The east side of the Uncompahgre River Basin has been a known contributor of dissolved selenium to recipient streams. Discharge of groundwater containing dissolved selenium contributes to surface-water selenium concentrations and loads; however, the groundwater system on the east side of the Uncompahgre River Basin is not well characterized. The U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board and the Bureau of Reclamation, has established a groundwater-monitoring network on the east side of the Uncompahgre River Basin. Thirty wells total were installed for this project: 10 in 2012 (DS 923, http://dx.doi.org/10.3133/ds923), and 20 monitoring wells were installed during April and June 2014 which are presented in this report. This report presents location data, lithologic logs, well-construction diagrams, and well-development information. Understanding the groundwater system can provide managers with an additional metric for evaluating the effectiveness of salinity and selenium control projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds955","collaboration":"Prepared in cooperation with Colorado Water Conservation Board and the Bureau of Reclamation","usgsCitation":"Thomas, J.C., 2015, Installation of a groundwater monitoring-well network on the east side of the Uncompahgre River in the Lower Gunnison River Basin, Colorado, 2014: U.S. Geological Survey Data Series 955, 44 p., https://dx.doi.org/10.3133/ds955.","productDescription":"iv, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2014-04-01","temporalEnd":"2014-06-30","ipdsId":"IP-065498","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":309538,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/ds923","text":"DS 923","description":"DS 923"},{"id":309537,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0955/ds955.pdf","text":"Report","size":"8.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 955"},{"id":309536,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0955/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin, Uncompahgre River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.08349609375,\n 38.75140585784823\n ],\n [\n -107.91458129882812,\n 38.777372574181335\n ],\n [\n -107.9183578491211,\n 38.63618191259742\n ],\n [\n -107.84385681152344,\n 38.525070076783955\n ],\n [\n -107.64472961425781,\n 38.451168926369206\n ],\n [\n -107.7978515625,\n 38.36346433068098\n ],\n [\n -107.91698455810547,\n 38.49954915714596\n ],\n [\n -107.9794692993164,\n 38.55058194928367\n ],\n [\n -107.99835205078124,\n 38.65039396101565\n ],\n [\n -108.0893325805664,\n 38.74444410121545\n ],\n [\n -108.08349609375,\n 38.75140585784823\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
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","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2015-10-07","noUsgsAuthors":false,"publicationDate":"2015-10-07","publicationStatus":"PW","scienceBaseUri":"56163426e4b0ba4884c61465","contributors":{"authors":[{"text":"Thomas, Judith C. 0000-0001-7883-1419 juthomas@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":1468,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"juthomas@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572894,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70157766,"text":"ofr20151180 - 2015 - Analysis of bathymetric surveys to identify coastal vulnerabilities at Cape Canaveral, Florida","interactions":[],"lastModifiedDate":"2015-10-09T07:58:25","indexId":"ofr20151180","displayToPublicDate":"2015-10-07T10:00:00","publicationYear":"2015","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":"2015-1180","title":"Analysis of bathymetric surveys to identify coastal vulnerabilities at Cape Canaveral, Florida","docAbstract":"
Cape Canaveral, Florida, is a prominent feature along the Southeast U.S. coastline. The region includes Merritt Island National Wildlife Refuge, Cape Canaveral Air Force Station, NASA’s Kennedy Space Center, and a large portion of Canaveral National Seashore. The actual promontory of the modern Cape falls within the jurisdictional boundaries of Cape Canaveral Air Force Station. Erosion hazards result from winter and tropical storms, changes in sand resources, sediment budgets, and sea-level rise. Previous work by the USGS has focused on the vulnerability of the dunes to storms, where updated bathymetry and topography have been used for modeling efforts. Existing research indicates that submerged shoals, ridges, and sandbars affect patterns of wave refraction and height, coastal currents, and control sediment transport. These seabed anomalies indicate the availability and movement of sand within the nearshore environment, which may be directly related to the stability of the Cape Canaveral shoreline. Understanding the complex dynamics of the offshore bathymetry and associated sediment pathways can help identify current and future erosion vulnerabilities due to short-term (for example, hurricane and other extreme storms) and long-term (for example, sea-level rise) hazards.
\nThe purpose of this work is to describe an updated bathymetric dataset collected in 2014 and compare it to previous datasets. The updated data focus on the bathymetric features and sediment transport pathways that connect the offshore regions to the shoreline and, therefore, are related to the protection of other portions of the coastal environment, such as dunes, that support infrastructure and ecosystems. Previous survey data include National Oceanic and Atmospheric Administration’s (NOAA) National Ocean Service (NOS) hydrographic survey from 1956 and a USGS survey from 2010 that is augmented with NOS surveys from 2006 and 2007. The primary result of this analysis is documentation and quantification of the nature and rates of bathymetric changes that are near (within about 2.5 km) the current Cape Canaveral shoreline and interpretation of the impact of these changes on future erosion vulnerability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151180","usgsCitation":"Thompson, D.M., Plant, N.G., and Hansen, M.E., 2015, Analysis of bathymetric surveys to identify coastal vulnerabilities at Cape Canaveral, Florida: U.S. Geological Survey Open–File Report 2015–1180, 24 p., https://dx.doi.org/10.3133/ofr20151180.","productDescription":"vi, 24 p.","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064347","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309576,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1180/coverthb.jpg"},{"id":309577,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1180/ofr20151180.pdf","size":"6.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1180"},{"id":309798,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.5066/F75Q4T4N","text":"Single-Beam Bathymetry Data, Cape Canaveral, Florida, 2010","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1180"}],"country":"United States","state":"Florida","city":"Cape Canaveral","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.63003540039062,\n 28.655645954019544\n ],\n [\n -80.57098388671874,\n 28.585727616133926\n ],\n [\n -80.56549072265625,\n 28.54954469910389\n ],\n [\n -80.55450439453125,\n 28.50369515241441\n ],\n [\n -80.53390502929688,\n 28.481969987679054\n ],\n [\n -80.52429199218749,\n 28.452996148032607\n ],\n [\n -80.53939819335938,\n 28.4433364363651\n ],\n [\n -80.5572509765625,\n 28.43971381702788\n ],\n [\n -80.57235717773438,\n 28.425222099239033\n ],\n [\n -80.58059692382812,\n 28.409520499193246\n ],\n [\n -80.4913330078125,\n 28.382943257980948\n ],\n [\n -80.44876098632812,\n 28.44454394857482\n ],\n [\n -80.45150756835938,\n 28.509729126769052\n ],\n [\n -80.48171997070312,\n 28.555576049185973\n ],\n [\n -80.48858642578125,\n 28.611048252984677\n ],\n [\n -80.52703857421875,\n 28.662876227341822\n ],\n [\n -80.54351806640625,\n 28.689382962051912\n ],\n [\n -80.63003540039062,\n 28.655645954019544\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
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Biological samples from various locations on Lake Powell and in the Colorado River in the tail water downstream of Glen Canyon Dam were collected by the Bureau of Reclamation and U.S. Geological Survey from December 1990 through December 2009 as part of a long-term water-quality monitoring program that began in 1964. These samples consisted of discrete (1-m deep) chlorophyll samples, discrete (1-m deep) wholewater phytoplankton samples, and 30-m vertically composited zooplankton samples filtered through an 80-µm plankton net. Chlorophyll concentration was determined by acetone extraction followed by trichromatic spectroscopy on 2,051 samples. Phytoplankton analysis consisted of identification to the genus or species level, enumeration, and estimation of biovolume on 1,397 samples. Phytoplankton analysis identified 646 different phytoplankton taxa. Zooplankton analysis consisted of identification to the genus or species level, enumeration, and estimation of biomass from 1,898 samples. Zooplankton analysis identified 114 different zooplankton taxa.
