{"pageNumber":"801","pageRowStart":"20000","pageSize":"25","recordCount":40759,"records":[{"id":70043175,"text":"70043175 - 2010 - Detecting Ecosystem Performance Anomalies for Land Management in the Upper Colorado River Basin Using Satellite Observations, Climate Data, and Ecosystem Models","interactions":[],"lastModifiedDate":"2013-02-14T14:24:43","indexId":"70043175","displayToPublicDate":"2010-08-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Detecting Ecosystem Performance Anomalies for Land Management in the Upper Colorado River Basin Using Satellite Observations, Climate Data, and Ecosystem Models","docAbstract":"This study identifies areas with ecosystem performance anomalies (EPA) within the Upper Colorado River Basin (UCRB) during 2005–2007 using satellite observations, climate data, and ecosystem models. The final EPA maps with 250-m spatial resolution were categorized as normal performance, underperformance, and overperformance (observed performance relative to weather-based predictions) at the 90% level of confidence. The EPA maps were validated using “percentage of bare soil” ground observations. The validation results at locations with comparable site potential showed that regions identified as persistently underperforming (overperforming) tended to have a higher (lower) percentage of bare soil, suggesting that our preliminary EPA maps are reliable and agree with ground-based observations. The 3-year (2005–2007) persistent EPA map from this study provides the first quantitative evaluation of ecosystem performance anomalies within the UCRB and will help the Bureau of Land Management (BLM) identify potentially degraded lands. Results from this study can be used as a prototype by BLM and other land managers for making optimal land management decisions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"MDPI","doi":"10.3390/rs2081880","usgsCitation":"Gu, Y., and Wylie, B.K., 2010, Detecting Ecosystem Performance Anomalies for Land Management in the Upper Colorado River Basin Using Satellite Observations, Climate Data, and Ecosystem Models: Remote Sensing, v. 2, no. 8, p. 1880-1891, https://doi.org/10.3390/rs2081880.","startPage":"1880","endPage":"1891","ipdsId":"IP-021971","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":475680,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs2081880","text":"Publisher Index Page"},{"id":267415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267414,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/rs2081880"}],"country":"United States","volume":"2","issue":"8","noUsgsAuthors":false,"publicationDate":"2010-07-29","publicationStatus":"PW","scienceBaseUri":"511e1583e4b071e86a19a439","contributors":{"authors":[{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":409,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":473105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":473106,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70200865,"text":"70200865 - 2010 - The thermal signature of volcanic eruptions on Io and Earth,","interactions":[],"lastModifiedDate":"2018-11-07T16:46:30","indexId":"70200865","displayToPublicDate":"2010-07-30T16:45:38","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"The thermal signature of volcanic eruptions on Io and Earth,","docAbstract":"<p><span>We investigate a spectrum-based technique to identify the style of active volcanic eruptions on Jupiter's moon Io. Thermal remote sensing of Io has had to rely primarily on low-spatial-resolution data, similar to low-spatial-resolution&nbsp;satellite data applied to detecting and charting the&nbsp;temporal evolution&nbsp;of terrestrial hot spots. These terrestrial analyses use data from sensors designed to monitor the weather and&nbsp;sea surface temperature. On Io, such low-spatial-resolution data are used to classify eruption styles (modes of emplacement) by means of several criteria related to the temporal evolution of the&nbsp;infrared spectrum&nbsp;associated with the eruptive activity at each hot spot, which we term “thermal signature.” We find that the ratio of the emission at 2 and 5</span><span>&nbsp;</span><span>µm, and how this ratio changes with time, is often diagnostic of eruption style, even in low-spatial-resolution data. Tests using thermal data for terrestrial “ground truth” cases show that our classification system is valid on Earth. The results of our analysis can be used to aid in the design of future space-based instruments that can be used for volcano monitoring on Io, as well as Earth.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2010.04.009","usgsCitation":"Davies, A., Keszthelyi, L., and Harris, A.J., 2010, The thermal signature of volcanic eruptions on Io and Earth,: Journal of Volcanology and Geothermal Research, v. 194, no. 4, p. 75-99, https://doi.org/10.1016/j.jvolgeores.2010.04.009.","productDescription":"25 p.","startPage":"75","endPage":"99","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":359287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"194","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5be40825e4b0b3fc5cf7cc12","contributors":{"authors":[{"text":"Davies, Ashley G.","contributorId":36827,"corporation":false,"usgs":true,"family":"Davies","given":"Ashley G.","affiliations":[],"preferred":false,"id":750974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":750975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harris, Andrew J. L.","contributorId":169434,"corporation":false,"usgs":false,"family":"Harris","given":"Andrew","email":"","middleInitial":"J. L.","affiliations":[],"preferred":false,"id":750976,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70230189,"text":"70230189 - 2010 - Global climate changes recorded in coastal wetland sediments: Empirical observations linked to theoretical predictions","interactions":[],"lastModifiedDate":"2022-04-04T14:34:11.92354","indexId":"70230189","displayToPublicDate":"2010-07-30T09:29:46","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Global climate changes recorded in coastal wetland sediments: Empirical observations linked to theoretical predictions","docAbstract":"<p><span>Whether coastal areas are experiencing, and responding to, an accelerated rate of global sea-level rise (GSLR) is critically important for the ∼2 billion people living near Earth's oceans. Accretion rates from a suite of physiographically diverse coastal wetlands surrounding Long Island, NY accelerated during the 20th century at 2.3 ± 0.2 × 10</span><sup>−2</sup><span>&nbsp;mm yr</span><sup>−2</sup><span>, which is comparable to reported rates of GSLR acceleration and global temperature changes. Wetlands varied in tidal range, salinity and geomorphic setting, and were located in embayments with limited human impacts in a region with limited and constant rates of subsidence. From geochronologies with temporal resolutions of 2–5 yr, we constructed new composite histories of sediment accretion and mineral deposition. Wetland dynamics are consistent with predictions from sedimentology and a numerical model of ecogeomorphic response, suggesting that these systems, and likely others worldwide, are responding to accelerated GSLR and related climatic changes.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2010GL043874","usgsCitation":"Kolker, A.S., Kirwan, M., Goodbred, S.L., and Cochran, J.K., 2010, Global climate changes recorded in coastal wetland sediments: Empirical observations linked to theoretical predictions: Geophysical Research Letters, v. 37, L14706, 5 p., https://doi.org/10.1029/2010GL043874.","productDescription":"L14706, 5 p.","costCenters":[],"links":[{"id":475682,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2010gl043874","text":"Publisher Index Page"},{"id":398009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.4658203125,\n              40.84706035607122\n            ],\n            [\n              -72.6470947265625,\n              40.98819156349393\n            ],\n            [\n              -73.685302734375,\n              40.9218144123785\n            ],\n            [\n              -74.02587890625,\n              40.730608477796636\n            ],\n            [\n              -74.0753173828125,\n              40.5930995321649\n            ],\n            [\n              -73.85009765625,\n              40.51797520038851\n            ],\n            [\n              -73.5150146484375,\n              40.56806745430726\n            ],\n            [\n              -73.14697265625,\n              40.60561205826018\n            ],\n            [\n              -72.4658203125,\n              40.84706035607122\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"37","noUsgsAuthors":false,"publicationDate":"2010-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Kolker, Alexander S.","contributorId":213409,"corporation":false,"usgs":false,"family":"Kolker","given":"Alexander","email":"","middleInitial":"S.","affiliations":[{"id":38749,"text":"Tulane University; Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":839421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirwan, Matthew L. 0000-0002-0658-3038","orcid":"https://orcid.org/0000-0002-0658-3038","contributorId":84060,"corporation":false,"usgs":true,"family":"Kirwan","given":"Matthew L.","affiliations":[],"preferred":false,"id":839422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goodbred, Steven L. sgoodbred@usgs.gov","contributorId":497,"corporation":false,"usgs":true,"family":"Goodbred","given":"Steven","email":"sgoodbred@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":839423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cochran, J. Kirk","contributorId":205683,"corporation":false,"usgs":false,"family":"Cochran","given":"J.","email":"","middleInitial":"Kirk","affiliations":[{"id":37144,"text":"School of Marine and Atmospheric Science, Stony Brook University, Stony Brook, NY 11794, USA","active":true,"usgs":false}],"preferred":false,"id":839424,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70159150,"text":"70159150 - 2010 - Use of EO-1 Hyperion data to calculate spectral band adjustment factors (SBAF) between the L7 ETM+ and Terra MODIS sensors","interactions":[],"lastModifiedDate":"2017-05-10T15:50:14","indexId":"70159150","displayToPublicDate":"2010-07-30T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Use of EO-1 Hyperion data to calculate spectral band adjustment factors (SBAF) between the L7 ETM+ and Terra MODIS sensors","docAbstract":"<p><span>Different applications and technology developments in Earth observations necessarily require different spectral coverage. Thus, even for the spectral bands designed to look at the same region of the electromagnetic spectrum, the relative spectral responses (RSR) of different sensors may be different. In this study, spectral band adjustment factors (SBAF) are derived using hyperspectral Earth Observing-1 (EO-1) Hyperion measurements to adjust for the spectral band differences between the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) top-of-atmosphere (TOA) reflectance measurements from 2000 to 2009 over the pseudo-invariant Libya 4 reference standard test site.