{"pageNumber":"301","pageRowStart":"7500","pageSize":"25","recordCount":46706,"records":[{"id":70202324,"text":"fs20193007 - 2019 - The Earth Mapping Resources Initiative (Earth MRI): Mapping the Nation’s critical mineral resources","interactions":[],"lastModifiedDate":"2019-09-13T13:31:42","indexId":"fs20193007","displayToPublicDate":"2019-02-25T11:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3007","displayTitle":"The Earth Mapping Resources Initiative (Earth MRI): Mapping the Nation’s Critical Mineral Resources","title":"The Earth Mapping Resources Initiative (Earth MRI): Mapping the Nation’s critical mineral resources","docAbstract":"<p>The Earth Mapping Resources Initiative (Earth MRI; formerly known as 3DEEP) is planned as a partnership between the U.S. Geological Survey (USGS), the Association of American State Geologists (AASG), and other Federal, State, and private-sector organizations. The goal of the effort is to improve our knowledge of the geologic framework in the United States and to identify areas that have the potential to contain undiscovered critical mineral resources. Enhancement of our domestic mineral supply will decrease our reliance on foreign sources of minerals that are fundamental to the Nation’s security and economy.</p><p>The intent of Earth MRI is to leverage the USGS’s existing relationships with States and the private sector to conduct state-of-the-art geologic mapping and airborne geophysical and topographic (lidar) surveys. Analyses of these datasets could point to potential buried critical mineral deposits.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193007","collaboration":"Prepared in cooperation with the Association of American State Geologists","usgsCitation":"Day, W.C., 2019, The Earth Mapping Resources Initiative (Earth MRI)—Mapping the Nation’s critical mineral resources (ver. 1.2, September 2019): U.S. Geological Survey Fact Sheet 2019–3007, 2 p., https://doi.org/10.3133/fs20193007.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-104191","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":495296,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13XHP2X","text":"USGS data release","linkHelpText":"Airborne magnetic and radiometric survey over Puerto Rico and the Surrounding Islands and Shelf, 2023-2024"},{"id":437563,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D3FQWZ","text":"USGS data release","linkHelpText":"Magnetic susceptibility and density measurements in the Wet Mountains, Colorado, 2022 to 2023"},{"id":437562,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98CW91W","text":"USGS data release","linkHelpText":"Airborne Magnetic Survey, Michigan Upper Peninsula Area, 2008"},{"id":367306,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3007/fs20193007.pdf","text":"Report","size":"8.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3007"},{"id":367308,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2019/3007/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":367305,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3007/coverthb.jpg"}],"edition":"Version 1.2: September 2019; Version 1.1: March  2019; Version 1.0: February  2019","contact":"<p><a href=\"https://minerals.usgs.gov/\" data-mce-href=\"https://minerals.usgs.gov/\">Mineral Resources Program</a><br>U.S. Geological Survey<br>913 National Center<br>12201 Sunrise Valley Drive <br>Reston, VA 20192<br>Email: <a href=\"mailto:Minerals@usgs.gov\" data-mce-href=\"mailto:Minerals@usgs.gov\">Minerals@usgs.gov</a><br>URL: <a href=\"https://www.usgs.gov/special-topic/earthmri\" data-mce-href=\"https://www.usgs.gov/special-topic/earthmri\">https://www.usgs.gov/special-topic/earthmri</a></p>","tableOfContents":"<ul><li>What is Earth MRI?</li><li>Why is Earth MRI Needed?</li><li>First Steps in Implementing Earth MRI</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-02-25","revisedDate":"2019-09-12","noUsgsAuthors":false,"publicationDate":"2019-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Day, Warren C. 0000-0002-9278-2120 wday@usgs.gov","orcid":"https://orcid.org/0000-0002-9278-2120","contributorId":1308,"corporation":false,"usgs":true,"family":"Day","given":"Warren","email":"wday@usgs.gov","middleInitial":"C.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":757836,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70201029,"text":"sir20185159 - 2019 - California’s exposure to volcanic hazards","interactions":[],"lastModifiedDate":"2019-12-10T12:19:03","indexId":"sir20185159","displayToPublicDate":"2019-02-25T05:35:49","publicationYear":"2019","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":"2018-5159","displayTitle":"California’s Exposure to Volcanic Hazards","title":"California’s exposure to volcanic hazards","docAbstract":"<p>The potential for damaging earthquakes, landslides, floods, tsunamis, and wildfires is widely recognized in California. The same cannot be said for volcanic eruptions, despite the fact that they occur in the state about as frequently as the largest earthquakes on the San Andreas Fault. At least ten eruptions have taken place in the past 1,000 years, and future volcanic eruptions are inevitable.</p><p>The U.S. Geological Survey’s (USGS) national volcanic threat assessment identifies eight young volcanic areas in California as moderate, high, or very high threat. Of the eight volcanic areas that exist in California, molten rock resides beneath at least seven of these—Medicine Lake volcano, Mount Shasta, Lassen Volcanic Center, Clear Lake volcanic field, the Long Valley volcanic region, Coso volcanic field, and Salton Buttes—and are therefore considered “active” volcanoes producing volcanic earthquakes, toxic gas emissions, hot springs, geothermal systems, and (or) ground movement.</p><p>The USGS California Volcano Observatory in Menlo Park, California, monitors these potentially hazardous volcanoes to help communities and government authorities understand, prepare for, and respond to volcanic activity. Although volcanic activity can sometimes be forecast, eruptions, like earthquakes or tsunamis, cannot be prevented. Understanding the hazards and identifying what and who is in harm’s way is the first step in mitigating volcanic risk and building community resilience to volcanic hazards.</p><p>This report, which was prepared in collaboration with the California Governor’s Office of Emergency Services and the California Geological Survey, provides a broad perspective on the state’s exposure to volcanic hazards by integrating volcanic hazard information with geospatial data on at-risk populations, infrastructure, and resources. This information is intended to prompt site- and sector-specific vulnerability analyses and preparation of hazard mitigation and response plans.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185159","collaboration":"Prepared in cooperation with the California Governor’s Office of Emergency Services and the California Geological Survey","usgsCitation":"Mangan, M., Ball, J., Wood, N., Jones, J.L., Peters, J., Abdollahian, N., Dinitz, L., Blankenheim, S., Fenton, J., and Pridmore, C., 2019, California’s exposure to volcanic hazards (ver. 1.1, December 2019): U.S. Geological Survey Scientific Investigations Report 2018–5159, 49 p., https://doi.org/10.3133/sir20185159.","productDescription":"Report: vi, 49 p.; 2 Appendixes","numberOfPages":"58","ipdsId":"IP-092973","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":370069,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5159/versionHist.txt"},{"id":361550,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5159/sir20185159_appendix2_ver1.1.xlsx","text":"Appendix 2","size":"39 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5159 Appendix 2"},{"id":361551,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5159/sir20185159_appendix3_ver1.1.xlsx","text":"Appendix 3","size":"34 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5159 Appendix 3"},{"id":361442,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5159/sir20185159ver1.1.pdf","text":"Report","size":"33.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5159"},{"id":370115,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5159/coverthb.jpg"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"https://volcanoes.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://volcanoes.usgs.gov/\">Volcano Science Center</a><br>U.S. Geological Survey<br>345 Middlefield Road, MS 910<br>Menlo Park, CA 94025</p>","tableOfContents":"<ul><li>Introduction</li><li>Hazards and Impacts</li><li>“Watch List” Volcanoes and Hazard Zones</li><li>Societal Exposure to Volcanic Hazards</li><li>Summary and Next Steps</li><li>Acknowledgments</li><li>References</li><li>Glossary</li><li>Appendixes 1–3</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-02-25","revisedDate":"2019-12-06","noUsgsAuthors":false,"publicationDate":"2019-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Mangan, Margaret 0000-0002-5273-8053 mmangan@usgs.gov","orcid":"https://orcid.org/0000-0002-5273-8053","contributorId":107982,"corporation":false,"usgs":true,"family":"Mangan","given":"Margaret","email":"mmangan@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":false,"id":751908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, Jessica 0000-0002-7837-8180 jlball@usgs.gov","orcid":"https://orcid.org/0000-0002-7837-8180","contributorId":213475,"corporation":false,"usgs":true,"family":"Ball","given":"Jessica","email":"jlball@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":751909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Nathan 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":71151,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":751910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Jamie L. 0000-0002-9967-3314 jamiejones@usgs.gov","orcid":"https://orcid.org/0000-0002-9967-3314","contributorId":172111,"corporation":false,"usgs":true,"family":"Jones","given":"Jamie L.","email":"jamiejones@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":751912,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":751917,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abdollahian, Nina 0000-0002-8607-2202 nabdollahian@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-2202","contributorId":92149,"corporation":false,"usgs":true,"family":"Abdollahian","given":"Nina","email":"nabdollahian@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":751911,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dinitz, Laura","contributorId":52330,"corporation":false,"usgs":true,"family":"Dinitz","given":"Laura","affiliations":[],"preferred":false,"id":751913,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blankenheim, Sharon","contributorId":210773,"corporation":false,"usgs":false,"family":"Blankenheim","given":"Sharon","email":"","affiliations":[{"id":28116,"text":"California Office of Emergency Services","active":true,"usgs":false}],"preferred":false,"id":751914,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fenton, Johanna","contributorId":210774,"corporation":false,"usgs":false,"family":"Fenton","given":"Johanna","affiliations":[{"id":38146,"text":"Caliifornia Office of Emergency Services","active":true,"usgs":false}],"preferred":false,"id":751915,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pridmore, Cynthia","contributorId":210775,"corporation":false,"usgs":false,"family":"Pridmore","given":"Cynthia","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":751916,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70204681,"text":"70204681 - 2019 - Can’t see the random forest for the decision trees: Selecting predictive models for restoration ecology","interactions":[],"lastModifiedDate":"2019-09-16T12:29:37","indexId":"70204681","displayToPublicDate":"2019-02-22T14:18:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Can’t see the random forest for the decision trees: Selecting predictive models for restoration ecology","docAbstract":"Improving predictions of restoration outcomes is increasingly important to resource managers for accountability and adaptive management, yet there is limited guidance for selecting a predictive model from the multitude available. The goal of this paper was to identify an optimal predictive framework for restoration ecology using eleven modeling frameworks (including, machine learning, inferential, and ensemble approaches), and three data groups (field data, geographic data [GIS], and a combination thereof). We test this approach with a dataset from a large post-fire sagebrush reestablishment project in the Great Basin, USA. Predictive power varied among models and data groups, ranging from 58-79% accuracy. Finer scale field data generally had the greatest predictive power, although GIS data were present in the best models overall. An ensemble prediction computed from the ten models parameterized to field data was well above average for accuracy but was outperformed by others that prioritized model parsimony by selecting predictor variables based on rankings of their importance among all candidate models. The variation in predictive power among a suite of modeling frameworks underscores the importance of a model comparison and refinement approach that evaluates multiple models and data groups, and selects variables based on their contribution to predictive power. The enhanced understanding of factors influencing restoration outcomes accomplished by this framework has the potential to aid the adaptive management process for improving future restoration outcomes.","language":"English","publisher":"Wiley","doi":"10.1111/rec.12938","usgsCitation":"Barnard, D., Germino, M., Pilliod, D., Arkle, R., Applestein, C., Davidson, B., and Fisk, M., 2019, Can’t see the random forest for the decision trees: Selecting predictive models for restoration ecology: Restoration Ecology, v. 27, no. 5, p. 1053-1063, https://doi.org/10.1111/rec.12938.","productDescription":"11 p.","startPage":"1053","endPage":"1063","ipdsId":"IP-092214","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":366415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnard, David 0000-0003-1877-3151","orcid":"https://orcid.org/0000-0003-1877-3151","contributorId":218008,"corporation":false,"usgs":true,"family":"Barnard","given":"David","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":218007,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":218009,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768049,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arkle, Robert 0000-0003-3021-1389","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":218013,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":218010,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768050,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davidson, Bill 0000-0003-1315-479X","orcid":"https://orcid.org/0000-0003-1315-479X","contributorId":218011,"corporation":false,"usgs":true,"family":"Davidson","given":"Bill","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768051,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fisk, Matthew 0000-0002-2250-0116","orcid":"https://orcid.org/0000-0002-2250-0116","contributorId":218012,"corporation":false,"usgs":true,"family":"Fisk","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768052,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70200942,"text":"sir20185150 - 2019 - Estimation of base flow on ungaged, periodically measured streams in small watersheds in western Pennsylvania","interactions":[],"lastModifiedDate":"2019-02-22T16:59:13","indexId":"sir20185150","displayToPublicDate":"2019-02-22T13:45:00","publicationYear":"2019","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":"2018-5150","displayTitle":"Estimation of Base Flow on Ungaged, Periodically Measured Streams in Small Watersheds in Western Pennsylvania","title":"Estimation of base flow on ungaged, periodically measured streams in small watersheds in western Pennsylvania","docAbstract":"<p>A 2.5-year data collection program was undertaken by the U.S. Geological Survey, in cooperation with the Pennsylvania Department of Environmental Protection (PADEP), to quantify and estimate base flow in small watersheds in western Pennsylvania where only periodic streamflow measurements had been obtained. Twelve streamgages with watershed areas of less than 10 square miles were established in western Pennsylvania for this study, with most established within Greene and Washington Counties (an area where a type of underground coal mining known as longwall mining occurs). Data from five previously established streamgages with watershed areas ranging from 48.9 to 281 square miles were also used in the analyses for this study. The index-gage method was used to relate streamflow at one streamgage referred to as the “index streamgage” to streamflow at another site of interest (usually an ungaged site, but for this study another streamgage) using a regression technique.