{"pageNumber":"1426","pageRowStart":"35625","pageSize":"25","recordCount":184723,"records":[{"id":70194461,"text":"70194461 - 2014 - Utilizing multi-sensor fire detections to map fires in the United States","interactions":[],"lastModifiedDate":"2018-04-23T09:10:31","indexId":"70194461","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Utilizing multi-sensor fire detections to map fires in the United States","docAbstract":"<p>In 2006, the Monitoring Trends in Burn Severity (MTBS) project began a cooperative effort between the US Forest Service (USFS) and the U.S.Geological Survey (USGS) to map and assess burn severity all large fires that have occurred in the United States since 1984. Using Landsat imagery, MTBS is mandated to map wildfire and prescribed fire that meet specific size criteria: greater than 1000 acres in the west and 500 acres in the east, regardless of ownership. Relying mostly on federal and state fire occurrence records, over 15,300 individual fires have been mapped. While mapping recorded fires, an additional 2,700 “unknown” or undocumented fires were discovered and assessed. It has become apparent that there are perhaps thousands of undocumented fires in the US that are yet to be mapped. Fire occurrence records alone are inadequate if MTBS is to provide a comprehensive accounting of fire across the US. Additionally, the sheer number of fires to assess has overwhelmed current manual procedures. To address these problems, the National Aeronautics and Space Administration (NASA) Applied Sciences Program is helping to fund the efforts of the USGS and its MTBS partners (USFS, National Park Service) to develop, and implement a system to automatically identify fires using satellite data. In near real time, USGS will combine active fire satellite detections from MODIS, AVHRR and GOES satellites with Landsat acquisitions. Newly acquired Landsat imagery will be routinely scanned to identify freshly burned area pixels, derive an initial perimeter and tag the burned area with the satellite date and time of detection. Landsat imagery from the early archive will be scanned to identify undocumented fires. Additional automated fire assessment processes will be developed. The USGS will develop these processes using open source software packages in order to provide freely available tools to local land managers providing them with the capability to assess fires at the local level.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1,","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"ISPRS Technical Commission I Symposium","conferenceDate":"November 17-20, 2014","conferenceLocation":"Denver, CO","language":"English","publisher":"ISPRS","doi":"10.5194/isprsarchives-XL-1-161-2014","usgsCitation":"Howard, S.M., Picotte, J.J., and Coan, M., 2014, Utilizing multi-sensor fire detections to map fires in the United States, <i>in</i> The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1,, v. XL-1, Denver, CO, November 17-20, 2014, p. 161-166, https://doi.org/10.5194/isprsarchives-XL-1-161-2014.","productDescription":"6 p.","startPage":"161","endPage":"166","ipdsId":"IP-060379","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473416,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/isprsarchives-xl-1-161-2014","text":"Publisher Index Page"},{"id":350086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"XL-1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-07","publicationStatus":"PW","scienceBaseUri":"5a6100c8e4b06e28e9c2540f","contributors":{"authors":[{"text":"Howard, Stephen M. 0000-0001-5255-5882 smhoward@usgs.gov","orcid":"https://orcid.org/0000-0001-5255-5882","contributorId":3483,"corporation":false,"usgs":true,"family":"Howard","given":"Stephen","email":"smhoward@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":723939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":725216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coan, Michael mcoan@usgs.gov","contributorId":5398,"corporation":false,"usgs":true,"family":"Coan","given":"Michael","email":"mcoan@usgs.gov","affiliations":[],"preferred":true,"id":725217,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188873,"text":"70188873 - 2014 - Geophysical investigations of the geologic and hydrothermal framework of the Pilgrim Springs Geothermal Area, Alaska","interactions":[],"lastModifiedDate":"2017-06-27T12:56:36","indexId":"70188873","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geophysical investigations of the geologic and hydrothermal framework of the Pilgrim Springs Geothermal Area, Alaska","docAbstract":"<p>Pilgrim Hot Springs, located on the Seward Peninsula in west-central Alaska, is characterized by hot springs, surrounding thawed regions, and elevated lake temperatures. The area is of interest because of its potential for providing renewable energy for Nome and nearby rural communities. We performed ground and airborne geophysical investigations of the Pilgrim Springs geothermal area to identify areas indicative of high heat flow and saline geothermal fluids, and to map key structures controlling hydrothermal fluid flow. Studies included ground gravity and magnetic measurements, as well as an airborne magnetic and frequency-domain electromagnetic (EM) survey. The structural and conceptual framework developed from this study provides critical information for future development of this resource and is relevant more generally to our understanding of geothermal systems in active extensional basins. </p><p>Potential field data reveal the Pilgrim area displays a complex geophysical fabric reflecting a network of intersecting fault and fracture sets ranging from inherited basement structures to Tertiary faults. Resistivity models derived from the airborne EM data reveal resistivity anomalies in the upper 100 m of the subsurface that suggest elevated temperatures and the presence of saline fluids. A northwest trending fabric across the northeastern portion of the survey area parallels structures to the east that may be related to accommodation between the two major mountain ranges south (Kigluaik) and east (Bendeleben) of Pilgrim Springs. The area from the springs southward to the range front, however, is characterized by east-west trending, range-front-parallel anomalies likely caused by late Cenozoic structures associated with north-south extension that formed the basin. The area around the springs (~10 km2 ) is coincident with a circular magnetic high punctuated by several east-west trending magnetic lows, the most prominent occurring directly over the springs. These features possibly result from hydrothermal alteration imposed by fluids migrating along intra-basin faults related to recent north-south extension. </p><p>The Pilgrim River valley is characterized by a NE-elongate gravity low that reveals a basin extending to depths of ~300 m beneath Pilgrim Springs and deepening to ~800 m to the southwest. The margins of the gravity low are sharply defined by northeasttrending gradients that probably reflect the edges of fault-bounded structural blocks. The southeastern edge of the low, which lies very close to the springs, also corresponds with prominent NE-striking anomalies seen in magnetic and resistivity models. Together, these features define a structure we refer to as the Northeast Fault. The location of the hot springs appears to be related to the intersection of the Northeast Fault with a N-oriented structure marked by the abrupt western edge of a resistivity low surrounding the hot springs. While the hot springs represent the primary outflow of geothermal fluids, additional outflow extends from the springs northeast along the Northeast fault to another thaw zone that we interpret to be a secondary region of concentrated upflow of geothermal fluids. </p><p>The Northeast Fault apparently controls shallow geothermal fluid flow, and may also provide an important pathway conveying deep fluids to the shallow subsurface. We suggest that geothermal fluids may derive from a reservoir residing beneath the sediment basin southwest of the springs. If so, the shape of the basin, which narrows and shallows towards the springs, may funnel fluids beneath the springs where they intersect the Northeast Fault allowing them to reach the surface. </p><p>An alternative pathway for reservoir fluids to reach intermediate to shallow depths may be afforded by the main Kigluaik range front fault that coincides with a resistivity anomaly possibly resulting from fluid flow and associated hydrothermal mineralization occurring within the fault zone. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings, Thirty-Ninth Workshop on Geothermal Reservoir Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Thirty-Ninth Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 24-26, 2014","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford University","usgsCitation":"Glen, J.M., McPhee, D., and Bedrosian, P.A., 2014, Geophysical investigations of the geologic and hydrothermal framework of the Pilgrim Springs Geothermal Area, Alaska, <i>in</i> Proceedings, Thirty-Ninth Workshop on Geothermal Reservoir Engineering, Stanford, CA, February 24-26, 2014, 9 p.","productDescription":"9 p.","ipdsId":"IP-054930","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":342971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536eaee4b062508e3c7aad","contributors":{"authors":[{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McPhee, Darcy 0000-0002-5177-3068 dmcphee@usgs.gov","orcid":"https://orcid.org/0000-0002-5177-3068","contributorId":2621,"corporation":false,"usgs":true,"family":"McPhee","given":"Darcy","email":"dmcphee@usgs.gov","affiliations":[{"id":412,"text":"National Cooperative Geologic Mapping Program","active":false,"usgs":true}],"preferred":true,"id":700770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700771,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70187359,"text":"70187359 - 2014 - The temperature-productivity squeeze: Constraints on brook trout growth along an Appalachian river continuum","interactions":[],"lastModifiedDate":"2017-05-04T12:34:08","indexId":"70187359","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"The temperature-productivity squeeze: Constraints on brook trout growth along an Appalachian river continuum","docAbstract":"<p><span>We tested the hypothesis that brook trout growth rates are controlled by a complex interaction of food availability, water temperature, and competitor density. We quantified trout diet, growth, and consumption in small headwater tributaries characterized as cold with low food and high trout density, larger tributaries characterized as cold with moderate food and moderate trout density, and large main stems characterized as warm with high food and low trout density. Brook trout consumption was highest in the main stem where diets shifted from insects in headwaters to fishes and crayfish in larger streams. Despite high water temperatures, trout growth rates also were consistently highest in the main stem, likely due to competitively dominant trout monopolizing thermal refugia. Temporal changes in trout density had a direct negative effect on brook trout growth rates. Our results suggest that competition for food constrains brook trout growth in small streams, but access to thermal refugia in productive main stem habitats enables dominant trout to supplement growth at a watershed scale. Brook trout conservation in this region should seek to relieve the “temperature-productivity squeeze,” whereby brook trout productivity is constrained by access to habitats that provide both suitable water temperature and sufficient prey.