Anthropogenic changes in climate and land use are driving changes in migration patterns of birds worldwide. Spatial changes in migration have been related to long-term temperature trends, but the intrinsic mechanisms by which migratory species adapt to environmental change remain largely unexplored. We show that, for a long-lived social species, older birds with more experience are critical for innovating new migration behaviours. Groups containing older, more experienced individuals establish new overwintering sites closer to the breeding grounds, leading to a rapid population-level shift in migration patterns. Furthermore, these new overwintering sites are in areas where changes in climate have increased temperatures and where food availability from agriculture is high, creating favourable conditions for overwintering. Our results reveal that the age structure of populations is critical for the behavioural mechanisms that allow species to adapt to global change, particularly for long-lived animals, where changes in behaviour can occur faster than evolution.
","language":"English","publisher":"Nature","doi":"10.1038/ncomms12793","usgsCitation":"Teitelbaum, C., Converse, S.J., Fagan, W., Böhning-Gaese, K., O’Hara, R.B., Lacy, A.E., and Mueller, T., 2016, Experience drives innovation of new migration patterns of whooping cranes in response to global change: Nature Communications, v. 7, p. 1-7, https://doi.org/10.1038/ncomms12793.","productDescription":"Article 12793: 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-076811","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470585,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/ncomms12793","text":"Publisher Index Page"},{"id":328304,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-06","publicationStatus":"PW","scienceBaseUri":"57d12c20e4b0571647cec22d","contributors":{"authors":[{"text":"Teitelbaum, Claire S.","contributorId":174360,"corporation":false,"usgs":false,"family":"Teitelbaum","given":"Claire S.","affiliations":[{"id":27439,"text":"Senckenberg Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":648095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":3513,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":648094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagan, William F.","contributorId":108239,"corporation":false,"usgs":true,"family":"Fagan","given":"William F.","affiliations":[],"preferred":false,"id":648096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Böhning-Gaese, Katrin","contributorId":174361,"corporation":false,"usgs":false,"family":"Böhning-Gaese","given":"Katrin","affiliations":[{"id":27439,"text":"Senckenberg Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":648097,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Hara, Robert B.","contributorId":46402,"corporation":false,"usgs":true,"family":"O’Hara","given":"Robert","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":648098,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lacy, Anne E","contributorId":174362,"corporation":false,"usgs":false,"family":"Lacy","given":"Anne","email":"","middleInitial":"E","affiliations":[{"id":16606,"text":"International Crane Foundation","active":true,"usgs":false}],"preferred":false,"id":648099,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mueller, Thomas","contributorId":91393,"corporation":false,"usgs":true,"family":"Mueller","given":"Thomas","affiliations":[],"preferred":false,"id":648100,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70176266,"text":"70176266 - 2016 - Effects of coded-wire-tagging on stream-dwelling Sea Lamprey larvae","interactions":[],"lastModifiedDate":"2016-09-07T10:42:52","indexId":"70176266","displayToPublicDate":"2016-09-07T11:40:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of coded-wire-tagging on stream-dwelling Sea Lamprey larvae","docAbstract":"The effects of coded wire tagging Sea Lamprey Petromyzon marinus larvae from a known-aged stream-dwelling population were assessed. Tagged larvae were significantly shorter on average than untagged larvae from 3 to 18 months after tagging. However, 30 months after tagging, the length distribution of tagged and untagged larvae did not differ and tagged Sea Lampreys were in better condition (i.e., higher condition factor) and more likely to have undergone metamorphosis than the untagged population. The reason why tagged larvae were more likely to metamorphose is not clear, but the increased likelihood of metamorphosis could have been a compensatory response to the period of slower growth after tagging. Slower growth after tagging was consistent across larval size-classes, so handling and displacement from quality habitat during the early part of the growing season was likely the cause rather than the tag burden. The tag effects observed in this study, if caused by displacement and handling, may be minimized in future studies if tagging is conducted during autumn after growth has concluded for the year.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02755947.2016.1185058","usgsCitation":"Johnson, N., Swink, W.D., Dawson, H.A., and Jones, M., 2016, Effects of coded-wire-tagging on stream-dwelling Sea Lamprey larvae: North American Journal of Fisheries Management, v. 36, no. 5, p. 1059-1067, https://doi.org/10.1080/02755947.2016.1185058.","productDescription":"9 p.","startPage":"1059","endPage":"1067","ipdsId":"IP-073267","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":328302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-30","publicationStatus":"PW","scienceBaseUri":"57d12c1fe4b0571647cec21f","contributors":{"authors":[{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":648135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swink, William D.","contributorId":126758,"corporation":false,"usgs":false,"family":"Swink","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":6595,"text":"Retired USGS Fishery Biologist","active":true,"usgs":false}],"preferred":false,"id":648136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dawson, Heather A.","contributorId":12409,"corporation":false,"usgs":true,"family":"Dawson","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":648137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Michael L.","contributorId":7219,"corporation":false,"usgs":false,"family":"Jones","given":"Michael L.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":648138,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176271,"text":"70176271 - 2016 - Assessing range-wide habitat suitability for the Lesser Prairie-Chicken","interactions":[],"lastModifiedDate":"2016-09-07T10:31:58","indexId":"70176271","displayToPublicDate":"2016-09-07T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Assessing range-wide habitat suitability for the Lesser Prairie-Chicken","docAbstract":"Population declines of many wildlife species have been linked to habitat loss incurred through land-use change. Incorporation of conservation planning into development planning may mitigate these impacts. The threatened Lesser Prairie-Chicken (Tympanuchus pallidicinctus) is experiencing loss of native habitat and high levels of energy development across its multijurisdictional range. Our goal was to explore relationships of the species occurrence with landscape characteristics and anthropogenic effects influencing its distribution through evaluation of habitat suitability associated with one particular habitat usage, lekking. Lekking has been relatively well-surveyed, though not consistently, in all jurisdictions. All five states in which Lesser Prairie-Chickens occur cooperated in development of a Maxent habitat suitability model. We created two models, one with state as a factor and one without state. When state was included it was the most important predictor, followed by percent of land cover consisting of known or suspected used vegetation classes within a 5000 m area around a lek. Without state, land cover was the most important predictor of relative habitat suitability for leks. Among the anthropogenic predictors, landscape condition, a measure of human impact integrated across several factors, was most important, ranking third in importance without state. These results quantify the relative suitability of the landscape within the current occupied range of Lesser Prairie-Chickens. These models, combined with other landscape information, form the basis of a habitat assessment tool that can be used to guide siting of development projects and targeting of areas for conservation.
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To mitigate this risk, various tools such as preshipment health certificates, quarantines, screening for specific disease agents and outright bans have been implemented. However, such measures only target known infectious agents and their hosts and may fail to prevent translocation of even well-recognized pathogens if they are carried by novel host species. In a recent example, we screened an imported shipment of Chinese firebelly newts (Cynops orientalis) for Batrachochytrium salamandrivorans, an emergent fungal pathogen of salamanders. All animals tested negative for the fungus. However, a virus was cultured from internal organs from 7 of the 11 individual dead salamanders and from two pools of tissues from four additional dead animals. Sequencing of a portion of the glycoprotein gene from all viral isolates indicated 100% identity and that they were most closely related to spring viraemia of carp virus (SVCV). Subsequently, SVCV-specific PCR testing indicated the presence of virus in internal organs from each of the four animals previously pooled, and whole-genome sequencing of one of the viral isolates confirmed genomic arrangement characteristic of SVCV. SVCV is a rhabdovirus pathogen of cyprinid fish that is listed as notifiable to the Office International des Epizooties. This discovery reveals a novel route for potential spillover of this economically important pathogen as rhabdovirus has not previously been documented in amphibians.
