From October 2008 until present, dozens of small impulsive explosive eruptions occurred from the Overlook vent on the southeast side of Halema‘uma‘u Crater, at Kīlauea volcano, USA. These eruptions were triggered by rockfalls from the walls of the volcanic vent and conduit onto the top of the lava column. Here we use microtextural observations and data from clasts erupted during the well-characterized 12 October 2008 explosive eruption at Halema‘uma‘u to extend existing models of eruption triggering. We present a potential mechanism for this eruption by combining microtextural observations with existing geophysical and visual data sets. We measure the size and number density of bubbles preserved in juvenile ejecta using 2D images and X-ray microtomography. Our data suggest that accumulations of large bubbles with diameters of >50μm to at least millimeters existed at shallow levels within the conduit prior to the 12 October 2008 explosion. Furthermore, a high number density of small bubbles <50 μm is measured in the clasts, implying very rapid nucleation of bubbles. Visual observations, combined with preexisting geophysical data, suggest that the impact of rockfalls onto the magma free surface induces pressure changes over short timescales that (1) nucleated new additional bubbles in the shallow conduit leading to high number densities of small bubbles and (2) expanded the preexisting bubbles driving upward acceleration. The trigger of eruption and bubble nucleation is thus external to the degassing system.
","language":"English","doi":"10.1029/2012JB009496","usgsCitation":"Carey, R.J., Manga, M., Degruyter, W., Swanson, D., Houghton, B.F., Orr, T., and Patrick, M.R., 2012, Externally triggered renewed bubble nucleation in basaltic magma: the 12 October 2008 eruption at Halema‘uma‘u Overlook vent, Kīlauea, Hawai‘i, USA: Journal of Geophysical Research B: Solid Earth, v. 117, no. 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2012 - The effect of nonylphenol on gene expression in Atlantic salmon smolts","interactions":[],"lastModifiedDate":"2013-03-11T21:26:16","indexId":"70043557","displayToPublicDate":"2012-11-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":874,"text":"Aquatic Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"The effect of nonylphenol on gene expression in Atlantic salmon smolts","docAbstract":"The parr–smolt transformation in Atlantic salmon (Salmo salar) is a complex developmental process that culminates in the ability to migrate to and live in seawater. Exposure to environmental contaminants like nonylphenol can disrupt smolt development and may be a contributing factor in salmon population declines. We used GRASP 16K cDNA microarrays to investigate the effects of nonylphenol on gene expression in Atlantic salmon smolts. Nonylphenol exposure reduced gill Na+/K+-ATPase activity and plasma cortisol and triiodothyronine levels. Transcriptional responses were examined in gill, liver, olfactory rosettes, hypothalamus, and pituitary. Expression of 124 features was significantly altered in the liver of fish exposed to nonylphenol; little to no transcriptional effects were observed in other tissues. mRNA abundance of genes involved in protein biosynthesis, folding, modification, transport and catabolism; nucleosome assembly, cell cycle, cell differentiation, microtubule-based movement, electron transport, and response to stress increased in nonylphenol-treated fish. This study expands our understanding of the effect of nonylphenol on smolting and provides potential targets for development of biomarkers.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Aquatic Toxicology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.aquatox.2012.05.009","usgsCitation":"Robertson, L.S., and McCormick, S., 2012, The effect of nonylphenol on gene expression in Atlantic salmon smolts: Aquatic Toxicology, v. 122-123, p. 36-43, https://doi.org/10.1016/j.aquatox.2012.05.009.","startPage":"36","endPage":"43","ipdsId":"IP-037923","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":269101,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.aquatox.2012.05.009"},{"id":269102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"122-123","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"513efd00e4b0dcc7339693e4","contributors":{"authors":[{"text":"Robertson, Laura S. lrobertson@usgs.gov","contributorId":2288,"corporation":false,"usgs":true,"family":"Robertson","given":"Laura","email":"lrobertson@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":473832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":2197,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen D.","email":"smccormick@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":473831,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70214974,"text":"70214974 - 2012 - Holocene diatom flora and climate history of Medicine Lake, Northern California, USA","interactions":[],"lastModifiedDate":"2020-10-06T20:44:11.072398","indexId":"70214974","displayToPublicDate":"2012-10-31T10:18:34","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5934,"text":"Nova Hedwigia, Beiheft","printIssn":"1438-9134","active":false,"publicationSubtype":{"id":10}},"title":"Holocene diatom flora and climate history of Medicine Lake, Northern California, USA","docAbstract":"A 226-cm-long sediment core spanning the past ~ 11,400 years was recovered from Medicine Lake, on the Modoc Plateau in northeastern California. Diatom assemblages provide a record of lake level that is driven by local and regional climate changes and changes in basin morphology due to the activity of Medicine Lake volcano. The diatom record indicates that throughout its history, Medicine Lake was an oligotrophic lake, dominated by Cyclotella stelligera and C. pseudostelligera. Variations in lake level are suggested by changes in the structure of the diatom assemblages. The lowest part of the core (11,400 to 10,300 cal yr B.P.) contains the transition from glacial to interglacial conditions. From about 11,000 to 5500 cal yr B.P., the lake filled two small, steep-sided basins or one basin with two steep-sided sub-basins connected by a shallow shelf. During this time, the diatom evidence (Cyclotella/Navicula ratio) indicates that effective moisture increased, leading to a deeper lake. Over the past 5500 years the diatom record indicates fluctuations in lake level. The change in lake level pattern from one of increasing depth prior to about 5500 cal yr B.P. to one of variable depths may be related to changes in the morphology of the Medicine Lake basin in addition to shifts in local and regional climate. During this latter period the Cyclotella/Navicula ratio varies, suggesting that the level of the lake fluctuated, resulting in changes in colonizable shelf area.
