{"pageNumber":"611","pageRowStart":"15250","pageSize":"25","recordCount":46679,"records":[{"id":70249837,"text":"70249837 - 2012 - Mapped versus actual burned area within wildfire perimeters: Characterizing the unburned","interactions":[],"lastModifiedDate":"2023-11-01T21:03:50.201344","indexId":"70249837","displayToPublicDate":"2012-11-01T15:58:22","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Mapped versus actual burned area within wildfire perimeters: Characterizing the unburned","docAbstract":"<div id=\"aep-abstract-id19\" class=\"abstract author\" lang=\"en\"><div id=\"aep-abstract-sec-id20\"><p id=\"sp0010\">For decades, wildfire studies have utilized fire occurrence as the primary data source for investigating the causes and effects of wildfire on the landscape. Fire occurrence data fall primarily into two categories: ignition points and perimeter polygons which are used to calculate a ‘burned area’ for a fire. However, understanding the relationships between climate and fire or between fire and its ecological effects requires an understanding of the burn heterogeneity across the landscape and the area within fire perimeters that remains unburned. This research characterizes unburned areas within fire perimeters, which provide ecological refugia and seed source for post-fire regeneration. We utilized differenced Normalized Burn Ratio (dNBR) data to examine the frequency, extent, and spatial patterns of unburned area in three national parks across the western US (Glacier, Yosemite, and Yukon-Charley Rivers). We characterized unburned area within fire perimeters by fire size and severity, characterized distance to an unburned area across the burned portion of the fire, and investigated patch dynamics of unburned patches within the fire perimeter. From 1984 through 2009, the total area within the fire perimeters that was classified as unburned from dNBR was 37% for Yosemite, 17% for Glacier, and 14% for Yukon-Charley. Variation in unburned area between fires was highest in Yosemite and lowest in Yukon-Charley. The unburned proportion significantly decreased with increasing fire size and severity across all three parks. Unburned patch size increased with size of fire perimeter, but patches decreased in density. There were no temporal trends in unburned area found. These results raise questions about the validity of relationships found between external forcing agents, such as climate, and ‘burned area’ values derived solely from polygon fire perimeters.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2012.08.020","usgsCitation":"Key, C.H., James Lutz, Key, C.H., Jonathan Kane, and Van Wagtendonk, J.W., 2012, Mapped versus actual burned area within wildfire perimeters: Characterizing the unburned: Forest Ecology and Management, v. 286, p. 38-47, https://doi.org/10.1016/j.foreco.2012.08.020.","productDescription":"10 p.","startPage":"38","endPage":"47","ipdsId":"IP-039364","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":422316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Montana, Wyoming","otherGeospatial":"Yosemite National Park, Glacier National Park, Yukon-Charley Rivers National Preserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.2239315959776,\n              45.14819375625538\n            ],\n            [\n              -111.2239315959776,\n              43.41806384026984\n            ],\n            [\n              -108.73003511160249,\n              43.41806384026984\n            ],\n            [\n              -108.73003511160249,\n              45.14819375625538\n            ],\n            [\n              -111.2239315959776,\n              45.14819375625538\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.90435217871973,\n              49.04942005803713\n            ],\n            [\n              -114.90435217871973,\n              48.12286489452612\n            ],\n            [\n              -112.71257971778198,\n              48.12286489452612\n            ],\n            [\n              -112.71257971778198,\n              49.04942005803713\n            ],\n            [\n              -114.90435217871973,\n              49.04942005803713\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -143.54242128938068,\n              65.82194598460669\n            ],\n            [\n              -143.54242128938068,\n              64.41714830535625\n            ],\n            [\n              -140.55414003938063,\n              64.41714830535625\n            ],\n            [\n              -140.55414003938063,\n              65.82194598460669\n            ],\n            [\n              -143.54242128938068,\n              65.82194598460669\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"286","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Key, Carl H carl_key@usgs.gov","contributorId":331312,"corporation":false,"usgs":true,"family":"Key","given":"Carl","email":"carl_key@usgs.gov","middleInitial":"H","affiliations":[],"preferred":true,"id":887307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"James Lutz","contributorId":331315,"corporation":false,"usgs":false,"family":"James Lutz","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":887310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Key, Carl H. carl_key@usgs.gov","contributorId":4138,"corporation":false,"usgs":true,"family":"Key","given":"Carl","email":"carl_key@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":887317,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jonathan Kane","contributorId":331316,"corporation":false,"usgs":false,"family":"Jonathan Kane","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":887311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Wagtendonk, Jan W jan_van_wagtendonk@usgs.gov","contributorId":331313,"corporation":false,"usgs":true,"family":"Van Wagtendonk","given":"Jan","email":"jan_van_wagtendonk@usgs.gov","middleInitial":"W","affiliations":[],"preferred":true,"id":887308,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70101174,"text":"70101174 - 2012 - Population ecology of breeding Pacific common eiders on the Yukon-Kuskokwim Delta, Alaska","interactions":[],"lastModifiedDate":"2014-04-10T11:45:15","indexId":"70101174","displayToPublicDate":"2012-11-01T11:40:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3773,"text":"Wildlife Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Population ecology of breeding Pacific common eiders on the Yukon-Kuskokwim Delta, Alaska","docAbstract":"Populations of Pacific common eiders (Somateria mollissima v-nigrum) on the Yukon-Kuskokwim Delta (YKD) in western Alaska declined by 50–90% from 1957 to 1992 and then stabilized at reduced numbers from the early 1990s to the present. We investigated the underlying processes affecting their population dynamics by collection and analysis of demographic data from Pacific common eiders at 3 sites on the YKD (1991–2004) for 29 site-years. We examined variation in components of reproduction, tested hypotheses about the influence of specific ecological factors on life-history variables, and investigated their relative contributions to local population dynamics. Reproductive output was low and variable, both within and among individuals, whereas apparent survival of adult females was high and relatively invariant (0.89 ± 0.005). All reproductive parameters varied across study sites and years. Clutch initiation dates ranged from 4 May to 28 June, with peak (modal) initiation occurring on 26 May. Females at an island study site consistently initiated clutches 3–5 days earlier in each year than those on 2 mainland sites. Population variance in nest initiation date was negatively related to the peak, suggesting increased synchrony in years of delayed initiation. On average, total clutch size (laid) ranged from 4.8 to 6.6 eggs, and declined with date of nest initiation. After accounting for partial predation and non-viability of eggs, average clutch size at hatch ranged from 2.0 to 5.8 eggs. Within seasons, daily survival probability (DSP) of nests was lowest during egg-laying and late-initiation dates. Estimated nest survival varied considerably across sites and years (mean = 0.55, range: 0.06–0.92), but process variance in nest survival was relatively low (0.02, CI: 0.01–0.05), indicating that most variance was likely attributed to sampling error. We found evidence that observer effects may have reduced overall nest survival by 0.0–0.36 across site-years. Study sites with lower sample sizes and more frequent visitations appeared to experience greater observer effects. In general, Pacific common eiders exhibited high spatio-temporal variance in reproductive components. Larger clutch sizes and high nest survival at early initiation dates suggested directional selection favoring early nesting. However, stochastic environmental effects may have precluded response to this apparent selection pressure. Our results suggest that females breeding early in the season have the greatest reproductive value, as these birds lay the largest clutches and have the highest probability of successfully hatching. We developed stochastic, stage-based, matrix population models that incorporated observed spatio-temporal (process) variance and co-variation in vital rates, and projected the stable stage distribution () and population growth rate (λ). We used perturbation analyses to examine the relative influence of changes in vital rates on λ and variance decomposition to assess the proportion of variation in λ explained by process variation in each vital rate. In addition to matrix-based λ, we estimated λ using capture–recapture approaches, and log-linear regression. We found the stable age distribution for Pacific common eiders was weighted heavily towards experienced adult females (≥4 yr of age), and all calculations of λ indicated that the YKD population was stable to slightly increasing (λmatrix = 1.02, CI: 1.00–1.04); λreverse-capture–recapture = 1.05, CI: 0.99–1.11; λlog-linear = 1.04, CI: 0.98–1.10). Perturbation analyses suggested the population would respond most dramatically to changes in adult female survival (relative influence of adult survival was 1.5 times that of fecundity), whereas retrospective variation in λ was primarily explained by fecundity parameters (60%), particularly duckling survival (42%). Among components of fecundity, sensitivities were highest for duckling survival, suggesti","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wildlife Monographs","largerWorkSubtype":{"id":10,"text":"Journal Article"},"publisher":"Wildlife Monographs","doi":"10.1002/wmon.8","usgsCitation":"Wilson, H.M., Flint, P.L., Powell, A., Grand, J., and Moral, C.L., 2012, Population ecology of breeding Pacific common eiders on the Yukon-Kuskokwim Delta, Alaska: Wildlife Monographs, v. 182, no. 1, 28 p., https://doi.org/10.1002/wmon.8.","productDescription":"28 p.","ipdsId":"IP-028472","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438809,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G6G0AV","text":"USGS data release","linkHelpText":"Pacific common eider (Somateria mollissima v-nigrum) nest records, Yukon-Kuskokwim Delta, Alaska, 1991-2004"},{"id":286181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286079,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/wmon.8"},{"id":286080,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/wmon.8/full"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon-kushokwim Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -165.1094,62.3668 ], [ -165.1094,63.2645 ], [ -162.7789,63.2645 ], [ -162.7789,62.3668 ], [ -165.1094,62.3668 ] ] ] } } ] }","volume":"182","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-10-24","publicationStatus":"PW","scienceBaseUri":"535594f7e4b0120853e8c109","contributors":{"authors":[{"text":"Wilson, Heather M.","contributorId":37056,"corporation":false,"usgs":false,"family":"Wilson","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":13236,"text":"U.S. Fish and Wildlife Service, Migratory Bird Management","active":true,"usgs":false}],"preferred":false,"id":492634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":492633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Abby N. abby_powell@usgs.gov","contributorId":2534,"corporation":false,"usgs":false,"family":"Powell","given":"Abby N.","email":"abby_powell@usgs.gov","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":492632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grand, J. Barry","contributorId":61950,"corporation":false,"usgs":true,"family":"Grand","given":"J. Barry","affiliations":[],"preferred":false,"id":492636,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moral, Christine L.","contributorId":57765,"corporation":false,"usgs":true,"family":"Moral","given":"Christine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":492635,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047415,"text":"70047415 - 2012 - Mapping temperature and radiant geothermal heat flux anomalies in the Yellowstone geothermal system using ASTER thermal infrared data","interactions":[],"lastModifiedDate":"2019-06-04T08:58:05","indexId":"70047415","displayToPublicDate":"2012-11-01T11:10:31","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1827,"text":"Geothermal Resources Council Transactions","active":true,"publicationSubtype":{"id":10}},"title":"Mapping temperature and radiant geothermal heat flux anomalies in the Yellowstone geothermal system using ASTER thermal infrared data","docAbstract":"<p>The purpose of this work was to use satellite-based thermal infrared (TIR) remote sensing data to measure, map, and monitor geothermal activity within the Yellowstone geothermal area to help meet the missions of both the U.S. Geological Survey Yellowstone Volcano Observatory and the Yellowstone National Park Geology Program. Specifically, the goals were to: 1) address the challenges of remotely characterizing the spatially and temporally dynamic thermal features in Yellowstone by using nighttime TIR data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and 2) estimate the temperature, geothermal radiant emittance, and radiant geothermal heat flux (GHF) for Yellowstone’s thermal areas (both Park wide and for individual thermal areas). </p>\n<br/>\n<p>ASTER TIR data (90-m pixels) acquired at night during January and February, 2010, were used to estimate surface temperature, radiant emittance, and radiant GHF from all of Yellowstone’s thermal features, produce thermal anomaly maps, and update field-based maps of thermal areas. A background subtraction technique was used to isolate the geothermal component of TIR radiance from thermal radiance due to insolation. A lower limit for the Yellowstone’s total radiant GHF was established at ~2.0 GW, which is ~30-45% of the heat flux estimated through geochemical (Cl-flux) methods. Additionally, about 5 km<sup>2</sup> was added to the geodatabase of mapped thermal areas. </p>\n<br/>\n<p>This work provides a framework for future satellite-based thermal monitoring at Yellowstone as well as exploration of other volcanic / geothermal systems on a global scale.