\nThe results of these analyses are presented in this report. From this record, further interpretation may be made concerning primary and secondary production in Lake Powell. These data provide a linkage between physical and chemical water-quality data and fisheries investigations in Lake Powell. They also provide information regarding the export of biological material from Glen Canyon Dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds959","collaboration":"Prepared in cooperation with Bureau of Reclamation","usgsCitation":"Vernieu, W.S., 2015, Biological data for water in Lake Powell and from Glen Canyon Dam releases, Utah and Arizona, 1990–2009: U.S. Geological Survey Data Series 959, 12 p., https://dx.doi.org/10.3133/ds959.","productDescription":"v, 12 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1990-12-01","temporalEnd":"2009-12-31","ipdsId":"IP-041385","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":309706,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0959/coverthb.jpg"},{"id":309707,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0959/ds959.pdf","text":"Report","size":"500 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 959 PDF"}],"country":"United States","state":"Utah, Arizona","otherGeospatial":"Lake Powell, Colorado River, Glen Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.1,\n 36.5\n ],\n [\n -112.1,\n 38.1\n ],\n [\n -109.8,\n 38.1\n ],\n [\n -109.8,\n 36.5\n ],\n [\n -112.1,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC Staff, Southwest Biological Science Center
U.S. Geological Survey
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http://sbsc.wr.usgs.gov/
Naturally–occurring hybrid treefrogs have been occasionally found in the eastern United States. However, these hybrids are almost always between members of the same species group. On 10 Jun 2014, at 2145 h, we located an individual making an unusual advertisement call along Bayou Manual Road in Sherburne Wildlife Management Area in the Atchafalaya Basin of south-central Louisiana, USA, and brought it back to the laboratory for further study. Physically, the treefrog appeared intermediate between a Green Treefrog and a Cope’s Gray Treefrog, which are members of different species groups. Call analysis also showed the individual to be intermediate between the two putative parental species. Flow cytometry was used to estimate the total genome size from nuclei of whole blood cells, and also determined the individual to be intermediate of the putative parental species. Despite vocalizing for mates, the hybrid did not appear to have viable spermatozoa, and was likely the result of an anomalous mis-mating event between a male Cope’s Gray Treefrog and a female Green Treefrog. To our knowledge, natural hybrids between a Cope’s Gray Treefrog and a Green Treefrog have not been previously reported.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Glorioso, B.M., Waddle, J., Jenkins, J.A., Olivier, H.M., and Layton, R.R., 2015, Hyla chrysoscelis (Cope’s gray treefrog) x Hyla cinerea (green treefrog): putative natural hybrid: Herpetological Review, v. 46, no. 3, p. 410-411.","productDescription":"2 p.","startPage":"410","endPage":"411","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059584","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":309686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":309684,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.zenscientist.com/index.php/pdflibrary2/Open-Access-Files/ssar_public/Herpetological-Review-1967-2015/2015-Herpetological-Review-46(3)-September/"}],"country":"United States","state":"Louisiana","otherGeospatial":"Atchafalaya Basin, Sherburne Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.70150756835938,\n 30.3995298034023\n ],\n [\n -91.70150756835938,\n 30.45518486497521\n ],\n [\n -91.65172576904297,\n 30.45518486497521\n ],\n [\n -91.65172576904297,\n 30.3995298034023\n ],\n [\n -91.70150756835938,\n 30.3995298034023\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5614e2ade4b0ba4884c611a4","contributors":{"authors":[{"text":"Glorioso, Brad M. 0000-0002-5400-7414 gloriosob@usgs.gov","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":4241,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","email":"gloriosob@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":576546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. 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Quantitative fatty acid signature analysis (QFASA) is a prominent method of diet estimation, particularly for marine mammal and bird species. Investigators using QFASA commonly use computer simulation to evaluate statistical characteristics of diet estimators for the populations they study. Similar computer simulations have been used to explore and compare the performance of different variations of the original QFASA diet estimator. In both cases, computer simulations involve bootstrap sampling prey signature data to construct pseudo-predator signatures with known properties. However, bootstrap sample sizes have been selected arbitrarily and pseudo-predator signatures therefore may not have realistic properties. I develop an algorithm to objectively establish bootstrap sample sizes that generates pseudo-predator signatures with realistic properties, thereby enhancing the utility of computer simulation for assessing QFASA estimator performance. The algorithm also appears to be computationally efficient, resulting in bootstrap sample sizes that are smaller than those commonly used. I illustrate the algorithm with an example using data from Chukchi Sea polar bears (Ursus maritimus) and their marine mammal prey. The concepts underlying the approach may have value in other areas of quantitative ecology in which bootstrap samples are post-processed prior to their use.
","language":"English","publisher":"Science Direct","doi":"10.1016/j.ecoinf.2015.09.011","usgsCitation":"Bromaghin, J.F., 2015, Simulating realistic predator signatures in quantitative fatty acid signature analysis: Ecological Informatics, v. 30, p. 68-71, https://doi.org/10.1016/j.ecoinf.2015.09.011.","productDescription":"4 p.","startPage":"68","endPage":"71","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067252","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":309683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5614e2ade4b0ba4884c611a6","contributors":{"authors":[{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":576564,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70158702,"text":"70158702 - 2015 - Water availability and subsidence in California's Central Valley","interactions":[],"lastModifiedDate":"2020-12-18T17:29:13.8648","indexId":"70158702","displayToPublicDate":"2015-10-06T14:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Water availability and subsidence in California's Central Valley","docAbstract":"The Central Valley in California (USA) covers about 52,000 km2 and is one of the most productive agricultural regions in the world. This agriculture relies heavily on surface-water diversions and groundwater pumpage to meet irrigation water demand. Because the valley is semi-arid and surface-water availability varies substantially, agriculture relies heavily on local groundwater. In the southern two thirds of the valley, the San Joaquin Valley, historic and recent groundwater pumpage has caused significant and extensive drawdowns, aquifer-system compaction and subsidence. During recent drought periods (2007-2009 and 2012-present), groundwater pumping has increased owing to a combination of decreased surface-water availability and land-use changes. Declining groundwater levels, approaching or surpassing historical low levels, have caused accelerated and renewed compaction and subsidence that likely is mostly permanent. The subsidence has caused operational, maintenance, and construction-design problems for water-delivery and floodcontrol canals in the San Joaquin Valley. Planning for the effects of continued subsidence in the area is important for water agencies. As land use, managed aquifer recharge, and surface-water availability continue to vary, long-term groundwater- level and subsidence monitoring and modelling are critical to understanding the dynamics of historical and continued groundwater use resulting in additional water-level and groundwater storage declines, and associated subsidence. Modeling tools such as the Central Valley Hydrologic Model, can be used in the evaluation of management strategies to mitigate adverse impacts due to subsidence while also optimizing water availability. This knowledge will be critical for successful implementation of recent legislation aimed toward sustainable groundwater use.
","language":"English","publisher":"University of California at Davis","doi":"10.1007/s10040-015-1339-x","usgsCitation":"Faunt, C.C., Sneed, M., Traum, J.A., and Brandt, J.T., 2015, Water availability and subsidence in California's Central Valley: San Francisco Estuary and Watershed Science, v. 13, no. 3, 8 p., https://doi.org/10.1007/s10040-015-1339-x.","productDescription":"8 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068386","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-015-1339-x","text":"Publisher Index Page"},{"id":381504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.05810546875,\n 40.70562793820589\n ],\n [\n -122.86010742187499,\n 40.38839687388361\n ],\n [\n -121.95922851562501,\n 37.93553306183642\n ],\n [\n -119.54223632812501,\n 35.074964853989556\n ],\n [\n -118.740234375,\n 35.0120020431607\n ],\n [\n -118.740234375,\n 36.10237644873644\n ],\n [\n -120.728759765625,\n 38.25543637637947\n ],\n [\n -122.05810546875,\n 40.70562793820589\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-17","publicationStatus":"PW","scienceBaseUri":"5614e2afe4b0ba4884c611a8","contributors":{"authors":[{"text":"Faunt, Claudia C. ccfaunt@usgs.gov","contributorId":149018,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia","email":"ccfaunt@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":576574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":149052,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":576575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807111,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brandt, Justin T. 0000-0002-9397-6824 jbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":157,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"jbrandt@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807112,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70158665,"text":"70158665 - 2015 - Effectiveness of a refuge for lake trout in western Lake Superior I: Empirical analysis of past performance","interactions":[],"lastModifiedDate":"2016-06-01T11:52:51","indexId":"70158665","displayToPublicDate":"2015-10-06T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Effectiveness of a refuge for lake trout in western Lake Superior I: Empirical analysis of past performance","docAbstract":"The Gull Island Shoal Refuge was created in 1976 in response to overfishing of the Lake Trout Salvelinus namaycush population in the Apostle Islands region of western Lake Superior. Our objective was to evaluate effectiveness of the refuge by determining whether Lake Trout abundance, growth, maturity, and mortality differed inside and outside the refuge. We compared abundance of wild and stocked fish captured inside and outside the refuge during spring large-mesh gill-net and summer graded-mesh gill-net surveys. We compared growth and mortality during four periods corresponding to four generations of wild Lake Trout, including the last generation that hatched before the refuge was instituted (sampled in 1981–1984) and three generations that were protected by the refuge (sampled in 1985–1992, 1993–2000, and 2001–2010). Maturity of wild fish inside and outside the refuge was compared only for the latter period (2001–2010) because maturity was not assessed earlier. After the refuge was created, wild Lake Trout abundance increased and stocked Lake Trout abundance decreased. Wild adults and juveniles were more abundant inside than outside the refuge, and stocked adults were less abundant inside than outside the refuge. Growth of wild fish did not differ inside versus outside the refuge before 2001, but wild fish grew faster to a shorter asymptotic length inside than outside the refuge during 2001–2010. Wild fish matured at a similar length but an older age inside than outside the refuge during 2001–2010. Survival of wild fish did not differ inside versus outside the refuge before 1993, but mortality was lower inside than outside the refuge during later periods (1993–2000 and 2001–2010). We conclude that the Gull Island Shoal Refuge enhanced the population growth of wild Lake Trout in the Apostle Islands region and should be retained in the future to sustain conditions that favor population growth.