Transient electromagnetic soundings were used to obtain information needed to refine hydrologic models of the San Luis Valley, Colorado. The soundings were able to map an aquitard called the blue clay that separates an unconfined surface aquifer from a deeper confined aquifer. The blue clay forms a conductor with an average resistivity of 6.9 ohm‐m. Above the conductor are found a mixture of gray clay and sand. The gray clay has an average resistivity of 21 ohm‐m, while the sand has a resistivity of greater than 100 ohm‐m. The large difference in resistivity of these units makes mapping them with a surface geophysical method relatively easy. The blue clay was deposited at the bottom of Lake Alamosa which filled most of the San Luis Valley during the Pleistocene. The geometry of the blue clay is influenced by a graben on the eastern side of the valley. The depth to the blue clay is greater over the graben. Along the eastern edge of valley the blue clay appears to be truncated by faults.
Hydrothermal systems currently are active near some gold deposits in northwestern Nevada. Possible links of these modern systems to gold mineralization were evaluated by chemically and isotopically analyzing water samples from the Brady, Dixie Valley, Humboldt House, San Emidio-Empire, Soda Lake, and Wabuska geothermal areas. In addition, quartz veins from Humboldt House and the adjacent Florida Canyon Mine were analyzed to compare ore and gangue phases with those predicted to form from proximal hydrothermal fluids.
Nearly all water samples are alkali-chloride-type. Total dissolved solids range from 800 to 3900 mg/L, and pH varies from 5.6 to 7.8. Geochemical modeling with SOLVEQ, WATCH, and CHILLER predict the precipitation of silica in all systems during cooling. Anhydrite, calcite, barite, pyrite, base-metal sulfides, and alumino-silicates are variably saturated at calculated reservoir temperatures and also precipitate during boiling/cooling of some fluids. Measured dissolved gold concentrations are low (<0.2μg/L), but are generally consistent with contents predicted by equilibrium of sampled solutions with elemental gold at reservoir temperatures. Although the modern geothermal waters can precipitate ore minerals, the low gold and other ore metal concentrations require very large fluid volumes to form a deposit of economic interest.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geological Society of Nevada Symposium, Great Basin Evolution and Metallogeny 2010","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geological Society of Nevada","usgsCitation":"Breit, G.N., Hunt, A.G., Wolf, R.E., Koenig, A.E., Fifarek, R., and Coolbaugh, M.F., 2010, Are modern geothermal waters in northwest Nevada forming epithermal gold deposits?, in Geological Society of Nevada Symposium, Great Basin Evolution and Metallogeny 2010, p. 833-844.","productDescription":"12 p.","startPage":"833","endPage":"844","ipdsId":"IP-020129","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595611c9e4b0d1f9f05067fe","contributors":{"authors":[{"text":"Breit, George N. 0000-0003-2188-6798 gbreit@usgs.gov","orcid":"https://orcid.org/0000-0003-2188-6798","contributorId":1480,"corporation":false,"usgs":true,"family":"Breit","given":"George","email":"gbreit@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolf, Ruth E. rwolf@usgs.gov","contributorId":903,"corporation":false,"usgs":true,"family":"Wolf","given":"Ruth","email":"rwolf@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koenig, Alan E. 0000-0002-5230-0924 akoenig@usgs.gov","orcid":"https://orcid.org/0000-0002-5230-0924","contributorId":1564,"corporation":false,"usgs":true,"family":"Koenig","given":"Alan","email":"akoenig@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":702472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fifarek, Richard","contributorId":193871,"corporation":false,"usgs":false,"family":"Fifarek","given":"Richard","email":"","affiliations":[],"preferred":false,"id":702476,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coolbaugh, Mark F.","contributorId":193870,"corporation":false,"usgs":false,"family":"Coolbaugh","given":"Mark","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":702475,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70190512,"text":"70190512 - 2010 - Composition, distribution, and potential toxicity of organochlorine mixtures in bed sediments of streams","interactions":[],"lastModifiedDate":"2017-09-05T13:59:12","indexId":"70190512","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Composition, distribution, and potential toxicity of organochlorine mixtures in bed sediments of streams","docAbstract":"Mixtures of organochlorine compounds have the potential for additive or interactive toxicity to organisms exposed in the stream. This study uses a variety of methods to identify mixtures and a modified concentration-addition approach to estimate their potential toxicity at 845 stream sites across the United States sampled between 1992 and 2001 for organochlorine pesticides and polychlorinated biphenyls (PCBs) in bed sediment. Principal-component (PC) analysis identified five PCs that account for 77% of the total variance in 14 organochlorine compounds in the original dataset. The five PCs represent: (1) chlordane-related compounds and dieldrin; (2) p,p′-DDT and its degradates; (3) o,p′-DDT and its degradates; (4) the pesticide degradates oxychlordane and heptachlor epoxide; and (5) PCBs. The PC analysis grouped compounds that have similar chemical structure (such as parent compound and degradate), common origin (in the same technical pesticide mixture), and(or) similar relation of concentrations to land use. For example, the highest concentrations of chlordane compounds and dieldrin occurred at urban sites, reflecting past use of parent pesticides for termite control. Two approaches to characterizing mixtures—PC-based mixtures and unique mixtures—were applied to all 299 samples with a detection of two or more organochlorine compounds. PC-based mixtures are defined by the presence (in the sample) of one or more compounds associated with that PC. Unique mixtures are defined as a specific combination of two or more compounds detected in a sample, regardless of how many other compounds were also detected in that sample. The simplest PC-based mixtures (containing compounds from 1 or 2 PCs) commonly occurred in a variety of land use settings. Complex mixtures (containing compounds from 3 or more PCs) were most common in samples from urban and mixed/urban sites, especially in the Northeast, reflecting high concentrations of multiple chlordane, dieldrin, DDT-related compounds, and(or) PCBs. The most commonly occurring unique mixture (p,p′-DDE, p,p′-DDD) occurred in both simple and complex PC-based mixtures, and at both urban and agricultural sites. Mean Probable Effect Concentration Quotients (PEC-Q) values, which estimate the potential toxicity of organochlorine contaminant mixtures, were highest for complex mixtures. Mean PEC-Q values were highest for urban sites in the Northeast, followed by mixed/urban sites in the Northeast and agricultural sites in cotton growing areas. These results demonstrate that the PEC-Q approach can be used in combination with PC-based and unique mixture analyses to relate potential aquatic toxicity of contaminant mixtures to mixture complexity, land use, and other surrogates for contaminant sources.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2009.09.052","usgsCitation":"Phillips, P., Nowell, L.H., Gilliom, R.J., Nakagaki, N., Riva-Murray, K., and VanAlstyne, C., 2010, Composition, distribution, and potential toxicity of organochlorine mixtures in bed sediments of streams: Science of the Total Environment, v. 408, no. 3, p. 594-606, https://doi.org/10.1016/j.scitotenv.2009.09.052.","productDescription":"13 p.","startPage":"594","endPage":"606","ipdsId":"IP-009456","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":345465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"408","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59afb7a0e4b0e9bde135114b","contributors":{"authors":[{"text":"Phillips, Patrick J. pjphilli@usgs.gov","contributorId":856,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick J.","email":"pjphilli@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":709537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":709538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilliom, Robert J. rgilliom@usgs.gov","contributorId":488,"corporation":false,"usgs":true,"family":"Gilliom","given":"Robert","email":"rgilliom@usgs.gov","middleInitial":"J.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":709539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nakagaki, Naomi 0000-0003-3653-0540 nakagaki@usgs.gov","orcid":"https://orcid.org/0000-0003-3653-0540","contributorId":1067,"corporation":false,"usgs":true,"family":"Nakagaki","given":"Naomi","email":"nakagaki@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":168876,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"VanAlstyne, Carolyn","contributorId":196180,"corporation":false,"usgs":false,"family":"VanAlstyne","given":"Carolyn","email":"","affiliations":[],"preferred":false,"id":709542,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70194333,"text":"70194333 - 2010 - A review of silver-rich mineral deposits and their metallogeny","interactions":[],"lastModifiedDate":"2017-11-29T11:16:19","indexId":"70194333","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"A review of silver-rich mineral deposits and their metallogeny","docAbstract":"Mineral deposits with large inventories or high grades of silver are found in four genetic groups: (1) volcanogenic massive sulfide (VMS), (2) sedimentary exhalative (SEDEX), (3) lithogene, and, (4) magmatichydrothermal. Principal differences between the four groups relate to source rocks and regions, metal associations, process and timing of mineralization, and tectonic setting. These four groups may be subdivided into specific metal associations on ternary diagrams based on relative metal contents.
The VMS deposits rarely contain more than 15,600 t Ag (500 Moz). Grades average 33 g/t Ag. Variable Ag- Pb-Zn-Cu-Au ± Sn concentrations are interpreted as having been derived both from shallow plutons and by leaching of the volcanic rock pile in regions of thin or no continental crust and the mineralization is syngenetic. Higher silver grades are associated with areas of abundant felsic volcanic rocks. The SEDEX deposits rarely contain more than 15,600 t Ag (500 Moz). Grades average 46 g/t Ag. Silver, lead, and zinc in relatively consistent proportions are leached from sedimentary rocks filling rift-related basins, where the continental crust is thin, and deposited as syngenetic to diagenetic massive sulfides. Pre-mineral volcanic rocks and their detritus may occur deep within the basin and gold is typically absent.
