Crustal pathways connecting deep sources of melt and the active volcanoes they supply are poorly understood. Beneath Mounts St. Helens, Adams, and Rainier these pathways connect subduction-induced ascending melts to shallow magma reservoirs. Petrogenetic modeling predicts that when these melts are emplaced as a succession of sills into the lower crust they generate deep crustal hot zones. While these zones are increasingly recognized as a primary site for silicic differentiation at a range of volcanic settings globally, imaging them remains challenging. Near Mount Rainier, ascending melt has previously been imaged ~28 km northwest of the volcano, while to the south, the volcano lies on the margin of a broad conductive region in the deep crust. Using 3D full-waveform tomography, we reveal an expansive low-velocity zone, which we interpret as a possible hot zone, linking ascending melts and shallow reservoirs. This hot zone may supply evolved magmas to Mounts St. Helens and Adams, and possibly Rainier, and could contain approximately twice the melt volume as the total eruptive products of all three volcanoes combined. Hot zones like this may be the primary reservoirs for arc volcanism, influencing compositional variations and spatial-segmentation along the entire 1100 km-long Cascades Arc.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-017-07123-w","usgsCitation":"Flinders, A.F., and Shen, Y., 2017, Seismic evidence for a possible deep crustal hot zone beneath Southwest Washington: Scientific Reports, v. 7, Article 7400; 10 p., https://doi.org/10.1038/s41598-017-07123-w.","productDescription":"Article 7400; 10 p.","ipdsId":"IP-077970","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469452,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-017-07123-w","text":"Publisher Index Page"},{"id":346465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 46\n ],\n [\n -121,\n 46\n ],\n [\n -121,\n 47.4\n ],\n [\n -123,\n 47.4\n ],\n [\n -123,\n 46\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-07","publicationStatus":"PW","scienceBaseUri":"59defbb3e4b05fe04ccd3d41","contributors":{"authors":[{"text":"Flinders, Ashton F. 0000-0003-2483-4635 aflinders@usgs.gov","orcid":"https://orcid.org/0000-0003-2483-4635","contributorId":196960,"corporation":false,"usgs":true,"family":"Flinders","given":"Ashton","email":"aflinders@usgs.gov","middleInitial":"F.","affiliations":[{"id":153,"text":"California Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":712091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shen, Yang","contributorId":196961,"corporation":false,"usgs":false,"family":"Shen","given":"Yang","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":712092,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191369,"text":"70191369 - 2017 - Domestic well locations and populations served in the contiguous U.S.: 1990","interactions":[],"lastModifiedDate":"2017-10-07T09:58:10","indexId":"70191369","displayToPublicDate":"2017-10-07T00:00:00","publicationYear":"2017","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":"Domestic well locations and populations served in the contiguous U.S.: 1990","docAbstract":"We estimate the location and population served by domestic wells in the contiguous United States in two ways: (1) the “Block Group Method” or BGM, uses data from the 1990 census, and (2) the “Road-Enhanced Method” or REM, refines the locations by using a buffer expansion and shrinkage technique along roadways to define areas where domestic wells exist. The fundamental assumption is that houses (and therefore domestic wells) are located near a named road. The results are presented as two nationally-consistent domestic-well population datasets.
While both methods can be considered valid, the REM map is more precise in locating domestic wells; the REM map has a smaller amount of spatial bias (Type 1 and Type 2 errors nearly equal vs biased in Type 1), total error (10.9% vs 23.7%), and distance error (2.0 km vs 2.7 km), when comparing the REM and BGM maps to a calibration map in California. However, the BGM map is more inclusive of all potential locations for domestic wells. Independent domestic well datasets from the USGS, and the States of MN, NV, and TX show that the BGM captures about 5 to 10% more wells than the REM.
One key difference between the BGM and the REM is the mapping of low density areas. The REM reduces areas mapped as low density by 57%, concentrating populations into denser regions. Therefore, if one is trying to capture all of the potential areas of domestic-well usage, then the BGM map may be more applicable. If location is more imperative, then the REM map is better at identifying areas of the landscape with the highest probability of finding a domestic well. Depending on the purpose of a study, a combination of both maps can be used.
Understanding patterns of habitat selection across a species’ geographic distribution can be critical for adequately managing populations and planning for habitat loss and related threats. However, studies of habitat selection can be time consuming and expensive over broad spatial scales, and a lack of standardized monitoring targets or methods can impede the generalization of site-based studies. Our objective was to collaborate with natural resource managers to define available nesting habitat for piping plovers (Charadrius melodus) throughout their U.S. Atlantic coast distribution from Maine to North Carolina, with a goal of providing science that could inform habitat management in response to sea-level rise. We characterized a data collection and analysis approach as being effective if it provided low-cost collection of standardized habitat-selection data across the species’ breeding range within 1–2 nesting seasons and accurate nesting location predictions. In the method developed, >30 managers and conservation practitioners from government agencies and private organizations used a smartphone application, “iPlover,” to collect data on landcover characteristics at piping plover nest locations and random points on 83 beaches and barrier islands in 2014 and 2015. We analyzed these data with a Bayesian network that predicted the probability a specific combination of landcover variables would be associated with a nesting site. Although we focused on a shorebird, our approach can be modified for other taxa. Results showed that the Bayesian network performed well in predicting habitat availability and confirmed predicted habitat preferences across the Atlantic coast breeding range of the piping plover. We used the Bayesian network to map areas with a high probability of containing nesting habitat on the Rockaway Peninsula in New York, USA, as an example application. Our approach facilitated the collation of evidence-based information on habitat selection from many locations and sources, which can be used in management and decision-making applications.
In March 2008, a new volcanic vent opened within Halemaʻumaʻu, a crater at the summit of Kīlauea Volcano in Hawaiʻi Volcanoes National Park on the Island of Hawaiʻi. This new vent is one of two ongoing eruptions on the volcano. The other is on Kīlauea’s East Rift Zone, where vents have been erupting nearly nonstop since 1983. The duration of these simultaneous summit and rift zone eruptions on Kīlauea is unmatched in at least 200 years.
Since 2008, Kīlauea’s summit eruption has consisted of continuous degassing, occasional explosive events, and an active, circulating lava lake. Because of ongoing volcanic hazards associated with the summit vent, including the emission of high levels of sulfur dioxide gas and fragments of hot lava and rock explosively hurled onto the crater rim, the area around Halemaʻumaʻu remains closed to the public as of 2017.
Through historical photos of past Halemaʻumaʻu eruptions and stunning 4K imagery of the current eruption, this 24-minute program tells the story of Kīlauea Volcano’s summit lava lake—now one of the two largest lava lakes in the world. It begins with a Hawaiian chant that expresses traditional observations of a bubbling lava lake and reflects the connections between science and culture that continue on Kīlauea today.