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10750-013-1794-0","usgsCitation":"Petty, J.T., Thorne, D., Huntsman, B.M., and Mazik, P.M., 2014, The temperature-productivity squeeze: Constraints on brook trout growth along an Appalachian river continuum: Hydrobiologia, v. 727, no. 1, p. 151-166, https://doi.org/10.1007/s10750-013-1794-0.","productDescription":"16 p.","startPage":"151","endPage":"166","ipdsId":"IP-042627","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Upper Shaver's Fork","volume":"727","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-12-31","publicationStatus":"PW","scienceBaseUri":"590c3dcbe4b0e541a038dd2d","contributors":{"authors":[{"text":"Petty, J. Todd","contributorId":166749,"corporation":false,"usgs":false,"family":"Petty","given":"J.","email":"","middleInitial":"Todd","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":693608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorne, David","contributorId":191765,"corporation":false,"usgs":false,"family":"Thorne","given":"David","email":"","affiliations":[{"id":24498,"text":"West Virginia Division of Natural Resources, Point Pleasant, WV","active":true,"usgs":false},{"id":25281,"text":"West Virginia University, WV","active":true,"usgs":false}],"preferred":false,"id":694167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huntsman, Brock M. 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":166748,"corporation":false,"usgs":false,"family":"Huntsman","given":"Brock","email":"","middleInitial":"M.","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":694168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":694169,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70188807,"text":"70188807 - 2014 - 13.3 – Stable Isotope Geochemistry of Mineral Deposits","interactions":[],"lastModifiedDate":"2017-06-26T13:00:54","indexId":"70188807","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"13.3 – Stable Isotope Geochemistry of Mineral Deposits","docAbstract":"<p><span>In this chapter, the intent is to summarize the results of traditional stable isotope studies (mainly H, B, O, C, and S) that have greatly contributed to the understanding of ore-forming processes over the last 60 years and to provide an up-to-date assessment of the application of new nontraditional isotope systems (Fe, Cu, Zn, Se, Mo, Hg, and Tl).</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in earth systems and environmental sciences: Treatise on geochemistry (Second Edition)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-08-095975-7.01103-7","usgsCitation":"Shanks, W.P., 2014, 13.3 – Stable Isotope Geochemistry of Mineral Deposits, chap. <i>of</i> Reference module in earth systems and environmental sciences: Treatise on geochemistry (Second Edition), p. 59-85, https://doi.org/10.1016/B978-0-08-095975-7.01103-7.","productDescription":"27 p.","startPage":"59","endPage":"85","ipdsId":"IP-038278","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":342890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59521d26e4b062508e3c36bd","contributors":{"authors":[{"text":"Shanks, W.C. Pat III","contributorId":93949,"corporation":false,"usgs":true,"family":"Shanks","given":"W.C.","suffix":"III","email":"","middleInitial":"Pat","affiliations":[],"preferred":false,"id":700452,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70188038,"text":"70188038 - 2014 - Evapotranspiration variability and its association with vegetation dynamics in the Nile Basin, 2002–2011","interactions":[],"lastModifiedDate":"2017-05-30T16:22:30","indexId":"70188038","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Evapotranspiration variability and its association with vegetation dynamics in the Nile Basin, 2002–2011","docAbstract":"<p><span>Evapotranspiration (ET) is a vital component in land-atmosphere interactions. In drylands, over 90% of annual rainfall evaporates. The Nile Basin in Africa is about 42% dryland in a region experiencing rapid population growth and development. The relationship of ET with climate, vegetation and land cover in the basin during 2002–2011 is analyzed using thermal-based Simplified Surface Energy Balance Operational (SSEBop) ET, Normalized Difference Vegetation Index (NDVI)-based MODIS Terrestrial (MOD16) ET, MODIS-derived NDVI as a proxy for vegetation productivity and rainfall from Tropical Rainfall Measuring Mission (TRMM). Interannual variability and trends are analyzed using established statistical methods. Analysis based on thermal-based ET revealed that &gt;50% of the study area exhibited negative ET anomalies for 7 years (2009, driest), while &gt;60% exhibited positive ET anomalies for 3 years (2007, wettest). NDVI-based monthly ET correlated strongly (r &gt; 0.77) with vegetation than thermal-based ET (0.52 &lt; r &lt; 0.73) at </span><i>p</i><span> &lt; 0.001. Climate-zone averaged thermal-based ET anomalies positively correlated (r = 0.6, </span><i>p</i><span> &lt; 0.05) with rainfall in 4 of the 9 investigated climate zones. Thermal-based and NDVI-based ET estimates revealed minor discrepancies over rainfed croplands (60 mm/yr higher for thermal-based ET), but a significant divergence over wetlands (440 mm/yr higher for thermal-based ET). Only 5% of the study area exhibited statistically significant trends in ET.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs6075885","usgsCitation":"Alemu, H., Senay, G., Kaptue, A.T., and Kovalskyy, V., 2014, Evapotranspiration variability and its association with vegetation dynamics in the Nile Basin, 2002–2011: Remote Sensing, v. 6, no. 7, p. 5885-5908, https://doi.org/10.3390/rs6075885.","productDescription":"24 p.","startPage":"5885","endPage":"5908","ipdsId":"IP-057424","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473457,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs6075885","text":"Publisher Index Page"},{"id":341890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Nile Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              23.818359375,\n              -3.688855143147035\n            ],\n            [\n              37.6171875,\n              -3.688855143147035\n            ],\n            [\n              37.6171875,\n              31.57853542647338\n            ],\n            [\n              23.818359375,\n              31.57853542647338\n            ],\n            [\n              23.818359375,\n              -3.688855143147035\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"6","issue":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-25","publicationStatus":"PW","scienceBaseUri":"592e84c7e4b092b266f10db3","contributors":{"authors":[{"text":"Alemu, Henok","contributorId":124527,"corporation":false,"usgs":false,"family":"Alemu","given":"Henok","email":"","affiliations":[{"id":5087,"text":"Geographic Information Science Center of Excellence (GIScCE), South Dakota State University, Brookings, USA","active":true,"usgs":false}],"preferred":false,"id":696572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":152206,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","email":"senay@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaptue, Armel T.","contributorId":189254,"corporation":false,"usgs":false,"family":"Kaptue","given":"Armel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":696573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kovalskyy, Valeriy","contributorId":192062,"corporation":false,"usgs":false,"family":"Kovalskyy","given":"Valeriy","email":"","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":696574,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70188032,"text":"70188032 - 2014 - Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data","interactions":[],"lastModifiedDate":"2017-05-31T15:19:27","indexId":"70188032","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data","docAbstract":"<p><span>Wetlands provide ecosystem goods and services vitally important to humans. Land managers and policymakers working to conserve wetlands require regularly updated information on the statuses of wetlands across the landscape. However, wetlands are challenging to map remotely with high accuracy and consistency. We investigated the use of multitemporal polarimetric synthetic aperture radar (SAR) data acquired with Canada’s Radarsat-2 system to track within-season changes in wetland vegetation and surface water. We speculated, </span><i>a priori</i><span>, how temporal and morphological traits of different types of wetland vegetation should respond over a growing season with respect to four energy-scattering mechanisms. We used ground-based monitoring data and other ancillary information to assess the limits and consistency of the SAR data for tracking seasonal changes in wetlands. We found the traits of different types of vertical emergent wetland vegetation were detected well with the SAR data and corresponded with our anticipated backscatter responses. We also found using data from Landsat’s optical/infrared sensors in conjunction with SAR data helped remove confusion of wetland features with upland grasslands. These results suggest SAR data can provide useful monitoring information on the statuses of wetlands over time.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w6030694","usgsCitation":"Gallant, A.L., Kaya, S.G., White, L., Brisco, B., Roth, M.F., Sadinski, W.J., and Rover, J., 2014, Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data: Water, v. 6, no. 3, p. 694-722, https://doi.org/10.3390/w6030694.","productDescription":"29 p.","startPage":"694","endPage":"722","ipdsId":"IP-053361","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473304,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w6030694","text":"Publisher Index Page"},{"id":341958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-24","publicationStatus":"PW","scienceBaseUri":"592fd640e4b0e9bd0ea8970a","contributors":{"authors":[{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaya, Shannon G.","contributorId":192330,"corporation":false,"usgs":false,"family":"Kaya","given":"Shannon","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":696253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Lori","contributorId":192557,"corporation":false,"usgs":false,"family":"White","given":"Lori","email":"","affiliations":[],"preferred":false,"id":696254,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brisco, Brian","contributorId":37665,"corporation":false,"usgs":true,"family":"Brisco","given":"Brian","email":"","affiliations":[],"preferred":false,"id":696255,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roth, Mark F. 0000-0001-5095-1865 mroth@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-1865","contributorId":3286,"corporation":false,"usgs":true,"family":"Roth","given":"Mark","email":"mroth@usgs.gov","middleInitial":"F.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":696256,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sadinski, Walter J. wsadinski@usgs.gov","contributorId":3287,"corporation":false,"usgs":true,"family":"Sadinski","given":"Walter","email":"wsadinski@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":696257,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rover, Jennifer 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":192333,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696258,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70187371,"text":"70187371 - 2014 - Influence of variable rainbow smelt and gizzard shad abundance on walleye diets and growth","interactions":[],"lastModifiedDate":"2017-05-01T12:58:13","indexId":"70187371","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Influence of variable rainbow smelt and gizzard shad abundance on walleye diets and growth","docAbstract":"<div class=\"hlFld-Abstract test\"><div class=\"abstractSection abstractInFull\"><p>Prey availability influences growth and condition of walleye (<i>Sander vitreus</i>) in large systems. In Lake Oahe, South Dakota, rainbow smelt (<i>Osmerus mordax</i>) and gizzard shad (<i>Dorosoma cepedianum</i>) are primary prey of walleye, but their abundance varies substantially year to year. To evaluate the influence of gizzard shad and rainbow smelt on walleye diets and growth in Lake Oahe, we compared recent estimates of walleye diets and growth in 2008 through 2010 with those from the late 1990s and early 2000s. Walleye diets differed seasonally with increased piscivory in July and October. In 2008, gizzard shad were the dominant prey item of walleye, representing about 60% of the diets by weight; however, by 2009, gizzard shad declined appreciably in the diet (22%) and were completely absent from walleye diets by 2010. Conversely, rainbow smelt abundance represented 12%, 27%, and 90% of walleye diets by weight in 2008, 2009 and 2010, respectively. Changes in growth corresponded to changes in diets, with the slowest growth occurring when gizzard shad were dominant in the diets and increasing growth every year thereafter. Because gizzard shad are only available during short periods (&lt;3 months) in late summer, walleye can only achieve about 50% of their annual maintenance energy requirements from this prey source. Conversely, rainbow smelt, which are available and consumed year round, provide a continuous energy source that contributes to high growth rates. Nonetheless, when abundant, gizzard shad may provide an important subsidy to Lake Oahe walleye during periods of low rainbow smelt abundance.