiero","contributorId":147151,"corporation":false,"usgs":false,"family":"Peter Ruggiero","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":570540,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Adams, Peter","contributorId":147152,"corporation":false,"usgs":false,"family":"Adams","given":"Peter","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":570541,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Foxgrover, Amy C. 0000-0003-0638-5776 afoxgrover@usgs.gov","orcid":"https://orcid.org/0000-0003-0638-5776","contributorId":3261,"corporation":false,"usgs":true,"family":"Foxgrover","given":"Amy","email":"afoxgrover@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":570542,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70155265,"text":"70155265 - 2014 - La Niña diversity and Northwest Indian Ocean Rim teleconnections","interactions":[],"lastModifiedDate":"2017-01-18T11:28:00","indexId":"70155265","displayToPublicDate":"2014-11-01T11:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1248,"text":"Climate Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"La Niña diversity and Northwest Indian Ocean Rim teleconnections","docAbstract":"<p><span>The differences in tropical Pacific sea surface temperature (SST) expressions of El Ni&ntilde;o-Southern Oscillation (ENSO) events of the same phase have been linked with different global atmospheric circulation patterns. This study examines the dynamical forcing of precipitation during October&ndash;December (OND) and March&ndash;May (MAM) over East Africa and during December&ndash;March (DJFM) over Central-Southwest Asia for 1950&ndash;2010 associated with four tropical Pacific SST patterns characteristic of La Ni&ntilde;a events, the cold phase of ENSO. The self-organizing map method along with a statistical distinguishability test was used to isolate La Ni&ntilde;a events, and seasonal precipitation forcing was investigated in terms of the tropical overturning circulation and thermodynamic and moisture budgets. Recent La Ni&ntilde;a events with strong opposing SST anomalies between the central and western Pacific Ocean (phases 3 and 4), force the strongest global circulation modifications and drought over the Northwest Indian Ocean Rim. Over East Africa during MAM and OND, subsidence is forced by an enhanced tropical overturning circulation and precipitation reductions are exacerbated by increases in moisture flux divergence. Over Central-Southwest Asia during DJFM, the thermodynamic forcing of subsidence is primarily responsible for precipitation reductions, with moisture flux divergence acting as a secondary mechanism to reduce precipitation. Eastern Pacific La Ni&ntilde;a events in the absence of west Pacific SST anomalies (phases 1 and 2), are associated with weaker global teleconnections, particularly over the Indian Ocean Rim. The weak regional teleconnections result in statistically insignificant precipitation modifications over East Africa and Central-Southwest Asia.</span></p>","language":"English","publisher":"EBSCO Publishing","publisherLocation":"Heidelberg","doi":"10.1007/s00382-014-2083-y","usgsCitation":"Hoell, A., Funk, C.C., and Barlow, M., 2014, La Niña diversity and Northwest Indian Ocean Rim teleconnections: Climate Dynamics, v. 43, no. 9-10, p. 2707-2724, https://doi.org/10.1007/s00382-014-2083-y.","productDescription":"18 p.","startPage":"2707","endPage":"2724","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052606","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":306484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"9-10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-02","publicationStatus":"PW","scienceBaseUri":"57f7f032e4b0bc0bec09f602","contributors":{"authors":[{"text":"Hoell, Andrew","contributorId":145803,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Mathew","contributorId":145834,"corporation":false,"usgs":false,"family":"Barlow","given":"Mathew","affiliations":[{"id":16250,"text":"University of Massechusetts, Lowell","active":true,"usgs":false}],"preferred":false,"id":565428,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70136059,"text":"70136059 - 2014 - Reducing risk from lahar hazards: Concepts, case studies, and roles for scientists","interactions":[],"lastModifiedDate":"2019-03-13T15:28:39","indexId":"70136059","displayToPublicDate":"2014-11-01T10:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3841,"text":"Journal of Applied Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Reducing risk from lahar hazards: Concepts, case studies, and roles for scientists","docAbstract":"<p>Lahars are rapid flows of mud-rock slurries that can occur without warning and catastrophically impact areas more than 100 km downstream of source volcanoes. Strategies to mitigate the potential for damage or loss from lahars fall into four basic categories: (1) avoidance of lahar hazards through land-use planning; (2) modification of lahar hazards through engineered protection structures; (3) lahar warning systems to enable evacuations; and (4) effective response to and recovery from lahars when they do occur. Successful application of any of these strategies requires an accurate understanding and assessment of the hazard, an understanding of the applicability and limitations of the strategy, and thorough planning. The human and institutional components leading to successful application can be even more important: engagement of all stakeholders in hazard education and risk-reduction planning; good communication of hazard and risk information among scientists, emergency managers, elected officials, and the at-risk public during crisis and non-crisis periods; sustained response training; and adequate funding for risk-reduction efforts. This paper reviews a number of methods for lahar-hazard risk reduction, examines the limitations and tradeoffs, and provides real-world examples of their application in the U.S. Pacific Northwest and in other volcanic regions of the world. An overriding theme is that lahar-hazard risk reduction cannot be effectively accomplished without the active, impartial involvement of volcano scientists, who are willing to assume educational, interpretive, and advisory roles to work in partnership with elected officials, emergency managers, and vulnerable communities.</p>","language":"English","publisher":"Springer-Verlag","doi":"10.1186/s13617-014-0016-4","usgsCitation":"Pierson, T.C., Wood, N.J., and Driedger, C.L., 2014, Reducing risk from lahar hazards: Concepts, case studies, and roles for scientists: Journal of Applied Volcanology, v. 3, no. 16, p. 1-25, https://doi.org/10.1186/s13617-014-0016-4.","productDescription":"25 p.","startPage":"1","endPage":"25","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056294","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472661,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13617-014-0016-4","text":"Publisher Index Page"},{"id":297074,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"16","noUsgsAuthors":false,"publicationDate":"2014-11-06","publicationStatus":"PW","scienceBaseUri":"54dd2c40e4b08de9379b36e2","contributors":{"authors":[{"text":"Pierson, Thomas C. 0000-0001-9002-4273 tpierson@usgs.gov","orcid":"https://orcid.org/0000-0001-9002-4273","contributorId":2498,"corporation":false,"usgs":true,"family":"Pierson","given":"Thomas","email":"tpierson@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":537068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Driedger, Carolyn L. 0000-0002-4011-4112 driedger@usgs.gov","orcid":"https://orcid.org/0000-0002-4011-4112","contributorId":537,"corporation":false,"usgs":true,"family":"Driedger","given":"Carolyn","email":"driedger@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537069,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70135072,"text":"70135072 - 2014 - Wave-driven sediment mobilization on a storm-controlled continental shelf (Northwest Iberia)","interactions":[],"lastModifiedDate":"2021-01-07T18:46:09.71468","indexId":"70135072","displayToPublicDate":"2014-11-01T10:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2381,"text":"Journal