</span></p>","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2010 : 25 - 30 July 2010, Honolulu, Hawaii, USA","conferenceTitle":"2010 IEEE International Geoscience and Remote Sensing Symposium","conferenceDate":"July 25-30, 2010","conferenceLocation":"Piscataway, N.J.","language":"English","publisher":"Institute of Electrical and Electronics Engineers (IEEE)","doi":"10.1109/IGARSS.2010.5652746","usgsCitation":"Chander, G., Mishra, N., Helder, D.L., Aaron, D., Choi, T., Angal, A., and Xiong, X., 2010, Use of EO-1 Hyperion data to calculate spectral band adjustment factors (SBAF) between the L7 ETM+ and Terra MODIS sensors, <i>in</i> IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2010 : 25 - 30 July 2010, Honolulu, Hawaii, USA, Piscataway, N.J., July 25-30, 2010, p. 1667-1670, https://doi.org/10.1109/IGARSS.2010.5652746.","productDescription":"4 p,","startPage":"1667","endPage":"1670","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-022546","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":309971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5620cec6e4b06217fc478b3d","contributors":{"authors":[{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":577709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mishra, N.","contributorId":67379,"corporation":false,"usgs":true,"family":"Mishra","given":"N.","email":"","affiliations":[],"preferred":false,"id":577710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Helder, Dennis L.","contributorId":105613,"corporation":false,"usgs":true,"family":"Helder","given":"Dennis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":577711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aaron, David","contributorId":83809,"corporation":false,"usgs":false,"family":"Aaron","given":"David","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":577712,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Choi, T.","contributorId":48698,"corporation":false,"usgs":true,"family":"Choi","given":"T.","affiliations":[],"preferred":false,"id":577713,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Angal, A.","contributorId":52716,"corporation":false,"usgs":true,"family":"Angal","given":"A.","affiliations":[],"preferred":false,"id":577714,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xiong, X.","contributorId":37885,"corporation":false,"usgs":true,"family":"Xiong","given":"X.","affiliations":[],"preferred":false,"id":577715,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70157297,"text":"70157297 - 2010 - The use of the Sonoran Desert as a pseudo-invariant site for optical sensor cross-calibration and long-term stability monitoring","interactions":[],"lastModifiedDate":"2017-04-25T16:32:13","indexId":"70157297","displayToPublicDate":"2010-07-30T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"The use of the Sonoran Desert as a pseudo-invariant site for optical sensor cross-calibration and long-term stability monitoring","docAbstract":"<p><span>The Sonoran Desert is a large, flat, pseudo-invariant site near the United States-Mexico border. It is one of the largest and hottest deserts in North America, with an area of 311,000 square km. This site is particularly suitable for calibration purposes because of its high spatial and spectral uniformity and reasonable temporal stability. This study uses measurements from four different sensors, Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), Aqua MODIS, and Landsat 5 (L5) Thematic Mapper (TM), to assess the suitability of this site for long-term stability monitoring and to evaluate the &ldquo;radiometric calibration differences&rdquo; between spectrally matching bands of all four sensors. In general, the drift in the top-of-atmosphere (TOA) reflectance of each sensor over a span of nine years is within the specified calibration uncertainties. Monthly precipitation measurements of the Sonoran Desert region were obtained from the Global Historical Climatology Network (GHCN), and their effects on the retrieved TOA reflectances were evaluated. To account for the combined uncertainties in the TOA reflectance due to the surface and atmospheric Bi-directional Reflectance Distribution Function (BRDF), a semi-empirical BRDF model has been adopted to monitor and reduce the impact of illumination geometry differences on the retrieved TOA reflectances. To evaluate calibration differences between the MODIS and Landsat sensors, correction for spectral response differences using a hyperspectral sensor is also demonstrated.</span></p>","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International","conferenceTitle":"2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","conferenceDate":"July 25-30, 2010","conferenceLocation":"Honolulu, Hawaii","language":"English","publisher":"IEEE","doi":"10.1109/IGARSS.2010.5652812","usgsCitation":"Angal, A., Chander, G., Choi, T., Wu, A., and Xiong, X., 2010, The use of the Sonoran Desert as a pseudo-invariant site for optical sensor cross-calibration and long-term stability monitoring, <i>in</i> Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International, Honolulu, Hawaii, July 25-30, 2010, p. 1656-1659, https://doi.org/10.1109/IGARSS.2010.5652812.","productDescription":"4 p.","startPage":"1656","endPage":"1659","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-022547","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":308259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55fbe44ee4b05d6c4e502913","contributors":{"authors":[{"text":"Angal, A.","contributorId":52716,"corporation":false,"usgs":true,"family":"Angal","given":"A.","affiliations":[],"preferred":false,"id":572620,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":572621,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choi, Taeyoung","contributorId":146955,"corporation":false,"usgs":false,"family":"Choi","given":"Taeyoung","email":"","affiliations":[],"preferred":false,"id":572622,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Aisheng","contributorId":65362,"corporation":false,"usgs":true,"family":"Wu","given":"Aisheng","email":"","affiliations":[],"preferred":false,"id":572623,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xiong, Xiaoxiong","contributorId":15088,"corporation":false,"usgs":true,"family":"Xiong","given":"Xiaoxiong","email":"","affiliations":[],"preferred":false,"id":572624,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70175162,"text":"70175162 - 2010 - Limiting factors of four rare plant species in `Ōla`A Forest of Hawai'i Volcanoes National Park","interactions":[],"lastModifiedDate":"2018-01-05T13:25:10","indexId":"70175162","displayToPublicDate":"2010-07-29T10:30:00","publicationYear":"2010","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-018","title":"Limiting factors of four rare plant species in `Ōla`A Forest of Hawai'i Volcanoes National Park","docAbstract":"<p>Three endangered or candidate endangered plant species native to `Ōla`a Forest (<i>Cyrtandra giffardii</i>, ha`iwale; <i>Phyllostegia floribunda</i>, a mint with no common name; and <i>Sicyos alba</i>, `ānunu) were studied for more than 2 years to determine their stand structures, short-term mortality rates, patterns of reproductive phenology, success of fruit production, seed germination rates in the greenhouse, presence of soil seed bank, and survival of both natural and planted seedlings. The role of rodents as seed predators was evaluated for <i>S. alba</i> using seed offerings in open and closed stations. A 4th endangered species at a remote site in `Ōla`a (<i>Cyrtandra tintinnabula</i>) was visited to determine its stand structure and mortality rate.</p>\n<p><i>Cyrtandra giffardii</i> displayed a stable population structure with many adults and few small or very large plants; the monitored population had a mortality rate of 7.3% over 3 years. Mortality of plantings from 2003-2004 in a re-introduced population of <i>Phyllostegia floribunda</i> was 21.4%. The stand structure of<i> C. tintinnabula</i> indicated a relatively stable population with both small and large plants present and a short-term mortality rate between visits of 14.5- 17.0%. Four groups of <i>S. alba</i> vines were monitored; 3 of these have persisted in place for at least 15 years. All species monitored had annual patterns of flower and fruit phenology, although male inflorescences of <i>S. alba</i> showed a subannual pattern. Successful transition of flowers to fruit was high for P. floribunda (51.5%), moderate for <i>C. giffardii</i> (23.3%) and undetermined for <i>S. alba</i>. High percentage viability was demonstrated for seeds <i>of P. floribunda</i> and <i>S. alba</i> (78.5-100% positive to strongly positive in tetrazolium tests), but seed viability was not tested for <i>C. giffardii</i>.</p>\n<p>Greenhouse germination rates were high for <i>P. floribunda</i> (88.0-92.0%), but variable and relatively low for <i>C. giffardii</i> (0-19.3%) and <i>S. alba</i> (4.0-11.1% in 2007 and 0 in 2008). No soil seed bank was detected for <i>S. alba</i> in 3 seasonal samplings, but <i>P. floribunda</i> was found to have a viable seed bank in April that persisted from at least the previous summer. Rodent predation of <i>S. alba</i> seeds was 93.3% in fruit offerings in accessible bait stations. Mortality of natural seedlings was high for both <i>P. floribunda</i> (90.2%) and <i>S. alba</i> (69.7%). Planted seedlings of <i>P. floribunda</i> produced flowers and fruit in their first year, and reproduction was higher in sunny plots than in shady plots. Mortality was high in both planting treatments, and survival rates did not differ significantly in sun and shade (&chi;<sup>2</sup> =0.48, df = 1, p = 0.490). Three planted seedlings of <i>S. alba</i> survived for 12-16 months but did not reproduce.</p>\n<p>Floral visitors were observed at <i>C. giffardii</i> and <i>P. floribunda</i> using digital video cameras and recorders. In almost 200 hours of observation, no visitors entered the flowers of <i>C. giffardii</i>, although 1 very small insect, either a micro-wasp (Hymenoptera) or fly (Diptera) was seen on the exterior of a corolla. In almost 300 hours of video observation, 3 floral visitors were identified at <i>P. floribunda</i> flowers. Honeybees (<i>Apis mellifera</i>) were likely pollinators, as they contacted both anthers and stigma of flowers. The mean visitation rate of honeybees was 0.003 visit/flower/hour, and visit duration ranged from 2 to 17 seconds. Fruit flies (Drosophilidae of undetermined species) crawled around flower interiors, but did not seem to forage for either nectar or pollen. Fruit fly mean visitation rate was 0.006 visit/flower/hour, and visit duration was 28 to 1,424 seconds. The 3rd observed insect visitor was an endemic geometrid moth caterpillar (<i>Lophoplusia giffardi</i>), which was seen feeding on foliage and flowers of <i>P. floribunda</i>.</p>\n<p>In conclusion, 2 of the 3 regularly-monitored rare plant species of `Ōla`a Forest appeared to have more than 1 limiting factor inhibiting the natural increase in their populations, while for <i>P. floribunda</i> the most important factor was high seedling mortality. Most plants of the monitored <i>C. giffardii</i> population appeared to be hybrids, probably with the more common species <i>C. lysiosepala</i>. Seed germination rates were low, and natural seedlings were not observed. Pollinators were not seen in many hours of observation, indicating that cross pollination is a rare or uncommon event. The re-introduced population of <i>P. floribunda</i> had relatively low mortality, and reproduction was successful with high rates of fruit formation from abundant flowers. Seed germination rates were high, and a soil seed bank was detected. Natural seedling recruitment was observed, but high seedling mortality indicated that this life stage was the most vulnerable in the species. The population of <i>S. alba</i> was small and the vine life form precluded an accurate estimate of the number of adult plants in `Ōla`a Forest. Natural dormancy was likely a factor in the observed low rate of seed germination. No soil seed bank was detected, and alien rodents were implicated as seed predators. Natural recruitment was observed at multiple sites in `Ōla`a, but seedling mortality was high. The cause of seedling mortality was not identified.