The Great Lakes strain of viral haemorrhagic septicaemia virus IVb (VHSV-IVb) is capable of infecting a wide number of naive species and has been associated with large fish kills in the Midwestern United States since its discovery in 2005. The yellow perch, Perca flavescens (Mitchill), a freshwater species commonly found throughout inland waters of the United States and prized for its high value in sport and commercial fisheries, is a species documented in several fish kills affiliated with VHS. In the present study, differences in survival after infection with VHSV IVb were observed among juvenile fish from three yellow perch broodstocks that were originally derived from distinct wild populations, suggesting innate differences in susceptibility due to genetic variance. While all three stocks were susceptible upon waterborne exposure to VHS virus infection, fish derived from the Midwest (Lake Winnebago, WI) showed significantly lower cumulative % survival compared with two perch stocks derived from the East Coast (Perquimans River, NC and Choptank River, MD) of the United States. However, despite differences in apparent susceptibility, clinical signs did not vary between stocks and included moderate-to-severe haemorrhages at the pelvic and pectoral fin bases and exophthalmia. After the 28-day challenge was complete, VHS virus was analysed in subsets of whole fish that had either survived or succumbed to the infection using both plaque assay and quantitative PCR methodologies. A direct correlation was identified between the two methods, suggesting the potential for both methods to be used to detect virus in a research setting.
","language":"English","publisher":"Blackwell Science","doi":"10.1111/jfd.12068","usgsCitation":"Olson, W., Emmenegger, E., Glenn, J., Winton, J., and Goetz, F., 2013, Comparative susceptibility among three stocks of yellow perch, Perca flavescens (Mitchill), to viral haemorrhagic septicaemia virus strain IVb from the Great Lakes: Journal of Fish Diseases, v. 36, no. 8, p. 711-719, https://doi.org/10.1111/jfd.12068.","productDescription":"9 p.","startPage":"711","endPage":"719","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042613","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":271432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.11,41.4 ], [ -92.11,48.85 ], [ -76.3,48.85 ], [ -76.3,41.4 ], [ -92.11,41.4 ] ] ] } } ] }","volume":"36","issue":"8","noUsgsAuthors":false,"publicationDate":"2013-01-11","publicationStatus":"PW","scienceBaseUri":"5178f0dbe4b0d842c705f6a4","contributors":{"authors":[{"text":"Olson, W.","contributorId":95357,"corporation":false,"usgs":true,"family":"Olson","given":"W.","email":"","affiliations":[],"preferred":false,"id":477922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Emmenegger, E.","contributorId":34324,"corporation":false,"usgs":true,"family":"Emmenegger","given":"E.","email":"","affiliations":[],"preferred":false,"id":477919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, J.","contributorId":71086,"corporation":false,"usgs":true,"family":"Glenn","given":"J.","email":"","affiliations":[],"preferred":false,"id":477921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winton, J.","contributorId":55627,"corporation":false,"usgs":true,"family":"Winton","given":"J.","email":"","affiliations":[],"preferred":false,"id":477920,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goetz, F.","contributorId":33203,"corporation":false,"usgs":true,"family":"Goetz","given":"F.","email":"","affiliations":[],"preferred":false,"id":477918,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045552,"text":"sir20135044 - 2013 - Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011","interactions":[],"lastModifiedDate":"2015-10-16T13:47:34","indexId":"sir20135044","displayToPublicDate":"2013-04-23T00:00:00","publicationYear":"2013","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":"2013-5044","title":"Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011","docAbstract":"The U.S. Geological Survey, in cooperation with the White Bear Lake Conservation District, the Minnesota Pollution Control Agency, the Minnesota Department of Natural Resources, and other State, county, municipal, and regional planning agencies, watershed organizations, and private organizations, conducted a study to characterize groundwater and surface-water interactions near White Bear Lake through 2011. During 2010 and 2011, White Bear Lake and other lakes in the northeastern part of the Twin Cities Metropolitan Area were at historically low levels. Previous periods of lower water levels in White Bear Lake correlate with periods of lower precipitation; however, recent urban expansion and increased pumping from the Prairie du Chien-Jordan aquifer have raised the question of whether a decline in precipitation is the primary cause for the recent water-level decline in White Bear Lake. Understanding and quantifying the amount of groundwater inflow to a lake and water discharge from a lake to aquifers is commonly difficult but is important in the management of lake levels. Three methods were used in the study to assess groundwater and surface-water interactions on White Bear Lake: (1) a historical assessment (1978-2011) of levels in White Bear Lake, local groundwater levels, and their relation to historical precipitation and groundwater withdrawals in the White Bear Lake area; (2) recent (2010-11) hydrologic and water-quality data collected from White Bear Lake, other lakes, and wells; and (3) water-balance assessments for White Bear Lake in March and August 2011. An analysis of covariance between average annual lake-level change and annual precipitation indicated the relation between the two variables was significantly different from 2003 through 2011 compared with 1978 through 2002, requiring an average of 4 more inches of precipitation per year to maintain the lake level. This shift in the linear relation between annual lake-level change and annual precipitation indicated the net effect of the non-precipitation terms on the water balance has changed relative to precipitation. The average amount of precipitation required each year to maintain the lake level has increased from 33 inches per year during 1978-2002 to 37 inches per year during 2003-11. The combination of lower precipitation and an increase in groundwater withdrawals can explain the change in the lake-level response to precipitation. Annual and summer groundwater withdrawals from the Prairie du Chien-Jordan aquifer have more than doubled from 1980 through 2010. Results from a regression model constructed with annual lake-level change, annual precipitation minus evaporation, and annual volume of groundwater withdrawn from the Prairie du Chien-Jordan aquifer indicated groundwater withdrawals had a greater effect than precipitation minus evaporation on water levels in the White Bear Lake area for all years since 2003. The recent (2003-11) decline in White Bear Lake reflects the declining water levels in the Prairie du Chien-Jordan aquifer; increases in groundwater withdrawals from this aquifer are a likely cause for declines in groundwater levels and lake levels. Synoptic, static groundwater-level and lake-level measurements in March/April and August 2011 indicated groundwater was potentially flowing into White Bear Lake from glacial aquifers to the northeast and south, and lake water was potentially discharging from White Bear Lake to the underlying glacial and Prairie du Chien-Jordan aquifers and glacial aquifers to the northwest. Groundwater levels in the Prairie du Chien-Jordan aquifer below White Bear Lake are approximately 0 to 19 feet lower than surface-water levels in the lake, indicating groundwater from the aquifer likely does not flow into White Bear Lake, but lake water may discharge into the aquifer. Groundwater levels from March/April to August 2011 declined more than 10 feet in the Prairie du Chien-Jordan aquifer south of White Bear Lake and to the north in Hugo, Minnesota. Water-quality analyses of pore water from nearshore lake-sediment and well-water samples, seepage-meter measurements, and hydraulic-head differences measured in White Bear Lake also indicated groundwater was potentially flowing into White Bear Lake from shallow glacial aquifers to the east and south. Negative temperature anomalies determined in shallow waters in the water-quality survey conducted in White Bear Lake indicated several shallow-water areas where groundwater may be flowing into the lake from glacial aquifers below the lake. Cool lake-sediment temperatures (less than 18 degrees Celsius) were measured in eight areas along the northeast, east, south, and southwest shores of White Bear Lake, indicating potential areas where groundwater may flow into the lake. Stable isotope analyses of well-water, precipitation, and lake-water samples indicated wells downgradient from White Bear Lake screened in the glacial buried aquifer or open to the Prairie du Chien-Jordan aquifer receive a mixture of surface water and groundwater; the largest surface-water contributions are in wells closer to White Bear Lake. A wide range in oxygen-18/oxygen-16 and deuterium/protium ratios was measured in well-water samples, indicating different sources of water are supplying water to the wells. Well water with oxygen-18/oxygen-16 and deuterium/protium ratios that plot close to the meteoric water line consisted mostly of groundwater because deuterium/protium ratios for most groundwater usually are similar to ratios for rainwater and snow, plotting close to meteoric water lines. Well water with oxygen-18/oxygen-16 and deuterium/protium ratios that plot between the meteoric water line and ratios for the surface-water samples from White Bear Lake consists of a mixture of surface water and groundwater; the percentage of each source varies relative to its ratios. White Bear Lake is the likely source of the surface water to the wells that have a mixture of surface water and groundwater because (1) it is the only large, deep lake near these wells; (2) these wells are near and downgradient from White Bear Lake; and (3) these wells obtain their water from relatively deep depths, and White Bear Lake is the deepest lake in that area. The percentages of surface-water contribution to the three wells screened in the glacial buried aquifer receiving surface water were 16, 48, and 83 percent. The percentages of surface-water contribution ranged from 5 to 79 percent for the five wells open to the Prairie du Chien-Jordan aquifer receiving surface water; wells closest to White Bear Lake had the largest percentages of surface-water contribution. Water-balance analysis of White Bear Lake in March and August 2011 indicated a potential discharge of 2.8 and 4.5 inches per month, respectively, over the area of the lake from the lake to local aquifers. Most of the sediments from a 12.4-foot lake core collected at the deepest part of White Bear Lake consisted of silts, sands, and gravels likely slumped from shallower waters, with a very low amount of low-permeability, organic material.