Puccinia psidii was first described by Winter (1884) on guava (Psidium guajava L.) in Brazil. The rust is still a major pest of native guava in Brazil and is often referred to as “guava rust” internationally. It is unusual among rust fungi because of its broad and ever-expanding host-range within the Myrtaceae plant family (Simpson et al. 2006). The pathogen is regarded as a major threat to Eucalyptus plantations and other Myrtaceae worldwide (Coutinho et al. 1998, Grgurinovic et al. 2006, Glen et al. 2007). Infections of leaves and meristems are particularly severe on susceptible seedlings, cuttings, young trees, and coppice, causing plants to be stunted and multi-branched, inhibiting normal growth and development, and sometimes causing death to young seedlings (Booth et al. 2000, Rayachhetry et al. 2001). The fungus has expanded its host-range in Brazil, affecting both native and introduced Myrtaceae (Coutinho et al. 1998).
Since its discovery in 1884, P. psidii has continually been discovered to have an expanding host-range within the Myrtaceae, affecting hosts throughout much of South and Central America and the Caribbean. Spreading out originally from Brazil in 1884, the fungus has been reported on hosts in the following countries (first record in parentheses): Paraguay (1884), Uruguay (1889), Ecuador (1891), Colombia (1913), Puerto Rico (1913), Cuba (1926), Dominican Republic (1933), Venezuela (1934), Jamaica (1936), Argentina (1946), Dominica (1948), Trinidad and Tobago (1951), Guatemala (1968), United States (Florida; 1977), Mexico (1981), El Salvador (1987), and Costa Rica (1998) (Simpson et al. 2006). It is possible that P. psidii was present in El Salvador and Costa Rica prior to 1980, but was not reported until 1987 and 1998, respectively.
Until recently, Puccinia psidii was restricted to the Neotropics, Mexico, and the state of Florida in the United States. While the rust has been present in Florida for over 30 years, only recently has it spread westward. Although possibly present earlier, P. psidii was found in California in November 2005 in a nursery in San Diego County on Myrtus communis and documented by a report in a nursery newsletter (Mellano 2006). Puccinia psidii was first found in Hawai`i on a young plant of `ōhi`a (Metrosideros polymorpha) in April 2005, in a nursery on the island of O`ahu (Killgore and Heu 2005; Uchida et al. 2006). The fungus subsequently spread to most islands of the Hawaiian chain, infecting `ōhi`a and other myrtaceous hosts (Hauff 2006, Anderson et al. 2007). P. psidii was first found in Japan in May 2007 on cultivated `ōhi`a (Kawanishi et al. 2009).
Most recently, a rust identified as Uredo rangelii was discovered in April 2010 in New South Wales, Australia (Carnegie et al. 2010). This rust is closely related to Puccinia psidii and is part of the guava rust complex described by Simpson et al. (2006). Although treated as a separate species by Simpson et al. (2006), many authors now consider U. rangelii a synonym for U. psidii, which is the anamorph (asexual stage) of P. psidii, and therefore, the same species (Glen et al. 2007, Carnegie et al. 2010). Because of the large diversity of native Myrtaceae present in Australia, the number of Myrtaceae hosts attacked by species of the guava rust complex will likely grow now that U. rangelii has arrived and is spreading in the country. As of this writing (June 2011), 94 species of Myrtaceae have been identified as hosts of U. rangelii in the states of New South Wales and Queensland. Damage is severe on nearly one-third of the species affected, and 16 of these species are threatened or endangered native species (Secretary of Australia, May 2011).
The presence of Puccinia psidii in Hawai`i is particularly alarming for at least two reasons: (1) M. polymorpha is the dominant overstory tree of the native forest, and (2) P. psidii is now established in the Pacific region, where numerous Myrtaceae species are native. Native ecosystems in Hawai`i and the Pacific could be seriously affected by the spread of P. psidii, as both native and introduced Myrtaceae are significant components of many different plant communities throughout the region (Glen et al. 2007). Because the guava rust complex (i.e., P. psidii and U. rangelii) now attacks well over 100 species of Myrtaceae worldwide, it is currently a priority for international quarantine and import restrictions in an effort to prevent further spread among Australasian and Pacific Myrtaceae.
Several different studies have been done to determine what degree of genetic variation exists between isolates of Puccinia psidii from many different host plants and many different locations (Langrell et al. 2008, Kawanishi et al. 2009, Kadooka 2010, Graça et al. 2011). So far, all of these studies have shown that all of the Hawaiian samples tested so far have had the same genetic composition. Given that the P. psidii strain in Hawai`i has continually been shown for over five years to lack genetic variation at microsatellite marker sites (which are believed to undergo relatively rapid genetic change), a baseline evaluation of incidence and severity should be especially valuable to provide comparisons with future conditions.
Worldwide, 23 Neotropical species in 11 genera and 59 Australasian and Pacific species in 13 genera had been recorded as hosts of Puccinia psidii before 2010 (Simpson et al. 2006, Anderson et al. 2007). Of those 82 species known to be hosts elsewhere, 42 are cultivated or naturalized in Hawai`i. Because of its wide host-range and aggressive pathogenicity, rust disease caused by P. psidii poses a considerable disease threat to many native and cultivated Myrtaceae throughout the world (Coutinho et al. 1998, Booth et al. 2000, Simpson et al. 2006). However, there are few reports comparing the severity of rust infection on native, introduced, and cultivated Myrtaceae (Rayachhetry et al. 2001, Perez et al. 2010). Since government agencies and the public are concerned about the extent of the rust movement within and to Hawai`i (Loope and La Rosa 2008, Loope 2010), there is a need to better understand the incidence, severity, and distribution of P. psidii in Hawai`i. To address that need, this research project was initiated to survey forests, surrounding plant communities, botanical gardens, and commercial nurseries to detect the presence and severity of P. psidii rust infections throughout Hawai`i on plants in the Myrtaceae family. This study provides a baseline on the host distribution and severity to compare current and future impacts of rust infections caused by P. psidii on native, naturalized, and cultivated Myrtaceae in Hawai`i.
No abstract available.