of Marine Systems","active":true,"publicationSubtype":{"id":10}},"title":"Wave-driven sediment mobilization on a storm-controlled continental shelf (Northwest Iberia)","docAbstract":"<p>Seafloor sediment mobilization on the inner Northwest Iberian continental shelf is caused largely by ocean surface waves. The temporal and spatial variability in the wave height, wave period, and wave direction has a profound effect on local sediment mobilization, leading to distinct sediment mobilization scenarios. Six grain-size specific sediment mobilization scenarios, representing seasonal average and storm conditions, were simulated with a physics-based numerical model. Model inputs included meteorological and oceanographic data in conjunction with seafloor grain-size and the shelf bathymetric data. The results show distinct seasonal variations, most importantly in wave height, leading to sediment mobilization, specifically on the inner shelf shallower than 30 m water depth where up to 49% of the shelf area is mobilized. Medium to severe storm events are modeled to mobilize up to 89% of the shelf area above 150 m water depth. The frequency of each of these seasonal and storm-related sediment mobilization scenarios is addressed using a decade of meteorological and oceanographic data. The temporal and spatial patterns of the modeled sediment mobilization scenarios are discussed in the context of existing geological and environmental processes and conditions to assist scientific, industrial and environmental efforts that are directly affected by sediment mobilization. Examples, where sediment mobilization plays a vital role, include seafloor nutrient advection, recurrent arrival of oil from oil-spill-laden seafloor sediment, and bottom trawling impacts.</p>","language":"English","publisher":"Elsevier","publisherLocation":"New York, NY","doi":"10.1016/j.jmarsys.2014.07.018","usgsCitation":"Oberle, F., Storlazzi, C., and Hanebuth, T., 2014, Wave-driven sediment mobilization on a storm-controlled continental shelf (Northwest Iberia): Journal of Marine Systems, v. 139, p. 362-372, https://doi.org/10.1016/j.jmarsys.2014.07.018.","productDescription":"11 p.","startPage":"362","endPage":"372","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061568","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":296503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Portugal, Spain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -10.78857421875,\n              40.58058466412761\n            ],\n            [\n              -7.75634765625,\n              40.58058466412761\n            ],\n            [\n              -7.75634765625,\n              43.35713822211053\n            ],\n            [\n              -10.78857421875,\n              43.35713822211053\n            ],\n            [\n              -10.78857421875,\n              40.58058466412761\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"139","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54882b66e4b02acb4f0c8c5a","contributors":{"authors":[{"text":"Oberle, Ferdinand 0000-0001-8871-3619","orcid":"https://orcid.org/0000-0001-8871-3619","contributorId":127792,"corporation":false,"usgs":false,"family":"Oberle","given":"Ferdinand","affiliations":[{"id":7156,"text":"MARUM – Center for Marine Environmental Sciences, University of Bremen","active":true,"usgs":false}],"preferred":false,"id":526779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":2333,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","email":"cstorlazzi@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":526778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanebuth, Till","contributorId":127793,"corporation":false,"usgs":false,"family":"Hanebuth","given":"Till","affiliations":[{"id":7156,"text":"MARUM – Center for Marine Environmental Sciences, University of Bremen","active":true,"usgs":false}],"preferred":false,"id":526780,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70141492,"text":"70141492 - 2014 - Relationships between annual plant productivity, nitrogen deposition and fire size in low-elevation California desert scrub","interactions":[],"lastModifiedDate":"2017-02-13T14:42:52","indexId":"70141492","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Relationships between annual plant productivity, nitrogen deposition and fire size in low-elevation California desert scrub","docAbstract":"<p>Although precipitation is correlated with fire size in desert ecosystems and is typically used as an indirect surrogate for fine fuel load, a direct link between fine fuel biomass and fire size has not been established. In addition, nitrogen (N) deposition can affect fire risk through its fertilisation effect on fine fuel production. In this study, we examine the relationships between fire size and precipitation, N deposition and biomass with emphasis on identifying biomass and N deposition thresholds associated with fire spreading across the landscape. We used a 28-year fire record of 582 burns from low-elevation desert scrub to evaluate the relationship of precipitation, N deposition and biomass with the distribution of fire sizes using quantile regression. We found that models using annual biomass have similar predictive ability to those using precipitation and N deposition at the lower to intermediate portions of the fire size distribution. No distinct biomass threshold was found, although within the 99th percentile of the distribution fire size increased with greater than 125 g m&ndash;2 of winter fine fuel production. The study did not produce an N deposition threshold, but did validate the value of 125 g m&ndash;2 of fine fuel for spread of fires.</p>","language":"English","publisher":"CSIRO","doi":"10.1071/WF13152","usgsCitation":"Rao, L.E., Matchett, J.R., Brooks, M.L., Johns, R., Minnich, R.A., and Allen, E.B., 2014, Relationships between annual plant productivity, nitrogen deposition and fire size in low-elevation California desert scrub: International Journal of Wildland Fire, v. 24, no. 1, p. 48-58, https://doi.org/10.1071/WF13152.","productDescription":"11 p.","startPage":"48","endPage":"58","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051479","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":472677,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf13152","text":"Publisher Index Page"},{"id":298047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.04687499999999,\n              32.602361666817515\n            ],\n            [\n              -123.04687499999999,\n              38.30718056188316\n            ],\n            [\n              -114.10400390625,\n              38.30718056188316\n            ],\n            [\n              -114.10400390625,\n              32.602361666817515\n            ],\n            [\n              -123.04687499999999,\n              32.602361666817515\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"24","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e7173ae4b02d776a66a018","contributors":{"authors":[{"text":"Rao, Leela E.","contributorId":139340,"corporation":false,"usgs":false,"family":"Rao","given":"Leela","email":"","middleInitial":"E.","affiliations":[{"id":12740,"text":"U.C. Riverside, Conservation Biology; CA Air Resources Board MSCD/ERRDB","active":true,"usgs":false}],"preferred":false,"id":540845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matchett, John R. 0000-0002-2905-6468 jmatchett@usgs.gov","orcid":"https://orcid.org/0000-0002-2905-6468","contributorId":1669,"corporation":false,"usgs":true,"family":"Matchett","given":"John","email":"jmatchett@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":540846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":540844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johns, Robert","contributorId":22411,"corporation":false,"usgs":false,"family":"Johns","given":"Robert","email":"","affiliations":[{"id":6984,"text":"UC Riverside","active":true,"usgs":false}],"preferred":false,"id":540847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Minnich, Richard