</p>","language":"English","publisher":"Geothermal Resources Council","publisherLocation":"Davis, CA","usgsCitation":"Vaughan, R.G., Lowenstern, J.B., Keszthelyi, L., Jaworowski, C., and Heasler, H., 2012, Mapping temperature and radiant geothermal heat flux anomalies in the Yellowstone geothermal system using ASTER thermal infrared data: Geothermal Resources Council Transactions, v. 36, p. 1403-1409.","productDescription":"7 p.","startPage":"1403","endPage":"1409","numberOfPages":"7","ipdsId":"IP-039085","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":287664,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287663,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1030414"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.156,44.1324 ], [ -111.156,45.109 ], [ -109.8242,45.109 ], [ -109.8242,44.1324 ], [ -111.156,44.1324 ] ] ] } } ] }","volume":"36","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5387056de4b0aa26cd7b53c9","contributors":{"authors":[{"text":"Vaughan, R. Greg 0000-0002-0850-6669","orcid":"https://orcid.org/0000-0002-0850-6669","contributorId":69030,"corporation":false,"usgs":true,"family":"Vaughan","given":"R.","email":"","middleInitial":"Greg","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":481983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowenstern, Jacob B. 0000-0003-0464-7779 jlwnstrn@usgs.gov","orcid":"https://orcid.org/0000-0003-0464-7779","contributorId":2755,"corporation":false,"usgs":true,"family":"Lowenstern","given":"Jacob","email":"jlwnstrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":481979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":52802,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo P.","email":"laz@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":481981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaworowski, Cheryl","contributorId":25989,"corporation":false,"usgs":true,"family":"Jaworowski","given":"Cheryl","affiliations":[],"preferred":false,"id":481980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heasler, Henry","contributorId":62683,"corporation":false,"usgs":true,"family":"Heasler","given":"Henry","affiliations":[],"preferred":false,"id":481982,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70039495,"text":"70039495 - 2012 - Incorporating movement patterns to improve survival estimates for juvenile bull trout","interactions":[],"lastModifiedDate":"2014-01-15T10:50:54","indexId":"70039495","displayToPublicDate":"2012-11-01T10:42:34","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating movement patterns to improve survival estimates for juvenile bull trout","docAbstract":"Populations of many fish species are sensitive to changes in vital rates during early life stages, but our understanding of the factors affecting growth, survival, and movement patterns is often extremely limited for juvenile fish. These critical information gaps are particularly evident for bull trout <i>Salvelinus confluentus</i>, a threatened Pacific Northwest char. We combined several active and passive mark–recapture and resight techniques to assess migration rates and estimate survival for juvenile bull trout (70–170 mm total length). We evaluated the relative performance of multiple survival estimation techniques by comparing results from a common Cormack–Jolly–Seber (CJS) model, the less widely used Barker model, and a simple return rate (an index of survival). Juvenile bull trout of all sizes emigrated from their natal habitat throughout the year, and thereafter migrated up to 50 km downstream. With the CJS model, high emigration rates led to an extreme underestimate of apparent survival, a combined estimate of site fidelity and survival. In contrast, the Barker model, which allows survival and emigration to be modeled as separate parameters, produced estimates of survival that were much less biased than the return rate. Estimates of age-class-specific annual survival from the Barker model based on all available data were 0.218±0.028 (estimate±SE) for age-1 bull trout and 0.231±0.065 for age-2 bull trout. This research demonstrates the importance of incorporating movement patterns into survival analyses, and we provide one of the first field-based estimates of juvenile bull trout annual survival in relatively pristine rearing conditions. These estimates can provide a baseline for comparison with future studies in more impacted systems and will help managers develop reliable stage-structured population models to evaluate future recovery strategies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"North American Journal of Fisheries Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/02755947.2012.720644","usgsCitation":"Bowerman, T., and Budy, P., 2012, Incorporating movement patterns to improve survival estimates for juvenile bull trout: North American Journal of Fisheries Management, v. 32, no. 6, p. 1123-1136, https://doi.org/10.1080/02755947.2012.720644.","productDescription":"14 p.","startPage":"1123","endPage":"1136","numberOfPages":"14","ipdsId":"IP-036702","costCenters":[{"id":609,"text":"Utah Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":498970,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02755947.2012.720644","text":"Publisher Index Page"},{"id":281076,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281075,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02755947.2012.720644"}],"country":"United States","state":"Oregon","otherGeospatial":"Blue Mountains;Skiphorton Creek;South Fork Walla Walla River;Walla Walla River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.07,45.58 ], [ -119.07,46.21 ], [ -117.39,46.21 ], [ -117.39,45.58 ], [ -119.07,45.58 ] ] ] } } ] }","volume":"32","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-11-01","publicationStatus":"PW","scienceBaseUri":"53cd6240e4b0b290850fe112","contributors":{"authors":[{"text":"Bowerman, Tracy","contributorId":95796,"corporation":false,"usgs":true,"family":"Bowerman","given":"Tracy","email":"","affiliations":[],"preferred":false,"id":466366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra","contributorId":24215,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","affiliations":[{"id":609,"text":"Utah Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":466365,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048307,"text":"70048307 - 2012 - Using geochemistry to identify the source of groundwater to Montezuma Well, a natural spring in Central Arizona, USA: Part 2","interactions":[],"lastModifiedDate":"2013-09-20T09:36:05","indexId":"70048307","displayToPublicDate":"2012-11-01T09:24:44","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1534,"text":"Environmental Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Using geochemistry to identify the source of groundwater to Montezuma Well, a natural spring in Central Arizona, USA: Part 2","docAbstract":"Montezuma Well is a unique natural spring located in a sinkhole surrounded by travertine. Montezuma Well is managed by the National Park Service, and groundwater development in the area is a potential threat to the water source for Montezuma Well. This research was undertaken to better understand the sources of groundwater to Montezuma Well. Strontium isotopes (<sup>87</sup>Sr/<sup>86</sup>Sr) indicate that groundwater in the recharge area has flowed through surficial basalts with subsequent contact with the underlying Permian aged sandstones and the deeper, karstic, Mississippian Redwall Limestone. The distinctive geochemistry in Montezuma Well and nearby Soda Springs (higher concentrations of alkalinity, As, B, Cl, and Li) is coincident with added carbon dioxide and mantle-sourced He. The geochemistry and isotopic data from Montezuma Well and Soda Springs allow for the separation of groundwater samples into four categories: (1) upgradient, (2) deep groundwater with carbon dioxide, (3) shallow Verde Formation, and (4) mixing zone. δ<sup>18</sup>O and δD values, along with noble gas recharge elevation data, indicate that the higher elevation areas to the north and east of Montezuma Well are the groundwater recharge zones for Montezuma Well and most of the groundwater in this portion of the Verde Valley. Adjusted groundwater age dating using likely <sup>14</sup>C and δ<sup>13</sup>C sources indicate an age for Montezuma Well and Soda Springs groundwaters at 5,400–13,300 years, while shallow groundwater in the Verde Formation appears to be older (18,900). Based on water chemistry and isotopic evidence, groundwater flow to Montezuma Well is consistent with a hydrogeologic framework that indicates groundwater flow by (1) recharge in higher elevation basalts to the north and east of Montezuma Well, (2) movement through the upgradient Permian and Mississippian units, especially the Redwall Limestone, and (3) contact with a basalt dike/fracture system that provides a mechanism for groundwater to flow to the surface. While the exact nature of the groundwater flow connections is still uncertain, the available data indicate that flow to Montezuma Well may be more susceptible to future groundwater development in the Redwall Limestone than from any other geologic unit. Overall, the shallow groundwater in the surrounding Verde Formation appears to be largely disconnected from deeper groundwater flowing to Montezuma Well.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Earth Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s12665-012-1844-3","usgsCitation":"Johnson, R.H., DeWitt, E., Wirt, L., Manning, A.H., and Hunt, A.G., 2012, Using geochemistry to identify the source of groundwater to Montezuma Well, a natural spring in Central Arizona, USA: Part 2: Environmental Earth Sciences, v. 67, no. 6, p. 1837-1853, https://doi.org/10.1007/s12665-012-1844-3.","productDescription":"17 p.","startPage":"1837","endPage":"1853","ipdsId":"IP-027796","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":277954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277952,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12665-012-1844-3"}],"country":"United States","state":"Arizona","otherGeospatial":"Montezuma Well","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.83,34.5 ], [ -111.83,34.83 ], [ -111.45,34.83 ], [ -111.45,34.5 ], [ -111.83,34.5 ] ] ] } } ] }","volume":"67","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-08-29","publicationStatus":"PW","scienceBaseUri":"523d6e6ae4b097188d6c771b","contributors":{"authors":[{"text":"Johnson, Raymond H. rhjohnso@usgs.gov","contributorId":707,"corporation":false,"usgs":true,"family":"Johnson","given":"Raymond","email":"rhjohnso@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":484278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeWitt, Ed","contributorId":65081,"corporation":false,"usgs":true,"family":"DeWitt","given":"Ed","affiliations":[],"preferred":false,"id":484282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wirt, Laurie","contributorId":13204,"corporation":false,"usgs":true,"family":"Wirt","given":"Laurie","affiliations":[],"preferred":false,"id":484281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":484279,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":484280,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70189352,"text":"70189352 - 2012 - Difference infiltrometer: a method to measure temporally variable infiltration rates during rainstorms","interactions":[],"lastModifiedDate":"2017-07-11T15:52:36","indexId":"70189352","displayToPublicDate":"2012-11-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Difference infiltrometer: a method to measure temporally variable infiltration rates during rainstorms","docAbstract":"<p><span>We developed a difference infiltrometer to measure time series of non-steady infiltration rates during rainstorms at the point scale. The infiltrometer uses two, tipping bucket rain gages. One gage measures rainfall onto, and the other measures runoff from, a small circular plot about 0.5-m in diameter. The small size allows the infiltration rate to be computed as the difference of the cumulative rainfall and cumulative runoff without having to route water through a large plot. Difference infiltrometers were deployed in an area burned by the 2010 Fourmile Canyon Fire near Boulder, Colorado, USA, and data were collected during the summer of 2011. The difference infiltrometer demonstrated the capability to capture different magnitudes of infiltration rates and temporal variability associated with convective (high intensity, short duration) and cyclonic (low intensity, long duration) rainstorms. Data from the difference infiltrometer were used to estimate saturated hydraulic conductivity of soil affected by the heat from a wildfire. The difference infiltrometer is portable and can be deployed in rugged, steep terrain and does not require the transport of water, as many rainfall simulators require, because it uses natural rainfall. It can be used to assess infiltration models, determine runoff coefficients, identify rainfall depth or rainfall intensity thresholds to initiate runoff, estimate parameters for infiltration models, and compare remediation treatments on disturbed landscapes. The difference infiltrometer can be linked with other types of soil monitoring equipment in long-term studies for detecting temporal and spatial variability at multiple time scales and in nested designs where it can be linked to hillslope and basin-scale runoff responses.