</p></div></div>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10402381.2014.914989","usgsCitation":"Fincel, M.J., Dembkowski, D., and Chipps, S.R., 2014, Influence of variable rainbow smelt and gizzard shad abundance on walleye diets and growth: Lake and Reservoir Management, v. 30, no. 3, p. 258-267, https://doi.org/10.1080/10402381.2014.914989.","productDescription":"10 p.","startPage":"258","endPage":"267","ipdsId":"IP-049945","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-16","publicationStatus":"PW","scienceBaseUri":"59084934e4b0fc4e448ffd8c","contributors":{"authors":[{"text":"Fincel, Mark J.","contributorId":171853,"corporation":false,"usgs":false,"family":"Fincel","given":"Mark","email":"","middleInitial":"J.","affiliations":[{"id":26957,"text":"South Dakota Game, Fish and Parks, Ft. Pierre, SD","active":true,"usgs":false}],"preferred":false,"id":693765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dembkowski, Daniel J.","contributorId":78237,"corporation":false,"usgs":true,"family":"Dembkowski","given":"Daniel J.","affiliations":[],"preferred":false,"id":693766,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693634,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191023,"text":"70191023 - 2014 - Dispersion analysis of passive surface-wave noise generated during hydraulic-fracturing operations","interactions":[],"lastModifiedDate":"2017-09-21T12:06:41","indexId":"70191023","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2165,"text":"Journal of Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Dispersion analysis of passive surface-wave noise generated during hydraulic-fracturing operations","docAbstract":"<p><span>Surface-wave dispersion analysis is useful for estimating near-surface shear-wave velocity models, designing receiver arrays, and suppressing surface waves. Here, we analyze whether passive seismic noise generated during hydraulic-fracturing operations can be used to extract surface-wave dispersion characteristics. Applying seismic interferometry to noise measurements, we extract surface waves by cross-correlating several minutes of passive records; this approach is distinct from previous studies that used hours or days of passive records for cross-correlation. For comparison, we also perform dispersion analysis for an active-source array that has some receivers in common with the passive array. The active and passive data show good agreement in the dispersive character of the fundamental-mode surface-waves. For the higher mode surface waves, however, active and passive data resolve the dispersive properties at different frequency ranges. To demonstrate an application of dispersion analysis, we invert the observed surface-wave dispersion characteristics to determine the near-surface, one-dimensional shear-wave velocity.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jappgeo.2014.09.008","usgsCitation":"Forghani-Arani, F., Willis, M., Snieder, R., Haines, S.S., Behura, J., Batzle, M., and Davidson, M., 2014, Dispersion analysis of passive surface-wave noise generated during hydraulic-fracturing operations: Journal of Applied Geophysics, v. 111, p. 129-134, https://doi.org/10.1016/j.jappgeo.2014.09.008.","productDescription":"6 p.","startPage":"129","endPage":"134","ipdsId":"IP-058038","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":473305,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1556315","text":"Publisher Index Page"},{"id":345987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59c4cf97e4b017cf313d3cb8","contributors":{"authors":[{"text":"Forghani-Arani, Farnoush","contributorId":196642,"corporation":false,"usgs":false,"family":"Forghani-Arani","given":"Farnoush","email":"","affiliations":[{"id":34665,"text":"Microseismic Inc.","active":true,"usgs":false}],"preferred":false,"id":710974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Willis, Mark","contributorId":196643,"corporation":false,"usgs":false,"family":"Willis","given":"Mark","email":"","affiliations":[{"id":34662,"text":"Halliburton","active":true,"usgs":false}],"preferred":false,"id":710975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Snieder, Roel","contributorId":196644,"corporation":false,"usgs":false,"family":"Snieder","given":"Roel","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":710976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710973,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Behura, Jyoti","contributorId":196645,"corporation":false,"usgs":false,"family":"Behura","given":"Jyoti","email":"","affiliations":[{"id":34663,"text":"Seismic Science LLC","active":true,"usgs":false}],"preferred":false,"id":710977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Batzle, Mike","contributorId":196646,"corporation":false,"usgs":false,"family":"Batzle","given":"Mike","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":710978,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davidson, Michael","contributorId":196647,"corporation":false,"usgs":false,"family":"Davidson","given":"Michael","email":"","affiliations":[{"id":17916,"text":"ConocoPhillips","active":true,"usgs":false}],"preferred":false,"id":710979,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70192418,"text":"70192418 - 2014 - Major and trace element geochemistry and background concentrations for soils in Connecticut","interactions":[],"lastModifiedDate":"2021-08-02T11:37:54.198201","indexId":"70192418","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5673,"text":"Northeastern Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Major and trace element geochemistry and background concentrations for soils in Connecticut","docAbstract":"<p>Soil samples were collected throughout Connecticut (CT) to determine the relationship of soil chemistry with the underlying geology and to better understand background concentrations of major and trace elements in soils. Soil samples were collected (1) from the upper 5 cm of surficial soil at 100 sites, (2) from the A horizon at 86 of these sites, and (3) from the deeper horizon, typically the C horizon, at 79 of these sites. The &lt;2-millimeter fraction of each sample was analyzed for 44 elements by methods that yield the total or near-total elemental content. Sample sites were characterized by glacial setting, underlying bedrock geology, and soil type. These spatial data were used with element concentrations in the C-horizon to relate geologic factors to soil chemistry. </p><p>Concentrations of elements in C-horizon soils varied with grain size in surficial glacial materials and with underlying rock types, as determined using nonparametric statistical procedures. Concentrations of most elements in C-horizon soils showed a positive correlation with silt and (or) clay content and were higher in surficial materials mapped as till, thick till, and (or) fines. Element concentrations in C-horizon soils showed significant differences among the underlying geologic provinces and were highest overlying the Grenville Belt and (or) the Grenville Shelf Sequence Provinces in western CT. These rocks consist mainly of carbonates and the relatively high element concentrations in overlying soils likely result from less influence of dilution by quartz compared to other provinces. Element concentrations in C-horizon soils in CT were compared with those in samples from other New England states overlying similar lithologic bedrock types. The upper range of As concentrations in C-horizon soils overlying the New Hampshire-Maine (NH-ME) Sequence in CT was 15 mg/kg, lower than the upper range of 24 mg/kg in C-horizon soils overlying the same sequence in ME. In CT, U concentration means were significantly higher in C-horizon soils overlying Avalonian granites, and U concentrations ranged as high as 14 mg/kg, compared to those in C-horizon soil samples collected from other New England states, which ranged as high as 6.1 mg/kg in a sample in NH overlying the NH-ME Sequence. </p><p>Element concentrations in C-horizon soils in CT were compared with those in samples collected from shallower depths. Concentrations of most major elements were highest in C-horizon soil samples, including Al, Ca, Fe, K, Na, and Ti, but element concentrations showed a relatively similar pattern in A-horizon and surficial soil samples among the underlying geologic provinces. Trace element concentrations, including Ba, W, Ga, Ni, Cs, Rb, Sr, Th, Sc, and U, also were higher in C-horizon soil samples than in overlying soil samples. Concentrations of Mg, and several trace elements, including Mn, P, As, Nb, Sn, Be, Bi, Hg, Se, Sb, La, Co, Cr, Pb, V, Y, Cu, Pb, and Zn were highest in some A-horizon or surficial soils, and indicate possible contributions from anthropogenic sources. Because element concentrations in soils above the C horizon are more likely to be affected by anthropogenic factors, concentration ranges in C-horizon soils and their spatially varying geologic associations should be considered when estimating background concentrations of elements in CT soils. <br></p>","language":"English","publisher":"Northeastern Geoscience","usgsCitation":"Brown, C.J., and Thomas, M., 2014, Major and trace element geochemistry and background concentrations for soils in Connecticut: Northeastern Geoscience, v. 32, p. 1-37.","productDescription":"37 p.","startPage":"1","endPage":"37","ipdsId":"IP-054875","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":352951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70188048,"text":"70188048 - 2014 - Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006","interactions":[],"lastModifiedDate":"2017-05-30T15:15:06","indexId":"70188048","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006","docAbstract":"<p><span>Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y</span><sup>−1</sup><span> during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs6031783","usgsCitation":"Xia, J., Liu, S., Liang, S., Chen, Y., Xu, W., and Yuan, W., 2014, Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006: Remote Sensing, v. 6, no. 3, p. 1783-1802, https://doi.org/10.3390/rs6031783.","productDescription":"20 p.","startPage":"1783","endPage":"1802","ipdsId":"IP-052038","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":486959,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs6031783","text":"Publisher Index