Since 2012, a multi-agency initiative to restore these native forage species has been under way. Evaluating the restoration success of Cisco Coregonus artedi and Bloater C. hoyi in Lake Ontario waters requires methods to identify stocked fish. However, juvenile Cisco and Bloater are fragile; thus, mass marking techniques that reduce the handling of individual fish are required and have not previously been evaluated. In 2014–2015 we evaluated the usefulness of calcein (SE-MARK) as a marker on bony structures, including the otolith. Juvenile Bloater and Cisco (14, 100, 128 d old) were immersed in a calcein bath at 5,000 mg/L of water for 4 min to apply the chemical marker. Observations of the marking retention were evaluated 8 d following the treatment. All fish immersed in calcein had strong brilliant marks (rating scale 3) on all bony structures including scales, fin rays, jaw bones, and vertebrate. The otolith was the only hard structure that did not show a brilliant marking due to the opaque nature of the structure. Our results suggest that calcein produces a strong discernable mark on hard bony structures of Cisco and Bloater; however, long-term retention needs further study.
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whitefish","interactions":[],"lastModifiedDate":"2016-07-27T11:31:40","indexId":"70175025","displayToPublicDate":"2016-03-22T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Integrating subsistence practice and species distribution modeling: assessing invasive elodea’s potential impact on Native Alaskan subsistence of Chinook salmon and whitefish","docAbstract":"Alaska has one of the most rapidly changing climates on earth and is experiencing an accelerated rate of human disturbance, including resource extraction and transportation infrastructure development. Combined, these factors increase the state’s vulnerability to biological invasion, which can have acute negative impacts on ecological integrity and subsistence practices. Of growing concern is the spread of Alaska’s first documented freshwater aquatic invasive plant Elodea spp. (elodea). In this study, we modeled the suitable habitat of elodea using global and state-specific species occurrence records and environmental variables, in concert with an ensemble of model algorithms. Furthermore, we sought to incorporate local subsistence concerns by using Native Alaskan knowledge and available statewide subsistence harvest data to assess the potential threat posed by elodea to Chinook salmon (Oncorhynchus tshawytscha) and whitefish (Coregonus nelsonii) subsistence. State models were applied to future climate (2040–2059) using five general circulation models best suited for Alaska. Model evaluations indicated that our results had moderate to strong predictability, with area under the receiver-operating characteristic curve values above 0.80 and classification accuracies ranging from 66 to 89 %. State models provided a more robust assessment of elodea habitat suitability. These ensembles revealed different levels of management concern statewide, based on the interaction of fish subsistence patterns, known spawning and rearing sites, and elodea habitat suitability, thus highlighting regions with additional need for targeted monitoring. Our results suggest that this approach can hold great utility for invasion risk assessments and better facilitate the inclusion of local stakeholder concerns in conservation planning and management.
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jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":643639,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"West, Amanda M.","contributorId":139058,"corporation":false,"usgs":false,"family":"West","given":"Amanda M.","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":643642,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stewart, Heather","contributorId":173199,"corporation":false,"usgs":false,"family":"Stewart","given":"Heather","affiliations":[{"id":27188,"text":"Alaska Department of Natural Resources Division of Agriculture","active":true,"usgs":false}],"preferred":false,"id":643643,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169145,"text":"70169145 - 2016 - Enhancing and restoring habitat for the desert tortoise","interactions":[],"lastModifiedDate":"2016-12-16T11:17:02","indexId":"70169145","displayToPublicDate":"2016-03-22T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Enhancing and restoring habitat for the desert tortoise","docAbstract":"Habitat has changed unfavorably during the past 150 y for the desert tortoise Gopherus agassizii, a federally threatened species with declining populations in the Mojave Desert and western Sonoran Desert. To support recovery efforts, we synthesized published information on relationships of desert tortoises with three habitat features (cover sites, forage, and soil) and candidate management practices for improving these features for tortoises. In addition to their role in soil health and facilitating recruitment of annual forage plants, shrubs are used by desert tortoises for cover and as sites for burrows. Outplanting greenhouse-grown seedlings, protected from herbivory, has successfully restored (>50% survival) a variety of shrubs on disturbed desert soils. Additionally, salvaging and reapplying topsoil using effective techniques is among the more ecologically beneficial ways to initiate plant recovery after severe disturbance. Through differences in biochemical composition and digestibility, some plant species provide better-quality forage than others. Desert tortoises selectively forage on particular annual and herbaceous perennial species (e.g., legumes), and forage selection shifts during the year as different plants grow or mature. Nonnative grasses provide low-quality forage and contribute fuel to spreading wildfires, which damage or kill shrubs that tortoises use for cover. Maintaining a diverse “menu” of native annual forbs and decreasing nonnative grasses are priorities for restoring most desert tortoise habitats. Reducing herbivory by nonnative animals, carefully timing herbicide applications, and strategically augmenting annual forage plants via seeding show promise for improving tortoise forage quality. Roads, another disturbance, negatively affect habitat in numerous ways (e.g., compacting soil, altering hydrology). Techniques such as recontouring road berms to reestablish drainage patterns, vertical mulching (“planting” dead plant material), and creating barriers to prevent trespasses can assist natural recovery on decommissioned backcountry roads. Most habitat enhancement efforts to date have focused on only one factor at a time (e.g., providing fencing) and have not included proactive restoration activities (e.g., planting native species on disturbed soils). A research and management priority in recovering desert tortoise habitats is implementing an integrated set of restorative habitat enhancements (e.g., reducing nonnative plants, improving forage quality, augmenting native perennial plants, and ameliorating altered hydrology) and monitoring short- and long-term indicators of habitat condition and the responses of desert tortoises to habitat restoration.
