Reservoirs often receive excess nitrogen (N) and phosphorus (P) lost from agricultural land, and may subsequently influence N and P delivery to inland and coastal waters through internal processes such as nutrient burial, denitrification, and nutrient turnover. Currently there is a need to better understand how reservoirs affect nutrient transport in agricultural landscapes, where few prior studies have provided joint views on the variation in net retention/loss among reservoirs, the role of reservoirs apart from natural lakes, and differences in effects on N versus P, especially over time frames >1 year. To address these needs, we compiled water quality data from many rivers in intermediate-to-large drainages of the Midwestern US, including tributaries to the Upper Mississippi River, Great Lakes, and Ohio River Basins, where cropland often covers >50 % of the contributing area. Incorporating 18 years of data (1990–2007), effects of reservoirs on river nutrient transport were examined using comparisons between reservoir out- flow sites and unimpeded river sites (N = 869, including 100 reservoir outflow sites) supported by mass balance analysis of individual reservoirs (n = 17). Reservoir outflows sites commonly had 20 % lower annual yields (mass per catchment area per year) of total N and total P (TP) than unimpeded rivers after accounting for cropland coverage. Reservoir outflow sites also had lower interannual variability in TP yields. The mass balance approach confirmed net N losses in reservoirs, suggesting denitrification of agricultural N, or N burial in sediments. Net retention of P ranged more widely, and multiple systems showed net P export, providing new evidence that legacy P within reservoir systems may mobilize over the long-term. Our results indicate that reservoirs broadly influence the downstream transport of N and P through agricultural river networks, including networks where natural lakes and wetlands are relatively scarce. This calls for a more complete understanding of agricultural reservoirs as open, connected features of river networks where biogeochemical processes are often influential to downstream water quality, but potentially sensitive to changes associated with sedimentation, eutrophication, infrastructure aging, and reservoir management.
","language":"English","publisher":"Springer","doi":"10.1007/s10533-015-0106-3","usgsCitation":"Powers, S.M., Tank, J., and Robertson, D.M., 2015, Control of nitrogen and phosphorus transport by reservoirs in agricultural landscapes: Biogeochemistry, v. 124, p. 417-439, https://doi.org/10.1007/s10533-015-0106-3.","productDescription":"23 p.","startPage":"417","endPage":"439","ipdsId":"IP-056109","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":355702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Midwest, Upper Mississippi River, Great Lakes, Ohio River Basin","volume":"124","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-22","publicationStatus":"PW","scienceBaseUri":"5b6fcbf3e4b0f5d57878ecc3","contributors":{"authors":[{"text":"Powers, Stephen M.","contributorId":35238,"corporation":false,"usgs":false,"family":"Powers","given":"Stephen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":556910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tank, Jennifer L.","contributorId":103870,"corporation":false,"usgs":true,"family":"Tank","given":"Jennifer L.","affiliations":[],"preferred":false,"id":556911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":556909,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70147788,"text":"ds933 - 2015 - Hydrologic data from wells at or in the vicinity of the San Juan coal mine, San Juan County, New Mexico","interactions":[],"lastModifiedDate":"2015-06-05T12:48:35","indexId":"ds933","displayToPublicDate":"2015-06-05T13:30:00","publicationYear":"2015","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":"933","title":"Hydrologic data from wells at or in the vicinity of the San Juan coal mine, San Juan County, New Mexico","docAbstract":"In 2010, in cooperation with the Mining and Minerals Division (MMD) of the State of New Mexico Energy, Minerals and Natural Resources Department, the U.S. Geological Survey (USGS) initiated a 4-year assessment of hydrologic conditions at the San Juan coal mine (SJCM), located about 14 miles west-northwest of the city of Farmington, San Juan County, New Mexico. The mine produces coal for power generation at the adjacent San Juan Generating Station (SJGS) and stores coal-combustion byproducts from the SJGS in mined-out surface-mining pits. The purpose of the hydrologic assessment is to identify groundwater flow paths away from SJCM coal-combustion-byproduct storage sites that might allow metals that may be leached from coal-combustion byproducts to eventually reach wells or streams after regional dewatering ceases and groundwater recovers to predevelopment levels. The hydrologic assessment, undertaken between 2010 and 2013, included compilation of existing data. The purpose of this report is to present data that were acquired and compiled by the USGS for the SJCM hydrologic assessment.
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This issue poses a challenge in species conservation where setting priorities requires estimating influences of potential stressors using observational data. We present a novel approach for inferring influence of a rare stressor on a rare species by blending predictive models with nonparametric permutation tests. We illustrate the approach with two case studies involving rare amphibians in Yosemite National Park, USA. The endangered frog, Rana sierrae, is known to be negatively impacted by non-native fish, while the threatened toad, Anaxyrus canorus, is potentially affected by packstock. Both stressors and amphibians are rare, occurring in ~10% of potential habitat patches. We first predict amphibian occupancy with a statistical model that includes all predictors but the stressor to stratify potential habitat by predicted suitability. A stratified permutation test then evaluates the association between stressor and amphibian, all else equal. Our approach confirms the known negative relationship between fish and R. sierrae, but finds no evidence of a negative relationship between current packstock use and A. canorus breeding. Our statistical approach has potential broad application for deriving understanding (not just prediction) from observational data.
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","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153041","usgsCitation":"Shoda, M.E., Lathrop, T., and Risch, M.R., 2015, Real-time, continuous water-quality monitoring in Indiana and Kentucky: U.S. Geological Survey Fact Sheet 2015-3041, 4 p., https://doi.org/10.3133/fs20153041.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061469","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":301044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153041.jpg"},{"id":301042,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3041/"},{"id":301043,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3041/pdf/fs2015-3041.pdf","text":"Report","size":"3.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Indiana, Kentucky","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.8089599609375,\n 41.759019938155404\n ],\n [\n -86.82769775390625,\n 41.76106872528616\n ],\n [\n -87.07489013671875,\n 41.66060124302088\n ],\n [\n -87.24517822265624,\n 41.623655390686395\n ],\n [\n -87.41546630859375,\n 41.638025739250786\n ],\n [\n -87.52532958984374,\n 41.724180549563606\n ],\n [\n -87.53356933593749,\n 39.35553794109382\n ],\n [\n -87.637939453125,\n 39.15988184949157\n ],\n [\n -87.5006103515625,\n 38.74551518488265\n ],\n [\n -87.967529296875,\n 38.26406296833961\n ],\n [\n -88.14880371093749,\n 37.67947293019486\n ],\n [\n -88.0718994140625,\n 37.505368263398104\n ],\n [\n -88.4619140625,\n 37.40943717748788\n ],\n [\n -88.43994140625,\n 37.10776507118514\n ],\n [\n -88.505859375,\n 37.08585785263673\n ],\n [\n -88.98376464843749,\n 37.24782120155428\n ],\n [\n -89.1815185546875,\n 37.06394430056685\n ],\n [\n -89.20898437499999,\n 36.60670888641815\n ],\n [\n -89.56054687499999,\n 36.575835338491764\n ],\n [\n -89.527587890625,\n 36.491973470593685\n ],\n [\n -88.04443359375,\n 36.50522086338427\n ],\n [\n -88.0718994140625,\n 36.69485094156225\n ],\n [\n -87.8302001953125,\n 36.64638529597495\n ],\n [\n -86.5283203125,\n 36.64638529597495\n ],\n [\n -85.242919921875,\n 36.62434536776987\n ],\n [\n -83.6773681640625,\n 36.59788913307022\n ],\n [\n -83.49334716796875,\n 36.66841891894786\n ],\n [\n -83.111572265625,\n 36.74768773190056\n ],\n [\n -82.69958496093749,\n 37.13404537126446\n ],\n [\n -82.2930908203125,\n 37.29153547292737\n ],\n [\n -81.990966796875,\n 37.54893261064111\n ],\n [\n -82.27111816406249,\n 37.67947293019486\n ],\n [\n -82.5018310546875,\n 38.00049145082287\n ],\n [\n -82.64465332031249,\n 38.156156969924915\n ],\n [\n -82.6007080078125,\n 38.44068226417387\n ],\n [\n -82.694091796875,\n 38.56105262446978\n ],\n [\n -82.8533935546875,\n 38.603993275591684\n ],\n [\n -82.891845703125,\n 38.77549900381297\n ],\n [\n -83.25439453125,\n 38.62116234642254\n ],\n [\n -83.51806640624999,\n 38.70694605159386\n ],\n [\n -83.682861328125,\n 38.638327308061875\n ],\n [\n -83.78173828125,\n 38.676933444637925\n ],\n [\n -83.9410400390625,\n 38.79690830348427\n ],\n [\n -84.2156982421875,\n 38.8225909761771\n ],\n [\n -84.30908203125,\n 39.01918369029134\n ],\n [\n -84.473876953125,\n 39.06184913429154\n ],\n [\n -84.7100830078125,\n 39.15136267949032\n ],\n [\n -84.825439453125,\n 39.11727568585595\n ],\n [\n -84.8089599609375,\n 41.759019938155404\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5572ba28e4b077dba76c1b94","contributors":{"authors":[{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lathrop, Timothy R. trlathro@usgs.gov","contributorId":4065,"corporation":false,"usgs":true,"family":"Lathrop","given":"Timothy R.","email":"trlathro@usgs.gov","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Risch, Martin R. 0000-0002-7908-7887 mrrisch@usgs.gov","orcid":"https://orcid.org/0000-0002-7908-7887","contributorId":2118,"corporation":false,"usgs":true,"family":"Risch","given":"Martin","email":"mrrisch@usgs.gov","middleInitial":"R.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547781,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156221,"text":"70156221 - 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Geodetic data for the BSF are sparse, and surface creep rates are generally poorly constrained. The two existing geodetic slip rate inversions resolve at least one locked patch within the creeping zones. We use the 3-D finite element code FaultMod to conduct dynamic rupture models based on both geodetic inversions, in order to determine the ability of rupture to propagate into the creeping regions, as well as to assess possible magnitudes for BSF ruptures. For both sets of models, we find that the distribution of aseismic creep limits the extent of coseismic rupture, due to the contrast in frictional properties between the locked and creeping regions.
