[1] Linkages between permafrost distribution and lake surface-area changes in cold regions have not been previously examined over a large scale because of the paucity of subsurface permafrost information. Here, a first large-scale examination of these linkages is made over a 5150 km2 area of Yukon Flats, Alaska, USA, by evaluating the relationship between lake surface-area changes during 1979–2009, derived from Landsat satellite data, and sublacustrine groundwater flow-path connectivity inferred from a pioneering, airborne geophysical survey of permafrost. The results suggest that the shallow (few tens of meters) thaw state of permafrost has more influence than deeper permafrost conditions on the evolving water budgets of lakes on a multidecadal time scale. In the region studied, these key shallow aquifers have high hydraulic conductivity and great spatial variability in thaw state, making groundwater flow and associated lake level evolution particularly sensitive to climate change owing to the close proximity of these aquifers to the atmosphere.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/grl.50187","usgsCitation":"Jepsen, S.M., Voss, C.I., Walvoord, M.A., Minsley, B.J., and Rover, J., 2013, Linkages between lake shrinkage/expansion and sublacustrine permafrost distribution determined from remote sensing of interior Alaska, USA: Geophysical Research Letters, v. 40, no. 5, p. 882-887, https://doi.org/10.1002/grl.50187.","productDescription":"6 p.","startPage":"882","endPage":"887","ipdsId":"IP-040838","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":473701,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/grl.50187","text":"Publisher Index Page"},{"id":341849,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148,\n 66.07\n ],\n [\n -145,\n 66.07\n ],\n [\n -145,\n 66.775\n ],\n [\n -148,\n 66.775\n ],\n [\n -148,\n 66.07\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-03-14","publicationStatus":"PW","scienceBaseUri":"592e84c8e4b092b266f10dc2","contributors":{"authors":[{"text":"Jepsen, Steven M. sjepsen@usgs.gov","contributorId":3892,"corporation":false,"usgs":true,"family":"Jepsen","given":"Steven","email":"sjepsen@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":696399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":696397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walvoord, Michelle Ann 0000-0003-4269-8366 walvoord@usgs.gov","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":147211,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"walvoord@usgs.gov","middleInitial":"Ann","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":696400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":696396,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rover, Jennifer 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":192333,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696398,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188859,"text":"70188859 - 2013 - Stratigraphy and chronology of Provo shoreline deposits and lake-level implications, Late Pleistocene Lake Bonneville, eastern Great Basin, USA","interactions":[],"lastModifiedDate":"2017-06-27T10:16:33","indexId":"70188859","displayToPublicDate":"2013-07-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1068,"text":"Boreas","active":true,"publicationSubtype":{"id":10}},"title":"Stratigraphy and chronology of Provo shoreline deposits and lake-level implications, Late Pleistocene Lake Bonneville, eastern Great Basin, USA","docAbstract":"The Provo shoreline of Lake Bonneville formed following the Bonneville flood, and, based on previous dating, was formed during a period of overflow from about 17.5 to 15.0 cal. ka. In many places the Provo shoreline consists of a pair of distinct shorelines, one ∼3 m higher than the other. We present data from two cuts through double beaches to show that the upper beach is younger and represents sedimentation after a lake-level rise. In addition, the lower beach deposits are internally stratified by beds that suggest three more lake-level rises during its development. The Provo beach complex thus appears to have been built during rising lake levels, which can be explained by rises in the overflow threshold by sequential landslide deposition. Evaluation of beach altitudes demonstrates that the two beach crests throughout the Bonneville basin experienced equivalent rebound from removal of the lake load, and therefore they formed after the rebound associated with the Bonneville flood occurred in early Provo time. However, radiocarbon ages on gastropods collected within the beach deposits suggest both that the sequence of five beach deposits formed from c.18.1 to c. 17.0 cal. ka, and that the Bonneville flood occurred before 18 cal. ka. These ages are discordant with previous dates on shells within offshore sands, and raise questions about the validity of radiocarbon ages for shells in Lake Bonneville as well as about the age of the Bonneville flood and Provo shoreline. The timing for maximum Provo lake depths and its association with climate stages during deglaciation remain unresolved.
","language":"English","publisher":"Wiley","doi":"10.1111/j.1502-3885.2012.00297.x","usgsCitation":"Miller, D., Oviatt, C., and McGeehin, J.P., 2013, Stratigraphy and chronology of Provo shoreline deposits and lake-level implications, Late Pleistocene Lake Bonneville, eastern Great Basin, USA: Boreas, v. 42, no. 2, p. 342-361, https://doi.org/10.1111/j.1502-3885.2012.00297.x.","productDescription":"20 p.","startPage":"342","endPage":"361","ipdsId":"IP-033686","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":342952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Nevada, Utah, Wyoming","otherGeospatial":"Lake Bonneville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.3,\n 42.7\n ],\n [\n -110.5,\n 42.7\n ],\n [\n -110.5,\n 37.5\n ],\n [\n -114.3,\n 37.5\n ],\n [\n -114.3,\n 42.7\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-10-25","publicationStatus":"PW","scienceBaseUri":"59536eaee4b062508e3c7ab3","contributors":{"authors":[{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oviatt, Charles G.","contributorId":13503,"corporation":false,"usgs":true,"family":"Oviatt","given":"Charles G.","affiliations":[],"preferred":false,"id":700722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGeehin, John P. mcgeehin@usgs.gov","contributorId":140956,"corporation":false,"usgs":true,"family":"McGeehin","given":"John","email":"mcgeehin@usgs.gov","middleInitial":"P.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":700723,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046942,"text":"ofr20121255 - 2013 - Groundwater quality and water-well characteristics in the Kickapoo Tribe of Oklahoma Jurisdictional Area, central Oklahoma, 1948--2011","interactions":[],"lastModifiedDate":"2013-07-09T15:46:19","indexId":"ofr20121255","displayToPublicDate":"2013-07-09T15:28:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1255","title":"Groundwater quality and water-well characteristics in the Kickapoo Tribe of Oklahoma Jurisdictional Area, central Oklahoma, 1948--2011","docAbstract":"In 2012, the U.S. Geological Survey, in cooperation with the Kickapoo Tribe of Oklahoma, compiled historical groundwater-quality data collected from 1948 to 2011 and water-well completion information in parts of Lincoln, Oklahoma, and Pottawatomie Counties in central Oklahoma to support the development of a comprehensive water-management plan for the Tribe’s jurisdictional area. In this study, water-quality data from 155 water wells, collected from 1948 to 2011, were retrieved from the U.S. Geological Survey National Water Information System database; these data include measurements of pH, specific conductance, and hardness and concentrations of the major ions, trace elements, and radionuclides that have Maximum Contaminant Levels or Secondary Maximum Contaminant Levels in public drinking-water supplies. Information about well characteristics includes ranges of well yield and well depth of private water wells in the study area and was compiled from the Oklahoma Water Resources Board Multi-Purpose Well Completion Report database. This report also shows depth to water from land surface by using shaded 30-foot contours that were created by using a geographic information system and spatial layers of a 2009 potentiometric surface (groundwater elevation) and land-surface elevation.\n\nWells in the study area produce water from the North Canadian River alluvial and terrace aquifers, the underlying Garber Sandstone and Wellington Formation that compose the Garber–Wellington aquifer, and the Chase, Council Grove, and Admire Groups. Water quality varies substantially between the alluvial and terrace aquifers and bedrock aquifers in the study area. Water from the alluvial aquifer has relatively high concentrations of dissolved solids and generally is used for livestock only, whereas water from the terrace aquifer has low concentrations of dissolved solids and is used extensively by households in the study area. Water from the bedrock aquifer also is used extensively by households but may have high concentrations of trace elements, including uranium, in some areas where groundwater pH is above 8.0.\n\nWell yields vary and are dependent on aquifer characteristics and well-completion practices. Well yields in the unconsolidated alluvial and terrace aquifers generally are higher than yields from bedrock aquifers but are limited by the thickness and extent of these river deposits. Well yields in the alluvium and terrace aquifers commonly range from 50 to 150 gallons per minute and may exceed 300 gallons per minute, whereas well yields in the bedrock aquifers commonly range from 25 to 50 gallons per minute in the western one-third of study area (Oklahoma County) and generally less than 25 gallons per minute in the eastern two-thirds of the study area (Lincoln and Pottawatomie Counties).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121255","collaboration":"Prepared in cooperation with the Kickapoo Tribe of Oklahoma","usgsCitation":"Becker, C., 2013, Groundwater quality and water-well characteristics in the Kickapoo Tribe of Oklahoma Jurisdictional Area, central Oklahoma, 1948--2011: U.S. Geological Survey Open-File Report 2012-1255, iv, 32 p.; Maps: 2 Sheets: 17 x 22 inches, https://doi.org/10.3133/ofr20121255.","productDescription":"iv, 32 p.; Maps: 2 Sheets: 17 x 22 inches","numberOfPages":"39","additionalOnlineFiles":"Y","temporalStart":"1948-01-01","temporalEnd":"2011-12-31","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":274808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121255.gif"},{"id":274806,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1255/Plate%201.pdf"},{"id":274807,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1255/Plate%202.pdf"},{"id":274804,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1255/"},{"id":274805,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1255/OFR_2012-1255.pdf"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Kickapoo Tribe Of Oklahoma Jurisdictional Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.333333,35.25 ], [ -97.333333,35.833333 ], [ -96.833333,35.833333 ], [ -96.833333,35.25 ], [ -97.333333,35.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dd22d8e4b0f72b44719c1b","contributors":{"authors":[{"text":"Becker, Carol 0000-0001-6652-4542 cjbecker@usgs.gov","orcid":"https://orcid.org/0000-0001-6652-4542","contributorId":2489,"corporation":false,"usgs":true,"family":"Becker","given":"Carol","email":"cjbecker@usgs.gov","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480654,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046941,"text":"sir20135128 - 2013 - Erosion monitoring along the Coosa River below Logan Martin Dam near Vincent, Alabama, using terrestrial light detection and ranging (T-LiDAR) technology","interactions":[],"lastModifiedDate":"2013-07-09T15:28:27","indexId":"sir20135128","displayToPublicDate":"2013-07-09T15:19:00","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":"2013-5128","title":"Erosion monitoring along the Coosa River below Logan Martin Dam near Vincent, Alabama, using terrestrial light detection and ranging (T-LiDAR) technology","docAbstract":"Alabama Power operates a series of dams on the Coosa River in east central Alabama. These dams form six reservoirs that provide power generation, flood control, recreation, economic opportunity, and fish and wildlife habitats to the region. The Logan Martin Reservoir is located approximately 45 kilometers east of Birmingham and borders Saint Clair and Talladega Counties. Discharges below the reservoir are controlled by power generation at Logan Martin Dam, and there has been an ongoing concern about the stability of the streambanks downstream of the dam. The U.S. Geological Survey, in cooperation with Alabama Power conducted a scientific investigation of the geomorphic conditions of a 115-meter length of streambank along the Coosa River by using tripod-mounted terrestrial light detection and ranging technology. Two surveys were conducted before and after the winter flood season of 2010 to determine the extent and magnitude of geomorphic change. A comparison of the terrestrial light detection and ranging datasets indicated that approximately 40 cubic meters of material had been eroded from the upstream section of the study area. The terrestrial light detection and ranging data included in this report consist of electronic point cloud files containing several million georeferenced data points, as well as a surface model measuring changes between scans.