{"pageNumber":"659","pageRowStart":"16450","pageSize":"25","recordCount":69040,"records":[{"id":70048542,"text":"70048542 - 2012 - Using hydrogeologic data to evaluate geothermal potential in the eastern Great Basin","interactions":[],"lastModifiedDate":"2017-09-20T13:33:11","indexId":"70048542","displayToPublicDate":"2012-11-15T15:27:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1827,"text":"Geothermal Resources Council Transactions","active":true,"publicationSubtype":{"id":10}},"title":"Using hydrogeologic data to evaluate geothermal potential in the eastern Great Basin","docAbstract":"In support of a larger study to evaluate geothermal resource development of high-permeability stratigraphic units in sedimentary basins, this paper integrates groundwater and thermal data to evaluate heat and fluid flow within the eastern Great Basin. Previously published information from a hydrogeologic framework, a potentiometric-surface map, and groundwater budgets was compared to a surficial heat-flow map. Comparisons between regional groundwater flow patterns and surficial heat flow indicate a strong spatial relation between regional groundwater movement and surficial heat distribution. Combining aquifer geometry and heat-flow maps, a selected group of subareas within the eastern Great Basin are identified that have high surficial heat flow and are underlain by a sequence of thick basin-fill deposits and permeable carbonate aquifers. These regions may have potential for future geothermal resources development.","conferenceTitle":"Geothermal Resources Council 2012 Annual Meeting","conferenceDate":"September 30 - October 3, 2012","conferenceLocation":"Reno, NV","language":"English","publisher":"Geothermal Resources Council","publisherLocation":"Davis, CA","issn":"01935933","isbn":"0934412979","usgsCitation":"Masbruch, M.D., Heilweil, V.M., and Brooks, L.E., 2012, Using hydrogeologic data to evaluate geothermal potential in the eastern Great Basin: Geothermal Resources Council Transactions, v. 36, p. 47-52.","productDescription":"6 p.","startPage":"47","endPage":"52","ipdsId":"IP-038338","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":279120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279119,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1030209"}],"projection":"Albers Equal Area Conic Projection","datum":"North American Datum 1983","country":"United States","state":"Nevada, Utah","otherGeospatial":"Great Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.43,34.49 ], [ -118.43,43.0 ], [ -109.82,43.0 ], [ -109.82,34.49 ], [ -118.43,34.49 ] ] ] } } ] }","volume":"36","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5287509ee4b03b89f6f155e7","contributors":{"authors":[{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heilweil, Victor M. heilweil@usgs.gov","contributorId":837,"corporation":false,"usgs":true,"family":"Heilweil","given":"Victor","email":"heilweil@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brooks, Lynette E. 0000-0002-9074-0939 lebrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-9074-0939","contributorId":2718,"corporation":false,"usgs":true,"family":"Brooks","given":"Lynette","email":"lebrooks@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485021,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040743,"text":"70040743 - 2012 - Walrus areas of use in the Chukchi Sea during sparse sea ice cover","interactions":[],"lastModifiedDate":"2018-06-16T17:50:19","indexId":"70040743","displayToPublicDate":"2012-11-15T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Walrus areas of use in the Chukchi Sea during sparse sea ice cover","docAbstract":"The Pacific walrus <i>Odobenus rosmarus divergens</i> feeds on benthic invertebrates on the continental shelf of the Chukchi and Bering Seas and rests on sea ice between foraging trips. With climate warming, ice-free periods in the Chukchi Sea have increased and are projected to increase further in frequency and duration. We radio-tracked walruses to estimate areas of walrus foraging and occupancy in the Chukchi Sea from June to November of 2008 to 2011, years when sea ice was sparse over the continental shelf in comparison to historical records. The earlier and more extensive sea ice retreat in June to September, and delayed freeze-up of sea ice in October to November, created conditions for walruses to arrive earlier and stay later in the Chukchi Sea than in the past. The lack of sea ice over the continental shelf from September to October caused walruses to forage in nearshore areas instead of offshore areas as in the past. Walruses did not frequent the deep waters of the Arctic Basin when sea ice retreated off the shelf. Walruses foraged in most areas they occupied, and areas of concentrated foraging generally corresponded to regions of high benthic biomass, such as in the northeastern (Hanna Shoal) and southwestern Chukchi Sea. A notable exception was the occurrence of concentrated foraging in a nearshore area of northwestern Alaska that is apparently depauperate in walrus prey. With increasing sea ice loss, it is likely that walruses will increase their use of coastal haul-outs and nearshore foraging areas, with consequences to the population that are yet to be understood.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Ecology Progress Series","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Inter-Research Science Center","publisherLocation":"Oldendorf/Luhe, Germany","doi":"10.3354/meps10057","usgsCitation":"Jay, C.V., Fischbach, A.S., and Kochnev, A., 2012, Walrus areas of use in the Chukchi Sea during sparse sea ice cover: Marine Ecology Progress Series, v. 468, p. 1-13, https://doi.org/10.3354/meps10057.","productDescription":"13 p.","startPage":"1","endPage":"13","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":474269,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps10057","text":"Publisher Index Page"},{"id":438806,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7C24TC3","text":"USGS data release","linkHelpText":"Walrus areas of use in the Chukchi Sea during sparse sea ice cover"},{"id":438805,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X928C3","text":"USGS data release","linkHelpText":"Data Supporting Walrus Areas of Use in the Chukchi Sea During Sparse Sea Ice Cover"},{"id":263178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263177,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3354/meps10057"}],"country":"Russia;United States","state":"Alaska;Chukotka","otherGeospatial":"Chukchi Sea","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 170.0,62.0 ], [ 170.0,74.0 ], [ -150.0,74.0 ], [ -150.0,62.0 ], [ 170.0,62.0 ] ] ] } } ] }","volume":"468","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50a60f00e4b0d446a665c9bc","contributors":{"authors":[{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":468946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":468945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kochnev, Anatoly A.","contributorId":18634,"corporation":false,"usgs":true,"family":"Kochnev","given":"Anatoly A.","affiliations":[],"preferred":false,"id":468947,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040727,"text":"fs20123131 - 2012 - Polar bear and walrus response to the rapid decline in Arctic sea ice","interactions":[],"lastModifiedDate":"2023-10-10T15:44:37.406137","indexId":"fs20123131","displayToPublicDate":"2012-11-15T00:00:00","publicationYear":"2012","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":"2012-3131","title":"Polar bear and walrus response to the rapid decline in Arctic sea ice","docAbstract":"The Arctic is warming faster than other regions of the world due to positive climate feedbacks associated with loss of snow and ice. One highly visible consequence has been a rapid decline in Arctic sea ice over the past 3 decades - a decline projected to continue and result in ice-free summers likely as soon as 2030. The polar bear (<i>Ursus maritimus</i>) and the Pacific walrus (<i>Odobenus rosmarus divergens</i>) are dependent on sea ice over the continental shelves of the Arctic Ocean's marginal seas. The continental shelves are shallow regions with high biological productivity, supporting abundant marine life within the water column and on the sea floor. Polar bears use sea ice as a platform for hunting ice seals; walruses use sea ice as a resting platform between dives to forage for clams and other bottom-dwelling invertebrates. How have sea ice changes affected polar bears and walruses? How will anticipated changes affect them in the future?","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123131","collaboration":"Changing Arctic Ecosystems","usgsCitation":"Oakley, K.L., Whalen, M.E., Douglas, D., Udevitz, M.S., Atwood, T.C., and Jay, C., 2012, Polar bear and walrus response to the rapid decline in Arctic sea ice: U.S. Geological Survey Fact Sheet 2012-3131, 4 p., https://doi.org/10.3133/fs20123131.","productDescription":"4 p.","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":263141,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3131/pdf/fs20123131.pdf"},{"id":263140,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3131/"},{"id":263179,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3131.jpg"}],"country":"Canada, Russia, United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Chukchi Sea, North Slope","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -179.9,\n              69.67065614831617\n            ],\n            [\n              -179.9,\n              67.32951967592086\n            ],\n            [\n              -179.9,\n              66.42627022691761\n            ],\n            [\n              -179.9,\n              66.07425263532508\n            ],\n            [\n              -174.377294217933,\n              65.69546776812888\n            ],\n            [\n              -172.6938794902832,\n              65.50038774322343\n            ],\n            [\n              -171.51349196779236,\n              65.27435276054041\n            ],\n            [\n              -169.47155521166385,\n              65.2455308113303\n            ],\n            [\n              -167.83282187796829,\n              65.54782673228209\n            ],\n            [\n              -164.55488905347332,\n              66.3985327629955\n            ],\n            [\n              -164.2097371828716,\n              65.98021849278214\n            ],\n            [\n              -161.75428358224264,\n              65.8614468966035\n            ],\n            [\n              -159.1111552490083,\n              66.36514352988564\n            ],\n            [\n              -161.46445659049846,\n              66.79563171603391\n            ],\n            [\n              -160.99630275833633,\n              67.10198380184622\n            ],\n            [\n              -162.5209027098882,\n              67.10008391740556\n            ],\n            [\n              -163.38524452322926,\n              67.17280545607508\n            ],\n            [\n              -163.83627197620214,\n              67.65337436504618\n            ],\n            [\n              -164.85808716414638,\n              67.8788401508586\n            ],\n            [\n              -162.50868914442228,\n              68.48569237521275\n            ],\n            [\n              -159.10666367667022,\n              68.63678437817632\n            ],\n            [\n              -158.20588308648612,\n              68.40917281433352\n            ],\n            [\n              -155.4494525177222,\n              68.31978509852135\n            ],\n            [\n              -154.33909019344748,\n              68.56051283654273\n            ],\n            [\n              -152.6105580143607,\n              68.24680912496277\n            ],\n            [\n              -148.59335761347026,\n              68.39130794570073\n            ],\n            [\n              -145.97247487237186,\n              68.459052430213\n            ],\n            [\n              -144.11091873856031,\n              68.41193052534604\n            ],\n            [\n              -142.5139591673007,\n              68.35012002174844\n            ],\n            [\n              -140.97459317026988,\n              68.25748463503783\n            ],\n            [\n              -139.49662448793165,\n              68.25539413887009\n            ],\n            [\n              -137.29278547942954,\n              68.15668494203871\n            ],\n            [\n              -135.0251935823291,\n              68.54626211205144\n            ],\n            [\n              -135.3298285345646,\n              69.01908063442536\n            ],\n            [\n              -135.3198900212557,\n              70.02501291995253\n            ],\n            [\n              -135.08826844056927,\n              71.25876851517873\n            ],\n            [\n              -135.0299363245674,\n              71.9660431463698\n            ],\n            [\n              -134.8568132866843,\n              73.06131385205776\n            ],\n            [\n              -134.97966638847916,\n              73.27915929547441\n            ],\n            [\n              -144.7886244719429,\n              73.22914376935367\n            ],\n            [\n              -144.9701314002228,\n              73.84277095191263\n            ],\n            [\n              -162.40483523974848,\n              74.05277583954424\n            ],\n            [\n              -179.9,\n              74.3950398951975\n            ],\n            [\n              -179.9,\n              71.18598721738704\n            ],\n            [\n              -179.9,\n              69.67065614831617\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              179.9,\n              74.38649078010306\n            ],\n            [\n              170,\n              74.38649078010306\n            ],\n            [\n              170,\n              66.19786824259768\n            ],\n            [\n              179.9,\n              66.19786824259768\n            ],\n            [\n              179.9,\n              74.38649078010306\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50a60ef5e4b0d446a665c9b4","contributors":{"authors":[{"text":"Oakley, Karen L. koakley@usgs.gov","contributorId":747,"corporation":false,"usgs":true,"family":"Oakley","given":"Karen","email":"koakley@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":468888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whalen, Mary E. 0000-0003-2820-5158 mwhalen@usgs.gov","orcid":"https://orcid.org/0000-0003-2820-5158","contributorId":203717,"corporation":false,"usgs":true,"family":"Whalen","given":"Mary","email":"mwhalen@usgs.gov","middleInitial":"E.