{"pageNumber":"383","pageRowStart":"9550","pageSize":"25","recordCount":46784,"records":[{"id":70187540,"text":"gip174 - 2017 - Eighty years of cooperative water science","interactions":[],"lastModifiedDate":"2019-10-17T06:41:25","indexId":"gip174","displayToPublicDate":"2017-05-09T11:45:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"174","displayTitle":"Eighty Years of Cooperative Water Science","title":"Eighty years of cooperative water science","docAbstract":"<p>The <i>Equus</i> Beds aquifer in south-central Kansas is a primary water source for the city of Wichita. The <i>Equus</i> Beds aquifer storage and recovery (ASR) project was developed to help the city of Wichita meet increasing current and future demands. The <i>Equus</i> Beds ASR project is a recent part of an 80-year cooperative water science effort with the city of Wichita. The U.S. Geological Survey (USGS) Kansas Water Science Center characterizes river and aquifer water-quality and quantity and evaluates changes that may or may not be related to ASR. The USGS data are used by the city of Wichita to make informed management decisions, satisfy regulatory requirements, and serve as a baseline to detect any subsequent changes that may be related to ASR.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip174","collaboration":"Prepared in cooperation with the City of Wichita, Kansas","usgsCitation":"Stone, M.L., 2017, Eighty years of cooperative water science (ver. 1.1, October 2019): U.S. Geological Survey General Information Product 174, 2 p., https://doi.org/10.3133/gip174.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-086697","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":368327,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/gip/0174/versionHist.txt","text":"Version History","linkFileType":{"id":2,"text":"txt"},"description":"GIP 174 Version History"},{"id":368326,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0174/gip174.pdf","text":"Report","size":"1.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 174"},{"id":346650,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0174/coverthb3.jpg"}],"country":"United States","state":"Kansas","county":"Wichita County","otherGeospatial":"<em>Equus</em> Beds Aquifer","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-101.485,38.7002],[-101.1293,38.7001],[-101.1254,38.264],[-101.5405,38.2631],[-101.5669,38.2633],[-101.5694,38.7004],[-101.485,38.7002]]]},\"properties\":{\"name\":\"Wichita\",\"state\":\"KS\"}}]}","edition":"Version 1.0: May 9, 2017; Version 1.1: October 15, 2019","contact":"<p><a href=\"mailto: dc_ks@usgs.gov\" data-mce-href=\"mailto: dc_ks@usgs.gov\">Director</a>,&nbsp;<a href=\"https://ks.water.usgs.gov\" data-mce-href=\"https://ks.water.usgs.gov\">Kansas Water Science Center</a><br>U.S. Geological Survey<br>1217 Biltmore Drive<br>Lawrence, KS 66049</p>","tableOfContents":"<ul><li>Why the <em>Equus</em> Beds Aquifer Storage and Recovery (ASR) Project?</li><li>History of Wichita Water-Supply Development and USGS/City of Wichita Cooperatively Funded Studies</li><li>Role of USGS Science in Managed Aquifer Recharge</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2017-05-09","revisedDate":"2019-10-15","noUsgsAuthors":false,"publicationDate":"2017-05-09","publicationStatus":"PW","scienceBaseUri":"5912d533e4b0e541a03d4513","contributors":{"authors":[{"text":"Stone, Mandy L. 0000-0002-6711-1536","orcid":"https://orcid.org/0000-0002-6711-1536","contributorId":214749,"corporation":false,"usgs":true,"family":"Stone","given":"Mandy L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":694383,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70187573,"text":"ofr20171050 - 2017 - Geophysical data collected during the 2014 minute 319 pulse flow on the Colorado River below Morelos Dam, United States and Mexico","interactions":[],"lastModifiedDate":"2017-05-09T18:05:56","indexId":"ofr20171050","displayToPublicDate":"2017-05-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1050","title":"Geophysical data collected during the 2014 minute 319 pulse flow on the Colorado River below Morelos Dam, United States and Mexico","docAbstract":"<p>Geophysical methods were used to monitor infiltration during a water release, referred to as a “pulse flow,” in the Colorado River delta in March and April 2014. The pulse flow was enabled by Minute 319 of the 1944 United States–Mexico Treaty concerning water of the Colorado River. Fieldwork was carried out by the U.S. Geological Survey and the Centro de Investigación Científica y de Educación Superior de Ensenada as part of a binational effort to monitor the hydrologic effects of the pulse flow along the limitrophe (border) reach of the Colorado River and into Mexico. Repeat microgravity measurements were made at 25 locations in the southern limitrophe reach to quantify aquifer storage change during the pulse flow. Observed increases in storage along the river were greater with distance to the south, and the amount of storage change decreased away from the river channel. Gravity data at four monitoring well sites indicate specific yield equal to 0.32±0.05. Electromagnetic induction methods were used at 12 transects in the limitrophe reach of the river along the United States– Mexico border, and farther south into Mexico. These data, which are sensitive to variation in soil texture and water content, suggest relatively homogeneous conditions. Repeat direct-current resistivity measurements were collected at two locations to monitor groundwater elevation. Results indicate rapid groundwater-level rise during the pulse flow in the limitrophe reach and smaller variation at a more southern transect. Together, these data are useful for hydrogeologic characterization and hydrologic model development. Electronic data files are provided in the accompanying data release (Kennedy and others, 2016a).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171050","collaboration":"Prepared in Cooperation with Universidad Autónoma de Baja California and Centro de Investigación Científica y de Educación Superior de Ensenada","usgsCitation":"Kennedy, J.R., Callegary, J.B., Macy, J.P., Reyes-Lopez, J., Pérez-Flores, M., 2017, Geophysical data collected during the 2014 minute 319 pulse flow on the Colorado River below Morelos Dam, United States and Mexico: U.S. Geological Survey Open-File Report 2017–1050, 48 p., https://doi.org/10.3133/ofr20171050.","productDescription":"Report: vii, 48 Pp.; Data Release","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-067382","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":438349,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K935M8","text":"USGS data release","linkHelpText":"Geophysical Data Collected during the 2014 Minute 319 Pulse Flow"},{"id":341001,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1050/ofr20171050.pdf","text":"Report","size":"8.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1050"},{"id":341000,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1050/coverthb.jpg"},{"id":341002,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7K935M8","text":"Data Release"}],"country":"Mexico, United States","state":"Arizona, Baja California, California","otherGeospatial":"Colorado River, Morelos Dam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115,\n              32.33333\n            ],\n            [\n              -114.5,\n              32.33333\n            ],\n            [\n              -114.5,\n              32.75\n            ],\n            [\n              -115,\n              32.75\n            ],\n            [\n              -115,\n              32.33333\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://az.water.usgs.gov/\" data-mce-href=\"https://az.water.usgs.gov/\">Arizona Water Science Center</a><br>U.S. Geological Survey<br>520 N. Park Avenue<br>Tucson, AZ 85719<br></p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Abstract&nbsp;<br></li><li>Introduction&nbsp;<br></li><li>Gravity Data&nbsp;<br></li><li>Electromagnetic Induction Data&nbsp;<br></li><li>Direct-Current Resistivity Data&nbsp;<br></li><li>Summary&nbsp;<br></li><li>References Cited&nbsp;<br></li><li>Appendix 1. Electronic Data Files<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-05-09","noUsgsAuthors":false,"publicationDate":"2017-05-09","publicationStatus":"PW","scienceBaseUri":"5912d534e4b0e541a03d4515","contributors":{"authors":[{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":694613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Callegary, James B. 0000-0003-3604-0517 jcallega@usgs.gov","orcid":"https://orcid.org/0000-0003-3604-0517","contributorId":2171,"corporation":false,"usgs":true,"family":"Callegary","given":"James","email":"jcallega@usgs.gov","middleInitial":"B.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":694614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macy, Jamie P. 0000-0003-3443-0079 jpmacy@usgs.gov","orcid":"https://orcid.org/0000-0003-3443-0079","contributorId":2173,"corporation":false,"usgs":true,"family":"Macy","given":"Jamie","email":"jpmacy@usgs.gov","middleInitial":"P.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":694615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reyes-Lopez, Jaime jaime.reyes63@uabc.edu.mx","contributorId":191892,"corporation":false,"usgs":false,"family":"Reyes-Lopez","given":"Jaime","email":"jaime.reyes63@uabc.edu.mx","affiliations":[],"preferred":false,"id":694616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perez-Flores, Marco mperez@cicese.mx","contributorId":191893,"corporation":false,"usgs":false,"family":"Perez-Flores","given":"Marco","email":"mperez@cicese.mx","affiliations":[],"preferred":false,"id":694617,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70187560,"text":"70187560 - 2017 - Drought, multi-seasonal climate, and wildfire in northern New Mexico","interactions":[],"lastModifiedDate":"2017-05-15T17:32:50","indexId":"70187560","displayToPublicDate":"2017-05-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Drought, multi-seasonal climate, and wildfire in northern New Mexico","docAbstract":"<p><span>Wildfire is increasingly a concern in the USA, where 10 million acres burned in 2015. Climate is a primary driver of wildfire, and understanding fire-climate relationships is crucial for informing fire management and modeling the effects of climate change on fire. In the southwestern USA, fire-climate relationships have been informed by tree-ring data that extend centuries prior to the onset of fire exclusion in the late 1800s. Variability in cool-season precipitation has been linked to fire occurrence, but the effects of the summer North American monsoon on fire are less understood, as are the effects of climate on fire seasonality. We use a new set of reconstructions for cool-season (October–April) and monsoon-season (July–August) moisture conditions along with a large new fire scar dataset to examine relationships between multi-seasonal climate variability, fire extent, and fire seasonality in the Jemez Mountains, New Mexico (1599–1899 CE). Results suggest that large fires burning in all seasons are strongly influenced by the current year cool-season moisture, but fires burning mid-summer to fall are also influenced by monsoon moisture. Wet conditions several years prior to the fire year during the cool season, and to a lesser extent during the monsoon season, are also important for spring through late-summer fires. Persistent cool-season drought longer than 3&nbsp;years may inhibit fires due to the lack of moisture to replenish surface fuels. This suggests that fuels may become increasingly limiting for fire occurrence in semi-arid regions that are projected to become drier with climate change.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10584-017-1958-4","usgsCitation":"Margolis, E.Q., Woodhouse, C.A., and Swetnam, T.W., 2017, Drought, multi-seasonal climate, and wildfire in northern New Mexico: Climatic Change, v. 142, no. 3, p. 433-446, https://doi.org/10.1007/s10584-017-1958-4.","productDescription":"14 p.","startPage":"433","endPage":"446","ipdsId":"IP-086088","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469860,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://link.springer.com/10.1007/s10584-017-1958-4","text":"External Repository"},{"id":340995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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85721","active":true,"usgs":false}],"preferred":false,"id":694569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swetnam, Thomas W.","contributorId":191872,"corporation":false,"usgs":false,"family":"Swetnam","given":"Thomas","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":694570,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70187561,"text":"70187561 - 2017 - Development of a coastal drought index using salinity data","interactions":[],"lastModifiedDate":"2017-05-09T11:20:57","indexId":"70187561","displayToPublicDate":"2017-05-09T00:00:00","publicationYear":"2017","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":"Development of a coastal drought index using salinity data","docAbstract":"<p><span>A critical aspect of the uniqueness of coastal drought is the effects on the salinity dynamics of creeks, rivers, and estuaries. The location of the freshwater–saltwater interface along the coast is an important factor in the ecological and socioeconomic dynamics of coastal communities. Salinity is a critical response variable that integrates hydrologic and coastal dynamics including sea level, tides, winds, precipitation, streamflow, and tropical storms. The position of the interface determines the composition of freshwater and saltwater aquatic communities as well as the freshwater availability for water intakes. Many definitions of drought have been proposed, with most describing a decline in precipitation having negative impacts on the water supply. Indices have been developed incorporating data such as rainfall, streamflow, soil moisture, and groundwater levels. These water-availability drought indices were developed for upland areas and may not be ideal for characterizing coastal drought. The availability of real-time and historical salinity datasets provides an opportunity for the development of a salinity-based coastal drought index. An approach similar to the standardized precipitation index (SPI) was modified and applied to salinity data obtained from sites in South Carolina and Georgia. Using the SPI approach, the index becomes a coastal salinity index (CSI) that characterizes coastal salinity conditions with respect to drought periods of higher-saline conditions and wet periods of higher-freshwater conditions. Evaluation of the CSI indicates that it provides additional coastal response information as compared to the SPI and the Palmer hydrologic drought index, and the CSI can be used for different estuary types and for comparison of conditions along coastlines.