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135128","collaboration":"Prepared in cooperation with the Alabama Power","usgsCitation":"Kimbrow, D.R., and Lee, K., 2013, Erosion monitoring along the Coosa River below Logan Martin Dam near Vincent, Alabama, using terrestrial light detection and ranging (T-LiDAR) technology: U.S. Geological Survey Scientific Investigations Report 2013-5128, iv, 9 p., https://doi.org/10.3133/sir20135128.","productDescription":"iv, 9 p.","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"links":[{"id":274803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135128.gif"},{"id":274801,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5128/"},{"id":274802,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5128/pdf/sir2013-5128.pdf"}],"country":"United States","state":"Alabama","county":"Shelby County","city":"Vincent","otherGeospatial":"Coosa River;Logan Martin Dam","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -86.345833,33.4125 ], [ -86.345833,33.429167 ], [ -86.333333,33.429167 ], [ -86.333333,33.4125 ], [ -86.345833,33.4125 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dd22d8e4b0f72b44719c17","contributors":{"authors":[{"text":"Kimbrow, Dustin R. dkimbrow@usgs.gov","contributorId":3915,"corporation":false,"usgs":true,"family":"Kimbrow","given":"Dustin","email":"dkimbrow@usgs.gov","middleInitial":"R.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Kathryn G.","contributorId":108009,"corporation":false,"usgs":true,"family":"Lee","given":"Kathryn G.","affiliations":[],"preferred":false,"id":480653,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046792,"text":"sim3253 - 2013 - Marine benthic habitat mapping of the West Arm, Glacier Bay National Park and Preserve, Alaska","interactions":[],"lastModifiedDate":"2013-07-09T15:47:55","indexId":"sim3253","displayToPublicDate":"2013-07-09T14:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3253","title":"Marine benthic habitat mapping of the West Arm, Glacier Bay National Park and Preserve, Alaska","docAbstract":"Seafloor geology and potential benthic habitats were mapped in West Arm, Glacier Bay National Park and Preserve, Alaska, using multibeam sonar, groundtruthed observations, and geological interpretations. The West Arm of Glacier Bay is a recently deglaciated fjord system under the influence of glacial and paraglacial marine processes. High glacially derived sediment and meltwater fluxes, slope instabilities, and variable bathymetry result in a highly dynamic estuarine environment and benthic ecosystem. We characterize the fjord seafloor and potential benthic habitats using the recently developed Coastal and Marine Ecological Classification Standard (CMECS) by the National Oceanic and Atmospheric Administration (NOAA) and NatureServe. Due to the high flux of glacially sourced fines, mud is the dominant substrate within the West Arm. Water-column characteristics are addressed using a combination of CTD and circulation model results. We also present sediment accumulation data derived from differential bathymetry. These data show the West Arm is divided into two contrasting environments: a dynamic upper fjord and a relatively static lower fjord. The results of these analyses serve as a test of the CMECS classification scheme and as a baseline for ongoing and future mapping efforts and correlations between seafloor substrate, benthic habitats, and glacimarine processes.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3253","usgsCitation":"Hodson, T.O., Cochrane, G.R., and Powell, R.D., 2013, Marine benthic habitat mapping of the West Arm, Glacier Bay National Park and Preserve, Alaska: U.S. Geological Survey Scientific Investigations Map 3253, Pamphlet: iii, 29 p.; Sheet 1: 41.86 inches x 38.86 inches; Sheet 2: 42.30 inches x 36.92 inches; Sheet 3: 41.86 inches x 38.86 inches; Sheet 4: 42.30 inches x 36.87 inches; Readme txt; Metadata folder; GIS data folder, https://doi.org/10.3133/sim3253.","productDescription":"Pamphlet: iii, 29 p.; Sheet 1: 41.86 inches x 38.86 inches; Sheet 2: 42.30 inches x 36.92 inches; Sheet 3: 41.86 inches x 38.86 inches; Sheet 4: 42.30 inches x 36.87 inches; Readme txt; Metadata folder; GIS data folder","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-034188","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":274809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3253.jpg"},{"id":274691,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3253/"},{"id":274794,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3253/sim3253_sheet1.pdf"},{"id":274795,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3253/sim3253_sheet2.pdf"},{"id":274796,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3253/sim3253_sheet3.pdf"},{"id":274797,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3253/sim3253_sheet4.pdf"},{"id":274793,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3253/sim3253_pamphlet.pdf"},{"id":274798,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3253/sim3253_readme.txt"},{"id":274799,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3253/metadata"},{"id":274800,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3253/data"}],"scale":"50000","projection":"Universal Transverse Mercator Zone 8N","country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay National Park And Preserve","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -137.269363,58.833333 ], [ -137.269363,59.083333 ], [ -136.563492,59.083333 ], [ -136.563492,58.833333 ], [ -137.269363,58.833333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dd22d8e4b0f72b44719c1f","contributors":{"authors":[{"text":"Hodson, Timothy O. 0000-0003-0962-5130","orcid":"https://orcid.org/0000-0003-0962-5130","contributorId":78634,"corporation":false,"usgs":true,"family":"Hodson","given":"Timothy","email":"","middleInitial":"O.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochrane, Guy R. 0000-0002-8094-4583 gcochrane@usgs.gov","orcid":"https://orcid.org/0000-0002-8094-4583","contributorId":2870,"corporation":false,"usgs":true,"family":"Cochrane","given":"Guy","email":"gcochrane@usgs.gov","middleInitial":"R.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":480267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Ross D.","contributorId":89768,"corporation":false,"usgs":true,"family":"Powell","given":"Ross","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":480269,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046811,"text":"70046811 - 2013 - A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring","interactions":[],"lastModifiedDate":"2013-07-09T11:08:17","indexId":"70046811","displayToPublicDate":"2013-07-09T10:57:29","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring","docAbstract":"Aim: To develop a novel global spatial framework for the integration and analysis of ecological and environmental data.\nLocation: The global land surface excluding Antarctica.\nMethods: A broad set of climate-related variables were considered for inclusion in a quantitative model, which partitions geographic space into bioclimate regions. Statistical screening produced a subset of relevant bioclimate variables, which were further compacted into fewer independent dimensions using principal components analysis (PCA). An ISODATA clustering routine was then used to classify the principal components into relatively homogeneous environmental strata. The strata were aggregated into global environmental zones based on the attribute distances between strata to provide structure and support a consistent nomenclature.\nResults: The global environmental stratification (GEnS) consists of 125 strata, which have been aggregated into 18 global environmental zones. The stratification has a 30 arcsec resolution (equivalent to 0.86 km2 at the equator). Aggregations of the strata were compared with nine existing global, continental and national bioclimate and ecosystem classifications using the Kappa statistic. Values range between 0.54 and 0.72, indicating good agreement in bioclimate and ecosystem patterns between existing maps and the GEnS.\nMain conclusions: The GEnS provides a robust spatial analytical framework for the aggregation of local observations, identification of gaps in current monitoring efforts and systematic design of complementary and new monitoring and research. The dataset is available for non-commercial use through the GEO portal (http://www.geoportal.org).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Global Ecology and Biogeography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/geb.12022","usgsCitation":"Metzger, M.J., Bunce, R.G., Jongman, R.H., Sayre, R.G., Trabucco, A., and Zomer, R., 2013, A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring: Global Ecology and Biogeography, v. 22, no. 5, p. 630-638, https://doi.org/10.1111/geb.12022.","productDescription":"9 p.","startPage":"630","endPage":"638","ipdsId":"IP-041917","costCenters":[{"id":180,"text":"Climate and Land Use Change Program","active":false,"usgs":true}],"links":[{"id":473702,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/geb.12022","text":"External Repository"},{"id":274747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274696,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/geb.12022/pdf"},{"id":274746,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/geb.12022"}],"otherGeospatial":"Earth","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","volume":"22","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-12-20","publicationStatus":"PW","scienceBaseUri":"51dd22d2e4b0f72b44719c13","contributors":{"authors":[{"text":"Metzger, Marc J.","contributorId":88635,"corporation":false,"usgs":true,"family":"Metzger","given":"Marc","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":480351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunce, Robert G.H.","contributorId":64539,"corporation":false,"usgs":true,"family":"Bunce","given":"Robert","email":"","middleInitial":"G.H.","affiliations":[],"preferred":false,"id":480349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jongman, Rob H.G.","contributorId":92566,"corporation":false,"usgs":true,"family":"Jongman","given":"Rob","email":"","middleInitial":"H.G.","affiliations":[],"preferred":false,"id":480352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sayre, Roger G. rsayre@usgs.gov","contributorId":2882,"corporation":false,"usgs":true,"family":"Sayre","given":"Roger","email":"rsayre@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":false,"id":480347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trabucco, Antonio","contributorId":10702,"corporation":false,"usgs":true,"family":"Trabucco","given":"Antonio","email":"","affiliations":[],"preferred":false,"id":480348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zomer, Robert","contributorId":83006,"corporation":false,"usgs":true,"family":"Zomer","given":"Robert","email":"","affiliations":[],"preferred":false,"id":480350,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70046911,"text":"ds780 - 2013 - Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection","interactions":[],"lastModifiedDate":"2026-05-20T17:08:37.120091","indexId":"ds780","displayToPublicDate":"2013-07-09T10:14:14","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":"780","title":"Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection","docAbstract":"The Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey (USGS) periodically collects airborne image data for the Colorado River corridor within Arizona (fig. 1) to allow scientists to study the impacts of Glen Canyon Dam water release on the corridor’s natural and cultural resources. These data are collected from just above Glen Canyon Dam (in Lake Powell) down to the entrance of Lake Mead, for a total distance of 450 kilometers (km) and within a 500-meter (m) swath centered on the river’s mainstem and its seven main tributaries (fig. 1). The most recent airborne data collection in 2009 acquired image data in four wavelength bands (blue, green, red, and near infrared) at a spatial resolution of 20 centimeters (cm). The image collection used the latest model of the Leica ADS40 airborne digital sensor (the SH52), which uses a single optic for all four bands and collects and stores band radiance in 12-bits. Davis (2012) reported on the performance of the SH52 sensor and on the processing steps required to produce the nearly flawless four-band image mosaic (sectioned into map tiles) for the river corridor. The final image mosaic has a total of only 3 km of surface defects in addition to some areas of cloud shadow because of persistent inclement weather during data collection. The 2009 four-band image mosaic is perhaps the best image dataset that exists for the entire Arizona part of the Colorado River.\n\nSome analyses of these image mosaics do not require the full 12-bit dynamic range or all four bands of the calibrated image database, in which atmospheric scattering (or haze) had not been removed from the four bands. To provide scientists and the general public with image products that are more useful for visual interpretation, the 12-bit image data were converted to 8-bit natural-color and color-infrared images, which also removed atmospheric scattering within each wavelength-band image. The conversion required an evaluation of the histograms of each band’s digital-number population within each map tile throughout the corridor and the determination of the digital numbers corresponding to the lower and upper one percent of the picture-element population within each map tile. Visual examination of the image tiles that were given a 1-percent stretch (whereby the lower 1- percent 12-bit digital number is assigned an 8-bit value of zero and the upper 1-percent 12-bit digital number is assigned an 8-bit value of 255) indicated that this stretch sufficiently removed atmospheric scattering, which provided improved image clarity and true natural colors for all surface materials.