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135044","collaboration":"Prepared in cooperation with the White Bear Lake Conservation District, Minnesota Pollution Control Agency, Minnesota Department of Natural Resources, Minnesota Board of Water and Soil Resources, Twin Cities Metropolitan Council, and the Groundwater/Surface-Water Interaction Partners","usgsCitation":"Jones, P.M., Trost, J.J., Rosenberry, D.O., Jackson, P., Bode, J.A., and O’Grady, R.M., 2013, Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011: U.S. Geological Survey Scientific Investigations Report 2013-5044, ix, 73 p.; Downloads Directory, https://doi.org/10.3133/sir20135044.","productDescription":"ix, 73 p.; Downloads Directory","numberOfPages":"88","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-030440","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":271388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135044.gif"},{"id":271385,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5044/"},{"id":271387,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5044/downloads/"},{"id":271386,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5044/sir2013-5044.pdf"}],"country":"United States","state":"Minnesota","county":"Anoka County, Ramsey County, Washington County","city":"Minneapolis","otherGeospatial":"White Bear Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.2080078125,\n 44.92883525162427\n ],\n [\n -93.2080078125,\n 45.2004253589021\n ],\n [\n -92.80357360839842,\n 45.2004253589021\n ],\n [\n -92.80357360839842,\n 44.92883525162427\n ],\n [\n -93.2080078125,\n 44.92883525162427\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51779f59e4b095699adf272a","contributors":{"authors":[{"text":"Jones, Perry M. 0000-0002-6569-5144 pmjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6569-5144","contributorId":2231,"corporation":false,"usgs":true,"family":"Jones","given":"Perry","email":"pmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trost, Jared J. 0000-0003-0431-2151 jtrost@usgs.gov","orcid":"https://orcid.org/0000-0003-0431-2151","contributorId":3749,"corporation":false,"usgs":true,"family":"Trost","given":"Jared","email":"jtrost@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477837,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":477835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, P. Ryan","contributorId":68571,"corporation":false,"usgs":true,"family":"Jackson","given":"P. Ryan","affiliations":[],"preferred":false,"id":477839,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bode, Jenifer A. jabode@usgs.gov","contributorId":3857,"corporation":false,"usgs":true,"family":"Bode","given":"Jenifer","email":"jabode@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":477838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Grady, Ryan M.","contributorId":83433,"corporation":false,"usgs":true,"family":"O’Grady","given":"Ryan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477840,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045558,"text":"70045558 - 2013 - Modeling ecological minimum requirements for distribution of greater sage-grouse leks: implications for population connectivity across their western range, U.S.A.","interactions":[],"lastModifiedDate":"2013-06-17T09:12:39","indexId":"70045558","displayToPublicDate":"2013-04-23T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Modeling ecological minimum requirements for distribution of greater sage-grouse leks: implications for population connectivity across their western range, U.S.A.","docAbstract":"Greater sage-grouse Centrocercus urophasianus (Bonaparte) currently occupy approximately half of their historical distribution across western North America. Sage-grouse are a candidate for endangered species listing due to habitat and population fragmentation coupled with inadequate regulation to control development in critical areas. Conservation planning would benefit from accurate maps delineating required habitats and movement corridors. However, developing a species distribution model that incorporates the diversity of habitats used by sage-grouse across their widespread distribution has statistical and logistical challenges. We first identified the ecological minimums limiting sage-grouse, mapped similarity to the multivariate set of minimums, and delineated connectivity across a 920,000 km2 region. We partitioned a Mahalanobis D2 model of habitat use into k separate additive components each representing independent combinations of species–habitat relationships to identify the ecological minimums required by sage-grouse. We constructed the model from abiotic, land cover, and anthropogenic variables measured at leks (breeding) and surrounding areas within 5 km. We evaluated model partitions using a random subset of leks and historic locations and selected D2 (k = 10) for mapping a habitat similarity index (HSI). Finally, we delineated connectivity by converting the mapped HSI to a resistance surface. Sage-grouse required sagebrush-dominated landscapes containing minimal levels of human land use. Sage-grouse used relatively arid regions characterized by shallow slopes, even terrain, and low amounts of forest, grassland, and agriculture in the surrounding landscape. Most populations were interconnected although several outlying populations were isolated because of distance or lack of habitat corridors for exchange. Land management agencies currently are revising land-use plans and designating critical habitat to conserve sage-grouse and avoid endangered species listing. Our results identifying attributes important for delineating habitats or modeling connectivity will facilitate conservation and management of landscapes important for supporting current and future sage-grouse populations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/ece3.557","usgsCitation":"Knick, S.T., Hanser, S.E., and Preston, K.L., 2013, Modeling ecological minimum requirements for distribution of greater sage-grouse leks: implications for population connectivity across their western range, U.S.A.: Ecology and Evolution, v. 3, no. 6, p. 1539-1551, https://doi.org/10.1002/ece3.557.","productDescription":"13 p.","startPage":"1539","endPage":"1551","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473866,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.557","text":"Publisher Index Page"},{"id":271384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271383,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ece3.557"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","volume":"3","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-04-22","publicationStatus":"PW","scienceBaseUri":"51779f5be4b095699adf2732","contributors":{"authors":[{"text":"Knick, Steven T. 0000-0003-4025-1704 steve_knick@usgs.gov","orcid":"https://orcid.org/0000-0003-4025-1704","contributorId":159,"corporation":false,"usgs":true,"family":"Knick","given":"Steven","email":"steve_knick@usgs.gov","middleInitial":"T.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":477845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanser, Steven E.","contributorId":99273,"corporation":false,"usgs":true,"family":"Hanser","given":"Steven","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":477847,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Preston, Kristine L.","contributorId":72693,"corporation":false,"usgs":true,"family":"Preston","given":"Kristine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":477846,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045508,"text":"70045508 - 2013 - Effects of currents and tides on fine-scale use of marine bird habitats in a Southeast Alaska hotspot","interactions":[],"lastModifiedDate":"2013-08-12T09:02:26","indexId":"70045508","displayToPublicDate":"2013-04-23T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2636,"text":"MEPS","active":true,"publicationSubtype":{"id":10}},"title":"Effects of currents and tides on fine-scale use of marine bird habitats in a Southeast Alaska hotspot","docAbstract":"Areas with high species richness have become focal points in the establishment of marine protected areas, but an understanding of the factors that support this diversity is still incomplete. In coastal areas, tidal currents—modulated by bathymetry and manifested in variable speeds—are a dominant physical feature of the environment. However, difficulties resolving tidally affected currents and depths at fine spatial-temporal scales have limited our ability to understand their influence the distribution of marine birds. We used a hydrographic model of the water mass in Glacier Bay, Alaska to link depths and current velocities with the locations of 15 common marine bird species observed during fine-scale boat-based surveys of the bay conducted during June of four consecutive years (2000-2003). Marine birds that forage on the bottom tended to occupy shallow habitats with slow-moving currents; mid-water foragers used habitats with intermediate depths and current speeds; and surface-foraging species tended to use habitats with fast-moving, deep waters. Within foraging groups there was variability among species in their use of habitats. While species obligated to foraging near bottom were constrained to use similar types of habitat, species in the mid-water foraging group were associated with a wider range of marine habitat characteristics. Species also showed varying levels of site use depending on tide stage. The dramatic variability in bottom topography—especially the presence of numerous sills, islands, headlands and channels—and large tidal ranges in Glacier Bay create a wide range of current-affected fine-scale foraging habitats that may contribute to the high diversity of marine bird species found there.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"MEPS","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Inter-Research","doi":"10.3354/meps10304","usgsCitation":"Drew, G.S., Piatt, J.F., and Hill, D.J., 2013, Effects of currents and tides on fine-scale use of marine bird habitats in a Southeast Alaska hotspot: MEPS, v. 487, p. 275-286, https://doi.org/10.3354/meps10304.","productDescription":"12 p.","startPage":"275","endPage":"286","ipdsId":"IP-042964","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":473868,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps10304","text":"Publisher Index Page"},{"id":271396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271395,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3354/meps10304"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,51.2 ], [ 172.5,71.4 ], [ -130.0,71.4 ], [ -130.0,51.2 ], [ 172.5,51.2 ] ] ] } } ] }","volume":"487","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51779f57e4b095699adf2726","contributors":{"authors":[{"text":"Drew, Gary S. 0000-0002-6789-0891 gdrew@usgs.gov","orcid":"https://orcid.org/0000-0002-6789-0891","contributorId":3311,"corporation":false,"usgs":true,"family":"Drew","given":"Gary","email":"gdrew@usgs.gov","middleInitial":"S.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":477667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":477666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hill, David J.","contributorId":77827,"corporation":false,"usgs":true,"family":"Hill","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":477668,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047132,"text":"70047132 - 2013 - Structural evolution of the east Sierra Valley system (Owens Valley and vicinity), California: a geologic and geophysical synthesis","interactions":[],"lastModifiedDate":"2013-07-26T14:18:05","indexId":"70047132","displayToPublicDate":"2013-04-22T14:05:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1816,"text":"Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Structural evolution of the east Sierra Valley system (Owens Valley and vicinity), California: a geologic and geophysical synthesis","docAbstract":"The tectonically active East Sierra Valley System (ESVS), which comprises the westernmost part of the Walker Lane-Eastern California Shear Zone, marks the boundary between the highly extended Basin and Range Province and the largely coherent Sierra Nevada-Great Valley microplate (SN-GVm), which is moving relatively NW. The recent history of the ESVS is characterized by oblique extension partitioned between NNW-striking normal and strike-slip faults oriented at an angle to the more northwesterly relative motion of the SN-GVm. Spatially variable extension and right-lateral shear have resulted in a longitudinally segmented valley system composed of diverse geomorphic and structural elements, including a discontinuous series of deep basins detected through analysis of isostatic gravity anomalies. Extension in the ESVS probably began in the middle Miocene in response to initial westward movement of the SN-GVm relative to the Colorado Plateau. At ca. 3-3.5 Ma, the SN-GVm became structurally separated from blocks directly to the east, resulting in significant basin-forming deformation in the ESVS. We propose a structural model that links high-angle normal faulting in the ESVS with coeval low-angle detachment faulting in adjacent areas to the east.