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":468889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":150115,"corporation":false,"usgs":true,"family":"Douglas","given":"David C.","email":"ddouglas@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":468886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":468887,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":468891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jay, C.","contributorId":73889,"corporation":false,"usgs":true,"family":"Jay","given":"C.","email":"","affiliations":[],"preferred":false,"id":468890,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70040717,"text":"70040717 - 2012 - Salinity of the Little Colorado River in Grand Canyon confers anti-parasitic properties on a native fish","interactions":[],"lastModifiedDate":"2021-01-05T19:07:48.575073","indexId":"70040717","displayToPublicDate":"2012-11-14T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Salinity of the Little Colorado River in Grand Canyon confers anti-parasitic properties on a native fish","docAbstract":"Water in the Little Colorado River within Grand Canyon is naturally high in salt (NaCl), which is known to prohibit development of external fish parasites such as Ich (<i>Ichthyophthirius multifiliis</i>). The naturally high salinity (>0.3%) of the Little Colorado River at baseflow may be one factor allowing survival and persistence of larval and juvenile humpback chub (<i>Gila cypha</i>) and other native fishes in Grand Canyon. We compared salinity readings from the Little Colorado River to those reported in the literature as being effective at removing protozoan parasites from fish. In laboratory tests, 10 juvenile roundtail chub (<i>Gila robusta</i>; 61–90 mm TL) were randomly placed into each of 12, 37-L aquaria filled with freshwater, water obtained from the Little Colorado River (0.3% salinity), or freshwater with table salt added until the salinity reached 0.3%. Roundtail chub was used as a surrogate for humpback chub in this study because the species is not listed as endangered but is morphologically and ecologically similar to humpback chub. All roundtail chub infected with Ich recovered and survived when placed in water from the Little Colorado River or water with 0.3% salinity, but all experimental fish placed in freshwater died because of Ich infection. The naturally high salinity of the Little Colorado River at baseflow (0.22%–0.36%), appears sufficiently high to interrupt the life cycle of Ich and may allow increased survival of larval and juvenile humpback chub relative to other areas within Grand Canyon.","language":"English","publisher":"Brigham Young University","doi":"10.3398/064.072.0307","usgsCitation":"Ward, D.L., 2012, Salinity of the Little Colorado River in Grand Canyon confers anti-parasitic properties on a native fish: Western North American Naturalist, v. 72, no. 3, p. 334-338, https://doi.org/10.3398/064.072.0307.","productDescription":"5 p.","startPage":"334","endPage":"338","ipdsId":"IP-033818","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488983,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol72/iss3/7","text":"External Repository"},{"id":381893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.0572,35.6882 ], [ -114.0572,36.5318 ], [ -111.828,36.5318 ], [ -111.828,35.6882 ], [ -114.0572,35.6882 ] ] ] } } ] }","volume":"72","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50a4bd81e4b0fd76c78323c9","contributors":{"authors":[{"text":"Ward, David L. 0000-0002-3355-0637 dlward@usgs.gov","orcid":"https://orcid.org/0000-0002-3355-0637","contributorId":3879,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dlward@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":468860,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70044973,"text":"70044973 - 2012 - Use of the continuous slope-area method to estimate runoff in a network of ephemeral channels, southeast Arizona, USA","interactions":[],"lastModifiedDate":"2013-05-28T12:00:46","indexId":"70044973","displayToPublicDate":"2012-11-14T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Use of the continuous slope-area method to estimate runoff in a network of ephemeral channels, southeast Arizona, USA","docAbstract":"The continuous slope-area (CSA) method is an innovative gaging method for indirect computation of complete-event discharge hydrographs that can be applied when direct measurement methods are unsafe, impractical, or impossible to apply. This paper reports on use of the method to produce event-specific discharge hydrographs in a network of sand-bedded ephemeral stream channels in southeast Arizona, USA, for water year 2008. The method provided satisfactory discharge estimates for flows that span channel banks, and for moderate to large flows, with about 10–16% uncertainty, respectively for total flow volume and peak flow, as compared to results obtained with an alternate method. Our results also suggest that the CSA method may be useful for estimating runoff of small flows, and during recessions, but with increased uncertainty.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2012.09.022","usgsCitation":"Stewart, A.M., Callegary, J.B., Smith, C.F., Gupta, H.V., Leenhouts, J.M., and Fritzinger, R.A., 2012, Use of the continuous slope-area method to estimate runoff in a network of ephemeral channels, southeast Arizona, USA: Journal of Hydrology, v. 472-473, p. 148-158, https://doi.org/10.1016/j.jhydrol.2012.09.022.","productDescription":"11 p.","startPage":"148","endPage":"158","ipdsId":"IP-019852","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":272900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272899,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2012.09.022"}],"country":"United States","state":"Arizona","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.2,3.0175 ], [ -110.2,8.333333333333334E-4 ], [ -10.15,8.333333333333334E-4 ], [ -10.15,3.0175 ], [ -110.2,3.0175 ] ] ] } } ] }","volume":"472-473","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5d1f0e4b0605bc571f025","contributors":{"authors":[{"text":"Stewart, Anne M. astewart@usgs.gov","contributorId":3938,"corporation":false,"usgs":true,"family":"Stewart","given":"Anne","email":"astewart@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Callegary, James B. 0000-0003-3604-0517 jcallega@usgs.gov","orcid":"https://orcid.org/0000-0003-3604-0517","contributorId":2171,"corporation":false,"usgs":true,"family":"Callegary","given":"James","email":"jcallega@usgs.gov","middleInitial":"B.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Christopher F. 0000-0002-8075-4763 cfsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":1338,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cfsmith@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":true,"id":476539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gupta, Hoshin V.","contributorId":7597,"corporation":false,"usgs":true,"family":"Gupta","given":"Hoshin","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":476542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leenhouts, James M. 0000-0001-5171-9240 leenhout@usgs.gov","orcid":"https://orcid.org/0000-0001-5171-9240","contributorId":225,"corporation":false,"usgs":true,"family":"Leenhouts","given":"James","email":"leenhout@usgs.gov","middleInitial":"M.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476538,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fritzinger, Robert A.","contributorId":78229,"corporation":false,"usgs":true,"family":"Fritzinger","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":476543,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70040735,"text":"fs20123118 - 2012 - Science to support the understanding of Ohio's water resources","interactions":[],"lastModifiedDate":"2012-11-14T16:18:55","indexId":"fs20123118","displayToPublicDate":"2012-11-14T00:00:00","publicationYear":"2012","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":"2012-3118","title":"Science to support the understanding of Ohio's water resources","docAbstract":"Ohio’s water resources support a complex web of human activities and nature—clean and abundant water is needed for drinking, recreation, farming, and industry, as well as for fish and wildlife needs. The distribution of rainfall can cause floods and droughts, which affects streamflow, groundwater, water availability, water quality, recreation, and aquatic habitats. Ohio is bordered by the Ohio River and Lake Erie and has over 44,000 miles of streams and more than 60,000 lakes and ponds (State of Ohio, 1994). Nearly all the rural population obtain drinking water from groundwater sources.\n\nThe U.S. Geological Survey (USGS) works in cooperation with local, State, and other Federal agencies, as well as universities, to furnish decisionmakers, policymakers, USGS scientists, and the general public with reliable scientific information and tools to assist them in management, stewardship, and use of Ohio’s natural resources. The diversity of scientific expertise among USGS personnel enables them to carry out large- and small-scale multidisciplinary studies. The USGS is unique among government organizations because it has neither regulatory nor developmental authority—its sole product is reliable, impartial, credible, relevant, and timely scientific information, equally accessible and available to everyone. The USGS Ohio Water Science Center provides reliable hydrologic and water-related ecological information to aid in the understanding of use and management of the Nation’s water resources, in general, and Ohio’s water resources, in particular. This fact sheet provides an overview of current (2012) or recently completed USGS studies and data activities pertaining to water resources in Ohio. More information regarding projects of the USGS Ohio Water Science Center is available at http://oh.water.usgs.gov/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123118","usgsCitation":"Shaffer, K., Kula, S., Bambach, P., and Runkle, D., 2012, Science to support the understanding of Ohio's water resources: U.S. Geological Survey Fact Sheet 2012-3118, 6 p.; maps (col.), https://doi.org/10.3133/fs20123118.","productDescription":"6 p.; maps (col.)","startPage":"1","endPage":"6","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":263164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3118.jpg"},{"id":263162,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3118/"},{"id":263163,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3118/pdf/fs2012-3118_web.pdf"}],"country":"United States","state":"Ohio","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.8203,38.4034 ], [ -84.8203,41.9773 ], [ -84.5182,41.9773 ], [ -84.5182,38.4034 ], [ -84.8203,38.4034 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50a4bd85e4b0fd76c78323ce","contributors":{"authors":[{"text":"Shaffer, Kimberly kshaffer@usgs.gov","contributorId":1589,"corporation":false,"usgs":true,"family":"Shaffer","given":"Kimberly","email":"kshaffer@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kula, Stephanie","contributorId":11893,"corporation":false,"usgs":true,"family":"Kula","given":"Stephanie","affiliations":[],"preferred":false,"id":468926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bambach, Phil","contributorId":24642,"corporation":false,"usgs":true,"family":"Bambach","given":"Phil","email":"","affiliations":[],"preferred":false,"id":468927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runkle, Donna","contributorId":51317,"corporation":false,"usgs":true,"family":"Runkle","given":"Donna","affiliations":[],"preferred":false,"id":468928,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040726,"text":"ds725 - 2012 - Micrometeorological, evapotranspiration, and soil-moisture data at the Amargosa Desert Research site in Nye County near Beatty, Nevada, 2006-11","interactions":[],"lastModifiedDate":"2026-05-13T13:30:43.81734","indexId":"ds725","displayToPublicDate":"2012-11-14T00:00:00","publicationYear":"2012","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":"725","title":"Micrometeorological, evapotranspiration, and soil-moisture data at the Amargosa Desert Research site in Nye County near Beatty, Nevada, 2006-11","docAbstract":"This report describes micrometeorological, evapotranspiration, and soil-moisture data collected since 2006 at the Amargosa Desert Research Site adjacent to a low-level radio-active waste and hazardous chemical waste facility near Beatty, Nevada. Micrometeorological data include precipitation, solar radiation, net radiation, air temperature, relative humidity, saturated and ambient vapor pressure, wind speed and direction, barometric pressure, near-surface soil temperature, soil-heat flux, and soil-water content. Evapotranspiration (ET) data include latent-heat flux, sensible-heat flux, net radiation, soil-heat flux, soil temperature, air temperature, vapor pressure, and other principal energy-budget data. Soil-moisture data include periodic measurements of volumetric water-content at experimental sites that represent vegetated native soil, devegetated native soil, and simulated waste disposal trenches - maximum measurement depths range from 5.25 to 29.25 meters. All data are compiled in electronic spreadsheets that are included with this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds725","usgsCitation":"Arthur, J.M., Johnson, M.J., Mayers, C.J., and Andraski, B.J., 2012, Micrometeorological, evapotranspiration, and soil-moisture data at the Amargosa Desert Research site in Nye County near Beatty, Nevada, 2006–11: U.S. Geological Survey Data Series 725, 12 p.","productDescription":"Report: iv, 12 p.; Appendixes: A-G","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":354739,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/725/data/ds725_appendixd.xlsx","text":"Appendix D","size":"170 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 725 Appendix D"},{"id":354738,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/725/data/ds725_appendixc.xlsx","text":"Appendix C","size":"8.9 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 725 Appendix C"},{"id":504281,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_97720.htm","linkFileType":{"id":5,"text":"html"}},{"id":354737,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/725/data/ds725_appendixb.xlsx","text":"Appendix B","size":"395 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 725 Appendix B"},{"id":354733,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/725/coverthb.jpg"},{"id":354742,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/725/data/ds725_appendixg.xlsx","text":"Appendix G","size":"142 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 725 Appendix G"},{"id":354734,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/725/pdf/ds725.pdf","text":"Report","size":"566 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 725"},{"id":354735,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/725/appendixUpdates.txt","text":"Appendix updates","description":"DS 725 Appendix Updates"},{"id":354740,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/725/data/ds725_appendixe.xlsx","text":"Appendix E","size":"27.6 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 725 Appendix E"},{"id":354741,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/725/data/ds725_appendixf.xlsx","text":"Appendix F","size":"79 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 725 Appendix F"},{"id":354736,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/725/data/ds725_appendixa.xlsx","text":"Appendix A","size":"17 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 725 Appendix A"}],"country":"United States","state":"Nevada","county":"Nye County","city":"Beatty","otherGeospatial":"Amargosa Desert","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.0,36.5 ], [ -117.0,37.0 ], [ -116.5,37.0 ], [ -116.5,36.5 ], [ -117.0,36.5 ] ] ] } } ] }","edition":"Version 1.0: November 2012; Version 1.1: March 2015; Version 1.2: June 2018","contact":"<p><a href=\"mailto:dc_nv@usgs.gov\" data-mce-href=\"mailto:dc_nv@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/nv-water\" target=\"blank\" data-mce-href=\"https://www.usgs.gov/centers/nv-water\">Nevada Water Science Center</a><br> U.S. Geological Survey<br> 2730 N. Deer Run Rd.<br> Carson City, Nevada 89701</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Site Description<br></li><li>Methods and Instrumentation<br></li><li>Micrometeorological Data<br></li><li>Evapotranspiration Data<br></li><li>Soil-Moisture Data<br></li><li>References Cited<br></li><li>Appendixes A–G<br></li></ul>","publishedDate":"2012-11-13","revisedDate":"2018-06-05","noUsgsAuthors":false,"publicationDate":"2012-11-13","publicationStatus":"PW","scienceBaseUri":"50a4bd7ce4b0fd76c78323c4","contributors":{"authors":[{"text":"Arthur, Jonathan M.","contributorId":85844,"corporation":false,"usgs":true,"family":"Arthur","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":468884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Michael J. johnsonm@usgs.gov","contributorId":2282,"corporation":false,"usgs":true,"family":"Johnson","given":"Michael","email":"johnsonm@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":468883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mayers, C. Justin cjmayers@usgs.gov","contributorId":94745,"corporation":false,"usgs":true,"family":"Mayers","given":"C.","email":"cjmayers@usgs.gov","middleInitial":"Justin","affiliations":[],"preferred":false,"id":468885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andraski, Brian J. 0000-0002-2086-0417 andraski@usgs.gov","orcid":"https://orcid.org/0000-0002-2086-0417","contributorId":168800,"corporation":false,"usgs":true,"family":"Andraski","given":"Brian","email":"andraski@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":468882,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040731,"text":"gip143 - 2012 - Stream ecosystems change with urban development","interactions":[],"lastModifiedDate":"2018-04-02T16:31:36","indexId":"gip143","displayToPublicDate":"2012-11-14T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"143","title":"Stream ecosystems change with urban development","docAbstract":"The healthy condition of the physical living space in a natural stream—defined by unaltered hydrology (streamflow), high diversity of habitat features, and natural water chemistry—supports diverse biological communities with aquatic species that are sensitive to disturbances.