","language":"English","publisher":"Nature","doi":"10.1038/emi.2016.94","usgsCitation":"Ip, S., Lorch, J.M., and Blehert, D.S., 2016, Detection of spring viraemia of carp virus in imported amphibians reveals an unanticipated foreign animal disease threat: Emerging Microbes & Infections, v. 5, e97: 7 p., https://doi.org/10.1038/emi.2016.94.","productDescription":"e97: 7 p.","ipdsId":"IP-072670","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":462089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/emi.2016.94","text":"Publisher Index Page"},{"id":328297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-25","publicationStatus":"PW","scienceBaseUri":"57d12c1de4b0571647cec210","contributors":{"authors":[{"text":"Ip, S. 0000-0003-4844-7533 hip@usgs.gov","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":727,"corporation":false,"usgs":true,"family":"Ip","given":"S.","email":"hip@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":648182,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":648184,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":140397,"corporation":false,"usgs":true,"family":"Blehert","given":"David","email":"dblehert@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":648186,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209683,"text":"70209683 - 2016 - Acquisition of a unique onshore/offshore geophysical and geochemical dataset in the Northern Malawi (Nyasa) Rift","interactions":[],"lastModifiedDate":"2020-04-21T15:56:34.816136","indexId":"70209683","displayToPublicDate":"2016-09-07T10:02:04","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Acquisition of a unique onshore/offshore geophysical and geochemical dataset in the Northern Malawi (Nyasa) Rift","docAbstract":"The Study of Extension and maGmatism in Malawi aNd Tanzania (SEGMeNT) project acquired a comprehensive suite of geophysical and geochemical datasets across the northern Malawi (Nyasa) rift in the East Africa rift system. Onshore/offshore active and passive seismic data, long‐period and wideband magnetotelluric data, continuous Global Positioning System data, and geochemical samples were acquired between 2012 and 2016. This combination of data is intended to elucidate the sedimentary, crustal, and upper‐mantle architecture of the rift, patterns of active deformation, and the origin and age of rift‐related magmatism. A unique component of our program was the acquisition of seismic data in Lake Malawi, including seismic reflection, onshore/offshore wide‐angle seismic reflection/refraction, and broadband seismic data from lake‐bottom seismometers, a towed streamer, and a large towed air‐gun source.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160112","collaboration":"","usgsCitation":"Shillington, D.J., Gaherty, J., Ebinger, C.J., Scholz, C., Selway, K., Nyblade, A.A., Bedrosian, P.A., Class, C., Nooner, S., Pritchard, M.E., Elliott, J.L., Chindandali, P.R., Mbogoni, G., Ferdinand, R.W., Boniface, N., Manya, S., Kamihanda, G., Saria, E., Mulibo, G., Salima, J., Mruma, A., Kalindekafe, L., Accardo, N.J., Daud, N., Kachingwe, M., Mesko, G.T., McCartney, T., Maquay, M., O’Donnell, J.P., Tepp, G., Mtelela, K., Trinhammer, P., Wood, D., Aaron, E., Gibaud, M., Rapa, M., Pfeifer, C., Mphepo, F., Gondwe, D., Arroyo, G., and Eddy, C., 2016, Acquisition of a unique onshore/offshore geophysical and geochemical dataset in the Northern Malawi (Nyasa) Rift: Seismological Research Letters, v. 87, no. 6, p. 1406-1416, https://doi.org/10.1785/0220160112.","productDescription":"11 p.","startPage":"1406","endPage":"1416","ipdsId":"IP-078426","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":374157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Malawi, Tanzania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 32.93701171875,\n -12.297068292853805\n ],\n [\n 35.04638671874999,\n -12.297068292853805\n ],\n [\n 35.04638671874999,\n -8.298470297067356\n ],\n [\n 32.93701171875,\n -8.298470297067356\n ],\n [\n 32.93701171875,\n -12.297068292853805\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"87","issue":"6","noUsgsAuthors":false,"publicationDate":"2016-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Shillington, Donna J.","contributorId":210202,"corporation":false,"usgs":false,"family":"Shillington","given":"Donna","email":"","middleInitial":"J.","affiliations":[{"id":38091,"text":"Lamont Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":787555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaherty, J. 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Since 1988, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, during October 2011 through September 2012 (water year 2012) and October 2012 through September 2013 (water year 2013). Major findings for this period include:
Director South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
The U.S. Geological Survey began collecting streamflow data, in cooperation with the North Dakota State Water Commission, on the Souris River in and near Minot, North Dakota, in April 1903. The gage was started up to better understand the water resources available in North Dakota. Currently (2016), water availability is still important as well as the flood monitoring and forecasting that has become an important component of this gage. Gage-height and streamflow data for the Souris River in and near Minot have been collected at five different streamgage locations during the years. This fact sheet describes the history of streamgaging (locations, gage-height data, and streamflow data) and flooding on the Souris River in and near Minot since 1903.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163061","usgsCitation":"Baker, K.K., and Robinson, S.M., History of U.S. Geological Survey streamgaging on the Souris River in and near Minot, North Dakota, 1903–2016: U.S. Geological Survey Fact Sheet 2016–3061, 6 p., https://dx.doi.org/10.3133/fs20163061.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","ipdsId":"IP-076990","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":328296,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3061/fs20163061.pdf","text":"Fact Sheet","size":"7.85 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3061"},{"id":328295,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3061/coverthb.jpg"}],"country":"United States","state":"North Dakota","city":"Minot","otherGeospatial":"Souris River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.42475128173828,\n 48.16104745279183\n ],\n [\n -101.42475128173828,\n 48.27908037971334\n ],\n [\n -101.17755889892578,\n 48.27908037971334\n ],\n [\n -101.17755889892578,\n 48.16104745279183\n ],\n [\n -101.42475128173828,\n 48.16104745279183\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, North Dakota Water Science Center
U.S. Geological Survey
821 E Interstate Ave
Bismarck, ND 58503
Michigan faces many challenges related to water resources, including flooding, drought, water-quality degradation and impairment, varying water availability, watershed-management issues, stormwater management, aquatic-ecosystem impairment, and invasive species. Michigan’s water resources include approximately 36,000 miles of streams, over 11,000 inland lakes, 3,000 miles of shoreline along the Great Lakes (MDEQ, 2016), and groundwater aquifers throughout the State.
The U.S. Geological Survey (USGS) works in cooperation with local, State, and other Federal agencies, as well as tribes and universities, to provide scientific information used to manage the water resources of Michigan. To effectively assess water resources, the USGS uses standardized methods to operate streamgages, water-quality stations, and groundwater stations. The USGS also monitors water quality in lakes and reservoirs, makes periodic measurements along rivers and streams, and maintains all monitoring data in a national, quality-assured, hydrologic database.
The USGS in Michigan investigates the occurrence, distribution, quantity, movement, and chemical and biological quality of surface water and groundwater statewide. Water-resource monitoring and scientific investigations are conducted statewide by USGS hydrologists, hydrologic technicians, biologists, and microbiologists who have expertise in data collection as well as various scientific specialties. A support staff consisting of computer-operations and administrative personnel provides the USGS the functionality to move science forward. Funding for USGS activities in Michigan comes from local and State agencies, other Federal agencies, direct Federal appropriations, and through the USGS Cooperative Matching Funds, which allows the USGS to partially match funding provided by local and State partners.
This fact sheet provides an overview of the USGS current (2016) capabilities to monitor and study Michigan’s vast water resources. More information regarding projects by the Michigan Water Science Center (MI WSC) is available at http://mi.water.usgs.gov/.
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\"}}]}","contact":"Director, Michigan-Ohio Water Science Center
U.S. Geological Survey
6520 Mercantile Way
Suite 5
Lansing, MI 48911
http://mi.water.usgs.gov/
Or
Director, Ohio Water Science Center
U.S. Geological Survey
6480 Doubletree Ave
Columbus, OH 43229
http://oh.water.usgs.gov/
Indigenous Arctic and Subarctic communities currently are facing a myriad of social and environmental changes. In response to these changes, studies concerning indigenous knowledge (IK) and climate change vulnerability, resiliency, and adaptation have increased dramatically in recent years. Risks to lives and livelihoods are often the focus of adaptation research; however, the cultural dimensions of climate change are equally important because cultural dimensions inform perceptions of risk. Furthermore, many Arctic and Subarctic IK climate change studies document observations of change and knowledge of the elders and older generations in a community, but few include the perspectives of the younger population. These observations by elders and older generations form a historical baseline record of weather and climate observations in these regions. However, many indigenous Arctic and Subarctic communities are composed of primarily younger residents. We focused on the differences in the cultural dimensions of climate change found between young adults and elders. We outlined the findings from interviews conducted in four indigenous communities in Subarctic Alaska. The findings revealed that (1) intergenerational observations of change were common among interview participants in all four communities, (2) older generations observed more overall change than younger generations interviewed by us, and (3) how change was perceived varied between generations. We defined “observations” as the specific examples of environmental and weather change that were described, whereas “perceptions” referred to the manner in which these observations of change were understood and contextualized by the interview participants. Understanding the differences in generational observations and perceptions of change are key issues in the development of climate change adaptation strategies.