","language":"English","publisher":"SME","usgsCitation":"Bolen, W.P., 2012, Perlite, 2011: Mining Engineering, v. 64, no. 6, p. 33-33.","productDescription":"1 p.","startPage":"33","endPage":"33","ipdsId":"IP-037002","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":338924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":338923,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://me.smenet.org/abstract.cfm?preview=1&articleID=2640&page=33"}],"volume":"64","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58df6ac8e4b02ff32c6aea75","contributors":{"authors":[{"text":"Bolen, Wallace P. wbolen@usgs.gov","contributorId":2121,"corporation":false,"usgs":true,"family":"Bolen","given":"Wallace","email":"wbolen@usgs.gov","middleInitial":"P.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":687444,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70038447,"text":"ofr20121120 - 2012 - A Markov chain analysis of the movements of juvenile salmonids, including sockeye salmon, in the forebay of McNary Dam, Washington and Oregon, 2006-09","interactions":[],"lastModifiedDate":"2012-06-02T01:01:38","indexId":"ofr20121120","displayToPublicDate":"2012-06-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1120","title":"A Markov chain analysis of the movements of juvenile salmonids, including sockeye salmon, in the forebay of McNary Dam, Washington and Oregon, 2006-09","docAbstract":"Passage and survival data were collected at McNary Dam between 2006 and 2009. These data have provided critical information for resource managers to implement structural and operational changes designed to improve the survival of juvenile salmonids as they migrate past the dam. Much of the valuable information collected at McNary Dam was in the form of three-dimensional (hereafter referred to as 3-D) tracks of fish movements in the forebay. These data depicted the behavior of multiple species (in three dimensions) during different diel periods, spill conditions, powerhouse operations, and testing of the surface bypass structures (temporary spillway weirs; TSWs). One of the challenges in reporting 3-D results is presenting the information in a manner that allows interested parties to summarize the behavior of many fish over many different conditions across multiple years. To accomplish this, we used a Markov chain analysis to characterize fish movement patterns in the forebay of McNary Dam. The Markov chain analysis allowed us to numerically summarize the behavior of fish in the forebay. This report is the second report published in 2012 that uses this analytical method. The first report included only fish released as part of the annual studies conducted at McNary Dam. This second report includes sockeye salmon that were released as part of studies conducted by the Chelan and Grant County Public Utility Districts at mid-Columbia River dams. The studies conducted in the mid-Columbia used the same transmitters as were used for McNary Dam studies, but transmitter pulse width was different between studies. Additionally, no passive integrated transponder tags were implanted in sockeye salmon. Differences in transmitter pulse width resulted in lower detection probabilities for sockeye salmon at McNary Dam. The absence of passive integrated transponder tags prevented us from determining if fish passed the powerhouse through the juvenile bypass system (JBS) or turbines. To facilitate comparison among species in this report, we combined JBS and turbine passage for yearling Chinook salmon, steelhead, and subyearling Chinook salmon even though we were able to differentiate between passage through the JBS or turbines for these three species. Information on passage proportions through the JBS and turbines can be found in the first report. Numerically summarizing the behavior of juvenile salmonids in the forebay of McNary Dam using the Markov chain analysis allowed us to confirm what had been previously summarized using visualization software. For example, within the powerhouse region, passage proportions among the three powerhouse areas were often greater in the southern and middle areas of the powerhouse compared to the northern area of the powerhouse for yearling and subyearling Chinook salmon. The opposite generally was observed for steelhead. The results of this analysis also allowed us to confirm and quantify the extent of milling behavior that was observed for steelhead. For fish that were first detected in the powerhouse region, less than 0.10 of the steelhead, on average, passed within each of the powerhouse areas. Instead, steelhead transitioned to adjoining areas in the spillway before passing the dam. In comparison, greater than 0.20 of the Chinook salmon passed within each of the powerhouse areas. Less milling behavior was observed for all species for fish that first approached the spillway. Compared to the powerhouse areas, a higher proportion of fish, regardless of species, passed the spillway areas and fewer transitioned to adjoining areas in the powerhouse. In addition to quantifying what had been previously speculated about the behavior of fish in the forebay of McNary Dam, the Markov chain analysis refined our understanding of how fish behavior and passage can be influenced by changes to the operations and structure of McNary Dam. For example, the addition of TSWs to the spillway area clearly influenced the passage of fish. Previous results have been reported showing that TSWs increased passage through non-turbine routes and the fish-track videos indicated, in general, how fish behaved before passing the TSWs. However, the analysis presented in this report allowed us to better understand how fish transitioned across the face of the dam before passing the TSWs and resulted in a quantitative way to measure the effect of moving the location of the TSWs from year to year. Installation of the TSWs in bays 22 and 20 clearly increased passage proportions through the southern one-third of the spillway area for all species, most significantly for steelhead. When the TSWs were moved to bays 19 and 20 in 2008, overall passage through the southern one-third of the spillway remained higher than 2006, but decreased from what was observed in 2007. Shifting the TSWs to the north decreased the proportion of fish passing through the TSWs and increased the number of fish that transitioned to adjoining areas before passing the dam. Perhaps the most interesting new information to come out of the two-step Markov chain analysis relates to how the performance of the TSWs was influenced by their proximity to the powerhouse. During 2007, the highest proportion of fish passing through TSW 22 was for fish that transitioned from the powerhouse area. In contrast, a relatively low proportion of fish passed through TSW 20 after coming from the powerhouse area. Instead, the proportion of fish that passed TSW 20 after coming from the northern part of the spillway was twice as high as the proportion of fish that passed through TSW 20 after coming from the powerhouse. During 2008, the TSW in bay 22 was moved to bay 19, leaving the TSW in bay 20 as the one closest to the powerhouse. As was the case when a TSW was located in bay 22, the proportion of fish passing through TSW 20 after coming from the powerhouse was higher than the proportion of fish passing TSW 20 after coming from the northern part of the spillway. Passage proportions for fish passing through TSW 19, the farthest north of the two TSWs during 2008, was higher for fish that came from the northern part of the spillway compared to the proportion of fish that passed through TSW 19 after coming from the powerhouse. The Markov chain analysis provided a mathematical way to characterize fish behavior in the forebay of McNary Dam and helped refine our understanding of how fish movements were influenced by operational and structural changes at the dam. The numerical information used to quantify the behavior of fish also can be used to construct simulations to examine how proposed fish passage structures might influence passage of juvenile salmonids. To demonstrate this, we used the results of the Markov chain analysis to examine how a virtual fish collector located in the center of the powerhouse might influence passage of juvenile salmonids at McNary Dam.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121120","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Adams, N.S., and Hatton, T., 2012, A Markov chain analysis of the movements of juvenile salmonids, including sockeye salmon, in the forebay of McNary Dam, Washington and Oregon, 2006-09: U.S. Geological Survey Open-File Report 2012-1120, viii, 71 p.; Appendices, https://doi.org/10.3133/ofr20121120.","productDescription":"viii, 71 p.; Appendices","temporalStart":"2006-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":257110,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1120.jpg"},{"id":257109,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1120/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon;Washington","otherGeospatial":"Mcnary Dam;Columbia River;Snake River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121,45.5 ], [ -121,48.25 ], [ -117.5,48.25 ], [ -117.5,45.5 ], [ -121,45.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd495be4b0b290850ef173","contributors":{"authors":[{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":464162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatton, Tyson W. 0000-0002-2874-0719","orcid":"https://orcid.org/0000-0002-2874-0719","contributorId":9112,"corporation":false,"usgs":true,"family":"Hatton","given":"Tyson W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":464163,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70038448,"text":"sim3165 - 2012 - Geologic map of the Themis Regio quadrangle (V-53), Venus","interactions":[],"lastModifiedDate":"2012-06-02T01:01:38","indexId":"sim3165","displayToPublicDate":"2012-06-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3165","title":"Geologic map of the Themis Regio quadrangle (V-53), Venus","docAbstract":"The Themis Regio quadrangle (V-53), Venus, has been geologically mapped at 1:5,000,000 scale as part of the NASA Planetary Geologic Mapping Program. The quadrangle extends from lat 25° to 50° S. and from long 270° to 300° E. and encompasses the Themis Regio highland, the surrounding plains, and the southernmost extension of Parga Chasmata. Themis Regio is a broad regional topographic high with a diameter of about 2,000 km and a height of about 0.5 km that has been interpreted previously as a hotspot underlain by a mantle plume. The Themis rise is dominated by coronae and lies at the terminus of the Parga Chasmata corona chain. Themis Regio is the only one of the three corona-dominated rises that contains significant extensional deformation. Fractures and grabens are much less common than along the rest of Parga Chasmata and are embayed by corona-related flows in places. Rift and corona formation has overlapped in time at Themis Regio.