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-15-00171.1","usgsCitation":"Conrads, P., and Darby, L.S., 2017, Development of a coastal drought index using salinity data: Bulletin of the American Meteorological Society, v. 98, no. 4, p. 753-766, https://doi.org/10.1175/BAMS-D-15-00171.1.","productDescription":"14 p.","startPage":"753","endPage":"766","ipdsId":"IP-067018","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":340993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-24","publicationStatus":"PW","scienceBaseUri":"5912d536e4b0e541a03d451b","contributors":{"authors":[{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":694571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Darby, Lisa S.","contributorId":191873,"corporation":false,"usgs":false,"family":"Darby","given":"Lisa","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":694572,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70187551,"text":"70187551 - 2017 - Historical analysis of riparian vegetation change in response to shifting management objectives on the Middle Rio Grande","interactions":[],"lastModifiedDate":"2017-05-08T15:44:02","indexId":"70187551","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Historical analysis of riparian vegetation change in response to shifting management objectives on the Middle Rio Grande","docAbstract":"<p><span>Riparian ecosystems are valuable to the ecological and human communities that depend on them. Over the past century, they have been subject to shifting management practices to maximize human use and ecosystem services, creating a complex relationship between water policy, management, and the natural ecosystem. This has necessitated research on the spatial and temporal dynamics of riparian vegetation change. The San Acacia Reach of the Middle Rio Grande has experienced multiple management and river flow fluctuations, resulting in threats to its riparian and aquatic ecosystems. This research uses remote sensing data, GIS, a review of management decisions, and an assessment of climate to both quantify how riparian vegetation has been altered over time and provide interpretations of the relationships between riparian change and shifting climate and management objectives. This research focused on four management phases from 1935 to 2014, each highlighting different management practices and climate-driven river patterns, providing unique opportunities to observe a direct relationship between river management, climate, and riparian response. Overall, we believe that management practices coupled with reduced surface river-flows with limited overbank flooding influenced the compositional and spatial patterns of vegetation, including possibly increasing non-native vegetation coverage. However, recent restoration efforts have begun to reduce non-native vegetation coverage.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/land6020029","usgsCitation":"Petrakis, R., van Leeuwen, W., Villarreal, M.L., Tashjian, P., Dello Russo, R., and Scott, C.A., 2017, Historical analysis of riparian vegetation change in response to shifting management objectives on the Middle Rio Grande: Land, v. 6, no. 2, p. 1-23, https://doi.org/10.3390/land6020029.","productDescription":"Article 29; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-079082","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469864,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land6020029","text":"Publisher Index Page"},{"id":438351,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154F84","text":"USGS data release","linkHelpText":"Middle Rio Grande Multitemporal Land Cover Classifications - 1935, 1962, 1987, 1999, and 2014"},{"id":340957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Middle Rio Grande","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.03979492187499,\n              33.61919376817004\n            ],\n            [\n              -106.75140380859374,\n              33.61919376817004\n            ],\n            [\n              -106.75140380859374,\n              34.27197081112463\n            ],\n            [\n              -107.03979492187499,\n              34.27197081112463\n            ],\n            [\n              -107.03979492187499,\n              33.61919376817004\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"6","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-22","publicationStatus":"PW","scienceBaseUri":"591183afe4b0e541a03c1a44","contributors":{"authors":[{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":694506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Leeuwen, Willem","contributorId":148978,"corporation":false,"usgs":false,"family":"van Leeuwen","given":"Willem","email":"","affiliations":[],"preferred":false,"id":694507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":694505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tashjian, Paul","contributorId":191857,"corporation":false,"usgs":false,"family":"Tashjian","given":"Paul","email":"","affiliations":[],"preferred":false,"id":694508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dello Russo, Regina","contributorId":191858,"corporation":false,"usgs":false,"family":"Dello Russo","given":"Regina","email":"","affiliations":[],"preferred":false,"id":694509,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scott, Christopher A.","contributorId":31664,"corporation":false,"usgs":true,"family":"Scott","given":"Christopher","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":694510,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70187541,"text":"70187541 - 2017 - Unconventional oil and gas spills: Risks, mitigation priorities, and state reporting requirements","interactions":[],"lastModifiedDate":"2017-07-12T16:02:48","indexId":"70187541","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","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":"Unconventional oil and gas spills: Risks, mitigation priorities, and state reporting requirements","docAbstract":"<p><span>Rapid growth in unconventional oil and gas (UOG) has produced jobs, revenue, and energy, but also concerns over spills and environmental risks. We assessed spill data from 2005 to 2014 at 31 481 UOG wells in Colorado, New Mexico, North Dakota, and Pennsylvania. We found 2–16% of wells reported a spill each year. Median spill volumes ranged from 0.5 m</span><sup>3</sup><span> in Pennsylvania to 4.9 m</span><sup>3</sup><span> in New Mexico; the largest spills exceeded 100 m</span><sup>3</sup><span>. Seventy-five to 94% of spills occurred within the first three years of well life when wells were drilled, completed, and had their largest production volumes. Across all four states, 50% of spills were related to storage and moving fluids via flowlines. Reporting rates varied by state, affecting spill rates and requiring extensive time and effort getting data into a usable format. Enhanced and standardized regulatory requirements for reporting spills could improve the accuracy and speed of analyses to identify and prevent spill risks and mitigate potential environmental damage. Transparency for data sharing and analysis will be increasingly important as UOG development expands. We designed an interactive spills data visualization tool (</span><a class=\"extLink\" href=\"http://snappartnership.net/groups/hydraulic-fracturing/webapp/spills.html\" data-mce-href=\"http://snappartnership.net/groups/hydraulic-fracturing/webapp/spills.html\">http://snappartnership.net/groups/hydraulic-fracturing/webapp/spills.html</a><span>) to illustrate the value of having standardized, public data.</span></p>","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b05749","usgsCitation":"Patterson, L.A., Konschnik, K.E., Wiseman, H., Fargione, J., Maloney, K.O., Kiesecker, J.M., Nicot, J., Baruch-Mordo, S., Entrekin, S., Trainor, A., and Saiers, J., 2017, Unconventional oil and gas spills: Risks, mitigation priorities, and state reporting requirements: Environmental Science & Technology, v. 51, no. 5, p. 2563-2573, https://doi.org/10.1021/acs.est.6b05749.","productDescription":"11 p.","startPage":"2563","endPage":"2573","ipdsId":"IP-076744","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":469868,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.6b05749","text":"Publisher Index Page"},{"id":340919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-21","publicationStatus":"PW","scienceBaseUri":"591183b0e4b0e541a03c1a4a","contributors":{"authors":[{"text":"Patterson, Lauren A.","contributorId":177289,"corporation":false,"usgs":false,"family":"Patterson","given":"Lauren","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":694403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Konschnik, Katherine E.","contributorId":191826,"corporation":false,"usgs":false,"family":"Konschnik","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":694404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiseman, Hannah","contributorId":191827,"corporation":false,"usgs":false,"family":"Wiseman","given":"Hannah","affiliations":[],"preferred":false,"id":694405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fargione, Joseph","contributorId":191828,"corporation":false,"usgs":false,"family":"Fargione","given":"Joseph","affiliations":[],"preferred":false,"id":694406,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":694402,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kiesecker, Joseph M.","contributorId":146679,"corporation":false,"usgs":false,"family":"Kiesecker","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":694407,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nicot, Jean-Philippe","contributorId":175575,"corporation":false,"usgs":false,"family":"Nicot","given":"Jean-Philippe","email":"","affiliations":[],"preferred":false,"id":694408,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baruch-Mordo, Sharon","contributorId":191830,"corporation":false,"usgs":false,"family":"Baruch-Mordo","given":"Sharon","email":"","affiliations":[],"preferred":false,"id":694409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Entrekin, Sally","contributorId":147949,"corporation":false,"usgs":false,"family":"Entrekin","given":"Sally","affiliations":[{"id":16964,"text":"University of Central Arkansas","active":true,"usgs":false}],"preferred":false,"id":694410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Trainor, Anne","contributorId":191831,"corporation":false,"usgs":false,"family":"Trainor","given":"Anne","affiliations":[],"preferred":false,"id":694411,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Saiers, James","contributorId":191832,"corporation":false,"usgs":false,"family":"Saiers","given":"James","affiliations":[],"preferred":false,"id":694412,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70187434,"text":"ofr20171044 - 2017 - Quality-assurance plan for water-quality activities in the U.S. Geological Survey Washington Water Science Center","interactions":[],"lastModifiedDate":"2017-05-09T10:19:44","indexId":"ofr20171044","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1044","title":"Quality-assurance plan for water-quality activities in the U.S. Geological Survey Washington Water Science Center","docAbstract":"<p class=\"p1\">In accordance with guidelines set forth by the Office of Water Quality in the Water Mission Area of the U.S. Geological Survey, a quality-assurance plan has been created for use by the Washington Water Science Center (WAWSC) in conducting water-quality activities. This qualityassurance plan documents the standards, policies, and procedures used by the WAWSC for activities related to the collection, processing, storage, analysis, and publication of water-quality data. The policies and procedures documented in this quality-assurance plan for water-quality activities complement the quality-assurance plans for surface-water and groundwater activities at the WAWSC. </p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171044","usgsCitation":"Conn, K.E., Huffman, R.L., and Barton, Cynthia, 2017, Quality-assurance plan for water-quality activities in the U.S. Geological Survey Washington Water Science Center: U.S. Geological Survey Open-File Report 2017–1044, 66 p., https://doi.org/10.3133/ofr20171044.","productDescription":"vi, 66 p.","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-083785","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":340969,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1044/ofr20171044.