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.9424","usgsCitation":"Moody, J.A., and Ebel, B.A., 2012, Difference infiltrometer: a method to measure temporally variable infiltration rates during rainstorms: Hydrological Processes, v. 26, no. 21, p. 3312-3318, https://doi.org/10.1002/hyp.9424.","productDescription":"7 p.","startPage":"3312","endPage":"3318","ipdsId":"IP-034604","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"21","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-07-03","publicationStatus":"PW","scienceBaseUri":"5965bacfe4b0d1f9f05b38d9","contributors":{"authors":[{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704333,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70189182,"text":"70189182 - 2012 - Uncertainty quantification for environmental models","interactions":[],"lastModifiedDate":"2017-07-07T09:52:05","indexId":"70189182","displayToPublicDate":"2012-11-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5454,"text":"SIAM News","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty quantification for environmental models","docAbstract":"Environmental models are used to evaluate the fate of fertilizers in agricultural settings (including soil denitrification), the degradation of hydrocarbons at spill sites, and water supply for people and ecosystems in small to large basins and cities—to mention but a few applications of these models. They also play a role in understanding and diagnosing potential environmental impacts of global climate change. The models are typically mildly to extremely nonlinear. The persistent demand for enhanced dynamics and resolution to improve model realism [17] means that lengthy individual model execution times will remain common, notwithstanding continued enhancements in computer power. In addition, high-dimensional parameter spaces are often defined, which increases the number of model runs required to quantify uncertainty [2]. Some environmental modeling projects have access to extensive funding and computational resources; many do not. The many recent studies of uncertainty quantification in environmental model predictions have focused on uncertainties related to data error and sparsity of data, expert judgment expressed mathematically through prior information, poorly known parameter values, and model structure (see, for example, [1,7,9,10,13,18]). Approaches for quantifying uncertainty include frequentist (potentially with prior information [7,9]), Bayesian [13,18,19], and likelihood-based. A few of the numerous methods, including some sensitivity and inverse methods with consequences for understanding and quantifying uncertainty, are as follows: Bayesian hierarchical modeling and Bayesian model averaging; single-objective optimization with error-based weighting [7] and multi-objective optimization [3]; methods based on local derivatives [2,7,10]; screening methods like OAT (one at a time) and the method of Morris [14]; FAST (Fourier amplitude sensitivity testing) [14]; the Sobol' method [14]; randomized maximum likelihood [10]; Markov chain Monte Carlo (MCMC) [10]. There are also bootstrapping and cross-validation approaches.Sometimes analyses are conducted using surrogate models [12]. The availability of so many options can be confusing. Categorizing methods based on fundamental questions assists in communicating the essential results of uncertainty analyses to stakeholders. Such questions can focus on model adequacy (e.g., How well does the model reproduce observed system characteristics and dynamics?) and sensitivity analysis (e.g., What parameters can be estimated with available data? What observations are important to parameters and predictions? What parameters are important to predictions?), as well as on the uncertainty quantification (e.g., How accurate and precise are the predictions?). The methods can also be classified by the number of model runs required: few (10s to 1000s) or many (10,000s to 1,000,000s). Of the methods listed above, the most computationally frugal are generally those based on local derivatives; MCMC methods tend to be among the most computationally demanding. Surrogate models (emulators)do not necessarily produce computational frugality because many runs of the full model are generally needed to create a meaningful surrogate model. With this categorization, we can, in general, address all the fundamental questions mentioned above using either computationally frugal or demanding methods. Model development and analysis can thus be conducted consistently using either computation-ally frugal or demanding methods; alternatively, different fundamental questions can be addressed using methods that require different levels of effort. Based on this perspective, we pose the question: Can computationally frugal methods be useful companions to computationally demanding meth-ods? The reliability of computationally frugal methods generally depends on the model being reasonably linear, which usually means smooth nonlin-earities and the assumption of Gaussian errors; both tend to be more valid with more linear","language":"English","publisher":"Society for Industrial and Applied Mathematics","usgsCitation":"Hill, M.C., Lu, D., Kavetski, D., Clark, M.P., and Ye, M., 2012, Uncertainty quantification for environmental models: SIAM News, v. 45, no. 9, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-041596","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343432,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://sinews.siam.org/Current-Issue/Issue-Archives/Issue-Archives-ListView/PID/2282/mcat/2279/evl/0/TagID/206?TagName=Volume-45-|-Number-9-|-November-2012"}],"volume":"45","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595f4c45e4b0d1f9f057e372","contributors":{"authors":[{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Dan","contributorId":58176,"corporation":false,"usgs":true,"family":"Lu","given":"Dan","affiliations":[],"preferred":false,"id":703762,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kavetski, Dmitri","contributorId":194182,"corporation":false,"usgs":false,"family":"Kavetski","given":"Dmitri","email":"","affiliations":[],"preferred":false,"id":703389,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Clark, Martyn P.","contributorId":194183,"corporation":false,"usgs":false,"family":"Clark","given":"Martyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":703390,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ye, Ming","contributorId":194184,"corporation":false,"usgs":false,"family":"Ye","given":"Ming","email":"","affiliations":[],"preferred":false,"id":703391,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70192878,"text":"70192878 - 2012 - Regional regression models of watershed suspended-sediment discharge for the eastern United States","interactions":[],"lastModifiedDate":"2017-11-21T15:23:06","indexId":"70192878","displayToPublicDate":"2012-11-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Regional regression models of watershed suspended-sediment discharge for the eastern United States","docAbstract":"<p><span>Estimates of mean annual watershed sediment discharge, derived from long-term measurements of suspended-sediment concentration and streamflow, often are not available at locations of interest. The goal of this study was to develop multivariate regression models to enable prediction of mean annual suspended-sediment discharge from available basin characteristics useful for most ungaged river locations in the eastern United States. The models are based on long-term mean sediment discharge estimates and explanatory variables obtained from a combined dataset of 1201 US Geological Survey (USGS) stations derived from a SPAtially Referenced Regression on Watershed attributes (SPARROW) study and the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES) database. The resulting regional regression models summarized for major US water resources regions 1–8, exhibited prediction&nbsp;</span><i>R</i><sup>2</sup><span><span>&nbsp;</span>values ranging from 76.9% to 92.7% and corresponding average model prediction errors ranging from 56.5% to 124.3%. Results from cross-validation experiments suggest that a majority of the models will perform similarly to calibration runs. The 36-parameter regional regression models also outperformed a 16-parameter national SPARROW model of suspended-sediment discharge and indicate that mean annual sediment loads in the eastern United States generally correlates with a combination of basin area, land use patterns, seasonal precipitation, soil composition, hydrologic modification, and to a lesser extent, topography.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2012.09.011","usgsCitation":"Roman, D.C., Vogel, R.M., and Schwarz, G., 2012, Regional regression models of watershed suspended-sediment discharge for the eastern United States: Journal of Hydrologic Engineering, v. 472-4723, p. 53-62, https://doi.org/10.1016/j.jhydrol.2012.09.011.","productDescription":"10 p.","startPage":"53","endPage":"62","ipdsId":"IP-023743","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":349232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"472-4723","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a610553e4b06e28e9c2553a","contributors":{"authors":[{"text":"Roman, David C.","contributorId":198831,"corporation":false,"usgs":false,"family":"Roman","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":717278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vogel, Richard M.","contributorId":66811,"corporation":false,"usgs":true,"family":"Vogel","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":false,"id":723122,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040657,"text":"pp1789G - 2012 - Effects of earthworms on slopewash, surface runoff, and fine-litter transport on a humid-tropical forested hillslope in eastern Puerto Rico: Chapter G in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>","interactions":[],"lastModifiedDate":"2013-02-01T14:17:12","indexId":"pp1789G","displayToPublicDate":"2012-11-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1789","chapter":"G","title":"Effects of earthworms on slopewash, surface runoff, and fine-litter transport on a humid-tropical forested hillslope in eastern Puerto Rico: Chapter G in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>","docAbstract":"Rainfall, slopewash (the erosion of soil particles), surface runoff, and fine-litter transport were measured in tropical wet forest on a hillslope in the Luquillo Experimental Forest, Puerto Rico, from February 1998 until April 2000. Slopewash data were collected using Gerlach troughs at eight plots, each 2 square meters in area. Earthworms were excluded by electroshocking from four randomly selected plots. The other four (control) plots were undisturbed. During the experiment, earthworm population in the electroshocked plots was reduced by 91 percent. At the end of the experiment, the electroshocked plots had 13 percent of earthworms by count and 6 percent by biomass as compared with the control plots. Rainfall during the sampling period (793 days) was 9,143 millimeters. Mean and maximum rainfall by sampling period (mean of 16 days) were 189 and 563 millimeters, respectively. Surface runoff averaged 0.6 millimeters and 1.2 millimeters by sampling period for the control and experimental plots, equal to 0.25 and 0.48 percent of mean rainfall, respectively. Disturbance of the soil environment by removal of earthworms doubled runoff and increased the transport (erosion) of soil and organic material by a factor of 4.4. When earthworms were removed, the erosion of mineral soil (soil mass left after ashing) and the transport of fine litter were increased by a factor of 5.3 and 3.4, respectively. It is assumed that increased runoff is a function of reduced soil porosity, resulting from decreased burrowing and reworking of the soil in the absence of earthworms. The background, or undisturbed, downslope transport of soil, as determined from the control plots, was 51 kilograms per hectare and the \"disturbance\" rate, determined from the experimental plots, was 261 kilograms per hectare. The background rate for downslope transport of fine litter was 71 kilograms per hectare and the disturbance rate was 246 kilograms per hectare. Data from this study indicate that the reduction in soil macrofauna population, in this case, earthworms, plays a key role in increasing runoff and soil erosion and, therefore, has important implications for forest and water management.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Water quality and landscape processes of four watersheds in eastern Puerto Rico (Professional Paper 1789)","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1789G","collaboration":"This report is Chapter G in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>. For more information, see: <a href=\"http://pubs.er.usgs.gov/publication/pp1789\" target=\"_blank\">Professional Paper 1789</a>.","usgsCitation":"Larsen, M.C., Liu, Z.L., and Zou, X., 2012, Effects of earthworms on slopewash, surface runoff, and fine-litter transport on a humid-tropical forested hillslope in eastern Puerto Rico: Chapter G in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>: U.S. Geological Survey Professional Paper 1789, 20 p., https://doi.org/10.3133/pp1789G.","productDescription":"20 p.","startPage":"179","endPage":"198","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":262995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp_1789_G.jpg"},{"id":262993,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1789/"},{"id":262994,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1789/pdfs/ChapterG.pdf"}],"country":"Puerto Rico","otherGeospatial":"Luquillo Experimental Forest","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -67.9455,17.8814 ], [ -67.9455,18.516 ], [ -65.2211,18.516 ], [ -65.2211,17.8814 ], [ -67.9455,17.8814 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50db391fe4b061270600960e","contributors":{"editors":[{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":509090,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Stallard, Robert F. 0000-0001-8209-7608 stallard@usgs.gov","orcid":"https://orcid.org/0000-0001-8209-7608","contributorId":1924,"corporation":false,"usgs":true,"family":"Stallard","given":"Robert","email":"stallard@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":509091,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Larsen, Matthew C. mclarsen@usgs.gov","contributorId":1568,"corporation":false,"usgs":true,"family":"Larsen","given":"Matthew","email":"mclarsen@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":468736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Zhigang Liu","contributorId":19443,"corporation":false,"usgs":true,"family":"Liu","given":"Zhigang","email":"","middleInitial":"Liu","affiliations":[],"preferred":false,"id":468737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zou, Xiaoming","contributorId":56521,"corporation":false,"usgs":true,"family":"Zou","given":"Xiaoming","email":"","affiliations":[],"preferred":false,"id":468738,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040666,"text":"pp1789D - 2012 - Atmospheric inputs to watersheds of the Luquillo Mountains in eastern Puerto Rico: Chapter D in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>","interactions":[],"lastModifiedDate":"2015-06-01T08:44:21","indexId":"pp1789D","displayToPublicDate":"2012-11-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1789","chapter":"D","title":"Atmospheric inputs to watersheds of the Luquillo Mountains in eastern Puerto Rico: Chapter D in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>","docAbstract":"Twenty years of precipitation-chemistry data from the National Atmospheric Deposition Program site at El Verde, Puerto Rico, demonstrate that three major sources control the composition of solutes in rain in eastern Puerto Rico. In order of importance, these sources are marine salts, temperate contamination from the Northern Hemisphere, and Sahara Desert dust. Marine salts are a source of roughly 82 percent of the ionic charge in precipitation; marine salt inputs are greatest in January. Evaluation of 15 years of U.S. Geological Survey data for four watersheds in eastern Puerto Rico suggests that large storms, including hurricanes, are associated with exceptionally high chloride concentrations in stream waters. Some of these storms were missed in sampling by the National Atmospheric Deposition Program, and therefore its data on the marine contribution likely underestimate chloride. The marine contribution is a weak source of acidity. Temperate contamination contributes about 10 percent of the ionic charge in precipitation; contaminants are primarily nitrate, ammonia, and sulfate derived from various manmade and natural sources. Peak deposition of temperate contaminants is during January, April, and May, months in which strong weather fronts arrive from the north. Temperate contamination, a strong source of acidity, is the only component that is increasing through time. Sahara Desert dust provides 5 percent of the ionic charge in precipitation; it is strongly seasonal, peaking in June and July during times of maximum dust transport from the Sahara and sub-Saharan regions. This dust contributes, on average, enough alkalinity to neutralize the acidity in June and July rains.