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3165","collaboration":"Prepared for the National Aeronautics and Space Administration","usgsCitation":"Stofan, E.R., and Brian, A.W., 2012, Geologic map of the Themis Regio quadrangle (V-53), Venus: U.S. Geological Survey Scientific Investigations Map 3165, i, 13p.; 1 Sheet; Sheet 1: 49.39 inches x 33.01 inches, https://doi.org/10.3133/sim3165.","productDescription":"i, 13p.; 1 Sheet; Sheet 1: 49.39 inches x 33.01 inches","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":257118,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3165.gif"},{"id":257115,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3165/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1ec2e4b0c8380cd56724","contributors":{"authors":[{"text":"Stofan, Ellen R.","contributorId":103746,"corporation":false,"usgs":true,"family":"Stofan","given":"Ellen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":464165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brian, Antony W.","contributorId":89623,"corporation":false,"usgs":true,"family":"Brian","given":"Antony","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":464164,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70038446,"text":"ofr20121119 - 2012 - A Markov chain analysis of the movements of juvenile salmonids in the forebay of McNary Dam, Washington and Oregon, 2006-09","interactions":[],"lastModifiedDate":"2012-06-02T01:01:38","indexId":"ofr20121119","displayToPublicDate":"2012-06-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1119","title":"A Markov chain analysis of the movements of juvenile salmonids in the forebay of McNary Dam, Washington and Oregon, 2006-09","docAbstract":"Passage and survival data for yearling and subyearling Chinook salmon and juvenile steelhead were collected at McNary Dam between 2006 and 2009. These data have provided critical information for resource managers to implement structural and operational changes designed to improve the survival of juvenile salmonids as they migrate past the dam. Much of the information collected at McNary Dam was in the form of three-dimensional tracks of fish movements in the forebay. These data depicted the behavior of multiple species (in three dimensions) during different diel periods, spill conditions, powerhouse operations, and test configurations of the surface bypass structures (temporary spillway weirs; TSWs). One of the challenges in reporting three-dimensional results is presenting the information in a manner that allows interested parties to summarize the behavior of many fish over many different conditions across multiple years. To accomplish this, we investigated the feasibility of using a Markov chain analysis to characterize fish movement patterns in the forebay of McNary Dam. The Markov chain analysis is one way that can be used to summarize numerically the behavior of fish in the forebay. Numerically summarizing the behavior of juvenile salmonids in the forebay of McNary Dam using the Markov chain analysis allowed us to confirm what had been previously summarized using visualization software. For example, proportions of yearling and subyearling Chinook salmon passing the three powerhouse areas was often greater in the southern and middle areas, compared to the northern area. The opposite generally was observed for steelhead. Results of this analysis also allowed us to confirm and quantify the extent of milling behavior that had been observed for steelhead. For fish that were first detected in the powerhouse region, less than 0.10 of the steelhead, on average, passed within each of the powerhouse areas. Instead, steelhead transitioned to adjoining areas in the spillway before passing the dam. In comparison, greater than 0.20 of the Chinook salmon passed within the powerhouse areas. Less milling behavior was observed for all species for fish that first approached the spillway. Compared to the powerhouse areas, a higher proportion of fish, regardless of species, passed the spillway areas and fewer transitioned to adjoining areas in the powerhouse. In addition to quantifying what had been previously speculated about the behavior of fish in the forebay of McNary Dam, the Markov chain analysis refined our understanding of how fish behavior and passage can be influenced by changes to the operations and structure of McNary Dam. For example, the addition of TSWs to the spillway area clearly influenced the passage of fish. Previous results have been reported showing that TSWs increased the number of fish passing through non-turbine routes and the fish-track videos indicated, in general, how fish behaved before passing through the TSWs. However, the analysis presented in this report allowed us to better understand how fish moved across the face of the dam before passing the TSWs and provided a way to quantify the effect of TSW location. Installation of the TSWs in bays 22 and 20 clearly increased passage proportions through the southern one-third of the spillway area for all species, most significantly for steelhead. When the TSWs were moved to bays 19 and 20 in 2008, overall passage through the southern one-third of the spillway remained higher than 2006, but decreased from what was observed in 2007. Shifting the TSWs to the north decreased the proportion of fish passing through the TSWs and increased the number of fish that moved to adjoining areas before passing the dam. Perhaps the most interesting new information to come out of the two-step Markov chain analysis relates to how the performance of the TSWs was influenced by their proximity to the powerhouse. During 2007, the highest proportion of fish passing through TSW22 was for fish that transitioned from the powerhouse area. In contrast, a relatively low proportion of fish passed through TSW20 after coming from the powerhouse area. Instead, the proportion of fish that passed TSW20 after coming from the northern part of the spillway was twice as high as the proportion of fish that passed through TSW20 after coming from the powerhouse. During 2008, the TSW in bay 22 was moved to bay 19, leaving the TSW in bay 20 as the one closest to the powerhouse. As was the case when a TSW was located in bay 22; the proportion of fish passing TSW20 after coming from the powerhouse was greater than the proportion of fish passing through TSW20 after coming from the northern part of the spillway. Passage proportions for fish passing through TSW19, the farthest north of the two TSWs during 2008, was higher for fish that came from the northern part of the spillway compared to the proportion of fish that passed through TSW19 after coming from the powerhouse. The Markov chain analysis provided a mathematical way to characterize fish behavior in the forebay of McNary Dam and helped refine our understanding of how fish movements were influenced by operational and structural changes at McNary Dam. The Markov chain analysis also could be used to examine how future structural and operational changes proposed for McNary Dam might influence the passage of juvenile salmonids.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121119","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Adams, N.S., and Hatton, T., 2012, A Markov chain analysis of the movements of juvenile salmonids in the forebay of McNary Dam, Washington and Oregon, 2006-09: U.S. Geological Survey Open-File Report 2012-1119, viii, 68 p.; Appendices, https://doi.org/10.3133/ofr20121119.","productDescription":"viii, 68 p.; Appendices","temporalStart":"2006-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":257111,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1119.jpg"},{"id":257108,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1119/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon;Washington","otherGeospatial":"Mcnary Dam;Columbia River;Snake River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121,45.5 ], [ -121,48.25 ], [ -117.5,48.25 ], [ -117.5,45.5 ], [ -121,45.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd495be4b0b290850ef171","contributors":{"authors":[{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":464160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatton, Tyson W. 0000-0002-2874-0719","orcid":"https://orcid.org/0000-0002-2874-0719","contributorId":9112,"corporation":false,"usgs":true,"family":"Hatton","given":"Tyson W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":464161,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187335,"text":"70187335 - 2012 - Geophysical study of the San Juan Mountains batholith complex, southwestern Colorado","interactions":[],"lastModifiedDate":"2019-12-17T09:16:06","indexId":"70187335","displayToPublicDate":"2012-06-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical study of the San Juan Mountains batholith complex, southwestern Colorado","docAbstract":"One of the largest and most pronounced gravity lows over North America is over the rugged San Juan Mountains of southwestern Colorado (USA). The mountain range is coincident with the San Juan volcanic field (SJVF), the largest erosional remnant of a widespread mid-Cenozoic volcanic field that spanned much of the southern Rocky Mountains. A buried, low-density silicic batholith complex related to the volcanic field has been the accepted interpretation of the source of the gravity low since the 1970s. However, this interpretation was based on gravity data processed with standard techniques that are problematic in the SJVF region. The combination of high-relief topography, topography with low densities, and the use of a common reduction density of 2670 kg/m3produces spurious large-amplitude gravity lows that may distort the geophysical signature of deeper features such as a batholith complex. We applied an unconventional processing procedure that uses geologically appropriate densities for the uppermost crust and digital topography to mostly remove the effect of the low-density units that underlie the topography associated with the SJVF. This approach resulted in a gravity map that provides an improved representation of deeper sources, including reducing the amplitude of the anomaly attributed to a batholith complex. We also reinterpreted vintage seismic refraction data that indicate the presence of low-velocity zones under the SJVF. Assuming that the source of the gravity low on the improved gravity anomaly map is the same as the source of the low seismic velocities, integrated modeling corroborates the interpretation of a batholith complex and then defines the dimensions and overall density contrast of the complex. Models show that the thickness of the batholith complex varies laterally to a significant degree, with the greatest thickness (∼20 km) under the western SJVF, and lesser thicknesses (<10 km) under the eastern SJVF. The largest group of nested calderas on the surface of the SJVF, the central caldera cluster, is not correlated with the thickest part of the batholith complex. This result is consistent with petrologic interpretations from recent studies that the batholith complex continued to be modified after cessation of volcanism and therefore is not necessarily representative of synvolcanic magma chambers. The total volume of the batholith complex is estimated to be 82,000–130,000 km3. The formation of such a large felsic batholith complex would inevitably involve production of a considerably greater volume of residuum, which could be present in the lower crust or uppermost mantle. The interpreted vertically averaged density contrast (–60 to –110 kg/m3), density (2590–2640 kg/m3), and seismic expression of the batholith complex are consistent with results of geophysical studies of other large batholiths in the western United States.