</p>","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"VanDeMark, J.R., Pratt, L.W., and Euaparadorn, M., 2010, Limiting factors of four rare plant species in `Ōla`A Forest of Hawai'i Volcanoes National Park: Technical Report HCSU-018, x, 72 p.","productDescription":"x, 72 p.","numberOfPages":"84","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-018754","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":325884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Hawai'i Volcanoes National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.27114868164062,\n              19.441989391028706\n            ],\n            [\n              -155.313720703125,\n              19.41220201468123\n            ],\n            [\n              -155.37551879882812,\n              19.368158505739157\n            ],\n            [\n              -155.40573120117188,\n              19.296886457967965\n            ],\n            [\n              -155.43731689453125,\n              19.216506191361127\n            ],\n            [\n              -155.40435791015622,\n              19.186677697957833\n            ],\n            [\n              -155.31097412109372,\n              19.21391262405755\n            ],\n            [\n              -155.27938842773435,\n              19.2489223284628\n            ],\n            [\n              -155.18325805664062,\n              19.235956641468505\n            ],\n            [\n              -155.16128540039062,\n              19.251515342943254\n            ],\n            [\n              -155.08712768554688,\n              19.281332062593734\n            ],\n            [\n              -155.03631591796875,\n              19.32280716454424\n            ],\n            [\n              -155.00335693359375,\n              19.370749630150478\n            ],\n            [\n              -155.03494262695312,\n              19.429039028956183\n            ],\n            [\n              -155.10086059570312,\n              19.458823317103146\n            ],\n            [\n              -155.13381958007812,\n              19.45752846172972\n            ],\n            [\n              -155.20660400390625,\n              19.43421929772404\n            ],\n            [\n              -155.27114868164062,\n              19.441989391028706\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a072b6e4b060ce18fb2dab","contributors":{"authors":[{"text":"VanDeMark, Joshua R.","contributorId":120307,"corporation":false,"usgs":true,"family":"VanDeMark","given":"Joshua","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":644165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pratt, Linda W. lpratt@usgs.gov","contributorId":3708,"corporation":false,"usgs":true,"family":"Pratt","given":"Linda","email":"lpratt@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":644166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Euaparadorn, Melody","contributorId":37240,"corporation":false,"usgs":true,"family":"Euaparadorn","given":"Melody","affiliations":[],"preferred":false,"id":644167,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":98550,"text":"sir20105142 - 2010 - Hydrogeology and numerical simulation of the unconsolidated glacial aquifer in the Pootatuck River Basin, Newtown, Connecticut","interactions":[],"lastModifiedDate":"2012-03-08T17:16:16","indexId":"sir20105142","displayToPublicDate":"2010-07-29T00:00:00","publicationYear":"2010","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":"2010-5142","title":"Hydrogeology and numerical simulation of the unconsolidated glacial aquifer in the Pootatuck River Basin, Newtown, Connecticut","docAbstract":"A study of the groundwater and stream-aquifer interaction in the Pootatuck River Basin, Newtown, Connecticut, was conducted to analyze the effect of production wells on the groundwater levels and streamflow in the Pootatuck River as part of a cooperative program between the U.S. Geological Survey and Newtown, Connecticut. This study will help address concerns about the increasing competition for water for human uses and protection of aquatic habitat. The groundwater-flow model developed in the study was designed for use as a tool to assist planners in assessing the effects of potential future development, which will change the amount and distribution of recharge available to the groundwater system.\r\n\r\nSeveral different techniques were used to investigate the interconnection between the stream and the aquifer. Temperature, groundwater levels, stream stage, and stable-isotope data collected during aquifer tests at the principal production wells in the Pootatuck River Basin, as well as groundwater-flow simulations of the system, indicate that more than half of the water pumped from the wells comes from the Pootatuck River. This finding potentially has a large effect on approaches for protecting the water quality of the pumped water. Increases in the amount of impervious surface from future development will reduce and redistribute recharge to the groundwater system. The simulation of future development scenarios showed a decrease in the simulated base flow in the main stem of the Pootatuck River and in all of the 26 simulated subbasins, with some of the subbasins showing a decrease of more than 20 percent when new development had 85 percent impervious area.\r\n\r\nThe groundwater-flow model and particle tracking were used to determine areas that contribute recharge to the five production wells available for use in the Pootatuck River Basin. These areas included narrow portions of the aquifer that extended beyond the immediate upgradient areas, probably because of deeper groundwater-flow paths. ","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105142","collaboration":"Prepared in cooperation with the Town of Newtown, Connecticut","usgsCitation":"Carlson, C.S., Mondazzi, R.A., Bjerklie, D.M., and Brown, C., 2010, Hydrogeology and numerical simulation of the unconsolidated glacial aquifer in the Pootatuck River Basin, Newtown, Connecticut: U.S. Geological Survey Scientific Investigations Report 2010-5142, ix, 84p. ; Appendices, https://doi.org/10.3133/sir20105142.","productDescription":"ix, 84p. ; Appendices","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":13945,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5142/","linkFileType":{"id":5,"text":"html"}},{"id":165526,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.36666666666666,41.31666666666667 ], [ -73.36666666666666,41.45 ], [ -73.21666666666667,41.45 ], [ -73.21666666666667,41.31666666666667 ], [ -73.36666666666666,41.31666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4af4e4b07f02db692058","contributors":{"authors":[{"text":"Carlson, Carl S. 0000-0001-7142-3519 cscarlso@usgs.gov","orcid":"https://orcid.org/0000-0001-7142-3519","contributorId":1694,"corporation":false,"usgs":true,"family":"Carlson","given":"Carl","email":"cscarlso@usgs.gov","middleInitial":"S.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mondazzi, Remo A.","contributorId":77898,"corporation":false,"usgs":true,"family":"Mondazzi","given":"Remo","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":305708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bjerklie, David M. 0000-0002-9890-4125 dmbjerkl@usgs.gov","orcid":"https://orcid.org/0000-0002-9890-4125","contributorId":3589,"corporation":false,"usgs":true,"family":"Bjerklie","given":"David","email":"dmbjerkl@usgs.gov","middleInitial":"M.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Craig J.","contributorId":104450,"corporation":false,"usgs":true,"family":"Brown","given":"Craig J.","affiliations":[],"preferred":false,"id":305709,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70004059,"text":"70004059 - 2010 - Environmental conditions affecting the efficiency and efficacy of piscicides for use in nonnative fish eradication","interactions":[],"lastModifiedDate":"2017-06-14T09:52:01","indexId":"70004059","displayToPublicDate":"2010-07-29T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":21,"text":"Thesis"},"publicationSubtype":{"id":28,"text":"Thesis"},"title":"Environmental conditions affecting the efficiency and efficacy of piscicides for use in nonnative fish eradication","docAbstract":"<p>Conservation of native fish is a pressing issue for fisheries managers. Conservation efforts often require eliminating threats posed by nonnative fish by eradicating them with piscicides. The piscicides rotenone and antimycin are used for eradication but their application is often inefficient or ineffective. My goal was to increase the efficiency and efficacy of nonnative fish eradication using piscicides. I identified environmental conditions affecting piscicide application, researched methods to overcome these problems, and provided tools that piscicide applicators can use to make piscicide application more efficient and effective. Rotenone and antimycin were exposed to varying levels of sunlight, turbulence, and dissolved organic matter (DOM) to determine the effect these environmental conditions have on piscicides. Bioassay fish were used to determine the toxicity of the piscicides. Sunlight and turbulence affected rotenone and antimycin but DOM did not. Increasing the concentration of chemical can increase the resistance to the effects of these environmental conditions; however, the effects of these conditions are considerable in natural settings. Observations of bioassay fish in stream applications of rotenone were used to develop a statistical model to predict the persistence of the piscicide. The model can be used to predict rotenone persistence in small montane streams and to estimate where rotenone concentrations need to be fortified. I measured the mixing rate of a chemical plume in different channel morphologies and at center or edge applications. Center application had a significantly shorter mixing distance than edge application, but mixing distance was not different among meandering, straight, and riffle/pool morphologies. 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,{"id":98542,"text":"ofr20101139 - 2010 - Preliminary assessment of factors influencing riverine fish communities in Massachusetts","interactions":[],"lastModifiedDate":"2019-12-26T15:57:09","indexId":"ofr20101139","displayToPublicDate":"2010-07-23T00:00:00","publicationYear":"2010","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":"2010-1139","title":"Preliminary assessment of factors influencing riverine fish communities in Massachusetts","docAbstract":"The U.S. Geological Survey, in cooperation with the Massachusetts Department of Conservation and Recreation (MDCR), Massachusetts Department of Environmental Protection (MDEP), and the Massachusetts Department of Fish and Game (MDFG), conducted a preliminary investigation of fish communities in small- to medium-sized Massachusetts streams. The objective of this investigation was to determine relations between fish-community characteristics and anthropogenic alteration, including flow alteration and impervious cover, relative to the effect of physical basin and land-cover (environmental) characteristics. Fish data were obtained for 756 fish-sampling sites from the Massachusetts Division of Fisheries and Wildlife fish-community database. A review of the literature was used to select a set of fish metrics responsive to flow alteration. Fish metrics tested include two fish-community metrics (fluvial-fish relative abundance and fluvial-fish species richness), and five indicator species metrics (relative abundance of brook trout, blacknose dace, fallfish, white sucker, and redfin pickerel). Streamflows were simulated for each fish-sampling site using the Sustainable Yield Estimator application (SYE). Daily streamflows and the SYE water-use database were used to determine a set of indicators of flow alteration, including percent alteration of August median flow, water-use intensity, and withdrawal and return-flow fraction. The contributing areas to the fish-sampling sites were delineated and used with a Geographic Information System (GIS) to determine a set of environmental characteristics, including elevation, basin slope, percent sand and gravel, percent wetland, and percent open water, and a set of anthropogenic-alteration variables, including impervious cover and dam density.\r\n\r\nTwo analytical techniques, quantile regression and generalized linear modeling, were applied to determine the association between fish-response variables and the selected environmental and anthropogenic explanatory variables. Quantile regression indicated that flow alteration and impervious cover were negatively associated with both fluvial-fish relative abundance and fluvial-fish species richness. Three generalized linear models (GLMs) were developed to quantify the response of fish communities to multiple environmental and anthropogenic variables. Flow-alteration variables are statistically significant for the fluvial-fish relative-abundance model.