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2015.1074959","usgsCitation":"Johnson, M.J., Hansen, M.J., and Seider, M.J., 2015, Effectiveness of a refuge for lake trout in western Lake Superior I: Empirical analysis of past performance: North American Journal of Fisheries Management, v. 35, no. 5, p. 988-1002, https://doi.org/10.1080/02755947.2015.1074959.","productDescription":"15 p.","startPage":"988","endPage":"1002","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1981-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-065170","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":309690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.99906921386719,\n 46.742213379963886\n ],\n [\n -90.99906921386719,\n 47.09069560264967\n ],\n [\n -90.37422180175781,\n 47.09069560264967\n ],\n [\n -90.37422180175781,\n 46.742213379963886\n ],\n [\n -90.99906921386719,\n 46.742213379963886\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-02","publicationStatus":"PW","scienceBaseUri":"5614e2abe4b0ba4884c611a0","contributors":{"authors":[{"text":"Johnson, Melissa J.","contributorId":148997,"corporation":false,"usgs":false,"family":"Johnson","given":"Melissa","email":"","middleInitial":"J.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":576417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Michael J. 0000-0001-8522-3876 michaelhansen@usgs.gov","orcid":"https://orcid.org/0000-0001-8522-3876","contributorId":5006,"corporation":false,"usgs":true,"family":"Hansen","given":"Michael","email":"michaelhansen@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":576416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seider, Michael J.","contributorId":19452,"corporation":false,"usgs":true,"family":"Seider","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":576418,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157070,"text":"fs20153058 - 2015 - Assessment of undiscovered continuous oil and gas resources in the Monterey Formation, San Joaquin Basin Province, California, 2015","interactions":[],"lastModifiedDate":"2018-02-15T14:57:35","indexId":"fs20153058","displayToPublicDate":"2015-10-06T11:30:00","publicationYear":"2015","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":"2015-3058","title":"Assessment of undiscovered continuous oil and gas resources in the Monterey Formation, San Joaquin Basin Province, California, 2015","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey assessed mean volumes of 21 million barrels of oil (MMBO), 27 billion cubic feet of gas, and 1 million barrels of natural gas liquids in two assessment units (AUs) that may contain continuous oil resources. Mean volumes of oil for the individual assessment units are 14 MMBO in the Monterey Buttonwillow AU and 7 MMBO in the Monterey Maricopa AU.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153058","collaboration":"Prepared in collaboration with National and Global Petroleum Assessment","usgsCitation":"Tennyson, M.E., Charpentier, R.R., Klett, T.R., Brownfield, M.E., Pitman, J.K., Gaswirth, S.B., Hawkins, S.J., Lillis, P.G., Marra, K.R., Mercier, T.J., Leathers, H.M., Schenk, C.J., and Whidden, K.J., 2015, Assessment of undiscovered continuous oil and gas resources in the Monterey Formation, San Joaquin Basin Province, California, 2015: U.S. Geological Survey Fact Sheet 2015-3058, 2 p., https://dx.doi.org/10.3133/fs20153058.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066185","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":308330,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3058/fs20153058.pdf","text":"Report","size":"797 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3058"},{"id":308329,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3058/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Monterey Formation, San Joaquin Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.16845703125,\n 34.93097858831627\n ],\n [\n -120.16845703125,\n 36.43896124085945\n ],\n [\n -118.63037109375,\n 36.43896124085945\n ],\n [\n -118.63037109375,\n 34.93097858831627\n ],\n [\n -120.16845703125,\n 34.93097858831627\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
http://energy.usgs.gov/
Statistical methods for the analysis and design of experiments using digital PCR (dPCR) have received only limited attention and have been misused in many instances. To address this issue and to provide a more general approach to the analysis of dPCR data, we describe a class of statistical models for the analysis and design of experiments that require quantification of nucleic acids. These models are mathematically equivalent to generalized linear models of binomial responses that include a complementary, log–log link function and an offset that is dependent on the dPCR partition volume. These models are both versatile and easy to fit using conventional statistical software. Covariates can be used to specify different sources of variation in nucleic acid concentration, and a model’s parameters can be used to quantify the effects of these covariates. For purposes of illustration, we analyzed dPCR data from different types of experiments, including serial dilution, evaluation of copy number variation, and quantification of gene expression. We also showed how these models can be used to help design dPCR experiments, as in selection of sample sizes needed to achieve desired levels of precision in estimates of nucleic acid concentration or to detect differences in concentration among treatments with prescribed levels of statistical power.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Washington, DC","doi":"10.1021/acs.analchem.5b02429","usgsCitation":"Dorazio, R., and Hunter, M., 2015, Statistical models for the analysis and design of digital polymerase chain (dPCR) experiments: Analytical Chemistry, v. 87, no. 21, p. 10886-10893, https://doi.org/10.1021/acs.analchem.5b02429.","productDescription":"8 p.","startPage":"10886","endPage":"10893","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066660","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":310034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"21","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-13","publicationStatus":"PW","scienceBaseUri":"56261492e4b0fb9a11dd7651","contributors":{"authors":[{"text":"Dorazio, Robert 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":149286,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":577747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Margaret 0000-0002-4760-9302 mhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":140627,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","email":"mhunter@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":577748,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70158597,"text":"70158597 - 2015 - Avian community responses to post-fire forest structure: Implications for fire management in mixed conifer forests","interactions":[],"lastModifiedDate":"2016-01-25T12:39:01","indexId":"70158597","displayToPublicDate":"2015-10-05T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Avian community responses to post-fire forest structure: Implications for fire management in mixed conifer forests","docAbstract":"Fire is a natural process and the dominant disturbance shaping plant and animal communities in many coniferous forests of the western US. Given that fire size and severity are predicted to increase in the future, it has become increasingly important to understand how wildlife responds to fire and post-fire management. The Angora Fire burned 1243 hectares of mixed conifer forest in South Lake Tahoe, California. We conducted avian point counts for the first 3 years following the fire in burned and unburned areas to investigate which habitat characteristics are most important for re-establishing or maintaining the native avian community in post-fire landscapes. We used a multi-species occurrence model to estimate how avian species are influenced by the density of live and dead trees and shrub cover. While accounting for variations in the detectability of species, our approach estimated the occurrence probabilities of all species detected including those that were rare or observed infrequently. Although all species encountered in this study were detected in burned areas, species-specific modeling results predicted that some species were strongly associated with specific post-fire conditions, such as a high density of dead trees, open-canopy conditions or high levels of shrub cover that occur at particular burn severities or at a particular time following fire. These results indicate that prescribed fire or managed wildfire which burns at low to moderate severity without at least some high-severity effects is both unlikely to result in the species assemblages that are unique to post-fire areas or to provide habitat for burn specialists. Additionally, the probability of occurrence for many species was associated with high levels of standing dead trees indicating that intensive post-fire harvest of these structures could negatively impact habitat of a considerable proportion of the avian community.
","language":"English","publisher":"Zoological Society of London","publisherLocation":"Cambridge, United Kingdom","doi":"10.1111/acv.12237","usgsCitation":"White, A.M., Manley, P.N., Tarbill, G., Richardson, T., Russell, R.E., Safford, H.D., and Dobrowski, S.Z., 2015, Avian community responses to post-fire forest structure: Implications for fire management in mixed conifer forests: Animal Conservation, 9 p., https://doi.org/10.1111/acv.12237.","productDescription":"9 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055788","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":309571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Lake Tahoe basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.1,\n 38.8\n ],\n [\n -120.1,\n 38.9\n ],\n [\n -120,\n 38.9\n ],\n [\n -120,\n 38.8\n ],\n [\n -120.1,\n 38.8\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-28","publicationStatus":"PW","scienceBaseUri":"5613911fe4b0ba4884c60f5e","contributors":{"authors":[{"text":"White, Angela M.","contributorId":84255,"corporation":false,"usgs":true,"family":"White","given":"Angela","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":576249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manley, Patricia N.","contributorId":79010,"corporation":false,"usgs":true,"family":"Manley","given":"Patricia","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":576250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tarbill, Gina","contributorId":148953,"corporation":false,"usgs":false,"family":"Tarbill","given":"Gina","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":576251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richardson, T.L.","contributorId":78607,"corporation":false,"usgs":true,"family":"Richardson","given":"T.L.","email":"","affiliations":[],"preferred":false,"id":576253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":576248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Safford, Hugh D.","contributorId":112922,"corporation":false,"usgs":true,"family":"Safford","given":"Hugh","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":576252,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dobrowski, Solomon Z.","contributorId":8751,"corporation":false,"usgs":true,"family":"Dobrowski","given":"Solomon","email":"","middleInitial":"Z.","affiliations":[],"preferred":false,"id":576254,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70158639,"text":"70158639 - 2015 - Response of the nitrogen-fixing lichen Lobaria pulmonaria to phosphorus, molybdenum, and vanadium","interactions":[],"lastModifiedDate":"2017-11-22T17:41:51","indexId":"70158639","displayToPublicDate":"2015-10-05T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Response of the nitrogen-fixing lichen Lobaria pulmonaria to phosphorus, molybdenum, and vanadium","docAbstract":"Nitrogen-fixing lichens (cyanolichens) are an important source of nitrogen (N) in Pacific Northwest forests, but limitation of lichen growth by elements essential for N fixation is poorly understood. To investigate how nutrient limitation may affect cyanolichen growth rates, we fertilized a tripartite cyanobacterial lichen (Lobaria pulmonaria) and a green algal non-nitrogen fixing lichen (Usnea longissima) with the micronutrients molybdenum (Mo) and vanadium (V), both known cofactors for enzymes involved in N fixation, and the macronutrient phosphorus (P). We then grew treated lichens in the field for one year in western Oregon, USA. Lichen growth was very rapid for both species and did not differ across treatments, despite a previous demonstration of P-limitation in L. pulmonaria at a nearby location. To reconcile these disparate findings, we analyzed P, Mo, and V concentrations, natural abundance δ15N isotopes, %N and change in thallus N in Lobaria pulmonaria from both growth experiments. Nitrogen levels in deposition and in lichens could not explain the large difference in growth or P limitation observed between the two studies. Instead, we provide evidence that local differences in P availability may have caused site-specific responses of Lobaria to P fertilization. In the previous experiment, Lobaria had low background levels of P, and treatment with P more than doubled growth. In contrast, Lobaria from the current experiment had much higher background P concentrations, similar to P-treated lichens in the previous experiment, consistent with the idea that ambient variation in P availability influences the degree of P limitation in cyanolichens. We conclude that insufficient P, Mo, and V did not limit the growth of either cyanolichens or chlorolichens at the site of the current experiment. Our findings point to the need to understand landscape-scale variation in P availability to cyanolichens, and its effect on spatial patterns of cyanolichen nutrient limitation and N fixation.
