No abstract available.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds764","usgsCitation":"du Bray, E.A., John, D.A., Box, S.E., Vikre, P.G., Fleck, R.J., and Cousens, B.L., 2016, Petrographic and geochemical data for Cenozoic volcanic rocks of the Bodie Hills, California and Nevada (ver. 1.1, August 2016): U.S. Geological Survey Data Series 764, 10 p., https://dx.doi.org/10.3133/ds764.","productDescription":"Report: iii, 10 p.; 3 Appendixes","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":504535,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98440.htm","linkFileType":{"id":5,"text":"html"}},{"id":271747,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/764/Appendix2.xls","text":"Appendix 2","size":"488 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2"},{"id":271750,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/764/coverthb2.jpg"},{"id":271749,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/764/Appendix3.xls","text":"Appendix 3","size":"568 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 3"},{"id":271746,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/764/DS764_pamphlet.pdf","text":"Report"},{"id":271745,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/764/"},{"id":271748,"rank":1,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/764/Appendix1.xls","text":"Appendix 1","size":"320 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 1"},{"id":327107,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/764/versionHist.txt","size":"4 kB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"California, Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.0 ], [ -114.13,42.0 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","edition":"Version 1.0: Originally posted April 23, 2013; Version 1.1: August 22, 2016","contact":"Director, Central Mineral and Environmental Resources Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225-0046
With advances in web applications, organic petrography and other related disciplines are in need of updated online resources and educational tools to aid professionals and students in the identification and interpretation of macerals. The U.S. Geological Survey (USGS) Organic Petrology Laboratory along with USGS Eastern Energy Resources Science Center Information Technology staff have developed five web atlases containing images of organic matter in geologic materials: 1. an American Society for Testing and Materials (ASTM) Atlas, 2. an Organic Petrology Taxonomy for International Classification (OPTIC) of Coal Macerals Atlas, 3. an Interactive Gulf Coast Photomicrograph Web Atlas (I-Map), 4. an Organic Material in Shales Atlas (Shale), and 5. an interactive Blue/White/Ultraviolet (UV) Light Atlas (Light). Each web atlas contains images of macerals with associated sample and petrographic data collected by the USGS. These webpages will provide means to preserve and circulate petrographic data collected by the USGS for coal and shale samples from all over the world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2012.09.012","usgsCitation":"Valentine, B.J., Morrissey, E., Park, A., Reidy, M.E., and Hackley, P.C., 2013, Development of web-based organic petrology photomicrograph atlases and internet resources for professionals and students: International Journal of Coal Geology, v. 111, p. 106-111, https://doi.org/10.1016/j.coal.2012.09.012.","productDescription":"6 p.","startPage":"106","endPage":"111","ipdsId":"IP-035471","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc03acee4b0fc368eb53b36","contributors":{"authors":[{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":746259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morrissey, Eric A. 0000-0001-9001-7487","orcid":"https://orcid.org/0000-0001-9001-7487","contributorId":204980,"corporation":false,"usgs":true,"family":"Morrissey","given":"Eric A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":746260,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Park, Andy J. 0000-0003-1454-1150","orcid":"https://orcid.org/0000-0003-1454-1150","contributorId":208185,"corporation":false,"usgs":true,"family":"Park","given":"Andy J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":746258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reidy, Mark E. 0000-0002-2302-0106 mreidy@usgs.gov","orcid":"https://orcid.org/0000-0002-2302-0106","contributorId":4035,"corporation":false,"usgs":true,"family":"Reidy","given":"Mark","email":"mreidy@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":746261,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":746262,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198399,"text":"70198399 - 2013 - Modern foraminifera, δ13C, and bulk geochemistry of central Oregon tidal marshes and their application in paleoseismology","interactions":[],"lastModifiedDate":"2018-08-03T10:49:44","indexId":"70198399","displayToPublicDate":"2013-05-01T10:49:33","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modern foraminifera, δ13C, and bulk geochemistry of central Oregon tidal marshes and their application in paleoseismology","title":"Modern foraminifera, δ13C, and bulk geochemistry of central Oregon tidal marshes and their application in paleoseismology","docAbstract":"We assessed the utility of δ13C and bulk geochemistry (total organic content and C:N) to reconstruct relative sea-level changes on the Cascadia subduction zone through comparison with an established sea-level indicator (benthic foraminifera). Four modern transects collected from three tidal environments at Siletz Bay, Oregon, USA, produced three elevation-dependent groups in both the foraminiferal and δ13C/bulk geochemistry datasets. Foraminiferal samples from the tidal flat and low marsh are identified by Miliammina fuscaabundances of > 45%, middle and high marsh by M. fusca abundances of < 45% and the highest marsh by Trochamminita irregularis abundances > 25%. The δ13C values from the groups defined with δ13C/bulk geochemistry analyses decrease with an increasing elevation; − 24.1 ± 1.7‰ in the tidal flat and low marsh; − 27.3 ± 1.4‰ in the middle and high marsh; and − 29.6 ± 0.8‰ in the highest marsh samples. We applied the modern foraminiferal and δ13C distributions to a core that contained a stratigraphic contact marking the great Cascadia earthquake of AD 1700. Both techniques gave similar values for coseismic subsidence across the contact (0.88 ± 0.39 m and 0.71 ± 0.56 m) suggesting that δ13C has potential for identifying amounts of relative sea-level change due to tectonics.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2013.02.032","usgsCitation":"Engelhart, S.E., Horton, B.P., Vane, C.H., Nelson, A.R., Witter, R., Brody, S.R., and Hawkes, A., 2013, Modern foraminifera, δ13C, and bulk geochemistry of central Oregon tidal marshes and their application in paleoseismology: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 377, p. 13-27, https://doi.org/10.1016/j.palaeo.2013.02.032.","productDescription":"15 p.","startPage":"13","endPage":"27","ipdsId":"IP-044830","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":473851,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/geo_facpubs/30","text":"External Repository"},{"id":356128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","volume":"377","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fd336e4b0f5d57878ed85","contributors":{"authors":[{"text":"Engelhart, Simon E.","contributorId":60104,"corporation":false,"usgs":false,"family":"Engelhart","given":"Simon","email":"","middleInitial":"E.","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":741493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horton, Benajamin P.","contributorId":192918,"corporation":false,"usgs":false,"family":"Horton","given":"Benajamin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":741494,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vane, Christopher H.","contributorId":88255,"corporation":false,"usgs":true,"family":"Vane","given":"Christopher","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":741495,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Alan R. 0000-0001-7117-7098 anelson@usgs.gov","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":812,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","email":"anelson@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":741496,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":741497,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brody, Sarah