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1044"},{"id":340968,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1044/coverthb.jpg"}],"contact":"<p><a href=\"mailto:dc_wa@usgs.gov\" data-mce-href=\"mailto:dc_wa@usgs.gov\">Director</a>, <a href=\"http://wa.water.usgs.gov\" target=\"blank\" data-mce-href=\"http://wa.water.usgs.gov\">Washington Water Science Center</a><br> U.S. Geological Survey<br> 934 Broadway, Suite 300<br> Tacoma, Washington 98402</p>","tableOfContents":"<ul><li>Abstract<br></li><li>1.0 Introduction<br></li><li>2.0 Organization and Responsibilities<br></li><li>3.0 Program and Project Planning<br></li><li>4.0 Water-Quality Laboratories<br></li><li>5.0 Washington Water Science Center Water-Quality Facilities and Instruments<br></li><li>6.0 Site Selection, Establishment, and Documentation<br></li><li>7.0 Discrete Water-Quality Samples<br></li><li>8.0 Continuous Water-Quality Monitoring<br></li><li>9.0 Data Management and Archival<br></li><li>10.0 Publication of Water-Quality Data<br></li><li>11.0 Water-Quality Training and Reviews<br></li><li>12.0 References<br></li><li>13.0 USGS Memoranda Applicable to Water-Quality Activities<br></li><li>Appendixes A–D<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-05-08","noUsgsAuthors":false,"publicationDate":"2017-05-08","publicationStatus":"PW","scienceBaseUri":"591183b2e4b0e541a03c1a54","contributors":{"authors":[{"text":"Conn, Kathleen E. 0000-0002-2334-6536 kconn@usgs.gov","orcid":"https://orcid.org/0000-0002-2334-6536","contributorId":3923,"corporation":false,"usgs":true,"family":"Conn","given":"Kathleen E.","email":"kconn@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":694018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huffman, Raegan L. 0000-0001-8523-5439 rhuffman@usgs.gov","orcid":"https://orcid.org/0000-0001-8523-5439","contributorId":1638,"corporation":false,"usgs":true,"family":"Huffman","given":"Raegan","email":"rhuffman@usgs.gov","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":694019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barton, Cynthia 0000-0001-8505-4347 cbarton@usgs.gov","orcid":"https://orcid.org/0000-0001-8505-4347","contributorId":3675,"corporation":false,"usgs":true,"family":"Barton","given":"Cynthia","email":"cbarton@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":694020,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70185642,"text":"ofr20171038 - 2017 - Report of the workshop on evidence-based design of national wildlife health programs","interactions":[],"lastModifiedDate":"2017-05-12T09:53:57","indexId":"ofr20171038","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1038","title":"Report of the workshop on evidence-based design of national wildlife health programs","docAbstract":"<h1>Summary</h1><p>This report summarizes a Wildlife Disease Association sponsored workshop held in 2016. The overall objective of the workshop was to use available evidence and selected subject matter expertise to define the essential functions of a National Wildlife Health Program and the resources needed to deliver a robust and reliable program, including the basic infrastructure, workforce, data and information systems, governance, organizational capacity, and essential features, such as wildlife disease surveillance, diagnostic services, and epidemiological investigation. This workshop also provided the means to begin the process of defining the essential attributes of a national wildlife health program that could be scalable and adaptable to each nation’s needs.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171038","collaboration":"Prepared in cooperation with the Wildlife Disease Association","usgsCitation":"Nguyen, N.T., Duff, J.P., Gavier-Widén, D., Grillo, T., He, H., Lee, H., Ratanakorn, P., Rijks, J.M., Ryser-Degiorgis, M.-P., Sleeman, J.M., Stephen, C., Tana, T., Uhart, M., and Zimmer, P., 2017, Report of the workshop on evidence-based design of national wildlife health programs: U.S. Geological Survey Open-File Report 2017–1038, 18 p., https://doi.org/10.3133/ofr20171038.","productDescription":"vi, 18 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-083971","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":340849,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1038/coverthb.jpg"},{"id":340850,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1038/ofr20171038.pdf","text":"Report","size":"811 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1038"}],"contact":"<p>Director, <a href=\"https://www.nwhc.usgs.gov/\" data-mce-href=\"https://www.nwhc.usgs.gov/\">National Wildlife Health Center</a><br> U.S. Geological Survey,<br>6006 Schroeder Road<br> Madison, WI 53711</p>","tableOfContents":"<p>Acknowledgments<br>1. Introduction<br>2.&nbsp;Introductory presentations<br>3.&nbsp;Facilitated small group discussions<br>4.&nbsp;Plenary session on additional need for a national wildlife health program<br>5.&nbsp;Plenary session on key features of a national wildlife health program<br>6.&nbsp;Next steps<br>Selected References<br>Appendixes<br></p>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-05-08","noUsgsAuthors":false,"publicationDate":"2017-05-08","publicationStatus":"PW","scienceBaseUri":"591183b2e4b0e541a03c1a56","contributors":{"authors":[{"text":"Nguyen, Natalie T. 0000-0001-9389-1655","orcid":"https://orcid.org/0000-0001-9389-1655","contributorId":191776,"corporation":false,"usgs":false,"family":"Nguyen","given":"Natalie T.","affiliations":[],"preferred":false,"id":694249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duff, J. Paul","contributorId":113593,"corporation":false,"usgs":true,"family":"Duff","given":"J.","email":"","middleInitial":"Paul","affiliations":[],"preferred":false,"id":694242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gavier-Widen, Dolores","contributorId":112623,"corporation":false,"usgs":true,"family":"Gavier-Widen","given":"Dolores","email":"","affiliations":[],"preferred":false,"id":694247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grillo, Tiggy","contributorId":191774,"corporation":false,"usgs":false,"family":"Grillo","given":"Tiggy","email":"","affiliations":[],"preferred":false,"id":694248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"He, Hongxuan","contributorId":191777,"corporation":false,"usgs":false,"family":"He","given":"Hongxuan","email":"","affiliations":[],"preferred":false,"id":694250,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, Hang","contributorId":175222,"corporation":false,"usgs":false,"family":"Lee","given":"Hang","affiliations":[{"id":27539,"text":"College of Veterinary Medicine, Seoul National University, Seoul, Republic of Korea","active":true,"usgs":false}],"preferred":false,"id":694244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ratanakorn, Parntep","contributorId":191779,"corporation":false,"usgs":false,"family":"Ratanakorn","given":"Parntep","email":"","affiliations":[],"preferred":false,"id":694251,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rijks, Jolianne M.","contributorId":191780,"corporation":false,"usgs":false,"family":"Rijks","given":"Jolianne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":694252,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ryser-Degiorgis, Marie-Pierre","contributorId":191785,"corporation":false,"usgs":false,"family":"Ryser-Degiorgis","given":"Marie-Pierre","email":"","affiliations":[],"preferred":false,"id":694254,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686190,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stephen, Craig","contributorId":168939,"corporation":false,"usgs":false,"family":"Stephen","given":"Craig","email":"","affiliations":[],"preferred":false,"id":694245,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tana, Toni","contributorId":191783,"corporation":false,"usgs":false,"family":"Tana","given":"Toni","email":"","affiliations":[],"preferred":false,"id":694253,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Uhart, Marcela","contributorId":54482,"corporation":false,"usgs":true,"family":"Uhart","given":"Marcela","email":"","affiliations":[],"preferred":false,"id":694246,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Zimmer, Patrick","contributorId":191784,"corporation":false,"usgs":false,"family":"Zimmer","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":694255,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70187525,"text":"70187525 - 2017 - Beyond exposure, sensitivity and adaptive capacity: A response based ecological framework to assess species climate change vulnerability","interactions":[],"lastModifiedDate":"2018-01-04T08:30:15","indexId":"70187525","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5385,"text":"Climate Change Responses","active":true,"publicationSubtype":{"id":10}},"title":"Beyond exposure, sensitivity and adaptive capacity: A response based ecological framework to assess species climate change vulnerability","docAbstract":"As the impacts of global climate change on species are increasingly evident, there is a clear need to adapt conservation efforts worldwide. Species vulnerability assessments (VAs) are increasingly used to summarize all relevant information to determine a species’ potential vulnerability to climate change and are frequently the first step in informing climate adaptation efforts. VAs commonly integrate multiple sources of information by utilizing a framework that distinguishes factors relevant to species exposure, sensitivity, and adaptive capacity. However, this framework was originally developed for human systems, and its use to evaluate species vulnerability has serious practical and theoretical limitations. By instead defining vulnerability as the degree to which a species is unable to exhibit any of the responses necessary for persistence under climate change (i.e., toleration of projected changes, migration to new climate-compatible areas, enduring in microrefugia, and evolutionary adaptation), we can bring VAs into the realm of ecological science without applying borrowed abstract concepts that have consistently challenged species-centric research and management. This response-based framework to assess species vulnerability to climate change allows better integration of relevant ecological data and past research, yielding results with much clearer implications for conservation and research prioritization.","language":"English","publisher":"BioMed Central","doi":"10.1186/s40665-017-0030-y","usgsCitation":"Fortini, L.B., and Schubert, O., 2017, Beyond exposure, sensitivity and adaptive capacity: A response based ecological framework to assess species climate change vulnerability: Climate Change Responses, v. 4, no. 2, 7 p., https://doi.org/10.1186/s40665-017-0030-y.","productDescription":"7 p.","ipdsId":"IP-080117","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":469867,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40665-017-0030-y","text":"Publisher Index Page"},{"id":340884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-20","publicationStatus":"PW","scienceBaseUri":"591183b0e4b0e541a03c1a4c","contributors":{"authors":[{"text":"Fortini, Lucas B. 0000-0002-5781-7295 lfortini@usgs.gov","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":4645,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas","email":"lfortini@usgs.gov","middleInitial":"B.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":694321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schubert, Olivia","contributorId":191810,"corporation":false,"usgs":false,"family":"Schubert","given":"Olivia","email":"","affiliations":[],"preferred":false,"id":694322,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70187518,"text":"70187518 - 2017 - Using publicly available data to quantify plant–pollinator interactions and evaluate conservation seeding mixes in the Northern Great Plains","interactions":[],"lastModifiedDate":"2017-06-01T10:28:51","indexId":"70187518","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1536,"text":"Environmental Entomology","active":true,"publicationSubtype":{"id":10}},"title":"Using publicly available data to quantify plant–pollinator interactions and evaluate conservation seeding mixes in the Northern Great Plains","docAbstract":"<p><span>Concern over declining pollinators has led to multiple conservation initiatives for improving forage for bees in agroecosystems. Using data available through the Pollinator Library (npwrc.usgs.gov/pollinator/), we summarize plant–pollinator interaction data collected from 2012–2015 on lands managed by the U.S. Fish and Wildlife Service and private lands enrolled in U.S. Department of Agriculture conservation programs in eastern North Dakota (ND). Furthermore, we demonstrate how plant–pollinator interaction data from the Pollinator Library and seed cost information can be used to evaluate hypothetical seeding mixes for pollinator habitat enhancements. We summarize records of 314 wild bee and 849 honey bee (</span><i>Apis mellifera</i><span> L.) interactions detected on 63 different plant species. The wild bee observations consisted of 46 species, 15 genera, and 5 families. Over 54% of all wild bee observations were represented by three genera</span><strong>―</strong><i>Bombus</i><span>, </span><i>Lassioglossum</i><span>, and </span><i>Melissodes</i><span>. The most commonly visited forbs by wild bees were </span><i>Monarda fistulosa</i><span>, </span><i>Sonchus arvensis</i><span>, and </span><i>Zizia aurea</i><span>. The most commonly visited forbs by </span><i>A. mellifera</i><span> were </span><i>Cirsium arvense</i><span>, </span><i>Melilotus officinalis</i><span>, and </span><i>Medicago sativa</i><span>. Among all interactions, 13% of </span><i>A. mellifera</i><span> and 77% of wild bee observations were made on plants native to ND. Our seed mix evaluation shows that mixes may often need to be tailored to meet the unique needs of wild bees and managed honey bees in agricultural landscapes. Our evaluation also demonstrates the importance of incorporating both biologic and economic information when attempting to design cost-effective seeding mixes for supporting pollinators in a critically important part of the United States.</span></p>","language":"English","publisher":"Entomological Society of America","doi":"10.1093/ee/nvx070","usgsCitation":"Otto, C., O’Dell, S., Bryant, R.B., Euliss, N., Bush, R., and Smart, M., 2017, Using publicly available data to quantify plant–pollinator interactions and evaluate conservation seeding mixes in the Northern Great Plains: Environmental Entomology, v. 46, no. 3, p. 565-578, https://doi.org/10.1093/ee/nvx070.","productDescription":"14 p.","startPage":"565","endPage":"578","ipdsId":"IP-081790","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":340909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-02","publicationStatus":"PW","scienceBaseUri":"591183b1e4b0e541a03c1a50","contributors":{"authors":[{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Dell, Samuel sodell@usgs.gov","contributorId":152473,"corporation":false,"usgs":true,"family":"O’Dell","given":"Samuel","email":"sodell@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bryant, R. B.","contributorId":191824,"corporation":false,"usgs":false,"family":"Bryant","given":"R.