\r\n\r\nImpervious cover is statistically significant for the fluvial-fish relative-abundance, fluvial-fish species richness, and brook trout relative-abundance models. The variables in the equations were demonstrated to be significant, and the variability explained by the models, as measured by the correlation between observed and predicted values, ranges from 39 to 65 percent. The GLM models indicated that, keeping all other variables the same, a one-unit (1 percent) increase in the percent depletion or percent surcharging of August median flow would result in a 0.4-percent decrease in the relative abundance (in counts per hour) of fluvial fish and that the relative abundance of fluvial fish was expected to be about 55 percent lower in net-depleted streams than in net-surcharged streams. The GLM models also indicated that a unit increase in impervious cover resulted in a 5.5-percent decrease in the relative abundance of fluvial fish and a 2.5-percent decrease in fluvial-fish species richness.\r\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20101139","collaboration":"Prepared in cooperation with the \r\nMassachusetts Department of Conservation and Recreation, the\r\nMassachusetts Department of Environmental Protection, and the Massachusetts Department of Fish and Game\r\n","usgsCitation":"Armstrong, D.S., Richards, T.A., and Brandt, S.L., 2010, Preliminary assessment of factors influencing riverine fish communities in Massachusetts: U.S. Geological Survey Open-File Report 2010-1139, ix, 43 p., https://doi.org/10.3133/ofr20101139.","productDescription":"ix, 43 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":376,"text":"Massachusetts Water Science 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 \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a15e4b07f02db603195","contributors":{"authors":[{"text":"Armstrong, David S. 0000-0003-1695-1233 darmstro@usgs.gov","orcid":"https://orcid.org/0000-0003-1695-1233","contributorId":1390,"corporation":false,"usgs":true,"family":"Armstrong","given":"David","email":"darmstro@usgs.gov","middleInitial":"S.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305687,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richards, Todd A.","contributorId":52266,"corporation":false,"usgs":true,"family":"Richards","given":"Todd","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":305688,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, Sara L.","contributorId":89240,"corporation":false,"usgs":true,"family":"Brandt","given":"Sara","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":305689,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70175002,"text":"70175002 - 2010 - Survival of feral cats, <i>Felis catus</i> (Carnivora: Felidae), on Mauna Kea, Hawai'i, based on tooth cementum lines","interactions":[],"lastModifiedDate":"2018-01-04T12:54:04","indexId":"70175002","displayToPublicDate":"2010-07-22T14:30:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2990,"text":"Pacific Science","active":true,"publicationSubtype":{"id":10}},"title":"Survival of feral cats, <i>Felis catus</i> (Carnivora: Felidae), on Mauna Kea, Hawai'i, based on tooth cementum lines","docAbstract":"<p><span>Feral cats (</span><i>Felis catus</i><span>) have spread throughout anthropogenic and insular environments of the world. They now threaten many species of native wildlife with chronic depredation. Knowledge of feral cat population dynamics is necessary to understand their ecological effects and to develop effective control strategies. However, there are few studies worldwide regarding annual or lifetime survival rates in remote systems, and none on Pacific islands. We constructed the age distribution and estimated survival of feral cats in a remote area of Hawai'i Island using cementum lines present in lower canine teeth. Our data suggest annual cementum line formation. A log-linear model estimated annual survival &ge; 1 yr of age to be 0.647. Relatively high survival coupled with high reproductive output allows individual cats to affect native wildlife for many years and cat populations to rebound quickly after control efforts.</span></p>","language":"English","publisher":"University of Hawai'i Press","publisherLocation":"Honolulu, HI","doi":"10.2984/64.3.381","usgsCitation":"Danner, R.M., Farmer, C., Hess, S., Stephens, R.M., and Banko, P.C., 2010, Survival of feral cats, <i>Felis catus</i> (Carnivora: Felidae), on Mauna Kea, Hawai'i, based on tooth cementum lines: Pacific Science, v. 64, no. 3, p. 381-389, https://doi.org/10.2984/64.3.381.","productDescription":"8 p.","startPage":"381","endPage":"389","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-012399","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":325650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Kea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.38650512695312,\n              19.903636146415863\n            ],\n            [\n              -155.44143676757812,\n              19.913965885756145\n            ],\n            [\n              -155.47714233398438,\n              19.91783936409827\n            ],\n            [\n              -155.50872802734375,\n              19.9100923125452\n            ],\n            [\n              -155.58837890625,\n              19.845518806331246\n            ],\n            [\n              -155.61721801757812,\n              19.85326901590216\n            ],\n            [\n              -155.643310546875,\n              19.837768218373313\n            ],\n            [\n              -155.643310546875,\n              19.797717490704738\n            ],\n            [\n              -155.58975219726562,\n              19.770580624242616\n            ],\n            [\n              -155.533447265625,\n              19.73956140498458\n            ],\n            [\n              -155.51010131835938,\n              19.727927643457424\n            ],\n            [\n              -155.46340942382812,\n              19.711121825769855\n            ],\n            [\n              -155.41397094726562,\n              19.724049534671522\n            ],\n            [\n              -155.379638671875,\n              19.76282638490852\n            ],\n            [\n              -155.35766601562497,\n              19.796425363822532\n            ],\n            [\n              -155.35491943359375,\n              19.830017252151734\n            ],\n            [\n              -155.35629272460938,\n              19.872642883577086\n            ],\n            [\n              -155.38650512695312,\n              19.903636146415863\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"64","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"579889cae4b0589fa1c6bb83","contributors":{"authors":[{"text":"Danner, Raymond M.","contributorId":69475,"corporation":false,"usgs":true,"family":"Danner","given":"Raymond","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":643566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, Chris cfarmer@usgs.gov","contributorId":3681,"corporation":false,"usgs":true,"family":"Farmer","given":"Chris","email":"cfarmer@usgs.gov","affiliations":[],"preferred":true,"id":643567,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hess, Steven C. shess@usgs.gov","contributorId":150178,"corporation":false,"usgs":true,"family":"Hess","given":"Steven C.","email":"shess@usgs.gov","affiliations":[],"preferred":false,"id":643568,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stephens, Robert M.","contributorId":150182,"corporation":false,"usgs":false,"family":"Stephens","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":17932,"text":"PCSU, robertms@hawaii.edu","active":true,"usgs":false}],"preferred":false,"id":643569,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":643570,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":98538,"text":"fs20103059 - 2010 - Divisions of geologic time-major chronostratigraphic and geochronologic units","interactions":[{"subject":{"id":79747,"text":"fs20073015 - 2007 - Divisions of Geologic Time—Major Chronostratigraphic and Geochronologic Units","indexId":"fs20073015","publicationYear":"2007","noYear":false,"title":"Divisions of Geologic Time—Major Chronostratigraphic and Geochronologic Units"},"predicate":"SUPERSEDED_BY","object":{"id":98538,"text":"fs20103059 - 2010 - Divisions of geologic time-major chronostratigraphic and geochronologic units","indexId":"fs20103059","publicationYear":"2010","noYear":false,"title":"Divisions of geologic time-major chronostratigraphic and geochronologic units"},"id":1},{"subject":{"id":98538,"text":"fs20103059 - 2010 - Divisions of geologic time-major chronostratigraphic and geochronologic units","indexId":"fs20103059","publicationYear":"2010","noYear":false,"title":"Divisions of geologic time-major chronostratigraphic and geochronologic units"},"predicate":"SUPERSEDED_BY","object":{"id":70198659,"text":"fs20183054 - 2018 - Divisions of geologic time—Major chronostratigraphic and geochronologic units","indexId":"fs20183054","publicationYear":"2018","noYear":false,"title":"Divisions of geologic time—Major chronostratigraphic and geochronologic units"},"id":2}],"supersededBy":{"id":70198659,"text":"fs20183054 - 2018 - Divisions of geologic time—Major chronostratigraphic and geochronologic units","indexId":"fs20183054","publicationYear":"2018","noYear":false,"title":"Divisions of geologic time—Major chronostratigraphic and geochronologic units"},"lastModifiedDate":"2021-04-21T12:38:01.255763","indexId":"fs20103059","displayToPublicDate":"2010-07-22T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-3059","title":"Divisions of geologic time-major chronostratigraphic and geochronologic units","docAbstract":"Effective communication in the geosciences requires consistent uses of stratigraphic nomenclature, especially divisions of geologic time. A geologic time scale is composed of standard stratigraphic divisions based on rock sequences and is calibrated in years. Over the years, the development of new dating methods and the refinement of previous methods have stimulated revisions to geologic time scales.\r\n\r\nAdvances in stratigraphy and geochronology require that any time scale be periodically updated. Therefore, Divisions of Geologic Time, which shows the major chronostratigraphic (position) and geochronologic (time) units, is intended to be a dynamic resource that will be modified to include accepted changes of unit names and boundary age estimates. This fact sheet is a modification of USGS Fact Sheet 2007-3015 by the U.S. Geological Survey Geologic Names Committee.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/fs20103059","usgsCitation":"U.S. Geological Survey Geologic Names Committee, 2010, Divisions of geologic time-major chronostratigraphic and geochronologic units: U.S. Geological Survey Fact Sheet 2010-3059, 2 p., https://doi.org/10.3133/fs20103059.