","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington, D.C.","doi":"10.3996/052015-JFWM-046","usgsCitation":"Abella, S.R., and Berry, K.H., 2016, Enhancing and restoring habitat for the desert tortoise: Journal of Fish and Wildlife Management, v. 7, no. 1, p. 255-279, https://doi.org/10.3996/052015-JFWM-046.","productDescription":"25 p.","startPage":"255","endPage":"279","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066485","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488430,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/052015-jfwm-046","text":"Publisher Index Page"},{"id":319189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.027099609375,\n 37.32648861334206\n ],\n [\n -113.75244140624999,\n 37.42252593456307\n ],\n [\n -113.521728515625,\n 37.33522435930641\n ],\n [\n -113.48876953125,\n 37.055177106660814\n ],\n [\n -113.5986328125,\n 36.4566360115962\n ],\n [\n -113.73046875,\n 36.1822249804225\n ],\n [\n -113.79638671875,\n 35.951329861522666\n ],\n [\n -113.895263671875,\n 35.60371874069731\n ],\n [\n -113.675537109375,\n 35.23664622093195\n ],\n [\n -113.51074218749999,\n 35.074964853989556\n ],\n [\n -113.44482421875,\n 34.97600151317591\n ],\n [\n -113.18115234375,\n 34.66032236481892\n ],\n [\n -113.203125,\n 34.379712580462204\n ],\n [\n -113.466796875,\n 34.19817309627726\n ],\n [\n -113.88427734374999,\n 34.125447565116126\n ],\n [\n -114.36767578124999,\n 34.03445260967645\n ],\n [\n -115.13671875,\n 34.17090836352573\n ],\n [\n -115.15869140624999,\n 33.8430453147447\n ],\n [\n -114.664306640625,\n 33.486435450999885\n ],\n [\n -114.81811523437501,\n 33.14675022877648\n ],\n [\n -115.04882812499999,\n 32.94414888814148\n ],\n [\n -115.3564453125,\n 33.119150226768866\n ],\n [\n -115.521240234375,\n 33.330528249028085\n ],\n [\n -116.114501953125,\n 33.779147331286474\n ],\n [\n -116.38916015624999,\n 33.90689555128866\n ],\n [\n -117.22412109375,\n 34.19817309627726\n ],\n [\n -117.630615234375,\n 34.15272698011818\n ],\n [\n -118.02612304687499,\n 34.14363482031264\n ],\n [\n -118.38867187500001,\n 34.288991865037524\n ],\n [\n -118.65234374999999,\n 34.52466147177172\n ],\n [\n -118.80615234374999,\n 34.75966612466248\n ],\n [\n -118.223876953125,\n 35.16482750605027\n ],\n [\n -118.487548828125,\n 35.39800594715108\n ],\n [\n -118.443603515625,\n 35.6126508187567\n ],\n [\n -118.14697265625,\n 35.7286770448517\n ],\n [\n -117.98217773437499,\n 35.639441068973916\n ],\n [\n -117.850341796875,\n 35.64836915737426\n ],\n [\n -117.98217773437499,\n 36.05798104702501\n ],\n [\n -118.048095703125,\n 36.38591277287651\n ],\n [\n -118.21289062499999,\n 36.5978891330702\n ],\n [\n -118.333740234375,\n 37.02886944696474\n ],\n [\n -118.35571289062499,\n 37.25656608611523\n ],\n [\n -118.0810546875,\n 37.23907530202184\n ],\n [\n -117.938232421875,\n 37.448696585910376\n ],\n [\n -117.740478515625,\n 37.56199695314352\n ],\n [\n -117.57568359374999,\n 37.49229399862877\n ],\n [\n -117.2900390625,\n 37.26530995561875\n ],\n [\n -116.79565429687499,\n 37.274052809979054\n ],\n [\n -116.5869140625,\n 37.25656608611523\n ],\n [\n -116.49902343749999,\n 37.204081555898526\n ],\n [\n -116.15844726562501,\n 37.16907157713011\n ],\n [\n -115.927734375,\n 37.142803443716836\n ],\n [\n -115.51025390625,\n 37.38761749978395\n ],\n [\n -114.993896484375,\n 37.24782120155428\n ],\n [\n -114.54345703125,\n 37.25656608611523\n ],\n [\n -114.3017578125,\n 37.212831514455964\n ],\n [\n -114.027099609375,\n 37.32648861334206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-01","publicationStatus":"PW","scienceBaseUri":"56f25e98e4b0f59b85de6ff1","contributors":{"authors":[{"text":"Abella, Scott R.","contributorId":103940,"corporation":false,"usgs":true,"family":"Abella","given":"Scott","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":623207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":623206,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169017,"text":"fs20163007 - 2016 - Landscape ecology of the Upper Mississippi River System: Lessons learned, challenges and opportunities","interactions":[],"lastModifiedDate":"2016-06-24T09:07:49","indexId":"fs20163007","displayToPublicDate":"2016-03-22T14:30:00","publicationYear":"2016","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":"2016-3007","title":"Landscape ecology of the Upper Mississippi River System: Lessons learned, challenges and opportunities","docAbstract":"The Upper Mississippi River System (UMRS) is a mosaic of river channels, backwater lakes, floodplain forests, and emergent marshes. This complex mosaic supports diverse aquatic and terrestrial plant communities, over 150 fish species; 40 freshwater mussel species; 50 amphibian and reptile species; and over 360 bird species, many of which use the UMRS as a critical migratory route. The river and floodplain are also hotspots for biogeochemical activity as the river-floodplain collects and processes nutrients derived from the UMR basin. These features qualify the UMRS as a Ramsar wetland of international significance.
Two centuries of land-use change, including construction for navigation and conversion of large areas to agriculture, has altered the broad-scale structure of the river and changed local environmental conditions in many areas. Such changes have affected rates of nutrient processing and transport, as well as the abundance of various fish, mussel, plant, and bird species. However, the magnitude and spatial scale of these effects are not well quantified, especially in regards to the best methods and locations for restoring various aspects of the river ecosystem.
The U.S. Congress declared the navigable portions of the Upper Mississippi River System (UMRS) a “nationally significant ecosystem and nationally significant commercial navigation system” in the Water Resources Development Act of 1986 (Public Law 99-662) and launched the Upper Mississippi River Restoration (UMRR) Program, the first comprehensive program for ecosystem restoration, monitoring, and research on a large river system. This fact sheet focuses on landscape ecological studies conducted by the U.S. Geological Survey to support decision making by the UMRR with respect to ecosystem restoration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163007","collaboration":"A Product of the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration (UMRR) Program","usgsCitation":"De Jager, N., 2016, Landscape Ecology of the Upper Mississippi River System: Lessons learned, challenges and opportunities. U.S. Geological Survey Fact Sheet 2016–3007, 4 p., https://dx.doi.org/10.3133/fs20163007.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041434","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":318908,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3007/coverthb.jpg"},{"id":318909,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3007/fs20163007.pdf","text":"Report","size":"6.58 MB","description":"FS 2016-3007"}],"country":"United States","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.62646484375,\n 36.4566360115962\n ],\n [\n -91.47216796875,\n 38.41055825094609\n ],\n [\n -93.93310546875,\n 39.7240885773337\n ],\n [\n -95.44921875,\n 40.48038142908172\n ],\n [\n -96.328125,\n 42.391008609205045\n ],\n [\n -96.50390625,\n 44.26093725039923\n ],\n [\n -96.52587890625,\n 45.19752230305685\n ],\n [\n -95.108642578125,\n 46.21785176740299\n ],\n [\n -94.09790039062499,\n 46.39998810407942\n ],\n [\n -92.735595703125,\n 46.51351558059737\n ],\n [\n -92.17529296875,\n 46.44542749723387\n ],\n [\n -90.3076171875,\n 44.94924926661153\n ],\n [\n -89.197998046875,\n 43.40504748787035\n ],\n [\n -88.22021484375,\n 42.706659563510385\n ],\n [\n -87.791748046875,\n 42.439674178149424\n ],\n [\n -87.60498046875,\n 40.830436877649255\n ],\n [\n -88.187255859375,\n 38.993572058209466\n ],\n [\n -88.53881835937499,\n 37.52715361723378\n ],\n [\n -89.527587890625,\n 36.5184659896759\n ],\n [\n -89.62646484375,\n 36.4566360115962\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
Phone: (608) 783-6451
http://www.umesc.usgs.gov/ltrmp.html
Bioremediation strategies, including bioaugmentation with chlorinated ethene-degrading enrichment cultures, have been successfully applied in the cleanup of subsurface environments contaminated with tetrachloroethene (PCE) and/or trichloroethene (TCE). However, these compounds are frequently found in the environment as components of mixtures that may also contain chlorinated ethanes and methanes. Under these conditions, the implementation of bioremediation may be complicated by inhibition effects, particularly when multiple dehalorespirers are present. We investigated the ability of the 1,1,2,2-tetrachloroethane (TeCA)-dechlorinating culture WBC-2 to biotransform TeCA alone, or a mixture of TeCA plus PCE and carbon tetrachloride (CT), in microcosms. The microcosms contained electron donors provided to biostimulate the added culture and sediment collected from a wetland where numerous “hotspots” of contamination with chlorinated solvent mixtures exist. The dominant TeCA biodegradation mechanism mediated by the WBC-2 culture in the microcosms was different in the presence of these wetland sediments than in the sediment-free enrichment culture or in previous WBC-2 bioaugmented microcosms and column tests conducted with wetland sediment collected at nearby sites. The co-contaminants and their daughter products also inhibited TeCA biodegradation by WBC-2. These results highlight the need to conduct biodegradability assays at new sites, particularly when multiple contaminants and dehalorespiring populations are present.