R.","contributorId":206699,"corporation":false,"usgs":false,"family":"Brody","given":"Sarah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":741498,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hawkes, Andrea D.","contributorId":20240,"corporation":false,"usgs":true,"family":"Hawkes","given":"Andrea D.","affiliations":[],"preferred":false,"id":741499,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70048532,"text":"70048532 - 2013 - Mapping landscape phenology preference of yellow-billed cuckoo with AVHRR data","interactions":[],"lastModifiedDate":"2018-08-06T13:00:51","indexId":"70048532","displayToPublicDate":"2013-05-01T10:33:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Mapping landscape phenology preference of yellow-billed cuckoo with AVHRR data","docAbstract":"We mapped habitat for threatened Yellow-billed Cuckoo (Coccycus americanus occidentalis) in the State of Arizona using the temporal greenness dynamics of the landscape, or the landscape phenology. Landscape phenometrics were derived from Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data for 1998 and 1999 by using Fourier harmonic analysis to analyze the waveform of the annual NDVI profile at each pixel. We modeled the spatial distribution of Yellow-billed Cuckoo habitat by coupling the field data of Cuckoo presence or absence and point-based samples of riparian and cottonwood-willow vegetation types with satellite phenometrics for 1998. Models were validated using field and satellite data collected in 1999. The results indicate that Yellow-billed Cuckoo occupy locations within their preferred habitat that exhibit peak greenness after the start of the summer monsoon and are greener and more dynamic than “average” habitat. Identification of preferred phenotypes within recognized habitat areas can be used to refine habitat models, inform predictions of habitat response to climate change, and suggest adaptation strategies.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Merging science and management in a rapidly changing world: Biodiversity and management of the Madrean Archipelago III and 7th Conference on Research and Resource Management in the Southwestern Deserts; 2012 May 1-5; Tucson, AZ","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"U.S. Department of Agriculture","publisherLocation":"Fort Collins, CO","usgsCitation":"Wallace, C., Villarreal, M.L., and van Riper, C., 2013, Mapping landscape phenology preference of yellow-billed cuckoo with AVHRR data, in Merging science and management in a rapidly changing world: Biodiversity and management of the Madrean Archipelago III and 7th Conference on Research and Resource Management in the Southwestern Deserts; 2012 May 1-5; Tucson, AZ, p. 506-508.","productDescription":"3 p.","startPage":"506","endPage":"508","numberOfPages":"3","ipdsId":"IP-037569","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":278912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278911,"type":{"id":15,"text":"Index Page"},"url":"https://treesearch.fs.fed.us/pubs/44487"}],"country":"United States","state":"Arizona","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.8166,31.3322 ], [ -114.8166,37.0043 ], [ -109.0452,37.0043 ], [ -109.0452,31.3322 ], [ -114.8166,31.3322 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527cc491e4b0850ea050ce8a","contributors":{"authors":[{"text":"Wallace, Cynthia S.A. cwallace@usgs.gov","contributorId":3335,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia S.A.","email":"cwallace@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":484981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":484980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":484979,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70056365,"text":"70056365 - 2013 - Assessing factors affecting the thermal properties of a passive thermal refuge using three-dimensional hydrodynamic flow and transport modeling","interactions":[],"lastModifiedDate":"2013-11-21T09:56:10","indexId":"70056365","displayToPublicDate":"2013-05-01T09:48:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2505,"text":"Journal of Waterway, Port, Coastal, Ocean Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Assessing factors affecting the thermal properties of a passive thermal refuge using three-dimensional hydrodynamic flow and transport modeling","docAbstract":"Everglades restoration activities may cause changes to temperature and salinity stratification at the Port of the Islands (POI) marina, which could affect its suitability as a cold weather refuge for manatees. To better understand how the Picayune Strand Restoration Project (PSRP) may alter this important resource in Collier County in southwestern Florida, the USGS has developed a three-dimensional hydrodynamic model for the marina and canal system at POI. Empirical data suggest that manatees aggregate at the site during winter because of thermal inversions that provide warmer water near the bottom that appears to only occur in the presence of salinity stratification. To study these phenomena, the environmental fluid dynamics code simulator was used to represent temperature and salinity transport within POI. Boundary inputs were generated using a larger two-dimensional model constructed with the flow and transport in a linked overland-aquifer density-dependent system simulator. Model results for a representative winter period match observed trends in salinity and temperature fluctuations and produce temperature inversions similar to observed values. Modified boundary conditions, representing proposed PSRP alterations, were also tested to examine the possible effect on the salinity stratification and temperature inversion within POI. Results show that during some periods, salinity stratification is reduced resulting in a subsequent reduction in temperature inversion compared with the existing conditions simulation. This may have an effect on POI’s suitability as a passive thermal refuge for manatees and other temperature-sensitive species. Additional testing was completed to determine the important physical relationships affecting POI’s suitability as a refuge.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Waterway, Port, Coastal, Ocean Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)WW.1943-5460.0000165","usgsCitation":"Decker, J.D., Swain, E.D., Stith, B., and Langtimm, C.A., 2013, Assessing factors affecting the thermal properties of a passive thermal refuge using three-dimensional hydrodynamic flow and transport modeling: Journal of Waterway, Port, Coastal, Ocean Engineering, v. 139, no. 3, p. 209-220, https://doi.org/10.1061/(ASCE)WW.1943-5460.0000165.","productDescription":"12 p.","startPage":"209","endPage":"220","numberOfPages":"12","ipdsId":"IP-016534","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":279310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279309,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1061/(ASCE)WW.1943-5460.0000165"}],"country":"United States","state":"Florida","otherGeospatial":"Faka Union Canal;Port Of The Islands Marina","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.234287,25.627031 ], [ -81.234287,26.139366 ], [ -80.658594,26.139366 ], [ -80.658594,25.627031 ], [ -81.234287,25.627031 ] ] ] } } ] }","volume":"139","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528f53efe4b0660d392bed8f","contributors":{"authors":[{"text":"Decker, Jeremy D. 0000-0002-0700-515X jdecker@usgs.gov","orcid":"https://orcid.org/0000-0002-0700-515X","contributorId":514,"corporation":false,"usgs":true,"family":"Decker","given":"Jeremy","email":"jdecker@usgs.gov","middleInitial":"D.