\n\nIn a highly degraded urban stream, the poor condition of the physical living space—streambank and tree root damage from altered hydrology, low diversity of habitat, and inputs of chemical contaminants—contributes to biological communities with low diversity and high tolerance to disturbance.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip143","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Bell, A.H., James, F.C., and McMahon, G., 2012, Stream ecosystems change with urban development: U.S. Geological Survey General Information Product 143, 1 p.: 17 x 11 inches, https://doi.org/10.3133/gip143.","productDescription":"1 p.: 17 x 11 inches","startPage":"1","endPage":"1","numberOfPages":"1","additionalOnlineFiles":"N","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":263150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip_143.jpg"},{"id":263148,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/143/"},{"id":263149,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/143/pdf/GIP143.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50a4bd8fe4b0fd76c78323d8","contributors":{"authors":[{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"James, F. Coles","contributorId":58154,"corporation":false,"usgs":true,"family":"James","given":"F.","email":"","middleInitial":"Coles","affiliations":[],"preferred":false,"id":468907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McMahon, Gerard 0000-0001-7675-777X gmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-777X","contributorId":191488,"corporation":false,"usgs":true,"family":"McMahon","given":"Gerard","email":"gmcmahon@usgs.gov","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468905,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040733,"text":"cir1378 - 2012 - Strategies for managing the effects of urban development on streams","interactions":[],"lastModifiedDate":"2018-04-02T16:31:21","indexId":"cir1378","displayToPublicDate":"2012-11-14T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1378","title":"Strategies for managing the effects of urban development on streams","docAbstract":"Urban development remains an important agent of environmental change in the United States. The U.S. population grew by 17 percent from 1982 to 1997, while urbanized land area grew by 47 percent, suggesting that urban land consumption far outpaced population growth (Fulton and others, 2001; Sierra Club, 2003; American Farmland Trust, 2009). Eighty percent of Americans now live in metropolitan areas. Each American effectively occupies about 20 percent more developed land (for housing, schools, shopping, roads, and other related services) than 20 years ago (Markham and Steinzor, 2006). Passel and Cohn (2008) predict a dramatic 48 percent increase in the population of the United States from 2005 to 2050. The advantages and challenges of living in these developed areas—convenience, congestion, employment, pollution—are part of the day-to-day realities of most Americans. Nowhere are the environmental changes associated with urban development more evident than in urban streams. The U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program investigation of the effects of urban development on stream ecosystems (EUSE) during 1999–2004 provides the most spatially comprehensive analysis of stream impacts of urban development that has been completed in the United States. A nationally consistent study design was used in nine metropolitan areas of the United States—Portland, Oregon; Salt Lake City, Utah; Birmingham, Alabama; Atlanta, Georgia; Raleigh, North Carolina; Boston, Massachusetts; Denver, Colorado; Dallas, Texas; and Milwaukee, Wisconsin. A summary report published as part of the EUSE study describes several of these impacts on urban streams (<a href=\"http://pubs.usgs.gov/circ/1373/\" target=\"_blank\">Coles and others, 2012</a>).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1378","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Cappiella, K., Stack, W.P., Fraley-McNeal, L., Lane, C., and McMahon, G., 2012, Strategies for managing the effects of urban development on streams: U.S. Geological Survey Circular 1378, vi, 69 p., https://doi.org/10.3133/cir1378.","productDescription":"vi, 69 p.","startPage":"i","endPage":"69","numberOfPages":"80","additionalOnlineFiles":"N","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":263159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir_1378.jpg"},{"id":263157,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1378/"},{"id":263158,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1378/pdf/Circular1378.pdf"}],"country":"United States","state":"Alabama;Colorado;Georgia;Massachusetts;North Carolina;Oregon;Texas;Utah;Wisconsin","city":"Atlanta;Birmingham;Boston;Dallas;Denver;Milwaukee;Portland;Raleigh;Salt Lake City","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50a4bd8ae4b0fd76c78323d3","contributors":{"authors":[{"text":"Cappiella, Karen","contributorId":83595,"corporation":false,"usgs":true,"family":"Cappiella","given":"Karen","email":"","affiliations":[],"preferred":false,"id":468923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stack, William P.","contributorId":25417,"corporation":false,"usgs":true,"family":"Stack","given":"William","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":468921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fraley-McNeal, Lisa","contributorId":96968,"corporation":false,"usgs":true,"family":"Fraley-McNeal","given":"Lisa","email":"","affiliations":[],"preferred":false,"id":468924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, Cecilia","contributorId":53664,"corporation":false,"usgs":true,"family":"Lane","given":"Cecilia","email":"","affiliations":[],"preferred":false,"id":468922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMahon, Gerard 0000-0001-7675-777X gmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-777X","contributorId":191488,"corporation":false,"usgs":true,"family":"McMahon","given":"Gerard","email":"gmcmahon@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":468920,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70040730,"text":"fs20123071 - 2012 - Urban development results in stressors that degrade stream ecosystems","interactions":[],"lastModifiedDate":"2018-04-02T16:31:49","indexId":"fs20123071","displayToPublicDate":"2012-11-14T00:00:00","publicationYear":"2012","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":"2012-3071","title":"Urban development results in stressors that degrade stream ecosystems","docAbstract":"In 2003, eighty-three percent of Americans lived in metropolitan areas, and considerable population increases are predicted within the next 50 years. Nowhere are the environmental changes associated with urban development more evident than in urban streams. Contaminants, habitat destruction, and increasing streamflow flashiness resulting from urban development have been associated with the disruption of biological communities, particularly the loss of sensitive aquatic biota. Every stream is connected downstream to other water bodies, and inputs of contaminants and (or) sediments to streams can cause degradation downstream with adverse effects on biological communities and on economically valuable resources, such as fisheries and tourism. Understanding how algal, invertebrate, and fish communities respond to physical and chemical stressors associated with urban development can provide important clues on how multiple stressors may be managed to protect stream health as a watershed becomes increasingly urbanized. This fact sheet highlights selected findings of a comprehensive assessment by the National Water-Quality Assessment Program of the U.S. Geological Survey (USGS) of the effects of urban development on stream ecosystems in nine metropolitan study areas.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123071","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Bell, A.H., Coles, J.F., McMahon, G., and Woodside, M., 2012, Urban development results in stressors that degrade stream ecosystems: U.S. Geological Survey Fact Sheet 2012-3071, 6 p., https://doi.org/10.3133/fs20123071.","productDescription":"6 p.","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":263153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3071.jpg"},{"id":263151,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3071/"},{"id":263152,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3071/pdf/2012-3071.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50a4bd95e4b0fd76c78323dd","contributors":{"authors":[{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coles, James F. 0000-0002-1953-012X jcoles@usgs.gov","orcid":"https://orcid.org/0000-0002-1953-012X","contributorId":2239,"corporation":false,"usgs":true,"family":"Coles","given":"James","email":"jcoles@usgs.gov","middleInitial":"F.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McMahon, Gerard 0000-0001-7675-777X gmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-777X","contributorId":191488,"corporation":false,"usgs":true,"family":"McMahon","given":"Gerard","email":"gmcmahon@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":468901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodside, Michael D. mdwoodsi@usgs.gov","contributorId":2903,"corporation":false,"usgs":true,"family":"Woodside","given":"Michael D.","email":"mdwoodsi@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":468904,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040686,"text":"70040686 - 2012 - Evaluating the predictive abilities of community occupancy models using AUC while accounting for imperfect detection","interactions":[],"lastModifiedDate":"2012-11-13T12:22:11","indexId":"70040686","displayToPublicDate":"2012-11-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the predictive abilities of community occupancy models using AUC while accounting for imperfect detection","docAbstract":"The ability to accurately predict patterns of species' occurrences is fundamental to the successful management of animal communities.  To determine optimal management strategies, it is essential to understand species-habitat relationships and how species habitat use is related to natural or human-induced environmental changes.  Using five years of monitoring data in the Chesapeake and Ohio Canal National Historical Park, Maryland, USA, we developed four multi-species hierarchical models for estimating amphibian wetland use that account for imperfect detection during sampling. The models were designed to determine which factors (wetland habitat characteristics, annual trend effects, spring/summer precipitation, and previous wetland occupancy) were most important for predicting future habitat use. We used the models to make predictions of species occurrences in sampled and unsampled wetlands and evaluated model projections using additional data.  Using a Bayesian approach, we calculated a posterior distribution of receiver operating characteristic area under the curve (ROC AUC) values, which allowed us to explicitly quantify the uncertainty in the quality of our predictions and to account for false negatives in the evaluation dataset.  We found that wetland hydroperiod (the length of time that a wetland holds water) as well as the occurrence state in the prior year were generally the most important factors in determining occupancy.  The model with only habitat covariates predicted species occurrences well; however, knowledge of wetland use in the previous year significantly improved predictive ability at the community level and for two of 12 species/species complexes.  Our results demonstrate the utility of multi-species models for understanding which factors affect species habitat use of an entire community (of species) and provide an improved methodology using AUC that is helpful for quantifying the uncertainty in model predictions while explicitly accounting for detection biases.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","publisherLocation":"Ithaca, NY","doi":"10.1890/11-1936.1","usgsCitation":"Zipkin, E., Grant, E., and Fagan, W., 2012, Evaluating the predictive abilities of community occupancy models using AUC while accounting for imperfect detection: Ecological Applications, v. 22, no. 7, p. 1962-1972, https://doi.org/10.1890/11-1936.1.","productDescription":"11 p.","startPage":"1962","endPage":"1972","numberOfPages":"11","ipdsId":"IP-033849","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":263097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263096,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/11-1936.1"}],"volume":"22","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50a3b9c8e4b0855e233c070a","contributors":{"authors":[{"text":"Zipkin, Elise F.","contributorId":70528,"corporation":false,"usgs":true,"family":"Zipkin","given":"Elise F.","affiliations":[],"preferred":false,"id":468789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Evan H. Campbell","contributorId":14686,"corporation":false,"usgs":true,"family":"Grant","given":"Evan H. Campbell","affiliations":[],"preferred":false,"id":468788,"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":468790,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040687,"text":"70040687 - 2012 - Joint estimation of habitat dynamics and species interactions: Disturbance reduces co-occurrence of non-native predators with an endangered toad","interactions":[],"lastModifiedDate":"2016-09-26T14:37:41","indexId":"70040687","displayToPublicDate":"2012-11-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Joint estimation of habitat dynamics and species interactions: Disturbance reduces co-occurrence of non-native predators with an endangered toad","docAbstract":"<p><strong>1.</strong> Ecologists have long been interested in the processes that determine patterns of species occurrence and co-occurrence. Potential short-comings of many existing empirical approaches that address these questions include a reliance on patterns of occurrence at a single time point, failure to account properly for imperfect detection and treating the environment as a static variable.</p><p><strong>2.</strong> We fit detection and non-detection data collected from repeat visits using a dynamic site occupancy model that simultaneously accounts for the temporal dynamics of a focal prey species, its predators and its habitat. Our objective was to determine how disturbance and species interactions affect the co-occurrence probabilities of an endangered toad and recently introduced non-native predators in stream breeding habitats. For this, we determined statistical support for alternative processes that could affect co-occurrence frequency in the system.</p><p><strong>3.</strong> We collected occurrence data at stream segments in two watersheds where streams were largely ephemeral and one watershed dominated by perennial streams. Co-occurrence probabilities of toads with non-native predators were related to disturbance frequency, with low co-occurrence in the ephemeral watershed and high co-occurrence in the perennial watershed. This occurred because once predators were established at a site, they were rarely lost from the site except in cases when the site dried out. Once dry sites became suitable again, toads colonized them much more rapidly than predators, creating a period of predator-free space.</p><p><strong>4.</strong> We attribute the dynamics to a storage effect, where toads persisting outside the stream environment during periods of drought rapidly colonized sites when they become suitable again. Our results support that even in highly connected stream networks, temporal disturbance can structure frequencies with which breeding amphibians encounter non-native predators.</p><p><strong>5.</strong> Dynamic multi-state occupancy models are a powerful tool for rigorously examining hypotheses about inter-species and species–habitat interactions. In contrast to previous methods that infer dynamic processes based on static patterns in occupancy, the approach we took allows the dynamic processes that determine species–species and species–habitat interactions to be directly estimated.