A.","contributorId":37759,"corporation":false,"usgs":false,"family":"Minnich","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":7004,"text":"Department of Earth Sciences, University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":540848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Edith B.","contributorId":139341,"corporation":false,"usgs":false,"family":"Allen","given":"Edith","email":"","middleInitial":"B.","affiliations":[{"id":12741,"text":"U of CA Dept of Botany and Plant Sciences","active":true,"usgs":false}],"preferred":false,"id":540849,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70136277,"text":"70136277 - 2014 - Does lake size matter? Combining morphology and process modeling to examine the contribution of lake classes to population-scale processes","interactions":[],"lastModifiedDate":"2015-08-19T09:14:55","indexId":"70136277","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"Does lake size matter? Combining morphology and process modeling to examine the contribution of lake classes to population-scale processes","docAbstract":"<p>With lake abundances in the thousands to millions, creating an intuitive understanding of the distribution of morphology and processes in lakes is challenging. To improve researchers&rsquo; understanding of large-scale lake processes, we developed a parsimonious mathematical model based on the Pareto distribution to describe the distribution of lake morphology (area, perimeter and volume). While debate continues over which mathematical representation best fits any one distribution of lake morphometric characteristics, we recognize the need for a simple, flexible model to advance understanding of how the interaction between morphometry and function dictates scaling across large populations of lakes. These models make clear the relative contribution of lakes to the total amount of lake surface area, volume, and perimeter. They also highlight the critical thresholds at which total perimeter, area and volume would be evenly distributed across lake size-classes have Pareto slopes of 0.63, 1 and 1.12, respectively. These models of morphology can be used in combination with models of process to create overarching &ldquo;lake population&rdquo; level models of process. To illustrate this potential, we combine the model of surface area distribution with a model of carbon mass accumulation rate. We found that even if smaller lakes contribute relatively less to total surface area than larger lakes, the increasing carbon accumulation rate with decreasing lake size is strong enough to bias the distribution of carbon mass accumulation towards smaller lakes. This analytical framework provides a relatively simple approach to upscaling morphology and process that is easily generalizable to other ecosystem processes.</p>","language":"English","publisher":"Freshwater Biological Association","doi":"10.5268/IW-5.1.740","usgsCitation":"Winslow, L.A., Read, J.S., Hanson, P.C., and Stanley, E.H., 2014, Does lake size matter? Combining morphology and process modeling to examine the contribution of lake classes to population-scale processes: Inland Waters, v. 5, p. 7-14, https://doi.org/10.5268/IW-5.1.740.","productDescription":"8 p.","startPage":"7","endPage":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051175","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"links":[{"id":306908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d5a8aee4b0518e3546a4bb","contributors":{"authors":[{"text":"Winslow, Luke A. 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":5919,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":537277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":537276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":537278,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":537279,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70139727,"text":"70139727 - 2014 - Last interglacial plant macrofossils and climates from Ziegler Reservoir, Snowmass Village, Colorado, USA","interactions":[],"lastModifiedDate":"2015-01-30T16:37:02","indexId":"70139727","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Last interglacial plant macrofossils and climates from Ziegler Reservoir, Snowmass Village, Colorado, USA","docAbstract":"<p><span>Ninety plant macrofossil taxa from the Ziegler Reservoir fossil site near Snowmass Village, Colorado, record environmental changes at high elevation (2705&nbsp;m&nbsp;asl) in the Rocky Mountains during the Last Interglacial Period. Present-day vegetation is aspen forest (</span><i>Populus tremuloides</i><span>) intermixed with species of higher (</span><i>Picea</i><span>,&nbsp;</span><i>Abies</i><span>) and lower (</span><i>Artemisia</i><span>,&nbsp;</span><i>Quercus</i><span>) elevations. Stratigraphic units 4&ndash;13 contain montane forest taxa found near the site today and several species that today generally live at lower elevations within (</span><i>Abies concolor</i><span>,&nbsp;</span><i>Lycopus americanus</i><span>) and outside Colorado (</span><i>Najas flexilis</i><span>). These data suggest near-modern climatic conditions, with slightly warmer summer and winter temperatures. This montane forest period was succeeded by a shorter treeless interval (Unit 14) representing colder and/or drier conditions. In units 15&ndash;16, conifer trees reoccur but deciduous and herb taxa are lacking, suggesting a return to warmer conditions, although cooler than during the earlier forest period. Comparison of these inferred paleoclimatic changes with the site's geochronologic framework indicates that the lower interval of sustained warmth correlates with late MIS 6&ndash;early 5b (~&nbsp;138&ndash;94&nbsp;ka), the cold interval with MIS 5b (~&nbsp;94&ndash;87&nbsp;ka), and the uppermost cool assemblages with MIS 5a (~&nbsp;87&ndash;77&nbsp;ka).</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.yqres.2014.07.008","usgsCitation":"Strickland, L.E., Baker, R.G., Thompson, R.S., and Miller, D.M., 2014, Last interglacial plant macrofossils and climates from Ziegler Reservoir, Snowmass Village, Colorado, USA: Quaternary Research, v. 82, no. 3, p. 553-566, https://doi.org/10.1016/j.yqres.2014.07.008.","productDescription":"14 p.","startPage":"553","endPage":"566","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054428","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":297662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Snowmass Village","otherGeospatial":"Ziegler Reservoir","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.98529243469238,\n              39.19467992738667\n            ],\n            [\n              -106.98529243469238,\n              39.22447414445149\n            ],\n            [\n              -106.94160461425781,\n              39.22447414445149\n            ],\n            [\n              -106.94160461425781,\n              39.19467992738667\n            ],\n            [\n              -106.98529243469238,\n              39.19467992738667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"82","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-20","publicationStatus":"PW","scienceBaseUri":"54dd2bdfe4b08de9379b3538","contributors":{"authors":[{"text":"Strickland, Laura E. 0000-0002-1958-7273 lstrickland@usgs.gov","orcid":"https://orcid.org/0000-0002-1958-7273","contributorId":4682,"corporation":false,"usgs":true,"family":"Strickland","given":"Laura","email":"lstrickland@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":539615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Richard G.","contributorId":38042,"corporation":false,"usgs":false,"family":"Baker","given":"Richard","email":"","middleInitial":"G.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":539616,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Robert S. 0000-0001-9287-2954 rthompson@usgs.gov","orcid":"https://orcid.org/0000-0001-9287-2954","contributorId":891,"corporation":false,"usgs":true,"family":"Thompson","given":"Robert","email":"rthompson@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":539617,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Dane M.","contributorId":127416,"corporation":false,"usgs":false,"family":"Miller","given":"Dane","email":"","middleInitial":"M.