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Water quality and landscape processes of four watersheds in eastern Puerto Rico (Professional Paper 1789)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1789D","collaboration":"This report is Chapter D in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>.  For more information, see: <a href=\"http://pubs.er.usgs.gov/publication/pp1789\" target=\"_blank\">Professional Paper 1789</a>.","usgsCitation":"Stallard, R.F., 2012, Atmospheric inputs to watersheds of the Luquillo Mountains in eastern Puerto Rico: Chapter D in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>: U.S. Geological Survey Professional Paper 1789, 28 p., https://doi.org/10.3133/pp1789D.","productDescription":"28 p.","startPage":"85","endPage":"112","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":263010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp_1789_D.jpg"},{"id":263008,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1789/"},{"id":263009,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1789/pdfs/ChapterD.pdf"}],"country":"Puerto Rico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -67.9455,17.8814 ], [ -67.9455,18.516 ], [ -65.2211,18.516 ], [ -65.2211,17.8814 ], [ -67.9455,17.8814 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d85caae4b0064e695a14d6","contributors":{"editors":[{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":509096,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Stallard, Robert F. 0000-0001-8209-7608 stallard@usgs.gov","orcid":"https://orcid.org/0000-0001-8209-7608","contributorId":1924,"corporation":false,"usgs":true,"family":"Stallard","given":"Robert","email":"stallard@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":509097,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Stallard, Robert F. 0000-0001-8209-7608 stallard@usgs.gov","orcid":"https://orcid.org/0000-0001-8209-7608","contributorId":1924,"corporation":false,"usgs":true,"family":"Stallard","given":"Robert","email":"stallard@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":468743,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040658,"text":"pp1789F - 2012 - Landslides and sediment budgets in four watersheds in eastern Puerto Rico: Chapter F in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>","interactions":[],"lastModifiedDate":"2013-02-01T14:18:05","indexId":"pp1789F","displayToPublicDate":"2012-11-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1789","chapter":"F","title":"Landslides and sediment budgets in four watersheds in eastern Puerto Rico: Chapter F in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>","docAbstract":"The low-latitude regions of the Earth are undergoing profound, rapid landscape change as forests are converted to agriculture to support growing population. Understanding the effects of these land-use changes requires analysis of watershed-scale geomorphic processes to better inform and manage this usually disorganized process. The investigation of hillslope erosion and the development of sediment budgets provides essential information for resource managers. Four small, montane, humid-tropical watersheds in the Luquillo Experimental Forest and nearby R&iacute;o Grande de Lo&iacute;za watershed, Puerto Rico (18&deg; 20' N., 65&deg; 45' W.), were selected to compare and contrast the geomorphic effects of land use and bedrock geology. Two of the watersheds are underlain largely by resistant Cretaceous volcaniclastic rocks but differ in land use and mean annual runoff: the Mameyes watershed, with predominantly primary forest cover and runoff of 2,750 millimeters per year, and the Can&oacute;vanas watershed, with mixed secondary forest and pasture and runoff of 970 millimeters per year. The additional two watersheds are underlain by relatively erodible granitic bedrock: the forested Icacos watershed, with runoff of 3,760 millimeters per year and the agriculturally developed Cayagu&aacute;s watershed, with a mean annual runoff of 1,620 millimeters per year. Annual sediment budgets were estimated for each watershed using landslide, slopewash, soil creep, treethrow, suspended sediment, and streamflow data. The budgets also included estimates of sediment storage in channel beds, bars, floodplains, and in colluvial deposits. In the two watersheds underlain by volcaniclastic rocks, the forested Mameyes and the developed Can&oacute;vanas watersheds, landslide frequency (0.21 and 0.04 landslides per square kilometer per year, respectively), slopewash (5 and 30 metric tons per square kilometer per year), and suspended sediment yield (325 and 424 metric tons per square kilometer per year), were lower than in the two watersheds underlain by granitic bedrock. In these granitic watersheds, landslide frequency, slopewash, and suspended sediment yield were 0.43 landslides per square kilometer per year, 20 metric tons per square kilometer per year, and 2,140 metric tons per square kilometer per year, respectively, in the forested Icacos watershed and 0.8 landslides per square kilometer per year, 105 metric tons per square kilometer per year, and 2,110 metric tons per square kilometer per year, respectively, in the agriculturally developed Cayagu&aacute;s watershed. Comparison of sediment budgets from the forested and developed watersheds indicates that human activities increase landslide frequency by as much as factor of 5 and slopewash by as much as a factor of 6. When the difference in annual runoff is considered, the effect of land use on suspended sediment yields is also notable. Sediment concentration, calculated as sediment yield normalized by runoff, was about 2.3 to 3.7 times as great in the two watersheds in secondary forest and pasture compared with sediment concentration in the watersheds in primary forest. Even in the two watersheds with primary forest cover, the Mameyes and Icacos, located in the Luquillo Experimental Forest, the effects of anthropogenic disturbance were marked: 43 to 63 percent of landslide-related erosion was associated with road construction and maintenance.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Water quality and landscape processes of four watersheds in eastern Puerto Rico (Professional Paper 1789)","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1789F","collaboration":"This report is Chapter F in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>. For more information, see: <a href=\"http://pubs.er.usgs.gov/publication/pp1789\" target=\"_blank\">Professional Paper 1789</a>.","usgsCitation":"Larsen, M.C., 2012, Landslides and sediment budgets in four watersheds in eastern Puerto Rico: Chapter F in <i>Water quality and landscape processes of four watersheds in eastern Puerto Rico</i>: U.S. Geological Survey Professional Paper 1789, 26 p., https://doi.org/10.3133/pp1789F.","productDescription":"26 p.","startPage":"153","endPage":"178","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":262998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp_1789_F.jpg"},{"id":262997,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1789/"},{"id":262996,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1789/pdfs/ChapterF.pdf"}],"country":"Puerto Rico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -67.9455,17.8814 ], [ -67.9455,18.516 ], [ -65.2211,18.516 ], [ -65.2211,17.8814 ], [ -67.9455,17.8814 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50df70b0e4b0dfbe79e6c651","contributors":{"editors":[{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":509092,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Stallard, Robert F. 0000-0001-8209-7608 stallard@usgs.gov","orcid":"https://orcid.org/0000-0001-8209-7608","contributorId":1924,"corporation":false,"usgs":true,"family":"Stallard","given":"Robert","email":"stallard@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":509093,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Larsen, Matthew C. mclarsen@usgs.gov","contributorId":1568,"corporation":false,"usgs":true,"family":"Larsen","given":"Matthew","email":"mclarsen@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":468739,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70154996,"text":"70154996 - 2012 - Externally triggered renewed bubble nucleation in basaltic magma: the 12 October 2008 eruption at Halema‘uma‘u Overlook vent, Kīlauea, Hawai‘i, USA","interactions":[],"lastModifiedDate":"2019-05-30T10:12:32","indexId":"70154996","displayToPublicDate":"2012-11-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Externally triggered renewed bubble nucleation in basaltic magma: the 12 October 2008 eruption at Halema‘uma‘u Overlook vent, Kīlauea, Hawai‘i, USA","docAbstract":"<p><span>From October 2008 until present, dozens of small impulsive explosive eruptions occurred from the Overlook vent on the southeast side of Halema&lsquo;uma&lsquo;u Crater, at Kīlauea volcano, USA. These eruptions were triggered by rockfalls from the walls of the volcanic vent and conduit onto the top of the lava column. Here we use microtextural observations and data from clasts erupted during the well-characterized 12 October 2008 explosive eruption at Halema&lsquo;uma&lsquo;u to extend existing models of eruption triggering. We present a potential mechanism for this eruption by combining microtextural observations with existing geophysical and visual data sets. We measure the size and number density of bubbles preserved in juvenile ejecta using 2D images and X-ray microtomography. Our data suggest that accumulations of large bubbles with diameters of &gt;50</span><i>&mu;</i><span>m to at least millimeters existed at shallow levels within the conduit prior to the 12 October 2008 explosion. Furthermore, a high number density of small bubbles &lt;50&nbsp;</span><i>&mu;</i><span>m is measured in the clasts, implying very rapid nucleation of bubbles. Visual observations, combined with preexisting geophysical data, suggest that the impact of rockfalls onto the magma free surface induces pressure changes over short timescales that (1) nucleated new additional bubbles in the shallow conduit leading to high number densities of small bubbles and (2) expanded the preexisting bubbles driving upward acceleration. The trigger of eruption and bubble nucleation is thus external to the degassing system.</span></p>","language":"English","doi":"10.1029/2012JB009496","usgsCitation":"Carey, R.J., Manga, M., Degruyter, W., Swanson, D., Houghton, B.F., Orr, T., and Patrick, M.R., 2012, Externally triggered renewed bubble nucleation in basaltic magma: the 12 October 2008 eruption at Halema‘uma‘u Overlook vent, Kīlauea, Hawai‘i, USA: Journal of Geophysical Research B: Solid Earth, v. 117, no. B11, e11202: 10 p., https://doi.org/10.1029/2012JB009496.","productDescription":"e11202: 10 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066884","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":474286,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2012jb009496","text":"Publisher Index Page"},{"id":306446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Overlook vent, Halema'uma'u crater, Kilauea volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.28050422668457,\n   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Tasmania","active":true,"usgs":false}],"preferred":false,"id":564513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manga, Michael","contributorId":145531,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":564514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Degruyter, Wim","contributorId":145532,"corporation":false,"usgs":false,"family":"Degruyter","given":"Wim","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":564515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swanson, Donald donswan@usgs.gov","contributorId":140000,"corporation":false,"usgs":true,"family":"Swanson","given":"Donald","email":"donswan@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":564516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false},{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":564517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orr, Tim R. torr@usgs.gov","contributorId":140376,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","email":"torr@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":564512,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":564518,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70041584,"text":"70041584 - 2012 - Developing accurate survey methods for estimating population sizes and trends of the critically endangered Nihoa Millerbird and Nihoa Finch.","interactions":[],"lastModifiedDate":"2018-01-05T12:39:22","indexId":"70041584","displayToPublicDate":"2012-10-31T02:30:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-034","title":"Developing accurate survey methods for estimating population sizes and trends of the critically endangered Nihoa Millerbird and Nihoa Finch.","docAbstract":"<p>This report describes the results of a comparative study of bird survey methods undertaken for the purpose of improving assessments of the conservation status for the two endemic passerines on the Island of Nihoa&mdash;Nihoa Millerbird (Sylviidae: <i>Acrocephalus familiaris kingi</i>) and Nihoa Finch (Fringilidae: <i>Telespiza ultima</i>; also referred herein as millerbird and finch)&mdash;both listed as endangered under the Federal Endangered Species Act (ESA) and Hawai`i Revised Statutes 195D. The current survey protocol, implemented since 1967, has produced a highly variable range of counts for both the millerbird and finch, making difficult assessments of population size and trend. This report details the analyses of bird survey data collected in 2010 and 2011 in which three survey methods were compared―strip-transect, line-transect, and point-transect sampling―and provides recommendations for improved survey methods and protocols. Funding for this research was provided through a Science Support Partnership grant sponsored jointly by the U.S. Geological Survey (USGS) and the U.S. Fish and Wildlife Service (USFWS).