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":694287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Euliss, Ned H. Jr.","contributorId":178233,"corporation":false,"usgs":false,"family":"Euliss","given":"Ned H. Jr.","affiliations":[],"preferred":false,"id":694288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bush, Rachel","contributorId":191796,"corporation":false,"usgs":false,"family":"Bush","given":"Rachel","email":"","affiliations":[],"preferred":false,"id":694289,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smart, Matthew 0000-0003-0711-3035 msmart@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-3035","contributorId":174424,"corporation":false,"usgs":true,"family":"Smart","given":"Matthew","email":"msmart@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694290,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70187326,"text":"ofr20171047 - 2017 - Characterization of peak streamflows and flood inundation at selected areas in North Carolina following Hurricane Matthew, October 2016","interactions":[],"lastModifiedDate":"2017-08-29T15:36:32","indexId":"ofr20171047","displayToPublicDate":"2017-05-05T12:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1047","title":"Characterization of peak streamflows and flood inundation at selected areas in North Carolina following Hurricane Matthew, October 2016","docAbstract":"<p>The passage of Hurricane Matthew through central and eastern North Carolina during October 7–9, 2016, brought heavy rainfall, which resulted in major flooding. More than 15 inches of rain was recorded in some areas. More than 600 roads were closed, including Interstates 95 and 40, and nearly 99,000 structures were affected by floodwaters. Immediately following the flooding, the U.S. Geological Survey documented 267 high-water marks, of which 254 were surveyed. North Carolina Emergency Management documented and surveyed 353 high-water marks. Using a subset of these highwater marks, six flood-inundation maps were created for hard-hit communities. Digital datasets of the inundation areas, study reach boundary, and water-depth rasters are available for download. In addition, peak gage-height data, peak streamflow data, and annual exceedance probabilities (in percent) were determined for 24 U.S. Geological Survey streamgages located near the heavily flooded communities.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171047","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Musser, J.W., Watson, K.M., and Gotvald, A.J., 2017, Characterization of peak streamflows and flood inundation at selected areas in North Carolina following Hurricane Matthew, October 2016 (ver. 2.0, August 2017): U.S. Geological Survey Open-File Report 2017–1047, 23 p., https://doi.org/10.3133/ofr20171047.","productDescription":"Report: v, 23 p.; Data Release, Version History","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085645","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":340658,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75X276T","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood inundation, flood depth, and high-water marks for selected areas in North Carolina from the October 2016 flood"},{"id":340659,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1047/ofr20171047.pdf","text":"Report","size":"4.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1047"},{"id":340657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1047/coverthb3.jpg"},{"id":342197,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1047/versionHist.txt","size":"2.31 MB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"North Carolina, South Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.75,\n              34\n            ],\n            [\n              -76.75,\n              34\n            ],\n            [\n              -76.75,\n              36.116667\n            ],\n            [\n              -79.75,\n              36.116667\n            ],\n            [\n              -79.75,\n              34\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: October 2016; Version 1.1: June 2017; Version 2.0: August 2017","contact":"<p><a href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/water/southatlantic/\" data-mce-href=\"https://www.usgs.gov/water/southatlantic/\">South Atlantic Water Science Center</a><br> U.S. Geological Survey<br> 720 Gracern Road<br> Stephenson Center, Suite 129<br> Columbia, SC 29210</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>General Weather Conditions and Precipitation That Contributed to the October 2016 Flooding</li><li>Methods Used</li><li>Estimated Magnitudes and Flood Exceedance Probabilities of Peak Streamflows</li><li>Flood-Inundation Maps</li><li>Summary</li><li>References Cited</li><li>Glossary</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-05-05","revisedDate":"2017-08-29","noUsgsAuthors":false,"publicationDate":"2017-05-05","publicationStatus":"PW","scienceBaseUri":"590d8f2de4b0e541a03a834a","contributors":{"authors":[{"text":"Musser, Jonathan W. 0000-0002-3543-0807 jwmusser@usgs.gov","orcid":"https://orcid.org/0000-0002-3543-0807","contributorId":2266,"corporation":false,"usgs":true,"family":"Musser","given":"Jonathan","email":"jwmusser@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watson, Kara M. 0000-0002-2685-0260 kmwatson@usgs.gov","orcid":"https://orcid.org/0000-0002-2685-0260","contributorId":2134,"corporation":false,"usgs":true,"family":"Watson","given":"Kara","email":"kmwatson@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gotvald, Anthony J. 0000-0002-9019-750X agotvald@usgs.gov","orcid":"https://orcid.org/0000-0002-9019-750X","contributorId":1970,"corporation":false,"usgs":true,"family":"Gotvald","given":"Anthony","email":"agotvald@usgs.gov","middleInitial":"J.","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":693341,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70187495,"text":"70187495 - 2017 - Oil and gas development influences big-game hunting in Wyoming","interactions":[],"lastModifiedDate":"2017-05-05T11:05:27","indexId":"70187495","displayToPublicDate":"2017-05-05T00:00:00","publicationYear":"2017","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":"Oil and gas development influences big-game hunting in Wyoming","docAbstract":"<p><span>Development from extracting oil and gas resources can have unintended effects on multiple ecosystem functions, with cascading effects on wildlife, ecosystem services, and local economies. Big-game hunting opportunities may be closely related to these effects, but empirical analyses of impacts of energy development on hunting are limited. We examined the influence of oil and gas development density on harvest efficiency, or harvest per unit of hunter effort, within all hunt areas in Wyoming, USA, from 2008 to 2014 for 3 big-game species: elk (</span><i>Cervus canadensis</i><span>), mule deer (</span><i>Odocoileus hemionus</i><span>), and pronghorn (</span><i>Antilocapra americana</i><span>). Using harvest/hunter day as the response variable, we compared linear mixed-effects models for each species that included total well density (i.e., all wells constructed up to the year of record), active well density (i.e., only those wells currently producing oil or gas in that year), or neither as a predictor variable. We used well densities as indicators of development in the absence of data specifying the locations of other oil and gas infrastructure (e.g., roads, well pads). Models also accounted for the fixed effects of road density, hunter density, proportion of the area that is public land with unrestricted hunter access, proportion of the area that is forested, year of observation, and random effects of variation among hunt areas nested within associated game herd units. Presence of oil and gas wells had a positive influence on harvest efficiency for elk and mule deer. Although there was no overall effect to pronghorn, there was a negative influence of wells on juvenile pronghorn harvest efficiency. Changes in harvest efficiency due to expanding oil and gas development could alter the time spent hunting by hunters and their chances of harvesting an animal. This could have subsequent impacts on hunter satisfaction, game populations, and economic revenue generated from recreational hunters.</span></p>","language":"English","publisher":"The Wildlife Society","publisherLocation":"Hoboken, NJ","doi":"10.1002/jwmg.21205","usgsCitation":"Dorning, M., Garman, S.L., Diffendorfer, J., Semmens, D.J., Hawbaker, T., and Bagstad, K.J., 2017, Oil and gas development influences big-game hunting in Wyoming: Journal of Wildlife Management, v. 81, no. 3, p. 379-392, https://doi.org/10.1002/jwmg.21205.","productDescription":"14 p.","startPage":"379","endPage":"392","ipdsId":"IP-075405","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":340855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70182142,"text":"sir20175010 - 2017 - Simulation of groundwater flow in the glacial aquifer system of northeastern Wisconsin with variable model complexity","interactions":[],"lastModifiedDate":"2017-05-04T15:33:55","indexId":"sir20175010","displayToPublicDate":"2017-05-04T12:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5010","title":"Simulation of groundwater flow in the glacial aquifer system of northeastern Wisconsin with variable model complexity","docAbstract":"<p>The U.S. Geological Survey, National Water-Quality Assessment seeks to map estimated intrinsic susceptibility of the glacial aquifer system of the conterminous United States. Improved understanding of the hydrogeologic characteristics that explain spatial patterns of intrinsic susceptibility, commonly inferred from estimates of groundwater age distributions, is sought so that methods used for the estimation process are properly equipped. An important step beyond identifying relevant hydrogeologic datasets, such as glacial geology maps, is to evaluate how incorporation of these resources into process-based models using differing levels of detail could affect resulting simulations of groundwater age distributions and, thus, estimates of intrinsic susceptibility.</p><p>This report describes the construction and calibration of three groundwater-flow models of northeastern Wisconsin that were developed with differing levels of complexity to provide a framework for subsequent evaluations of the effects of process-based model complexity on estimations of groundwater age distributions for withdrawal wells and streams. Preliminary assessments, which focused on the effects of model complexity on simulated water levels and base flows in the glacial aquifer system, illustrate that simulation of vertical gradients using multiple model layers improves simulated heads more in low-permeability units than in high-permeability units. Moreover, simulation of heterogeneous hydraulic conductivity fields in coarse-grained and some fine-grained glacial materials produced a larger improvement in simulated water levels in the glacial aquifer system compared with simulation of uniform hydraulic conductivity within zones. The relation between base flows and model complexity was less clear; however, the relation generally seemed to follow a similar pattern as water levels. Although increased model complexity resulted in improved calibrations, future application of the models using simulated particle tracking is anticipated to evaluate if these model design considerations are similarly important for understanding the primary modeling objective - to simulate reasonable groundwater age distributions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175010","usgsCitation":"Juckem, P.F., Clark, B.R., and Feinstein, D.T., 2017, Simulation of groundwater flow in the glacial aquifer system of northeastern Wisconsin with variable model complexity: U.S. Geological Survey Scientific Investigations Report 2017–5010, 52 p., https://doi.org/10.3133/sir20175010.","productDescription":"viii, 52 p.","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077195","costCenters":[{"id":677,"text":"Wisconsin Water Science 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 \"}}]}","publicComments":"National Water-Quality Assessment","contact":"<p><a href=\"mailto:dc_wiD@usgs.gov\" data-mce-href=\"mailto:dc_wiD@usgs.gov\">Director,</a>&nbsp;<a href=\"https://www.usgs.gov/centers/wisconsin-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/wisconsin-water-science-center\">Wisconsin Water Science Center</a><br>U.S. Geological Survey<br> 8505 Research Way<br> Middleton, WI 53562</p>","tableOfContents":"<ul><li>Foreword</li><li>Abstract</li><li>Introduction</li><li>Conceptual Model of the Groundwater System</li><li>Hydrogeologic Characteristics of the Groundwater-Flow System&nbsp;</li><li>Model Construction</li><li>Model Calibration</li><li>Limitations of the Groundwater-Flow Models&nbsp;</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-05-04","noUsgsAuthors":false,"publicationDate":"2017-05-04","publicationStatus":"PW","scienceBaseUri":"590c3dc6e4b0e541a038dd1d","contributors":{"authors":[{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Brian R. 0000-0001-6611-3807 brclark@usgs.gov","orcid":"https://orcid.org/0000-0001-6611-3807","contributorId":1502,"corporation":false,"usgs":true,"family":"Clark","given":"Brian","email":"brclark@usgs.gov","middleInitial":"R.