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":486541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stith, Bradley bstith@usgs.gov","contributorId":3596,"corporation":false,"usgs":true,"family":"Stith","given":"Bradley","email":"bstith@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":486544,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langtimm, Catherine A. 0000-0001-8499-5743 clangtimm@usgs.gov","orcid":"https://orcid.org/0000-0001-8499-5743","contributorId":3045,"corporation":false,"usgs":true,"family":"Langtimm","given":"Catherine","email":"clangtimm@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":486543,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70047837,"text":"70047837 - 2013 - Vascular plant and vertebrate species richness in national parks of the eastern United States","interactions":[],"lastModifiedDate":"2013-11-15T09:49:42","indexId":"70047837","displayToPublicDate":"2013-05-01T09:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":56,"text":"Natural Resource Technical Report NPS/NCR/NCRO/NRTR","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"2013/002","title":"Vascular plant and vertebrate species richness in national parks of the eastern United States","docAbstract":"Given the estimates that species diversity is diminishing at 50-100 times the normal rate, it is critical that we be able to evaluate changes in species richness in order to make informed decisions for conserving species diversity. In this study, we examined the potential of vascular plant species richness to be used as a surrogate for vertebrate species richness in the classes of amphibians, reptiles, birds, and mammals. Vascular plants, as primary producers, represent the biotic starting point for ecological community structure and are the logical place to start for understanding vertebrate species associations. We used data collected by the United States (US) National Park Service (NPS) on species presence within parks in the eastern US to estimate simple linear regressions between plant species richness and vertebrate richness. Because environmental factors may also influence species diversity, we performed simple linear regressions of species richness versus natural logarithm of park area, park latitude, mean annual precipitation, mean annual temperature, and human population density surrounding the parks. We then combined plant species richness and environmental variables in multiple regressions to determine the variables that remained as significant predictors of vertebrate species richness. As expected, we detected significant relationships between plant species richness and amphibian, bird, and mammal species richness. In some cases, plant species richness was predicted by park area alone. Species richness of mammals was only related to plant species richness. Reptile species richness, on the other hand, was related to plant species richness, park latitude and annual precipitation, while amphibian species richness was related to park latitude, park area, and plant species richness. Thus, plant species richness predicted species richness of different vertebrate groups to varying degrees and should not be used exclusively as a surrogate for vertebrate species richness. Plant species richness should be included with other variables such as area and climate when considering strategies to manage and conserve species in US National Parks. It is not always appropriate to draw conclusions about analyses of taxonomic surrogates from one area to another. Two patterns evident from the linear regressions were the increase in species richness with the increase of park area and with increase of vascular plant species richness. To test whether there were differences in these patterns among networks, we used analysis of covariance (ANCOVA). Differences among networks were detected only in bird species richness versus plant species richness and for all taxa except mammals for vertebrate species richness versus park area. Some of these results may be due to small sample size among networks, and therefore, low statistical power. Other factors that could have contributed to these results were differences in average park area and habitat heterogeneity among networks, latitudinal gradients, low variation in mean annual precipitation, and different use of vegetation by migratory species. Based on these results we recommend that management of biodiversity be approached from local and site specific criteria rather than applying management directives derived from other regions of the US. It is also recommended that analyses similar to those presented here be conducted for all national parks, once data become available for all networks in the US, to gain a better understanding of how vascular plant species richness, area, and vertebrate species richness are related in the US.","language":"English","publisher":"National Park Service","publisherLocation":"Washington, D.C.","usgsCitation":"Hatfield, J., Myrick, K.E., Huston, M.A., Weckerly, F.W., and Green, M.C., 2013, Vascular plant and vertebrate species richness in national parks of the eastern United States: Natural Resource Technical Report NPS/NCR/NCRO/NRTR 2013/002, v. 002, no. 2013, vi, 50 p.","productDescription":"vi, 50 p.","numberOfPages":"60","ipdsId":"IP-050677","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":279101,"type":{"id":11,"text":"Document"},"url":"https://www.pwrc.usgs.gov/prodabs/pubpdfs/7906_Hatfield.pdf"},{"id":279102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"projection":"Albers equal-area conic projection","country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.55,32.1 ], [ -100.55,50.68 ], [ -66.4,50.68 ], [ -66.4,32.1 ], [ -100.55,32.1 ] ] ] } } ] }","volume":"002","issue":"2013","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5287509fe4b03b89f6f155ea","contributors":{"authors":[{"text":"Hatfield, Jeffrey S. jhatfield@usgs.gov","contributorId":151,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeffrey S.","email":"jhatfield@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":483103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myrick, Kaci E.","contributorId":18667,"corporation":false,"usgs":true,"family":"Myrick","given":"Kaci","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":483105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huston, Michael A.","contributorId":57351,"corporation":false,"usgs":true,"family":"Huston","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":483107,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weckerly, Floyd W.","contributorId":10298,"corporation":false,"usgs":false,"family":"Weckerly","given":"Floyd","email":"","middleInitial":"W.","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":483104,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Green, M. Clay","contributorId":55325,"corporation":false,"usgs":true,"family":"Green","given":"M.","email":"","middleInitial":"Clay","affiliations":[],"preferred":false,"id":483106,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148138,"text":"70148138 - 2013 - A novel approach to surveying sturgeon using side-scan sonar and occupancy modeling","interactions":[],"lastModifiedDate":"2015-05-27T14:25:37","indexId":"70148138","displayToPublicDate":"2013-05-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"A novel approach to surveying sturgeon using side-scan sonar and occupancy modeling","docAbstract":"Technological advances represent opportunities to enhance and supplement traditional fisheries sampling approaches. One example with growing importance for fisheries research is hydroacoustic technologies such as side-scan sonar. Advantages of side-scan sonar over traditional techniques include the ability to sample large areas efficiently and the potential to survey fish without physical handling-important for species of conservation concern, such as endangered sturgeons. Our objectives were to design an efficient survey methodology for sampling Atlantic Sturgeon Acipenser oxyrinchus by using side-scan sonar and to developmethods for analyzing these data. In North Carolina and South Carolina, we surveyed six rivers thought to contain varying abundances of sturgeon by using a combination of side-scan sonar, telemetry, and video cameras (i.e., to sample jumping sturgeon). Lower reaches of each river near the saltwater-freshwater interface were surveyed on three occasions (generally successive days), and we used occupancy modeling to analyze these data.We were able to detect sturgeon in five of six rivers by using these methods. Side-scan sonar was effective in detecting sturgeon, with estimated gear-specific detection probabilities ranging from 0.2 to 0.5 and river-specific occupancy estimates (per 2-km river segment) ranging from 0.0 to 0.8. Future extensions of this occupancy modeling framework will involve the use of side-scan sonar data to assess sturgeon habitat and abundance in different river systems.