</p>","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1365-2656.2012.02001.x","usgsCitation":"Miller, D., Brehme, C.S., Hines, J., Nichols, J., and Fisher, R.N., 2012, Joint estimation of habitat dynamics and species interactions: Disturbance reduces co-occurrence of non-native predators with an endangered toad: Journal of Animal Ecology, v. 81, no. 6, p. 1288-1297, https://doi.org/10.1111/j.1365-2656.2012.02001.x.","productDescription":"10 p.","startPage":"1288","endPage":"1297","numberOfPages":"10","ipdsId":"IP-029983","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":474270,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-2656.2012.02001.x","text":"Publisher Index Page"},{"id":263103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263102,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2656.2012.02001.x"}],"volume":"81","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-06-15","publicationStatus":"PW","scienceBaseUri":"50a3b9d8e4b0855e233c0716","contributors":{"authors":[{"text":"Miller, David A.W.","contributorId":19423,"corporation":false,"usgs":true,"family":"Miller","given":"David A.W.","affiliations":[],"preferred":false,"id":468795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brehme, Cheryl S. 0000-0001-8904-3354 cbrehme@usgs.gov","orcid":"https://orcid.org/0000-0001-8904-3354","contributorId":3419,"corporation":false,"usgs":true,"family":"Brehme","given":"Cheryl","email":"cbrehme@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":468793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hines, James E. jhines@usgs.gov","contributorId":3506,"corporation":false,"usgs":true,"family":"Hines","given":"James E.","email":"jhines@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":468794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":468791,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":468792,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70040700,"text":"70040700 - 2012 - Microbial colonization and controls in dryland systems","interactions":[],"lastModifiedDate":"2012-11-13T12:40:33","indexId":"70040700","displayToPublicDate":"2012-11-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2846,"text":"Nature Reviews Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Microbial colonization and controls in dryland systems","docAbstract":"Drylands constitute the most extensive terrestrial biome, covering more than one-third of the Earth's continental surface. In these environments, stress limits animal and plant life, so life forms that can survive desiccation and then resume growth following subsequent wetting assume the foremost role in ecosystem processes. In this Review, we describe how these organisms assemble in unique soil- and rock-surface communities to form a thin veneer of mostly microbial biomass across hot and cold deserts. These communities mediate inputs and outputs of gases, nutrients and water from desert surfaces, as well as regulating weathering, soil stability, and hydrological and nutrient cycles. The magnitude of regional and global desert-related environmental impacts is affected by these surface communities; here, we also discuss the challenges for incorporating the consideration of these communities and their effects into the management of dryland resources.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Nature Reviews Microbiology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Nature Publishing Group","publisherLocation":"London, U.K.","doi":"10.1038/nrmicro2854","usgsCitation":"Pointing, S.B., and Belnap, J., 2012, Microbial colonization and controls in dryland systems: Nature Reviews Microbiology, v. 10, no. 8, p. 551-562, https://doi.org/10.1038/nrmicro2854.","productDescription":"12 p.","startPage":"551","endPage":"562","ipdsId":"IP-036400","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":474271,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/nrmicro2854","text":"Publisher Index Page"},{"id":263106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263105,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1038/nrmicro2854"}],"volume":"10","issue":"8","noUsgsAuthors":false,"publicationDate":"2012-07-16","publicationStatus":"PW","scienceBaseUri":"50a3b9dde4b0855e233c071a","contributors":{"authors":[{"text":"Pointing, Stephen B.","contributorId":8347,"corporation":false,"usgs":true,"family":"Pointing","given":"Stephen","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":468822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":468821,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040704,"text":"tm5B9 - 2012 - Determination of steroid hormones and related compounds in filtered and unfiltered water by solid-phase extraction, derivatization, and gas chromatography with tandem mass spectrometry","interactions":[],"lastModifiedDate":"2018-08-15T14:56:07","indexId":"tm5B9","displayToPublicDate":"2012-11-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"5-B9","title":"Determination of steroid hormones and related compounds in filtered and unfiltered water by solid-phase extraction, derivatization, and gas chromatography with tandem mass spectrometry","docAbstract":"A new analytical method has been developed and implemented at the U.S. Geological Survey National Water Quality Laboratory that determines a suite of 20 steroid hormones and related compounds in filtered water (using laboratory schedule 2434) and in unfiltered water (using laboratory schedule 4434). This report documents the procedures and initial performance data for the method and provides guidance on application of the method and considerations of data quality in relation to data interpretation. The analytical method determines 6 natural and 3 synthetic estrogen compounds, 6 natural androgens, 1 natural and 1 synthetic progestin compound, and 2 sterols: cholesterol and 3--coprostanol. These two sterols have limited biological activity but typically are abundant in wastewater effluents and serve as useful tracers. Bisphenol A, an industrial chemical used primarily to produce polycarbonate plastic and epoxy resins and that has been shown to have estrogenic activity, also is determined by the method.\n\nA technique referred to as isotope-dilution quantification is used to improve quantitative accuracy by accounting for sample-specific procedural losses in the determined analyte concentration. Briefly, deuterium- or carbon-13-labeled isotope-dilution standards (IDSs), all of which are direct or chemically similar isotopic analogs of the method analytes, are added to all environmental and quality-control and quality-assurance samples before extraction. Method analytes and IDS compounds are isolated from filtered or unfiltered water by solid-phase extraction onto an octadecylsilyl disk, overlain with a graded glass-fiber filter to facilitate extraction of unfiltered sample matrices. The disks are eluted with methanol, and the extract is evaporated to dryness, reconstituted in solvent, passed through a Florisil solid-phase extraction column to remove polar organic interferences, and again evaporated to dryness in a reaction vial. The method compounds are reacted with activated -methyl--trimethylsilyl trifluoroacetamide at 65 degrees Celsius for 1 hour to form trimethylsilyl or trimethylsilyl-enol ether derivatives that are more amenable to gas chromatographic separation than the underivatized compounds. Analysis is carried out by gas chromatography with tandem mass spectrometry using calibration standards that are derivatized concurrently with the sample extracts.\n\nAnalyte concentrations are quantified relative to specific IDS compounds in the sample, which directly compensate for procedural losses (incomplete recovery) in the determined and reported analyte concentrations. Thus, reported analyte concentrations (or analyte recoveries for spiked samples) are corrected based on recovery of the corresponding IDS compound during the quantification process. Recovery for each IDS compound is reported for each sample and represents an absolute recovery in a manner comparable to surrogate recoveries for other organic methods used by the National Water Quality Laboratory. Thus, IDS recoveries provide a useful tool for evaluating sample-specific analytical performance from an absolute mass recovery standpoint. IDS absolute recovery will differ and typically be lower than the corresponding analyte’s method recovery in spiked samples. However, additional correction of reported analyte concentrations is unnecessary and inappropriate because the analyte concentration (or recovery) already is compensated for by the isotope-dilution quantification procedure.\n\nMethod analytes were spiked at 10 and 100 nanograms per liter (ng/L) for most analytes (10 times greater spike levels were used for bisphenol A and 100 times greater spike levels were used for 3--coprostanol and cholesterol) into the following validation-sample matrices: reagent water, wastewater-affected surface water, a secondary-treated wastewater effluent, and a primary (no biological treatment) wastewater effluent. Overall method recovery for all analytes in these matrices averaged 100 percent, with overall relative standard deviation of 28 percent. Mean recoveries of the 20 individual analytes for spiked reagent-water samples prepared along with field samples and analyzed in 2009–2010 ranged from 84–104 percent, with relative standard deviations of 6–36 percent. Concentrations for two analytes, equilin and progesterone, are reported as estimated because these analytes had excessive bias or variability, or both. Additional database coding is applied to other reported analyte data as needed, based on sample-specific IDS recovery performance.\n\nDetection levels were derived statistically by fortifying reagent water at six different levels (0.1 to 4 ng/L) and range from about 0.4 to 4 ng/L for 16 analytes. Interim reporting levels applied to analytes in this report range from 0.8 to 8 ng/L. Bisphenol A and the sterols (cholesterol and 3-beta-coprostanol) were consistently detected in laboratory and field blanks. The minimum reporting levels were set at 100 ng/L for bisphenol A and at 200 ng/L for the two sterols to prevent any bias associated with the presence of these compounds in the blanks. A minimum reporting level of 2 ng/L was set for 11-ketotestosterone to minimize false positive risk from an interfering siloxane compound emanating as chromatographic-column bleed, from vial septum material, or from other sources at no more than 1 ng/L.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm5B9","collaboration":"Book 5, Chapter B9 of U.S. Geological Survey Techniques and Methods","usgsCitation":"Foreman, W., Gray, J.L., ReVello, R., Lindley, C.E., Losche, S.A., and Barber, L.B., 2012, Determination of steroid hormones and related compounds in filtered and unfiltered water by solid-phase extraction, derivatization, and gas chromatography with tandem mass spectrometry: U.S. Geological Survey Techniques and Methods 5-B9, x, 118 p.; ill., https://doi.org/10.3133/tm5B9.","productDescription":"x, 118 p.; ill.","startPage":"i","endPage":"118","numberOfPages":"131","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":263112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_5_B9.gif"},{"id":263089,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/5b9/TM5-B9.pdf"},{"id":263088,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/5b9/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50a3b9c4e4b0855e233c0706","contributors":{"authors":[{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":468831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, James L. 0000-0002-0807-5635 jlgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":1253,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"jlgray@usgs.gov","middleInitial":"L.","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":468830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"ReVello, Rhiannon C. rcrevell@usgs.gov","contributorId":4128,"corporation":false,"usgs":true,"family":"ReVello","given":"Rhiannon C.","email":"rcrevell@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468833,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindley, Chris E. clindley@usgs.gov","contributorId":2337,"corporation":false,"usgs":true,"family":"Lindley","given":"Chris","email":"clindley@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":468832,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Losche, Scott A. salosche@usgs.gov","contributorId":4694,"corporation":false,"usgs":true,"family":"Losche","given":"Scott","email":"salosche@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":468834,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":468829,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70040706,"text":"sir20125183 - 2012 - Conceptual and numerical models of the glacial aquifer system north of Aberdeen, South Dakota","interactions":[],"lastModifiedDate":"2017-10-14T11:24:59","indexId":"sir20125183","displayToPublicDate":"2012-11-13T00:00:00","publicationYear":"2012","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":"2012-5183","title":"Conceptual and numerical models of the glacial aquifer system north of Aberdeen, South Dakota","docAbstract":"This U.S. Geological Survey report documents a conceptual and numerical model of the glacial aquifer system north of Aberdeen, South Dakota, that can be used to evaluate and manage the city of Aberdeen's water resources. The glacial aquifer system in the model area includes the Elm, Middle James, and Deep James aquifers, with intervening confining units composed of glacial till. The Elm aquifer ranged in thickness from less than 1 to about 95 feet (ft), with an average thickness of about 24 ft; the Middle James aquifer ranged in thickness from less than 1 to 91 ft, with an average thickness of 13 ft; and the Deep James aquifer ranged in thickness from less than 1 to 165 ft, with an average thickness of 23 ft. The confining units between the aquifers consisted of glacial till and ranged in thickness from 0 to 280 ft. The general direction of groundwater flow in the Elm aquifer in the model area was from northwest to southeast following the topography. Groundwater flow in the Middle James aquifer was to the southeast. Sparse data indicated a fairly flat potentiometric surface for the Deep James aquifer. Horizontal hydraulic conductivity for the Elm aquifer determined from aquifer tests ranged from 97 to 418 feet per day (ft/d), and a confined storage coefficient was determined to be 2.4x10<sup>-5</sup>. Estimates of the vertical hydraulic conductivity of the sediments separating the Elm River from the Elm aquifer, determined from the analysis of temperature gradients, ranged from 0.14 to 2.48 ft/d. Average annual precipitation in the model area was 19.6 inches per year (in/yr), and agriculture was the primary land use. Recharge to the Elm aquifer was by infiltration of precipitation through overlying outwash, lake sediments, and glacial till. The annual recharge for the model area, calculated by using a soil-water-balance method for water year (WY) 1975-2009, ranged from 0.028 inch in WY 1980 to 4.52 inches in WY 1986, with a mean of 1.56 inches. The annual potential evapotranspiration, calculated in soil-water-balance analysis, ranged from 21.8 inches in WY 1983 to 27.0 inches in WY 1985, with a mean of 24.6 inches. Water use from the glacial aquifer system primarily was from the Elm aquifer for irrigation, municipal, and suburban water supplies, and the annual rate ranged from 1.0 to 2.4 cubic feet per second (ft<sup>3</sup>/s). The MODFLOW-2005 numerical model represented the Elm aquifer, the Middle James aquifer, and the Deep James aquifer with model layers 1-3 respectively separated by confining layers 1-2 respectively. Groundwater flow was simulated with 75 stress periods beginning October 1, 1974, and ending September 30, 2009. Model grid spacing was 200 by 200 ft and boundaries were represented by specified-head boundaries and no-flow boundaries. The model used parameter estimation that focused on minimizing the difference between 954 observed and simulated hydraulic heads for 135 wells. Calibrated mean horizontal hydraulic conductivity values for model layers 1-3 were 94, 41, and 30 ft/d respectively. Vertical hydraulic conductivity values for confining layers 1 and 2 were 0.0002 and 0.0003 ft/d, respectively. Calibrated specific yield for model layer 1was 0.1 and specific storage ranged from 0.0003 to 0.0005 per foot. Calibrated mean recharge rates ranged from 2.5 in/yr where glacial till thickness was less than 10 ft to 0.8 in/yr where glacial till thickness was greater than 30 ft. Calibrated mean annual evapotranspiration rate was 8.8 in/yr. Simulated net streamflow gain from model layer 1 was 3.1 ft<sup>3</sup>/s.