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES00723.1","usgsCitation":"Drenth, B.J., Keller, G.R., and Thompson, R.A., 2012, Geophysical study of the San Juan Mountains batholith complex, southwestern Colorado: Geosphere, v. 8, no. 3, p. 669-684, https://doi.org/10.1130/GES00723.1.","productDescription":"16 p.","startPage":"669","endPage":"684","ipdsId":"IP-026514","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":474496,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00723.1","text":"Publisher Index Page"},{"id":340695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"San Juan Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.05029296875,\n 36.99377838872517\n ],\n [\n -105.97412109375,\n 36.99377838872517\n ],\n [\n -105.97412109375,\n 38.48369476951686\n ],\n [\n -109.05029296875,\n 38.48369476951686\n ],\n [\n -109.05029296875,\n 36.99377838872517\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59084936e4b0fc4e448ffda2","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":693511,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keller, G. Randy","contributorId":40602,"corporation":false,"usgs":true,"family":"Keller","given":"G.","email":"","middleInitial":"Randy","affiliations":[],"preferred":false,"id":693513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Ren A. 0000-0002-3044-3043 rathomps@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":1265,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren","email":"rathomps@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693512,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037976,"text":"70037976 - 2012 - Modeling radium distribution in coastal aquifers during sea level changes: The Dead Sea case","interactions":[],"lastModifiedDate":"2012-06-06T01:01:36","indexId":"70037976","displayToPublicDate":"2012-05-31T12:13:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Modeling radium distribution in coastal aquifers during sea level changes: The Dead Sea case","docAbstract":"We present a new approach to studying the behavior of radium isotopes in a coastal aquifer. In order to simulate radium isotope distributions in the dynamic flow field of the Dead Sea aquifer, a multi-species density dependent flow model (SUTRA-MS) was used. Field data show that the activity of 226Ra decreases from 140 to 60 dpm/L upon entering the aquifer from the Dead Sea, and then further decreases linearly due to mixing with Ra-poor fresh water. On the other hand, an increase is observed in the activity of the shorter-lived isotopes (up to 52 dpm/L 224Ra and 31 dpm/L 223Ra), which are relatively low in Dead Sea water (up to 2.5 dpm/L 224Ra and 0.5 dpm/L 223Ra). The activities of the short lived radium isotopes also decrease with decreasing salinity, which is due to the effect of salinity on the adsorption of radium. The relationship between 224Ra and salinity suggests that the adsorption partition coefficient (K) is linearly related to salinity. Simulations of the steady-state conditions, show that the distance where equilibrium activity is attained for each radium isotope is affected by the isotope half-life, K and the groundwater velocity, resulting in a longer distance for the long-lived radium isotopes. K affects the radium distribution in transient conditions, especially that of the long-lived radium isotopes. The transient conditions in the Dead Sea system, with a 1 m/yr lake level drop, together with the radium field data, constrains K to be relatively low (<10). Thus, the sharp decrease in 226Ra cannot be explained by adsorption, and it is better explained by removal via coprecipitation, probably with barite or celestine.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochimica et Cosmochimica Acta","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.gca.2012.03.022","usgsCitation":"Kiro, Y., Yechieli, Y., Voss, C.I., Starinsky, A., and Weinstein, Y., 2012, Modeling radium distribution in coastal aquifers during sea level changes: The Dead Sea case: Geochimica et Cosmochimica Acta, v. 88, p. 237-254, https://doi.org/10.1016/j.gca.2012.03.022.","productDescription":"18 p.","startPage":"237","endPage":"254","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"links":[{"id":257213,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.gca.2012.03.022","linkFileType":{"id":5,"text":"html"}},{"id":257226,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Isreal","otherGeospatial":"Dead Sea","volume":"88","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5c20e4b0c8380cd6fa5f","contributors":{"authors":[{"text":"Kiro, Yael","contributorId":88996,"corporation":false,"usgs":true,"family":"Kiro","given":"Yael","email":"","affiliations":[],"preferred":false,"id":463191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yechieli, Yoseph","contributorId":95320,"corporation":false,"usgs":true,"family":"Yechieli","given":"Yoseph","email":"","affiliations":[],"preferred":false,"id":463192,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":463189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starinsky, Abraham","contributorId":98988,"corporation":false,"usgs":true,"family":"Starinsky","given":"Abraham","email":"","affiliations":[],"preferred":false,"id":463193,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weinstein, Yishai","contributorId":44404,"corporation":false,"usgs":true,"family":"Weinstein","given":"Yishai","email":"","affiliations":[],"preferred":false,"id":463190,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70007502,"text":"70007502 - 2012 - Microbial transformations of arsenic: Mobilization from glauconitic sediments to water","interactions":[],"lastModifiedDate":"2012-06-06T01:01:36","indexId":"70007502","displayToPublicDate":"2012-05-31T11:29:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Microbial transformations of arsenic: Mobilization from glauconitic sediments to water","docAbstract":"In the Inner Coastal Plain of New Jersey, arsenic (As) is released from glauconitic sediment to carbon- and nutrient-rich shallow groundwater. This As-rich groundwater discharges to a major area stream. We hypothesize that microbes play an active role in the mobilization of As from glauconitic subsurface sediments into groundwater in the Inner Coastal Plain of New Jersey. We have examined the potential impact of microbial activity on the mobilization of arsenic from subsurface sediments into the groundwater at a site on Crosswicks Creek in southern New Jersey. The As contents of sediments 33–90 cm below the streambed were found to range from 15 to 26.4 mg/kg, with siderite forming at depth. Groundwater beneath the streambed contains As at concentrations up to 89 μg/L. Microcosms developed from site sediments released 23 μg/L of As, and active microbial reduction of As(V) was observed in microcosms developed from site groundwater. DNA extracted from site sediments was amplified with primers for the 16S rRNA gene and the arsenate respiratory reductase gene, arrA, and indicated the presence of a diverse anaerobic microbial community, as well as the presence of potential arsenic-reducing bacteria. In addition, high iron (Fe) concentrations in groundwater and the presence of iron-reducing microbial genera suggests that Fe reduction in minerals may provide an additional mechanism for release of associated As, while arsenic-reducing microorganisms may serve to enhance the mobility of As in groundwater at this site.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.watres.2012.02.044","usgsCitation":"Mumford, A., Barringer, J., Benzel, W., Reilly, P.A., and Young, L., 2012, Microbial transformations of arsenic: Mobilization from glauconitic sediments to water: Water Research, v. 46, no. 9, p. 2859-2868, https://doi.org/10.1016/j.watres.2012.02.044.","productDescription":"10 p.","startPage":"2859","endPage":"2868","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":257221,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257210,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.watres.2012.02.044","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey","volume":"46","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5661e4b0c8380cd6d564","contributors":{"authors":[{"text":"Mumford, Adam C.","contributorId":27307,"corporation":false,"usgs":true,"family":"Mumford","given":"Adam C.","affiliations":[],"preferred":false,"id":356537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barringer, Julia L.","contributorId":59419,"corporation":false,"usgs":true,"family":"Barringer","given":"Julia L.","affiliations":[],"preferred":false,"id":356538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benzel, William 0000-0002-4085-1876 wbenzel@usgs.gov","orcid":"https://orcid.org/0000-0002-4085-1876","contributorId":3594,"corporation":false,"usgs":true,"family":"Benzel","given":"William","email":"wbenzel@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":356536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reilly, Pamela A. 0000-0002-2937-4490 jankowsk@usgs.gov","orcid":"https://orcid.org/0000-0002-2937-4490","contributorId":653,"corporation":false,"usgs":true,"family":"Reilly","given":"Pamela","email":"jankowsk@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, L.Y.","contributorId":76547,"corporation":false,"usgs":true,"family":"Young","given":"L.Y.","email":"","affiliations":[],"preferred":false,"id":356539,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037892,"text":"70037892 - 2012 - Metals in sediments and fish from Sea Lots and Point Lisas harbors, Trinidad and Tobago","interactions":[],"lastModifiedDate":"2017-05-24T12:26:53","indexId":"70037892","displayToPublicDate":"2012-05-31T10:49:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Metals in sediments and fish from Sea Lots and Point Lisas harbors, Trinidad and Tobago","docAbstract":"Concentrations of heavy metals were determined in nearshore marine sediments and fish tissue from Sea Lots area on the west coast, at Caroni Lagoon National Park, and in the Point Lisas harbor, Trinidad. The most dominant metals found in sediments were Al, Fe and Zn with mean concentrations highest at Sea Lots (Al-39420 μg/g; Fe-45640 μg/g; Zn-245 μg/g), when compared to sediments from Point Lisas (Al-11936 μg/g; Fe-30171 μg/g; Zn-69 μg/g) and Caroni (Al-0400 μg/g; Fe-19000 μg/g; Zn-32 μg/g), High concentration of Cu, Al, Fe and Zn were also detected in fish tissue from Point Lisas and Caroni. Metal concentrations in fish tissue showed significant correlation with sediment metals concentration, which suggests that tissue levels are influenced by sediment concentration. Of the metals, only Zn, Hg and Cu had a bioaccumulation factor (BAF) greater than one, which suggests a high bioaccumulation potential for these metals.