</p><p>Streamflow regressions were developed for all newly established streamgages by using the Maintenance of Variance Extension, Type 1 (MOVE.1) method. Not all streamflow data from the newly established streamgages were used for MOVE.1 regression development; only data that have little to no influence from runoff were considered. Runoff-influenced streamflow for this study was defined as streamflow on a day that precipitation occurs plus streamflow on the following 2 days. One streamflow value per day selected from a specified schedule that captures numerous non-runoff periods was used to develop a MOVE.1 regression.</p><p>Prediction limits were calculated from the regression to provide the upper and lower bounds for the regression-produced streamflow estimates. Using these data, base flow at a site can be estimated with the index-gage method. The log<sub>10</sub>-tranformed prediction interval width and other regression diagnostics were used as indicators of regression quality when comparing streamgage relations to determine the best index streamgage among the streamgages established for this study. It was determined that index streamgages within about 10 miles of the site of interest provided the best estimated base flow and could, in the future, be used by mine operators and the PADEP to quantify base flow and to evaluate the effects of mining on streamflow.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185150","collaboration":"Prepared in cooperation with the Pennsylvania Department of Environmental Protection","usgsCitation":"Hittle, E., and Risser, D.W., 2019, Estimation of base flow on ungaged, periodically measured streams in small watersheds in western Pennsylvania: U.S. Geological Survey Scientific Investigations Report 2018–5150, 42 p., https://doi.org/10.3133/sir20185150.","productDescription":"Report: ix, 42 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-093027","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":361469,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F18XX9","text":"USGS data release","description":"USGS data release","linkHelpText":"Index-gage Data and Regressions in Support of Estimation of Base Flow on Ungaged, Periodically Measured Streams in Small Watersheds in Western Pennsylvania"},{"id":361422,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5150/coverthb.jpg"},{"id":361423,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5150/sir20185150.pdf","text":"Report","size":"25.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5150"}],"country":"United States","state":"Pennsylvania","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.52429199218749,\n              39.72831341029745\n            ],\n            [\n              -79,\n              39.72831341029745\n            ],\n            [\n              -79,\n              42\n            ],\n            [\n              -80.52429199218749,\n              42\n            ],\n            [\n              -80.52429199218749,\n              39.72831341029745\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_pa@usgs.gov\" data-mce-href=\"mailto:dc_pa@usgs.gov\">Director</a>, <a href=\"http://pa.water.usgs.gov/\" data-mce-href=\"http://pa.water.usgs.gov/\">Pennsylvania Water Science Center</a><br>U.S. Geological Survey<br>215 Limekiln Road<br>New Cumberland, PA 17070</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Streamgage Network</li><li>Development of a Method for the Estimation of Base Flow on Ungaged, Periodically Measured Streams</li><li>Analysis of Streamflow Estimation</li><li>Accuracy and Limitations</li><li>Application of Techniques to Estimate Natural Streamflow at an Ungaged Site</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. Results of MOVE.1 regression diagnostics for streamflow at U.S. Geological Survey streamgage 03111235 (DogTrib) streamflow estimated by using U.S. Geological Survey streamgages 03111200 (Dunkle) and 03111890 (MWheeling) with and without runoff-influenced streamflow</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2019-02-22","noUsgsAuthors":false,"publicationDate":"2019-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Hittle, Elizabeth A. 0000-0002-1771-7724 ehittle@usgs.gov","orcid":"https://orcid.org/0000-0002-1771-7724","contributorId":2038,"corporation":false,"usgs":true,"family":"Hittle","given":"Elizabeth","email":"ehittle@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":751414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Risser, Dennis W. 0000-0001-9597-5406 dwrisser@usgs.gov","orcid":"https://orcid.org/0000-0001-9597-5406","contributorId":898,"corporation":false,"usgs":true,"family":"Risser","given":"Dennis","email":"dwrisser@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":751415,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70202311,"text":"70202311 - 2019 - Reimagining the potential of Earth observations for ecosystem service assessments","interactions":[],"lastModifiedDate":"2019-02-22T13:11:01","indexId":"70202311","displayToPublicDate":"2019-02-22T13:10:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Reimagining the potential of Earth observations for ecosystem service assessments","docAbstract":"<p><span>The benefits nature provides to people, called ecosystem services, are increasingly recognized and accounted for in assessments of infrastructure development,&nbsp;</span>agricultural management<span>, conservation prioritization, and sustainable sourcing. These assessments are often limited by data, however, a gap with tremendous potential to be filled through Earth observations (EO), which produce a variety of data across spatial and temporal extents and resolutions. Despite widespread recognition of this potential, in practice few ecosystem service studies use EO. Here, we identify challenges and opportunities to using EO in ecosystem service modeling and assessment. Some challenges are technical, related to data awareness, processing, and access. These challenges require systematic investment in model platforms and&nbsp;data management. Other challenges are more conceptual but still systemic; they are byproducts of the structure of existing ecosystem service models and addressing them requires scientific investment in solutions and tools applicable to a wide range of models and approaches. We also highlight new ways in which EO can be leveraged for ecosystem service assessments, identifying promising new areas of research. More widespread use of EO for ecosystem service assessment will only be achieved if all of these types of challenges are addressed. This will require non-traditional funding and partnering opportunities from private and public agencies to promote data exploration, sharing, and archiving. Investing in this integration will be reflected in better and more accurate ecosystem service assessments worldwide.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.02.150","usgsCitation":"Ramirez-Reyes, C., Brauman, K.A., Chaplin-Kramer, R., Galford, G.L., Adamo, S.B., Anderson, C.B., Anderson, C., Allington, G.R., Bagstad, K.J., Coe, M.T., Cord, A.F., Dee, L.E., Gould, R.K., Jain, M., Kowal, V.A., Muller-Karger, F.E., Norriss, J., Potapov, P.V., Qui, J., Rieb, J.T., Robinson, B.E., Samberg, L.H., Singh, N., Szeto, S.H., Voigt, B., Watson, K., and Wright, T.M., 2019, Reimagining the potential of Earth observations for ecosystem service assessments: Science of the Total Environment, v. 665, p. 1053-1063, https://doi.org/10.1016/j.scitotenv.2019.02.150.","productDescription":"11 p.","startPage":"1053","endPage":"1063","ipdsId":"IP-103295","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467876,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.02.150","text":"Publisher Index Page"},{"id":361470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"665","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ramirez-Reyes, Carlos 0000-0002-7407-071X","orcid":"https://orcid.org/0000-0002-7407-071X","contributorId":213446,"corporation":false,"usgs":false,"family":"Ramirez-Reyes","given":"Carlos","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":757742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brauman, Kate A.","contributorId":190423,"corporation":false,"usgs":false,"family":"Brauman","given":"Kate","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":757743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chaplin-Kramer, Rebecca 0000-0002-1539-5231","orcid":"https://orcid.org/0000-0002-1539-5231","contributorId":213447,"corporation":false,"usgs":false,"family":"Chaplin-Kramer","given":"Rebecca","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":757744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galford, Gillian L. 0000-0003-2192-7385","orcid":"https://orcid.org/0000-0003-2192-7385","contributorId":213448,"corporation":false,"usgs":false,"family":"Galford","given":"Gillian","email":"","middleInitial":"L.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":757745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adamo, Susana B. 0000-0002-9168-7172","orcid":"https://orcid.org/0000-0002-9168-7172","contributorId":213449,"corporation":false,"usgs":false,"family":"Adamo","given":"Susana","email":"","middleInitial":"B.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":757746,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Christopher B. 0000-0001-7392-4368","orcid":"https://orcid.org/0000-0001-7392-4368","contributorId":213450,"corporation":false,"usgs":false,"family":"Anderson","given":"Christopher","email":"","middleInitial":"B.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":757747,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Anderson, Clarissa 0000-0001-5970-0253","orcid":"https://orcid.org/0000-0001-5970-0253","contributorId":213451,"corporation":false,"usgs":false,"family":"Anderson","given":"Clarissa","email":"","affiliations":[{"id":34004,"text":"Scripps Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":757748,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Allington, Ginger R. H. 0000-0003-0446-0576","orcid":"https://orcid.org/0000-0003-0446-0576","contributorId":213452,"corporation":false,"usgs":false,"family":"Allington","given":"Ginger","email":"","middleInitial":"R. H.","affiliations":[{"id":34680,"text":"George Washington University","active":true,"usgs":false}],"preferred":false,"id":757749,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":757741,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Coe, Michael T. 0000-0002-7470-0697","orcid":"https://orcid.org/0000-0002-7470-0697","contributorId":213453,"corporation":false,"usgs":false,"family":"Coe","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":16705,"text":"Woods Hole Research 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0000-0002-6307-8783","orcid":"https://orcid.org/0000-0002-6307-8783","contributorId":213456,"corporation":false,"usgs":false,"family":"Gould","given":"Rachelle","email":"","middleInitial":"K.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":757753,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Jain, Meha 0000-0002-6821-473X","orcid":"https://orcid.org/0000-0002-6821-473X","contributorId":213457,"corporation":false,"usgs":false,"family":"Jain","given":"Meha","email":"","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":757754,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Kowal, Virginia A. 0000-0002-9290-4183","orcid":"https://orcid.org/0000-0002-9290-4183","contributorId":213458,"corporation":false,"usgs":false,"family":"Kowal","given":"Virginia","email":"","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":757755,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Muller-Karger, Frank E.","contributorId":206626,"corporation":false,"usgs":false,"family":"Muller-Karger","given":"Frank","email":"","middleInitial":"E.","affiliations":[{"id":37356,"text":"University of South Florida, Saint Petersburg, FL","active":true,"usgs":false}],"preferred":false,"id":757756,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Norriss, Jessica","contributorId":213459,"corporation":false,"usgs":false,"family":"Norriss","given":"Jessica","email":"","affiliations":[{"id":38760,"text":"Upstream Tech","active":true,"usgs":false}],"preferred":false,"id":757757,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Potapov, Peter V.","contributorId":192037,"corporation":false,"usgs":false,"family":"Potapov","given":"Peter","email":"","middleInitial":"V.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":757758,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Qui, Jiangxiao 0000-0002-3741-5213","orcid":"https://orcid.org/0000-0002-3741-5213","contributorId":213460,"corporation":false,"usgs":false,"family":"Qui","given":"Jiangxiao","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":757759,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Rieb, Jesse T. 0000-0003-1144-8743","orcid":"https://orcid.org/0000-0003-1144-8743","contributorId":213461,"corporation":false,"usgs":false,"family":"Rieb","given":"Jesse","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":757760,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Robinson, Brian E. 0000-0002-8972-8318","orcid":"https://orcid.org/0000-0002-8972-8318","contributorId":213462,"corporation":false,"usgs":true,"family":"Robinson","given":"Brian","email":"","middleInitial":"E.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":757761,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Samberg, Leah H.","contributorId":213463,"corporation":false,"usgs":false,"family":"Samberg","given":"Leah","email":"","middleInitial":"H.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":757762,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Singh, Nagendra 0000-0002-3682-9051","orcid":"https://orcid.org/0000-0002-3682-9051","contributorId":213464,"corporation":false,"usgs":false,"family":"Singh","given":"Nagendra","email":"","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":757763,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Szeto, Sabrina H.","contributorId":213465,"corporation":false,"usgs":false,"family":"Szeto","given":"Sabrina","email":"","middleInitial":"H.","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":757764,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Voigt, Brian","contributorId":208483,"corporation":false,"usgs":false,"family":"Voigt","given":"Brian","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":757765,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Watson, Keri","contributorId":213466,"corporation":false,"usgs":false,"family":"Watson","given":"Keri","email":"","affiliations":[{"id":38761,"text":"Sewanee-University of the South","active":true,"usgs":false}],"preferred":false,"id":757766,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Wright, T. Maxwell","contributorId":213467,"corporation":false,"usgs":false,"family":"Wright","given":"T.","email":"","middleInitial":"Maxwell","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":757767,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}}
