The 2004–2008 eruption of Mount St. Helens produced seven dacite spines mantled by cataclastic fault rocks, comprising an outer fault core and an inner damage zone. These fault rocks provide remarkable insights into the mechanical processes that accompany extrusion of degassed magma, insights that are useful in forecasting dome-forming eruptions. The outermost part of the fault core consists of finely comminuted fault gouge that is host to 1- to 3-mm-thick layers of extremely fine-grained slickenside-bearing ultracataclasite. Interior to the fault core, there is an ∼2-m-thick damage zone composed of cataclastic breccia and sheared dacite, and interior to the damage zone, there is massive to flow-banded dacite lava of the spine interior. Structures and microtextures indicate entirely brittle deformation, including rock breakage, tensional dilation, shearing, grain flow, and microfaulting, as well as gas and fluid migration through intergranular pores and fractures in the damage zone. Slickenside lineations and consistent orientations of Riedel shears indicate upward shear of the extruding spines against adjacent conduit wall rocks.
Paleomagnetic directions, demagnetization paths, oxide mineralogy, and petrology indicate that cataclasis took place within dacite in a solidified steeply dipping volcanic conduit at temperatures above 500 °C. Low water content of matrix glass is consistent with brittle behavior at these relatively high temperatures, and the presence of tridymite indicates solidification depths of <1 km. Cataclasis was coincident with the eruption’s seismogenic zone at <1.5 km.
More than a million small and low-frequency “drumbeat” earthquakes with coda magnitudes (Md) <2.0 and frequencies <5 Hz occurred during the 2004–2008 eruption. Our field data provide a means with which to estimate slip-patch dimensions for shear planes and to compare these with estimates of slip patches based on seismic moments and shear moduli for dacite rock and granular fault gouge. Based on these comparisons, we find that aseismic creep is achieved by micron-scale displacements on Riedel shears and by granular flow, whereas the drumbeat earthquakes require millimeter to centimeter displacements on relatively large (e.g., ∼1000 m2) slip patches, possibly along observed extensive principal shear zones within the fault core but probably not along the smaller Riedel shears. Although our field and structural data are compatible with stick-slip models, they do not rule out seismic and infrasound models that call on resonance of steam-filled fractures to generate the drumbeat earthquakes. We suggest that stick-slip and gas release processes may be coupled, and that regardless of the source mechanism, the distinctive drumbeat earthquakes are proving to be an effective precursor for dome-forming eruptions.
Our data document a continuous cycle of deformation along the conduit margins beginning with episodes of fracture in the damage zone and followed by transfer of motion to the fault core. We illustrate the cycle of deformation using a hypothetical cross section of the Mount St. Helens conduit, extending from the surface to the depth of magmatic solidification.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B30716.1","usgsCitation":"Pallister, J.S., Cashman, K.V., Hagstrum, J.T., Beeler, N.M., Moran, S.C., and Denlinger, R.P., 2013, Faulting within the Mount St. Helens conduit and implications for volcanic earthquakes: GSA Bulletin, v. 125, no. 3-4, p. 359-376, https://doi.org/10.1130/B30716.1.","productDescription":"18 p.","startPage":"359","endPage":"376","ipdsId":"IP-037093","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":348071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","volume":"125","issue":"3-4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-11-21","publicationStatus":"PW","scienceBaseUri":"59fc2eade4b0531197b27fe0","contributors":{"authors":[{"text":"Pallister, John S. 0000-0002-2041-2147 jpallist@usgs.gov","orcid":"https://orcid.org/0000-0002-2041-2147","contributorId":2024,"corporation":false,"usgs":true,"family":"Pallister","given":"John","email":"jpallist@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":719391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cashman, Katharine V.","contributorId":199542,"corporation":false,"usgs":false,"family":"Cashman","given":"Katharine","email":"","middleInitial":"V.","affiliations":[{"id":13025,"text":"Department of Geological Sciences, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":719394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagstrum, Jonathan T. 0000-0002-0689-280X jhag@usgs.gov","orcid":"https://orcid.org/0000-0002-0689-280X","contributorId":3474,"corporation":false,"usgs":true,"family":"Hagstrum","given":"Jonathan","email":"jhag@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":719390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beeler, Nicholas M. 0000-0002-3397-8481 nbeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-3397-8481","contributorId":2682,"corporation":false,"usgs":true,"family":"Beeler","given":"Nicholas","email":"nbeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":719392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moran, Seth C. 0000-0001-7308-9649 smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":548,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":719395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719393,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70154883,"text":"70154883 - 2013 - Evaluating methodological assumptions of a catch-curve survival estimation of unmarked precocial shorebird chickes","interactions":[],"lastModifiedDate":"2015-07-15T14:06:15","indexId":"70154883","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating methodological assumptions of a catch-curve survival estimation of unmarked precocial shorebird chickes","docAbstract":"Estimating productivity for precocial species can be difficult because young birds leave their nest within hours or days of hatching and detectability thereafter can be very low. Recently, a method for using a modified catch-curve to estimate precocial chick daily survival for age based count data was presented using Piping Plover (Charadrius melodus) data from the Missouri River. However, many of the assumptions of the catch-curve approach were not fully evaluated for precocial chicks. We developed a simulation model to mimic Piping Plovers, a fairly representative shorebird, and age-based count-data collection. Using the simulated data, we calculated daily survival estimates and compared them with the known daily survival rates from the simulation model. We conducted these comparisons under different sampling scenarios where the ecological and statistical assumptions had been violated. Overall, the daily survival estimates calculated from the simulated data corresponded well with true survival rates of the simulation. Violating the accurate aging and the independence assumptions did not result in biased daily survival estimates, whereas unequal detection for younger or older birds and violating the birth death equilibrium did result in estimator bias. Assuring that all ages are equally detectable and timing data collection to approximately meet the birth death equilibrium are key to the successful use of this method for precocial shorebirds.