","language":"English","publisher":"Wiley","doi":"10.1002/2015GL063802","usgsCitation":"Lozos, J.C., Harris, R.A., Murray, J.R., and Lienkaemper, J.J., 2015, Dynamic rupture models of earthquakes on the Bartlett Springs Fault, Northern California: Geophysical Research Letters, v. 42, no. 11, p. 4343-4349, https://doi.org/10.1002/2015GL063802.","productDescription":"7 p.","startPage":"4343","endPage":"4349","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060677","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":306828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bartlett Springs Fault, Northern California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.5025634765625,\n 37.931200459333716\n ],\n [\n -124.5025634765625,\n 40.29628651711716\n ],\n [\n -120.83312988281249,\n 40.29628651711716\n ],\n [\n -120.83312988281249,\n 37.931200459333716\n ],\n [\n -124.5025634765625,\n 37.931200459333716\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-05","publicationStatus":"PW","scienceBaseUri":"55d4572fe4b0518e354694ba","contributors":{"authors":[{"text":"Lozos, Julian C.","contributorId":146525,"corporation":false,"usgs":false,"family":"Lozos","given":"Julian","email":"","middleInitial":"C.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":568111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Ruth A. 0000-0002-9247-0768 harris@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-0768","contributorId":786,"corporation":false,"usgs":true,"family":"Harris","given":"Ruth","email":"harris@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":568108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":568109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lienkaemper, James J. 0000-0002-7578-7042 jlienk@usgs.gov","orcid":"https://orcid.org/0000-0002-7578-7042","contributorId":1941,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"James","email":"jlienk@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":568110,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148427,"text":"70148427 - 2015 - Effects of ungulate disturbance and weather variation on Pediocactus winkleri: Insights from long-term monitoring","interactions":[],"lastModifiedDate":"2020-12-31T14:52:34.280534","indexId":"70148427","displayToPublicDate":"2015-06-04T14:00:00","publicationYear":"2015","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}},"displayTitle":"Effects of ungulate disturbance and weather variation on Pediocactus winkleri: Insights from long-term monitoring","title":"Effects of ungulate disturbance and weather variation on Pediocactus winkleri: Insights from long-term monitoring","docAbstract":"Population dynamics and effects of large ungulate disturbances on Winkler cactus (Pediocactus winkleri K.D. 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Box 186, Bluff, Utah 84512","active":true,"usgs":false}],"preferred":false,"id":548209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":548207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flagg, Cody B. cflagg@usgs.gov","contributorId":4573,"corporation":false,"usgs":true,"family":"Flagg","given":"Cody","email":"cflagg@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":548210,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70141799,"text":"ds69AA - 2015 - Assessment of unconvential (tight) gas resources in Upper Cook Inlet Basin, South-central Alaska","interactions":[],"lastModifiedDate":"2015-06-04T09:31:10","indexId":"ds69AA","displayToPublicDate":"2015-06-04T09:15:00","publicationYear":"2015","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":"69","chapter":"AA","title":"Assessment of unconvential (tight) gas resources in Upper Cook Inlet Basin, South-central Alaska","docAbstract":"A geologic model was developed for the assessment of potential Mesozoic tight-gas resources in the deep, central part of upper Cook Inlet Basin, south-central Alaska. The basic premise of the geologic model is that organic-bearing marine shales of the Middle Jurassic Tuxedni Group achieved adequate thermal maturity for oil and gas generation in the central part of the basin largely due to several kilometers of Paleogene and Neogene burial. In this model, hydrocarbons generated in Tuxedni source rocks resulted in overpressure, causing fracturing and local migration of oil and possibly gas into low-permeability sandstone and siltstone reservoirs in the Jurassic Tuxedni Group and Chinitna and Naknek Formations. Oil that was generated either remained in the source rock and subsequently was cracked to gas which then migrated into low-permeability reservoirs, or oil initially migrated into adjacent low-permeability reservoirs, where it subsequently cracked to gas as adequate thermal maturation was reached in the central part of the basin. Geologic uncertainty exists on the (1) presence of adequate marine source rocks, (2) degree and timing of thermal maturation, generation, and expulsion, (3) migration of hydrocarbons into low-permeability reservoirs, and (4) preservation of this petroleum system. Given these uncertainties and using known U.S. tight gas reservoirs as geologic and production analogs, a mean volume of 0.64 trillion cubic feet of gas was assessed in the basin-center tight-gas system that is postulated to exist in Mesozoic rocks of the upper Cook Inlet Basin. This assessment of Mesozoic basin-center tight gas does not include potential gas accumulations in Cenozoic low-permeability reservoirs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds69AA","usgsCitation":"Schenk, C.J., Nelson, P.H., Klett, T., Le, P., and Anderson, C.P., 2015, Assessment of unconvential (tight) gas resources in Upper Cook Inlet Basin, South-central Alaska: U.S. Geological Survey Data Series 69, 3 Chapters: variously paged; Upper Cook Inlet Basin Database, https://doi.org/10.3133/ds69AA.","productDescription":"3 Chapters: variously paged; Upper Cook Inlet Basin Database","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049080","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":301037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds69AA.jpg"},{"id":301033,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-aa/REPORTS/DDS-69-AA-Chapter1.pdf","text":"Chapter 1","size":"15.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Chapter 1","linkHelpText":"Geologic Model and Assessment of Potential Unconventional (Tight) Gas Resources in Upper Cook Inlet Basin, South-Central Alaska"},{"id":301031,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-aa/"},{"id":301034,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-aa/REPORTS/DDS-69-AA-Chapter2.pdf","text":"Chapter 2","size":"312 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Chapter 2","linkHelpText":"Tabular Data and Graphical Images in Support of the U.S. Geological Survey National Oil and Gas Assessment—Southern Alaska Province (5003), Cook Inlet"},{"id":301035,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-aa/REPORTS/DDS-69-AA-Chapter3.pdf","text":"Chapter 3","size":"336 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Chapter 3","linkHelpText":"The GIS Project for the Assessment of Unconventional (Tight) Gas Resources in Upper Cook Inlet Basin, South-Central Alaska"},{"id":301036,"type":{"id":9,"text":"Database"},"url":"https://energy.usgs.gov/OilGas/AssessmentsData/NationalOilGasAssessment/USBasinSummaries.aspx?provcode=5003","text":"Upper Cook Inlet Basin Database","description":"Upper Cook Inlet Basin Database","linkHelpText":"GIS/Data/Metadata"}],"country":"United States","state":"Alaska","otherGeospatial":"Cook Inlet Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.017333984375,\n 58.59688654973872\n ],\n [\n -154.017333984375,\n 62.865168668923125\n ],\n [\n -147.952880859375,\n 62.865168668923125\n ],\n [\n -147.952880859375,\n 58.59688654973872\n ],\n [\n -154.017333984375,\n 58.59688654973872\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557168b7e4b077dba762289d","contributors":{"compilers":[{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":548202,"contributorType":{"id":3,"text":"Compilers"},"rank":1}],"authors":[{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":548193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Philip H. pnelson@usgs.gov","contributorId":862,"corporation":false,"usgs":true,"family":"Nelson","given":"Philip","email":"pnelson@usgs.gov","middleInitial":"H.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":548194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klett, Timothy R. 0000-0001-9779-1168 tklett@usgs.gov","orcid":"https://orcid.org/0000-0001-9779-1168","contributorId":709,"corporation":false,"usgs":true,"family":"Klett","given":"Timothy R.","email":"tklett@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":548199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Le, Phuong A. 0000-0003-2477-509X ple@usgs.gov","orcid":"https://orcid.org/0000-0003-2477-509X","contributorId":2151,"corporation":false,"usgs":true,"family":"Le","given":"Phuong A.","email":"ple@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":548200,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Christopher P.","contributorId":140859,"corporation":false,"usgs":false,"family":"Anderson","given":"Christopher","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":548201,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188816,"text":"70188816 - 2015 - SHRIMP U–Pb and REE data pertaining to the origins of xenotime in Belt Supergroup rocks: evidence for ages of deposition, hydrothermal alteration, and metamorphism","interactions":[],"lastModifiedDate":"2017-06-27T11:01:16","indexId":"70188816","displayToPublicDate":"2015-06-04T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1168,"text":"Canadian Journal of Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"SHRIMP U–Pb and REE data pertaining to the origins of xenotime in Belt Supergroup rocks: evidence for ages of deposition, hydrothermal alteration, and metamorphism","docAbstract":"The Belt–Purcell Supergroup, northern Idaho, western Montana, and southern British Columbia, is a thick succession of Mesoproterozoic sedimentary rocks with an age range of about 1470–1400 Ma. Stratigraphic layers within several sedimentary units were sampled to apply the new technique of U–Pb dating of xenotime that sometimes forms as rims on detrital zircon during burial diagenesis; xenotime also can form epitaxial overgrowths on zircon during hydrothermal and metamorphic events. Belt Supergroup units sampled are the Prichard and Revett Formations in the lower Belt, and the McNamara and Garnet Range Formations and Pilcher Quartzite in the upper Belt. Additionally, all samples that yielded xenotime were also processed for detrital zircon to provide maximum age constraints for the time of deposition and information about provenances; the sample of Prichard Formation yielded monazite that was also analyzed. Ten xenotime overgrowths from the Prichard Formation yielded a U–Pb age of 1458 ± 4 Ma. However, because scanning electron microscope – backscattered electrons (SEM–BSE) imagery suggests complications due to possible analysis of multiple age zones, we prefer a slightly older age of 1462 ± 6 Ma derived from the three oldest samples, within error of a previous U–Pb zircon age on the syn-sedimentary Plains sill. We interpret the Prichard xenotime as diagenetic in origin. Monazite from the Prichard Formation, originally thought to be detrital, yielded Cretaceous metamorphic ages. Xenotime from the McNamara and Garnet Range Formations and Pilcher Quartzite