,{"id":70205845,"text":"70205845 - 2019 - Factors affecting species richness and distribution spatially and temporally within a protected area using multi-season occupancy models","interactions":[],"lastModifiedDate":"2019-10-08T13:12:54","indexId":"70205845","displayToPublicDate":"2019-02-22T13:10:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting species richness and distribution spatially and temporally within a protected area using multi-season occupancy models","docAbstract":"Exploring trends in species richness and the distribution of individual species over time as well as the factors affecting these trends informs conservation priorities in protecting species and ecosystems as a whole. We used data from 41 park-wide line transect surveys in 2009 and 2014 and multi-season occupancy models with multi-species data to explore trends in species richness and distribution of individual species and factors affecting these trends in Nyungwe National Park (NNP), Rwanda. Mammalian species richness and the distributional range of 5 of the 7 species increased between 2009 and 2014 in NNP. The probability of colonization of a species into a new area in 2014, where it was not present in 2009, was highest in sites with a lower probability of poaching activity, close to tourist trails, and at lower elevations. The probability of colonization with no poaching activity was about 50% but dropped to about 10% with a 100% chance of poaching activity. Duiker species had the largest increase in distribution during the study, while there was a decrease in the distribution of the eastern chimpanzee and blue monkey.  Our results suggest that increased patrols should be implemented in areas of the park with low species richness and areas with a low probability of occurrence for species of conservation concern to combat poaching activity and thus increase the probability of a species moving into a new area. Our use of a single multi-season model for multiple species explicitly accounts for imperfect detection and species-specific identities, while allowing for inferences to be made about rarely detected species by sharing covariates with common species. These results can be used to improve conservation planning in NNP for species management and ranger patrol protocols and our modelling framework is broadly applicable to any protected area with presence/absence species field data.","language":"English","publisher":"Wiley","doi":"10.1111/acv.12491","usgsCitation":"Moore, J.F., Hines, J.E., and Masozera, M.K., 2019, Factors affecting species richness and distribution spatially and temporally within a protected area using multi-season occupancy models: Animal Conservation, v. 22, no. 5, p. 503-514, https://doi.org/10.1111/acv.12491.","productDescription":"12 p.","startPage":"503","endPage":"514","ipdsId":"IP-098950","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":368106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Rwanda","otherGeospatial":"Nyungwe Forest National Park","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[30.4191,-1.13466],[30.81613,-1.69891],[30.75831,-2.28725],[30.4697,-2.41386],[29.93836,-2.34849],[29.63218,-2.91786],[29.02493,-2.83926],[29.11748,-2.29221],[29.25483,-2.21511],[29.29189,-1.62006],[29.57947,-1.34131],[29.82152,-1.44332],[30.4191,-1.13466]]]},\"properties\":{\"name\":\"Rwanda\"}}]}","volume":"22","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Jennifer F.","contributorId":189122,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":772590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":772589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masozera, Michel K.","contributorId":201300,"corporation":false,"usgs":false,"family":"Masozera","given":"Michel","email":"","middleInitial":"K.","affiliations":[{"id":35968,"text":"Wildlife Conservation Society, Rwanda Program","active":true,"usgs":false}],"preferred":false,"id":772591,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70202326,"text":"70202326 - 2019 - Assessing vulnerability and threat from housing development to Conservation Opportunity Areas in State Wildlife Action Plans across the United States","interactions":[],"lastModifiedDate":"2019-02-22T12:52:37","indexId":"70202326","displayToPublicDate":"2019-02-22T12:52:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2603,"text":"Landscape and Urban Planning","active":true,"publicationSubtype":{"id":10}},"title":"Assessing vulnerability and threat from housing development to Conservation Opportunity Areas in State Wildlife Action Plans across the United States","docAbstract":"<p><span>Targeting conservation actions efficiently requires information on vulnerability of and threats to conservation targets, but such information is rarely included in conservation plans. In the U.S., recently updated State Wildlife Action Plans identify Conservation Opportunity Areas (COAs) selected by each state as priority areas for future action to conserve wildlife and habitats. The question is how threatened these COAs are by habitat loss and degradation, major threats to wildlife in the U.S. that are often caused by housing development. We compiled spatial data on COAs across the conterminous U.S. We estimated COA vulnerability using current land protection status and COA threat using projected housing growth derived from U.S. census data. COAs comprise 1–46% of each region. Across regions, 28–82% of the area within COAs is vulnerable to future housing development, and 5–55% and 7–23% of that vulnerable COA area is threatened by projected dense housing and rapid housing growth, respectively. COA vulnerability is greatest in the East. Threat from dense housing and rapid housing growth is highest in the Northeast and Pacific Southwest, respectively. Results highlight that many areas identified as important for reducing wildlife listings under the U.S. Endangered Species Act may need further protection to fulfill their conservation goals because they are both vulnerable to and threatened by future housing development. Our analyses can help practitioners target local government outreach, land protection efforts, and landscape-scale mitigation programs to decrease future COA loss from housing development, and could be expanded to address additional COA threats (e.g., wildfire, invasive species).</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.landurbplan.2018.10.025","usgsCitation":"Carter, S.K., Maxted, S.S., Bergeson, T.L., Helmers, D.P., Scott, L., and Radeloff, V.C., 2019, Assessing vulnerability and threat from housing development to Conservation Opportunity Areas in State Wildlife Action Plans across the United States: Landscape and Urban Planning, v. 185, p. 237-245, https://doi.org/10.1016/j.landurbplan.2018.10.025.","productDescription":"9 p.","startPage":"237","endPage":"245","ipdsId":"IP-088249","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":467878,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.landurbplan.2018.10.025","text":"Publisher Index Page"},{"id":361465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"185","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":757838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maxted, Shelley S.","contributorId":213499,"corporation":false,"usgs":false,"family":"Maxted","given":"Shelley","email":"","middleInitial":"S.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":757839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergeson, Tara L. E.","contributorId":213500,"corporation":false,"usgs":false,"family":"Bergeson","given":"Tara","email":"","middleInitial":"L. E.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":757840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Helmers, David P.","contributorId":213501,"corporation":false,"usgs":false,"family":"Helmers","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":757841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scott, Lori","contributorId":213502,"corporation":false,"usgs":false,"family":"Scott","given":"Lori","email":"","affiliations":[{"id":17658,"text":"NatureServe","active":true,"usgs":false}],"preferred":false,"id":757842,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Radeloff, Volker C.","contributorId":149494,"corporation":false,"usgs":false,"family":"Radeloff","given":"Volker","email":"","middleInitial":"C.","affiliations":[{"id":13679,"text":"SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":757843,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70202332,"text":"70202332 - 2019 - Morphodynamics of a field of crescent-shaped rippled scour depressions: Northern Monterey Bay, CA","interactions":[],"lastModifiedDate":"2019-02-22T12:38:16","indexId":"70202332","displayToPublicDate":"2019-02-22T12:38:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Morphodynamics of a field of crescent-shaped rippled scour depressions: Northern Monterey Bay, CA","docAbstract":"<p><span>Despite the prevalence of rippled scour depression (RSD) on the world's&nbsp;continental shelves&nbsp;and their importance as nursery habitats for many commercially-important species, the processes responsible for their formation and geomorphic evolution are still not well understood. Most studies that focused on RSD evolution have been based on data acquired over multiple years to decades, and often during calmer summer months. Here, multiple geophysical&nbsp;seafloor mapping&nbsp;surveys of a field of RSD's off Santa Cruz, California, USA, were conducted over the course of two winters with distinctly different oceanographic forcing; these results were compared to time series&nbsp;oceanographic measurements&nbsp;made within the survey area, and put into the context of long-term trends from survey data collected during previous decades. Although the migration of these features across the seafloor occurs on decadal time scales, significant change was detected within a given year, depending on the wave climate and&nbsp;</span>fluvial sediment<span>&nbsp;input. RSDs shrank up to 16% or grew up to 28% in a span of a few months. Such change was predominantly the result of redistribution of&nbsp;fine-grained sediment&nbsp;input to the system by local rivers. Migration of the seafloor features appears to be the result of accumulation of fine-grained sediment at the boundary between the RSD and the surrounding fine-grained cap.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2018.10.006","usgsCitation":"Rosenberger, K.J., Storlazzi, C.D., and Dartnell, P., 2019, Morphodynamics of a field of crescent-shaped rippled scour depressions: Northern Monterey Bay, CA: Marine Geology, v. 407, p. 44-59, https://doi.org/10.1016/j.margeo.2018.10.006.","productDescription":"16 p.","startPage":"44","endPage":"59","ipdsId":"IP-093455","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467879,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2018.10.006","text":"Publisher Index Page"},{"id":437564,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71C1W36","text":"USGS data release","linkHelpText":"Bathymetry, acoustic-backscatter, and time-series datasets collected between 2014 and 2016 of a field of crescent-shaped rippled scour depressions in northern Monterey Bay, California"},{"id":361461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Northern Monterey Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.0333,\n              36.925\n            ],\n            [\n              -122,\n              36.925\n            ],\n            [\n              -122,\n              36.9583\n            ],\n            [\n              -122.0333,\n              36.9583\n            ],\n            [\n              -122.0333,\n              36.925\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"407","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":757870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":757871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757872,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70202032,"text":"ds1103 - 2019 - Least Bell’s Vireo (Vireo bellii pusillus) and Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys in the Hansen Dam Basin, Los Angeles County, California—2018 data summary","interactions":[],"lastModifiedDate":"2019-02-26T09:20:22","indexId":"ds1103","displayToPublicDate":"2019-02-22T08:15:04","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1103","displayTitle":"Least Bell’s Vireo (<em>Vireo bellii pusillus</em>) and Southwestern Willow Flycatcher (<em>Empidonax traillii extimus</em>) Surveys in the Hansen Dam Basin, Los Angeles County, California—2018 Data Summary","title":"Least Bell’s Vireo (Vireo bellii pusillus) and Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys in the Hansen Dam Basin, Los Angeles County, California—2018 data summary","docAbstract":"<h1>Executive Summary</h1><p>We surveyed for Least Bell’s Vireos (<i>Vireo bellii pusillus</i>; vireo) and Southwestern Willow Flycatchers (<i>Empidonax traillii extimus</i>; flycatcher) in cooperation with the U.S. Army Corps of Engineers along Big Tujunga Creek in the Hansen Dam Basin in Los Angeles County, California, in 2018. Four vireo surveys were conducted between April 25 and July 17, 2018, and three flycatcher surveys were conducted between May 22 and July 17, 2018. We found 77 territorial male vireos, 54 of which were confirmed as paired. Seventy-seven percent of vireos were detected in habitat characterized as mixed willow, and 84 percent of vireos were detected in habitat with greater than 50 percent native plant cover. One transient Willow Flycatcher of unknown subspecies was observed in the survey area in 2018.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1103","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Pottinger, R.E., and Kus, B.E., 2019, Least Bell’s Vireo (Vireo bellii pusillus) and Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys in the Hansen Dam Basin, Los Angeles County, California—2018 data summary: U.S. Geological Survey Data Series 1103, 11 p., https://doi.org/10.3133/ds1103.","productDescription":"iv, 12 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-103361","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":361420,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1103/ds1103.