\n\nThe lower and upper 1-percent, 12-bit digital numbers for each wavelength-band image in the image tiles exhibit erratic variations along the river corridor; the variations exhibited similar trends in both the lower and upper 1-percent digital numbers for all four wavelength-band images (figs. 2–5). The erratic variations are attributed to (1) daily variations in atmospheric water-vapor content due to monsoonal storms, (2) variations in channel water color due to variable sediment input from tributaries, and (3) variations in the amount of topographic shadows within each image tile, in which reflectance is dominated by atmospheric scattering.\n\nTo make the surface colors of the stretched, 8-bit images consistent among adjacent image tiles, it was necessary to average both the lower and upper 1-percent digital values for each wavelength-band image over 20 river miles to subdue the erratic variations. The average lower and upper 1-percent digital numbers for each image tile (figs. 2–5) were used to convert the 12-bit image values to 8-bit values and the resulting 8-bit four-band images were stored as natural-color (red, green, and blue wavelength bands) and color-infrared (near-infrared, red, and green wavelength bands) images in embedded geotiff format, 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.\n\nAll image data are projected in the State Plane (SP) map projection using the central Arizona zone (202) and the North American Datum of 1983 (NAD83). The map-tile scheme used to segment the corridor image mosaic followed the standard USGS quarter-quadrangle (QQ) map borders, but the high resolution (20 cm) of the images required further quarter segmentation (QQQ) of the standard QQ tiles, where the image mosaic covered a large fraction of a QQ map tile (segmentation shown in (figure 6), where QQ_1 to QQ_4 shows the number convention used to designate a quarter of a QQ tile). To minimize the size of each image tile, each image or map tile was subset to only include that part of the tile that had image data. In addition, some QQQ image tiles within a QQ tile were combined when adjacent QQQ map tiles were small. Thus, some image tiles consist of combinations of QQQ map tiles, some consist of an entire QQ map tile, and some consist of two adjoining QQ map tiles. The final image tiles number 143, which is a large number of files to list on the Internet for both the natural-color and color-infrared images. Thus, the image tiles were placed in seven file folders based on the one-half-degree geographic boundaries within the study area (fig. 7). The map tiles in each file folder were compressed to minimize folder size for more efficient downloading. The file folders are sequentially referred to as zone 1 through zone 7, proceeding down river (fig. 7). The QQ designations of the image tiles contained within each folder or zone are shown on the index map for each respective zone (figs. 8–14).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds780","usgsCitation":"Davis, P.A., 2013, Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection: U.S. Geological Survey Data Series 780, Readme PDF; Readme Folder; 16 Index Maps; 14 Image Files; Metadata; Shapefiles, https://doi.org/10.3133/ds780.","productDescription":"Readme PDF; Readme Folder; 16 Index Maps; 14 Image Files; Metadata; Shapefiles","additionalOnlineFiles":"Y","ipdsId":"IP-043164","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":504568,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98676.htm","linkFileType":{"id":5,"text":"html"}},{"id":274741,"rank":8,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds780.png"},{"id":274740,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/780/shapefiles/shapefiles.html"},{"id":274734,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/780/"},{"id":274739,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/780/metadata/metadata.html"},{"id":274738,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/780/index_maps/index_maps.html"},{"id":274737,"rank":2,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/780/image_files/image_files.html"},{"id":274736,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/780/1_readme"},{"id":274735,"rank":7,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/780/1_readme.pdf"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.0,35.25 ], [ -114.0,37.0 ], [ -111.0,37.0 ], [ -111.0,35.25 ], [ -114.0,35.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dd22d9e4b0f72b44719c23","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":480606,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046787,"text":"tm13B1 - 2013 - Modeling crustal deformation near active faults and volcanic centers: a catalog of deformation models and modeling approaches","interactions":[],"lastModifiedDate":"2019-03-25T13:27:13","indexId":"tm13B1","displayToPublicDate":"2013-07-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"13-B1","title":"Modeling crustal deformation near active faults and volcanic centers: a catalog of deformation models and modeling approaches","docAbstract":"This manual provides the physical and mathematical concepts for selected models used to interpret deformation measurements near active faults and volcanic centers. The emphasis is on analytical models of deformation that can be compared with data from the Global Positioning System (GPS) receivers, Interferometric synthetic aperture radar (InSAR), leveling surveys, tiltmeters and strainmeters. Source models include pressurized spherical, ellipsoidal, and horizontal penny-shaped geometries in an elastic, homogeneous, flat half-space. Vertical dikes and faults are described following the mathematical notation for rectangular dislocations in an elastic, homogeneous, flat half-space. All the analytical expressions were verified against numerical models developed by use of COMSOL Multyphics, a Finite Element Analysis software (http://www.comsol.com). In this way, typographical errors present were identified and corrected. Matlab scripts are also provided to facilitate the application of these models.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: Modeling of Volcanic Processes in Book 13 Volcano Monitoring","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm13B1","usgsCitation":"Battaglia, M., Cervelli, P.F., and Murray, J.R., 2013, Modeling crustal deformation near active faults and volcanic centers: a catalog of deformation models and modeling approaches: U.S. Geological Survey Techniques and Methods 13-B1, Report: viii, 96 p.; Readme; dMODELS: Matlab Script; dMODELS: Matlab Scripts compiled for LINUX OS 64bit; dMODELS: Matlab Scripts compiled for Windos OS 32bit & 64bit, https://doi.org/10.3133/tm13B1.","productDescription":"Report: viii, 96 p.; Readme; dMODELS: Matlab Script; dMODELS: Matlab Scripts compiled for LINUX OS 64bit; dMODELS: Matlab Scripts compiled for Windos OS 32bit & 64bit","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":619,"text":"Volcano Science Center-Menlo Park","active":false,"usgs":true}],"links":[{"id":274601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm13b1.jpg"},{"id":274542,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/13/b1/pdf/tm13-b1.pdf"},{"id":274543,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/tm/13/b1/tm13-b1_README.txt"},{"id":274541,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/13/b1/"},{"id":274544,"type":{"id":4,"text":"Application Site"},"url":"https://pubs.usgs.gov/tm/13/b1/tm13-b1_MATLAB.zip"},{"id":274545,"type":{"id":4,"text":"Application Site"},"url":"https://pubs.usgs.gov/tm/13/b1/tm13-b1_LINUX.zip"},{"id":274546,"type":{"id":4,"text":"Application Site"},"url":"https://pubs.usgs.gov/tm/13/b1/tm13-b1_WIN7.zip"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dbd154e4b0f81004b77c9a","contributors":{"authors":[{"text":"Battaglia, Maurizio mbattaglia@usgs.gov","contributorId":2526,"corporation":false,"usgs":true,"family":"Battaglia","given":"Maurizio","email":"mbattaglia@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":480253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cervelli, Peter F. 0000-0001-6765-1009 pcervelli@usgs.gov","orcid":"https://orcid.org/0000-0001-6765-1009","contributorId":1936,"corporation":false,"usgs":true,"family":"Cervelli","given":"Peter","email":"pcervelli@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":535565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":480254,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047176,"text":"70047176 - 2013 - Statewide summary for Florida","interactions":[],"lastModifiedDate":"2022-12-27T17:50:25.624609","indexId":"70047176","displayToPublicDate":"2013-07-07T16:14:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"chapter":"L","title":"Statewide summary for Florida","docAbstract":"Throughout the past century, emergent wetlands have been declining across the Gulf of Mexico. Emergent wetland ecosystems provide a multitude of resources, including plant and wildlife habitat, commercial and recreational economic activity, and natural barriers against storms. As emergent wetland losses increase, so does the need for information on the causes and effects of this loss; emergent wetland mapping, monitoring, and restoration efforts; and education. This report provides scientists, managers, and citizens with valuable baseline information on the status and trends of emergent wetlands along the coast of the Gulf of Mexico. The Statewide Summary for Florida provides status and trends information for Florida using what data is available during the 1950-2010 time period.
The State of Florida (Figure 1) is approximately 151,670 km2 (58,560 mi2 ) large with an average elevation of 30.5 m (100 ft) (Dahl, 2005). The Florida gulf coast stretches approximately 1,000 km (621 miles) from the Alabama State line to the Dry Tortugas in the Florida Keys (Handley et al., 2007). The climate varies along the coast, ranging from temperate continental in the panhandle to oceanic subtropical in the Keys. Due to this climatic gradient, the Gulf coast of Florida is divisible into two ecoregions, the Louisianian in the north along the panhandle, and the West Indian in the south along the length of the peninsula (Bailey 1978). The Lousianian ecoregion extends from Cedar Key north and west along the panhandle to the Alabama state line. It is characterized by extensive emergent coastal wetlands, temperate fauna, small tidal ranges (
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Emergent wetlands status and trends in the northern Gulf of Mexico: 1950-2010","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"conferenceTitle":"2013 Gulf of Mexico Alliance (GOMA) All Hands Meeting","conferenceDate":"June 25-27, 2013","conferenceLocation":"Tampa, FL","language":"English","publisher":"U.S. Geological Survey and U.S. Environmental Protection Agency","usgsCitation":"Handley, L.R., Spear, K.A., Baumstark, R., Moyer, R., and Thatcher, C.A., 2013, Statewide summary for Florida, 11 p.","productDescription":"11 p.","ipdsId":"IP-044999","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":280681,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275319,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://gom.usgs.gov/web/Site/EmWetStatusTrends"}],"country":"United 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Center","active":true,"usgs":true}],"preferred":true,"id":481232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baumstark, René","contributorId":17903,"corporation":false,"usgs":true,"family":"Baumstark","given":"René","affiliations":[],"preferred":false,"id":481235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moyer, Ryan","contributorId":48460,"corporation":false,"usgs":true,"family":"Moyer","given":"Ryan","affiliations":[],"preferred":false,"id":481236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":481233,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046782,"text":"sim3256 - 2013 - Comparative mineral mapping in the Colorado Mineral Belt using AVIRIS and ASTER remote sensing data","interactions":[],"lastModifiedDate":"2013-07-05T13:09:59","indexId":"sim3256","displayToPublicDate":"2013-07-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3256","title":"Comparative mineral mapping in the Colorado Mineral Belt using AVIRIS and ASTER remote sensing data","docAbstract":"This report presents results of interpretation of spectral remote sensing data covering the eastern Colorado Mineral Belt in central Colorado, USA, acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensors. This study was part of a multidisciplinary mapping and data integration project at the U.S. Geological Survey that focused on long-term resource planning by land-managing entities in Colorado.\n\nThe map products were designed primarily for the regional mapping and characterization of exposed surface mineralogy, including that related to hydrothermal alteration and supergene weathering of pyritic rocks. Alteration type was modeled from identified minerals based on standard definitions of alteration mineral assemblages. Vegetation was identified using the ASTER data and subdivided based on per-pixel chlorophyll content (depth of 0.68 micrometer absorption band) and dryness (fit and depth of leaf biochemical absorptions in the shortwave infrared spectral region). The vegetation results can be used to estimate the abundance of fire fuels at the time of data acquisition (2002 and 2003). The AVIRIS- and ASTER-derived mineral mapping results can be readily compared using the toggleable layers in the GeoPDF file, and by using the provided GIS-ready raster datasets.