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In this study, headlands along the California coast are classified to advance understanding of headland dynamics and littoral cell boundaries in support of improved coastal management decisions. Geomorphological parameters for 78 headlands were quantified from geological maps, remote-sensing imagery, navigational charts, and shoreline geospatial databases. K-means cluster analysis grouped the headlands into eight distinct classes based on headland perimeter, bathymetric slope ratio, and the headland apex angle. Wave data were used to investigate the potential for sediment transport around the headland types and determine the efficacy of the headland as a littoral cell boundary. Four classes of headland appear to function well as littoral cell boundaries, with headland size (e.g., perimeter or area) and a marked change in nearshore bathymetry across the headland being relevant attributes. About half of the traditional California littoral cell boundaries align with headland classes that are expected to perform poorly in blocking alongshore sediment transport, calling into question these boundaries. Better definition of these littoral cell boundaries is important for regional sediment management decisions.
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Sea-level rise is particularly critical for low-lying carbonate reef-lined atoll islands; these islands have limited land and water available for human habitation, water and food sources, and ecosystems that are vulnerable to inundation from sea-level rise. Here we demonstrate that sea-level rise will result in larger waves and higher wave-driven water levels along atoll islands’ shorelines than at present. Numerical model results reveal waves will synergistically interact with sea-level rise, causing twice as much land forecast to be flooded for a given value of sea-level rise than currently predicted by current models that do not take wave-driven water levels into account. Atolls with islands close to the shallow reef crest are more likely to be subjected to greater wave-induced run-up and flooding due to sea-level rise than those with deeper reef crests farther from the islands’ shorelines. It appears that many atoll islands will be flooded annually, salinizing the limited freshwater resources and thus likely forcing inhabitants to abandon their islands in decades, not centuries, as previously thought.
","language":"English","publisher":"Nature Publishing Group","publisherLocation":"London, United Kingdom","doi":"10.1038/srep14546","collaboration":"Deltares U.S.A., Hawaii Cooperative Studies Unit","usgsCitation":"Storlazzi, C.D., Elias, E.P., and Berkowitz, P., 2015, Many atolls may be uninhabitable within decades due to climate change: Scientific Reports, v. 5, p. 1-9, https://doi.org/10.1038/srep14546.","productDescription":"Art 14546: 9 p.","startPage":"1","endPage":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063820","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471730,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep14546","text":"Publisher Index Page"},{"id":309559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Midway Atoll, Laysan Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -177.33083724975583,\n 28.21986116672942\n ],\n [\n -177.34182357788086,\n 28.213810689875928\n ],\n [\n -177.36448287963867,\n 28.21910487587188\n ],\n [\n -177.37546920776367,\n 28.221978752630008\n ],\n [\n -177.39006042480466,\n 28.217894799357122\n ],\n [\n -177.39967346191406,\n 28.18945405424149\n ],\n [\n -177.38079071044922,\n 28.194598154006137\n ],\n [\n -177.36825942993164,\n 28.197623979398678\n ],\n [\n -177.3625946044922,\n 28.203675373165503\n ],\n [\n -177.352294921875,\n 28.20382665361861\n ],\n [\n -177.32603073120117,\n 28.20231383944811\n ],\n [\n -177.31813430786133,\n 28.20791114488013\n ],\n [\n -177.31985092163086,\n 28.216835971157135\n ],\n [\n -177.33083724975583,\n 28.21986116672942\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -171.7060089111328,\n 25.7989638778495\n ],\n [\n -171.73261642456052,\n 25.732024280088133\n ],\n [\n -171.7624855041504,\n 25.74192073145334\n ],\n [\n -171.7741584777832,\n 25.774696838890705\n ],\n [\n -171.71184539794922,\n 25.800045732089465\n ],\n [\n -171.7060089111328,\n 25.7989638778495\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-25","publicationStatus":"PW","scienceBaseUri":"56139123e4b0ba4884c60f66","contributors":{"authors":[{"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":576452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elias, Edwin P.L.","contributorId":47295,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","email":"","middleInitial":"P.L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":576453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berkowitz, Paul pberkowitz@usgs.gov","contributorId":4642,"corporation":false,"usgs":true,"family":"Berkowitz","given":"Paul","email":"pberkowitz@usgs.gov","affiliations":[],"preferred":true,"id":576454,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70158666,"text":"70158666 - 2015 - Effectiveness of a refuge for Lake Trout in Western Lake Superior II: Simulation of future performance","interactions":[],"lastModifiedDate":"2016-06-01T11:53:35","indexId":"70158666","displayToPublicDate":"2015-10-05T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Effectiveness of a refuge for Lake Trout in Western Lake Superior II: Simulation of future performance","docAbstract":"Historically, Lake Superior supported one of the largest and most diverse Lake Trout Salvelinus namaycush fisheries in the Laurentian Great Lakes, but Lake Trout stocks collapsed due to excessive fishery exploitation and predation by Sea Lampreys Petromyzon marinus. Lake Trout stocking, Sea Lamprey control, and fishery regulations, including a refuge encompassing Gull Island Shoal (Apostle Islands region), were used to enable recovery of Lake Trout stocks that used this historically important spawning shoal. Our objective was to determine whether future sustainability of Lake Trout stocks will depend on the presence of the Gull Island Shoal Refuge. We constructed a stochastic age-structured simulation model to assess the effect of maintaining the refuge as a harvest management tool versus removing the refuge. In general, median abundances of age-4, age-4 and older (age-4+), and age-8+ fish collapsed at lower instantaneous fishing mortality rates (F) when the refuge was removed than when the refuge was maintained. With the refuge in place, the F that resulted in collapse depended on the rate of movement into and out of the refuge. Too many fish stayed in the refuge when movement was low (0–2%), and too many fish became vulnerable to fishing when movement was high (≥22%); thus, the refuge was more effective at intermediate rates of movement (10–11%). With the refuge in place, extinction did not occur at any simulated level of F, whereas refuge removal led to extinction at all combinations of commercial F and recreational F. Our results indicate that the Lake Trout population would be sustained by the refuge at all simulated F-values, whereas removal of the refuge would risk population collapse at much lower F (0.700–0.744). Therefore, the Gull Island Shoal Refuge is needed to sustain the Lake Trout population in eastern Wisconsin waters of Lake Superior.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/02755947.2015.1074960","usgsCitation":"Akins, A.L., Hansen, M.J., and Seider, M.J., 2015, Effectiveness of a refuge for Lake Trout in Western Lake Superior II: Simulation of future performance: North American Journal of Fisheries Management, v. 35, no. 5, p. 1003-1018, https://doi.org/10.1080/02755947.2015.1074960.","productDescription":"16 p.","startPage":"1003","endPage":"1018","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065104","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":309581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Minnesota, Wisconsin","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.451416015625,\n 48.77067246880509\n ],\n [\n -86.275634765625,\n 48.436489955944154\n ],\n [\n -85.97900390625,\n 47.931066347509784\n ],\n [\n -85.594482421875,\n 47.87214396888731\n ],\n [\n -85.111083984375,\n 47.938426929481054\n ],\n [\n -84.803466796875,\n 47.938426929481054\n ],\n [\n -84.847412109375,\n 47.81315451752768\n ],\n [\n -85.01220703125,\n 47.58393661978137\n ],\n [\n -84.88037109375,\n 47.45037978769006\n ],\n [\n -84.66064453125,\n 47.30903424774781\n ],\n [\n -84.78149414062499,\n 47.05515408550348\n ],\n [\n -84.78149414062499,\n 46.94276208682137\n ],\n [\n -84.451904296875,\n 46.875213396722685\n ],\n [\n -84.55078125,\n 46.717268685073954\n ],\n [\n -84.638671875,\n 46.53619267489863\n ],\n [\n -84.825439453125,\n 46.48326472915561\n ],\n [\n -84.979248046875,\n 46.626806395355175\n ],\n [\n -84.91333007812499,\n 46.7549166192819\n ],\n [\n -85.067138671875,\n 46.800059446787316\n ],\n [\n -85.50659179687499,\n 46.717268685073954\n ],\n [\n -86.06689453125,\n 46.694667307773116\n ],\n [\n -86.561279296875,\n 46.521075663842836\n ],\n [\n -86.8798828125,\n 46.521075663842836\n ],\n [\n -87.07763671875,\n 46.543749602738565\n ],\n [\n -87.374267578125,\n 46.521075663842836\n ],\n [\n -87.703857421875,\n 46.89023157359399\n ],\n [\n -88.231201171875,\n 46.965259400349275\n ],\n [\n -88.428955078125,\n 46.927758623434435\n ],\n [\n -88.26416015625,\n 47.092565552235705\n ],\n [\n -87.86865234374999,\n 47.30903424774781\n ],\n [\n -87.60498046875,\n 47.42065432071321\n ],\n [\n -87.923583984375,\n 47.50978034953473\n ],\n [\n -88.385009765625,\n 47.47266286861342\n ],\n [\n -88.76953125,\n 47.234489635299184\n ],\n [\n -89.483642578125,\n 46.912750956378915\n ],\n [\n -89.967041015625,\n 46.800059446787316\n ],\n [\n -90.4833984375,\n 46.619261036171515\n ],\n [\n -90.692138671875,\n 46.70973594407157\n ],\n [\n -90.94482421875,\n 46.702202151643455\n ],\n [\n -90.758056640625,\n 46.93526088057719\n ],\n [\n -90.94482421875,\n 46.93526088057719\n ],\n [\n -91.3623046875,\n 46.830133640447386\n ],\n [\n -91.845703125,\n 46.73986059969267\n ],\n [\n -92.054443359375,\n 46.7549166192819\n ],\n [\n -92.076416015625,\n 46.807579571992385\n ],\n [\n -91.395263671875,\n 47.16730970131578\n ],\n [\n -90.911865234375,\n 47.53945544742392\n ],\n [\n -90.1318359375,\n 47.80577611936809\n ],\n [\n -89.58251953125,\n 47.96785877999253\n ],\n [\n -89.26391601562499,\n 48.188063481211415\n ],\n [\n -89.23095703125,\n 48.472921272487824\n ],\n [\n -88.9013671875,\n 48.61838518688487\n ],\n [\n -88.43994140625,\n 48.90083790234088\n ],\n [\n -88.22021484375,\n 49.001843917978526\n ],\n [\n -86.451416015625,\n 48.77067246880509\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-02","publicationStatus":"PW","scienceBaseUri":"56139122e4b0ba4884c60f62","contributors":{"authors":[{"text":"Akins, Andrea L","contributorId":148998,"corporation":false,"usgs":false,"family":"Akins","given":"Andrea","email":"","middleInitial":"L","affiliations":[{"id":17613,"text":"University of Wisconsin - Stevens Point","active":true,"usgs":false}],"preferred":false,"id":576420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Michael J. 0000-0001-8522-3876 michaelhansen@usgs.gov","orcid":"https://orcid.org/0000-0001-8522-3876","contributorId":5006,"corporation":false,"usgs":true,"family":"Hansen","given":"Michael","email":"michaelhansen@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":576419,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seider, Michael J.","contributorId":19452,"corporation":false,"usgs":true,"family":"Seider","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":576421,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70158676,"text":"70158676 - 2015 - Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios","interactions":[],"lastModifiedDate":"2015-12-07T11:17:03","indexId":"70158676","displayToPublicDate":"2015-10-05T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios","docAbstract":"Hindcast and 21st century winds, simulated by General Circulation Models (GCMs), were used to drive global- and regional-scale spectral wind-wave generation models in the Pacific Ocean Basin to assess future wave conditions along the margins of the North American west coast and Hawaiian Islands. Three-hourly winds simulated by four separate GCMs were used to generate an ensemble of wave conditions for a recent historical time-period (1976–2005) and projections for the mid and latter parts of the 21st century under two radiative forcing scenarios (RCP 4.5 and RCP 8.5), as defined by the fifth phase of the Coupled Model Inter-comparison Project (CMIP5) experiments. Comparisons of results from historical simulations with wave buoy and ERA-Interim wave reanalysis data indicate acceptable model performance of wave heights, periods, and directions, giving credence to generating projections. Mean and extreme wave heights are projected to decrease along much of the North American west coast. Extreme wave heights are projected to decrease south of ∼50°N and increase to the north, whereas extreme wave periods are projected to mostly increase. Incident wave directions associated with extreme wave heights are projected to rotate clockwise at the eastern end of the Aleutian Islands and counterclockwise offshore of Southern California. Local spatial patterns of the changing wave climate are similar under the RCP 4.5 and RCP 8.5 scenarios, but stronger magnitudes of change are projected under RCP 8.5. Findings of this study are similar to previous work using CMIP3 GCMs that indicates decreasing mean and extreme wave conditions in the Eastern North Pacific, but differ from other studies with respect to magnitude and local patterns of change. This study contributes toward a larger ensemble of global and regional climate projections needed to better assess uncertainty of potential future wave climate change, and provides model boundary conditions for assessing the impacts of climate change on coastal systems.
","language":"English","publisher":"Elsevier Science Ltd","publisherLocation":"Oxford, United Kingdom","doi":"10.1016/j.ocemod.2015.07.004","collaboration":"Christie Hegermiller, UCSC; Peter Ruggiero, Oregon State University; Maarten van Ormondt, Deltares,","usgsCitation":"Erikson, L., Hegermiller, C., Barnard, P., Ruggiero, P., and van Ormondt, M., 2015, Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios: Ocean Modelling, v. 96, no. 1, p. 171-185, https://doi.org/10.1016/j.ocemod.2015.07.004.","productDescription":"15 p.","startPage":"171","endPage":"185","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051162","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -180,\n -3.513421045640032\n ],\n [\n -180,\n 65.2198939361321\n ],\n [\n -78.046875,\n 65.2198939361321\n ],\n [\n -78.046875,\n -3.513421045640032\n ],\n [\n -180,\n -3.513421045640032\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"96","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56139126e4b0ba4884c60f6a","contributors":{"authors":[{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":147149,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":576458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hegermiller, Christie 0000-0002-6383-7508 chegermiller@usgs.gov","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":149010,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","email":"chegermiller@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruggiero, Peter","contributorId":15709,"corporation":false,"usgs":false,"family":"Ruggiero","given":"Peter","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":576461,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Ormondt, Martin","contributorId":149011,"corporation":false,"usgs":false,"family":"van Ormondt","given":"Martin","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":576462,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157362,"text":"ofr20151176 - 2015 - Preliminary estimates of annual agricultural pesticide use for counties of the conterminous United States, 2013","interactions":[],"lastModifiedDate":"2016-06-29T13:17:10","indexId":"ofr20151176","displayToPublicDate":"2015-10-05T09:45:00","publicationYear":"2015","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":"2015-1176","title":"Preliminary estimates of annual agricultural pesticide use for counties of the conterminous United States, 2013","docAbstract":"This report provides preliminary estimates of annual agricultural use of 387 pesticide compounds in counties of the conterminous United States in 2013, compiled by means of methods described in Thelin and Stone (2013) and Baker and Stone (2015). U.S. Department of Agriculture county-level data for harvested-crop acreage were used in conjunction with proprietary Crop Reporting District-level pesticide-use data to estimate county-level pesticide use. Where Crop Reporting District data were not available or were incomplete, estimated pesticide use values were calculated with two different methods, resulting in a low and a high estimate based on different assumptions about missing survey data (Thelin and Stone, 2013). Preliminary estimates in this report are expected to be revised upon availability of updated crop acreages in the 2017 Agricultural Census, to be published by the U.S. Department of Agriculture in 2019. Estimates of annual agricultural pesticide use are provided as downloadable, tab-delimited files, which are organized by compound, year, state Federal Information Processing Standard (FIPS) code, county Federal Information Processing Standard code, and amount in kilograms (kg). The files, listed below, are a continuation of the 1992–2009 and 2008–2012 pesticide-use estimates reported by Stone (2013) and Baker and Stone (2015), respectively:
\nHigh estimates of county pesticide use, arranged by pesticide name:
\nTable 1. 1-Methyl Cyclopropene through Chlorantraniliprole
Table 2. Chlorethoxyfos through Diflufenzopyr
Table 3. Dimethenamid through Gibberellic Acid
Table 4. Glufosinate through Metiram
Table 5. Metolachlor through Propazine
Table 6. Propiconazole through Triasulfuron
Table 7. Tribenuron Methyl through Zoxamide
Low estimates of county pesticide use, arranged by pesticide name:
\nTable 8. 1-Methyl Cyclopropene through Chlorantraniliprole
Table 9. Chlorethoxyfos through Diflufenzopyr
Table 10. Dimethenamid through Gibberellic Acid
Table 11. Glufosinate through Metiram
Table 12. Metolachlor through Propazine
Table 13. Propiconazole through Triasulfuron
Table 14. Tribenuron Methyl through Zoxamide
Baker, N.T., and Stone, W.W., 2015, Estimated annual agricultural pesticide use for counties of the conterminous United States, 2008–12: U.S. Geological Survey Data Series 907, 9 p., accessed July, 12, 2015, at http://dx.doi.org/10.3133/ds907.
\nStone, W.W., 2013, Estimated annual agricultural pesticide use for counties of the conterminous United States, 1992–2009: U.S. Geological Survey Data Series 752, 1 p., 14 tables
\nThelin, G.P., and Stone, W.W., 2013, Estimation of annual agricultural pesticide use for counties of the conterminous United States,
1992–2009: U.S. Geological Survey Scientific Investigations Report 2013–5009, 54 p.