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1103"},{"id":361419,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1103/coverthb.jpg"}],"country":"United States","state":"California","county":"Los Angeles County","otherGeospatial":"Big Tujunga Creek , Hansen Dam Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.40412139892578,\n              34.25700362097726\n            ],\n            [\n              -118.36515426635742,\n              34.25700362097726\n            ],\n            [\n              -118.36515426635742,\n              34.2732120461364\n            ],\n            [\n              -118.40412139892578,\n              34.2732120461364\n            ],\n            [\n              -118.40412139892578,\n              34.25700362097726\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br>U.S. Geological Survey<br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2019-02-22","noUsgsAuthors":false,"publicationDate":"2019-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Pottinger, Ryan E. 0000-0002-0263-0300","orcid":"https://orcid.org/0000-0002-0263-0300","contributorId":213445,"corporation":false,"usgs":true,"family":"Pottinger","given":"Ryan E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":756785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":756784,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70202314,"text":"70202314 - 2019 - Assessing lek attendance of male greater sage‐grouse using fine‐resolution GPS data: Implications for population monitoring of lek mating grouse","interactions":[],"lastModifiedDate":"2021-04-16T19:30:05.818684","indexId":"70202314","displayToPublicDate":"2019-02-21T16:56:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Assessing lek attendance of male greater sage‐grouse using fine‐resolution GPS data: Implications for population monitoring of lek mating grouse","docAbstract":"<p><span>Counts of males displaying on breeding grounds are the primary management tool used to assess population trends in lekking grouse species. Despite the importance of male lek attendance (i.e., proportion of males on leks available for detection) influencing lek counts, patterns of within season and between season variability in attendance rates are not well understood. We used high‐frequency global positioning system (GPS) telemetry data from male greater sage‐grouse (</span><i>Centrocercus urophasianus; n</i><span> = 67) over five lekking seasons (2013–2017) at eight study sites in Nevada to estimate lek attendance rates. Specifically, we recorded daily locations of sage‐grouse in relation to mapped lek boundaries and used generalized additive models to assess temporal variation in attendance rates by age class (subadult vs. adult). Average timing of peak attendance occurred on 16 April but varied from March 16, 2014 to April 21 , 2016. Overall, adult males attended leks at higher rates (0.683 at peak) and earlier in the season (19 March) than subadults (0.421 at peak on April 19). Peak attendance probability was positively related to cumulative winter precipitation. Daily probabilities of lek switching differed between adults (0.019 at peak on March 3) and subadults (0.046 at peak on March 22), and lek switching was negatively related to distance to nearest lek. Our results indicate variable patterns in lek attendance through time, and that lek switching may occur at higher rates than previously thought. We demonstrate the use of generalizable daily attendance curves to date‐correct lek counts and derive estimates of male abundance, although such an approach will likely require the incorporation of information on age structure to produce robust results that are useful for population monitoring.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/1438-390X.1019","usgsCitation":"Wann, G.T., Coates, P.S., Prochazka, B.G., Severson, J.P., Monroe, A., and Aldridge, C., 2019, Assessing lek attendance of male greater sage‐grouse using fine‐resolution GPS data: Implications for population monitoring of lek mating grouse: Population Ecology, v. 61, no. 2, p. 183-197, https://doi.org/10.1002/1438-390X.1019.","productDescription":"15 p.","startPage":"183","endPage":"197","ipdsId":"IP-098337","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":467880,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/1438-390x.1019","text":"Publisher Index Page"},{"id":361440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","volume":"61","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Wann, Gregory T. 0000-0001-9076-7819 wanng@usgs.gov","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":3855,"corporation":false,"usgs":true,"family":"Wann","given":"Gregory","email":"wanng@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":757781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Severson, John P. 0000-0002-1754-6689","orcid":"https://orcid.org/0000-0002-1754-6689","contributorId":213469,"corporation":false,"usgs":true,"family":"Severson","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":757784,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":213471,"corporation":false,"usgs":false,"family":"Aldridge","given":"Cameron L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":757785,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70202234,"text":"ofr20171064 - 2019 - Evaluation of recommended revisions to Bulletin 17B","interactions":[],"lastModifiedDate":"2019-02-22T10:08:21","indexId":"ofr20171064","displayToPublicDate":"2019-02-21T15:45:00","publicationYear":"2019","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":"2017-1064","displayTitle":"Evaluation of Recommended Revisions to Bulletin 17B","title":"Evaluation of recommended revisions to Bulletin 17B","docAbstract":"<p>For the past 36 years, Bulletin 17B, published by the Interagency Committee on Water Data in 1982, has guided flood-frequency analyses in the United States. During this period, much has been learned about both hydrology and statistical methods. In keeping with the tradition of periodically updating the Bulletin 17B guidelines in light of advances in our understanding and methods, the Hydrologic Frequency Analysis Work Group (HFAWG) was charged by the Subcommittee on Hydrology (SOH) of the Advisory Committee on Water Information (ACWI) to consider possible updates to Bulletin 17B.</p><p>The purpose of this report is to consider the statistical performance of possible revisions to Bulletin 17B procedures. Of particular interest are procedures designed to accommodate more general forms of flood information. The concern is how the proposed procedures would affect the precision, accuracy and robustness of flood-frequency estimates. The investigations reported here focus on techniques for the following:</p><ul><li>incorporating information related to historical flooding that occurred outside the period of systematic streamgaging; and</li><li>identification of potentially influential low floods (PILFs).</li></ul><p>The proposed changes, which mostly involve generalizing Bulletin 17B’s method-of-moments procedures by using the Expected Moments Algorithm (EMA), are relatively modest, at least in the sense that they would not affect the main features of Bulletin 17B. The proposed methods include the following:</p><ul><li>continued use of the log-Pearson Type 3 (LP3) distribution;</li><li>continued use of the Method-of-Moments fitting method applied to the logarithms of annual-peak-flow data; and</li><li>a generalization of the Grubbs-Beck test used in Bulletin 17B to identify low outliers. The new multiple Grubbs-Beck test is sensitive to multiple PILFs.</li></ul><p>The hydrological literature already provides extensive support for the theory behind the proposed changes. The remaining question is practical: How well do the proposed methods perform under typical and realistic conditions and, specifically, with difficult records occasionally encountered in practice? In order to answer these questions, the HFAWG commissioned the work reported here. The following four major sets of results are provided:</p><ul><li>Monte Carlo simulations of fitting procedures employing data drawn from simulated LP3 populations;</li><li>Monte Carlo simulations of fitting procedures employing data drawn from non-LP3 populations that were selected to reflect likely deviations of flood series from LP3 distributions, based on the experience of HFAWG members;</li><li>a direct comparison of the fitted LP3 distributions for 82 real “test sites” identified by an independent data group as both “typical” and “challenging” for flood-frequency estimation; and</li><li>simulations of fitting procedures using records obtained by resampling with replacement from the longest of the 82 test-site records.</li></ul><p>Collectively, these studies provide a reasonably comprehensive, valid, and robust assessment of the properties of the Bulletin 17B methods and proposed alternatives. The experiments and analysis indicate that the flood quantile estimators, proposed as a revision of Bulletin 17B, do the following:</p><ul><li>perform generally as well as, and in some cases much better than, Bulletin 17B estimators in terms of the mean square error of flood quantiles estimates;</li><li>allow for incorporation and efficient statistical treatment of broader classes of flood-frequency data and information, including historical information, binomial data and interval data; and</li><li>generally confirm studies and the theoretical findings reported in the hydrological literature that would support use of updated estimation procedures that have been developed since Bulletin 17B was published.</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171064","collaboration":" ","usgsCitation":"Cohn, T.A., Barth, N.A., England, J.F., Jr., Faber, B.A., Mason, R.R., Jr., and Stedinger, J.R., 2019, Evaluation of recommended revisions to Bulletin 17B: U.S. Geological Survey Open-File Report 2017–1064, 141 p., https://doi.org/10.3133/ofr20171064.","productDescription":"xii, 141 p.","numberOfPages":"158","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065341","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":361297,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1064/ofr20171064.pdf","text":"Report","size":"15.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1064"},{"id":361296,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1064/coverthb.jpg"}],"contact":"<p>Chief, Analysis and Prediction Branch<br>Integrated Modeling and Prediction Division<br>Water Mission Area<br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Mail Stop 415<br>Reston, VA 20192</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Literature Sources: The History of Flooding and Flood Risk Estimation</li><li>Metrics for Evaluating Flood-Frequency Estimators</li><li>Estimation</li><li>Comparisons of Methods</li><li>Examples Based on Real Data at Selected Test Sites</li><li>Conclusions</li><li>References Cited</li><li>Appendix 1. Characteristics of 82 Test Sites</li><li>Appendix 2. Graphical Comparisons Between the EMA and B17B at 82 Test Sites</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-02-21","noUsgsAuthors":false,"publicationDate":"2019-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Cohn, Timothy A. tacohn@usgs.gov","contributorId":2927,"corporation":false,"usgs":true,"family":"Cohn","given":"Timothy A.","email":"tacohn@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":757590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Nancy A.  0000-0002-7060-8244","orcid":"https://orcid.org/0000-0002-7060-8244","contributorId":213309,"corporation":false,"usgs":false,"family":"Barth","given":"Nancy A. ","affiliations":[{"id":38734,"text":"former employee","active":true,"usgs":false}],"preferred":false,"id":757408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"England, John F. Jr. 0000-0001-5563-6274","orcid":"https://orcid.org/0000-0001-5563-6274","contributorId":213310,"corporation":false,"usgs":false,"family":"England","given":"John","suffix":"Jr.","email":"","middleInitial":"F.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":757409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faber, Beth A.","contributorId":213311,"corporation":false,"usgs":false,"family":"Faber","given":"Beth","email":"","middleInitial":"A.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":757410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mason,, Robert R. Jr. 0000-0002-3998-3468 rrmason@usgs.gov","orcid":"https://orcid.org/0000-0002-3998-3468","contributorId":176493,"corporation":false,"usgs":true,"family":"Mason,","given":"Robert R.","suffix":"Jr.","email":"rrmason@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":false,"id":757411,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stedinger, Jery R. 0000-0002-7081-729X","orcid":"https://orcid.org/0000-0002-7081-729X","contributorId":213312,"corporation":false,"usgs":false,"family":"Stedinger","given":"Jery R.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":757412,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70228331,"text":"70228331 - 2019 - Spatial ecology of closely-related taxa: The case of the little shearwater complex in the North Atlantic Ocean","interactions":[],"lastModifiedDate":"2022-02-09T18:22:16.947611","indexId":"70228331","displayToPublicDate":"2019-02-21T12:03:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3810,"text":"Zoological Journal of the Linnean Society","active":true,"publicationSubtype":{"id":10}},"title":"Spatial ecology of closely-related taxa: The case of the little shearwater complex in the North Atlantic Ocean","docAbstract":"<p><span>Seabirds inhabiting vast water masses provide numerous examples where opposing phenomena, such as natal and breeding philopatry vs. vagility have dug cryptic taxonomic boundaries among closely related taxa. The taxonomy of little shearwaters of the North Atlantic Ocean (Little–Audubon’s shearwater complex,&nbsp;</span><i>Puffinus assimilis</i><span>–</span><i>lherminieri</i><span>) still remains unclear, and complementary information on non-breeding distributions and at-sea behaviour becomes essential to unravel divergent local adaptations to specific habitats. Using miniaturized light-level geolocators from seven study areas in the North Atlantic, we evaluate the spatial and habitat segregation, estimate the timing of their key life-cycle events and describe the at-sea behaviour of three taxa of these little shearwaters year-round to distinguish ecological patterns and specializations that could ultimately unravel potential lineage divergences. We also assess morphometric data from birds that were breeding at each study area to further discuss potential adaptations to specific habitats. Our results show that, while birds from different taxa segregated in space and habitats, they share ecological plasticity, similar annual phenology and diel foraging behaviour. These ecological inconsistencies, while defining the evolutionary stressors faced by these taxa, do not suggest the existence of three Evolutionary Significant Units. However, they confirm the recent evolutionary divergence among the three little shearwaters of the North Atlantic.