","language":"English","publisher":"Schweitzerbart and Borntraeger Science Publishers","usgsCitation":"Starratt, S.W., 2012, Holocene diatom flora and climate history of Medicine Lake, Northern California, USA: Nova Hedwigia, Beiheft, v. 141, p. 485-504.","productDescription":"30 p.","startPage":"485","endPage":"504","ipdsId":"IP-027311","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":379045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379030,"type":{"id":15,"text":"Index Page"},"url":"https://www.schweizerbart.de/publications/detail/isbn/9783443510633/Nova_Hedwigia_Beiheft_141"}],"country":"United States","state":"California","otherGeospatial":"Medicine Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.62311553955077,\n 41.56909591089941\n ],\n [\n -121.5757369995117,\n 41.56909591089941\n ],\n [\n -121.5757369995117,\n 41.59567534818466\n ],\n [\n -121.62311553955077,\n 41.59567534818466\n ],\n [\n -121.62311553955077,\n 41.56909591089941\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"141","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":800473,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70041584,"text":"70041584 - 2012 - Developing accurate survey methods for estimating population sizes and trends of the critically endangered Nihoa Millerbird and Nihoa Finch.","interactions":[],"lastModifiedDate":"2018-01-05T12:39:22","indexId":"70041584","displayToPublicDate":"2012-10-31T02:30:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-034","title":"Developing accurate survey methods for estimating population sizes and trends of the critically endangered Nihoa Millerbird and Nihoa Finch.","docAbstract":"This report describes the results of a comparative study of bird survey methods undertaken for the purpose of improving assessments of the conservation status for the two endemic passerines on the Island of Nihoa—Nihoa Millerbird (Sylviidae: Acrocephalus familiaris kingi) and Nihoa Finch (Fringilidae: Telespiza ultima; also referred herein as millerbird and finch)—both listed as endangered under the Federal Endangered Species Act (ESA) and Hawai`i Revised Statutes 195D. The current survey protocol, implemented since 1967, has produced a highly variable range of counts for both the millerbird and finch, making difficult assessments of population size and trend. This report details the analyses of bird survey data collected in 2010 and 2011 in which three survey methods were compared―strip-transect, line-transect, and point-transect sampling―and provides recommendations for improved survey methods and protocols. Funding for this research was provided through a Science Support Partnership grant sponsored jointly by the U.S. Geological Survey (USGS) and the U.S. Fish and Wildlife Service (USFWS).
\nPoint-transect surveys indicated that millerbirds were more abundant than shown by the striptransect method, and were estimated at 802 birds in 2010 (95%CI = 652 – 964) and 704 birds in 2011 (95%CI = 579 – 837). Point-transect surveys yielded population estimates with improved precision which will permit trends to be detected in shorter time periods and with greater statistical power than is available from strip-transect survey methods. Mean finch population estimates and associated uncertainty were not markedly different among the three survey methods, but the performance of models used to estimate density and population size are expected to improve as the data from additional surveys are incorporated. Using the pointtransect survey, the mean finch population size was estimated at 2,917 birds in 2010 (95%CI = 2,037 – 3,965) and 2,461 birds in 2011 (95%CI = 1,682 – 3,348). Preliminary testing of the line-transect method in 2011 showed that it would not generate sufficient detections to effectively model bird density, and consequently, relatively precise population size estimates. Both species were fairly evenly distributed across Nihoa and appear to occur in all or nearly all available habitat. The time expended and area traversed by observers was similar among survey methods; however, point-transect surveys do not require that observers walk a straight transect line, thereby allowing them to avoid culturally or biologically sensitive areas and minimize the adverse effects of recurrent travel to any particular area. In general, pointtransect surveys detect more birds than strip-survey methods, thereby improving precision and resulting population size and trend estimation. The method is also better suited for the steep and uneven terrain of Nihoa
","language":"English","publisher":"UniverIsity of Hawaii at Hilio","publisherLocation":"Hilo, HI","usgsCitation":"Gorresen, P.M., Camp, R.J., Brinck, K., and Farmer, C., 2012, Developing accurate survey methods for estimating population sizes and trends of the critically endangered Nihoa Millerbird and Nihoa Finch.: Technical Report HCSU-034, v, 70 p.","productDescription":"v, 70 p.","numberOfPages":"77","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041045","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad43e4b05e859bdfb8c4","contributors":{"authors":[{"text":"Gorresen, P. Marcos mgorresen@usgs.gov","contributorId":3975,"corporation":false,"usgs":true,"family":"Gorresen","given":"P.","email":"mgorresen@usgs.gov","middleInitial":"Marcos","affiliations":[],"preferred":false,"id":644962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":116175,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":false,"id":644963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":644964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farmer, Chris cfarmer@usgs.gov","contributorId":3681,"corporation":false,"usgs":true,"family":"Farmer","given":"Chris","email":"cfarmer@usgs.gov","affiliations":[],"preferred":true,"id":644965,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70040555,"text":"70040555 - 2012 - Predicting biological condition in southern California streams","interactions":[],"lastModifiedDate":"2012-11-01T14:54:04","indexId":"70040555","displayToPublicDate":"2012-10-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2603,"text":"Landscape and Urban Planning","active":true,"publicationSubtype":{"id":10}},"title":"Predicting biological condition in southern California streams","docAbstract":"As understanding of the complex relations among environmental stressors and biological responses improves, a logical next step is predictive modeling of biological condition at unsampled sites. We developed a boosted regression tree (BRT) model of biological condition, as measured by a benthic macroinvertebrate index of biotic integrity (BIBI), for streams in urbanized Southern Coastal California. We also developed a multiple linear regression (MLR) model as a benchmark for comparison with the BRT model. The BRT model explained 66% of the variance in B-IBI, identifying watershed population density and combined percentage agricultural and urban land cover in the riparian buffer as the most important predictors of B-IBI, but with watershed mean precipitation and watershed density of manmade channels also important. The MLR model explained 48% of the variance in B-IBI and included watershed population density and combined percentage agricultural and urban land cover in the riparian buffer. For a verification data set, the BRT model correctly classified 75% of impaired sites (B-IBI < 40) and 78% of unimpaired sites (B-IBI = 40). For the same verification data set, the MLR model correctly classified 69% of impaired sites and 87% of unimpaired sites. The BRT model should not be used to predict B-IBI for specific sites; however, the model can be useful for general applications such as identifying and prioritizing regions for monitoring, remediation or preservation, stratifying new bioassessments according to anticipated biological condition, or assessing the potential for change in stream biological condition based on anticipated changes in population density and development in stream buffers.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landscape and Urban Planning","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.landurbplan.2012.07.009","usgsCitation":"Brown, L.R., May, J., Rehn, A.C., Ode, P.R., Waite, I.R., and Kennen, J., 2012, Predicting biological condition in southern California streams: Landscape and Urban Planning, v. 108, no. 1, p. 17-27, https://doi.org/10.1016/j.landurbplan.2012.07.009.","productDescription":"11 p.","startPage":"17","endPage":"27","numberOfPages":"11","ipdsId":"IP-022005","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":262887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262886,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.landurbplan.2012.07.009"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.0 ], [ -114.13,42.0 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","volume":"108","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e17e8fe4b0ff1e7c578675","contributors":{"authors":[{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"May, Jason T. 0000-0002-5699-2112","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":14791,"corporation":false,"usgs":true,"family":"May","given":"Jason T.","affiliations":[],"preferred":false,"id":468504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rehn, Andrew C.","contributorId":47650,"corporation":false,"usgs":true,"family":"Rehn","given":"Andrew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":468506,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ode, Peter R.","contributorId":45968,"corporation":false,"usgs":true,"family":"Ode","given":"Peter","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":468505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468502,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468501,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70040578,"text":"70040578 - 2012 - Recent advances in applying decision science to managing national forests","interactions":[],"lastModifiedDate":"2012-11-01T16:12:13","indexId":"70040578","displayToPublicDate":"2012-10-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Recent advances in applying decision science to managing national forests","docAbstract":"Management of federal public forests to meet sustainability goals and multiple use regulations is an immense challenge. To succeed, we suggest use of formal decision science procedures and tools in the context of structured decision making (SDM). SDM entails four stages: problem structuring (framing the problem and defining objectives and evaluation criteria), problem analysis (defining alternatives, evaluating likely consequences, identifying key uncertainties, and analyzing tradeoffs), decision point (identifying the preferred alternative), and implementation and monitoring the preferred alternative with adaptive management feedbacks. We list a wide array of models, techniques, and tools available for each stage, and provide three case studies of their selected use in National Forest land management and project plans. Successful use of SDM involves participation by decision-makers, analysts, scientists, and stakeholders. We suggest specific areas for training and instituting SDM to foster transparency, rigor, clarity, and inclusiveness in formal decision processes regarding management of national forests.