","language":"English","publisher":"Published at Carleton University by the Resilience Alliance","doi":"10.5751/ES-08463-210328","usgsCitation":"Herman-Mercer, N.M., Matkin, E., Laituri, M.J., Toohey, R.C., Massey, M., Elder, K., Schuster, P.F., and Mutter, E.A., 2016, Changing times, changing stories: Generational differences in climate change perspectives from four remote indigenous communities in Subarctic Alaska: Ecology and Society, v. 21, no. 3, Art. 28; 19 p., https://doi.org/10.5751/ES-08463-210328.","productDescription":"Art. 28; 19 p.","ipdsId":"IP-064992","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470589,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-08463-210328","text":"Publisher Index Page"},{"id":328309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Chevak, Kotlik, Pilot Station, St. Mary’s","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.4208984375,\n 61.04233185542855\n ],\n [\n -166.387939453125,\n 63.44068640036803\n ],\n [\n -159.840087890625,\n 63.41611461038977\n ],\n [\n -159.78515624999997,\n 61.04233185542855\n ],\n [\n -166.4208984375,\n 61.04233185542855\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d13a38e4b0571647cf8d9b","contributors":{"authors":[{"text":"Herman-Mercer, Nicole M. 0000-0001-5933-4978 nhmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-5933-4978","contributorId":3927,"corporation":false,"usgs":true,"family":"Herman-Mercer","given":"Nicole","email":"nhmercer@usgs.gov","middleInitial":"M.","affiliations":[{"id":438,"text":"National Research Program - 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For instance, whether moisture availability gradually decreased, remained relatively constant, or increased during the last 7000 years remains a matter of debate. To assess Holocene limnology, hydrology and moisture dynamics, the coastal lakes Lago Preola and Gorgo Basso, located in southwestern Sicily, were investigated through several stratigraphic analyses of ostracodes, including multivariate analyses of assemblages, transfer functions of salinity, and biochemical analyses of valves (Sr/Ca, δ18O and δ13C). During the early Holocene, the Gorgo Basso and Lago Preola ostracode records are similar. After an initial period of moderate salinity (1690–6100 mg/l from ca. 10,000–8190 cal yr BP), syndepositional or diagenetic dissolution of ostracode valves suggests that salinity declined to <250 mg/L from ca. 8190 to 7000 cal yr BP at both sites. After ca. 6250 cal yr BP, the ostracode records are strikingly different. Lago Preola became much more saline, with paleosalinity values that ranged from 2270 to about 24,420 mg/L. We suggest that Lago Preola's change from a freshwater to mesosaline lake at about 6250 cal yr BP was related to sea level rise and resulting intrusion of seawater-influenced groundwater. In contrast, Gorgo Basso remained a freshwater lake. The salinity of Gorgo Basso declined somewhat after 6250 cal yr BP, in comparison to the early Holocene, ranging from about 550 to 1680 mg/L. Cypria ophtalmica, a species capable of rapid swimming and flourishing in waters with low dissolved oxygen levels, became dominant at approximately the time when Greek civilization took root in Sicily (2600 cal yr BP), and it completely dominates the record during Roman occupation (roughly 2100 to 1700 cal yr BP). These freshwater conditions at Gorgo Basso suggest high effective moisture when evergreen olive-oak forests collapsed in response to increased Greco-Roman land use and fire. Ostracode valve geochemistry (Sr/Ca, δ18O) suggests significant changes in early vs. late Holocene hydrochemistry, either as changes in salinity or in the seasonality of precipitation. Harmonizing the autecological and geochemical data from Gorgo Basso suggests the latter was more likely, with relatively more late Holocene precipitation falling during the spring, summer, and fall, than winter compared to the early Holocene. Our ostracode-inferred paleosalinity data indicate that moisture availability did not decline during the late Holocene in the central Mediterranean region. Instead, moisture availability was lowest during the early Holocene, and most abundant during the late Holocene.
","language":"English","publisher":"Pergamon Press","doi":"10.1016/j.quascirev.2016.08.013","usgsCitation":"Curry, B., Henne, P., Mezquita-Joanes, F., Marrone, F., Pieri, V., La Mantia, T., Calo, C., and Tinner, W., 2016, Holocene paleoclimate inferred from salinity histories of adjacent lakes in southwestern Sicily (Italy): Quaternary Science Reviews, v. 150, p. 67-83, https://doi.org/10.1016/j.quascirev.2016.08.013.","productDescription":"17 p.","startPage":"67","endPage":"83","ipdsId":"IP-070996","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":328313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","state":"Trapani Province","otherGeospatial":"Riserva Naturale Integrale Lago Preola e Gorghi Tondi, Sicily","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 12.6,\n 37.6\n ],\n [\n 12.6,\n 37.64\n ],\n [\n 12.66,\n 37.64\n ],\n [\n 12.66,\n 37.6\n ],\n [\n 12.6,\n 37.6\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d13a3de4b0571647cf8ddc","contributors":{"authors":[{"text":"Curry, B Brandon","contributorId":174032,"corporation":false,"usgs":false,"family":"Curry","given":"B Brandon","affiliations":[{"id":27342,"text":"Illinois State Geological Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, IL, USA","active":true,"usgs":false}],"preferred":false,"id":647000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":646999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mezquita-Joanes, Francesc","contributorId":174033,"corporation":false,"usgs":false,"family":"Mezquita-Joanes","given":"Francesc","email":"","affiliations":[{"id":27343,"text":"Department of Microbiology and Ecology/ICBiBE, University of Valencia, Spain","active":true,"usgs":false}],"preferred":false,"id":647001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marrone, Federico","contributorId":174034,"corporation":false,"usgs":false,"family":"Marrone","given":"Federico","email":"","affiliations":[{"id":27344,"text":"Universita' degli Studi di Palermo, Sicily, Italy","active":true,"usgs":false}],"preferred":false,"id":647002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pieri, Valentina","contributorId":174035,"corporation":false,"usgs":false,"family":"Pieri","given":"Valentina","email":"","affiliations":[{"id":27345,"text":"Royal Belgian Institure of Natural Sciences, Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":647005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"La Mantia, Tommaso","contributorId":169175,"corporation":false,"usgs":false,"family":"La Mantia","given":"Tommaso","email":"","affiliations":[{"id":25431,"text":"University of Palermo","active":true,"usgs":false}],"preferred":false,"id":647003,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Calo, Camilla","contributorId":174036,"corporation":false,"usgs":false,"family":"Calo","given":"Camilla","email":"","affiliations":[{"id":27346,"text":"Institute of Plant Sciences & Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":647006,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tinner, Willy 0000-0001-7352-0144","orcid":"https://orcid.org/0000-0001-7352-0144","contributorId":169167,"corporation":false,"usgs":false,"family":"Tinner","given":"Willy","email":"","affiliations":[{"id":25430,"text":"University of Bern","active":true,"usgs":false}],"preferred":false,"id":647004,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70199782,"text":"70199782 - 2016 - Metformin and other pharmaceuticals widespread in wadeable streams of the southeastern United States","interactions":[],"lastModifiedDate":"2018-09-27T17:03:47","indexId":"70199782","displayToPublicDate":"2016-09-04T16:45:55","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5022,"text":"Environmental Science & Technology Letters","onlineIssn":"2328-8930","active":true,"publicationSubtype":{"id":10}},"title":"Metformin and other pharmaceuticals widespread in wadeable streams of the southeastern United States","docAbstract":"Pharmaceutical contaminants are growing aquatic-health concerns and largely attributed to wastewater treatment facility (WWTF) discharges. Five biweekly water samples from 59 small Piedmont (United States) streams were analyzed for 108 pharmaceuticals and degradates using high-performance liquid chromatography and tandem mass spectrometry. The antidiabetic metformin was detected in 89% of samples and at 97% of sites. At least one pharmaceutical was detected at every site (median of 6, maximum of 45), and several were detected at ≥10% of sites at concentrations reported to affect multiple aquatic end points. Maximal cumulative (all detected compounds) concentrations per site ranged from 17 to 16000 ng L–1. Watershed urbanization, water table depth, soil thickness, and WWTF metrics correlated significantly with in-stream pharmaceutical contamination. Comparable pharmaceutical concentrations and detections at sites with and without permitted wastewater discharges demonstrate the importance of non-WWTF sources and the need for broad-scale mitigation. The results highlight a fundamental biochemical link between global human-health crises like diabetes and aquatic ecosystem health.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.estlett.6b00170","usgsCitation":"Bradley, P.M., Journey, C.A., Button, D.T., Carlisle, D.M., Clark, J.M., Mahler, B., Nakagaki, N., Qi, S.L., Waite, I.R., and Van Metre, P., 2016, Metformin and other pharmaceuticals widespread in wadeable streams of the southeastern United States: Environmental Science & Technology Letters, v. 3, no. 6, p. 243-249, https://doi.org/10.1021/acs.estlett.6b00170.","productDescription":"7 p.","startPage":"243","endPage":"249","ipdsId":"IP-074282","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":462091,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.estlett.6b00170","text":"Publisher Index Page"},{"id":357870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.3552303599749,\n 29.6305\n ],\n [\n -76.0284,\n 29.6305\n ],\n [\n -76.0284,\n 38.4013255312409\n ],\n [\n -88.3552303599749,\n 38.4013255312409\n ],\n [\n -88.3552303599749,\n 29.6305\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"6","noUsgsAuthors":false,"publicationDate":"2016-05-24","publicationStatus":"PW","scienceBaseUri":"5bc032a7e4b0fc368eb53a69","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":189681,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Button, Daniel T. 0000-0002-7479-884X dtbutton@usgs.gov","orcid":"https://orcid.org/0000-0002-7479-884X","contributorId":2084,"corporation":false,"usgs":true,"family":"Button","given":"Daniel","email":"dtbutton@usgs.gov","middleInitial":"T.