Director, Indiana Water Science Center
5957 Lakeside Blvd.
Indianapolis, IN 46278
http://in.water.usgs.gov/
Introduction
\nPesticide-Use Estimates
\nAcknowledgments
\nEmpirical relationships between field-derived Leaf Area Index (LAI) and Leaf Angle Distribution (LAD) and polarimetric synthetic aperture radar (PolSAR) based biophysical indicators were created and applied to map S. alterniflora marsh canopy structure. PolSAR and field data were collected near concurrently in the summers of 2010, 2011, and 2012 in coastal marshes, and PolSAR data alone were acquired in 2009. Regression analyses showed that LAI correspondence with the PolSAR biophysical indicator variables equaled or exceeded those of vegetation water content (VWC) correspondences. In the final six regressor model, the ratio HV/VV explained 49% of the total 77% explained LAI variance, and the HH-VV coherence and phase information accounted for the remainder. HV/HH dominated the two regressor LAD relationship, and spatial heterogeneity and backscatter mechanism followed by coherence information dominated the final three regressor model that explained 74% of the LAD variance. Regression results applied to 2009 through 2012 PolSAR images showed substantial changes in marsh LAI and LAD. Although the direct cause was not substantiated, following a release of freshwater in response to the 2010 Deepwater Horizon oil spill, the fairly uniform interior marsh structure of 2009 was more vertical and dense shortly after the oil spill cessation. After 2010, marsh structure generally progressed back toward the 2009 uniformity; however, the trend was more disjointed in oil impact marshes.
","language":"English","publisher":"Molecular Diversity Preservation International","publisherLocation":"Basel, Switzerland","doi":"10.3390/rs70911295","collaboration":"Amina Rangoonwala USGS, Cathleen E Jones NASA-CalTech","usgsCitation":"Ramsey, E.W., Rangoonwala, A., and Jones, C.E., 2015, Structural classification of marshes with Polarimetric SAR highlighting the temporal mapping of marshes exposed to oil: Remote Sensing, v. 7, no. 9, p. 11295-11321, https://doi.org/10.3390/rs70911295.","productDescription":"27 p.","startPage":"11295","endPage":"11321","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063104","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471732,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs70911295","text":"Publisher Index Page"},{"id":309543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.5,\n 29\n ],\n [\n -92.5,\n 30\n ],\n [\n -89.5,\n 30\n ],\n [\n -89.5,\n 29\n ],\n [\n -92.5,\n 29\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"9","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-02","publicationStatus":"PW","scienceBaseUri":"56139126e4b0ba4884c60f6e","contributors":{"authors":[{"text":"Ramsey, Elijah W. III 0000-0002-4518-5796 ramseye@usgs.gov","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":2883,"corporation":false,"usgs":true,"family":"Ramsey","given":"Elijah","suffix":"III","email":"ramseye@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":576455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rangoonwala, Amina 0000-0002-0556-0598 rangoonwalaa@usgs.gov","orcid":"https://orcid.org/0000-0002-0556-0598","contributorId":3455,"corporation":false,"usgs":true,"family":"Rangoonwala","given":"Amina","email":"rangoonwalaa@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":576456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Cathleen E.","contributorId":11890,"corporation":false,"usgs":true,"family":"Jones","given":"Cathleen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":576457,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70158670,"text":"70158670 - 2015 - The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines","interactions":[],"lastModifiedDate":"2019-12-11T13:24:59","indexId":"70158670","displayToPublicDate":"2015-10-05T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines","docAbstract":"A numerical model, XBeach, calibrated and validated on field data collected at Roi-Namur Island on Kwajalein Atoll in the Republic of Marshall Islands, was used to examine the effects of different coral reef characteristics on potential coastal hazards caused by wave-driven flooding and how these effects may be altered by projected climate change. The results presented herein suggest that coasts fronted by relatively narrow reefs with steep fore reef slopes (~1:10 and steeper) and deeper, smoother reef flats are expected to experience the highest wave runup. Wave runup increases for higher water levels (sea level rise), higher waves, and lower bed roughness (coral degradation), which are all expected effects of climate change. Rising sea levels and climate change will therefore have a significant negative impact on the ability of coral reefs to mitigate the effects of coastal hazards in the future.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015GL064861","usgsCitation":"Quataert, E., Storlazzi, C.D., van Rooijen, A., van Dongeren, A., and Cheriton, O., 2015, The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines: Geophysical Research Letters, v. 42, no. 15, p. 6407-6415, https://doi.org/10.1002/2015GL064861.","productDescription":"9 p.","startPage":"6407","endPage":"6415","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064753","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471733,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl064861","text":"Publisher Index Page"},{"id":309544,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Republic of the Marshall Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 167.8271484375,\n 7.798078531355303\n ],\n [\n 169.63989257812497,\n 7.798078531355303\n ],\n [\n 169.63989257812497,\n 10.077037154404719\n ],\n [\n 167.8271484375,\n 10.077037154404719\n ],\n [\n 167.8271484375,\n 7.798078531355303\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"15","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-04","publicationStatus":"PW","scienceBaseUri":"56139126e4b0ba4884c60f70","chorus":{"doi":"10.1002/2015gl064861","url":"http://dx.doi.org/10.1002/2015gl064861","publisher":"Wiley-Blackwell","authors":"Quataert Ellen, Storlazzi Curt, van Rooijen Arnold, Cheriton Olivia, van Dongeren Ap","journalName":"Geophysical Research Letters","publicationDate":"8/4/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Quataert, Ellen","contributorId":149000,"corporation":false,"usgs":false,"family":"Quataert","given":"Ellen","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":576425,"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":576424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Rooijen, Arnold","contributorId":149001,"corporation":false,"usgs":false,"family":"van Rooijen","given":"Arnold","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":576426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Dongeren, Ap","contributorId":149002,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":576427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cheriton, Olivia 0000-0003-3011-9136 ocheriton@usgs.gov","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":149003,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","email":"ocheriton@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576428,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70158664,"text":"70158664 - 2015 - Fish assemblages in the Upper Esopus Creek, NY: Current status, variability, and controlling factors","interactions":[],"lastModifiedDate":"2019-12-11T13:20:58","indexId":"70158664","displayToPublicDate":"2015-10-05T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Fish assemblages in the Upper Esopus Creek, NY: Current status, variability, and controlling factors","docAbstract":"The Upper Esopus Creek receives water diversions from a neighboring basin through the Shandaken Tunnel (the portal) from the Schoharie Reservoir. Although the portal is closed during floods, mean flows and turbidity of portal waters are generally greater than in Esopus Creek above their confluence. These conditions could potentially affect local fish assemblages, yet such effects have not been assessed in this highly regulated stream. We studied water quality, hydrology, temperature, and fish assemblages at 18 sites in the Upper Esopus Creek during 2009–2011 to characterize the effects of the portal input on resident-fish assemblages and to document the status of the fishery resource. In general, fish-community richness increased by 2–3 species at mainstem sites near the portal, and median density and biomass of fish communities at sites downstream of the portal were significantly lower than they were at sites upstream of the portal. Median densities of Salmo trutta (Brown Trout) and all trout species were significantly lower than at mainstem sites downstream from the portal—25.1 fish/0.1 ha and 148.9 fish/0.1 ha, respectively—than at mainstem sites upstream from the portal—68.8 fish/0.1 ha and 357.7 fish/0.1 ha, respectively—yet median biomass for Brown Trout and all trout did not differ between sites from both reaches. The median density of young-of-year Brown Trout at downstream sites (9.3 fish/0.1 ha) was significantly lower than at upstream sites (33.9 fish/0.1 ha). Waters from the portal appeared to adversely affect the density and biomass of young-of-year Brown Trout, but lower temperatures and increased flows also improved habitat quality for mature trout at downstream sites during summer. These findings, and those from companion studies, indicate that moderately turbid waters from the portal had few if any adverse impacts on trout populations and overall fish communities in the Upper Esopus Creek during this study.
","language":"English","publisher":"Eagle Hill Institute","publisherLocation":"Steuben, ME","doi":"10.1656/045.022.0209","collaboration":"Cornell Cooperative Extension of Ulster County; USGS","usgsCitation":"Baldigo, B.P., George, S.D., and Keller, W.T., 2015, Fish assemblages in the Upper Esopus Creek, NY: Current status, variability, and controlling factors: Northeastern Naturalist, v. 22, no. 2, p. 345-371, https://doi.org/10.1656/045.022.0209.","productDescription":"27 p.","startPage":"345","endPage":"371","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042999","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":309548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Upper Esopus Creek, Catskill Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.16571044921875,\n 41.748775021355044\n ],\n [\n -73.9874267578125,\n 41.748775021355044\n ],\n [\n -73.9874267578125,\n 42.409262623071186\n ],\n [\n -75.16571044921875,\n 42.409262623071186\n ],\n [\n -75.16571044921875,\n 41.748775021355044\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56139122e4b0ba4884c60f64","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":576413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":576414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keller, Walter T","contributorId":148996,"corporation":false,"usgs":false,"family":"Keller","given":"Walter","email":"","middleInitial":"T","affiliations":[{"id":17612,"text":"Retired Fisheries Manager, NYS Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":576415,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156829,"text":"70156829 - 2015 - Borehole strainmeter measurements spanning the 2014, Mw6.0 South Napa Earthquake, California: The effect from instrument calibration","interactions":[],"lastModifiedDate":"2015-11-18T16:19:37","indexId":"70156829","displayToPublicDate":"2015-10-05T06:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Borehole strainmeter measurements spanning the 2014, Mw6.0 South Napa Earthquake, California: The effect from instrument calibration","docAbstract":"The 24 August 2014 Mw6.0 South Napa, California earthquake produced significant offsets on 12 borehole strainmeters in the San Francisco Bay area. These strainmeters are located between 24 and 80 km from the source and the observed offsets ranged up to 400 parts-per-billion (ppb), which exceeds their nominal precision by a factor of 100. However, the observed offsets of tidally calibrated strains differ by up to 130 ppb from predictions based on a moment tensor derived from seismic data. The large misfit can be attributed to a combination of poor instrument calibration and better modeling of the strain fit from the earthquake. Borehole strainmeters require in-situ calibration, which historically has been accomplished by comparing their measurements of Earth tides with the strain-tides predicted by a model. Although the borehole strainmeter accurately measure the deformation within the borehole, the long-wavelength strain signals from tides or other tectonic processes recorded in the borehole are modified by the presence of the borehole and the elastic properties of the grout and the instrument. Previous analyses of surface-mounted, strainmeter data and their relationship with the predicted tides suggest that tidal models could be in error by 30%. The poor fit of the borehole strainmeter data from this earthquake can be improved by simultaneously varying the components of the model tides up to 30% and making small adjustments to the point-source model of the earthquake, which reduces the RMS misfit from 130 ppb to 18 ppb. This suggests that relying on tidal models to calibrate borehole strainmeters significantly reduces their accuracy.