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2015.12.033","collaboration":"U.S. Army, Aberdeen Proving Ground (Maryland)","usgsCitation":"Lorah, M.M., Schiffmacher, E.N., Becker, J.G., and Voytek, M.A., 2016, The effects of co-contaminants and native wetland sediments on the activity and dominant transformation mechanisms of a 1,1,2,2-tetrachloroethane (TeCA)-degrading enrichment culture: Chemosphere, v. 147, p. 239-247, https://doi.org/10.1016/j.chemosphere.2015.12.033.","productDescription":"9 p.","startPage":"239","endPage":"247","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069806","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":488787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemosphere.2015.12.033","text":"Publisher Index Page"},{"id":324363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576e59b6e4b07657d1a43caf","chorus":{"doi":"10.1016/j.chemosphere.2015.12.033","url":"http://dx.doi.org/10.1016/j.chemosphere.2015.12.033","publisher":"Elsevier BV","authors":"Schiffmacher Emily N., Becker Jennifer G., Lorah Michelle M., Voytek Mary A.","journalName":"Chemosphere","publicationDate":"3/2016","publiclyAccessibleDate":"1/13/2017"},"contributors":{"authors":[{"text":"Lorah, Michelle M. 0000-0002-9236-587X mmlorah@usgs.gov","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":1437,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","email":"mmlorah@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schiffmacher, Emily N.","contributorId":172429,"corporation":false,"usgs":false,"family":"Schiffmacher","given":"Emily","email":"","middleInitial":"N.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":640694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Becker, Jennifer G.","contributorId":172430,"corporation":false,"usgs":false,"family":"Becker","given":"Jennifer","email":"","middleInitial":"G.","affiliations":[{"id":27038,"text":"Michigan Technological University and University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":640696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voytek, Mary A.","contributorId":91943,"corporation":false,"usgs":true,"family":"Voytek","given":"Mary","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":640695,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169158,"text":"70169158 - 2016 - Spatial genetic structure of Long-tailed Ducks (Clangula hyemalis) among Alaskan, Canadian, and Russian breeding populations","interactions":[],"lastModifiedDate":"2021-08-27T16:20:37.812591","indexId":"70169158","displayToPublicDate":"2016-03-22T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":894,"text":"Arctic","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatial genetic structure of Long-tailed Ducks (Clangula hyemalis) among Alaskan, Canadian, and Russian breeding populations","title":"Spatial genetic structure of Long-tailed Ducks (Clangula hyemalis) among Alaskan, Canadian, and Russian breeding populations","docAbstract":"Arctic ecosystems are changing at an unprecedented rate. How Arctic species are able to respond to such environmental change is partially dependent on the connections between local and broadly distributed populations. For species like the Long-tailed Duck (Clangula hyemalis), we have limited telemetry and band-recovery information from which to infer population structure and migratory connectivity; however, genetic analyses can offer additional insights. To examine population structure in the Long-tailed Duck, we characterized variation at mtDNA control region and microsatellite loci among four breeding areas in Alaska, Canada, and Russia. We observed significant differences in the variance of mtDNA haplotype frequencies between the Yukon-Kuskokwim Delta (YKD) and the three Arctic locations (Arctic Coastal Plain in Alaska, eastern Siberia, and central Canadian Arctic). However, like most sea duck genetic assessments, our study found no evidence of population structure based on autosomal microsatellite loci. Long-tailed Ducks use multiple wintering areas where pair formation occurs with some populations using both the Pacific and Atlantic Oceans. This situation provides a greater opportunity for admixture across breeding locales, which would likely homogenize the nuclear genome even in the presence of female philopatry. The observed mtDNA differentiation was largely due to the presence of two divergent clades: (A) a clade showing signs of admixture among all breeding locales and (B) a clade primarily composed of YKD samples. We hypothesize that the pattern of mtDNA differentiation reflects some degree of philopatry to the YKD and isolation of two refugial populations with subsequent expansion and admixture. We recommend additional genetic assessments throughout the circumpolar range of Long-tailed Ducks to further quantify aspects of genetic diversity and migratory connectivity in this species.
","language":"English","publisher":"Arctic Institute of North America","publisherLocation":"Montreal","doi":"10.14430/arctic4548","usgsCitation":"Wilson, R.E., Gust, J., Petersen, M.R., and Talbot, S.L., 2016, Spatial genetic structure of Long-tailed Ducks (Clangula hyemalis) among Alaskan, Canadian, and Russian breeding populations: Arctic, v. 69, no. 1, p. 65-78, https://doi.org/10.14430/arctic4548.","productDescription":"Article: 14 p.; Data Release","startPage":"65","endPage":"78","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058269","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438629,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HX19RJ","text":"USGS data release","linkHelpText":"Long-tailed Duck (Clangula hyemalis) Microsatellite DNA Data, Alaska, Canada, Russia, 1994-2002"},{"id":319212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335474,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7HX19RJ"}],"country":"Canada, Russia, United States","otherGeospatial":"Arctic Coastal Plain, central Canadian Arctic, eastern Siberia, Yukon-Kuskokwim Delta","volume":"69","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-01","publicationStatus":"PW","scienceBaseUri":"56f3be4fe4b0f59b85e02f08","contributors":{"authors":[{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":623264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gust, J. R.","contributorId":167730,"corporation":false,"usgs":false,"family":"Gust","given":"J. R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":623267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petersen, Margaret R. 0000-0001-6082-3189 mrpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-6082-3189","contributorId":167729,"corporation":false,"usgs":true,"family":"Petersen","given":"Margaret","email":"mrpetersen@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":623265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":623266,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169142,"text":"ds983 - 2016 - Water temperature profiles for reaches of the Raging River during summer baseflow, King County, western Washington, July 2015","interactions":[],"lastModifiedDate":"2016-03-23T08:58:18","indexId":"ds983","displayToPublicDate":"2016-03-22T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"983","title":"Water temperature profiles for reaches of the Raging River during summer baseflow, King County, western Washington, July 2015","docAbstract":"Re-introducing wood into rivers where it was historically removed is one approach to improving habitat conditions in rivers of the Pacific Northwest. The Raging River drainage basin, which flows into the Snoqualmie River at Fall City, western Washington, was largely logged during the 20th century and wood was removed from its channel. To improve habitat conditions for several species of anadromous salmonids that spawn and rear in the Raging River, King County Department of Transportation placed untethered log jams in a 250-meter reach where wood was historically removed. The U.S. Geological Survey measured longitudinal profiles of near-streambed temperature during summer baseflow along 1,026 meters of channel upstream, downstream, and within the area of wood placements. These measurements were part of an effort by King County to monitor the geomorphic and biological responses to these wood placements. Near-streambed temperatures averaged over about 1-meter intervals were measured with a fiber‑optic distributed temperature sensor every 30 minutes for 7 days between July 7 and 13, 2015. Vertical temperature profiles were measured coincident with the longitudinal temperature profile at four locations at 0 centimeters (cm) (at the streambed), and 35 and 70 cm beneath the streambed to document thermal dynamics of the hyporheic zone and surface water in the study reach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds983","collaboration":"Prepared in cooperation with King County Department of Natural Resource and Parks","usgsCitation":"Gendaszek, A.S., and Opatz, C.C., 2016, Water temperature profiles for reaches of the Raging River during summer baseflow, King County, western Washington, July 2015: U.S. Geological Survey Data Series 983, 8 p.,\nhttps://dx.doi.org/10.3133/ds983.","productDescription":"Report: iii, 8 p.; Tables 1-3","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070544","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":319142,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0983/coverthb.jpg"},{"id":319143,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0983/ds983.pdf","text":"Report","size":"4.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 983"},{"id":319144,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0983/ds983_table01.xlsx","text":"Table 1","size":"1.2 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 983 Table 1"},{"id":319145,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0983/ds983_table02.xlsx","text":"Table 2","size":"56 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 983 Table 2"},{"id":319146,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0983/ds983_table03.xlsx","text":"Table 3","size":"70 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 983 Table 3"}],"country":"United States","state":"Washington","county":"King County","otherGeospatial":"Raging River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.8639,\n 47.45\n ],\n [\n -121.8639,\n 47.4569\n ],\n [\n -121.8583,\n 47.4569\n ],\n [\n -121.8583,\n 47.45\n ],\n [\n -121.8639,\n 47.45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.