Lithogene silver-rich deposits are epigenetic products of varying combinations of compaction, dewatering, meteoric water recharge, and metamorphism of rift basin-related clastic sedimentary and interbedded volcanic rocks. Individual deposits may contain more than 15,600 t Ag (500 Moz) at high grades. Ores are characterized by four well-defined metal associations, including Ag, Ag-Pb-Zn, Ag-Cu, and Ag-Co-Ni-U. Leaching, transport, and deposition of metals may occur both in specific sedimentary strata and other rock types adjacent to the rift. Multiple mineralizing events lasting 10 to 15 m.y., separated by as much as 1 b.y., may occur in a single basin. Gold is absent at economic levels.
The magmatic-hydrothermal silver-rich deposits are epigenetic and related to cordilleran igneous and volcanic suites. Six magmatic-hydrothermal districts each contain more than 31,000 t Ag (1,000 Moz) with grades of veins >600 g/t Ag. Mineralization occurs as veins, massive sulfides in carbonate rocks, and disseminated deposits including porphyry silver deposits, a proposed exploration model. Most deposits are epithermal with low-sulfidation alteration assemblages. Deposits are often telescoped and well-zoned. All large and high-grade magmatic-hydrothermal deposits appear confined to regions of relatively thick continental crust above Cenozoic consuming plate margins on the eastern side of the Pacific Rim. Silver in these deposits may be partly derived by hydrothermal leaching of rocks under or adjacent to the deposits.
Specific metal associations in SEDEX and lithogene deposits may reflect confinement of fluid flow to and derivation of metals from specific source rock types. Variable metal associations in VMS and magmatichydrothermal deposits may reflect derivation of metals from a more diverse suite of rocks by convecting hydrothermal systems and processes related to the generation of magma. The discovery rate for silver-rich deposits has accelerated during the past decade, with new deposit types, metal associations, and exploration models being identified that provide numerous exploration and research opportunities.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The challenge of finding new mineral resources: Global metallogeny, innovative exploration, and new discoveries; SEG Special Publication 15 Vol. 1","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Society of Economic Geologists","usgsCitation":"Graybeal, F., and Vikre, P.G., 2010, A review of silver-rich mineral deposits and their metallogeny, chap. of The challenge of finding new mineral resources: Global metallogeny, innovative exploration, and new discoveries; SEG Special Publication 15 Vol. 1, p. 85-117.","productDescription":"33 p.","startPage":"85","endPage":"117","ipdsId":"IP-021427","costCenters":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":349514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349513,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.segweb.org/store/detail.aspx?id=EDOCSP15V1CH07"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a610acde4b06e28e9c256e1","contributors":{"authors":[{"text":"Graybeal, Frederick","contributorId":139000,"corporation":false,"usgs":false,"family":"Graybeal","given":"Frederick","email":"","affiliations":[{"id":12586,"text":"Consultant","active":true,"usgs":false}],"preferred":true,"id":723332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vikre, Peter G. 0000-0001-7895-5972 pvikre@usgs.gov","orcid":"https://orcid.org/0000-0001-7895-5972","contributorId":139033,"corporation":false,"usgs":true,"family":"Vikre","given":"Peter","email":"pvikre@usgs.gov","middleInitial":"G.","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":723331,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193761,"text":"70193761 - 2010 - Use of induced polarization to characterize the hydrogeologic framework of the zone of surface‐water/groundwater exchange at the Hanford 300 Area, WA","interactions":[],"lastModifiedDate":"2020-03-10T14:37:11","indexId":"70193761","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Use of induced polarization to characterize the hydrogeologic framework of the zone of surface‐water/groundwater exchange at the Hanford 300 Area, WA","docAbstract":"An extensive continuous waterborne electrical imaging (CWEI) survey was conducted along the Columbia River corridor adjacent to the U.S. Department of Energy (DOE) Hanford 300 Area, WA, in order to improve the conceptual model for exchange between surface water and U‐contaminated groundwater. The primary objective was to determine spatial variability in the depth to the Hanford‐Ringold (H‐R) contact, an important lithologic boundary that limits vertical transport of groundwater along the river corridor. Resistivity and induced polarization (IP) measurements were performed along six survey lines parallel to the shore (each greater than 2.5 km in length), with a measurement recorded every 0.5–3.0 m depending on survey speed, resulting in approximately 65,000 measurements. The H‐R contact was clearly resolved in images of the normalized chargeability along the river corridor due to the large contrast in surface area (hence polarizability) of the granular material between the two lithologic units. Cross sections of the lithologic structure along the river corridor reveal a large variation in the thickness of the overlying Hanford unit (the aquifer through which contaminated groundwater discharges to the river) and clearly identify locations along the river corridor where the underlying Ringold unit is exposed to the riverbed. Knowing the distribution of the Hanford and Ringold units along the river corridor substantially improves the conceptual model for the hydrogeologic framework regulating U exchange between groundwater and Columbia River water relative to current models based on projections of data from boreholes on land into the river.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Symposium on the Application of Geophysics to Engineering and Environmental Problems 2010","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.4133/1.3445539","usgsCitation":"Slater, L., Ntarlagiannis, D., Day-Lewis, F.D., Mwakanyamale, K., Lane, J.W., Ward, A., and Versteeg, R.J., 2010, Use of induced polarization to characterize the hydrogeologic framework of the zone of surface‐water/groundwater exchange at the Hanford 300 Area, WA, in Symposium on the Application of Geophysics to Engineering and Environmental Problems 2010, p. 955-960, https://doi.org/10.4133/1.3445539.","productDescription":"6 p.","startPage":"955","endPage":"960","ipdsId":"IP-018653","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":350805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Hanford 300 site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.28319931030273,\n 46.35699885440808\n ],\n [\n -119.26620483398438,\n 46.35699885440808\n ],\n [\n -119.26620483398438,\n 46.37547772047758\n ],\n [\n -119.28319931030273,\n 46.37547772047758\n ],\n [\n -119.28319931030273,\n 46.35699885440808\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2010-05-17","publicationStatus":"PW","scienceBaseUri":"5a719270e4b0a9a2e9dbde20","contributors":{"authors":[{"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":720289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ntarlagiannis, Dimitrios","contributorId":150729,"corporation":false,"usgs":false,"family":"Ntarlagiannis","given":"Dimitrios","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":720288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":720285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mwakanyamale, Kisa","contributorId":75847,"corporation":false,"usgs":true,"family":"Mwakanyamale","given":"Kisa","email":"","affiliations":[],"preferred":false,"id":726190,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":false,"id":720286,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ward, Andy","contributorId":7184,"corporation":false,"usgs":true,"family":"Ward","given":"Andy","email":"","affiliations":[],"preferred":false,"id":720287,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Versteeg, Roelof J.","contributorId":73501,"corporation":false,"usgs":true,"family":"Versteeg","given":"Roelof","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":720290,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70227339,"text":"70227339 - 2010 - Landscape-level impact of tropical forest loss and fragmentation on bird occurrence in eastern Guatemala","interactions":[],"lastModifiedDate":"2022-01-10T16:44:20.889201","indexId":"70227339","displayToPublicDate":"2009-12-04T10:34:03","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Landscape-level impact of tropical forest loss and fragmentation on bird occurrence in eastern Guatemala","docAbstract":"Tropical forest destruction and fragmentation of habitat patches may reduce population persistence at the landscape level. Given the complex nature of simultaneously evaluating the effects of these factors on biotic populations, statistical presence/absence modelling has become an important tool in conservation biology. This study uses logistic regression to evaluate the independent effects of tropical forest cover and fragmentation on bird occurrence in eastern Guatemala. Logistic regression models were constructed for 10 species with varying response to habitat alteration. Predictive variables quantified forest cover, fragmentation and their interaction at three different radii (200, 500 and 1000 m scales) of 112 points where presence of target species was determined. Most species elicited a response to the 1000 m scale, which was greater than most species’ reported territory size. Thus, their presence at the landscape scale is probably regulated by extra-territorial phenomena, such as dispersal. Although proportion of forest cover was the most important predictor of species’ presence, there was strong evidence of area-independent and -dependent fragmentation effects on species presence, results that contrast with other studies from northernmost latitudes. Species’ habitat breadth was positively correlated with AIC model values, indicating a better fit for species more restricted to tropical forest. Species with a narrower habitat breadth also elicited stronger negative responses to forest loss. Habitat breadth is thus a simple measure that can be directly related to species’ vulnerability to landscape modification. Model predictive accuracy was acceptable for 4 of 10 species, which were in turn those with narrower habitat breadths.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2009.10.038","usgsCitation":"Cerezo, A., Perelman, S., and Robbins, C.S., 2010, Landscape-level impact of tropical forest loss and fragmentation on bird occurrence in eastern Guatemala: Ecological Modelling, v. 221, no. 3, p. 512-526, https://doi.org/10.1016/j.ecolmodel.2009.10.038.","productDescription":"15 p.","startPage":"512","endPage":"526","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":394110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Guatemala","otherGeospatial":"Cerro San Gil Watershed Protection Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.02084350585938,\n 15.542345184874382\n ],\n [\n -88.60954284667967,\n 15.542345184874382\n ],\n [\n -88.60954284667967,\n 15.786967677939279\n ],\n [\n -89.02084350585938,\n 15.786967677939279\n ],\n [\n -89.02084350585938,\n 15.542345184874382\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"221","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cerezo, A.","contributorId":8201,"corporation":false,"usgs":true,"family":"Cerezo","given":"A.","email":"","affiliations":[],"preferred":false,"id":830517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perelman, Susana","contributorId":271044,"corporation":false,"usgs":false,"family":"Perelman","given":"Susana","email":"","affiliations":[],"preferred":false,"id":830518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robbins, Chandler S. crobbins@usgs.gov","contributorId":4275,"corporation":false,"usgs":true,"family":"Robbins","given":"Chandler","email":"crobbins@usgs.gov","middleInitial":"S.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":830519,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227365,"text":"70227365 - 2010 - Mercury flux to sediments of Lake Tahoe, California–Nevada","interactions":[],"lastModifiedDate":"2022-01-11T14:40:59.618352","indexId":"70227365","displayToPublicDate":"2009-11-04T08:31:35","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Mercury flux to sediments of Lake Tahoe, California–Nevada","docAbstract":"We report estimates of mercury (Hg) flux to the sediments of Lake Tahoe, California–Nevada: 2 and 15–20 µg/m2/year in preindustrial and modern sediments, respectively. These values result in a modern to preindustrial flux ratio of 7.5–10, which is similar to flux ratios recently reported for other alpine lakes in California, and greater than the value of 3 typically seen worldwide. We offer plausible hypotheses to explain the high flux ratios, including (1) proportionally less photoreduction and evasion of Hg with the onset of cultural eutrophication and (2) a combination of enhanced regional oxidation of gaseous elemental Hg and transport of the resulting reactive gaseous Hg to the surface with nightly downslope flows of air. If either of these mechanisms is correct, it could lead to local/regional solutions to lessen the impact of globally increasing anthropogenic emissions of Hg on Lake Tahoe and other alpine ecosystems.