formed at about 1160– 1050 Ma, several hundred million years after deposition, and probably also experienced Early Cretaceous growth. These xenotime overgrowths are interpreted as metamorphic–diagenetic in origin (i.e., derived during greenschist facies metamorphism elsewhere in the basin, but deposited in sub-greenschist facies rocks). Several xenotime grains are older detrital grains of igneous derivation. A previous study on the Revett Formation at the Spar Lake Ag–Cu deposit provides data for xenotime overgrowths in several ore zones formed by hydrothermal processes; herein, those results are compared with data from newly analyzed diagenetic, metamorphic, and magmatic xenotime overgrowths. The origin of a xenotime overgrowth is reflected in its rareearth element (REE) pattern. Detrital (i.e., igneous) xenotime has a large negative Eu anomaly and is heavy rare-earth element (HREE)-enriched (similar to REE in igneous zircon). Diagenetic xenotime has a small negative Eu anomaly and flat HREE (Tb to Lu). Hydrothermal xenotime is depleted in light rare-earth element (LREE), has a small negative Eu anomaly, and decreasing HREE. Metamorphic xenotime is very LREE-depleted, has a very small negative Eu anomaly, and is strongly depleted in HREE (from Gd to Lu). Because these characteristics seem to be process related, they may be useful for interpretation of xenotime of unknown origin. The occurrence of 1.16–1.05 Ga metamorphic xenotime, in the apparent absence of pervasive deformation structures, suggests that the heating may be related to poorly understood regional heating due to broad regional underplating of mafic magma. These results may be additional evidence (together with published ages from metamorphic titanite, zircon, monazite, and garnet) for an enigmatic, Grenville-age metamorphic event that is more widely recognized in the southwestern and eastern United States
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjes-2014-0239","usgsCitation":"Aleinikoff, J.N., Lund, K., and Fanning, C.M., 2015, SHRIMP U–Pb and REE data pertaining to the origins of xenotime in Belt Supergroup rocks: evidence for ages of deposition, hydrothermal alteration, and metamorphism: Canadian Journal of Earth Sciences, v. 52, no. 9, p. 722-745, https://doi.org/10.1139/cjes-2014-0239.","productDescription":"24 p. ","startPage":"722","endPage":"745","ipdsId":"IP-056309","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":472032,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjes-2014-0239","text":"External Repository"},{"id":342886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, British Columbia, Idaho, Montana, Oregon, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.75390625,\n 44.008620115415354\n ],\n [\n -107.5341796875,\n 46.76996843356982\n ],\n [\n -111.02783203125,\n 46.93526088057719\n ],\n [\n -113.4228515625,\n 49.05227025601607\n ],\n [\n -113.84033203125,\n 50.52739681329302\n ],\n [\n -114.43359375,\n 51.57706953722565\n ],\n [\n -117.6416015625,\n 53.44880683542759\n ],\n [\n -121.59667968749999,\n 52.77618568896171\n ],\n [\n -120.58593749999999,\n 51.08282186160978\n ],\n [\n -119.68505859375,\n 49.36806633482156\n ],\n [\n -119.3115234375,\n 47.916342040161155\n ],\n [\n -118.7841796875,\n 45.90529985724799\n ],\n [\n -118.037109375,\n 44.29240108529005\n ],\n [\n -107.75390625,\n 44.008620115415354\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59521d22e4b062508e3c3698","contributors":{"authors":[{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":700477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lund, Karen 0000-0002-4249-3582 klund@usgs.gov","orcid":"https://orcid.org/0000-0002-4249-3582","contributorId":1235,"corporation":false,"usgs":true,"family":"Lund","given":"Karen","email":"klund@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":700478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fanning, C. Mark","contributorId":193462,"corporation":false,"usgs":false,"family":"Fanning","given":"C.","email":"","middleInitial":"Mark","affiliations":[],"preferred":false,"id":700479,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70141611,"text":"cir1410 - 2015 - The U.S. Geological Survey Geologic Collections Management System (GCMS)—A master catalog and collections management plan for U.S. Geological Survey geologic samples and sample collections","interactions":[],"lastModifiedDate":"2022-09-27T12:26:21.94595","indexId":"cir1410","displayToPublicDate":"2015-06-03T16:00:00","publicationYear":"2015","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":"1410","title":"The U.S. Geological Survey Geologic Collections Management System (GCMS)—A master catalog and collections management plan for U.S. Geological Survey geologic samples and sample collections","docAbstract":"The U.S. Geological Survey (USGS) is widely recognized in the earth science community as possessing extensive collections of earth materials collected by research personnel over the course of its history. In 2006, a Geologic Collections Inventory was conducted within the USGS Geology Discipline to determine the extent and nature of its sample collections, and in 2008, a working group was convened by the USGS National Geologic and Geophysical Data Preservation Program to examine ways in which these collections could be coordinated, cataloged, and made available to researchers both inside and outside the USGS. The charge to this working group was to evaluate the proposition of creating a Geologic Collections Management System (GCMS), a centralized database that would (1) identify all existing USGS geologic collections, regardless of size, (2) create a virtual link among the collections, and (3) provide a way for scientists and other researchers to obtain access to the samples and data in which they are interested. Additionally, the group was instructed to develop criteria for evaluating current collections and to establish an operating plan and set of standard practices for handling, identifying, and managing future sample collections. Policies and procedures promoted by the GCMS would be based on extant best practices established by the National Science Foundation and the Smithsonian Institution. The resulting report—USGS Circular 1410, “The U.S. Geological Survey Geologic Collections Management System (GCMS): A Master Catalog and Collections Management Plan for U.S. Geological Survey Geologic Samples and Sample Collections”—has been developed for sample repositories to be a guide to establishing common practices in the collection, retention, and disposal of geologic research materials throughout the USGS.
While constructing this report, the GCMS’s potential customers and their needs were considered. Two critical definitions have been clarified: a repository is a facility for the long-term management of geologic collections, and a collection is a set of specimens that have been brought together on the basis of some common characteristic. Required sample metadata for newly collected samples, as well as for older collections, were also stipulated and are listed and explained in this report. Several basic policies are also recommended by the GCMS in order to standardize operations among the physical repositories where collections are currently housed. The GCMS Collection Management Plan provides a set of protocols and templates for the management of scientific collections, including access, storage, transfer, and disposal of physical geologic samples and data. This plan is flexible to allow each repository to adapt the practices best suited to its collections.
The general consideration for implementation of the GCMS is that all active USGS geologic sample repositories will form the core of GCMS and that participating science centers will develop procedures based on proposed GCMS methodologies. The GCMS is a collective resource for the entire USGS community and the users who discover the geologic materials kept in these repositories and seek to access them.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1410","usgsCitation":"Geologic Materials Repository Working Group, 2015, The U.S. Geological Survey Geologic Collections Management System (GCMS)—A master catalog and collections management plan for U.S. Geological Survey geologic samples and sample collections: U.S. Geological Survey Circular 1410, Report: xvi, 108 p.; 3 Appendixes, https://doi.org/10.3133/cir1410.","productDescription":"Report: xvi, 108 p.; 3 Appendixes","numberOfPages":"126","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-045796","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":5060,"text":"Data Preservation Program","active":true,"usgs":true}],"links":[{"id":407378,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/survey-manual/im-css-2019-01","text":"Survey Manual Instructional Memorandum CSS 2019-01","description":"Survey Manual Instructional Memorandum CSS 2019-01"},{"id":301025,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1410/"},{"id":301028,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/circ/1410/downloads/GCMSAppendix4.pdf","text":"Appendix 4","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 4","linkHelpText":"GCMS Handbook for Collection Repositories"},{"id":301027,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/circ/1410/downloads/GCMSAppendix3.pdf","text":"Appendix 3","size":"11.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 3","linkHelpText":"GCMS Policy Manual"},{"id":301026,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1410/pdf/circ1410.pdf","text":"Report","size":"23.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1410.jpg"},{"id":301029,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/circ/1410/downloads/Forms/","text":"Appendix 5","size":"7.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 5","linkHelpText":"Forms for the Long-term Management and Preservation of USGS Geological Materials"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5570171de4b0d9246a9fd153","contributors":{"authors":[{"text":"Geologic Materials Repository Working Group","contributorId":141061,"corporation":true,"usgs":false,"organization":"Geologic Materials Repository Working Group","id":548192,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70147914,"text":"sir20155056 - 2015 - Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014","interactions":[],"lastModifiedDate":"2015-06-03T14:00:29","indexId":"sir20155056","displayToPublicDate":"2015-06-03T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5056","title":"Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014","docAbstract":"From August 28 to 29, 2011, Tropical Storm Irene delivered rainfall ranging from about 4 inches to more than 7 inches in the White River Basin. The rainfall resulted in severe flooding throughout the basin and significant damage along the White River and Tweed River. In response to the flooding, the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, conducted a new flood study to aid in the flood recovery and restoration. This flood study includes a 20.7-mile reach of the White River from the downstream end at about 2,000 feet downstream from the State Route 107 bridge in the Village of Bethel, Vermont, to the upstream end at about 1,000 feet upstream from the River Brook Drive bridge in the Village of Rochester, Vt., and a 7.9-mile reach of the Tweed River from its mouth in Stockbridge, Vt., to the confluence of the West and South Branches of the Tweed River and continuing upstream on the South Branch Tweed River to the Pittsfield, Vt., town line.