Page"},{"id":341874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-26","publicationStatus":"PW","scienceBaseUri":"592e84c7e4b092b266f10dae","contributors":{"authors":[{"text":"Xia, Jiangzhou","contributorId":192427,"corporation":false,"usgs":false,"family":"Xia","given":"Jiangzhou","email":"","affiliations":[],"preferred":false,"id":696484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liang, Shunlin","contributorId":192428,"corporation":false,"usgs":false,"family":"Liang","given":"Shunlin","email":"","affiliations":[],"preferred":false,"id":696485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Yang","contributorId":192429,"corporation":false,"usgs":false,"family":"Chen","given":"Yang","email":"","affiliations":[],"preferred":false,"id":696486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xu, Wenfang","contributorId":192430,"corporation":false,"usgs":false,"family":"Xu","given":"Wenfang","email":"","affiliations":[],"preferred":false,"id":696487,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yuan, Wenping","contributorId":83435,"corporation":false,"usgs":true,"family":"Yuan","given":"Wenping","email":"","affiliations":[],"preferred":false,"id":696488,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70189074,"text":"70189074 - 2014 - Spectroscopy from Space","interactions":[],"lastModifiedDate":"2020-11-05T16:48:04.612491","indexId":"70189074","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3281,"text":"Reviews in Mineralogy and Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Spectroscopy from Space","docAbstract":"<p>This chapter reviews detection of materials on solid and liquid (lakes and ocean) surfaces in the solar system using ultraviolet to infrared spectroscopy from space, or near space (high altitude aircraft on the Earth), or in the case of remote objects, earth-based and earth-orbiting telescopes. Point spectrometers and imaging spectrometers have been probing the surfaces of our solar system for decades. Spacecraft carrying imaging spectrometers are currently in orbit around Mercury, Venus, Earth, Mars, and Saturn, and systems have recently visited Jupiter, comets, asteroids, and one spectrometer-carrying spacecraft is on its way to Pluto. Together these systems are providing a wealth of data that will enable a better understanding of the composition of condensed matter bodies in the solar system.</p><p>Minerals, ices, liquids, and other materials have been detected and mapped on the Earth and all planets and/or their satellites where the surface can be observed from space, with the exception of Venus whose thick atmosphere limits surface observation. Basaltic minerals (e.g., pyroxene and olivine) have been detected with spectroscopy on the Earth, Moon, Mars and some asteroids. The greatest mineralogic diversity seen from space is observed on the Earth and Mars. The Earth, with oceans, active tectonic and hydrologic cycles, and biological processes, displays the greatest material diversity including the detection of amorphous and crystalline inorganic materials, organic compounds, water and water ice.</p><p>Water ice is a very common mineral throughout the Solar System and has been unambiguously detected or inferred in every planet and/or their moon(s) where good spectroscopic data has been obtained.</p><p>In addition to water ice, other molecular solids have been observed in the solar system using spectroscopic methods. Solid carbon dioxide is found on all systems beyond the Earth except Pluto, although CO<sub>2</sub><span>&nbsp;</span>sometimes appears to be trapped in other solids rather than as an ice on some objects. The largest deposits of carbon dioxide ice are found on Mars. Sulfur dioxide ice is found in the Jupiter system. Nitrogen and methane ices are common beyond the Uranian system.</p><p>Saturn’s moon Titan probably has the most complex active extra-terrestrial surface chemistry involving organic compounds. Some of the observed or inferred compounds include ices of benzene (C<sub>6</sub>H<sub>6</sub>), cyanoacetylene (HC<sub>3</sub>N), toluene (C<sub>7</sub>H<sub>8</sub>), cyanogen (C<sub>2</sub>N<sub>2</sub>), acetonitrile (CH<sub>3</sub>CN), water (H<sub>2</sub>O), carbon dioxide (CO<sub>2</sub>), and ammonia (NH<sub>3</sub>). Confirming compounds on Titan is hampered by its thick smoggy atmosphere, where in relative terms the atmospheric interferences that hamper surface characterization lie between that of Venus and Earth.</p><p>In this chapter we exclude discussion of the planets Jupiter, Saturn, Uranus, and Neptune because their thick atmospheres preclude observing the surface, even if surfaces exist. However, we do discuss spectroscopic observations on a number of the extra-terrestrial satellite bodies. Ammonia was predicted on many icy moons but is notably absent among the definitively detected ices with possible exceptions on Charon and possible trace amounts on some of the Saturnian satellites. Comets, storehouses of many compounds that could exist as ices in their nuclei, have only had small amounts of water ice definitively detected on their surfaces from spectroscopy. Only two asteroids have had a direct detection of surface water ice, although its presence can be inferred in others.</p>","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/rmg.2014.78.10","usgsCitation":"Clark, R.N., Swayze, G.A., Carlson, R.R., Grundy, W., and Noll, K., 2014, Spectroscopy from Space: Reviews in Mineralogy and Geochemistry, v. 78, no. 1, p. 399-446, https://doi.org/10.2138/rmg.2014.78.10.","productDescription":"48 p.","startPage":"399","endPage":"446","ipdsId":"IP-036673","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-27","publicationStatus":"PW","scienceBaseUri":"595611b9e4b0d1f9f0506772","contributors":{"authors":[{"text":"Clark, Roger N. 0000-0002-7021-1220 rclark@usgs.gov","orcid":"https://orcid.org/0000-0002-7021-1220","contributorId":515,"corporation":false,"usgs":true,"family":"Clark","given":"Roger","email":"rclark@usgs.gov","middleInitial":"N.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swayze, Gregg A. 0000-0002-1814-7823 gswayze@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7823","contributorId":518,"corporation":false,"usgs":true,"family":"Swayze","given":"Gregg","email":"gswayze@usgs.gov","middleInitial":"A.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson, Robert R.","contributorId":71944,"corporation":false,"usgs":true,"family":"Carlson","given":"Robert","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":702931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grundy, Will","contributorId":156333,"corporation":false,"usgs":false,"family":"Grundy","given":"Will","email":"","affiliations":[],"preferred":false,"id":702932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noll, Keith","contributorId":193877,"corporation":false,"usgs":false,"family":"Noll","given":"Keith","email":"","affiliations":[],"preferred":false,"id":702933,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70188053,"text":"70188053 - 2014 - A design for a sustained assessment of climate forcings and feedbacks on land use land cover change","interactions":[],"lastModifiedDate":"2017-05-30T13:53:35","indexId":"70188053","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"A design for a sustained assessment of climate forcings and feedbacks on land use land cover change","docAbstract":"<p><span>Land use and land cover change (LULCC) significantly influences the climate system. Hence, to prepare the nation for future climate change and variability, a sustained assessment of LULCC and its climatic impacts needs to be undertaken. To address this objective, not only do we need to determine contemporary trends in land use and land cover that affect, or are affected by, weather and climate but also identify sectors and regions that are most affected by weather and climate variability. Moreover, it is critical that we recognize land cover and regions that are most vulnerable to climate change and how end-use practices are adapting to climate change. This paper identifies a series of steps that need to be undertaken to address these key items. In addition, national-scale institutional capabilities are identified and discussed. Included in the discussions are challenges and opportunities for collaboration among these institutions for a sustained assessment.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-12-00208.1","usgsCitation":"Loveland, T., and Mahmood, R., 2014, A design for a sustained assessment of climate forcings and feedbacks on land use land cover change: Bulletin of the American Meteorological Society, v. 95, p. 1563-1572, https://doi.org/10.1175/BAMS-D-12-00208.1.","productDescription":"10 p.","startPage":"1563","endPage":"1572","ipdsId":"IP-055002","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473302,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/bams-d-12-00208.1","text":"Publisher Index Page"},{"id":341866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84c7e4b092b266f10da9","contributors":{"authors":[{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahmood, Rezaul","contributorId":34376,"corporation":false,"usgs":true,"family":"Mahmood","given":"Rezaul","affiliations":[],"preferred":false,"id":696332,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70188054,"text":"70188054 - 2014 - Earth observation based assessment of the water production and water consumption of Nile Basin agro-ecosystems","interactions":[],"lastModifiedDate":"2017-05-31T16:11:56","indexId":"70188054","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Earth observation based assessment of the water production and water consumption of Nile Basin agro-ecosystems","docAbstract":"<p><span>The increasing competition for water resources requires a better understanding of flows, fluxes, stocks, and the services and benefits related to water consumption. This paper explains how public domain Earth Observation data based on Moderate Resolution Imaging Spectroradiometer (MODIS), Second Generation Meteosat (MSG), Tropical Rainfall Measurement Mission (TRMM) and various altimeter measurements can be used to estimate net water production (rainfall (P) &gt; evapotranspiration (ET)) and net water consumption (ET &gt; P) of Nile Basin agro-ecosystems. Rainfall data from TRMM and the Famine Early Warning System Network (FEWS-NET) RainFall Estimates (RFE) products were used in conjunction with actual evapotranspiration from the Operational Simplified Surface Energy Balance (SSEBop) and ETLook models. Water flows laterally between net water production and net water consumption areas as a result of runoff and withdrawals. This lateral flow between the 15 sub-basins of the Nile was estimated, and partitioned into stream flow and non-stream flow using the discharge data. A series of essential water metrics necessary for successful integrated water management are explained and computed. Net water withdrawal estimates (natural and humanly instigated) were assumed to be the difference between net rainfall (P</span><sub>net</sub><span>) and actual evapotranspiration (ET) and some first estimates of withdrawals—without flow meters—are provided. Groundwater-dependent ecosystems withdraw large volumes of groundwater, which exceed water withdrawals for the irrigation sector. There is a strong need for the development of more open-access Earth Observation databases, especially for information related to actual ET. The fluxes, flows and storage changes presented form the basis for a global framework to describe monthly and annual water accounts in ungauged river basins. </span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs61110306","usgsCitation":"Bastiaanssen, W., Karimi, P., Rebelo, L., Duan, Z., Senay, G., Muthuwatte, L., and Smakhtin, V., 2014, Earth observation based assessment of the water production and water consumption of Nile Basin agro-ecosystems: Remote Sensing, v. 6, no. 11, p. 10306-10334, https://doi.org/10.3390/rs61110306.","productDescription":"29 p.","startPage":"10306","endPage":"10334","ipdsId":"IP-057431","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473300,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs61110306","text":"Publisher Index Page"},{"id":341872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Nile Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              