","language":"English","publisher":"Waterbird Society","doi":"10.1675/063.036.0112","usgsCitation":"McGowan, C., and Gardner, B., 2013, Evaluating methodological assumptions of a catch-curve survival estimation of unmarked precocial shorebird chickes: Waterbirds, v. 36, no. 1, p. 82-87, https://doi.org/10.1675/063.036.0112.","productDescription":"6 p.","startPage":"82","endPage":"87","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038383","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473938,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.036.0112","text":"Publisher Index Page"},{"id":305766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55a78436e4b0183d66e45e88","contributors":{"authors":[{"text":"McGowan, Conor P. cmcgowan@usgs.gov","contributorId":145496,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":564310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":564875,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70157244,"text":"70157244 - 2013 - Tamarisk: Ecohydrology of a successful plant","interactions":[],"lastModifiedDate":"2025-12-31T16:48:33.87161","indexId":"70157244","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Tamarisk: Ecohydrology of a successful plant","docAbstract":"This chapter explores the ecohydrology of tamarisk, with particular emphasis on water use, salt tolerance, potential for salinizing flood plains, drought tolerance and rooting depths, and ecological interactions with native plants on western rivers. It presents the working hypothesis that tamarisk is adapted to water stress, with low to moderate water use that tends to replace mesic vegetation when conditions on flow-regulated rivers become unsuitable for those species, rather than as an invasive species that displaces and out-competes native species under all conditions. It includes data on the annualized rates of evapotranspiration, transpiration, and stomatal conductance by tamarisk stands on western US rivers. It also cites the lack of evidence that simply removing tamarisk from a riverbank will improve salinity or allow native mesic vegetation to return.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tamarix: A case study of ecological change in the American West","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Oxford University Press","publisherLocation":"New York, NY","doi":"10.1093/acprof:osobl/9780199898206.003.0005","usgsCitation":"Nagler, P.L., and Quigley, M.F., 2013, Tamarisk: Ecohydrology of a successful plant, chap. of Tamarix: A case study of ecological change in the American West, p. 63-84, https://doi.org/10.1093/acprof:osobl/9780199898206.003.0005.","productDescription":"22 p.","startPage":"63","endPage":"84","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026847","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":308133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55f94142e4b05d6c4e5013ad","contributors":{"editors":[{"text":"Sher, Anna","contributorId":112677,"corporation":false,"usgs":true,"family":"Sher","given":"Anna","affiliations":[],"preferred":false,"id":953196,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Quigley, Martin F.","contributorId":112538,"corporation":false,"usgs":true,"family":"Quigley","given":"Martin","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":953197,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":572389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quigley, Martin F.","contributorId":112538,"corporation":false,"usgs":true,"family":"Quigley","given":"Martin","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":572390,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70154989,"text":"70154989 - 2013 - Daily survival rate for nests and chicks of Least Terns (Sternula antillarum) at natural nest sites in South Carolina","interactions":[],"lastModifiedDate":"2016-11-30T14:40:52","indexId":"70154989","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Daily survival rate for nests and chicks of Least Terns (Sternula antillarum) at natural nest sites in South Carolina","docAbstract":"Although a species of conservation concern, little is known about the reproductive success of Least Terns (Sternula antillarum) throughout the southeastern USA where availability of natural beaches for nesting is limited. Daily survival rate (DSR) of nests and chicks was examined at four natural nesting sites in Cape Romain National Wildlife Refuge, South Carolina, 2009–2010. Measures of nest success (n = 257 nests) ranged from 0–93% among colony sites. The DSR of nests was primarily related to colony site, but year and estimates of predation risk also were related to DSR. Predation was the principal cause of identifiable nest loss, accounting for 47% of nest failures when the two years of data were pooled. The probability (± SE) of a chick surviving from hatching to fledging = 0.449 ± 0.01 (n = 92 chicks). DSR of chicks was negatively related to tide height and rainfall. Therefore, productivity of Least Terns is being lost during both the nesting and chick stage through a combination of biotic and abiotic factors that may prove difficult to fully mitigate or manage. Although natural nesting sites within Cape Romain National Wildlife Refuge intermittently produce successful nests, the consistency of productivity over the long term is still unknown. Given that the long term availability of anthropogenic nest sites (e.g., rooftops, dredge-spoil islands) for Least Terns is questionable, further research is required both locally and throughout the region to assess the extent to which natural sites act as population sources or sinks.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.036.0101","usgsCitation":"Brooks, G.L., Sanders, F.J., Gerard, P., and Jodice, P.G., 2013, Daily survival rate for nests and chicks of Least Terns (Sternula antillarum) at natural nest sites in South Carolina: Waterbirds, v. 36, no. 1, p. 1-10, https://doi.org/10.1675/063.036.0101.","productDescription":"10 p.","startPage":"1","endPage":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-035360","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":305899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","otherGeospatial":"Cape Romain National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.52796936035156,\n 33.00636021320537\n ],\n [\n -79.52796936035156,\n 33.09643121740349\n ],\n [\n -79.3267822265625,\n 33.09643121740349\n ],\n [\n -79.3267822265625,\n 33.00636021320537\n ],\n [\n -79.52796936035156,\n 33.00636021320537\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b0beaae4b09a3b01b53086","contributors":{"authors":[{"text":"Brooks, Gillian L.","contributorId":31033,"corporation":false,"usgs":true,"family":"Brooks","given":"Gillian","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":565335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanders, Felicia J.","contributorId":56574,"corporation":false,"usgs":false,"family":"Sanders","given":"Felicia","email":"","middleInitial":"J.","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":565336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerard, Patrick D.","contributorId":140181,"corporation":false,"usgs":false,"family":"Gerard","given":"Patrick D.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":565337,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":1119,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":564468,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191526,"text":"70191526 - 2013 - Implications of the Mw9.0 Tohoku-Oki earthquake for ground motion scaling with source, path, and site parameters","interactions":[],"lastModifiedDate":"2017-10-17T11:44:12","indexId":"70191526","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Implications of the Mw9.0 Tohoku-Oki earthquake for ground motion scaling with source, path, and site parameters","title":"Implications of the Mw9.0 Tohoku-Oki earthquake for ground motion scaling with source, path, and site parameters","docAbstract":"The Mw9.0 Tohoku-oki Japan earthquake produced approximately 2,000 ground motion recordings. We consider 1,238 three-component accelerograms corrected with component-specific low-cut filters. The recordings have rupture distances between 44 km and 1,000 km, time-averaged shear wave velocities of VS30 = 90 m/s to 1,900 m/s, and usable response spectral periods of 0.01 sec to >10 sec. The data support the notion that the increase of ground motions with magnitude saturates at large magnitudes. High-frequency ground motions demonstrate faster attenuation with distance in backarc than in forearc regions, which is only captured by one of the four considered ground motion prediction equations for subduction earthquakes. Recordings within 100 km of the fault are used to estimate event terms, which are generally positive (indicating model underprediction) at short periods and zero or negative (overprediction) at long periods. We find site amplification to scale minimally with VS30 at high frequencies, in contrast with other active tectonic regions, but to scale strongly with VS30 at low frequencies.
","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/1.4000115","usgsCitation":"Stewart, J.P., Midorikawa, S., Graves, R.W., Khodaverdi, K., Kishida, T., Miura, H., Bozorgnia, Y., and Campbell, K.W., 2013, Implications of the Mw9.0 Tohoku-Oki earthquake for ground motion scaling with source, path, and site parameters: Earthquake Spectra, v. 29, no. S1, p. S1-S21, https://doi.org/10.1193/1.4000115.","productDescription":"21 p.","startPage":"S1","endPage":"S21","ipdsId":"IP-042067","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":346689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"S1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-03-01","publicationStatus":"PW","scienceBaseUri":"59e71695e4b05fe04cd331f2","contributors":{"authors":[{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":712796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Midorikawa, Saburoh","contributorId":197120,"corporation":false,"usgs":false,"family":"Midorikawa","given":"Saburoh","email":"","affiliations":[],"preferred":false,"id":712797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Robert W. rwgraves@usgs.gov","contributorId":3149,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","middleInitial":"W.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":712798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Khodaverdi, Khatareh","contributorId":197119,"corporation":false,"usgs":false,"family":"Khodaverdi","given":"Khatareh","email":"","affiliations":[],"preferred":false,"id":712799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kishida, Tadahiro","contributorId":140538,"corporation":false,"usgs":false,"family":"Kishida","given":"Tadahiro","email":"","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":712800,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miura, Hiroyuki","contributorId":197118,"corporation":false,"usgs":false,"family":"Miura","given":"Hiroyuki","email":"","affiliations":[],"preferred":false,"id":712801,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bozorgnia, Yousef","contributorId":197121,"corporation":false,"usgs":false,"family":"Bozorgnia","given":"Yousef","email":"","affiliations":[],"preferred":false,"id":712802,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Campbell, Kenneth W.","contributorId":74391,"corporation":false,"usgs":false,"family":"Campbell","given":"Kenneth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":712803,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70148142,"text":"70148142 - 2013 - Factors influencing survival and mark retention in postmetamorphic boreal chorus frogs","interactions":[],"lastModifiedDate":"2015-05-27T13:58:03","indexId":"70148142","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1337,"text":"Copeia","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing survival and mark retention in postmetamorphic boreal chorus frogs","docAbstract":"The ability to track individual animals is crucial in many field studies and often requires applying marks to captured individuals. Toe clipping has historically been a standard marking method for wild amphibian populations, but more recent marking methods include visual implant elastomer and photo identification. Unfortunately, few studies have investigated the influence and effectiveness of marking methods for recently metamorphosed individuals and as a result little is known about this life-history phase for most amphibians. Our focus was to explore survival probabilities, mark retention, and mark migration in postmetamorphic Boreal Chorus Frogs (Psuedacris maculata) in a laboratory setting. One hundred forty-seven individuals were assigned randomly to two treatment groups or a control group. Frogs in the first treatment group were marked with visual implant elastomer, while frogs in the second treatment group were toe clipped. Growth and mortality were recorded for one year and resulting data were analyzed using known-fate models in Program MARK. Model selection results suggested that survival probabilities of frogs varied with time and showed some variation among marking treatments. We found that frogs with multiple toes clipped on the same foot had lower survival probabilities than individuals in other treatments, but individuals can be marked by clipping a single toe on two different feet without any mark loss or negative survival effects. Individuals treated with visual implant elastomer had a mark migration rate of 4% and mark loss rate of 6%, and also showed very little negative survival impacts relative to control individuals.