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"MDPI","doi":"10.3390/geosciences3020176","usgsCitation":"Stevens, C., Stone, P., and Blakely, R.J., 2013, Structural evolution of the east Sierra Valley system (Owens Valley and vicinity), California: a geologic and geophysical synthesis: Geosciences, v. 3, no. 2, p. 176-215, https://doi.org/10.3390/geosciences3020176.","productDescription":"40 p.","startPage":"176","endPage":"215","numberOfPages":"40","ipdsId":"IP-038757","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":473869,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences3020176","text":"Publisher Index Page"},{"id":275462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275461,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/geosciences3020176"}],"country":"United States","state":"California","otherGeospatial":"East Sierra Nevada Valley System","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.0,35.0 ], [ -119.0,38.0 ], [ -117.0,38.0 ], [ -117.0,35.0 ], [ -119.0,35.0 ] ] ] } } ] }","volume":"3","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-04-22","publicationStatus":"PW","scienceBaseUri":"51f39a68e4b0a32220222fb1","contributors":{"authors":[{"text":"Stevens, Calvin H.","contributorId":59848,"corporation":false,"usgs":true,"family":"Stevens","given":"Calvin H.","affiliations":[],"preferred":false,"id":481149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Paul 0000-0002-1439-0156 pastone@usgs.gov","orcid":"https://orcid.org/0000-0002-1439-0156","contributorId":273,"corporation":false,"usgs":true,"family":"Stone","given":"Paul","email":"pastone@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":481147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":481148,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045522,"text":"70045522 - 2013 - Controls on variations in MODIS fire radiative power in Alaskan boreal forests: implications for fire severity conditions","interactions":[],"lastModifiedDate":"2013-04-22T11:01:53","indexId":"70045522","displayToPublicDate":"2013-04-22T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3253,"text":"Remote Sensing and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Controls on variations in MODIS fire radiative power in Alaskan boreal forests: implications for fire severity conditions","docAbstract":"Fire activity in the Alaskan boreal forest, though episodic at annual and intra-annual time scales, has experienced an increase over the last several decades. Increases in burned area and fire severity are not only releasing more carbon to the atmosphere, but likely shifting vegetation composition in the region towards greater deciduous dominance and a reduction in coniferous stands. While some recent studies have addressed qualitative differences between large and small fire years in the Alaskan boreal forest, the ecological effects of a greater proportion of burning occurring during large fire years and during late season fires have not yet been examined.\n\nSome characteristics of wildfires that can be detected remotely are related to fire severity and can provide new information on spatial and temporal patterns of burning. This analysis focused on boreal wildfire intensity (fire radiative power, or FRP) contained in the Moderate Resolution Imaging Spectroradiometer (MODIS) daily active fire product from 2003 to 2010. We found that differences in FRP resulted from seasonality and intra-annual variability in fire activity levels, vegetation composition, latitudinal variation, and fire spread behavior.\n\nOur studies determined two general categories of active fire detections: new detections associated with the spread of the fire front and residual pixels in areas that had already experienced front burning. Residual pixels had a lower average FRP than front pixels, but represented a high percentage of all pixels during periods of high fire activity (large fire years, late season burning, and seasonal periods of high fire activity). As a result, the FRP from periods of high fire activity was less intense than those from periods of low fire activity. Differences related to latitude were greater than expected, with higher latitudes burning later in the season and at a higher intensity than lower latitudes. Differences in vegetation type indicate that coniferous vegetation is the most fire prone, but deciduous vegetation is not particularly fire resistant, as the proportion of active fire detections in deciduous stands is roughly the same as the fraction of deciduous vegetation in the region.\n\nQualitative differences between periods of high and low fire activity are likely to reflect important differences in fire severity. Large fire years are likely to be more severe, characterized by more late season fires and a greater proportion of residual burning. Given the potential for severe fires to effect changes in vegetation cover, the shift toward a greater proportion of area burning during large fire years may influence vegetation patterns in the region over the medium to long term.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing and the Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2012.11.017","usgsCitation":"Barrett, K., and Kasischke, E.S., 2013, Controls on variations in MODIS fire radiative power in Alaskan boreal forests: implications for fire severity conditions: Remote Sensing and the Environment, v. 130, p. 171-181, https://doi.org/10.1016/j.rse.2012.11.017.","productDescription":"11 p.","startPage":"171","endPage":"181","ipdsId":"IP-042197","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":271341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271340,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2012.11.017"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,51.2 ], [ 172.5,71.4 ], [ -130.0,71.4 ], [ -130.0,51.2 ], [ 172.5,51.2 ] ] ] } } ] }","volume":"130","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51764ddae4b0f989f99e008a","chorus":{"doi":"10.1016/j.rse.2012.11.017","url":"http://dx.doi.org/10.1016/j.rse.2012.11.017","publisher":"Elsevier BV","authors":"Barrett Kirsten, Kasischke Eric S.","journalName":"Remote Sensing of Environment","publicationDate":"3/2013"},"contributors":{"authors":[{"text":"Barrett, Kirsten","contributorId":26600,"corporation":false,"usgs":true,"family":"Barrett","given":"Kirsten","affiliations":[],"preferred":false,"id":477728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kasischke, Eric S.","contributorId":106781,"corporation":false,"usgs":true,"family":"Kasischke","given":"Eric","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":477729,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045541,"text":"sir20125233 - 2013 - Variations in soil detachment rates after wildfire as a function of soil depth, flow properties, and root properties","interactions":[],"lastModifiedDate":"2013-04-22T11:54:13","indexId":"sir20125233","displayToPublicDate":"2013-04-22T00:00:00","publicationYear":"2013","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":"2012-5233","title":"Variations in soil detachment rates after wildfire as a function of soil depth, flow properties, and root properties","docAbstract":"Wildfire affects hillslope erosion through increased surface runoff and increased sediment availability, both of which contribute to large post-fire erosion events. Relations between soil detachment rate, soil depth, flow and root properties, and fire impacts are poorly understood and not represented explicitly in commonly used post-fire erosion models. Detachment rates were measured on intact soil cores using a modified tilting flume. The cores were mounted flush with the flume-bed and a measurement was made on the surface of the core. The core was extruded upward, cut off, and another measurement was repeated at a different depth below the original surface of the core. Intact cores were collected from one site burned by the 2010 Fourmile Canyon (FMC) fire in Colorado and from one site burned by the 2010 Pozo fire in California. Each site contained contrasting vegetation and soil types. Additional soil samples were collected alongside the intact cores and were analyzed in the laboratory for soil properties (organic matter, bulk density, particle-size distribution) and for root properties (root density and root-length density). Particle-size distribution and root properties were different between sites, but sites were similar in terms of bulk density and organic matter. Soil detachment rates had similar relations with non-uniform shear stress and non-uniform unit stream power. Detachment rates within single sampling units displayed a relatively weak and inconsistent relation to flow variables. When averaged across all clusters, the detachment rate displayed a linear relation to shear stress, but variability in soil properties meant that the shear stress accounted for only a small proportion of the overall variability in detachment rates (R2 = 0.23; R2 is the coefficient of determination). Detachment rate was related to root-length density in some clusters (R2 values up to 0.91) and unrelated in others (R2 values <0.1). The overall R2 value improved and the range of exponents became narrower by applying a multivariate regression model where boundary shear stress and root-length density were included as explanatory variables. This suggests that an erodibility parameter which incorporates the effects of both flow and root properties on detachment could improve the representation of sediment availability after wildfire.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125233","usgsCitation":"Moody, J.A., and Nyman, P., 2013, Variations in soil detachment rates after wildfire as a function of soil depth, flow properties, and root properties: U.S. Geological Survey Scientific Investigations Report 2012-5233, vi, 40 p., https://doi.org/10.3133/sir20125233.","productDescription":"vi, 40 p.","additionalOnlineFiles":"N","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":271348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125233.gif"},{"id":271346,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5233/SIR12-5233-508.pdf"},{"id":271347,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5233/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51764ddde4b0f989f99e009a","contributors":{"authors":[{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":477802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nyman, Peter","contributorId":64137,"corporation":false,"usgs":true,"family":"Nyman","given":"Peter","email":"","affiliations":[],"preferred":false,"id":477803,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045470,"text":"70045470 - 2013 - Complex resistivity signatures of ethanol in sand-clay mixtures","interactions":[],"lastModifiedDate":"2013-04-21T19:27:31","indexId":"70045470","displayToPublicDate":"2013-04-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Complex resistivity signatures of ethanol in sand-clay mixtures","docAbstract":"We performed complex resistivity (CR) measurements on laboratory columns to investigate changes in electrical properties as a result of varying ethanol (EtOH) concentration (0% to 30% v/v) in a sand–clay (bentonite) matrix. We applied Debye decomposition, a phenomenological model commonly used to fit CR data, to determine model parameters (time constant: τ, chargeability: m, and normalized chargeability: mn). The CR data showed a significant (P ≤ 0.001) time-dependent variation in the clay driven polarization response (~ 12 mrad) for 0% EtOH concentration. This temporal variation probably results from the clay–water reaction kinetics trending towards equilibrium in the sand–clay–water system. The clay polarization is significantly suppressed (P ≤ 0.001) for both measured phase (ϕ) and imaginary conductivity (σ″) with increasing EtOH concentration. Normalized chargeability consistently decreases (by up to a factor of ~ 2) as EtOH concentration increases from 0% to 10% and 10 to 20%, respectively. We propose that such suppression effects are associated with alterations in the electrical double layer (EDL) at the clay–fluid interface due to (a) strong EtOH adsorption on clay, and (b) complex intermolecular EtOH–water interactions and subsequent changes in ionic mobility on the surface in the EDL. Changes in the CR data following a change of the saturating fluid from EtOH 20% to plain water indicate strong hysteresis effects in the electrical response, which we attribute to persistent EtOH adsorption on clay. Our results demonstrate high sensitivity of CR measurements to clay–EtOH interactions in porous media, indicating the potential application of this technique for characterization and monitoring of ethanol contamination in sediments containing clays.