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":539618,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70141388,"text":"70141388 - 2014 - Factors influencing nest survival and productivity of Red-throated Loons (<i>Gavia stellata</i>) in Alaska","interactions":[],"lastModifiedDate":"2015-02-18T15:13:40","indexId":"70141388","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing nest survival and productivity of Red-throated Loons (<i>Gavia stellata</i>) in Alaska","docAbstract":"<p><span>Red-throated Loon (</span><i><i>Gavia stellata</i></i><span>) numbers in Alaska have fluctuated dramatically over the past 3 decades; however, the demographic processes contributing to these population dynamics are poorly understood. To examine spatial and temporal variation in productivity, we estimated breeding parameters at 5 sites in Alaska: at Cape Espenberg and the Copper River Delta we estimated nest survival, and at 3 sites within the Yukon-Kuskokwim Delta we estimated nest survival and productivity. Nest survival varied broadly among sites and years; annual estimates (lower, upper 95% confidence interval) ranged from 0.09 (0.03, 0.29) at Cape Espenberg in 2001 to 0.93 (0.76, 0.99) at the Copper River Delta in 2002. Annual variation among sites was not concordant, suggesting that site-scale factors had a strong influence on nest survival. Models of nest survival indicated that visits to monitor nests had a negative effect on nest daily survival probability, which if not accounted for biased nest survival strongly downward. The sensitivity of breeding Red-throated Loons to nest monitoring suggests other sources of disturbance that cause incubating birds to flush from their nests may also reduce nest survival. Nest daily survival probability at the Yukon-Kuskokwim Delta was negatively associated with an annual index of fox occurrence. Survival through the incubation and chick-rearing periods on the Yukon-Kuskokwim Delta ranged from 0.09 (0.001, 0.493) to 0.50 (0.04, 0.77). Daily survival probability during the chick-rearing period was lower for chicks that had a sibling in 2 of 3 years, consistent with the hypothesis that food availability was limited. Estimates of annual productivity on the Yukon-Kuskokwim Delta ranged from 0.17 to 1.0 chicks per pair. Productivity was not sufficient to maintain population stability in 2 of 3 years, indicating that nest depredation by foxes and poor foraging conditions during chick rearing can have important effects on productivity.</span></p>","language":"English","publisher":"Cooper Ornithological Society","doi":"10.1650/CONDOR-14-25.1","usgsCitation":"Rizzolo, D., Schmutz, J.A., McCloskey, S., and Fondell, T., 2014, Factors influencing nest survival and productivity of Red-throated Loons (<i>Gavia stellata</i>) in Alaska: The Condor, v. 116, no. 4, p. 574-587, https://doi.org/10.1650/CONDOR-14-25.1.","productDescription":"14 p.","startPage":"574","endPage":"587","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054060","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":472671,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-14-25.1","text":"Publisher Index Page"},{"id":298042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Cape Espenberg, Copper River Delta, Yukon-Kuskokwim Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -163.9434814453125,\n              66.53733030908982\n            ],\n            [\n              -163.9434814453125,\n              66.60612896127468\n            ],\n            [\n              -163.5699462890625,\n              66.60612896127468\n            ],\n            [\n              -163.5699462890625,\n              66.53733030908982\n            ],\n            [\n              -163.9434814453125,\n              66.53733030908982\n            ]\n          ]\n        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       -145.53176879882812,\n              60.43621988470893\n            ],\n            [\n              -145.272216796875,\n              60.43621988470893\n            ],\n            [\n              -145.272216796875,\n              60.354130331374286\n            ],\n            [\n              -145.53176879882812,\n              60.354130331374286\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"116","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e5c5c1e4b02d776a669ebb","contributors":{"authors":[{"text":"Rizzolo, Daniel drizzolo@usgs.gov","contributorId":5631,"corporation":false,"usgs":true,"family":"Rizzolo","given":"Daniel","email":"drizzolo@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":540744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","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":540745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCloskey, Sarah E. smccloskey@usgs.gov","contributorId":4850,"corporation":false,"usgs":true,"family":"McCloskey","given":"Sarah E.","email":"smccloskey@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":540746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fondell, Thomas F. tfondell@usgs.gov","contributorId":139310,"corporation":false,"usgs":true,"family":"Fondell","given":"Thomas F.","email":"tfondell@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":540747,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70134754,"text":"70134754 - 2014 - Energy demands for maintenance, growth, pregnancy, and lactation of female Pacific walruses (<i>Odobenus rosmarus divergens</i>)","interactions":[],"lastModifiedDate":"2018-06-16T17:45:00","indexId":"70134754","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3075,"text":"Physiological and Biochemical Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Energy demands for maintenance, growth, pregnancy, and lactation of female Pacific walruses (<i>Odobenus rosmarus divergens</i>)","docAbstract":"<p>Decreases in sea ice have altered habitat use and activity patterns of female Pacific walruses Odobenus rosmarus divergens and could affect their energetic demands, reproductive success, and population status. However, a lack of physiological data from walruses has hampered efforts to develop the bioenergetics models required for fully understanding potential population-level impacts. We analyzed long-term longitudinal data sets of caloric consumption and body mass from nine female Pacific walruses housed at six aquaria using a hierarchical Bayesian approach to quantify relative energetic demands for maintenance, growth, pregnancy, and lactation. By examining body mass fluctuations in response to food consumption, the model explicitly uncoupled caloric demand from caloric intake. This is important for pinnipeds because they sequester and deplete large quantities of lipids throughout their lifetimes. Model outputs were scaled to account for activity levels typical of free-ranging Pacific walruses, averaging 83% of the time active in water and 17% of the time hauled-out resting. Estimated caloric requirements ranged from 26,900 kcal d&minus;1 for 2-yr-olds to 93,370 kcal d&minus;1 for simultaneously lactating and pregnant walruses. Daily consumption requirements were higher for pregnancy than lactation, reflecting energetic demands of increasing body size and lipid deposition during pregnancy. Although walruses forage during lactation, fat sequestered during pregnancy sustained 27% of caloric requirements during the first month of lactation, suggesting that walruses use a mixed strategy of capital and income breeding. Ultimately, this model will aid in our understanding of the energetic and population consequences of sea ice loss.</p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/678237","usgsCitation":"Noren, S.R., Udevitz, M.S., and Jay, C.V., 2014, Energy demands for maintenance, growth, pregnancy, and lactation of female Pacific walruses (<i>Odobenus rosmarus divergens</i>): Physiological and Biochemical Zoology, v. 87, no. 6, p. 837-854, https://doi.org/10.1086/678237.","productDescription":"18 p.","startPage":"837","endPage":"854","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049042","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":296465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5482e545e4b0aa6d77853002","contributors":{"authors":[{"text":"Noren, Shawn R.","contributorId":127697,"corporation":false,"usgs":false,"family":"Noren","given":"Shawn","email":"","middleInitial":"R.