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125183","collaboration":"Prepared in cooperation with the city of Aberdeen","usgsCitation":"Marini, K.A., Hoogestraat, G., Aurand, K.R., and Putnam, L.D., 2012, Conceptual and numerical models of the glacial aquifer system north of Aberdeen, South Dakota: U.S. Geological Survey Scientific Investigations Report 2012-5183, x, 98 p., https://doi.org/10.3133/sir20125183.","productDescription":"x, 98 p.","numberOfPages":"112","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":263092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5183.gif"},{"id":263090,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5183/"},{"id":263091,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5183/sir2012-5183.pdf"}],"scale":"100000","projection":"Universal Transverse Mercator projection, Zone 14 North","country":"United States","state":"South Dakota","city":"Aberdeen","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.67,45.583 ], [ -98.67,45.25 ], [ -98.17,45.25 ], [ -98.17,45.583 ], [ -98.67,45.583 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50a3b9c0e4b0855e233c0702","contributors":{"authors":[{"text":"Marini, Katrina A.","contributorId":90181,"corporation":false,"usgs":true,"family":"Marini","given":"Katrina","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":468841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoogestraat, Galen K.","contributorId":22442,"corporation":false,"usgs":true,"family":"Hoogestraat","given":"Galen K.","affiliations":[],"preferred":false,"id":468840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aurand, Katherine R. kaurand@usgs.gov","contributorId":2713,"corporation":false,"usgs":true,"family":"Aurand","given":"Katherine","email":"kaurand@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":468839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Putnam, Larry D. ldputnam@usgs.gov","contributorId":990,"corporation":false,"usgs":true,"family":"Putnam","given":"Larry","email":"ldputnam@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":468838,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70155289,"text":"70155289 - 2012 - Invertebrate and fish assemblage relations to dissolved oxygen minima in lowland streams of southwestern Louisiana","interactions":[],"lastModifiedDate":"2022-11-15T15:21:38.096355","indexId":"70155289","displayToPublicDate":"2012-11-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Invertebrate and fish assemblage relations to dissolved oxygen minima in lowland streams of southwestern Louisiana","docAbstract":"<div class=\"para\"><p>Dissolved oxygen (DO) concentrations in lowland streams are naturally lower than those in upland streams; however, in some regions where monitoring data are lacking, DO criteria originally established for upland streams have been applied to lowland streams. This study investigated the DO concentrations at which fish and invertebrate assemblages at 35 sites located on lowland streams in southwestern Louisiana began to demonstrate biological thresholds.</p><p>Average threshold values for taxa richness, diversity and abundance metrics were 2.6 and 2.3 mg/L for the invertebrate and fish assemblages, respectively. These thresholds are approximately twice the DO concentration that some native fish species are capable of tolerating and are comparable with DO criteria that have been recently applied to some coastal streams in Louisiana and Texas. DO minima &gt;2.5 mg/L were favoured for all but extremely tolerant taxa. Extremely tolerant taxa had respiratory adaptations that gave them a competitive advantage, and their success when DO minima were &lt;2 mg/L could be related more to reductions in competition or predation than to DO concentration directly.</p><p>DO generally had an inverse relation to the amount of agriculture in the buffer area; however, DO concentrations at sites with both low and high amounts of agriculture (including three least-disturbed sites) declined to &lt;2.5 mg/L. Thus, although DO fell below a concentration that was identified as an approximate biological threshold, sources of this condition were sometimes natural (allochthonous material) and had little relation to anthropogenic activity.</p></div>","language":"English","publisher":"Wiley","doi":"10.1002/rra.2623","usgsCitation":"Justus, B., Mize, S.V., and Kroes, D., 2012, Invertebrate and fish assemblage relations to dissolved oxygen minima in lowland streams of southwestern Louisiana: River Research and Applications, v. 30, no. 1, p. 11-28, https://doi.org/10.1002/rra.2623.","productDescription":"17 p.","startPage":"11","endPage":"28","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-021710","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":306552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"southwestern Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -93.84269601826499,\n              29.739642109173403\n            ],\n            [\n              -91.51525267091078,\n              29.568877718366423\n            ],\n            [\n              -91.52835272727444,\n              31.587517115832796\n            ],\n            [\n              -93.79466247826318,\n              31.80301091261765\n            ],\n            [\n              -93.49772786734353,\n              31.0615648200843\n            ],\n            [\n              -93.85142938917427,\n              29.735850494713688\n            ],\n            [\n              -93.84269601826499,\n              29.739642109173403\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"30","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2012-11-12","publicationStatus":"PW","scienceBaseUri":"55c9cb35e4b08400b1fdb715","contributors":{"authors":[{"text":"Justus, B. G. 0000-0002-3458-9656 bjustus@usgs.gov","orcid":"https://orcid.org/0000-0002-3458-9656","contributorId":2052,"corporation":false,"usgs":true,"family":"Justus","given":"B. G.","email":"bjustus@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":565497,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mize, Scott V. 0000-0001-6751-5568 svmize@usgs.gov","orcid":"https://orcid.org/0000-0001-6751-5568","contributorId":2997,"corporation":false,"usgs":true,"family":"Mize","given":"Scott","email":"svmize@usgs.gov","middleInitial":"V.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":567674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":567675,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040697,"text":"sir20125178 - 2012 - Bankfull-channel geometry and discharge curves for the Rocky Mountains Hydrologic Region in Wyoming","interactions":[],"lastModifiedDate":"2012-11-09T14:45:25","indexId":"sir20125178","displayToPublicDate":"2012-11-09T00:00:00","publicationYear":"2012","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":"2012-5178","title":"Bankfull-channel geometry and discharge curves for the Rocky Mountains Hydrologic Region in Wyoming","docAbstract":"Regional curves relate bankfull-channel geometry and bankfull discharge to drainage area in regions with similar runoff characteristics and are used to estimate the bankfull discharge and bankfull-channel geometry when the drainage area of a stream is known. One-variable, ordinary least-squares regressions relating bankfull discharge, cross-sectional area, bankfull width, and bankfull mean depth to drainage area were developed from data collected at 35 streamgages in or near Wyoming. Watersheds draining to these streamgages are within the Rocky Mountains Hydrologic Region of Wyoming and neighboring states.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125178","collaboration":"Prepared in cooperation with the Wyoming Department of Environmental Quality, Wyoming Game and Fish Department, and the U.S. Department of Agriculture Forest Service, Region 2","usgsCitation":"Foster, K., 2012, Bankfull-channel geometry and discharge curves for the Rocky Mountains Hydrologic Region in Wyoming: U.S. Geological Survey Scientific Investigations Report 2012-5178, iv, 20 p., https://doi.org/10.3133/sir20125178.","productDescription":"iv, 20 p.","numberOfPages":"27","costCenters":[{"id":684,"text":"Wyoming Water Science Center","active":false,"usgs":true}],"links":[{"id":263072,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5178.gif"},{"id":263070,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5178/"},{"id":263071,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5178/sir2012-5178.pdf"}],"scale":"2000000","projection":"Albers Equal-area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Colorado;Montana;Wyoming","otherGeospatial":"Rocky Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.0,40.0 ], [ -112.0,45.5 ], [ -104.0,45.5 ], [ -104.0,40.0 ], [ -112.0,40.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"509e25e7e4b0cbd9af3af6fd","contributors":{"authors":[{"text":"Foster, Katharine","contributorId":38664,"corporation":false,"usgs":true,"family":"Foster","given":"Katharine","email":"","affiliations":[],"preferred":false,"id":468810,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040691,"text":"sir20125240 - 2012 - Concentrations, loads, and yields of select constituents from major tributaries of the Mississippi and Missouri Rivers in Iowa, water years 2004-2008","interactions":[],"lastModifiedDate":"2012-11-09T09:11:28","indexId":"sir20125240","displayToPublicDate":"2012-11-09T00:00:00","publicationYear":"2012","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":"2012-5240","title":"Concentrations, loads, and yields of select constituents from major tributaries of the Mississippi and Missouri Rivers in Iowa, water years 2004-2008","docAbstract":"Excess nutrients, suspended-sediment loads, and the presence of pesticides in Iowa rivers can have deleterious effects on water quality in State streams, downstream major rivers, and the Gulf of Mexico. Fertilizer and pesticides are used to support crop growth on Iowa's highly productive agricultural landscape and for household and commercial lawns and gardens. Water quality was characterized near the mouths of 10 major Iowa tributaries to the Mississippi and Missouri Rivers from March 2004 through September 2008. Stream loads were calculated for select ions, nutrients, and sediment using approximately monthly samples, and samples from storm and snowmelt events. Water-quality samples collected using standard streamflow-integrated protocols were analyzed for major ions, nutrients, carbon, pesticides, and suspended sediment. Statistical data summaries of sample data used parametric and nonparametric techniques to address potential bias related to censored data and multiple levels of censoring of data below analytical detection limits. Constituent stream loads were computed using standard pre-defined models in S-LOADEST that include streamflow and time terms plus additional terms for streamflow variability and streamflow anomalies. Streamflow variability terms describe the difference in streamflow from recent average conditions, whereas streamflow anomaly terms account for deviations from average conditions from long- to short-term sequentially. Streamflow variability or anomaly terms were included in 44 of 80 site/constituent individual models, demonstrating the usefulness of these terms in increasing accuracy of the load estimates. Constituent concentrations in Iowa streams exhibit streamflow, seasonal, and spatial patterns related to the landform and climate gradients across the studied basins. The streamflow-concentration relation indicated dilution for ions such as chloride and sulfate. Other constituent concentrations, such as dissolved organic carbon and suspended sediment, increased with streamflow. Nitrogen concentrations (total nitrogen and nitrate plus nitrite) increased with low and moderate streamflows, but decreased with high streamflows. Seasonal patterns observed in constituent concentrations were affected by streamflow, algae blooms, and pesticide application. The various landform regions produced different water-quality responses across the study basins; for example, total phosphorus, suspended sediment, and turbidity were greatest from the steep, loess-dominated southwestern Iowa basins. Nutrient concentrations, though not regulated for drinking water at the study sites, were high compared to drinking-water limits and criteria for protection of aquatic life proposed for other Midwestern states (Iowa criteria for aquatic life have not been proposed). Nitrate plus nitrite concentrations exceeded the drinking-water limit [10 milligrams per liter (mg/L)] in 11 percent of all samples at the 10 sites, and exceeded Minnesota's proposed aquatic life criteria (4.9 mg/L) in 68 percent of samples. The Wisconsin standard for total phosphorus (0.1 mg/L) was exceeded in 92 percent of samples. Ammonia standards, current during sample collection and at publication of this report, for protection of aquatic life were met for all samples, but draft criteria proposed in 2009 to protect more sensitive species like mussels, were exceeded at three sites. Loads and yields also differed among sites and years. The Big Sioux, Little Sioux, and Des Moines Rivers produced the greatest sulfate yields. Mississippi River tributaries had greater chloride yields than Missouri River tributaries. The Big Sioux River also had the lowest silica yields and total nitrogen and nitrate yields, whereas nitrogen yields were greater in the northeastern rivers. The Boyer and Nishnabotna River total phosphorus yields were the greatest in the study. The Boyer River orthophosphate yields were greatest except in 2008, when the Maquoketa River produced the greatest yield. Rivers in southwestern Iowa's Western Loess Hills and Steeply Rolling Loess Prairie ecoregions had the greatest suspended-sediment yields, whereas the smallest yields were in the Big Sioux and Wapsipinicon Rivers. In the 10 Iowa rivers studied, combined annual total nitrogen stream transport ranged from 3.68 to 9.95 tons per square mile per year, and total phosphorus transport ranged from 0.138 to 0.570 tons per square mile per year. Six-month loads relative to fertilizer use ranged from 8 to 56 percent for nitrogen, and 1.0 to 11.1 percent for phosphorus. The smallest loads relative to fertilizer use for both nitrogen and phosphorus occurred in July-December of dry years, and the largest nitrogen and phosphorus loads relative to use were in wet years from January-June.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125240","collaboration":"In cooperation with the Iowa Department of Natural Resources","usgsCitation":"Garrett, J.D., 2012, Concentrations, loads, and yields of select constituents from major tributaries of the Mississippi and Missouri Rivers in Iowa, water years 2004-2008: U.S. Geological Survey Scientific Investigations Report 2012-5240, vi, 61 p., https://doi.org/10.3133/sir20125240.","productDescription":"vi, 61 p.","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-016631","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":263043,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5240.gif"},{"id":263042,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5240/sir2012-5240.pdf"},{"id":263039,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5240/"}],"projection":"Albers Equal-area Conic projection","country":"United States","state":"Iowa;Minnesota;South Dakota","otherGeospatial":"Mississippi River;Missouri River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.0,40.0 ], [ -97.0,46.0 ], [ -85.0,46.0 ], [ -85.0,40.0 ], [ -97.0,40.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"509e25f3e4b0cbd9af3af701","contributors":{"authors":[{"text":"Garrett, Jessica D. 0000-0002-4466-3709 jgarrett@usgs.gov","orcid":"https://orcid.org/0000-0002-4466-3709","contributorId":4229,"corporation":false,"usgs":true,"family":"Garrett","given":"Jessica","email":"jgarrett@usgs.gov","middleInitial":"D.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468799,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040694,"text":"sim3228 - 2012 - Flood-inundation maps for the Leaf River at Hattiesburg, Mississippi","interactions":[],"lastModifiedDate":"2012-11-09T11:57:32","indexId":"sim3228","displayToPublicDate":"2012-11-09T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3228","title":"Flood-inundation maps for the Leaf River at Hattiesburg, Mississippi","docAbstract":"Digital flood-inundation maps for a 1.7-mile reach of the Leaf River were developed by the U.S. Geological Survey (USGS) in cooperation with the City of Hattiesburg, City of Petal, Forrest County, Mississippi Emergency Management Agency, Mississippi Department of Homeland Security, and the Emergency Management District. The Leaf River study reach extends from just upstream of the U.S. Highway 11 crossing to just downstream of East Hardy/South Main Street and separates the cities of Hattiesburg and Petal, Mississippi. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation/\" target=\"_blank\">http://water.usgs.gov/osw/flood_inundation/</a>, depict estimates of the areal extent of flooding corresponding to selected water-surface elevations (stages) at the USGS streamgage at Leaf River at Hattiesburg, Mississippi (02473000). Current conditions at the USGS streamgage may be obtained through the National Water Information System Web site at <a href=\"http://waterdata.usgs.gov/ms/nwis/uv/?site_no=02473000&PARAmeter_cd=00065,00060\" target=\"_blank\">http://waterdata.usgs.gov/ms/nwis/uv/?site_no=02473000&PARAmeter_cd=00065,00060</a>. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood-warning system (<a href=\"http://water.weather.gov/ahps/\" target=\"_blank\">http://water.weather.gov/ahps/</a>). The NWS forecasts flood hydrographs at many places that are often collocated at USGS streamgages. The forecasted peak-stage information, available on the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relations at the Leaf River at Hattiesburg, Mississippi, streamgage and documented high-water marks from recent and historical floods. The hydraulic model was then used to determine 13 water-surface profiles for flood stages at 1.0-foot intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water-surface elevation at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model [derived from Light Detection and Ranging (LiDAR) data having a 0.6-foot vertical accuracy and 9.84-foot horizontal resolution] in order to delineate the area flooded at each 1-foot increment of stream stage. The availability of these maps, when combined with real-time stage information from USGS streamgages and forecasted stream stage from the NWS, provides emergency management personnel and residents with critical information during flood-response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3228","collaboration":"Prepared in cooperation with the City of Hattiesburg, City of Petal, Forrest County, Mississippi Emergency Management Agency, Mississippi Department of Homeland Security, and the Emergency Management District","usgsCitation":"Storm, J.B., 2012, Flood-inundation maps for the Leaf River at Hattiesburg, Mississippi: U.S. Geological Survey Scientific Investigations Map 3228, Pamphlet: vi, 8 p.; 13 Sheets: 17 x 22 inches; Downloads directory, https://doi.org/10.3133/sim3228.","productDescription":"Pamphlet: vi, 8 p.; 13 Sheets: 17 x 22 inches; Downloads directory","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"links":[{"id":263066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3228.jpg"},{"id":263052,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3228/download/"},{"id":263053,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet1.pdf"},{"id":263054,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet2.pdf"},{"id":263055,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet3.pdf"},{"id":263056,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet4.pdf"},{"id":263057,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet6.pdf"},{"id":263050,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3228/"},{"id":263051,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3228/pdf/sim_3228.pdf"},{"id":263058,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet5.pdf"},{"id":263059,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet7.pdf"},{"id":263060,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet8.pdf"},{"id":263061,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet9.pdf"},{"id":263062,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet10.pdf"},{"id":263063,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet11.pdf"},{"id":263064,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet12.pdf"},{"id":263065,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3228/sheets/sim_3228_sheet13.pdf"}],"projection":"Transverse Mercator projection","datum":"North American Datum of 1983 and North American Vergical Datum of 1988","country":"United States","state":"Mississippi","county":"Forrest County","otherGeospatial":"Leaf River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.32,31.3 ], [ -89.32,31.37 ], [ -89.25,31.37 ], [ -89.25,31.3 ], [ -89.32,31.3 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"509e2601e4b0cbd9af3af70d","contributors":{"authors":[{"text":"Storm, John B. 0000-0002-5657-536X jbstorm@usgs.gov","orcid":"https://orcid.org/0000-0002-5657-536X","contributorId":3684,"corporation":false,"usgs":true,"family":"Storm","given":"John","email":"jbstorm@usgs.gov","middleInitial":"B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468801,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040698,"text":"sir20125187 - 2012 - Simulated effects of alternative withdrawal strategies on groundwater flow in the unconfined Kirkwood-Cohansey aquifer system, the Rio Grande water-bearing zone, and the Atlantic City 800-foot sand in the Great Egg Harbor and Mullica River Basins, New Jersey","interactions":[],"lastModifiedDate":"2019-02-21T10:44:00","indexId":"sir20125187","displayToPublicDate":"2012-11-09T00:00:00","publicationYear":"2012","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":"2012-5187","title":"Simulated effects of alternative withdrawal strategies on groundwater flow in the unconfined Kirkwood-Cohansey aquifer system, the Rio Grande water-bearing zone, and the Atlantic City 800-foot sand in the Great Egg Harbor and Mullica River Basins, New Jersey","docAbstract":"Groundwater is essential for water supply and plays a critical role in maintaining the environmental health of freshwater and estuarine ecosystems in the Atlantic Coastal basins of New Jersey. The unconfined Kirkwood-Cohansey aquifer system and the confined Atlantic City 800-foot sand are major sources of groundwater in the area, and each faces different water-supply concerns. The U.S. Geological Survey (USGS), in cooperation with the New Jersey Department of Environmental Protection (NJDEP), conducted a study to simulate the effects of withdrawals in the Kirkwood-Cohansey aquifer system, the Atlantic City 800-foot sand, and the Rio Grande water-bearing zone and to evaluate potential scenarios. The study area encompasses Atlantic County and parts of Burlington, Camden, Gloucester, Ocean, Cape May, and Cumberland Counties. The major hydrogeologic units affecting water supply in the study area are the surficial Kirkwood-Cohansey aquifer system, a thick diatomaceous clay confining unit in the upper part of Kirkwood Formation; the Rio Grande water-bearing zone; and the Atlantic City 800-foot sand of the Kirkwood Formation. Hydrogeologic data from 18 aquifer tests and specific capacity data from 230 wells were analyzed to provide horizontal hydraulic conductivity of the aquifers. Groundwater withdrawals are greatest from the Kirkwood-Cohansey aquifer system, and 65 percent of the water is used for public supply. Groundwater withdrawals from the Atlantic City 800-foot sand are about half those from the Kirkwood-Cohansey aquifer system. Ninety-five percent of the withdrawals from the Atlantic City 800-foot sand is used for public supply. Data from six streamgaging stations and 51 low-flow partial record sites were used to estimate base flow in the area. Base flow ranges from 60 to 92 percent of streamflow. A groundwater flow model of the Kirkwood-Cohansey aquifer system, the Rio Grande water-bearing zone, and the Atlantic City 800-foot sand was developed and calibrated using water-level data from 148 wells and base-flow data from 22 gaging or low-flow partial record stations. The Kirkwood-Cohansey aquifer system within the Great Egg Harbor River and the Mullica River Basins was simulated on a monthly basis from 1998 through 2006. An existing regional model of the New Jersey Coastal Plain was revised to provide boundary conditions for the Great Egg Harbor and Mullica River Basin model (referred to as the Great Egg-Mullica model). In the Great Egg-Mullica model, monthly groundwater recharge rates used in the model ranged from 10-15 inches per year in 2001 to 20-25 inches per year in 2005. The mean-absolute error for 10 of the 14 long-term hydrographs used in model calibration was less than 5 ft. Groundwater flow budgets for the Great Egg-Mullica model calibration periods, May 2005 and September 2006, and for the entire model calibration period 1998 to 2006, showed that nearly 70 percent of the water entering the Atlantic City 800-foot sand came from the horizontal connection with the Kirkwood-Cohansey aquifer system in updip areas. The groundwater flow model was used to simulate scenarios under three possible conditions: average 1998 to 2006 withdrawals (Average scenario), full-allocation withdrawals (Full Allocation scenario), and projected 2050-demand withdrawals (2050 Demand scenario). Withdrawals in the Full Allocation scenario are nearly twice the withdrawals from the Average scenario, primarily because of the potential for large agricultural withdrawals if all allocations are used. Withdrawals for the 2050 Demand scenario are about 50 percent greater than those for the Average scenario, primarily due to expected increases in withdrawals for public supply. Monthly base-flow depletion criteria were determined using the Low-Flow Margin method, currently under consideration by NJDEP, to estimate available water on an annual basis at the Hydrologic Unit Code 11 (HUC11) level and to determine whether a water-supply deficit exists. Simulations of various groundwater-withdrawal scenarios were made using the calibrated model, and results were compared with baseline conditions (no withdrawals) to determine where and when base-flow deficits may be occurring and may be expected to occur in the future. Scenarios were simulated to assess base-flow depletion that could occur from different groundwater-withdrawal situations. In the Average scenario, deficits occurred in 7 of the 14 subbasins. In the Full Allocation scenario, deficits occurred in 11 of the subbasins. In the 2050 Demand scenario, deficits occurred in 9 of the 14 subbasins. The largest deficits occurred in the Absecon Creek subbasin because the base-flow depletion criteria for this subbasin is small due to the surface-water diversions that are already occurring there and because existing groundwater withdrawals in the subbasin have resulted in base-flow depletion under current (1998-2006) conditions. Three adjusted scenarios, variations of the Average, Full Allocation, and 2050 Demand scenarios, were simulated; for the adjusted scenarios, the withdrawals were modified in stages with the intent to successively eliminate or minimize the base-flow deficits. Modifications included shifting withdrawals to a deeper part of the Kirkwood-Cohansey aquifer system, implementing seasonal conjunctive use of shallow and deep aquifers, and specifying reductions in withdrawals within a HUC11 subbasin in deficit. The adjusted scenarios are intended to show the relative effectiveness of each of the three approaches in reducing the deficits. Most of the deficits under the Average, Full Allocation, and 2050 Demand scenarios were eliminated by reductions in withdrawals or allocations. Shifting withdrawals to a deeper part of the Kirkwood-Cohansey aquifer system or seasonal conjunctive use did not eliminate deficits for any subbasin. Reductions in withdrawals accounted for more than 95 percent of the total reduction of deficits in all but one subbasin.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125187","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Pope, D.A., Carleton, G.B., Buxton, D.E., Walker, R.L., Shourds, J.L., and Reilly, P.A., 2012, Simulated effects of alternative withdrawal strategies on groundwater flow in the unconfined Kirkwood-Cohansey aquifer system, the Rio Grande water-bearing zone, and the Atlantic City 800-foot sand in the Great Egg Harbor and Mullica River Basins, New Jersey: U.S. Geological Survey Scientific Investigations Report 2012-5187, Report: x, 139 p.; Appendixes: 2-3, https://doi.org/10.3133/sir20125187.","productDescription":"Report: x, 139 p.; Appendixes: 2-3","numberOfPages":"153","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":263087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5187.png"},{"id":263086,"rank":0,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5187/support/sir2012-5187-appendix3.xls","text":"Appendix 3","linkFileType":{"id":3,"text":"xlsx"}},{"id":263083,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5187/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":263084,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5187/support/sir2012-5187.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}},{"id":263085,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5187/support/sir2012-5187-appendix2.xls","text":"Appendix 2","linkFileType":{"id":3,"text":"xlsx"}},{"id":361403,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70G3J3J","text":"MODFLOW-2000 model used to evaluate alternative withdrawal strategies on groundwater flow in the unconfined Kirkwood-Cohansey aquifer system, the Rio Grande water-bearing zone, and the Atlantic City 800-foot sand in the Great Egg Harbor and Mullica River Basins, New Jersey"}],"scale":"24000","country":"United States","state":"New Jersey","otherGeospatial":"Great Egg Harbor;Mullica River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.5,39.0 ], [ -75.5,40.25 ], [ -73.75,40.25 ], [ -73.75,39.0 ], [ -75.5,39.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"509e2607e4b0cbd9af3af711","contributors":{"authors":[{"text":"Pope, Daryll A. dpope@usgs.gov","contributorId":3796,"corporation":false,"usgs":true,"family":"Pope","given":"Daryll","email":"dpope@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":468813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carleton, Glen B. 0000-0002-7666-4407 carleton@usgs.gov","orcid":"https://orcid.org/0000-0002-7666-4407","contributorId":3795,"corporation":false,"usgs":true,"family":"Carleton","given":"Glen","email":"carleton@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":468812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buxton, Debra E. dbuxton@usgs.gov","contributorId":4777,"corporation":false,"usgs":true,"family":"Buxton","given":"Debra","email":"dbuxton@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":468814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walker, Richard L.","contributorId":38961,"corporation":false,"usgs":true,"family":"Walker","given":"Richard","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":468816,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shourds, Jennifer L. 0000-0002-7631-9734 jshourds@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-9734","contributorId":5821,"corporation":false,"usgs":true,"family":"Shourds","given":"Jennifer","email":"jshourds@usgs.gov","middleInitial":"L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reilly, Pamela A. 0000-0002-2937-4490 jankowsk@usgs.gov","orcid":"https://orcid.org/0000-0002-2937-4490","contributorId":653,"corporation":false,"usgs":true,"family":"Reilly","given":"Pamela","email":"jankowsk@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468811,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70040798,"text":"70040798 - 2012 - Mapping the potential distribution of the invasive Red Shiner, Cyprinella lutrensis (Teleostei: Cyprinidae) across waterways of the conterminous United States","interactions":[],"lastModifiedDate":"2012-11-19T12:00:46","indexId":"70040798","displayToPublicDate":"2012-11-09T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Mapping the potential distribution of the invasive Red Shiner, Cyprinella lutrensis (Teleostei: Cyprinidae) across waterways of the conterminous United States","docAbstract":"Predicting the future spread of non-native aquatic species continues to be a high priority for natural resource managers striving to maintain biodiversity and ecosystem function. Modeling the potential distributions of alien aquatic species through spatially explicit mapping is an increasingly important tool for risk assessment and prediction. Habitat modeling also facilitates the identification of key environmental variables influencing species distributions. We modeled the potential distribution of an aggressive invasive minnow, the red shiner (Cyprinella lutrensis), in waterways of the conterminous United States using maximum entropy (Maxent). We used inventory records from the USGS Nonindigenous Aquatic Species Database, native records for C. lutrensis from museum collections, and a geographic information system of 20 raster climatic and environmental variables to produce a map of potential red shiner habitat. Summer climatic variables were the most important environmental predictors of C. lutrensis distribution, which was consistent with the high temperature tolerance of this species. Results from this study provide insights into the locations and environmental conditions in the US that are susceptible to red shiner invasion.