The video briefly recounts the eruptive history of Halemaʻumaʻu and describes the formation and continued growth of the current summit vent and lava lake. It features USGS Hawaiian Volcano Observatory scientists sharing their insights on the summit eruption—how they monitor the lava lake, how and why the lake level rises and falls, why explosive events occur, the connection between Kīlauea’s ongoing summit and East Rift Zone eruptions, and the impacts of the summit eruption on the Island of Hawaiʻi and beyond. The video is also available at the following U.S. Geological Survey Multimedia Gallery link (video hosted on YouTube): Kīlauea summit eruption—Lava returns to Halemaʻumaʻu
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip182","usgsCitation":"Babb, J.L., Wessells, S.M., and Neal, C.A., 2017, Kīlauea summit eruption—Lava returns to Halemaʻumaʻu: U.S. Geological Survey General Information Product 182, video, 24 minutes, https://doi.org/10.3133/gip182.","productDescription":"Video: 24 minutes; Transcript; Subtitles","onlineOnly":"Y","ipdsId":"IP-090208","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":346514,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/182/gip182subtitles.srt","text":"Subtitles SRT","size":"24 KB","description":"GIP 182"},{"id":346515,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://www.usgs.gov/media/videos/k-lauea-summit-eruption-lava-returns-halema-uma-u","text":"Kīlauea summit eruption—Lava returns to Halemaʻumaʻu","description":"GIP 182","linkHelpText":" - From the U.S. Geological Survey Multimedia Gallery (video hosted on YouTube)"},{"id":346428,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/gip/182/gip182_lowresolution.mp4","text":"Movie (MP4) Small","size":"215 MB","description":"GIP 182"},{"id":346429,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/gip/182/gip182_highresolution.mp4","text":"Movie (MP4) Large","size":"2.9 GB","description":"GIP 182"},{"id":346427,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/182/gip182.transcript.pdf","text":"Transcript","size":"115 KB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 182"},{"id":346246,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/182/coverthb.jpg"},{"id":346460,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/gip/182/gip182_midresolution.mp4","text":"Movie (MP4) Medium","size":"1.1 GB","description":"GIP 182"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.30118942260742,\n 19.390019824987313\n ],\n [\n -155.23475646972656,\n 19.390019824987313\n ],\n [\n -155.23475646972656,\n 19.43907564961802\n ],\n [\n -155.30118942260742,\n 19.43907564961802\n ],\n [\n -155.30118942260742,\n 19.390019824987313\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Hawaiian Volcano Observatory
U.S. Geological Survey
P.O. Box 51
Hawaiʻi Volcanoes National Park, HI 96718-0051
askHVO@usgs.gov
Director
U.S. Geological Survey, South Atlantic Water Science Center
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
(803) 750-6100
https://www.usgs.gov/centers/sa-water
Groundwater-quality data were collected from 559 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program from January through December 2014. The data were collected from four types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; and enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some constituents of special interest (arsenic speciation, chromium [VI] and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1063","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Arnold, T.L., Bexfield, L.M., Musgrove, MaryLynn, Lindsey, B.D., Stackelberg, P.E., Barlow, J.R., DeSimone, L.A., Kulongoski, J.T., Kingsbury, J.A., Ayotte, J.D., Fleming, B.J., and Belitz, Kenneth, 2017, Groundwater-quality data from the National Water-Quality Assessment Project, January through December 2014 and select quality-control data from May 2012 through December 2014: U.S. Geological Survey Data Series 1063, 83 p., https://doi.org/10.3133/ds1063.","productDescription":"Report: viii, 83 p.; Data Release","numberOfPages":"96","onlineOnly":"Y","ipdsId":"IP-079602","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":346378,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7W0942N","text":"USGS 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\"}}]}\n","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801-2347
https://il.water.usgs.gov/
The National Park Service (NPS) manages the Nation’s most iconic destinations that attract millions of visitors from across the Nation and around the world. Trip-related spending by NPS visitors generates and supports a considerable amount of economic activity within park gateway communities. This economic effects analysis measures how NPS visitor spending cycles through local economies, generating business sales and supporting jobs and income.
In 2016, the National Park System received an estimated 330,971,689 recreation visits. Visitors to National Parks spent an estimated \\$18.4 billion in local gateway regions (defined as communities within 60 miles of a park). The contribution of this spending to the national economy was 318 thousand jobs, \\$12.0 billion in labor income, \\$19.9 billion in value added, and \\$34.9 billion in economic output. The lodging sector saw the highest direct contributions with \\$5.7 billion in economic output directly contributed to local gateway economies nationally. The sector with the next greatest direct contributions was the restaurants and bars sector, with \\$3.7 billion in economic output directly contributed to local gateway economies nationally.Results from the Visitor Spending Effects report series are available online via an interactive tool. Users can view year-by-year trend data and explore current year visitor spending, jobs, labor income, value added, and economic output effects by sector for national, state, and local economies. This interactive tool is available at https://www.nps.gov/subjects/socialscience/vse.htm.
","language":"English","publisher":"National Park Service","usgsCitation":"Cullinane Thomas, C., and Koontz, L., 2017, 2016 National Park visitor spending effects: Economic contributions to local communities, states, and the Nation: Natural Resource Report NPS/NRSS/EQD/NRR—2017/1421, v, 38 p.","productDescription":"v, 38 p.","numberOfPages":"48","ipdsId":"IP-084996","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":346440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346422,"type":{"id":15,"text":"Index Page"},"url":"https://www.nps.gov/nature/customcf/NPS_Data_Visualization/docs/2016_VSE.pdf"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d7449be4b05fe04cc7e2f3","contributors":{"authors":[{"text":"Cullinane Thomas, Catherine 0000-0001-8168-1271 ccullinanethomas@usgs.gov","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":141097,"corporation":false,"usgs":true,"family":"Cullinane Thomas","given":"Catherine","email":"ccullinanethomas@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":712038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koontz, Lynne koontzl@usgs.gov","contributorId":2174,"corporation":false,"usgs":false,"family":"Koontz","given":"Lynne","email":"koontzl@usgs.gov","affiliations":[{"id":7016,"text":"Environmental Quality Division, National Park Service, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":712039,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191346,"text":"70191346 - 2017 - Ice duration drives winter nitrate accumulation in north temperate lakes","interactions":[],"lastModifiedDate":"2017-10-26T09:46:08","indexId":"70191346","displayToPublicDate":"2017-10-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Ice duration drives winter nitrate accumulation in north temperate lakes","docAbstract":"The duration of winter ice cover on lakes varies substantially with climate variability, and has decreased over the last several decades in many temperate lakes. However, little is known of how changes in seasonal ice cover may affect biogeochemical processes under ice. We examined winter nitrogen (N) dynamics under ice using a 30+ yr dataset from five oligotrophic/mesotrophic north temperate lakes to determine how changes in inorganic N species varied with ice duration. Nitrate accumulated during winter and was strongly related to the number of days since ice-on. Exogenous inputs accounted for less than 3% of nitrate accumulation in four of the five lakes, suggesting a paramount role of nitrification in regulating N transformation and the timing of chemical conditions under ice. Winter nitrate accumulation rates ranged from 0.15 μg N L−1 d−1 to 2.7 μg N L−1 d−1 (0.011–0.19 μM d−1), and the mean for intermediate depths was 0.94 μg N L−1 d−1(0.067 μM d−1). Given that winters with shorter ice duration (< 120 d) have become more frequent in these lakes since the late 1990s, peak winter nitrate concentrations and cumulative nitrate production under ice may be declining. As ice extent and duration change, the physical and chemical conditions supporting life will shift. This research suggests we may expect changes in the form and amount of inorganic N, and altered dissolved nitrogen : phosphorus ratios, in lakes during winters with shorter ice duration.