\n\nThe results relating to mineral occurrence and distribution were an important source of data for studies documenting the effects of mining and un-mined, altered rocks on aquatic ecosystems at the watershed level. These studies demonstrated a high correlation between metal concentrations in streams and the presence of hydrothermal alteration and (or) pyritic mine waste as determined by analysis of the map products presented herein. The mineral mapping results were also used to delineate permissive areas for various mineral deposit types.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3256","usgsCitation":"Rockwell, B.W., 2013, Comparative mineral mapping in the Colorado Mineral Belt using AVIRIS and ASTER remote sensing data: U.S. Geological Survey Scientific Investigations Map 3256, Pamphlet: iv, 8 p.; Map: 1 Sheet: 50 x 108 inches; Downloads Directory, https://doi.org/10.3133/sim3256.","productDescription":"Pamphlet: iv, 8 p.; Map: 1 Sheet: 50 x 108 inches; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":274504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3256.gif"},{"id":274500,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3256/"},{"id":274501,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3256/downloads/pdf/SIM3256_pamphlet.pdf"},{"id":274502,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3256/downloads/GeoPDF/SIM3256_map.pdf"},{"id":274503,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3256/downloads/"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0603,36.9924 ], [ -109.0603,41.0034 ], [ -102.0409,41.0034 ], [ -102.0409,36.9924 ], [ -109.0603,36.9924 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d7dccfe4b0b0351701e177","contributors":{"authors":[{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617 barnabyr@usgs.gov","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":2195,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby","email":"barnabyr@usgs.gov","middleInitial":"W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":480243,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046781,"text":"sim3262 - 2013 - Flood-inundation maps for the Saddle River from Upper Saddle River Borough to Saddle River Borough, New Jersey, 2013","interactions":[],"lastModifiedDate":"2013-07-05T11:58:23","indexId":"sim3262","displayToPublicDate":"2013-07-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3262","title":"Flood-inundation maps for the Saddle River from Upper Saddle River Borough to Saddle River Borough, New Jersey, 2013","docAbstract":"Digital flood-inundation maps for a 4.1-mile reach of the Saddle River from 0.6 miles downstream from the New Jersey-New York State boundary in Upper Saddle River Borough to 0.2 miles downstream from the East Allendale Road bridge in Saddle River Borough, New Jersey, were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection (NJDEP). The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to select water levels (stages) at the USGS streamgage 01390450, Saddle River at Upper Saddle River, New Jersey. Current conditions for estimating near real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/nwis/uv?site_no=01390450. The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.\n\nIn this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relations (in effect March 2013) at USGS streamgage 01390450, Saddle River at Upper Saddle River, New Jersey, and documented high-water marks from recent floods. The hydraulic model was then used to determine eight water-surface profiles for flood stages at 0.5-foot (ft) intervals referenced to the streamgage datum, North American Vertical Datum of 1988 (NAVD 88), and ranging from bankfull, 0.5 ft below NWS Action Stage, to the upper extent of the stage-discharge rating which is approximately 1 ft higher than the highest recorded water level at the streamgage. Action Stage is the stage which when reached by a rising stream the NWS or a partner needs to take some type of mitigation action in preparation for possible significant hydrologic activity. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84 ft) digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level.\n\nThe availability of these maps along with real-time streamflow data and information regarding current stage from USGS streamgages and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3262","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Watson, K.M., and Hoppe, H.L., 2013, Flood-inundation maps for the Saddle River from Upper Saddle River Borough to Saddle River Borough, New Jersey, 2013: U.S. Geological Survey Scientific Investigations Map 3262, Pamphlet: vi, 8 p.; Maps: 8 Sheets: 17 x 22 inches; Downloads Directory, https://doi.org/10.3133/sim3262.","productDescription":"Pamphlet: vi, 8 p.; Maps: 8 Sheets: 17 x 22 inches; Downloads Directory","additionalOnlineFiles":"Y","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":274498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3262.png"},{"id":274490,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3262/downloads/map_sheets/sim3262_40.pdf"},{"id":274488,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3262/downloads/sim3262-pamphlet.pdf"},{"id":274489,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3262/downloads/map_sheets/sim3262_30.pdf"},{"id":274491,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3262/downloads/map_sheets/sim3262_35.pdf"},{"id":274492,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3262/downloads/map_sheets/sim3262_45.pdf"},{"id":274493,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3262/downloads/map_sheets/sim3262_50.pdf"},{"id":274494,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3262/downloads/map_sheets/sim3262_55.pdf"},{"id":274495,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3262/downloads/map_sheets/sim3262_60.pdf"},{"id":274496,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3262/downloads/map_sheets/sim3262_65.pdf"},{"id":274497,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3262/downloads"},{"id":274499,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3262"}],"country":"United States","state":"New Jersey","otherGeospatial":"Saddle River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.120833,41.025 ], [ -74.120833,41.083333 ], [ -74.063889,41.083333 ], [ -74.063889,41.025 ], [ -74.120833,41.025 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d7dcd4e4b0b0351701e17b","contributors":{"authors":[{"text":"Watson, Kara M. 0000-0002-2685-0260 kmwatson@usgs.gov","orcid":"https://orcid.org/0000-0002-2685-0260","contributorId":2134,"corporation":false,"usgs":true,"family":"Watson","given":"Kara","email":"kmwatson@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoppe, Heidi L. hhoppe@usgs.gov","contributorId":1513,"corporation":false,"usgs":true,"family":"Hoppe","given":"Heidi","email":"hhoppe@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":480241,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70115381,"text":"70115381 - 2013 - Water and sediment temperatures at mussel beds in the upper Mississippi River basin","interactions":[],"lastModifiedDate":"2020-12-30T13:21:30.252536","indexId":"70115381","displayToPublicDate":"2013-07-03T10:02:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5254,"text":"Freshwater Mollusk Biology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Water and sediment temperatures at mussel beds in the upper Mississippi River basin","docAbstract":"Native freshwater mussels are in global decline and urgently need protection and conservation. Declines in the abundance and diversity of North American mussels have been attributed to human activities that cause pollution, waterquality degradation, and habitat destruction. Recent studies suggest that effects of climate change may also endanger native mussel assemblages, as many mussel species are living close to their upper thermal tolerances. Adult and juvenile mussels spend a large fraction of their lives burrowed into sediments of rivers and lakes. Our objective was to measure surface water and sediment temperatures at known mussel beds in the Upper Mississippi (UMR) and St. Croix (SCR) rivers to estimate the potential for sediments to serve as thermal refugia. Across four mussel beds in the UMR and SCR, surface waters were generally warmer than sediments in summer, and were cooler than sediments in winter. This suggests that sediments may act as a thermal buffer for mussels in these large rivers. Although the magnitude of this effect was usually <3.0°C, sediments were up to 7.5°C cooler at one site in May, suggesting site-specific variation in the ability of sediments to act as thermal buffers. Sediment temperatures in the UMR exceeded those shown to cause mortality in laboratory studies. These data suggest that elevated water temperatures resulting from global warming, thermal discharges, water extraction, and/or droughts have the potential to adversely affect native mussel assemblages.
","language":"English","publisher":"BioOne","doi":"10.31931/fmbc.v16i2.2013.53-62","usgsCitation":"Newton, T.J., Sauer, J., and Karns, B., 2013, Water and sediment temperatures at mussel beds in the upper Mississippi River basin: Freshwater Mollusk Biology and Conservation, v. 16, no. 2, p. 53-62, https://doi.org/10.31931/fmbc.v16i2.2013.53-62.","productDescription":"10 p.","startPage":"53","endPage":"62","ipdsId":"IP-041287","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":473704,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc.v16i2.2013.53-62","text":"Publisher Index Page"},{"id":381721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.25,40.01 ], [ -95.25,47.5 ], [ -89.27,47.5 ], [ -89.27,40.01 ], [ -95.25,40.01 ] ] ] } } ] }","volume":"16","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53b67b89e4b014fc094d547d","contributors":{"authors":[{"text":"Newton, Teresa J. 0000-0001-9351-5852 tnewton@usgs.gov","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":2470,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa","email":"tnewton@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":495608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, Jennifer","contributorId":56329,"corporation":false,"usgs":true,"family":"Sauer","given":"Jennifer","affiliations":[],"preferred":false,"id":495609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karns, Byron","contributorId":86691,"corporation":false,"usgs":true,"family":"Karns","given":"Byron","affiliations":[],"preferred":false,"id":495610,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046777,"text":"sir20135070 - 2013 - Geohydrology, water quality, and simulation of groundwater flow in the stratified-drift aquifer system in Virgil Creek and Dryden Lake Valleys, Town of Dryden, Tompkins County, New York","interactions":[],"lastModifiedDate":"2016-01-11T08:55:33","indexId":"sir20135070","displayToPublicDate":"2013-07-03T00:00:00","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":"2013-5070","title":"Geohydrology, water quality, and simulation of groundwater flow in the stratified-drift aquifer system in Virgil Creek and Dryden Lake Valleys, Town of Dryden, Tompkins County, New York","docAbstract":"In 2002, the U.S. Geological Survey, in cooperation with the Tompkins County Planning Department and the Town of Dryden, New York, began a study of the stratified-drift aquifer system in the Virgil Creek and Dryden Lake Valleys in the Town of Dryden, Tompkins County. The study provided geohydrologic data needed by the town and county to develop a strategy to manage and protect their water resources. In this study area, three extensive confined sand and gravel aquifers (the upper, middle, and lower confined aquifers) compose the stratified-drift aquifer system. The Dryden Lake Valley is a glaciated valley oriented parallel to the direction of ice movement. Erosion by ice extensively widened and deepened the valley, truncated bedrock hillsides, and formed a nearly straight, U-shaped bedrock trough. The maximum thickness of the valley fill in the central part of the valley is about 400 feet (ft). The Virgil Creek Valley in the east part of the study area underwent less severe erosion by ice than the Dryden Lake Valley, and hence, it has a bedrock floor that is several hundred feet higher in altitude than that in the Dryden Lake Valley. The sources and amounts of recharge were difficult to identify in most areas because the confined aquifers are overlain by confining units. However, in the vicinity of the Virgil Creek Dam, the upper confined aquifer crops out at land surface in the floodplain of a gorge eroded by Virgil Creek, and this is where the aquifer receives large amounts of recharge from precipitation that directly falls over the aquifer and from seepage losses from Virgil Creek. The results of streamflow measurements made in Virgil Creek where it flows through the gorge indicated that the stream lost 1.2 cubic feet per second (ft3/s) or 0.78 million gallons per day (Mgal/d) of water in the reach extending from 220 ft downstream from the dam to 1,200 ft upstream from the dam. In the southern part of the study area, large amounts of recharge also replenish the stratified-drift aquifers at the Valley Heads Moraine, which consists of heterogeneous sediments including coarse-grained outwash and kame sediments, as well as zones containing till with a fine-grained matrix. In