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Aquatic Invasions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"REABIC","publisherLocation":"Helsinki, Finland","doi":"10.3391/ai.2012.7.3.009","usgsCitation":"Poulos, H.M., Chernoff, B., Fuller, P., and Butman, D., 2012, Mapping the potential distribution of the invasive Red Shiner, Cyprinella lutrensis (Teleostei: Cyprinidae) across waterways of the conterminous United States: Aquatic Invasions, v. 7, no. 3, p. 377-385, https://doi.org/10.3391/ai.2012.7.3.009.","productDescription":"9 p.","startPage":"377","endPage":"385","ipdsId":"IP-035517","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":474273,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2012.7.3.009","text":"Publisher Index Page"},{"id":263264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263263,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3391/ai.2012.7.3.009"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01611111111111111,5.555555555555556E-4 ], [ -0.01611111111111111,0.0011111111111111111 ], [ -67,0.0011111111111111111 ], [ -67,5.555555555555556E-4 ], [ -0.01611111111111111,5.555555555555556E-4 ] ] ] } } ] }","volume":"7","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50abfc1ce4b0afbc75eb985e","contributors":{"authors":[{"text":"Poulos, Helen M.","contributorId":75271,"corporation":false,"usgs":true,"family":"Poulos","given":"Helen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":469049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chernoff, Barry","contributorId":25701,"corporation":false,"usgs":true,"family":"Chernoff","given":"Barry","email":"","affiliations":[],"preferred":false,"id":469047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Pam L. 0000-0002-9389-9144","orcid":"https://orcid.org/0000-0002-9389-9144","contributorId":91226,"corporation":false,"usgs":true,"family":"Fuller","given":"Pam L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":469050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butman, David","contributorId":51011,"corporation":false,"usgs":true,"family":"Butman","given":"David","affiliations":[],"preferred":false,"id":469048,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040672,"text":"ofr20121182 - 2012 - Predicting sea-level rise vulnerability of terrestrial habitat and wildlife of the Northwestern Hawaiian Islands","interactions":[],"lastModifiedDate":"2018-04-24T14:23:16","indexId":"ofr20121182","displayToPublicDate":"2012-11-08T00:00:00","publicationYear":"2012","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":"2012-1182","title":"Predicting sea-level rise vulnerability of terrestrial habitat and wildlife of the Northwestern Hawaiian Islands","docAbstract":"If current climate change trends continue, rising sea levels may inundate low-lying islands across the globe, placing island biodiversity at risk. Recent models predict a rise of approximately one meter (1 m) in global sea level by 2100, with larger increases possible in areas of the Pacific Ocean. Pacific Islands are unique ecosystems home to many endangered endemic plant and animal species. The Northwestern Hawaiian Islands (NWHI), which extend 1,930 kilometers (km) beyond the main Hawaiian Islands, are a World Heritage Site and part of the Papahanaumokuakea Marine National Monument. These NWHI support the largest tropical seabird rookery in the world, providing breeding habitat for 21 species of seabirds, 4 endemic land bird species and essential foraging, breeding, or haul-out habitat for other resident and migratory wildlife. In recent years, concern has grown about the increasing vulnerability of the NWHI and their wildlife populations to changing climatic patterns, particularly the uncertainty associated with potential impacts from global sea-level rise (SLR) and storms. In response to the need by managers to adapt future resource protection strategies to climate change variability and dynamic island ecosystems, we have synthesized and down scaled analyses for this important region. This report describes a 2-year study of a remote northwestern Pacific atoll ecosystem and identifies wildlife and habitat vulnerable to rising sea levels and changing climate conditions. A lack of high-resolution topographic data for low-lying islands of the NWHI had previously precluded an extensive quantitative model of the potential impacts of SLR on wildlife habitat. The first chapter (chapter 1) describes the vegetation and topography of 20 islands of Papahanaumokuakea Marine National Monument, the distribution and status of wildlife populations, and the predicted impacts for a range of SLR scenarios. Furthermore, this chapter explores the potential effects of SLR on wildlife breeding habitats for each island. The subsequent chapter (chapter 2) details a study of the Laysan Island ecosystem, describing a quantitative model that incorporates SLR, storm wave, and rising groundwater inundation. Wildlife, storm, and oceanographic data allowed for an assessment of the phenological and spatial vulnerability of Laysan Island's breeding bird species to SLR and storms. Using remote sensing and geospatial techniques, we estimated topography, classified vegetation, modeled SLR, and evaluated a range of climate change scenarios. On the basis of high-resolution airborne data collected during 2010-11 (root-mean-squared error = 0.05-0.18 m), we estimated the maximum elevation of 20 individual islands extending from Kure Atoll to French Frigate Shoals (range: 1.8-39.7 m) and computed the mean elevation (1.7 m, standard deviation 1.1 m) across all low-lying islands. We also analyzed general climate models to describe rainfall and temperature scenarios expected to influence adaptation of some plants and animals for this region. Outcomes for the NWHI predicted an increase in temperature of 1.8-2.6 degrees Celsius (&deg;C) and an annual decrease in precipitation of 24.7-76.3 millimeters (mm) across the NWHI by 2100. Our models of passive SLR (excluding wave-driven effects, erosion, and accretion) showed that approximately 4 percent of the total land area in the NWHI will be lost with scenarios of +1.0 m of SLR and 26 percent will be lost with +2.0 m of SLR. Some atolls are especially vulnerable to SLR. For example, at Pearl and Hermes Atoll our analysis indicated substantial habitat losses with 43 percent of the land area inundated at +1.0 m SLR and 92 percent inundated at +2.0 m SLR. Across the NWHI, seven islands will be completely submerged with +2.0 m SLR. The limited global ranges of some tropical nesting birds make them particularly vulnerable to climate change impacts in the NWHI. Climate change scenarios and potential SLR impacts presented here emphasize the need for early climate change adaptation and mitigation planning, especially for species with limited breeding distributions and/or ranges restricted primarily to the low-lying NWHI: <i>Cyperus pennatiformis</i> var. <i>bryanii</i>, Black-footed Albatross (<i>Phoebastria nigripes</i>), Laysan Albatross (<i>P. immutabilis</i>), Bonin Petrel (<i>Pterodroma hypoleuca</i>), Gray-backed Tern (<i>Onychoprion lunatus</i>), Laysan Teal (<i>Anas laysanensis</i>), Laysan Finch (<i>Telespiza cantans</i>), and Hawaiian monk seal (<i>Monachus schauinslandi</i>). Furthermore, SLR scenarios that include the effects of wave dynamics and groundwater rise may indicate amplified vulnerability to climate change driven habitat loss on low-lying islands. In chapter 2, we incorporated the combined effects of SLR, dynamic wave-driven inundation, and rising groundwater in a quantitative study specifically for the Laysan Island ecosystem. This is the first hydrodynamic model to simulate the combined impacts of SLR and wave-driven inundation in the NWHI. We developed a high-resolution digital elevation model (mean vertical accuracy of 0.32 m) for the island. Then using recent satellite imagery, geospatial models, and historical oceanographic, storm, and biological data we estimated potential inundation extent, habitat loss, and wildlife population impacts for a range of potential SLR scenarios (0.00, +0.50, +1.00, +1.50, and +2.00 m) that may occur over the next century. Additionally, we estimated the carrying capacity of Laysan Island for five species based on the available population monitoring data and described how potential losses in nesting habitat could influence population dynamics for Black-footed Albatross, Laysan Albatross, Red-footed Booby (Sula sula), Laysan Teal, and Laysan Finch. For some other seabird populations (Masked Booby, <i>S. dactylatra</i>; Brown Booby, <i>S. leucogaster</i>; Great Frigatebird, <i>Fregata minor</i>; and Sooty Tern, <i>Onychoprion fuscata</i>), we used recent colony distribution data, land cover maps, and nesting behavior to estimate potential losses of nesting habitat from SLR and wave-driven inundation. We observed far greater potential impacts of SLR to wildlife with the dynamic wave-driven modeling approach than with the passive modeling approach. Depending on SLR scenario and coastal orientation, during storms under a +2.00 m SLR scenario, the wave-driven inundation model predicted three times more inundation than the passive model (17.2 percent of total terrestrial area versus 4.6 percent, respectively). Large-wave events generally added 1 m of water height to passive inundation surfaces, therefore our dynamic models (during storm events) forecasted comparable inundation extents earlier than passive models. Although wave-driven water levels were highest in the northwest quadrant of Laysan Island, the greatest extent of inundation occurred in the southeast where coastal dunes less than 3 m above mean sea level provide little protection from wave-driven inundation. When wave-driven inundation was included in the SLR model for Laysan Island greater nesting habitat loss and potential impacts on wildlife population dynamics were predicted. The consequences of habitat loss due to SLR may be worse for species with colonies in the wave-exposed coastal zones (for example, Black-footed Albatross) and for populations already near the island's carrying capacity (for example, Laysan Teal). Species whose peak incubation and chick-rearing periods coincide with seasonally high wave heights also will be increasingly vulnerable, especially those species nesting on the ground in areas vulnerable to inundation, such as Gray-backed Tern and Black-footed Albatross. Other species that have space for population growth, or are not restricted to a narrow range of habitat types on Laysan (for instance, Sooty Terns), may be less sensitive to habitat loss from SLR over the next century. Our assessments of inundation risk, habitat loss, and wildlife species vulnerability synthesize current knowledge about individual islands and contribute to a broader understanding of the impacts of inundation from SLR and storm-induced waves. Yet, most NWHI and their bird populations lack monitoring data to evaluate adaptations to and impacts of climate change. Exceptions include some data sets from long-term monitoring of wildlife populations, tides, or weather at French Frigate Shoals, Laysan Island, and Midway Atoll. These data sets are potentially valuable baselines, which could be informative for adaptive learning (integrating management and science) to predict, adapt, and mitigate the effects of climate change on NWHI wildlife in the future. This study provides the first quantitative vulnerability assessment for all of the low-lying NWHI, and results identify biological communities, locales, and resident endangered species of Papahanaumokuakea Marine National Monument expected to be at risk from SLR. This report is also intended as a reference for managers and conservation planners, a tool to identify and potentially reduce uncertainty, and a starting place for developing climate change monitoring priorities and future scientific studies.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121182","collaboration":"Chapter 1: Climate change vulnerability assessment of the low-lying northwestern Hawaiian Islands; Chapter 2: Sea-level rise and wave-driven inundation models for Laysan Island","usgsCitation":"Reynolds, M.H., Berkowitz, P., Courtot, K., and Krause, C.M., 2012, Predicting sea-level rise vulnerability of terrestrial habitat and wildlife of the Northwestern Hawaiian Islands: U.S. Geological Survey Open-File Report 2012-1182, ix, 139 p., https://doi.org/10.3133/ofr20121182.","productDescription":"ix, 139 p.","numberOfPages":"153","onlineOnly":"Y","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":438807,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P5WHVH","text":"USGS data release","linkHelpText":"Northwestern Hawaiian Islands Sea-level Rise Scenarios and Models 2010-2015"},{"id":263022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1182.gif"},{"id":263021,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1182/of2012-1182.pdf"},{"id":263020,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1182/"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,10.0 ], [ -180.0,33.0 ], [ -150.0,33.0 ], [ -150.0,10.0 ], [ -180.0,10.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"509cf2bce4b0e374086f468b","contributors":{"editors":[{"text":"Reynolds, Michelle H. 0000-0001-7253-8158 mreynolds@usgs.gov","orcid":"https://orcid.org/0000-0001-7253-8158","contributorId":3871,"corporation":false,"usgs":true,"family":"Reynolds","given":"Michelle","email":"mreynolds@usgs.gov","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":509100,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Berkowitz, Paul pberkowitz@usgs.gov","contributorId":4642,"corporation":false,"usgs":true,"family":"Berkowitz","given":"Paul","email":"pberkowitz@usgs.gov","affiliations":[],"preferred":true,"id":509101,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Courtot, Karen N.","contributorId":26909,"corporation":false,"usgs":true,"family":"Courtot","given":"Karen N.","affiliations":[],"preferred":false,"id":509102,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Krause, Crystal M.","contributorId":101919,"corporation":false,"usgs":true,"family":"Krause","given":"Crystal","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":509103,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Reynolds, Michelle H. 0000-0001-7253-8158 mreynolds@usgs.gov","orcid":"https://orcid.org/0000-0001-7253-8158","contributorId":3871,"corporation":false,"usgs":true,"family":"Reynolds","given":"Michelle","email":"mreynolds@usgs.gov","middleInitial":"H.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":468766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berkowitz, Paul pberkowitz@usgs.gov","contributorId":4642,"corporation":false,"usgs":true,"family":"Berkowitz","given":"Paul","email":"pberkowitz@usgs.gov","affiliations":[],"preferred":true,"id":468767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Courtot, Karen N.","contributorId":26909,"corporation":false,"usgs":true,"family":"Courtot","given":"Karen N.","affiliations":[],"preferred":false,"id":468768,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krause, Crystal M.","contributorId":101919,"corporation":false,"usgs":true,"family":"Krause","given":"Crystal","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":468769,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040679,"text":"fs20123126 - 2012 - Mapping grasslands suitable for cellulosic biofuels in the Greater Platte River Basin, United States","interactions":[],"lastModifiedDate":"2012-11-08T14:38:17","indexId":"fs20123126","displayToPublicDate":"2012-11-08T00:00:00","publicationYear":"2012","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":"2012-3126","title":"Mapping grasslands suitable for cellulosic biofuels in the Greater Platte River Basin, United States","docAbstract":"Biofuels are an important component in the development of alternative energy supplies, which is needed to achieve national energy independence and security in the United States. The most common biofuel product today in the United States is corn-based ethanol; however, its development is limited because of concerns about global food shortages, livestock and food price increases, and water demand increases for irrigation and ethanol production. Corn-based ethanol also potentially contributes to soil erosion, and pesticides and fertilizers affect water quality. Studies indicate that future potential production of cellulosic ethanol is likely to be much greater than grain- or starch-based ethanol. As a result, economics and policy incentives could, in the near future, encourage expansion of cellulosic biofuels production from grasses, forest woody biomass, and agricultural and municipal wastes. If production expands, cultivation of cellulosic feedstock crops, such as switchgrass (<i>Panicum virgatum L.