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Forest Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.foreco.2012.08.024","usgsCitation":"Marcot, B., Thompson, M.P., Runge, M.C., Thompson, F., McNulty, S., Cleaves, D., Tomosy, M., Fisher, L.A., and Andrew, B., 2012, Recent advances in applying decision science to managing national forests: Forest Ecology and Management, v. 285, p. 123-132, https://doi.org/10.1016/j.foreco.2012.08.024.","productDescription":"10 p.","startPage":"123","endPage":"132","numberOfPages":"12","ipdsId":"IP-040803","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":262900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262899,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.foreco.2012.08.024"}],"country":"United States","volume":"285","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e49d37e4b0e8fec6cda8ad","contributors":{"authors":[{"text":"Marcot, Bruce G.","contributorId":58015,"corporation":false,"usgs":true,"family":"Marcot","given":"Bruce G.","affiliations":[],"preferred":false,"id":468592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Matthew P.","contributorId":25045,"corporation":false,"usgs":true,"family":"Thompson","given":"Matthew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":468590,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":468588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Frank R.","contributorId":6730,"corporation":false,"usgs":true,"family":"Thompson","given":"Frank R.","affiliations":[],"preferred":false,"id":468589,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McNulty, Steven","contributorId":95765,"corporation":false,"usgs":true,"family":"McNulty","given":"Steven","affiliations":[],"preferred":false,"id":468596,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cleaves, David","contributorId":80972,"corporation":false,"usgs":true,"family":"Cleaves","given":"David","affiliations":[],"preferred":false,"id":468594,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tomosy, Monica","contributorId":70255,"corporation":false,"usgs":true,"family":"Tomosy","given":"Monica","email":"","affiliations":[],"preferred":false,"id":468593,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fisher, Larry A.","contributorId":80973,"corporation":false,"usgs":true,"family":"Fisher","given":"Larry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":468595,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Andrew, Bliss","contributorId":45970,"corporation":false,"usgs":true,"family":"Andrew","given":"Bliss","email":"","affiliations":[],"preferred":false,"id":468591,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70040531,"text":"ds730 - 2012 - Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2011","interactions":[],"lastModifiedDate":"2019-05-30T12:04:39","indexId":"ds730","displayToPublicDate":"2012-10-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"730","title":"Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2011","docAbstract":"Between January 1 and December 31, 2011, the Alaska Volcano Observatory (AVO) located 4,364 earthquakes, of which 3,651 occurred within 20 kilometers of the 33 volcanoes with seismograph subnetworks. There was no significant seismic activity above background levels in 2011 at these instrumented volcanic centers. This catalog includes locations, magnitudes, and statistics of the earthquakes located in 2011 with the station parameters, velocity models, and other files used to locate these earthquakes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds730","usgsCitation":"Dixon, J.P., Stihler, S.D., Power, J.A., and Searcy, C.K., 2012, Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2011: U.S. Geological Survey Data Series 730, Report: iv; 82 p.; Zip file, https://doi.org/10.3133/ds730.","productDescription":"Report: iv; 82 p.; Zip file","numberOfPages":"90","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":121,"text":"Alaska Volcano Observatory","active":false,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":262861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_730.jpg"},{"id":262855,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/730/","linkFileType":{"id":5,"text":"html"}},{"id":262857,"rank":1000,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/730/2011_AVO_Seismic_Catalog.zip","text":"Seismic Catalog","size":"14 MB","linkFileType":{"id":6,"text":"zip"},"description":"Seismic Catalog"},{"id":262856,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/730/pdf/ds730.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -181.82373046875,\n 50.86491125522503\n ],\n [\n -182.120361328125,\n 52.09975692575725\n ],\n [\n -170.33203125,\n 61.33353967329142\n ],\n [\n -153.45703125,\n 65.47650756256367\n ],\n [\n -141.15234374999997,\n 66.26685631430843\n ],\n [\n -141.15234374999997,\n 59.88893689676585\n ],\n [\n -153.8525390625,\n 53.69670647530323\n ],\n [\n -181.82373046875,\n 50.86491125522503\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5090e8dae4b0e1c52f42b7df","contributors":{"authors":[{"text":"Dixon, James P. 0000-0002-8478-9971 jpdixon@usgs.gov","orcid":"https://orcid.org/0000-0002-8478-9971","contributorId":3163,"corporation":false,"usgs":true,"family":"Dixon","given":"James","email":"jpdixon@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":468498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stihler, Scott D.","contributorId":31373,"corporation":false,"usgs":true,"family":"Stihler","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":468499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Power, John A. 0000-0002-7233-4398 jpower@usgs.gov","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":2768,"corporation":false,"usgs":true,"family":"Power","given":"John","email":"jpower@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":468497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Searcy, Cheryl K.","contributorId":107013,"corporation":false,"usgs":true,"family":"Searcy","given":"Cheryl","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":468500,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70040508,"text":"70040508 - 2012 - Watershed regressions for pesticides (warp) models for predicting atrazine concentrations in Corn Belt