","language":"English","publisher":"Kluwer Academic Publishers","doi":"10.1007/s10661-016-5228-0","usgsCitation":"Cooke, S., Martins, E.G., Struthers, D.P., Gutowsky, L.F., Powers, M.H., Doka, S.E., Dettmers, J.M., Crook, D.A., Lucas, M.C., Holbrook, C., and Krueger, C., 2016, A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations: Environmental Monitoring and Assessment, v. 188, no. 239, 18 p., https://doi.org/10.1007/s10661-016-5228-0.","productDescription":"18 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073964","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471130,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/file/1387959/1/Accepted%20Journal%20Article","text":"External Repository"},{"id":326047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"188","issue":"239","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-22","publicationStatus":"PW","scienceBaseUri":"57a315b9e4b006cb45558a20","contributors":{"authors":[{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":644582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martins, Eduardo G","contributorId":173417,"corporation":false,"usgs":false,"family":"Martins","given":"Eduardo","email":"","middleInitial":"G","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":644583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Struthers, Daniel P","contributorId":173418,"corporation":false,"usgs":false,"family":"Struthers","given":"Daniel","email":"","middleInitial":"P","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":644584,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gutowsky, Lee F G","contributorId":149696,"corporation":false,"usgs":false,"family":"Gutowsky","given":"Lee","email":"","middleInitial":"F G","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":644585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":644586,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doka, Susan E.","contributorId":173419,"corporation":false,"usgs":false,"family":"Doka","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":644587,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dettmers, John M.","contributorId":27395,"corporation":false,"usgs":true,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":644588,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crook, David A","contributorId":173420,"corporation":false,"usgs":false,"family":"Crook","given":"David","email":"","middleInitial":"A","affiliations":[{"id":12877,"text":"Charles Darwin University","active":true,"usgs":false}],"preferred":false,"id":644589,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lucas, Martyn C.","contributorId":18725,"corporation":false,"usgs":true,"family":"Lucas","given":"Martyn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":644590,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":644581,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Krueger, Charles C.","contributorId":73131,"corporation":false,"usgs":true,"family":"Krueger","given":"Charles C.","affiliations":[],"preferred":false,"id":644591,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70169299,"text":"70169299 - 2016 - Permissible Home Range Estimation (PHRE) in restricted habitats: A new algorithm and an evaluation for sea otters","interactions":[],"lastModifiedDate":"2016-03-24T08:44:05","indexId":"70169299","displayToPublicDate":"2016-03-22T09:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Permissible Home Range Estimation (PHRE) in restricted habitats: A new algorithm and an evaluation for sea otters","docAbstract":"Parametric and nonparametric kernel methods dominate studies of animal home ranges and space use. Most existing methods are unable to incorporate information about the underlying physical environment, leading to poor performance in excluding areas that are not used. Using radio-telemetry data from sea otters, we developed and evaluated a new algorithm for estimating home ranges (hereafter Permissible Home Range Estimation, or “PHRE”) that reflects habitat suitability. We began by transforming sighting locations into relevant landscape features (for sea otters, coastal position and distance from shore). Then, we generated a bivariate kernel probability density function in landscape space and back-transformed this to geographic space in order to define a permissible home range. Compared to two commonly used home range estimation methods, kernel densities and local convex hulls, PHRE better excluded unused areas and required a smaller sample size. Our PHRE method is applicable to species whose ranges are restricted by complex physical boundaries or environmental gradients and will improve understanding of habitat-use requirements and, ultimately, aid in conservation efforts.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0150547","collaboration":"USFWS","usgsCitation":"Tarjan, L.M., and Tinker, M.T., 2016, Permissible Home Range Estimation (PHRE) in restricted habitats: A new algorithm and an evaluation for sea otters: PLoS ONE, v. 11, no. 3, https://doi.org/10.1371/journal.pone.0150547.","productDescription":"20 p.","startPage":"e0150547","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072967","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471131,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0150547","text":"Publisher Index Page"},{"id":438630,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76H4FH8","text":"USGS data release","linkHelpText":"Geospatial data collected from tagged sea otters in central California, 1998-2012"},{"id":319336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-22","publicationStatus":"PW","scienceBaseUri":"56f50fcce4b0f59b85e1eb77","contributors":{"authors":[{"text":"Tarjan, Lily M","contributorId":167782,"corporation":false,"usgs":false,"family":"Tarjan","given":"Lily","email":"","middleInitial":"M","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":623488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":623487,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159388,"text":"sir20155152 - 2016 - Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska","interactions":[],"lastModifiedDate":"2016-03-22T10:17:15","indexId":"sir20155152","displayToPublicDate":"2016-03-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5152","title":"Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska","docAbstract":"Digital flood-inundation maps for a 12.5-mile reach of the Big Papillion Creek from 0.6 mile upstream from the State Street Bridge to the 72nd Street Bridge in Omaha, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the Papio-Missouri River Natural Resources District. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Big Papillion Creek at Fort Street at Omaha, Nebraska (station 06610732). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at this site.
\nFlood profiles were computed for the 12.5-mile reach by means of a one-dimensional step-backwater model. The model was calibrated by using the current (2015) stage-discharge relation at streamgages for the Big Papillion Creek at Fort Street at Omaha, Nebraska, and the Big Papillion Creek at Q Street at Omaha, Nebraska. The hydraulic model was then used to compute 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum for the Big Papillion Creek at Fort Street and ranging from 18 ft (or near bankfull) to 32 ft, which exceeds the “major flood stage” as defined by the National Weather Service. The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging data having a 1.18-ft vertical accuracy and 3.28-ft horizontal resolution) to delineate the area flooded at each flood stage (water level).
\nThe availability of these flood-inundation maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155152","collaboration":"Prepared in cooperation with the Papio-Missouri River Natural Resources District","usgsCitation":"Strauch, K.R., Dietsch, B.J., and Anderson, K.J., 2016, Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska: U.S. Geological Survey Scientific Investigations Report 2015–5152, 11 p., https://dx.doi.org/10.3133/sir20155152.","productDescription":"Report: v, 11 p.; Datasets; Metadata","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066029","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":314625,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_river_areas_GRIDS.zip","text":"River area GRIDS","size":"52.9 MB","description":"SIR 2015–5152 River area GRIDS"},{"id":314626,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_river_areas_shapefiles.zip","text":"River area shapefiles","size":"2.2 MB","description":"SIR 2015–5152 River area shapefiles"},{"id":314628,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_metadata_BigPapio_at_Fort_FIM_GRID.txt","text":"GRID metadata","size":"20.0 kb","description":"SIR 2015–5152 GRID metadata"},{"id":314629,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_metadata_BigPapio_at_Fort_FIM_shapefile.txt","text":"Shapefile metadata","size":"20.0 kb","description":"SIR 2015–5152 Shapefile metadata"},{"id":314466,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152.pdf","text":"Report","size":"2.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5152"},{"id":314622,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_levee_areas_GRIDS.zip","text":"Levee area GRIDS","size":"1.6 MB","description":"SIR 2015–5152 Levee area GRIDS"},{"id":314623,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_levee_areas_shapefiles.zip","text":"Levee area shapefiles","size":"144 kb","description":"SIR 2015–5152 Levee area shapefiles"},{"id":314465,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5152/coverthb.jpg"}],"country":"United States","state":"Nebraska","city":"Omaha","otherGeospatial":"Big Papillion Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.16676330566406,\n 41.23702755320388\n ],\n [\n -96.16676330566406,\n 41.35052580597025\n ],\n [\n -96.01020812988281,\n 41.35052580597025\n ],\n [\n -96.01020812988281,\n 41.23702755320388\n ],\n [\n -96.16676330566406,\n 41.23702755320388\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Seepage investigations have been conducted annually by the U.S. Geological Survey from 1988 to 1998 and from 2004 to the present (2014) along a 64-mile reach of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, as part of the Mesilla Basin monitoring program. Results of the investigation conducted in 2014 are presented in this report. The 2014 seepage investigation was conducted on February 11, 2014, during the low-flow conditions of the non-irrigation season. During the 2014 investigation, discharge was measured at 23 sites along the main-stem Rio Grande and 19 inflow sites within the study reach. Because of extended drought conditions affecting the basin, many sites along the Rio Grande (17 main-stem and 9 inflow) were observed to be dry in February 2014. Water-quality samples were collected during the seepage investigation at sites with flowing water as part of a long-term monitoring effort in the region.