","language":"English","publisher":"The American Society of Ichthyologists and Herpetologists","doi":"10.1643/CH-12-129","usgsCitation":"Swanson, J.E., Bailey, L., Muths, E.L., and Funk, W.C., 2013, Factors influencing survival and mark retention in postmetamorphic boreal chorus frogs: Copeia, v. 2013, no. 4, p. 670-675, https://doi.org/10.1643/CH-12-129.","productDescription":"6 p.","startPage":"670","endPage":"675","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045724","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":300866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2013","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5566eac7e4b0d9246a9ec2e1","contributors":{"authors":[{"text":"Swanson, Jennifer E.","contributorId":140894,"corporation":false,"usgs":false,"family":"Swanson","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":547478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Larissa L.","contributorId":93183,"corporation":false,"usgs":true,"family":"Bailey","given":"Larissa L.","affiliations":[],"preferred":false,"id":547477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":547476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, W. Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":97589,"corporation":false,"usgs":false,"family":"Funk","given":"W.","email":"","middleInitial":"Chris","affiliations":[{"id":6998,"text":"Department of Biology, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":547479,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173893,"text":"70173893 - 2013 - Nestling diets and provisioning rates of sympatric Golden-fronted and Ladder-backed Woodpeckers","interactions":[],"lastModifiedDate":"2016-06-16T15:50:54","indexId":"70173893","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Nestling diets and provisioning rates of sympatric Golden-fronted and Ladder-backed Woodpeckers","docAbstract":"We examined comparative food use and provisioning of Golden-fronted (Melanerpes aurifrons) and Ladder-backed (Picoides scalaris) woodpeckers at the Rob and Bessie Welder Wildlife Foundation Refuge, in San Patricio County, Texas. We combined video surveillance and direct observations to monitor provisioning rates and identify items delivered by adult woodpeckers to nestlings. We collected 328 hours of data at Ladder-backed Woodpecker nest cavities and 230 hours of data at Golden-fronted Woodpecker nest cavities. Ladder-backed Woodpecker nestling diets consisted of 100% animal matter, comprised of invertebrate larvae (99%) and invertebrate adults (< 1%). Diets of Golden-fronted Woodpecker nestlings were also high in animal matter (77%) with more invertebrate adults (55%) and fewer invertebrate larvae (27%), but also included vegetable matter (16%). Morisita's measure of overlap suggested a relatively low dietary overlap of 31% between nestlings of these two sympatric woodpecker species. Foraging methods used by these species may explain their low dietary overlap and facilitate their coexistence.
","language":"English","publisher":"Bioone","doi":"10.1676/12-041.1","usgsCitation":"Schroeder, E.L., Boal, C.W., and Glasscock, S.N., 2013, Nestling diets and provisioning rates of sympatric Golden-fronted and Ladder-backed Woodpeckers: Wilson Journal of Ornithology, v. 128, no. 1, p. 188-192, https://doi.org/10.1676/12-041.1.","productDescription":"5 p.","startPage":"188","endPage":"192","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-039878","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":323797,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Rob and Bessie Welder Wildlife Foundation Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.44186401367186,\n 28.120438687101064\n ],\n [\n -97.45285034179688,\n 28.11014311115806\n ],\n [\n -97.45525360107422,\n 28.105297792243157\n ],\n [\n -97.44255065917967,\n 28.098635121405312\n ],\n [\n -97.42795944213867,\n 28.110445936323273\n ],\n [\n -97.44186401367186,\n 28.120438687101064\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"128","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5763cdb7e4b07657d19ba789","contributors":{"authors":[{"text":"Schroeder, Evonne L.","contributorId":172043,"corporation":false,"usgs":false,"family":"Schroeder","given":"Evonne","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":639408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":638897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glasscock, Selma N.","contributorId":172044,"corporation":false,"usgs":false,"family":"Glasscock","given":"Selma","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":639409,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70044195,"text":"fs20133011 - 2013 - Concentrations of chloride and sodium in groundwater in New Hampshire from 1960 through 2011","interactions":[],"lastModifiedDate":"2016-08-10T15:32:19","indexId":"fs20133011","displayToPublicDate":"2013-02-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3011","title":"Concentrations of chloride and sodium in groundwater in New Hampshire from 1960 through 2011","docAbstract":"Several studies from the 1970s and more recently (for example, Hall (1975), Daley and others (2009) and Mullaney (2009)) have found that concentrations of chloride and sodium in groundwater in New Hampshire have increased during the past 50 years. Increases likely are related to road salt and other anthropogenic sources, such as septic systems, wastewater, and contamination from landfills and salt-storage areas. According to water-quality data reported to the New Hampshire Department of Environmental Services (NHDES), about 100 public water systems (5 percent) in 2010 had at least one groundwater sample with chloride concentrations that were equal to or exceeded the U.S. Environmental Protection Agency (USEPA) secondary maximum contaminant level (SMCL) of 250 mg/L before the water was treated for public consumption. The SMCL for chloride is a measurement of potential cosmetic or aesthetic effects of chloride in water. High concentrations of chloride and sodium in drinking-water sources can be costly to remove.
\nA new cooperative study between the U.S. Geological Survey (USGS) and the NHDES (Medalie, 2012) assessed chloride and sodium levels in groundwater in New Hampshire from the 1960s through 2011. The purpose of the study was to integrate all data on concentrations of chloride and sodium from groundwater in New Hampshire available from various Federal and State sources, including from the NHDES, the New Hamsphire Department of Health and Human Services, the USGS, and the U.S. Environmental Protection SurveyAgency (USEPA), for public and private (domestic) wells and to organize the data into a database. Medalie (2012) explained the many assumptions and limitations of disparate data that were collected to meet wide-ranging objectives. This fact sheet summarizes the most important findings of the data.