</p>\n<p>Point-transect surveys indicated that millerbirds were more abundant than shown by the striptransect method, and were estimated at 802 birds in 2010 (95%CI = 652 &ndash; 964) and 704 birds in 2011 (95%CI = 579 &ndash; 837). Point-transect surveys yielded population estimates with improved precision which will permit trends to be detected in shorter time periods and with greater statistical power than is available from strip-transect survey methods. Mean finch population estimates and associated uncertainty were not markedly different among the three survey methods, but the performance of models used to estimate density and population size are expected to improve as the data from additional surveys are incorporated. Using the pointtransect survey, the mean finch population size was estimated at 2,917 birds in 2010 (95%CI = 2,037 &ndash; 3,965) and 2,461 birds in 2011 (95%CI = 1,682 &ndash; 3,348). Preliminary testing of the line-transect method in 2011 showed that it would not generate sufficient detections to effectively model bird density, and consequently, relatively precise population size estimates. Both species were fairly evenly distributed across Nihoa and appear to occur in all or nearly all available habitat. The time expended and area traversed by observers was similar among survey methods; however, point-transect surveys do not require that observers walk a straight transect line, thereby allowing them to avoid culturally or biologically sensitive areas and minimize the adverse effects of recurrent travel to any particular area. In general, pointtransect surveys detect more birds than strip-survey methods, thereby improving precision and resulting population size and trend estimation. The method is also better suited for the steep and uneven terrain of Nihoa</p>","language":"English","publisher":"UniverIsity of Hawaii at Hilio","publisherLocation":"Hilo, HI","usgsCitation":"Gorresen, P.M., Camp, R.J., Brinck, K., and Farmer, C., 2012, Developing accurate survey methods for estimating population sizes and trends of the critically endangered Nihoa Millerbird and Nihoa Finch.: Technical Report HCSU-034, v, 70 p.","productDescription":"v, 70 p.","numberOfPages":"77","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041045","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad43e4b05e859bdfb8c4","contributors":{"authors":[{"text":"Gorresen, P. Marcos mgorresen@usgs.gov","contributorId":3975,"corporation":false,"usgs":true,"family":"Gorresen","given":"P.","email":"mgorresen@usgs.gov","middleInitial":"Marcos","affiliations":[],"preferred":false,"id":644962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":116175,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":false,"id":644963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":644964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farmer, Chris cfarmer@usgs.gov","contributorId":3681,"corporation":false,"usgs":true,"family":"Farmer","given":"Chris","email":"cfarmer@usgs.gov","affiliations":[],"preferred":true,"id":644965,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040572,"text":"70040572 - 2012 - The hydrology of a drained topographical depression within an agricutlural field in north-central Iowa","interactions":[],"lastModifiedDate":"2021-01-05T18:53:14.329024","indexId":"70040572","displayToPublicDate":"2012-10-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3627,"text":"Transactions of the American Society of Agricultural and Biological Engineers","active":true,"publicationSubtype":{"id":10}},"title":"The hydrology of a drained topographical depression within an agricutlural field in north-central Iowa","docAbstract":"North-central Iowa is an agriculturally intensive area comprising the southeastern portion of the Prairie Pothole Region, a landscape containing a high density of enclosed topographical depressions. Artificial drainage practices have been implemented throughout the area to facilitate agricultural production. Vertical surface drains are utilized to drain the topographical depressions that accumulate water. This study focuses on the hydrology of a drained topographical depression located in a 39.5 ha agricultural field. To assess the hydrology of the drained depression, a water balance was constructed for 11 ponding events during the 2008 growing season. Continuous pond and groundwater level data were obtained with pressure transducers. Flows into the vertical surface drain were calculated based on pond depth. Precipitation inflows and evaporative outflows of the ponds were calculated using climatic data. Groundwater levels were used to assess groundwater/pond interactions. Results of the water balances show distinct differences between the inflows to and outflows from the depression based on antecedent conditions. In wet conditions, groundwater inflow sustained the ponds. The ponds receded only after the groundwater level declined to below the land surface. In drier conditions, groundwater was not a source of water to the depression. During these drier conditions, infiltration comprised 30% of the outflows from the depression during declining pond stages. Over the entire study period, the surface drain, delivering water to the stream, was the largest outflow from the pond, accounting for 97% of the outflow, while evapotranspiration was just 2%. Precipitation onto the pond surface proved to be a minor component, accounting for 4% of the total inflows.","language":"English","publisher":"American Society of Agricultural and Biological Engineers","doi":"10.13031/2013.42367","usgsCitation":"Roth, J.L., and Capel, P.D., 2012, The hydrology of a drained topographical depression within an agricutlural field in north-central Iowa: Transactions of the American Society of Agricultural and Biological Engineers, v. 55, no. 5, p. 1801-1814, https://doi.org/10.13031/2013.42367.","productDescription":"15 p.","startPage":"1801","endPage":"1814","ipdsId":"IP-034171","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":381889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.6395,40.3754 ], [ -96.6395,43.5012 ], [ -90.1401,43.5012 ], [ -90.1401,40.3754 ], [ -96.6395,40.3754 ] ] ] } } ] }","volume":"55","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e507d0e4b0e8fec6cea015","contributors":{"authors":[{"text":"Roth, Jason L. 0000-0001-5440-2775 jroth@usgs.gov","orcid":"https://orcid.org/0000-0001-5440-2775","contributorId":4789,"corporation":false,"usgs":true,"family":"Roth","given":"Jason","email":"jroth@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":468569,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040555,"text":"70040555 - 2012 - Predicting biological condition in southern California streams","interactions":[],"lastModifiedDate":"2012-11-01T14:54:04","indexId":"70040555","displayToPublicDate":"2012-10-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2603,"text":"Landscape and Urban Planning","active":true,"publicationSubtype":{"id":10}},"title":"Predicting biological condition in southern California streams","docAbstract":"As understanding of the complex relations among environmental stressors and biological responses improves, a logical next step is predictive modeling of biological condition at unsampled sites. We developed a boosted regression tree (BRT) model of biological condition, as measured by a benthic macroinvertebrate index of biotic integrity (BIBI), for streams in urbanized Southern Coastal California. We also developed a multiple linear regression (MLR) model as a benchmark for comparison with the BRT model. The BRT model explained 66% of the variance in B-IBI, identifying watershed population density and combined percentage agricultural and urban land cover in the riparian buffer as the most important predictors of B-IBI, but with watershed mean precipitation and watershed density of manmade channels also important. The MLR model explained 48% of the variance in B-IBI and included watershed population density and combined percentage agricultural and urban land cover in the riparian buffer. For a verification data set, the BRT model correctly classified 75% of impaired sites (B-IBI < 40) and 78% of unimpaired sites (B-IBI = 40). For the same verification data set, the MLR model correctly classified 69% of impaired sites and 87% of unimpaired sites. The BRT model should not be used to predict B-IBI for specific sites; however, the model can be useful for general applications such as identifying and prioritizing regions for monitoring, remediation or preservation, stratifying new bioassessments according to anticipated biological condition, or assessing the potential for change in stream biological condition based on anticipated changes in population density and development in stream buffers.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landscape and Urban Planning","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.landurbplan.2012.07.009","usgsCitation":"Brown, L.R., May, J., Rehn, A.C., Ode, P.R., Waite, I.R., and Kennen, J., 2012, Predicting biological condition in southern California streams: Landscape and Urban Planning, v. 108, no. 1, p. 17-27, https://doi.org/10.1016/j.landurbplan.2012.07.009.","productDescription":"11 p.","startPage":"17","endPage":"27","numberOfPages":"11","ipdsId":"IP-022005","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":262887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262886,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.landurbplan.2012.07.009"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.0 ], [ -114.13,42.0 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","volume":"108","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e17e8fe4b0ff1e7c578675","contributors":{"authors":[{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"May, Jason T. 0000-0002-5699-2112","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":14791,"corporation":false,"usgs":true,"family":"May","given":"Jason T.","affiliations":[],"preferred":false,"id":468504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rehn, Andrew C.","contributorId":47650,"corporation":false,"usgs":true,"family":"Rehn","given":"Andrew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":468506,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ode, Peter R.","contributorId":45968,"corporation":false,"usgs":true,"family":"Ode","given":"Peter","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":468505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468502,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468501,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70040531,"text":"ds730 - 2012 - Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2011","interactions":[],"lastModifiedDate":"2019-05-30T12:04:39","indexId":"ds730","displayToPublicDate":"2012-10-30T00:00:00","publicationYear":"2012","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":"730","title":"Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2011","docAbstract":"<p>Between January 1 and December 31, 2011, the Alaska Volcano Observatory (AVO) located 4,364 earthquakes, of which 3,651 occurred within 20 kilometers of the 33 volcanoes with seismograph subnetworks. There was no significant seismic activity above background levels in 2011 at these instrumented volcanic centers. This catalog includes locations, magnitudes, and statistics of the earthquakes located in 2011 with the station parameters, velocity models, and other files used to locate these earthquakes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds730","usgsCitation":"Dixon, J.P., Stihler, S.D., Power, J.A., and Searcy, C.K., 2012, Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2011: U.S. Geological Survey Data Series 730, Report: iv; 82 p.; Zip file, https://doi.org/10.3133/ds730.","productDescription":"Report: iv; 82 p.; Zip file","numberOfPages":"90","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":121,"text":"Alaska Volcano Observatory","active":false,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":262861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_730.jpg"},{"id":262855,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/730/","linkFileType":{"id":5,"text":"html"}},{"id":262857,"rank":1000,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/730/2011_AVO_Seismic_Catalog.zip","text":"Seismic Catalog","size":"14 MB","linkFileType":{"id":6,"text":"zip"},"description":"Seismic Catalog"},{"id":262856,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/730/pdf/ds730.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"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              -181.82373046875,\n              50.86491125522503\n            ],\n            [\n              -182.120361328125,\n              52.09975692575725\n            ],\n            [\n              -170.33203125,\n              61.33353967329142\n            ],\n            [\n              -153.45703125,\n              65.47650756256367\n            ],\n            [\n              -141.15234374999997,\n              66.26685631430843\n            ],\n            [\n              -141.15234374999997,\n              59.88893689676585\n            ],\n            [\n              -153.8525390625,\n              53.69670647530323\n            ],\n            [\n              -181.82373046875,\n              50.86491125522503\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5090e8dae4b0e1c52f42b7df","contributors":{"authors":[{"text":"Dixon, James P. 0000-0002-8478-9971 jpdixon@usgs.gov","orcid":"https://orcid.org/0000-0002-8478-9971","contributorId":3163,"corporation":false,"usgs":true,"family":"Dixon","given":"James","email":"jpdixon@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":468498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stihler, Scott D.","contributorId":31373,"corporation":false,"usgs":true,"family":"Stihler","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":468499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Power, John A. 0000-0002-7233-4398 jpower@usgs.gov","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":2768,"corporation":false,"usgs":true,"family":"Power","given":"John","email":"jpower@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":468497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Searcy, Cheryl K.","contributorId":107013,"corporation":false,"usgs":true,"family":"Searcy","given":"Cheryl","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":468500,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040506,"text":"sir20125211 - 2012 - Investigation of land subsidence in the Houston-Galveston region of Texas by using the Global Positioning System and interferometric synthetic aperture radar, 1993-2000","interactions":[],"lastModifiedDate":"2016-08-05T16:28:10","indexId":"sir20125211","displayToPublicDate":"2012-10-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5211","title":"Investigation of land subsidence in the Houston-Galveston region of Texas by using the Global Positioning System and interferometric synthetic aperture radar, 1993-2000","docAbstract":"<p>Since the early 1900s, groundwater has been the primary source of municipal, industrial, and agricultural water supplies for the Houston-Galveston region, Texas. The region's combination of hydrogeology and nearly century-long use of groundwater has resulted in one of the largest areas of subsidence in the United States; by 1979, as much as 3 meters (m) of subsidence had occurred, and approximately 8,300 square kilometers of land had subsided more than 0.3 m. The U.S. Geological Survey, in cooperation with the Harris-Galveston Subsidence District, used interferometric synthetic aperture radar (InSAR) data obtained for four overlapping scenes from European remote sensing satellites ERS-1 and ERS-2 to analyze land subsidence in the Houston-Galveston region of Texas. The InSAR data were processed into 27 interferograms that delineate and quantify land-subsidence patterns and magnitudes. Contemporaneous data from the Global Positioning System (GPS) were reprocessed by the National Geodetic Survey and analyzed to support, verify, and provide temporal resolution to the InSAR investigation.