The distribution of the Greater Yellowstone Ecosystem grizzly bear (Ursus arctos) population has expanded into areas unoccupied since the early 20th century. Up-to-date information on the area and extent of this distribution is crucial for federal, state, and tribal wildlife and land managers to make informed decisions regarding grizzly bear management. The most recent estimate of grizzly bear distribution (2004) utilized fixed-kernel density estimators to describe distribution. This method was complex and computationally time consuming and excluded observations of unmarked bears. Our objective was to develop a technique to estimate grizzly bear distribution that would allow for the use of all verified grizzly bear location data, as well as provide the simplicity to be updated more frequently. We placed all verified grizzly bear locations from all sources from 1990 to 2004 and 1990 to 2010 onto a 3-km × 3-km grid and used zonal analysis and ordinary kriging to develop a predicted surface of grizzly bear distribution. We compared the area and extent of the 2004 kriging surface with the previous 2004 effort and evaluated changes in grizzly bear distribution from 2004 to 2010. The 2004 kriging surface was 2.4% smaller than the previous fixed-kernel estimate, but more closely represented the data. Grizzly bear distribution increased 38.3% from 2004 to 2010, with most expansion in the northern and southern regions of the range. This technique can be used to provide a current estimate of grizzly bear distribution for management and conservation applications.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.368","usgsCitation":"Haroldson, M.A., Schwartz, C.C., Thompson, D.J., Bjornlie, D., Gunther, K.A., Cain, S.L., Tyers, D.B., Frey, K.L., and Aber, B.C., 2014, Methods to estimate distribution and range extent of grizzly bears in the Greater Yellowstone Ecosystem: Wildlife Society Bulletin, v. 38, no. 1, p. 182-187, https://doi.org/10.1002/wsb.368.","productDescription":"6 p.","startPage":"182","endPage":"187","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044551","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":499961,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/e37bdcc3f366472dab22afe3097cb52b","text":"External Repository"},{"id":438772,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RLJ1E6","text":"USGS data release","linkHelpText":"Occupied Range of the Yellowstone Grizzly Bear 2008-2022"},{"id":438771,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90J6L48","text":"USGS data release","linkHelpText":"Occupied Range of the Yellowstone Grizzly Bear 2006-2020"},{"id":296027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-11-08","publicationStatus":"PW","scienceBaseUri":"5465d633e4b04d4b7dbd6607","contributors":{"authors":[{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwartz, Charles C.","contributorId":55950,"corporation":false,"usgs":true,"family":"Schwartz","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":521357,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Daniel J.","contributorId":149795,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":5116,"text":"Large Carnivore Section, Wyoming Game & Fish Department, 260 Buena Vista, Lander, WY 82520, USA","active":true,"usgs":false}],"preferred":false,"id":521361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bjornlie, Daniel D.","contributorId":145512,"corporation":false,"usgs":false,"family":"Bjornlie","given":"Daniel D.","affiliations":[{"id":16140,"text":"Wyoming Game & Fish Department, Large Carnivore Section, Lander, Wyoming 82520, USA","active":true,"usgs":false}],"preferred":false,"id":521360,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Gunther, Kerry A.","contributorId":190246,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5130,"text":"Bear Management Office, Yellowstone National Park, WY 82190, USA","active":true,"usgs":false}],"preferred":false,"id":521362,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cain, Steven L.","contributorId":145511,"corporation":false,"usgs":false,"family":"Cain","given":"Steven","email":"","middleInitial":"L.","affiliations":[{"id":16139,"text":"National Park Service, Grand Teton National Park, Moose, Wyoming 83012, USA","active":true,"usgs":false}],"preferred":false,"id":521363,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tyers, Daniel B.","contributorId":124587,"corporation":false,"usgs":false,"family":"Tyers","given":"Daniel","email":"","middleInitial":"B.","affiliations":[{"id":5129,"text":"U.S. Forest Service, 2327 University Way, Bozeman, MT 59715, USA","active":true,"usgs":false}],"preferred":false,"id":521359,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Frey, Kevin L.","contributorId":124580,"corporation":false,"usgs":false,"family":"Frey","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":5125,"text":"Montana Fish Wildlife and Parks, Bear Management Office, 1400 South 19th Avenue, Bozeman, MT 59718","active":true,"usgs":false}],"preferred":false,"id":525131,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Aber, Bryan C.","contributorId":124581,"corporation":false,"usgs":false,"family":"Aber","given":"Bryan","email":"","middleInitial":"C.","affiliations":[{"id":5126,"text":"Idaho Department of Fish and Game, 3726 Highway 20, Island Park, ID 83429","active":true,"usgs":false}],"preferred":false,"id":525132,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70074264,"text":"70074264 - 2014 - Seismological analyses of the 2010 March 11, Pichilemu, Chile Mw 7.0 and Mw 6.9 coastal intraplate earthquakes","interactions":[],"lastModifiedDate":"2014-03-04T16:23:23","indexId":"70074264","displayToPublicDate":"2014-03-01T09:10:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Seismological analyses of the 2010 March 11, Pichilemu, Chile Mw 7.0 and Mw 6.9 coastal intraplate earthquakes","docAbstract":"On 2010 March 11, a sequence of large, shallow continental crust earthquakes shook central Chile. Two normal faulting events with magnitudes around Mw 7.0 and Mw 6.9 occurred just 15 min apart, located near the town of Pichilemu. These kinds of large intraplate, inland crustal earthquakes are rare above the Chilean subduction zone, and it is important to better understand their relationship with the 2010 February 27, Mw 8.8, Maule earthquake, which ruptured the adjacent megathrust plate boundary. We present a broad seismological analysis of these earthquakes by using both teleseismic and regional data. We compute seismic moment tensors for both events via a W-phase inversion, and test sensitivities to various inversion parameters in order to assess the stability of the solutions. The first event, at 14 hr 39 min GMT, is well constrained, displaying a fault plane with strike of N145°E, and a preferred dip angle of 55°SW, consistent with the trend of aftershock locations and other published results. Teleseismic finite-fault inversions for this event show a large slip zone along the southern part of the fault, correlating well with the reported spatial density of aftershocks. The second earthquake (14 hr 55 min GMT) appears to have ruptured a fault branching southward from the previous ruptured fault, within the hanging wall of the first event. Modelling seismograms at regional to teleseismic distances (Δ > 10°) is quite challenging because the observed seismic wave fields of both events overlap, increasing apparent complexity for the second earthquake. We perform both point- and extended-source inversions at regional and teleseismic distances, assessing model sensitivities resulting from variations in fault orientation, dimension, and hypocentre location. Results show that the focal mechanism for the second event features a steeper dip angle and a strike rotated slightly clockwise with respect to the previous event. This kind of geological fault configuration, with secondary rupture in the hanging wall of a large normal fault, is commonly observed in extensional geological regimes. We propose that both earthquakes form part of a typical normal fault diverging splay, where the secondary fault connects to the main fault at depth. To ascertain more information on the spatial and temporal details of slip for both events, we gathered near-fault seismological and geodetic data. Through forward modelling of near-fault synthetic seismograms we build a kinematic k−2 earthquake source model with spatially distributed slip on the fault that, to first-order, explains both coseismic static displacement GPS vectors and short-period seismometer observations at the closest sites. As expected, the results for the first event agree with the focal mechanism derived from teleseismic modelling, with a magnitude Mw 6.97. Similarly, near-fault modelling for the second event suggests rupture along a normal fault, Mw 6.90, characterized by a steeper dip angle (dip = 74°) and a strike clockwise rotated (strike = 155°) with respect to the previous event.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Journal International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggt513","usgsCitation":"Ruiz, J.A., Hayes, G., Carrizo, D., Kanamori, H., Socquet, A., and Comte, D., 2014, Seismological analyses of the 2010 March 11, Pichilemu, Chile Mw 7.0 and Mw 6.9 coastal intraplate earthquakes: Geophysical Journal International, v. 196, no. 3, 21 p., https://doi.org/10.1093/gji/ggt513.","productDescription":"21 p.","ipdsId":"IP-053432","costCenters":[{"id":415,"text":"National Earthquake Information Center","active":false,"usgs":true}],"links":[{"id":473147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggt513","text":"Publisher Index Page"},{"id":283363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281636,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1093/gji/ggt513"}],"country":"Chile","city":"Pichilemu","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -72.056,-34.586 ], [ -72.056,-34.165 ], [ -71.746,-34.165 ], [ -71.746,-34.586 ], [ -72.056,-34.586 ] ] ] } } ] }","volume":"196","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-02-07","publicationStatus":"PW","scienceBaseUri":"5351705fe4b05569d805a39a","contributors":{"authors":[{"text":"Ruiz, Javier A.","contributorId":39287,"corporation":false,"usgs":true,"family":"Ruiz","given":"Javier","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":489457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Gavin P. 0000-0003-3323-0112","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":6157,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":489455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carrizo, Daniel","contributorId":36456,"corporation":false,"usgs":true,"family":"Carrizo","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":489456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kanamori, Hiroo","contributorId":106120,"corporation":false,"usgs":true,"family":"Kanamori","given":"Hiroo","affiliations":[],"preferred":false,"id":489460,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Socquet, Anne","contributorId":65764,"corporation":false,"usgs":true,"family":"Socquet","given":"Anne","email":"","affiliations":[],"preferred":false,"id":489459,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Comte, Diana","contributorId":40514,"corporation":false,"usgs":true,"family":"Comte","given":"Diana","email":"","affiliations":[],"preferred":false,"id":489458,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70095570,"text":"70095570 - 2014 - Nitrogen deposition effects on diatom communities in lakes from three National Parks in Washington State","interactions":[],"lastModifiedDate":"2016-05-30T13:26:49","indexId":"70095570","displayToPublicDate":"2014-03-01T09:07:54","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen deposition effects on diatom communities in lakes from three National Parks in Washington State","docAbstract":"The goal of this study was to document if lakes in National Parks in Washington have exceeded critical levels of nitrogen (N) deposition, as observed in other Western States. We measured atmospheric N deposition, lake water quality, and sediment diatoms at our study lakes. Water chemistry showed that our study lakes were ultra-oligotrophic with ammonia and nitrate concentrations often at or below detection limits with low specific conductance (−1 year−1 and were variable both within and across the parks. Diatom assemblages in a single sediment core from Hoh Lake (Olympic National Park) displayed a shift to increased relative abundances of Asterionella formosa and Fragilaria tenera beginning in the 1969–1975 timeframe, whereas these species were not found at the remaining (nine) sites. These diatom species are known to be indicative of N enrichment and were used to determine an empirical critical load of N deposition, or threshold level, where changes in diatom communities were observed at Hoh Lake. However, N deposition at the remaining nine lakes does not seem to exceed a critical load at this time. At Milk Lake, also in Olympic National Park, there was some evidence that climate change might be altering diatom communities, but more research is needed to confirm this. We used modeled precipitation for Hoh Lake and annual inorganic N concentrations from a nearby National Atmospheric Deposition Program station, to calculate elevation-corrected N deposition for 1980–2009 at Hoh Lake. An exponential fit to this data was hindcasted to the 1969–1975 time period, and we estimate a critical load of 1.0 to 1.2 kg N ha−1 year−1 for wet deposition for this lake.