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Hampshire\",\"nation\":\"USA \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51307c5fe4b04c194073ad93","contributors":{"authors":[{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475083,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70179674,"text":"70179674 - 2013 - Upper crustal structure of Alabama from regional magnetic and gravity data: Using geology to interpret geophysics, and vice versa","interactions":[],"lastModifiedDate":"2017-01-11T08:58:18","indexId":"70179674","displayToPublicDate":"2013-02-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Upper crustal structure of Alabama from regional magnetic and gravity data: Using geology to interpret geophysics, and vice versa","docAbstract":"Aeromagnetic and gravity data sets obtained for Alabama (United States) have been digitally merged and filtered to enhance upper-crustal anomalies. Beneath the Appalachian Basin in northwestern Alabama, broad deep-crustal anomalies of the continental interior include the Grenville front and New York–Alabama lineament (dextral fault). Toward the east and south, high-angle discordance between the northeast-trending Appalachians and the east-west–trending wedge of overlapping Mesozoic and Cenozoic Gulf Coastal Plain sediments reveals how bedrock geophysical signatures progressively change with deeper burial. High-frequency magnetic anomalies in the Appalachian deformed domain (ADD) correspond to amphibolites and mylonites outlining terranes, while broader, lower-amplitude domains include Paleozoic intrusive bodies and Grenville basement gneiss. Fundamental ADD structures (e.g., the Alexander City, Towaliga, and Goat Rock–Bartletts Ferry faults) can be traced southward beneath the Gulf Coastal Plain to the suture with Gondwanan crust of the Suwannee terrane. Within the ADD, there is clear magnetic distinction between Laurentian crust and the strongly linear, high-frequency magnetic highs of peri-Gondwanan (Carolina-Uchee) arc terranes. The contact (Central Piedmont suture) corresponds to surface exposures of the Bartletts Ferry fault. ADD magnetic and gravity signatures are truncated by the east-west–trending Altamaha magnetic low associated with the Suwannee suture. Arcuate northeast-trending magnetic linears of the Suwannee terrane reflect internal structure and Mesozoic failed-rift trends. Geophysical data can be used to make inferences on surface and subsurface geology and vice versa, which has applicability anywhere that bedrock is exposed or concealed beneath essentially non-magnetic sedimentary cover.
","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/GES00703.1","usgsCitation":"Steltenpohl, M.G., Horton, J.W., Hatcher, R., Zietz, I., Daniels, D.L., and Higgins, M.W., 2013, Upper crustal structure of Alabama from regional magnetic and gravity data: Using geology to interpret geophysics, and vice versa: Geosphere, v. 9, no. 4, p. 1044-1064, https://doi.org/10.1130/GES00703.1.","productDescription":"21 p.","startPage":"1044","endPage":"1064","ipdsId":"IP-026836","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":473941,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00703.1","text":"Publisher Index Page"},{"id":333036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"9","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"587724a2e4b0315b4c11fe82","contributors":{"authors":[{"text":"Steltenpohl, Mark G.","contributorId":178199,"corporation":false,"usgs":false,"family":"Steltenpohl","given":"Mark","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":658189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horton, J. Wright Jr. 0000-0001-6756-6365 whorton@usgs.gov","orcid":"https://orcid.org/0000-0001-6756-6365","contributorId":173694,"corporation":false,"usgs":true,"family":"Horton","given":"J.","suffix":"Jr.","email":"whorton@usgs.gov","middleInitial":"Wright","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":658186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hatcher, Robert D.","contributorId":178197,"corporation":false,"usgs":false,"family":"Hatcher","given":"Robert D.","affiliations":[],"preferred":false,"id":658187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zietz, Isidore","contributorId":178196,"corporation":false,"usgs":false,"family":"Zietz","given":"Isidore","affiliations":[],"preferred":false,"id":658184,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Daniels, David L. 0000-0003-0599-8036 dave@usgs.gov","orcid":"https://orcid.org/0000-0003-0599-8036","contributorId":1792,"corporation":false,"usgs":true,"family":"Daniels","given":"David","email":"dave@usgs.gov","middleInitial":"L.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":658185,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Higgins, Michael W.","contributorId":178198,"corporation":false,"usgs":false,"family":"Higgins","given":"Michael","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":658188,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70044170,"text":"ds709R - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-27T16:10:20","indexId":"ds709R","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","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":"709","chapter":"R","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dudkash mineral district, which has industrial mineral deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Dudkash) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Dudkash area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709R","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey; This report is Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709-R)","usgsCitation":"Davis, P.A., Arko, S.A., and Harbin, M., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme; 4 Index Maps; 16 Image Files; 16 Metadata Files; 1 Shapefile, https://doi.org/10.3133/ds709R.","productDescription":"HTML Document; Readme; 4 Index Maps; 16 Image Files; 16 Metadata Files; 1 Shapefile","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":268489,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/r/1_readme.txt"},{"id":268490,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/r/index_maps/index_maps.html"},{"id":268491,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/r/image_files/image_files.html"},{"id":268492,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/r/metadata/metadata.html"},{"id":268493,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/r/shapefiles/shapefiles.html"},{"id":268488,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/r/"},{"id":268494,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_R.png"}],"country":"Afghanistan","otherGeospatial":"Dudkash Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 58.0,29.0 ], [ 58.0,40.0 ], [ 77.0,40.0 ], [ 77.0,29.0 ], [ 58.0,29.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512f2afbe4b0cad81a732d7b","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":474970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":474971,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70044146,"text":"70044146 - 2013 - Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study","interactions":[],"lastModifiedDate":"2017-05-10T15:48:47","indexId":"70044146","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study","docAbstract":"Cross-calibration of satellite sensors permits the quantitative comparison of measurements obtained from different Earth Observing (EO) systems. Cross-calibration studies usually use simultaneous or near-simultaneous observations from several spaceborne sensors to develop band-by-band relationships through regression analysis. The investigation described in this paper focuses on evaluation of the uncertainties inherent in the cross-calibration process, including contributions due to different spectral responses, spectral resolution, spectral filter shift, geometric misregistrations, and spatial resolutions. The hyperspectral data from the Environmental Satellite SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY and the EO-1 Hyperion, along with the relative spectral responses (RSRs) from the Landsat 7 Enhanced Thematic Mapper (TM) Plus and the Terra Moderate Resolution Imaging Spectroradiometer sensors, were used for the spectral uncertainty study. The data from Landsat 5 TM over five representative land cover types (desert, rangeland, grassland, deciduous forest, and coniferous forest) were used for the geometric misregistrations and spatial-resolution study. The spectral resolution uncertainty was found to be within 0.25%, spectral filter shift within 2.5%, geometric misregistrations within 0.35%, and spatial-resolution effects within 0.1% for the Libya 4 site. The one-sigma uncertainties presented in this paper are uncorrelated, and therefore, the uncertainties can be summed orthogonally. Furthermore, an overall total uncertainty was developed. In general, the results suggested that the spectral uncertainty is more dominant compared to other uncertainties presented in this paper. Therefore, the effect of the sensor RSR differences needs to be quantified and compensated to avoid large uncertainties in cross-calibration results.