{"pageNumber":"835","pageRowStart":"20850","pageSize":"25","recordCount":40783,"records":[{"id":70042305,"text":"70042305 - 2009 - Importance of light, temperature, zooplankton, and fish in predicting the nighttime vertical distribution of Mysis diluviana","interactions":[],"lastModifiedDate":"2022-09-05T17:02:28.814924","indexId":"70042305","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":860,"text":"Aquatic Biology","active":true,"publicationSubtype":{"id":10}},"title":"Importance of light, temperature, zooplankton, and fish in predicting the nighttime vertical distribution of Mysis diluviana","docAbstract":"<p><span>The opossum shrimp&nbsp;</span><i>Mysis diluviana<span>&nbsp;</span></i><span>(formerly&nbsp;</span><i>M. relicta</i><span>) performs large amplitude diel vertical migrations in Lake Ontario and its nighttime distribution is influenced by temperature, light and the distribution of its predators and prey. At one location in southeastern Lake Ontario, we measured the vertical distribution of mysids, mysid predators (i.e. planktivorous fishes) and mysid prey (i.e. zooplankton), in addition to light and temperature, on 8 occasions from May to September, 2004 and 2005. We use these data to test 3 different predictive models of mysid habitat selection, based on: (1) laboratory-derived responses of mysids to different light and temperature gradients in the absence of predator or prey cues; (2) growth rate of mysids, as estimated with a mysid bioenergetics model, given known prey densities and temperatures at different depths in the water column; (3) ratio of growth rates (</span><i>g</i><span>) and mortality risk (μ) associated with the distribution of predatory fishes. The model based on light and temperature preferences was a better predictor of mysid vertical distribution than the models based on growth rate and&nbsp;</span><i>g</i><span>:μ on all 8 occasions. Although mysid temperature and light preferences probably evolved as mechanisms to reduce predation while increasing foraging intake, the response to temperature and light alone predicts mysid vertical distribution across seasons in Lake Ontario.</span></p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/ab00161","usgsCitation":"Boscarino, B., Rudstam, L.G., Ellenberger, S., and O’Gorman, R., 2009, Importance of light, temperature, zooplankton, and fish in predicting the nighttime vertical distribution of Mysis diluviana: Aquatic Biology, v. 5, p. 263-279, https://doi.org/10.3354/ab00161.","productDescription":"17 p.","startPage":"263","endPage":"279","ipdsId":"IP-011081","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":476014,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/ab00161","text":"Publisher Index 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G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":471237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellenberger, S.A.","contributorId":221950,"corporation":false,"usgs":false,"family":"Ellenberger","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":813101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Gorman, Robert rogorman@usgs.gov","contributorId":3451,"corporation":false,"usgs":true,"family":"O’Gorman","given":"Robert","email":"rogorman@usgs.gov","affiliations":[],"preferred":true,"id":813102,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":98085,"text":"sir20095257 - 2009 - Geomorphology and river dynamics of the lower Copper River, Alaska","interactions":[],"lastModifiedDate":"2018-04-23T10:30:15","indexId":"sir20095257","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","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":"2009-5257","title":"Geomorphology and river dynamics of the lower Copper River, Alaska","docAbstract":"<p>Located in south-central Alaska, the Copper River drains an area of more than 24,000 square miles. The average annual flow of the river near its mouth is 63,600 cubic feet per second, but is highly variable between winter and summer. In the winter, flow averages approximately 11,700 cubic feet per second, and in the summer, due to snowmelt, rainfall, and glacial melt, flow averages approximately 113,000 cubic feet per second, an order of magnitude higher. About 15 miles upstream of its mouth, the Copper River flows past the face of Childs Glacier and enters a large, broad, delta. The Copper River Highway traverses this flood plain, and in 2008, 11 bridges were located along this section of the highway. The bridges cross several parts of the Copper River and in recent years, the changing course of the river has seriously damaged some of the bridges.</p><p>Analysis of aerial photography from 1991, 1996, 2002, 2006, and 2007 indicates the eastward migration of a channel of the Copper River that has resulted in damage to the Copper River Highway near Mile 43.5. Migration of another channel in the flood plain has resulted in damage to the approach of Bridge 339. As a verification of channel change, flow measurements were made at bridges along the Copper River Highway in 2005–07. Analysis of the flow measurements indicate that the total flow of the Copper River has shifted from approximately 50 percent passing through the bridges at Mile 27, near the western edge of the flood plain, and 50 percent passing through the bridges at Mile 36–37 to approximately 5 percent passing through the bridges at Mile 27 and 95 percent through the bridges at Mile 36–37 during average flow periods.</p><p>The U.S. Geological Survey’s Multi-Dimensional Surface-Water Modeling System was used to simulate water-surface elevation and velocity, and to compute bed shear stress at two areas where the Copper River is affecting the Copper River Highway. After calibration, the model was used to examine the effects that betterments, such as guide banks or bridge extensions, would have on flow conditions and to provide sound conceptual information that could help decide if a proposed betterment will work or determine potential problems that need to be addressed for a particular betterment. The ability of the model to simulate these hydraulic conditions was constrained by the accuracy and level of channel geometry detail, which is constantly changing in the lower Copper River.