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37277,"text":"WMA - 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2016 - A python framework for environmental model uncertainty analysis","interactions":[],"lastModifiedDate":"2016-11-30T11:44:14","indexId":"70178585","displayToPublicDate":"2016-09-03T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A python framework for environmental model uncertainty analysis","docAbstract":"We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses. The FOSM-based analyses can also be completed prior to parameter estimation to help inform important modeling decisions, such as parameterization and objective function formulation. Complete workflows for several types of FOSM-based and non-linear analyses are documented in example notebooks implemented using Jupyter that are available in the online pyEMU repository. Example workflows include basic parameter and forecast analyses, data worth analyses, and error-variance analyses, as well as usage of parameter ensemble generation and management capabilities. These workflows document the necessary steps and provides insights into the results, with the goal of educating users not only in how to apply pyEMU, but also in the underlying theory of applied uncertainty quantification.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2016.08.017","usgsCitation":"White, J.T., Fienen, M., and Doherty, J.E., 2016, A python framework for environmental model uncertainty analysis: Environmental Modelling and Software, v. 85, p. 217-228, https://doi.org/10.1016/j.envsoft.2016.08.017.","productDescription":"12 p.","startPage":"217","endPage":"228","ipdsId":"IP-077464","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":331312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"85","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"583ff34ee4b04fc80e437264","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":177065,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":654467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, John E.","contributorId":8817,"corporation":false,"usgs":false,"family":"Doherty","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":7046,"text":"Watermark Numerical Computing","active":true,"usgs":false}],"preferred":false,"id":654468,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176247,"text":"70176247 - 2016 - Sex differences in contaminant concentrations of fish: a synthesis","interactions":[],"lastModifiedDate":"2018-08-08T10:18:06","indexId":"70176247","displayToPublicDate":"2016-09-03T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5200,"text":"Biology of Sex Differences","active":true,"publicationSubtype":{"id":10}},"title":"Sex differences in contaminant concentrations of fish: a synthesis","docAbstract":"Comparison of whole-fish polychlorinated biphenyl (PCB) and total mercury (Hg) concentrations in mature males with those in mature females may provide insights into sex differences in behavior, metabolism, and other physiological processes. In eight species of fish, we observed that males exceeded females in whole-fish PCB concentration by 17 to 43%. Based on results from hypothesis testing, we concluded that these sex differences were most likely primarily driven by a higher rate of energy expenditure, stemming from higher resting metabolic rate (or standard metabolic rate (SMR)) and higher swimming activity, in males compared with females. A higher rate of energy expenditure led to a higher rate of food consumption, which, in turn, resulted in a higher rate of PCB accumulation. For two fish species, the growth dilution effect also made a substantial contribution to the sex difference in PCB concentrations, although the higher energy expenditure rate for males was still the primary driver. Hg concentration data were available for five of the eight species. For four of these five species, the ratio of PCB concentration in males to PCB concentration in females was substantially greater than the ratio of Hg concentration in males to Hg concentration in females. In sea lamprey (Petromyzon marinus), a very primitive fish, the two ratios were nearly identical. The most plausible explanation for this pattern was that certain androgens, such as testosterone and 11-ketotestosterone, enhanced Hg-elimination rate in males. In contrast, long-term elimination of PCBs is negligible for both sexes. According to this explanation, males ingest Hg at a higher rate than females, but also eliminate Hg at a higher rate than females, in fish species other than sea lamprey. Male sea lamprey do not possess either of the above-specified androgens. These apparent sex differences in SMRs, activities, and Hg-elimination rates in teleost fishes may also apply, to some degree, to higher vertebrates including humans. Our synthesis findings will be useful in: (1) developing sex-specific bioenergetics models for fish, (2) developing sex-specific risk assessment models for exposure of humans and wildlife to contaminants, and (3) refining Hg mass balance models for fish and higher vertebrates.","language":"English","publisher":"BioMed Central","doi":"10.1186/s13293-016-0090-x","usgsCitation":"Madenjian, C.P., Rediske, R.R., Krabbenhoft, D.P., Stapanian, M.A., Chernyak, S.M., and O'Keefe, J., 2016, Sex differences in contaminant concentrations of fish: a synthesis: Biology of Sex Differences, v. 7, p. 1-16, https://doi.org/10.1186/s13293-016-0090-x.","productDescription":"Article 42; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-076759","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":470590,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13293-016-0090-x","text":"Publisher Index Page"},{"id":328230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-02","publicationStatus":"PW","scienceBaseUri":"57cbe61be4b0f2f0cec372ad","contributors":{"authors":[{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":648066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rediske, Richard R.","contributorId":79053,"corporation":false,"usgs":true,"family":"Rediske","given":"Richard","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":648067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":648069,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chernyak, Sergei M.","contributorId":98668,"corporation":false,"usgs":true,"family":"Chernyak","given":"Sergei","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":648070,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O'Keefe, James P.","contributorId":99499,"corporation":false,"usgs":true,"family":"O'Keefe","given":"James P.","affiliations":[],"preferred":false,"id":648071,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70175719,"text":"ofr20161119 - 2016 - Shallow geology, sea-floor texture, and physiographic zones of Vineyard and western Nantucket Sounds, Massachusetts","interactions":[],"lastModifiedDate":"2017-11-10T10:18:01","indexId":"ofr20161119","displayToPublicDate":"2016-09-02T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1119","title":"Shallow geology, sea-floor texture, and physiographic zones of Vineyard and western Nantucket Sounds, Massachusetts","docAbstract":"Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Vineyard and western Nantucket Sounds, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs/video, and surficial sediment samples collected within the 494-square-kilometer study area. Interpretations of seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a result of a collaborative effort between the U.S. Geological Survey and the Massachusetts Office of Coastal Zone Management to characterize the surface and subsurface geologic framework offshore of Massachusetts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161119","collaboration":"Prepared in cooperation with the Massachusetts Office of Coastal Zone Management","usgsCitation":"Baldwin, W.E., Foster, D.S., Pendleton, E.A., Barnhardt, W.A., Schwab, W.C., Andrews, B.D., and Ackerman, S.D., 2016, Shallow geology, sea-floor texture, and physiographic zones of Vineyard and western Nantucket Sounds, Massachusetts: U.S. Geological Survey Open-File Report 2016–1119, https://dx.doi.org/10.3133/ofr20161119.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072016","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328161,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1119/coverthb.jpg"},{"id":326826,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2016/1119/index.html","text":"Report HTML"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.1,\n 41.25\n ],\n [\n -71.1,\n 41.6\n ],\n [\n -70.4,\n 41.6\n ],\n [\n -70.4,\n 41.25\n ],\n [\n -71.1,\n 41.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
http://woodshole.er.usgs.gov/
A Presidential disaster was declared in northwestern Massachusetts, following flooding from tropical storm Irene on August 28, 2011. During the storm, 3 to 10 inches of rain fell on soils that were susceptible to flash flooding because of wet antecedent conditions. The gage height at one U.S. Geological Survey streamgage rose nearly 20 feet in less than 4 hours because of the combination of saturated soils and intense rainfall. On August 28, 2011, in the Deerfield and Hoosic River Basins in northwestern Massachusetts, new peaks of record were set at six of eight U.S. Geological Survey long-term streamgages with 46 to 100 years of record. Additionally, high-water marks were surveyed and indirect measurements of peak discharge were calculated at two discontinued streamgages in the Deerfield and Hoosic River Basins with 24 and 61 years of record, respectively. This data resulted in new historic peaks of record at the two discontinued streamgages from tropical storm Irene.