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Geoscience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","publisherLocation":"Washington, D.C.","doi":"10.1109/TGRS.2012.2228008","usgsCitation":"Chander, G., Helder, D., Aaron, D., Mishra, N., and Shrestha, A., 2013, Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study: IEEE Transactions on Geoscience and Remote Sensing, v. 51, no. 3, p. 1282-1296, https://doi.org/10.1109/TGRS.2012.2228008.","productDescription":"15 p.","startPage":"1282","endPage":"1296","ipdsId":"IP-039167","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":268519,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512f2af9e4b0cad81a732d77","contributors":{"authors":[{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":474896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Helder, D. L. 0000-0002-7379-4679","orcid":"https://orcid.org/0000-0002-7379-4679","contributorId":51496,"corporation":false,"usgs":true,"family":"Helder","given":"D. L.","affiliations":[],"preferred":false,"id":474897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aaron, David","contributorId":83809,"corporation":false,"usgs":false,"family":"Aaron","given":"David","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":474899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mishra, N.","contributorId":67379,"corporation":false,"usgs":true,"family":"Mishra","given":"N.","email":"","affiliations":[],"preferred":false,"id":474898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shrestha, A.K.","contributorId":104783,"corporation":false,"usgs":true,"family":"Shrestha","given":"A.K.","email":"","affiliations":[],"preferred":false,"id":474900,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70044171,"text":"ds709S - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-27T16:24:33","indexId":"ds709S","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","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":"709","chapter":"S","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kunduz mineral district, which has celestite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Kunduz) and the WGS84 datum. The final image mosaics were subdivided into five overlapping tiles or quadrants because of the large size of the target area. The five image tiles (or quadrants) for the Kunduz area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709-S)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709S","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey; Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","usgsCitation":"Davis, P.A., Arko, S.A., and Harbin, M., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme; 4 Index Maps; 16 Image Files; 16 Metadata Files; 1 Shapefile, https://doi.org/10.3133/ds709S.","productDescription":"HTML Document; Readme; 4 Index Maps; 16 Image Files; 16 Metadata Files; 1 Shapefile","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":268501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_S.png"},{"id":268498,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/s/image_files/image_files.html"},{"id":268499,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/s/metadata/metadata.html"},{"id":268500,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/s/shapefiles/shapefiles.html"},{"id":268495,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/s/"},{"id":268496,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/s/1_readme.txt"},{"id":268497,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/s/index_maps/index_maps.html"}],"country":"Afghanistan","otherGeospatial":"Kunduz Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 58.0,29.0 ], [ 58.0,40.0 ], [ 77.0,40.0 ], [ 77.0,29.0 ], [ 58.0,29.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512f2afde4b0cad81a732d7f","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":474973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":474974,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70044136,"text":"70044136 - 2013 - Applications of spectral band adjustment factors (SBAF) for cross-calibration","interactions":[],"lastModifiedDate":"2013-02-27T17:44:54","indexId":"70044136","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Applications of spectral band adjustment factors (SBAF) for cross-calibration","docAbstract":"To monitor land surface processes over a wide range of temporal and spatial scales, it is critical to have coordinated observations of the Earth's surface acquired from multiple spaceborne imaging sensors. However, an integrated global observation framework requires an understanding of how land surface processes are seen differently by various sensors. This is particularly true for sensors acquiring data in spectral bands whose relative spectral responses (RSRs) are not similar and thus may produce different results while observing the same target. The intrinsic offsets between two sensors caused by RSR mismatches can be compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of the two sensors. The motivation of this work comes from the need to compensate the spectral response differences of multispectral sensors in order to provide a more accurate cross-calibration between the sensors. In this paper, radiometric cross-calibration of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors was performed using near-simultaneous observations over the Libya 4 pseudoinvariant calibration site in the visible and near-infrared spectral range. The RSR differences of the analogous ETM+ and MODIS spectral bands provide the opportunity to explore, understand, quantify, and compensate for the measurement differences between these two sensors. The cross-calibration was initially performed by comparing the top-of-atmosphere (TOA) reflectances between the two sensors over their lifetimes. The average percent differences in the long-term trends ranged from $-$5% to $+$6%. The RSR compensated ETM+ TOA reflectance (ETM+$^{ast}$) measurements were then found to agree with MODIS TOA reflectance to within 5% for all bands when Earth Observing-1 Hy- erion hyperspectral data were used to produce the SBAFs. These differences were later reduced to within 1% for all bands (except band 2) by using Environmental Satellite Scanning Imaging Absorption Spectrometer for Atmospheric Cartography hyperspectral data to produce the SBAFs.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Geoscience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","publisherLocation":"Washington, D.C.","doi":"10.1109/TGRS.2012.2228007","usgsCitation":"Chander, G., 2013, Applications of spectral band adjustment factors (SBAF) for cross-calibration: IEEE Transactions on Geoscience and Remote Sensing, v. 51, no. 3, p. 1267-1281, https://doi.org/10.1109/TGRS.2012.2228007.","productDescription":"15 p.","startPage":"1267","endPage":"1281","ipdsId":"IP-037261","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":268517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268516,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2012.2228007"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512f2adfe4b0cad81a732d73","contributors":{"authors":[{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":474863,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70044294,"text":"sir20135016 - 2013 - Macrophyte and pH buffering updates to the Klamath River water-quality model upstream of Keno Dam, Oregon","interactions":[],"lastModifiedDate":"2013-03-01T14:08:40","indexId":"sir20135016","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5016","title":"Macrophyte and pH buffering updates to the Klamath River water-quality model upstream of Keno Dam, Oregon","docAbstract":"A hydrodynamic, water temperature, and water-quality model of the Link River to Keno Dam reach of the upper Klamath River was updated to account for macrophytes and enhanced pH buffering from dissolved organic matter, ammonia, and orthophosphorus. Macrophytes had been observed in this reach by field personnel, so macrophyte field data were collected in summer and fall (June-October) 2011 to provide a dataset to guide the inclusion of macrophytes in the model. Three types of macrophytes were most common: pondweed (Potamogeton species), coontail (Ceratophyllum demersum), and common waterweed (Elodea canadensis). Pondweed was found throughout the Link River to Keno Dam reach in early summer with densities declining by mid-summer and fall. Coontail and common waterweed were more common in the lower reach near Keno Dam and were at highest density in summer. All species were most dense in shallow water (less than 2 meters deep) near shore. The highest estimated dry weight biomass for any sample during the study was 202 grams per square meter for coontail in August. Guided by field results, three macrophyte groups were incorporated into the CE-QUAL-W2 model for calendar years 2006-09. The CE-QUAL-W2 model code was adjusted to allow the user to initialize macrophyte populations spatially across the model grid. The default CE-QUAL-W2 model includes pH buffering by carbonates, but does not include pH buffering by organic matter, ammonia, or orthophosphorus. These three constituents, especially dissolved organic matter, are present in the upper Klamath River at concentrations that provide substantial pH buffering capacity. In this study, CE-QUAL-W2 was updated to include this enhanced buffering capacity in the simulation of pH. Acid dissociation constants for ammonium and phosphoric acid were taken from the literature. For dissolved organic matter, the number of organic acid groups and each group's acid dissociation constant (Ka) and site density (moles of sites per mole of carbon) were derived by fitting a theoretical buffering response to measured upper Klamath River alkalinity titration curves. The organic matter buffering in the Klamath River was modeled with two monoprotic organic acids: carboxylic acids with a mean pKa of 5.584 and site density of 0.1925, and phenolic organic acids with a mean pKa of 9.594 and site density of 0.6466. Total inorganic carbon concentrations in the model boundary inputs were recalculated based on the new buffering equations. CE-QUAL-W2 was also adjusted to allow the simulation of nonconservative alkalinity caused by nitrification, denitrification, photosynthesis, and respiration. The Klamath River model was recalibrated after the macrophyte and pH buffering updates producing improved predictions for pH, dissolved oxygen, and particulate carbon.