","language":"English","publisher":"William Byrd Press for John Hopkins Press","publisherLocation":"Richmond, VA","doi":"10.1002/2015JB012278","usgsCitation":"Langbein, J.O., 2015, Borehole strainmeter measurements spanning the 2014, Mw6.0 South Napa Earthquake, California: The effect from instrument calibration: Journal of Geophysical Research, v. 120, no. 10, p. 7190-7202, https://doi.org/10.1002/2015JB012278.","productDescription":"13 p.","startPage":"7190","endPage":"7202","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065802","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471734,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012278","text":"Publisher Index Page"},{"id":311547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Napa","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.54425048828125,\n 37.903032319353656\n ],\n [\n -122.54425048828125,\n 38.48261976950729\n ],\n [\n -122.00729370117188,\n 38.48261976950729\n ],\n [\n -122.00729370117188,\n 37.903032319353656\n ],\n [\n -122.54425048828125,\n 37.903032319353656\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-05","publicationStatus":"PW","scienceBaseUri":"564daf45e4b0112df6c62df0","contributors":{"authors":[{"text":"Langbein, John O. 0000-0002-7821-8101 langbein@usgs.gov","orcid":"https://orcid.org/0000-0002-7821-8101","contributorId":3293,"corporation":false,"usgs":true,"family":"Langbein","given":"John","email":"langbein@usgs.gov","middleInitial":"O.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":570734,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70072588,"text":"70072588 - 2015 - A review of the recent geochemical evolution of Piton de la Fournaise volcano (1927-2010)","interactions":[],"lastModifiedDate":"2015-10-27T16:25:39","indexId":"70072588","displayToPublicDate":"2015-10-04T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"A review of the recent geochemical evolution of Piton de la Fournaise volcano (1927-2010)","docAbstract":"Between 1927 and 2010, more than one hundred eruptions of Piton de la Fournaise produced ~1 km3 of lava, and the volcano’s summit collapsed twice (in 1931 and 2007). These lavas display, respectively, 20 and 65 % of the Sr–Nd and the Pb isotope ranges reported for La Réunion volcanoes over their known eruptive record (3.8 Ma). Variations in major and trace element concentrations and Sr–Pb isotopes do not define a temporal trend at the scale of the century, but display systematic short-term cyclic fluctuations. The positive correlation between 87Sr/86Sr and ratios of trace elements that are more versus less incompatible during partial melting of the mantle (e.g., Nd/Sm, La/Sm) probably results from the sampling of small-scale heterogeneities within the plume source. Changes in the degree of melting and/or crystallization are debated, but these appear ultimately linked to source properties. Lead isotopes do not co-vary with Sr isotopes, in part because of the partitioning of Pb into dense metallic phases that are preferentially sampled during high-flux eruptions. Taken together, Sr–Nd–Pb–Os–Th isotopes do not support contamination of magma with genetically unrelated components, such as the underlying Indian oceanic crust, mantle lithosphere, seawater, or seawater-altered lavas. Yet, in some rare cases (e.g. the 1998 Hudson eruption), the compositional patterns suggest that the parental magma assimilated older volcanic products within the edifice, such as crystal cumulates and/or interstitial differentiated melts. The geochemical fluctuations over the 1927–2010 time period constrain the residence time of magma in the shallow reservoir to 10–30 years and its size to 0.1–0.3 km3. The magma residence time during the course of the long-lived 1998 eruption is estimated to be an order of magnitude shorter, but the reservoir was probably of similar size. Instead, the shorter magma residence for the 1998 eruption was probably due to a higher magma flux.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Active volcanoes of the southwest Indian Ocean","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-642-31395-0_11","usgsCitation":"Pietruszka, A., and Vlastelic, I., 2015, A review of the recent geochemical evolution of Piton de la Fournaise volcano (1927-2010), chap. of Active volcanoes of the southwest Indian Ocean, p. 185-201, https://doi.org/10.1007/978-3-642-31395-0_11.","productDescription":"17 p.","startPage":"185","endPage":"201","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045693","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":310690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Piton de la Fournaise, Réunion island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 55.66841125488281,\n -21.188893398817655\n ],\n [\n 55.81535339355469,\n -21.204257977694652\n ],\n [\n 55.80230712890625,\n -21.2836161525487\n ],\n [\n 55.68214416503906,\n -21.290653925975697\n ],\n [\n 55.64094543457031,\n -21.218340770952555\n ],\n [\n 55.65605163574218,\n -21.188893398817655\n ],\n [\n 55.66841125488281,\n -21.188893398817655\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2015-10-04","publicationStatus":"PW","scienceBaseUri":"5630a02be4b093cee78203e1","contributors":{"authors":[{"text":"Pietruszka, Aaron J.","contributorId":97024,"corporation":false,"usgs":true,"family":"Pietruszka","given":"Aaron J.","affiliations":[],"preferred":false,"id":518465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vlastelic, Ivan","contributorId":149458,"corporation":false,"usgs":false,"family":"Vlastelic","given":"Ivan","email":"","affiliations":[],"preferred":false,"id":578494,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70158030,"text":"ofr20151189 - 2015 - Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2014","interactions":[],"lastModifiedDate":"2015-10-05T11:04:29","indexId":"ofr20151189","displayToPublicDate":"2015-10-02T17:00:00","publicationYear":"2015","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":"2015-1189","title":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2014","docAbstract":"Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during the spawning season in spring 2014 were incorporated into capture-recapture analyses of population dynamics.
\nCormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish were examined to provide corroborating evidence of recruitment. Model estimates of survival and recruitment were used to derive estimates of changes in population size over time and to determine the status of the populations through 2013. Separate analyses were conducted for each species and also for each subpopulation of Lost River suckers (LRS). Shortnose suckers (SNS) and one subpopulation of LRS migrate into tributary rivers to spawn, whereas the other LRS subpopulation spawns at groundwater upwelling areas along the eastern shoreline of the lake.
\nIn 2014, we captured, tagged, and released 496 LRS at four lakeshore spawning areas and recaptured an additional 970 individuals that had been tagged in previous years. Across all four areas, the remote antennas detected 6,370 individual LRS during the spawning season. Spawning activity peaked in April and most individuals were encountered at Cinder Flats and Sucker Springs. In the Williamson River, we captured, tagged, and released 3,038 LRS and 267 SNS, and recaptured 762 LRS and 156 SNS that had been tagged in previous years. Remote PIT tag antennas in the traps at the weir on the Williamson River and remote antenna systems that spanned the river at three different locations on the Williamson and Sprague Rivers detected a total of 23,446 LRS and 6,259 SNS. Most LRS passed upstream in the first and second weeks of April when water temperatures were increasing and greater than 10 °C. In contrast, upstream passage for SNS occurred in two pulses, one in early April and one in late April to early May, when water temperatures were increasing and near or greater than 12 °C. Finally, an additional 375 LRS and 884 SNS were captured in trammel net sampling at pre-spawn staging areas in the northeastern part of the lake. Of these, 111 of the LRS and 390 of the SNS had been PIT-tagged in previous years. For LRS captured at the staging areas that had encounter histories that were informative about their spawning location, 79 percent of the fish were members of the subpopulation that spawns in the rivers.
\nCapture-recapture analyses for the LRS subpopulation that spawns at the shoreline areas included encounter histories for more than 13,200 individuals, and analyses for the subpopulation that spawns in the rivers included more than 36,400 encounter histories. With a few exceptions, the survival of males and females in both subpopulations was high (greater than 0.88) between 1999 and 2012. Notably lower survival occurred for both sexes from the rivers in 2000, for males from the shoreline areas in 2002, and for males from the rivers in 2006 and 2012. Between 2001 and 2013, the abundance of males in the lakeshore spawning subpopulation decreased by at least 55 percent and the abundance of females decreased by at least 42 percent. Capture-recapture models suggested that the abundance of both sexes in the river spawning subpopulation of LRS had increased substantially since 2006; increases were mostly due to large estimated recruitment events in 2006 and 2008. We know that the estimates in 2006 are substantially biased in favor of recruitment because of a sampling issue. We are skeptical of the magnitude of recruitment indicated by the 2008 estimates as well because (1) few small individuals that would indicate the presence of new recruits were captured in that year, and (2) recapture probabilities in recruitment models based on just physical recaptures of fish were lower than desired for robust inferences from capture-recapture models. If we assume instead that little or no recruitment occurred for this subpopulation, the abundance of both sexes in the river spawning subpopulation likely has decreased at rates similar to the rates for the lakeshore spawning subpopulation between 2002 and 2013.