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":302,"text":"Geologic Names Committee","active":false,"usgs":true}],"links":[{"id":125948,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2010_3059.jpg"},{"id":356913,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20183054","text":"Fact Sheet 2018-3054","linkHelpText":"- Divisions of Geologic Time—Major Chronostratigraphic and Geochronologic Units"},{"id":356914,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20073015","text":"Fact Sheet 2007-3015","linkHelpText":"- Divisions of Geologic Time—Major Chronostratigraphic and Geochronologic Units"},{"id":13928,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2010/3059/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":356955,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2010/3059/pdf/FS10-3059.pdf","text":"Report","size":"237 kB","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a61e4b07f02db635ffd","contributors":{"authors":[{"text":"U.S. Geological Survey Geologic Names Committee","contributorId":127948,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey Geologic Names Committee","id":535032,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":98537,"text":"sir20105138 - 2010 - Predicting S-wave velocities for unconsolidated sediments at low effective pressure","interactions":[],"lastModifiedDate":"2012-02-02T00:15:33","indexId":"sir20105138","displayToPublicDate":"2010-07-22T00:00:00","publicationYear":"2010","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":"2010-5138","title":"Predicting S-wave velocities for unconsolidated sediments at low effective pressure","docAbstract":"Accurate S-wave velocities for shallow sediments are important in performing a reliable elastic inversion for gas hydrate-bearing sediments and in evaluating velocity models for predicting S-wave velocities, but few S-wave velocities are measured at low effective pressure. Predicting S-wave velocities by using conventional methods based on the Biot-Gassmann theory appears to be inaccurate for laboratory-measured velocities at effective pressures less than about 4-5 megapascals (MPa). Measured laboratory and well log velocities show two distinct trends for S-wave velocities with respect to P-wave velocity: one for the S-wave velocity less than about 0.6 kilometer per second (km/s) which approximately corresponds to effective pressure of about 4-5 MPa, and the other for S-wave velocities greater than 0.6 km/s. To accurately predict S-wave velocities at low effective pressure less than about 4-5 MPa, a pressure-dependent parameter that relates the consolidation parameter to shear modulus of the sediments at low effective pressure is proposed. The proposed method in predicting S-wave velocity at low effective pressure worked well for velocities of water-saturated sands measured in the laboratory. However, this method underestimates the well-log S-wave velocities measured in the Gulf of Mexico, whereas the conventional method performs well for the well log velocities. The P-wave velocity dispersion due to fluid in the pore spaces, which is more pronounced at high frequency with low effective pressures less than about 4 MPa, is probably a cause for this discrepancy.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105138","usgsCitation":"Lee, M.W., 2010, Predicting S-wave velocities for unconsolidated sediments at low effective pressure: U.S. Geological Survey Scientific Investigations Report 2010-5138, iv, 13 p., https://doi.org/10.3133/sir20105138.","productDescription":"iv, 13 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":125950,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5138.jpg"},{"id":13927,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5138/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e48b3e4b07f02db53196a","contributors":{"authors":[{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":305678,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":98533,"text":"sir20105144 - 2010 - Distribution of Isotopic and Environmental Tracers in Groundwater, Northern Ada County, Southwestern Idaho","interactions":[],"lastModifiedDate":"2012-03-08T17:16:32","indexId":"sir20105144","displayToPublicDate":"2010-07-21T00:00:00","publicationYear":"2010","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":"2010-5144","title":"Distribution of Isotopic and Environmental Tracers in Groundwater, Northern Ada County, Southwestern Idaho","docAbstract":"Residents of northern Ada County, Idaho, depend on groundwater for domestic and agricultural uses. The population of this area is growing rapidly and groundwater resources must be understood for future water-resource management. The U.S. Geological Survey, in cooperation with the Idaho Department of Water Resources, used a suite of isotopic and environmental tracers to gain a better understanding of groundwater ages, recharge sources, and flowpaths in northern Ada County. Thirteen wells were sampled between September and October 2009 for field parameters, major anions and cations, nutrients, oxygen and hydrogen isotopes, tritium, radiocarbon, chlorofluorocarbons, and dissolved gasses. Well depths ranged from 30 to 580 feet below land surface. Wells were grouped together based on their depth and geographic location into the following four categories: shallow aquifer, intermediate/deep aquifer, Willow Creek aquifer, and Dry Creek aquifer.\r\n\r\nMajor cations and anions indicated calcium-bicarbonate and sodium-bicarbonate water types in the study area. Oxygen and hydrogen isotopes carried an oxygen-18 excess signature, possibly indicating recharge from evaporated sources or water-rock interactions in the subsurface. Chlorofluorocarbons detected modern (post-1940s) recharge in every well sampled; tritium data indicated modern water (post-1951) in seven, predominantly shallow wells. Nutrient concentrations tended to be greater in wells signaling recent recharge based on groundwater age dating, thus confirming the presence of recent recharge in these wells. Corrected radiocarbon results generated estimated residence times from modern to 5,100 years before present. Residence time tended to increase with depth, as confirmed by all three age-tracers. The disagreement among residence times indicates that samples were well-mixed and that the sampled aquifers contain a mixture of young and old recharge. Due to a lack of data, no conclusions about sources of recharge could be drawn from this study.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105144","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Adkins, C.B., and Bartolino, J.R., 2010, Distribution of Isotopic and Environmental Tracers in Groundwater, Northern Ada County, Southwestern Idaho: U.S. Geological Survey Scientific Investigations Report 2010-5144, vi, 30 p. , https://doi.org/10.3133/sir20105144.","productDescription":"vi, 30 p. ","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":201504,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":13923,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5144/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.58333333333333,43.5 ], [ -116.58333333333333,43.833333333333336 ], [ -116,43.833333333333336 ], [ -116,43.5 ], [ -116.58333333333333,43.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a7fe4b07f02db64878a","contributors":{"authors":[{"text":"Adkins, Candice B.","contributorId":34234,"corporation":false,"usgs":true,"family":"Adkins","given":"Candice","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":305656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartolino, James R. 0000-0002-2166-7803 jrbartol@usgs.gov","orcid":"https://orcid.org/0000-0002-2166-7803","contributorId":2548,"corporation":false,"usgs":true,"family":"Bartolino","given":"James","email":"jrbartol@usgs.gov","middleInitial":"R.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305655,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":98529,"text":"sir20105093 - 2010 - Sediment oxygen demand in the Saddle River and Salem River watersheds, New Jersey, July-August 2008","interactions":[],"lastModifiedDate":"2012-03-08T17:16:32","indexId":"sir20105093","displayToPublicDate":"2010-07-20T00:00:00","publicationYear":"2010","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":"2010-5093","title":"Sediment oxygen demand in the Saddle River and Salem River watersheds, New Jersey, July-August 2008","docAbstract":"Many factors, such as river depth and velocity, biochemical oxygen demand, and algal productivity, as well as sediment oxygen demand, can affect the concentration of dissolved oxygen in the water column. Measurements of sediment oxygen demand, in conjunction with those of other water-column water-quality constituents, are useful for quantifying the mechanisms that affect in-stream dissolved-oxygen concentrations. Sediment-oxygen-demand rates are also needed to develop and calibrate a water-quality model being developed for the Saddle River and Salem River Basins in New Jersey to predict dissolved-oxygen concentrations. This report documents the methods used to measure sediment oxygen demand in the Saddle River and Salem River watersheds along with the rates of sediment oxygen demand that were obtained during this investigation.\r\n\r\nIn July and August 2008, sediment oxygen demand was measured in situ in the Saddle River and Salem River watersheds. In the Saddle River Basin, sediment oxygen demand was measured twice at two sites and once at a third location; in the Salem River Basin, sediment oxygen demand was measured three times at two sites and once at a third location.\r\n\r\nIn situ measurements of sediment oxygen demand in the Saddle River and Salem River watersheds ranged from 0.8 to 1.4 g/m2d (grams per square meter per day) and from 0.6 to 7.1 g/m2d at 20 degrees Celsius, respectively. Except at one site in this study, rates of sediment oxygen demand generally were low. The highest rate of sediment oxygen demand measured during this investigation, 7.1 g/m2d, which occurred at Courses Landing in the Salem River Basin, may be attributable to the consumption of oxygen by a large amount of organic matter (54 grams per kilogram as organic carbon) in the streambed sediments or to potential error during data collection. In general, sediment oxygen demand increased with the concentration of organic carbon in the streambed sediments. Repeated measurements made 6 to 7 days apart at the same site locations resulted in similar values.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105093","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Heckathorn, H.A., and Gibs, J., 2010, Sediment oxygen demand in the Saddle River and Salem River watersheds, New Jersey, July-August 2008: U.S. Geological Survey Scientific Investigations Report 2010-5093, x, 10 p., https://doi.org/10.3133/sir20105093.","productDescription":"x, 10 p.","additionalOnlineFiles":"N","temporalStart":"2008-07-01","temporalEnd":"2008-08-31","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":125701,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5093.jpg"},{"id":13919,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5093/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.25,40.833333333333336 ], [ -74.25,41.166666666666664 ], [ -74,41.166666666666664 ], [ -74,40.833333333333336 ], [ -74.25,40.833333333333336 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e632","contributors":{"authors":[{"text":"Heckathorn, Heather A. haheck@usgs.gov","contributorId":1728,"corporation":false,"usgs":true,"family":"Heckathorn","given":"Heather","email":"haheck@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":305647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibs, Jacob jgibs@usgs.gov","contributorId":1729,"corporation":false,"usgs":true,"family":"Gibs","given":"Jacob","email":"jgibs@usgs.gov","affiliations":[],"preferred":true,"id":305648,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":98523,"text":"ofr20101123 - 2010 - Three-dimensional geologic model of the Arbuckle-Simpson aquifer, south-central Oklahoma","interactions":[],"lastModifiedDate":"2012-02-10T00:11:53","indexId":"ofr20101123","displayToPublicDate":"2010-07-17T00:00:00","publicationYear":"2010","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":"2010-1123","title":"Three-dimensional geologic model of the Arbuckle-Simpson aquifer, south-central Oklahoma","docAbstract":"The Arbuckle-Simpson aquifer of south-central Oklahoma encompasses more than 850 square kilometers and is the principal water resource for south-central Oklahoma. Rock units comprising the aquifer are characterized by limestone, dolomite, and sandstones assigned to two lower Paleozoic units: the Arbuckle and Simpson Groups. Also considered to be part of the aquifer is the underlying Cambrian-age Timbered Hills Group that contains limestone and sandstone. The highly faulted and fractured nature of the Arbuckle-Simpson units and the variable thickness (600 to 2,750 meters) increases the complexity in determining the subsurface geologic framework of this aquifer. \r\n\r\nA three-dimensional EarthVision (Trademark) geologic framework model was constructed to quantify the geometric relationships of the rock units of the Arbuckle-Simpson aquifer in the Hunton anticline area. This 3-D EarthVision (Trademark) geologic framework model incorporates 54 faults and four modeled units: basement, Arbuckle-Timbered Hills Group, Simpson Group, and post-Simpson. Primary data used to define the model's 54 faults and four modeled surfaces were obtained from geophysical logs, cores, and cuttings from 126 water and petroleum wells. The 3-D framework model both depicts the volumetric extent of the aquifer and provides the stratigraphic layer thickness and elevation data used to construct a MODFLOW version 2000 regional groundwater-flow model.