23.818359375,\n              -3.688855143147035\n            ],\n            [\n              37.6171875,\n              -3.688855143147035\n            ],\n            [\n              37.6171875,\n              31.57853542647338\n            ],\n            [\n              23.818359375,\n              31.57853542647338\n            ],\n            [\n              23.818359375,\n              -3.688855143147035\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"6","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-24","publicationStatus":"PW","scienceBaseUri":"592e84c6e4b092b266f10da3","contributors":{"authors":[{"text":"Bastiaanssen, Wim","contributorId":192421,"corporation":false,"usgs":false,"family":"Bastiaanssen","given":"Wim","email":"","affiliations":[],"preferred":false,"id":696478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karimi, Poolad","contributorId":192422,"corporation":false,"usgs":false,"family":"Karimi","given":"Poolad","email":"","affiliations":[],"preferred":false,"id":696479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rebelo, Lisa-Maria","contributorId":192423,"corporation":false,"usgs":false,"family":"Rebelo","given":"Lisa-Maria","email":"","affiliations":[],"preferred":false,"id":696480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duan, Zheng","contributorId":192424,"corporation":false,"usgs":false,"family":"Duan","given":"Zheng","email":"","affiliations":[],"preferred":false,"id":696481,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muthuwatte, Lal","contributorId":192425,"corporation":false,"usgs":false,"family":"Muthuwatte","given":"Lal","email":"","affiliations":[],"preferred":false,"id":696482,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smakhtin, Vladimir","contributorId":192426,"corporation":false,"usgs":false,"family":"Smakhtin","given":"Vladimir","email":"","affiliations":[],"preferred":false,"id":696483,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70187420,"text":"70187420 - 2014 - Normative standards for land use in Vermont: Implications for biodiversity","interactions":[],"lastModifiedDate":"2017-05-02T12:52:14","indexId":"70187420","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Normative standards for land use in Vermont: Implications for biodiversity","docAbstract":"<p><span>The conversion of natural lands to developed uses poses a great threat to global terrestrial biodiversity. Natural resource managers, tasked with managing wildlife as a public trust, require techniques for predicting&nbsp;</span><i>how much</i><span>&nbsp;and&nbsp;</span><i>where</i><span>&nbsp;wildlife habitat is likely to be converted in the future. Here, we develop a methodology to&nbsp;estimate the “social carrying capacity for development” – </span><i>SK<sub>d</sub></i><span> – for 251 towns across the state of Vermont, USA. </span><i>SK<sub>d</sub></i><span> represents town residents’ minimum acceptable human population size and level of development within town boundaries. To estimate </span><i>SK<sub>d</sub></i><span> across towns within the state of Vermont (USA), as well as the average state-wide </span><i>SK<sub>d</sub></i><span>, we administered a visual preference survey (</span><i>n</i><span>&nbsp;=&nbsp;1505 responses) to Vermont residents, and asked respondents to rate alternative landuse scenarios in a fictional Vermont town on a scale of +4 (highly acceptable) to −4 (highly unacceptable). We additionally collected demographic data such as age and income, as well as ancillary information such as participation in town-planning meetings and location of residence. We used model selection and AIC to fit a cubic function to the response data, allowing us&nbsp;to estimate </span><i>SK<sub>d</sub></i><span>&nbsp;at a town scale based on town demographic characteristics. On average, Vermonters had a&nbsp;</span><i>SK<sub>d</sub></i><span>&nbsp;of 9.1% development on the landscape; this estimate is 68% higher than year 2000 levels for development (5.4%). Respondents indicated that management action to curb development was appropriate at 9.4% development (roughly the statewide </span><i>SK<sub>d</sub></i><span> average). Management by local, regional, and state levels were considered acceptable for curbing development while federal level management of development was considered unacceptable. Given a scenario where development levels were at </span><i>SK<sub>d</sub></i><span>, we predicted a 16,753&nbsp;km</span><sup>2</sup><span> reduction in forested land (−11.16%) and a 1038&nbsp;km</span><sup>2</sup><span> reduction in farmland (−60.45%). Such changes would dramatically alter biodiversity patterns state-wide. In a companion paper, we estimate how these changes would affect the distribution of wildlife species.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2013.07.009","usgsCitation":"Bettigole, C.A., Donovan, T., Manning, R., and Austin, J., 2014, Normative standards for land use in Vermont: Implications for biodiversity: Biological Conservation, v. 169, p. 392-400, https://doi.org/10.1016/j.biocon.2013.07.009.","productDescription":"9 p.","startPage":"392","endPage":"400","ipdsId":"IP-040027","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70187380,"text":"70187380 - 2014 - A new map of global ecological land units — An ecophysiographic stratification approach","interactions":[],"lastModifiedDate":"2022-09-16T18:13:10.033614","indexId":"70187380","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"title":"A new map of global ecological land units — An ecophysiographic stratification approach","docAbstract":"<p>In response to the need and an intergovernmental commission for a high resolution and data-derived global ecosystem map, land surface elements of global ecological pattern were characterized in an ecophysiographic stratification of the planet. The stratification produced 3,923 terrestrial ecological land units (ELUs) at a base resolution of 250 meters. The ELUs were derived from data on land surface features in a three step approach. The first step involved acquiring or developing four global raster datalayers representing the primary components of ecosystem structure: bioclimate, landform, lithology, and land cover. These datasets generally represent the most accurate, current, globally comprehensive, and finest spatial and thematic resolution data available for each of the four inputs. The second step involved a spatial combination of the four inputs into a single, new integrated raster dataset where every cell represents a combination of values from the bioclimate, landforms, lithology, and land cover datalayers. This foundational global raster datalayer, called ecological facets (EFs), contains 47,650 unique combinations of the four inputs. The third step involved an aggregation of the EFs into the 3,923 ELUs. This subdivision of the Earth’s surface into relatively fine, ecological land areas is designed to be useful for various types of ecosystem research and management applications, including assessments of climate change impacts to ecosystems, economic and non-economic valuation of ecosystem services, and conservation planning.</p>","language":"English","publisher":"Association of American Geographers, U. S. Geological Survey, GEO BON","isbn":"978-0-89291-276-6","usgsCitation":"Sayre, R., Dangermond, J., Frye, C., Vaughan, R., Aniello, P., Breyer, S.P., Cribbs, D., Hopkins, D., Nauman, R., Derrenbacher, W., Wright, D.J., Brown, C., Convis, C., Smith, J.H., Benson, L., VanSistine, D.P., Warner, H., Cress, J.J., Danielson, J.J., Hamann, S.L., Cecere, T., Reddy, A.D., Burton, D., Grosse, A., TRUE, D., Metzger, M., Hartmann, J., Moosdorf, N., Durr, H., Paganini, M., Defourny, P., Arino, O., Maynard, S., Anderson, M., and Comer, P., 2014, A new map of global ecological land units — An ecophysiographic stratification approach, 46 p.","productDescription":"46 p.","ipdsId":"IP-060509","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":340699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":406868,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://geobon.org/documents/biodiversity-monitoring/"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59084934e4b0fc4e448ffd8a","contributors":{"authors":[{"text":"Sayre, Roger 0000-0001-6703-7105 rsayre@usgs.gov","orcid":"https://orcid.org/0000-0001-6703-7105","contributorId":191629,"corporation":false,"usgs":true,"family":"Sayre","given":"Roger","email":"rsayre@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true}],"preferred":true,"id":693663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dangermond, Jack","contributorId":191630,"corporation":false,"usgs":false,"family":"Dangermond","given":"Jack","email":"","affiliations":[],"preferred":false,"id":693664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frye, Charlie","contributorId":191631,"corporation":false,"usgs":false,"family":"Frye","given":"Charlie","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. 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,{"id":70188320,"text":"70188320 - 2014 - Detecting the influence of best management practices on vegetation near ephemeral streams with Landsat data","interactions":[],"lastModifiedDate":"2017-06-06T14:00:55","indexId":"70188320","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Detecting the influence of best management practices on vegetation near ephemeral streams with Landsat data","docAbstract":"<p><span>Various best management practices (BMPs) have been implemented on rangelands with the goals of controlling nonpoint source pollution, reducing the impact of livestock in ecologically important riparian areas, and improving grazing distribution. Providing off-stream water sources to livestock in pastures, cross-fencing, and rotational grazing are common rangeland BMPs that have demonstrated success in drawing livestock grazing pressure away from streams. We evaluated the effects of rangeland BMP implementation with six commercial-scale pastures in the northern mixed-grass prairie. Four pastures received a BMP suite consisting of off-stream water, cross-fencing, and deferred-rotation grazing, and two pastures did not receive BMPs. We hypothesized that the BMPs increased the quantity of riparian vegetation cover relative to the conditions in these pastures during the pre-BMP period and to the two pastures that did not receive BMPs. We used a series of 30-m Landsat normalized difference vegetation index (NDVI) images to track the spatial and temporal changes (1984–2010, </span><i>n</i><span> = 24) in vegetation cover, to which NDVI has been well correlated. Validation indicated that the remotely sensed signal from in-channel vegetation was representative of ground conditions. The BMP suite was associated with a 15% increase in the in-channel NDVI (0–30 m from stream centerline) and 18% increase in the riparian NDVI (30–180 m from stream center line). Conversely, the in-channel and riparian NDVI of non-BMP pastures declined 30% and 18% over the study period. The majority of change occurred within 2 yr of BMP implementation. The patterns of in-channel NDVI among pastures suggested that BMP implementation likely altered grazing distribution by decreasing the preferential use of riparian and in-channel areas. We demonstrated that satellite imagery time series are useful in retrospectively evaluating the efficacy of conservation practices, providing critical information to guide adaptive management and decision makers.