</p>\n<p>The interferograms show that the area of historical subsidence in downtown Houston along the Houston Ship Channel has stabilized and that recent subsidence occurs farther west and north of Galveston Bay. Three areas of recent subsidence were delineated along a broad arcuate (bowshaped) feature from Spring, Tex., southwest to Cypress, Tex., and south to Sugar Land, Tex., with subsidence rates ranging from 15 millimeters per year (mm/yr) to greater than 60 mm/yr. Multiyear interferograms near Seabrook, Tex., within the historical subsidence area and nearby Galveston Bay, show several fringes of subsidence (approximately 85 millimeters from January 1996 to December 1997) in the area; however it is difficult to determine the subsidence magnitude near Seabrook because many of the InSAR fringes were truncated or ill-defined. Horizontal and vertical GPS data throughout the area support the InSAR measured subsidence rates and extent. The subsidence rates for a few GPS stations northwest of Houston began to decrease in 2007, which may indicate that subsidence may be decreasing in these areas.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125211","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District","usgsCitation":"Bawden, G.W., Johnson, M., Kasmarek, M.C., Brandt, J.T., and Middleton, C.S., 2012, Investigation of land subsidence in the Houston-Galveston region of Texas by using the Global Positioning System and interferometric synthetic aperture radar, 1993-2000: U.S. Geological Survey Scientific Investigations Report 2012-5211, v, 88 p., https://doi.org/10.3133/sir20125211.","productDescription":"v, 88 p.","numberOfPages":"98","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":262833,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5211.gif"},{"id":262830,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5211/","linkFileType":{"id":5,"text":"html"}},{"id":262831,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5211/pdf/sir2012-5211.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Texas","city":"Galveston, Houston","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"508eb5e2e4b0b59cf7f5a7e2","contributors":{"authors":[{"text":"Bawden, Gerald W. gbawden@usgs.gov","contributorId":1071,"corporation":false,"usgs":true,"family":"Bawden","given":"Gerald","email":"gbawden@usgs.gov","middleInitial":"W.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Michaela R. 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":1013,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela R.","email":"mrjohns@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kasmarek, Mark C. 0000-0003-2808-2506 mckasmar@usgs.gov","orcid":"https://orcid.org/0000-0003-2808-2506","contributorId":1968,"corporation":false,"usgs":true,"family":"Kasmarek","given":"Mark","email":"mckasmar@usgs.gov","middleInitial":"C.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brandt, Justin T. 0000-0002-9397-6824 jbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":157,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"jbrandt@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":468484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Middleton, Clifton S.","contributorId":62457,"corporation":false,"usgs":true,"family":"Middleton","given":"Clifton","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":468488,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70040504,"text":"70040504 - 2012 - A basin-scale approach for assessing water resources in a semiarid environment: San Diego region, California and Mexico","interactions":[],"lastModifiedDate":"2017-09-20T13:31:51","indexId":"70040504","displayToPublicDate":"2012-10-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A basin-scale approach for assessing water resources in a semiarid environment: San Diego region, California and Mexico","docAbstract":"<p><span>Many basins throughout the world have sparse hydrologic and geologic data, but have increasing demands for water and a commensurate need for integrated understanding of surface and groundwater resources. This paper demonstrates a methodology for using a distributed parameter water-balance model, gaged surface-water flow, and a reconnaissance-level groundwater flow model to develop a first-order water balance. Flow amounts are rounded to the nearest 5 million cubic meters per year. </span><br><br><span>The San Diego River basin is 1 of 5 major drainage basins that drain to the San Diego coastal plain, the source of public water supply for the San Diego area. The distributed parameter water-balance model (Basin Characterization Model) was run at a monthly timestep for 1940–2009 to determine a median annual total water inflow of 120 million cubic meters per year for the San Diego region. The model was also run specifically for the San Diego River basin for 1982–2009 to provide constraints to model calibration and to evaluate the proportion of inflow that becomes groundwater discharge, resulting in a median annual total water inflow of 50 million cubic meters per year. On the basis of flow records for the San Diego River at Fashion Valley (US Geological Survey gaging station 11023000), when corrected for upper basin reservoir storage and imported water, the total is 30 million cubic meters per year. The difference between these two flow quantities defines the annual groundwater outflow from the San Diego River basin at 20 million cubic meters per year. These three flow components constitute a first-order water budget estimate for the San Diego River basin. The ratio of surface-water outflow and groundwater outflow to total water inflow are 0.6 and 0.4, respectively. Using total water inflow determined using the Basin Characterization Model for the entire San Diego region and the 0.4 partitioning factor, groundwater outflow from the San Diego region, through the coastal plain aquifer to the Pacific Ocean, is calculated to be approximately 50 million cubic meters per year. </span><br><br><span>The area-scale assessment of water resources highlights several hydrologic features of the San Diego region. Groundwater recharge is episodic; the Basin Characterization Model output shows that 90 percent of simulated recharge occurred during 3 percent of the 1982–2009 period. The groundwater aquifer may also be quite permeable. A reconnaissance-level groundwater flow model for the San Diego River basin was used to check the water budget estimates, and the basic interaction of the surface-water and groundwater system, and the flow values, were found to be reasonable. Horizontal hydraulic conductivity values of the volcanic and metavolcanic bedrock in San Diego region range from 1 to 10 m per day. Overall, results establish an initial hydrologic assessment formulated on the basis of sparse hydrologic data. The described flow variability, extrapolation, and unique characteristics represent a realistic view of current (2012) hydrologic understanding for the San Diego region.</span></p>","language":"English","publisher":"European Geosciences Union","publisherLocation":"Munich, Germany","doi":"10.5194/hess-16-3817-2012","usgsCitation":"Flint, L.E., Flint, A.L., Stolp, B., and Danskin, W., 2012, A basin-scale approach for assessing water resources in a semiarid environment: San Diego region, California and Mexico: Hydrology and Earth System Sciences, v. 16, no. 10, p. 3817-3833, https://doi.org/10.5194/hess-16-3817-2012.","productDescription":"17 p.","startPage":"3817","endPage":"3833","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":474288,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-16-3817-2012","text":"Publisher Index Page"},{"id":262836,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Mexico","state":"California","otherGeospatial":"Otay River, San Diego River, San Dieguito River, Sweetwater River, Tijuana River ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.08154296875001,\n              32.616243412727385\n            ],\n            [\n              -115.84533691406249,\n              32.46806060917602\n            ],\n            [\n              -115.87280273437499,\n              32.24532861404601\n            ],\n            [\n              -115.77392578125,\n              31.93817848559113\n            ],\n            [\n              -115.68603515624999,\n              31.41460027631321\n            ],\n            [\n              -116.16943359374999,\n              31.541089879585808\n            ],\n            [\n              -116.510009765625,\n              31.924192605327708\n            ],\n            [\n              -116.74621582031249,\n              32.06861069132688\n            ],\n            [\n              -116.971435546875,\n              32.491230287947594\n            ],\n            [\n              -117.11975097656249,\n              32.616243412727385\n            ],\n            [\n              -117.2515869140625,\n              32.685619853722\n            ],\n            [\n              -117.26806640625,\n              32.91187391621322\n            ],\n            [\n              -117.3065185546875,\n              33.119150226768866\n            ],\n            [\n              -116.70227050781249,\n              33.33970700424026\n            ],\n            [\n              -116.2738037109375,\n              32.90726224488304\n            ],\n            [\n              -116.08154296875001,\n              32.616243412727385\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"10","noUsgsAuthors":false,"publicationDate":"2012-10-26","publicationStatus":"PW","scienceBaseUri":"508f9760e4b0a1b43c29ca03","contributors":{"authors":[{"text":"Flint, L. E. 0000-0002-7868-441X","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":38180,"corporation":false,"usgs":true,"family":"Flint","given":"L.","middleInitial":"E.","affiliations":[],"preferred":false,"id":468481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, A. L.","contributorId":102453,"corporation":false,"usgs":true,"family":"Flint","given":"A.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":468483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stolp, Bernard J. 0000-0003-3803-1497","orcid":"https://orcid.org/0000-0003-3803-1497","contributorId":71942,"corporation":false,"usgs":true,"family":"Stolp","given":"Bernard J.","affiliations":[],"preferred":false,"id":468482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danskin, W.R. 0000-0001-8672-5501","orcid":"https://orcid.org/0000-0001-8672-5501","contributorId":22713,"corporation":false,"usgs":true,"family":"Danskin","given":"W.R.","affiliations":[],"preferred":false,"id":468480,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040509,"text":"ofr20121204 - 2012 - Landslides in Colorado, USA--Impacts and loss estimation for 2010","interactions":[],"lastModifiedDate":"2012-11-05T11:04:12","indexId":"ofr20121204","displayToPublicDate":"2012-10-29T00:00:00","publicationYear":"2012","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":"2012-1204","title":"Landslides in Colorado, USA--Impacts and loss estimation for 2010","docAbstract":"The focus of this study is to investigate landslides and consequent losses which affected Colorado in the year 2010. By obtaining landslide reports from a variety of sources, this report will demonstrate the feasibility of creating a profile of landslides and their effects on communities. A short overview of the current status of landslide-loss studies for the United States is introduced, followed by a compilation of landslide occurrence and associated losses and impacts which affected Colorado for the year 2010. Direct costs are summarized in descriptive and tabular form, and where possible, indirect costs are also noted or estimated. Total direct costs of landslides in Colorado for the year 2010 were approximately $9,149,335.00 (2010 U.S. dollars). (Since not all data for damages and costs were obtained, this figure realistically could be considerably higher.) Indirect costs were noted where available but are not totaled due to the fact that most indirect costs were not obtainable for various reasons outlined later in this report. Casualty data are considered as being within the scope of loss evaluation, and are reported in Appendix 1, but are not assigned dollar losses. More details on the source material for loss data not found in the reference section are reported in Appendix 2, and Appendix 3 summarizes notes on landslide-loss investigations in general and lessons learned during the process of loss-data collection.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121204","usgsCitation":"Highland, L.M., 2012, Landslides in Colorado, USA--Impacts and loss estimation for 2010: U.S. Geological Survey Open-File Report 2012-1204, v, 49 p.; maps (col.), https://doi.org/10.3133/ofr20121204.","productDescription":"v, 49 p.; maps (col.)","startPage":"i","endPage":"49","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":262832,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1204.gif"},{"id":262828,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1204/","linkFileType":{"id":5,"text":"html"}},{"id":262829,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1204/OF12-1204.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Colorado","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"508eb5efe4b0b59cf7f5a7e6","contributors":{"authors":[{"text":"Highland, Lynn M. highland@usgs.gov","contributorId":1292,"corporation":false,"usgs":true,"family":"Highland","given":"Lynn","email":"highland@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":468491,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040502,"text":"70040502 - 2012 - Compartment-based hydrodynamics and water quality modeling of a northern Everglades wetland, Florida, USA","interactions":[],"lastModifiedDate":"2013-01-17T21:25:45","indexId":"70040502","displayToPublicDate":"2012-10-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Compartment-based hydrodynamics and water quality modeling of a northern Everglades wetland, Florida, USA","docAbstract":"The last remaining large remnant of softwater wetlands in the US Florida Everglades lies within the Arthur R. Marshall Loxahatchee National Wildlife Refuge. However, Refuge water quality today is impacted by pumped stormwater inflows to the eutrophic and mineral-enriched 100-km canal, which circumscribes the wetland. Optimal management is a challenge and requires scientifically based predictive tools to assess and forecast the impacts of water management on Refuge water quality. In this research, we developed a compartment-based numerical model of hydrodynamics and water quality for the Refuge. Using the numerical model, we examined the dynamics in stage, water depth, discharge from hydraulic structures along the canal, and exchange flow among canal and marsh compartments. We also investigated the transport of chloride, sulfate and total phosphorus from the canal to the marsh interior driven by hydraulic gradients as well as biological removal of sulfate and total phosphorus. The model was calibrated and validated using long-term stage and water quality data (1995-2007). Statistical analysis indicates that the model is capable of capturing the spatial (from canal to interior marsh) gradients of constituents across the Refuge. Simulations demonstrate that flow from the eutrophic and mineral-enriched canal impacts chloride and sulfate in the interior marsh. In contrast, total phosphorus in the interior marsh shows low sensitivity to intrusion and dispersive