Using real-time PCR, we tested 15 wolf (Canis lupus) feces from the Superior National Forest (SNF), Minnesota, USA, and 191 from Yellowstone National Park (YNP), USA, collected during summer and 13 during winter for canine parvovirus (CPV)-2 DNA. We also tested 20 dog feces for CPV-2 DNA. The PCR assay was 100% sensitive and specific with a minimum detection threshold of 104 50% tissue culture infective dose. Virus was detected in two winter specimens but none of the summer specimens. We suggest applying the technique more broadly especially with winter feces.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/0090-3558-48.2.473","usgsCitation":"Mech, L.D., Almberg, E., Smith, D., Goyal, S., and Singer, R.S., 2012, Use of real-time PCR to detect canine parvovirus in feces of free-ranging wolves: Journal of Wildlife Diseases, v. 48, no. 2, p. 473-476, https://doi.org/10.7589/0090-3558-48.2.473.","productDescription":"4 p.","startPage":"473","endPage":"476","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474501,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/0090-3558-48.2.473","text":"Publisher Index Page"},{"id":381835,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wyoming","otherGeospatial":"Superior National Forest, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.615478515625,\n 48.04136507445029\n ],\n [\n -90.098876953125,\n 48.10743118848039\n ],\n [\n -90.87890625,\n 48.25394114463431\n ],\n [\n -91.571044921875,\n 48.05605376398125\n ],\n [\n -91.92260742187499,\n 48.22467264956519\n ],\n [\n -92.28515625,\n 48.31242790407178\n ],\n [\n -92.43896484375,\n 48.21735290928554\n ],\n [\n -92.197265625,\n 46.76244305208004\n ],\n [\n -89.56054687499999,\n 48.011975126709956\n ],\n [\n -89.615478515625,\n 48.04136507445029\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.07177734375,\n 43.46089378008257\n ],\n [\n -108.8525390625,\n 43.46089378008257\n ],\n [\n -108.8525390625,\n 45.00365115687186\n ],\n [\n -111.07177734375,\n 45.00365115687186\n ],\n [\n -111.07177734375,\n 43.46089378008257\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbf67e4b08c986b329b3a","contributors":{"authors":[{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":356861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Almberg, Emily S.","contributorId":101111,"corporation":false,"usgs":true,"family":"Almberg","given":"Emily S.","affiliations":[],"preferred":false,"id":356864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Douglas","contributorId":56088,"corporation":false,"usgs":true,"family":"Smith","given":"Douglas","email":"","affiliations":[],"preferred":false,"id":356863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goyal, Sagar","contributorId":28471,"corporation":false,"usgs":true,"family":"Goyal","given":"Sagar","affiliations":[],"preferred":false,"id":356862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singer, Randall S.","contributorId":106742,"corporation":false,"usgs":true,"family":"Singer","given":"Randall","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":356865,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70007202,"text":"70007202 - 2012 - Mapping socio-environmentally vulnerable populations access and exposure to ecosystem services at the U.S.-Mexico borderlands","interactions":[],"lastModifiedDate":"2012-06-06T01:01:36","indexId":"70007202","displayToPublicDate":"2012-05-31T09:59:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":836,"text":"Applied Geography","active":true,"publicationSubtype":{"id":10}},"title":"Mapping socio-environmentally vulnerable populations access and exposure to ecosystem services at the U.S.-Mexico borderlands","docAbstract":"Socio-environmental vulnerable populations are often unrepresented in land-use planning yet have great potential for loss when exposed to changes in ecosystem services. Administrative boundaries, cultural differences, and language barriers increase the disassociation between land-use management and marginalized populations living in the U.S.–Mexico borderlands. This paper describes the development of a Modified Socio-Environmental Vulnerability Index (M-SEVI), using determinants from binational census and neighborhood data that describe levels of education, access to resources, migratory status, housing, and number of dependents, to provide a simplified snapshot of the region's populace that can be used in binational planning efforts. We apply this index at the SCW, located on the border between Arizona, USA and Sonora, Mexico. For comparison, the Soil and Water Assessment Tool is concurrently applied to assess the provision of erosion- and flood control services over a 9-year period. We describe how this coupling of data can form the base for an ecosystem services assessment across political boundaries that can be used by land-use planners. Results reveal potential disparities in environmental risks and burdens throughout the binational watershed in residential districts surrounding and between urban centers. The M-SEVI can be used as an important first step in addressing environmental justice for binational decision-making.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.apgeog.2012.01.006","usgsCitation":"Norman, L.M., Villarreal, M., Lara-Valencia, F., Yuan, Y., Nie, W., Wilson, S., Amaya, G., and Sleeter, R., 2012, Mapping socio-environmentally vulnerable populations access and exposure to ecosystem services at the U.S.-Mexico borderlands: Applied Geography, v. 34, p. 413-424, https://doi.org/10.1016/j.apgeog.2012.01.006.","productDescription":"12 p.","startPage":"413","endPage":"424","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":257198,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.apgeog.2012.01.006","linkFileType":{"id":5,"text":"html"}},{"id":257224,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States;Mexico","state":"Arizona","otherGeospatial":"Sonora","volume":"34","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5074e4b0c8380cd6b6ce","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":356052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L.","contributorId":107012,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel L.","affiliations":[],"preferred":false,"id":356058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lara-Valencia, Francisco","contributorId":77409,"corporation":false,"usgs":true,"family":"Lara-Valencia","given":"Francisco","email":"","affiliations":[],"preferred":false,"id":356055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yuan, Yongping","contributorId":75799,"corporation":false,"usgs":true,"family":"Yuan","given":"Yongping","email":"","affiliations":[],"preferred":false,"id":356054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nie, Wenming","contributorId":7126,"corporation":false,"usgs":true,"family":"Nie","given":"Wenming","email":"","affiliations":[],"preferred":false,"id":356053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, Sylvia","contributorId":105160,"corporation":false,"usgs":true,"family":"Wilson","given":"Sylvia","email":"","affiliations":[],"preferred":false,"id":356057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amaya, Gladys","contributorId":86212,"corporation":false,"usgs":true,"family":"Amaya","given":"Gladys","email":"","affiliations":[],"preferred":false,"id":356056,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sleeter, Rachel 0000-0003-3477-0436 rsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-0436","contributorId":666,"corporation":false,"usgs":true,"family":"Sleeter","given":"Rachel","email":"rsleeter@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":356051,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70005708,"text":"70005708 - 2012 - Preferential flow occurs in unsaturated conditions","interactions":[],"lastModifiedDate":"2012-06-01T01:01:40","indexId":"70005708","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Preferential flow occurs in unsaturated conditions","docAbstract":"Because it commonly generates high-speed, high-volume flow with minimal exposure to solid earth materials, preferential flow in the unsaturated zone is a dominant influence in many problems of infiltration, recharge, contaminant transport, and ecohydrology. By definition, preferential flow occurs in a portion of a medium – that is, a preferred part, whether a pathway, pore, or macroscopic subvolume. There are many possible classification schemes, but usual consideration of preferential flow includes macropore or fracture flow, funneled flow determined by macroscale heterogeneities, and fingered flow determined by hydraulic instability rather than intrinsic heterogeneity. That preferential flow is spatially concentrated associates it with other characteristics that are typical, although not defining: it tends to be unusually fast, to transport high fluxes, and to occur with hydraulic disequilibrium within the medium. It also has a tendency to occur in association with large conduits and high water content, although these are less universal than is commonly assumed. Predictive unsaturated-zone flow models in common use employ several different criteria for when and where preferential flow occurs, almost always requiring a nearly saturated medium. A threshold to be exceeded may be specified in terms of the following (i) water content; (ii) matric potential, typically a value high enough to cause capillary filling in a macropore of minimum size; (iii) infiltration capacity or other indication of incipient surface ponding; or (iv) other conditions related to total filling of certain pores. Yet preferential flow does occur without meeting these criteria. My purpose in this commentary is to point out important exceptions and implications of ignoring them. Some of these pertain mainly to macropore flow, others to fingered or funneled flow, and others to combined or undifferentiated flow modes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrological Processes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/hyp.8380","usgsCitation":"Nimmo, J.R., 2012, Preferential flow occurs in unsaturated conditions: Hydrological Processes, v. 26, no. 5, p. 786-789, https://doi.org/10.1002/hyp.8380.","productDescription":"4 p.","startPage":"786","endPage":"789","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"links":[{"id":257090,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257084,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/hyp.8380","linkFileType":{"id":5,"text":"html"}}],"volume":"26","issue":"5","noUsgsAuthors":false,"publicationDate":"2011-12-12","publicationStatus":"PW","scienceBaseUri":"505a821fe4b0c8380cd7b905","contributors":{"authors":[{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":353098,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70037871,"text":"70037871 - 2012 - Deposition and accumulation of airborne organic