streams","interactions":[],"lastModifiedDate":"2012-10-29T17:16:28","indexId":"70040508","displayToPublicDate":"2012-10-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Watershed regressions for pesticides (warp) models for predicting atrazine concentrations in Corn Belt streams","docAbstract":"Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region-specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP-CB) were developed for annual maximum moving-average (14-, 21-, 30-, 60-, and 90-day durations) and annual 95th-percentile atrazine concentrations in streams of the Corn Belt region. The WARP-CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model-development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model-development sites. The WARP-CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine-use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP-CB models. The WARP-CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine-use intensities of 17 kg/km2 of watershed area or greater.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of the American Water Resources Association","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1752-1688.2012.00661.x","usgsCitation":"Stone, W.W., and Gilliom, R.J., 2012, Watershed regressions for pesticides (warp) models for predicting atrazine concentrations in Corn Belt streams: Journal of the American Water Resources Association, v. 48, no. 5, p. 970-986, https://doi.org/10.1111/j.1752-1688.2012.00661.x.","productDescription":"17 p.","startPage":"970","endPage":"986","numberOfPages":"17","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":262839,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262835,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1752-1688.2012.00661.x","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Corn Belt","volume":"48","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-05-31","publicationStatus":"PW","scienceBaseUri":"508f9790e4b0a1b43c29ca15","contributors":{"authors":[{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468490,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilliom, Robert J. rgilliom@usgs.gov","contributorId":488,"corporation":false,"usgs":true,"family":"Gilliom","given":"Robert","email":"rgilliom@usgs.gov","middleInitial":"J.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":468489,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70040504,"text":"70040504 - 2012 - A basin-scale approach for assessing water resources in a semiarid environment: San Diego region, California and Mexico","interactions":[],"lastModifiedDate":"2017-09-20T13:31:51","indexId":"70040504","displayToPublicDate":"2012-10-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A basin-scale approach for assessing water resources in a semiarid environment: San Diego region, California and Mexico","docAbstract":"Many basins throughout the world have sparse hydrologic and geologic data, but have increasing demands for water and a commensurate need for integrated understanding of surface and groundwater resources. This paper demonstrates a methodology for using a distributed parameter water-balance model, gaged surface-water flow, and a reconnaissance-level groundwater flow model to develop a first-order water balance. Flow amounts are rounded to the nearest 5 million cubic meters per year.
The San Diego River basin is 1 of 5 major drainage basins that drain to the San Diego coastal plain, the source of public water supply for the San Diego area. The distributed parameter water-balance model (Basin Characterization Model) was run at a monthly timestep for 1940–2009 to determine a median annual total water inflow of 120 million cubic meters per year for the San Diego region. The model was also run specifically for the San Diego River basin for 1982–2009 to provide constraints to model calibration and to evaluate the proportion of inflow that becomes groundwater discharge, resulting in a median annual total water inflow of 50 million cubic meters per year. On the basis of flow records for the San Diego River at Fashion Valley (US Geological Survey gaging station 11023000), when corrected for upper basin reservoir storage and imported water, the total is 30 million cubic meters per year. The difference between these two flow quantities defines the annual groundwater outflow from the San Diego River basin at 20 million cubic meters per year. These three flow components constitute a first-order water budget estimate for the San Diego River basin. The ratio of surface-water outflow and groundwater outflow to total water inflow are 0.6 and 0.4, respectively. Using total water inflow determined using the Basin Characterization Model for the entire San Diego region and the 0.4 partitioning factor, groundwater outflow from the San Diego region, through the coastal plain aquifer to the Pacific Ocean, is calculated to be approximately 50 million cubic meters per year.
The area-scale assessment of water resources highlights several hydrologic features of the San Diego region. Groundwater recharge is episodic; the Basin Characterization Model output shows that 90 percent of simulated recharge occurred during 3 percent of the 1982–2009 period. The groundwater aquifer may also be quite permeable. A reconnaissance-level groundwater flow model for the San Diego River basin was used to check the water budget estimates, and the basic interaction of the surface-water and groundwater system, and the flow values, were found to be reasonable. Horizontal hydraulic conductivity values of the volcanic and metavolcanic bedrock in San Diego region range from 1 to 10 m per day. Overall, results establish an initial hydrologic assessment formulated on the basis of sparse hydrologic data. The described flow variability, extrapolation, and unique characteristics represent a realistic view of current (2012) hydrologic understanding for the San Diego region.