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Contaminant Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jconhyd.2013.03.005","usgsCitation":"Personna, Y.R., Slater, L., Ntarlagiannis, D., Werkema, D.D., and Szabo, Z., 2013, Complex resistivity signatures of ethanol in sand-clay mixtures: Journal of Contaminant Hydrology, v. 149, p. 76-87, https://doi.org/10.1016/j.jconhyd.2013.03.005.","productDescription":"12 p.","startPage":"76","endPage":"87","ipdsId":"IP-045055","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":271323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271322,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2013.03.005"}],"volume":"149","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5174fc5ee4b074c2b055647d","contributors":{"authors":[{"text":"Personna, Yves Robert","contributorId":77820,"corporation":false,"usgs":false,"family":"Personna","given":"Yves","email":"","middleInitial":"Robert","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slater, Lee","contributorId":55707,"corporation":false,"usgs":false,"family":"Slater","given":"Lee","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ntarlagiannis, Dimitrios","contributorId":55303,"corporation":false,"usgs":false,"family":"Ntarlagiannis","given":"Dimitrios","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":477575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":2240,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":477574,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70043239,"text":"70043239 - 2013 - Climatic trends over Ethiopia: regional signals and drivers","interactions":[],"lastModifiedDate":"2013-06-17T09:07:21","indexId":"70043239","displayToPublicDate":"2013-04-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Climatic trends over Ethiopia: regional signals and drivers","docAbstract":"This study analyses observed and projected climatic trends over Ethiopia, through analysis of temperature and rainfall records and related meteorological fields. The observed datasets include gridded station records and reanalysis products; while projected trends are analysed from coupled model simulations drawn from the IPCC 4th Assessment. Upward trends in air temperature of + 0.03 °C year−1 and downward trends in rainfall of − 0.4 mm month−1 year−1 have been observed over Ethiopia's southwestern region in the period 1948-2006. These trends are projected to continue to 2050 according to the Geophysical Fluid Dynamics Lab model using the A1B scenario. Large scale forcing derives from the West Indian Ocean where significant warming and increased rainfall are found. Anticyclonic circulations have strengthened over northern and southern Africa, limiting moisture transport from the Gulf of Guinea and Congo. Changes in the regional Walker and Hadley circulations modulate the observed and projected climatic trends. Comparing past and future patterns, the key features spread westward from Ethiopia across the Sahel and serve as an early warning of potential impacts.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Climatology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/joc.3560","usgsCitation":"Jury, M.R., and Funk, C.C., 2013, Climatic trends over Ethiopia: regional signals and drivers: International Journal of Climatology, v. 33, no. 8, p. 1924-1935, https://doi.org/10.1002/joc.3560.","productDescription":"12 p.","startPage":"1924","endPage":"1935","ipdsId":"IP-021460","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":271307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271306,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/joc.3560"}],"country":"Ethiopia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 33.0,3.4 ], [ 33.0,15.0 ], [ 48.0,15.0 ], [ 48.0,3.4 ], [ 33.0,3.4 ] ] ] } } ] }","volume":"33","issue":"8","noUsgsAuthors":false,"publicationDate":"2012-08-15","publicationStatus":"PW","scienceBaseUri":"5174fc52e4b074c2b0556471","contributors":{"authors":[{"text":"Jury, Mark R.","contributorId":28145,"corporation":false,"usgs":true,"family":"Jury","given":"Mark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":473217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":473216,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043896,"text":"70043896 - 2013 - Crater topography on Titan: implications for landscape evolution","interactions":[],"lastModifiedDate":"2013-04-22T13:26:38","indexId":"70043896","displayToPublicDate":"2013-04-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Crater topography on Titan: implications for landscape evolution","docAbstract":"We present a comprehensive review of available crater topography measurements for Saturn’s moon Titan. In general, the depths of Titan’s craters are within the range of depths observed for similarly sized fresh craters on Ganymede, but several hundreds of meters shallower than Ganymede’s average depth vs. diameter trend. Depth-to-diameter ratios are between 0.0012 ± 0.0003 (for the largest crater studied, Menrva, D ~ 425 km) and 0.017 ± 0.004 (for the smallest crater studied, Ksa, D ~ 39 km). When we evaluate the Anderson–Darling goodness-of-fit parameter, we find that there is less than a 10% probability that Titan’s craters have a current depth distribution that is consistent with the depth distribution of fresh craters on Ganymede. There is, however, a much higher probability that the relative depths are uniformly distributed between 0 (fresh) and 1 (completely infilled). This distribution is consistent with an infilling process that is relatively constant with time, such as aeolian deposition. Assuming that Ganymede represents a close ‘airless’ analogue to Titan, the difference in depths represents the first quantitative measure of the amount of modification that has shaped Titan’s surface, the only body in the outer Solar System with extensive surface–atmosphere exchange.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Icarus","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.icarus.2012.11.030","usgsCitation":"Neish, C.D., Kirk, R.L., Lorenz, R.D., Bray, V., Schenk, P., Stiles, B., Turtle, E., Mitchell, K., and Hayes, A., 2013, Crater topography on Titan: implications for landscape evolution: Icarus, v. 223, no. 1, p. 82-90, https://doi.org/10.1016/j.icarus.2012.11.030.","productDescription":"9 p.","startPage":"82","endPage":"90","ipdsId":"IP-039849","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":473872,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2060/20140006611","text":"External Repository"},{"id":271363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271362,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.icarus.2012.11.030"}],"otherGeospatial":"Titan","volume":"223","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51765be6e4b0f989f99e00d4","contributors":{"authors":[{"text":"Neish, Catherine D.","contributorId":13355,"corporation":false,"usgs":true,"family":"Neish","given":"Catherine","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":474416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirk, R. L.","contributorId":94698,"corporation":false,"usgs":true,"family":"Kirk","given":"R.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":474422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenz, R. D.","contributorId":90441,"corporation":false,"usgs":false,"family":"Lorenz","given":"R.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":474421,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bray, V.J.","contributorId":72692,"corporation":false,"usgs":true,"family":"Bray","given":"V.J.","email":"","affiliations":[],"preferred":false,"id":474420,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schenk, P.","contributorId":105484,"corporation":false,"usgs":true,"family":"Schenk","given":"P.","affiliations":[],"preferred":false,"id":474423,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stiles, B.W.","contributorId":43900,"corporation":false,"usgs":true,"family":"Stiles","given":"B.W.","email":"","affiliations":[],"preferred":false,"id":474418,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Turtle, E.","contributorId":45530,"corporation":false,"usgs":true,"family":"Turtle","given":"E.","affiliations":[],"preferred":false,"id":474419,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mitchell, Ken","contributorId":8211,"corporation":false,"usgs":true,"family":"Mitchell","given":"Ken","email":"","affiliations":[],"preferred":false,"id":474415,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hayes, A.","contributorId":26415,"corporation":false,"usgs":true,"family":"Hayes","given":"A.","affiliations":[],"preferred":false,"id":474417,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70043596,"text":"70043596 - 2013 - Breaking the speed limit--comparative sprinting performance of brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta)","interactions":[],"lastModifiedDate":"2013-04-19T23:29:14","indexId":"70043596","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Breaking the speed limit--comparative sprinting performance of brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta)","docAbstract":"Sprinting behavior of free-ranging fish has long been thought to exceed that of captive fish. Here we present data from wild-caught brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta), volitionally entering and sprinting against high-velocity flows in an open-channel flume. Performance of the two species was nearly identical, with the species attaining absolute speeds > 25 body lengths·s−1. These speeds far exceed previously published observations for any salmonid species and contribute to the mounting evidence that commonly accepted estimates of swimming performance are low. Brook trout demonstrated two distinct modes in the relationship between swim speed and fatigue time, similar to the shift from prolonged to sprint mode described by other authors, but in this case occurring at speeds > 19 body lengths·s−1. This is the first demonstration of multiple modes of sprint swimming at such high swim speeds. Neither species optimized for distance maximization, however, indicating that physiological limits alone are poor predictors of swimming performance. By combining distributions of volitional swim speeds with endurance, we were able to account for >80% of the variation in distance traversed by both species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Fisheries and Aquatic Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"NRC Research Press","publisherLocation":"Ottawa, Canada","doi":"10.1139/cjfas-2012-0186","usgsCitation":"Castro-Santos, T., Sanz-Ronda, F.J., and Ruiz-Legazpi, J., 2013, Breaking the speed limit--comparative sprinting performance of brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta): Canadian Journal of Fisheries and Aquatic Sciences, v. 70, no. 2, p. 280-293, https://doi.org/10.1139/cjfas-2012-0186.","productDescription":"14 p.","startPage":"280","endPage":"293","ipdsId":"IP-042550","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":271286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271285,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1139/cjfas-2012-0186"}],"volume":"70","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595ae4b0c173799e78da","contributors":{"authors":[{"text":"Castro-Santos, Theodore 0000-0003-2575-9120","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":32573,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","affiliations":[],"preferred":false,"id":473935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanz-Ronda, Francisco Javier","contributorId":88251,"corporation":false,"usgs":true,"family":"Sanz-Ronda","given":"Francisco","email":"","middleInitial":"Javier","affiliations":[],"preferred":false,"id":473936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruiz-Legazpi, Jorge","contributorId":95368,"corporation":false,"usgs":true,"family":"Ruiz-Legazpi","given":"Jorge","affiliations":[],"preferred":false,"id":473937,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045494,"text":"ofr20131086 - 2013 - Estimation of capture zones and drawdown at the Northwest and West Well Fields, Miami-Dade County, Florida, using an unconstrained Monte Carlo analysis: recent (2004) and proposed conditions","interactions":[],"lastModifiedDate":"2013-04-19T10:55:31","indexId":"ofr20131086","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","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":"2013-1086","title":"Estimation of capture zones and drawdown at the Northwest and West Well Fields, Miami-Dade County, Florida, using an unconstrained Monte Carlo analysis: recent (2004) and proposed conditions","docAbstract":"Travel-time capture zones and drawdown for two production well fields, used for drinking-water supply in Miami-Dade County, southeastern Florida, were delineated by the U.S Geological Survey using an unconstrained Monte Carlo analysis. The well fields, designed to supply a combined total of approximately 250 million gallons of water per day, pump from the highly transmissive Biscayne aquifer in the urban corridor between the Everglades and Biscayne Bay. A transient groundwater flow model was developed and calibrated to field data to ensure an acceptable match between simulated and observed values for aquifer heads and net exchange of water between the aquifer and canals. Steady-state conditions were imposed on the transient model and a post-processing backward particle-tracking approach was implemented. Multiple stochastic realizations of horizontal hydraulic conductivity, conductance of canals, and effective porosity were simulated for steady-state conditions representative of dry, average and wet hydrologic conditions to calculate travel-time capture zones of potential source areas of the