contaminants in Yosemite National Park, Calfornia","interactions":[],"lastModifiedDate":"2020-12-29T20:08:57.691715","indexId":"70037871","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Deposition and accumulation of airborne organic contaminants in Yosemite National Park, Calfornia","docAbstract":"Deposition and accumulation of airborne organic contaminants in Yosemite National Park were examined by sampling atmospheric deposition, lichen, zooplankton, and lake sediment at different elevations. Passive samplers were deployed in high‐elevation lakes to estimate surface‐water concentrations. Detected compounds included current‐use pesticides chlorpyrifos, dacthal, and endosulfans and legacy compounds chlordane, dichlorodiphenyltrichloroethane‐related compounds, dieldrin, hexachlorobenzene, and polychlorinated biphenyls. Concentrations in snow were similar among sites and showed little variation with elevation. Endosulfan concentrations in summer rain appeared to coincide with application rates in the San Joaquin Valley. More than 70% of annual pesticide inputs from atmospheric deposition occurred during the winter, largely because most precipitation falls as snow. Endosulfan and chlordane concentrations in lichen increased with elevation, indicating that mountain cold‐trapping might be an important control on accumulation of these compounds. By contrast, chlorpyrifos concentrations were inversely correlated with elevation, indicating that distance from source areas was the dominant control. Sediment concentrations were inversely correlated with elevation, possibly because of the organic carbon content of sediments but also perhaps the greater mobility of organic contaminants at lower elevations. Surface‐water concentrations inferred from passive samplers were at sub–parts‐per‐trillion concentrations, indicating minimal exposure to aquatic organisms from the water column. Concentrations in sediment generally were low, except for dichlorodiphenyldichloroethane in Tenaya Lake, which exceeded sediment guidelines for protection of benthic organisms.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.1727","usgsCitation":"Mast, A.M., Alvarez, D., and Zaugg, S.D., 2012, Deposition and accumulation of airborne organic contaminants in Yosemite National Park, Calfornia: Environmental Toxicology and Chemistry, v. 31, no. 3, p. 524-533, https://doi.org/10.1002/etc.1727.","productDescription":"10 p.","startPage":"524","endPage":"533","temporalStart":"2008-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"links":[{"id":381742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite Naitonal Park;Sequoia National Park;Kings Canyon National Park;San Joaquin Valley;Sierra Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122,35.5 ], [ -122,38.5 ], [ -118,38.5 ], [ -118,35.5 ], [ -122,35.5 ] ] ] } } ] }","volume":"31","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-12-21","publicationStatus":"PW","scienceBaseUri":"5059feb5e4b0c8380cd4eea2","contributors":{"authors":[{"text":"Mast, Alisa M.","contributorId":88598,"corporation":false,"usgs":true,"family":"Mast","given":"Alisa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":462922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alvarez, David A.","contributorId":72755,"corporation":false,"usgs":true,"family":"Alvarez","given":"David A.","affiliations":[],"preferred":false,"id":462921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zaugg, Steven D. sdzaugg@usgs.gov","contributorId":768,"corporation":false,"usgs":true,"family":"Zaugg","given":"Steven","email":"sdzaugg@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":462920,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70003329,"text":"70003329 - 2012 - Development and evaluation of a boat-mounted RFID antenna for monitoring freshwater mussels","interactions":[],"lastModifiedDate":"2012-06-01T01:01:40","indexId":"70003329","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Development and evaluation of a boat-mounted RFID antenna for monitoring freshwater mussels","docAbstract":"Development of radio frequency identification (RFID) technology and passive integrated transponder (PIT) tags has substantially increased the ability of researchers and managers to monitor populations of aquatic organisms. However, use of transportable RFID antenna systems (i.e., backpack-mounted) is currently limited to wadeable aquatic environments (<1.4 m water depth). We describe the design, construction, and evaluation of a boat-mounted RFID antenna to detect individually PIT-tagged benthic aquatic organisms (mussels). We evaluated the effects of tag orientation on detection distances in water with a 32-mm half-duplex PIT tag. Detection distances up to 50 cm from the antenna coils were obtained, but detection distance was dependent on tag orientation. We also evaluated detection distance of PIT tags beneath the sediment to simulate detection of burrowing mussels with 23- and 32-mm tags. In sand substrate, the maximum detection distance varied from 3.5 cm and 4.5 cm (vertical tag orientation) to 24.7 cm and 39.4 cm (45° tag orientation) for the 23- and 32-mm PIT tags, respectively. Our results suggest a 1.4-m total detection width for tagged mussels on the substrate surface by the boat-mounted antenna system regardless of tag orientation. However, burrowed mussels may require multiple passes to increase detection that would be influenced by depth, tag orientation, and tag size. Construction of the boat-mounted antenna was relatively low in cost (<500 USD) and had several advantages (less labor and time intensive, increased safety) over traditional mussel sampling techniques (diving, snorkeling) in nonwadeable habitats.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Society for Freshwater Science","publisherLocation":"http://www.freshwater-science.org/","doi":"10.1899/11-045.1","usgsCitation":"Fischer, J., Neebling, T.E., and Quist, M.C., 2012, Development and evaluation of a boat-mounted RFID antenna for monitoring freshwater mussels: Freshwater Science, v. 31, no. 1, p. 148-153, https://doi.org/10.1899/11-045.1.","productDescription":"6 p.","startPage":"148","endPage":"153","costCenters":[{"id":342,"text":"Idaho Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":257089,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257088,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1899/11-045.1"}],"volume":"31","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a001fe4b0c8380cd4f5d1","contributors":{"authors":[{"text":"Fischer, Jesse R.","contributorId":86618,"corporation":false,"usgs":true,"family":"Fischer","given":"Jesse R.","affiliations":[],"preferred":false,"id":346910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neebling, Travis E.","contributorId":76175,"corporation":false,"usgs":true,"family":"Neebling","given":"Travis","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":346909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quist, Michael C. mquist@usgs.gov","contributorId":4042,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":350,"text":"Iowa Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":346908,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038437,"text":"ofr20121082 - 2012 - Assessment of soil-gas contamination at three former fuel-dispensing sites, Fort Gordon, Georgia, 2010—2011","interactions":[],"lastModifiedDate":"2012-06-01T01:01:41","indexId":"ofr20121082","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1082","title":"Assessment of soil-gas contamination at three former fuel-dispensing sites, Fort Gordon, Georgia, 2010—2011","docAbstract":"Soil gas was assessed for contaminants at three former fuel-dispensing sites at Fort Gordon, Georgia, from October 2010 to September 2011. The assessment included delineation of organic contaminants using soil-gas samplers collected from the former fuel-dispensing sites at 8th Street, Chamberlain Avenue, and 12th Street. This assessment was conducted to provide environmental contamination data to Fort Gordon personnel pursuant to requirements for the Resource Conservation and Recovery Act Part B Hazardous Waste Permit process. Soil-gas samplers installed and retrieved during June and August 2011 at the 8th Street site had detections above the method detection level (MDL) for the mass of total petroleum hydrocarbons (TPH), benzene, toluene, ortho-xylene, undecane, tridecane, pentadecane, and chloroform. Total petroleum hydrocarbons soil-gas mass exceeded the MDL of 0.02 microgram in 54 of the 55 soil-gas samplers. The highest detection of TPH soil-gas mass was 146.10 micrograms, located in the central part of the site. Benzene mass exceeded the MDL of 0.01 microgram in 23 soil-gas samplers, whereas toluene was detected in only 10 soil-gas samplers. Ortho-xylene was detected above the MDL in only one soil-gas sampler. The highest soil-gas mass detected for undecane, tridecane, and pentadecane was located in the northeastern corner of the 8th Street site. Chloroform mass greater than the MDL of 0.01 microgram was detected in less than one-third of the soil-gas samplers. Soil-gas masses above the MDL were identified for TPH, gasoline-related compounds, diesel-range alkanes, trimethylbenzenes, naphthalene, 2-methyl-napthalene, octane, and tetrachloroethylene for the July 2011 soil-gas survey at the Chamberlain Avenue site. All 30 of the soil-gas samplers contained TPH mass above the MDL. The highest detection of TPH mass, 426.36 micrograms, was for a soil-gas sampler located near the northern boundary of the site. Gasoline-related compounds and diesel-range alkanes were detected in multiple soil-gas samplers, and the highest detections of these compounds were located near the central part of the site near existing, nonoperational, fuel-dispensing pumps. Trimethylbenzenes were detected in less than half of the soil-gas samplers. Naphthalene soil-gas mass was detected above the MDL in 10 soil-gas samplers, whereas 2-methyl-napthalene was detected above the MDL in half of the soil-gas samplers. Octane mass was detected above the MDL in one soil-gas sampler located near the central part of the site. Tetrachloroethylene soil-gas mass was detected above the MDL in more than half of the soil-gas samplers, and the highest tetrachloroethylene soil-gas mass of 0.90 microgram was located in the northeastern part of the site. Soil-gas samplers collected at the 12th Street site during July 2011 contained soil-gas mass above the MDL for TPH, toluene, undecane, tridecane, and pentadecane (diesel-range alkanes), trichloroethylene, 1,4-dichlorobenzene, chloroform, and 1,2,4-trimethylbenzene. The highest detected TPH mass was 24.37 micrograms in a soil-gas sampler located in the northern part of the site. The highest detection of toluene soil-gas mass was from a soil-gas sampler located near the southern boundary of the site. The diesel-range alkanes were detected above the MDL in five soil-gas samplers; the highest detection of soil-gas diesel mass, 0.65 microgram, was located in the southern part of the site. Trichloroethylene and 1,4-dichlorobenzene were detected above the MDL in the northern part of the site in one soil-gas sampler that also had one of the highest detections of TPH. Chloroform was detected above the MDL in three soil-gas samplers, whereas 1,2,4-trimethylbenzene soil-gas mass was detected above the MDL in two soil-gas samplers.