</span></p>","language":"English","publisher":"Oxford University Press on behalf of The Linnean Society of London","doi":"10.1093/zoolinnean/zlaa045","usgsCitation":"Ramos, R., Paiva, V., Zajikova, Z., Precheur, C., Mackin, W., Fagundes, A., Jodice, P.G., Zino, F., Gonzalez-Solis, J., and Bretagnolle, V., 2019, Spatial ecology of closely-related taxa: The case of the little shearwater complex in the North Atlantic Ocean: Zoological Journal of the Linnean Society, v. 191, no. 2, p. 482-502, https://doi.org/10.1093/zoolinnean/zlaa045.","productDescription":"21 p.","startPage":"482","endPage":"502","ipdsId":"IP-098130","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":467883,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10261/228870","text":"External Repository"},{"id":395706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North Atlantic Ocean","volume":"191","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Ramos, R.","contributorId":275186,"corporation":false,"usgs":false,"family":"Ramos","given":"R.","email":"","affiliations":[{"id":56742,"text":"Universitat de Barcelona","active":true,"usgs":false}],"preferred":false,"id":833787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paiva, V.H.","contributorId":275187,"corporation":false,"usgs":false,"family":"Paiva","given":"V.H.","affiliations":[{"id":56743,"text":"University of Coimbra","active":true,"usgs":false}],"preferred":false,"id":833788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zajikova, Z.","contributorId":275425,"corporation":false,"usgs":false,"family":"Zajikova","given":"Z.","email":"","affiliations":[],"preferred":false,"id":834076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Precheur, C.","contributorId":275188,"corporation":false,"usgs":false,"family":"Precheur","given":"C.","email":"","affiliations":[{"id":56744,"text":"Université de La Rochelle, Université des Antilles","active":true,"usgs":false}],"preferred":false,"id":833789,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mackin, William","contributorId":275426,"corporation":false,"usgs":false,"family":"Mackin","given":"William","email":"","affiliations":[],"preferred":false,"id":834077,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fagundes, A.I.","contributorId":275189,"corporation":false,"usgs":false,"family":"Fagundes","given":"A.I.","affiliations":[{"id":56743,"text":"University of Coimbra","active":true,"usgs":false}],"preferred":false,"id":833790,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833791,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zino, F.","contributorId":275190,"corporation":false,"usgs":false,"family":"Zino","given":"F.","affiliations":[{"id":56745,"text":"Freira Conservation Project","active":true,"usgs":false}],"preferred":false,"id":833792,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gonzalez-Solis, J.","contributorId":275192,"corporation":false,"usgs":false,"family":"Gonzalez-Solis","given":"J.","email":"","affiliations":[{"id":56742,"text":"Universitat de Barcelona","active":true,"usgs":false}],"preferred":false,"id":833794,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bretagnolle, V.","contributorId":275191,"corporation":false,"usgs":false,"family":"Bretagnolle","given":"V.","affiliations":[{"id":56746,"text":"Université des Antille","active":true,"usgs":false}],"preferred":false,"id":833793,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70202301,"text":"70202301 - 2019 - Estimating sand concentrations using ADCP‐based acoustic inversion in a large fluvial system characterized by bi‐modal suspended‐sediment distributions","interactions":[],"lastModifiedDate":"2019-06-18T10:16:40","indexId":"70202301","displayToPublicDate":"2019-02-21T11:11:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Estimating sand concentrations using ADCP‐based acoustic inversion in a large fluvial system characterized by bi‐modal suspended‐sediment distributions","docAbstract":"<p><span>Quantifying sediment flux within rivers is a challenge for many disciplines due, mainly, to difficulties inherent to traditional sediment sampling methods. These methods are operationally complex, high cost, and high risk. Additionally, the resulting data provide a low spatial and temporal resolution estimate of the total sediment flux, which has impeded advances in the understanding of the hydro‐geomorphic characteristics of rivers. Acoustic technologies have been recognized as a leading tool for increasing the resolution of sediment data by relating their echo intensity level measurements to suspended sediment. Further effort is required to robustly test and develop these techniques across a wide range of conditions found in natural river systems. This article aims to evaluate the application of acoustic inversion techniques using commercially available, down‐looking acoustic Doppler current profilers (ADCPs) in quantifying suspended sediment in a large sand bed river with varying bi‐modal particle size distributions, wash load and suspended‐sand ratios, and water stages. To achieve this objective, suspended sediment was physically sampled along the Paraná River, Argentina, under various hydro‐sedimentological regimes. Two ADCPs emitting different sound frequencies were used to simultaneously profile echo intensity level within the water column. Using the sonar equation, calibrations were determined between suspended‐sand concentrations and acoustic backscatter to solve the inverse problem. The study also analyzed the roles played by each term of the sonar equation, such as ADCP frequency, power supply, instrument constants, and particle size distributions typically found in sand bed rivers, on sediment attenuation and backscatter. Calibrations were successfully developed between corrected backscatter and suspended‐sand concentrations for all sites and ADCP frequencies, resulting in mean suspended‐sand concentration estimates within about 40% of the mean sampled concentrations. Noise values, calculated using the sonar equation and sediment sample characteristics, were fairly constant across evaluations, suggesting that they could be applied to other sand bed rivers.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/esp.4572","usgsCitation":"Szupiany, R.N., Lopez Weibel, C., Guerrero, M., Latosinski, F., Wood, M.S., Dominguez Ruben, L., and Oberg, K., 2019, Estimating sand concentrations using ADCP‐based acoustic inversion in a large fluvial system characterized by bi‐modal suspended‐sediment distributions: Earth Surface Processes and Landforms, v. 44, no. 6, p. 1295-1308, https://doi.org/10.1002/esp.4572.","productDescription":"14 p.","startPage":"1295","endPage":"1308","ipdsId":"IP-100807","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":467884,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/esp.4572","text":"External Repository"},{"id":361404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -60.934295654296875,\n              -32.11514862261243\n            ],\n            [\n              -60.29296874999999,\n              -32.11514862261243\n            ],\n            [\n              -60.29296874999999,\n              -31.421631960419596\n            ],\n            [\n              -60.934295654296875,\n              -31.421631960419596\n            ],\n            [\n              -60.934295654296875,\n              -32.11514862261243\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"44","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Szupiany, Ricardo N.","contributorId":189755,"corporation":false,"usgs":false,"family":"Szupiany","given":"Ricardo","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":757709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez Weibel, Cecilia","contributorId":189756,"corporation":false,"usgs":false,"family":"Lopez Weibel","given":"Cecilia","email":"","affiliations":[],"preferred":false,"id":757710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guerrero, Massimo","contributorId":213431,"corporation":false,"usgs":false,"family":"Guerrero","given":"Massimo","email":"","affiliations":[{"id":38756,"text":"University of Bologna, Italy","active":true,"usgs":false}],"preferred":false,"id":757711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Latosinski, Francisco","contributorId":213432,"corporation":false,"usgs":false,"family":"Latosinski","given":"Francisco","email":"","affiliations":[{"id":38757,"text":"Universidad Nacional del Litoral, Argentina","active":true,"usgs":false}],"preferred":false,"id":757712,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757707,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dominguez Ruben, Lucas","contributorId":213433,"corporation":false,"usgs":false,"family":"Dominguez Ruben","given":"Lucas","affiliations":[{"id":38757,"text":"Universidad Nacional del Litoral, Argentina","active":true,"usgs":false}],"preferred":false,"id":757713,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Oberg, Kevin 0000-0002-7024-3361 kaoberg@usgs.gov","orcid":"https://orcid.org/0000-0002-7024-3361","contributorId":175229,"corporation":false,"usgs":true,"family":"Oberg","given":"Kevin","email":"kaoberg@usgs.gov","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":757708,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70202134,"text":"ofr20191011 - 2019 - Evaluation of Chinook salmon (Oncorhynchus tshawytscha) fry survival at Lookout Point Reservoir, western Oregon, 2017","interactions":[],"lastModifiedDate":"2019-02-21T16:47:19","indexId":"ofr20191011","displayToPublicDate":"2019-02-21T08:44:09","publicationYear":"2019","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":"2019-1011","displayTitle":"Evaluation of Chinook Salmon (<em>Oncorhynchus tshawytscha</em>) Fry Survival in Lookout Point Reservoir, Western Oregon, 2017","title":"Evaluation of Chinook salmon (Oncorhynchus tshawytscha) fry survival at Lookout Point Reservoir, western Oregon, 2017","docAbstract":"<p class=\"p1\">A field study was conducted to estimate survival of fry-sized juvenile Chinook salmon (<i>Oncorhynchus tshawytscha</i>) in Lookout Point Reservoir, western Oregon, during 2017. The field study consisted of releasing three groups of genetically marked fish in the reservoir and monthly fish sampling. Fish were released during April 18–19 (43,950 fish), May 30–June 2 (44,145 fish), and on June 28, 2017 (3,920 fish). Reservoir sampling began in May and occurred monthly through October, consisting of 5-day events where juvenile Chinook salmon were collected using various gear types (electrofishing, shoreline traps, gill nets). Data were analyzed using two models: (1) a staggered release-recovery model (SRRM), and (2) a parentage-based tagging (PBT) <i>N</i>-mixture model. The SRRM provided survival estimates from two periods: (1) mid-April to late May (S<span class=\"s1\">SRRM1</span>), and (2) late May to late June (S<span class=\"s1\">SRRM2</span>). Multiple estimates of survival were possible for each period using different combinations of recovery data from the three groups of fish that were released. Survival estimates for S<span class=\"s1\">SRRM1 </span>ranged from 0.470 to 0.520. Estimates for S<span class=\"s1\">SRRM2 </span>ranged from 0.968 to 0.969; cumulative survival from mid-April to late June (S<span class=\"s1\">SRRM2</span>) was estimated at 0.870. We suspect that issues with the third release group led to biased survival results using the SRRM. The PBT <i>N</i>-mixture model provided survival estimates from six periods: (1) mid-April to mid-May (S<span class=\"s1\">NMIX1</span>), (2) mid-May to mid-June (S<span class=\"s1\">NMIX2</span>), (3) mid-June to mid-July (S<span class=\"s1\">NMIX3</span>), (4) mid-July to mid-August (S<span class=\"s1\">NMIX4</span>), (5) mid-August to mid-September (S<span class=\"s1\">NMIX5</span>), and (6) mid-September to mid-October (S<span class=\"s1\">NMIX6</span>). Survival estimates from the PBT <i>N</i>-mixture model were lowest for S<span class=\"s1\">NMIX1 </span>(0.461) and increased monthly to a high of 0.970 for S<span class=\"s1\">NMIX6</span>. Cumulative survival from mid-April to mid-July was 0.233 and overall survival from mid-April to mid-October was 0.188. This suggests that most mortality occurred early in the study when juvenile Chinook salmon were small. This could be because these fish were most vulnerable to predation in the reservoir at that time. We determined that mortality of juvenile Chinook salmon was high in the reservoir during this study and similar estimates of parr-to-smolt survival have been observed in other systems. Additional analyses are required, including results from the second year of study (2018), and potentially similar evaluations will need to be made at other locations to determine if reservoir mortality is a limiting survival factor for Chinook salmon in the Middle Fork Willamette River.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191011","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and Oregon State University","usgsCitation":"Kock, T.J., Perry, R.W., Hansen, G.S., Haner, P.V., Pope, A.C., Plumb, J.M., Cogliati, K.M., and Hansen, A.C., 2019, Evaluation of Chinook salmon (Oncorhynchus tshawytscha) fry survival at Lookout Point Reservoir, western Oregon, 2017: U.S. Geological Survey Open-File Report 2019-1011, 42 p., https://doi.org/10.3133/ofr20191011.","productDescription":"vi, 42 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-102234","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":361397,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1011/coverthb.jpg"},{"id":361398,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1011/ofr20191011.pdf","text":"Report","size":"12.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1011"}],"country":"United States","state":"Oregon","otherGeospatial":"Lookout Point Reservoir","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.89718627929688,\n              43.91768033000405\n            ],\n            [\n              -122.81410217285155,\n              43.98589821991874\n            ],\n            [\n              -122.64244079589842,\n              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PSC"},"publishedDate":"2019-02-21","noUsgsAuthors":false,"publicationDate":"2019-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Gabriel S. 0000-0001-6272-3632 ghansen@usgs.gov","orcid":"https://orcid.org/0000-0001-6272-3632","contributorId":3422,"corporation":false,"usgs":true,"family":"Hansen","given":"Gabriel","email":"ghansen@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haner, Philip V. 0000-0001-6940-487X phaner@usgs.gov","orcid":"https://orcid.org/0000-0001-6940-487X","contributorId":2364,"corporation":false,"usgs":true,"family":"Haner","given":"Philip","email":"phaner@usgs.gov","middleInitial":"V.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pope, Adam C. 0000-0002-7253-2247 apope@usgs.gov","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":5664,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","email":"apope@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":757006,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757007,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cogliati, Karen M.","contributorId":200086,"corporation":false,"usgs":false,"family":"Cogliati","given":"Karen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":757008,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hansen, Amy C. 0000-0002-0298-9137 achansen@usgs.gov","orcid":"https://orcid.org/0000-0002-0298-9137","contributorId":4350,"corporation":false,"usgs":true,"family":"Hansen","given":"Amy","email":"achansen@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757009,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70202295,"text":"70202295 - 2019 - Using the Distinct Population Segment concept to protect fishes with low levels of genomic differentiation: conservation of an endemic minnow (Hitch, Lavinia exilicauda)","interactions":[],"lastModifiedDate":"2019-03-15T12:33:32","indexId":"70202295","displayToPublicDate":"2019-02-20T16:17:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using the Distinct Population Segment concept to protect fishes with low levels of genomic differentiation: conservation of an endemic minnow (Hitch, <i>Lavinia exilicauda</i>)","title":"Using the Distinct Population Segment concept to protect fishes with low levels of genomic differentiation: conservation of an endemic minnow (Hitch, Lavinia exilicauda)","docAbstract":"<p><span>In the United States, the Endangered Species Act (ESA) of 1973 was enacted to conserve species which are endangered or threatened throughout all or a portion of their range. The definition of ‘species’ includes subspecies and distinct population segments (DPSs). In freshwater fishes, use of DPS designations has largely been restricted to salmonid fishes (Salmonidae), although the DPS concept is increasingly applied to other fishes as well. As more taxa approach threatened status, the difficult question becomes what to do when genetic evidence does not strongly support formal taxonomic designations (full species or subspecies). We examine the potential use of the DPS concept to protect fishes using the example of Hitch (</span><i>Lavinia exilicauda</i><span>), a cyprinid fish endemic to California. The Hitch is divided up into three formally described, geographically separated subspecies. However, genomic studies (RADseq), presented here with three independent analyses using a large data set, only weakly support subspecies designations. Results suggest population but not subspecies structure. Nevertheless, conventional taxonomic methods, strong contemporary isolation, the importance of protecting genetic diversity, and high cultural values still qualify all three designated subspecies for DPS status and demonstrate how taxa such as Clear Lake Hitch can warrant protection under the ESA.