","language":"English","publisher":"Springer","doi":"10.1007/s11270-013-1857-x","usgsCitation":"Sheibley, R.W., Enache, M., Swarzenski, P.W., Moran, P.W., and Foreman, J.R., 2014, Nitrogen deposition effects on diatom communities in lakes from three National Parks in Washington State: Water, Air, & Soil Pollution, v. 225, art1985: 23 p., https://doi.org/10.1007/s11270-013-1857-x.","productDescription":"art1985: 23 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052849","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":473148,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11270-013-1857-x","text":"Publisher Index Page"},{"id":283449,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":283386,"rank":1,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11270-013-1857-x"}],"country":"United States","state":"Washington","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.79,45.55 ], [ -124.79,49.0 ], [ -116.92,49.0 ], [ -116.92,45.55 ], [ -124.79,45.55 ] ] ] } } ] }","volume":"225","noUsgsAuthors":false,"publicationDate":"2014-02-01","publicationStatus":"PW","scienceBaseUri":"574d65ece4b07e28b6684919","contributors":{"authors":[{"text":"Sheibley, Richard W. 0000-0003-1627-8536 sheibley@usgs.gov","orcid":"https://orcid.org/0000-0003-1627-8536","contributorId":87452,"corporation":false,"usgs":true,"family":"Sheibley","given":"Richard","email":"sheibley@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":491305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Enache, Mihaela","contributorId":55743,"corporation":false,"usgs":true,"family":"Enache","given":"Mihaela","affiliations":[],"preferred":false,"id":491304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":491302,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moran, Patrick W. 0000-0002-2002-3539 pwmoran@usgs.gov","orcid":"https://orcid.org/0000-0002-2002-3539","contributorId":489,"corporation":false,"usgs":true,"family":"Moran","given":"Patrick","email":"pwmoran@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foreman, James R. 0000-0003-0535-4580 jforeman@usgs.gov","orcid":"https://orcid.org/0000-0003-0535-4580","contributorId":3669,"corporation":false,"usgs":true,"family":"Foreman","given":"James","email":"jforeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":491303,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70097332,"text":"70097332 - 2014 - Estrogen and androgen receptor activities of hydraulic fracturing chemicals and surface and ground water in a drilling-dense region","interactions":[],"lastModifiedDate":"2018-09-14T15:14:16","indexId":"70097332","displayToPublicDate":"2014-03-01T09:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1504,"text":"Endocrinology","active":true,"publicationSubtype":{"id":10}},"title":"Estrogen and androgen receptor activities of hydraulic fracturing chemicals and surface and ground water in a drilling-dense region","docAbstract":"The rapid rise in natural gas extraction using hydraulic fracturing increases the potential for contamination of surface and ground water from chemicals used throughout the process. Hundreds of products containing more than 750 chemicals and components are potentially used throughout the extraction process, including more than 100 known or suspected endocrine-disrupting chemicals. We hypothesized thataselected subset of chemicalsusedin natural gas drilling operationsandalso surface and ground water samples collected in a drilling-dense region of Garfield County, Colorado, would exhibit estrogen and androgen receptor activities. Water samples were collected, solid-phase extracted, and measured for estrogen and androgen receptor activities using reporter gene assays in human cell lines. Of the 39 unique water samples, 89%, 41%, 12%, and 46% exhibited estrogenic, antiestrogenic, androgenic, and antiandrogenic activities, respectively. Testing of a subset of natural gas drilling chemicals revealed novel antiestrogenic, novel antiandrogenic, and limited estrogenic activities. The Colorado River, the drainage basin for this region, exhibited moderate levels of estrogenic, antiestrogenic, and antiandrogenic activities, suggesting that higher localized activity at sites with known natural gas–related spills surrounding the river might be contributing to the multiple \nreceptor activities observed in this water source. The majority of water samples collected from sites in a drilling-dense region of Colorado exhibited more estrogenic, antiestrogenic, or antiandrogenic activities than reference sites with limited nearby drilling operations. Our data suggest that natural gas drilling operationsmayresult in elevated endocrine-disrupting chemical activity in surface and ground water.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Endocrinology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Endocrine Press","doi":"10.1210/en.2013-1697","usgsCitation":"Kassotis, C., Tillitt, D.E., Davis, J.W., Hormann, A.M., and Nagel, S., 2014, Estrogen and androgen receptor activities of hydraulic fracturing chemicals and surface and ground water in a drilling-dense region: Endocrinology, v. 155, no. 3, p. 897-907, https://doi.org/10.1210/en.2013-1697.","productDescription":"11 p.","startPage":"897","endPage":"907","ipdsId":"IP-049070","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":473149,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1210/en.2013-1697","text":"Publisher Index Page"},{"id":283996,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1210/en.2013-1697"},{"id":283999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0603,36.9924 ], [ -109.0603,41.0034 ], [ -102.0409,41.0034 ], [ -102.0409,36.9924 ], [ -109.0603,36.9924 ] ] ] } } ] }","volume":"155","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517037e4b05569d805a1ed","contributors":{"authors":[{"text":"Kassotis, Christopher D.","contributorId":26967,"corporation":false,"usgs":true,"family":"Kassotis","given":"Christopher D.","affiliations":[],"preferred":false,"id":491532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":491531,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, J. Wade hdavis@usgs.gov","contributorId":94585,"corporation":false,"usgs":true,"family":"Davis","given":"J.","email":"hdavis@usgs.gov","middleInitial":"Wade","affiliations":[],"preferred":false,"id":491535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hormann, Anette M.","contributorId":32077,"corporation":false,"usgs":true,"family":"Hormann","given":"Anette","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":491533,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nagel, Susan C.","contributorId":56147,"corporation":false,"usgs":true,"family":"Nagel","given":"Susan C.","affiliations":[],"preferred":false,"id":491534,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70098977,"text":"70098977 - 2014 - Assessment of floodplain vulnerability during extreme Mississippi River flood 2011","interactions":[],"lastModifiedDate":"2014-03-20T08:56:01","indexId":"70098977","displayToPublicDate":"2014-03-01T08:49:15","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of floodplain vulnerability during extreme Mississippi River flood 2011","docAbstract":"Regional change in the variability and magnitude of flooding could be a major consequence of future global climate change. Extreme floods have the capacity to rapidly transform landscapes and expose landscape vulnerabilities through highly variable spatial patterns of inundation, erosion, and deposition. We use the historic activation of the Birds Point-New Madrid Floodway during the Mississippi and Ohio River Flooding of 2011 as a scientifically unique stress experiment to analyze indicators of floodplain vulnerability. We use pre- and postflood airborne Light Detection and Ranging data sets to locate erosional and depositional hotspots over the 540 km2 agricultural Floodway. While riparian vegetation between the river and the main levee breach likely prevented widespread deposition, localized scour and deposition occurred near the levee breaches. Eroded gullies nearly 1 km in length were observed at a low ridge of a relict meander scar of the Mississippi River. Our flow modeling and spatial mapping analysis attributes this vulnerability to a combination of erodible soils, flow acceleration associated with legacy fluvial landforms, and a lack of woody vegetation to anchor soil and enhance flow resistance. Results from this study could guide future mitigation and adaptation measures in cases of extreme flooding.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Chemical Society","doi":"10.1021/es404760t","usgsCitation":"Goodwell, A.E., Zhu, Z., Dutta, D., Greenberg, J.A., Kumar, P., Garcia, M., Rhoads, B.L., Holmes, R.R., Parker, G., Berretta, D.P., and Jacobson, R.B., 2014, Assessment of floodplain vulnerability during extreme Mississippi River flood 2011: Environmental Science & Technology, v. 48, no. 5, p. 2619-2625, https://doi.org/10.1021/es404760t.","productDescription":"7 p.","startPage":"2619","endPage":"2625","ipdsId":"IP-049213","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":284301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284281,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es404760t"},{"id":284282,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.acs.org/doi/abs/10.1021/es404760t"}],"state":"Illinois","city":"Cairo","otherGeospatial":"Birds Point New Madrid (bpnm) Floodway","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.2314,36.973 ], [ -89.2314,37.088 ], [ -89.139,37.088 ], [ -89.139,36.973 ], [ -89.2314,36.973 ] ] ] } } ] }","volume":"48","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-02-17","publicationStatus":"PW","scienceBaseUri":"53517025e4b05569d805a166","contributors":{"authors":[{"text":"Goodwell, Allison E.","contributorId":37639,"corporation":false,"usgs":true,"family":"Goodwell","given":"Allison","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":491819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Zhenduo","contributorId":83828,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhenduo","affiliations":[],"preferred":false,"id":491825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dutta, Debsunder","contributorId":76642,"corporation":false,"usgs":true,"family":"Dutta","given":"Debsunder","email":"","affiliations":[],"preferred":false,"id":491823,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greenberg, Jonathan A.","contributorId":46870,"corporation":false,"usgs":true,"family":"Greenberg","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":491820,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kumar, Praveen","contributorId":81405,"corporation":false,"usgs":true,"family":"Kumar","given":"Praveen","affiliations":[],"preferred":false,"id":491824,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garcia, Marcelo H.","contributorId":74236,"corporation":false,"usgs":false,"family":"Garcia","given":"Marcelo H.","affiliations":[{"id":33106,"text":"University of Illinois at Urbana Champaign","active":true,"usgs":false}],"preferred":false,"id":491822,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rhoads, Bruce L.","contributorId":20248,"corporation":false,"usgs":true,"family":"Rhoads","given":"Bruce","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":491818,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Holmes, Robert R. 