We developed a methodology to predict brook trout (Salvelinus fontinalis) distribution using summer temperature metrics as predictor variables. Our analysis used long-term fish and hourly water temperature data from the Dog River, Vermont (USA). Commonly used metrics (e.g., mean, maximum, maximum 7-day maximum) tend to smooth the data so information on temperature variation is lost. Therefore, we developed a new set of metrics (called event metrics) to capture temperature variation by describing the frequency, area, duration, and magnitude of events that exceeded a user-defined temperature threshold. We used 16, 18, 20, and 22°C. We built linear discriminant models and tested and compared the event metrics against the commonly used metrics. Correct classification of the observations was 66% with event metrics and 87% with commonly used metrics. However, combined event and commonly used metrics correctly classified 92%. Of the four individual temperature thresholds, it was difficult to assess which threshold had the “best” accuracy. The 16°C threshold had slightly fewer misclassifications; however, the 20°C threshold had the fewest extreme misclassifications. Our method leveraged the volumes of existing long-term data and provided a simple, systematic, and adaptable framework for monitoring changes in fish distribution, specifically in the case of irregular, extreme temperature events.
","language":"English","publisher":"Springer Netherlands","doi":"10.1007/s10750-012-1336-1","usgsCitation":"Parrish, D.L., Butryn, R.S., and Rizzo, D.M., 2012, Summer temperature metrics for predicting brook trout (Salvelinus fontinalis) distribution in streams: Hydrobiologia, v. 703, no. 1, p. 47-57, https://doi.org/10.1007/s10750-012-1336-1.","productDescription":"11 p.","startPage":"47","endPage":"57","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-024699","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323409,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"703","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2012-10-20","publicationStatus":"PW","scienceBaseUri":"575a9337e4b04f417c27518a","contributors":{"authors":[{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Butryn, Ryan S.","contributorId":87042,"corporation":false,"usgs":true,"family":"Butryn","given":"Ryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":638286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rizzo, Donna M.","contributorId":171679,"corporation":false,"usgs":false,"family":"Rizzo","given":"Donna","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":638287,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70040432,"text":"sir20105090E - 2012 - Sandstone copper assessment of the Chu-Sarysu Basin, Central Kazakhstan: Chapter E in Global mineral resource assessment","interactions":[{"subject":{"id":70040432,"text":"sir20105090E - 2012 - Sandstone copper assessment of the Chu-Sarysu Basin, Central Kazakhstan: Chapter E in Global mineral resource assessment","indexId":"sir20105090E","publicationYear":"2012","noYear":false,"chapter":"E","title":"Sandstone copper assessment of the Chu-Sarysu Basin, Central Kazakhstan: Chapter E in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2015-06-19T11:13:59","indexId":"sir20105090E","displayToPublicDate":"2012-10-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"E","title":"Sandstone copper assessment of the Chu-Sarysu Basin, Central Kazakhstan: Chapter E in Global mineral resource assessment","docAbstract":"Mineral resource assessments represent a synthesis of available information to estimate the location, quality, and quantity of undiscovered mineral resources in the upper part of the Earth’s crust. This report presents a probabilistic mineral resource assessment of undiscovered sandstone copper deposits within the late Paleozoic Chu-Sarysu Basin in central Kazakhstan by the U.S. Geological Survey as a contribution to a global assessment of mineral resources. The purposes of this study are to: (1) provide a database of known sandstone copper deposits and significant prospects in this area, (2) delineate permissive areas (tracts) for undiscovered sandstone copper deposits within 2 km of the surface at a scale of 1:1,000,000, (3) estimate numbers of undiscovered deposits within these permissive tracts at several levels of confidence, and (4) provide probabilistic estimates of amounts of copper (Cu), silver (Ag), and mineralized rock that could be contained in undiscovered deposits within each tract. The assessment uses the three-part form of mineral resource assessment based on mineral deposit models (Singer, 1993; Singer and Menzie, 2010).
\nDelineation of permissive tracts for resources is based on the distribution of a Carboniferous oxidized nonmarine clastic (red bed) stratigraphic sequence that lies between overlying Permian and underlying Devonian evaporite-bearing sequences. Subsurface information on the extent and depth of this red bed sequence and structural features that divide the basin into sub-basins was used to define four permissive tracts. Structure contour maps, mineral occurrence databases, drill hole lithologic logs, geophysical maps, soil geochemical maps, locations of producing gas fields, and evidence for former gas accumulations were considered in conjunction with descriptive deposit models and grade and tonnage models to guide the assessment team’s estimates of undiscovered deposits in each tract.
\nThe four permissive tracts are structural sub-basins of the Chu-Sarysu Basin and range in size from 750 to 65,000 km². Probabilistic estimates of numbers of undiscovered sandstone copper deposits were made for the four tracts by a group of experts. Using these probabilistic estimates, Monte Carlo simulation was used to estimate the amount of metal contained within each tract. The results of the simulation serve as the basis for estimates of the metal endowment.