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121082","collaboration":"Prepared in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon","usgsCitation":"Caldwell, A.W., Falls, W.F., Guimaraes, W.B., Ratliff, W.H., Wellborn, J.B., and Landmeyer, J., 2012, Assessment of soil-gas contamination at three former fuel-dispensing sites, Fort Gordon, Georgia, 2010—2011: U.S. Geological Survey Open-File Report 2012-1082, v, 7 p.; Figures; Tables, https://doi.org/10.3133/ofr20121082.","productDescription":"v, 7 p.; Figures; Tables","startPage":"i","endPage":"37","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-10-01","temporalEnd":"2011-09-30","costCenters":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":257053,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1082.jpg"},{"id":257044,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1082/pdf/2012-1082.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":257043,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1082/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Georgia","otherGeospatial":"Fort Gordon","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ee59e4b0c8380cd49cf5","contributors":{"authors":[{"text":"Caldwell, Andral W. 0000-0003-1269-5463 acaldwel@usgs.gov","orcid":"https://orcid.org/0000-0003-1269-5463","contributorId":3228,"corporation":false,"usgs":true,"family":"Caldwell","given":"Andral","email":"acaldwel@usgs.gov","middleInitial":"W.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falls, W. Fred 0000-0003-2928-9795 wffalls@usgs.gov","orcid":"https://orcid.org/0000-0003-2928-9795","contributorId":107754,"corporation":false,"usgs":true,"family":"Falls","given":"W.","email":"wffalls@usgs.gov","middleInitial":"Fred","affiliations":[],"preferred":false,"id":464135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guimaraes, Wladmir B. wbguimar@usgs.gov","contributorId":3818,"corporation":false,"usgs":true,"family":"Guimaraes","given":"Wladmir","email":"wbguimar@usgs.gov","middleInitial":"B.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ratliff, W. Hagan","contributorId":60347,"corporation":false,"usgs":true,"family":"Ratliff","given":"W.","email":"","middleInitial":"Hagan","affiliations":[],"preferred":false,"id":464134,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wellborn, John B.","contributorId":24822,"corporation":false,"usgs":true,"family":"Wellborn","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":464133,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Landmeyer, James 0000-0002-5640-3816 jlandmey@usgs.gov","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":3257,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James","email":"jlandmey@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464131,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70038440,"text":"sir20125091 - 2012 - Reconnaissance of land-use sources of pesticides in drinking water, McKenzie River, Oregon","interactions":[],"lastModifiedDate":"2012-06-05T01:01:48","indexId":"sir20125091","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5091","title":"Reconnaissance of land-use sources of pesticides in drinking water, McKenzie River, Oregon","docAbstract":"The Eugene Water and Electric Board (EWEB) provides water and electricity to the City of Eugene, Oregon, from the McKenzie River. In the spring of 2002, EWEB initiated a pesticide monitoring program in cooperation with the U.S. Geological Survey as part of their Drinking Water Source Protection Plan. Approximately twice yearly pesticide samples were collected from 2002 to 2010 at a suite of sampling sites representing varying land uses in the lower McKenzie River basin. A total of 117 ambient samples were collected from 28 tributary and mainstem sites, including those dominated by forestry, urban, and agricultural activities, as well as the mouths of major tributaries characterized by a mixture of upstream land use. Constituents tested included 175 compounds in filtered water (72 herbicides, 43 insecticides, 10 fungicides, and 36 of their degradation products, as well as 14 pharmaceutical compounds). No attempt was made to sample different site types equivalently; sampling was instead designed primarily to characterize representative storm events during spring and fall runoff conditions in order to assess or confirm the perceived importance of the different site types as sources for pesticides. Sampling was especially limited for agricultural sites, which were only sampled during two spring storm surveys. A total of 43 compounds were detected at least once, with many of these detected only at low concentrations (<0.1 micrograms per liter). Nine compounds were detected at the drinking- water intake, and most of these were reported as estimates less than the laboratory reporting level. Human-health benchmark concentrations were consistently several orders of magnitude higher than detected concentrations at the intake, indicating that pesticide concentrations present a negligible threat to human health. The largest number of pesticide detections occurred during spring storm surveys and primarily were associated with urban stormwater drains. Urban sites also were associated with the highest concentrations, occasionally exceeding 1 microgram per liter. Many of the compounds detected at urban sites were relatively hydrophobic (do not mix easily with water), persistent, and suspected of endocrine disruption. In contrast, forestry compounds were rarely detectable in the McKenzie River, even though forest land predominates in the basin and forestry pesticide use was detected in small tributaries draining forested lands following application. Agricultural pesticide runoff was not well characterized by the limited data available, although a large number of compounds was estimated to be used in the basin and concentrations were moderately high in the few samples collected from small tributaries draining agricultural lands. Results from this analysis indicate that urban pesticide use is potentially an important source for pesticides of concern for drinking water, not limited exclusively to storm conditions. Forestry pesticide use is not considered a likely threat to drinking water quality at the present time (2012). A more complete understanding of agricultural chemicals in runoff in the McKenzie River basin requires further investigation. In addition to evaluating the data collected in this study, a conceptual model describing pesticide contamination in the McKenzie River basin is provided, based on current scientific understanding that is consistent with the data analysis presented in this report. This model is intended to provide a foundation for future monitoring in the basin.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125091","collaboration":"Prepared in cooperation with Eugene Water and Electric Board","usgsCitation":"Kelly, V.J., Anderson, C., and Morgenstern, K., 2012, Reconnaissance of land-use sources of pesticides in drinking water, McKenzie River, Oregon: U.S. Geological Survey Scientific Investigations Report 2012-5091, vi, 38 p.; Appendices; PDF Download of Appendix B, https://doi.org/10.3133/sir20125091.","productDescription":"vi, 38 p.; Appendices; PDF Download of Appendix B","startPage":"i","endPage":"46","numberOfPages":"52","additionalOnlineFiles":"N","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":257054,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5091.jpg"},{"id":257049,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5091/","linkFileType":{"id":5,"text":"html"}},{"id":257050,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5091/pdf/sir20125091.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon","otherGeospatial":"Mckenzie River Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a98ade4b0c8380cd82b45","contributors":{"authors":[{"text":"Kelly, Valerie J. vjkelly@usgs.gov","contributorId":4161,"corporation":false,"usgs":true,"family":"Kelly","given":"Valerie","email":"vjkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":1151,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey W.","email":"chauncey@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":464141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morgenstern, Karl","contributorId":57716,"corporation":false,"usgs":true,"family":"Morgenstern","given":"Karl","email":"","affiliations":[],"preferred":false,"id":464143,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038439,"text":"sir20125070 - 2012 - Representation of regional urban development conditions using a watershed-based gradient study design","interactions":[],"lastModifiedDate":"2018-04-02T16:30:50","indexId":"sir20125070","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5070","title":"Representation of regional urban development conditions using a watershed-based gradient study design","docAbstract":"As part of the U.S. Geological Survey National Water-Quality Assessment Program, the effects of urbanization on stream ecosystems (EUSE) have been intensively investigated in nine metropolitan areas in the United States, including Boston, Massachusetts; Atlanta, Georgia; Birmingham, Alabama; Raleigh, North Carolina; Salt Lake City, Utah; Denver, Colorado; Dallas–Fort Worth, Texas; Portland, Oregon; and Milwaukee–Green Bay, Wisconsin. Each of the EUSE study area watersheds was associated with one ecological region of the United States. This report evaluates whether each metropolitan area can be generalized across the ecological regions (ecoregions) within which the EUSE study watersheds are located. Seven characteristics of the EUSE watersheds that affect stream ecosystems were examined to determine the similarities in the same seven characteristics of the watersheds in the entire ecoregion. Land cover (percentage developed, forest and shrubland, and herbaceous and cultivated classes), average annual temperature, average annual precipitation, average surface elevation, and average percentage slope were selected as human-influenced, climate, and topography characteristics. Three findings emerged from this comparison that have implications for the use of EUSE data in models used to predict stream ecosystem condition. One is that the predominant or \"background\" land-cover type (either forested or agricultural land) in each ecoregion also