","language":"English","publisher":"ASLO","doi":"10.1002/lol2.10048","usgsCitation":"Powers, S.M., Labou, S.G., Baulch, H.M., Hunt, R.J., Lottig, N.R., Hampton, S.E., and Stanley, E.H., 2017, Ice duration drives winter nitrate accumulation in north temperate lakes: Limnology and Oceanography Letters, v. 2, no. 5, p. 177-186, https://doi.org/10.1002/lol2.10048.","productDescription":"12 p.","startPage":"177","endPage":"186","ipdsId":"IP-082184","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":469455,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lol2.10048","text":"Publisher Index Page"},{"id":346432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-13","publicationStatus":"PW","scienceBaseUri":"59d7449ce4b05fe04cc7e2f8","contributors":{"authors":[{"text":"Powers, Steven M","contributorId":196949,"corporation":false,"usgs":false,"family":"Powers","given":"Steven","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":712024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Labou, Stephanie G.","contributorId":194571,"corporation":false,"usgs":false,"family":"Labou","given":"Stephanie","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":712025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baulch, Helen M.","contributorId":194573,"corporation":false,"usgs":false,"family":"Baulch","given":"Helen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":712026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712023,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lottig, Noah R.","contributorId":172031,"corporation":false,"usgs":false,"family":"Lottig","given":"Noah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":712027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hampton, Stephanie E.","contributorId":178718,"corporation":false,"usgs":false,"family":"Hampton","given":"Stephanie","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":712028,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":712029,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70191344,"text":"70191344 - 2017 - Spatial early warning signals in a lake manipulation","interactions":[],"lastModifiedDate":"2017-12-19T09:38:09","indexId":"70191344","displayToPublicDate":"2017-10-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Spatial early warning signals in a lake manipulation","docAbstract":"Rapid changes in state have been documented for many of Earth's ecosystems. Despite a growing toolbox of methods for detecting declining resilience or early warning indicators (EWIs) of ecosystem transitions, these methods have rarely been evaluated in whole-ecosystem trials using reference ecosystems. In this study, we experimentally tested EWIs of cyanobacteria blooms based on changes in the spatial structure of a lake. We induced a cyanobacteria bloom by adding nutrients to an experimental lake and mapped fine-resolution spatial patterning of cyanobacteria using a mobile sensor platform. Prior to the bloom, we detected theoretically predicted spatial EWIs based on variance and spatial autocorrelation, as well as a new index based on the extreme values. Changes in EWIs were not discernible in an unenriched reference lake. Despite the fluid environment of a lake where spatial heterogeneity driven by biological processes may be overwhelmed by physical mixing, spatial EWIs detected an approaching bloom suggesting the utility of spatial metrics for signaling ecological thresholds.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1941","usgsCitation":"Butitta, V.L., Carpenter, S.R., Loken, L.C., Pace, M.L., and Stanley, E.H., 2017, Spatial early warning signals in a lake manipulation: Ecosphere, v. 8, no. 5, p. 1-11, https://doi.org/10.1002/ecs2.1941.","productDescription":"e01941; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-084890","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":469456,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1941","text":"Publisher Index Page"},{"id":346434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-02","publicationStatus":"PW","scienceBaseUri":"59d7449ce4b05fe04cc7e2fc","contributors":{"authors":[{"text":"Butitta, Vince L. 0000-0001-7569-4770","orcid":"https://orcid.org/0000-0001-7569-4770","contributorId":196947,"corporation":false,"usgs":false,"family":"Butitta","given":"Vince","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":712019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carpenter, Stephen R. 0000-0001-8097-8700","orcid":"https://orcid.org/0000-0001-8097-8700","contributorId":196945,"corporation":false,"usgs":false,"family":"Carpenter","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":712017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pace, Michael L. 0000-0001-5945-6131","orcid":"https://orcid.org/0000-0001-5945-6131","contributorId":196946,"corporation":false,"usgs":false,"family":"Pace","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":712018,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":712016,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190780,"text":"ofr20171114 - 2017 - User’s Manual for the National Water Information System of the U.S. Geological Survey: Aggregate Water-Use Data System, Version 3.2","interactions":[],"lastModifiedDate":"2017-10-10T11:40:29","indexId":"ofr20171114","displayToPublicDate":"2017-10-04T03:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1114","title":"User’s Manual for the National Water Information System of the U.S. Geological Survey: Aggregate Water-Use Data System, Version 3.2","docAbstract":"The Aggregate Water-Use Data System (AWUDS) is the database management system used to enter, store, and analyze state aggregate water-use data. It is part of the U.S. Geological Survey National Water Information System. AWUDS has a graphical user interface that facilitates data entry, revision, review, and approval. This document provides information on the basic functions of AWUDS and the steps for carrying out common tasks that are a part of compiling an aggregated dataset. Also included are explanations of terminology and descriptions of user-interface structure, procedures for using the AWUDS operations, and dataset-naming conventions. Information on water-use category definitions, data-collection methods, and data sources are found in the report “Guidelines for preparation of State water-use estimates,” available at https://pubs.er.usgs.gov/publication/ofr20171029.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171114","usgsCitation":"Nawyn, J.P., Sargent, B.P., Hoopes, B.C., Augenstein, T.W., Rowland, K.M., and Barber, N.L., 2017, User’s Manual for the National Water Information System of the U.S. Geological Survey: Aggregate Water-Use Data System, Version 3.2: U.S. Geological Survey Open-File Report 2017–1114, 29 p., https://doi.org/10.3133/ofr20171114.","productDescription":"iv, 29 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-088071","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":346324,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1114/coverthb.jpg"},{"id":346325,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1114/ofr20171114.pdf","text":"Report","size":".99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1114"}],"contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
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Lawrenceville, NJ 08648
or visit our website
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Many large rivers around the world no longer flow to their deltas, due to ever greater water withdrawals and diversions for human needs. However, the importance of riparian ecosystems is drawing increasing recognition, leading to the allocation of environmental flows to restore river processes. Accurate estimates of riparian plant evapotranspiration (ET) are needed to understand how the riverine system responds to these rare events and achieve the goals of environmental flows. In 2014, historic environmental flows were released into the Lower Colorado River at Morelos Dam (Mexico); this once perennial but now dry reach is the final stretch to the mighty Colorado River Delta. One of the primary goals was to supply native vegetation restoration sites along the reach with water to help seedlings establish and boost groundwater levels to foster the planted saplings. Patterns in ET before, during, and after the flows are useful for evaluating whether this goal was met and understanding the role that ET plays in this now ephemeral river system. Here, diurnal fluctuations in groundwater levels and MODIS data were used to compare estimates of ET specifically at three native vegetation restoration sites during 2014 planned flow events, while MODIS data was used to evaluate long-term (2002 – 2016) ET responses to restoration efforts at these sites. Overall, ET was generally 0 - 10 mm d-1 across sites and although daily ET values from groundwater data were highly variable, weekly averaged estimates were highly correlated with MODIS-derived estimates at most sites. The influence of the 2014 flow events was not immediately apparent in the results, although the process of clearing vegetation and planting native vegetation at the restoration sites was clearly visible in the results.