the southern part of the study area, the confining units are thin and likely to be discontinuous in some places, resulting in windows of permeable sediment, which can more readily transmit recharge from precipitation and from tributaries that lose water as they flow over the valley floor. In contrast, in the northern part of the study area, the confining units are thick, continuous, and comprise homogeneous fine-grained sediments that more effectively confine the aquifers than in the southern part of the study area. Most groundwater in the northern part of the study area discharges to the Village of Dryden municipal production wells, to the outlet to Dryden Lake, to Virgil Creek, and as groundwater underflow that exits the northern boundary of the study area. Most northward-flowing groundwater in the southern part of the study area discharges to Dryden Lake, to the inlet to Dryden Lake, and to homeowner, nonmunicipal community (a mobile home community and several apartments), and commercial wells. Most of this pumped water is returned to the groundwater system via septic systems. Most southward-flowing groundwater in the southern part of the study area discharges to the headwaters of Owego Creek and to agricultural wells; some flow also exits the southern boundary of the study area as groundwater underflow. The largest user of groundwater in the study area is the Village of Dryden. Water use in the village has approximately tripled between the early 1970s when withdrawals ranged between 18 and 30 million gallons per year (Mgal/yr) and from 2000 through 2008 when withdrawals ranged between 75 and 85 Mgal/yr. The estimated groundwater use by homeowners, nonmunicipal communities, and small commercial facilities outside the area supplied by the Village of Dryden municipal wells is estimated to be about 18.4 Mgal/yr. Most of this pumped water is returned to the groundwater system via septic systems. For this investigation, an aquifer test was conducted at the Village of Dryden production well TM 981 (finished in the middle confined aquifer at a well depth of 72 ft) at the Jay Street pumping station during June 19–21, 2007. The aquifer test consisted of pumping production well TM 981 at 104 gallons per minute over a 24-hour period. The drawdown in well TM 981 at the end of 24 hours of pumping was 19.2 ft. Results of the aquifer-test analysis for a partially penetrating well in a confined aquifer indicated that the transmissivity was 1,560 feet squared per day, and the horizontal hydraulic conductivity was 87 feet per day, based on a saturated thickness of 18 ft. During 2003–5, 14 surface-water samples were collected at 8 sites, including Virgil Creek, Dryden Lake outlet, and several tributaries. During 2003 through 2009, eight groundwater samples were collected from eight wells, including three municipal production wells, two test wells, and three domestic wells. Calcium dominates the cation composition, and bicarbonate dominates the anion composition in most groundwater and surface-water samples. None of the common inorganic constituents collected exceeded any Federal or State water-quality standards. Results from a three-dimensional, finite-difference groundwater-flow model were used to compute a water budget and to estimate the areal extent of the zone of groundwater contribution to the Village of Dryden municipal production wells. The model-computed water budget indicated that the sources of recharge to the confined aquifer system are precipitation that falls directly on the valley-fill sediments (40 percent of total recharge), stream leakage (35.5 percent), seepage from wetlands and ponds (12 percent), unchanneled runoff and groundwater inflow from the uplands (8.5 percent), and groundwater underflow into the eastern end of the model area (4 percent). Most groundwater discharges to surface-water bodies, including Dryden Lake (33 percent), streams (33 percent), and wetlands and ponds (10 percent of the total). In addition, some groundwater discharges as underflow out of the southern and northern ends of the model area (15 percent), to simulated pumping wells (4.5 percent), and to drains that represent seepage from the bluffs exposed in the gorge in the vicinity of the Virgil Creek Dam (4.5 percent). The areal extents of the zones of groundwater contribution for Village of Dryden municipal production wells TM 202 (Lake Road pump station, finished in the upper confined aquifer) and TM 981 (Jay Street pump station, finished in the middle confined aquifer) are 0.5 square mile (mi2) and 0.9 mi2, respectively. The areal extent of the zone of contribution to production well TM 202 extends 2.2 miles (mi) southeast into the Virgil Creek Valley, whereas production well TM 981 extends 3.8 mi south in the Dryden Lake Valley. The areal extent of the zone of contribution to production well TM1046 (South Street pump station) is 1.4 mi2 and extends 2.4 mi into Dryden Lake Valley and 0.5 mi into Virgil Creek Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135070","collaboration":"Prepared in cooperation with the Town of Dryden and theTompkins County Planning Department","usgsCitation":"Miller, T.S., and Bugliosi, E.F., 2013, Geohydrology, water quality, and simulation of groundwater flow in the stratified-drift aquifer system in Virgil Creek and Dryden Lake Valleys, Town of Dryden, Tompkins County, New York: U.S. Geological Survey Scientific Investigations Report 2013-5070, ix, 104 p.; Figures 8, 13, 18: 3 Sheets: 30 x 38 inches, https://doi.org/10.3133/sir20135070.","productDescription":"ix, 104 p.; Figures 8, 13, 18: 3 Sheets: 30 x 38 inches","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":274464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135070.gif"},{"id":274461,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5070/pdf/sir2013-5070_miller_fig08_sheet.pdf","text":"Plate 08"},{"id":274462,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5070/pdf/sir2013-5070_miller_fig18_11x17.pdf","text":"Plate 18"},{"id":274459,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5070/"},{"id":274460,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5070/pdf/sir2013-5070_miller_508.pdf","text":"Report"},{"id":274463,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5070/pdf/sir2013-5070_miller_fig13_11x17.pdf","text":"Plate 13"}],"country":"United States","state":"New York","county":"Tompkins County","city":"Dryden","otherGeospatial":"Virgil Creek Valley;Dryden Lake Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.314059,42.479558 ], [ -76.314059,42.50096 ], [ -76.286107,42.50096 ], [ -76.286107,42.479558 ], [ -76.314059,42.479558 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d539d4e4b011afeb0c75c3","contributors":{"authors":[{"text":"Miller, Todd S. tsmiller@usgs.gov","contributorId":1190,"corporation":false,"usgs":true,"family":"Miller","given":"Todd","email":"tsmiller@usgs.gov","middleInitial":"S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bugliosi, Edward F. ebuglios@usgs.gov","contributorId":1083,"corporation":false,"usgs":true,"family":"Bugliosi","given":"Edward","email":"ebuglios@usgs.gov","middleInitial":"F.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480219,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046776,"text":"tm6A42 - 2013 - Advective transport observations with MODPATH-OBS--documentation of the MODPATH observation process","interactions":[],"lastModifiedDate":"2013-07-03T10:08:43","indexId":"tm6A42","displayToPublicDate":"2013-07-03T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A42","title":"Advective transport observations with MODPATH-OBS--documentation of the MODPATH observation process","docAbstract":"The MODPATH-OBS computer program described in this report is designed to calculate simulated equivalents for observations related to advective groundwater transport that can be represented in a quantitative way by using simulated particle-tracking data. The simulated equivalents supported by MODPATH-OBS are (1) distance from a source location at a defined time, or proximity to an observed location; (2) time of travel from an initial location to defined locations, areas, or volumes of the simulated system; (3) concentrations used to simulate groundwater age; and (4) percentages of water derived from contributing source areas. Although particle tracking only simulates the advective component of conservative transport, effects of non-conservative processes such as retardation can be approximated through manipulation of the effective-porosity value used to calculate velocity based on the properties of selected conservative tracers. This program can also account for simple decay or production, but it cannot account for diffusion. Dispersion can be represented through direct simulation of subsurface heterogeneity and the use of many particles.\n\nMODPATH-OBS acts as a postprocessor to MODPATH, so that the sequence of model runs generally required is MODFLOW, MODPATH, and MODPATH-OBS. The version of MODFLOW and MODPATH that support the version of MODPATH-OBS presented in this report are MODFLOW-2005 or MODFLOW-LGR, and MODPATH-LGR. MODFLOW-LGR is derived from MODFLOW-2005, MODPATH 5, and MODPATH 6 and supports local grid refinement. MODPATH-LGR is derived from MODPATH 5. It supports the forward and backward tracking of particles through locally refined grids and provides the output needed for MODPATH_OBS. For a single grid and no observations, MODPATH-LGR results are equivalent to MODPATH 5. MODPATH-LGR and MODPATH-OBS simulations can use nearly all of the capabilities of MODFLOW-2005 and MODFLOW-LGR; for example, simulations may be steady-state, transient, or a combination. Though the program name MODPATH-OBS specifically refers to observations, the program also can be used to calculate model prediction of observations.\n\nMODPATH-OBS is primarily intended for use with separate programs that conduct sensitivity analysis, data needs assessment, parameter estimation, and uncertainty analysis, such as UCODE_2005, and PEST.\n\nIn many circumstances, refined grids in selected parts of a model are important to simulated hydraulics, detailed inflows and outflows, or other system characteristics. MODFLOW-LGR and MODPATH-LGR support accurate local grid refinement in which both mass (flows) and energy (head) are conserved across the local grid boundary. MODPATH-OBS is designed to take advantage of these capabilities. For example, particles tracked between a pumping well and a nearby stream, which are simulated poorly if a river and well are located in a single large grid cell, can be simulated with improved accuracy using a locally refined grid in MODFLOW-LGR, MODPATH-LGR, and MODPATH-OBS. The locally-refined-grid approach can provide more accurate simulated equivalents to observed transport between the well and the river.\n\nThe documentation presented here includes a brief discussion of previous work, description of the methods, and detailed descriptions of the required input files and how the output files are typically used.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Ground water in Book 6 Modeling Techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A42","collaboration":"Prepared in cooperation with the U.S. Department of Energy; This report is Chapter 42 of Section A: Ground water in Book 6 Modeling Techniques","usgsCitation":"Hanson, R.T., Kauffman, L., Hill, M.C., Dickinson, J., and Mehl, S., 2013, Advective transport observations with MODPATH-OBS--documentation of the MODPATH observation process: U.S. Geological Survey Techniques and Methods 6-A42, viii, 96 p., https://doi.org/10.3133/tm6A42.","productDescription":"viii, 96 p.","numberOfPages":"108","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":274458,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm6a42.jpg"},{"id":274456,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/06/a42/"},{"id":274457,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a42/pdf/tm6-a42.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d539cee4b011afeb0c75bf","contributors":{"authors":[{"text":"Hanson, R. T.","contributorId":91148,"corporation":false,"usgs":true,"family":"Hanson","given":"R.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":480218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauffman, L.K.","contributorId":76624,"corporation":false,"usgs":true,"family":"Kauffman","given":"L.K.","email":"","affiliations":[],"preferred":false,"id":480216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hill, M. C.","contributorId":48993,"corporation":false,"usgs":true,"family":"Hill","given":"M.