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10144","usgsCitation":"Baumsteiger, J., Young, M.J., and Moyle, P.B., 2019, Using the Distinct Population Segment concept to protect fishes with low levels of genomic differentiation: conservation of an endemic minnow (Hitch, Lavinia exilicauda): Transactions of the American Fisheries Society, v. 148, no. 2, p. 406-416, https://doi.org/10.1002/tafs.10144.","productDescription":"11 p.","startPage":"406","endPage":"416","ipdsId":"IP-097862","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":361396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"148","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Baumsteiger, Jason","contributorId":200425,"corporation":false,"usgs":false,"family":"Baumsteiger","given":"Jason","email":"","affiliations":[],"preferred":false,"id":757690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moyle, Peter B.","contributorId":117099,"corporation":false,"usgs":false,"family":"Moyle","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":757691,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70201134,"text":"sir20185155 - 2019 - Stochastic model for simulating Souris River Basin regulated streamflow upstream from Minot, North Dakota","interactions":[],"lastModifiedDate":"2019-02-21T16:34:58","indexId":"sir20185155","displayToPublicDate":"2019-02-20T12:45:38","publicationYear":"2019","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":"2018-5155","displayTitle":"Stochastic Model for Simulating Souris River Basin Regulated Streamflow Upstream from Minot, North Dakota","title":"Stochastic model for simulating Souris River Basin regulated streamflow upstream from Minot, North Dakota","docAbstract":"<p>The Souris River Basin is a 24,000 square-mile basin in the Provinces of Saskatchewan and Manitoba in Canada, and the State of North Dakota in the United States. Above-average snowpack during the winter of 2010–11, along with record-setting rains in May and June of 2011, led to record flooding that caused extensive damage to Minot, North Dakota, and numerous smaller communities in Saskatchewan, Manitoba, and North Dakota. As a result, the International Souris River Board created the Souris River Flood Task Force to evaluate potential reservoir operation changes and flood control measures to manage future floods and droughts. Part of this evaluation involved identifying a need for a stochastic streamflow model to estimate the likelihood of future flooding or drought.</p><p>A stochastic natural (unregulated) streamflow simulation model described in a previous report was built upon in this report to include the effects of regulation of four reservoirs (Rafferty, Alameda, and Boundary Reservoirs and Lake Darling) and their operation guidelines. First, a regulated reservoir storage/streamflow routing model was developed and calibrated from when all four reservoirs were in operation until the end of the reconstructed natural streamflow dataset provided by the U.S. Army Corps of Engineers (1992–2011). The regulated reservoir storage/streamflow routing model then was combined with the stochastic natural (unregulated) streamflow model to provide a stochastic regulated streamflow simulation model for the Souris River Basin upstream from Minot, North Dakota.</p><p>The stochastic regulated streamflow simulation model was used to estimate regulated flood frequency curves, which are useful for feasibility and design of critical structures such as levees or bridges. Three potential future climatic conditions were considered in this analysis: condition A (wet equilibrium), representing wet (similar to 1970–2017) climatic conditions; condition B (transition), representing transition from wet to dry (similar to 1912–69) climatic conditions; and condition C (dry equilibrium), representing dry climatic conditions. Comparison of the estimated flood frequency curves for regulated flow among the three climatic conditions indicated large differences in flood magnitudes for the more extreme (1-percent or less) annual exceedance probabilities. The estimated 0.2-percent annual exceedance probability flood magnitude for the Souris River upstream from Minot, N. Dak., was 29,300 cubic feet per second for condition A (wet equilibrium), compared to 14,800 cubic feet per second for condition C (dry equilibrium). For comparison, the recorded peak streamflow for 2011 for the Souris River upstream from Minot, N. Dak., was 26,900 cubic feet per second. Although it is not possible to predict how long the current (1970–2017) wet climatic conditions may persist, flood risk for at least the next 25 years, or until about 2040, may be represented best by climatic condition A.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185155","collaboration":"Prepared in cooperation with the North Dakota State Water Commission","usgsCitation":"Kolars, K.A., Vecchia, A.V., and Galloway, J.M., 2019, Stochastic model for simulating Souris River Basin regulated streamflow upstream from Minot, North Dakota: U.S. Geological Survey Scientific Investigations Report 2018–5155, 24 p., https://doi.org/10.3133/sir20185155.","productDescription":"viii, 24 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-090130","costCenters":[{"id":34685,"text":"Dakota Water Science 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         [\n              -103.568115234375,\n              48.52388120259336\n            ],\n            [\n              -104.04052734375,\n              48.99824008113872\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/dakota-water\" href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a> <br>U.S. Geological Survey<br>821 East Interstate Avenue <br>Bismarck, ND 58503</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Stochastic Regulated Streamflow Model</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-02-20","noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kolars, Kelsey A. 0000-0002-0540-3285","orcid":"https://orcid.org/0000-0002-0540-3285","contributorId":210965,"corporation":false,"usgs":true,"family":"Kolars","given":"Kelsey","email":"","middleInitial":"A.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401 avecchia@usgs.gov","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":1173,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"avecchia@usgs.gov","middleInitial":"V.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752861,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70201276,"text":"sir20185138 - 2019 - Hydraulic and water-quality indicators of aquifer zones contributing groundwater flow to wells in the Santa Fe Group aquifer system near southeast Albuquerque, New Mexico, 2013–16","interactions":[],"lastModifiedDate":"2019-05-21T16:40:24","indexId":"sir20185138","displayToPublicDate":"2019-02-20T12:03:37","publicationYear":"2019","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":"2018-5138","displayTitle":"Hydraulic and Water-Quality Indicators of Aquifer Zones Contributing Groundwater Flow to Wells in the Santa Fe Group Aquifer System near Southeast Albuquerque, New Mexico, 2013–16","title":"Hydraulic and water-quality indicators of aquifer zones contributing groundwater flow to wells in the Santa Fe Group aquifer system near southeast Albuquerque, New Mexico, 2013–16","docAbstract":"<p>An ethylene dibromide (EDB) plume extends approximately 5,880 feet northeast from the Bulk Fuels Facility on Kirtland Air Force Base. The leading edge of the EDB plume is about 3,700 feet upgradient from several water-supply wells. The water-supply wells are screened in the upper Santa Fe Group aquifer system. Within the upper Santa Fe Group, two primary clay-rich layers, the A1 and A2 units, separate water-producing zones. The U.S. Geological Survey, in cooperation with the Albuquerque Bernalillo County Water Utility Authority and the U.S. Air Force, installed four sentinel well nests and two aquifer-test pumping wells between the EDB plume and the water-supply wells. The purpose of the sentinel wells is to provide early warning of EDB plume migration towards water-supply wells. The sentinel well nests include at least three wells that are screened above, in between, and below the A1 and A2 units. The two aquifer-test pumping wells, installed for performing hydraulic tests on the aquifer system, are screened across both clay layers, as are the nearby water-supply wells. Well-bore flow logging indicated that greater than 60 percent of groundwater flow to the wells was through the deepest interval below the lowermost clay layer (A1 unit). The interval between the A1 and A2 units is the second most productive interval. Water-quality data also indicated that water drawn from the aquifer-test pumping wells and previously studied nearby water-supply wells is most similar in composition to water from the sentinel wells screened in the middle and deep intervals.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185138","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority and the U.S. Air Force","usgsCitation":"Travis, R.E., and Myers, N.C., 2019, Hydraulic and water-quality indicators of aquifer zones contributing groundwater flow to wells in the Santa Fe Group aquifer system near southeast Albuquerque, New Mexico, 2013–16 (ver. 1.1, May 2019): U.S. Geological Survey Scientific Investigations Report 2018–5138, 21 p., https://doi.org/10.3133/sir20185138.","productDescription":"v, 21 p.","numberOfPages":"32","onlineOnly":"Y","temporalStart":"2013-01-01","temporalEnd":"2016-12-31","ipdsId":"IP-093706","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":361320,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5138/coverthb3.jpg"},{"id":361321,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5138/sir20185138.pdf","text":"Report","size":"2.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5138"},{"id":363734,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5138/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2018–5138 Version History"}],"country":"United States","state":"New Mexico","county":"Bernalillo County","city":"Albuquerque","otherGeospatial":"Kirtland Air Force Base, Santa Fe Group Aquifer","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107,\n              34.9\n            ],\n            [\n              -106.33,\n              34.9\n            ],\n            [\n              -106.33,\n              35.25\n            ],\n            [\n              -107,\n              35.25\n            ],\n            [\n              -107,\n              34.9\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":" Version 1.1 : May 14, 2019","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/nm-water\" href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd. NE<br>Albuquerque, NM 87113<br></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Groundwater Flow To Wells</li><li>Summary</li><li>Acknowledgments</li><li>References</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-02-20","revisedDate":"2019-05-21","noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Travis, R. E. 0000-0001-8601-7791 rtravis@usgs.gov","orcid":"https://orcid.org/0000-0001-8601-7791","contributorId":206438,"corporation":false,"usgs":true,"family":"Travis","given":"R.","email":"rtravis@usgs.gov","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myers, Nathan C. 0000-0002-7469-3693 nmyers@usgs.gov","orcid":"https://orcid.org/0000-0002-7469-3693","contributorId":1055,"corporation":false,"usgs":true,"family":"Myers","given":"Nathan","email":"nmyers@usgs.gov","middleInitial":"C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753457,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70202282,"text":"70202282 - 2019 - Dynamic N-mixture models with temporal variability in detection probability","interactions":[],"lastModifiedDate":"2019-02-20T10:44:50","indexId":"70202282","displayToPublicDate":"2019-02-20T10:44:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic N-mixture models with temporal variability in detection probability","docAbstract":"<p><span>In theory parameters of dynamic N-mixture models can be estimated with multiple years of data without the robust design under the assumption of constant detection probability. However, such an assumption can rarely be met in long-term studies, and the consequences of violating this assumption in the inferences of dynamic N-mixture models have not been assessed. In this study we used simulation studies to evaluate inferences of the original dynamic N-mixture model and two of its spatial extensions in the face of temporal variability in detection probability. We first evaluated the dynamic N-mixture models when detection probability that varied temporally was wrongly treated as a constant. We then evaluated if the robust design was necessary for dynamic N-mixture models to provide valid parameter estimates when detection probability was correctly assumed to vary temporally. Our results showed that, when detection probability that varied temporally was wrongly treated as a constant, biases were introduced in the parameter estimates of dynamic N-mixture models. When detection probability was correctly assumed to vary temporally, the models could provide valid parameter estimates with the robust design. The model could also provide valid parameter estimates when detection probability was a random effect, even without the robust design. Based on our results, we strongly recommended considering temporal variability in detection probability when using dynamic N-mixture models to analyze long-term data and adopting the robust design in long-term surveys. Our work here is not only useful for data analysis but also important for research design, and thus are relevant to a wide range of studies.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.12.007","usgsCitation":"Zhao, Q., and Royle, J.A., 2019, Dynamic N-mixture models with temporal variability in detection probability: Ecological Modelling, v. 393, p. 20-24, https://doi.org/10.1016/j.ecolmodel.2018.12.007.","productDescription":"5 p.","startPage":"20","endPage":"24","ipdsId":"IP-103124","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":361376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"393","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhao, Qing","contributorId":213406,"corporation":false,"usgs":false,"family":"Zhao","given":"Qing","email":"","affiliations":[{"id":34045,"text":"Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523","active":true,"usgs":false}],"preferred":false,"id":757623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":757622,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227202,"text":"70227202 - 2019 - On the eruption age and provenance of the Old Crow tephra","interactions":[],"lastModifiedDate":"2022-01-04T13:38:54.208359","indexId":"70227202","displayToPublicDate":"2019-02-20T07:33:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"On the eruption age and provenance of the Old Crow tephra","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>Tephrochronology&nbsp;is used to correlate and reconstruct geographically disparate sedimentary records of changing environment, climate, and landscape throughout geologic time. Single&nbsp;tephra&nbsp;layers represent isochronous markers across broad regions, thus accurate and precise radiometric constraints on the timing of eruption are critical to their utility. The Old Crow tephra is found throughout eastern&nbsp;Beringia&nbsp;and represents the largest preserved Pleistocene ashfall event in the region. Despite its volume and significance as a stratigraphic marker, the provenance of this tephra is debated, and the interpreted eruption age of&nbsp;marine isotope stage&nbsp;(MIS) 5 at ∼125 ka has vacillated. To investigate provenance and eruption age, we develop a geochemical fingerprint for the Old Crow tephra via&nbsp;titanomagnetite&nbsp;geochemistry, and&nbsp;zircon&nbsp;crystallization/cooling age via coupled U/Pb, U/Th, and (U</span><img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\"><span>Th)/He zircon&nbsp;geochronology. Our results indicate that Old Crow oxides are geochemically distinct from the commonly assumed source-caldera system at the Emmons Lake Volcanic Center (ELVC). Zircon crystals from the Old Crow tephra range in age from Proterozoic to Pleistocene, with concordant zircon U/Pb, U/Th, and (U</span><img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\"><span>Th)/He dates on the youngest population of grains suggesting crystallization in their parent&nbsp;magma, and in turn eruption, at 202.9 ± 9.5 ka. We discuss strengths and shortcomings of our radiogenic datasets in light of this result and review the far-reaching implications of a change in Old Crow eruption age.