\nPeak flows that resulted from tropical storm Irene (August 28, 2011) were determined at the U.S. Geological Survey streamgages by using stage-discharge rating curves and indirect computation methods. For six streamgages, indirect computation methods were used to compute the peak flows. Peak flows from tropical storm Irene had annual exceedance probabilities (AEPs) that ranged from 5.4 percent to less than 0.2 percent at 10 streamgages in northwestern Massachusetts.
\nDischarges calculated for select AEPs as a part of this study were compared with discharges published for the same AEPs in the effective Federal Emergency Management Agency flood insurance studies (FISs) for communities in the study area. Discharges estimated for the 10-, 2-, 1-, and 0.2-percent AEPs at two streamgages on the main stem of the Deerfield River ranged from about 3 percent lower to 14 percent higher than discharges in the FISs. AEP discharges calculated for two streamgages on tributaries to the Deerfield River were 27 to 89 percent higher than the FISs. For the four streamgages in the Hoosic River Basin, the 10-, 2-, 1-, and 0.2-percent AEP discharges calculated ranged from about 33 percent lower to 5 percent higher than the FISs.
\nThe simulated 1-percent AEP discharge water-surface elevations (nonregulatory) from recent (2015–16) hydraulic models for river reaches in the study area, which include the Deerfield, Green, and North Rivers in the Deerfield River Basin and the Hoosic River in the Hoosic River Basin, were compared with water-surface profiles in the FISs. The water-surface elevation comparisons were generally done downstream and upstream from bridges, dams, and major tributaries. The simulated 1-percent AEP discharge water-surface elevations of the recent hydraulic studies averaged 2.2, 2.3, 0.3, and 0.7 ft higher than water-surface elevations in the FISs for the Deerfield, Green, North, and Hoosic Rivers, respectively. The differences in water-surface elevations between the recent (2015–16) hydraulic studies and the FISs likely are because of (1) improved land elevation data from light detection and ranging (lidar) data collected in 2012, (2) detailed surveying of hydraulic structures and cross sections throughout the river reaches in 2012–13 (reflecting structure and cross section changes during the last 30–35 years), (3) updated hydrology analyses (30–35 water years of additional peak flow data at streamgages), and (4) high-water marks from the 2011 tropical storm Irene flood being used for model calibration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165027","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Bent, G.C., Olson, S.A., and Massey, A.J., 2016, Tropical storm Irene flood of August 2011 in northwestern Massachusetts: U.S. Geological Survey Scientific Investigations Report 2016–5027, 28 p., https://dx.doi.org/10.3133/sir20165027.","productDescription":"v, 28 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067697","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":327911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5027/coverthb.jpg"},{"id":327912,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5027/sir20165027.pdf","text":"Report","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5027"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.61688232421875,\n 42.731378652044185\n ],\n [\n -72.60452270507812,\n 42.718263627309774\n ],\n [\n -72.58804321289061,\n 42.693539313660004\n ],\n [\n -72.55989074707031,\n 42.653656930109726\n ],\n [\n -72.55302429199219,\n 42.64153569439977\n ],\n [\n -72.5592041015625,\n 42.628906895633456\n ],\n [\n -72.55851745605469,\n 42.61122227199062\n ],\n [\n -72.56813049316406,\n 42.603641609996586\n ],\n [\n -72.57637023925781,\n 42.59606002548659\n ],\n [\n -72.58049011230469,\n 42.59454359788448\n ],\n [\n -72.57980346679686,\n 42.58493869951935\n ],\n [\n -72.57568359375,\n 42.578871685346364\n ],\n [\n -72.57431030273438,\n 42.560161341916064\n ],\n [\n -72.58323669433594,\n 42.54296310520116\n ],\n [\n -72.59078979492188,\n 42.52677220056902\n ],\n [\n -72.60246276855469,\n 42.50804623455747\n ],\n [\n -72.62718200683594,\n 42.50500906265383\n ],\n [\n -72.652587890625,\n 42.50956476517422\n ],\n [\n -72.6800537109375,\n 42.51766297209017\n ],\n [\n -72.69515991210938,\n 42.52879629320373\n ],\n [\n -72.70683288574219,\n 42.51766297209017\n ],\n [\n -72.71781921386719,\n 42.50754004948742\n ],\n [\n -72.74116516113281,\n 42.49387150323448\n ],\n [\n -72.78923034667969,\n 42.47817430242153\n ],\n [\n -72.80845642089844,\n 42.46753847696729\n ],\n [\n -72.82699584960938,\n 42.50500906265383\n ],\n [\n -72.84347534179688,\n 42.52069952914966\n ],\n [\n -72.85308837890624,\n 42.53638605645048\n ],\n [\n -72.89840698242188,\n 42.55055114674488\n ],\n [\n -72.90252685546875,\n 42.54448078729858\n ],\n [\n -72.90390014648438,\n 42.53739795519656\n ],\n [\n -72.94166564941406,\n 42.53638605645048\n ],\n [\n -72.94647216796874,\n 42.525760129656845\n ],\n [\n -72.96363830566406,\n 42.51968735985934\n ],\n [\n -72.97531127929688,\n 42.53588010092859\n ],\n [\n -72.9876708984375,\n 42.54852775918642\n ],\n [\n -73.00277709960938,\n 42.55560932868032\n ],\n [\n -73.01239013671875,\n 42.562184352321886\n ],\n [\n -73.02200317382812,\n 42.57027573801005\n ],\n [\n -73.02818298339844,\n 42.58645536081647\n ],\n [\n -73.04054260253906,\n 42.601619944327965\n ],\n [\n -73.04672241210938,\n 42.605157816197334\n ],\n [\n -73.06938171386719,\n 42.58696090638245\n ],\n [\n -73.06800842285156,\n 42.5798828953732\n ],\n [\n -73.06869506835938,\n 42.560161341916064\n ],\n [\n -73.05770874023438,\n 42.54144538620976\n ],\n [\n -73.05770874023438,\n 42.53486817758702\n ],\n [\n -73.07212829589844,\n 42.52677220056902\n ],\n [\n -73.10508728027344,\n 42.51158941527828\n ],\n [\n -73.11126708984375,\n 42.49690921618136\n ],\n [\n -73.14628601074219,\n 42.50500906265383\n ],\n [\n -73.15864562988281,\n 42.49944053092116\n ],\n [\n -73.16963195800781,\n 42.489820989777066\n ],\n [\n -73.18954467773438,\n 42.48830197960227\n ],\n [\n -73.21563720703125,\n 42.49032731830467\n ],\n [\n -73.22181701660156,\n 42.50905859240087\n ],\n [\n -73.22181701660156,\n 42.52829027619378\n ],\n [\n -73.21769714355469,\n 42.54448078729858\n ],\n [\n -73.21151733398436,\n 42.553586105099654\n ],\n [\n -73.20533752441406,\n 42.56370156708076\n ],\n [\n -73.19366455078125,\n 42.587971985214814\n ],\n [\n -73.201904296875,\n 42.58594981115061\n ],\n [\n -73.23211669921875,\n 42.58493869951935\n ],\n [\n -73.24928283691406,\n 42.5995982130586\n ],\n [\n -73.25889587402344,\n 42.5995982130586\n ],\n [\n -73.26301574707031,\n 42.58746644784856\n ],\n [\n -73.32069396972655,\n 42.59252163701558\n ],\n [\n -73.26507568359375,\n 42.74600367786244\n ],\n [\n -72.61688232421875,\n 42.731378652044185\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
The U.S. Geological Survey developed flood elevations in cooperation with the Federal Emergency Management Agency for a 14.3-mile reach of the Green River in Colrain, Leyden, and Greenfield, Massachusetts, to assist landowners and emergency management workers to prepare for and recover from floods. The river reach extends from the U.S. Geological Survey Green River near Colrain, MA (01170100) streamgage downstream to the confluence with the Deerfield River. A series of seven digital flood inundation maps were developed for the upper 4.4 miles of the river reach downstream from the stream. Flood discharges corresponding to the 50-, 10-, 1-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows and the flood flows associated with the stages of 10.2, 12.4, and 14.4 feet (ft) at the Green River streamgage were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations and to place the Tropical Storm Irene flood of August 28, 2011 (stage 13.97 ft), into historical context. The hydraulic model was calibrated by using the current (2015) stage-discharge relation at the U.S. Geological Survey Green River near Colrain, MA (01170100) streamgage and from documented high-water marks from the Tropical Storm Irene flood, which had a flow higher than a 0.2-percent annual exceedance probability flood discharge.