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":526372,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":526371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":526373,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70139630,"text":"70139630 - 2014 - Population viability of <i>Pediocactus brady</i> (Cactaceae) in a changing climate","interactions":[],"lastModifiedDate":"2015-01-29T10:31:24","indexId":"70139630","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":724,"text":"American Journal of Botany","active":true,"publicationSubtype":{"id":10}},"title":"Population viability of <i>Pediocactus brady</i> (Cactaceae) in a changing climate","docAbstract":"<p>&bull;&nbsp;<i>Premise of the study:</i>&nbsp;A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for&nbsp;<i>Pediocactus bradyi</i>, an endangered cactus in northern Arizona.</p>\n<p>&nbsp;</p>\n<p>&bull;&nbsp;<i>Methods:</i>&nbsp;We used a matrix model to calculate stochastic population growth rates (&lambda;<sub>s</sub>) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect &lambda;<sub>s</sub>, and (2) quantify variability in &lambda;<sub>s</sub>&nbsp;based on temporal replication of data.</p>\n<p>&nbsp;</p>\n<p>&bull;&nbsp;<i>Key results:</i>&nbsp;Overall &lambda;<sub>s</sub>&nbsp;was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced &lambda;<sub>s</sub>, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate &lambda;<sub>s</sub>&nbsp;estimates.</p>\n<p>&nbsp;</p>\n<p>&bull;&nbsp;<i>Conclusions: Pediocactus bradyi</i>&nbsp;may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events.</p>","language":"English","publisher":"Botanical Society of America","doi":"10.3732/ajb.1400035","usgsCitation":"Shryock, D.F., Esque, T., and Huges, L., 2014, Population viability of <i>Pediocactus brady</i> (Cactaceae) in a changing climate: American Journal of Botany, v. 101, no. 11, p. 1944-1953, https://doi.org/10.3732/ajb.1400035.","productDescription":"10 p.","startPage":"1944","endPage":"1953","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053992","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472668,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3732/ajb.1400035","text":"Publisher Index Page"},{"id":297604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.873046875,\n              31.653381399664\n            ],\n            [\n              -114.873046875,\n              36.949891786813296\n            ],\n            [\n              -109.072265625,\n              36.949891786813296\n            ],\n            [\n              -109.072265625,\n              31.653381399664\n            ],\n            [\n              -114.873046875,\n              31.653381399664\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"101","issue":"11","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2c28e4b08de9379b3673","contributors":{"authors":[{"text":"Shryock, Daniel F. dshryock@usgs.gov","contributorId":5139,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel","email":"dshryock@usgs.gov","middleInitial":"F.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":539457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":3221,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":539456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huges, Lee","contributorId":138963,"corporation":false,"usgs":false,"family":"Huges","given":"Lee","email":"","affiliations":[{"id":12596,"text":"Retired, BLM, AZ Strip Field Office, St George, UT","active":true,"usgs":false}],"preferred":false,"id":539458,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70155249,"text":"70155249 - 2014 - Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices","interactions":[],"lastModifiedDate":"2017-01-18T11:29:34","indexId":"70155249","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices","docAbstract":"<p>In southern Ethiopia, Eastern Kenya, and southern Somalia poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009 and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers support disaster risk reduction while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST) gradient, we explore the dominant modes of East African rainfall variability, links between these modes and sea surface temperatures, and a simple index-based monitoring-prediction system suitable for drought early warning.</p>","language":"English","publisher":"EGU","doi":"10.5194/hessd-11-3111-2014","collaboration":"Andrew Hoell; Shraddhanand Shukla; Ileana Blade Mendoza; Brant Liebmann; Jason B. Roberts; Franklin R. Robertson; Gregory Husak","usgsCitation":"Funk, C.C., Hoell, A., Shukla, S., Blade, I., Liebmann, B., Roberts, J., and Robertson, F.R., 2014, Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices: Hydrology and Earth System Sciences, v. 11, p. 3111-3136, https://doi.org/10.5194/hessd-11-3111-2014.","productDescription":"26 p.","startPage":"3111","endPage":"3136","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055482","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472670,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hessd-11-3111-2014","text":"Publisher Index Page"},{"id":306849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d45733e4b0518e354694e0","contributors":{"authors":[{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoell, Andrew","contributorId":145805,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shukla, Shraddhanand","contributorId":145802,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565361,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blade, Ileana","contributorId":145806,"corporation":false,"usgs":false,"family":"Blade","given":"Ileana","email":"","affiliations":[{"id":16237,"text":"Institut Catala de Ciencies del Clima","active":true,"usgs":false}],"preferred":false,"id":565362,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liebmann, Brant","contributorId":145807,"corporation":false,"usgs":false,"family":"Liebmann","given":"Brant","email":"","affiliations":[{"id":16238,"text":"NOAA Earth Systems Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":565363,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roberts, Jason B.","contributorId":145808,"corporation":false,"usgs":false,"family":"Roberts","given":"Jason B.","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":565364,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robertson, Franklin R.","contributorId":145809,"corporation":false,"usgs":false,"family":"Robertson","given":"Franklin","email":"","middleInitial":"R.","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":565365,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70145116,"text":"70145116 - 2014 - MTpy: A Python toolbox for magnetotellurics","interactions":[],"lastModifiedDate":"2018-02-08T09:37:05","indexId":"70145116","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"displayTitle":"<i>MTpy</i>: A Python toolbox for magnetotellurics","title":"MTpy: A Python toolbox for magnetotellurics","docAbstract":"<p id=\"sp0030\">We present the software package&nbsp;<i>MTpy</i>&nbsp;that allows handling, processing, and imaging of magnetotelluric (MT) data sets. Written in Python, the code is open source, containing sub-packages and modules for various tasks within the standard MT data processing and handling scheme. Besides the independent definition of classes and functions,&nbsp;<i>MTpy</i>&nbsp;provides wrappers and convenience scripts to call standard external data processing and modelling software.