Net seepage gain or loss was computed for each subreach (the interval between two adjacent measurement locations along the river) by subtracting the discharge measured at the upstream location from the discharge measured at the closest downstream location along the river and then subtracting any inflow to the river within the subreach. An estimated gain or loss was determined to be meaningful when it exceeded the cumulative measurement uncertainty associated with the net seepage computation. The cumulative seepage loss in the 64-mile study reach in 2014 was 16.0 plus or minus 2.9 cubic feet per second.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165010","usgsCitation":"Briody, A.C., Robertson, A.J., and Thomas, Nicole, 2016, Seepage investigation of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, 2014: U.S. Geological Survey Scientific Investigations Report 2016–5010, 15 p., https://dx.doi.org/10.3133/sir20165010.","productDescription":"Report: vi, 12 p., Appendix: 3 p.","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068494","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":319116,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5010/coverthb.jpg"},{"id":319117,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5010/sir20165010.pdf","text":"Report","size":"3.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5010"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.9,\n 32.5\n ],\n [\n -106.9,\n 31.75\n ],\n [\n -106.5,\n 31.75\n ],\n [\n -106.5,\n 32.5\n ],\n [\n -106.9,\n 32.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montogmery Blvd., NE Suite 400
Albuquerque, NM 87109–1311
Seepage investigations have been conducted annually by the U.S. Geological Survey from 1988 to 1998 and from 2004 to the present (2015) along a 64-mile reach of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, as part of the Mesilla Basin monitoring program. Results of the investigation conducted in 2015 are presented in this report. The 2015 seepage investigation was conducted on February 10, 2015, during the low-flow conditions of the non-irrigation season. During the 2015 investigation, discharge was measured at 23 sites along the main-stem Rio Grande and 19 inflow sites within the study reach. Because of extended drought conditions affecting the basin, many sites along the Rio Grande (17 main-stem and 10 inflow) were observed to be dry in February 2015.
\nNet seepage gain or loss was computed for each subreach (the interval between two adjacent measurement locations along the river) by subtracting the discharge measured at the upstream location from the discharge measured at the closest downstream location along the river and then subtracting any inflow to the river within the subreach. An estimated gain or loss was determined to be meaningful when it exceeded the cumulative measurement uncertainty associated with the net seepage computation. The cumulative seepage loss in the 64-mile study reach in 2015 was 17.3 plus or minus 2.6 cubic feet per second. Gaining and losing reaches identified in this investigation generally correspond to seepage patterns observed in previous investigations conducted during dry years, with the gaining reaches occurring primarily at the southern (downstream) end of the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165011","usgsCitation":"Briody, A.C., Robertson, A.J., and Thomas, Nicole, 2016, Seepage investigation of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5011, 15 p., https://dx.doi.org/10.3133/sir20165011.","productDescription":"vi., 15 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069688","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":319125,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5011/sir20165011.pdf","text":"Report","size":"3.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5011"},{"id":319124,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5011/coverthb.jpg"}],"country":"United States","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.85302734374999,\n 31.728167146023935\n ],\n [\n -106.85302734374999,\n 32.41706632846282\n ],\n [\n -106.3970947265625,\n 32.41706632846282\n ],\n [\n -106.3970947265625,\n 31.728167146023935\n ],\n [\n -106.85302734374999,\n 31.728167146023935\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montogmery Blvd., NE Suite 400
Albuquerque, NM 87109–1311
This report, prepared by the U.S. Geological Survey in cooperation with the Kansas Department of Agriculture, Division of Water Resources, presents derivative statistics of 2013 irrigation water use in Kansas. The published regional and county-level statistics from the previous 4 years (2009–12) are shown with the 2013 statistics and are used to calculate a 5-year average. An overall Kansas average and regional averages also are calculated and presented. Total reported irrigation water use in 2013 was 3.3 million acre-feet of water applied to 3.0 million irrigated acres.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds981","collaboration":"Prepared in cooperation with the Kansas Department of Agriculture, Division of Water Resources","usgsCitation":"Lanning-Rush, J.L., 2016, Irrigation water use in Kansas, 2013: U.S. Geological Survey Data Series 981, 12 p., https://dx.doi.org/10.3133/ds981.","productDescription":"Report: iv, 12 p.; Tables 6-12; Appendix: 2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070156","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":318889,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0981/ds981.pdf","text":"Report","size":"617 kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 981"},{"id":318890,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0981/downloads/ds981_tables6to12.xlsx","text":"Tables 6–12","size":"80 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 981 Tables "},{"id":318888,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0981/coverthb_new.jpg"},{"id":318893,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0981/downloads/ds981_appendix.pdf","text":"Water-Use Report","size":"1.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 981 Appendix"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.29541015625,\n 39.99395569397331\n ],\n [\n -102.06298828125,\n 40.01078714046552\n ],\n [\n -102.052001953125,\n 36.98500309285596\n ],\n [\n -94.603271484375,\n 36.99377838872517\n ],\n [\n -94.6142578125,\n 39.13006024213511\n ],\n [\n -94.76806640624999,\n 39.172658670429946\n ],\n [\n -94.82299804687499,\n 39.2407625100131\n ],\n [\n -94.910888671875,\n 39.29179704377487\n ],\n [\n -94.8779296875,\n 39.38526381099777\n ],\n [\n -94.976806640625,\n 39.436192999314095\n ],\n [\n -95.086669921875,\n 39.53793974517628\n ],\n [\n -95.042724609375,\n 39.57182223734374\n ],\n [\n -95.042724609375,\n 39.63953756436671\n ],\n [\n -94.9658203125,\n 39.73253798438173\n ],\n [\n -94.910888671875,\n 39.73253798438173\n ],\n [\n -94.888916015625,\n 39.78321267821705\n ],\n [\n -94.910888671875,\n 39.842286020743394\n ],\n [\n -94.95483398437499,\n 39.8928799002948\n ],\n [\n -95.03173828125,\n 39.90973623453719\n ],\n [\n -95.06469726562499,\n 39.87601941962116\n ],\n [\n -95.174560546875,\n 39.926588421909436\n ],\n [\n -95.29541015625,\n 39.99395569397331\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
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Non-native fish introductions are a major threat to biodiversity and fisheries, and occur through numerous pathways that vary regionally in importance. A key strategy for managing invasions is to focus prevention efforts on pathways posing the greatest risk of future introductions. We identified high-risk pathways for fish establishment in the Mid-Atlantic region of the United States based on estimates of probability of establishment and records of previous introductions, which were considered in the context of emerging socioeconomic trends. We used estimates of propagule pressure, species’ environmental tolerance, and size of species pool to assess the risk of establishment by pathway. Pathways varied considerably in historic importance and species composition, with the majority of species introduced intentionally via stocking (primarily for sport, forage, or biocontrol) or bait release. Bait release, private stocking, illegal introductions intended to establish reproducing populations (e.g., of sport fish), aquaculture, and the sale of live organisms all create risks for future invasions in the Mid-Atlantic region. Of these pathways, bait release probably poses the greatest risk of introductions for the Mid-Atlantic region because propagule pressure is moderate, most released species are tolerant of local environmental conditions, and the pool of species available for transplantation is large. Our findings differ considerably from studies in other regions (e.g., bait release is a dominant pathway in the Mid-Atlantic region, whereas illegal introduction of sport fish is dominant in the western US and aquarium releases are dominant in Florida), demonstrating the need for regional-scale assessments of, and management strategies for, introduction pathways.