\nThis report presents water-surface elevations determined for the study reaches using the U.S. Army Corps of Engineers one-dimensional step-backwater Hydrologic Engineering Center River Analysis System model, also known as HEC– RAS. The water-surface elevations were determined for floods having a 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probability (AEP) and for the floodway.
\nEighteen high-water marks from Tropical Storm Irene were available along the studied reaches. The discharges in the Tropical Storm Irene HEC–RAS model were adjusted so that the resulting water-surface elevations matched the high-water mark elevations along the study reaches. This allowed for an estimation of the water-surface profile throughout the study area resulting from Tropical Storm Irene. From a comparison of the estimated water-surface profile of Tropical Storm Irene to the water-surface profiles of the 1- and 0.2-percent AEP floods, it was determined that the high-water elevations resulting from Tropical Storm Irene exceeded the estimated 1-percent AEP flood throughout the White River and Tweed River study reaches and exceeded the estimated 0.2-percent AEP flood in 16.7 of the 28.6 study reach miles. 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 18.2-centimeter vertical accuracy at the 95-percent confidence level and 1-meter horizontal resolution to delineate the area flooded for each water-surface profile.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155056","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Olson, S.A., 2015, Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014: U.S. Geological Survey Scientific Investigations Report 2015-5056, Report: vi, 32 p.; Readme; Map file and datasets; Metadata, https://doi.org/10.3133/sir20155056.","productDescription":"Report: vi, 32 p.; Readme; Map file and datasets; Metadata","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-057993","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":301023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155056.jpg"},{"id":301018,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5056/"},{"id":301019,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5056/pdf/sir2015-5056.pdf","text":"Report","size":"2.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301020,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2015/5056/attachments/sir2015-5056_readme.txt","text":"Readme","size":"1.09 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Readme"},{"id":301021,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5056/attachments/sir2015-5056_map.zip","text":"Map file and datasets","size":"2.11 GB","linkFileType":{"id":6,"text":"zip"},"description":"Map file and datasets","linkHelpText":"Contains the published map file and the map dataset. 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2015 - Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2013","interactions":[],"lastModifiedDate":"2015-06-03T10:47:23","indexId":"ofr20151082","displayToPublicDate":"2015-06-03T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1082","title":"Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2013","docAbstract":"Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2013 (October 1, 2012, through September 30, 2013) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB) in the cooperative study. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 37 sampling stations by the PWSB and at 14 continuous-record streamgages by the USGS during WY 2013 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2013.
\nThe largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of 30 cubic feet per second (ft3/s) to the reservoir during WY 2013. For the same time period, annual mean1 streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.45 to about 19 ft3/s. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,300,000 kilograms (kg) of sodium and 2,100,000 kg of chloride to the Scituate Reservoir during WY 2013; sodium and chloride yields for the tributaries ranged from 8,600 to 58,000 kilograms per square mile (kg/mi2) and from 14,000 to 97,000 kg/mi2, respectively.
\nAt the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 18 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as nitrogen (N), median nitrate concentration was less than 0.01 mg/L as N, median orthophosphate concentration was 0.128 mg/L as phosphate, and median concentrations of total coliform bacteria and Escherichia coli (E. coli) were 330 and 15 colony-forming units per 100 milliliters (CFU/100mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 100 kilograms per day (kg/d; 50 kilograms per day per square mile [kg/d/mi2]), 10 grams per day (g/d; 5.1 grams per day per square mile [g/d/mi2]), 73 g/d (28 g/d/mi2), 720 g/d (320 g/d/mi2), 21,000 colony-forming units per day (CFU×106/d; 8,700 CFU×106/d/mi2), and 1,000 CFU×106/d (510 CFU×106/d/mi2), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151082","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2015, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2013: U.S. Geological Survey Open-File Report 2015-1082, Report: v, 31 p.; Appendix, https://doi.org/10.3133/ofr20151082.","productDescription":"Report: v, 31 p.; Appendix","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-10-01","temporalEnd":"2013-09-30","ipdsId":"IP-056176","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":301013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151082.jpg"},{"id":301012,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1082/attachments/ofr2015-1082_appendix1.xlsx","text":"Appendix 1","size":"32 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 1","linkHelpText":"Water-quality data collected by the Providence Water Supply Board at 37 monitoring stations in the Scituate Reservoir drainage area, Rhode Island, water year 2013."},{"id":301011,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1082/pdf/ofr2015-1082.pdf","text":"Report","size":"873 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301010,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1082/"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.78947448730469,\n 41.74160260664948\n ],\n [\n -71.78947448730469,\n 41.92782492551717\n ],\n [\n -71.5484619140625,\n 41.92782492551717\n ],\n [\n -71.5484619140625,\n 41.74160260664948\n ],\n [\n -71.78947448730469,\n 41.74160260664948\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5570171de4b0d9246a9fd151","contributors":{"authors":[{"text":"Smith, Kirk P. 0000-0003-0269-474X kpsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-474X","contributorId":1516,"corporation":false,"usgs":true,"family":"Smith","given":"Kirk","email":"kpsmith@usgs.gov","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545615,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70146944,"text":"ofr20151073 - 2015 - Southern Salish Sea Habitat Map Series: Admiralty Inlet","interactions":[],"lastModifiedDate":"2015-06-05T08:29:44","indexId":"ofr20151073","displayToPublicDate":"2015-06-03T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1073","subseriesTitle":"Southern Salish Sea Habitat Map Series","title":"Southern Salish Sea Habitat Map Series: Admiralty Inlet","docAbstract":"In 2010 the Environmental Protection Agency, Region 10 initiated the Puget Sound Scientific Studies and Technical Investigations Assistance Program, designed to support research in support of implementing the Puget Sound Action Agenda. The Action Agenda was created in response to Puget Sound having been designated as one of 28 estuaries of national significance under section 320 of the U.S. Clean Water Act, and its overall goal is to restore the Puget Sound Estuary's environment by 2020. The Southern Salish Sea Mapping Project was funded by the Assistance Program request for proposals process, which also supports a large number of coastal-zone- and ocean-management issues. The issues include the recommendations of the Marine Protected Areas Work Group to the Washington State Legislature (Van Cleve and others, 2009), which endorses a Puget Sound and coast-wide marine conservation needs assessment, gap analysis of existing Marine Protected Areas (MPA) and recommendations for action. This publication is the first of four U.S. Geological Survey Scientific Investigation Maps that make up the Southern Salish Sea Mapping Project. The remaining three map blocks to be published in the future, located south of Admiralty Inlet, are shown in figure 1.
\nPuget Sound is a deep, fjord-type estuary covering an area of 2,330 km2 in the Pacific Northwest region of the United States (fig. 1). It is connected to the ocean by the Strait of Juan de Fuca, a turbulent passage approximately 160 km in length and 22 km wide at its west end, expanding to over 40 km wide at its east end (Thomson, 1994). During the Pleistocene, the area was occupied several times by lobes of continental ice, resulting in a complex basin-fill of glacial and interglacial deposits that are locally as thick as 1100 m (Johnson and others, 2001). The last glaciation, called the Fraser glaciation, began after 28,800±740 14C yr B.P. when ice started a slow expansion (Clague, 1981). At peak advance the westward Juan de Fuca lobe reached the edge of the continental shelf through the Juan de Fuca Strait shortly before 14,460±200 14C yr B.P. (Herzer and Bornhold, 1982). The southward Puget lobe advanced to its terminal position in Puget Sound by around 14,150 14C yr B.P. (Porter and Swanson, 1998). Ice retreated from its maximum to northern Whidbey Island by 13,650±350 14C yr B.P. (Dethier and others, 1995). Retreating glaciers resulted in a thick sequence of ice-contact, glacial-marine sediment, and early post-glacial sediments (Linden and Schurrer, 1988). These deposits have experienced the effects of a marine transgression followed by regression, resulting in a sea-level several tens of meters lower than the present day (Linden and Schurrer, 1988). A second transgression brought sea level to about the present level by around 5,470±120 14C yr B.P. (Clague and others, 1982) establishing the present oceanographic and geologic environment
\nPuget Sound is separated into four interconnected basins; Whidbey, Central (Main), Hood Canal, and South (Thomson, 1994). The Whidbey, Central, and Hood Canal basins are the three main branches of the Puget Sound estuary and are separated from the Strait of Juan de Fuca by a double sill at Admiralty Inlet. The Admiralty Inlet map area includes the Inlet and a portion of the Whidbey Basin (fig. 1). The shallower South Basin is separated by a sill at Tacoma Narrows and is highly branched with numerous finger inlets. Flow within Puget Sound is dominated by tidal currents of as much as 1 m/s at Admiralty Inlet, reducing to approximately 0.5 m/s in the Central Basin (Lavelle and others, 1988). The lack of silt and clay-sized sediments in the Admiralty Inlet map area is likely a result of the strong currents (see Ground-Truth Studies for the Admiralty Inlet Map Area, sheet 3). The subtidal component of flow reaches approximately 0.1 m/s and is driven by density gradients arising from the contrast in salty ocean water at the entrance and freshwater inputs from stream flow (Lavelle and others, 1988). The total freshwater input to Puget Sound is approximately 3.4 x 106 m3/day, primarily from the Skagit River (Cannon, 1983). The subtidal circulation mostly consists of a two-layered flow in the basins with fresher water exiting at the surface and saltier water entering at depth (Ebbesmeyer and Cannon, 2001). In general, surface waters flow north and deeper waters flow south; variations arise from wind effects that can drive a surface current in the same direction as the wind, and a baroclinic response in the lower layer to about 100-m depth (Matsuura and Cannon, 1997). Oceanographic properties are influenced by temporal forcing parameters such as reduced stream flow during the 2000-01 drought that increased surface salinity and decreased differences between surface and bottom waters (Newton and others, 2003).