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":480215,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dickinson, J.E.","contributorId":28790,"corporation":false,"usgs":true,"family":"Dickinson","given":"J.E.","email":"","affiliations":[],"preferred":false,"id":480214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mehl, S.W.","contributorId":84555,"corporation":false,"usgs":true,"family":"Mehl","given":"S.W.","affiliations":[],"preferred":false,"id":480217,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046764,"text":"sir20135126 - 2013 - Actual evapotranspiration modeling using the operational Simplified Surface Energy Balance (SSEBop) approach","interactions":[],"lastModifiedDate":"2017-05-31T16:21:40","indexId":"sir20135126","displayToPublicDate":"2013-07-02T00:00:00","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":"2013-5126","title":"Actual evapotranspiration modeling using the operational Simplified Surface Energy Balance (SSEBop) approach","docAbstract":"Remote-sensing technology and surface-energy-balance methods can provide accurate and repeatable estimates of actual evapotranspiration (ETa) when used in combination with local weather datasets over irrigated lands. Estimates of ETa may be used to provide a consistent, accurate, and efficient approach for estimating regional water withdrawals for irrigation and associated consumptive use (CU), especially in arid cropland areas that require supplemental water due to insufficient natural supplies from rainfall, soil moisture, or groundwater. ETa in these areas is considered equivalent to CU, and represents the part of applied irrigation water that is evaporated and/or transpired, and is not available for immediate reuse. A recent U.S. Geological Survey study demonstrated the application of the remote-sensing-based Simplified Surface Energy Balance (SSEB) model to estimate 10-year average ETa at 1-kilometer resolution on national and regional scales, and compared those ETa values to the U.S. Geological Survey’s National Water-Use Information Program’s 1995 county estimates of CU. The operational version of the operational SSEB (SSEBop) method is now used to construct monthly, county-level ETa maps of the conterminous United States for the years 2000, 2005, and 2010. The performance of the SSEBop was evaluated using eddy covariance flux tower datasets compiled from 2005 datasets, and the results showed a strong linear relationship in different land cover types across diverse ecosystems in the conterminous United States (correlation coefficient [r] ranging from 0.75 to 0.95). For example, r for woody savannas (0.75), grassland (0.75), forest (0.82), cropland (0.84), shrub land (0.89), and urban (0.95). A comparison of the remote-sensing SSEBop method for estimating ETa and the Hamon temperature method for estimating potential ET (ETp) also was conducted, using regressions of all available county averages of ETa for 2005 and 2010, and yielded correlations of r = 0.60 and r = 0.71, respectively. Correlations generally are stronger in the Southeast where ETa is close to ETp. SSEBop ETa provides more spatial detail and accuracy in the Southwest where irrigation is practiced in a smaller proportion of the region.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135126","collaboration":"Groundwater Resources Program","usgsCitation":"Savoca, M.E., Senay, G., Maupin, M.A., Kenny, J., and Perry, C.A., 2013, Actual evapotranspiration modeling using the operational Simplified Surface Energy Balance (SSEBop) approach: U.S. Geological Survey Scientific Investigations Report 2013-5126, iv, 15 p., https://doi.org/10.3133/sir20135126.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":274426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135126.jpg"},{"id":274424,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5126/"},{"id":274423,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5126/pdf/sir20135126.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.800,24.50000 ], [ -124.800,49.383333 ], [ -66.9500,49.383333 ], [ -66.9500,24.50000 ], [ -124.800,24.50000 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d3e84fe4b09630fbdc5246","contributors":{"authors":[{"text":"Savoca, Mark E. mesavoca@usgs.gov","contributorId":1961,"corporation":false,"usgs":true,"family":"Savoca","given":"Mark","email":"mesavoca@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":66808,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","affiliations":[],"preferred":false,"id":480188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maupin, Molly A. 0000-0002-2695-5505 mamaupin@usgs.gov","orcid":"https://orcid.org/0000-0002-2695-5505","contributorId":951,"corporation":false,"usgs":true,"family":"Maupin","given":"Molly","email":"mamaupin@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480185,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kenny, Joan F.","contributorId":69132,"corporation":false,"usgs":true,"family":"Kenny","given":"Joan F.","affiliations":[],"preferred":false,"id":480189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perry, Charles A. cperry@usgs.gov","contributorId":2093,"corporation":false,"usgs":true,"family":"Perry","given":"Charles","email":"cperry@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":480187,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046762,"text":"ofr20121244 - 2013 - Monitoring of stage and velocity, for computation of discharge in the Summit Conduit near Summit, Illinois, 2010-2012","interactions":[],"lastModifiedDate":"2013-07-02T10:56:34","indexId":"ofr20121244","displayToPublicDate":"2013-07-02T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1244","title":"Monitoring of stage and velocity, for computation of discharge in the Summit Conduit near Summit, Illinois, 2010-2012","docAbstract":"Lake Michigan diversion accounting is the process used by the U. S. Army Corps of Engineers to quantify the amount of water that is diverted from the Lake Michigan watershed into the Illinois and Mississippi River Basins. A network of streamgages within the Chicago area waterway system monitor tributary river flows and the major river flow on the Chicago Sanitary and Ship Canal near Lemont as one of the instrumental tools used for Lake Michigan diversion accounting. The mean annual discharges recorded by these streamgages are used as additions or deductions to the mean annual discharge recorded by the main stream gaging station currently used in the Lake Michigan diversion accounting process, which is the Chicago Sanitary and Ship Canal near Lemont, Illinois (station number 05536890). A new stream gaging station, Summit Conduit near Summit, Illinois (station number 414757087490401), was installed on September 23, 2010, for the purpose of monitoring stage, velocity, and discharge through the Summit Conduit for the U.S. Army Corps of Engineers in accordance with Lake Michigan diversion accounting. Summit Conduit conveys flow from a small part of the lower Des Plaines River watershed underneath the Des Plaines River directly into the Chicago Sanitary and Ship Canal. Because the Summit Conduit discharges into the Chicago Sanitary and Ship Canal upstream from the stream gaging station at Lemont, Illinois, but does not contain flow diverted from the Lake Michigan watershed, it is considered a flow deduction to the discharge measured by the Lemont stream gaging station in the Lake Michigan diversion accounting process. This report offers a technical summary of the techniques and methods used for the collection and computation of the stage, velocity, and discharge data at the Summit Conduit near Summit, Illinois stream gaging station for the 2011 and 2012 Water Years. The stream gaging station Summit Conduit near Summit, Illinois (station number 414757087490401) is an example of a nonstandard stream gage. Traditional methods of equating stage to discharge historically were not effective. Examples of the nonstandard conditions include the converging tributary flows directly upstream of the gage; the trash rack and walkway near the opening of the conduit introducing turbulence and occasionally entraining air bubbles into the flow; debris within the conduit creating conditions of variable backwater and the constant influx of smaller debris that escapes the trash rack and catches or settles in the conduit and on the equipment. An acoustic Doppler velocity meter was installed to measure stage and velocity to compute discharge. The stage is used to calculate area based the stage-area rating. The index-velocity from the acoustic Doppler velocity meter is applied to the velocity-velocity rating and the product of the two rated values is a rated discharge by the index-velocity method. Nonstandard site conditions prevalent at the Summit Conduit stream gaging station generally are overcome through the index-velocity method. Despite the difficulties in gaging and measurements, improvements continue to be made in data collection, transmission, and measurements. Efforts to improve the site and to improve the ratings continue to improve the quality and quantity of the data available for Lake Michigan diversion accounting.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121244","collaboration":"In cooperation with U.S. Army Corps of Engineers","usgsCitation":"Johnson, K.K., and Goodwin, G.E., 2013, Monitoring of stage and velocity, for computation of discharge in the Summit Conduit near Summit, Illinois, 2010-2012: U.S. Geological Survey Open-File Report 2012-1244, vi, 45 p., appendixes, https://doi.org/10.3133/ofr20121244.","productDescription":"vi, 45 p., appendixes","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":274421,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121244.jpg"},{"id":274419,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1244/pdf/ofr2012-1244.pdf"},{"id":274420,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1244/"}],"scale":"100000","projection":"Albers Equal-Area Conic","country":"United States","state":"Illinois","city":"Summit","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.249569,41.499964 ], [ -88.249569,42.154369 ], [ -87.399673,42.154369 ], [ -87.399673,41.499964 ], [ -88.249569,41.499964 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d3e859e4b09630fbdc525e","contributors":{"authors":[{"text":"Johnson, Kevin K. 0000-0003-2703-5994 johnsonk@usgs.gov","orcid":"https://orcid.org/0000-0003-2703-5994","contributorId":4220,"corporation":false,"usgs":true,"family":"Johnson","given":"Kevin","email":"johnsonk@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodwin, Greg E.","contributorId":45987,"corporation":false,"usgs":true,"family":"Goodwin","given":"Greg","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":480182,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70048502,"text":"70048502 - 2013 - Modeling the colonization of Hawaii by hoary bats (Lasiurus cinereus)","interactions":[],"lastModifiedDate":"2013-11-15T10:23:34","indexId":"70048502","displayToPublicDate":"2013-07-01T15:33:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Modeling the colonization of Hawaii by hoary bats (Lasiurus cinereus)","docAbstract":"The Hawaiian archipelago, the most isolated cluster of islands on Earth, has been colonized successfully twice by bats. The putative “lava tube bat” of Hawaii is extinct, whereas the Hawaiian Hoary Bat, Lasiurus cinereus semotus, survives as an endangered species. We conducted a three-stage analysis to identify conditions under which hoary bats originally colonized Hawaii. We used FLIGHT to determine if stores of fat would provide the energy necessary to fly from the Farallon Islands (California) to Hawaii, a distance of 3,665 km. The Farallons are a known stopover and the closest landfall to Hawaii for hoary bats during migrations within North America. Our modeling variables included physiological, morphological, and behavioral data characterizing North American Hoary Bat populations. The second step of our modeling process investigated the potential limiting factor of water during flight. The third step in our modeling examines the role that prevailing trade winds may have played in colonization flights. Of our 36 modeling scenarios, 17 (47 %) require tailwind assistance within the range of observed wind speeds, and 7 of these scenarios required <10 m s−1 tailwinds as regularly expected due to easterly trade winds. Therefore the climatic conditions needed for bats to colonize Hawaii may not occur infrequently either in contemporary times or since the end of the Pleistocene. Hawaii’s hoary bats have undergone divergence from mainland populations resulting in smaller body size and unique pelage color.