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/19425120.2013.816396","usgsCitation":"Flowers, H.J., and Hightower, J.E., 2013, A novel approach to surveying sturgeon using side-scan sonar and occupancy modeling: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 5, no. 1, p. 211-223, https://doi.org/10.1080/19425120.2013.816396.","productDescription":"13 p.","startPage":"211","endPage":"223","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043165","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473857,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/19425120.2013.816396","text":"Publisher Index Page"},{"id":300869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, South Carolina","otherGeospatial":"Cape Fear River, Edisto River, Neuse River, Pee Dee-Waccamaw River, Roanoke River, Santee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.76123046875,\n 36.53612263184686\n ],\n [\n -78.92578124999999,\n 35.782170703266075\n ],\n [\n -80.123291015625,\n 35.003003395276714\n ],\n [\n -80.91430664062499,\n 34.116352469972746\n ],\n [\n -81.84814453125,\n 33.247875947924385\n ],\n [\n -81.529541015625,\n 33.00866349457558\n ],\n [\n -81.38671875,\n 32.602361666817515\n ],\n [\n -81.112060546875,\n 32.24997445586331\n ],\n [\n -80.85937499999999,\n 31.924192605327708\n ],\n [\n -80.31005859375,\n 32.52828936482526\n ],\n [\n -79.881591796875,\n 32.75032260780972\n ],\n [\n -79.25537109375,\n 33.165145408240285\n ],\n [\n -78.936767578125,\n 33.669496972795535\n ],\n [\n -78.06884765624999,\n 33.93424531117312\n ],\n [\n -77.82714843749999,\n 34.1890858311724\n ],\n [\n -77.266845703125,\n 34.63320791137959\n ],\n [\n -76.53076171875,\n 34.687427949314845\n ],\n [\n -76.0693359375,\n 35.074964853989556\n ],\n [\n -75.509033203125,\n 35.28150065789119\n ],\n [\n -75.552978515625,\n 35.84453450421662\n ],\n [\n -75.882568359375,\n 36.56260003738548\n ],\n [\n -77.76123046875,\n 36.53612263184686\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-09-19","publicationStatus":"PW","scienceBaseUri":"5566eab3e4b0d9246a9ec2ca","contributors":{"authors":[{"text":"Flowers, H. Jared","contributorId":140974,"corporation":false,"usgs":false,"family":"Flowers","given":"H.","email":"","middleInitial":"Jared","affiliations":[],"preferred":false,"id":547784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hightower, Joseph E. jhightower@usgs.gov","contributorId":835,"corporation":false,"usgs":true,"family":"Hightower","given":"Joseph","email":"jhightower@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547467,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045743,"text":"ds709Y - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ahankashan mineral district in Afghanistan","interactions":[],"lastModifiedDate":"2013-05-01T21:37:12","indexId":"ds709Y","displayToPublicDate":"2013-05-01T00:00:00","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":"Y","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ahankashan mineral district 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 Ahankashan mineral district, which has copper and gold deposits.\n\nALOS 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, 2010),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.\n\nThe 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. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were 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).\n\nAll image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Ahankashan) 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 Ahankashan 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/ds709Y","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey","usgsCitation":"Davis, P.A., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ahankashan mineral district in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme; 4 Index Maps; 10 Image Files; 10 Metadata; Shapefiles, https://doi.org/10.3133/ds709Y.","productDescription":"HTML Document; Readme; 4 Index Maps; 10 Image Files; 10 Metadata; Shapefiles","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":271706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709Y.png"},{"id":271700,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/y/"},{"id":271701,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/y/1_readme.txt"},{"id":271702,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/y/index_maps/index_maps.html"},{"id":271703,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/y/image_files/image_files.html"},{"id":271704,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/y/metadata/metadata.html"},{"id":271705,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/y/shapefiles/shapefiles.html"}],"country":"Afghanistan","otherGeospatial":"Ahankashan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.52,29.38 ], [ 60.52,38.49 ], [ 74.89,38.49 ], [ 74.89,29.38 ], [ 60.52,29.38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51822b6be4b04bbc6ead2702","contributors":{"editors":[{"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":509319,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"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":478226,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045744,"text":"ds709AA - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan mineral district in Afghanistan","interactions":[],"lastModifiedDate":"2013-05-01T21:52:05","indexId":"ds709AA","displayToPublicDate":"2013-05-01T00:00:00","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":"AA","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan mineral district 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 South Bamyan mineral district, which has areas with a spectral reflectance anomaly that require field investigation.\n\nALOS 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),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.\n\nThe 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. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were 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).\n\nAll image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for South Bamyan) and the WGS84 datum. The final image mosaics for the South Bamyan 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/ds709AA","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey","usgsCitation":"Davis, P.A., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan mineral district in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme; 4 Index Maps; 2 Image Files; 2 Metadata; Shapefiles, https://doi.org/10.3133/ds709AA.","productDescription":"HTML Document; Readme; 4 Index Maps; 2 Image Files; 2 Metadata; Shapefiles","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":271713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709AA.png"},{"id":271709,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/aa/index_maps/index_maps.html"},{"id":271710,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/aa/image_files/image_files.html"},{"id":271711,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/aa/metadata/metadata.html"},{"id":271712,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/aa/shapefiles/shapefiles.html"},{"id":271707,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/aa/"},{"id":271708,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/aa/1_readme.txt"}],"country":"Afghanistan","otherGeospatial":"South Bamyan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.52,29.38 ], [ 60.52,38.49 ], [ 74.89,38.49 ], [ 74.89,29.38 ], [ 60.52,29.38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51822b6ce4b04bbc6ead270a","contributors":{"editors":[{"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":509320,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"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":478227,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70042887,"text":"70042887 - 2013 - Short-term variability of 7Be atmospheric deposition and watershed response in a Pacific coastal stream, Monterey Bay, California, USA","interactions":[],"lastModifiedDate":"2013-05-10T10:30:22","indexId":"70042887","displayToPublicDate":"2013-05-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2263,"text":"Journal