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As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0091001","usgsCitation":"Villa, F., Bagstad, K.J., Voigt, B., Johnson, G.W., Portela, R., Honzak, M., and Batker, D., 2014, A methodology for adaptable and robust ecosystem services assessment: PLoS ONE, v. 9, no. 3, e91001; 18 p., https://doi.org/10.1371/journal.pone.0091001.","productDescription":"e91001; 18 p.","ipdsId":"IP-051219","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":473151,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0091001","text":"Publisher Index Page"},{"id":283998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":283997,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0091001"}],"volume":"9","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-03-13","publicationStatus":"PW","scienceBaseUri":"53516ef2e4b05569d8059f23","contributors":{"authors":[{"text":"Villa, Ferdinando","contributorId":84249,"corporation":false,"usgs":true,"family":"Villa","given":"Ferdinando","affiliations":[],"preferred":false,"id":491526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":491524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voigt, Brian","contributorId":102962,"corporation":false,"usgs":true,"family":"Voigt","given":"Brian","affiliations":[],"preferred":false,"id":491530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Gary W.","contributorId":90618,"corporation":false,"usgs":true,"family":"Johnson","given":"Gary","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":491527,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Portela, Rosimeiry","contributorId":102791,"corporation":false,"usgs":true,"family":"Portela","given":"Rosimeiry","email":"","affiliations":[],"preferred":false,"id":491529,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Honzak, Miroslav","contributorId":97815,"corporation":false,"usgs":true,"family":"Honzak","given":"Miroslav","email":"","affiliations":[],"preferred":false,"id":491528,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Batker, David","contributorId":39288,"corporation":false,"usgs":true,"family":"Batker","given":"David","email":"","affiliations":[],"preferred":false,"id":491525,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173443,"text":"70173443 - 2014 - Linking bovine tuberculosis on cattle farms to white-tailed deer and environmental variables using Bayesian hierarchical analysis","interactions":[],"lastModifiedDate":"2016-06-22T09:27:36","indexId":"70173443","displayToPublicDate":"2014-03-01T03:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Linking bovine tuberculosis on cattle farms to white-tailed deer and environmental variables using Bayesian hierarchical analysis","docAbstract":"Bovine tuberculosis is a bacterial disease caused by Mycobacterium bovis in livestock and wildlife with hosts that include Eurasian badgers (Meles meles), brushtail possum (Trichosurus vulpecula), and white-tailed deer (Odocoileus virginianus). Risk-assessment efforts in Michigan have been initiated on farms to minimize interactions of cattle with wildlife hosts but research onM. bovis on cattle farms has not investigated the spatial context of disease epidemiology. To incorporate spatially explicit data, initial likelihood of infection probabilities for cattle farms tested for M. bovis, prevalence of M. bovis in white-tailed deer, deer density, and environmental variables for each farm were modeled in a Bayesian hierarchical framework. We used geo-referenced locations of 762 cattle farms that have been tested for M. bovis, white-tailed deer prevalence, and several environmental variables that may lead to long-term survival and viability of M. bovis on farms and surrounding habitats (i.e., soil type, habitat type). Bayesian hierarchical analyses identified deer prevalence and proportion of sandy soil within our sampling grid as the most supported model. Analysis of cattle farms tested for M. bovisidentified that for every 1% increase in sandy soil resulted in an increase in odds of infection by 4%. Our analysis revealed that the influence of prevalence of M. bovis in white-tailed deer was still a concern even after considerable efforts to prevent cattle interactions with white-tailed deer through on-farm mitigation and reduction in the deer population. Cattle farms test positive for M. bovis annually in our study area suggesting that the potential for an environmental source either on farms or in the surrounding landscape may contributing to new or re-infections with M. bovis. Our research provides an initial assessment of potential environmental factors that could be incorporated into additional modeling efforts as more knowledge of deer herd factors and cattle farm prevalence is documented.
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David 0000-0003-3068-1073 wwalter@usgs.gov","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":5083,"corporation":false,"usgs":true,"family":"Walter","given":"W.","email":"wwalter@usgs.gov","middleInitial":"David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Rick","contributorId":172191,"corporation":false,"usgs":false,"family":"Smith","given":"Rick","email":"","affiliations":[],"preferred":false,"id":639851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vanderklok, Mike","contributorId":172192,"corporation":false,"usgs":false,"family":"Vanderklok","given":"Mike","email":"","affiliations":[],"preferred":false,"id":639852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"VerCauterren, Kurt C.","contributorId":113875,"corporation":false,"usgs":true,"family":"VerCauterren","given":"Kurt","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":639853,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176216,"text":"70176216 - 2014 - Geologic assessment of undiscovered oil and gas resources in Aptian carbonates, onshore northern Gulf of Mexico Basin, United States","interactions":[],"lastModifiedDate":"2016-09-01T15:40:50","indexId":"70176216","displayToPublicDate":"2014-03-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1344,"text":"Cretaceous Research","active":true,"publicationSubtype":{"id":10}},"title":"Geologic assessment of undiscovered oil and gas resources in Aptian carbonates, onshore northern Gulf of Mexico Basin, United States","docAbstract":"Carbonate lithofacies of the Lower Cretaceous Sligo Formation and James Limestone were regionally evaluated using established U.S. Geological Survey (USGS) assessment methodology for undiscovered conventional hydrocarbon resources. The assessed area is within the Upper Jurassic–Cretaceous–Tertiary Composite total petroleum system, which was defined for the assessment. Hydrocarbons reservoired in carbonate platform Sligo-James oil and gas accumulations are interpreted to originate primarily from the Jurassic Smackover Formation. Emplacement of hydrocarbons occurred via vertical migration along fault systems; long-range lateral migration also may have occurred in some locations. Primary reservoir facies include porous patch reefs developed over paleostructural salt highs, carbonate shoals, and stacked linear reefs at the carbonate shelf margin. Hydrocarbon traps dominantly are combination structural-stratigraphic. Sealing lithologies include micrite, calcareous shale, and argillaceous lime mudstone. A geologic model, supported by discovery history analysis of petroleum geology data, was used to define a single regional assessment unit (AU) for conventional reservoirs in carbonate facies of the Sligo Formation and James Limestone. The AU is formally entitled Sligo-James Carbonate Platform Oil and Gas (50490121). A fully risked mean undiscovered technically recoverable resource in the AU of 50 million barrels of oil (MMBO), 791 billion cubic feet of natural gas (BCFG), and 26 million barrels of natural gas liquids was estimated. Substantial new development through horizontal drilling has occurred since the time of this assessment (2010), resulting in cumulative production of >200 BCFG and >1 MMBO.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.cretres.2013.12.005","usgsCitation":"Hackley, P.C., and Karlsen, A.W., 2014, Geologic assessment of undiscovered oil and gas resources in Aptian carbonates, onshore northern Gulf of Mexico Basin, United States: Cretaceous Research, v. 48, p. 225-234, https://doi.org/10.1016/j.cretres.2013.12.005.","productDescription":"10 p.","startPage":"225","endPage":"234","ipdsId":"IP-051557","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":328195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100,\n 26\n ],\n [\n -100,\n 34\n ],\n [\n -88,\n 34\n ],\n [\n -88,\n 26\n ],\n [\n -100,\n 26\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c9512de4b0f2f0cec15be9","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":647833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karlsen, Alexander W.","contributorId":105382,"corporation":false,"usgs":true,"family":"Karlsen","given":"Alexander","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":647834,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182175,"text":"70182175 - 2014 - CO2 and CH4 emissions from streams in a lake-rich landscape: Patterns, controls, and regional significance","interactions":[],"lastModifiedDate":"2018-04-02T16:36:33","indexId":"70182175","displayToPublicDate":"2014-03-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"CO2 and CH4 emissions from streams in a lake-rich landscape: Patterns, controls, and regional significance","docAbstract":"Aquatic ecosystems are important components of landscape carbon budgets. In lake-rich landscapes, both lakes and streams may be important sources of carbon gases (CO2 and CH4) to the atmosphere, but the processes that control gas concentrations and emissions in these interconnected landscapes have not been adequately addressed. We use multiple data sets that vary in their spatial and temporal extent during 2001–2012 to investigate the carbon gas source strength of streams in a lake-rich landscape and to determine the contribution of lakes, metabolism, and groundwater to stream CO2 and CH4. We show that streams emit roughly the same mass of CO2 (23.4 Gg C yr−1; 0.49 mol CO2 m−2 d−1) as lakes at a regional scale (27 Gg C yr−1) and that stream CH4 emissions (189 Mg C yr−1; 8.46 mmol CH4 m−2 d−1) are an important component of the regional greenhouse gas balance. Gas transfer velocity variability (range = 0.34 to 13.5 m d−1) contributed to the variability of gas flux in this landscape. Groundwater inputs and in-stream metabolism control stream gas supersaturation at the landscape scale, while carbon cycling in lakes and deep groundwaters does not control downstream gas emissions. Our results indicate the need to consider connectivity of all aquatic ecosystems (lakes, streams, wetlands, and groundwater) in lake-rich landscapes and their connections with the terrestrial environment in order to understand the full nature of the carbon cycle.