well fields. Quarry lakes, formed as a product of rock-mining activities, whose effects have previously not been considered in estimation of capture zones, were represented using high hydraulic-conductivity, high-porosity cells, with the bulk hydraulic conductivity of each cell calculated based on estimates of aquifer hydraulic conductivity, lake depths and aquifer thicknesses. A post-processing adjustment, based on calculated residence times using lake outflows and known lake volumes, was utilized to adjust particle endpoints to account for an estimate of residence-time-based mixing of lakes. Drawdown contours of 0.1 and 0.25 foot were delineated for the dry, average, and wet hydrologic conditions as well. In addition, 95-percent confidence intervals (CIs) were calculated for the capture zones and drawdown contours to delineate a zone of uncertainty about the median estimates. Results of the Monte Carlo simulations indicate particle travel distances at the Northwest Well Field (NWWF) and West Well Field (WWF) are greatest to the west, towards the Everglades. The man-made quarry lakes substantially affect particle travel distances. In general near the NWWF, the capture zones in areas with lakes were smaller in areal extent than capture zones in areas without lakes. It is possible that contamination could reach the well fields quickly, within 10 days in some cases, if it were introduced into lakes nearest to supply wells, with one of the lakes being only approximately 650 feet from the nearest supply well. In addition to estimating drawdown and travel-time capture zones of 10, 30, 100, and 210 days for the NWWF and the WWF under more recent conditions, two proposed scenarios were evaluated with Monte Carlo simulations: the potential hydrologic effects of proposed Everglades groundwater seepage mitigation and quarry-lake expansion. The seepage mitigation scenario included the addition of two proposed anthropogenic features to the model: (1) an impermeable horizontal flow barrier east of the L-31N canal along the western model boundary between the Everglades and the urban areas of Miami-Dade County, and (2) a recharge canal along the Dade-Broward Levee near the NWWF. Capture zones and drawdown for the WWF were substantially affected by the addition of the barrier, which eliminates flow from the western boundary into the active model domain, shifting the predominant capture zone source area from the west more to the north and south. The 95-percent CI for the 210-day capture zone moved slightly in the NWWF as a result of the recharge canal. The lake-expansion scenario incorporated a proposed increase in the number and surface area of lakes by an additional 25 square miles. This scenario represents a 150-percent increase from the 2004 lake surface area near both well fields, but with the majority of increase proposed near the NWWF. The lake-expansion scenario substantially decreased the extent of the 210-day capture zone of the NWWF, which is limited to the lakes nearest the well field under proposed conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131086","collaboration":"Prepared in cooperation with the Miami-Dade County Water and Sewer Department and Department of Regulatory and Economic Resources","usgsCitation":"Brakefield, L.K., Hughes, J.D., Langevin, C.D., and Chartier, K., 2013, Estimation of capture zones and drawdown at the Northwest and West Well Fields, Miami-Dade County, Florida, using an unconstrained Monte Carlo analysis: recent (2004) and proposed conditions: U.S. Geological Survey Open-File Report 2013-1086, x, 127 p., https://doi.org/10.3133/ofr20131086.","productDescription":"x, 127 p.","numberOfPages":"140","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":271256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131086.gif"},{"id":271254,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1086/"},{"id":271255,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1086/pdf/ofr2013-1086.pdf"}],"country":"United States","state":"Florida","county":"Miami-dade","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.35,25.40 ], [ -80.35,25.60 ], [ -80.15,25.60 ], [ -80.15,25.40 ], [ -80.35,25.40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595be4b0c173799e78de","contributors":{"authors":[{"text":"Brakefield, Linzy K. lbrake@usgs.gov","contributorId":2080,"corporation":false,"usgs":true,"family":"Brakefield","given":"Linzy","email":"lbrake@usgs.gov","middleInitial":"K.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":477630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":477628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chartier, Kevin","contributorId":64128,"corporation":false,"usgs":true,"family":"Chartier","given":"Kevin","affiliations":[],"preferred":false,"id":477631,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045491,"text":"sir20135083 - 2013 - Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11","interactions":[],"lastModifiedDate":"2013-04-19T09:29:00","indexId":"sir20135083","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","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":"2013-5083","title":"Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11","docAbstract":"Sedimentation is an ongoing maintenance problem for reservoirs, limiting reservoir storage capacity and navigation. Because Lower Granite Reservoir in Washington is the most upstream of the four U.S. Army Corps of Engineers reservoirs on the lower Snake River, it receives and retains the largest amount of sediment. In 2008, in cooperation with the U.S. Army Corps of Engineers, the U.S. Geological Survey began a study to quantify sediment transport to Lower Granite Reservoir. Samples of suspended sediment and bedload were collected from streamgaging stations on the Snake River near Anatone, Washington, and the Clearwater River at Spalding, Idaho. Both streamgages were equipped with an acoustic Doppler velocity meter to evaluate the efficacy of acoustic backscatter for estimating suspended-sediment concentrations and transport. In 2009, sediment sampling was extended to 10 additional locations in tributary watersheds to help identify the dominant source areas for sediment delivery to Lower Granite Reservoir. Suspended-sediment samples were collected 9–15 times per year at each location to encompass a range of streamflow conditions and to capture significant hydrologic events such as peak snowmelt runoff and rain-on-snow. Bedload samples were collected at a subset of stations where the stream conditions were conducive for sampling, and when streamflow was sufficiently high for bedload transport. At most sampling locations, the concentration of suspended sediment varied by 3–5 orders of magnitude with concentrations directly correlated to streamflow. The largest median concentrations of suspended sediment (100 and 94 mg/L) were in samples collected from stations on the Palouse River at Hooper, Washington, and the Salmon River at White Bird, Idaho, respectively. The smallest median concentrations were in samples collected from the Selway River near Lowell, Idaho (11 mg/L), the Lochsa River near Lowell, Idaho (11 mg/L), the Clearwater River at Orofino, Idaho (13 mg/L), and the Middle Fork Clearwater River at Kooskia, Idaho (15 mg/L). The largest measured concentrations of suspended sediment (3,300 and 1,400 mg/L) during a rain-on-snow event in January 2011 were from samples collected at the Potlatch River near Spalding, Idaho, and the Palouse River at Hooper, Washington, respectively. Generally, samples collected from agricultural watersheds had a high percentage of silt and clay-sized suspended sediment, whereas samples collected from forested watersheds had a high percentage of sand. During water years 2009–11, Lower Granite Reservoir received about 10 million tons of suspended sediment from the combined loads of the Snake and Clearwater Rivers. The Snake River accounted for about 2.97 million tons per year (about 89 percent) of the total suspended sediment, 1.48 million tons per year (about 90 percent) of the suspended sand, and about 1.52 million tons per year (87 percent) of the suspended silt and clay. Of the suspended sediment transported to Lower Granite Reservoir, the Salmon River accounted for about 51 percent of the total suspended sediment, about 56 percent of the suspended sand, and about 44 percent of the suspended silt and clay. About 6.2 million tons (62 percent) of the sediment contributed to Lower Granite Reservoir during 2009–11 entered during water year 2011, which was characterized by an above average winter snowpack and sustained spring runoff. A comparison of historical data collected from the Snake River near Anatone with data collected during this study indicates that concentrations of total suspended sediment and suspended sand in the Snake River were significantly smaller during water years 1972–79 than during 2008–11. Most of the increased sediment content in the Snake River is attributable to an increase of sand-size material. During 1972–79, sand accounted for an average of 28 percent of the suspended-sediment load; during 2008–11, sand accounted for an average of 48 percent. Historical data from the Clearwater River at Spalding indicates that the concentrations of total suspended sediment collected during 1972–79 were not significantly different from the concentrations measured during this study. However, the suspended-sand concentrations in the Clearwater River were significantly smaller during 1972–79 than during 2008–11. The increase in suspended-sand concentrations in the Snake and Clearwater Rivers are probably attributable to numerous severe forest fires that burned large areas of central Idaho from 1980–2010. Acoustic backscatter from an acoustic Doppler velocity meter proved to be an effective method of estimating suspended-sediment concentration and load for most streamflow conditions in the Snake and Clearwater Rivers. Models based on acoustic backscatter were able to simulate most of the variability in suspended-sediment concentrations in the Clearwater River at Spalding (coefficient of determination [R2]=0.93) and the Snake River near Anatone (R2=0.92). Acoustic backscatter seems to be especially effective for estimating suspended-sediment concentration and load over short (monthly and single storm event) and long (annual) time scales when sediment load is highly variable. However, during high streamflow events acoustic surrogate tools may be unable to capture the contribution of suspended sand moving near the bottom of the water column and thus, underestimate the total load of suspended sediment. At the stations where bedload was collected, the particle-size distribution at low streamflows typically was unimodal with sand comprising the dominant particle size. At higher streamflows and during peak bedload discharge, the particle size typically was bimodal and was comprised primarily of sand and coarse gravel. About 55,000 tons of bedload was discharged from the Snake River to Lower Granite Reservoir during water years 2009–11, about 0.62 percent of the total sediment load delivered by the Snake River. About 9,500 tons of bedload was discharged from the Clearwater River to Lower Granite Reservoir during 2009–11, about 0.83 percent of the total sediment load discharged by the Clearwater River during 2009–11.