\nOn offshore seismic-reflection profiles, Pleistocene strata (excluding latest Pleistocene glacial and post-glacial deposits) form a distinct seismic unit, bounded below by pre-Tertiary or Tertiary basement and above by typically flat-lying latest Pleistocene to Holocene deposits that fill in erosional or depositional relief (Johnson and others, 2001). Cores from central Puget Sound have accumulation rates that range from 85 to 1200 mg/cm2/yr, or 0.12 to 2.4 cm/yr; the highest accumulation rates are near the southern end of central Puget Sound (Carpenter and others, 1985). Carpenter and others (1985) un-weighted arithmetic mean of accumulation rates for central Puget Sound deeper stations is 480±340 (± one standard deviation) mg/cm2/yr. Lavelle and others (1985) also found rates as high as 1200 mg/cm2/yr over the past approximately 70 years in cores in the Central Basin off of and north and south of Elliott Bay. Puget Sound basin rates are comparable to rates in midshelf silt deposits on the Washington coast north of the Columbia River (Nittrouer and others, 1979).
\nThe deep subtidal (in other words, below SCUBA depths) habitats of Puget Sound are relatively poorly known. A few subtidal surveys exist for several habitat types from the 1960s and 1970s (reviewed in Dethier, 1990), using grab and box core data. The Dethier (1990) review divides habitat up into Coast and Marine Ecological Classification Standard (CMECS) substrate, water column energy, and depth zones but does not attempt to map these habitats, rather it is an inventory of habitats found in the area and the flora and fauna associated with each habitat.
\nThe approach of the Southern Salish Sea Mapping project is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, and bottom-sediment sampling data. This approach is based in part on methods presented and data collection and product needs identified at the Washington State Seafloor Mapping Workshop (Washington State Seafloor Mapping Workshop Steering Committee, 2008), attended by coastal and marine managers and scientists. The map products display seafloor geomorphology and substrate, and identify potential marine benthic habitats. It is emphasized that the more interpretive habitat and geology maps rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. Oceanographic current and wave data is not included in this analysis, however, the accompanying geographic information system (GIS) data set is designed and intended to be combined with oceanographic and biologic data sets assembled by others in the future and some of the GIS data has already been incorporated in the unpublished Nature Conservancy Benthic Habitats of Puget Sound database.
\nThis publication includes four map sheets, explanatory text, and a descriptive pamphlet. Each map sheet is published as a portable document format (PDF) file. ESRI ArcGIS compatible geotiffs (for example, bathymetry) and shapefiles (for example video observation points) will be available for download in the data catalog associated with this publication (Cochrane, 2015). An ArcGIS Project File with the symbology used to generate the map sheets is also provided. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151073","usgsCitation":"Cochrane, G.R., Dethier, M.N., Hodson, T.O., Kull, K.K., Golden, N., Ritchie, A.C., Moegling, C., and Pacunski, R.E., 2015, Southern Salish Sea Habitat Map Series: Admiralty Inlet: U.S. Geological Survey Open-File Report 2015-1073, Report: iv, 34 p.; 4 Plates: 40 x 36 inches, https://doi.org/10.3133/ofr20151073.","productDescription":"Report: iv, 34 p.; 4 Plates: 40 x 36 inches","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-054193","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":300998,"rank":6,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151073.jpg"},{"id":300985,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1073/"},{"id":300995,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/935/downloads/AdmiraltyInlet/ds935_AdmiraltyInlet.html","text":"Data Catalog—Admiralty Inlet, Washington","linkHelpText":"Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":300989,"rank":9,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1073/pdf/ofr20151073_pamphlet.pdf","text":"Pamphlet","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2015-1073 Pamphlet"},{"id":300990,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1073/pdf/ofr20151073_sheet1.pdf","text":"Sheet 1","size":"159 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2015-1073 Sheet 1","linkHelpText":"Bathymetry Map of the of Admiralty Inlet Map Area, Washington By Andrew C. 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Such synchrony requires tuning to an internal or external clock. Evidence exists for lunar reproductive cycles in some species, but its recognition in shell flux time series has proven difficult, raising questions about reproductive strategies. Using spectral analysis of a 4-year time series (mostly at weekly resolution) from the northern Gulf of Mexico, we show that the shell flux ofGloborotalia menardii, Globigerinella siphonifera, Orbulina universa, Globigerinoides sacculifer, Globigerinoides ruber (both pink and white varieties), Pulleniatina obliquiloculata, Neogloboquadrina dutertrei, Globigerinella calida and Globigerinita glutinata is characterised by lunar periodicity. However, the lunar rhythm is not present in all size fractions of each species and tends to be more dominant in the flux of larger shells, consistent with reproduction being more prevalent in larger specimens. Lunar periodicity is superimposed on longer term/seasonal changes in the shell fluxes, but accounts for a significant part of the variance in the fluxes. The amplitude of the lunar cycle increases roughly proportional with the magnitude of the flux, demonstrating that most of the population is indeed affected by lunar-phased synchronisation. In most species peak fluxes occur predominantly around, or just after, full moon. Only G. siphonifera and G. calida show a contrasting pattern with peaks concentrated around new moon. Although the exact cause of the synchronisation remains elusive, our data considerably increase the number of species for which lunar synchronised reproduction is reported and suggest that such reproductive behaviour is common in many species of planktonic foraminifera.
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Sequoia and Kings Canyon National Parks have received complaints that pack stock may affect Sierra Nevada bighorn sheep (Ovis canadensis sierrae; SNBS), a federally endangered subspecies that occurs in largely disjunct herds in the Sierra Nevada Range of California. The potential effects are thought to be displacement of SNBS from meadows on their summer range (altered habitat use) or, more indirectly, through changes in SNBS habitat or forage quality. Our goals were to conduct an association analysis to quantify the degree of potential spatial overlap in meadow use between SNBS and pack stock and to compare differences in vegetation community composition, structure, and diversity among meadows with different levels of use by bighorn sheep and pack stock. For the association analysis, we used two approaches: (1) we quantified the proportion of meadows that were within the herd home ranges of bighorn sheep and were potentially open to pack stock, and, (2) we used Monte Carlo simulations and use-availability analyses to compare the proportion of meadows used by bighorn sheep relative to the proportional occurrence or area of meadows available to bighorn sheep that were used by pack stock. To evaluate potential effects of pack stock on meadow plant communities and SNBS forage, we sampled vegetation in 2011 and 2012 at 100 plots to generate data that allowed us to compare:
\n1. Herbaceous plant species composition, structure, and diversity in plots with different combinations of use by pack stock and SNBS;
\n2. Cover of bare ground in plots with different combinations of use by pack stock and SNBS; and,
\n3. Total cover, diversity, and species composition of SNBS forage species in plots with different combinations of use by pack stock and SNBS.