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11359","usgsCitation":"Shanafield, M., Jurado, H.G., Burgueno, J.E., Hernandez, J.R., Jarchow, C., and Nagler, P.L., 2017, Short-term and long-term evapotranspiration rates at ecological restoration sites along a large river receiving rare flow events: Hydrological Processes, v. 31, no. 24, p. 4328-4337, https://doi.org/10.1002/hyp.11359.","productDescription":"10 p.","startPage":"4328","endPage":"4337","ipdsId":"IP-068603","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469457,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.11359","text":"Publisher Index Page"},{"id":346385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","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 -115.08453369140625,\n 32.217448573031014\n ],\n [\n -114.63821411132812,\n 32.217448573031014\n ],\n [\n -114.63821411132812,\n 32.751477587458865\n ],\n [\n -115.08453369140625,\n 32.751477587458865\n ],\n [\n -115.08453369140625,\n 32.217448573031014\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"24","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-17","publicationStatus":"PW","scienceBaseUri":"59d5f342e4b05fe04cc652b8","contributors":{"authors":[{"text":"Shanafield, Margaret","contributorId":196916,"corporation":false,"usgs":false,"family":"Shanafield","given":"Margaret","email":"","affiliations":[],"preferred":false,"id":711930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurado, Hugo Gutierrez","contributorId":196917,"corporation":false,"usgs":false,"family":"Jurado","given":"Hugo","email":"","middleInitial":"Gutierrez","affiliations":[],"preferred":false,"id":711931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burgueno, Jesus Eliana Rodriguez","contributorId":196918,"corporation":false,"usgs":false,"family":"Burgueno","given":"Jesus","email":"","middleInitial":"Eliana Rodriguez","affiliations":[],"preferred":false,"id":711932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hernandez, Jorge Ramirez","contributorId":196919,"corporation":false,"usgs":false,"family":"Hernandez","given":"Jorge","email":"","middleInitial":"Ramirez","affiliations":[],"preferred":false,"id":711933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jarchow, Christopher 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":196069,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":711928,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":711927,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191324,"text":"70191324 - 2017 - A comparison of three federal datasets for thermoelectric water withdrawals in the United States for 2010","interactions":[],"lastModifiedDate":"2017-10-04T11:08:52","indexId":"70191324","displayToPublicDate":"2017-10-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of three federal datasets for thermoelectric water withdrawals in the United States for 2010","docAbstract":"Historically, thermoelectric water withdrawal has been estimated by the Energy Information Administration (EIA) and the U.S. Geological Survey's (USGS) water-use compilations. Recently, the USGS developed models for estimating withdrawal at thermoelectric plants to provide estimates independent from plant operator-reported withdrawal data. This article compares three federal datasets of thermoelectric withdrawals for the United States in 2010: one based on the USGS water-use compilation, another based on EIA data, and the third based on USGS model-estimated data. The withdrawal data varied widely. Many plants had three different withdrawal values, and for approximately 54% of the plants the largest withdrawal value was twice the smallest, or larger. The causes of discrepancies among withdrawal estimates included definitional differences, definitional noise, and various nondefinitional causes. The uncertainty in national totals can be characterized by the range among the three datasets, from 5,640 m3/s (129 billion gallons per day [bgd]) to 6,954 m3/s (158 bgd), or by the aggregate difference between the smallest and largest values at each plant, from 4,014 m3/s (92 bgd) to 8,590 m3/s (196 bgd). When used to assess the accuracy of reported values, the USGS model estimates identify plants that need to be reviewed.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12551","usgsCitation":"Harris, M.A., and Diehl, T.H., 2017, A comparison of three federal datasets for thermoelectric water withdrawals in the United States for 2010: Journal of the American Water Resources Association, v. 53, no. 5, p. 1062-1080, https://doi.org/10.1111/1752-1688.12551.","productDescription":"19 p.","startPage":"1062","endPage":"1080","ipdsId":"IP-072613","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":469458,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12551","text":"Publisher Index Page"},{"id":438193,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HX19VW","text":"USGS data release","linkHelpText":"Thermoelectric power plant water withdrawals and associated attributes for three Federal datasets in the United States, 2010"},{"id":346380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-09","publicationStatus":"PW","scienceBaseUri":"59d5f344e4b05fe04cc652c1","contributors":{"authors":[{"text":"Harris, Melissa A. 0000-0003-2659-9763 mharris@usgs.gov","orcid":"https://orcid.org/0000-0003-2659-9763","contributorId":1903,"corporation":false,"usgs":true,"family":"Harris","given":"Melissa","email":"mharris@usgs.gov","middleInitial":"A.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711925,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191322,"text":"70191322 - 2017 - Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.","interactions":[],"lastModifiedDate":"2017-12-11T13:37:05","indexId":"70191322","displayToPublicDate":"2017-10-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.","docAbstract":"We present a logistic regression approach for forecasting the probability of future groundwater levels declining or maintaining below specific groundwater-level thresholds. We tested our approach on 102 groundwater wells in different climatic regions and aquifers of the United States that are part of the U.S. Geological Survey Groundwater Climate Response Network. We evaluated the importance of current groundwater levels, precipitation, streamflow, seasonal variability, Palmer Drought Severity Index, and atmosphere/ocean indices for developing the logistic regression equations. Several diagnostics of model fit were used to evaluate the regression equations, including testing of autocorrelation of residuals, goodness-of-fit metrics, and bootstrap validation testing. The probabilistic predictions were most successful at wells with high persistence (low month-to-month variability) in their groundwater records and at wells where the groundwater level remained below the defined low threshold for sustained periods (generally three months or longer). The model fit was weakest at wells with strong seasonal variability in levels and with shorter duration low-threshold events. We identified challenges in deriving probabilistic-forecasting models and possible approaches for addressing those challenges.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12582","usgsCitation":"Dudley, R.W., Hodgkins, G.A., and Dickinson, J.E., 2017, Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.: Journal of the American Water Resources Association, v. 53, no. 6, p. 1424-1436, https://doi.org/10.1111/1752-1688.12582.","productDescription":"13 p.","startPage":"1424","endPage":"1436","ipdsId":"IP-071588","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":346381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"6","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-21","publicationStatus":"PW","scienceBaseUri":"59d5f344e4b05fe04cc652c7","contributors":{"authors":[{"text":"Dudley, Robert W. 0000-0002-0934-0568 rwdudley@usgs.gov","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":2223,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert","email":"rwdudley@usgs.gov","middleInitial":"W.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711920,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190966,"text":"fs20173075 - 2017 - Biological and ecological science for Nevada—The Silver State","interactions":[],"lastModifiedDate":"2017-10-11T14:55:41","indexId":"fs20173075","displayToPublicDate":"2017-10-04T00:00:00","publicationYear":"2017","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":"2017-3075","title":"Biological and ecological science for Nevada—The Silver State","docAbstract":"Nevada is rich in minerals, energy, rangelands, mountains, deserts, lakes, fish, and wildlife. Many enterprises critical to Nevada's economy are based on natural resources including solar energy, livestock production, hunting, fishing, and other outdoor recreation. Nevada is a national leader in both geothermal and solar utility-scale energy production, and invested more than $1.2 million in 2016 in solar development alone. Agriculture, primarily livestock production, generates more than half a billion dollars annually, and wildlife watching, hunting, and fishing contribute more than $1 billion to Nevada's economy annually.