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135083","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Clark, G.M., Fosness, R.L., and Wood, M.S., 2013, Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11: U.S. Geological Survey Scientific Investigations Report 2013-5083, vi, 58 p., https://doi.org/10.3133/sir20135083.","productDescription":"vi, 58 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":271216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135083.jpg"},{"id":271214,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5083/"},{"id":271215,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5083/pdf/sir20135083.pdf"}],"country":"United States","state":"Idaho;Washington","otherGeospatial":"Lower Snake And Clearwater River Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119,44 ], [ -119,47.5 ], [ -113,47.5 ], [ -113,44 ], [ -119,44 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595de4b0c173799e78f2","contributors":{"authors":[{"text":"Clark, Gregory M. gmclark@usgs.gov","contributorId":1377,"corporation":false,"usgs":true,"family":"Clark","given":"Gregory","email":"gmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":477620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045493,"text":"sir20135082 - 2013 - Water volume and sediment volume and density in Lake Linganore between Boyers Mill Road Bridge and Bens Branch, Frederick County, Maryland, 2012","interactions":[],"lastModifiedDate":"2023-03-09T20:13:19.08246","indexId":"sir20135082","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","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":"2013-5082","title":"Water volume and sediment volume and density in Lake Linganore between Boyers Mill Road Bridge and Bens Branch, Frederick County, Maryland, 2012","docAbstract":"To assist in understanding sediment loadings and the management of water resources, a bathymetric survey was conducted in the part of Lake Linganore between Boyers Mill Road Bridge and Bens Branch in Frederick County, Maryland. The bathymetric survey was performed in January 2012 by the U.S. Geological Survey, in cooperation with the City of Frederick and Frederick County. A separate, but related, field effort to collect 18 sediment cores was conducted in March and April 2012. Depth and location data from the bathymetric survey and location data for the sediment cores were compiled and edited by using geographic information system (GIS) software. A three-dimensional triangulated irregular network (TIN) model of the lake bottom was created to calculate the volume of stored water in the reservoir. Large-scale topographic maps of the valley prior to inundation in 1972 were provided by the Frederick County Division of Utilities and Solid Waste Management and digitized for comparison with current (2012) conditions in order to calculate sediment volume. Cartographic representations of both water depth and sediment accumulation were produced, along with an accuracy assessment for the resulting bathymetric model. Vertical accuracies at the 95-percent confidence level for the collected data, the bathymetric surface model, and the bathymetric contour map were calculated to be 0.64 feet (ft), 1.77 ft, and 2.30 ft, respectively. A dry bulk sediment density was calculated for each of the 18 sediment cores collected during March and April 2012, and used to determine accumulated sediment mass. Water-storage capacity in the study area is 110 acre-feet (acre-ft) at a full-pool elevation 308 ft above the National Geodetic Vertical Datum of 1929, whereas total sediment volume in the study area is 202 acre-ft. These totals indicate a loss of about 65 percent of the original water-storage capacity in the 40 years since dam construction. This corresponds to an average rate of sediment accumulation of 5.1 acre-ft per year since Linganore Creek was impounded. Sediment thicknesses ranged from 0 to 16.7 ft. Sediment densities ranged from 0.38 to 1.08 grams per cubic centimeter, and generally decreased in the downstream direction. The total accumulated-sediment mass was 156,000 metric tons between 1972 and 2012.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135082","collaboration":"Prepared in cooperation with the City of Frederick, Maryland and Frederick County, Maryland","usgsCitation":"Sekellick, A.J., Banks, W.S., and Myers, M., 2013, Water volume and sediment volume and density in Lake Linganore between Boyers Mill Road Bridge and Bens Branch, Frederick County, Maryland, 2012: U.S. Geological Survey Scientific Investigations Report 2013-5082, vi, 17 p., https://doi.org/10.3133/sir20135082.","productDescription":"vi, 17 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":271218,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5082/pdf/sir2013-5082.pdf"},{"id":271217,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5082/"},{"id":271219,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135082.gif"}],"country":"United States","state":"Maryl","county":"Frederick","otherGeospatial":"Linganore Creek Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.40,39.15 ], [ -77.40,39.45 ], [ -77.05,39.45 ], [ -77.05,39.15 ], [ -77.40,39.15 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595ee4b0c173799e78f6","contributors":{"authors":[{"text":"Sekellick, Andrew J. 0000-0002-0440-7655 ajsekell@usgs.gov","orcid":"https://orcid.org/0000-0002-0440-7655","contributorId":4125,"corporation":false,"usgs":true,"family":"Sekellick","given":"Andrew","email":"ajsekell@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banks, William S.L.","contributorId":35281,"corporation":false,"usgs":true,"family":"Banks","given":"William","email":"","middleInitial":"S.L.","affiliations":[],"preferred":false,"id":477627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Myers, Michael K. mkmyers@usgs.gov","contributorId":5160,"corporation":false,"usgs":true,"family":"Myers","given":"Michael K.","email":"mkmyers@usgs.gov","affiliations":[{"id":375,"text":"Maryland, Delaware, and the District of Columbia Water Science Center","active":false,"usgs":true}],"preferred":false,"id":477626,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045451,"text":"70045451 - 2013 - A review of selected inorganic surface water quality-monitoring practices: are we really measuring what we think, and if so, are we doing it right?","interactions":[],"lastModifiedDate":"2016-11-30T13:14:40","indexId":"70045451","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"A review of selected inorganic surface water quality-monitoring practices: are we really measuring what we think, and if so, are we doing it right?","docAbstract":"Successful environmental/water quality-monitoring programs usually require a balance between analytical capabilities, the collection and preservation of representative samples, and available financial/personnel resources. Due to current economic conditions, monitoring programs are under increasing pressure to do more with less. Hence, a review of current sampling and analytical methodologies, and some of the underlying assumptions that form the bases for these programs seems appropriate, to see if they are achieving their intended objectives within acceptable error limits and/or measurement uncertainty, in a cost-effective manner. That evaluation appears to indicate that several common sampling/processing/analytical procedures (e.g., dip (point) samples/measurements, nitrogen determinations, total recoverable analytical procedures) are generating biased or nonrepresentative data, and that some of the underlying assumptions relative to current programs, such as calendar-based sampling and stationarity are no longer defensible. The extensive use of statistical models as well as surrogates (e.g., turbidity) also needs to be re-examined because the hydrologic interrelationships that support their use tend to be dynamic rather than static. As a result, a number of monitoring programs may need redesigning, some sampling and analytical procedures may need to be updated, and model/surrogate interrelationships may require recalibration.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/es304058q","usgsCitation":"Horowitz, A.J., 2013, A review of selected inorganic surface water quality-monitoring practices: are we really measuring what we think, and if so, are we doing it right?: Environmental Science & Technology, v. 47, no. 6, p. 2471-2486, https://doi.org/10.1021/es304058q.","productDescription":"16 p.","startPage":"2471","endPage":"2486","ipdsId":"IP-043699","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":271277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271276,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es304058q"}],"volume":"47","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-03-01","publicationStatus":"PW","scienceBaseUri":"51725951e4b0c173799e78d6","contributors":{"authors":[{"text":"Horowitz, Arthur J. 0000-0002-3296-730X horowitz@usgs.gov","orcid":"https://orcid.org/0000-0002-3296-730X","contributorId":1400,"corporation":false,"usgs":true,"family":"Horowitz","given":"Arthur","email":"horowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477514,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045469,"text":"sir20135059 - 2013 - Sources of suspended-sediment loads in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary, south Texas, 1958–2010","interactions":[],"lastModifiedDate":"2016-08-05T14:08:52","indexId":"sir20135059","displayToPublicDate":"2013-04-18T00:00:00","publicationYear":"2013","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":"2013-5059","title":"Sources of suspended-sediment loads in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary, south Texas, 1958–2010","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe-Blanco River Authority; San Antonio River Authority; and San Antonio Water System, developed, calibrated, and tested a Hydrological Simulation Program-FORTRAN (HSPF) watershed model to simulate streamflow and suspended-sediment concentrations and loads during 1958-2010 in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary in south Texas. Data available to simulate suspended-sediment concentrations and loads consisted of historical sediment data collected during 1942-82 in the study area and suspended-sediment concentration data collected periodically by the USGS during 2006-7 and 2010 at three USGS streamflow-gaging stations (08211000 Nueces River near Mathis, Tex. [the Mathis gage], 08211200 Nueces River at Bluntzer, Tex. [the Bluntzer gage], and 08211500 Nueces River at Calallen, Tex. [the Calallen gage]), and at one ungaged location on a Nueces River tributary (USGS station 08211050 Bayou Creek at Farm Road 666 near Mathis, Tex.). The Mathis gage is downstream from Wesley E. Seale Dam, which was completed in 1958 to impound Lake Corpus Christi. Suspended-sediment data collected before and after completion of Wesley E. Seale Dam provide insights to the effects of the dam and reservoir on suspended-sediment loads transported by the lower Nueces River downstream from the dam to the Nueces Estuary. Annual suspended-sediment loads at the Nueces River near the Mathis, Tex., gage were considerably lower for a given annual mean discharge after the dam was completed than before the dam was completed.
\nMost of the suspended sediment transported by the Nueces River downstream from Wesley E. Seale Dam occurred during high-flow releases from the dam or during floods. During October 1964-September 1971, about 536,000 tons of suspended sediment were transported by the Nueces River past the Mathis gage. Of this amount, about 473,000 tons, or about 88 percent, were transported by large runoff events (mean streamflow exceeding 1,000 cubic feet per second).
\nTo develop the watershed model to simulate suspended-sediment concentrations and loads in the lower Nueces River watershed during 1958-2010, streamflow simulations were calibrated and tested with available data for 2001-10 from the Bluntzer and Calallen gages. Streamflow data for the Nueces River obtained from the Mathis gage were used as input to the model at the upstream boundary of the model. Simulated streamflow volumes for the Bluntzer and Calallen gages showed good agreement with measured streamflow volumes. For 2001-10, simulated streamflow at the Calallen gage was within 3 percent of measured streamflow.
\nThe HSPF model was calibrated to simulate suspended sediment using suspended-sediment data collected at the Mathis, Bluntzer, and Calallen gages during 2006-7. Model simulated suspended-sediment loads at the Calallen gage were within 5 percent of loads that were estimated, by regression, from suspended-sediment sample analysis and measured streamflow. The calibrated watershed model was used to estimate streamflow and suspended-sediment loads for 1958-2010, including loads transported to the Nueces Estuary. During 1958-2010, on average, an estimated 288 tons per day (tons/d) of suspended sediment were delivered to the lower Nueces River; an estimated 278 tons/d were delivered to the estuary. The annual suspended-sediment load was highly variable, depending on the occurrence of runoff events and high streamflows. During 1958-2010, the annual total sediment loads to the estuary varied from an estimated 3.8 to 2,490 tons/d. On average, 113 tons/d, or about 39 percent of the estimated annual suspended-sediment contribution, originated from cropland in the study watershed. Releases from Lake Corpus Christi delivered an estimated 94 tons/d of suspended sediment or about 33 percent of the 288 tons/d estimated to have been delivered to the lower Nueces River. Erosion of stream-channel bed and banks accounted for 44 tons/d or about 15 percent of the estimated total suspended-sediment load. All other land categories, except cropland, accounted for an estimated 36 tons/d, or about 12 percent of the total. An estimated 10 tons/d of suspended sediment or about 3 percent of the suspended-sediment load delivered to the lower Nueces River were removed by water withdrawals before reaching the Nueces Estuary.