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":669775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530 dtfeinst@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":1907,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel","email":"dtfeinst@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669776,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70182588,"text":"pp1834 - 2017 - Baseline and projected future carbon storage and carbon fluxes in ecosystems of Hawai‘i","interactions":[],"lastModifiedDate":"2023-12-14T13:39:43.690272","indexId":"pp1834","displayToPublicDate":"2017-05-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1834","title":"Baseline and projected future carbon storage and carbon fluxes in ecosystems of Hawai‘i","docAbstract":"<p>This assessment was conducted to fulfill the requirements of section 712 of the Energy Independence and Security Act of 2007 and to improve understanding of factors influencing carbon balance in ecosystems of Hawai‘i. Ecosystem carbon storage, carbon fluxes, and carbon balance were examined for major terrestrial ecosystems on the seven main Hawaiian islands in two time periods: baseline (from 2007 through 2012) and future (projections from 2012 through 2061). The assessment incorporated observed data, remote sensing, statistical methods, and simulation models. The national assessment has been completed for the conterminous United States, using methodology described in SIR 2010-5233, with results provided in three regional reports (PP 1804, PP 1797, and PP 1897), and for Alaska, with results provided in PP 1826. </p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1834","usgsCitation":"Selmants, P.C., Giardina, C.P., Jacobi, J.D., and Zhu, Zhiliang, eds., 2017, Baseline and projected future carbon storage and carbon fluxes in ecosystems of Hawai‘i: U.S. Geological Survey Professional Paper 1834, 134 p., https://doi.org/10.3133/pp1834.","productDescription":"vii, 134 p.","numberOfPages":"146","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-077242","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":340802,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/pp1787","text":"Professional Paper 1787","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in the Great Plains Region of the United States"},{"id":340799,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/pp1826","text":"Professional Paper 1826","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of Alaska"},{"id":340797,"rank":13,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter8.pdf","text":"Chapter 8. Projected Future Carbon Storage and Carbon Fluxes in Terrestrial Ecosystems of Hawai‘i From Changes in Climate, Land Use, and Disturbance","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Benjamin M. Sleeter, Jinxun Liu, Colin J. Daniel, Todd J. Hawbaker, Tamara S. Wilson, Lucas B. Fortini, James D. Jacobi, Paul C. Selmants, Christian P. Giardina, Creighton M. Litton, and R. Flint Hughes"},{"id":340796,"rank":12,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter7.pdf","text":"Chapter 7. Baseline and Projected Future Aquatic Carbon Fluxes to Nearshore Waters in Hawai‘i","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Richard A. MacKenzie, Ayron M. Strauch, Tracy N. Wiegner, Steven L. Colbert, Edward G. Stets, and Robert G. 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Gon III, and Paul Berkowitz"},{"id":340821,"rank":5,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_executive_summary.pdf","text":"Executive Summary","size":"250 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Paul C. Selmants, Christian P. Giardina, James D. Jacobi, Lucas B. Fortini, R. Flint Hughes, Todd J. Hawbaker, Richard A. MacKenzie, Benjamin M. Sleeter, and Zhiliang Zhu"},{"id":340803,"rank":19,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20105233","text":"Scientific Investigations Report 2010-5233","linkHelpText":"- A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios"},{"id":340798,"rank":14,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter9.pdf","text":"Chapter 9. Hawai‘i Carbon Balance","size":"600 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Paul C. Selmants, Christian P. Giardina, Benjamin M.Sleeter, Jinxun Liu, and Zhiliang Zhu"},{"id":340786,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834.pdf","text":"Report","size":"23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826"},{"id":340787,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1834/coverthb.jpg"},{"id":340788,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_cover.pdf","text":"Covers","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826"},{"id":340789,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_front.pdf","text":"Front Matter","size":"241 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826"},{"id":340790,"rank":6,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter1.pdf","text":"Chapter 1. Scope and Methodology","size":"665 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Christian P. Giardina, Paul C. Selmants, and James D. Jacobi"},{"id":340792,"rank":8,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter3.pdf","text":"Chapter 3. Projecting End-of-Century Shifts in the Spatial Pattern of Plant-Available Water Across Hawai‘i to Assess Implications to Vegetation Shifts","size":"5.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Lucas B. Fortini, James D. Jacobi, and Jonathan P. Price"},{"id":340793,"rank":9,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter4.pdf","text":"Chapter 4. Influence of Invasive Species on Carbon Storage in Hawai‘i’s Ecosystems","size":"620 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By R. Flint Hughes, Gregory P. Asner, Creighton M. Litton, Paul C. Selmants, Todd J. Hawbaker, James D. Jacobi, Christian P. Giardina, and Benjamin M. Sleeter"},{"id":340795,"rank":11,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter6.pdf","text":"Chapter 6. Baseline Carbon Storage and Carbon Fluxes in Terrestrial Ecosystems of Hawai‘i","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Paul C. Selmants, Christian P. Giardina, Sinan Sousan, David E. Knapp, Heather L. Kimball, Todd J. Hawbaker, Alvaro Moreno, Jami Seirer, Steve W. Running, Tomoaki Miura, Rafael Bergstrom, R. Flint Hughes, Creighton M. Litton, and Gregory P. Asner"},{"id":342057,"rank":20,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DB80B9","text":"Hawaii Land Cover and Habitat Status","linkHelpText":"(Chapter 2)"},{"id":340800,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/pp1804","text":"Professional Paper 1804","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Eastern United States"},{"id":340801,"rank":17,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/pp1797","text":"Professional Paper 1797","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Western United States"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"https://www2.usgs.gov/climate_landuse/lcs/\" data-mce-href=\"https://www2.usgs.gov/climate_landuse/lcs/\">Land Change Science Program</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>MS 519A National Center<br>Reston, VA 20192<br></p>","tableOfContents":"<ul><li>Executive Summary<br></li><li>Chapter 1. Scope and Methodology<br></li><li>Chapter 2. Baseline Land Cover<br></li><li>Chapter 3. Projecting End-of-Century Shifts in the Spatial Pattern of Plant-Available Water Across Hawai‘i to Assess Implications to Vegetation Shifts<br></li><li>Chapter 4. Influence of Invasive Species on Carbon Storage in Hawai‘i’s Ecosystems<br></li><li>Chapter 5. Wildland Fires and Greenhouse Gas Emissions in Hawai‘i<br></li><li>Chapter 6. Baseline Carbon Storage and Carbon Fluxes in Terrestrial Ecosystems of Hawai‘i<br></li><li>Chapter 7. Baseline and Projected Future Aquatic Carbon Fluxes to Nearshore Waters in Hawai‘i<br></li><li>Chapter 8. Projected Future Carbon Storage and Carbon Fluxes in Terrestrial Ecosystems of Hawai‘i From Changes in Climate, Land Use, and Disturbance<br></li><li>Chapter 9. Hawai‘i Carbon Balance<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-05-04","noUsgsAuthors":false,"publicationDate":"2017-05-04","publicationStatus":"PW","scienceBaseUri":"590c3dcae4b0e541a038dd27","contributors":{"editors":[{"text":"Selmants, Paul C. 0000-0001-6211-3957 pselmants@usgs.gov","orcid":"https://orcid.org/0000-0001-6211-3957","contributorId":182694,"corporation":false,"usgs":true,"family":"Selmants","given":"Paul C.","email":"pselmants@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":694156,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Giardina, Christian P. 0000-0002-3431-5073","orcid":"https://orcid.org/0000-0002-3431-5073","contributorId":182695,"corporation":false,"usgs":false,"family":"Giardina","given":"Christian","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":694157,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":694158,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true}],"preferred":true,"id":694159,"contributorType":{"id":2,"text":"Editors"},"rank":4}]}}
,{"id":70187355,"text":"ofr20171049 - 2017 - Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada","interactions":[],"lastModifiedDate":"2023-11-03T16:52:08.991249","indexId":"ofr20171049","displayToPublicDate":"2017-05-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1049","title":"Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada","docAbstract":"<p>We map the 385-kilometer (km) long surface trace of the right-lateral, strike-slip Denali Fault between the Totschunda-Denali Fault intersection in Alaska, United States and the village of Haines Junction, Yukon, Canada. In Alaska, digital elevation models based on light detection and ranging and interferometric synthetic aperture radar data enabled our fault mapping at scales of 1:2,000 and 1:10,000, respectively. Lacking such resources in Yukon, we developed new structure-from-motion digital photogrammetry products from legacy aerial photos to map the fault surface trace at a scale of 1:10,000 east of the international border. The section of the fault that we map, referred to as the Eastern Denali Fault, did not rupture during the 2002 Denali Fault earthquake (moment magnitude 7.9). Seismologic, geodetic, and geomorphic evidence, along with a paleoseismic record of past ground-rupturing earthquakes, demonstrate Holocene and contemporary activity on the fault, however. This map of the Eastern Denali Fault surface trace complements other data sets by providing an openly accessible digital interpretation of the location, length, and continuity of the fault’s surface trace based on the accompanying digital topography dataset. Additionally, the digitized fault trace may provide geometric constraints useful for modeling earthquake scenarios and related seismic hazard.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171049","usgsCitation":"Bender, A.M., and Haeussler, P.J., 2017, Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada: U.S. Geological Survey Open-File Report 2017–1049, 10 p., https://doi.org/10.3133/ofr20171049.","productDescription":"iii, 10 p.","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-084514","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":438353,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T151WC","text":"USGS data release","linkHelpText":"Eastern Denali Fault Surface Trace Map, Eastern Alaska and Adjacent Canada, 1978-2008"},{"id":422373,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_105646.htm","linkFileType":{"id":5,"text":"html"}},{"id":340824,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1049/coverthb.jpg"},{"id":340825,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1049/ofr20171049.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1049"}],"country":"Canada, United States","state":"Alaska, Yukon","otherGeospatial":"Denali Fault","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -147,\n              60\n            ],\n            [\n              -135,\n              60\n            ],\n            [\n              -135,\n              64\n            ],\n            [\n              -147,\n              64\n            ],\n            [\n              -147,\n              60\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"http://alaska.usgs.gov/\" data-mce-href=\"http://alaska.usgs.gov/\">Alaska Science Center</a><br>U.S. Geological Survey<br>4210 University Dr.<br>Anchorage, AK 99508<br></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Purpose and Scope<br></li><li>Photogrammetry and Fault Trace Digitization Methods<br></li><li>Digitized Features<br></li><li>Accompanying Files<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-05-04","noUsgsAuthors":false,"publicationDate":"2017-05-04","publicationStatus":"PW","scienceBaseUri":"590c3dc9e4b0e541a038dd25","contributors":{"authors":[{"text":"Bender, Adrian M. 0000-0001-7469-1957 abender@usgs.gov","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":4963,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","email":"abender@usgs.gov","middleInitial":"M.","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":693600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":693601,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70185687,"text":"ofr20161212 - 2017 - The U.S. Geological Survey Monthly Water Balance Model Futures Portal","interactions":[],"lastModifiedDate":"2017-05-03T14:33:53","indexId":"ofr20161212","displayToPublicDate":"2017-05-03T12:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1212","title":"The U.S. Geological Survey Monthly Water Balance Model Futures Portal","docAbstract":"<p>The U.S. Geological Survey Monthly Water Balance Model Futures Portal (<a href=\"https://my.usgs.gov/mows/\" data-mce-href=\"https://my.usgs.gov/mows/\">https://my.usgs.gov/mows/</a>) is a user-friendly interface that summarizes monthly historical and simulated future conditions for seven hydrologic and meteorological variables (actual evapotranspiration, potential evapotranspiration, precipitation, runoff, snow water equivalent, atmospheric temperature, and streamflow) at locations across the conterminous United States (CONUS).</p><p>The estimates of these hydrologic and meteorological variables were derived using a Monthly Water Balance Model (MWBM), a modular system that simulates monthly estimates of components of the hydrologic cycle using monthly precipitation and atmospheric temperature inputs. Precipitation and atmospheric temperature from 222 climate datasets spanning historical conditions (1952 through 2005) and simulated future conditions (2020 through 2099) were summarized for hydrographic features and used to drive the&nbsp;MWBM for the CONUS. The MWBM input and output variables were organized into an open-access database. An Open Geospatial Consortium, Inc., Web Feature Service allows the querying and identification of hydrographic features across the CONUS. To connect the Web Feature Service to the open-access database, a user interface—the Monthly Water Balance Model Futures Portal—was developed to allow the dynamic generation of summary files and plots &nbsp;based on plot type, geographic location, specific climate datasets, period of record, MWBM variable, and other options. Both the plots and the data files are made available to the user for download</p><p>&nbsp;<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161212","collaboration":"Prepared in cooperation with the U.S. Department of the Interior South Central Climate Science Center and the U.S. Environmental Protection Agency","usgsCitation":"Bock, A.R., Hay, L.E., Markstrom, S.L., Emmerich, Chris, and Talbert, Marian, 2017, The U.S. Geological Survey Monthly Water Balance Model Futures Portal: U.S. Geological Survey Open-File Report 2016–1212, 21 p., https://doi.org/10.3133/ofr20161212.","productDescription":"vii, 21 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-079824","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":340150,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1212/ofr20161212.pdf","text":"Report","size":"3.