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The monarch’s multi-generational migration between overwintering grounds in central Mexico and the summer breeding grounds in the northern U.S. and southern Canada is celebrated in all three countries and creates shared management responsibilities across North America. Here we present a novel Bayesian multivariate auto-regressive state-space model to assess quasi-extinction risk and aid in the establishment of a target population size for monarch conservation planning. We find that, given a range of plausible quasi-extinction thresholds, the population has a substantial probability of quasi-extinction, from 11–57% over 20 years, although uncertainty in these estimates is large. Exceptionally high population stochasticity, declining numbers, and a small current population size act in concert to drive this risk. An approximately 5-fold increase of the monarch population size (relative to the winter of 2014–15) is necessary to halve the current risk of quasi-extinction across all thresholds considered. Conserving the monarch migration thus requires active management to reverse population declines, and the establishment of an ambitious target population size goal to buffer against future environmentally driven variability.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/srep23265","usgsCitation":"Semmens, B.X., Semmens, D.J., Thogmartin, W.E., Wiederholt, R., Lopez-Hoffman, L., Diffendorfer, J., Pleasants, J., Oberhauser, K.S., and Taylor, O.R., 2016, Quasi-extinction risk and population targets for the Eastern, migratory population of monarch butterflies (Danaus plexippus): Scientific Reports, v. 6, Article number 23265; 7 p., https://doi.org/10.1038/srep23265.","productDescription":"Article number 23265; 7 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066835","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":471134,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep23265","text":"Publisher Index Page"},{"id":320161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-21","publicationStatus":"PW","scienceBaseUri":"571756e6e4b0ef3b7caa62a9","contributors":{"authors":[{"text":"Semmens, Brice X.","contributorId":149775,"corporation":false,"usgs":false,"family":"Semmens","given":"Brice","email":"","middleInitial":"X.","affiliations":[{"id":17820,"text":"Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":626766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":626765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":626767,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiederholt, Ruscena","contributorId":149125,"corporation":false,"usgs":false,"family":"Wiederholt","given":"Ruscena","affiliations":[{"id":17653,"text":"School of Natural Resources & the Environment, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":626768,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":626769,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":626770,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pleasants, John M.","contributorId":168616,"corporation":false,"usgs":false,"family":"Pleasants","given":"John M.","affiliations":[{"id":25341,"text":"Department of Ecology, Evolution, and Organismal Biology, Iowa State University","active":true,"usgs":false}],"preferred":false,"id":626771,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oberhauser, Karen S.","contributorId":27737,"corporation":false,"usgs":true,"family":"Oberhauser","given":"Karen","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":626772,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Taylor, Orley R.","contributorId":168617,"corporation":false,"usgs":false,"family":"Taylor","given":"Orley","email":"","middleInitial":"R.","affiliations":[{"id":25342,"text":"Department of Ecology and Evolutionary Biology, University of Kansas","active":true,"usgs":false}],"preferred":false,"id":626773,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70169330,"text":"70169330 - 2016 - Coral-associated bacterial diversity is conserved across two deep-sea Anthothela species","interactions":[],"lastModifiedDate":"2016-04-07T11:39:47","indexId":"70169330","displayToPublicDate":"2016-03-21T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"title":"Coral-associated bacterial diversity is conserved across two deep-sea Anthothela species","docAbstract":"Cold-water corals, similar to tropical corals, contain diverse and complex microbial assemblages. These bacteria provide essential biological functions within coral holobionts, facilitating increased nutrient utilization and production of antimicrobial compounds. To date, few cold-water octocoral species have been analyzed to explore the diversity and abundance of their microbial associates. For this study, 23 samples of the family Anthothelidae were collected from Norfolk (n = 12) and Baltimore Canyons (n = 11) from the western Atlantic in August 2012 and May 2013. Genetic testing found that these samples comprised two Anthothela species (Anthothela grandiflora and Anthothela sp.) and Alcyonium grandiflorum. DNA was extracted and sequenced with primers targeting the V4-V5 variable region of the 16S rRNA gene using 454 pyrosequencing with GS FLX Titanium chemistry. Results demonstrated that the coral host was the primary driver of bacterial community composition. Al. grandiflorum, dominated by Alteromonadales and Pirellulales had much higher species richness, and a distinct bacterial community compared to Anthothela samples. Anthothela species (A. grandiflora and Anthothela sp.) had very similar bacterial communities, dominated by Oceanospirillales and Spirochaetes. Additional analysis of core-conserved bacteria at 90% sample coverage revealed genus level conservation across Anthothela samples. This core included unclassified Oceanospirillales, Kiloniellales, Campylobacterales, and genus Spirochaeta. Members of this core were previously recognized for their functional capabilities in nitrogen cycling and suggest the possibility of a nearly complete nitrogen cycle within Anthothela species. Overall, many of the bacterial associates identified in this study have the potential to contribute to the acquisition and cycling of nutrients within the coral holobiont.
","language":"English","publisher":"Frontiers in Microbiology","doi":"10.3389/fmicb.2016.00458","usgsCitation":"Lawler, S.N., Kellogg, C.A., France, S.C., Clostio, R.W., Brooke, S.D., and Ross, S., 2016, Coral-associated bacterial diversity is conserved across two deep-sea Anthothela species: Frontiers in Microbiology, v. 7, art458: 18 p., https://doi.org/10.3389/fmicb.2016.00458.","productDescription":"art458: 18 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070380","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471135,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2016.00458","text":"Publisher Index Page"},{"id":319379,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Norfolk Canyon; Baltimore Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.124755859375,\n 37.60552821745789\n ],\n [\n -74.1357421875,\n 37.322120359451766\n ],\n [\n -73.729248046875,\n 37.31338308990806\n ],\n [\n -73.7567138671875,\n 37.64468458716586\n ],\n [\n -74.124755859375,\n 37.60552821745789\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.7841796875,\n 38.55246141354153\n ],\n [\n -73.8720703125,\n 38.33303882235456\n ],\n [\n -73.54248046875,\n 38.302869955150044\n ],\n [\n -73.4326171875,\n 38.50519140240354\n ],\n [\n -73.7841796875,\n 38.55246141354153\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"56f50fb6e4b0f59b85e1ead5","contributors":{"authors":[{"text":"Lawler, Stephanie N.","contributorId":149424,"corporation":false,"usgs":false,"family":"Lawler","given":"Stephanie","email":"","middleInitial":"N.","affiliations":[{"id":17733,"text":"University of South Florida, St. Petersburg, FL","active":true,"usgs":false}],"preferred":false,"id":623799,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":623800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"France, Scott C","contributorId":167845,"corporation":false,"usgs":false,"family":"France","given":"Scott","email":"","middleInitial":"C","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":623801,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clostio, Rachel W","contributorId":167846,"corporation":false,"usgs":false,"family":"Clostio","given":"Rachel","email":"","middleInitial":"W","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":623802,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brooke, Sandra D.","contributorId":167844,"corporation":false,"usgs":false,"family":"Brooke","given":"Sandra","email":"","middleInitial":"D.","affiliations":[{"id":24836,"text":"Coastal and Marine Laboratory, Florida State University","active":true,"usgs":false}],"preferred":false,"id":623803,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ross, Steve W.","contributorId":41134,"corporation":false,"usgs":false,"family":"Ross","given":"Steve W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":623804,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70156258,"text":"sir20155071 - 2016 - Arsenic and radionuclide occurrence and relation to geochemistry in groundwater of the Gulf Coast Aquifer System in Houston, Texas, 2007–11","interactions":[],"lastModifiedDate":"2016-03-22T08:40:17","indexId":"sir20155071","displayToPublicDate":"2016-03-21T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5071","title":"Arsenic and radionuclide occurrence and relation to geochemistry in groundwater of the Gulf Coast Aquifer System in Houston, Texas, 2007–11","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the City of Houston, began a study in 2007 to determine concentrations, spatial extent, and associated geochemical conditions that might be conducive for mobility and transport of selected naturally occurring trace elements and radionuclides in the Gulf Coast aquifer system in Houston, Texas. Water samples were collected from 91 municipal supply wells completed in the Evangeline and Chicot aquifers of the Gulf Coast aquifer system in northeastern, northwestern, and southwestern Houston; hereinafter referred to as northeast, northwest and southwest Houston areas. Wells were sampled in three phases: (1) 28 municipal supply wells were sampled during 2007–8, (2) 60 municipal supply wells during 2010, and (3) 3 municipal supply wells during December 2011. During each phase of sampling, samples were analyzed for major ions, selected trace elements, and radionuclides. At a subset of wells, concentrations of arsenic species and other radionuclides (carbon-14, radium-226, radium-228, radon-222, and tritium) also were analyzed. Selected physicochemical properties were measured in the field at the time each sample was collected, and oxidation-reduction potential and unfiltered sulfides also were measured at selected wells. The source-water (the raw, ambient water withdrawn from municipal supply wells prior to water treatment) samples were collected for assessment of aquifer conditions in order to provide community water-system operators information that could be important when they make decisions about which treatment processes to apply before distributing finished drinking water.