</p>\n<p id=\"sp0035\">In its current state, modules and functions of&nbsp;<i>MTpy</i>&nbsp;work on raw and pre-processed MT data. However, opposite to providing a static compilation of software, we prefer to introduce&nbsp;<i>MTpy</i>&nbsp;as a flexible software toolbox, whose contents can be combined and utilised according to the respective needs of the user. Just as the overall functionality of a mechanical toolbox can be extended by adding new tools,&nbsp;<i>MTpy</i>&nbsp;is a flexible framework, which will be dynamically extended in the future. Furthermore, it can help to unify and extend existing codes and algorithms within the (academic) MT community.</p>\n<p id=\"sp0040\">In this paper, we introduce the structure and concept of&nbsp;<i>MTpy &nbsp;</i>. Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric (<span id=\"mmlsi0001\" class=\"mathmlsrc\"><span class=\"formulatext stixSupport mathImg\" title=\"Click to view the MathML source\" data-mathurl=\"/science?_ob=MathURL&amp;_method=retrieve&amp;_eid=1-s2.0-S0098300414001794&amp;_mathId=si0001.gif&amp;_user=111111111&amp;_pii=S0098300414001794&amp;_rdoc=1&amp;_issn=00983004&amp;md5=c0f8e921697c4a6bafdc8188eaee938a\"><span>E</span></span></span>-) and magnetic flux density (<span class=\"boldFont\">B</span>-) field time series as input, the conversion into MiniSEED data format, as well as the generation of a graphical data representation in the form of a Phase Tensor pseudosection.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2014.07.013","usgsCitation":"Krieger, L., and Peacock, J.R., 2014, MTpy: A Python toolbox for magnetotellurics: Computers & Geosciences, v. 72, p. 167-175, https://doi.org/10.1016/j.cageo.2014.07.013.","productDescription":"9 p.","startPage":"167","endPage":"175","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051294","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":299334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551fb9abe4b027f0aee3baf2","contributors":{"authors":[{"text":"Krieger, Lars","contributorId":140053,"corporation":false,"usgs":false,"family":"Krieger","given":"Lars","email":"","affiliations":[{"id":13368,"text":"University of Adelaide, Australia","active":true,"usgs":false}],"preferred":false,"id":543941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peacock, Jared R. 0000-0002-0439-0224 jpeacock@usgs.gov","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":4996,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared","email":"jpeacock@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":543940,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70168458,"text":"70168458 - 2014 - Inland capture fishery contributions to global food security and threats to their future","interactions":[],"lastModifiedDate":"2018-04-24T13:54:31","indexId":"70168458","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5055,"text":"Global Food Security","active":true,"publicationSubtype":{"id":10}},"title":"Inland capture fishery contributions to global food security and threats to their future","docAbstract":"<p><span>Inland fish and fisheries play important roles in ensuring global food security. They provide a crucial source of animal protein and essential micronutrients for local communities, especially in the developing world. Data concerning fisheries production and consumption of freshwater fish are generally inadequately assessed, often leading decision makers to undervalue their importance. Modification of inland waterways for alternative uses of freshwater (particularly dams for hydropower and water diversions for human use) negatively impacts the productivity of inland fisheries for food security at local and regional levels. This paper highlights the importance of inland fisheries to global food security, the challenges they face due to competing demands for freshwater, and possible solutions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gfs.2014.09.005","usgsCitation":"Youn, S., Taylor, W.W., Lynch, A., Cowx, I.G., Beard, T., Bartley, D., and Wu, F., 2014, Inland capture fishery contributions to global food security and threats to their future: Global Food Security, v. 3, no. 3-4, p. 142-148, https://doi.org/10.1016/j.gfs.2014.09.005.","productDescription":"7 p.","startPage":"142","endPage":"148","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058030","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":323947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"3-4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576913d0e4b07657d19ff135","contributors":{"authors":[{"text":"Youn, So-Jung","contributorId":166926,"corporation":false,"usgs":false,"family":"Youn","given":"So-Jung","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":620579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, William W.","contributorId":166927,"corporation":false,"usgs":false,"family":"Taylor","given":"William","email":"","middleInitial":"W.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":620581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lynch, Abigail J. ajlynch@usgs.gov","contributorId":146923,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail J.","email":"ajlynch@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":false,"id":620580,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cowx, Ian G.","contributorId":37228,"corporation":false,"usgs":false,"family":"Cowx","given":"Ian","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":620794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beard, T. Douglas Jr. 0000-0003-2632-2350 dbeard@usgs.gov","orcid":"https://orcid.org/0000-0003-2632-2350","contributorId":3314,"corporation":false,"usgs":true,"family":"Beard","given":"T. Douglas","suffix":"Jr.","email":"dbeard@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":false,"id":620578,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bartley, Devin","contributorId":166934,"corporation":false,"usgs":false,"family":"Bartley","given":"Devin","affiliations":[],"preferred":false,"id":620795,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wu, Felicia","contributorId":166935,"corporation":false,"usgs":false,"family":"Wu","given":"Felicia","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":620796,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70150320,"text":"70150320 - 2014 - Predicting probability of occurrence and factors affecting distribution and abundance of three Ozark endemic crayfish species at multiple spatial scales","interactions":[],"lastModifiedDate":"2015-07-01T13:04:04","indexId":"70150320","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting probability of occurrence and factors affecting distribution and abundance of three Ozark endemic crayfish species at multiple spatial scales","docAbstract":"<ol id=\"fwb12442-list-0001\" class=\"numbered\">\n<li>Crayfishes and other freshwater aquatic fauna are particularly at risk globally due to anthropogenic demand, manipulation and exploitation of freshwater resources and yet are often understudied. The Ozark faunal region of Missouri and Arkansas harbours a high level of aquatic biological diversity, especially in regard to endemic crayfishes. Three such endemics,&nbsp;<i>Orconectes eupunctus</i>,<i>Orconectes marchandi</i>&nbsp;and&nbsp;<i>Cambarus hubbsi</i>, are threatened by limited natural distribution and the invasions of&nbsp;<i>Orconectes neglectus</i>.</li>\n<li>We examined how natural and anthropogenic abiotic factors influence these three species across multiple spatial scales. Local and landscape environmental variables were used as predictors in classification and regression tree models at stream segment and segmentshed scales to determine their relation to presence/absence and density of the three species.</li>\n<li><i>Orconectes eupunctus</i>&nbsp;presence was positively associated with stream size, current velocity and spring flow volume.&nbsp;<i>Orconectes marchandi</i>&nbsp;presence was predicted primarily by dolomite geology and water chemistry variables.&nbsp;<i>Cambarus hubbsi</i>&nbsp;was associated with larger stream size, with highest densities occurring in deep waters. Stream segment and segmentshed scale models were similar, but there were important differences based on species and response variables (presence/absence versus density). Stream segment scale models consistently performed better than or equal to segmentshed scale models.