","language":"English","publisher":"Springer","doi":"10.1007/s11270-009-0262-y","usgsCitation":"Drevnick, P.E., Shinneman, A.L., Lamborg, C.H., Engstrom, D., Bothner, M., and Oris, J.T., 2010, Mercury flux to sediments of Lake Tahoe, California–Nevada: Water, Air, & Soil Pollution, v. 210, p. 399-407, https://doi.org/10.1007/s11270-009-0262-y.","productDescription":"9 p.","startPage":"399","endPage":"407","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":475952,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/3923","text":"External Repository"},{"id":394181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Lake Tahoe","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.18630981445312,\n 38.89744587262311\n ],\n [\n -119.91302490234374,\n 38.89744587262311\n ],\n [\n -119.91302490234374,\n 39.28860847419942\n ],\n [\n -120.18630981445312,\n 39.28860847419942\n ],\n [\n -120.18630981445312,\n 38.89744587262311\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"210","noUsgsAuthors":false,"publicationDate":"2009-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Drevnick, Paul E.","contributorId":218351,"corporation":false,"usgs":false,"family":"Drevnick","given":"Paul","email":"","middleInitial":"E.","affiliations":[{"id":39814,"text":"Alberta Environment and Parks, Environmental Monitoring and Science Division","active":true,"usgs":false}],"preferred":false,"id":830602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shinneman, Avery L. C.","contributorId":271054,"corporation":false,"usgs":false,"family":"Shinneman","given":"Avery","email":"","middleInitial":"L. C.","affiliations":[],"preferred":false,"id":830603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamborg, Carl H.","contributorId":100307,"corporation":false,"usgs":true,"family":"Lamborg","given":"Carl","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":830604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engstrom, Daniel R","contributorId":220562,"corporation":false,"usgs":false,"family":"Engstrom","given":"Daniel R","affiliations":[{"id":15307,"text":"St. Croix Watershed Research Station, Science Museum of Minnesota","active":true,"usgs":false}],"preferred":false,"id":830605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bothner, Michael H. mbothner@usgs.gov","contributorId":139855,"corporation":false,"usgs":true,"family":"Bothner","given":"Michael H.","email":"mbothner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":830606,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oris, James T.","contributorId":179017,"corporation":false,"usgs":false,"family":"Oris","given":"James","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":830607,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208543,"text":"70208543 - 2010 - Monitoring and modelling landscape dynamics","interactions":[],"lastModifiedDate":"2020-02-20T10:06:36","indexId":"70208543","displayToPublicDate":"2009-10-20T12:38:49","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring and modelling landscape dynamics","docAbstract":"No abstract available.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-009-9417-x","usgsCitation":"Houet, T., Verburg, P.H., and Loveland, T., 2010, Monitoring and modelling landscape dynamics: Landscape Ecology, v. 25, no. 2, p. 163-167, https://doi.org/10.1007/s10980-009-9417-x.","productDescription":"5 p.","startPage":"163","endPage":"167","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":475954,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-009-9417-x","text":"Publisher Index Page"},{"id":372347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"2","noUsgsAuthors":false,"publicationDate":"2009-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Houet, Thomas","contributorId":167857,"corporation":false,"usgs":false,"family":"Houet","given":"Thomas","email":"","affiliations":[{"id":24840,"text":"University of Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":782369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verburg, Peter H.","contributorId":222519,"corporation":false,"usgs":false,"family":"Verburg","given":"Peter","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":782370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782371,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200490,"text":"70200490 - 2010 - Polychlorinated biphenyls, dioxins, furans, and organochlorine pesticides in belted kingfisher eggs from the upper Hudson River basin, New York, USA","interactions":[],"lastModifiedDate":"2018-11-20T12:45:25","indexId":"70200490","displayToPublicDate":"2009-10-02T10:49:48","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Polychlorinated biphenyls, dioxins, furans, and organochlorine pesticides in belted kingfisher eggs from the upper Hudson River basin, New York, USA","docAbstract":"Nesting belted kingfishers (hereafter kingfishers, Ceryle alcyon) were studied on the Hudson River near Fort Edward south to New Baltimore (NY, USA) and three nearby river drainages in 2004. Concentrations of 28 organochlorine pesticides, 160 polychlorinated biphenyl (PCB) congeners, and 17 dioxin and furan (PCDD‐F) congeners were quantified in kingfisher eggs. The pattern of organochlorine pesticides and PCDD‐F congeners did not differ significantly between 14 eggs collected from individual nests on the Hudson River and five eggs similarly collected on three other nearby rivers. In contrast, the pattern of PCB congeners in eggs collected on the Hudson River differed significantly from the other rivers. The differences in patterns of PCB congeners were associated with a higher representation of lower‐numbered congeners on the Hudson River than the other rivers. The higher prevalence of the lower‐numbered congeners and lower prevalence of the higher‐numbered congeners is consistent with Aroclor 1016 and 1242 being the source of the PCBs on the Hudson River. Concentrations in a sample egg collected at each nest were compared to nest survival and egg success (the proportion of eggs hatching in a clutch if at least one egg hatched) of the remaining eggs in the clutch. Models that predicted nest survival and egg success as functions of contaminant levels were poorly distinguished from models that presumed no such associations. Small sample sizes could have contributed to the inability to distinguish among contaminant and no toxicant models. However, we cannot rule out the possibility that contaminant concentrations on the Hudson River were not sufficiently high to demonstrate a relationship between contaminant concentrations and reproductive success in kingfishers.