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2013GB004661","usgsCitation":"Crawford, J.T., Lottig, N.R., Stanley, E.H., Walker, J.F., Hanson, P.C., Finlay, J.C., and Striegl, R.G., 2014, CO2 and CH4 emissions from streams in a lake-rich landscape: Patterns, controls, and regional significance: Global Biogeochemical Cycles, v. 28, no. 3, p. 197-210, https://doi.org/10.1002/2013GB004661.","productDescription":"14 p.","startPage":"197","endPage":"210","ipdsId":"IP-046128","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":335834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-10","publicationStatus":"PW","scienceBaseUri":"58ac0e31e4b0ce4410e7d604","contributors":{"authors":[{"text":"Crawford, John T. 0000-0003-4440-6945 jtcrawford@usgs.gov","orcid":"https://orcid.org/0000-0003-4440-6945","contributorId":4081,"corporation":false,"usgs":true,"family":"Crawford","given":"John","email":"jtcrawford@usgs.gov","middleInitial":"T.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":669881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lottig, Noah R.","contributorId":172031,"corporation":false,"usgs":false,"family":"Lottig","given":"Noah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":669885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":669883,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walker, John F. jfwalker@usgs.gov","contributorId":1081,"corporation":false,"usgs":true,"family":"Walker","given":"John","email":"jfwalker@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":669926,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finlay, Jacques C.","contributorId":19695,"corporation":false,"usgs":true,"family":"Finlay","given":"Jacques","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":669884,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":669882,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70168379,"text":"70168379 - 2014 - Similar resilience attributes in lakes with different management practices","interactions":[],"lastModifiedDate":"2016-02-11T13:35:48","indexId":"70168379","displayToPublicDate":"2014-03-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Similar resilience attributes in lakes with different management practices","docAbstract":"Liming has been used extensively in Scandinavia and elsewhere since the 1970s to counteract the negative effects of acidification. Communities in limed lakes usually return to acidified conditions once liming is discontinued, suggesting that liming is unlikely to shift acidified lakes to a state equivalent to pre-acidification conditions that requires no further management intervention. While this suggests a low resilience of limed lakes, attributes that confer resilience have not been assessed, limiting our understanding of the efficiency of costly management programs. In this study, we assessed community metrics (diversity, richness, evenness, biovolume), multivariate community structure and the relative resilience of phytoplankton in limed, acidified and circum-neutral lakes from 1997 to 2009, using multivariate time series modeling. We identified dominant temporal frequencies in the data, allowing us to track community change at distinct temporal scales. We assessed two attributes of relative resilience (cross-scale and within-scale structure) of the phytoplankton communities, based on the fluctuation frequency patterns identified. We also assessed species with stochastic temporal dynamics. Liming increased phytoplankton diversity and richness; however, multivariate community structure differed in limed relative to acidified and circum-neutral lakes. Cross-scale and within-scale attributes of resilience were similar across all lakes studied but the contribution of those species exhibiting stochastic dynamics was higher in the acidified and limed compared to circum-neutral lakes. From a resilience perspective, our results suggest that limed lakes comprise a particular condition of an acidified lake state. This explains why liming does not move acidified lakes out of a “degraded” basin of attraction. In addition, our study demonstrates the potential of time series modeling to assess the efficiency of restoration and management outcomes through quantification of the attributes contributing to resilience in ecosystems.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0091881","usgsCitation":"Baho, D.L., Drakare, S., Johnson, R.K., Allen, C.R., and Angeler, D., 2014, Similar resilience attributes in lakes with different management practices: PLoS ONE, v. 9, no. 3, e91881: 10 p., https://doi.org/10.1371/journal.pone.0091881.","productDescription":"e91881: 10 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054485","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":473159,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0091881","text":"Publisher Index Page"},{"id":317958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Sweden","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[22.18317,65.72374],[21.21352,65.02601],[21.36963,64.41359],[19.77888,63.60955],[17.84778,62.7494],[17.11955,61.34117],[17.83135,60.63658],[18.78772,60.08191],[17.86922,58.95377],[16.82919,58.71983],[16.44771,57.04112],[15.87979,56.1043],[14.66668,56.20089],[14.10072,55.40778],[12.94291,55.36174],[12.6251,56.30708],[11.78794,57.44182],[11.02737,58.85615],[11.46827,59.43239],[12.30037,60.11793],[12.63115,61.29357],[11.99206,61.80036],[11.93057,63.12832],[12.57994,64.06622],[13.57192,64.04911],[13.91991,64.44542],[13.55569,64.78703],[15.10841,66.19387],[16.10871,67.30246],[16.76888,68.01394],[17.72918,68.01055],[17.99387,68.56739],[19.87856,68.40719],[20.02527,69.06514],[20.64559,69.10625],[21.97853,68.61685],[23.53947,67.93601],[23.56588,66.39605],[23.90338,66.00693],[22.18317,65.72374]]]},\"properties\":{\"name\":\"Sweden\"}}]}","volume":"9","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-11","publicationStatus":"PW","scienceBaseUri":"56bdbecbe4b06458514aeee2","contributors":{"authors":[{"text":"Baho, Didier L.","contributorId":166724,"corporation":false,"usgs":false,"family":"Baho","given":"Didier","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":619958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drakare, Stina","contributorId":166738,"corporation":false,"usgs":false,"family":"Drakare","given":"Stina","email":"","affiliations":[],"preferred":false,"id":619959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Richard K.","contributorId":21810,"corporation":false,"usgs":true,"family":"Johnson","given":"Richard","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":619960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":619838,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":619961,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187418,"text":"70187418 - 2014 - Productivity and linkages of the food web of the southern region of the western Antarctic Peninsula continental shelf","interactions":[],"lastModifiedDate":"2017-05-02T13:18:55","indexId":"70187418","displayToPublicDate":"2014-03-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3194,"text":"Progress in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Productivity and linkages of the food web of the southern region of the western Antarctic Peninsula continental shelf","docAbstract":"The productivity and linkages in the food web of the southern region of the west Antarctic Peninsula continental shelf were investigated using a multi-trophic level mass balance model. Data collected during the Southern Ocean Global Ocean Ecosystem Dynamics field program were combined with data from the literature on the abundance and diet composition of zooplankton, fish, seabirds and marine mammals to calculate energy flows in the food web and to infer the overall food web structure at the annual level. Sensitivity analyses investigated the effects of variability in growth and biomass of Antarctic krill (Euphausia superba) and in the biomass of Antarctic krill predators on the structure and energy fluxes in the food web. Scenario simulations provided insights into the potential responses of the food web to a reduced contribution of large phytoplankton (diatom) production to total primary production, and to reduced consumption of primary production by Antarctic krill and mesozooplankton coincident with increased consumption by microzooplankton and salps. Model-derived estimates of primary production were 187–207 g C m−2 y−1, which are consistent with observed values (47–351 g C m−2 y−1). Simulations showed that Antarctic krill provide the majority of energy needed to sustain seabird and marine mammal production, thereby exerting a bottom-up control on higher trophic level predators. Energy transfer to top predators via mesozooplanton was a less efficient pathway, and salps were a production loss pathway because little of the primary production they consumed was passed to higher trophic levels. Increased predominance of small phytoplankton (nanoflagellates and cryptophytes) reduced the production of Antarctic krill and of its predators, including seabirds and seals.