</li>\n<li>Anthropogenic abiotic environmental variables were of minor importance in most models, with the exception of&nbsp;<i>O.&nbsp;marchandi</i>&nbsp;being negatively related to road density and human population density. Classification tree models predicting distribution performed well when compared to random assignment, but regression trees were generally poor in explaining variation in density.</li>\n<li>We found that a range of environmental variables were important in predicting crayfish distribution and abundance at multiple spatial scales and their importance was species-, response variable- and scale dependent. We would encourage others to examine the influence of spatial scale on species distribution and abundance patterns.</li>\n</ol>","language":"English","publisher":"Wiley","doi":"10.1111/fwb.12442","usgsCitation":"Nolen, M., Magoulick, D.D., DiStefano, R., Imhoff, E., and Wagner, B., 2014, Predicting probability of occurrence and factors affecting distribution and abundance of three Ozark endemic crayfish species at multiple spatial scales: Freshwater Biology, v. 59, no. 11, p. 2374-2389, https://doi.org/10.1111/fwb.12442.","productDescription":"16 p.","startPage":"2374","endPage":"2389","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055875","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Eleven Point River, Spring River, Strawberry River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.08740234375,\n              35.62158189955968\n            ],\n            [\n              -92.08740234375,\n              36.50963615733049\n            ],\n            [\n              -91.01074218749999,\n              36.50963615733049\n            ],\n            [\n              -91.01074218749999,\n              35.62158189955968\n            ],\n            [\n              -92.08740234375,\n              35.62158189955968\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"59","issue":"11","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-08","publicationStatus":"PW","scienceBaseUri":"55950f36e4b0b6d21dd6cbff","contributors":{"authors":[{"text":"Nolen, Matthew S.","contributorId":145443,"corporation":false,"usgs":false,"family":"Nolen","given":"Matthew S.","affiliations":[],"preferred":false,"id":564056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":556705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DiStefano, Robert J.","contributorId":28132,"corporation":false,"usgs":true,"family":"DiStefano","given":"Robert J.","affiliations":[],"preferred":false,"id":564057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Imhoff, Emily M.","contributorId":145444,"corporation":false,"usgs":false,"family":"Imhoff","given":"Emily M.","affiliations":[],"preferred":false,"id":564058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Brian K.","contributorId":145445,"corporation":false,"usgs":false,"family":"Wagner","given":"Brian K.","affiliations":[],"preferred":false,"id":564059,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70156768,"text":"70156768 - 2014 - Estimates of natural salinity and hydrology in a subtropical estuarine ecosystem: implications for Greater Everglades restoration","interactions":[],"lastModifiedDate":"2015-08-31T11:45:35","indexId":"70156768","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Estimates of natural salinity and hydrology in a subtropical estuarine ecosystem: implications for Greater Everglades restoration","docAbstract":"<p><span>Disruption of the natural patterns of freshwater flow into estuarine ecosystems occurred in many locations around the world beginning in the twentieth century. To effectively restore these systems, establishing a pre-alteration perspective allows managers to develop science-based restoration targets for salinity and hydrology. This paper describes a process to develop targets based on natural hydrologic functions by coupling paleoecology and regression models using the subtropical Greater Everglades Ecosystem as an example. Paleoecological investigations characterize the circa 1900 CE (pre-alteration) salinity regime in Florida Bay based on molluscan remains in sediment cores. These paleosalinity estimates are converted into time series estimates of paleo-based salinity, stage, and flow using numeric and statistical models. Model outputs are weighted using the mean square error statistic and then combined. Results indicate that, in the absence of water management, salinity in Florida Bay would be about 3 to 9 salinity units lower than current conditions. To achieve this target, upstream freshwater levels must be about 0.25&nbsp;m higher than indicated by recent observed data, with increased flow inputs to Florida Bay between 2.1 and 3.7 times existing flows. This flow deficit is comparable to the average volume of water currently being diverted from the Everglades ecosystem by water management. The products (paleo-based Florida Bay salinity and upstream hydrology) provide estimates of pre-alteration hydrology and salinity that represent target restoration conditions. This method can be applied to any estuarine ecosystem with available paleoecologic data and empirical and/or model-based hydrologic data.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1007/s12237-014-9783-8","usgsCitation":"Marshall, F.E., Wingard, G.L., and Pitts, P.A., 2014, Estimates of natural salinity and hydrology in a subtropical estuarine ecosystem: implications for Greater Everglades restoration: Estuaries and Coasts, v. 37, no. 6, p. 1449-1466, https://doi.org/10.1007/s12237-014-9783-8.","productDescription":"18 p.","startPage":"1449","endPage":"1466","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043059","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":307723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":307638,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/article/10.1007/s12237-014-9783-8"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Bay, Everglades National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.64215087890625,\n              25.107984454913446\n            ],\n            [\n              -81.64215087890625,\n              25.91111496561543\n            ],\n            [\n              -80.10406494140625,\n              25.91111496561543\n            ],\n            [\n              -80.10406494140625,\n              25.107984454913446\n            ],\n            [\n              -81.64215087890625,\n              25.107984454913446\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"37","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-12","publicationStatus":"PW","scienceBaseUri":"55e57aade4b05561fa208690","contributors":{"authors":[{"text":"Marshall, Frank E.","contributorId":88962,"corporation":false,"usgs":true,"family":"Marshall","given":"Frank","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":570444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":570443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pitts, Patrick A.","contributorId":90118,"corporation":false,"usgs":true,"family":"Pitts","given":"Patrick","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":570445,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70156364,"text":"70156364 - 2014 - A systematic approach towards the identification and protection of vulnerable marine ecosystems","interactions":[],"lastModifiedDate":"2015-09-16T10:42:44","indexId":"70156364","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3916,"text":"Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"A systematic approach towards the identification and protection of vulnerable marine ecosystems","docAbstract":"<p><span>The United Nations General Assembly in 2006 and 2009 adopted resolutions that call for the identification and protection of&nbsp;</span><i>vulnerable marine ecosystems</i><span>&nbsp;(VMEs) from significant adverse impacts of bottom fishing. While general criteria have been produced, there are no guidelines or protocols that elaborate on the process from initial identification through to the protection of VMEs. Here, based upon an expert review of existing practices, a 10-step framework is proposed: (1) Comparatively assess potential VME indicator taxa and habitats in a region; (2) determine VME thresholds; (3) consider areas already known for their ecological importance; (4) compile information on the distributions of likely VME taxa and habitats, as well as related environmental data; (5) develop predictive distribution models for VME indicator taxa and habitats; (6) compile known or likely fishing impacts; (7) produce a predicted VME naturalness distribution (areas of low cumulative impacts); (8) identify areas of higher value to user groups; (9) conduct management strategy evaluations to produce trade-off scenarios; (10) review and re-iterate, until spatial management scenarios are developed that fulfil international obligations and regional conservation and management objectives. To date, regional progress has been piecemeal and incremental. The proposed 10-step framework combines these various experiences into a systematic approach.