\nCapture-recapture analyses for SNS included encounter histories for more than 19,200 individuals. Most annual survival estimates between 2001 and 2012 were high (greater than 0.80), but SNS experienced more years of low survival than either LRS subpopulation. Annual survival of both sexes was relatively low in 2004, 2010, and 2012. In addition, male survival was low in 2002. Capture-recapture models and size composition data indicate that recruitment of new individuals into the SNS spawning population was trivial between 2001 and 2005. Models indicate that more than 10 percent of the population was new recruits in a number of more recent years. As a result, capture-recapture modeling suggests that the abundance of adult spawning SNS was relatively stable between 2006 and 2010. We are skeptical of the estimated recruitment in 2006 because of the known sampling issue. We also are skeptical of the estimated recruitment in other recent years because few small individuals that would indicate the presence of new recruits were captured in any of those years, and recapture probabilities in recruitment models were low. The best-case scenario for SNS, based on capture-recapture recruitment modeling, indicates that the abundance of males in the spawning population decreased by 77 percent and the abundance of females decreased by 73 percent between 2001 and 2013. Decreases in abundance for both sexes likely are greater than these estimates indicate.
\nDespite relatively high survival in most years, we conclude that both species have experienced substantial decreases in the abundance of spawning adults because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains worrisome, especially for shortnose suckers. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.
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Three aeromagnetic surveys were flown to improve understanding of the geology and structure in the Sacramento Valley. The resulting data serve as a basis for geophysical interpretations, and support geological mapping, water and mineral resource investigations, and other topical studies. Local spatial variations in the Earth's magnetic field (evident as anomalies on aeromagnetic maps) reflect the distribution of magnetic minerals, primarily magnetite, in the underlying rocks. In many cases the volume content of magnetic minerals can be related to rock type, and abrupt spatial changes in the amount of magnetic minerals commonly mark lithologic or structural boundaries. Bodies of serpentinite and other mafic and ultramafic rocks tend to produce the most intense positive magnetic anomalies (for example, in the northwest part of the map). These rock types are the inferred sources, concealed beneath weakly magnetic, valley-fill deposits, of the most prominent magnetic features in the map area, the magnetic highs that extend along the valley axis. Cenozoic volcanic rocks are also an important source of magnetic anomalies and coincide with short-wavelength anomalies that can be either positive (strong central positive anomaly flanked by lower-amplitude negative anomalies) or negative (strong central negative anomaly flanked by lower-amplitude positive anomalies), reflecting the contribution of remanent magnetization. Rocks with more felsic compositions or even some sedimentary units also can cause measurable magnetic anomalies. For example, the long, linear, narrow north-trending anomalies (with amplitudes of <50 nanoteslas [nT]) along the western margin of the valley coincide with exposures of the Mesozoic Great Valley sequence. Note that isolated, short-wavelength anomalies, such as those in the city of Sacramento and along some of the major roads, are caused by manmade features.
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zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":148146,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria","email":"zulanger@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":574063,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70146877,"text":"tm6D3 - 2015 - Documentation of a restart option for the U.S. Geological Survey coupled Groundwater and Surface-Water Flow (GSFLOW) model","interactions":[],"lastModifiedDate":"2017-08-01T12:43:52","indexId":"tm6D3","displayToPublicDate":"2015-10-02T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-D3","title":"Documentation of a restart option for the U.S. Geological Survey coupled Groundwater and Surface-Water Flow (GSFLOW) model","docAbstract":"A new option to write and read antecedent conditions (also referred to as initial conditions) has been developed for the U.S. Geological Survey (USGS) Groundwater and Surface-Water Flow (GSFLOW) numerical, hydrologic simulation code. GSFLOW is an integration of the USGS Precipitation-Runoff Modeling System (PRMS) and USGS Modular Groundwater-Flow Model (MODFLOW), and provides three simulation modes: MODFLOW-only, PRMS-only, and GSFLOW (or coupled). The new capability, referred to as the restart option, can be used for all three simulation modes, such that the results from a pair (or set) of spin-up and restart simulations are nearly identical to results produced from a continuous simulation for the same time period. The restart option writes all results to files at the end of a spin-up simulation that are required to initialize a subsequent restart simulation. Previous versions of GSFLOW have had some capability to save model results for use as antecedent condiitions in subsequent simulations; however, the existing capabilities were not comprehensive or easy to use. The new restart option supersedes the previous methods. The restart option was developed in collaboration with the National Oceanic and Atmospheric Administration, National Weather Service as part of the Integrated Water Resources Science and Services Partnership. The primary focus for the development of the restart option was to support medium-range (7- to 14-day) forecasts of low streamflow conditions made by the National Weather Service for critical water-supply basins in which groundwater plays an important role.
\nThe spin-up simulation should be run for a sufficient length of time necessary to establish antecedent conditions throughout a model domain. Each GSFLOW application can require different lengths of time to account for the hydrologic stresses to propagate through a coupled groundwater and surface-water system. Typically, groundwater hydrologic processes require many years to come into equilibrium with dynamic climate and other forcing (or stress) data, such as precipitation and well pumping, whereas runoff-dominated surface-water processes respond relatively quickly. Use of a spin-up simulation can substantially reduce execution-time requirements for applications where the time period of interest is small compared to the time for hydrologic memory; thus, use of the restart option can be an efficient strategy for forecast and calibration simulations that require multiple simulations starting from the same day.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section D: Ground-water/Surface-water in Book 6U.S. Geological Survey
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411 National Center
Reston, VA 20192
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The U.S. Geological Survey (USGS) researches Earth science to help address complex issues affecting society and the environment. In 2006, the USGS held the first Scientific Information Management Workshop to bring together staff from across the organization to discuss the data and information management issues affecting the integration and delivery of Earth science research and investigate the use of “communities of practice” as mechanisms to share expertise about these issues. Out of this effort emerged the Council for Data Integration, which was conceived as an official organizational function that would help guide data integration activities and formalize communities of practice into working groups; however, by 2009 it became evident that many members of the Council for Data Integration had an interest in developing data integration solutions and sharing expertise in a less formal, grassroots manner, which transformed the Council into a Community for Data Integration (CDI). As of 2014, the CDI represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the USGS and the CDI community.
\nThe CDI fosters an environment for collaboration and sharing by bringing together expertise from external partners and representatives across the USGS who are involved in research, data management, and information technology. Membership is voluntary and open to USGS employees and other individuals and organizations willing to contribute to the community (if interested, contact cdi@usgs.gov). The purpose of the CDI is to do the following:
• advance understanding of Earth systems through enhanced use of data and information including associated tools and techniques,
• provide a forum for people doing work with data integration to come together to share ideas and learn new skills and techniques, and
• grow overall USGS capabilities with data and information by increasing visibility of the work of many people throughout the USGS and the CDI community.
To achieve these goals, the CDI operates within four applied areas: monthly forums, annual workshop/webinar series, working groups, and projects. The monthly forums, also known as the Opportunity/Challenge of the Month, provide an open dialogue to share and learn about data integration efforts or to present problems that invite the community to offer solutions, advice, and support. Since 2010, the CDI has also sponsored annual workshops/webinar series to encourage the exchange of ideas, sharing of activities, presentations of current projects, and networking among members. Stemming from common interests, the working groups are focused on efforts to address data management and technical challenges including the development of standards and tools, improving interoperability and information infrastructure, and data preservation within USGS and its partners. The growing support for the activities of the working groups led to the CDI’s first formal request for proposals (RFP) process in 2013 to fund projects that produced tangible products. As of 2014, the CDI continues to hold an annual RFP that creates data management tools and practices, collaboration tools, and training in support of data integration and delivery.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151184","usgsCitation":"Langseth, M.L., Chang, M.Y., Carlino, Jennifer, Birch, D.D., Bradley, Joshua, Bristol, R.S., Conzelmann, Craig, Diehl, R.H., Earle, Paul, Ellison, L.E., Everette, A.L., Fuller, Pam, Gordon, J.M., Govoni, D.L., Guy, M.R., Henkel, H.S., Hutchison, V.B., Kern, Tim, Lightsom, F.L., Long, J.W., Longhenry, Ryan, Preston, T.M., Smith, Stan, Viger, R.J., Wesenberg, Katherine, and Wood, Eric, 2015, Community for Data Integration 2014 annual report: U.S. Geological Survey Open-File Report 2015–1184, 40 p., https://dx.doi.org/10.3133/ofr20151184.","productDescription":"vi, 40 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066330","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":309412,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1184/ofr20151184.pdf","text":"Report","size":"7.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1184"},{"id":309411,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1184/coverthb.jpg"}],"contact":"Director, Core Science Analytics and Synthesis
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108 National Center
12201 Sunrise Valley Drive
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