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101123","collaboration":"Prepared in cooperation with Oklahoma State University and the Oklahoma Water Resources Board","usgsCitation":"Faith, J.R., Blome, C.D., Pantea, M.P., Puckette, J.O., Halihan, T., Osborn, N., Christenson, S., and Pack, S., 2010, Three-dimensional geologic model of the Arbuckle-Simpson aquifer, south-central Oklahoma: U.S. Geological Survey Open-File Report 2010-1123, Report: iii, 26 p.; CD-ROM; Downloads Directory, https://doi.org/10.3133/ofr20101123.","productDescription":"Report: iii, 26 p.; CD-ROM; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":263,"text":"Environmental Change Science Center","active":false,"usgs":true}],"links":[{"id":118487,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1123.jpg"},{"id":13913,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1123/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.33333333333333,34.166666666666664 ], [ -97.33333333333333,34.666666666666664 ], [ -96.33333333333333,34.666666666666664 ], [ -96.33333333333333,34.166666666666664 ], [ -97.33333333333333,34.166666666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a08e4b07f02db5f9d2a","contributors":{"authors":[{"text":"Faith, Jason R.","contributorId":92758,"corporation":false,"usgs":true,"family":"Faith","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":305630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blome, Charles D. 0000-0002-3449-9378 cblome@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-9378","contributorId":1246,"corporation":false,"usgs":true,"family":"Blome","given":"Charles","email":"cblome@usgs.gov","middleInitial":"D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":305624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pantea, Michael P. mpantea@usgs.gov","contributorId":1549,"corporation":false,"usgs":true,"family":"Pantea","given":"Michael","email":"mpantea@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":305625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Puckette, James O.","contributorId":60349,"corporation":false,"usgs":true,"family":"Puckette","given":"James","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":305628,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Halihan, Todd","contributorId":68856,"corporation":false,"usgs":true,"family":"Halihan","given":"Todd","affiliations":[],"preferred":false,"id":305629,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Osborn, Noel","contributorId":102975,"corporation":false,"usgs":true,"family":"Osborn","given":"Noel","affiliations":[],"preferred":false,"id":305631,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Christenson, Scott","contributorId":59128,"corporation":false,"usgs":true,"family":"Christenson","given":"Scott","affiliations":[],"preferred":false,"id":305627,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pack, Skip","contributorId":33809,"corporation":false,"usgs":true,"family":"Pack","given":"Skip","email":"","affiliations":[],"preferred":false,"id":305626,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":98522,"text":"ofr20101068 - 2010 - Practical guidelines to select and scale earthquake records for nonlinear response history analysis of structures","interactions":[],"lastModifiedDate":"2019-07-17T16:34:34","indexId":"ofr20101068","displayToPublicDate":"2010-07-17T00:00:00","publicationYear":"2010","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":"2010-1068","title":"Practical guidelines to select and scale earthquake records for nonlinear response history analysis of structures","docAbstract":" Earthquake engineering practice is increasingly using nonlinear response history analysis (RHA) to demonstrate performance of structures. This rigorous method of analysis requires selection and scaling of ground motions appropriate to design hazard levels. Presented herein is a modal-pushover-based scaling (MPS) method to scale ground motions for use in nonlinear RHA of buildings and bridges. In the MPS method, the ground motions are scaled to match (to a specified tolerance) a target value of the inelastic deformation of the first-'mode' inelastic single-degree-of-freedom (SDF) system whose properties are determined by first-'mode' pushover analysis. Appropriate for first-?mode? dominated structures, this approach is extended for structures with significant contributions of higher modes by considering elastic deformation of second-'mode' SDF system in selecting a subset of the scaled ground motions. Based on results presented for two bridges, covering single- and multi-span 'ordinary standard' bridge types, and six buildings, covering low-, mid-, and tall building types in California, the accuracy and efficiency of the MPS procedure are established and its superiority over the ASCE/SEI 7-05 scaling procedure is demonstrated. \r\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20101068","collaboration":"In Cooperation with the Earthquake Engineering Research Institute","usgsCitation":"Kalkan, E., and Chopra, A.K., 2010, Practical guidelines to select and scale earthquake records for nonlinear response history analysis of structures: U.S. Geological Survey Open-File Report 2010-1068, vi, 118 p.; Notations; Appendix, https://doi.org/10.3133/ofr20101068.","productDescription":"vi, 118 p.; Notations; Appendix","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":118493,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1068.jpg"},{"id":13912,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1068/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad2e4b07f02db681cbe","contributors":{"authors":[{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":305622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chopra, Anil K.","contributorId":79202,"corporation":false,"usgs":true,"family":"Chopra","given":"Anil","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":305623,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":98518,"text":"tm11C4 - 2010 - Land-Use Portfolio Modeler, Version 1.0","interactions":[],"lastModifiedDate":"2012-02-02T00:14:54","indexId":"tm11C4","displayToPublicDate":"2010-07-17T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"11-C4","title":"Land-Use Portfolio Modeler, Version 1.0","docAbstract":"Natural hazards pose significant threats to the public safety and economic health of many communities throughout the world. Community leaders and decision-makers continually face the challenges of planning and allocating limited resources to invest in protecting their communities against catastrophic losses from natural-hazard events. Public efforts to assess community vulnerability and encourage loss-reduction measures through mitigation often focused on either aggregating site-specific estimates or adopting standards based upon broad assumptions about regional risks. The site-specific method usually provided the most accurate estimates, but was prohibitively expensive, whereas regional risk assessments were often too general to be of practical use. Policy makers lacked a systematic and quantitative method for conducting a regional-scale risk assessment of natural hazards. In response, Bernknopf and others developed the portfolio model, an intermediate-scale approach to assessing natural-hazard risks and mitigation policy alternatives. \r\n\r\nThe basis for the portfolio-model approach was inspired by financial portfolio theory, which prescribes a method of optimizing return on investment while reducing risk by diversifying investments in different security types. In this context, a security type represents a unique combination of features and hazard-risk level, while financial return is defined as the reduction in losses resulting from an investment in mitigation of chosen securities. Features are selected for mitigation and are modeled like investment portfolios. Earth-science and economic data for the features are combined and processed in order to analyze each of the portfolios, which are then used to evaluate the benefits of mitigating the risk in selected locations. Ultimately, the decision maker seeks to choose a portfolio representing a mitigation policy that maximizes the expected return-on-investment, while minimizing the uncertainty associated with that return-on-investment. \r\n\r\nThe portfolio model, now known as the Land-Use Portfolio Model (LUPM), provided the framework for the development of the Land-Use Portfolio Modeler, Version 1.0 software (LUPM v1.0). The software provides a geographic information system (GIS)-based modeling tool for evaluating alternative risk-reduction mitigation strategies for specific natural-hazard events. The modeler uses information about a specific natural-hazard event and the features exposed to that event within the targeted study region to derive a measure of a given mitigation strategy`s effectiveness. Harnessing the spatial capabilities of a GIS enables the tool to provide a rich, interactive mapping environment in which users can create, analyze, visualize, and compare different\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/tm11C4","usgsCitation":"Taketa, R., and Hong, M., 2010, Land-Use Portfolio Modeler, Version 1.0: U.S. Geological Survey Techniques and Methods 11-C4, vi, 44 p.; Appendices, https://doi.org/10.3133/tm11C4.","productDescription":"vi, 44 p.; Appendices","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":118495,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_11_c4.gif"},{"id":13908,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/tm11c4/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6adf28","contributors":{"authors":[{"text":"Taketa, Richard","contributorId":25250,"corporation":false,"usgs":true,"family":"Taketa","given":"Richard","affiliations":[],"preferred":false,"id":305615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hong, Makiko","contributorId":31495,"corporation":false,"usgs":true,"family":"Hong","given":"Makiko","email":"","affiliations":[],"preferred":false,"id":305616,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":98521,"text":"ofr20101079 - 2010 - Hawaiian Volcano Observatory seismic data, January to March 2009","interactions":[],"lastModifiedDate":"2016-08-29T19:13:38","indexId":"ofr20101079","displayToPublicDate":"2010-07-17T00:00:00","publicationYear":"2010","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":"2010-1079","title":"Hawaiian Volcano Observatory seismic data, January to March 2009","docAbstract":"<p>This U.S. Geological Survey (USGS), Hawaiian Volcano Observatory (HVO) summary presents seismic data gathered during January&ndash;March 2009. The seismic summary offers earthquake hypocenters without interpretation as a source of preliminary data and is complete in that most data for events of M&ge;1.5 are included. All latitude and longitude references in this report are stated in Old Hawaiian Datum.</p>\n<p>The HVO summaries have been published in various forms since 1956. Summaries prior to 1974 were issued quarterly, but cost, convenience of preparation and distribution, and the large quantities of data necessitated an annual publication, beginning with Summary 74 for the year 1974. Since 2004, summaries have been identified simply by year, rather than by summary number.