\nThe association analyses indicated the potential for overlap between pack stock and SNBS was minimal; only 1 percent of the potential meadow area in the SNBS herd home ranges overlapped that of pack stock meadows. There were no systematic differences in overall vegetation structure or composition, or in diversity, cover, or composition of forage species, that indicated pack stock were altering SNBS habitat or affecting their nutrition. Variation in plant species composition was influenced primarily by random differences among meadows and environmental gradients, and there was little evidence that pack stock use contributed in meaningful ways to this variation. The few differences among meadows with different levels of use by bighorn sheep and pack stock either were minor or were not in a direction consistent with negative effects of pack stock on SNBS. We conclude that the current plan for managing pack stock grazing has been successful in minimizing significant negative effects on Sierra Nevada bighorn sheep at Sequoia and Kings Canyon National Parks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151102","usgsCitation":"Klinger, R.C., Few, A.P., Knox, K.A., Hatfield, B.E., Clark, J., German, D.W., and Stephenson, T.R., 2015, Evaluating potential overlap between pack stock and Sierra Nevada bighorn sheep (Ovis canadensis sierrae) in Sequoia and Kings Canyon National Parks, California: U.S. Geological Survey Open-File Report 2015-1102, vi, 46 p., https://doi.org/10.3133/ofr20151102.","productDescription":"vi, 46 p.","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063428","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":300951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151102.png"},{"id":300950,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1102/pdf/ofr2015-1102.pdf","text":"Report","size":"545 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300949,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1102/"}],"country":"United States","state":"California","otherGeospatial":"Kings Canyon National Parks, Sequoia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.4708251953125,\n 37.02886944696474\n ],\n [\n -118.98193359375,\n 36.43454191900892\n ],\n [\n -118.83911132812499,\n 36.14231087352999\n ],\n [\n -118.01513671875,\n 36.146746777814364\n ],\n [\n -118.05908203124999,\n 36.230981283477924\n ],\n [\n -118.037109375,\n 36.46105407505434\n ],\n [\n -118.267822265625,\n 36.68163606561519\n ],\n [\n -118.311767578125,\n 36.804886560237236\n ],\n [\n -118.3172607421875,\n 37.02886944696474\n ],\n [\n -118.35571289062499,\n 37.068327517596586\n ],\n [\n -119.4708251953125,\n 37.02886944696474\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"556d741ce4b0d9246a9f9963","contributors":{"authors":[{"text":"Klinger, Robert C. 0000-0003-3193-3199 rcklinger@usgs.gov","orcid":"https://orcid.org/0000-0003-3193-3199","contributorId":5395,"corporation":false,"usgs":true,"family":"Klinger","given":"Robert","email":"rcklinger@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":548026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Few, Alexandra P.","contributorId":140965,"corporation":false,"usgs":false,"family":"Few","given":"Alexandra","email":"","middleInitial":"P.","affiliations":[{"id":13632,"text":"CDFW, Bishop, CA","active":true,"usgs":false}],"preferred":false,"id":548027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knox, Kathleen A.","contributorId":140966,"corporation":false,"usgs":false,"family":"Knox","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[{"id":13632,"text":"CDFW, Bishop, CA","active":true,"usgs":false}],"preferred":false,"id":548028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatfield, Brian E.","contributorId":140967,"corporation":false,"usgs":false,"family":"Hatfield","given":"Brian","email":"","middleInitial":"E.","affiliations":[{"id":13632,"text":"CDFW, Bishop, CA","active":true,"usgs":false}],"preferred":false,"id":548029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Jonathan","contributorId":139380,"corporation":false,"usgs":false,"family":"Clark","given":"Jonathan","email":"","affiliations":[{"id":12456,"text":"former USGS scientist","active":true,"usgs":false}],"preferred":false,"id":548030,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"German, David W.","contributorId":140968,"corporation":false,"usgs":false,"family":"German","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":13632,"text":"CDFW, Bishop, CA","active":true,"usgs":false}],"preferred":false,"id":548031,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stephenson, Thomas R.","contributorId":64114,"corporation":false,"usgs":true,"family":"Stephenson","given":"Thomas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":548032,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70160778,"text":"70160778 - 2015 - Potential impact of Chironomus plumosus larvae on hypolimnetic oxygen in the central basin of Lake Erie","interactions":[],"lastModifiedDate":"2015-12-30T13:59:56","indexId":"70160778","displayToPublicDate":"2015-06-01T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Potential impact of Chironomus plumosus larvae on hypolimnetic oxygen in the central basin of Lake Erie","docAbstract":"Previous studies have indicated that burrow-irrigating infauna can increase sediment oxygen demand (SOD) and impact hypolimnetic oxygen in stratified lakes. We conducted laboratory microcosm experiments and computer simulations with larvae of the burrowing benthic midge Chironomus plumosus to quantify burrow oxygen uptake rates and subsequent contribution to sediment oxygen demand in central Lake Erie. Burrow oxygen uptake and water flow velocities through burrows were measured using oxygen microelectrodes and hot film anemometry, respectively. Burrow oxygen consumption averaged 2.66 × 10− 10 (SE = ± 7.82 × 10− 11) mol O2/burrow/s at 24 °C and 9.64 × 10− 10 (SE = ± 4.86 × 10− 10) mol O2/burrow/s at 15 °C. In sealed microcosm experiments, larvae increased SOD 500% at 24 °C (density = 1508/m2) and 375% at 15 °C (density = 864/m2). To further evaluate effects of densities of C. plumosus burrows on SOD we developed a 3-D transport reaction model of the process. Using experimental data and chironomid abundance data in faunal surveys in 2009 and 2010, we estimated that bioirrigation by a population of 140 larvae/m2 could account for between 2.54 × 10− 11 mol/L/s (model results) and 5.58 × 10− 11 mol/L/s (experimental results) of the average 4.22 × 10− 11 mol/L/s oxygen depletion rate between 1970 and 2003, which could have accounted for 60–132% of the oxygen decline. At present, it appears that the population density of this species may be an important factor in development of hypoxic or anoxic conditions in central Lake Erie.
","language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Toronto","doi":"10.1016/j.jglr.2015.02.008","collaboration":"Soster (senior author; DePauw Univ), Matisoff (Case Western Univ), Edwards (Univ Niagara)","usgsCitation":"Soster, F.M., Matisoff, G., Schloesser, D.W., and Edwards, W.J., 2015, Potential impact of Chironomus plumosus larvae on hypolimnetic oxygen in the central basin of Lake Erie: Journal of Great Lakes Research, v. 41, no. 2, p. 348-357, https://doi.org/10.1016/j.jglr.2015.02.008.","productDescription":"10 p.","startPage":"348","endPage":"357","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061609","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.31986999511719,\n 41.43088670022892\n ],\n [\n -82.35557556152344,\n 41.426768045309\n ],\n [\n -82.38922119140625,\n 41.415440397070654\n ],\n [\n -82.43110656738281,\n 41.39741506646461\n ],\n [\n -82.47367858886717,\n 41.38299120166604\n ],\n [\n -82.51075744628906,\n 41.38196080315539\n ],\n [\n -82.55538940429688,\n 41.396384896536276\n ],\n [\n -82.58834838867188,\n 41.41235069554362\n ],\n [\n -82.60688781738281,\n 41.41852995163519\n ],\n [\n -82.65151977539062,\n 41.57025176609894\n ],\n [\n -82.63984680175781,\n 41.645722822493845\n ],\n [\n -82.54989624023438,\n 41.67342470920953\n ],\n [\n -82.48260498046875,\n 41.668808555620586\n ],\n [\n -82.35626220703124,\n 41.64623592868676\n ],\n [\n -82.29515075683594,\n 41.58925619641459\n ],\n [\n -82.3040771484375,\n 41.48389104267175\n ],\n [\n -82.31986999511719,\n 41.43088670022892\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56850ee1e4b0a04ef4933a9e","contributors":{"authors":[{"text":"Soster, Frederick M.","contributorId":9092,"corporation":false,"usgs":true,"family":"Soster","given":"Frederick","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":583873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matisoff, Gerald","contributorId":15046,"corporation":false,"usgs":true,"family":"Matisoff","given":"Gerald","email":"","affiliations":[],"preferred":false,"id":583874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schloesser, Donald W. dschloesser@usgs.gov","contributorId":3579,"corporation":false,"usgs":true,"family":"Schloesser","given":"Donald","email":"dschloesser@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, William J.","contributorId":47206,"corporation":false,"usgs":true,"family":"Edwards","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":583875,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70144300,"text":"70144300 - 2015 - Coupling geophysical investigation with hydrothermal modeling to constrain the enthalpy classification of a potential geothermal resource.","interactions":[],"lastModifiedDate":"2015-10-23T12:34:52","indexId":"70144300","displayToPublicDate":"2015-06-01T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Coupling geophysical investigation with hydrothermal modeling to constrain the enthalpy classification of a potential geothermal resource.","docAbstract":"An appreciable challenge in volcanology and geothermal resource development is to understand the relationships between volcanic systems and low-enthalpy geothermal resources. The enthalpy of an undeveloped geothermal resource in the Karckar region of Armenia is investigated by coupling geophysical and hydrothermal modeling. The results of 3-dimensional inversion of gravity data provide key inputs into a hydrothermal circulation model of the system and associated hot springs, which is used to evaluate possible geothermal system configurations. Hydraulic and thermal properties are specified using maximum a priori estimates. Limited constraints provided by temperature data collected from an existing down-gradient borehole indicate that the geothermal system can most likely be classified as low-enthalpy and liquid dominated. We find the heat source for the system is likely cooling quartz monzonite intrusions in the shallow subsurface and that meteoric recharge in the pull-apart basin circulates to depth, rises along basin-bounding faults and discharges at the hot springs. While other combinations of subsurface properties and geothermal system configurations may fit the temperature distribution equally well, we demonstrate that the low-enthalpy system is reasonably explained based largely on interpretation of surface geophysical data and relatively simple models.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.jvolgeores.2015.03.020","usgsCitation":"White, J., Karakhanian, A., Connor, C., Connor, L., Hughes, J.D., Malservisi, R., and Wetmore, P., 2015, Coupling geophysical investigation with hydrothermal modeling to constrain the enthalpy classification of a potential geothermal resource.: Journal of Volcanology and Geothermal Research, v. 298, p. 59-70, https://doi.org/10.1016/j.jvolgeores.2015.03.020.","productDescription":"12 p.","startPage":"59","endPage":"70","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055208","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":310594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Armenia","otherGeospatial":"Karckar Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 42.34130859375,\n 38.38042167460681\n ],\n [\n 42.34130859375,\n 41.62776153144345\n ],\n [\n 47.8564453125,\n 41.62776153144345\n ],\n [\n 47.8564453125,\n 38.38042167460681\n ],\n [\n 42.34130859375,\n 38.38042167460681\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"298","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562b5a2be4b00162522207c6","contributors":{"authors":[{"text":"White, Jeremy T. jwhite@usgs.gov","contributorId":3930,"corporation":false,"usgs":true,"family":"White","given":"Jeremy T.","email":"jwhite@usgs.gov","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":false,"id":543463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karakhanian, Arkadi","contributorId":139920,"corporation":false,"usgs":false,"family":"Karakhanian","given":"Arkadi","email":"","affiliations":[{"id":13315,"text":"Georisk Scientific Research Company","active":true,"usgs":false}],"preferred":false,"id":543464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connor, Chuck","contributorId":139921,"corporation":false,"usgs":false,"family":"Connor","given":"Chuck","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":543465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Connor, Laura","contributorId":139922,"corporation":false,"usgs":false,"family":"Connor","given":"Laura","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":543466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":543467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Malservisi, Rocco","contributorId":139923,"corporation":false,"usgs":false,"family":"Malservisi","given":"Rocco","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":543468,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wetmore, Paul","contributorId":139924,"corporation":false,"usgs":false,"family":"Wetmore","given":"Paul","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":543469,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203358,"text":"70203358 - 2015 - Modeling and management of pit lake water chemistry 2: Case studies","interactions":[],"lastModifiedDate":"2019-05-07T13:32:35","indexId":"70203358","displayToPublicDate":"2015-06-01T13:28:17","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Modeling and management of pit lake water chemistry 2: Case studies","docAbstract":"Pit lakes, a common product of open pit mining techniques, may become long-term, post-mining environmental risks or long-term, post-mining water resources depending upon management decisions. This study reviews two published pit lake modeling studies and one pit lake monitoring program in order to increase the transparency of approaches used in pit lake prediction and management. The first model is a two-year limnological simulation of the existing Dexter pit lake, Nevada, USA that accurately modeled temperature profiles, salinity profiles, and turnover events observed between 1999 and 2000. The second model is a 55-year prediction of a future pit lake in the Martha Mine, New Zealand that identified the need for additional mitigation and evaluated potential effects of cost-effective mitigation options. The final study reviews eight years of monitoring data collected from the Berkeley pit lake, Montana, USA, from 2004 to 2012. This study identifies changes in the physical limnology and water quality of the pit lake that resulted from metal recovery operations, and highlights the value of monitoring programs in general. Whereas these pit lakes are different in many ways, the management tools discussed herein maximized the value and understanding of the post-mining resources.