\nDuring 2010, additional suspended-sediment data were collected during selected runoff events to provide new data for model testing and to help better understand the sources of suspended-sediment loads. The model was updated and used to estimate and compare sediment yields from each of 64 subwatersheds comprising the lower Nueces River watershed study area for three selected runoff events: November 20-21, 2009, September 7-8, 2010, and September 20-21, 2010. These three runoff events were characterized by heavy rainfall centered near the study area and during which minimal streamflow and suspended-sediment load entered the lower Nueces River upstream from Wesley E. Seale Dam. During all three runoff events, model simulations showed that the greatest sediment yields originated from the subwatersheds, which were largely cropland. In particular, the Bayou Creek subwatersheds were major contributors of suspended-sediment load to the lower Nueces River during the selected runoff events. During the November 2009 runoff event, high suspended-sediment concentrations in the Nueces River water withdrawn for the City of Corpus Christi public-water supply caused problems during the water-treatment process, resulting in failure to meet State water-treatment standards for turbidity in drinking water. Model simulations of the November 2009 runoff event showed that the Bayou Creek subwatersheds were the primary source of suspended-sediment loads during that runoff event.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135059","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe-Blanco River Authority; San Antonio River Authority; and San Antonio Water System","usgsCitation":"Ockerman, D.J., Heitmuller, F.T., and Wehmeyer, L.L., 2013, Sources of suspended-sediment loads in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary, south Texas, 1958–2010: U.S. Geological Survey Scientific Investigations Report 2013-5059, ix, 57 p., https://doi.org/10.3133/sir20135059.","productDescription":"ix, 57 p.","numberOfPages":"67","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":271052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135059.gif"},{"id":271053,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5059/"},{"id":271054,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5059/pdf/sir2013-5059.pdf"}],"country":"United States","state":"Texas","otherGeospatial":"Lower Nueces River Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.15,27.72 ], [ -98.15,28.26 ], [ -97.15,28.26 ], [ -97.15,27.72 ], [ -98.15,27.72 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"517107dee4b0053160634243","contributors":{"authors":[{"text":"Ockerman, Darwin J. 0000-0003-1958-1688 ockerman@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":1579,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","email":"ockerman@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heitmuller, Franklin T.","contributorId":67476,"corporation":false,"usgs":true,"family":"Heitmuller","given":"Franklin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":477572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wehmeyer, Loren L.","contributorId":90412,"corporation":false,"usgs":true,"family":"Wehmeyer","given":"Loren","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":477573,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70125479,"text":"70125479 - 2013 - Managing bay and estuarine ecosystems for multiple services","interactions":[],"lastModifiedDate":"2014-09-18T13:28:32","indexId":"70125479","displayToPublicDate":"2013-04-17T13:27:19","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Managing bay and estuarine ecosystems for multiple services","docAbstract":"Managers are moving from a model of managing individual sectors, human activities, or ecosystem services to an ecosystem-based management (EBM) approach which attempts to balance the range of services provided by ecosystems. Applying EBM is often difficult due to inherent tradeoffs in managing for different services. This challenge particularly holds for estuarine systems, which have been heavily altered in most regions and are often subject to intense management interventions. Estuarine managers can often choose among a range of management tactics to enhance a particular service; although some management actions will result in strong tradeoffs, others may enhance multiple services simultaneously. Management of estuarine ecosystems could be improved by distinguishing between optimal management actions for enhancing multiple services and those that have severe tradeoffs. This requires a framework that evaluates tradeoff scenarios and identifies management actions likely to benefit multiple services. We created a management action-services matrix as a first step towards assessing tradeoffs and providing managers with a decision support tool. We found that management actions that restored or enhanced natural vegetation (e.g., salt marsh and mangroves) and some shellfish (particularly oysters and oyster reef habitat) benefited multiple services. In contrast, management actions such as desalination, salt pond creation, sand mining, and large container shipping had large net negative effects on several of the other services considered in the matrix. Our framework provides resource managers a simple way to inform EBM decisions and can also be used as a first step in more sophisticated approaches that model service delivery.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Estuaries and Coasts","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Estuarine Research Federation","publisherLocation":"Port Republic, MD","doi":"10.1007/s12237-013-9602-7","usgsCitation":"Needles, L.A., Lester, S.E., Ambrose, R., Andren, A., Beyeler, M., Connor, M.S., Eckman, J.E., Costa-Pierce, B.A., Gaines, S.D., Lafferty, K.D., Lenihan, J.S., Parrish, J., Peterson, M.S., Scaroni, A.E., Weis, J.S., and Wendt, D.E., 2013, Managing bay and estuarine ecosystems for multiple services: Estuaries and Coasts, 14 p., https://doi.org/10.1007/s12237-013-9602-7.","productDescription":"14 p.","numberOfPages":"14","ipdsId":"IP-044843","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294014,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12237-013-9602-7"}],"noUsgsAuthors":false,"publicationDate":"2013-04-17","publicationStatus":"PW","scienceBaseUri":"541bf43ce4b0e96537ddf762","contributors":{"authors":[{"text":"Needles, Lisa A.","contributorId":20266,"corporation":false,"usgs":true,"family":"Needles","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":501479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lester, Sarah E.","contributorId":61689,"corporation":false,"usgs":true,"family":"Lester","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":501486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ambrose, Richard","contributorId":84675,"corporation":false,"usgs":true,"family":"Ambrose","given":"Richard","affiliations":[],"preferred":false,"id":501491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andren, Anders","contributorId":42151,"corporation":false,"usgs":true,"family":"Andren","given":"Anders","email":"","affiliations":[],"preferred":false,"id":501482,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beyeler, Marc","contributorId":28546,"corporation":false,"usgs":true,"family":"Beyeler","given":"Marc","email":"","affiliations":[],"preferred":false,"id":501480,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Connor, Michael S.","contributorId":82237,"corporation":false,"usgs":true,"family":"Connor","given":"Michael","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":501490,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eckman, James E.","contributorId":42900,"corporation":false,"usgs":true,"family":"Eckman","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":501483,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Costa-Pierce, Barry A.","contributorId":80598,"corporation":false,"usgs":true,"family":"Costa-Pierce","given":"Barry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":501489,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gaines, Steven D.","contributorId":47708,"corporation":false,"usgs":true,"family":"Gaines","given":"Steven","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":501484,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501476,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lenihan, Junter S.","contributorId":6777,"corporation":false,"usgs":true,"family":"Lenihan","given":"Junter","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":501477,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Parrish, Julia","contributorId":39708,"corporation":false,"usgs":true,"family":"Parrish","given":"Julia","affiliations":[],"preferred":false,"id":501481,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Peterson, Mark S.","contributorId":8979,"corporation":false,"usgs":true,"family":"Peterson","given":"Mark","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":501478,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Scaroni, Amy E.","contributorId":68235,"corporation":false,"usgs":true,"family":"Scaroni","given":"Amy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":501487,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Weis, Judith S.","contributorId":71080,"corporation":false,"usgs":true,"family":"Weis","given":"Judith","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":501488,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wendt, Dean E.","contributorId":53716,"corporation":false,"usgs":true,"family":"Wendt","given":"Dean","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":501485,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70045060,"text":"tm12B1 - 2013 - SLAMMER: Seismic LAndslide Movement Modeled using Earthquake Records","interactions":[],"lastModifiedDate":"2014-12-09T10:42:54","indexId":"tm12B1","displayToPublicDate":"2013-04-17T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"12-B1","title":"SLAMMER: Seismic LAndslide Movement Modeled using Earthquake Records","docAbstract":"This program is designed to facilitate conducting sliding-block analysis (also called permanent-deformation analysis) of slopes in order to estimate slope behavior during earthquakes. The program allows selection from among more than 2,100 strong-motion records from 28 earthquakes and allows users to add their own records to the collection. Any number of earthquake records can be selected using a search interface that selects records based on desired properties. Sliding-block analyses, using any combination of rigid-block (Newmark), decoupled, and fully coupled methods, are then conducted on the selected group of records, and results are compiled in both graphical and tabular form. Simplified methods for conducting each type of analysis are also included.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B in Book 12","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm12B1","collaboration":"This report is Chapter 1 of Section B in Book 12.","usgsCitation":"Jibson, R.W., Rathje, E.M., Jibson, M.W., and Lee, Y.W., 2013, SLAMMER: Seismic LAndslide Movement Modeled using Earthquake Records (First posted April 16, 2013; Revised and reposted November 12, 2014, version 1.1): U.S. Geological Survey Techniques and Methods 12-B1, SLAMMER Installation File; ReadMe File, https://doi.org/10.3133/tm12B1.","productDescription":"SLAMMER Installation File; ReadMe File","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040038","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":271025,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm12b1.gif"},{"id":271024,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/tm/12b1/ReadMe.txt"},{"id":271023,"rank":2,"type":{"id":4,"text":"Application Site"},"url":"https://pubs.usgs.gov/tm/12b1/slammerinstall.jar"},{"id":271026,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/12b1/"}],"edition":"First posted April 16, 2013; Revised and reposted November 12, 2014, version 1.1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"516fb651e4b05024ef3cd3e4","contributors":{"authors":[{"text":"Jibson, Randall W. 0000-0003-3399-0875 jibson@usgs.gov","orcid":"https://orcid.org/0000-0003-3399-0875","contributorId":2985,"corporation":false,"usgs":true,"family":"Jibson","given":"Randall","email":"jibson@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":476704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rathje, Ellen M.","contributorId":9544,"corporation":false,"usgs":true,"family":"Rathje","given":"Ellen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":476705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jibson, Matthew W.","contributorId":69199,"corporation":false,"usgs":true,"family":"Jibson","given":"Matthew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":476707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, Yong W.","contributorId":20241,"corporation":false,"usgs":true,"family":"Lee","given":"Yong","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":476706,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045486,"text":"70045486 - 2013 - Modeling light use efficiency in a subtropical mangrove forest equipped with CO2 eddy covariance","interactions":[],"lastModifiedDate":"2013-04-19T14:02:26","indexId":"70045486","displayToPublicDate":"2013-04-16T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Modeling light use efficiency in a subtropical mangrove forest equipped with CO2 eddy covariance","docAbstract":"Despite the importance of mangrove ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these forests remain poorly understood. This limited understanding is partly a result of the challenges associated with in situ flux studies. Tower-based CO2 eddy covariance (EC) systems are installed in only a few mangrove forests worldwide, and the longest EC record from the Florida Everglades contains less than 9 years of observations. A primary goal of the present study was to develop a methodology to estimate canopy-scale