The hydraulic model was used to compute water-surface profiles for flood stages referenced to the streamgage and ranging from the 50-percent annual exceedance probability (bankfull flow) at 7.6 ft (439.8 ft above the North American Vertical Datum of 1988 [NAVD 88]) to 14.4 ft (446.7 ft NAVD 88), which exceeds the maximum recorded water level of 13.97 ft (Tropical Storm Irene) at the streamgage. The mapped stages of 7.6 to 14.4 ft were selected to match the stages for bankfull; the 50-, 10-, 1-, and 0.2-percent annual exceedance probabilities; incremental stages of 10.2 and 12.4 ft; and the maximum stage of the stage-discharge rating curve. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 0.5-ft vertical accuracy to create a set of flood-inundation maps.
The availability of the flood-inundation maps, combined with information regarding near real-time stage from U.S. Geological Survey Green River near Colrain, MA (01170100) streamgage, can provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, and postflood recovery efforts. The flood-inundation maps are nonregulatory but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165107","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Flynn, R.H., Bent, G.C., and Lombard, P.J., 2016, Flood-inundation maps for the Green River in Colrain, Leyden, and Greenfield, Massachusetts, from U.S. Geological Survey streamgage 01170100 Green River near Colrain to the confluence with the Deerfield River (ver. 1.1, November 2016): U.S. Geological Survey Scientific Investigations Report 2016–5107, 18 p., appendixes, https://doi.org/10.3133/sir20165107.","productDescription":"Report: vi, 18 p.; Appendix 2; Application Site; Metadata; Spatial Data","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-062774","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":331081,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5107/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016-5107"},{"id":331083,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2016/5107/sir20165107_flood-inundation_gis.zip","text":"Flood Inundation GIS","size":"4.59 MB"},{"id":327919,"rank":6,"type":{"id":4,"text":"Application Site"},"url":"https://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html","text":"Flood Inundation Mapper ","linkFileType":{"id":5,"text":"html"},"description":"SIR 2016-5107"},{"id":327920,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2016/5107/sir20165107_appendix2_metadata.xml ","text":"Appendix 2 - ","size":"13.6 KB xml","description":"SIR 2016-5107","linkHelpText":"metadata"},{"id":327917,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5107/sir20165107.pdf","text":"Report","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5107"},{"id":327918,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5107/sir20165107_appendix2_gis.zip","text":"Appendix 2 - ","size":"160 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5107 - Spatial Data","linkHelpText":"GIS"},{"id":327916,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5107/coverthb2.jpg"},{"id":331082,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2016/5107/sir20165107_flood-inundation_metadata.xml","text":"Flood Inundation GIS ","size":"26 KB xml","linkHelpText":"metadata"}],"country":"United States","state":"Massachusetts","city":"Colrain, Greenfield, Leyden","otherGeospatial":"Green River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.55,\n 42.55\n ],\n [\n -72.55,\n 42.72\n ],\n [\n -72.7,\n 42.72\n ],\n [\n -72.7,\n 42.55\n ],\n [\n -72.55,\n 42.55\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted September 2, 2016; Version 1.1: November 23, 2016","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
For the final phase of wastewater treatment operations at Joint Base McGuire-Dix-Lakehurst in Burlington County, New Jersey, treated effluent is pumped to 12 infiltration basins on a Land Application Site to recharge the unconfined Kirkwood-Cohansey aquifer system. Two of the 12 infiltration basins are operationally ineffective because discharged effluent fails to percolate and remains ponded on the basin surfaces. A study conducted by the U.S. Geological Survey, in cooperation with the U.S. Department of Defense, investigated the potential hydrogeologic conditions preventing infiltration in these basins by testing the geophysical, lithological, and hydraulic characteristics of the aquifer material underlying the site. Saturated sand, sandy clay, and unsaturated sand were encountered in succession through the upper 4 feet of sediment below land surface at the two ineffective basins. Water levels in auger borings penetrating the clay and underlying dry sand were measured as deeper than water levels in nested auger borings in the saturated sand overlying the clay, which indicates a downward vertical gradient was established after removal of the clay in the deeper borings created a conduit for drainage from the surficial saturated sands. Ground-penetrating radar surveys and additional water levels measured in piezometer wells adjacent to the infiltration basins indicated a lack of connectivity between the ponded basin water and the regional water table, and demonstrated that perched conditions were not present in native formation materials outside the inoperable basins. Therefore, the near-surface low permeability clay is likely preventing infiltration from the basin surface and causes the ineffectiveness of the two basins for wastewater land application operations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165065","collaboration":"Prepared in cooperation with the U.S. Department of Defense","usgsCitation":"Fiore, A.R., 2016, Hydrogeologic barriers to the infiltration of treated wastewater at the Joint Base McGuire-Dix-Lakehurst Land Application Site, Burlington County, New Jersey: U.S. Geological Survey Scientific Investigations Report 2016–5065, 83 p., https://dx.doi.org/10.3133/sir20165065.","productDescription":"viii, 83 p.","numberOfPages":"96","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069659","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":328197,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5065/sir20165065.pdf","text":"Report","size":"7.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5065"},{"id":328196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5065/coverthb.jpg"}],"country":"United States","state":"New Jersey","county":"Burlington County","otherGeospatial":"Joint Base McGuire-Dix-Lakehurst","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.65,\n 40.0125\n ],\n [\n -74.65,\n 39.954167\n ],\n [\n -74.575,\n 39.954167\n ],\n [\n -74.575,\n 40.0125\n ],\n [\n -74.65,\n 40.0125\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
http://nj.usgs.gov/
The vertical avoidance behavior of the tadpole madtom (Noturus gyrinus) exposed to environmentally relevant concentrations of the granular formulation of the lampricide Bayluscide® was evaluated. The lampricide formulation (3.2 percent active ingredient coated on a sand granule) is used to control larval sea lamprey populations in the Great Lakes. The tadpole madtom was chosen as a surrogate to the federally endangered northern madtom (Noturus stigmosus) based on similar life history characteristics and habitat requirements. Vertical avoidance of tadpole madtoms in response to the granular formulation was documented in clear Plexiglas columns (107 centimeters in height, 30.5 centimeters in diameter) for 1 hour after chemical application. Each avoidance trial produced data consisting of the number of tadpole madtoms avoiding the chemical at a given time. Based on the overall data, tadpole madtoms in treated columns were 11.7 times more likely to display avoidance compared to those in untreated controls. Results indicate that it is likely that northern madtoms will be able to detect and avoid Bayluscide® from granular applications if their response is similar to that of the tadpole madtom.