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135016","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A.B., Rounds, S.A., Asbill-Case, J.R., and Deas, M., 2013, Macrophyte and pH buffering updates to the Klamath River water-quality model upstream of Keno Dam, Oregon: U.S. Geological Survey Scientific Investigations Report 2013-5016, viii, 54 p., https://doi.org/10.3133/sir20135016.","productDescription":"viii, 54 p.","numberOfPages":"64","onlineOnly":"N","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":268629,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5016/pdf/sir20135016.pdf"},{"id":268628,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5016/index.html"},{"id":268630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2013_5016.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 122,42.03 ], [ 122,42.33 ], [ 121.75,42.33 ], [ 121.75,42.03 ], [ 122,42.03 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5131dc02e4b0140546f53bf9","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":56317,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett","email":"annett@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":475250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asbill-Case, Jessica R.","contributorId":32058,"corporation":false,"usgs":true,"family":"Asbill-Case","given":"Jessica","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":475249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deas, Michael L.","contributorId":98830,"corporation":false,"usgs":true,"family":"Deas","given":"Michael L.","affiliations":[],"preferred":false,"id":475251,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044134,"text":"70044134 - 2013 - Overview of intercalibration of satellite instruments","interactions":[],"lastModifiedDate":"2013-02-27T17:45:28","indexId":"70044134","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Overview of intercalibration of satellite instruments","docAbstract":"Inter-calibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be inter-operable, the instruments must be cross-calibrated. To meet the stringent needs of such applications requires that instruments provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d'unités (SI) traceable Calibration and Validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stability monitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Inter-calibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Inter-calibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated inter-calibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms of change. This paper summarizes the state-of-the-art of post-launch radiometric calibration of remote sensing satellite instruments, through inter-calibration.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Geoscience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","publisherLocation":"Washington, D.C.","doi":"10.1109/TGRS.2012.2228654","usgsCitation":"Chander, G., Hewison, T., Fox, N., Wu, X., Xiong, X., and Blackwell, W., 2013, Overview of intercalibration of satellite instruments: IEEE Transactions on Geoscience and Remote Sensing, v. 51, no. 3, p. 1056-1080, https://doi.org/10.1109/TGRS.2012.2228654.","productDescription":"25 p.","startPage":"1056","endPage":"1080","ipdsId":"IP-038923","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":268515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268514,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2012.2228654"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512f2afee4b0cad81a732d87","contributors":{"authors":[{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":474856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hewison, T.J.","contributorId":75403,"corporation":false,"usgs":true,"family":"Hewison","given":"T.J.","email":"","affiliations":[],"preferred":false,"id":474857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fox, N.","contributorId":90905,"corporation":false,"usgs":true,"family":"Fox","given":"N.","email":"","affiliations":[],"preferred":false,"id":474858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, X.","contributorId":31925,"corporation":false,"usgs":true,"family":"Wu","given":"X.","email":"","affiliations":[],"preferred":false,"id":474854,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xiong, X.","contributorId":37885,"corporation":false,"usgs":true,"family":"Xiong","given":"X.","affiliations":[],"preferred":false,"id":474855,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blackwell, W.J.","contributorId":23405,"corporation":false,"usgs":true,"family":"Blackwell","given":"W.J.","email":"","affiliations":[],"preferred":false,"id":474853,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70043595,"text":"70043595 - 2013 - A data-based conservation planning tool for Florida panthers","interactions":[],"lastModifiedDate":"2013-03-04T21:06:08","indexId":"70043595","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1550,"text":"Environmental Modeling & Assessment","onlineIssn":" 1573-296","printIssn":"1420-2026","active":true,"publicationSubtype":{"id":10}},"title":"A data-based conservation planning tool for Florida panthers","docAbstract":"Habitat loss and fragmentation are the greatest threats to the endangered Florida panther (Puma concolor coryi). We developed a data-based habitat model and user-friendly interface so that land managers can objectively evaluate Florida panther habitat. We used a geographic information system (GIS) and the Mahalanobis distance statistic (D2) to develop a model based on broad-scale landscape characteristics associated with panther home ranges. Variables in our model were Euclidean distance to natural land cover, road density, distance to major roads, human density, amount of natural land cover, amount of semi-natural land cover, amount of permanent or semi-permanent flooded area–open water, and a cost–distance variable. We then developed a Florida Panther Habitat Estimator tool, which automates and replicates the GIS processes used to apply the statistical habitat model. The estimator can be used by persons with moderate GIS skills to quantify effects of land-use changes on panther habitat at local and landscape scales. Example applications of the tool are presented.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modeling and Assessment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10666-012-9336-0","usgsCitation":"Murrow, J.L., Thatcher, C., van Manen, F., and Clark, J.D., 2013, A data-based conservation planning tool for Florida panthers: Environmental Modeling & Assessment, v. 18, no. 2, p. 159-170, https://doi.org/10.1007/s10666-012-9336-0.","productDescription":"12 p.","startPage":"159","endPage":"170","ipdsId":"IP-040629","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":268388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268382,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10666-012-9336-0"}],"country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.63,24.52 ], [ -87.63,31.0 ], [ -80.0,31.0 ], [ -80.0,24.52 ], [ -87.63,24.52 ] ] ] } } ] }","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-09-09","publicationStatus":"PW","scienceBaseUri":"5135d072e4b03b8ec4025b38","contributors":{"authors":[{"text":"Murrow, Jennifer L.","contributorId":92945,"corporation":false,"usgs":true,"family":"Murrow","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":473934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thatcher, Cindy A.","contributorId":79604,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy A.","affiliations":[],"preferred":false,"id":473933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Manen, Frank T.","contributorId":51172,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank T.","affiliations":[],"preferred":false,"id":473932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":473931,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044062,"text":"70044062 - 2013 - Estimation of evapotranspiration across the conterminous United States using a regression with climate and land-cover data","interactions":[],"lastModifiedDate":"2016-03-28T09:01:08","indexId":"70044062","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Estimation of evapotranspiration across the conterminous United States using a regression with climate and land-cover data","docAbstract":"Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water-balance method was combined with a climate and land-cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971-2000 across the U.S. to obtain long-term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land-cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land-cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land-cover data can also improve those predictions. Using the climate and land-cover data at an 800-m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land-cover data are plentiful.