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https://www.usgs.gov/ask/
1-888-ASK-USGS (1-888-275-8747)
A robust monitoring network that provides quantitative information about the status of imperiled species at key life stages and geographic locations over time is fundamental for sustainable management of fisheries resources. For anadromous species, management actions in one geographic domain can substantially affect abundance of subsequent life stages that span broad geographic regions. Quantitative metrics (e.g., abundance, movement, survival, life history diversity, and condition) at multiple life stages are needed to inform how management actions (e.g., hatcheries, harvest, hydrology, and habitat restoration) influence salmon population dynamics. The existing monitoring network for endangered Sacramento River winterrun Chinook Salmon (SRWRC, Oncorhynchus tshawytscha) in California’s Central Valley was compared to conceptual models developed for each life stage and geographic region of the life cycle to identify relevant SRWRC metrics. We concluded that the current monitoring network was insufficient to diagnose when (life stage) and where (geographic domain) chronic or episodic reductions in SRWRC cohorts occur, precluding within- and among-year comparisons. The strongest quantitative data exist in the Upper Sacramento River, where abundance estimates are generated for adult spawners and emigrating juveniles. However, once SRWRC leave the upper river, our knowledge of their identity, abundance, and condition diminishes, despite the juvenile monitoring enterprise. We identified six system-wide recommended actions to strengthen the value of data generated from the existing monitoring network to assess resource management actions: (1) incorporate genetic run identification; (2) develop juvenile abundance estimates; (3) collect data for life history diversity metrics at multiple life stages; (4) expand and enhance real-time fish survival and movement monitoring; (5) collect fish condition data; and (6) provide timely public access to monitoring data in open data formats. To illustrate how updated technologies can enhance the existing monitoring to provide quantitative data on SRWRC, we provide examples of how each recommendation can address specific management issues.
","language":"English","publisher":"Delta Science Program and the UC Davis John Muir Instutute of the Environment","doi":"10.15447/sfews.2017v15iss3art1","usgsCitation":"Johnson, R.C., Windell, S., Brandes, P.L., Conrad, J.L., Ferguson, J., Goertler, P.A., Harvey, B.N., Heublein, J., Isreal, J.A., Kratville, D.W., Kirsch, J.E., Perry, R.W., Pisciotto, J., Poytress, W.R., Reece, K., and Swart, B.G., 2017, Science advancements key to increasing management value of life stage monitoring networks for endangered Sacramento River winter-run Chinook salmon in California: San Francisco Estuary and Watershed Science, v. 15, no. 3, p. 1-41, https://doi.org/10.15447/sfews.2017v15iss3art1.","productDescription":"Article 1; 41 p.","startPage":"1","endPage":"41","ipdsId":"IP-076305","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":469459,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2017v15iss3art1","text":"Publisher Index Page"},{"id":346362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6019287109375,\n 37.400710068740565\n ],\n [\n -121.39343261718749,\n 37.400710068740565\n ],\n [\n -121.39343261718749,\n 40.643135583312805\n ],\n [\n -122.6019287109375,\n 40.643135583312805\n ],\n [\n -122.6019287109375,\n 37.400710068740565\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-27","publicationStatus":"PW","scienceBaseUri":"59d4a1a2e4b05fe04cc4e0d6","contributors":{"authors":[{"text":"Johnson, Rachel C.","contributorId":196877,"corporation":false,"usgs":false,"family":"Johnson","given":"Rachel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":711845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Windell, Sean","contributorId":196878,"corporation":false,"usgs":false,"family":"Windell","given":"Sean","email":"","affiliations":[],"preferred":false,"id":711846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandes, Patricia L.","contributorId":196879,"corporation":false,"usgs":false,"family":"Brandes","given":"Patricia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":711847,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrad, J. 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L.","affiliations":[],"preferred":false,"id":711850,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harvey, Brett N.","contributorId":196883,"corporation":false,"usgs":false,"family":"Harvey","given":"Brett","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":711851,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Heublein, Joseph","contributorId":196884,"corporation":false,"usgs":false,"family":"Heublein","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":711852,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Isreal, Joshua A.","contributorId":196885,"corporation":false,"usgs":false,"family":"Isreal","given":"Joshua","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":711853,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kratville, Daniel W.","contributorId":196892,"corporation":false,"usgs":false,"family":"Kratville","given":"Daniel","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":711864,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kirsch, Joseph E.","contributorId":171939,"corporation":false,"usgs":false,"family":"Kirsch","given":"Joseph","email":"","middleInitial":"E.","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":711854,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"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":711844,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pisciotto, Joseph","contributorId":196886,"corporation":false,"usgs":false,"family":"Pisciotto","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":711856,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Poytress, William R.","contributorId":196887,"corporation":false,"usgs":false,"family":"Poytress","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711857,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Reece, Kevin","contributorId":196888,"corporation":false,"usgs":false,"family":"Reece","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":711858,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Swart, Brycen G.","contributorId":196889,"corporation":false,"usgs":false,"family":"Swart","given":"Brycen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":711859,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70191276,"text":"70191276 - 2017 - UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery","interactions":[],"lastModifiedDate":"2017-10-03T10:46:10","indexId":"70191276","displayToPublicDate":"2017-10-03T00:00:00","publicationYear":"2017","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":"UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery","docAbstract":"The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy.