of Environmental Radioactivity","active":true,"publicationSubtype":{"id":10}},"title":"Short-term variability of 7Be atmospheric deposition and watershed response in a Pacific coastal stream, Monterey Bay, California, USA","docAbstract":"Beryllium-7 is a powerful and commonly used tracer for environmental processes such as watershed sediment provenance, soil erosion, fluvial and nearshore sediment cycling, and atmospheric fallout. However, few studies have quantified temporal or spatial variability of 7Be accumulation from atmospheric fallout, and parameters that would better define the uses and limitations of this geochemical tracer. We investigated the abundance and variability of 7Be in atmospheric deposition in both rain events and dry periods, and in stream surface-water samples collected over a ten-month interval at sites near northern Monterey Bay (37°N, 122°W) on the central California coast, a region characterized by a rainy winters, dry summers, and small mountainous streams with flashy hydrology. The range of 7Be activity in rainwater samples from the main sampling site was 1.3–4.4 Bq L−1, with a mean (±standard deviation) of 2.2 ± 0.9 Bq L−1, and a volume-weighted average of 2.0 Bq L−1. The range of wet atmospheric deposition was 18–188 Bq m−2 per rain event, with a mean of 72 ± 53 Bq m−2. Dry deposition fluxes of 7Be ranged from less than 0.01 up to 0.45 Bq m−2 d−1, with an estimated dry season deposition of 7 Bq m−2 month−1. Annualized 7Be atmospheric deposition was approximately 1900 Bq m−2 yr−1, with most deposition via rainwater (>95%) and little via dry deposition. Overall, these activities and deposition fluxes are similar to values found in other coastal locations with comparable latitude and Mediterranean-type climate. Particulate 7Be values in the surface water of the San Lorenzo River in Santa Cruz, California, ranged from <0.01 Bq g−1 to 0.6 Bq g−1, with a median activity of 0.26 Bq g−1. A large storm event in January 2010 characterized by prolonged flooding resulted in the entrainment of 7Be-depleted sediment, presumably from substantial erosion in the watershed. There were too few particulate 7Be data over the storm to accurately model a 7Be load, but the results suggest enhanced watershed export of 7Be from small, mountainous river systems compared to other watershed types.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Radioactivity","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvrad.2013.02.004","usgsCitation":"Conaway, C., Storlazzi, C., Draut, A.E., and Swarzenski, P.W., 2013, Short-term variability of 7Be atmospheric deposition and watershed response in a Pacific coastal stream, Monterey Bay, California, USA: Journal of Environmental Radioactivity, v. 120, p. 94-103, https://doi.org/10.1016/j.jenvrad.2013.02.004.","startPage":"94","endPage":"103","numberOfPages":"10","ipdsId":"IP-041747","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":272171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272170,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jenvrad.2013.02.004"}],"country":"United States","state":"California","otherGeospatial":"Monterey Bay;San Lorenzo River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.3,36.9 ], [ -122.3,37.3 ], [ -122.9,37.3 ], [ -122.9,36.9 ], [ -122.3,36.9 ] ] ] } } ] }","volume":"120","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518e16e1e4b05ebc8f7cc2ff","contributors":{"authors":[{"text":"Conaway, Christopher H.","contributorId":52620,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher H.","affiliations":[],"preferred":false,"id":472506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":77889,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","affiliations":[],"preferred":false,"id":472507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Draut, Amy E.","contributorId":92215,"corporation":false,"usgs":true,"family":"Draut","given":"Amy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":472508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472505,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045732,"text":"70045732 - 2013 - Habitat use of breeding green turtles Chelonia mydas tagged in Dry Tortugas National Park: Making use of local and regional MPAs","interactions":[],"lastModifiedDate":"2022-11-14T16:49:55.107374","indexId":"70045732","displayToPublicDate":"2013-05-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Habitat use of breeding green turtles Chelonia mydas tagged in Dry Tortugas National Park: Making use of local and regional MPAs","title":"Habitat use of breeding green turtles Chelonia mydas tagged in Dry Tortugas National Park: Making use of local and regional MPAs","docAbstract":"Use of existing marine protected areas (MPAs) by far-ranging marine turtles can be determined using satellite telemetry. Because of a lack of information on MPA use by marine turtles in the Gulf of Mexico, we used satellite transmitters in 2010 and 2011 to track movements of 11 adult female breeding green turtles (Chelonia mydas) tagged in Dry Tortugas National Park (DRTO), in the Gulf of Mexico, south Florida, USA. Throughout the study period, turtles emerged every 9–18 days to nest. During the intervals between nesting episodes (i.e., inter-nesting periods), the turtles consistently used a common core-area within the DRTO boundary, determined using individual 50% kernel-density estimates (KDEs). We mapped the area in DRTO where individual turtle 50% KDEs overlapped using the USGS Along-Track Reef-Imaging System, and determined the diversity and distribution of various benthic-cover types within the mapped area. We also tracked turtles post-nesting as they transited to foraging sites 5–282 km away from tagging beaches; these sites were located both within DRTO and in the surrounding area of the Florida Keys and Florida Keys National Marine Sanctuary (FKNMS), a regional MPA. Year-round residency of 9 out of 11 individuals (82%) both within DRTO and in the FKNMS represents novel non-migratory behavior, which offers an opportunity for conservation of this imperiled species at both local and regional scales. These data comprise the first satellite-tracking results on adult nesting green turtles at this remote study site. Additional tracking could reveal whether the distinct inter-nesting and foraging sites delineated here will be repeatedly used in the future by these and other breeding green turtles.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.biocon.2013.03.019","usgsCitation":"Hart, K., Zawada, D., Fujisaki, I., and Lidz, B.H., 2013, Habitat use of breeding green turtles Chelonia mydas tagged in Dry Tortugas National Park: Making use of local and regional MPAs: Biological Conservation, v. 161, p. 142-154, https://doi.org/10.1016/j.biocon.2013.03.019.","productDescription":"13 p.","startPage":"142","endPage":"154","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":271688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.76673820002982,\n 24.702032234521695\n ],\n [\n -82.80111355697035,\n 24.72611070301882\n ],\n [\n -82.86737930528973,\n 24.725734512768284\n ],\n [\n -82.90051217944944,\n 24.717834254792294\n ],\n [\n -82.96719208869578,\n 24.649344358619032\n ],\n [\n -82.96553544498762,\n 24.5665042001456\n ],\n [\n -82.89678473110656,\n 24.566880870376693\n ],\n [\n -82.80028523511646,\n 24.617720954532814\n ],\n [\n -82.76632403910288,\n 24.66891673942027\n ],\n [\n -82.76632403910288,\n 24.702032234521695\n ],\n [\n -82.76673820002982,\n 24.702032234521695\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"161","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51822b69e4b04bbc6ead26fa","chorus":{"doi":"10.1016/j.biocon.2013.03.019","url":"http://dx.doi.org/10.1016/j.biocon.2013.03.019","publisher":"Elsevier BV","authors":"Hart Kristen M., Zawada David G., Fujisaki Ikuko, Lidz Barbara H.","journalName":"Biological Conservation","publicationDate":"5/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Hart, Kristen","contributorId":49253,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[],"preferred":false,"id":478212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zawada, David G. 0000-0003-4547-4878 dzawada@usgs.gov","orcid":"https://orcid.org/0000-0003-4547-4878","contributorId":1898,"corporation":false,"usgs":true,"family":"Zawada","given":"David