We use sediment ages and mercury (Hg) concentrations to estimate past and future concentrations in the South River, Virginia, where Hg was released between 1930 and 1950 from a manufacturing process related to nylon production. In a previous study, along a 40 km (25 mi) reach, samples were collected from 26 of 54 fine-grained deposits that formed in the lee of large wood obstructions in the channel and analyzed for grain size, Hg concentration, and organic content. We also obtained radiometric dates from six deposits. To create a history that reflects the full concentration distribution (which contains concentrations as high as 900 mg/kg [900 ppm]), here, we treat the deposits as a single reservoir exchanging contaminated sediments with the overlying water column, and assume that the total sediment mass in storage and the distribution of sediment ages are time invariant. We use reservoir theory to reconstruct the annual history of Hg concentration on suspended sediment using data from our previous study and new results presented here. Many different reconstructed histories fit our data. To constrain results, we use information from a well-preserved core (and our estimate of the total mass of Hg stored in 2007) to specify the years associated with the peak concentration of 900 mg/kg. Our results indicate that around 850 kg (1874 lb) of Hg was stored in the deposits between 1955 and 1961, compared to only 80 kg (176 lb) today. Simulations of future Hg remediation suggest that 100-yr timescales will be needed for the South River to remove Hg-contaminated sediments from the channel perimeter through natural processes.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/eg.08151313007","usgsCitation":"Skalak, K., and Pizzuto, J., 2014, Reconstructing suspended sediment mercury contamination of a steep, gravel-bed river using reservoir theory: Environmental Geosciences, v. 20, no. 1, p. 17-35, https://doi.org/10.1306/eg.08151313007.","productDescription":"19 p.","startPage":"17","endPage":"35","ipdsId":"IP-045487","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":340438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5901b1c0e4b0c2e071a99bb2","contributors":{"authors":[{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":692988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pizzuto, James","contributorId":12366,"corporation":false,"usgs":true,"family":"Pizzuto","given":"James","affiliations":[],"preferred":false,"id":692989,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70193619,"text":"70193619 - 2014 - Volcanic tremor masks its seismogenic source: Results from a study of noneruptive tremor recorded at Mount St. Helens, Washington","interactions":[],"lastModifiedDate":"2019-03-05T09:40:22","indexId":"70193619","displayToPublicDate":"2014-03-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Volcanic tremor masks its seismogenic source: Results from a study of noneruptive tremor recorded at Mount St. Helens, Washington","docAbstract":"On 2 October 2004, a significant noneruptive tremor episode occurred during the buildup to the 2004–2008 eruption of Mount St. Helens (Washington). This episode was remarkable both because no explosion followed, and because seismicity abruptly stopped following the episode. This sequence motivated us to consider a model for volcanic tremor that does not involve energetic gas release from magma but does involve movement of conduit magma through extension on its way toward the surface. We found that the tremor signal was composed entirely of Love and Rayleigh waves and that its spectral bandwidth increased and decreased with signal amplitude, with broader bandwidth signals containing both higher and lower frequencies. Our modeling results demonstrate that the forces giving rise to this tremor were largely normal to conduit walls, generating hybrid head waves along conduit walls that are coupled to internally reflected waves. Together these form a crucial part of conduit resonance, giving tremor wavefields that are largely a function of waveguide geometry and velocity. We find that the mechanism of tremor generation fundamentally masks the nature of the seismogenic source giving rise to resonance. Thus multiple models can be invoked to explain volcanic tremor, requiring that information from other sources (such as visual observations, geodesy, geology, and gas geochemistry) be used to constrain source models. With concurrent GPS and field data supporting rapid rise of magma, we infer that tremor resulted from drag of nearly solid magma along rough conduit walls as magma was forced toward the surface.
","language":"English","publisher":"AGU","publisherLocation":"Washington, D.C.","doi":"10.1002/2013JB010698","usgsCitation":"Denlinger, R.P., and Moran, S.C., 2014, Volcanic tremor masks its seismogenic source: Results from a study of noneruptive tremor recorded at Mount St. Helens, Washington: Journal of Geophysical Research B: Solid Earth, v. 119, no. 3, p. 2230-2251, https://doi.org/10.1002/2013JB010698.","productDescription":"22 p.","startPage":"2230","endPage":"2251","ipdsId":"IP-051670","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473162,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013jb010698","text":"Publisher Index Page"},{"id":348092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.29362487792969,\n 46.13845231463026\n ],\n [\n -122.10617065429688,\n 46.13845231463026\n ],\n [\n -122.10617065429688,\n 46.26771487683375\n ],\n [\n -122.29362487792969,\n 46.26771487683375\n ],\n [\n -122.29362487792969,\n 46.13845231463026\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"119","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-31","publicationStatus":"PW","scienceBaseUri":"59fc2eabe4b0531197b27fae","contributors":{"authors":[{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moran, Seth C. 0000-0001-7308-9649 smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":548,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719653,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190469,"text":"70190469 - 2014 - Distinguishing between tectonic and lithologic controls on bedrock channel longitudinal profiles using cosmogenic 10Be erosion rates and channel steepness index","interactions":[],"lastModifiedDate":"2017-09-01T10:10:41","indexId":"70190469","displayToPublicDate":"2014-03-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Distinguishing between tectonic and lithologic controls on bedrock channel longitudinal profiles using cosmogenic 10Be erosion rates and channel steepness index","title":"Distinguishing between tectonic and lithologic controls on bedrock channel longitudinal profiles using cosmogenic 10Be erosion rates and channel steepness index","docAbstract":"Knickpoints in fluvial channel longitudinal profiles and channel steepness index values derived from digital elevation data can be used to detect tectonic structures and infer spatial patterns of uplift. However, changes in lithologic resistance to channel incision can also influence the morphology of longitudinal profiles. We compare the spatial patterns of both channel steepness index and cosmogenic 10Be-determined erosion rates from four landscapes in Italy, where the geology and tectonics are well constrained, to four theoretical predictions of channel morphologies, which can be interpreted as the result of primarily tectonic or lithologic controls. These data indicate that longitudinal profile forms controlled by unsteady or nonuniform tectonics can be distinguished from those controlled by nonuniform lithologic resistance. In each landscape the distribution of channel steepness index and erosion rates is consistent with model predictions and demonstrates that cosmogenic nuclide methods can be applied to distinguish between these two controlling factors.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2013.12.010","usgsCitation":"Cyr, A.J., Granger, D., Olivetti, V., and Molin, P., 2014, Distinguishing between tectonic and lithologic controls on bedrock channel longitudinal profiles using cosmogenic 10Be erosion rates and channel steepness index: Geomorphology, v. 209, p. 27-38, https://doi.org/10.1016/j.geomorph.2013.12.010.","productDescription":"12 p.","startPage":"27","endPage":"38","ipdsId":"IP-025041","costCenters":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":345413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"209","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59aa71dae4b0e9bde130cff0","contributors":{"authors":[{"text":"Cyr, Andrew J. 0000-0003-2293-5395 acyr@usgs.gov","orcid":"https://orcid.org/0000-0003-2293-5395","contributorId":3539,"corporation":false,"usgs":true,"family":"Cyr","given":"Andrew","email":"acyr@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":709329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granger, Darryl E.","contributorId":40137,"corporation":false,"usgs":true,"family":"Granger","given":"Darryl E.","affiliations":[],"preferred":false,"id":709330,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Olivetti, Valerio","contributorId":191611,"corporation":false,"usgs":false,"family":"Olivetti","given":"Valerio","email":"","affiliations":[],"preferred":false,"id":709332,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Molin, Paola","contributorId":196097,"corporation":false,"usgs":false,"family":"Molin","given":"Paola","email":"","affiliations":[],"preferred":false,"id":709331,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70194142,"text":"70194142 - 2014 - Mercury dynamics in a coastal aquifer: Maunalua Bay, Oʻahu, Hawaiʻi","interactions":[],"lastModifiedDate":"2018-03-29T15:08:25","indexId":"70194142","displayToPublicDate":"2014-03-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Mercury dynamics in a coastal aquifer: Maunalua Bay, Oʻahu, Hawaiʻi","docAbstract":"We evaluated the influence of groundwater–seawater interaction on mercury dynamics in Maunalua Bay, a coral reef ecosystem located on the south shore of Oʻahu, Hawaiʻi, by combining geochemical data with submarine groundwater discharge (SGD) rates. During a rising tide, unfiltered total mercury (U-HgT) concentrations in seawater increased from ∼6 to 20 pM at Black Point (west Bay) and from ∼2.5 to 8 pM at Niu (central Bay). We attribute this change to an increase in suspended particulate matter at high tide. Approximately 90% of mercury in groundwater at Niu was in the filtered (<0.45 μm) fraction, with a concentration of ∼4 pM. Groundwater discharge during a period of amplified SGD at Niu appeared to contribute to an increase in total mercury concentrations in filtered seawater (F-HgT; 1.2 to 2.4 pM) and in unfiltered seawater (U-HgT; 2.5 to 3.2 pM). The larger magnitude of change in F-HgT relative to U-HgT suggests mercury complexation and/or solubility dynamics in seawater were altered by the addition of groundwater. We used site specific 222Rn derived SGD flux estimates and groundwater F-HgT concentrations to calculate mercury loadings at Black Point (∼3 nmol m−2 d−1) and at Niu (∼1 nmol m−2 d−1). We calculated a weighted average Maunalua Bay groundwater mercury flux of 0.68 ± 0.67 mol yr−1 by combining the proportional flux of F-HgT from three distinct SGD zones, and place these results into a broader context by comparing and contrasting flux estimates from locations around the world. Results from existing SGD studies should be evaluated to develop future sampling strategies that address more targeted questions about mercury biogeochemical cycling at the groundwater–seawater interface.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2014.01.012","usgsCitation":"Ganguli, P.M., Swarzenski, P.W., Dulaiova, H., Glenn, C.R., and Flegal, A.R., 2014, Mercury dynamics in a coastal aquifer: Maunalua Bay, Oʻahu, Hawaiʻi: Estuarine, Coastal and Shelf Science, v. 140, p. 52-65, https://doi.org/10.1016/j.ecss.2014.01.012.","productDescription":"14 p.","startPage":"52","endPage":"65","ipdsId":"IP-051822","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":352960,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Maunalua Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.36517333984375,\n 21.160080508753136\n ],\n [\n -157.57278442382812,\n 21.160080508753136\n ],\n [\n -157.57278442382812,\n 21.783731071583155\n ],\n [\n -158.36517333984375,\n 21.783731071583155\n ],\n [\n -158.36517333984375,\n 21.160080508753136\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"140","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeedebe4b0da30c1bfc73a","contributors":{"authors":[{"text":"Ganguli, Priya M.","contributorId":147439,"corporation":false,"usgs":false,"family":"Ganguli","given":"Priya","email":"","middleInitial":"M.","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":722337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dulaiova, Henrieta","contributorId":184206,"corporation":false,"usgs":false,"family":"Dulaiova","given":"Henrieta","email":"","affiliations":[],"preferred":false,"id":722338,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glenn, Craig R.","contributorId":200438,"corporation":false,"usgs":false,"family":"Glenn","given":"Craig","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":722339,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flegal, A. Russell","contributorId":200439,"corporation":false,"usgs":false,"family":"Flegal","given":"A.","email":"","middleInitial":"Russell","affiliations":[],"preferred":false,"id":722340,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70143405,"text":"70143405 - 2014 - Optical sensors for water quality","interactions":[],"lastModifiedDate":"2015-03-19T09:29:10","indexId":"70143405","displayToPublicDate":"2014-03-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2593,"text":"Lakeline","active":true,"publicationSubtype":{"id":10}},"title":"Optical sensors for water quality","docAbstract":"Shifts in land use, population, and climate have altered hydrologic systems in the United States in ways that affect water quality and ecosystem function. Water diversions, detention in reservoirs, increased channelization, and changes in rainfall and snowmelt are major causes, but there are also more subtle causes such as changes in soil temperature, atmospheric deposition, and shifting vegetation patterns. The effects on water quality are complex and interconnected, and occur at timeframes of minutes (e.g., flash floods) to decades (e.g., evolving management practices).