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1212"},{"id":340149,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1212/coverthb.jpg"}],"contact":"<p>Director, USGS Colorado Water Science Center<br>U.S. Geological Survey<br>Box 25046, Mail Stop 415<br>Denver, CO 80225</p><p><a href=\"http://co.water.usgs.gov/\" data-mce-href=\"http://co.water.usgs.gov/\">http://co.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Portal Components</li><li>The Monthly Water Balance Model Futures Portal</li><li>Portal Operation</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Bias-Corrected Spatially Disaggregated CMIP3 Projection Ensembles Accessible in the Monthly Water Balance Model Futures Portal</li><li>Appendix 2. Bias-Corrected Spatially Disaggregated CMIP5 Projection Ensembles Accessible in Monthly Water Balance Model Futures Portal</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2017-05-03","noUsgsAuthors":false,"publicationDate":"2017-05-03","publicationStatus":"PW","scienceBaseUri":"590aec43e4b0fc4e4492ab9b","contributors":{"authors":[{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":686396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":686397,"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":1986,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven L.","email":"markstro@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":686398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Emmerich, Christopher emmerichc@usgs.gov","contributorId":189893,"corporation":false,"usgs":true,"family":"Emmerich","given":"Christopher","email":"emmerichc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":686399,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Talbert, Marian mtalbert@usgs.gov","contributorId":5180,"corporation":false,"usgs":true,"family":"Talbert","given":"Marian","email":"mtalbert@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":false,"id":692511,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70187427,"text":"70187427 - 2017 - Designing ecological climate change impact assessments to reflect key climatic drivers","interactions":[],"lastModifiedDate":"2017-06-07T10:15:21","indexId":"70187427","displayToPublicDate":"2017-05-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Designing ecological climate change impact assessments to reflect key climatic drivers","docAbstract":"<div class=\"article-section__content mainAbstract\"><p>Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.</p></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13653","usgsCitation":"Sofaer, H., Barsugli, J.J., Jarnevich, C.S., Abatzoglou, J.T., Talbert, M., Miller, B.W., and Morisette, J.T., 2017, Designing ecological climate change impact assessments to reflect key climatic drivers: Global Change Biology, v. 23, no. 7, p. 2537-2553, https://doi.org/10.1111/gcb.13653.","productDescription":"17 p.","startPage":"2537","endPage":"2553","ipdsId":"IP-079685","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":340760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-06","publicationStatus":"PW","scienceBaseUri":"590aec45e4b0fc4e4492ab9f","contributors":{"authors":[{"text":"Sofaer, Helen 0000-0002-9450-5223 hsofaer@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":169118,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"hsofaer@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":694009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barsugli, Joseph J.","contributorId":191728,"corporation":false,"usgs":false,"family":"Barsugli","given":"Joseph","email":"","middleInitial":"J.","affiliations":[{"id":17861,"text":"NOAA/Earth System Research Laboratory/Physical Sciences Division, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":694010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":694011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abatzoglou, John T.","contributorId":191729,"corporation":false,"usgs":false,"family":"Abatzoglou","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":33345,"text":" University of Idaho","active":true,"usgs":false}],"preferred":false,"id":694012,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Talbert, Marian 0000-0003-0588-0265 mtalbert@usgs.gov","orcid":"https://orcid.org/0000-0003-0588-0265","contributorId":191730,"corporation":false,"usgs":true,"family":"Talbert","given":"Marian","email":"mtalbert@usgs.gov","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":false,"id":694013,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Brian W. 0000-0003-1716-1161 bwmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":191731,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"bwmiller@usgs.gov","middleInitial":"W.","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":false,"id":694014,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":694015,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70187426,"text":"70187426 - 2017 - Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants","interactions":[],"lastModifiedDate":"2017-06-01T10:27:32","indexId":"70187426","displayToPublicDate":"2017-05-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants","docAbstract":"<p><strong>Aim</strong></p><p>The distributions of exotic species reflect patterns of human-mediated dispersal, species climatic tolerances and a suite of other biotic and abiotic factors. The relative importance of each of these factors will shape how the spread of exotic species is affected by ongoing economic globalization and climate change. However, patterns of trade may be correlated with variation in scientific sampling effort globally, potentially confounding studies that do not account for sampling patterns.</p><p><strong>Location</strong></p><p>Global.</p><p><strong>Time period</strong></p><p>Museum records, generally from the 1800s up to 2015.</p><p><strong>Major taxa studied</strong></p><p>Plant species exotic to the United States.</p><p><strong>Methods</strong></p><p>We used data from the Global Biodiversity Information Facility (GBIF) to summarize the number of plant species with exotic occurrences in the United States that also occur in each other country world-wide. We assessed the relative importance of trade and climatic similarity for explaining variation in the number of shared species while evaluating several methods to account for variation in sampling effort among countries.</p><p><strong>Results</strong></p><p>Accounting for variation in sampling effort reversed the relative importance of trade and climate for explaining numbers of shared species. Trade was strongly correlated with numbers of shared U.S. exotic plants between the United States and other countries before, but not after, accounting for sampling variation among countries. Conversely, accounting for sampling effort strengthened the relationship between climatic similarity and species sharing. Using the number of records as a measure of sampling effort provided a straightforward approach for the analysis of occurrence data, whereas species richness estimators and rarefaction were less effective at removing sampling bias.</p><p><strong>Main conclusions</strong></p><p>Our work provides support for broad-scale climatic limitation on the distributions of exotic species, illustrates the need to account for variation in sampling effort in large biodiversity databases, and highlights the difficulty in inferring causal links between the economic drivers of invasion and global patterns of exotic species occurrence.</p>","language":"English","publisher":"Wiley","doi":"10.1111/geb.12577","usgsCitation":"Sofaer, H., and Jarnevich, C.S., 2017, Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants: Global Ecology and Biogeography, v. 26, no. 6, p. 669-678, https://doi.org/10.1111/geb.12577.","productDescription":"10 p.","startPage":"669","endPage":"678","ipdsId":"IP-076101","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":438354,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z31WSS","text":"USGS data release","linkHelpText":"Data associated with Sofaer and Jarnevich 'Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants'"},{"id":340761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-20","publicationStatus":"PW","scienceBaseUri":"590aec46e4b0fc4e4492aba1","contributors":{"authors":[{"text":"Sofaer, Helen 0000-0002-9450-5223 hsofaer@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":169118,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"hsofaer@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":694007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":694008,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70184212,"text":"gip172 - 2017 - Land change monitoring, assessment, and projection (LCMAP) revolutionizes land cover and land change research","interactions":[],"lastModifiedDate":"2017-05-03T10:03:12","indexId":"gip172","displayToPublicDate":"2017-05-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"172","title":"Land change monitoring, assessment, and projection (LCMAP) revolutionizes land cover and land change research","docAbstract":"<p>When nature and humanity change Earth’s landscapes - through flood or fire, public policy, natural resources management, or economic development - the results are often dramatic and lasting.</p><p>Wildfires can reshape ecosystems. Hurricanes with names like Sandy or Katrina will howl for days while altering the landscape for years. One growing season in the evolution of drought-resistant genetics can transform semiarid landscapes into farm fields.</p><p>In the past, valuable land cover maps created for understanding the effects of those events - whether changes in wildlife habitat, water-quality impacts, or the role land use and land cover play in affecting weather and climate - came out at best every 5 to 7 years. Those high quality, high resolution maps were good, but users always craved more: even higher quality data, additional land cover and land change variables, more detailed legends, and most importantly, more frequent land change information.</p><p>Now a bold new initiative called Land Change Monitoring, Assessment, and Projection (LCMAP) promises to fulfill that demand.</p><p>Developed at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, LCMAP provides definitive, timely information on how, why, and where the planet is changing. LCMAP’s continuous monitoring process can detect changes as they happen every day that Landsat satellites acquire clear observations. The result will be to place near real-time information in the hands of land and resource managers who need to understand the effects these changes have on landscapes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip172","usgsCitation":"Young, S.M., 2017, Land Change Monitoring, Assessment, and Projection (LCMAP) revolutionizes land cover and land change research: U.S. Geological Survey General Information Product 172, 4 p., https://doi.org/10.3133/gip172.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-083103","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":340452,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0172/coverthb.jpg"},{"id":340453,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0172/gip172.pdf","size":"7.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 172"}],"contact":"<p>Director,&nbsp;Earth Resources Observation and Science (EROS) Center<br>U.S. Geological Survey<br>47914 252nd Street<br>Sioux Falls, SD 57198</p><p><a href=\"https://eros.usgs.gov\" data-mce-href=\"https://eros.usgs.gov\">https://eros.usgs.gov</a></p>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2017-05-02","noUsgsAuthors":false,"publicationDate":"2017-05-02","publicationStatus":"PW","scienceBaseUri":"59099aade4b0fc4e449157e6","contributors":{"authors":[{"text":"Young, Steven 0000-0002-7904-9696 steven.young.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-7904-9696","contributorId":173131,"corporation":false,"usgs":true,"family":"Young","given":"Steven","email":"steven.young.ctr@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":680572,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70200519,"text":"70200519 - 2017 - Developing an effective Agassiz's Desert Tortoise monitoring program: Final report to the Coachella Valley Conservation Commission","interactions":[],"lastModifiedDate":"2018-10-23T14:57:38","indexId":"70200519","displayToPublicDate":"2017-05-01T14:57:19","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Developing an effective Agassiz's Desert Tortoise monitoring program: Final report to the Coachella Valley Conservation Commission","docAbstract":"<p>Agassiz’s desert tortoise (Gopherus agassizii) is a conservation-reliant species with populations north and west of the Colorado River protected as threatened under the Endangered Species Act (Averill-Murray et al. 2012). Since it was listed under this category in 1990, a great deal has been learned about the natural history of the species, and it is now one of the best-studied turtles in the United States (Lovich and Ennen 2013). However, the accumulated body of scientific data available for the species has not yet been translated into recovery or delisting of the species. Successful conservation of any species requires knowledge of their natural history and how vital rates affect their ability to maintain stable populations in the face of natural and anthropogenic stresses. </p><p>Agassiz’s desert tortoises occur from southwestern Utah to near the Mexican border in California – a distance of over 450 km – but population densities vary greatly across this immense landscape (U.S. Fish and Wildlife Service 2015). Tortoises occur in the Sonoran Desert of California, including the eastern and western ends of the Coachella Valley, where it is one of 27 species covered under the Coachella Valley Multiple Species Habitat Conservation Plan and Natural Community Conservation Plan (CVMSHCP/NCCP). The southern portion of Joshua Tree National Park (JTNP) lies within this 1.1 million acre planning area, and was predicted to be an area of low-density tortoise populations using habitat suitability modeling (Barrows 2011). JTNP is near the southern distributional limit of G. agassizii, yet very little has been published regarding the ecology of tortoises in the Sonoran Desert of California.