G.","email":"dzawada@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":478209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fujisaki, Ikuko","contributorId":31108,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":478211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lidz, Barbara H. blidz@usgs.gov","contributorId":2475,"corporation":false,"usgs":true,"family":"Lidz","given":"Barbara","email":"blidz@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":478210,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045736,"text":"sir20135045 - 2013 - Investigations of groundwater system and simulation of regional groundwater flow for North Penn Area 7 Superfund site, Montgomery County, Pennsylvania","interactions":[],"lastModifiedDate":"2015-05-01T08:11:34","indexId":"sir20135045","displayToPublicDate":"2013-05-01T00:00:00","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":"2013-5045","title":"Investigations of groundwater system and simulation of regional groundwater flow for North Penn Area 7 Superfund site, Montgomery County, Pennsylvania","docAbstract":"Groundwater in the vicinity of several industrial facilities in Upper Gwynedd Township and vicinity, Montgomery County, in southeast Pennsylvania has been shown to be contaminated with volatile organic compounds (VOCs), the most common of which is the solvent trichloroethylene (TCE). The 2-square-mile area was placed on the National Priorities List as the North Penn Area 7 Superfund site by the U.S. Environmental Protection Agency (USEPA) in 1989. The U.S. Geological Survey (USGS) conducted geophysical logging, aquifer testing, and water-level monitoring, and measured streamflows in and near North Penn Area 7 from fall 2000 through fall 2006 in a technical assistance study for the USEPA to develop an understanding of the hydrogeologic framework in the area as part of the USEPA Remedial Investigation. In addition, the USGS developed a groundwater-flow computer model based on the hydrogeologic framework to simulate regional groundwater flow and to estimate directions of groundwater flow and pathways of groundwater contaminants. The study area is underlain by Triassic- and Jurassic-age sandstones and shales of the Lockatong Formation and Brunswick Group in the Mesozoic Newark Basin. Regionally, these rocks strike northeast and dip to the northwest. The sequence of rocks form a fractured-sedimentary-rock aquifer that acts as a set of confined to partially confined layers of differing permeabilities. Depth to competent bedrock typically is less than 20 ft below land surface. The aquifer layers are recharged locally by precipitation and discharge locally to streams. The general configuration of the potentiometric surface in the aquifer is similar to topography, except in areas affected by pumping. The headwaters of Wissahickon Creek are nearby, and the stream flows southwest, parallel to strike, to bisect North Penn Area 7. Groundwater is pumped in the vicinity of North Penn Area 7 for industrial use, public supply, and residential supply. Results of field investigations by USGS at the site and results from other studies support, and are consistent with, a conceptual model of a layered leaky aquifer where the dip of the beds has a strong control on hydraulic connections in the groundwater system. Connections within and (or) parallel to bedding tend to be greater than across bedding. Transmissivities of aquifer intervals isolated by packers ranged over three orders of magnitude [from about 2.8 to 2,290 square feet per day (ft2/d) or 0.26 to 213 square meters per day (m2/d)], did not appear to differ much by mapped geologic unit, but showed some relation to depth being relatively smaller in the shallowest and deepest intervals (0 to 50 ft and more than 250 ft below land surface, respectively) compared to the intermediate depth intervals (50 to 250 ft below land surface) tested. Transmissivities estimated from multiple-observation well aquifer tests ranged from about 700 to 2,300 ft2/d (65 to 214 m2/d). Results of chemical analyses of water from isolated intervals or monitoring wells open to short sections of the aquifer show vertical differences in concentrations; chloride and silica concentrations generally were greater in shallow intervals than in deeper intervals. Chloride concentrations greater than 100 milligrams per liter (mg/L), combined with distinctive chloride/bromide ratios, indicate a different source of chloride in the western part of North Penn Area 7 than elsewhere in the site. Groundwater flow at a regional scale under steady-state conditions was simulated by use of a numerical model (MODFLOW-2000) for North Penn Area 7 with different layers representing saprolite/highly weathered rock near the surface and unweathered competent bedrock. The sedimentary formations that underlie the study area were modeled using dipping model layers for intermediate and deep zones of unweathered, fractured rock. Horizontal cell model size was 100 meters (m) by 100 meters (328 ft by 328 ft), and model layer thickness ranged from 6 m (19.7 ft) representing shallow weathered rock and saprolite up to 200 m (656 ft) representing deeper dipping bedrock. The model did not include detailed structure to account for local-scale differences in hydraulic properties, with the result that local-scale groundwater flow may not be well simulated. Additional detailed multi-well aquifer tests would be needed to establish the extent of interconnection between intervals at the local scale to address remediation of contamination at each source area. This regional groundwater-flow model was calibrated against measured groundwater levels (1996, 2000, and 2005) and base flow estimated from selected streamflow measurements by use of nonlinear-regression parameter-estimation algorithms to determine hydraulic conductivity and anisotropy of hydraulic conductivity, streambed hydraulic conductivity, and recharge during calibration periods. Results of the simulation using the calibrated regional model indicate that the aquifer appears to be anisotropic where hydraulic conductivity is greatest parallel to the orientation of bedding of the formations underlying the area and least in the cross-bed direction. The maximum hydraulic conductivity is aligned with the average regional strike of the formations, which is “subhorizontal” in the model because the altitudes of the beds and model cells vary in the strike, as well as dip, direction. Estimated subhorizontal hydraulic conductivities (in strike direction parallel to dipping beds) range from 0.001 to 1.67 meters per day (0.0032 to 5.5 feet per day). The ratio of minimum (dip direction) to maximum (strike direction) subhorizontal hydraulic conductivity ranges from 1/3.1 to 1/8.6, and the ratio of vertical to horizontal hydraulic conductivity ranges from 1/1 to 1/478. However, limited available field data precluded rigorous calibration of vertical anisotropy in the model. Estimated recharge rates corresponding to calibration periods in 1996, 2000, and 2005 are 150, 109, and 124 millimeters per year (5.9, 4.3, and 4.9 inches per year), respectively. The calibrated groundwater-flow model was used to simulate groundwater flow under steady-state conditions during periods of relatively high withdrawals (pumpage) (1990) and relatively low withdrawals (2000 and 2005). Groundwater-flow paths originating from recharge areas near known areas of soil contamination (sources) were simulated. Pumped industrial and production wells captured more groundwater from several of these sources during 1990 than after 1990 when pumping declined or ceased and greater amounts of contaminated groundwater moved away from North Penn Area 7 Superfund site to surrounding areas. Uncertainty in simulated groundwater-flow paths from contaminant sources and contributing areas, resulting from uncertainty in estimated hydraulic properties of the model, was illustrated through Monte Carlo simulations. The effect of uncertainty in the vertical anisotropy was not included in the Monte Carlo simulations. Contributing areas indicating the general configuration of groundwater flow towards production well MG-202 (L-22) in the study area also were simulated for the different time periods; as simulated, the