","language":"English","publisher":"MDPI","doi":"10.3390/rs9101020","usgsCitation":"Sturdivant, E.J., Lentz, E.E., Thieler, E.R., Farris, A.S., Weber, K.M., Remsen, D.P., Miner, S., and Henderson, R.E., 2017, UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery: Remote Sensing, v. 9, no. 10, p. 1-20, https://doi.org/10.3390/rs9101020.","productDescription":"20 p.","startPage":"1","endPage":"20","ipdsId":"IP-090271","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469461,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9101020","text":"Publisher Index Page"},{"id":438194,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KW5F04","text":"USGS data release","linkHelpText":"Topographic, imagery, and raw data associated with unmanned aerial systems (UAS) flights over Black Beach, Falmouth, Massachusetts on 18 March 2016"},{"id":346346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Buzzards Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.95451354980469,\n 41.51834634058004\n ],\n [\n -70.60089111328125,\n 41.51834634058004\n ],\n [\n -70.60089111328125,\n 41.77028745790557\n ],\n [\n -70.95451354980469,\n 41.77028745790557\n ],\n [\n -70.95451354980469,\n 41.51834634058004\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-03","publicationStatus":"PW","scienceBaseUri":"59d4a1a3e4b05fe04cc4e0da","contributors":{"authors":[{"text":"Sturdivant, Emily J. 0000-0002-2420-3115 esturdivant@usgs.gov","orcid":"https://orcid.org/0000-0002-2420-3115","contributorId":175325,"corporation":false,"usgs":true,"family":"Sturdivant","given":"Emily","email":"esturdivant@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farris, Amy S. 0000-0002-4668-7261 afarris@usgs.gov","orcid":"https://orcid.org/0000-0002-4668-7261","contributorId":196866,"corporation":false,"usgs":true,"family":"Farris","given":"Amy","email":"afarris@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weber, Kathryn M. 0000-0002-5498-7117 kweber@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-7117","contributorId":196867,"corporation":false,"usgs":true,"family":"Weber","given":"Kathryn","email":"kweber@usgs.gov","middleInitial":"M.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Remsen, David P.","contributorId":196868,"corporation":false,"usgs":false,"family":"Remsen","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":711833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miner, Simon","contributorId":196869,"corporation":false,"usgs":false,"family":"Miner","given":"Simon","email":"","affiliations":[],"preferred":false,"id":711834,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Henderson, Rachel E. 0000-0001-5810-7941 rehenderson@contractor.usgs.gov","orcid":"https://orcid.org/0000-0001-5810-7941","contributorId":196870,"corporation":false,"usgs":true,"family":"Henderson","given":"Rachel","email":"rehenderson@contractor.usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711835,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70191067,"text":"70191067 - 2017 - Program MAMO: Models for avian management optimization-user guide","interactions":[],"lastModifiedDate":"2018-01-04T09:32:10","indexId":"70191067","displayToPublicDate":"2017-10-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"TR-HCSU-077","title":"Program MAMO: Models for avian management optimization-user guide","docAbstract":"The following chapters describe the structure and code of MAMO, and walk the reader through running the different components of the program with sample data. This manual should be used alongside a computer running R, so that the reader can copy and paste code into R, observe the output, and follow along interactively. Taken together, chapters 2–4 will allow the user to replicate a simulation study investigating the consequences of climate change and two potential management actions on the population dynamics of a vulnerable and iconic Hawaiian forest bird, the ‘I‘iwi (Drepanis coccinea; hereafter IIWI).
","language":"English","publisher":"University of Hawaii at Hilo","usgsCitation":"Guillaumet, A., and Paxton, E., 2017, Program MAMO: Models for avian management optimization-user guide: Technical Report TR-HCSU-077, Report: iii, 84 p.; Code.","productDescription":"Report: iii, 84 p.; Code","ipdsId":"IP-079991","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":346356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346037,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/10790/3312"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d4a1a4e4b05fe04cc4e0e2","contributors":{"authors":[{"text":"Guillaumet, Alban","contributorId":150397,"corporation":false,"usgs":false,"family":"Guillaumet","given":"Alban","email":"","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":711083,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":711082,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191294,"text":"70191294 - 2017 - Rafinesque's Sicilian whale, Balena gastrytis","interactions":[],"lastModifiedDate":"2017-10-03T15:24:32","indexId":"70191294","displayToPublicDate":"2017-10-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":890,"text":"Archives of Natural History","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Rafinesque's Sicilian whale, Balena gastrytis","title":"Rafinesque's Sicilian whale, Balena gastrytis","docAbstract":"In 1815, the naturalist Constantine S. Rafinesque described a new species of cetacean, Balena gastrytis, from Sicily, based on a whale that stranded on Carini beach near Palermo. In comparing the characteristics of his new whale with known species, Rafinesque also took the opportunity to name a new genus, Cetoptera, to replace Balaenoptera Lacépède, 1804. Unfortunately, few of Rafinesque's contemporaries saw his article, which appeared in Il Portafoglio, a local journal that he published and distributed. The journal remains rare, and awareness of the whale remains minimal, despite its relevance to cetacean taxonomy and understanding of whale diversity and distribution in the Mediterranean. We describe the circumstances of the stranding of the Sicilian whale and provide Rafinesque's original description of the whale, as well as an evaluation of its reported characteristics and its current identity.
","language":"English","publisher":"Edinburgh University Press","doi":"10.3366/anh.2017.0446","usgsCitation":"Woodman, N., and Mead, J.G., 2017, Rafinesque's Sicilian whale, Balena gastrytis: Archives of Natural History, v. 44, no. 2, p. 229-240, https://doi.org/10.3366/anh.2017.0446.","productDescription":"12 p.","startPage":"229","endPage":"240","ipdsId":"IP-076486","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":346365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d4a1a2e4b05fe04cc4e0cd","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":711868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mead, James G.","contributorId":196893,"corporation":false,"usgs":false,"family":"Mead","given":"James","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":711869,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191300,"text":"70191300 - 2017 - Sustainability of utility-scale solar energy – critical ecological concepts","interactions":[],"lastModifiedDate":"2017-10-03T16:43:05","indexId":"70191300","displayToPublicDate":"2017-10-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Sustainability of utility-scale solar energy – critical ecological concepts","docAbstract":"Renewable energy development is an arena where ecological, political, and socioeconomic values collide. Advances in renewable energy will incur steep environmental costs to landscapes in which facilities are constructed and operated. Scientists – including those from academia, industry, and government agencies – have only recently begun to quantify trade-offs in this arena, often using ground-mounted, utility-scale solar energy facilities (USSE, ≥1 megawatt) as a model. Here, we discuss five critical ecological concepts applicable to the development of more sustainable USSE with benefits over fossil-fuel-generated energy: (1) more sustainable USSE development requires careful evaluation of trade-offs between land, energy, and ecology; (2) species responses to habitat modification by USSE vary; (3) cumulative and large-scale ecological impacts are complex and challenging to mitigate; (4) USSE development affects different types of ecosystems and requires customized design and management strategies; and (5) long-term ecological consequences associated with USSE sites must be carefully considered. These critical concepts provide a framework for reducing adverse environmental impacts, informing policy to establish and address conservation priorities, and improving energy production sustainability.