</span></p>","language":"English","publisher":"ScienceDirect","doi":"10.1016/j.marpol.2013.11.017","usgsCitation":"Ardron, J.A., Clark, M.R., Penney, A.J., Hourigan, T.F., Rowden, A.A., Dunstan, P.K., Watling, L., Shank, T., Tracey, D.M., Dunn, M.R., and Parker, S.J., 2014, A systematic approach towards the identification and protection of vulnerable marine ecosystems: Marine Science, v. 49, p. 146-154, https://doi.org/10.1016/j.marpol.2013.11.017.","productDescription":"9 p.","startPage":"146","endPage":"154","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":472672,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/6371","text":"External Repository"},{"id":308183,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55fa92ade4b05d6c4e501a48","contributors":{"authors":[{"text":"Ardron, Jeff A.","contributorId":146751,"corporation":false,"usgs":false,"family":"Ardron","given":"Jeff","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":568875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Malcolm R.","contributorId":146752,"corporation":false,"usgs":false,"family":"Clark","given":"Malcolm","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":568876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Penney, Andrew J.","contributorId":146753,"corporation":false,"usgs":false,"family":"Penney","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":568877,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hourigan, Thomas F.","contributorId":146754,"corporation":false,"usgs":false,"family":"Hourigan","given":"Thomas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":568878,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowden, Ashley A.","contributorId":146755,"corporation":false,"usgs":false,"family":"Rowden","given":"Ashley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":568879,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunstan, Piers K.","contributorId":146756,"corporation":false,"usgs":false,"family":"Dunstan","given":"Piers","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":568880,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Watling, Les","contributorId":54755,"corporation":false,"usgs":false,"family":"Watling","given":"Les","email":"","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":568881,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shank, Timothy M.","contributorId":100722,"corporation":false,"usgs":true,"family":"Shank","given":"Timothy M.","affiliations":[],"preferred":false,"id":568882,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tracey, Di M.","contributorId":146757,"corporation":false,"usgs":false,"family":"Tracey","given":"Di","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":568883,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dunn, Matthew R.","contributorId":146758,"corporation":false,"usgs":false,"family":"Dunn","given":"Matthew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":568884,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Parker, Steven J.","contributorId":68904,"corporation":false,"usgs":true,"family":"Parker","given":"Steven","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":568885,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70155250,"text":"70155250 - 2014 - A seasonal agricultural drought forecast system for food-insecure regions of East Africa","interactions":[],"lastModifiedDate":"2017-01-18T11:29:02","indexId":"70155250","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A seasonal agricultural drought forecast system for food-insecure regions of East Africa","docAbstract":"<p><span>&nbsp;The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. More accurate seasonal agricultural drought forecasts for this region can inform better water and agricultural management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts and floods. Here we describe the development and implementation of a seasonal agricultural drought forecast system for East Africa (EA) that provides decision support for the Famine Early Warning Systems Network's science team. We evaluate this forecast system for a region of equatorial EA (2&deg; S to 8&deg; N, and 36&deg; to 46&deg; E) for the March-April-May growing season. This domain encompasses one of the most food insecure, climatically variable and socio-economically vulnerable regions in EA, and potentially the world: this region has experienced famine as recently as 2011.&nbsp;</span><br /><br /><span>To assess the agricultural outlook for the upcoming season our forecast system simulates soil moisture (SM) scenarios using the Variable Infiltration Capacity (VIC) hydrologic model forced with climate scenarios for the upcoming season. First, to show that the VIC model is appropriate for this application we forced the model with high quality atmospheric observations and found that the resulting SM values were consistent with the Food and Agriculture Organization's (FAO's) Water Requirement Satisfaction Index (WRSI), an index used by FEWS NET to estimate crop yields. Next we tested our forecasting system with hindcast runs (1993&ndash;2012). We found that initializing SM forecasts with start-of-season (5 March) SM conditions resulted in useful SM forecast skill (&gt; 0.5 correlation) at 1-month, and in some cases at 3 month lead times. Similarly, when the forecast was initialized with mid-season (i.e. 5 April) SM conditions the skill until the end-of-season improved. This shows that early-season rainfall is critical for end-of-season outcomes. Finally we show that, in terms of forecasting spatial patterns of SM anomalies, the skill of this agricultural drought forecast system is generally greater (&gt; 0.8 correlation) during drought years. This means that this system might be particularity useful for identifying the events that present the greatest risk to the region.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hessd-11-3049-2014","usgsCitation":"Shukla, S., McNally, A., Husak, G., and Funk, C.C., 2014, A seasonal agricultural drought forecast system for food-insecure regions of East Africa: Hydrology and Earth System Sciences, v. 11, p. 3049-3081, https://doi.org/10.5194/hessd-11-3049-2014.","productDescription":"33 p.","startPage":"3049","endPage":"3081","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055486","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":488387,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hessd-11-3049-2014","text":"Publisher Index Page"},{"id":306851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d4572be4b0518e3546949c","contributors":{"authors":[{"text":"Shukla, Shraddhanand","contributorId":145802,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNally, Amy","contributorId":145810,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","email":"","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Husak, Gregory","contributorId":145811,"corporation":false,"usgs":false,"family":"Husak","given":"Gregory","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565366,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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