flow paths do not pass through any identified contaminant source in North Penn Area 7. However, contributing areas to wells, such as MG-202, located near many pumped wells are particularly complex and, in some cases, include areas that contribute flow to streams that subsequently recharge the aquifer through stream loss. In these cases, water-quality constituents, including contaminants that are present in surface water may be drawn into the aquifer to nearby pumped wells. Results of a simulated shutdown of well MG-202 under steady-state 2005 conditions showed that the area contributing recharge for nearby production well MG-76 (L-17), when MG-202 is not pumping, shifts downstream and is similar to the area contributing recharge for MG-202 when both wells are pumping. Concentrations of constituents in groundwater samples collected in fall 2005 or spring 2006 were compared to simulated groundwater-flow paths for the year 2005 to provide a qualitative assessment of model results. The observed spatial distribution of selected constituents, including TCE, CFC-11, and CFC-113 in groundwater in 2005 and the chloride/bromide mass ratios in 2006, generally were consistent with the model results of the simulated 2005 groundwater-flow paths at North Penn Area 7, indicating the presence of several separate sources of contaminants within North Penn Area 7.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135045","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Senior, L.A., and Goode, D., 2013, Investigations of groundwater system and simulation of regional groundwater flow for North Penn Area 7 Superfund site, Montgomery County, Pennsylvania (Version 1: Originally posted April 30, 2013; Version 1.1: April 30, 2015): U.S. Geological Survey Scientific Investigations Report 2013-5045, xii, 95 p., https://doi.org/10.3133/sir20135045.","productDescription":"xii, 95 p.","numberOfPages":"112","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1990-01-01","temporalEnd":"2006-07-01","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":300001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135045.jpg"},{"id":271689,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5045/"},{"id":271690,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5045/support/sir2013-5045.pdf","text":"Report","size":"14.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"scale":"24000","projection":"Universal Transverse Mercator, Zone 18","datum":"North American Datum of 1927","country":"United States","state":"Pennsylvania","county":"Montgomery","city":"Upper Gwynedd","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.33050537109375,\n 40.17939793281656\n ],\n [\n -75.33050537109375,\n 40.23079086353824\n ],\n [\n -75.23162841796875,\n 40.23079086353824\n ],\n [\n -75.23162841796875,\n 40.17939793281656\n ],\n [\n -75.33050537109375,\n 40.17939793281656\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1: Originally posted April 30, 2013; Version 1.1: April 30, 2015","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5543522ee4b0a658d79414af","contributors":{"authors":[{"text":"Senior, Lisa A. 0000-0003-2629-1996 lasenior@usgs.gov","orcid":"https://orcid.org/0000-0003-2629-1996","contributorId":2150,"corporation":false,"usgs":true,"family":"Senior","given":"Lisa","email":"lasenior@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goode, Daniel J. 0000-0002-8527-2456 djgoode@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":2433,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel J.","email":"djgoode@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478214,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045741,"text":"sir20135024 - 2013 - Estimated rates of groundwater recharge to the Chicot, Evangeline and Jasper aquifers by using environmental tracers in Montgomery and adjacent counties, Texas, 2008 and 2011","interactions":[],"lastModifiedDate":"2016-08-05T14:04:03","indexId":"sir20135024","displayToPublicDate":"2013-05-01T00:00:00","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":"2013-5024","title":"Estimated rates of groundwater recharge to the Chicot, Evangeline and Jasper aquifers by using environmental tracers in Montgomery and adjacent counties, Texas, 2008 and 2011","docAbstract":"Montgomery County is in the northern part of the Houston, Texas, metropolitan area, the fourth most populous metropolitan area in the United States. As populations have increased since the 1980s, groundwater has become an important resource for public-water supply and industry in the rapidly growing area of Montgomery County. Groundwater availability from the Gulf Coast aquifer system is a primary concern for water managers and community planners in Montgomery County and requires a better understanding of the rate of recharge to the system. The Gulf Coast aquifer system in Montgomery County consists of the Chicot, Evangeline, and Jasper aquifers, the Burkeville confining unit, and underlying Catahoula confining system. The individual sand and clay sequences of the aquifers composing the Gulf Coast aquifer system are not laterally or vertically continuous on a regional scale; however, on a local scale, individual sand and clay lenses can extend over several miles. The U.S. Geological Survey, in cooperation with the Lone Star Groundwater Conservation District, collected groundwater-quality samples from selected wells within or near Montgomery County in 2008 and analyzed these samples for concentrations of chlorofluorocarbons (CFCs), sulfur hexafluoride (SF6), tritium (3H), helium-3/tritium (3He/3H), helium-4 (4He), and dissolved gases (DG) that include argon, carbon dioxide, methane, nitrogen and oxygen. Groundwater ages, or apparent age, representing residence times since time of recharge, were determined by using the assumption of a piston-flow transport model. Most of the environmental tracer data indicated the groundwater was recharged prior to the 1950s, limiting the usefulness of CFCs, SF6, and 3H concentrations as tracers. In many cases, no tracer was usable at a well for the purpose of estimating an apparent age. Wells not usable for estimating an apparent age were resampled in 2011 and analyzed for concentrations of major ions and carbon-14 (14C). At six of these wells, additional 4He and DG samples were collected and analyzed.
\nRecharge rates estimated from environmental tracer data are dependent upon several hydrogeologic variables and have inherent uncertainties. By using the recharge estimates derived from samples collected from 14 wells completed in the Chicot aquifer for which apparent groundwater ages could be determined, recharge to the Chicot aquifer ranged from 0.2 to 7.2 inches (in.) per year (yr). Based on data from one well, estimated recharge to the unconfined zone of the Evangeline aquifer (outcrop) was 0.1 in./yr. Based on data collected from eight wells, estimated rates of recharge to the confined zone of the Evangeline aquifer ranged from less than 0.1 to 2.8 in./yr. Based on data from one well, estimated recharge to the unconfined zone of the Jasper aquifer (outcrop) was 0.5 in./yr. Based on data collected from nine wells, estimated rates of recharge to the confined zone of the Jasper aquifer ranged from less than 0.1 to 0.1 in./yr. The complexity of the hydrogeology in the area, uncertainty in the conceptual model, and numerical assumptions required in the determination of the recharge rates all pose limitations and need to be considered when evaluating these data on a countywide or regional scale. The estimated recharge rates calculated for this study are specific to each well location and should not be extrapolated or inferred as a countywide average. Local variations in the hydrogeology and surficial conditions can affect the recharge rate at a local scale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135024","collaboration":"Prepared in cooperation with the Lone Star Groundwater Conservation District","usgsCitation":"Oden, T., and Truini, M., 2013, Estimated rates of groundwater recharge to the Chicot, Evangeline and Jasper aquifers by using environmental tracers in Montgomery and adjacent counties, Texas, 2008 and 2011: U.S. Geological Survey Scientific Investigations Report 2013-5024, Document: viii, 50 p.; Appendixes 