","language":"English","publisher":"SETAC","doi":"10.1002/etc.26","usgsCitation":"Custer, T.W., Custer, C.M., and Gray, B.R., 2010, Polychlorinated biphenyls, dioxins, furans, and organochlorine pesticides in belted kingfisher eggs from the upper Hudson River basin, New York, USA: Environmental Toxicology and Chemistry, v. 29, no. 1, p. 99-110, https://doi.org/10.1002/etc.26.","productDescription":"12 p.","startPage":"99","endPage":"110","costCenters":[{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":475955,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.26","text":"Publisher Index Page"},{"id":358582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Hudson River","volume":"29","issue":"1","noUsgsAuthors":false,"publicationDate":"2010-01-01","publicationStatus":"PW","scienceBaseUri":"5bf52b6ce4b045bfcae28026","contributors":{"authors":[{"text":"Custer, Thomas W. 0000-0003-3170-6519 tcuster@usgs.gov","orcid":"https://orcid.org/0000-0003-3170-6519","contributorId":2835,"corporation":false,"usgs":true,"family":"Custer","given":"Thomas","email":"tcuster@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":749134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":749135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":749136,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192443,"text":"70192443 - 2010 - Effect of hypersaline cooling canals on aquifer salinization","interactions":[],"lastModifiedDate":"2017-10-25T15:39:36","indexId":"70192443","displayToPublicDate":"2009-10-02T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Effect of hypersaline cooling canals on aquifer salinization","docAbstract":"The combined effect of salinity and temperature on density-driven convection was evaluated in this study for a large (28 km2) cooling canal system (CCS) at a thermoelectric power plant in south Florida, USA. A two-dimensional cross-section model was used to evaluate the effects of hydraulic heterogeneities, cooling canal salinity, heat transport, and cooling canal geometry on aquifer salinization and movement of the freshwater/saltwater interface. Four different hydraulic conductivity configurations, with values ranging over several orders of magnitude, were evaluated with the model. For all of the conditions evaluated, aquifer salinization was initiated by the formation of dense, hypersaline fingers that descended downward to the bottom of the 30-m thick aquifer. Saline fingers reached the aquifer bottom in times ranging from a few days to approximately 5 years for the lowest hydraulic conductivity case. Aquifer salinization continued after saline fingers reached the aquifer bottom and coalesced by lateral movement away from the site. Model results showed that aquifer salinization was most sensitive to aquifer heterogeneity, but was also sensitive to CCS salinity, temperature, and configuration.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-009-0502-7","usgsCitation":"Hughes, J.D., Langevin, C.D., and Brakefield-Goswami, L., 2010, Effect of hypersaline cooling canals on aquifer salinization: Hydrogeology Journal, v. 18, p. 25-38, https://doi.org/10.1007/s10040-009-0502-7.","productDescription":"14 p.","startPage":"25","endPage":"38","ipdsId":"IP-010714","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":347401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","noUsgsAuthors":false,"publicationDate":"2009-08-12","publicationStatus":"PW","scienceBaseUri":"59f1a2abe4b0220bbd9d9fdb","contributors":{"authors":[{"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":715853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":715862,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brakefield-Goswami, Linzy","contributorId":198373,"corporation":false,"usgs":false,"family":"Brakefield-Goswami","given":"Linzy","email":"","affiliations":[],"preferred":false,"id":715861,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230291,"text":"70230291 - 2010 - Effects of temperature on silicate weathering: Solute fluxes and chemical weathering in a temperate rain forest watershed, Jamieson Creek, British Columbia","interactions":[],"lastModifiedDate":"2022-04-06T15:16:31.137286","indexId":"70230291","displayToPublicDate":"2009-09-22T10:09:41","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of temperature on silicate weathering: Solute fluxes and chemical weathering in a temperate rain forest watershed, Jamieson Creek, British Columbia","docAbstract":"Chemical weathering of silicate minerals has long been known as a sink for atmospheric CO2, and feedbacks between weathering and climate are believed to affect global climate. While warmer temperatures are believed to increase rates of weathering, weathering in cool climates can be accelerated by increased mineral exposure due to mechanical weathering by ice. In this study, chemical weathering of silicate minerals is investigated in a small temperate watershed. The Jamieson Creek watershed is covered by mature coniferous forest and receives high annual precipitation (4000 mm), mostly in the form of rainfall, and is underlain by quartz diorite bedrock and glacial till. Analysis of pore water concentration gradients indicates that weathering in hydraulically unsaturated ablation till is dominated by dissolution of plagioclase and hornblende. However, a watershed scale solute mass balance indicates high relative fluxes of K and Ca, indicating preferential leaching of these solutes possibly from the relatively unweathered lodgement till. Weathering rates for plagioclase and hornblende calculated from a watershed scale solute mass balance are similar in magnitude to rates determined using pore water concentration gradients.
When compared to the Rio Icacos basin in Puerto Rico, a pristine tropical watershed with similar annual precipitation and bedrock, but with dissimilar regolith properties, fluxes of weathering products in stream discharge from the warmer site are 1.8 to 16.2-fold higher, respectively, and regolith profile-averaged plagioclase weathering rates are 3.8 to 9.0-fold higher. This suggests that the Arrhenius effect, which predicts a 3.5- to 9-fold increase in the dissolution rate of plagioclase as temperature is increased from 3.4° to 22 °C, may explain the greater weathering fluxes and rates at the Rio Icacos site. However, more modest differences in K and Ca fluxes between the two sites are attributed to accelerated leaching of those solutes from glacial till at Jamieson Creek. Our findings suggest that under conditions of high rainfall and favorable topography, weathering rates of silicate minerals in warm tropical systems will tend to be higher than in cool temperate systems, even if the temperate system is has been perturbed by an episode of glaciation that deposits regolith high in fresh mineral surface area.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2009.09.005","usgsCitation":"Turner, B.F., White, A.F., and Brantley, S., 2010, Effects of temperature on silicate weathering: Solute fluxes and chemical weathering in a temperate rain forest watershed, Jamieson Creek, British Columbia: Chemical Geology, v. 369, no. 1-2, p. 62-78, https://doi.org/10.1016/j.chemgeo.2009.09.005.","productDescription":"17 p.","startPage":"62","endPage":"78","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":398223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"British Columbia","otherGeospatial":"Jamieson Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.09940338134764,\n 49.50269476415281\n ],\n [\n -123.00567626953125,\n 49.50269476415281\n ],\n [\n -123.00567626953125,\n 49.570649710591326\n ],\n [\n -123.09940338134764,\n 49.570649710591326\n ],\n [\n -123.09940338134764,\n 49.50269476415281\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"369","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Turner, Benjamin F.","contributorId":289845,"corporation":false,"usgs":false,"family":"Turner","given":"Benjamin","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":839886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Arthur F. afwhite@usgs.gov","contributorId":3718,"corporation":false,"usgs":true,"family":"White","given":"Arthur","email":"afwhite@usgs.gov","middleInitial":"F.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":839887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brantley, Susan L.","contributorId":38461,"corporation":false,"usgs":true,"family":"Brantley","given":"Susan L.","affiliations":[],"preferred":false,"id":839888,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208552,"text":"70208552 - 2010 - Addressing foundational elements of regional land-use change forecasting","interactions":[],"lastModifiedDate":"2022-09-08T17:22:22.467504","indexId":"70208552","displayToPublicDate":"2009-08-06T14:26:37","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Addressing foundational elements of regional land-use change forecasting","docAbstract":"Regional land-use models must address several foundational elements, including understanding geographic setting, establishing regional land-use histories, modeling process and representing drivers of change, representing local land-use patterns, managing issues of scale and complexity, and development of scenarios. Key difficulties include managing an array of biophysical and socioeconomic processes across multiple spatial and temporal scales, and acquiring and utilizing empirical data to support the analysis of those processes. The Southeastern and Pacific Northwest regions of the United States, two heavily forested regions with significant forest industries, are examined in the context of these foundational elements. Geographic setting fundamentally affects both the primary land cover (forest) in the two regions, and the structure and form of land use (forestry). Land-use histories of the regions can be used to parameterize land-use models, validate model performance, and explore land-use scenarios. Drivers of change in the two regions are many and varied, with issues of scale and complexity posing significant challenges. Careful scenario development can be used to simplify process-based land-use models, and can improve our ability to address specific research questions. The successful modeling of land-use change in these two areas requires integration of both top-down and bottom-up drivers of change, using scenario frameworks to both guide and simplify the modeling process. Modular approaches, with utilization and integration of existing process models, allow regional land-use modelers the opportunity to better represent primary drivers of land-use change. However, availability of data to represent driving forces remains a primary obstacle.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-009-9391-3","usgsCitation":"Sohl, T.L., Loveland, T., Sleeter, B.M., Sayler, K., and Barnes, C., 2010, Addressing foundational elements of regional land-use change forecasting: Landscape Ecology, v. 25, no. 2, p. 233-247, https://doi.org/10.1007/s10980-009-9391-3.","productDescription":"15 p.","startPage":"233","endPage":"247","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":372365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n 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loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":782444,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sayler, Kristi L. 0000-0003-2514-242X sayler@usgs.gov","orcid":"https://orcid.org/0000-0003-2514-242X","contributorId":2988,"corporation":false,"usgs":true,"family":"Sayler","given":"Kristi","email":"sayler@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782445,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnes, Christopher 0000-0002-4608-4364 christopher.barnes.