\nThe team estimates that 26 undiscovered deposits occur within the Chu-Sarysu Basin, and that these deposits contain an arithmetic mean of at least 21.5 million metric tons (Mt) of copper and 21,900 metric tons (t) of silver. The undiscovered deposits are in addition to the 7 known deposits that contain identified resources of 27.6 Mt of copper. Sixty percent of the estimated mean undiscovered copper resources are associated with the two permissive tracts that contain the identified resources; the remaining estimated resources are associated with the two tracts that have no known deposits. For the three tracts that contain 95 percent of the estimated undiscovered copper resources, the probability that each tract contains its estimated mean or more is about 40 percent. For the tract with 5 percent of the estimated undiscovered cop-per resources, the probability that it contains that amount or more is 25 percent.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090E","collaboration":"Prepared in cooperation with the Centre for Russian and Central EurAsian Mineral Studies—Natural History Museum, London, United Kingdom, and Mining and Economic Consulting, Ltd., Almaty, Kazakhstan","usgsCitation":"Box, S.E., Syusyura, B., Hayes, T.S., Taylor, C.D., Zientek, M.L., Hitzman, M., Seltmann, R., Chechetkin, V., Dolgopolova, A., Cossette, P.M., and Wallis, J., 2012, Sandstone copper assessment of the Chu-Sarysu Basin, Central Kazakhstan: Chapter E in Global mineral resource assessment: U.S. Geological Survey Scientific Investigations Report 2010-5090, Report: vi, 63 p.; Metadata Folder; GIS Data, 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Vladimir","contributorId":71821,"corporation":false,"usgs":true,"family":"Chechetkin","given":"Vladimir","affiliations":[],"preferred":false,"id":514673,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dolgopolova, Alla","contributorId":96943,"corporation":false,"usgs":true,"family":"Dolgopolova","given":"Alla","email":"","affiliations":[],"preferred":false,"id":514676,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cossette, Pamela M. 0000-0002-9608-6595 pcossette@usgs.gov","orcid":"https://orcid.org/0000-0002-9608-6595","contributorId":1458,"corporation":false,"usgs":true,"family":"Cossette","given":"Pamela","email":"pcossette@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":514667,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wallis, John C.","contributorId":45755,"corporation":false,"usgs":true,"family":"Wallis","given":"John C.","affiliations":[],"preferred":false,"id":514672,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70040405,"text":"ofr20121187 - 2012 - Preliminary assessment of channel stability and bed-material transport in the Tillamook Bay tributaries and Nehalem River basin, northwestern Oregon","interactions":[],"lastModifiedDate":"2019-04-25T10:08:31","indexId":"ofr20121187","displayToPublicDate":"2012-10-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1187","title":"Preliminary assessment of channel stability and bed-material transport in the Tillamook Bay tributaries and Nehalem River basin, northwestern Oregon","docAbstract":"This report summarizes a preliminary study of bed-material transport, vertical and lateral channel changes, and existing datasets for the Tillamook (drainage area 156 square kilometers [km2]), Trask (451 km2), Wilson (500 km2), Kilchis (169 km2), Miami (94 km2), and Nehalem (2,207 km2) Rivers along the northwestern Oregon coast. This study, conducted in coopera-tion with the U.S. Army Corps of Engineers and Oregon Department of State Lands to inform permitting decisions regarding instream gravel mining, revealed that:
Study areas along the six rivers can be divided into reaches based on tidal influence and topography. The fluvial (nontidal or dominated by riverine processes) reaches vary in length (2.4-9.3 kilometer [km]), gradient (0.0011-0.0075 meter of elevation change per meter of channel length [m/m]), and bed-material composition (a mixture of alluvium and intermittent bedrock outcrops to predominately alluvium). In fluvial reaches, unit bar area (square meter of bar area per meter of channel length [m2/m]) as mapped from 2009 photographs ranged from 7.1 m2/m on the Tillamook River to 27.9 m2/m on the Miami River.
In tidal reaches, all six rivers flow over alluvial deposits, but have varying gradients (0.0001-0.0013 m/m) and lengths affected by tide (1.3-24.6 km). The Miami River has the steepest and shortest tidal reach and the Nehalem River has the flattest and longest tidal reach. Bars in the tidal reaches are generally composed of sand and mud. Unit bar area was greatest in the Tidal Nehalem Reach, where extensive mud flats flank the lower channel.
Background factors such as valley and channel confinement, basin geology, channel slope, and tidal extent control the spatial variation in the accumulation and texture of bed material. Presently, the Upper Fluvial Wilson and Miami Reaches and Fluvial Nehalem Reach have the greatest abundance of gravel bars, likely owing to local bed-material sources in combination with decreasing channel gradient and valley confinement.
Natural and human-caused disturbances such as mass movements, logging, fire, channel modifications for navigation and flood control, and gravel mining also have varying effects on channel condition, bed-material transport, and distribution and area of bars throughout the study areas and over time.
Existing datasets include at least 16 and 18 sets of aerial and orthophotographs that were taken of the study areas in the Tillamook Bay tributary basins and Nehalem River basin, respectively, from 1939 to 2011. These photographs are available for future assessments of long-term changes in channel condition, bar area, and vegetation establishment patterns. High resolution Light Detection And Ranging (LiDAR) surveys acquired in 2007-2009 could support future quantitative analyses of channel morphology and bed-material transport in all study areas.