\nGeochemical conditions of groundwater of the Gulf Coast aquifer system are suitable in some instances for release of arsenic and radionuclides from aquifer materials. Recent changes to the U.S. Environmental Protection Agency (EPA) primary drinking-water regulations for arsenic and a selected number of natural radionuclides have highlighted the necessity for municipal supply system managers to be aware of the occurrence and distribution of these constituents in their source water. Concentrations of arsenic ranged from 0.58 to 23.5 micrograms per liter (μg/L), with relatively low median and 75th percentile concentrations (2.7 and 3.6 μg/L, respectively). The gross alpha-particle activity completed within 72 hours after sample collection ranged from R-1.1 (nondetect where the result was below the sample specific critical level) to 39.7 picocuries per liter (pCi/L), with a median of 10.3 pCi/L. After 30 days, the gross alpha-particle activities in the 91 samples ranged from R-0.94 to 25.5 pCi/L, with a median of 5.60 pCi/L. Concentrations of uranium ranged from less than 0.02 to 42.7 μg/L, with a median value of 1.69 μg/L and a 75th-percentile value of 6.48 μg/L. The maximum concentrations of radium-226 and combined radium (sum of radium-226 plus radium-228) were 4.34 pCi/L and 3.23 pCi/L, respectively.
\nAquifer major-ion geochemistry was characterized and shown to contain three chemical types of water as grouped by a simplified predominant cation and anion classification system: (1) calcium- bicarbonate type, (2) sodium-bicarbonate type, and (3) sodium-chloride type. Aquifer geochemistry also was characterized into four reduction-oxidation (redox) categories: (1) oxic, (2) suboxic, (3) mixed, and (4) anoxic. Within the anoxic category, groundwater was further characterized into four presumed predominant reduction processes: (1) iron or sulfate or both [Fe(III)/SO4] reducing, (2) iron [Fe(III)] reducing, (3) iron and sulfate [Fe(III)-SO4] reducing, or (4) methanogenic, as defined by composition of redox species. The oxic category was associated with calcium-bicarbonate-type water, and the methanogenic-anoxic process was associated exclusively with the sodium-bicarbonate-type water. The species of arsenic and the dominant radionuclide present were associated with specific redox categories. Arsenate was associated primarily with oxic water and did not exceed 3.5 µg/L, whereas arsenite was associated with iron-reducing, anoxic water samples and, at the highest concentrations, occurred in sulfate-reducing, anoxic; methanogenic-anoxic; or both water samples. Uranium was associated exclusively with the oxic water, whereas the highest concentrations of combined radium were associated with the iron-reducing, anoxic water. The gross alpha-particle activity was greatest in the oxic waters where the source of the radioactivity was the uranium.
\nAssociated geochemical conditions conducive for mobility of arsenic and radionuclides and their spatial and vertical extent in the Gulf Coast aquifer system in Houston are important aspects to the areal management of the municipal groundwater supplies in Houston. Ongoing research is seeking to define chemical or geological factors that are the optimal indicators for elevated concentrations of these naturally occurring constituents.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155071","collaboration":"Prepared in cooperation with the City of Houston","usgsCitation":"Oden, J.H., and Szabo, Zoltan, 2015, Arsenic and radionuclide occurrence and relation to geochemistry in groundwater of the Gulf Coast Aquifer System in Houston, Texas, 2007–11: U.S. Geological Scientific Investigations Report 2015–5071, 105 p., 4 apps., https://dx.doi.org/10.3133/sir20155071.","productDescription":"Report: xi, 105 p.; Appendixes: 29 p. ","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055471","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":318941,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5071/coverthb.jpg"},{"id":318942,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5071/sir20155071.pdf","text":"Report","size":"3.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5071"},{"id":318943,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5071/sir20155071_appendix1to4.pdf","text":"Appendixes 1–4","size":"428 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5071 Appendixes 1–4"}],"country":"United States","state":"Texas","city":"Houston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.35333251953125,\n 29.5232805008286\n ],\n [\n -94.515380859375,\n 29.441989466225706\n ],\n [\n -94.64996337890625,\n 29.351057685705033\n ],\n [\n -94.84222412109375,\n 29.216904948184734\n ],\n [\n -95.05645751953124,\n 29.048966726566885\n ],\n [\n -95.3118896484375,\n 28.86632376895912\n ],\n [\n -95.53436279296875,\n 28.878349647602047\n ],\n [\n -95.75958251953125,\n 29.07297469064491\n ],\n [\n -95.877685546875,\n 29.27202470909843\n ],\n [\n -95.92987060546874,\n 29.34148119149953\n ],\n [\n -95.98480224609374,\n 29.420460341013133\n ],\n [\n -96.03973388671875,\n 29.44916482692468\n ],\n [\n -96.06170654296875,\n 29.49698759653577\n ],\n [\n -96.02325439453124,\n 29.508939763268394\n ],\n [\n -96.0589599609375,\n 29.554345125748267\n ],\n [\n -96.08367919921875,\n 29.587788659909958\n ],\n [\n -96.0205078125,\n 29.633158589140564\n ],\n [\n -96.05072021484375,\n 29.680894340704334\n ],\n [\n -96.0040283203125,\n 29.702368038541767\n ],\n [\n -96.01776123046875,\n 29.716681287231072\n ],\n [\n -96.04522705078125,\n 29.728607435707517\n ],\n [\n -96.05072021484375,\n 29.790600550959457\n ],\n [\n -96.1029052734375,\n 29.81205076752506\n ],\n [\n -96.119384765625,\n 29.87637380707133\n ],\n [\n -96.12487792968749,\n 29.938275329718987\n ],\n [\n -96.10015869140625,\n 29.99775972557893\n ],\n [\n -96.12487792968749,\n 30.035811042667792\n ],\n [\n -96.1578369140625,\n 30.083354648756153\n ],\n [\n -96.17980957031249,\n 30.128499916692782\n ],\n [\n -96.1688232421875,\n 30.171250084367482\n ],\n [\n -96.119384765625,\n 30.225848323247707\n ],\n [\n -96.09466552734375,\n 30.28041626667403\n ],\n [\n -96.14410400390625,\n 30.334953881988564\n ],\n [\n -96.16333007812499,\n 30.37761431777479\n ],\n [\n -96.185302734375,\n 30.4060442699695\n ],\n [\n -96.2347412109375,\n 30.441570071519443\n ],\n [\n -95.7623291015625,\n 30.68988785772121\n ],\n [\n -95.30914306640625,\n 30.904581367044212\n ],\n [\n -95.240478515625,\n 30.871582821957446\n ],\n [\n -95.22125244140625,\n 30.831497881307943\n ],\n [\n -95.16357421875,\n 30.7937555812177\n ],\n [\n -95.13885498046875,\n 30.741835717889792\n ],\n [\n -95.108642578125,\n 30.69697330439986\n ],\n [\n -95.00976562499999,\n 30.652090026760014\n ],\n [\n -95.00976562499999,\n 30.62373195163005\n ],\n [\n -95.0372314453125,\n 30.58354378627138\n ],\n [\n -94.976806640625,\n 30.576450026618076\n ],\n [\n -94.9273681640625,\n 30.56462594065098\n ],\n [\n -94.85321044921875,\n 30.545704405480997\n ],\n [\n -94.866943359375,\n 30.517315187761888\n ],\n [\n -94.83673095703125,\n 30.479449996609706\n ],\n [\n -94.8834228515625,\n 30.462879341709886\n ],\n [\n -94.8394775390625,\n 30.439202087235607\n ],\n [\n -94.7955322265625,\n 30.38472258144958\n ],\n [\n -94.7735595703125,\n 30.344435586368462\n ],\n [\n -94.78729248046875,\n 30.299389313522617\n ],\n [\n -94.61151123046875,\n 30.097613277217132\n ],\n [\n -94.52636718749999,\n 29.971590978566113\n ],\n [\n -94.44122314453124,\n 29.816816857649936\n ],\n [\n -94.37805175781249,\n 29.676121784724305\n ],\n [\n -94.35333251953125,\n 29.5232805008286\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Extreme rainfall in September 2013 caused destructive floods in part of the Front Range in Boulder County, Colorado. Erosion from these floods cut roads and isolated mountain communities for several weeks, and large volumes of eroded sediment were deposited downstream, which caused further damage of property and infrastructures. Estimates of peak discharge for these floods and the associated rainfall characteristics will aid land and emergency managers in the future. Several methods (an ensemble) were used to estimate peak discharge at 21 measurement sites, and the ensemble average and standard deviation provided a final estimate of peak discharge and its uncertainty. Because of the substantial erosion and deposition of sediment, an additional estimate of peak discharge was made based on the flow resistance caused by sediment transport effects.