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2018.12.026","usgsCitation":"Burgess, S.D., Coble, M., Vazquez, J.A., Coombs, M.L., and Wallace, K.L., 2019, On the eruption age and provenance of the Old Crow tephra: Quaternary Science Reviews, v. 207, p. 64-79, https://doi.org/10.1016/j.quascirev.2018.12.026.","productDescription":"16 p.","startPage":"64","endPage":"79","ipdsId":"IP-092238","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467887,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2018.12.026","text":"Publisher Index Page"},{"id":393841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -168.5302734375,\n              52.93539665862316\n            ],\n            [\n              -158.642578125,\n              52.93539665862316\n            ],\n            [\n              -158.642578125,\n              56.992882804633986\n            ],\n            [\n              -168.5302734375,\n              56.992882804633986\n            ],\n            [\n              -168.5302734375,\n              52.93539665862316\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"207","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burgess, Seth D. 0000-0002-4238-3797 sburgess@usgs.gov","orcid":"https://orcid.org/0000-0002-4238-3797","contributorId":200371,"corporation":false,"usgs":true,"family":"Burgess","given":"Seth","email":"sburgess@usgs.gov","middleInitial":"D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":830066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coble, Matthew 0000-0002-7536-0559","orcid":"https://orcid.org/0000-0002-7536-0559","contributorId":270794,"corporation":false,"usgs":false,"family":"Coble","given":"Matthew","email":"","affiliations":[{"id":56217,"text":"Victoria University of Wellington","active":true,"usgs":false}],"preferred":false,"id":830067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":830068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":830069,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":830070,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70202058,"text":"tm7C21 - 2019 - User’s guide for Assessment Tract Aggregation GUI (ATA GUI)—A graphical user interface for the AggtEx.fn R script","interactions":[],"lastModifiedDate":"2019-03-12T11:01:57","indexId":"tm7C21","displayToPublicDate":"2019-02-19T15:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C21","displayTitle":"User’s Guide for  Assessment Tract Aggregation GUI (ATA GUI)—A Graphical User Interface for the AggtEx.fn R Script","title":"User’s guide for Assessment Tract Aggregation GUI (ATA GUI)—A graphical user interface for the AggtEx.fn R script","docAbstract":"<p>The U.S. Geological Survey three-part method for mineral resource assessments estimates numbers of undiscovered mineral deposits as probability distributions in geologically defined regions termed “permissive tracts.” This report describes a graphical user interface (GUI) script developed in open-source statistical software (R) that aggregates estimated undiscovered deposits of a given type from two or more permissive tracts using the AggtEx.fn R script. The AggtEx.fn R script aggregates undiscovered deposit estimates assuming independence, total dependence, or some degree of correlation among aggregated areas, given a user-specified correlation matrix. The script outputs three sets of aggregated estimates based on those three assumptions.</p><p>The GUI script described in this report, Assessment Tract Aggregation GUI (ATA GUI), provides an easy-to-use tool that supports implementation of the AggtEx.fn R script, installation of the R packages needed to run the application, and creation of a combined input file from individual files generated by the MapMark4GUI software. Users can also use EMINERS output information by creating a file of output values following the MapMark4GUI output file format. The probabilistic estimates of aggregated undiscovered deposits produced by ATA GUI can be used as input for MapMark4GUI to estimate contained resources for the aggregated tracts. MapMark4GUI uses Monte Carlo simulation to combine undiscovered deposit estimates with tonnage and grade models to simulate undiscovered mineral resources for a region of interest. This simulation includes the amounts of commodities and rock that could be present within a permissive tract. This report includes instructions on installing and running the ATA GUI script and describes the input and output files used and created during the aggregation process.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer programs in Book 7: <i>Automated data processing and computations</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C21","collaboration":" ","usgsCitation":"Shapiro, J.L., and Robinson, G.R., Jr., 2019, User’s guide for Assessment Tract Aggregation GUI (ATA GUI)—A graphical user interface for the AggtEx.fn R script: U.S. Geological Survey Techniques and Methods, book 7, chap. C21, 9 p., https://doi.org/10.3133/tm7c21.","productDescription":"Report: iv, 9 p.; Assessment Tract Aggregation GUI Package","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098557","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":361327,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c21/coverthb.jpg"},{"id":361328,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c21/tmc721.pdf","text":"Report","size":"1.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-C21"},{"id":361329,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c21/tm7c21_ATAGUI_Package.zip","text":"Assessment Tract Aggregation GUI Package","size":"751 KB","linkFileType":{"id":6,"text":"zip"}}],"contact":"<p><a href=\"https://minerals.usgs.gov/east/index.html\" data-mce-href=\"https://minerals.usgs.gov/east/index.html\">Eastern Mineral and Environmental Resources Science Center</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>954 Mail Stop <br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Background</li><li>Assessment Tract Aggregation GUI</li><li>Assessment Tract Aggregation GUI Package</li><li>Input Files</li><li>Installation Instructions</li><li>Launching Assessment Tract Aggregation GUI</li><li>Output Files</li><li>Using the Aggregation Results to Estimate Undiscovered Resources with MapMark4GUI</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-02-19","noUsgsAuthors":false,"publicationDate":"2019-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Shapiro, Jason L. 0000-0002-7641-9735","orcid":"https://orcid.org/0000-0002-7641-9735","contributorId":204311,"corporation":false,"usgs":true,"family":"Shapiro","given":"Jason L.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":756815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Jr. 0000-0002-9676-9564","orcid":"https://orcid.org/0000-0002-9676-9564","contributorId":8479,"corporation":false,"usgs":true,"family":"Robinson","suffix":"Jr.","email":"","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":756816,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70202265,"text":"70202265 - 2019 - Occupancy models for citizen-science data","interactions":[],"lastModifiedDate":"2019-02-19T13:21:25","indexId":"70202265","displayToPublicDate":"2019-02-19T13:21:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Occupancy models for citizen-science data","docAbstract":"<ol class=\"\"><li>Large‐scale citizen‐science projects, such as atlases of species distribution, are an important source of data for macroecological research, for understanding the effects of climate change and other drivers on biodiversity, and for more applied conservation tasks, such as early‐warning systems for biodiversity loss.</li><li>However, citizen‐science data are challenging to analyse because the observation process has to be taken into account. Typically, the observation process leads to heterogeneous and non‐random sampling, false absences, false detections, and spatial correlations in the data. Increasingly, occupancy models are being used to analyse atlas data.</li><li>We advocate a dual approach to strengthen inference from citizen science data for the questions the programme is intended to address: (a) the survey design should be chosen with a particular set of questions and associated analysis strategy in mind and (b) the statistical methods should be tailored not only to those questions but also to the specific characteristics of the data.</li><li>We review the consequences of particular survey design choices that typically need to be made in atlas‐style citizen‐science projects. These include spatial resolution of the sampling units, allocation of effort in space, and collection of information about the observation process. On the analysis side, we review extensions of the basic occupancy models that are frequently necessary with atlas data, including methods for dealing with heterogeneity, non‐independent detections, false detections, and violation of the closure assumption.</li><li>New technologies, such as cell‐phone apps and fixed remote detection devices, are revolutionizing citizen‐science projects. There is an opportunity to maximize the usefulness of the resulting datasets if the protocols are rooted in robust statistical designs and data analysis issues are being considered. Our review provides guidelines for designing new projects and an overview of the current methods that can be used to analyse data from such projects.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13090","usgsCitation":"Altwegg, R., and Nichols, J.D., 2019, Occupancy models for citizen-science data: Methods in Ecology and Evolution, v. 10, no. 1, p. 8-21, https://doi.org/10.1111/2041-210X.13090.","productDescription":"14 p.","startPage":"8","endPage":"21","ipdsId":"IP-096838","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13090","text":"Publisher Index Page"},{"id":361349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Altwegg, Res","contributorId":171528,"corporation":false,"usgs":false,"family":"Altwegg","given":"Res","email":"","affiliations":[],"preferred":false,"id":757564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":200533,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":757553,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70202237,"text":"70202237 - 2019 - Improved automated detection of subpixel-scale inundation – Revised Dynamic Surface Water Extent (DSWE) partial surface water tests","interactions":[],"lastModifiedDate":"2019-02-19T11:45:14","indexId":"70202237","displayToPublicDate":"2019-02-19T11:45:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Improved automated detection of subpixel-scale inundation – Revised Dynamic Surface Water Extent (DSWE) partial surface water tests","docAbstract":"<p><span>In order to produce useful hydrologic and aquatic habitat data from the Landsat system, the U.S. Geological Survey has developed the “Dynamic Surface Water Extent” (DSWE) Landsat Science Product. DSWE will provide long-term, high-temporal resolution data on variations in inundation extent. The model used to generate DSWE is composed of five decision-rule based tests that do not require scene-based training. To allow its general application, required inputs are limited to the Landsat at-surface reflectance product and a digital elevation model. Unlike other Landsat-based water products, DSWE includes pixels that are only partially covered by water to increase inundation dynamics information content. Previously published DSWE model development included one wetland-focused test developed through visual inspection of field-collected Everglades spectra. A comparison of that test’s output against Everglades Depth Estimation Network (EDEN) in situ data confirmed the expectation that omission errors were a prime source of inaccuracy in vegetated environments. Further evaluation exposed a tendency toward commission error in coniferous forests. Improvements to the subpixel level “partial surface water” (PSW) component of DSWE was the focus of this research. Spectral mixture models were created from a variety of laboratory and image-derived endmembers. Based on the mixture modeling, a more “aggressive” PSW rule improved accuracy in herbaceous wetlands and reduced errors of commission elsewhere, while a second “conservative” test provides an alternative when commission errors must be minimized. Replication of the EDEN-based experiments using the revised PSW tests yielded a statistically significant increase in mean overall agreement (4%, p = 0.01, n = 50) and a statistically significant decrease (11%, p = 0.009, n = 50) in mean errors of omission. Because the developed spectral mixture models included image-derived vegetation endmembers and laboratory spectra for soil groups found across the US, simulations suggest where the revised DSWE PSW tests perform as they do in the Everglades and where they may prove problematic. Visual comparison of DSWE outputs with an unusual variety of coincidently collected images for locations spread throughout the US support conclusions drawn from Everglades quantitative analyses and highlight DSWE PSW component strengths and weaknesses.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs11040374","usgsCitation":"Jones, J., 2019, Improved automated detection of subpixel-scale inundation – Revised Dynamic Surface Water Extent (DSWE) partial surface water tests: Remote Sensing, v. 11, no. 4, p. 1-26, https://doi.org/10.3390/rs11040374.","productDescription":"Article 374; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-102379","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":467892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11040374","text":"Publisher Index Page"},{"id":361339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":757437,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70202260,"text":"70202260 - 2019 - Estimating uncertainty of North American landbird population sizes","interactions":[],"lastModifiedDate":"2019-02-19T11:38:08","indexId":"70202260","displayToPublicDate":"2019-02-19T11:38:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating uncertainty of North American landbird population sizes","docAbstract":"<p><span>An important metric for many aspects of species conservation planning and risk assessment is an estimate of total population size. For landbirds breeding in North America, Partners in Flight (PIF) generates global, continental, and regional population size estimates. These estimates are an important component of the PIF species assessment process, but have also been used by others for a range of applications. The PIF population size estimates are primarily calculated using a formula designed to extrapolate bird counts recorded by the North American Breeding Bird Survey (BBS) to regional population estimates. The extrapolation formula includes multiple assumptions and sources of uncertainty, but there were previously no attempts to quantify this uncertainty in the published population size estimates aside from a categorical data quality score. Using a Monte Carlo approach, we propagated the main sources of uncertainty arising from individual components of the model through to the final estimation of landbird population sizes. This approach results in distributions of population size estimates rather than point estimates. We found the width of uncertainty of population size estimates to be generally narrower than the order-of-magnitude distances between the population size score categories PIF uses in the species assessment process, suggesting confidence in the categorical ranking used by PIF. Our approach provides a means to identify species whose uncertainty bounds span more than one categorical rank, which was not previously possible with the data quality scores. Although there is still room for additional improvements to the estimation of avian population sizes and uncertainty, particularly with respect to replacing categorical model components with empirical estimates, our estimates of population size distributions have broader utility to a range of conservation planning and risk assessment activities relying on avian population size estimates.