</p>\n<p>Summaries originally issued as administrative reports were republished in 2007 as Open-File Reports. All the summaries since 1956 are available at<a href=\"http://pubs.usgs.gov/of/2007/1316-1345/\" target=\"_blank\">http://pubs.usgs.gov/of/2007/1316-1345/</a>&nbsp;(last accessed 02/24/2010). In January 1986, HVO adopted CUSP (<span>C</span>alifornia Institute of Technology&nbsp;<span>U</span>SGS&nbsp;<span>S</span>eismic<span>P</span>rocessing). Summary 86, available at<a href=\"http://pubs.er.usgs.gov/usgspubs/ofr/ofr92301\" target=\"_blank\">http://pubs.er.usgs.gov/usgspubs/ofr/ofr92301</a>&nbsp;(last accessed 02/24/2010), includes a description of the seismic instrumentation, calibration, and processing used in recent years. The present summary includes background information about the seismic network to provide the end user with an understanding of the processing parameters and how the data were gathered.</p>\n<p>Earthworm software, documentation available at&nbsp;<a href=\"http://folkworm.ceri.memphis.edu/ew-doc/\" target=\"_blank\">http://folkworm.ceri.memphis.edu/ew-doc/</a>&nbsp;(last accessed 02/24/2010), was first installed at HVO in 1999 as part of an upgrade to tsunami warning capabilities in the Pacific region. This improved and expanded data exchange with the Pacific Tsunami Warning Center in Ewa Beach, Oahu, that included not only seismic waveforms, but also parametric earthquake data. Although Earthworm does included modules for earthquake triggering and earthquake location, this software was never used to generate catalog hypocenter locations at HVO.</p>\n<p>During 2009, HVO migrated from CUSP to seismic processing software developed by the&nbsp;<span>C</span>alifornia&nbsp;<span>I</span>ntegrated&nbsp;<span>S</span>eismic<span>N</span>etwork or CISN. This software is now referred to as AQMS, for&nbsp;<span>A</span>dvanced National Seismic System&nbsp;<span>Q</span>uake&nbsp;<span>M</span>anagement<span>S</span>ystem. Summary data for this year will be presented in two reports; the first report includes earthquakes processed on the CUSP platform for January&ndash;March; earthquakes for the last three quarters, processed on the AQMS platform, will be published in a separate summary with a description of AQMS production parameters.</p>\n<p>A report by Klein and Koyanagi (USGS Open-File Report 80-302, 1980) tabulates instrumentation, calibration, and recording history of each seismic station in the network. It is designed as a reference for users of seismograms and phase data and includes and augments the information in the station table in this summary.</p>\n<p>Figures 11&ndash;14 are maps showing computer-located hypocenters. The maps were generated using the&nbsp;<span>G</span>eneric&nbsp;<span>M</span>apping&nbsp;<span>T</span>ools (GMT), found at&nbsp;<a href=\"http://gmt.soest.hawaii.edu/\" target=\"_blank\">http://gmt.soest.hawaii.edu/</a>&nbsp;(last accessed 01/22/2010), in place of traditional QPLOT maps.</p>","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101079","usgsCitation":"Nakata, J.S., and Okubo, P.G., 2010, Hawaiian Volcano Observatory seismic data, January to March 2009: U.S. Geological Survey Open-File Report 2010-1079, iii, 50 p., https://doi.org/10.3133/ofr20101079.","productDescription":"iii, 50 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":13911,"rank":100,"type":{"id":15,"text":"Index 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20.059801254410598\n            ],\n            [\n              -155.43457031249997,\n              20.0933371611593\n            ],\n            [\n              -155.4949951171875,\n              20.111391984160917\n            ],\n            [\n              -155.55679321289062,\n              20.128155311797183\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e95e","contributors":{"authors":[{"text":"Nakata, Jennifer S.","contributorId":18364,"corporation":false,"usgs":true,"family":"Nakata","given":"Jennifer","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":305621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Okubo, Paul G. 0000-0002-0381-6051 pokubo@usgs.gov","orcid":"https://orcid.org/0000-0002-0381-6051","contributorId":2730,"corporation":false,"usgs":true,"family":"Okubo","given":"Paul","email":"pokubo@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":305620,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":98519,"text":"sim3116 - 2010 - Geologic map of the Lakshmi Planum quadrangle (V-7), Venus","interactions":[],"lastModifiedDate":"2019-12-30T16:09:33","indexId":"sim3116","displayToPublicDate":"2010-07-17T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3116","title":"Geologic map of the Lakshmi Planum quadrangle (V-7), Venus","docAbstract":"The Lakshmi Planum quadrangle is in the northern hemisphere of Venus and extends from lat 50 degrees to 75 degrees N., and from long 300 degrees to 360 degrees E. The elevated volcanic plateau of Lakshmi Planum, which represents a very specific and unique class of highlands on Venus, dominates the northern half of the quadrangle. The surface of the planum stands 3-4 km above mean planetary radius and the plateau is surrounded by the highest Venusian mountain ranges, 7-10 km high. \r\n\r\nBefore the Magellan mission, the geology of the Lakshmi Planum quadrangle was known on the basis of topographic data acquired by the Pioneer-Venus and Venera-15/16 altimeter and radar images received by the Arecibo telescope and Venera-15/16 spacecraft. These data showed unique topographic and morphologic structures of the mountain belts, which have no counterparts elsewhere on Venus, and the interior volcanic plateau with two large and low volcanic centers and large blocks of tessera-like terrain. From the outside, Lakshmi Planum is outlined by a zone of complexly deformed terrains that occur on the regional outer slope of Lakshmi. Vast low-lying plains surround this zone. After acquisition of the Venera-15/16 data, two classes of hypotheses were formulated to explain the unique structure of Lakshmi Planum and its surrounding. The first proposed that the western portion of Ishtar Terra, dominated by Lakshmi Planum, was a site of large-scale upwelling while the alternative hypothesis considered this region as a site of large-scale downwelling and underthrusting. \r\n\r\nEarly Magellan results showed important details of the general geology of this area displayed in the Venera-15/16 images. Swarms of extensional structures and massifs of tesserae populate the southern slope of Lakshmi. The zone of fractures and grabens form a giant arc thousands of kilometers long and hundreds of kilometers wide around the southern flank of Lakshmi Planum. From the north, the deformational zones consist mostly of contractional structures such as ridges. Corona and corona-like structures are not typical features of this zone but occur within separate branches of extensional structures oriented radial to the edge of Lakshmi. The southeastern edge of Lakshmi appears to be the source of large volcanic flows that extend to the south toward the lowland areas of Sedna Planitia. Colette and Sacajawea Paterae in the interior of Lakshmi are low volcanic centers with very deep central depressions. Lava flows sourced by Colette and Sacajawea form distinctive radial patterns around these volcanoes. Magellan gravity data show that the northern and northeastern portions of the quadrangle, which correspond to Lakshmi Planum, represent a significant geoid anomaly with the peak value of about 90 m over Maxwell Montes at the eastern edge of the map area. Maxwell is characterized also by very high vertical gravity acceleration values (as much as 268 mGal). The lowland of Sedna Planitia to the south of Lakshmi has mostly negative geoid values (down to -40 m). \r\n\r\nThe key geological structure of the quadrangle is Lakshmi Planum, the mode of formation of which is still a major unresolved problem. The topographic configuration, gravity signature, and pattern of deformation inside Lakshmi and along its boundaries make this feature unique on Venus. Thus, geological mapping of this region allows addressing several important questions that should help to put some constraints on the existing models of Lakshmi formation. What is the sequence of events in the formation and evolution of such a unique morphologic and topographic feature? What are the characteristics of the marginal areas of Lakshmi: the compact mountain belts and broad zones of deformation in the transition zone between Lakshmi and surrounding lowlands? How do the units in Lakshmi Planum quadrangle compare with the units mapped in neighboring and distant regions of Venus and what information do they provide concerning models for Venus","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sim3116","collaboration":"Prepared for the National Aeronautics and Space Administration\r\n","usgsCitation":"Ivanov, M.A., and Head, J.W., 2010, Geologic map of the Lakshmi Planum quadrangle (V-7), Venus: U.S. Geological Survey Scientific Investigations Map 3116, HTML, https://doi.org/10.3133/sim3116.","productDescription":"HTML","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":13909,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3116/","linkFileType":{"id":5,"text":"html"}},{"id":118496,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3116.jpg"}],"scale":"5000000","projection":"Lambert","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afce4b07f02db69660f","contributors":{"authors":[{"text":"Ivanov, Mikhail A.","contributorId":25245,"corporation":false,"usgs":true,"family":"Ivanov","given":"Mikhail","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":305617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Head, James W. III","contributorId":102954,"corporation":false,"usgs":true,"family":"Head","given":"James","suffix":"III","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":305618,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047032,"text":"dds49009 - 2010 - Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Level 3 Ecoregions","interactions":[],"lastModifiedDate":"2013-11-25T16:00:42","indexId":"dds49009","displayToPublicDate":"2010-07-15T14:01:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"490-09","title":"Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Level 3 Ecoregions","docAbstract":"This data set represents the estimated area of level 3 ecological landscape regions (ecoregions), as defined by Omernik (1987), compiled for every catchment of NHDPlus for the conterminous United States. The source data set is Level III Ecoregions of the Continental United States (U.S. Environmental Protection Agency, 2003). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as \"the New England Method.\" This technique involves \"burning in\" the 1:100,000-scale NHD and when available building \"walls\" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's  Major River Basins (MRBs, Crawford and others, 2006).  MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2.  MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6.  MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9.  MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper.  MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12.  MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16.  MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17.  MRB8, covering California River basins, contains NHDPlus Production Unit 18.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49009","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Level 3 Ecoregions: U.S. Geological Survey Data Series 490-09, Datatset, https://doi.org/10.3133/dds49009.","productDescription":"Datatset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274993,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/nhd_eco3.