Late-middle and late Pleistocene, and Holocene, inland aeolian sand and loess blanket >90,000 km2 of the unglaciated eastern United States of America (USA). Deposits are most extensive in the Lower Mississippi Valley (LMV) and Atlantic Coastal Plain (ACP), areas presently lacking significant aeolian activity. They provide evidence of paleoclimate intervals when wind erosion and deposition were dominant land-altering processes. This study synthesizes available data for aeolian sand deposits in the LMV, the Eastern Gulf Coastal Plain (EGCP) and the ACP, and loess deposits in the Middle Atlantic Coastal Plain (MACP). Data indicate: (a) the most recent major aeolian activity occurred in response to and coincident with growth and decay of the Laurentide Ice Sheet (LIS); (b) by ∼40 ka, aeolian processes greatly influenced landscape evolution in all three regions; (c) aeolian activity peaked in OIS2; (d) OIS3 and OIS2 aeolian records are in regional agreement with paleoecological records; and (e) limited aeolian activity occurred in the Holocene (EGCP and ACP). Paleoclimate and atmospheric-circulation models (PCMs/ACMs) for the last glacial maximum (LGM) show westerly winter winds for the unglaciated eastern USA, but do not resolve documented W and SW winds in the SEACP and WNW and N winds in the MACP. The minimum areal extent of aeolian deposits in the EGCP and ACP is ∼10,000 km2. For the LMV, it is >80,000 km2. Based on these estimates, published PCMs/ACMs likely underrepresent the areal extent of LGM aeolian activity, as well as the extent and complexity of climatic changes during this interval.
","language":"English","publisher":"International Society of Aeolian Research","publisherLocation":"Amsterdam","doi":"10.1016/j.aeolia.2015.01.011","usgsCitation":"Markewich, H.W., Litwin, R.J., Wysocki, D., and Pavich, M.J., 2015, Synthesis on Quaternary aeolian research in the unglaciated eastern United States: Aeolian Research, v. 17, p. 139-191, https://doi.org/10.1016/j.aeolia.2015.01.011.","productDescription":"53 p.","startPage":"139","endPage":"191","numberOfPages":"53","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062506","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":308016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55f15833e4b0dacf699eb983","contributors":{"authors":[{"text":"Markewich, Helaine W. 0000-0001-9656-3243 helainem@usgs.gov","orcid":"https://orcid.org/0000-0001-9656-3243","contributorId":2008,"corporation":false,"usgs":true,"family":"Markewich","given":"Helaine","email":"helainem@usgs.gov","middleInitial":"W.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":571450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Litwin, Ronald J. 0000-0002-8661-1296 rlitwin@usgs.gov","orcid":"https://orcid.org/0000-0002-8661-1296","contributorId":2478,"corporation":false,"usgs":true,"family":"Litwin","given":"Ronald","email":"rlitwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":571453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wysocki, Douglas A.","contributorId":61320,"corporation":false,"usgs":true,"family":"Wysocki","given":"Douglas A.","affiliations":[],"preferred":false,"id":571452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pavich, Milan J. mpavich@usgs.gov","contributorId":2348,"corporation":false,"usgs":true,"family":"Pavich","given":"Milan","email":"mpavich@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":571451,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70154992,"text":"70154992 - 2015 - The role of the geophysical template and environmental regimes in controlling stream-living trout populations","interactions":[],"lastModifiedDate":"2017-11-22T18:03:32","indexId":"70154992","displayToPublicDate":"2015-06-01T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The role of the geophysical template and environmental regimes in controlling stream-living trout populations","docAbstract":"The importance of multiple processes and instream factors to aquatic biota has been explored extensively, but questions remain about how local spatiotemporal variability of aquatic biota is tied to environmental regimes and the geophysical template of streams. We used an individual-based trout model to explore the relative role of the geophysical template versus environmental regimes on biomass of trout (Oncorhynchus clarkii clarkii). We parameterized the model with observed data from each of the four headwater streams (their local geophysical template and environmental regime) and then ran 12 simulations where we replaced environmental regimes (stream temperature, flow, turbidity) of a given stream with values from each neighboring stream while keeping the geophysical template fixed. We also performed single-parameter sensitivity analyses on the model results from each of the four streams. Although our modeled findings show that trout biomass is most responsive to changes in the geophysical template of streams, they also reveal that biomass is restricted by available habitat during seasonal low flow, which is a product of both the stream’s geophysical template and flow regime. Our modeled results suggest that differences in the geophysical template among streams render trout more or less sensitive to environmental change, emphasizing the importance of local fish–habitat relationships in streams.
","language":"English","publisher":"National Research Council Canada","publisherLocation":"Ottawa","doi":"10.1139/cjfas-2014-0377","collaboration":"U.S. Forest Service, Weyerhaeuser Corporation","usgsCitation":"Penaluna, B.E., Railsback, S., Dunham, J., Johnson, S., Bilby, R.E., and Skaugset, A.E., 2015, The role of the geophysical template and environmental regimes in controlling stream-living trout populations: Canadian Journal of Fisheries and Aquatic Sciences, v. 72, no. 6, p. 893-901, https://doi.org/10.1139/cjfas-2014-0377.","productDescription":"9 p.","startPage":"893","endPage":"901","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052252","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":305960,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b361b6e4b09a3b01b5dabd","contributors":{"authors":[{"text":"Penaluna, Brooke E.","contributorId":104817,"corporation":false,"usgs":true,"family":"Penaluna","given":"Brooke","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":564477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Railsback, Steve F.","contributorId":68449,"corporation":false,"usgs":true,"family":"Railsback","given":"Steve F.","affiliations":[],"preferred":false,"id":565685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B. jdunham@usgs.gov","contributorId":145517,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","email":"jdunham@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":564476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, S.","contributorId":70323,"corporation":false,"usgs":true,"family":"Johnson","given":"S.","email":"","affiliations":[],"preferred":false,"id":565686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bilby, Richard E.","contributorId":145928,"corporation":false,"usgs":false,"family":"Bilby","given":"Richard","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":565687,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skaugset, Arne E.","contributorId":145929,"corporation":false,"usgs":false,"family":"Skaugset","given":"Arne","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":565688,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70155261,"text":"70155261 - 2015 - The leading mode of observed and CMIP5 ENSO-residual sea surface temperatures and associated changes in Indo-Pacific climate","interactions":[],"lastModifiedDate":"2018-03-27T13:00:12","indexId":"70155261","displayToPublicDate":"2015-06-01T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"The leading mode of observed and CMIP5 ENSO-residual sea surface temperatures and associated changes in Indo-Pacific climate","docAbstract":"SSTs in the western Pacific Ocean have tracked closely with CMIP5 simulations despite recent hiatus cooling in the eastern Pacific. This paper quantifies these similarities and associated circulation and precipitation variations using the first global 1900–2012 ENSO-residual empirical orthogonal functions (EOFs) of 35 variables: observed SSTs; 28 CMIP5 SST simulations; Simple Ocean Data Assimilation (SODA) 25-, 70-, and 171-m ocean temperatures and sea surface heights (SSHs); and Twentieth Century Reanalysis, version 2 (20CRv2), surface winds and precipitation.