is the predominant land-cover type within the associated EUSE study watersheds. The second finding is that in all EUSE study areas, the watersheds account for the range of developed land conditions that exist in the corresponding ecoregion watersheds. However, six of the nine EUSE study area watersheds have significantly different distributions of developed land from the ecoregion watersheds. Finally, in seven of the nine EUSE/ecoregion comparisons, the distributions of the values of climate variables in the EUSE watersheds are different from the distributions for watersheds in the corresponding ecoregions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125070","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Terziotti, S., McMahon, G., and Bell, A.H., 2012, Representation of regional urban development conditions using a watershed-based gradient study design: U.S. Geological Survey Scientific Investigations Report 2012-5070, viii, 91 p.; Appendix, https://doi.org/10.3133/sir20125070.","productDescription":"viii, 91 p.; Appendix","startPage":"i","endPage":"109","numberOfPages":"117","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":13634,"text":"South Atlantic Water Science 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In this study, we defined an objective threshold for alteration for Oklahoma streams using a combination of the expected range of 27 flow indices and a discriminant analysis to predict flow regime group. We found that fish functional groups in reference flow conditions had species that were more intolerant to flow alterations and preferences for stream habitat and faster flowing water. In contrast, altered sites had more tolerant species that preferred lentic habitat and slower water velocity. Ordination graphs of the presence and functional groups of species revealed an underlying geographical pattern roughly conforming to ecoregions, although there was separation between reference and altered sites within the larger geographical framework. Additionally, we found that reservoir construction and operation significantly altered fish assemblages in two different systems, Bird Creek in central Oklahoma and the Kiamichi River in southeastern Oklahoma. The Bird Creek flow regime shifted from a historically intermittent stream to one with stable perennial flows, and changes in fish assemblage structure covaried with changes in all five components of the flow regime. In contrast, the Kiamichi River flow regime did not change significantly for most flow components despite shifts in fish assemblage structure; however, most of the species associated with shifts in assemblage structure in the Kiamichi River system were characteristic of lentic environments and were likely related more to proximity of reservoirs in the drainage system than changes in flow. The spatial patterns in fish assemblage response to flow alteration, combined with different temporal responses of hydrology and fish assemblage structure at sites downstream of reservoirs, indicate that interactions between flow regime and aquatic biota vary depending on ecological setting. This supports the notion that regional variation in natural flow regimes could affect the development of flow recommendations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70038444","usgsCitation":"Fisher, W.L., Seilheimer, T.S., and Taylor, J.M., 2012, Biological assessment of environmental flows for Oklahoma: U.S. Geological Survey Open-File Report 2012-1114, vi, 18 p.; Figures; Tables; Appendix, https://doi.org/10.3133/70038444.","productDescription":"vi, 18 p.; Figures; Tables; Appendix","startPage":"i","endPage":"43","numberOfPages":"49","additionalOnlineFiles":"N","costCenters":[{"id":473,"text":"New York Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":257071,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1114.gif"},{"id":257068,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1114/","linkFileType":{"id":5,"text":"html"}},{"id":257069,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1114/pdf/ofr2012-1114_report_508.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oklahoma","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f163e4b0c8380cd4ac29","contributors":{"authors":[{"text":"Fisher, William L. wfisher@usgs.gov","contributorId":1229,"corporation":false,"usgs":true,"family":"Fisher","given":"William","email":"wfisher@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":464154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seilheimer, Titus S.","contributorId":50772,"corporation":false,"usgs":true,"family":"Seilheimer","given":"Titus","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":464155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Jason M.","contributorId":100678,"corporation":false,"usgs":true,"family":"Taylor","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":464156,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038438,"text":"sir20125035 - 2012 - Invertebrate response to changes in streamflow hydraulics in two urban areas in the United States","interactions":[],"lastModifiedDate":"2012-06-01T01:01:40","indexId":"sir20125035","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5035","title":"Invertebrate response to changes in streamflow hydraulics in two urban areas in the United States","docAbstract":"Stream hydrology is foundational to aquatic ecosystems and has been shown to be a structuring element for fish and invertebrates. The relations among urbanization, hydraulics, and invertebrate communities were investigated by the U.S. Geological Survey, National Water-Quality Assessment Program by using measures of stream hydraulics in two areas of the United States. Specifically, the hypothesis that the effects of urbanization on streamflow and aquatic biota are transferable across geographic regions was tested. Data from sites in Raleigh, North Carolina, and Milwaukee–Green Bay, Wisconsin, were compared and indicate that increasing urbanization has an effect on hydraulic characteristics (Reynolds number, shear stress, and stream power for example) in each metropolitan area, though limited commonality of significant correlations was noted between areas. Correspondence of significant correlations between invertebrate and hydraulic metrics between study areas also was limited. The links between urbanization, hydraulics, and invertebrates could be seen only in the Raleigh data. Connections among these three elements in the Milwaukee–Green Bay data were not clear and likely were obscured by antecedent land cover. Observed biotic differences due to hydrology and urbanization characteristics are not similar between geographic regions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125035","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Knight, R., and Cuffney, T.F., 2012, Invertebrate response to changes in streamflow hydraulics in two urban areas in the United States: U.S. Geological Survey Scientific Investigations Report 2012-5035, vi, 19 p., https://doi.org/10.3133/sir20125035.","productDescription":"vi, 19 p.","startPage":"i","endPage":"19","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":257056,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5035.jpg"},{"id":257045,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5035/","linkFileType":{"id":5,"text":"html"}},{"id":257046,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5035/pdf/2012-5035.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3e60e4b0c8380cd63d16","contributors":{"authors":[{"text":"Knight, Rodney R. rrknight@usgs.gov","contributorId":2272,"corporation":false,"usgs":true,"family":"Knight","given":"Rodney R.","email":"rrknight@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":false,"id":464137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cuffney, Thomas F. 0000-0003-1164-5560 tcuffney@usgs.gov","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":517,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"tcuffney@usgs.gov","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464136,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70038435,"text":"ofr20121109 - 2012 - Introduction to geospatial semantics and technology workshop handbook","interactions":[],"lastModifiedDate":"2012-06-01T01:01:40","indexId":"ofr20121109","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1109","title":"Introduction to geospatial semantics and technology workshop handbook","docAbstract":"The workshop is a tutorial on introductory geospatial semantics with hands-on exercises using standard Web browsers. The workshop is divided into two sections, general semantics on the Web and specific examples of geospatial semantics using data from The National Map of the U.S. Geological Survey and the Open Ontology Repository. The general semantics section includes information and access to publicly available semantic archives. The specific session includes information on geospatial semantics with access to semantically enhanced data for hydrography, transportation, boundaries, and names. The Open Ontology Repository offers open-source ontologies for public use.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121109","usgsCitation":"Varanka, D.E., 2012, Introduction to geospatial semantics and technology workshop handbook: U.S. Geological Survey Open-File Report 2012-1109, iii, 107 p., https://doi.org/10.3133/ofr20121109.","productDescription":"iii, 107 p.","startPage":"i","endPage":"107","numberOfPages":"110","costCenters":[{"id":161,"text":"Center of Excellence for Geospatial Information Science (CEGIS)","active":false,"usgs":true}],"links":[{"id":257055,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1109.gif"},{"id":257040,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1109/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3dece4b0c8380cd6395d","contributors":{"authors":[{"text":"Varanka, Dalia E. 0000-0003-2857-9600 dvaranka@usgs.gov","orcid":"https://orcid.org/0000-0003-2857-9600","contributorId":1296,"corporation":false,"usgs":true,"family":"Varanka","given":"Dalia","email":"dvaranka@usgs.gov","middleInitial":"E.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":464128,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70038445,"text":"ofr20121108 - 2012 - Monitoring of stream restoration habitat on the main stem of the Methow River, Washington, during the pre-treatment phase (October 2008-May 2012) with a progress report for activities from March 2011 to November 2011","interactions":[],"lastModifiedDate":"2016-05-04T12:00:42","indexId":"ofr20121108","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1108","title":"Monitoring of stream restoration habitat on the main stem of the Methow River, Washington, during the pre-treatment phase (October 2008-May 2012) with a progress report for activities from March 2011 to November 2011","docAbstract":"