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ 65.327751,51.657387 ], [ 65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e519e4e4b069f8d27cca8e","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480904,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70237833,"text":"70237833 - 2010 - A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska","interactions":[],"lastModifiedDate":"2022-10-26T11:47:36.243469","indexId":"70237833","displayToPublicDate":"2010-07-15T06:45:34","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"aep-abstract-id11\" class=\"abstract author\"><div id=\"aep-abstract-sec-id12\"><p>Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (&gt;&nbsp;0.5&nbsp;m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30&nbsp;m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250&nbsp;m and 500&nbsp;m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275&nbsp;m spatial resolution for a 1067&nbsp;km<sup>2</sup><span>&nbsp;</span>study area in Arctic Alaska. The study area is centered at 69&nbsp;°N, ranges in elevation from 130 to 770&nbsp;m, is composed primarily of rolling topography with gentle slopes less than 10°, and is free of glaciers and perennial snow cover. Shrubs &gt;&nbsp;0.5&nbsp;m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from<span>&nbsp;</span><i>in situ</i><span>&nbsp;</span>shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250&nbsp;m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000–2009.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2010.01.012","usgsCitation":"Selkowitz, D.J., 2010, A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska: Remote Sensing of Environment, v. 114, no. 7, p. 1338-1352, https://doi.org/10.1016/j.rse.2010.01.012.","productDescription":"15 p.","startPage":"1338","endPage":"1352","ipdsId":"IP-014402","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":408739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -141.38130176598017,\n              68.19430047782723\n            ],\n            [\n              -141.38130176598017,\n              72.2825482136995\n            ],\n            [\n              -161.95663358999144,\n              72.2825482136995\n            ],\n            [\n              -161.95663358999144,\n              68.19430047782723\n            ],\n            [\n              -141.38130176598017,\n              68.19430047782723\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"114","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Selkowitz, David J. 0000-0003-0824-7051 dselkowitz@usgs.gov","orcid":"https://orcid.org/0000-0003-0824-7051","contributorId":3259,"corporation":false,"usgs":true,"family":"Selkowitz","given":"David","email":"dselkowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":855817,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":98514,"text":"fs20103012 - 2010 - Impacts and predictions of coastal change during hurricanes","interactions":[],"lastModifiedDate":"2012-02-02T00:14:35","indexId":"fs20103012","displayToPublicDate":"2010-07-15T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-3012","title":"Impacts and predictions of coastal change during hurricanes","docAbstract":"Beaches serve as a natural barrier between the ocean and inland communities, ecosystems, and resources. These dynamic environments move and change in response to winds, waves, and currents. During a powerful hurricane, changes to beaches can be large, and the results are sometimes catastrophic. Lives are lost, communities are destroyed, and millions of dollars are spent on rebuilding. There is a clear need to identify areas of our coastline that are likely to experience extreme and devastating erosion during a hurricane. It is also important to determine risk levels associated with development in areas where the land shifts and moves with each landfalling storm. The U.S. Geological Survey (USGS) provides scientific support for hurricane planning and response. Using observations of beach changes and models of waves and storm surge, we are predicting how the coast will respond to hurricanes and identifying areas vulnerable to extreme coastal changes. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20103012","usgsCitation":"Stockdon, H., and Sallenger, A., 2010, Impacts and predictions of coastal change during hurricanes: U.S. Geological Survey Fact Sheet 2010-3012, 2 p., https://doi.org/10.3133/fs20103012.","productDescription":"2 p.","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":125843,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2010_3012.jpg"},{"id":13905,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2010/3012/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e89f","contributors":{"authors":[{"text":"Stockdon, Hilary","contributorId":100090,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","affiliations":[],"preferred":false,"id":305598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sallenger, Abby","contributorId":9363,"corporation":false,"usgs":true,"family":"Sallenger","given":"Abby","email":"","affiliations":[],"preferred":false,"id":305597,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70158952,"text":"70158952 - 2010 - Carbon dioxide (CO<i>2</i>) sequestration in deep saline aquifers and formations: Chapter 3","interactions":[],"lastModifiedDate":"2017-04-24T11:32:25","indexId":"70158952","displayToPublicDate":"2010-07-15T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Carbon dioxide (CO<i>2</i>) sequestration in deep saline aquifers and formations: Chapter 3","docAbstract":"<p><span>Carbon dioxide (CO</span><sub>2</sub><span>) capture and sequestration in geologic media is one among many emerging strategies to reduce atmospheric emissions of anthropogenic CO</span><sub>2</sub><span>. This chapter looks at the potential of deep saline aquifers – based on their capacity and close proximity to large point sources of CO</span><sub>2</sub><span> – as repositories for the geologic sequestration of CO</span><sub>2</sub><span>. The petrochemical characteristics which impact on the suitability of saline aquifers for CO</span><sub>2</sub><span> sequestration and the role of coupled geochemical transport models and numerical tools in evaluating site feasibility are also examined. The full-scale commercial CO</span><sub>2</sub><span> sequestration project at Sleipner is described together with ongoing pilot and demonstration projects.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Developments and Innovation in Carbon Dioxide (Co2) Capture and Storage Technology: Carbon Dioxide (Co2) Storage and Utilisation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Woodhead Publishing Limited","publisherLocation":"Oxford","doi":"10.1533/9781845699581.1.57","usgsCitation":"Rosenbauer, R.J., and Thomas, B., 2010, Carbon dioxide (CO<i>2</i>) sequestration in deep saline aquifers and formations: Chapter 3, chap. <i>of</i> Developments and Innovation in Carbon Dioxide (Co2) Capture and Storage Technology: Carbon Dioxide (Co2) Storage and Utilisation, v. 2, p. 57-103, https://doi.org/10.1533/9781845699581.1.57.","productDescription":"47 p.","startPage":"57","endPage":"103","ipdsId":"IP-015053","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":340179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0ea7e4b006455f2d61fc","contributors":{"authors":[{"text":"Rosenbauer, Robert J. brosenbauer@usgs.gov","contributorId":204,"corporation":false,"usgs":true,"family":"Rosenbauer","given":"Robert","email":"brosenbauer@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":577028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Burt","contributorId":95454,"corporation":false,"usgs":true,"family":"Thomas","given":"Burt","affiliations":[],"preferred":false,"id":577029,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70190352,"text":"70190352 - 2010 - Sediment transport and deposition on a river-dominated tidal flat: An idealized model study","interactions":[],"lastModifiedDate":"2017-08-28T17:06:08","indexId":"70190352","displayToPublicDate":"2010-07-15T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Sediment transport and deposition on a river-dominated tidal flat: An idealized model study","docAbstract":"<p><span>A 3-D hydrodynamic model is used to investigate how different size classes of river-derived sediment are transported, exported and trapped on an idealized, river-dominated tidal flat. The model is composed of a river channel flanked by sloping tidal flats, a configuration motivated by the intertidal region of the Skagit River mouth in Washington State, United States. It is forced by mixed tides and a pulse of freshwater and sediment with various settling velocities. In this system, the river not only influences stratification but also contributes a significant cross-shore transport. As a result, the bottom stress is strongly ebb-dominated in the channel because of the seaward advance of strong river flow as the tidal flats drain during ebbs. Sediment deposition patterns and mass budgets are sensitive to settling velocity. The lateral sediment spreading scales with an advective distance (settling time multiplied by lateral flow speed), thereby confining the fast settling sediment classes in the channel. Residual sediment transport is landward on the flats, because of settling lag, but is strongly seaward in the channel. The seaward transport mainly occurs during big ebbs and is controlled by a length scale ratio&nbsp;</span><i>L</i><sub><i>d</i></sub><span>/</span><i>X</i><sub><i>WL</i></sub><span>, where<span>&nbsp;</span></span><i>L</i><sub><i>d</i></sub><span><span>&nbsp;</span>is a cross-shore advective distance (settling time multiplied by river outlet velocity), and<span>&nbsp;</span></span><i>X</i><sub><i>WL</i></sub><span><span>&nbsp;</span>is the immersed cross-shore length of the intertidal zone. Sediment trapping requires<span>&nbsp;</span></span><i>L</i><sub><i>d</i></sub><span>/</span><i>X</i><sub><i>WL</i></sub><span><span>&nbsp;</span>&lt; 1, leading to more trapping for the faster settling classes. Sensitivity studies show that including stratification and reducing tidal range both favor sediment trapping, whereas varying channel geometries and asymmetry of tides has relatively small impacts. Implications of the modeling results on the south Skagit intertidal region are discussed.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2010JC006248","usgsCitation":"Sherwood, C.R., Chen, S., Geyer, W.R., and Ralston, D.K., 2010, Sediment transport and deposition on a river-dominated tidal flat: An idealized model study: Journal of Geophysical Research C: Oceans, v. 115, no. C10, 16 p., https://doi.org/10.1029/2010JC006248.","productDescription":"16 p.","ipdsId":"IP-020709","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":475685,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2010jc006248","text":"Publisher Index Page"},{"id":345222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"C10","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2010-10-16","publicationStatus":"PW","scienceBaseUri":"59a52bd6e4b0fa5ae7c74846","contributors":{"authors":[{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":708644,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Shih-Nan","contributorId":195907,"corporation":false,"usgs":false,"family":"Chen","given":"Shih-Nan","email":"","affiliations":[],"preferred":false,"id":708645,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Geyer, W. Rockwell","contributorId":195908,"corporation":false,"usgs":false,"family":"Geyer","given":"W.","email":"","middleInitial":"Rockwell","affiliations":[],"preferred":false,"id":708646,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ralston, David K. 0000-0002-0774-3101","orcid":"https://orcid.org/0000-0002-0774-3101","contributorId":195909,"corporation":false,"usgs":false,"family":"Ralston","given":"David","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":708647,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
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