</span></p>","language":"English","publisher":"Elsevier","doi":"10.2111/REM-D-12-00185.1","usgsCitation":"Rigge, M.B., Smart, A., Wylie, B.K., and de Van Kamp, K., 2014, Detecting the influence of best management practices on vegetation near ephemeral streams with Landsat data: Rangeland Ecology and Management, v. 67, no. 1, p. 1-8, https://doi.org/10.2111/REM-D-12-00185.1.","productDescription":"8 p.","startPage":"1","endPage":"8","ipdsId":"IP-035745","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":342160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"67","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5937bf2fe4b0f6c2d0d9c781","contributors":{"authors":[{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":697194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smart, Alexander","contributorId":24262,"corporation":false,"usgs":true,"family":"Smart","given":"Alexander","affiliations":[],"preferred":false,"id":697310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":697311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de Van Kamp, Kendall","contributorId":192662,"corporation":false,"usgs":false,"family":"de Van Kamp","given":"Kendall","email":"","affiliations":[],"preferred":false,"id":697312,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70189202,"text":"70189202 - 2014 - Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models","interactions":[],"lastModifiedDate":"2017-07-05T16:57:14","indexId":"70189202","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models","docAbstract":"<p><span>This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km</span><sup>2</sup><span>) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2013WR014063","usgsCitation":"Rakovec, O., Hill, M.C., Clark, M., Weerts, A.H., Teuling, A.J., and Uijlenhoet, R., 2014, Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models: Water Resources Research, v. 50, no. 1, p. 409-426, https://doi.org/10.1002/2013WR014063.","productDescription":"18 p.","startPage":"409","endPage":"426","ipdsId":"IP-053395","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":487085,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1808/19328","text":"External Repository"},{"id":343373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-01-17","publicationStatus":"PW","scienceBaseUri":"595dfab7e4b0d1f9f056a7aa","contributors":{"authors":[{"text":"Rakovec, O.","contributorId":194218,"corporation":false,"usgs":false,"family":"Rakovec","given":"O.","email":"","affiliations":[],"preferred":false,"id":703468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, M.P.","contributorId":194219,"corporation":false,"usgs":false,"family":"Clark","given":"M.P.","email":"","affiliations":[],"preferred":false,"id":703469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weerts, A. H.","contributorId":194220,"corporation":false,"usgs":false,"family":"Weerts","given":"A.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":703470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teuling, A. J.","contributorId":138517,"corporation":false,"usgs":false,"family":"Teuling","given":"A.","email":"","middleInitial":"J.","affiliations":[{"id":6920,"text":"Wageningen University, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":703471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Uijlenhoet, R.","contributorId":138518,"corporation":false,"usgs":false,"family":"Uijlenhoet","given":"R.","email":"","affiliations":[{"id":6920,"text":"Wageningen University, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":703472,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70189135,"text":"70189135 - 2014 - Carbonate rocks of the Seward Peninsula, Alaska: Their correlation and paleogeographic significance","interactions":[],"lastModifiedDate":"2018-05-07T21:00:10","indexId":"70189135","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Carbonate rocks of the Seward Peninsula, Alaska: Their correlation and paleogeographic significance","docAbstract":"Paleozoic carbonate strata deposited in shallow platform to off-platform settings occur across the Seward Peninsula and range from unmetamorphosed Ordovician–Devonian(?) rocks of the York succession in the west to highly deformed and metamorphosed Cambrian–Devonian units of the Nome Complex in the east. Faunal and lithologic correlations indicate that early Paleozoic strata in the two areas formed as part of a single carbonate platform.\n\nThe York succession makes up part of the York terrane and consists of Ordovician, lesser Silurian, and limited, possibly Devonian rocks. Shallow-water facies predominate, but subordinate graptolitic shale and calcareous turbidites accumulated in deeper water, intraplatform basin environments, chiefly during the Middle Ordovician. Lower Ordovician strata are mainly lime mudstone and peloid-intraclast grainstone deposited in a deepening upward regime; noncarbonate detritus is abundant in lower parts of the section. Upper Ordovician and Silurian rocks include carbonate mudstone, skeletal wackestone, and coral-stromatoporoid biostromes that are commonly dolomitic and accumulated in warm, shallow to very shallow settings with locally restricted circulation.\n\nThe rest of the York terrane is mainly Ordovician and older, variously deformed and metamorphosed carbonate and siliciclastic rocks intruded by early Cambrian (and younger?) metagabbros. Older (Neoproterozoic–Cambrian) parts of these units are chiefly turbidites and may have been basement for the carbonate platform facies of the York succession; younger, shallow- and deep-water strata likely represent previously unrecognized parts of the York succession and its offshore equivalents. Intensely deformed and altered Mississippian carbonate strata crop out in a small area at the western edge of the terrane.\n\nMetacarbonate rocks form all or part of several units within the blueschist- and greenschist-facies Nome Complex. The Layered sequence includes mafic meta¬igneous rocks and associated calcareous metaturbidites of Ordovician age as well as shallow-water Silurian dolostones. Scattered metacarbonate rocks are chiefly Cambrian, Ordovician, Silurian, and Devonian dolostones that formed in shallow, warm-water settings with locally restricted circulation and marbles of less constrained Paleozoic age. Carbonate metaturbidites occur on the northeast and southeast coasts and yield mainly Silurian and lesser Ordovician and Devonian conodonts; the northern succession also includes debris flows with meter-scale clasts and an argillite interval with Late Ordovician graptolites and lenses of radiolarian chert. Mafic igneous rocks at least partly of Early Devonian age are common in the southern succession.\n\nCarbonate rocks on Seward Peninsula experienced a range of deformational and thermal histories equivalent to those documented in the Brooks Range. Conodont color alteration indices (CAIs) from Seward Peninsula, like those from the Brooks Range, define distinct thermal provinces that likely reflect structural burial. Penetratively deformed high-pressure metamorphic rocks of the Nome Complex (CAIs ≥5) correspond to rocks of the Schist belt in the southern Brooks Range; both record subduction during early stages of the Jurassic–Cretaceous Brooks Range orogeny. Weakly metamorphosed to unmetamorphosed strata of the York terrane (CAIs mainly 2–5), like Brooks Range rocks in the Central belt and structural allochthons to the north, experienced moderate to shallow burial during the main phase of the Brooks Range orogeny. The nature of the contact between the York terrane and the Nome Complex is uncertain; it may be a thrust fault, an extensional surface, or a thrust fault later reactivated as an extensional fault.\n\nLithofacies and biofacies data indicate that, in spite of their divergent Mesozoic histories, rocks of the York terrane and protoliths of the Nome Complex formed as part of the same lower Paleozoic carbonate platform. Stratigraphies in both","language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.2506(03)","usgsCitation":"Dumoulin, J.A., Harris, A., and Repetski, J.E., 2014, Carbonate rocks of the Seward Peninsula, Alaska: Their correlation and paleogeographic significance: GSA Special Papers, v. 506, p. 59-110, https://doi.org/10.1130/2014.2506(03).","productDescription":"52 p.","startPage":"59","endPage":"110","ipdsId":"IP-046076","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":343246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"506","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59576338e4b0d1f9f051b544","contributors":{"authors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":703118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Alta aharris@usgs.gov","contributorId":148394,"corporation":false,"usgs":true,"family":"Harris","given":"Alta","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":703120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Repetski, John E. 0000-0002-2298-7120 jrepetski@usgs.gov","orcid":"https://orcid.org/0000-0002-2298-7120","contributorId":2596,"corporation":false,"usgs":true,"family":"Repetski","given":"John","email":"jrepetski@usgs.gov","middleInitial":"E.","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":703119,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70187415,"text":"70187415 - 2014 - Incorporating detection probability into northern Great Plains pronghorn population estimates","interactions":[],"lastModifiedDate":"2017-05-02T13:34:29","indexId":"70187415","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating detection probability into northern Great Plains pronghorn population estimates","docAbstract":"<p><span>Pronghorn (</span><i>Antilocapra americana</i><span>) abundances commonly are estimated using fixed-wing surveys, but these estimates are likely to be negatively biased because of violations of key assumptions underpinning line-transect methodology. Reducing bias and improving precision of abundance estimates through use of detection probability and mark-resight models may allow for more responsive pronghorn management actions. Given their potential application in population estimation, we evaluated detection probability and mark-resight models for use in estimating pronghorn population abundance. We used logistic regression to quantify probabilities that detecting pronghorn might be influenced by group size, animal activity, percent vegetation, cover type, and topography. We estimated pronghorn population size by study area and year using mixed logit-normal mark-resight (MLNM) models. Pronghorn detection probability increased with group size, animal activity, and percent vegetation; overall detection probability was 0.639 (95% CI = 0.612–0.667) with 396 of 620 pronghorn groups detected. Despite model selection uncertainty, the best detection probability models were 44% (range = 8–79%) and 180% (range = 139–217%) greater than traditional pronghorn population estimates. Similarly, the best MLNM models were 28% (range = 3–58%) and 147% (range = 124–180%) greater than traditional population estimates. Detection probability of pronghorn was not constant but depended on both intrinsic and extrinsic factors. When pronghorn detection probability is a function of animal group size, animal activity, landscape complexity, and percent vegetation, traditional aerial survey techniques will result in biased pronghorn abundance estimates. Standardizing survey conditions, increasing resighting occasions, or accounting for variation in individual heterogeneity in mark-resight models will increase the accuracy and precision of pronghorn population estimates.