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.1517","usgsCitation":"Moore-O’Leary, K.A., Hernandez, R.R., Johnston, D.S., Abella, S.R., Tanner, K.E., Swanson, A.C., Kreitler, J.R., and Lovich, J.E., 2017, Sustainability of utility-scale solar energy – critical ecological concepts: Frontiers in Ecology and the Environment, v. 15, no. 7, p. 385-394, https://doi.org/10.1002/fee.1517.","productDescription":"10 p.","startPage":"385","endPage":"394","ipdsId":"IP-070391","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469463,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.1517","text":"Publisher Index Page"},{"id":346373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-14","publicationStatus":"PW","scienceBaseUri":"59d4a1a0e4b05fe04cc4e0c5","contributors":{"authors":[{"text":"Moore-O’Leary, Kara A.","contributorId":196913,"corporation":false,"usgs":false,"family":"Moore-O’Leary","given":"Kara","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":711883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hernandez, Rebecca R.","contributorId":196899,"corporation":false,"usgs":false,"family":"Hernandez","given":"Rebecca","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnston, Dave S.","contributorId":196914,"corporation":false,"usgs":false,"family":"Johnston","given":"Dave","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":711885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abella, Scott R.","contributorId":103940,"corporation":false,"usgs":true,"family":"Abella","given":"Scott","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711886,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tanner, Karen E.","contributorId":196901,"corporation":false,"usgs":false,"family":"Tanner","given":"Karen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":711887,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Swanson, Amanda C.","contributorId":196902,"corporation":false,"usgs":false,"family":"Swanson","given":"Amanda","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":711888,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":711882,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":711889,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70191273,"text":"70191273 - 2017 - Projected atoll shoreline and run-up changes in response to sea-level rise and varying large wave conditions at Wake and Midway Atolls, Northwestern Hawaiian Islands","interactions":[],"lastModifiedDate":"2017-10-03T09:57:18","indexId":"70191273","displayToPublicDate":"2017-10-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Projected atoll shoreline and run-up changes in response to sea-level rise and varying large wave conditions at Wake and Midway Atolls, Northwestern Hawaiian Islands","docAbstract":"Atoll islands are dynamic features that respond to seasonal alterations in wave conditions and sea level. It is unclear how shoreline wave run-up and erosion patterns along these low elevation islands will respond to projected sea-level rise (SLR) and changes in wave climate over the next century, hindering communities' preparation for the future. To elucidate how these processes may respond to climate change, extreme boreal winter and summer wave conditions under future sea-level rise (SLR) and wave climate scenarios were simulated at two atolls, Wake and Midway, using a shallow-water hydrodynamic model. Nearshore wave conditions were used to compute the potential longshore sediment flux along island shorelines via the CERC empirical formula and wave-driven erosion was calculated as the divergence of the longshore drift; run-up and the locations where the run-up exceed the berm elevation were also determined. SLR is projected to predominantly drive future island morphological change and flooding. Seaward shorelines (i.e., ocean fronted shorelines directly facing incident wave energy) were projected to experience greater erosion and flooding with SLR and in hypothetical scenarios where changes to deep water wave directions were altered, as informed by previous climate change forced Pacific wave modeling efforts. These changes caused nearshore waves to become more shore-normal, increasing wave attack along previously protected shorelines. With SLR, leeward shorelines (i.e., an ocean facing shoreline but sheltered from incident wave energy) became more accretive on windward islands and marginally more erosive along leeward islands. These shorelines became more accretionary and subject to more flooding with nearshore waves becoming more shore-normal. Lagoon shorelines demonstrated the greatest SLR-driven increase in erosion and run-up. They exhibited the greatest relative change with increasing wave heights where both erosion and run-up magnitudes increased. Wider reef flat-fronted seaward shorelines became more accretive as all oceanographic forcing parameters increased in magnitude and exhibited large run-up increases following increasing wave heights. Island end shorelines became subject to increased flooding, erosion at Wake, and accretion at Midway with SLR. Under future conditions, windward and leeward islands are projected to become thinner as ocean facing and lagoonal shorelines erode, with leeward islands becoming more elongate. Island shorelines will change dramatically over the next century as SLR and altered wave climates drive new erosional regimes. It is vital to the sustainability of island communities that the relative magnitudes of these effects are addressed when planning for projected future climates.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2017.08.002","usgsCitation":"Shope, J.B., Storlazzi, C.D., and Hoeke, R., 2017, Projected atoll shoreline and run-up changes in response to sea-level rise and varying large wave conditions at Wake and Midway Atolls, Northwestern Hawaiian Islands: Geomorphology, v. 295, p. 537-550, https://doi.org/10.1016/j.geomorph.2017.08.002.","productDescription":"14 p.","startPage":"537","endPage":"550","ipdsId":"IP-079684","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469460,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2017.08.002","text":"Publisher Index Page"},{"id":346343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Midway Atoll, Wake Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 166.59135818481445,\n 19.267720754724763\n ],\n [\n 166.66070938110352,\n 19.267720754724763\n ],\n [\n 166.66070938110352,\n 19.32232118910101\n ],\n [\n 166.59135818481445,\n 19.32232118910101\n ],\n [\n 166.59135818481445,\n 19.267720754724763\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -177.41306304931638,\n 28.183704473332227\n ],\n [\n -177.31590270996094,\n 28.183704473332227\n ],\n [\n -177.31590270996094,\n 28.22727253361662\n ],\n [\n -177.41306304931638,\n 28.22727253361662\n ],\n [\n -177.41306304931638,\n 28.183704473332227\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"295","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d4a1a3e4b05fe04cc4e0de","contributors":{"authors":[{"text":"Shope, James B.","contributorId":135949,"corporation":false,"usgs":false,"family":"Shope","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":10653,"text":"University of California at Santa Cruz, Earth and Planetary Science Department","active":true,"usgs":false}],"preferred":false,"id":711812,"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":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoeke, Ron 0000-0003-0576-9436","orcid":"https://orcid.org/0000-0003-0576-9436","contributorId":196862,"corporation":false,"usgs":false,"family":"Hoeke","given":"Ron","email":"","affiliations":[],"preferred":false,"id":711813,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191290,"text":"70191290 - 2017 - Feeding ecology of the walleye (Percidae, Sander vitreus), a resurgent piscivore in Lake Huron (Laurentian Great Lakes) after shifts in the prey community","interactions":[],"lastModifiedDate":"2018-03-28T11:14:21","indexId":"70191290","displayToPublicDate":"2017-10-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Feeding ecology of the walleye (Percidae, Sander vitreus), a resurgent piscivore in Lake Huron (Laurentian Great Lakes) after shifts in the prey community","title":"Feeding ecology of the walleye (Percidae, Sander vitreus), a resurgent piscivore in Lake Huron (Laurentian Great Lakes) after shifts in the prey community","docAbstract":"Recovering populations of piscivores can challenge understanding of ecosystem function due to impacts on prey and to potentially altered food webs supporting their production. Stocks of walleye (Percidae, Sander vitreus), an apex predator in the Laurentian Great Lakes, crashed in the mid‐1900s. Management efforts led to recovery by 2009, but recovery coincided with environmental and fish community changes that also had implications for the feeding ecology of walleye. To evaluate potential changes in feeding ecology for this apex predator, we assessed diets in the main basin of Lake Huron and in Saginaw Bay, a large embayment of Lake Huron, during 2009–2011. Walleye switched their diets differently in the main basin and Saginaw Bay, with non‐native round goby (Gobiidae, Neogobius melanostomus) and rainbow smelt (Osmeridae, Osmerus mordax) more prevalent in diets in the main basin, and invertebrates, yellow perch (Percidae,Perca flavescens) and gizzard shad (Clupeidae, Dorosoma cepedianum) more prevalent in diets in the bay. Feeding strategy plots indicated that there was a high degree of individual specialisation by walleye in the bay and the main basin. Bioenergetic simulations indicated that walleye in Saginaw Bay need to consume 10%–18% more food than a walleye that spends part or all of the year in the main basin, respectively, in order to achieve the same growth rate. The differences in diets between the bay and main basin highlight the flexibility of this apex predator in the face of environmental changes, but changes in diet can alter energy pathways supporting piscivore production.