transport. We conducted a rainfall-driven scenario test in which the pumped inflow concentrations of chloride, sulfate and total phosphorus were equal to rainfall concentrations (wet deposition). This test shows that pumped inflow is the dominant factor responsible for the substantially increased chloride and sulfate concentrations in the interior marsh. Therefore, the present day Refuge should not be classified as solely a rainfall-driven or ombrotrophic wetland. The model provides an effective screening tool for studying the impacts of various water management alternatives on water quality across the Refuge, and demonstrates the practicality of similarly modeling other wetland systems. As a general rule, modeling provides one component of a multi-faceted effort to provide technical support for ecosystem management decisions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Modelling","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ecolmodel.2012.09.007","usgsCitation":"Wang, H., Meselhe, E.A., Waldon, M.G., Harwell, M., and Chen, C., 2012, Compartment-based hydrodynamics and water quality modeling of a northern Everglades wetland, Florida, USA: Ecological Modelling, v. 247, p. 273-285, https://doi.org/10.1016/j.ecolmodel.2012.09.007.","productDescription":"13 p.","startPage":"273","endPage":"285","numberOfPages":"12","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":262837,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262823,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2012.09.007","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","volume":"247","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"508f9770e4b0a1b43c29ca07","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":4421,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":468469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meselhe, Ehab A.","contributorId":70660,"corporation":false,"usgs":true,"family":"Meselhe","given":"Ehab","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":468473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waldon, Michael G.","contributorId":19442,"corporation":false,"usgs":true,"family":"Waldon","given":"Michael","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":468472,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harwell, Matthew C.","contributorId":14702,"corporation":false,"usgs":true,"family":"Harwell","given":"Matthew C.","affiliations":[],"preferred":false,"id":468471,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Chunfang","contributorId":11078,"corporation":false,"usgs":true,"family":"Chen","given":"Chunfang","email":"","affiliations":[],"preferred":false,"id":468470,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70044068,"text":"70044068 - 2012 - Wildlife contact analysis: Emerging methods, questions, and challenges","interactions":[],"lastModifiedDate":"2013-03-29T15:32:51","indexId":"70044068","displayToPublicDate":"2012-10-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":982,"text":"Behavioral Ecology and Sociobiology","active":true,"publicationSubtype":{"id":10}},"title":"Wildlife contact analysis: Emerging methods, questions, and challenges","docAbstract":"Recent technological advances, such as proximity loggers, allow researchers to collect complete interaction histories, day and night, among sampled individuals over several months to years. Social network analyses are an obvious approach to analyzing interaction data because of their flexibility for fitting many different social structures as well as the ability to assess both direct contacts and indirect associations via intermediaries. For many network properties, however, it is not clear whether estimates based upon a sample of the network are reflective of the entire network. In wildlife applications, networks may be poorly sampled and boundary effects will be common. We present an alternative approach that utilizes a hierarchical modeling framework to assess the individual, dyadic, and environmental factors contributing to variation in the interaction rates and allows us to estimate the underlying process variation in each. In a disease control context, this approach will allow managers to focus efforts on those types of individuals and environments that contribute the most toward super-spreading events. We account for the sampling distribution of proximity loggers and the non-independence of contacts among groups by only using contact data within a group during days when the group membership of proximity loggers was known. This allows us to separate the two mechanisms responsible for a pair not contacting one another: they were not in the same group or they were in the same group but did not come within the specified contact distance. We illustrate our approach with an example dataset of female elk from northwestern Wyoming and conclude with a number of important future research directions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Behavioral Ecology and Sociobiology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s00265-012-1376-6","usgsCitation":"Cross, P.C., Creech, T., Ebinger, M.R., Heisey, D.M., Irvine, K.M., and Creel, S., 2012, Wildlife contact analysis: Emerging methods, questions, and challenges: Behavioral Ecology and Sociobiology, v. 66, no. 10, p. 1437-1447, https://doi.org/10.1007/s00265-012-1376-6.","productDescription":"11 p.","startPage":"1437","endPage":"1447","numberOfPages":"11","ipdsId":"IP-036680","costCenters":[{"id":482,"text":"Northern Rocky Mountain Science CenterNational Wildlife Health Center","active":false,"usgs":true}],"links":[{"id":270401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270400,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00265-012-1376-6"}],"country":"United States","volume":"66","issue":"10","noUsgsAuthors":false,"publicationDate":"2012-07-12","publicationStatus":"PW","scienceBaseUri":"5156b7f0e4b06ea905cdc04a","contributors":{"authors":[{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":474758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Creech, Tyler G.","contributorId":89422,"corporation":false,"usgs":true,"family":"Creech","given":"Tyler G.","affiliations":[],"preferred":false,"id":474761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebinger, Michael R. mebinger@usgs.gov","contributorId":5771,"corporation":false,"usgs":true,"family":"Ebinger","given":"Michael","email":"mebinger@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":474759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heisey, Dennis M. dheisey@usgs.gov","contributorId":2455,"corporation":false,"usgs":true,"family":"Heisey","given":"Dennis","email":"dheisey@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":474757,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":474756,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Creel, Scott","contributorId":15089,"corporation":false,"usgs":true,"family":"Creel","given":"Scott","affiliations":[],"preferred":false,"id":474760,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70040488,"text":"ofr20121144 - 2012 - Geologic assessment of undiscovered conventional oil and gas resources--Middle Eocene Claiborne Group, United States part of the Gulf of Mexico Basin","interactions":[],"lastModifiedDate":"2012-11-09T09:56:23","indexId":"ofr20121144","displayToPublicDate":"2012-10-26T00:00:00","publicationYear":"2012","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":"2012-1144","title":"Geologic assessment of undiscovered conventional oil and gas resources--Middle Eocene Claiborne Group, United States part of the Gulf of Mexico Basin","docAbstract":"The Middle Eocene Claiborne Group was assessed using established U.S. Geological Survey (USGS) assessment methodology for undiscovered conventional hydrocarbon resources as part of the 2007 USGS assessment of Paleogene-Neogene strata of the United States part of the Gulf of Mexico Basin including onshore and State waters. The assessed area is within the Upper Jurassic-Cretaceous-Tertiary Composite total petroleum system, which was defined as part of the assessment. Source rocks for Claiborne oil accumulations are interpreted to be organic-rich downdip shaley facies of the Wilcox Group and the Sparta Sand of the Claiborne Group; gas accumulations may have originated from multiple sources including the Jurassic Smackover and Haynesville Formations and Bossier Shale, the Cretaceous Eagle Ford and Pearsall(?) Formations, and the Paleogene Wilcox Group and Sparta Sand. Hydrocarbon generation in the basin started prior to deposition of Claiborne sediments and is ongoing at present. Emplacement of hydrocarbons into Claiborne reservoirs has occurred primarily via vertical migration along fault systems; long-range lateral migration also may have occurred in some locations. Primary reservoir sands in the Claiborne Group include, from oldest to youngest, the Queen City Sand, Cook Mountain Formation, Sparta Sand, Yegua Formation, and the laterally equivalent Cockfield Formation. Hydrocarbon traps dominantly are rollover anticlines associated with growth faults; salt structures and stratigraphic traps also are important. Sealing lithologies probably are shaley facies within the Claiborne and in the overlying Jackson Group. A geologic model, supported by spatial analysis of petroleum geology data including discovered reservoir depths, thicknesses, temperatures, porosities, permeabilities, and pressures, was used to divide the Claiborne Group into seven assessment units (AU) with distinctive structural and depositional settings. The AUs include (1) Lower Claiborne Stable Shelf Gas and Oil (50470120), (2) Lower Claiborne Expanded Fault Zone Gas (50470121), (3) Lower Claiborne Slope and Basin Floor Gas (50470122), (4) Lower Claiborne Cane River (50470123), (5) Upper Claiborne Stable Shelf Gas and Oil (50470124), (6) Upper Claiborne Expanded Fault Zone Gas (50470125), and (7) Upper Claiborne Slope and Basin Floor Gas (50470126). Total estimated mean undiscovered conventional hydrocarbon resources in the seven assessment units combined are 52 million barrels of oil, 19.145 trillion cubic feet of natural gas, and 1.205 billion barrels of natural gas liquids. A recurring theme that emerged from the evaluation of the seven Claiborne AUs is that the great bulk of undiscovered hydrocarbon resources comprise non-associated gas and condensate contained in deep (mostly >12,000 feet), overpressured, structurally complex outer shelf or slope and basin floor reservoirs. The continuing development of these downdip objectives is expected to be the primary focus of exploration activity for the onshore Middle Eocene Gulf Coast in the coming decades.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121144","usgsCitation":"Hackley, P.C., 2012, Geologic assessment of undiscovered conventional oil and gas resources--Middle Eocene Claiborne Group, United States part of the Gulf of Mexico Basin: U.S. Geological Survey Open-File Report 2012-1144, vi, 87 p., https://doi.org/10.3133/ofr20121144.","productDescription":"vi, 87 p.","numberOfPages":"93","onlineOnly":"Y","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":262821,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1144.jpg"},{"id":262817,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1144/","linkFileType":{"id":5,"text":"html"}},{"id":262818,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1144/pdf/OFR2012_1144.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States;Mexico","state":"Arkansas;Alabama;Florida;Georgia;Kentucky;Louisiana;Mississippi;Missouri;Oklahoma;Tennessee;Texas","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.0,24.0 ], [ -104.0,38.0 ], [ -83.0,38.0 ], [ -83.0,24.0 ], [ -104.0,24.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"508ba2f4e4b0d7f30c145737","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":468429,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040495,"text":"ds670 - 2012 - Archive of digital boomer subbottom profile data collected in the Atlantic Ocean offshore northeast Florida during USGS cruises 03FGS01 and 03FGS02 in September and October of 2003","interactions":[],"lastModifiedDate":"2012-11-09T11:14:57","indexId":"ds670","displayToPublicDate":"2012-10-26T00:00:00","publicationYear":"2012","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":"670","title":"Archive of digital boomer subbottom profile data collected in the Atlantic Ocean offshore northeast Florida during USGS cruises 03FGS01 and 03FGS02 in September and October of 2003","docAbstract":"In September and October of 2003, the U.S. Geological Survey (USGS), in cooperation with the Florida Geological Survey, conducted geophysical surveys of the Atlantic Ocean offshore northeast Florida from St. Augustine, Florida, to the Florida-Georgia border. This report serves as an archive of unprocessed digital boomer subbottom profile data, trackline maps, navigation files, Geographic Information System (GIS) files, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FGDC) metadata. Filtered and gained (a relative increase in signal amplitude) digital images of the seismic profiles are also provided. Refer to the Acronyms page for expansions of all acronyms and abbreviations used in this report. The USGS St. Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, 03FGS01 tells us the data were collected in 2003 as part of cooperative work with the Florida Geological Survey (FGS) and that the data were collected during the first field activity for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity identification (ID). The naming convention used for each seismic line is as follows: yye##a, where 'yy' are the last two digits of the year in which the data were collected, 'e' is a 1-letter abbreviation for the equipment type (for example, b for boomer), '##' is a 2-digit number representing a specific track, and 'a' is a letter representing the section of a line if recording was prematurely terminated or rerun for quality or acquisition problems. The boomer plate is an acoustic energy source that consists of capacitors charged to a high voltage and discharged through a transducer in the water. The transducer is towed on a sled floating on the water surface and when discharged emits a short acoustic pulse, or shot, which propagates through the water, sediment column, or rock beneath. The acoustic energy is reflected at density boundaries (such as the seafloor, sediment, or rock layers beneath the seafloor), detected by hydrophone receivers, and recorded by a PC-based seismic acquisition system. This process is repeated at timed intervals (for example, 0.5 seconds) and recorded for specific intervals of time (for example, 100 milliseconds). In this way, a two-dimensional (2-D) vertical profile of the shallow geologic structure beneath the ship track is produced. Refer to the handwritten FACS operation log (PDF, 442 KB) for diagrams and descriptions of acquisition geometry, which varied throughout the cruises. Table 1 displays a summary of acquisition parameters. See the digital FACS equipment logs (PDF, 9-13 KB each) for details about the acquisition equipment used. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG Y (Barry and others, 1975) format (rev. 0), except for the first 3,200 bytes of the card image header, which are stored in ASCII format instead of the standard EBCDIC format. The SEG Y files may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU) (Cohen and Stockwell, 2005). See the How To Download SEG Y Data page for download instructions. The printable profiles provided here are Graphics Interchange Format (GIF) images that were filtered and gained using SU software. Refer to the Software page for details about the processing and links to example SU processing scripts and USGS software for viewing the SEG Y files (Zihlman, 1992).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds670","collaboration":"Other Contributors: Jacobs Technology, Inc., Florida Geological Survey. For DVD ordering information see: <a href=\"http://pubs.usgs.gov/ds/670/\" target=\"_blank\">DS 670</a>.","usgsCitation":"Calderon, K., Forde, A.S., Dadisman, S.V., Wiese, D.S., and Phelps, D.C., 2012, Archive of digital boomer subbottom profile data collected in the Atlantic Ocean offshore northeast Florida during USGS cruises 03FGS01 and 03FGS02 in September and October of 2003: U.S. Geological Survey Data Series 670, HTML Document; DVD, https://doi.org/10.3133/ds670.","productDescription":"HTML Document; DVD","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":262820,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_670.png"},{"id":262813,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/670/","linkFileType":{"id":5,"text":"html"}},{"id":262814,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/670/index.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida;Georgia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.75,29.75 ], [ -81.75,31.0 ], [ -81.0,31.0 ], [ -81.0,29.75 ], [ -81.75,29.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"508ba2dce4b0d7f30c14572f","contributors":{"authors":[{"text":"Calderon, Karynna","contributorId":92739,"corporation":false,"usgs":true,"family":"Calderon","given":"Karynna","email":"","affiliations":[],"preferred":false,"id":468452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":468448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dadisman, Shawn V. sdadisman@usgs.gov","contributorId":2207,"corporation":false,"usgs":true,"family":"Dadisman","given":"Shawn","email":"sdadisman@usgs.gov","middleInitial":"V.","affiliations":[],"preferred":true,"id":468449,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiese, Dana S. dwiese@usgs.gov","contributorId":2476,"corporation":false,"usgs":true,"family":"Wiese","given":"Dana","email":"dwiese@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":468450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phelps, Daniel C.","contributorId":88194,"corporation":false,"usgs":true,"family":"Phelps","given":"Daniel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":468451,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70040493,"text":"ds724 - 2012 - Archive of digital chirp subbottom profile data collected during USGS cruise 10BIM04 offshore Cat Island, Mississippi, September 2010","interactions":[],"lastModifiedDate":"2012-11-09T11:18:50","indexId":"ds724","displayToPublicDate":"2012-10-26T00:00:00","publicationYear":"2012","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":"724","title":"Archive of digital chirp subbottom profile data collected during USGS cruise 10BIM04 offshore Cat Island, Mississippi, September 2010","docAbstract":"In September of 2010, the U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers (USACE), conducted a geophysical survey to investigate the geologic controls on barrier island framework of Cat Island, Miss., as part of a broader USGS study on Barrier Island Mapping (BIM). These surveys were funded through the Mississippi Coastal Improvements Program (MsCIP) and the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project as part of the Holocene Coastal Evolution of the Mississippi-Alabama Region Subtask. This report serves as an archive of unprocessed digital chirp subbottom data, trackline maps, navigation files, GIS files, Field Activity Collection System (FACS) logs, and formal FGDC metadata. Gained (showing a relative increase in signal amplitude) digital images of the seismic profiles are also provided. Refer to the Acronyms page for expansions of acronyms and abbreviations used in this report. The USGS Saint Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, 10BIM04 tells us the data were collected in 2010 during the fourth field activity for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity identification (ID). All chirp systems use a signal of continuously varying frequency; the EdgeTech SB-512i system used during this survey produces high-resolution, shallow-penetration (typically less than 50 milliseconds (ms)) profile images of sub-seafloor stratigraphy. The towfish contains a transducer that transmits and receives acoustic energy; it was housed within a float system (built at the SPCMSC), which allows the towfish to be towed at a constant depth of 1.07 meters (m) below the sea surface. As transmitted acoustic energy intersects density boundaries, such as the seafloor or sub-surface sediment layers, some energy is reflected back toward the transducer, received, and recorded by a Personal Computer (PC)-based seismic acquisition system. This process is repeated at regular time intervals (for example, 0.125 seconds (s)), and returned energy is recorded for a specific duration (for example, 50 ms). In this way, a two-dimensional (2-D) vertical image of the shallow geologic structure beneath the ship track is produced. Figure 1 displays the acquisition geometry. Refer to table 1 for a summary of acquisition parameters and table 2 for trackline statistics. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG Y rev. 0 format (Barry and others, 1975); the first 3,200 bytes of the card image header are in American Standard Code for Information Interchange (ASCII) format instead of Extended Binary Coded Decimal Interchange Code (EBCDIC) format. The SEG Y files may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU) (Cohen and Stockwell, 2010). See the How To Download SEG Y Data page for download instructions. The printable profiles provided here are GIF images that were processed and gained using SU software, and they can be viewed from the Profiles page or from links located on the trackline maps; refer to the Software page for links to example SU processing scripts. The SEG Y files are available on the DVD version of this report or on the Web, downloadable via the USGS Coastal and Marine Geoscience Data System (http://cmgds.marine.usgs.gov). The data are also available for viewing using GeoMapApp (http://www.geomapapp.org) and Virtual Ocean (http://www.virtualocean.org) multi-platform open source software.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds724","collaboration":"For DVD ordering information see: <a href=\"http://pubs.usgs.gov/ds/724/\" target=\"_blank\">DS 724</a>.","usgsCitation":"Forde, A.S., Dadisman, S.V., Kindinger, J.L., Miselis, J.L., Wiese, D.S., and Buster, N.A., 2012, Archive of digital chirp subbottom profile data collected during USGS cruise 10BIM04 offshore Cat Island, Mississippi, September 2010: U.S. Geological Survey Data Series 724, HTML Document; 2 DVDs, https://doi.org/10.3133/ds724.","productDescription":"HTML Document; 2 DVDs","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":262819,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_724.png"},{"id":262815,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/724/","linkFileType":{"id":5,"text":"html"}},{"id":262816,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/724/index.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Mississippi","otherGeospatial":"Cat Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.283333,30.0 ], [ -89.283333,30.333333 ], [ -89.033333,30.333333 ], [ -89.033333,30.0 ], [ -89.283333,30.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"508ba2ece4b0d7f30c145733","contributors":{"authors":[{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":468438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dadisman, Shawn V. sdadisman@usgs.gov","contributorId":2207,"corporation":false,"usgs":true,"family":"Dadisman","given":"Shawn","email":"sdadisman@usgs.gov","middleInitial":"V.","affiliations":[],"preferred":true,"id":468440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kindinger, Jack L. jkindinger@usgs.gov","contributorId":815,"corporation":false,"usgs":true,"family":"Kindinger","given":"Jack","email":"jkindinger@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":468439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":468443,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiese, Dana S. dwiese@usgs.gov","contributorId":2476,"corporation":false,"usgs":true,"family":"Wiese","given":"Dana","email":"dwiese@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":468441,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buster, Noreen A. 0000-0001-5069-9284 nbuster@usgs.gov","orcid":"https://orcid.org/0000-0001-5069-9284","contributorId":3750,"corporation":false,"usgs":true,"family":"Buster","given":"Noreen","email":"nbuster@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":468442,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70040503,"text":"pp1795A - 2012 - History of earthquakes and tsunamis along the eastern Aleutian-Alaska megathrust, with implications for tsunami hazards in the California Continental Borderland","interactions":[],"lastModifiedDate":"2018-05-07T21:32:12","indexId":"pp1795A","displayToPublicDate":"2012-10-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1795","chapter":"A","title":"History of earthquakes and tsunamis along the eastern Aleutian-Alaska megathrust, with implications for tsunami hazards in the California Continental Borderland","docAbstract":"During the past several years, devastating tsunamis were generated along subduction zones in Indonesia, Chile, and most recently Japan. Both the Chile and Japan tsunamis traveled across the Pacific Ocean and caused localized damage at several coastal areas in California. The question remains as to whether coastal California, in particular the California Continental Borderland, is vulnerable to more extensive damage from a far-field tsunami sourced along a Pacific subduction zone. Assuming that the coast of California is at risk from a far-field tsunami, its coastline is most exposed to a trans-Pacific tsunami generated along the eastern Aleutian-Alaska subduction zone. We present the background geologic constraints that could control a possible giant (M<sub>w</sub> ~9) earthquake sourced along the eastern Aleutian-Alaska megathrust. Previous great earthquakes (M<sub>w</sub> ~8) in 1788, 1938, and 1946 ruptured single segments of the eastern Aleutian-Alaska megathrust. However, in order to generate a giant earthquake, it is necessary to rupture through multiple segments of the megathrust. Potential barriers to a throughgoing rupture, such as high-relief fracture zones or ridges, are absent on the subducting Pacific Plate between the Fox and Semidi Islands. Possible asperities (areas on the megathrust that are locked and therefore subject to infrequent but large slip) are identified by patches of high moment release observed in the historical earthquake record, geodetic studies, and the location of forearc basin gravity lows. Global Positioning System (GPS) data indicate that some areas of the eastern Aleutian-Alaska megathrust, such as that beneath Sanak Island, are weakly coupled. We suggest that although these areas will have reduced slip during a giant earthquake, they are not really large enough to form a barrier to rupture. A key aspect in defining an earthquake source for tsunami generation is determining the possibility of significant slip on the updip end of the megathrust near the trench. Large slip on the updip part of the eastern Aleutian-Alaska megathrust is a viable possibility owing to the small frontal accretionary prism and the presence of arc basement relatively close to the trench along most of the megathrust.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Studies by the U.S. Geological Survey in Alaska, 2011","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1795A","collaboration":"Studies by the U.S. Geological Survey in Alaska, 2011; http://pubs.usgs.gov/pp/1795/","usgsCitation":"Ryan, H., von Huene, R.E., Wells, R., Scholl, D.W., Kirby, S., and Draut, A.E., 2012, History of earthquakes and tsunamis along the eastern Aleutian-Alaska megathrust, with implications for tsunami hazards in the California Continental Borderland: U.S. Geological Survey Professional Paper 1795, iv, 31 p.; maps (col.), https://doi.org/10.3133/pp1795A.","productDescription":"iv, 31 p.; maps (col.)","startPage":"i","endPage":"31","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":262827,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp_1795_A.gif"},{"id":262824,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1795/a/","linkFileType":{"id":5,"text":"html"}},{"id":262825,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1795/a/pp1795a.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Islands","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"508ba2fce4b0d7f30c14573b","contributors":{"editors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":509072,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Dusel-Bacon, C. 0000-0001-8481-739X","orcid":"https://orcid.org/0000-0001-8481-739X","contributorId":26085,"corporation":false,"usgs":true,"family":"Dusel-Bacon","given":"C.","affiliations":[],"preferred":false,"id":509071,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Ryan, Holly F.","contributorId":67616,"corporation":false,"usgs":true,"family":"Ryan","given":"Holly F.","affiliations":[],"preferred":false,"id":468477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"von Huene, Roland E. 0000-0003-1301-3866 rvonhuene@usgs.gov","orcid":"https://orcid.org/0000-0003-1301-3866","contributorId":191070,"corporation":false,"usgs":true,"family":"von Huene","given":"Roland","email":"rvonhuene@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":468476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wells, Ray E. 0000-0002-7796-0160 rwells@usgs.gov","orcid":"https://orcid.org/0000-0002-7796-0160","contributorId":2692,"corporation":false,"usgs":true,"family":"Wells","given":"Ray E.","email":"rwells@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":468474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scholl, David W. 0000-0001-6500-6962 dscholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6500-6962","contributorId":3738,"corporation":false,"usgs":true,"family":"Scholl","given":"David","email":"dscholl@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":468475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirby, Stephen","contributorId":89412,"corporation":false,"usgs":true,"family":"Kirby","given":"Stephen","affiliations":[],"preferred":false,"id":468478,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Draut, Amy E.","contributorId":92215,"corporation":false,"usgs":true,"family":"Draut","given":"Amy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":468479,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
]}