1-5, https://doi.org/10.3133/sir20135024.","productDescription":"Document: viii, 50 p.; Appendixes 1-5","numberOfPages":"61","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042849","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":271699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135024.gif"},{"id":271693,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5024/SIR2013-5024.pdf"},{"id":271694,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5024/Appendixes/Appendix%202.xlsx","text":"Appendix 2"},{"id":271695,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5024/Appendixes/Appendix%201.xlsx","text":"Appendix 1"},{"id":271692,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5024/"},{"id":271696,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5024/Appendixes/Appendix%203.pdf","text":"Appendix 3"},{"id":271697,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5024/Appendixes/Appendix%204.xlsx","text":"Appendix 4"},{"id":271698,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5024/Appendixes/Appendix%205.xlsx","text":"Appendix 5"}],"country":"United States","state":"Texas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.6,25.8 ], [ -106.6,36.5 ], [ -93.5,36.5 ], [ -93.5,25.8 ], [ -106.6,25.8 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51822b53e4b04bbc6ead26f6","contributors":{"authors":[{"text":"Oden, Timothy D. toden@usgs.gov","contributorId":1284,"corporation":false,"usgs":true,"family":"Oden","given":"Timothy D.","email":"toden@usgs.gov","affiliations":[],"preferred":true,"id":478225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Truini, Margot mtruini@usgs.gov","contributorId":599,"corporation":false,"usgs":true,"family":"Truini","given":"Margot","email":"mtruini@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478224,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045745,"text":"ds709BB - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Bamyan mineral district in Afghanistan","interactions":[],"lastModifiedDate":"2013-05-01T22:02:40","indexId":"ds709BB","displayToPublicDate":"2013-05-01T00:00:00","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":"BB","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Bamyan mineral district 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 North Bamyan mineral district, which has copper deposits.\n\nALOS 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), 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.\n\nThe 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. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were 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).\n\nAll image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for North Bamyan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the North Bamyan 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/ds709BB","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey","usgsCitation":"Davis, P.A., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Bamyan mineral district in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme; 4 Index Maps; 4 Image Files; 4 Metadata; Shapefiles, https://doi.org/10.3133/ds709BB.","productDescription":"HTML Document; Readme; 4 Index Maps; 4 Image Files; 4 Metadata; Shapefiles","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":271720,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709BB.jpg"},{"id":271716,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/bb/index_maps/index_maps.html"},{"id":271717,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/bb/image_files/image_files.html"},{"id":271718,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/bb/metadata/metadata.html"},{"id":271719,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/bb/shapefiles/shapefiles.html"},{"id":271714,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/bb/"},{"id":271715,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/bb/1_readme.txt"}],"country":"Afghanistan","otherGeospatial":"North Bamyan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.52,29.38 ], [ 60.52,38.49 ], [ 74.89,38.49 ], [ 74.89,29.38 ], [ 60.52,29.38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51822b6ce4b04bbc6ead2706","contributors":{"editors":[{"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":509321,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"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":478228,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70173756,"text":"70173756 - 2013 - Incorporating harvest rates into the sex-age-kill model for white-tailed deer","interactions":[],"lastModifiedDate":"2016-06-08T16:14:05","indexId":"70173756","displayToPublicDate":"2013-05-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating harvest rates into the sex-age-kill model for white-tailed deer","docAbstract":"Although monitoring population trends is an essential component of game species management, wildlife managers rarely have complete counts of abundance. Often, they rely on population models to monitor population trends. As imperfect representations of real-world populations, models must be rigorously evaluated to be applied appropriately. Previous research has evaluated population models for white-tailed deer (Odocoileus virginianus); however, the precision and reliability of these models when tested against empirical measures of variability and bias largely is untested. We were able to statistically evaluate the Pennsylvania sex-age-kill (PASAK) population model using realistic error measured using data from 1,131 radiocollared white-tailed deer in Pennsylvania from 2002 to 2008. We used these data and harvest data (number killed, age-sex structure, etc.) to estimate precision of abundance estimates, identify the most efficient harvest data collection with respect to precision of parameter estimates, and evaluate PASAK model robustness to violation of assumptions. Median coefficient of variation (CV) estimates by Wildlife Management Unit, 13.2% in the most recent year, were slightly above benchmarks recommended for managing game species populations. Doubling reporting rates by hunters or doubling the number of deer checked by personnel in the field reduced median CVs to recommended levels. The PASAK model was robust to errors in estimates for adult male harvest rates but was sensitive to errors in subadult male harvest rates, especially in populations with lower harvest rates. In particular, an error in subadult (1.5-yr-old) male harvest rates resulted in the opposite error in subadult male, adult female, and juvenile population estimates. Also, evidence of a greater harvest probability for subadult female deer when compared with adult (≥2.5-yr-old) female deer resulted in a 9.5% underestimate of the population using the PASAK model. Because obtaining appropriate sample sizes, by management unit, to estimate harvest rate parameters each year may be too expensive, assumptions of constant annual harvest rates may be necessary. However, if changes in harvest regulations or hunter behavior influence subadult male harvest rates, the PASAK model could provide an unreliable index to population changes.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.486","usgsCitation":"Norton, A.S., Diefenbach, D.R., Rosenberry, C.S., and Wallingford, B.D., 2013, Incorporating harvest rates into the sex-age-kill model for white-tailed deer: Journal of Wildlife Management, v. 77, no. 3, p. 606-615, https://doi.org/10.1002/jwmg.486.","productDescription":"10 p.","startPage":"606","endPage":"615","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-031059","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2012-12-11","publicationStatus":"PW","scienceBaseUri":"575941ffe4b04f417c2568a4","contributors":{"authors":[{"text":"Norton, Andrew S.","contributorId":171631,"corporation":false,"usgs":false,"family":"Norton","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":638133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":638068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Christopher S.","contributorId":171633,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":638134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallingford, Bret D.","contributorId":171632,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":638135,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}