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,{"id":70044100,"text":"70044100 - 2013 - Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example","interactions":[],"lastModifiedDate":"2013-02-26T17:59:42","indexId":"70044100","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","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":"Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example","docAbstract":"Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landscape Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10980-012-9830-4","usgsCitation":"Cross, P.C., Caillaud, D., and Heisey, D.M., 2013, Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example: Landscape Ecology, v. 28, no. 2, p. 247-257, https://doi.org/10.1007/s10980-012-9830-4.","productDescription":"11 p.","startPage":"247","endPage":"257","ipdsId":"IP-034645","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":268415,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10980-012-9830-4"},{"id":268416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-11-30","publicationStatus":"PW","scienceBaseUri":"53cd7a2ae4b0b2908510d4ed","contributors":{"authors":[{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":474810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caillaud, Damien","contributorId":31650,"corporation":false,"usgs":true,"family":"Caillaud","given":"Damien","email":"","affiliations":[],"preferred":false,"id":474811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heisey, Dennis M. dheisey@usgs.gov","contributorId":2455,"corporation":false,"usgs":true,"family":"Heisey","given":"Dennis","email":"dheisey@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":474809,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70044075,"text":"ds713 - 2013 - Drill hole data for coal beds in the Powder River Basin, Montana and Wyoming","interactions":[],"lastModifiedDate":"2026-05-07T17:06:34.968308","indexId":"ds713","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","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":"713","title":"Drill hole data for coal beds in the Powder River Basin, Montana and Wyoming","docAbstract":"This report by the U.S. Geological Survey (USGS) of the Powder River Basin (PRB) of Montana and Wyoming is part of the U.S. Coal Resources and Reserves Assessment Project. Essential to that project was the creation of a comprehensive drill hole database that was used for coal bed correlation and for coal resource and reserve assessments in the PRB. This drill hole database was assembled using data from the USGS National Coal Resources Data System, several other Federal and State agencies, and selected mining companies. Additionally, USGS personnel manually entered lithologic picks into the database from geophysical logs of coalbed methane, oil, and gas wells. Of the 29,928 drill holes processed, records of 21,393 are in the public domain and are included in this report. 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Making these spatial correlations typically involves geological and geophysical studies in order to map structures and their relationship to springs at the surface. Geophysical studies include gravity and magnetic surveys, which are useful for identifying buried, intra-basin structures, especially in areas where highly magnetic, dense mafic volcanic rocks are interbedded with, and faulted against less magnetic, less dense sedimentary rock. High-resolution magnetic data can also be collected from the air in order to provide continuous coverage. Unmanned aerial systems (UAS) are well-suited for conducting these surveys as they can provide uniform, low-altitude, high-resolution coverage of an area without endangering crew. In addition, they are more easily adaptable to changes in flight plans as data are collected, and improve efficiency. We have developed and tested a new system to collect magnetic data using small-platform UAS. We deployed this new system in Surprise Valley, CA, in September, 2012, on NASA's SIERRA UAS to perform a reconnaissance survey of the entire valley as well as detailed surveys in key transition zones. This survey has enabled us to trace magnetic anomalies seen in ground-based profiles along their length. Most prominent of these is an intra-basin magnetic high that we interpret as a buried, faulted mafic dike that runs a significant length of the valley. Though this feature lacks surface expression, it appears to control the location of geothermal springs. All of the major hot springs on the east side of the valley lie along the edge of the high, and more specifically, at structural transitions where the high undergoes steps, bends, or breaks. The close relationship between the springs and structure terminations revealed by this study is unprecedented. Collecting magnetic data via UAS represents a new capability in geothermal exploration of remote and dangerous areas that significantly enhances our ability to map the subsurface.
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Since the early 1990s, three U.S. National Land Cover Database (NLCD) products (circa 1992, 2001, and 2006) have been released as free downloads for users. The NLCD 2006 also provides land cover change products between 2001 and 2006. To continue providing updated national land cover and change datasets, a new initiative in developing NLCD 2011 is currently underway. We present a new Comprehensive Change Detection Method (CCDM) designed as a key component for the development of NLCD 2011 and the research results from two exemplar studies. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (CV, RCVMAX, dNBR, and dNDVI) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. For NLCD 2011, the improved and enhanced change products obtained from the CCDM provide critical information on location, magnitude, and direction of potential change areas and serve as a basis for further characterizing land cover changes for the nation. An accuracy assessment from the two study areas show 100% agreement between CCDM mapped no-change class with reference dataset, and 18% and 82% disagreement for the change class for WRS path/row p22r39 and p33r33, respectively. The strength of the CCDM is that the method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and anthropogenic disturbances potentially associated with land cover changes on different landscapes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2013.01.012","usgsCitation":"Jin, S., Yang, L., Danielson, P., Homer, C.G., Fry, J., and Xian, G., 2013, A comprehensive change detection method for updating the National Land Cover Database to circa 2011: Remote Sensing of Environment, v. 132, p. 159-175, https://doi.org/10.1016/j.rse.2013.01.012.","productDescription":"17 p.","startPage":"159","endPage":"175","ipdsId":"IP-041925","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":268381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268380,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2013.01.012"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","volume":"132","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd49a9e4b0b290850ef516","chorus":{"doi":"10.1016/j.rse.2013.01.012","url":"http://dx.doi.org/10.1016/j.rse.2013.01.012","publisher":"Elsevier BV","authors":"Jin Suming, Yang Limin, Danielson Patrick, Homer Collin, Fry Joyce, Xian George","journalName":"Remote Sensing of Environment","publicationDate":"5/2013","auditedOn":"4/22/2016"},"contributors":{"authors":[{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":474161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":474160,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Patrick 0000-0002-2990-2783 pdanielson@usgs.gov","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":3551,"corporation":false,"usgs":true,"family":"Danielson","given":"Patrick","email":"pdanielson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":474159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":474157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fry, Joyce 0000-0002-8466-9582 jfry@usgs.gov","orcid":"https://orcid.org/0000-0002-8466-9582","contributorId":3147,"corporation":false,"usgs":true,"family":"Fry","given":"Joyce","email":"jfry@usgs.gov","affiliations":[],"preferred":true,"id":474158,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xian, George 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":76589,"corporation":false,"usgs":true,"family":"Xian","given":"George","affiliations":[],"preferred":false,"id":474162,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70042646,"text":"70042646 - 2013 - Salmon-mediated nutrient flux in selected streams of the Columbia River basin, USA","interactions":[],"lastModifiedDate":"2013-04-20T19:45:03","indexId":"70042646","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Salmon-mediated nutrient flux in selected streams of the Columbia River basin, USA","docAbstract":"Salmon provide an important resource subsidy and linkage between marine and land-based ecosystems. This flow of energy and nutrients is not uni-directional (i.e., upstream only); in addition to passive nutrient export via stream flow, juvenile emigrants actively export nutrients from freshwater environments. In some cases, nutrient export can exceed import. We evaluated nutrient fluxes in streams across central Idaho, USA using Chinook salmon (Oncorhynchus tshawytscha) adult escapement and juvenile production data from 1998 to 2008. We found in the majority of stream-years evaluated, adults imported more nutrients than progeny exported; however, in 3% of the years, juveniles exported more nutrients than their parents imported. On average, juvenile emigrants exported 22 ± 3% of the nitrogen and 30 ± 4% of the phosphorus their parents imported. This relationship was density dependent and nonlinear; during periods of low adult abundance juveniles were larger and exported up to 194% and 268% of parental nitrogen and phosphorus inputs, respectively. We highlight minimum escapement thresholds that appear to 1) maintain consistently positive net nutrient flux and 2) reduce the average proportional rate of export across study streams. Our results suggest a state-shift occurs when adult spawner abundance falls below a threshold to a point where the probability of juvenile nutrient exports exceeding adult imports becomes increasingly likely.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Fisheries and Aquatic Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Canadian Science Publishing","publisherLocation":"Ottawa, Ontario","doi":"10.1139/cjfas-2012-0347","usgsCitation":"Kohler, A.E., Kusnierz, P.C., Copeland, T., Venditti, D.A., Denny, L., Gable, J., Lewis, B., Kinzer, R., Barnett, B., and Wipfli, M.S., 2013, Salmon-mediated nutrient flux in selected streams of the Columbia River basin, USA: Canadian Journal of Fisheries and Aquatic Sciences, v. 70, no. 3, p. 502-512, https://doi.org/10.1139/cjfas-2012-0347.","productDescription":"11 p.","startPage":"502","endPage":"512","ipdsId":"IP-039469","costCenters":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":268392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268391,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1139/cjfas-2012-0347"}],"country":"United States","state":"Idaho","otherGeospatial":"Columbia River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.46,42.15 ], [ -121.46,48.13 ], [ -111.19,48.13 ], [ -111.19,42.15 ], [ -121.46,42.15 ] ] ] } } ] }","volume":"70","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515ea0f6e4b088aa2258098c","contributors":{"authors":[{"text":"Kohler, Andre E.","contributorId":62491,"corporation":false,"usgs":true,"family":"Kohler","given":"Andre","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":471974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kusnierz, Paul C.","contributorId":13881,"corporation":false,"usgs":true,"family":"Kusnierz","given":"Paul","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":471970,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Copeland, Timothy","contributorId":27760,"corporation":false,"usgs":true,"family":"Copeland","given":"Timothy","email":"","affiliations":[],"preferred":false,"id":471971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Venditti, David A.","contributorId":38036,"corporation":false,"usgs":true,"family":"Venditti","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471972,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Denny, Lytle","contributorId":96172,"corporation":false,"usgs":true,"family":"Denny","given":"Lytle","email":"","affiliations":[],"preferred":false,"id":471977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gable, Josh","contributorId":7156,"corporation":false,"usgs":true,"family":"Gable","given":"Josh","email":"","affiliations":[],"preferred":false,"id":471969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lewis, Bert","contributorId":92138,"corporation":false,"usgs":true,"family":"Lewis","given":"Bert","email":"","affiliations":[],"preferred":false,"id":471976,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kinzer, Ryan","contributorId":45201,"corporation":false,"usgs":true,"family":"Kinzer","given":"Ryan","email":"","affiliations":[],"preferred":false,"id":471973,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barnett, Bruce","contributorId":82565,"corporation":false,"usgs":true,"family":"Barnett","given":"Bruce","email":"","affiliations":[],"preferred":false,"id":471975,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":471968,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70057429,"text":"ofr20131202B - 2013 - Hyperspectral surface materials map of quadrangle 3562, Khawja-Jir (403) and Murghab (404) quadrangles, Afghanistan, showing iron-bearing minerals and other materials","interactions":[],"lastModifiedDate":"2014-03-10T10:09:31","indexId":"ofr20131202B","displayToPublicDate":"2013-02-25T12:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1202","chapter":"B","title":"Hyperspectral surface materials map of quadrangle 3562, Khawja-Jir (403) and Murghab (404) quadrangles, Afghanistan, showing iron-bearing minerals and other materials","docAbstract":"This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan.