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-4608-4364","contributorId":198908,"corporation":false,"usgs":true,"family":"Barnes","given":"Christopher","email":"christopher.barnes.ctr@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":782446,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70118928,"text":"70118928 - 2010 - Field evaluation of a two-dimensional hydrodynamic model near boulders for habitat calculation","interactions":[],"lastModifiedDate":"2017-01-11T16:08:27","indexId":"70118928","displayToPublicDate":"2009-06-24T11:24:35","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Field evaluation of a two-dimensional hydrodynamic model near boulders for habitat calculation","docAbstract":"Two-dimensional hydrodynamic models are now widely used in aquatic habitat studies. To test the sensitivity of calculated habitat outcomes to limitations of such a model and of typical field data, bathmetry, depth and velocity data were collected for three discharges in the vicinity of two large boulders in the South Platte River (Colorado) and used in the River2D model. Simulated depth and velocity were compared with observed values at 204 locations and the differences in habitat numbers produced by observed and simulated conditions were calculated. The bulk of the differences between simulated and observed depth and velocity values were found to lie within the likely error of measurement. However, the effect of flow simulation outliers on potential habitat outcomes must be considered when using 2D models for habitat simulation. Furthermore, the shape of the habitat suitability relation can influence the effects of simulation errors. Habitat relations with steep slopes in the velocity ranges found in similar study areas are expected to be sensitive to the magnitude of error found here. Comparison of habitat values derived from simulated and observed depth and velocity revealed a small tendency to under-predict habitat values.","language":"English","publisher":"Wiley","doi":"10.1002/rra.1278","usgsCitation":"Waddle, T., 2010, Field evaluation of a two-dimensional hydrodynamic model near boulders for habitat calculation: River Research and Applications, v. 26, no. 6, p. 730-741, https://doi.org/10.1002/rra.1278.","productDescription":"12 p.","startPage":"730","endPage":"741","numberOfPages":"12","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":475960,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.1278","text":"Publisher Index Page"},{"id":291486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"6","noUsgsAuthors":false,"publicationDate":"2009-06-24","publicationStatus":"PW","scienceBaseUri":"53db5843e4b0fba533fa357a","contributors":{"authors":[{"text":"Waddle, Terry","contributorId":47848,"corporation":false,"usgs":true,"family":"Waddle","given":"Terry","affiliations":[],"preferred":false,"id":497511,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97513,"text":"ds402 - 2010 - A Compilation of Spatial Datasets and Surface-Water and Ground-Water Data from the U.S. Geological Survey and Other Federal and Oklahoma State Agencies for the Kickapoo Tribe of Oklahoma","interactions":[],"lastModifiedDate":"2012-02-02T00:14:32","indexId":"ds402","displayToPublicDate":"2009-05-19T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"402","title":"A Compilation of Spatial Datasets and Surface-Water and Ground-Water Data from the U.S. Geological Survey and Other Federal and Oklahoma State Agencies for the Kickapoo Tribe of Oklahoma","docAbstract":"This report contains spatial datasets of natural and anthropogenic features and spatial datasets detailing surface-water, ground-water, and other types of environmental information collected in and surrounding Kickapoo Tribal Lands. Spatial datasets were compiled from Federal and Oklahoma State agencies. Surface-water, ground-water, and other types of environmental information of natural and anthropogenic features were compiled from USGS National Water Information System database, Oklahoma Department of Environmental Quality online Geographic Information System data viewer, Oklahoma Water Resources Board online Water Information Mapping System, and U.S. Environmental Protection Agency online Modernized STORET database.\r\n\r\nThese spatial datasets were compiled from many different sources with varying quality. Because of the different sources, features common to multiple layers may not overlay exactly. Users should check the metadata to determine proper use of these data. These data were not checked for accuracy or completeness. Should a question of accuracy or completeness arise, the user should contact the originator cited in the metadata. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ds402","collaboration":"Prepared by the U.S. Geological Survey in cooperation with the Kickapoo Tribe of Oklahoma Department of Environmental Programs","usgsCitation":"Mashburn, S., 2010, A Compilation of Spatial Datasets and Surface-Water and Ground-Water Data from the U.S. Geological Survey and Other Federal and Oklahoma State Agencies for the Kickapoo Tribe of Oklahoma: U.S. Geological Survey Data Series 402, 1 DVD; Downloads Directory, https://doi.org/10.3133/ds402.","productDescription":"1 DVD; Downloads Directory","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":126275,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_402.jpg"},{"id":13470,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/402/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4950e4b0b290850ef0b9","contributors":{"authors":[{"text":"Mashburn, Shana Lichelle","contributorId":51403,"corporation":false,"usgs":true,"family":"Mashburn","given":"Shana Lichelle","affiliations":[],"preferred":false,"id":302357,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70208542,"text":"70208542 - 2010 - Exploring subtle land use and land cover changes: A framework for future landscape studies","interactions":[],"lastModifiedDate":"2020-02-20T10:08:47","indexId":"70208542","displayToPublicDate":"2009-05-16T12:27:17","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Exploring subtle land use and land cover changes: A framework for future landscape studies","docAbstract":"Land cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling.
","language":"English","publisher":"Springer ","doi":"10.1007/s10980-009-9362-8","usgsCitation":"Houet, T., Loveland, T., Hubert-Moy, L., Gaucherel, C., Napton, D., Barnes, C., and Sayler, K., 2010, Exploring subtle land use and land cover changes: A framework for future landscape studies: Landscape Ecology, v. 25, no. 2, p. 249-266, https://doi.org/10.1007/s10980-009-9362-8.","productDescription":"18 p.","startPage":"249","endPage":"266","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":475961,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-00389832","text":"External Repository"},{"id":372346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"France, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -5.185546875,\n 47.249406957888446\n ],\n [\n -1.23046875,\n 47.249406957888446\n ],\n [\n -1.23046875,\n 49.095452162534826\n ],\n [\n -5.185546875,\n 49.095452162534826\n ],\n [\n -5.185546875,\n 47.249406957888446\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.140625,\n 43.02071359427862\n ],\n [\n -97.36083984375,\n 43.02071359427862\n ],\n [\n -97.36083984375,\n 44.071800467511565\n ],\n [\n -99.140625,\n 44.071800467511565\n ],\n [\n -99.140625,\n 43.02071359427862\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"2","noUsgsAuthors":false,"publicationDate":"2009-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Houet, Thomas","contributorId":167857,"corporation":false,"usgs":false,"family":"Houet","given":"Thomas","email":"","affiliations":[{"id":24840,"text":"University of Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":782362,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782363,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hubert-Moy, Laurence","contributorId":222517,"corporation":false,"usgs":false,"family":"Hubert-Moy","given":"Laurence","email":"","affiliations":[],"preferred":false,"id":782364,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaucherel, Cedric","contributorId":222518,"corporation":false,"usgs":false,"family":"Gaucherel","given":"Cedric","email":"","affiliations":[],"preferred":false,"id":782365,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Napton, Darrell","contributorId":176288,"corporation":false,"usgs":false,"family":"Napton","given":"Darrell","affiliations":[],"preferred":false,"id":782366,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnes, Christopher 0000-0002-4608-4364 christopher.barnes.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-4608-4364","contributorId":198908,"corporation":false,"usgs":true,"family":"Barnes","given":"Christopher","email":"christopher.barnes.ctr@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":782367,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sayler, Kristi L. 0000-0003-2514-242X sayler@usgs.gov","orcid":"https://orcid.org/0000-0003-2514-242X","contributorId":2988,"corporation":false,"usgs":true,"family":"Sayler","given":"Kristi","email":"sayler@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782368,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192884,"text":"70192884 - 2010 - Predicting unsaturated zone nitrogen mass balances in agricultural settings of the United States","interactions":[],"lastModifiedDate":"2022-09-08T17:30:43.44453","indexId":"70192884","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Predicting unsaturated zone nitrogen mass balances in agricultural settings of the United States","docAbstract":"Unsaturated zone N fate and transport were evaluated at four sites to identify the predominant pathways of N cycling: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard and cornfield (Zea mays L.) in the lower Merced River study basin, California; and corn–soybean [Glycine max (L.) Merr.] rotations in study basins at Maple Creek, Nebraska, and at Morgan Creek, Maryland. We used inverse modeling with a new version of the Root Zone Water Quality Model (RZWQM2) to estimate soil hydraulic and nitrogen transformation parameters throughout the unsaturated zone; previous versions were limited to 3-m depth and relied on manual calibration. The overall goal of the modeling was to derive unsaturated zone N mass balances for the four sites. RZWQM2 showed promise for deeper simulation profiles. Relative root mean square error (RRMSE) values for predicted and observed nitrate concentrations in lysimeters were 0.40 and 0.52 for California (6.5 m depth) and Nebraska (10 m), respectively, and index of agreement (d) values were 0.60 and 0.71 (d varies between 0 and 1, with higher values indicating better agreement). For the shallow simulation profile (1 m) in Maryland, RRMSE and d for nitrate were 0.22 and 0.86, respectively. Except for Nebraska, predictions of average nitrate concentration at the bottom of the simulation profile agreed reasonably well with measured concentrations in monitoring wells. The largest additions of N were predicted to come from inorganic fertilizer (153–195 kg N ha−1 yr−1 in California) and N fixation (99 and 131 kg N ha−1 yr−1 in Maryland and Nebraska, respectively). Predicted N losses occurred primarily through plant uptake (144–237 kg N ha−1 yr−1) and deep seepage out of the profile (56–102 kg N ha−1 yr−1). Large reservoirs of organic N (up to 17,500 kg N ha−1 m−1 at Nebraska) were predicted to reside in the unsaturated zone, which has implications for potential future transfer of nitrate to groundwater.