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161130","usgsCitation":"Boogaard, M.A., Erickson, R.A., and Hubert, T.D, 2016, Evaluation of avoidance behavior of tadpole madtoms (Noturus gyrinus) as a surrogate for the endangered northern madtom (Noturus stigmosus) in response to granular Bayluscide: U.S. Geological Survey Open-File Report 2016‒1130, 6 p., https://dx.doi.org/10.3133/ofr20161130. ","productDescription":"Report: iv, 6 p. ","startPage":"1","endPage":"6","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-075622","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":438554,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K35RS7","text":"USGS data release","linkHelpText":"Evaluation of avoidance behavior of tadpole madtoms (Noturus gyrinus) as a surrogate to the endangered northern madtom (Noturus stigmosus) in response to granular Bayluscide&amp;amp;amp;reg;"},{"id":326363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1130/coverthb.jpg"},{"id":326364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1130/ofr20161130.pdf","text":"Report","size":"509 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1130"}],"country":"United States","otherGeospatial":"Great Lakes ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.935546875,\n 46.49839225859763\n ],\n [\n -82.880859375,\n 46.49839225859763\n ],\n [\n -81.82617187499999,\n 46.31658418182218\n ],\n [\n -80.2001953125,\n 46.07323062540838\n ],\n [\n -79.8046875,\n 45.55252525134013\n ],\n [\n -79.453125,\n 45.089035564831036\n ],\n [\n -79.8046875,\n 44.62175409623324\n ],\n [\n -80.5078125,\n 44.402391829093915\n ],\n [\n -81.03515625,\n 44.59046718130883\n ],\n [\n -81.4306640625,\n 44.18220395771566\n ],\n [\n -81.650390625,\n 43.73935207915473\n ],\n [\n -81.6943359375,\n 43.13306116240612\n ],\n [\n -82.08984375,\n 42.87596410238254\n ],\n [\n -82.2216796875,\n 42.68243539838623\n ],\n [\n -81.2548828125,\n 42.87596410238254\n ],\n [\n -80.5517578125,\n 42.84375132629021\n ],\n [\n -80.068359375,\n 43.197167282501276\n ],\n [\n -79.716796875,\n 43.67581809328344\n ],\n [\n -79.1455078125,\n 43.866218006556394\n ],\n [\n -77.87109375,\n 44.08758502824518\n ],\n [\n -77.2998046875,\n 44.05601169578525\n ],\n [\n -76.9482421875,\n 44.308126684886126\n ],\n [\n -75.9814453125,\n 44.308126684886126\n ],\n [\n -75.7177734375,\n 43.929549935614595\n ],\n [\n -76.5087890625,\n 43.32517767999296\n ],\n [\n -77.51953125,\n 43.068887774169625\n ],\n [\n -78.92578124999999,\n 43.13306116240612\n ],\n [\n -78.75,\n 42.65012181368025\n ],\n [\n -79.40917968749999,\n 42.09822241118974\n ],\n [\n -81.03515625,\n 41.672911819602085\n ],\n [\n -81.8701171875,\n 41.3108238809182\n ],\n [\n -82.8369140625,\n 41.37680856570233\n ],\n [\n -83.4521484375,\n 41.57436130598913\n ],\n [\n -83.4521484375,\n 42.22851735620852\n ],\n [\n -82.6611328125,\n 42.90816007196054\n ],\n [\n -82.7490234375,\n 43.67581809328344\n ],\n [\n -83.0126953125,\n 43.8028187190472\n ],\n [\n -83.671875,\n 43.58039085560786\n ],\n [\n -84.111328125,\n 43.83452678223684\n ],\n [\n -83.75976562499999,\n 44.33956524809713\n ],\n [\n -83.5400390625,\n 44.84029065139799\n ],\n [\n -83.84765625,\n 45.24395342262324\n ],\n [\n -84.462890625,\n 45.521743896993634\n ],\n [\n -84.9462890625,\n 45.36758436884978\n ],\n [\n -85.95703125,\n 44.5278427984555\n ],\n [\n -86.17675781249999,\n 44.02442151965934\n ],\n [\n -86.17675781249999,\n 43.51668853502909\n ],\n [\n -85.9130859375,\n 42.84375132629021\n ],\n [\n -85.9130859375,\n 41.96765920367816\n ],\n [\n -86.4404296875,\n 41.64007838467894\n ],\n [\n -87.3193359375,\n 41.37680856570233\n ],\n [\n -88.06640625,\n 41.64007838467894\n ],\n [\n -88.06640625,\n 42.45588764197166\n ],\n [\n -88.11035156249999,\n 43.42100882994726\n ],\n [\n -88.11035156249999,\n 43.89789239125797\n ],\n [\n -88.41796875,\n 43.67581809328344\n ],\n [\n -88.76953125,\n 44.24519901522129\n ],\n [\n -88.2861328125,\n 45.089035564831036\n ],\n [\n -87.802734375,\n 45.55252525134013\n ],\n [\n -87.275390625,\n 46.042735653846506\n ],\n [\n -86.572265625,\n 46.31658418182218\n ],\n [\n -86.17675781249999,\n 46.31658418182218\n ],\n [\n -85.4296875,\n 46.34692761055676\n ],\n [\n -85.078125,\n 46.46813299215554\n ],\n [\n -83.935546875,\n 46.49839225859763\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
http://www.umesc.usgs.gov/
The combined geothermal discharge from over 10,000 features in Yellowstone National Park (YNP) can be can be estimated from the Cl flux in the Madison, Yellowstone, Falls, and Snake Rivers. Over the last 30 years, the Cl flux in YNP Rivers has been calculated using discharge measurements and Cl concentrations determined in discrete water samples and it has been determined that approximately 12% of the Cl flux exiting YNP is from the Snake River. The relationship between electrical conductivity and concentrations of Cl and other geothermal solutes was quantified at a monitoring site located downstream from the thermal inputs in the Snake River. Beginning in 2012, continuous (15 min) electrical conductivity measurements have been made at the monitoring site. Combining continuous electrical conductivity and discharge data, the Cl and other geothermal solute fluxes were determined. The 2013–2015 Cl fluxes (5.3–5.8 kt/yr) determined using electrical conductivity are comparable to historical data. In addition, synoptic water samples and discharge data were obtained from sites along the Snake River under low-flow conditions of September 2014. The synoptic water study extended 17 km upstream from the monitoring site. Surface inflows were sampled to identify sources and to quantify solute loading. The Lewis River was the primary source of Cl, Na, K, Cl, SiO2, Rb, and As loads (50–80%) in the Snake River. The largest source of SO4 was from the upper Snake River (50%). Most of the Ca and Mg (50–55%) originate from the Snake Hot Springs. Chloride, Ca, Mg, Na, K, SiO2, F, HCO3, SO4, B, Li, Rb, and As behave conservatively in the Snake River, and therefore correlate well with conductivity (R2 ≥ 0.97).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2016.08.006","usgsCitation":"McCleskey, R.B., Lowenstern, J.B., Schaper, J., Nordstrom, D.K., Heasler, H.P., and Mahony, D., 2016, Geothermal solute flux monitoring and the source and fate of solutes in the Snake River, Yellowstone National Park, WY: Applied Geochemistry, v. 73, p. 142-156, https://doi.org/10.1016/j.apgeochem.2016.08.006.","productDescription":"15 p.","startPage":"142","endPage":"156","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-077823","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470591,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2016.08.006","text":"Publisher Index Page"},{"id":328226,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.52005767822266,\n 44.14218189856008\n ],\n [\n -110.52297592163086,\n 44.14698597918344\n ],\n [\n -110.52726745605469,\n 44.15215916724574\n ],\n [\n -110.53396224975586,\n 44.15388346250658\n ],\n [\n -110.54271697998047,\n 44.15634665405655\n ],\n [\n -110.54769515991211,\n 44.16275047090301\n ],\n [\n -110.55387496948242,\n 44.168784200722875\n ],\n [\n -110.56537628173828,\n 44.17691028989048\n ],\n [\n -110.58425903320312,\n 44.175925369020135\n ],\n [\n -110.64760208129883,\n 44.15573086580812\n ],\n [\n -110.66442489624023,\n 44.14489194082416\n ],\n [\n -110.66116333007812,\n 44.13996449871928\n ],\n [\n -110.65326690673828,\n 44.14168915023695\n ],\n [\n -110.63764572143553,\n 44.14957262989197\n ],\n [\n -110.6022834777832,\n 44.16250418310723\n ],\n [\n -110.5854606628418,\n 44.16582898159794\n ],\n [\n -110.57413101196289,\n 44.17026175476358\n ],\n [\n -110.56554794311523,\n 44.168291674483854\n ],\n [\n -110.55644989013672,\n 44.16275047090301\n ],\n [\n -110.55112838745116,\n 44.15696243587891\n ],\n [\n -110.54546356201172,\n 44.1510506651172\n ],\n [\n -110.52194595336914,\n 44.140334071142775\n ],\n [\n -110.52005767822266,\n 44.14218189856008\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"73","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ca94aae4b0f2f0cec194e6","chorus":{"doi":"10.1016/j.apgeochem.2016.08.006","url":"http://dx.doi.org/10.1016/j.apgeochem.2016.08.006","publisher":"Elsevier BV","authors":"McCleskey R. Blaine, Lowenstern Jacob B., Schaper Jonas, Nordstrom D. Kirk, Heasler Henry P., Mahony Dan","journalName":"Applied Geochemistry","publicationDate":"10/2016"},"contributors":{"authors":[{"text":"McCleskey, R. 