We studied home range use, spatial activity patterns, and annual survival of southern flying squirrels (SFS; Glaucomys volans) across fragmented landscapes of west-central Illinois. We calculated seasonal home range sizes and annual survival from 67 animals (36 males, 31 females) captured during 2014–2016. Home range and core area sizes were similar (P ≥ 0.46) among males and females across summer (April–September) and winter (October–March) seasons. Average distance between consecutive animal locations did not vary by sex, season, or year. Similarly, cumulative distance between consecutive locations did not vary by sex, season, or year and ranged from 1,189 to 1,661 m between summer and winter seasons. Mean annual composite home range and core area sizes were 10.39 and 1.25 ha, respectively; estimated home ranges (10.3 ha) of females are the largest documented for this species. We documented 8 deaths, all attributed to predation, the majority (63%) of which occurred during winter; annual survival was 71%. Our results underscore effects of habitat productivity on seasonal home range dynamics and space use patterns of SFS in fragmented landscapes. SFS may compensate for reduced availability of overstory mast-producing trees that characterize unproductive habitats and low-density populations by exhibiting similar movement patterns and use of available habitat by both sexes throughout the year. Winter communal nesting appears to be influenced by availability of cavity trees, thereby confirming the importance of standing snags in contributing essential habitat to flying squirrel populations in fragmented forests.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/jmammal/gyx089","usgsCitation":"Jacques, C.N., Zweep, J.S., Jenkins, S.E., and Klaver, R.W., 2017, Home range use and survival of southern flying squirrels in fragmented forest landscapes: Journal of Mammalogy, v. 98, no. 5, p. 1479-1488, https://doi.org/10.1093/jmammal/gyx089.","productDescription":"10 p.","startPage":"1479","endPage":"1488","ipdsId":"IP-078131","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469462,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyx089","text":"Publisher Index Page"},{"id":348089,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","volume":"98","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-27","publicationStatus":"PW","scienceBaseUri":"59fc2ea3e4b0531197b27f7d","contributors":{"authors":[{"text":"Jacques, Christopher N.","contributorId":15521,"corporation":false,"usgs":true,"family":"Jacques","given":"Christopher","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":719769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zweep, James S.","contributorId":199664,"corporation":false,"usgs":false,"family":"Zweep","given":"James","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":719770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenkins, Sean E.","contributorId":199666,"corporation":false,"usgs":false,"family":"Jenkins","given":"Sean","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":719771,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719146,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189003,"text":"fs20173050 - 2017 - Assessment of undiscovered oil and gas resources in the Ventura Basin Province, California, 2016","interactions":[],"lastModifiedDate":"2018-02-15T14:56:46","indexId":"fs20173050","displayToPublicDate":"2017-10-02T15:20:00","publicationYear":"2017","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":"2017-3050","title":"Assessment of undiscovered oil and gas resources in the Ventura Basin Province, California, 2016","docAbstract":"The U.S. Geological Survey (USGS) completed a geology-based assessment of undiscovered, technically recoverable conventional and continuous oil and gas resources in the part of the Ventura Basin Province that lies onshore or within State waters (within 3 miles of the shoreline) of California (fig. 1). Conventional oil and gas resources are those that have migrated upward into structural or stratigraphic traps from deep zones where the oil and gas is generated; water is present below the oil or gas. Continuous accumulations, in contrast, are those in which oil or gas is pervasively present in essentially all wells that penetrate them, that may not be structurally or stratigraphically trapped, and that typically lack oil-water or gas-water contacts. They are commonly produced with well-stimulation technology, such as hydraulic fracturing, referred to as “unconventional.” The same stimulation technology, however, is also used in many conventionally trapped accumulations. We estimated both the likely range of oil and gas volumes remaining to be discovered in accumulations similar to existing conventional oil and gas fields in the Ventura Basin Province (previously assessed by Keller [1995] as 1,060 million barrels of oil [MMBO], 1,900 billion cubic feet of gas [BCFG], and 60 million barrels of natural gas liquids [MMBNGL]), and the potential for oil and gas that might be present in a continuous accumulation at extreme depth in the floor of the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173050","usgsCitation":"Tennyson, M.E., Schenk, C.J., Pitman, J.K., Lillis, P.G., Klett, T.R., Brownfield, M.E., Finn, T.M., Gaswirth, S.B., Hawkins, S.J., Marra, K.R., Mercier, T.J., Le, P.A., and Leathers-Miller, H.M., 2017, Assessment of undiscovered oil and gas resources in the Ventura Basin Province, California, 2016: U.S. Geological Survey Fact Sheet 2017–3050, 2 p., https://doi.org/10.3133/fs20173050.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-082217","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":346251,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20153058","text":"Fact Sheet 2015-3058: ","linkHelpText":"Assessment of undiscovered continuous oil and gas resources in the Monterey Formation, San Joaquin Basin Province, California, 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U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The U.S. Geological Survey, in cooperation with the New York City Department of Environmental Protection, sampled 37 sites in the reservoir area for nutrients, major ions, metals, pesticides and their degradates, volatile organic compounds, temperature, pH, and specific conductance during fall 2015. Data collection was done to characterize the local groundwater-flow system and identify potential sources of seeps from the southern embankment at the Hillview Reservoir. Water-quality samples were collected in accordance with standard U.S. Geological Survey methods at 37 sites in and adjacent to Hillview Reservoir. These 37 sites were sampled to determine (1) baseline water-quality conditions of the saturated, low-permeability sediments that compose the earthen embankment that surrounds the reservoir, (2) water-quality conditions in the southwestern part of the study area in relation to the seeps on the embankment, and (3) temporal variation of water-quality conditions between 2006 and 2015 (not included in this report). The physical parameters and the results of the water-quality analysis from the 37 sites are included in this report and can be downloaded from the U.S. Geological Survey National Water Information System website.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1057","issn":"2327-0271","isbn":"978-1-4113-4179-1","collaboration":" Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Chu, Anthony, and Noll, M.L., 2017, Water-quality data from an earthen dam site in southern Westchester County, New York, 2015: U.S. Geological Survey Data Series 1057, 83 p., https://doi.org/10.3133/ds1057.","productDescription":"Report: vi, 83 p.; Table 2","numberOfPages":"94","onlineOnly":"N","ipdsId":"IP-084827","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":346167,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/ds1057/coverthb.jpg"},{"id":346486,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/ds1057/ds1057_table02.csv","text":"Table 2","size":"114 KB","linkFileType":{"id":7,"text":"csv"},"description":"DS 1057, Table 2","linkHelpText":"Concentrations of water-quality constituents"},{"id":346168,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/ds1057/ds1057.pdf","text":"Report","size":"2.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1057"}],"country":"United States","state":"New York","county":"Westchester County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.87413024902342,\n 40.9055340480462\n ],\n [\n -73.86451721191406,\n 40.9055340480462\n ],\n [\n -73.86451721191406,\n 40.91818248731055\n ],\n [\n -73.87413024902342,\n 40.91818248731055\n ],\n [\n -73.87413024902342,\n 40.9055340480462\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
2045 Route 112, Building 4
Coram, NY 11727
(518) 285–5602
or visit our website at
https://ny.water.usgs.gov