Although the synoptic-scale rainfall was extreme (annual exceedance probability greater than 1,000 years, about 450 millimeters in 7 days) for these mountains, the resulting peak discharges were not. Ensemble average peak discharges per unit drainage area (unit peak discharge, [Qu]) for the floods were 1–2 orders of magnitude less than those for the maximum worldwide floods with similar drainage areas and had a wide range of values (0.21–16.2 cubic meters per second per square kilometer [m3 s-1 km-2]). One possible explanation for these differences was that the band of high-accumulation, high-intensity rainfall was narrow (about 50 kilometers wide), oriented nearly perpendicular to the predominant drainage pattern of the mountains, and therefore entire drainage areas were not subjected to the same range of extreme rainfall. A linear relation (coefficient of determination [R2]=0.69) between Qu and the rainfall intensity (ITc, computed for a time interval equal to the time-of-concentration for the drainage area upstream from each site), had the form: Qu=0.26(ITc-8.6), where the coefficient 0.26 can be considered to be an area-averaged peak runoff coefficient for the September 2013 rain storms in Boulder County, and the 8.6 millimeters per hour to be the rainfall intensity corresponding to a soil moisture threshold that controls the soil infiltration rate. Peak discharge estimates based on the sediment transport effects were generally less than the ensemble average and indicated that sediment transport may be a mechanism that limits velocities in these types of mountain streams such that the Froude number fluctuates about 1 suggesting that this type of floodflow can be approximated as critical flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165003","usgsCitation":"Moody, J.A., 2016, Estimates of peak flood discharge for 21 sites in the Front Range in Colorado in response to extreme rainfall in September 2013: U.S. Geological Survey Scientific Investigations Report 2016–5003, 64 p., https://dx.doi.org/10.3133/sir20165003.","productDescription":"vi, 65p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068930","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":319140,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5003/sir20165003.pdf","text":"Report","size":"14.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5003"},{"id":319139,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5003/coverthb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.833333333333,\n 40.33333333333333\n ],\n [\n -105,\n 40.33333333333333\n ],\n [\n -105,\n 39.83333333333333\n ],\n [\n -105.833333333333,\n 39.83333333333333\n ],\n [\n -105.833333333333,\n 40.33333333333333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, Office of Surface Water
U.S. Geological Survey
415 National Center
12201 Sunrise Valley Drive
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Avian botulism type E is responsible for extensive waterbird mortality on the Great Lakes, yet the actual site of toxin exposure remains unclear. Beached carcasses are often used to describe the spatial aspects of botulism mortality outbreaks, but lack specificity of offshore toxin source locations. We detail methodology for developing a neural network model used for predicting waterbird carcass motions in response to wind, wave, and current forcing, in lieu of a complex analytical relationship. This empirically trained model uses current velocity, wind velocity, significant wave height, and wave peak period in Lake Michigan simulated by the Great Lakes Coastal Forecasting System. A detailed procedure is further developed to use the model for back-tracing waterbird carcasses found on beaches in various parts of Lake Michigan, which was validated using drift data for radiomarked common loon (Gavia immer) carcasses deployed at a variety of locations in northern Lake Michigan during September and October of 2013. The back-tracing model was further used on 22 non-radiomarked common loon carcasses found along the shoreline of northern Lake Michigan in October and November of 2012. The model-estimated origins of those cases pointed to some common source locations offshore that coincide with concentrations of common loons observed during aerial surveys. The neural network source tracking model provides a promising approach for identifying locations of botulinum neurotoxin type E intoxication and, in turn, contributes to developing an understanding of the dynamics of toxin production and possible trophic transfer pathways.
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The objectives of the study were to quantify inorganic and organic accretion rates in back-barrier and mainland marsh and estuarine environments. Various field and laboratory methods were used to achieve these objectives, including subsurface imaging using Ground Penetrating Radar (GPR), sediment sampling, lithologic and microfossil analyses, and geochronology techniques to produce barrier island stratigraphic cross sections to help interpret the recent (last 2000 years) geologic evolution of the island.
This data series report is an archive of GPR and associated Global Positioning System (GPS) data collected in April 2013 from Dauphin Island and adjacent barrier-island environments. In addition to GPR data, marsh core and vibracore data were also collected collected but are not reported (or included) in the current report. Data products, including elevation-corrected subsurface profile images of the processed GPR data, unprocessed digital GPR trace data, post-processed GPS data, Geographic Information System (GIS) files and accompanying Federal Geographic Data Committee (FGDC) metadata, can be downloaded from the Data Downloads page.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds982","usgsCitation":"Forde, A.S., Smith, C.G., and Reynolds, B.J., 2016, Archive of ground penetrating radar data collected during USGS field activity 13BIM01—Dauphin Island, Alabama, April 2013: U.S. Geological Survey Data Series 982, https://dx.doi.org/10.3133/ds982.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068738","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438631,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H70DSZ","text":"USGS data release","linkHelpText":"Sedimentary Data Collected in April 2013 From Dauphin Island and Salt Marshes of Coastal Alabama"},{"id":318974,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":318878,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0982/index.html"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.32832628252302,\n 30.222222538874064\n ],\n [\n -88.0647962871504,\n 30.23742743361879\n ],\n [\n -88.07755483450525,\n 30.261370373972056\n ],\n [\n -88.12286967511226,\n 30.286827097172534\n ],\n [\n -88.13694807219358,\n 30.27124988630632\n ],\n [\n -88.34636422878367,\n 30.235907049955017\n ],\n [\n -88.32832628252302,\n 30.222222538874064\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
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Detection of West Nile virus (WNV) in ducks has been reported in North America in isolated cases of mortality in wild waterbirds and following outbreaks in farmed ducks. Although the virus has been noted as an apparent incidental finding in several species of ducks, little is known about the prevalence of exposure or the outcome of infection with WNV in wild ducks in North America. From 2004–06, we collected sera from 1,406 wild-caught American Wigeon (Anas americana), Mallard (Anas platyrhynchos), and Northern Pintail (Anas acuta) ducks at national wildlife refuges (NWRs) in North Dakota and Wood Ducks (Aix sponsa) at NWRs in South Carolina and Tennessee. We measured the prevalence of previous exposure to WNV in these ducks by measuring WNV antibodies and evaluated variation in exposure among species, age, and year. Additionally, we evaluated the performance of a commercial antibody to wild bird immunoglobulin in duck species that varied in their phylogenetic relatedness to the bird species the antibody was directed against. As determined by a screening immunoassay and a confirmatory plaque reduction neutralization assay, the prevalence of WNV antibody was 10%. In light of experimental studies that show ducks to be relatively resistant to mortality caused by WNV, the antibody prevalence we detected suggests that wild ducks may be less-frequently exposed to WNV than expected for birds inhabiting wetlands where they may acquire infection from mosquitoes.
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