\nHowever, water-quality monitoring has historically focused on discrete samples collected weekly or monthly, and laboratory analyses that can take days or weeks to complete. Low-frequency data and delayed access hampers a timely response during events, limits the ability to identify specific causes or actions, and may result in poorly quantified effects on ecosystems and human health at local to regional scales.
\n\n
Recent advancements in commercially available in situ sensors, data platforms, and new techniques for data analysis provide an opportunity to monitor water quality in rivers, lakes, and estuaries on the time scales in which changes occur. For example, measurements that capture the variability in freshwater systems over time help to assess how shifts in seasonal runoff, changes in precipitation intensity, and increased frequencies of disturbances (such as fire and insect outbreaks) affect the storage, production, and transport of carbon and nitrogen in watersheds. Transmitting these data in real-time also provides information that can be used for early trend detection, help identify monitoring gaps, and provide sciencebased decision support across a range of issues related to water quality, freshwater ecosystems, and human health.
","language":"English","publisher":"North American Lake Management Society","usgsCitation":"Pellerin, B.A., and Bergamaschi, B., 2014, Optical sensors for water quality: Lakeline, no. Spring, p. 13-17.","productDescription":"5 p.","startPage":"13","endPage":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033523","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":298740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"Spring","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"550bf333e4b02e76d759cdf5","contributors":{"authors":[{"text":"Pellerin, Brian A. bpeller@usgs.gov","contributorId":1451,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":1448,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian A.","email":"bbergama@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542696,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148689,"text":"70148689 - 2014 - Oyster reef restoration in the northern Gulf of Mexico: extent, methods and outcomes","interactions":[],"lastModifiedDate":"2015-07-24T10:26:13","indexId":"70148689","displayToPublicDate":"2014-03-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2926,"text":"Ocean and Coastal Management","active":true,"publicationSubtype":{"id":10}},"title":"Oyster reef restoration in the northern Gulf of Mexico: extent, methods and outcomes","docAbstract":"Shellfish reef restoration to support ecological services has become more common in recent decades, driven by increasing awareness of the functional decline of shellfish systems. Maximizing restoration benefits and increasing efficiency of shellfish restoration activities would greatly benefit from understanding and measurement of system responses to management activities. This project (1) compiles a database of northern Gulf of Mexico inshore artificial oyster reefs created for restoration purposes, and (2) quantitatively assesses a subset of reefs to determine project outcomes. We documented 259 artificial inshore reefs created for ecological restoration. Information on reef material, reef design and monitoring was located for 94, 43 and 20% of the reefs identified. To quantify restoration success, we used diver surveys to quantitatively sample oyster density and substrate volume of 11 created reefs across the coast (7 with rock; 4 with shell), paired with 7 historic reefs. Reefs were defined as fully successful if there were live oysters, and partially successful if there was hard substrate. Of these created reefs, 73% were fully successful, while 82% were partially successful. These data highlight that critical information related to reef design, cost, and success remain difficult to find and are generally inaccessible or lost, ultimately hindering efforts to maximize restoration success rates. Maintenance of reef creation information data, development of standard reef performance measures, and inclusion of material and reef design testing within reef creation projects would be highly beneficial in implementing adaptive management. Adaptive management protocols seek specifically to maximize short and long-term restoration success, but are critically dependent on tracking and measuring system responses to management activities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocecoaman.2013.12.002","usgsCitation":"LaPeyre, M.K., Furlong, J.N., Brown, L.A., Piazza, B.P., and Brown, K., 2014, Oyster reef restoration in the northern Gulf of Mexico: extent, methods and outcomes: Ocean and Coastal Management, v. 89, p. 20-28, https://doi.org/10.1016/j.ocecoaman.2013.12.002.","productDescription":"9 p.","startPage":"20","endPage":"28","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046200","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.20703125,\n 27.916766641249065\n ],\n [\n -97.20703125,\n 31.005862904624205\n ],\n [\n -84.847412109375,\n 31.005862904624205\n ],\n [\n -84.847412109375,\n 27.916766641249065\n ],\n [\n -97.20703125,\n 27.916766641249065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"89","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b361b6e4b09a3b01b5dab3","contributors":{"authors":[{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":549056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Furlong, Jessica N.","contributorId":145458,"corporation":false,"usgs":false,"family":"Furlong","given":"Jessica","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":565677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Laura A.","contributorId":145457,"corporation":false,"usgs":false,"family":"Brown","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":565678,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piazza, Bryan P.","contributorId":11022,"corporation":false,"usgs":true,"family":"Piazza","given":"Bryan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":565679,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Ken","contributorId":145926,"corporation":false,"usgs":false,"family":"Brown","given":"Ken","email":"","affiliations":[],"preferred":false,"id":565680,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70068744,"text":"sir20105090I - 2014 - Porphyry copper assessment of Central America and the Caribbean Basin","interactions":[{"subject":{"id":70068744,"text":"sir20105090I - 2014 - Porphyry copper assessment of Central America and the Caribbean Basin","indexId":"sir20105090I","publicationYear":"2014","noYear":false,"chapter":"I","title":"Porphyry copper assessment of Central America and the Caribbean Basin"},"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":"2022-12-12T17:03:35.638028","indexId":"sir20105090I","displayToPublicDate":"2014-02-28T14:29:00","publicationYear":"2014","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":"I","title":"Porphyry copper assessment of Central America and the Caribbean Basin","docAbstract":"Mineral resource assessments provide a synthesis of available information about distributions of mineral deposits in the Earth’s crust. The U.S. Geological Survey prepared a probabilistic mineral resource assessment of undiscovered resources in porphyry copper deposits in Central America and the Caribbean Basin in collaboration with geoscientists from academia and the minerals industry. The purpose of the study was to (1) delineate permissive areas (tracts) for undiscovered porphyry copper deposits within 1 kilometer of the surface at a scale of 1:1,000,000; (2) provide a database of known porphyry copper deposits and significant prospects; (3) estimate numbers of undiscovered deposits within the permissive tracts; and (4) provide probabilistic estimates of amounts of copper, molybdenum, gold, and silver that could be contained in undiscovered deposits. The assessment was done using a three-part mineral resource assessment based on established mineral deposit models. Permissive tracts were delineated based primarily on distributions of mapped igneous rocks related to magmatic arcs that formed in tectonic settings associated with convergent plate margins. Five permissive tracts were delineated: the Early Cretaceous through Eocene Santiago tract, the Late Cretaceous through Oligocene Chortis tract, the Paleocene through Oligocene Darién tract, the Miocene and Pliocene Cocos tract, and the Eocene to Holocene Lesser Antilles tract. These tracts range in size from about 3,000 to about 204,000 square kilometers.
\nProbabilistic estimates of numbers of undiscovered deposits were made for all tracts. To estimate the number of undiscovered porphyry copper deposits, data on known mineral deposits, prospects, and occurrences were considered along with mapped alteration zones, local stream-sediment geochemistry, exploration history, descriptive deposit models, and grade and tonnage models.
\nMost porphyry copper exploration in Central America and the Caribbean Basin has focused on Panama and on the exposed Cretaceous to Eocene central Cordilleran arc that extends from Cuba and Jamaica through Haiti and the Dominican Republic to Puerto Rico and the Virgin Islands. Interest in gold has prompted exploration of historical precious-metal prospects and small mines, some of which may represent high-sulfidation epithermal systems or skarns overlying, or adjacent to, porphyry copper systems.