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The NAAMP is a longterm monitoring program in which observers collect anuran calling observation data at fixed locations along random roadside routes. We assessed occupancy trends for 14 species. We found weak evidence for a general regional pattern of decline in calling anurans within breeding habitats along roads in the southeastern USA over the last 13 y. Two species had positive regional trends with 95% posterior intervals that did not include zero (Hyla cinerea and Pseudacris crucifer). Five other species also showed an increasing trend, while eight species showed a declining trend, although 95% posterior intervals included zero. We also assessed state level trends for 107 species/state combinations. Of these, 14 showed a significant decline and 12 showed a significant increase in occupancy (i.e., credible intervals did not include zero for these 26 trends).
","language":"English","publisher":"Partners in Amphibian and Reptile Conservation","publisherLocation":"Texarkana, TX","usgsCitation":"Villena Carpio, O., Royle, J., Weir, L., Foreman, T.M., Gazenski, K.D., and Campbell Grant, E., 2016, Southeast regional and state trends in anuran occupancy from calling survey data (2001-2013) from the North American Amphibian Monitoring Program: Herpetological Conservation and Biology, v. 11, no. 2, p. 373-385.","startPage":"373","endPage":"385","numberOfPages":"13","ipdsId":"IP-073199","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":328215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328214,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol11_issue2.html"}],"country":"United States","state":"Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, 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\"}}]}","volume":"11","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ca94ace4b0f2f0cec194ec","contributors":{"authors":[{"text":"Villena Carpio, Oswaldo ovillenacarpio@usgs.gov","contributorId":127375,"corporation":false,"usgs":true,"family":"Villena Carpio","given":"Oswaldo","email":"ovillenacarpio@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":647922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":647923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weir, Linda lweir@usgs.gov","contributorId":174278,"corporation":false,"usgs":true,"family":"Weir","given":"Linda","email":"lweir@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":647919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foreman, Tasha M.","contributorId":174279,"corporation":false,"usgs":true,"family":"Foreman","given":"Tasha","email":"","middleInitial":"M.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":647924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gazenski, Kimberly D.","contributorId":55306,"corporation":false,"usgs":true,"family":"Gazenski","given":"Kimberly","email":"","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":647925,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":23233,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan H.","affiliations":[],"preferred":false,"id":647926,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178869,"text":"70178869 - 2016 - Scale-dependent habitat selection and size-based dominance in adult male American alligators","interactions":[],"lastModifiedDate":"2016-12-09T15:40:59","indexId":"70178869","displayToPublicDate":"2016-09-02T00:00:00","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":"Scale-dependent habitat selection and size-based dominance in adult male American alligators","docAbstract":"Habitat selection is an active behavioral process that may vary across spatial and temporal scales. Animals choose an area of primary utilization (i.e., home range) then make decisions focused on resource needs within patches. Dominance may affect the spatial distribution of conspecifics and concomitant habitat selection. Size-dependent social dominance hierarchies have been documented in captive alligators, but evidence is lacking from wild populations. We studied habitat selection for adult male American alligators (Alligator mississippiensis; n = 17) on the Pearl River in central Mississippi, USA, to test whether habitat selection was scale-dependent and individual resource selectivity was a function of conspecific body size. We used K-select analysis to quantify selection at the home range scale and patches within the home range to determine selection congruency and important habitat variables. In addition, we used linear models to determine if body size was related to selection patterns and strengths. Our results indicated habitat selection of adult male alligators was a scale-dependent process. Alligators demonstrated greater overall selection for habitat variables at the patch level and less at the home range level, suggesting resources may not be limited when selecting a home range for animals in our study area. Further, diurnal habitat selection patterns may depend on thermoregulatory needs. There was no relationship between resource selection or home range size and body size, suggesting size-dependent dominance hierarchies may not have influenced alligator resource selection or space use in our sample. Though apparent habitat suitability and low alligator density did not manifest in an observed dominance hierarchy, we hypothesize that a change in either could increase intraspecific interactions, facilitating a dominance hierarchy. Due to the broad and diverse ecological roles of alligators, understanding the factors that influence their social dominance and space use can provide great insight into their functional role in the ecosystem.
","language":"English","publisher":"PLOS One","doi":"10.1371/journal.pone.0161814","usgsCitation":"Strickland, B.A., Vilella, F., and Belant, J.L., 2016, Scale-dependent habitat selection and size-based dominance in adult male American alligators: PLoS ONE, p. 1-16, https://doi.org/10.1371/journal.pone.0161814.","productDescription":"e0161814; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-070818","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":470592,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0161814","text":"Publisher Index Page"},{"id":331825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Pearl River, Ross Barnett Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.96566772460936,\n 32.48601763026006\n ],\n [\n -89.96566772460936,\n 32.601783214045184\n ],\n [\n -89.77203369140625,\n 32.601783214045184\n ],\n [\n -89.77203369140625,\n 32.48601763026006\n ],\n [\n -89.96566772460936,\n 32.48601763026006\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-02","publicationStatus":"PW","scienceBaseUri":"584bd0dde4b077fc20250e08","contributors":{"authors":[{"text":"Strickland, Bradley A.","contributorId":177343,"corporation":false,"usgs":false,"family":"Strickland","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":655399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vilella, Francisco 0000-0003-1552-9989 fvilella@usgs.gov","orcid":"https://orcid.org/0000-0003-1552-9989","contributorId":171363,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":655386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belant, Jerrold L.","contributorId":108394,"corporation":false,"usgs":false,"family":"Belant","given":"Jerrold","email":"","middleInitial":"L.","affiliations":[{"id":35599,"text":"Carnivore Ecology Laboratory, Mississippi State University, Mississippi State, MS","active":true,"usgs":false}],"preferred":false,"id":655400,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}