</span></p>","language":"English","publisher":"American Ornithological Society","doi":"10.5751/ACE-01331-140104","usgsCitation":"Stanton, J.C., Blancher, P.J., Rosenberg, K.V., Panjabi, A.O., and Thogmartin, W.E., 2019, Estimating uncertainty of North American landbird population sizes: Avian Conservation and Ecology, v. 14, no. 1, Article 4; 16 p., https://doi.org/10.5751/ACE-01331-140104.","productDescription":"Article 4; 16 p.","ipdsId":"IP-090781","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467893,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-01331-140104","text":"Publisher Index Page"},{"id":437569,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90SWVFU","text":"USGS data release","linkHelpText":"Population Size uncertainty estimates"},{"id":361335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":757536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blancher, Peter J.","contributorId":175182,"corporation":false,"usgs":false,"family":"Blancher","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":757537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberg, Kenneth V.","contributorId":171463,"corporation":false,"usgs":false,"family":"Rosenberg","given":"Kenneth","email":"","middleInitial":"V.","affiliations":[{"id":27615,"text":"Cornell Lab of Ornithology, Conservation Science Program","active":true,"usgs":false}],"preferred":false,"id":757538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Panjabi, Arvind O.","contributorId":169967,"corporation":false,"usgs":false,"family":"Panjabi","given":"Arvind","email":"","middleInitial":"O.","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":757539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":757540,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70200151,"text":"sir20185125 - 2019 - Potential for increased inundation in flood-prone regions of southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69","interactions":[],"lastModifiedDate":"2019-02-19T14:54:42","indexId":"sir20185125","displayToPublicDate":"2019-02-19T11:28:48","publicationYear":"2019","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":"2018-5125","displayTitle":"Potential for Increased Inundation in Flood-Prone Regions of Southeast Florida in Response to Climate and Sea-Level Changes in Broward County, Florida, 2060–69","title":"Potential for increased inundation in flood-prone regions of southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69","docAbstract":"<p>The U.S. Geological Survey, in cooperation with Broward County Environmental Planning and Resilience Division, has developed county-scale and local-scale groundwater/surface-water models to study the potential for increased inundation and flooding in eastern Broward County that are due to changes in future climate and sea-level rise. These models were constructed by using MODFLOW 2005, with the surface-water system represented by using the Surface-Water Routing process and a new Urban Runoff process. The local-scale model allowed the use of finer grid resolution in a selected area of the county, whereas the county-scale model provided boundary conditions for the local-scale model and insight into the hydrologic behavior of the larger system. The aquifer layering, properties, and boundaries relied heavily on a previous three-dimensional variable-density solute-transport model of the same area developed by the U.S. Geological Survey. The surface-water system within these new models actively simulates a part of the extensive canal network by using level-pool routing and active structure operations within the Surface-Water Routing process. These models were used to simulate a historical base-case period (1990–99) by using measured data and regional climate model rainfall and potential evapotranspiration output. The simulated flow and water-level results generally captured the behavior of the hydrologic system. A future period (2060–69) was simulated by using regional climate model rainfall and potential evapotranspiration output representing a wetter and drier future and low, intermediate, and high sea-level rise projections. The results were used to evaluate the potential effects on the surface-water drainage system, coastal-structure operation, and wet-season groundwater levels.</p><p>Future period simulations using the county-scale model indicate that (1) the effects of the changing climate and sea level are much more evident in eastern and coastal areas of Broward County compared to western areas, with increases in groundwater level nearly equivalent to sea-level rise; (2) coastal groundwater-level increases are distributed farther inland in the wetter future scenarios than in the drier future scenarios; (3) water levels at the westernmost groundwater station locations exhibited little change caused by sea-level rise and showed more dependence on changes in precipitation; (4) there was a reduced west-to-east groundwater gradient with increasing sea-level rise; and (5) increased downstream tidal stage at the S–13 structure resulted in increased reliance on the pump to control upstream inland canal stages. Future simulations using the local-scale model indicate similar behavior as seen in the county-scale model: (1) the coastal areas exhibited the largest impacts in groundwater levels in the future scenarios; (2) the westernmost, interior areas exhibited little change during the future scenarios; and (3) there was an increased reliance on the pump at the S–13 coastal structure but to a lesser extent than indicated in the county-scale model because of the reduced temporal scale of the local-scale model.</p><p>Possible adaptation and mitigation strategies were simulated to evaluate the county-scale and local-scale models’ ability to simulate hydrologic changes. Alterations to S–13 pump operations within the county-scale model were tested, and results indicate a reduced effect of sea-level rise inland of the control structure, but the affected area is spatially limited. The concept of using pumps to reduce the local groundwater levels in two neighborhood-sized areas was tested by using the local-scale model. The MODFLOW 2005 Drain package was used to remove groundwater by using drainage elevations set to zero, 1 foot, and 2 feet above average wet-season groundwater levels. Area 1 was well connected to coastal boundaries, and a high rate of groundwater removal was required, whereas the rate of groundwater removal required was greatly reduced in Area 2, which is less connected to tidal boundaries. Water for these scenarios was assumed to be pumped to tide with no downstream effects.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185125","collaboration":"Prepared in cooperation with the Broward County Environmental Planning and Resilience Division","usgsCitation":"Decker, J.D., Hughes, J.D., and Swain, E.D., 2019, Potential for increased inundation in flood-prone regions of southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69: U.S. Geological Survey Scientific Investigations Report 2018–5125, 106 p., https://doi.org/10.3133/sir20185125.","productDescription":"Report: viii, 106 p.; Data Release","numberOfPages":"118","onlineOnly":"Y","ipdsId":"IP-066244","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":361163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5125/sir20185125.pdf","text":"Report","size":"10.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5125"},{"id":361162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5125/coverthb.jpg"},{"id":361164,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E6INWZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW 2005 data sets for the simulation of potential increased inundation in flood-prone regions of Southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69"}],"country":"United States","state":"Florida","county":"Broward County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.44326782226562,\n              25.95557515483912\n            ],\n            [\n              -80.07522583007812,\n              25.95557515483912\n            ],\n            [\n              -80.07522583007812,\n              26.331576128197028\n            ],\n            [\n              -80.44326782226562,\n              26.331576128197028\n            ],\n            [\n              -80.44326782226562,\n              25.95557515483912\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\" href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\">Caribbean-Florida Water Science Center</a> <br>U.S. Geological Survey <br>4446 Pet Lane, Suite 108 <br>Lutz, FL 33559</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Simulation of the Hydrologic System for Historical Conditions During 1990–99</li><li>Effects of Climate Changes and Sea-Level Rise on Groundwater Levels, Canal Stages, and Flows at Coastal Structures</li><li>Simulation of Hypothetical Mitigation Strategies</li><li>Model Limitations</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Simulated Groundwater Response to Individual Precipitation Events</li><li>Appendix 2. Numerical Model Construction</li><li>Appendix 3. Sensitivity Testing of Numerical Models</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-02-19","noUsgsAuthors":false,"publicationDate":"2019-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Decker, Jeremy D. 0000-0002-0700-515X","orcid":"https://orcid.org/0000-0002-0700-515X","contributorId":202857,"corporation":false,"usgs":true,"family":"Decker","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748293,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":748294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748295,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70205813,"text":"70205813 - 2019 - The effects of topographic surveying technique and data resolution on the detection and interpretation of geomorphic change","interactions":[],"lastModifiedDate":"2019-10-04T10:30:15","indexId":"70205813","displayToPublicDate":"2019-02-19T10:21:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"The effects of topographic surveying technique and data resolution on the detection and interpretation of geomorphic change","docAbstract":"<p><span>Change detection of high resolution topographic data is commonly used in river valleys to quantify reach- and site-scale&nbsp;sediment budgets&nbsp;by estimating the erosion/deposition volume, and to interpret the&nbsp;geomorphic processes&nbsp;driving erosion and deposition.&nbsp;Field survey&nbsp;data are typically collected as point clouds that are often converted to gridded&nbsp;raster&nbsp;datasets and the ultimate choice of grid resolution is left to the user. This choice may have important implications for both the quantification and interpretation of&nbsp;geomorphic change. Here we used concurrent topographic data collected by&nbsp;terrestrial laser scanning&nbsp;(TLS) and structure-from-motion (SfM)&nbsp;photogrammetry&nbsp;to quantify the influence of grid resolution and sampling technique on (a) the sediment budget and (b) the presence and role of geomorphic processes (i.e., alluvial, colluvial, aeolian, and fluvial transport) driving topographic change at four sites along the Colorado River in Grand Canyon, Arizona, USA. We found that while both techniques produced similar estimates for site-scale sediment budgets, the magnitude of detected topographic change was dampened at coarser pixel resolutions. An overall decrease in the areal extent of erosion and deposition were observed, respectively, when coarsening pixel size from 5</span><span>&nbsp;</span><span>cm to 1</span><span>&nbsp;</span><span>m among all sites. Coarser resolution data tended to affect interpretation of landscape change along the margins of river valleys. For example, when changing from 5</span><span>&nbsp;</span><span>cm to 1</span><span>&nbsp;</span><span>m pixel resolution, the inferred contribution of aeolian changes to total site-scale geomorphic change increased in area by 7.9%, whereas the inferred contribution of alluvial and colluvial processes decreased in area by 97.9% and 88.2%, respectively. More generally, we found that coarsening pixel sizes disproportionately attributed geomorphic change to one or more of the most common processes operating at a site. We also found that coarsening pixel resolution amplified the net sediment imbalance at the site scale, driving the imbalance at erosional sites further into erosion and vice versa for depositional sites. Our results have implications both for point cloud data collection and for raster dataset processing. We argue that selecting the finest obtainable resolution is not always warranted to accurately quantify and interpret geomorphic change, because&nbsp;remote sensing&nbsp;technique, topographic data resolution, and analysis procedure can be optimized to capture the spatial scale of those processes driving landscape change. However, in landscapes at or near sediment equilibrium (i.e., equal amounts of erosion and deposition), the finest obtainable topographic data resolution is warranted to avoid amplifying sediment imbalance and erroneously inferring that sites are trending toward erosion or deposition.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2019.02.020","usgsCitation":"Kasprak, A., Bransky, N., Sankey, J.B., Caster, J., and Sankey, T.T., 2019, The effects of topographic surveying technique and data resolution on the detection and interpretation of geomorphic change: Geomorphology, v. 333, p. 1-15, https://doi.org/10.1016/j.geomorph.2019.02.020.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-102800","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":467895,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2019.02.020","text":"Publisher Index Page"},{"id":368004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.6865234375,\n              35.70414710206052\n            ],\n            [\n              -111.4178466796875,\n              35.70414710206052\n            ],\n            [\n              -111.4178466796875,\n              36.97842095659727\n            ],\n            [\n              -113.6865234375,\n              36.97842095659727\n            ],\n            [\n              -113.6865234375,\n              35.70414710206052\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"333","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128 akasprak@usgs.gov","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":190848,"corporation":false,"usgs":true,"family":"Kasprak","given":"Alan","email":"akasprak@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":772462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bransky, Nathaniel D.","contributorId":219526,"corporation":false,"usgs":false,"family":"Bransky","given":"Nathaniel D.","affiliations":[],"preferred":false,"id":772463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":772464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":772465,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sankey, Temulen T.","contributorId":214481,"corporation":false,"usgs":false,"family":"Sankey","given":"Temulen","email":"","middleInitial":"T.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":772466,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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