\nThis assessment estimated a total mean of 37 undiscovered porphyry copper deposits within the assessed permissive tracts in Central America and the Caribbean Basin. This represents more than five times the seven known deposits. Predicted mean (arithmetic) resources that could be associated with these undiscovered deposits are about 130 million metric tons of copper and about 5,200 metric tons of gold, as well as byproduct molybdenum and silver. The reported identified resources for the seven known deposits total about 39 million metric tons of copper and about 930 metric tons of gold. The assessment area is estimated to contain nearly four times as much copper and six times as much gold in undiscovered porphyry copper deposits as has been identified to date.
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Oil spread in a southwesterly direction and was deposited on shores and waters in western Prince William Sound (WPWS). The sea otter (Enhydra lutris) was one of more than 20 nearshore species considered to have been injured by the spill. Since 1989, the U.S. Geological Survey has led a research program to evaluate effects of the spill on sea otters and assess progress toward recovery, as defined by demographic and biochemical indicators. Here, we provide an update on the status of sea otter populations in WPWS, presenting findings through 2013. To assess recovery based on demographic indicators, we used aerial surveys to estimate abundance and annual collections of sea otter carcasses to evaluate patterns in ages-at-death. To assess recovery based on biochemical indicators, we quantified transcription rates for a suite of genes selected as potential indicators of oil exposure in sea otters based on laboratory studies of a related species, the mink (Mustela vison). In our most recent assessment of sea otter recovery, which incorporated results from a subset of studies through 2009, we concluded that recovery of sea otters in WPWS was underway. This conclusion was based on increasing abundance throughout WPWS, including increasing numbers at northern Knight Island, an area that was heavily oiled in 1989 and where the local sea otter population had previously shown protracted injury and lack of recovery. However, we did not conclude that the WPWS sea otter population had fully recovered, due to indications of continuing reduced survival and exposure to lingering oil in sea otters at Knight Island, at least through 2009. Based on data available through 2013, we now conclude that the status of sea otters—at all spatial scales within WPWS—is consistent with the designation of recovery from the spill as defined by the Exxon Valdez Oil Spill Trustee Council. The support for this conclusion is based primarily on demographic data, including (1) a return to estimated pre-spill abundance of sea otters at northern Knight Island, and (2) a return to pre-spill mortality patterns. Gene transcription rates in 2012 were similar in sea otters from oiled, moderately oiled and unoiled areas, suggesting abatement of exposure effects in 2012. However, because 2012 gene transcription rates generally were low for sea otters from all areas relative to 2008, we cannot fully interpret these observations without data from a wider panel of genes. This slight uncertainty with respect to the data from the biochemical indicator is outweighed by the strength of the data for the demographic indicators. The return to pre-spill numbers and mortality patterns suggests a gradual dissipation of lingering oil over the past two decades, to the point where continuing exposure is no longer of biological significance to the WPWS sea otter population.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141030","issn":"2331-1258","usgsCitation":"Ballachey, B.E., Monson, D., Esslinger, G.G., Kloecker, K.A., Bodkin, J.L., Bowen, L., and Miles, A.K., 2014, 2013 update on sea otter studies to assess recovery from the 1989 Exxon Valdez oil spill, Prince William Sound, Alaska: U.S. Geological Survey Open-File Report 2014-1030, iv, 40 p., https://doi.org/10.3133/ofr20141030.","productDescription":"iv, 40 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-051870","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":282939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141030.jpg"},{"id":282938,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1030/pdf/ofr2014-1030.pdf"},{"id":282937,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1030/"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -148.5,60.0 ], [ -148.5,61.0 ], [ -146.5,61.0 ], [ -146.5,60.0 ], [ -148.5,60.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4928e4b0b290850eeec9","contributors":{"authors":[{"text":"Ballachey, Brenda E. 0000-0003-1855-9171 bballachey@usgs.gov","orcid":"https://orcid.org/0000-0003-1855-9171","contributorId":2966,"corporation":false,"usgs":true,"family":"Ballachey","given":"Brenda","email":"bballachey@usgs.gov","middleInitial":"E.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":490272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monson, Daniel H. 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":140480,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel H.","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":490273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esslinger, George G. 0000-0002-3459-0083 gesslinger@usgs.gov","orcid":"https://orcid.org/0000-0002-3459-0083","contributorId":131009,"corporation":false,"usgs":true,"family":"Esslinger","given":"George","email":"gesslinger@usgs.gov","middleInitial":"G.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":490274,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kloecker, Kimberly A. 0000-0002-2461-968X kkloecker@usgs.gov","orcid":"https://orcid.org/0000-0002-2461-968X","contributorId":3442,"corporation":false,"usgs":true,"family":"Kloecker","given":"Kimberly","email":"kkloecker@usgs.gov","middleInitial":"A.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":490276,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bodkin, James L. 0000-0003-1641-4438 jbodkin@usgs.gov","orcid":"https://orcid.org/0000-0003-1641-4438","contributorId":748,"corporation":false,"usgs":true,"family":"Bodkin","given":"James","email":"jbodkin@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":490277,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":490275,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miles, A. 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Modifications include changes to the main ModelMuse window where the model is designed, addition of methods for generating a finite-element mesh suitable for SUTRA, defining how some functions shouldapply when using a finite-element mesh rather than a finite-difference grid (as originally programmed in ModelMuse), and applying spatial interpolation to angles. In addition, the report describes ways of handling objects on the front view of the model and displaying data. A tabulation contains a summary of the new or modified dialog boxes.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Ground water in Book 6 Modeling Techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A49","collaboration":"This report is Chapter 49 of Section A: Ground water in Book 6 Modeling Techniques. This Techniques and Methods report supplements USGS Techniques and Methods 6-A29.","usgsCitation":"Winston, R.B., 2014, Modifications made to ModelMuse to add support for the Saturated-Unsaturated Transport model (SUTRA): U.S. Geological Survey Techniques and Methods 6-A49, iii, 6 p., https://doi.org/10.3133/tm6A49.","productDescription":"iii, 6 p.","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-052670","costCenters":[{"id":434,"text":"National Research Program","active":false,"usgs":true}],"links":[{"id":282934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm6a49.jpg"},{"id":282932,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/06/a49/"},{"id":282933,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a49/pdf/tm6-a49.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd67fde4b0b29085101bf3","contributors":{"authors":[{"text":"Winston, Richard B. 0000-0002-6287-8834 rbwinst@usgs.gov","orcid":"https://orcid.org/0000-0002-6287-8834","contributorId":3567,"corporation":false,"usgs":true,"family":"Winston","given":"Richard","email":"rbwinst@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":490013,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70094491,"text":"ofr20141033 - 2014 - Logs and data from trenches across the Berryessa Fault at the Jerd Creek site, northeastern Napa County, California, 2011-2012","interactions":[],"lastModifiedDate":"2014-02-28T08:25:10","indexId":"ofr20141033","displayToPublicDate":"2014-02-28T08:00:00","publicationYear":"2014","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":"2014-1033","title":"Logs and data from trenches across the Berryessa Fault at the Jerd Creek site, northeastern Napa County, California, 2011-2012","docAbstract":"The primary purpose of this report is to provide drafted field logs of exploratory trenches excavated across the Berryessa Fault section of the northern Green Valley Fault (Lienkaemper, 2012; Lienkaemper and others, 2013) in 2011 and 2012 that show evidence for at least one surface-rupturing earthquake in the past few centuries. The site location and site detail are shown on sheet 1. The trench logs are shown on sheets 1, 2, 3 and 4. We also provide radiocarbon ages used for chronological modeling of the earthquake history and a field description of a soil profile in one trench. A formal report based on these logs and data is in preparation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141033","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation","usgsCitation":"Lienkaemper, J.J., Rosa, C.M., Cappelle, I.J., Wolf, E.M., Knepprath, N.E., Piety, L.A., Derouin, S.A., Reidy, L.M., Redwine, J.L., and Sickler, R.R., 2014, Logs and data from trenches across the Berryessa Fault at the Jerd Creek site, northeastern Napa County, California, 2011-2012: U.S. Geological Survey Open-File Report 2014-1033, Sheets 1-4: 40.0 x 18.0 inches or smaller; Pamphlet: iii, 6 p.; Appendix, https://doi.org/10.3133/ofr20141033.","productDescription":"Sheets 1-4: 40.0 x 18.0 inches or smaller; Pamphlet: iii, 6 p.; Appendix","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-046261","costCenters":[{"id":380,"text":"Menlo ParkCalif. 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2014 - Assessment of undiscovered sandstone copper deposits of the Kodar-Udokan area, Russia","interactions":[{"subject":{"id":70094933,"text":"sir20105090M - 2014 - Assessment of undiscovered sandstone copper deposits of the Kodar-Udokan area, Russia","indexId":"sir20105090M","publicationYear":"2014","noYear":false,"chapter":"M","title":"Assessment of undiscovered sandstone copper deposits of the Kodar-Udokan area, Russia"},"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":"2022-12-12T17:05:12.920879","indexId":"sir20105090M","displayToPublicDate":"2014-02-28T07:40:00","publicationYear":"2014","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":"M","title":"Assessment of undiscovered sandstone copper deposits of the Kodar-Udokan area, Russia","docAbstract":"Mineral resource assessments integrate and synthesize available information as a basis for estimating the location, quality, and quantity of undiscovered mineral resources. This probabilistic mineral resource assessment of undiscovered sandstone copper deposits within Paleoproterozoic metasedimentary rocks of the Kodar-Udokan area in Russia is a contribution to a global assessment led by the U.S. Geological Survey (USGS). The purposes of this study are to (1) delineate permissive areas (tracts) to indicate where undiscovered sandstone-hosted copper deposits may occur within 2 km of the surface, (2) provide a database of known sandstone copper deposits and significant prospects, (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) and mineralized rock that could be contained in undiscovered deposits within each tract. The workshop for the assessment, held in October 2009, used a three-part form of mineral resource assessment as described by Singer (1993) and Singer and Menzie (2010).