\nWhile estimated independently, these leading EOFs across all variables fit together in a meaningful way, and the authors refer to them jointly as the west Pacific warming mode (WPWM). WPWM SST EOFs correspond closely in space and time. Their spatial patterns form a “western V” extending from the Maritime Continent into the extratropical Pacific. Their temporal principal components (PCs) have increased rapidly since 1990; this increase has been primarily due to radiative forcing and not natural decadal variability.
\nWPWM circulation changes appear consistent with a Matsuno–Gill-like atmospheric response associated with an ocean–atmosphere dipole structure contrasting increased (decreased) western (eastern) Pacific precipitation, SSHs, and ocean temperatures. These changes have enhanced the Walker circulation and modulated weather on a global scale. An AGCM experiment and the WPWM of global boreal spring precipitation indicate significant drying across parts of East Africa, the Middle East, the southwestern United States, southern South America, and Asia. Changes in the WPWM have tracked closely with precipitation and the increase in drought frequency over the semiarid and water-insecure areas of East Africa, the Middle East, and southwest Asia.
","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JCLI-D-14-00334.1","usgsCitation":"Funk, C.C., and Hoell. Andrew, 2015, The leading mode of observed and CMIP5 ENSO-residual sea surface temperatures and associated changes in Indo-Pacific climate: Journal of Climate, v. 28, no. 11, p. 4309-4329, https://doi.org/10.1175/JCLI-D-14-00334.1.","productDescription":"21 p.","startPage":"4309","endPage":"4329","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056779","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":306492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-27","publicationStatus":"PW","scienceBaseUri":"57f7ef1ae4b0bc0bec09eee2","contributors":{"authors":[{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565415,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoell. Andrew","contributorId":145831,"corporation":false,"usgs":false,"family":"Hoell. Andrew","affiliations":[{"id":13549,"text":"UC Santa Barbara Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565416,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148564,"text":"70148564 - 2015 - Predicting alpine headwater stream intermittency: a case study in the northern Rocky Mountains","interactions":[],"lastModifiedDate":"2015-09-16T09:26:57","indexId":"70148564","displayToPublicDate":"2015-06-01T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3892,"text":"Ecohydrology & Hydrobiology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting alpine headwater stream intermittency: a case study in the northern Rocky Mountains","docAbstract":"This investigation used climatic, geological, and environmental data coupled with observational stream intermittency data to predict alpine headwater stream intermittency. Prediction was made using a random forest classification model. Results showed that the most important variables in the prediction model were snowpack persistence, represented by average snow extent from March through July, mean annual mean monthly minimum temperature, and surface geology types. For stream catchments with intermittent headwater streams, snowpack, on average, persisted until early June, whereas for stream catchments with perennial headwater streams, snowpack, on average, persisted until early July. Additionally, on average, stream catchments with intermittent headwater streams were about 0.7 °C warmer than stream catchments with perennial headwater streams. Finally, headwater stream catchments primarily underlain by coarse, permeable sediment are significantly more likely to have intermittent headwater streams than those primarily underlain by impermeable bedrock. Comparison of the predicted streamflow classification with observed stream status indicated a four percent classification error for first-order streams and a 21 percent classification error for all stream orders in the study area.
","language":"English","publisher":"International Centre for Ecology","publisherLocation":"Warsaw","doi":"10.1016/j.ecohyd.2015.04.002","usgsCitation":"Sando, R., and Blasch, K.W., 2015, Predicting alpine headwater stream intermittency: a case study in the northern Rocky Mountains: Ecohydrology & Hydrobiology, v. 15, no. 2, p. 68-80, https://doi.org/10.1016/j.ecohyd.2015.04.002.","productDescription":"13 p.","startPage":"68","endPage":"80","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052878","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":301221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557ff73ae4b023124e8ef98a","contributors":{"authors":[{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":3874,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","email":"","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":548640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blasch, Kyle W. 0000-0002-0590-0724 kblasch@usgs.gov","orcid":"https://orcid.org/0000-0002-0590-0724","contributorId":1631,"corporation":false,"usgs":true,"family":"Blasch","given":"Kyle","email":"kblasch@usgs.gov","middleInitial":"W.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548641,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148562,"text":"70148562 - 2015 - Performance metrics and variance partitioning reveal sources of uncertainty in species distribution models","interactions":[],"lastModifiedDate":"2015-06-15T10:14:45","indexId":"70148562","displayToPublicDate":"2015-06-01T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Performance metrics and variance partitioning reveal sources of uncertainty in species distribution models","docAbstract":"Species distribution models (SDMs) are widely used in basic and applied ecology, making it important to understand sources and magnitudes of uncertainty in SDM performance and predictions. We analyzed SDM performance and partitioned variance among prediction maps for 15 rare vertebrate species in the southeastern USA using all possible combinations of seven potential sources of uncertainty in SDMs: algorithms, climate datasets, model domain, species presences, variable collinearity, CO2 emissions scenarios, and general circulation models. The choice of modeling algorithm was the greatest source of uncertainty in SDM performance and prediction maps, with some additional variation in performance associated with the comprehensiveness of the species presences used for modeling. Other sources of uncertainty that have received attention in the SDM literature such as variable collinearity and model domain contributed little to differences in SDM performance or predictions in this study. Predictions from different algorithms tended to be more variable at northern range margins for species with more northern distributions, which may complicate conservation planning at the leading edge of species' geographic ranges. The clear message emerging from this work is that researchers should use multiple algorithms for modeling rather than relying on predictions from a single algorithm, invest resources in compiling a comprehensive set of species presences, and explicitly evaluate uncertainty in SDM predictions at leading range margins.
","language":"English","publisher":"Elsevier Science B.V.","publisherLocation":"Amsterdam","doi":"10.1016/j.ecolmodel.2015.03.017","usgsCitation":"Watling, J., Brandt, L., Bucklin, D., Fujisaki, I., Mazzotti, F., Romanach, S.S., and Speroterra, C., 2015, Performance metrics and variance partitioning reveal sources of uncertainty in species distribution models: Ecological Modelling, v. 309-310, p. 48-59, https://doi.org/10.1016/j.ecolmodel.2015.03.017.","productDescription":"12 p.","startPage":"48","endPage":"59","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061287","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":301222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"309-310","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557ff73ae4b023124e8ef986","contributors":{"authors":[{"text":"Watling, James I.","contributorId":101963,"corporation":false,"usgs":true,"family":"Watling","given":"James I.","affiliations":[],"preferred":false,"id":548632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Laura A.","contributorId":18608,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":548633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bucklin, David N.","contributorId":58963,"corporation":false,"usgs":true,"family":"Bucklin","given":"David N.","affiliations":[],"preferred":false,"id":548634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fujisaki, Ikuko","contributorId":42152,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":548635,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":548636,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":548631,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Speroterra, Carolina","contributorId":34451,"corporation":false,"usgs":true,"family":"Speroterra","given":"Carolina","affiliations":[],"preferred":false,"id":548637,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70148546,"text":"70148546 - 2015 - High-frequency, long-duration water sampling in acid mine drainage studies: a short review of current methods and recent advances in automated water samplers","interactions":[],"lastModifiedDate":"2015-06-12T09:37:16","indexId":"70148546","displayToPublicDate":"2015-06-01T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"High-frequency, long-duration water sampling in acid mine drainage studies: a short review of current methods and recent advances in automated water samplers","docAbstract":"Hand-collected grab samples are the most common water sampling method but using grab sampling to monitor temporally variable aquatic processes such as diel metal cycling or episodic events is rarely feasible or cost-effective. Currently available automated samplers are a proven, widely used technology and typically collect up to 24 samples during a deployment. However, these automated samplers are not well suited for long-term sampling in remote areas or in freezing conditions. There is a critical need for low-cost, long-duration, high-frequency water sampling technology to improve our understanding of the geochemical response to temporally variable processes. This review article will examine recent developments in automated water sampler technology and utilize selected field data from acid mine drainage studies to illustrate the utility of high-frequency, long-duration water sampling.
","language":"English","publisher":"International Association of Geochemistry and Cosmochemistry","publisherLocation":"New York, NY","doi":"10.1016/j.apgeochem.2015.04.004","usgsCitation":"Chapin, T., 2015, High-frequency, long-duration water sampling in acid mine drainage studies: a short review of current methods and recent advances in automated water samplers: Applied Geochemistry, v. 59, p. 118-124, https://doi.org/10.1016/j.apgeochem.2015.04.004.","productDescription":"7 p.","startPage":"118","endPage":"124","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054825","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":472043,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2015.04.004","text":"Publisher Index Page"},{"id":301184,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557c02d2e4b023124e8edf21","chorus":{"doi":"10.1016/j.apgeochem.2015.04.004","url":"http://dx.doi.org/10.1016/j.apgeochem.2015.04.004","publisher":"Elsevier BV","authors":"Chapin Thomas P.","journalName":"Applied Geochemistry","publicationDate":"8/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Chapin, Thomas 0000-0001-6587-0734 tchapin@usgs.gov","orcid":"https://orcid.org/0000-0001-6587-0734","contributorId":758,"corporation":false,"usgs":true,"family":"Chapin","given":"Thomas","email":"tchapin@usgs.gov","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":548566,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}