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.634","usgsCitation":"Jacques, C.N., Jenks, J., Grovenburg, T.W., Klaver, R.W., and DePerno, C.S., 2014, Incorporating detection probability into northern Great Plains pronghorn population estimates: Journal of Wildlife Management, v. 78, no. 1, p. 164-174, https://doi.org/10.1002/jwmg.634.","productDescription":"11 p.","startPage":"164","endPage":"174","ipdsId":"IP-042502","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473276,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/231","text":"External Repository"},{"id":340745,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-12-16","publicationStatus":"PW","scienceBaseUri":"59099ab1e4b0fc4e44915810","contributors":{"authors":[{"text":"Jacques, Christopher N.","contributorId":15521,"corporation":false,"usgs":true,"family":"Jacques","given":"Christopher","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":693977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenks, Jonathan A.","contributorId":51591,"corporation":false,"usgs":true,"family":"Jenks","given":"Jonathan A.","affiliations":[],"preferred":false,"id":693978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grovenburg, Troy W.","contributorId":57712,"corporation":false,"usgs":true,"family":"Grovenburg","given":"Troy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":693979,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":693980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DePerno, Christopher S.","contributorId":10327,"corporation":false,"usgs":true,"family":"DePerno","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":693981,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70187708,"text":"70187708 - 2014 - Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)","interactions":[],"lastModifiedDate":"2017-05-31T16:12:20","indexId":"70187708","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)","docAbstract":"<p>Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) (http://landsat.usgs.gov/WELD.php). The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests' absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. GoogleEarth™ time-series images were used to validate the products. Mapped forest cover loss totaled 53,084 km2 and was found to be depicted conservatively, with a user's accuracy of 78% and a producer's accuracy of 68%. Excluding errors of adjacency, user's and producer's accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km2 and nearly matched the estimated area from the reference (GoogleEarth™) classification; however, user's (42%) and producer's (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user's and producer's accuracies rose to 62% and 75%, respectively. Compared to recent 2001–2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user's and producer's accuracies) and urban gain (72% and 18% for respective user's and producer's accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for national-scale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by improving training data, creating a more robust image feature space, adding contemporaneous Landsat 5 data to the inputs, and modifying definition sets to account for differences in temporal and spatial observational scales. The presented land cover extent and change data are available via the official WELD website (ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/).</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2013.08.014","usgsCitation":"Hansen, M., Egorov, A., Potapov, P., Stehman, S., Tyukavina, A., Turubanova, S., Roy, D.P., Goetz, S., Loveland, T., Ju, J., Kommareddy, A., Kovalskyy, V., Forsyth, C., and Bents, T., 2014, Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD): Remote Sensing of Environment, v. 140, p. 466-484, https://doi.org/10.1016/j.rse.2013.08.014.","productDescription":"19 p.","startPage":"466","endPage":"484","ipdsId":"IP-046262","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"140","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591c0fcce4b0a7fdb43ddf00","contributors":{"authors":[{"text":"Hansen, M.C.","contributorId":69690,"corporation":false,"usgs":false,"family":"Hansen","given":"M.C.","email":"","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":695302,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Egorov, Alexey","contributorId":81719,"corporation":false,"usgs":false,"family":"Egorov","given":"Alexey","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":695303,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Potapov, P.V.","contributorId":19677,"corporation":false,"usgs":false,"family":"Potapov","given":"P.V.","email":"","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":695304,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stehman, S.V.","contributorId":91974,"corporation":false,"usgs":false,"family":"Stehman","given":"S.V.","email":"","affiliations":[{"id":27852,"text":"State University of New York, Syracuse","active":true,"usgs":false}],"preferred":false,"id":695306,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tyukavina, A.","contributorId":19872,"corporation":false,"usgs":false,"family":"Tyukavina","given":"A.","email":"","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":695307,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Turubanova, S.A.","contributorId":108388,"corporation":false,"usgs":false,"family":"Turubanova","given":"S.A.","email":"","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":695308,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roy, David P.","contributorId":54761,"corporation":false,"usgs":false,"family":"Roy","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false},{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false},{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":695309,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goetz, S.J.","contributorId":55186,"corporation":false,"usgs":false,"family":"Goetz","given":"S.J.","email":"","affiliations":[{"id":25456,"text":"Woods Hole Research Center, Falmouth, MA, United States","active":true,"usgs":false}],"preferred":false,"id":695310,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Loveland, Thomas R. 0000-0003-3114-6646","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":106125,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas R.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":695311,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ju, J.","contributorId":85801,"corporation":false,"usgs":false,"family":"Ju","given":"J.","email":"","affiliations":[{"id":12721,"text":"NASA GSFC SSAI","active":true,"usgs":false}],"preferred":false,"id":695312,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kommareddy, A.","contributorId":105638,"corporation":false,"usgs":false,"family":"Kommareddy","given":"A.","email":"","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":695317,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kovalskyy, Valeriy","contributorId":192062,"corporation":false,"usgs":false,"family":"Kovalskyy","given":"Valeriy","email":"","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":695318,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Forsyth, C.","contributorId":192034,"corporation":false,"usgs":false,"family":"Forsyth","given":"C.","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":695319,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bents, T.","contributorId":139577,"corporation":false,"usgs":false,"family":"Bents","given":"T.","email":"","affiliations":[{"id":33302,"text":"University of Kansas, Lawrence","active":true,"usgs":false}],"preferred":false,"id":695320,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70189138,"text":"70189138 - 2014 - New ichnological, paleobotanical and detrital zircon data from an unnamed rock unit in Yukon-Charley Rivers National Preserve (Cretaceous: Alaska): Stratigraphic implications for the region","interactions":[],"lastModifiedDate":"2017-06-30T16:04:04","indexId":"70189138","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3000,"text":"Palaios","active":true,"publicationSubtype":{"id":10}},"title":"New ichnological, paleobotanical and detrital zircon data from an unnamed rock unit in Yukon-Charley Rivers National Preserve (Cretaceous: Alaska): Stratigraphic implications for the region","docAbstract":"<p><span>A paleontological reconnaissance survey on Cretaceous and Paleogene terrestrial units along the Yukon River drainage through much of east-central Alaska has provided new chronostratigraphic constraints, paleoclimatological data, and the first information on local biodiversity within an ancient, high-latitude ecosystem. The studied unnamed rock unit is most notable for its historic economic gold placer deposits, but our survey documents its relevance as a source rock for Mesozoic terrestrial vertebrates, invertebrates, and associated flora. Specifically, new U-Pb ages from detrital zircons combined with ichnological data are indicative of a Late Cretaceous age for at least the lower section of the studied rock unit, previously considered to be representative of nearly exclusively Paleogene deposition. Further, the results of our survey show that this sedimentary rock unit preserves the first record of dinosaurs in the vast east-central Alaska region. Lastly, paleobotanical data, when compared to correlative rock units, support previous interpretations that the Late Cretaceous continental ecosystem of Alaska was heterogeneous in nature and seasonal.</span></p>","language":"English","publisher":"Society for Sedimentary Geology","doi":"10.2110/palo.2013.054","usgsCitation":"Fiorillo, A.R., Fanti, F., Hults, C., and Hasiotis, S.T., 2014, New ichnological, paleobotanical and detrital zircon data from an unnamed rock unit in Yukon-Charley Rivers National Preserve (Cretaceous: Alaska): Stratigraphic implications for the region: Palaios, v. 29, no. 1, p. 16-26, https://doi.org/10.2110/palo.2013.054.","productDescription":"11 p.","startPage":"16","endPage":"26","ipdsId":"IP-053208","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":343247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-12","publicationStatus":"PW","scienceBaseUri":"59576338e4b0d1f9f051b541","contributors":{"authors":[{"text":"Fiorillo, Anthony R.","contributorId":194070,"corporation":false,"usgs":false,"family":"Fiorillo","given":"Anthony","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fanti, Federico","contributorId":194071,"corporation":false,"usgs":false,"family":"Fanti","given":"Federico","email":"","affiliations":[],"preferred":false,"id":703134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hults, Chad chults@usgs.gov","contributorId":194069,"corporation":false,"usgs":true,"family":"Hults","given":"Chad","email":"chults@usgs.gov","affiliations":[],"preferred":true,"id":703132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hasiotis, Stephen T","contributorId":194072,"corporation":false,"usgs":false,"family":"Hasiotis","given":"Stephen","email":"","middleInitial":"T","affiliations":[],"preferred":false,"id":703135,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70189139,"text":"70189139 - 2014 - Sulfur and oxygen isotopic study of Paleozoic sediment-hosted Zn-Pb(-Ag-Au-Ba-F) deposits and associated hydrothermal alteration zones in the Nome Complex, Seward Peninsula, Alaska","interactions":[],"lastModifiedDate":"2018-11-20T09:53:26","indexId":"70189139","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Sulfur and oxygen isotopic study of Paleozoic sediment-hosted Zn-Pb(-Ag-Au-Ba-F) deposits and associated hydrothermal alteration zones in the Nome Complex, Seward Peninsula, Alaska","docAbstract":"Results of sulfur and oxygen isotope studies of sedimentary exhalative (SEDEX) Zn-Pb(-Ag-Au-Ba-F) deposits hosted in metamorphosed Paleozoic clastic and carbonate rocks of the Nome Complex, Seward Peninsula, Alaska, are consistent with data for similar deposits worldwide.  Stable isotopic studies of the Nome Complex are challenging because the rocks have undergone Mesozoic blueschist- and greenschist-facies metamorphism and deformation at temperatures estimated from 390–490 °C.  Studies of sulfur and oxygen isotopes in other areas suggest that, in the absence of chemical and mineralogical evidence for metasomatism, the principal effect of metamorphism is re-equilibration between individual minerals at the temperature of metamorphism, which commonly leads to a narrowing of the overall range of isotope values for a suite of rocks, but generally does not significantly modify the average whole rock value for that suite.