\nPermissive tracts were delineated by estimating the volume of rock that contains the stratigraphic section ranging from the Chitkanda to the Sakukan Formations of the Udokan Complex to a depth of 2 km and then projecting this rock volume to the surface. The six permissive tracts delineated in this assessment occur in several domains, referred to as troughs in Russian literature, which represent remnants of a much larger basin that likely covered the Kodar-Udokan region. Tracts range in size from about 100 km2 to 800 km2. The mapped distributions of rocks as shown on 1:200,000-scale geologic maps, supplemented in some areas by prospect mapping and drilling, were used to delineate the tracts.
\nIn this study area, data are insufficient to constrain the original basin geometry or the structural or stratigraphic traps that would have localized copper mineralization. Some alteration is described, and the types of sandstone cements vary; however, no patterns are known that provide evidence for regional flow paths of metal-bearing brines that could localize deposits.
\nThis probabilistic assessment indicates that a significant amount of undiscovered copper is associated with sediment-hosted stratabound copper deposits in the Kodar-Udokan Trough. In the assessment, a mean of 21 undiscovered deposits is estimated to occur within the Kodar-Udokan area. There are two known deposits in the area that contain drill-identified resources of 19.6 million metric tons of copper. Using Monte Carlo simulation, probabilistic estimates of the numbers of undiscovered sandstone copper deposits for these tracts were combined with tonnage and grade distributions of sandstone copper deposits to forecast an arithmetic mean of 20.6 million metric tons of undiscovered copper. Significant value can be expected from associated metals, particularly silver.
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Center","active":true,"usgs":true}],"preferred":true,"id":490982,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wintzer, Niki E. 0000-0003-3085-435X nwintzer@usgs.gov","orcid":"https://orcid.org/0000-0003-3085-435X","contributorId":5297,"corporation":false,"usgs":true,"family":"Wintzer","given":"Niki","email":"nwintzer@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":490988,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70072589,"text":"ofr20141006 - 2014 - Precipitation variability of the Grand Canyon region, 1893 through 2009, and its implications for studying effects of gullying of Holocene terraces and associated archeological sites in Grand Canyon, Arizona","interactions":[],"lastModifiedDate":"2014-02-27T13:48:39","indexId":"ofr20141006","displayToPublicDate":"2014-02-27T13:38:00","publicationYear":"2014","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":"2014-1006","title":"Precipitation variability of the Grand Canyon region, 1893 through 2009, and its implications for studying effects of gullying of Holocene terraces and associated archeological sites in Grand Canyon, Arizona","docAbstract":"A daily precipitation dataset covering a large part of the American Southwest was compiled for online electronic distribution (http://pubs.usgs.gov/of/2014/1006/). The dataset contains 10.8 million observations spanning January 1893 through January 2009 from 846 weather stations in six states and 13 climate divisions. In addition to processing the data for distribution, water-year totals and other statistical parameters were calculated for each station with more than 2 years of observations. Division-wide total precipitation, expressed as the average deviation from the individual station means of a climate division, shows that the region—including the Grand Canyon, Arizona, area—has been affected by alternating multidecadal episodes of drought and wet conditions.
\nIn addition to compiling and analyzing the long-term regional precipitation data, a second dataset consisting of high-temporal-resolution precipitation measurements collected between November 2003 and January 2009 from 10 localities along the Colorado River in Grand Canyon was compiled. An exploratory study of these high-temporal-resolution precipitation measurements suggests that on a daily basis precipitation patterns are generally similar to those at a long-term weather station in the canyon, which in turn resembles the patterns at other long-term stations on the canyon rims; however, precipitation amounts recorded by the individual inner canyon weather stations can vary substantially from station to station. Daily and seasonal rainfall patterns apparent in these data are not random. For example, the inner canyon record, although short and fragmented, reveals three episodes of widespread, heavy precipitation in late summer 2004, early winter 2005, and summer 2007. The 2004 event and several others had sufficient rainfall to initiate potentially pervasive erosion of the late Holocene terraces and related archeological features located along the Colorado River in Grand Canyon.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141006","usgsCitation":"Hereford, R., Bennett, G., and Fairley, H., 2014, Precipitation variability of the Grand Canyon region, 1893 through 2009, and its implications for studying effects of gullying of Holocene terraces and associated archeological sites in Grand Canyon, Arizona: U.S. Geological Survey Open-File Report 2014-1006, Report: iii, 23 p.; Database, https://doi.org/10.3133/ofr20141006.","productDescription":"Report: iii, 23 p.; Database","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1893-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-025450","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":282905,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1006/downloads/ofr2014-1006_Database.zip"},{"id":282903,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1006/"},{"id":282904,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1006/pdf/ofr2014-1006.pdf"},{"id":282906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141006.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River;Grand Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.01,32.0 ], [ -119.01,41.01 ], [ -103.77,41.01 ], [ -103.77,32.0 ], [ -119.01,32.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd6c54e4b0b290851047c0","contributors":{"authors":[{"text":"Hereford, Richard 0000-0002-0892-7367 rhereford@usgs.gov","orcid":"https://orcid.org/0000-0002-0892-7367","contributorId":3620,"corporation":false,"usgs":true,"family":"Hereford","given":"Richard","email":"rhereford@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":488507,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennett, Glenn E. gbennett@usgs.gov","contributorId":4153,"corporation":false,"usgs":true,"family":"Bennett","given":"Glenn E.","email":"gbennett@usgs.gov","affiliations":[],"preferred":true,"id":488508,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fairley, Helen C.","contributorId":10506,"corporation":false,"usgs":true,"family":"Fairley","given":"Helen C.","affiliations":[],"preferred":false,"id":488509,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70093635,"text":"sir20145006 - 2014 - Mean annual, seasonal, and monthly precipitation and runoff in Arkansas, 1951-2011","interactions":[],"lastModifiedDate":"2014-02-27T11:03:37","indexId":"sir20145006","displayToPublicDate":"2014-02-27T10:52:00","publicationYear":"2014","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":"2014-5006","title":"Mean annual, seasonal, and monthly precipitation and runoff in Arkansas, 1951-2011","docAbstract":"This report describes long-term annual, seasonal, and monthly means for precipitation and runoff in Arkansas for the period from 1951 through 2011. Precipitation means were estimated using data from the Parameter-elevation Regressions on Independent Slopes Model database; while total runoff, groundwater runoff, and surface runoff means were estimated using data from 123 active and inactive U.S. Geological Survey continuous-record streamflow-gaging stations located in Arkansas and surrounding States. Annual precipitation in Arkansas for the period from 1951 through 2011 had a mean of 49.8 inches. Of the six physiographic sections in Arkansas, the Ouachita Mountains had the largest mean annual precipitation at 53.0 inches, while the Springfield-Salem plateaus had the smallest mean annual precipitation at 45.5 inches. The mean annual total runoff for Arkansas was 17.8 inches. The Ouachita Mountains had the largest mean annual total runoff at 20.4 inches, while the Springfield-Salem plateaus had the smallest mean annual total runoff at 15.0 inches. Runoff is diminished during the dry season, which is attributed to increased losses from evapotranspiration, consumptive uses including irrigation, and increased withdrawals for public and private water supplies. The decline in runoff during the dry season is observed across the State in all physiographic sections. Spatial results for precipitation and runoff are presented in a series of maps that are available for download from the publication Web page in georeferenced raster formats.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145006","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission","usgsCitation":"Pugh, A., and Westerman, D.A., 2014, Mean annual, seasonal, and monthly precipitation and runoff in Arkansas, 1951-2011: U.S. Geological Survey Scientific Investigations Report 2014-5006, Report: v, 40 p.; Downloads Directory: Appendixes 1-3, https://doi.org/10.3133/sir20145006.","productDescription":"Report: v, 40 p.; Downloads Directory: Appendixes 1-3","numberOfPages":"49","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1951-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-053322","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":282887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145006.jpg"},{"id":282884,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5006/"},{"id":282885,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5006/pdf/sir2014-5006.pdf"},{"id":282886,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5006/downloads/"}],"projection":"USA Contiguous Albers Equal Area Conic USGS version","datum":"North American Datum 1983","country":"United States","state":"Arkansas","otherGeospatial":"Ouachita Mountains;Springfield-salem Plateaus","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.75,32.0 ], [ -95.75,38.0 ], [ -88.9,38.0 ], [ -88.9,32.0 ], [ -95.75,32.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd666be4b0b29085100bb6","contributors":{"authors":[{"text":"Pugh, Aaron L. apugh@usgs.gov","contributorId":2480,"corporation":false,"usgs":true,"family":"Pugh","given":"Aaron L.","email":"apugh@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westerman, Drew A. 0000-0002-8522-776X dawester@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-776X","contributorId":4526,"corporation":false,"usgs":true,"family":"Westerman","given":"Drew","email":"dawester@usgs.gov","middleInitial":"A.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490102,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}