","language":"English","publisher":"Acsess","doi":"10.2134/jeq2009.0310","usgsCitation":"Nolan, B.T., Puckett, L., Ma, L., Green, C.T., Bayless, E.R., and Malone, R.W., 2010, Predicting unsaturated zone nitrogen mass balances in agricultural settings of the United States: Journal of Environmental Quality, v. 39, no. 3, p. 1051-1065, https://doi.org/10.2134/jeq2009.0310.","productDescription":"15 p.","startPage":"1051","endPage":"1065","ipdsId":"IP-013623","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":348668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Randall 0000-0002-0357-3635 ebayless@usgs.gov","orcid":"https://orcid.org/0000-0002-0357-3635","contributorId":1518,"corporation":false,"usgs":true,"family":"Bayless","given":"E.","email":"ebayless@usgs.gov","middleInitial":"Randall","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":721733,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Malone, Robert W.","contributorId":10347,"corporation":false,"usgs":false,"family":"Malone","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":721734,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171013,"text":"70171013 - 2010 - Monitoring and characterizing natural hazards with satellite InSAR imagery","interactions":[],"lastModifiedDate":"2021-01-08T16:39:36.991136","indexId":"70171013","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5089,"text":"Annals of GIS","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring and characterizing natural hazards with satellite InSAR imagery","docAbstract":"Interferometric synthetic aperture radar (InSAR) provides an all-weather imaging capability for measuring ground-surface deformation and inferring changes in land surface characteristics. InSAR enables scientists to monitor and characterize hazards posed by volcanic, seismic, and hydrogeologic processes, by landslides and wildfires, and by human activities such as mining and fluid extraction or injection. Measuring how a volcano's surface deforms before, during, and after eruptions provides essential information about magma dynamics and a basis for mitigating volcanic hazards. Measuring spatial and temporal patterns of surface deformation in seismically active regions is extraordinarily useful for understanding rupture dynamics and estimating seismic risks. Measuring how landslides develop and activate is a prerequisite to minimizing associated hazards. Mapping surface subsidence or uplift related to extraction or injection of fluids during exploitation of groundwater aquifers or petroleum reservoirs provides fundamental data on aquifer or reservoir properties and improves our ability to mitigate undesired consequences. Monitoring dynamic water-level changes in wetlands improves hydrological modeling predictions and the assessment of future flood impacts. In addition, InSAR imagery can provide near-real-time estimates of fire scar extents and fire severity for wildfire management and control. All-weather satellite radar imagery is critical for studying various natural processes and is playing an increasingly important role in understanding and forecasting natural hazards.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/19475681003700914","usgsCitation":"Lu, Z., Zhang, J., Zhang, Y., and Dzurisin, D., 2010, Monitoring and characterizing natural hazards with satellite InSAR imagery: Annals of GIS, v. 16, no. 1, p. 55-66, https://doi.org/10.1080/19475681003700914.","productDescription":"12 p.","startPage":"55","endPage":"66","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":488987,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/19475681003700914","text":"Publisher Index Page"},{"id":382027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576913dae4b07657d19ff1b6","contributors":{"authors":[{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":629537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Jixian","contributorId":36396,"corporation":false,"usgs":true,"family":"Zhang","given":"Jixian","affiliations":[],"preferred":false,"id":629538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Yonghong","contributorId":82563,"corporation":false,"usgs":true,"family":"Zhang","given":"Yonghong","email":"","affiliations":[],"preferred":false,"id":629539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dzurisin, Daniel 0000-0002-0138-5067 dzurisin@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-5067","contributorId":538,"corporation":false,"usgs":true,"family":"Dzurisin","given":"Daniel","email":"dzurisin@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":629540,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":79157,"text":"sim2899 - 2010 - Geologic map of Lassen Volcanic National Park and vicinity, California","interactions":[],"lastModifiedDate":"2022-04-14T19:09:33.427847","indexId":"sim2899","displayToPublicDate":"2006-09-20T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2899","title":"Geologic map of Lassen Volcanic National Park and vicinity, California","docAbstract":"The geologic map of Lassen Volcanic National Park (LVNP) and vicinity encompasses 1,905 km2 at the south end of the Cascade Range in Shasta, Lassen, Tehama, and Plumas Counties, northeastern California (fig. 1, sheet 3). The park includes 430 km2 of scenic volcanic features, glacially sculpted terrain, and the most spectacular array of thermal features in the Cascade Range. Interest in preserving the scenic wonders of the Lassen area as a national park arose in the early 1900s to protect it from commercial development and led to the establishment in 1907 of two small national monuments centered on Lassen Peak and Cinder Cone. The eruptions of Lassen Peak in 1914-15 were the first in the Cascade Range since widespread settling of the West in the late 1800s. Through the printed media, the eruptions aroused considerable public interest and inspired renewed efforts, which had languished since 1907, to establish a national park. In 1916, Lassen Volcanic National Park was established by combining the areas of the previously established national monuments and adjacent lands. The southernmost Cascade Range is bounded on the west by the Sacramento Valley and the Klamath Mountains, on the south by the Sierra Nevada, and on the east by the Basin and Range geologic provinces. Most of the map area is underlain by middle to late Pleistocene volcanic rocks; Holocene, early Pleistocene, and late Pliocene volcanic rocks (<3.5 m.y.) are less common. Paleozoic and Mesozoic rocks are inferred to underlie the volcanic deposits (Jachens and Saltus, 1983), but the nearest exposures of pre-Tertiary rocks are 15 km to the south, 9 km to the southwest, and 12 km to the west. Diller (1895) recognized the young volcanic geology and produced the first geologic map of the Lassen area. The map (sheet 1) builds on and extends geologic mapping by Williams (1932), Macdonald (1963, 1964, 1965), and Wilson (1961). The Lassen Peak area mapped by Christiansen and others (2002) and published in greater detail (1:24,000) was modified for inclusion here. Figure 2 (sheet 3) shows the mapping credit for previous work; figure 3 (sheet 3) shows locations discussed throughout the text. A CD-ROM entitled Database for the Geologic Map of Lassen Volcanic National Park and Vicinity, California accompanies the printed map (Muffler and others, 2010). The CD-ROM contains ESRI compatible geographic information system data files used to create the 1:50,000-scale geologic map, both geologic and topographic data and their associated metadata files, and printable versions of the geologic map and pamphlet as PDF formatted files. The 1:50,000-scale geologic map was compiled from 1:24,000-scale geologic maps of individual quadrangles that are also included in the CD-ROM. It also contains ancillary data that support the map including locations of rock samples selected for chemical analysis (Clynne and others, 2008) and radiometric dating, photographs of geologic features, and links to related data or web sites. Data contained in the CD-ROM are also available on this Web site. The southernmost Cascade Range consists of a regional platform of basalt and basaltic andesite, with subordinate andesite and sparse dacite. Nested within these regional rocks are 'volcanic centers', defined as large, long-lived, composite, calc-alkaline edifices erupting the full range of compositions from basalt to rhyolite, but dominated by andesite and dacite. Volcanic centers are produced by the focusing of basaltic flux from the mantle and resultant enhanced interaction of mafic magma with the crust. Collectively, volcanic centers mark the axis of the southernmost Cascade Range. The map area includes the entire Lassen Volcanic Center, parts of three older volcanic centers (Maidu, Dittmar, and Latour), and the products of regional volcanism (fig. 4, sheet 3). Terminology used for subdivision of the Lassen Volcanic Center has been modified from Clynne (1984, 1990).","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sim2899","usgsCitation":"Clynne, M.A., and Muffler, L.P., 2010, Geologic map of Lassen Volcanic National Park and vicinity, California: U.S. Geological Survey Scientific Investigations Map 2899, Report: iii, 95 p.; 3 Sheets: 58.00 × 42.00 inches or smaller; Database, https://doi.org/10.3133/sim2899.","productDescription":"Report: iii, 95 p.; 3 Sheets: 58.00 × 42.00 inches or smaller; Database","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":438843,"rank":101,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N23XJ6","text":"USGS data release","linkHelpText":"Database for the geologic map of Lassen Volcanic National Park and vicinity, California"},{"id":115898,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_2899.gif"},{"id":398747,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_94720.htm"},{"id":14411,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/2899/","linkFileType":{"id":5,"text":"html"}}],"scale":"50000","projection":"Lambert Conformal Conic projection","country":"United States","state":"California","otherGeospatial":"Lassen Volcanic National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.75,\n 40.3333\n ],\n [\n -121.125,\n 40.3333\n ],\n [\n -121.125,\n 40.6667\n ],\n [\n -121.75,\n 40.6667\n ],\n [\n -121.75,\n 40.3333\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b1ae4b07f02db6a867b","contributors":{"authors":[{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":289245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muffler, L.J. Patrick","contributorId":72739,"corporation":false,"usgs":false,"family":"Muffler","given":"L.J.","email":"","middleInitial":"Patrick","affiliations":[],"preferred":false,"id":289246,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":96233,"text":"96233 - 2010 - Stream network and stream segment temperature models software","interactions":[],"lastModifiedDate":"2018-12-21T08:48:12","indexId":"96233","displayToPublicDate":"2002-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Stream network and stream segment temperature models software","docAbstract":"This set of programs simulates steady-state stream temperatures throughout a dendritic stream network handling multiple time periods per year. The software requires a math co-processor and 384K RAM. Also