</p><p>Reproductive output is an important gross measure of the ability of a population to persist. When integrated with data on fertility and survivorship, this information forms a foundation for assessing population status and formulating effective management strategies (e.g., Congdon et al. 1993, 1994), especially for imperiled species. One aspect of the biology of G. agassizii that has been particularly well-studied is reproductive output. However, most of what we know about this topic comes from research in the Mojave Desert portion of the species’ range (Ernst and Lovich 2009). Comparatively little has been published on the reproductive ecology of populations living in the Sonoran Desert ecosystem of California. Publications by Lovich et al. (1999, 2011, 2012, 2014, 2015) constitute the main body of literature on desert tortoise reproductive ecology in the Sonoran Desert of California, with one study population located at the western end of the CVMSHCP/NCCP area. Collecting data on Agassiz’s desert tortoise ecology in the Sonoran Desert ecosystem is important due to significant differences between the two adjacent desert ecosystems, especially the timing and amounts of annual precipitation, and their potential effects on reproductive output (e.g., Lovich et al. 5 2015). There are also differences in the vulnerability of tortoises to the effects of a warming, drying climate between the two deserts (Barrows 2011; Zylstra et al. 2012). </p><p>The overall goal of this study was to collect data on demography, reproductive output, and genetic affinities at a study site in the Sonoran Desert portion of JTNP in the eastern end of the CVMSHCP/NCCP area. Specific objectives included: 1) Collect data to establish baselines on tortoise populations and/or their habitat suitability in core habitat within the CVNCCP area, including biotic and abiotic variables affecting persistence of tortoise populations; 2) Compare and contrast with data collected on desert tortoises at USGS/BLM study site near Palm Springs over 16 years; 3) Support long-term modeling efforts needed to determine tortoise population viability; 4) Refine modeled relationships with identified threats such as fire, invasive species and climate change; and 5) Prioritize adaptive management needs for the desert tortoise in and beyond the CVNCCP area. The data from this study will aid in determining baseline estimates of the desert tortoise population size within the planning area as well as establish a marked population of Agassiz’s desert tortoises for future monitoring. Data will be integrated with habitat modeling in order to refine model output. Genetic data will be collected on both the north and south sides of Interstate 10 to determine the potential effects of habitat fragmentation and genetic mixing. Analyses are ongoing and results beyond those presented in this report will be published in peer-reviewed scientific journals following inclusion of additional data collected on the south side of Shavers Valley in 2017-2018. </p>","language":"English","publisher":"Coachella Valley Conservation Commission","usgsCitation":"Lovich, J.E., and Puffer, S., 2017, Developing an effective Agassiz's Desert Tortoise monitoring program: Final report to the Coachella Valley Conservation Commission, 26 p.","productDescription":"26 p.","ipdsId":"IP-088374","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":358690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358644,"type":{"id":11,"text":"Document"},"url":"https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=152890&inline"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10ac2ce4b034bf6a7e6966","contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":749275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Puffer, Shellie R. 0000-0003-4957-0963","orcid":"https://orcid.org/0000-0003-4957-0963","contributorId":193099,"corporation":false,"usgs":true,"family":"Puffer","given":"Shellie R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":749276,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70261470,"text":"70261470 - 2017 - Annual review 2016: Exploration review","interactions":[],"lastModifiedDate":"2024-12-11T16:58:29.035525","indexId":"70261470","displayToPublicDate":"2017-05-01T10:56:34","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2755,"text":"Mining Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Annual review 2016: Exploration review","docAbstract":"This summary of international mineral exploration activities for the year 2016 draws upon information from industry sources, published literature, SNL Metals & Mining (SNL), an offering of S&P Global Market Intelligence (New York, NY), and specialists in the U.S. Geological Survey (USGS) National Minerals Information Center. Three types of information are reported and analyzed in this annual review of international exploration: 1) budgetary statistics expressed in U.S. dollars provided by SNL; 2) regional and site-specific exploration activities that took place in 2016 as compiled by the USGS and 3) regional events and legislation that affected exploration activities including economic, social and political conditions, which were derived from published sources and discussions with USGS and industry specialists. Commodity and regional compilations are presented in this summary. Because multiple sources were used to develop commodity and regional compilations, statistics may vary depending on the source and type of data that are being reported.","language":"English","publisher":"Society for Mining, Metallurgy, & Exploration","usgsCitation":"Karl, N.A., and Wilburn, D.R., 2017, Annual review 2016: Exploration review: Mining Engineering, v. 69, no. 5, p. 28-49.","productDescription":"22 p.","startPage":"28","endPage":"49","ipdsId":"IP-085928","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":464992,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://me.smenet.org/abstract.cfm?preview=1&articleID=7513&page=28","linkFileType":{"id":5,"text":"html"}},{"id":465021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karl, Nick A 0000-0003-2858-2498","orcid":"https://orcid.org/0000-0003-2858-2498","contributorId":246006,"corporation":false,"usgs":true,"family":"Karl","given":"Nick","email":"","middleInitial":"A","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":920667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilburn, David R. 0000-0002-5371-7617 wilburn@usgs.gov","orcid":"https://orcid.org/0000-0002-5371-7617","contributorId":1755,"corporation":false,"usgs":true,"family":"Wilburn","given":"David","email":"wilburn@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":920668,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70193094,"text":"70193094 - 2017 - PRISM Software: Processing and Review Interface for Strong‐Motion Data","interactions":[],"lastModifiedDate":"2017-10-31T10:51:32","indexId":"70193094","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"PRISM Software: Processing and Review Interface for Strong‐Motion Data","docAbstract":"<p><span>A continually increasing number of high‐quality digital strong‐motion records from stations of the National Strong Motion Project (NSMP) of the U.S. Geological Survey, as well as data from regional seismic networks within the United States, calls for automated processing of strong‐motion records with human review limited to selected significant or flagged records. The NSMP has developed the Processing and Review Interface for Strong Motion data (PRISM) software to meet this need. In combination with the Advanced National Seismic System Quake Monitoring System (AQMS), PRISM automates the processing of strong‐motion records. When used without AQMS, PRISM provides batch‐processing capabilities. The PRISM software is platform independent (coded in Java), open source, and does not depend on any closed‐source or proprietary software. The software consists of two major components: a record processing engine composed of modules for each processing step, and a review tool, which is a graphical user interface for manual review, edit, and processing. To facilitate use by non‐NSMP earthquake engineers and scientists, PRISM (both its processing engine and review tool) is easy to install and run as a stand‐alone system on common operating systems such as Linux, OS X, and Windows. PRISM was designed to be flexible and extensible to accommodate implementation of new processing techniques. All the computing features have been thoroughly tested.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160200","usgsCitation":"Jones, J.M., Kalkan, E., Stephens, C.D., and Ng, P., 2017, PRISM Software: Processing and Review Interface for Strong‐Motion Data: Seismological Research Letters, v. 88, no. 3, p. 851-866, https://doi.org/10.1785/0220160200.","productDescription":"16 p.","startPage":"851","endPage":"866","ipdsId":"IP-066608","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-22","publicationStatus":"PW","scienceBaseUri":"59f98bb7e4b0531197af9fee","contributors":{"authors":[{"text":"Jones, Jeanne M. 0000-0001-7549-9270 jmjones@usgs.gov","orcid":"https://orcid.org/0000-0001-7549-9270","contributorId":4676,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","email":"jmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":717964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":717963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stephens, Christopher D. 0000-0003-0858-3709 cdstephens@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-3709","contributorId":2788,"corporation":false,"usgs":true,"family":"Stephens","given":"Christopher","email":"cdstephens@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":717965,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ng, Peter 0000-0001-8509-5544 png@usgs.gov","orcid":"https://orcid.org/0000-0001-8509-5544","contributorId":3317,"corporation":false,"usgs":true,"family":"Ng","given":"Peter","email":"png@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":717966,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192141,"text":"70192141 - 2017 - Reconstructing a herbivore’s diet using a novel rbcL DNA mini-barcode for plants","interactions":[],"lastModifiedDate":"2018-03-29T13:32:36","indexId":"70192141","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5538,"text":"AoB PLANTS","active":true,"publicationSubtype":{"id":10}},"title":"Reconstructing a herbivore’s diet using a novel rbcL DNA mini-barcode for plants","docAbstract":"<p><span>Next Generation Sequencing and the application of metagenomic analyses can be used to answer questions about animal diet choice and study the consequences of selective foraging by herbivores. The quantification of herbivore diet choice with respect to native versus exotic plant species is particularly relevant given concerns of invasive species establishment and their effects on ecosystems. While increased abundance of white-tailed deer (</span><i>Odocoileus virginianus</i><span>) appears to correlate with increased incidence of invasive plant species, data supporting a causal link is scarce. We used a metabarcoding approach (PCR amplicons of the plant<span>&nbsp;</span></span><i>rbc</i><span>L gene) to survey the diet of white-tailed deer (fecal samples), from a forested site in Warren County, Virginia with a comprehensive plant species inventory and corresponding reference collection of plant barcode and chloroplast sequences. We sampled fecal pellet piles and extracted DNA from 12 individual deer in October 2014. These samples were compared to a reference DNA library of plant species collected within the study area. For 72 % of the amplicons, we were able to assign taxonomy at the species level, which provides for the first time—sufficient taxonomic resolution to quantify the relative frequency at which native and exotic plant species are being consumed by white-tailed deer. For each of the 12 individual deer we collected three subsamples from the same fecal sample, resulting in sequencing 36 total samples. Using Qiime, we quantified the plant DNA found in all 36 samples, and found that variance within samples was less than variance between samples (</span><i>F</i><span> = 1.73,<span>&nbsp;</span></span><i>P</i><span> = 0.004), indicating additional subsamples may not be necessary. Species level diversity ranged from 60 to 93 OTUs per individual and nearly 70 % of all plant sequences recovered were from native plant species. The number of species detected did reduce significantly (range 4–12) when we excluded species whose OTU composed &lt;1 % of each sample’s total. When compared to the abundance of native and non-natives plants inventoried in the local community, our results support the observation that white-tailed deer have strong foraging preferences, but these preferences were not consistent for species in either class. Deer forage behaviour may favour some exotic species, but not all.