photosynthetic light use efficiency in this forest. These tower-based observations represent a basis for associating CO2 fluxes with canopy light use properties, and thus provide the means for utilizing satellite-based reflectance data for larger scale investigations. We present a model for mangrove canopy light use efficiency utilizing the enhanced green vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that is capable of predicting changes in mangrove forest CO2 fluxes caused by a hurricane disturbance and changes in regional environmental conditions, including temperature and salinity. Model parameters are solved for in a Bayesian framework. The model structure requires estimates of ecosystem respiration (RE), and we present the first ever tower-based estimates of mangrove forest RE derived from nighttime CO2 fluxes. Our investigation is also the first to show the effects of salinity on mangrove forest CO2 uptake, which declines 5% per each 10 parts per thousand (ppt) increase in salinity. Light use efficiency in this forest declines with increasing daily photosynthetic active radiation, which is an important departure from the assumption of constant light use efficiency typically applied in satellite-driven models. The model developed here provides a framework for estimating CO2 uptake by these forests from reflectance data and information about environmental conditions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Copernicus Publications","publisherLocation":"Göttingen, Germany","doi":"10.5194/bg-10-2145-2013","usgsCitation":"Barr, J., Engel, V., Fuentes, J., Fuller, D., and Kwon, H., 2013, Modeling light use efficiency in a subtropical mangrove forest equipped with CO2 eddy covariance: Biogeosciences, v. 10, p. 2145-2158, https://doi.org/10.5194/bg-10-2145-2013.","productDescription":"9 p.","startPage":"2145","endPage":"2158","numberOfPages":"9","ipdsId":"IP-040912","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":473875,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-10-2145-2013","text":"Publisher Index Page"},{"id":271261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271260,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/bg-10-2145-2013"}],"country":"United States","volume":"10","noUsgsAuthors":false,"publicationDate":"2013-03-27","publicationStatus":"PW","scienceBaseUri":"51726790e4b0c173799e79fb","contributors":{"authors":[{"text":"Barr, J.G.","contributorId":101895,"corporation":false,"usgs":true,"family":"Barr","given":"J.G.","email":"","affiliations":[],"preferred":false,"id":477604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engel, V. 0000-0002-3858-7308","orcid":"https://orcid.org/0000-0002-3858-7308","contributorId":107905,"corporation":false,"usgs":true,"family":"Engel","given":"V.","affiliations":[],"preferred":false,"id":477605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuentes, J.D.","contributorId":8687,"corporation":false,"usgs":true,"family":"Fuentes","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":477601,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuller, D.O.","contributorId":83004,"corporation":false,"usgs":true,"family":"Fuller","given":"D.O.","email":"","affiliations":[],"preferred":false,"id":477603,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kwon, H.","contributorId":61317,"corporation":false,"usgs":true,"family":"Kwon","given":"H.","email":"","affiliations":[],"preferred":false,"id":477602,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045456,"text":"ofr20131073 - 2013 - Residential and service-population exposure to multiple natural hazards in the Mount Hood region of Clackamas County, Oregon","interactions":[],"lastModifiedDate":"2013-04-16T16:17:45","indexId":"ofr20131073","displayToPublicDate":"2013-04-16T00:00:00","publicationYear":"2013","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":"2013-1073","title":"Residential and service-population exposure to multiple natural hazards in the Mount Hood region of Clackamas County, Oregon","docAbstract":"The objective of this research is to document residential and service-population exposure to natural hazards in the rural communities of Clackamas County, Oregon, near Mount Hood. The Mount Hood region of Clackamas County has a long history of natural events that have impacted its small, tourism-based communities. To support preparedness and emergency-management planning in the region, a geospatial analysis of population exposure was used to determine the number and type of residents and service populations in flood-, wildfire-, and volcano-related hazard zones. Service populations are a mix of residents and tourists temporarily benefitting from local services, such as retail, education, or recreation. In this study, service population includes day-use visitors at recreational sites, overnight visitors at hotels and resorts, children at schools, and community-center visitors. Although the heavily-forested, rural landscape suggests few people are in the area, there are seasonal peaks of thousands of visitors to the region. “Intelligent” dasymetric mapping efforts using 30-meter resolution land-cover imagery and U.S. Census Bureau data proved ineffective at adequately capturing either the spatial distribution or magnitude of population at risk. Consequently, an address-point-based hybrid dasymetric methodology of assigning population to the physical location of buildings mapped with a global positioning system was employed. The resulting maps of the population (1) provide more precise spatial distributions for hazard-vulnerability assessments, (2) depict appropriate clustering due to higher density structures, such as apartment complexes and multi-unit commercial buildings, and (3) provide new information on the spatial distribution and temporal variation of people utilizing services within the study area.\n\nEstimates of population exposure to flooding, wildfire, and volcanic hazards were determined by using overlay analysis in a geographic information system. Population exposure to flood hazards is low (less than 10 percent of residents) and does not vary substantially between 100-year and 500-year flood-hazard scenarios. Moderate, moderate-to-high, and high wildfire-risk areas within the study region account for 72 percent of residents, 62 percent of employees, and 60 percent of daytime visitors to recreation sites. Fifteen percent of businesses in the study area are in moderate-to-high or high wildfire-risk areas but these businesses represent 51 percent of the local workforce. A volcanic event at Mount Hood could directly impact up to 60 percent of residents in their homes and 87 percent of employees at their workplaces. The proximal volcanic-hazard zone alone includes 65 percent of employees, 80 percent of schools and community facilities, more than 60 percent of overnight visitors in peak seasons, and 82–100 percent of daytime visitors to recreation sites during the summer and winter months, respectively. The number of day-use visitors to recreation sites in the region is greatest during winter months (averaging 129,300 people per month), whereas overnight visitors are greatest during summer months (averaging 34,000 per month). This analysis of residential and service-population exposure to natural hazards supports the development of targeted risk-reduction efforts in the region, while also expanding the discourse on characterizing and assessing population dynamics in tourist-frequented areas.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131073","collaboration":"Prepared in cooperation with the Clackamas County Emergency Management Department","usgsCitation":"Mathie, A., and Wood, N., 2013, Residential and service-population exposure to multiple natural hazards in the Mount Hood region of Clackamas County, Oregon: U.S. Geological Survey Open-File Report 2013-1073, iv, 48 p., https://doi.org/10.3133/ofr20131073.","productDescription":"iv, 48 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":271018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131073.jpg"},{"id":271017,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1073/pdf/ofr20131073.pdf"},{"id":271016,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1073/"}],"country":"United States","state":"Oregon","county":"Clackamas County","otherGeospatial":"Mount Hood","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.868,44.8857 ], [ -122.868,45.4617 ], [ -121.651,45.4617 ], [ -121.651,44.8857 ], [ -122.868,44.8857 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"516e64dbe4b00154e4368b6b","contributors":{"authors":[{"text":"Mathie, Amy M.","contributorId":82803,"corporation":false,"usgs":true,"family":"Mathie","given":"Amy M.","affiliations":[],"preferred":false,"id":477522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Nathan 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":71151,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":477521,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045399,"text":"cir1383A - 2013 - U.S. Geological Survey Climate and Land Use Change Science Strategy—A Framework for Understanding and Responding to Global Change","interactions":[],"lastModifiedDate":"2023-02-23T21:18:35.601132","indexId":"cir1383A","displayToPublicDate":"2013-04-15T17:35:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1383","chapter":"A","displayTitle":"U.S. Geological Survey climate and land use change science strategy—A framework for understanding and responding to global change","title":"U.S. Geological Survey Climate and Land Use Change Science Strategy—A Framework for Understanding and Responding to Global Change","docAbstract":"The U.S. Geological Survey (USGS), a nonregulatory Federal science agency with national scope and responsibilities, is uniquely positioned to serve the Nation’s needs in understanding and responding to global change, including changes in climate, water availability, sea level, land use and land cover, ecosystems, and global biogeochemical cycles. Global change is among the most challenging and formidable issues confronting our Nation and society. Scientists agree that global environmental changes during this century will have far-reaching societal implications (Intergovernmental Panel on Climate Change, 2007; U.S. Global Change Research Program, 2009). In the face of these challenges, the Nation can benefit greatly by using natural science information in decisionmaking.
Since the passage of the U.S. Global Change Research Act of 1990, the USGS has made substantial scientific contributions to understanding the interactive living and nonliving components of the Earth system. USGS natural science activities have led to fundamental advances in observing and understanding climate and land-cover change and the effects these changes have on ecosystems, natural-resource availability, and societal sustainability. Most of these major advances were pursued in partnership with other organizations within and outside the Department of the Interior. The inherent value of partnerships with other U.S. Global Change Research Program agencies and natural-resource managers is emphasized in all aspects of the planning and implementation of this Science Strategy for the coming decade.
Over the next 10 years, the USGS will make substantial contributions to understanding how Earth systems interact, respond to, and cause global change. The USGS will work with science partners, decisionmakers, and resource managers at local to international levels (including Native American tribes) to improve understanding of past and present change; develop relevant forecasts; and identify those lands, resources, and communities most vulnerable to global change processes. Science will play an essential role in helping communities and land and resource managers understand local to global implications, anticipate effects, prepare for changes, and reduce the risks associated with decisionmaking in a changing environment. USGS partners and stakeholders will benefit from the data, predictive models, and decision-support products and services resulting from the implementation of this strategy.
This Science Strategy recognizes core USGS strengths that are applied to key societal problems. It establishes seven goals for USGS global change science and strategic actions that may be implemented in the short term (1–5 years) and the longer term (5–10 years) to improve our understanding of the following areas of inquiry:
In addition to the seven thematic goals, we address the central role of monitoring in accordance with the USGS Science Strategy recommendation that global change research should rely on existing “…decades of observational data and long-term records to interpret consequences of climate variability and change to the Nation’s biological populations, ecosystems, and land and water resources” (U.S. Geological Survey, 2007, p. 19). We also briefly describe specific needs and opportunities for coordinating USGS global change science among USGS Mission Areas and address the need for a comprehensive and sustained communications strategy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1383A","usgsCitation":"Burkett, V.R., Kirtland, D.A., Taylor, I.L., Belnap, Jayne, Cronin, T.M., Dettinger, M.D., Frazier, E.L., Haines, J.W., Loveland, T.R., Milly, P.C.D., O’Malley, Robin, Thompson, R.S., Maule, A.G., McMahon, Gerard, and Striegl, R.G., 2013, U.S. Geological Survey climate and land use change science strategy—A framework for understanding and responding to global change: U.S. Geological Survey Circular 1383–A, 43 p.","productDescription":"viii, 43 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270884,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1383a/images/coverthb.gif"},{"id":270883,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1383a/circ1383-A.pdf","text":"Report","size":"20.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1383-A"}],"country":"United States","contact":"Land Resources
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192