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bat Evolution, Ecology, and Conservation","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","publisherLocation":"New York","doi":"10.1007/978-1-4614-7397-8_10","isbn":"9781461473961","usgsCitation":"Bonaccorso, F., and McGuire, L.P., 2013, Modeling the colonization of Hawaii by hoary bats (Lasiurus cinereus), chap. of Bat Evolution, Ecology, and Conservation, p. 187-205, https://doi.org/10.1007/978-1-4614-7397-8_10.","productDescription":"19 p.","startPage":"187","endPage":"205","numberOfPages":"19","ipdsId":"IP-038836","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":278661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278660,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/978-1-4614-7397-8_10"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -178.31,18.91 ], [ -178.31,28.4 ], [ -154.81,28.4 ], [ -154.81,18.91 ], [ -178.31,18.91 ] ] ] } } ] }","noUsgsAuthors":false,"publicationDate":"2013-07-08","publicationStatus":"PW","scienceBaseUri":"5274cd7ee4b089748f072438","contributors":{"authors":[{"text":"Bonaccorso, Frank J.","contributorId":73089,"corporation":false,"usgs":true,"family":"Bonaccorso","given":"Frank J.","affiliations":[],"preferred":false,"id":484859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Liam P.","contributorId":66161,"corporation":false,"usgs":true,"family":"McGuire","given":"Liam","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484858,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043567,"text":"70043567 - 2013 - Effects of sampling conditions on DNA-based estimates of American black bear abundance","interactions":[],"lastModifiedDate":"2016-04-19T11:24:29","indexId":"70043567","displayToPublicDate":"2013-07-01T15:24:00","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":"Effects of sampling conditions on DNA-based estimates of American black bear abundance","docAbstract":"DNA-based capture-mark-recapture techniques are commonly used to estimate American black bear (Ursus americanus) population abundance (N). Although the technique is well established, many questions remain regarding study design. In particular, relationships among N, capture probability of heterogeneity mixtures A and B (pA and pB, respectively, or p, collectively), the proportion of each mixture (π), number of capture occasions (k), and probability of obtaining reliable estimates of N are not fully understood. We investigated these relationships using 1) an empirical dataset of DNA samples for which true N was unknown and 2) simulated datasets with known properties that represented a broader array of sampling conditions. For the empirical data analysis, we used the full closed population with heterogeneity data type in Program MARK to estimate N for a black bear population in Great Smoky Mountains National Park, Tennessee. We systematically reduced the number of those samples used in the analysis to evaluate the effect that changes in capture probabilities may have on parameter estimates. Model-averaged N for females and males were 161 (95% CI = 114–272) and 100 (95% CI = 74–167), respectively (pooled N = 261, 95% CI = 192–419), and the average weekly p was 0.09 for females and 0.12 for males. When we reduced the number of samples of the empirical data, support for heterogeneity models decreased. For the simulation analysis, we generated capture data with individual heterogeneity covering a range of sampling conditions commonly encountered in DNA-based capture-mark-recapture studies and examined the relationships between those conditions and accuracy (i.e., probability of obtaining an estimated N that is within 20% of true N), coverage (i.e., probability that 95% confidence interval includes true N), and precision (i.e., probability of obtaining a coefficient of variation ≤20%) of estimates using logistic regression. The capture probability for the larger of 2 mixture proportions of the population (i.e., pA or pB, depending on the value of π) was most important for predicting accuracy and precision, whereas capture probabilities of both mixture proportions (pA and pB) were important to explain variation in coverage. Based on sampling conditions similar to parameter estimates from the empirical dataset (pA = 0.30, pB = 0.05, N = 250, π = 0.15, and k = 10), predicted accuracy and precision were low (60% and 53%, respectively), whereas coverage was high (94%). Increasing pB, the capture probability for the predominate but most difficult to capture proportion of the population, was most effective to improve accuracy under those conditions. However, manipulation of other parameters may be more effective under different conditions. In general, the probabilities of obtaining accurate and precise estimates were best when p≥ 0.2. Our regression models can be used by managers to evaluate specific sampling scenarios and guide development of sampling frameworks or to assess reliability of DNA-based capture-mark-recapture studies.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.534","usgsCitation":"Laufenberg, J.S., van Manen, F., and Clark, J.D., 2013, Effects of sampling conditions on DNA-based estimates of American black bear abundance: Journal of Wildlife Management, v. 77, no. 5, p. 1010-1020, https://doi.org/10.1002/jwmg.534.","productDescription":"11 p.","startPage":"1010","endPage":"1020","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037908","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":288188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288185,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.534"}],"country":"United States","state":"Tennessee","otherGeospatial":"Great Smoky Mountains National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":473856,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70103838,"text":"70103838 - 2013 - Field calibration and validation of remote-sensing surveys","interactions":[],"lastModifiedDate":"2017-11-10T18:26:14","indexId":"70103838","displayToPublicDate":"2013-07-01T13:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Field calibration and validation of remote-sensing surveys","docAbstract":"The Optical Collection Suite (OCS) is a ground-truth sampling system designed to perform in situ measurements that help calibrate and validate optical remote-sensing and swath-sonar surveys for mapping and monitoring coastal ecosystems and ocean planning. The OCS system enables researchers to collect underwater imagery with real-time feedback, measure the spectral response, and quantify the water clarity with simple and relatively inexpensive instruments that can be hand-deployed from a small vessel. This article reviews the design and performance of the system, based on operational and logistical considerations, as well as the data requirements to support a number of coastal science and management projects. The OCS system has been operational since 2009 and has been used in several ground-truth missions that overlapped with airborne lidar bathymetry (ALB), hyperspectral imagery (HSI), and swath-sonar bathymetric surveys in the Gulf of Maine, southwest Alaska, and the US Virgin Islands (USVI). Research projects that have used the system include a comparison of backscatter intensity derived from acoustic (multibeam/interferometric sonars) versus active optical (ALB) sensors, ALB bottom detection, and seafloor characterization using HSI and ALB.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2013.800655","usgsCitation":"Pe’eri, S., McLeod, A., Lavoie, P., Ackerman, S.D., Gardner, J., and Parrish, C., 2013, Field calibration and validation of remote-sensing surveys: International Journal of Remote Sensing, v. 34, no. 18, p. 6423-6436, https://doi.org/10.1080/01431161.2013.800655.","productDescription":"14 p.","startPage":"6423","endPage":"6436","numberOfPages":"14","ipdsId":"IP-044361","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":286999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286989,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2013.800655"}],"country":"United States;U.S. Virgin Islands","state":"Alaska","otherGeospatial":"Gulf Of Maine","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -133.810887,17.774787 ], [ -133.810887,56.580001 ], [ -64.599525,56.580001 ], [ -64.599525,17.774787 ], [ -133.810887,17.774787 ] ] ] } } ] }","volume":"34","issue":"18","noUsgsAuthors":false,"publicationDate":"2013-06-10","publicationStatus":"PW","scienceBaseUri":"536ca767e4b060efff280dab","contributors":{"authors":[{"text":"Pe’eri, Shachak","contributorId":106015,"corporation":false,"usgs":true,"family":"Pe’eri","given":"Shachak","email":"","affiliations":[],"preferred":false,"id":493459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLeod, Andy","contributorId":96592,"corporation":false,"usgs":true,"family":"McLeod","given":"Andy","email":"","affiliations":[],"preferred":false,"id":493457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lavoie, Paul","contributorId":51206,"corporation":false,"usgs":true,"family":"Lavoie","given":"Paul","email":"","affiliations":[],"preferred":false,"id":493455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ackerman, Seth D. 0000-0003-0945-2794 sackerman@usgs.gov","orcid":"https://orcid.org/0000-0003-0945-2794","contributorId":178676,"corporation":false,"usgs":true,"family":"Ackerman","given":"Seth","email":"sackerman@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":493454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, James","contributorId":93387,"corporation":false,"usgs":true,"family":"Gardner","given":"James","affiliations":[],"preferred":false,"id":493456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parrish, Christopher","contributorId":98635,"corporation":false,"usgs":true,"family":"Parrish","given":"Christopher","affiliations":[],"preferred":false,"id":493458,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70048501,"text":"70048501 - 2013 - A five-year study of Hawaiian hoary bat (Lasiurus cinereus semotus) occupancy on the island of Hawai`i","interactions":[],"lastModifiedDate":"2014-06-20T14:10:14","indexId":"70048501","displayToPublicDate":"2013-07-01T13:42:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"HCSU-041","title":"A five-year study of Hawaiian hoary bat (Lasiurus cinereus semotus) occupancy on the island of Hawai`i","docAbstract":"Using acoustic recordings of the vocalizations of the endangered Hawaiian hoary bat (Lasiurus \ncinereus semotus) collected over a five-year period (2007–2011) from 25 survey areas across \nthe island of Hawai`i, we modeled the relationship between habitat attributes and bat \noccurrence. Our data support the conclusion that hoary bats concentrate in the coastal lowlands \nof Hawai`i during the breeding season, May through October, and migrate to interior highlands \nduring the winter non-breeding season. Highest occupancy peaked on the Julian date 15 \nSeptember across the five-year average and during the season of fledging by the young of the \nyear. Although the Hawaiian hoary bat is a habitat generalist species and occurs from sea level \nto the highest volcanic peaks on Hawai`i, there was a significant association between\noccupancy and the prevalence of mature forest cover. Trends in occupancy were stable to\nslightly increasing during the breeding season over the five years of our surveys.","language":"English","publisher":"University of Hawai‘i at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Gorressen, M.P., Bonaccorso, F., Pinzari, C., Todd, C.M., Montoya-Aiona, K., and Brinck, K., 2013, A five-year study of Hawaiian hoary bat (Lasiurus cinereus semotus) occupancy on the island of Hawai`i, iv, 48 p.","productDescription":"iv, 48 p.","numberOfPages":"54","ipdsId":"IP-046159","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":279187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278237,"type":{"id":15,"text":"Index Page"},"url":"https://hilo.hawaii.edu/hcsu/publications.php"}],"projection":"Universal Transverse Mercator 5 North projection","datum":"North American Datum of 1983","country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.2729,18.8676 ], [ -156.2729,20.2894 ], [ -154.6488,20.2894 ], [ -154.6488,18.8676 ], [ -156.2729,18.8676 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528c96a9e4b0c629af44dd8f","contributors":{"authors":[{"text":"Gorressen, Marcos P.","contributorId":40887,"corporation":false,"usgs":true,"family":"Gorressen","given":"Marcos","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonaccorso, Frank J.","contributorId":73089,"corporation":false,"usgs":true,"family":"Bonaccorso","given":"Frank J.","affiliations":[],"preferred":false,"id":484857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pinzari, Corinna A.","contributorId":57359,"corporation":false,"usgs":true,"family":"Pinzari","given":"Corinna A.","affiliations":[],"preferred":false,"id":484855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Todd, Christopher M.","contributorId":64548,"corporation":false,"usgs":true,"family":"Todd","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":484856,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Montoya-Aiona, Kristina 0000-0002-1776-5443 kmontoya-aiona@usgs.gov","orcid":"https://orcid.org/0000-0002-1776-5443","contributorId":5899,"corporation":false,"usgs":true,"family":"Montoya-Aiona","given":"Kristina","email":"kmontoya-aiona@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":484853,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":484852,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70125966,"text":"70125966 - 2013 - Comparative phylogeography reveals deep lineages and regional evolutionary hotspots in the Mojave and Sonoran Deserts","interactions":[],"lastModifiedDate":"2014-09-18T12:55:06","indexId":"70125966","displayToPublicDate":"2013-07-01T12:48:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Comparative phylogeography reveals deep lineages and regional evolutionary hotspots in the Mojave and Sonoran Deserts","docAbstract":"Aim: We explored lineage diversification within desert-dwelling fauna. Our goals were (1) to determine whether phylogenetic lineages and population expansions were consistent with younger Pleistocene climate fluctuation hypotheses or much older events predicted by pre-Pleistocene vicariance hypotheses, (2) to assess concordance in spatial patterns of genetic divergence and diversity among species and (3) to identify regional evolutionary hotspots of divergence and diversity and assess their conservation status.
\nLocation: Mojave, Colorado, and Sonoran Deserts, USA.
\nMethods: We analysed previously published gene sequence data for twelve species. We used Bayesian gene tree methods to estimate lineages and divergence times. Within each lineage, we tested for population expansion and age of expansion using coalescent approaches. We mapped interpopulation genetic divergence and intra-population genetic diversity in a GIS to identify hotspots of highest genetic divergence and diversity and to assess whether protected lands overlapped with evolutionary hotspots.
\nResults: In seven of the 12 species, lineage divergence substantially predated the Pleistocene. Historical population expansion was found in eight species, but expansion events postdated the Last Glacial Maximum (LGM) in only four. For all species assessed, six hotspots of high genetic divergence and diversity were concentrated in the Colorado Desert, along the Colorado River and in the Mojave/Sonoran ecotone. At least some proportion of the land within each recovered hotspot was categorized as protected, yet four of the six also overlapped with major areas of human development.