A review of deposited and mined gravel volumes reported for instream gravel mining sites shows that bed-material deposition tends to rebuild mined bar surfaces in most years. Mean annual deposition volumes on individual bars exceeded 3,000 cubic meters (m3) on Donaldson Bar on the Wilson River, Dill Bar on the Kilchis River, and Plant and Winslow Bars on the Nehalem River. Cumulative reported volumes of bed-material deposition were greatest at Donaldson and Dill Bars, totaling over 25,000 m3 per site from 2004 to 2011. Within this period, reported cumulative mined volumes were greatest for the Donaldson, Plant, and Winslow Bars, ranging from 24,470 to 33,940 m3.
Analysis of historical stage-streamflow data collected by the U.S. Geological Survey on the Wilson River near Tillamook (14301500) and Nehalem River near Foss (14301000) shows that these rivers have episodically aggraded and incised, mostly following high flow events, but they do not exhibit systematic, long-term trends in bed elevation.
Multiple cross sections show that channels near bridge crossings in all six study areas are dynamic with many subject to incision and aggradation as well as lateral shifts in thalweg position and bank deposition and erosion.
In fluvial reaches, unit bar area declined a net 5.3-83.6 percent from 1939 to 2009. The documented reduction in bar area may be attributable to several factors, including vegetation establishment and stabilization of formerly active bar surfaces, lateral channel changes and resulting alterations in sediment deposition and erosion patterns, and streamflow and/or tide differences between photographs. Other factors that may be associated with the observed reduction in bar area but not assessed in this reconnaissance level study include changes in the sediment and hydrology regimes of these rivers over the analysis period.
In tidal reaches, unit bar area increased on the Tillamook and Nehalem Rivers (98.0 and 14.7 percent, respectively), but declined a net 24.2 to 83.1 percent in the other four tidal reaches. Net increases in bar area in the Tidal Tillamook and Nehalem Reaches were possibly attributable to tidal differences between the photographs as well as sediment deposition behind log booms and pile structures on the Tillamook River between 1939 and 1967.
The armoring ratio (ratio of the median grain sizes of a bar's surface and subsurface layers) was 1.6 at Lower Waldron Bar on the Miami River, tentatively indicating a relative balance between transport capacity and sediment supply at this location. Armoring ratios, however, ranged from 2.4 to 5.5 at sites on the Trask, Wilson, Kilchis, and Nehalem Rivers; these coarse armor layers probably reflect limited bed-material supply at these sites.
On the basis of mapping results, measured armoring ratios, and channel cross section surveys, preliminary conclusions are that the fluvial reaches on the Tillamook, Trask, Kilchis, and Nehalem Rivers are currently sediment supply-limited in terms of bed material - that is, the transport capacity of the channel generally exceeds the supply of bed material. The relation between transport capacity and sediment is more ambiguous for the fluvial reaches on the Wilson and Miami Rivers, but transport-limited conditions are likely for at least parts of these reaches. Some of these reaches have possibly evolved from sediment supply-limited to transport-limited over the last several decades in response to changing basin and climate conditions.
Because of exceedingly low gradients, all the tidal reaches are transport-limited. Bed material in these reaches, however, is primarily sand and finer grain-size material and probably transported as suspended load from upstream reaches. These reaches will be most susceptible to watershed conditions affecting the supply and transport of fine sediment.
Compared to basins on the southwestern Oregon coast, such as the Chetco and Rogue River basins, these six basins likely transport overall less gravel bed material. Although tentative in the absence of actual transport measurements, this conclusion is supported by the much lower area and frequency of bars and longer tidal reaches along all the northcoast rivers examined in this study.
Previous studies suggest that the expansive and largely unvegetated bars visible in the 1939 photographs are primarily associated with voluminous sedimentation starting soon after the first Tillamook Burn fire in 1933. However, USGS studies of temporal bar trends in other Oregon coastal rivers unaffected by the Tillamook Burn show similar declines in bar area over approximately the same analysis period. In the Umpqua and Chetco River basins, historical declines in bar area are associated with long-term decreases in flood magnitude. Other factors may include changes in the type and volume of large wood and riparian vegetation. Further characterization of hydrology patterns in these basins and possible linkages with climate factors related to flood peaks, such as the Pacific Decadal Oscillation, could support inferences of expected future changes in vegetation establishment and channel planform and profile.
More detailed investigations of bed-material transport rates and channel morphology would support assessments of lateral and vertical channel condition and longitudinal trends in bed material. Such assessments would be most practical for the fluvial study areas on the Wilson, Kilchis, Miami, and Nehalem Rivers and relevant to several ongoing management and ecological issues pertaining to sand and gravel transport. Tidal reaches may also be logical subjects for indepth analysis where studies would be more relevant to the deposition and transport of fine sediment (and associated channel and riparian conditions and processes) rather than coarse bed material.