included is a program (SSTEMP) designed to predict the steady state stream temperature within a single stream segment for a single time period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Fort Collins, CO","doi":"10.3133/96233","usgsCitation":"Bartholow, J., 2010, Stream network and stream segment temperature models software, HTML Document; Downloads Directory, https://doi.org/10.3133/96233.","productDescription":"HTML Document; Downloads Directory","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":347873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":350373,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencebase.gov/catalog/item/53ea4091e4b008eaa4f4c457","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b16e4b07f02db6a5271","contributors":{"authors":[{"text":"Bartholow, John","contributorId":81835,"corporation":false,"usgs":true,"family":"Bartholow","given":"John","affiliations":[],"preferred":false,"id":299299,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97524,"text":"ofr20091102 - 2009 - Modeling habitat of the desert tortoise (Gopherus agassizii) in the Mojave and parts of the Sonoran Deserts of California, Nevada, Utah, and Arizona","interactions":[],"lastModifiedDate":"2019-10-04T08:46:53","indexId":"ofr20091102","displayToPublicDate":"2019-10-03T14:15:00","publicationYear":"2009","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":"2009-1102","displayTitle":"Modeling Habitat of the Desert Tortoise (Gopherus agassizii) in the Mojave and Parts of the Sonoran Deserts of California, Nevada, Utah, and Arizona","title":"Modeling habitat of the desert tortoise (Gopherus agassizii) in the Mojave and parts of the Sonoran Deserts of California, Nevada, Utah, and Arizona","docAbstract":"Habitat modeling is an important tool used to simulate the potential distribution of a species for a variety of basic and applied questions. The desert tortoise (Gopherus agassizii) is a federally listed threatened species in the Mojave Desert and parts of the Sonoran Desert of California, Nevada, Utah, and Arizona. Land managers in this region require reliable information about the potential distribution of desert tortoise habitat to plan conservation efforts, guide monitoring activities, monitor changes in the amount and quality of habitat available, minimize and mitigate disturbances, and ultimately to assess the status of the tortoise and its habitat toward recovery of the species. By applying information from the literature and our knowledge or assumptions of environmental variables that could potentially explain variability in the quality of desert tortoise habitat, we developed a quantitative habitat model for the desert tortoise using an extensive set of field-collected presence data. Sixteen environmental data layers were converted into a grid covering the study area and merged with the desert tortoise presence data that we gathered for input into the Maxent habitat-modeling algorithm. This model provides output of the statistical probability of habitat potential that can be used to map potential areas of desert tortoise habitat. This type of analysis, while robust in its predictions of habitat, does not account for anthropogenic changes that may have altered habitat with relatively high potential into areas with lower potential.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20091102","collaboration":"Prepared as a part of the Department of the Interior on the Landscape - Mojave Project for the Western Region, of the U.S. Geological Survey ","usgsCitation":"Nussear, K.E., Esque, T.C., Inman, R.D., Gass, Leila, Thomas, K.A., Wallace, C.S.A., Blainey, J.B., Miller, D.M., and Webb, R.H., 2009, Modeling habitat of the desert tortoise (Gopherus agassizii) in the Mojave and parts of the Sonoran Deserts of California, Nevada, Utah, and Arizona: U.S. Geological Survey Open-File Report 2009-1102, 18 p.","productDescription":"Report: iv, 18 p.; 2 Companion Files","numberOfPages":"18","additionalOnlineFiles":"Y","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":367969,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2009/1102/ofr20091102_dt_Habitat_Model.zip","size":"162 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Habitat Model"},{"id":195896,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2009/1102/coverthb.gif"},{"id":367970,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2009/1102/ofr20091102_Environmental_Layers.zip","size":"27.4 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Environmental Layers"},{"id":367968,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2009/1102/ofr20091102.pdf","text":"Report","size":"1.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2009-1102"}],"country":"United States","state":"California, Nevada, Utah, Arizona","otherGeospatial":"Mojave Desert, Sonoran Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.30029296875,\n 32.76880048488168\n ],\n [\n -109.2919921875,\n 32.76880048488168\n ],\n [\n -109.2919921875,\n 39.2492708462234\n ],\n [\n -120.30029296875,\n 39.2492708462234\n ],\n [\n -120.30029296875,\n 32.76880048488168\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Modoc Hall, Room 3006
Sacramento, CA 95819
Fishery-independent (FI) surveys provide critical information used for the sustainable management and conservation of fish populations. Because fisheries management often requires the effects of management actions to be evaluated and detected within a relatively short time frame, it is important that research be directed toward FI survey evaluation, especially with respect to the ability to detect temporal trends. Using annual FI gill-net survey data for Lake Erie walleyes Sander vitreus collected from 1978 to 2006 as a case study, our goals were to (1) highlight the usefulness of hierarchical models for estimating spatial and temporal sources of variation in catch per effort (CPE); (2) demonstrate how the resulting variance estimates can be used to examine the statistical power to detect temporal trends in CPE in relation to sample size, duration of sampling, and decisions regarding what data are most appropriate for analysis; and (3) discuss recommendations for evaluating FI surveys and analyzing the resulting data to support fisheries management. This case study illustrated that the statistical power to detect temporal trends was low over relatively short sampling periods (e.g., 5–10 years) unless the annual decline in CPE reached 10–20%. For example, if 50 sites were sampled each year, a 10% annual decline in CPE would not be detected with more than 0.80 power until 15 years of sampling, and a 5% annual decline would not be detected with more than 0.8 power for approximately 22 years. Because the evaluation of FI surveys is essential for ensuring that trends in fish populations can be detected over management-relevant time periods, we suggest using a meta-analysis–type approach across systems to quantify sources of spatial and temporal variation. This approach can be used to evaluate and identify sampling designs that increase the ability of managers to make inferences about trends in fish stocks.
","language":"English","publisher":"Taylor & Francis","doi":"10.1577/M08-197.1","usgsCitation":"Wagner, T., Vandergoot, C.S., and Tyson, J., 2009, Evaluating the power to detect temporal trends in fishery independent surveys: A case study based on Gillnets Set in the Ohio waters of Lake Erie for walleye: North American Journal of Fisheries Management, v. 29, no. 3, p. 805-816, https://doi.org/10.1577/M08-197.1.","productDescription":"11 p.","startPage":"805","endPage":"816","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-008027","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.5352783203125,\n 41.97174336327968\n ],\n [\n -80.540771484375,\n 42.32606244456202\n ],\n [\n -81.287841796875,\n 42.200038266046754\n ],\n [\n -82.40295410156249,\n 41.672911819602085\n ],\n [\n -82.6885986328125,\n 41.672911819602085\n ],\n [\n -83.067626953125,\n 41.86137915587359\n ],\n [\n -83.111572265625,\n 41.95131994679697\n ],\n [\n -83.4356689453125,\n 41.701627343789184\n ],\n [\n -82.9852294921875,\n 41.56203190200195\n ],\n [\n -82.99072265625,\n 41.46742831254425\n ],\n [\n -82.913818359375,\n 41.40153558289846\n ],\n [\n -82.7490234375,\n 41.422134246213616\n ],\n [\n -82.6611328125,\n 41.44684402008925\n ],\n [\n -82.45788574218749,\n 41.347948493443546\n ],\n [\n -82.0458984375,\n 41.492120839687786\n ],\n [\n -81.88110351562499,\n 41.44272637767212\n ],\n [\n -81.6888427734375,\n 41.44684402008925\n ],\n [\n -81.3262939453125,\n 41.7180304600481\n ],\n [\n -81.1285400390625,\n 41.79179268262892\n ],\n [\n -80.804443359375,\n 41.87774145109676\n ],\n [\n -80.5352783203125,\n 41.97174336327968\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2009-06-01","publicationStatus":"PW","scienceBaseUri":"57651f33e4b07657d19c7898","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergoot, Christopher S.","contributorId":71849,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":639602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tyson, Jeff","contributorId":147298,"corporation":false,"usgs":false,"family":"Tyson","given":"Jeff","affiliations":[],"preferred":false,"id":639603,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041533,"text":"70041533 - 2009 - The observed relationship between wave conditions and beach response, Ocean Beach, San Francisco, CA","interactions":[],"lastModifiedDate":"2015-10-29T14:24:25","indexId":"70041533","displayToPublicDate":"2015-07-06T08:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"The observed relationship between wave conditions and beach response, Ocean Beach, San Francisco, CA","docAbstract":"Understanding how sandy beaches respond to storms is critical for effective sediment management and developing successful erosion mitigation efforts. However, only limited progress has been made in relating observed beach changes to wave conditions, with one of the major limiting factors being the lack of temporally dense beach topography and nearshore wave data in most studies. This study uses temporally dense beach topographic and offshore wave data to directly link beach response and wave forcing with generally good results. Ocean Beach is an open coast high-energy sandy beach located in San Francisco, CA, USA. From April 2004 through the end of 2008, 60 three-dimensional topographic beach surveys were conducted on approximately a monthly basis, with more frequent “short-term surveys during the winters of 2005-06 and 2006-07. Shoreline position data from the short-term surveys show good correlation with offshore wave height, period, and direction averaged over several days prior to the survey (mean R*=0.54 for entire beach). There is, however, considerable alongshore variation in model performance, with R- values ranging from 0.81 to 0.19 for individual sections of the beach. After wave height, the direction of wave approach was the most important factor in determining the response of the shoreline, followed by wave period. Our results indicate that an empirical predictive model of beach response to wave conditions at Ocean Beach is possible with frequent beach mapping and wave data, and that such a model could be useful to coastal managers.