</span></p>","language":"English","publisher":"Oxford University Press","doi":"10.1093/aobpla/plx015","usgsCitation":"Erickson, D.L., Reed, E., Ramachandran, P., Bourg, N., McShea, W.J., and Ottesen, A., 2017, Reconstructing a herbivore’s diet using a novel rbcL DNA mini-barcode for plants: AoB PLANTS, v. 9, no. 3, p. 1-17, https://doi.org/10.1093/aobpla/plx015.","productDescription":"Article plx015; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-084958","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/aobpla/plx015","text":"Publisher Index Page"},{"id":352162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-21","publicationStatus":"PW","scienceBaseUri":"5afee886e4b0da30c1bfc464","contributors":{"authors":[{"text":"Erickson, David L.","contributorId":197853,"corporation":false,"usgs":false,"family":"Erickson","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":714429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Elizabeth","contributorId":197854,"corporation":false,"usgs":false,"family":"Reed","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":714430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramachandran, Padmini","contributorId":197855,"corporation":false,"usgs":false,"family":"Ramachandran","given":"Padmini","email":"","affiliations":[],"preferred":false,"id":714431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bourg, Norman 0000-0002-7443-1992 nbourg@usgs.gov","orcid":"https://orcid.org/0000-0002-7443-1992","contributorId":197809,"corporation":false,"usgs":true,"family":"Bourg","given":"Norman","email":"nbourg@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":714428,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McShea, William J.","contributorId":197834,"corporation":false,"usgs":false,"family":"McShea","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714432,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ottesen, Andrea","contributorId":197856,"corporation":false,"usgs":false,"family":"Ottesen","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":714433,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70191275,"text":"70191275 - 2017 - National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project","interactions":[],"lastModifiedDate":"2017-10-03T11:47:48","indexId":"70191275","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NETN/NRR—2017/1437","title":"National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project","docAbstract":"<p><span>The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program classifies, describes, and maps existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&amp;M) Program. The NPS VMI Program is managed by the NPS I&amp;M Division and provides baseline vegetation information to the NPS Natural Resource I&amp;M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Northeast Temperate Network, and NPS Appalachian National Scenic Trail (APPA) have completed vegetation classification and mapping of APPA for the NPS VMI Program.</span><br><br><span>Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of APPA and to determine how best to map the vegetation types by using aerial imagery. Analyses of data from 1,618 vegetation plots were used to describe USNVC associations of APPA. Data from 289 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Data from 269 validation sites were collected to assess vegetation mapping prior to submitting the vegetation map for accuracy assessment (AA). Data from 3,265 AA sites were collected, of which 3,204 were used to test accuracy of the vegetation map layer. The collective of these datasets affirmed 280 USNVC associations for the APPA vegetation mapping project.</span><br><br><span>To map the vegetation and land cover of APPA, 169 map classes were developed. The 169 map classes consist of 150 that represent natural (including ruderal) vegetation types in the USNVC, 11 that represent cultural (agricultural and developed) vegetation types in the USNVC, 5 that represent natural landscapes with catastrophic disturbance or some other modification to natural vegetation preventing accurate classification in the USNVC, and 3 that represent nonvegetated water (non-USNVC). Features were interpreted from viewing 4-band digital aerial imagery using digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). (Digital aerial imagery was collected each fall during 2009–11 to capture leaf-phenology change of hardwood trees across the latitudinal range of APPA.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in GIS. Polygon units were mapped to either a 0.5-hectare (ha) or 0.25-ha minimum mapping unit, depending on vegetation type or scenario; however, polygon units were mapped to 0.1 ha for alpine vegetation.</span><br><br><span>A geodatabase containing various feature-class layers and tables provide locations and support data to USNVC vegetation types (vegetation map layer), vegetation plots, verification sites, validation sites, AA sites, project boundary extent and zones, and aerial image centers and flight lines. The feature-class layer and related tables of the vegetation map layer provide 30,395 polygons of detailed attribute data covering 110,919.7 ha, with an average polygon size of 3.6 ha; the vegetation map coincides closely with the administrative boundary for APPA.</span><br><br><span>Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 28,242 polygons (92.9% of polygons) and cover 106,413.0 ha (95.9%) of the map extent for APPA. The map layer indicates APPA to be 92.4% forest and woodland (102,480.8 ha), 1.7% shrubland (1866.3 ha), and 1.8% herbaceous cover (2,065.9 ha). Map classes representing park-special vegetation (undefined in the USNVC) apply to 58 polygons (0.2% of polygons) and cover 404.3 ha (0.4%) of the map extent. Map classes representing USNVC cultural types apply to 1,777 polygons (5.8% of polygons) and cover 2,516.3 ha (2.3%) of the map extent. Map classes representing nonvegetated water (non-USNVC) apply to 332 polygons (1.1% of polygons) and cover 1,586.2 ha (1.4%) of the map extent.</span></p>","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Hop, K.D., Strassman, A.C., Hall, M., Menard, S., Largay, E., Sattler, S., Hoy, E.E., Ruhser, J., Hlavacek, E., and Dieck, J., 2017, National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project: Natural Resource Report NPS/NETN/NRR—2017/1437, 1620 p.","productDescription":"1620 p.","ipdsId":"IP-082135","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":346348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346344,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2240273"}],"country":"United States","otherGeospatial":"Appalachian National Scenic Trail","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d4a1a9e4b05fe04cc4e0fb","contributors":{"authors":[{"text":"Hop, Kevin D. 0000-0002-9928-4773 khop@usgs.gov","orcid":"https://orcid.org/0000-0002-9928-4773","contributorId":1438,"corporation":false,"usgs":true,"family":"Hop","given":"Kevin","email":"khop@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strassman, Andrew C. 0000-0002-9792-7181 astrassman@usgs.gov","orcid":"https://orcid.org/0000-0002-9792-7181","contributorId":4575,"corporation":false,"usgs":true,"family":"Strassman","given":"Andrew","email":"astrassman@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Mark","contributorId":196864,"corporation":false,"usgs":false,"family":"Hall","given":"Mark","email":"","affiliations":[],"preferred":false,"id":711820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Menard, Shannon","contributorId":167864,"corporation":false,"usgs":false,"family":"Menard","given":"Shannon","email":"","affiliations":[{"id":17658,"text":"NatureServe","active":true,"usgs":false}],"preferred":false,"id":711821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Largay, Ery","contributorId":196865,"corporation":false,"usgs":false,"family":"Largay","given":"Ery","email":"","affiliations":[],"preferred":false,"id":711822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sattler, Stephanie 0000-0003-4417-2480 ssattler@usgs.gov","orcid":"https://orcid.org/0000-0003-4417-2480","contributorId":191016,"corporation":false,"usgs":true,"family":"Sattler","given":"Stephanie","email":"ssattler@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711823,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hoy, Erin E. 0000-0002-2853-3242 ehoy@usgs.gov","orcid":"https://orcid.org/0000-0002-2853-3242","contributorId":4523,"corporation":false,"usgs":true,"family":"Hoy","given":"Erin","email":"ehoy@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711824,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ruhser, Janis 0000-0001-9987-2578 jruhser@usgs.gov","orcid":"https://orcid.org/0000-0001-9987-2578","contributorId":149646,"corporation":false,"usgs":true,"family":"Ruhser","given":"Janis","email":"jruhser@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711825,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hlavacek, Enrika 0000-0002-9872-2305 ehlavacek@usgs.gov","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":149114,"corporation":false,"usgs":true,"family":"Hlavacek","given":"Enrika","email":"ehlavacek@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711826,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dieck, Jennifer 0000-0002-4388-4534 jdieck@usgs.gov","orcid":"https://orcid.org/0000-0002-4388-4534","contributorId":149647,"corporation":false,"usgs":true,"family":"Dieck","given":"Jennifer","email":"jdieck@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711827,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70187141,"text":"ofr20171029 - 2017 - Guidelines for preparation of State water-use estimates for 2015","interactions":[],"lastModifiedDate":"2017-05-02T08:59:14","indexId":"ofr20171029","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1029","title":"Guidelines for preparation of State water-use estimates for 2015","docAbstract":"<p>The U.S. Geological Survey (USGS) has estimated the use of water in the United States at 5-year intervals since 1950. This report describes the water-use categories and data elements used for the national water-use compilation conducted as part of the USGS National Water-Use Science Project. The report identifies sources of water-use information, provides standard methods and techniques for estimating water use at the county level, and outlines steps for preparing documentation for the United States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands.</p><p>As part of this USGS program to document water use on a national scale, estimates of water withdrawals for the categories of public supply, self-supplied domestic, industrial, irrigation, and thermoelectric power are prepared for each county in each State, District, or territory by using the guidelines in this report. County estimates of water withdrawals for aquaculture, livestock, and mining are prepared for each State by using a county-based national model, although water-use programs in each State or Water Science Center have the option of producing independent county estimates of water withdrawals for these categories. Estimates of water withdrawals and consumptive use for thermoelectric power will be aggregated to the county level for each State by the national project; additionally, irrigation consumptive use at the county level will also be provided, although study chiefs in each State have the option of producing independent county estimates of water withdrawals and consumptive use for these categories.</p><p>Estimates of deliveries of water from public supplies for domestic use by county also will be prepared for each State. As a result, total domestic water use can be determined for each State by combining self-supplied domestic withdrawals and public-supplied domestic deliveries. Fresh groundwater and surface-water estimates will be prepared for all categories of use, and saline groundwater and surface-water estimates by county will be prepared for the categories of public supply, industrial, mining, and thermoelectric power. Power production for thermoelectric power and irrigated acres by irrigation system type will be compiled. If data are available, reclaimed-wastewater use will be compiled for the public-supply, industrial, mining, thermoelectric-power, and irrigation categories.</p><p>Optional water-use categories are commercial, hydroelectric power, and wastewater treatment. Optional data elements are public-supply deliveries to commercial, industrial, and thermoelectric-power users; consumptive use (for categories other than thermoelectric power and irrigation); irrigation conveyance loss; and number of facilities. Aggregation of water-use data by stream basin (eight-digit hydrologic unit code) and principal aquifers also is optional.</p><p>Water-use data compiled by the States will be stored in the USGS Aggregate Water-Use Data System (AWUDS). This database is a comprehensive aggregated database designed to store mandatory and optional data elements. AWUDS contains several routines that can be used for quality assurance and quality control of the data, and AWUDS produces tables of water-use data from the previous compilations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171029","collaboration":"National Water-Use Science Project","usgsCitation":"Bradley, M.W., comp., 2017, Guidelines for preparation of State water-use estimates for 2015: U.S. Geological Survey Open-File Report 2017–1029, 54 p., https://doi.org/10.3133/ofr20171029.","productDescription":"viii, 54 p.","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-078880","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":340450,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1029/coverthb2.jpg"},{"id":340259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1029/ofr20171029.pdf","text":"Report","size":"719 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1029"},{"id":340258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1029/coverthb.jpg"}],"contact":"<p>Director, Lower Mississippi-Gulf Water Science Center—Tennessee <br>640 Grassmere&nbsp;Park<br>Suite 100<br>Nashville, TN 37211</p><p><a href=\"https://tn.water.usgs.gov/\" data-mce-href=\"https://tn.water.usgs.gov/\">https://tn.water.usgs.gov</a>/</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Water-Use Compilation Requirements<br></li><li>Compilation Methods<br></li><li>Public Supply<br></li><li>Self-Supplied Domestic<br></li><li>Commercial<br></li><li>Industrial<br></li><li>Thermoelectric Power<br></li><li>Mining<br></li><li>Livestock<br></li><li>Aquaculture<br></li><li>Irrigation<br></li><li>Hydroelectric Power<br></li><li>Wastewater Treatment<br></li><li>Reservoir Evaporation<br></li><li>References<br></li><li>Glossary<br></li><li>Appendix 1. Coding Forms for the Compilation of Water-Use Data<br></li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2017-05-01","noUsgsAuthors":false,"publicationDate":"2017-05-01","publicationStatus":"PW","scienceBaseUri":"59084922e4b0fc4e448ffd40","contributors":{"compilers":[{"text":"Bradley, Mike 0000-0002-2979-265X mbradley@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-265X","contributorId":582,"corporation":false,"usgs":true,"family":"Bradley","given":"Mike","email":"mbradley@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":692793,"contributorType":{"id":3,"text":"Compilers"},"rank":1}]}}
]}