\nFlown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines.
\nThe reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131202B","collaboration":"Prepared in cooperation with the U.S. Geological Survey under the auspices of the U.S. Department of Defense Task Force for Business and Stability Operations","usgsCitation":"King, T., Hoefen, T.M., Kokaly, R., Livo, K.E., Johnson, M., and Giles, S.A., 2013, Hyperspectral surface materials map of quadrangle 3562, Khawja-Jir (403) and Murghab (404) quadrangles, Afghanistan, showing iron-bearing minerals and other materials: U.S. Geological Survey Open-File Report 2013-1202, 37 x 23 inches, https://doi.org/10.3133/ofr20131202B.","productDescription":"37 x 23 inches","onlineOnly":"Y","ipdsId":"IP-050472","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":282356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131202b.jpg"},{"id":283578,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1202/B/"},{"id":283579,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1202/B/pdf/ofr2013-1202b.pdf"}],"scale":"250000","projection":"Universal Transverse Mercator","datum":"WGS 1984","country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 62.0,35.0 ], [ 62.0,36.0 ], [ 64.0,36.0 ], [ 64.0,35.0 ], [ 62.0,35.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd61dae4b0b290850fdc9e","contributors":{"authors":[{"text":"King, Trude","contributorId":29831,"corporation":false,"usgs":true,"family":"King","given":"Trude","email":"","affiliations":[],"preferred":false,"id":486684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":81442,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","affiliations":[],"preferred":false,"id":486685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Livo, Keith E. 0000-0001-7331-8130 elivo@usgs.gov","orcid":"https://orcid.org/0000-0001-7331-8130","contributorId":1750,"corporation":false,"usgs":true,"family":"Livo","given":"Keith","email":"elivo@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":486683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Michaela R. 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":1013,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela R.","email":"mrjohns@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Giles, Stuart A. 0000-0002-8696-5078 sgiles@usgs.gov","orcid":"https://orcid.org/0000-0002-8696-5078","contributorId":1233,"corporation":false,"usgs":true,"family":"Giles","given":"Stuart","email":"sgiles@usgs.gov","middleInitial":"A.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486682,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70146651,"text":"70146651 - 2013 - Fens as whole-ecosystem gauges of groundwater recharge under climate change","interactions":[],"lastModifiedDate":"2015-04-20T09:17:35","indexId":"70146651","displayToPublicDate":"2013-02-25T10:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Fens as whole-ecosystem gauges of groundwater recharge under climate change","docAbstract":"Currently, little is known about the impact of climate change on groundwater recharge in the Sierra Nevada and southern Cascade Range of California or other mountainous regions of the world. The purpose of this study was to determine whether small alpine peat lands called fens can be used as whole-ecosystem gauges of groundwater recharge through time. Fens are sustained by groundwater discharge and are highly sensitive to changes in groundwater flow due to hydrologic disturbance including climate change. Seven fens in the Sierra Nevada and southern Cascade Range were studied over a 50-80 year period using historic aerial photography. In each aerial photograph, fen areas were identified as open lawn and partially treed areas that exhibited (1) dark brownish-green coloring or various shades of gray and black in black and white imagery and (2) mottling of colors and clustering of vegetation, which signified a distinct moss canopy with overlying clumped sedge vegetation. In addition to the aerial photography study, a climate analysis for the study sites was carried out using both measured data (U.S. Department of Agriculture Natural Resources Conservation Service SNOwpack TELemetry system) and modeled data (a downscaled version of the Parameter-elevation Regressions on Independent Slopes Model) for the period from 1951 to 2010. Over the study period, the five fens in the Sierra Nevada were found to be decreasing between 10% and 16% in delineated area. The climate analysis revealed significant increases through time in annual mean minimum temperature (Tmin) between 1951-1980 and 1981-2010. In addition, April 1 snow water equivalent and snowpack longevity also decreased between 1951-1980 and 1981-2010. For the fens in the Cascade Range, there were no discernible changes in delineated area. At these sites, increases in Tmin occurred only within the past 20-25 years and decreases in snowpack longevity were more subtle. A conceptual model is presented, which illustrates that basic differences in hydrogeology of the Sierra Nevada vs. the Cascade Range may control the threshold at which changes in delineated fen areas are discernible. Overall, the results from this study show that fens in the Sierra Nevada have strong potential as whole ecosystem gauges for determining long-term changes in groundwater recharge under climate change. Due to either more moderate climate change and/or hydrogeological differences, fens in the southern Cascade Range currently do not appear to have the same utility. A greater sample size of fens in the Sierra Nevada is needed to confirm the general applicability of this method. In addition, future work needs to focus on integrating fen monitoring with geochemical and/or isotopic process-level studies in order to quantify changes in groundwater recharge identified using this new approach.
","language":"English","publisher":"European Geophysical Society","publisherLocation":"New York, NY","doi":"10.1016/j.jhydrol.2012.11.056","usgsCitation":"Drexler, J., Knifong, D.L., Tuil, J., Flint, L.E., and Flint, A.L., 2013, Fens as whole-ecosystem gauges of groundwater recharge under climate change: Journal of Hydrology, v. 481, p. 22-34, https://doi.org/10.1016/j.jhydrol.2012.11.056.","productDescription":"13 p.","startPage":"22","endPage":"34","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040704","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":299768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"481","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5536233ae4b0b22a15807a94","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":1659,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith Z.","email":"jdrexler@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":545228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knifong, Donna L. dknifong@usgs.gov","contributorId":1517,"corporation":false,"usgs":true,"family":"Knifong","given":"Donna","email":"dknifong@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":545227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tuil, JayLee","contributorId":140341,"corporation":false,"usgs":false,"family":"Tuil","given":"JayLee","email":"","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":545230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545226,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}