\nMain conclusions: Most of the species studied here diversified into distinct Mojave and Sonoran lineages prior to the LGM – supporting older diversification hypotheses. Several evolutionary hotspots were recovered but are not strategically paired with areas of protected land. Long-term preservation of species-level biodiversity would entail selecting areas for protection in Mojave and Sonoran Deserts to retain divergent genetic diversity and ensure connectedness across environmental gradients.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Diversity and Distributions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford, England","doi":"10.1111/ddi.12022","usgsCitation":"Wood, D.A., Vandergast, A.G., Barr, K.R., Inman, R.D., Esque, T., Nussear, K.E., and Fisher, R.N., 2013, Comparative phylogeography reveals deep lineages and regional evolutionary hotspots in the Mojave and Sonoran Deserts: Diversity and Distributions, v. 19, no. 7, p. 722-737, https://doi.org/10.1111/ddi.12022.","productDescription":"16 p.","startPage":"722","endPage":"737","numberOfPages":"16","ipdsId":"IP-041224","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":473706,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12022","text":"Publisher Index Page"},{"id":294158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294151,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/ddi.12022"}],"country":"United States","otherGeospatial":"Colorado Desert;Mojave Desert;Sonoran Desert","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.47,31.33 ], [ -119.47,37.78 ], [ -109.89,37.78 ], [ -109.89,31.33 ], [ -119.47,31.33 ] ] ] } } ] }","volume":"19","issue":"7","noUsgsAuthors":false,"publicationDate":"2012-12-04","publicationStatus":"PW","scienceBaseUri":"541bf421e4b0e96537ddf668","contributors":{"authors":[{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":97617,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barr, Kelly R. kelly_barr@usgs.gov","contributorId":5628,"corporation":false,"usgs":true,"family":"Barr","given":"Kelly","email":"kelly_barr@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501812,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Inman, Richard D. rdinman@usgs.gov","contributorId":3316,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":501810,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":3221,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":501809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501808,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501807,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70048579,"text":"70048579 - 2013 - Delivering integrated HAZUS-MH flood loss analyses and flood inundation maps over the Web","interactions":[],"lastModifiedDate":"2013-10-24T11:17:54","indexId":"70048579","displayToPublicDate":"2013-07-01T11:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2246,"text":"Journal of Emergency Management","active":true,"publicationSubtype":{"id":10}},"title":"Delivering integrated HAZUS-MH flood loss analyses and flood inundation maps over the Web","docAbstract":"Catastrophic flooding is responsible for more loss of life and damages to property than any other natural hazard. Recently developed flood inundation mapping technologies make it possible to view the extent and depth of flooding on the land surface over the Internet; however, by themselves these technologies are unable to provide estimates of losses to property and infrastructure. The Federal Emergency Management Agency’s (FEMA's) HAZUS-MH software is extensively used to conduct flood loss analyses in the United States, providing a nationwide database of population and infrastructure at risk. Unfortunately, HAZUS-MH requires a dedicated Geographic Information System (GIS) workstation and a trained operator, and analyses are not adapted for convenient delivery over the Web. This article describes a cooperative effort by the US Geological Survey (USGS) and FEMA to make HAZUS-MH output GIS and Web compatible and to integrate these data with digital flood inundation maps in USGS’s newly developed Inundation Mapping Web Portal. By running the computationally intensive HAZUS-MH flood analyses offline and converting the output to a Web-GIS compatible format, detailed estimates of flood losses can now be delivered to anyone with Internet access, thus dramatically increasing the availability of these forecasts to local emergency planners and first responders.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Emergency Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Prime National Publication Corporation","doi":"10.5055/jem.2013.0145","usgsCitation":"Hearn, Longenecker, H.E., Aguinaldo, J.J., and Rahav, A.N., 2013, Delivering integrated HAZUS-MH flood loss analyses and flood inundation maps over the Web: Journal of Emergency Management, v. 11, no. 4, p. 293-302, https://doi.org/10.5055/jem.2013.0145.","productDescription":"10 p.","startPage":"293","endPage":"302","numberOfPages":"10","ipdsId":"IP-039135","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":278377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278373,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5055/jem.2013.0145"}],"volume":"11","issue":"4","noUsgsAuthors":false,"publicationDate":"2017-02-16","publicationStatus":"PW","scienceBaseUri":"526a416fe4b0c0d229f9f66b","contributors":{"authors":[{"text":"Hearn, Jr. phearn@usgs.gov","contributorId":1950,"corporation":false,"usgs":true,"family":"Hearn","suffix":"Jr.","email":"phearn@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":485124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Longenecker, Herbert E. III","contributorId":105217,"corporation":false,"usgs":true,"family":"Longenecker","given":"Herbert","suffix":"III","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":485127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aguinaldo, John J.","contributorId":73287,"corporation":false,"usgs":true,"family":"Aguinaldo","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":485126,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rahav, Ami N. arahav@usgs.gov","contributorId":69463,"corporation":false,"usgs":true,"family":"Rahav","given":"Ami","email":"arahav@usgs.gov","middleInitial":"N.","affiliations":[],"preferred":false,"id":485125,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70048520,"text":"70048520 - 2013 - Rebuilding after collapse: evidence for long-term cohort dynamics in the native Hawaiian rain forest","interactions":[],"lastModifiedDate":"2013-11-15T10:25:05","indexId":"70048520","displayToPublicDate":"2013-07-01T11:04:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Rebuilding after collapse: evidence for long-term cohort dynamics in the native Hawaiian rain forest","docAbstract":"Questions: Do long-term observations in permanent plots confirm the conceptual model of Metrosideros polymorpha cohort dynamics as postulated in 1987? Do regeneration patterns occur independently of substrate age, i.e. of direct volcanic disturbance impact?\n\nLocation: The windward mountain slopes of the younger Mauna Loa and the older Mauna Kea volcanoes (island of Hawaii, USA).\n\nMethods: After widespread forest decline (dieback), permanent plots were established in 1976 in 13 dieback and 13 non-dieback patches to monitor the population structure of M. polymorpha at ca. 5-yr intervals. Within each plot of 20 × 20 m, all trees with DBH >2.5 cm were individually tagged, measured and tree vigour assessed; regeneration was quantified in 16 systematically placed subplots of 3 × 5 m. Data collected in the subplots included the total number of M. polymorpha seedlings and saplings (five stem height classes). Here we analyse monitoring data from six time steps from 1976 to 2003 using repeated measures ANOVA to test specific predictions derived from the 1987 conceptual model.\n\nResults: Regeneration was significantly different between dieback and non-dieback plots. In dieback plots, the collapse in the 1970s was followed by a ‘sapling wave’ that by 2003 led to new cohort stands of M. polymorpha. In non-dieback stands, seedling emergence did not result in sapling waves over the same period. Instead, a ‘sapling gap’ (i.e. very few or no M. polymorpha saplings) prevailed as typical for mature stands. Canopy dieback in 1976, degree of recovery by 2003 and the number of living trees in 2003 were unrelated to substrate age.\n\nConclusions: Population development of M. polymorpha supports the cohort dynamics model, which predicts rebuilding of the forest with the same canopy species after dieback. The lack of association with substrate age suggests that the long-term maintenance of cohort structure in M. polymorpha does not depend on volcanic disturbance but may be related to other environmental mechanisms, such as climate anomalies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Vegetation Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/jvs.12000","usgsCitation":"Boehmer, H., Wagner, H.H., Jacobi, J.D., Gerrish, G.C., and Mueller-Dombois, D., 2013, Rebuilding after collapse: evidence for long-term cohort dynamics in the native Hawaiian rain forest: Journal of Vegetation Science, v. 24, no. 4, p. 639-650, https://doi.org/10.1111/jvs.12000.","productDescription":"12 p.","startPage":"639","endPage":"650","numberOfPages":"12","ipdsId":"IP-026370","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":473711,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/75550","text":"External Repository"},{"id":278376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278375,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jvs.12000"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.707,19.1549 ], [ -155.707,20.1673 ], [ -154.8068,20.1673 ], [ -154.8068,19.1549 ], [ -155.707,19.1549 ] ] ] } } ] }","volume":"24","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-11-27","publicationStatus":"PW","scienceBaseUri":"526a4174e4b0c0d229f9f6ae","contributors":{"authors":[{"text":"Boehmer, Hans Juergen","contributorId":45996,"corporation":false,"usgs":true,"family":"Boehmer","given":"Hans Juergen","affiliations":[],"preferred":false,"id":484938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Helene H.","contributorId":12309,"corporation":false,"usgs":true,"family":"Wagner","given":"Helene","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":484937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":484936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerrish, Grant C.","contributorId":69049,"corporation":false,"usgs":true,"family":"Gerrish","given":"Grant","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":484939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mueller-Dombois, Dieter","contributorId":100730,"corporation":false,"usgs":true,"family":"Mueller-Dombois","given":"Dieter","affiliations":[],"preferred":false,"id":484940,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70041208,"text":"70041208 - 2013 - Assessment of the NASA-USGS Global Land Survey (GLS) Datasets","interactions":[],"lastModifiedDate":"2017-04-06T16:00:45","indexId":"70041208","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of the NASA-USGS Global Land Survey (GLS) Datasets","docAbstract":"The Global Land Survey (GLS) datasets are a collection of orthorectified, cloud-minimized Landsat-type satellite images, providing near complete coverage of the global land area decadally since the early 1970s. The global mosaics are centered on 1975, 1990, 2000, 2005, and 2010, and consist of data acquired from four sensors: Enhanced Thematic Mapper Plus, Thematic Mapper, Multispectral Scanner, and Advanced Land Imager. The GLS datasets have been widely used in land-cover and land-use change studies at local, regional, and global scales. This study evaluates the GLS datasets with respect to their spatial coverage, temporal consistency, geodetic accuracy, radiometric calibration consistency, image completeness, extent of cloud contamination, and residual gaps. In general, the three latest GLS datasets are of a better quality than the GLS-1990 and GLS-1975 datasets, with most of the imagery (85%) having cloud cover of less than 10%, the acquisition years clustered much more tightly around their target years, better co-registration relative to GLS-2000, and better radiometric absolute calibration. Probably, the most significant impediment to scientific use of the datasets is the variability of image phenology (i.e., acquisition day of year). This paper provides end-users with an assessment of the quality of the GLS datasets for specific applications, and where possible, suggestions for mitigating their deficiencies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2013.02.026","usgsCitation":"Gutman, G., Huang, C., Chander, G., Noojipady, P., and Masek, J.G., 2013, Assessment of the NASA-USGS Global Land Survey (GLS) Datasets: Remote Sensing of Environment, v. 134, p. 249-265, https://doi.org/10.1016/j.rse.2013.02.026.","productDescription":"17 p.","startPage":"249","endPage":"265","ipdsId":"IP-037259","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":339371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"UNITED STATES","volume":"134","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e753eee4b09da6799c0c53","contributors":{"authors":[{"text":"Gutman, Garik","contributorId":190654,"corporation":false,"usgs":false,"family":"Gutman","given":"Garik","email":"","affiliations":[],"preferred":false,"id":690210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huang, Chengquan","contributorId":25378,"corporation":false,"usgs":true,"family":"Huang","given":"Chengquan","affiliations":[],"preferred":false,"id":690211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":690212,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noojipady, Praveen","contributorId":24260,"corporation":false,"usgs":true,"family":"Noojipady","given":"Praveen","email":"","affiliations":[],"preferred":false,"id":690213,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Masek, Jeffery G.","contributorId":87438,"corporation":false,"usgs":true,"family":"Masek","given":"Jeffery","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":690214,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193598,"text":"70193598 - 2013 - Integrating satellite observations and modern climate measurements with the recent sedimentary record: An example from Southeast Alaska","interactions":[],"lastModifiedDate":"2017-11-02T14:32:48","indexId":"70193598","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Integrating satellite observations and modern climate measurements with the recent sedimentary record: An example from Southeast Alaska","docAbstract":"Assessments of climate change over time scales that exceed the last 100 years require robust integration of high-quality instrument records with high-resolution paleoclimate proxy data. In this study, we show that the recent biogenic sediments accumulating in two temperate ice-free fjords in Southeast Alaska preserve evidence of North Pacific Ocean climate variability as recorded by both instrument networks and satellite observations. Multicore samples EW0408-32MC and EW0408-43MC were investigated with 137Cs and excess 210Pb geochronometry, three-dimensional computed tomography, high-resolution scanning XRF geochemistry, and organic stable isotope analyses. EW0408-32MC (57.162°N, 135.357°W, 146 m depth) is a moderately bioturbated continuous record that spans AD ∼1930–2004. EW0408-43MC (56.965°N, 135.268°W, 91 m depth) is composed of laminated diatom oozes, a turbidite, and a hypopycnal plume (river flood) deposit. A discontinuous event-based varve chronology indicates 43MC spans AD ∼1940–1981. Decadal-scale fluctuations in sedimentary Br/Cl ratios accurately reflect changes in marine organic matter accumulation that display the same temporal pattern as that of the Pacific Decadal Oscillation. An estimated Sitka summer productivity parameter calibrated using SeaWiFS satellite observations support these relationships. The correlation of North Pacific climate regime states, primary productivity, and sediment geochemistry indicate the accumulation of biogenic sediment in Southeast Alaska temperate fjords can be used as a sensitive recorder of past productivity variability, and by inference, past climate conditions in the high-latitude Gulf of Alaska.
","language":"English","publisher":"AGU","doi":"10.1002/jgrc.20243","usgsCitation":"Addison, J.A., Finney, B., Jaeger, J.M., Stoner, J.S., Norris, R.D., and Hangsterfer, A., 2013, Integrating satellite observations and modern climate measurements with the recent sedimentary record: An example from Southeast Alaska: Journal of Geophysical Research: Oceans, v. 118, no. 7, p. 3444-3461, https://doi.org/10.1002/jgrc.20243.","productDescription":"18 p.","startPage":"3444","endPage":"3461","ipdsId":"IP-043226","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473724,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrc.20243","text":"Publisher Index Page"},{"id":348106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155,\n 50\n ],\n [\n -120,\n 50\n ],\n [\n -120,\n 61\n ],\n [\n -155,\n 61\n ],\n [\n -155,\n 50\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-07-17","publicationStatus":"PW","scienceBaseUri":"59fc2eace4b0531197b27fc1","contributors":{"authors":[{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":719559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finney, Bruce P.","contributorId":88074,"corporation":false,"usgs":true,"family":"Finney","given":"Bruce P.","affiliations":[],"preferred":false,"id":719561,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jaeger, John M.","contributorId":11423,"corporation":false,"usgs":true,"family":"Jaeger","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":719562,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stoner, Joseph S.","contributorId":84171,"corporation":false,"usgs":true,"family":"Stoner","given":"Joseph","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":719563,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Norris, Richard D.","contributorId":51651,"corporation":false,"usgs":true,"family":"Norris","given":"Richard","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":719564,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hangsterfer, Alexandra","contributorId":199603,"corporation":false,"usgs":false,"family":"Hangsterfer","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":719560,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ]}