</i>) and miscanthus (<i>Miscanthus species</i>), is expected to increase dramatically. The main objective of this study is to identify grasslands in the Great Plains that are potentially suitable for cellulosic feedstock (such as switchgrass) production. Producing ethanol from noncropland holdings (such as grassland) will minimize the effects of biofuel developments on global food supplies. Our pilot study area is the Greater Platte River Basin, which includes a broad range of plant productivity from semiarid grasslands in the west to the fertile corn belt in the east. The Greater Platte River Basin was the subject of related U.S. Geological Survey (USGS) integrated research projects.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123126","usgsCitation":"Wylie, B.K., and Gu, Y., 2012, Mapping grasslands suitable for cellulosic biofuels in the Greater Platte River Basin, United States: U.S. Geological Survey Fact Sheet 2012-3126, 2 p., https://doi.org/10.3133/fs20123126.","productDescription":"2 p.","numberOfPages":"2","ipdsId":"IP-038945","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":263031,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3126/"},{"id":263032,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3126/FS2012-3126.pdf"},{"id":263033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3126.gif"}],"country":"United States","state":"Colorado;Nebraska;South Dakota;Wyoming","otherGeospatial":"Greater Platte River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.790000,38.570000 ], [ -107.790000,44.450000 ], [ -95.310000,44.450000 ], [ -95.310000,38.570000 ], [ -107.790000,38.570000 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"509cf293e4b0e374086f467b","contributors":{"authors":[{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":468783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":409,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":468782,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040651,"text":"ofr20121222 - 2012 - Microbial source tracking markers at three inland recreational lakes in Ohio, 2011","interactions":[],"lastModifiedDate":"2012-11-07T10:33:02","indexId":"ofr20121222","displayToPublicDate":"2012-11-07T00:00:00","publicationYear":"2012","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":"2012-1222","title":"Microbial source tracking markers at three inland recreational lakes in Ohio, 2011","docAbstract":"During the 2011 recreational season, samples were collected for <i>E. coli</i> and microbial source tracking (MST) marker concentrations to begin to understand potential sources of fecal contamination at three inland recreational lakes in Ohio - Buckeye, Atwood, and Tappan Lakes. The results from 32 regular samples, 4 field blanks, and 7 field replicates collected at 5 sites are presented in this report. At the three lakes, the ruminant-associated marker was found most often (57-73 percent of samples) but at estimated quantities, followed by the dog-associated marker (30-43 percent of samples). The human-associated marker was found in 14 and 50 percent of samples from Atwood and Tappan Lakes, respectively, but was not found in any samples from the two Buckeye Lake sites. The gull-associated marker was detected in only two samples, both from Tappan Lake.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121222","collaboration":"Prepared in cooperation with the Ohio Water Development Authority and Muskingum Watershed Conservancy District","usgsCitation":"Francy, D.S., and Stelzer, E.A., 2012, Microbial source tracking markers at three inland recreational lakes in Ohio, 2011: U.S. Geological Survey Open-File Report 2012-1222, iv, 8 p., https://doi.org/10.3133/ofr20121222.","productDescription":"iv, 8 p.","numberOfPages":"16","onlineOnly":"Y","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":262981,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1222/"},{"id":262982,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1222/pdf/ofr2012-1222.pdf"},{"id":262983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1222.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Atwood Lake;Buckeye Lake;Tappan Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.0,39.75 ], [ -83.0,41.0 ], [ -80.75,41.0 ], [ -80.75,39.75 ], [ -83.0,39.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e03f5de4b0fec3206eb4e5","contributors":{"authors":[{"text":"Francy, Donna S. 0000-0001-9229-3557 dsfrancy@usgs.gov","orcid":"https://orcid.org/0000-0001-9229-3557","contributorId":1853,"corporation":false,"usgs":true,"family":"Francy","given":"Donna","email":"dsfrancy@usgs.gov","middleInitial":"S.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468717,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stelzer, Erin A. 0000-0001-7645-7603 eastelzer@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":1933,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin","email":"eastelzer@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468718,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040649,"text":"cir1379 - 2012 - The United States National Climate Assessment - Alaska Technical Regional Report","interactions":[],"lastModifiedDate":"2012-11-08T08:41:59","indexId":"cir1379","displayToPublicDate":"2012-11-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1379","title":"The United States National Climate Assessment - Alaska Technical Regional Report","docAbstract":"The Alaskan landscape is changing, both in terms of effects of human activities as a consequence of increased population, social and economic development and their effects on the local and broad landscape; and those effects that accompany naturally occurring hazards such as volcanic eruptions, earthquakes, and tsunamis. Some of the most prevalent changes, however, are those resulting from a changing climate, with both near term and potential upcoming effects expected to continue into the future. Alaska's average annual statewide temperatures have increased by nearly 4&deg;F from 1949 to 2005, with significant spatial variability due to the large latitudinal and longitudinal expanse of the State. Increases in mean annual temperature have been greatest in the interior region, and smallest in the State's southwest coastal regions. In general, however, trends point toward increases in both minimum temperatures, and in fewer extreme cold days. Trends in precipitation are somewhat similar to those in temperature, but with more variability. On the whole, Alaska saw a 10-percent increase in precipitation from 1949 to 2005, with the greatest increases recorded in winter. The National Climate Assessment has designated two well-established scenarios developed by the Intergovernmental Panel on Climate Change (Nakicenovic and others, 2001) as a minimum set that technical and author teams considered as context in preparing portions of this assessment. These two scenarios are referred to as the Special Report on Emissions Scenarios A2 and B1 scenarios, which assume either a continuation of recent trends in fossil fuel use (A2) or a vigorous global effort to reduce fossil fuel use (B1). Temperature increases from 4 to 22&deg;F are predicted (to 2070-2099) depending on which emissions scenario (A2 or B1) is used with the least warming in southeast Alaska and the greatest in the northwest. Concomitant with temperature changes, by the end of the 21st century the growing season is expected to lengthen by 15-25 days in some areas of Alaska, with much of that corresponding with earlier spring snow melt. Future projections of precipitation (30-80 years) over Alaska show an increase across the State, with the largest changes in the northwest and smallest in the southeast. Because of increasing temperatures and growing season length, however, increased precipitation may not correspond with increased water availability, due to temperature related increased evapotranspiration. The extent of snow cover in the Northern Hemisphere has decreased by about 10 percent since the late 1960s, with stronger trends noted since the late 1980s. Alaska has experienced similar trends, with a strong decrease in snow cover extent occurring in May. When averaged across the State, the disappearance of snow in the spring has occurred from 4 to 6 days earlier per decade, and snow return in fall has occurred approximately 2 days later per decade. This change appears to be driven by climate warming rather than a decrease in winter precipitation, with average winter temperatures also increasing by about 2.5&deg;F. The extent of sea ice has been declining, as has been widely published in both national and scientific media outlets, and is projected to continue to decline during this century. The observed decline in annual sea ice minimum extent (September) has occurred more rapidly than was predicted by climate models and has been accompanied by decreases in ice thickness and in the presence of multi-year ice. This decrease was first documented by satellite imagery in the late 1970s for the Bering and Chukchi Seas, and is projected to continue, with the potential for the disappearance of summer sea ice by mid- to late century. A new phenomenon that was not reported in previous assessments is ocean acidification. Uptake of carbon dioxide (CO2) by oceans has a significant effect on marine biogeochemistry by reducing seawater pH. Ocean acidification is of particular concern in Alaska, because cold sea water absorbs CO2 more rapidly than warm water, and a decrease in sea ice extent has allowed increased sea surface exposure and more uptake of CO2 into these northern waters. Ocean acidification will likely affect the ability of organisms to produce and maintain shell material, such as aragonite or calcite (calcium carbonate minerals structured from carbonate ions), required by many shelled organism, from mollusks to corals to microscopic organisms at the base of the food chain. Direct biological effects in Alaska further along the food chain have yet to be studied and may vary among organisms. Some of the potentially most significant changes to Alaska that could result from a changing climate are the effects on the terrestrial cryosphere - particularly glaciers and permafrost. Alaskan glaciers are changing at a rapid rate, the primary driver appearing to be temperature. Statewide, glaciers lost 13 cubic miles of ice annually from the 1950s to the 1990s, and that rate doubled in the 2000s. However, like temperature and precipitation, glacier ice loss is not spatially uniform; most glaciers are losing mass, yet some are growing (for example Hubbard Glacier in southeast Alaska). Alaska glaciers with the most rapid loss are those terminating in sea water or lakes. With this increasing rate of melt, the contribution of surplus fresh water entering into the oceans from Alaska's glaciers, as well as those in neighboring British Columbia, Canada, is approximately 20 percent of that contributed by the Greenland Ice Sheet. Permafrost degradation (that is, the thawing of ice-rich soils) is currently (2012) impacting infrastructure and surface-water availability in areas of both discontinuous and continuous ground ice. Over most of the State, the permafrost is warming, with increasing temperatures broadly consistent with increasing air temperatures. On the Arctic coastal plain of Alaska, permafrost temperatures showed some cooling in the 1950s and 1960s but have been followed by a roughly 5&deg;F increase since the 1980s. Many areas in the continuous permafrost zone have seen increases in temperature in the seasonally active layer and a decrease in re-freezing rates. Changes in the discontinuous permafrost zone are initially much more observable due to the resulting thermokarst terrain (land surface formed as ice rich permafrost thaws), most notable in boreal forested areas. Climate warming in Alaska has potentially broad implications for human health and food security, especially in rural areas, as well as increased risk for injury with changing winter ice conditions. Additionally, such warming poses the potential for increasing damage to existing water and sanitation facilities and challenges for development of new facilities, especially in areas underlain by permafrost. Non-infectious and infectious diseases also are becoming an increasing concern. For example, from 1999 to 2006 there was a statistically significant increase in medical claims for insectbite reactions in five of six regions of Alaska, with the largest percentage increase occurring in the most northern areas. The availability and quality of subsistence foods, normally considered to be very healthy, may change due to changing access, changing habitats, and spoilage of meat in food storage cellars. These and other trends and potential outcomes resulting from a changing climate are further described in this report. In addition, we describe new science leadership activities that have been initiated to address and provide guidance toward conducting research aimed at making available information for policy makers and land management agencies to better understand, address, and plan for changes to the local and regional environment. This report cites data in both metric and standard units due to the contributions by numerous authors and the direct reference of their data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1379","usgsCitation":"Markon, C., Trainor, S., and Chapin, F.S., 2012, The United States National Climate Assessment - Alaska Technical Regional Report: U.S. Geological Survey Circular 1379, xiv, 148 p., https://doi.org/10.3133/cir1379.","productDescription":"xiv, 148 p.","numberOfPages":"166","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":262980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir_1379.jpg"},{"id":262978,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1379/"},{"id":262979,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1379/pdf/circ1379.pdf"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -172.45,51.21 ], [ -172.45,71.39 ], [ -129.99,71.39 ], [ -129.99,51.21 ], [ -172.45,51.21 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"509cf2f2e4b0e374086f46ae","contributors":{"editors":[{"text":"Markon, Carl J.","contributorId":67122,"corporation":false,"usgs":true,"family":"Markon","given":"Carl J.","affiliations":[],"preferred":false,"id":509084,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Trainor, Sarah F.","contributorId":21396,"corporation":false,"usgs":true,"family":"Trainor","given":"Sarah F.","affiliations":[],"preferred":false,"id":509082,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Chapin, F. Stuart III","contributorId":65632,"corporation":false,"usgs":false,"family":"Chapin","given":"F.","suffix":"III","email":"","middleInitial":"Stuart","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":509083,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Markon, Carl J.","contributorId":67122,"corporation":false,"usgs":true,"family":"Markon","given":"Carl J.","affiliations":[],"preferred":false,"id":468713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trainor, Sarah F.","contributorId":21396,"corporation":false,"usgs":true,"family":"Trainor","given":"Sarah F.","affiliations":[],"preferred":false,"id":468711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chapin, F. Stuart III","contributorId":65632,"corporation":false,"usgs":false,"family":"Chapin","given":"F.","suffix":"III","email":"","middleInitial":"Stuart","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":468712,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}