","language":"English","publisher":"Coastal Education & Research Foundation","usgsCitation":"Hansen, J., and Barnard, P., 2009, The observed relationship between wave conditions and beach response, Ocean Beach, San Francisco, CA: Journal of Coastal Research, no. Special Issue 56, p. 1771-1775.","productDescription":"5 p.","startPage":"1771","endPage":"1775","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-011160","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":310776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","otherGeospatial":"Ocean Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.60604858398438,\n 37.505368263398104\n ],\n [\n -122.60604858398438,\n 37.804358908571395\n ],\n [\n -122.43301391601562,\n 37.804358908571395\n ],\n [\n -122.43301391601562,\n 37.505368263398104\n ],\n [\n -122.60604858398438,\n 37.505368263398104\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"Special Issue 56","publicComments":"Proceedings of the 10th International Coastal Symposium","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56334344e4b048076347eeed","contributors":{"authors":[{"text":"Hansen, J.E.","contributorId":11855,"corporation":false,"usgs":true,"family":"Hansen","given":"J.E.","email":"","affiliations":[],"preferred":false,"id":578725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, P.L.","contributorId":20527,"corporation":false,"usgs":true,"family":"Barnard","given":"P.L.","email":"","affiliations":[],"preferred":false,"id":578726,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70004127,"text":"70004127 - 2009 - Responses of stream nitrate and dissolved organic carbon loadings to hydrological forcing and climate change in an upland forest of the northeast USA","interactions":[],"lastModifiedDate":"2015-11-16T14:43:54","indexId":"70004127","displayToPublicDate":"2015-06-08T09:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Responses of stream nitrate and dissolved organic carbon loadings to hydrological forcing and climate change in an upland forest of the northeast USA","docAbstract":"[1] In coming decades, higher annual temperatures, increased growing season length, and increased dormant season precipitation are expected across the northeastern United States in response to anthropogenic forcing of global climate. We synthesized long-term stream hydrochemical data from the Sleepers River Research Watershed in Vermont, United States, to explore the relationship of catchment wetness to stream nitrate and DOC loadings. We modeled changes in growing season length and precipitation patterns to simulate future climate scenarios and to assess how stream nutrient loadings respond to climate change. Model results for the 2070–2099 time period suggest that stream nutrient loadings during both the dormant and growing seasons will respond to climate change. During a warmer climate, growing season stream fluxes (runoff +20%, nitrate +57%, and DOC +58%) increase as more precipitation (+28%) and quick flow (+39%) occur during a longer growing season (+43 days). During the dormant season, stream water and nutrient loadings decrease. Net annual stream runoff (+8%) and DOC loading (+9%) increases are commensurate with the magnitude of the average increase of net annual precipitation (+7%). Net annual stream water and DOC loadings are primarily affected by increased dormant season precipitation. In contrast, decreased annual loading of stream nitrate (−2%) reflects a larger effect of growing season controls on stream nitrate and the effects of lengthened growing seasons in a warmer climate. Our findings suggest that leaching of nitrate and DOC from catchment soils will be affected by anthropogenic climate forcing, thereby affecting the timing and magnitude of annual stream loadings in the northeastern United States.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2008JG000778","usgsCitation":"Sebestyen, S.D., Boyer, E.W., and Shanley, J.B., 2009, Responses of stream nitrate and dissolved organic carbon loadings to hydrological forcing and climate change in an upland forest of the northeast USA: Journal of Geophysical Research, v. 114, no. G2, 11 p., https://doi.org/10.1029/2008JG000778.","productDescription":"11 p.","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-006854","costCenters":[],"links":[{"id":475963,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2008jg000778","text":"Publisher Index Page"},{"id":311383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311382,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1029/2008JG000778/abstract"}],"country":"United States","state":"Vermont","otherGeospatial":"Sleepers River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.8890380859375,\n 44.10139306449849\n ],\n [\n -71.8890380859375,\n 44.896741421341964\n ],\n [\n -71.0101318359375,\n 44.896741421341964\n ],\n [\n -71.0101318359375,\n 44.10139306449849\n ],\n [\n -71.8890380859375,\n 44.10139306449849\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"114","issue":"G2","noUsgsAuthors":false,"publicationDate":"2009-04-07","publicationStatus":"PW","scienceBaseUri":"564b0c5be4b0ebfbef0d3183","contributors":{"authors":[{"text":"Sebestyen, Stephen D.","contributorId":107562,"corporation":false,"usgs":true,"family":"Sebestyen","given":"Stephen","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":579889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":579890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579891,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041566,"text":"70041566 - 2009 - Monitoring and modeling shoreline response due to shoreface nourishment on a high-energy coast","interactions":[],"lastModifiedDate":"2015-10-29T13:03:31","indexId":"70041566","displayToPublicDate":"2015-06-02T05:15:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring and modeling shoreline response due to shoreface nourishment on a high-energy coast","docAbstract":"Shoreface nourishment can be an efficient technique to feed sediment into the littoral zone without the order of magnitude cost increase incurred by directly nourishing the beach. An erosion hot spot at Ocean Beach in San Francisco, California, USA, threatens valuable public infrastructure as well as safe recreational use of the beach. In an effort to reduce the erosion at this location, a new beneficial reuse plan was implemented in May 2005 for the sediment dredged annually from the main shipping channel at the mouth of San Francisco Bay. From 2005 to 2007, approximately 230,000 m of sand was placed annually at depths between 9 and 14 m, in a location where strong tidal currents and open-ocean waves could potentially feed sediment onto the section of beach experiencing critical erosion. The evolution of the disposal mound and adjacent beach were monitored with 12 multibeam bathymetric surveys, and over 40 high-resolution beach topographic surveys. In addition, sediment transport processes were investigated using sediment grab samples, acoustic Doppler profilers, and two separate models: a cross-shore profile model (UNIBEST-TC) and a coastal area model (Delft3D). The results of the monitoring and modeling demonstrate that the disposal mound may be effective in dissipating wave energy striking this vulnerable stretch of coast with negligible shadowing effects, but a positive shoreline response can only be achieved by placing the sediment in water depths less than 5 m.
","language":"English","publisher":"Coastal Education & Research Foundation","usgsCitation":"Barnard, P.L., Erikson, L., and Hansen, J.E., 2009, Monitoring and modeling shoreline response due to shoreface nourishment on a high-energy coast: Journal of Coastal Research, no. Special Issue 56, p. 29-33.","productDescription":"5 p.","startPage":"29","endPage":"33","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-011076","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":310769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","otherGeospatial":"Fort Funston, Ocean Beach, Point Lobos","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.33251953125,\n 37.67947293019486\n ],\n [\n -122.05261230468751,\n 36.16448788632064\n ],\n [\n -121.343994140625,\n 36.50963615733049\n ],\n [\n -121.00341796874999,\n 36.92793899776678\n ],\n [\n -121.72302246093749,\n 37.67947293019486\n ],\n [\n -122.1844482421875,\n 38.190704293996504\n ],\n [\n -122.288818359375,\n 38.12591462924157\n ],\n [\n -123.33251953125,\n 37.67947293019486\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"Special Issue 56","publicComments":"Proceedings of the 10th International Coastal Symposium","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5633433ee4b048076347eed2","contributors":{"authors":[{"text":"Barnard, P. L.","contributorId":115273,"corporation":false,"usgs":true,"family":"Barnard","given":"P.","email":"","middleInitial":"L.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":578708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":3170,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":578709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, J. E.","contributorId":120364,"corporation":false,"usgs":true,"family":"Hansen","given":"J.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":578710,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157388,"text":"70157388 - 2009 - Estimating phosphorus concentrations following alum treatment using apparent settling velocity","interactions":[],"lastModifiedDate":"2018-02-06T12:36:14","indexId":"70157388","displayToPublicDate":"2015-06-01T05:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating phosphorus concentrations following alum treatment using apparent settling velocity","docAbstract":"he apparent settling velocity (Vs) is a term used in empirical, steady-state, mass-balance lake models to represent the net phosphorus flux from the water column. The Vollenweider (1969) mixed-reactor lake model was rearranged and used to calculate Vs values for total phosphorus (TP) for three lakes treated with alum to reduce the internal flux of P to the water column (Delavan Lake, Wisconsin; Lake Morey, Vermont; and West Twin Lake, Ohio). An analysis of Vs values was conducted using data from these three lakes for both the pre- and post-alum treated conditions. Analysis of Vs values for both the pre- and post-alum conditions in Lake Morey and West Twin Lake resulted in a post-treatment mean Vs value of 7 ± 2.0 m·yr−1. The effect of the alum treatment, although short-lived in Delavan Lake, resulted in a mean post-treatment Vs value of 3.4 ± 0.3 m·yr−1. The consistency in the post-treatment Vs values in Lake Morey and West Twin Lake is used to demonstrate a predictive analysis method for water column TP concentrations in lakes following a successful treatment of the anoxic sediment area with alum. Additional pre- and post-alum in-lake and watershed loading data are needed to advance this concept into a management model.
","language":"English","publisher":"North American Lake Management Society","doi":"10.1080/07438149909353949","usgsCitation":"Panuska, J., and Robertson, D.M., 2009, Estimating phosphorus concentrations following alum treatment using apparent settling velocity: Lake and Reservoir Management, v. 15, no. 1, p. 28-38, https://doi.org/10.1080/07438149909353949.","productDescription":"11 p.","startPage":"28","endPage":"38","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":475965,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/07438149909353949","text":"Publisher Index Page"},{"id":308376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio, Vermont, Wisconsin","otherGeospatial":"Lake Delevan, Lake Morey, West Twin 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