\n\tSulfur isotope studies of the stratabound and locally stratiform sulfide lenses at the Aurora Creek-Christophosen deposit, which is of possible Late Devonian-early Carboniferous age, show a large range of δ34Ssulfide values from -9.7 to 39.4‰, suggesting multiple sulfur sources and possibly complex processes of sulfide formation that may include bacterial sulfate reduction, thermochemical sulfate reduction, and Rayleigh distillation.  Low δ34S values probably represent bacterial sulfide minerals remobilized from the host metasedimentary rocks either during the original seafloor mineralization or are related to a Cretaceous mineralizing event that produced Au-vein and base-metal replacement deposits; the latter process is supported by Pb isotope data.  \nThe Wheeler North deposit is similar to Aurora Creek-Christophosen but does not have negative δ34S values.  It also probably formed in an euxinic sub-basin.\nThe stratabound Nelson deposit, and the deformed veins at the Galena and Quarry deposits, may be older than the Aurora Creek-Christophosen and Wheeler North deposits.  The Nelson deposit has a lower and narrower range of δ34S values (1.9 to 10.4‰), averaging about 8‰.  The Galena and Quarry veins display δ34S values that are similar to those of the stratabound Nelson deposit.  Barite samples from the Aurora Creek-Christophosen, Wheeler North, and Quarry deposits have 34S-enriched δ34S values between 25 and 30‰ that are consistent with derivation of the sulfur from coeval (Paleozoic) seawater sulfate.  \nGiven their δ34S values, it is likely that the Aurora Creek-Christophosen and Wheeler North deposits formed in closed sub-basins with euxinic conditions that led to extreme Rayleigh distillation to produce the very large range and very high δ34S values.  The Nelson deposit probably formed within an anoxic but not euxinic sub-basin. At Nelson, sulfide was likely derived by a subsurface thermochemical sulfate reduction (TSR) reaction, similar to reactions that are inferred to have produced the sulfides in the Galena and Quarry deposits, which are interpreted as feeder veins for the stratabound deposits.\n\tCalculations of oxygen isotope temperatures are based on the assumption that evolved seawater with δ18O of 3‰ was the mineralizing and altering fluid related to the formation of the sulfide deposits. Temperatures of aluminous alteration and sulfide mineralization were between 109 and 209 °C, determined on the basis of oxygen isotope fractionations between the mineralizing fluid and proportionate amounts of quartz and muscovite in the rocks.  These temperature estimates agree well with known temperatures of SEDEX mineralization worldwide.   Sulfur isotope values also are generally consistent with the known ranges in SEDEX deposits worldwide (δ34S ≈ -5 to 25‰).","language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.2506(08)","usgsCitation":"Shanks, W.P., Slack, J.F., Till, A.B., Thurston, R., and Gemery-Hill, P., 2014, Sulfur and oxygen isotopic study of Paleozoic sediment-hosted Zn-Pb(-Ag-Au-Ba-F) deposits and associated hydrothermal alteration zones in the Nome Complex, Seward Peninsula, Alaska: GSA Special Papers, v. 506, p. 235-258, https://doi.org/10.1130/2014.2506(08).","productDescription":"24 p.","startPage":"235","endPage":"258","ipdsId":"IP-054559","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":343249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"506","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59576338e4b0d1f9f051b53c","contributors":{"authors":[{"text":"Shanks, W.C. Pat III","contributorId":93949,"corporation":false,"usgs":true,"family":"Shanks","given":"W.C.","suffix":"III","email":"","middleInitial":"Pat","affiliations":[],"preferred":false,"id":703137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":703138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Till, Alison B. atill@usgs.gov","contributorId":2482,"corporation":false,"usgs":true,"family":"Till","given":"Alison","email":"atill@usgs.gov","middleInitial":"B.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":703136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurston, Roland","contributorId":194075,"corporation":false,"usgs":false,"family":"Thurston","given":"Roland","affiliations":[],"preferred":false,"id":703139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gemery-Hill, Pamela","contributorId":194076,"corporation":false,"usgs":false,"family":"Gemery-Hill","given":"Pamela","email":"","affiliations":[],"preferred":false,"id":703140,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70189226,"text":"70189226 - 2014 - Effects of iron on optical properties of dissolved organic matter","interactions":[],"lastModifiedDate":"2018-04-02T16:50:30","indexId":"70189226","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Effects of iron on optical properties of dissolved organic matter","docAbstract":"<p><span>Iron is a source of interference in the spectroscopic analysis of dissolved organic matter (DOM); however, its effects on commonly employed ultraviolet and visible (UV–vis) light adsorption and fluorescence measurements are poorly defined. Here, we describe the effects of iron(II) and iron(III) on the UV–vis absorption and fluorescence of solutions containing two DOM fractions and two surface water samples. In each case, regardless of DOM composition, UV–vis absorption increased linearly with increasing iron(III). Correction factors were derived using iron(III) absorption coefficients determined at wavelengths commonly used to characterize DOM. Iron(III) addition increased specific UV absorbances (SUVA) and decreased the absorption ratios (</span><i>E</i><sub>2</sub><span>:</span><i>E</i><sub>3</sub><span>) and spectral slope ratios (</span><i>S</i><sub>R</sub><span>) of DOM samples. Both iron(II) and iron(III) quenched DOM fluorescence at pH 6.7. The degree and region of fluorescence quenching varied with the iron:DOC concentration ratio, DOM composition, and pH. Regions of the fluorescence spectra associated with greater DOM conjugation were more susceptible to iron quenching, and DOM fluorescence indices were sensitive to the presence of both forms of iron. Analyses of the excitation–emission matrices using a 7- and 13-component parallel factor analysis (PARAFAC) model showed low PARAFAC sensitivity to iron addition.</span></p>","language":"English","publisher":"ACS Publications","doi":"10.1021/es502670r","usgsCitation":"Poulin, B., Ryan, J.N., and Aiken, G.R., 2014, Effects of iron on optical properties of dissolved organic matter: Environmental Science & Technology, v. 48, no. 17, p. 10098-10106, https://doi.org/10.1021/es502670r.","productDescription":"9 p.","startPage":"10098","endPage":"10106","ipdsId":"IP-058675","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-13","publicationStatus":"PW","scienceBaseUri":"595f4c42e4b0d1f9f057e362","contributors":{"authors":[{"text":"Poulin, Brett 0000-0002-5555-7733 bpoulin@usgs.gov","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":194253,"corporation":false,"usgs":true,"family":"Poulin","given":"Brett","email":"bpoulin@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryan, Joseph N.","contributorId":54290,"corporation":false,"usgs":false,"family":"Ryan","given":"Joseph","email":"","middleInitial":"N.","affiliations":[{"id":604,"text":"University of Colorado- Boulder","active":false,"usgs":true}],"preferred":false,"id":703602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703601,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189207,"text":"70189207 - 2014 - Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)","interactions":[],"lastModifiedDate":"2017-07-05T16:20:39","indexId":"70189207","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)","docAbstract":"<p>The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km<sup>2</sup><span>&nbsp;</span>basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks.</p><p>The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output.</p><p>Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.</p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/2013EI000554.1","usgsCitation":"Hay, L.E., LaFontaine, J.H., and Markstrom, S.L., 2014, Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99): Earth Interactions, v. 18, p. 1-32, https://doi.org/10.1175/2013EI000554.1.","productDescription":"32 p.","startPage":"1","endPage":"32","ipdsId":"IP-052922","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":473306,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/2013ei000554.1","text":"Publisher Index Page"},{"id":343366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia","otherGeospatial":"Apalachicola–Chattahoochee–Flint River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -85.60546875,\n              29.6594160549124\n            ],\n            [\n              -83.7158203125,\n              29.6594160549124\n            ],\n            [\n              -83.7158203125,\n              34.470335121217474\n            ],\n            [\n              -85.60546875,\n              34.470335121217474\n            ],\n            [\n              -85.60546875,\n              29.6594160549124\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"18","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-14","publicationStatus":"PW","scienceBaseUri":"595dfab7e4b0d1f9f056a7a6","contributors":{"authors":[{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":703495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703496,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189677,"text":"70189677 - 2014 - 1.13 – Emerging contaminants","interactions":[],"lastModifiedDate":"2017-07-19T16:21:53","indexId":"70189677","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"1.13 – Emerging contaminants","docAbstract":"<p><span>Since the Industrial Revolution, a diversity of large-scale chemical innovations has impacted aquatic systems in urban environments. Beginning in the 1990s, there has been a growing scientific interest and public awareness of the effects of the chemicals used in domestic, commercial, industrial, and agricultural applications, referred to in this article as ‘emerging contaminants’ (ECs), on ecosystem and human health. The growing global population and its increasing demands on water supplies in conjunction with climate-induced changes in hydrologic regimes place stress on freshwater resources, resulting in a greater reliance on reuse of reclaimed municipal wastewater treatment plant (WWTP) effluents to meet human and environmental needs. WWTP effluents are a major source of ECs, and it is important to have an understanding of the chemical composition of the reclaimed water, because many ECs are biologically active and the effects of chronic exposure to low concentration complex mixtures are unknown. Several classes of ECs that have been shown to be widespread in the aquatic environment are discussed in this chapter, including surfactants, complexing agents, fragrances, antimicrobials, industrial chemicals, pharmaceuticals, natural and synthetic estrogens, and disinfection byproducts. All of these compounds are biologically active via a variety of modes of action, and can occur in aquatic systems at concentrations ranging from &lt;0.001 to &gt;100&nbsp;μg&nbsp;l</span><sup>−1</sup><span>.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Comprehensive water quality and purification","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-382182-9.00015-3","usgsCitation":"Barber, L.B., 2014, 1.13 – Emerging contaminants, chap. <i>of</i> Comprehensive water quality and purification, v. 1, p. 245-266, https://doi.org/10.1016/B978-0-12-382182-9.00015-3.","productDescription":"22 p.","startPage":"245","endPage":"266","ipdsId":"IP-042295","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59706fbce4b0d1f9f065a903","contributors":{"authors":[{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":705747,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
]}