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20095257","collaboration":"Prepared in cooperation with the Alaska Department of Transportation and Public Facilities under Project COPPER RIVER HWY MP 27-49 HYDROLOGY STUDY - AKSAS 61959","usgsCitation":"Brabets, T.P., and Conaway, J.S., 2009, Geomorphology and river dynamics of the lower Copper River, Alaska: U.S. Geological Survey Scientific Investigations Report 2009-5257, vi, 43 p., https://doi.org/10.3133/sir20095257.","productDescription":"vi, 43 p.","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":125874,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5257.jpg"},{"id":353645,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2009/5257/pdf/sir20095257.pdf","text":"Report","size":"6.8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":13319,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5257/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -148,60 ], [ -148,64 ], [ -140,64 ], [ -140,60 ], [ -148,60 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac9e4b07f02db67c4c1","contributors":{"authors":[{"text":"Brabets, Timothy P. tbrabets@usgs.gov","contributorId":2087,"corporation":false,"usgs":true,"family":"Brabets","given":"Timothy","email":"tbrabets@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":304099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conaway, Jeffrey S. 0000-0002-3036-592X jconaway@usgs.gov","orcid":"https://orcid.org/0000-0002-3036-592X","contributorId":2026,"corporation":false,"usgs":true,"family":"Conaway","given":"Jeffrey","email":"jconaway@usgs.gov","middleInitial":"S.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":304100,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70187155,"text":"70187155 - 2009 - Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000","interactions":[],"lastModifiedDate":"2017-05-23T14:09:52","indexId":"70187155","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000","docAbstract":"<p>Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon storage and loss. Here we use the General Ensemble Biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China's upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sinks/source pattern showed a high degree of spatial heterogeneity, Carbon sinks were associated with forest areas without disturbances, whereas carbon Sources were primarily caused by stand-replacing disturbances. This highlights the importance of land-use history in determining the regional carbon sinks/source pattern.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"An integrated assessment of China’s ecological restoration programs","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","isbn":"978-90-481-2655-2","usgsCitation":"Zhao, S., Liu, S., Yin, R., Li, Z., Deng, Y., Tan, K., Deng, X., Rothstein, D., and Qi, J., 2009, Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000, chap. <i>of</i> An integrated assessment of China’s ecological restoration programs, p. 99-112.","productDescription":"14 p.","startPage":"99","endPage":"112","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":340268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340266,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.springer.com/us/book/9789048126545"}],"country":"China","otherGeospatial":"Jinsha watershed, Yangtze River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 97.36,21.62 ], [ 97.36,32.38 ], [ 104.08,32.38 ], [ 104.08,21.62 ], [ 97.36,21.62 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5900608ee4b0e85db3a5df86","contributors":{"editors":[{"text":"Yin, Runsheng","contributorId":150057,"corporation":false,"usgs":false,"family":"Yin","given":"Runsheng","email":"","affiliations":[{"id":17896,"text":"State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, China","active":true,"usgs":false}],"preferred":false,"id":692821,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Zhao, Shuqing","contributorId":9152,"corporation":false,"usgs":true,"family":"Zhao","given":"Shuqing","email":"","affiliations":[],"preferred":false,"id":692817,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":692818,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yin, Runsheng","contributorId":150057,"corporation":false,"usgs":false,"family":"Yin","given":"Runsheng","email":"","affiliations":[{"id":17896,"text":"State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, China","active":true,"usgs":false}],"preferred":false,"id":692819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Zhengpeng","contributorId":80812,"corporation":false,"usgs":true,"family":"Li","given":"Zhengpeng","affiliations":[],"preferred":false,"id":692820,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deng, Yulin","contributorId":191348,"corporation":false,"usgs":false,"family":"Deng","given":"Yulin","email":"","affiliations":[],"preferred":false,"id":692822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tan, Kun","contributorId":191349,"corporation":false,"usgs":false,"family":"Tan","given":"Kun","email":"","affiliations":[],"preferred":false,"id":692823,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Deng, Xiangzheng","contributorId":191350,"corporation":false,"usgs":false,"family":"Deng","given":"Xiangzheng","email":"","affiliations":[],"preferred":false,"id":692824,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rothstein, David","contributorId":191351,"corporation":false,"usgs":false,"family":"Rothstein","given":"David","email":"","affiliations":[],"preferred":false,"id":692825,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Qi, Jiaguo","contributorId":191352,"corporation":false,"usgs":false,"family":"Qi","given":"Jiaguo","email":"","affiliations":[],"preferred":false,"id":692826,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70034027,"text":"70034027 - 2009 - Predicting the natural flow regime: Models for assessing hydrological alteration in streams","interactions":[],"lastModifiedDate":"2017-10-25T12:51:49","indexId":"70034027","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the natural flow regime: Models for assessing hydrological alteration in streams","docAbstract":"Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national- and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also demonstrate how the models can be applied to predict expected natural flow characteristics at ungaged sites. ?? 2009 John Wiley & Sons, Ltd.","language":"English","publisher":"Wiley","doi":"10.1002/rra.1247","issn":"15351459","usgsCitation":"Carlisle, D., Falcone, J., Wolock, D., Meador, M.R., and Norris, R., 2009, Predicting the natural flow regime: Models for assessing hydrological alteration in streams: River Research and Applications, v. 26, no. 2, p. 118-136, https://doi.org/10.1002/rra.1247.","productDescription":"19 p.","startPage":"118","endPage":"136","ipdsId":"IP-004184","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":244636,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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R.","contributorId":74400,"corporation":false,"usgs":true,"family":"Meador","given":"M.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":443722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Norris, R.H.","contributorId":32016,"corporation":false,"usgs":true,"family":"Norris","given":"R.H.","email":"","affiliations":[],"preferred":false,"id":443720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70043324,"text":"70043324 - 2009 - A simple technique for continuous measurement of time-variable gas transfer in surface waters","interactions":[],"lastModifiedDate":"2018-10-03T10:36:42","indexId":"70043324","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2622,"text":"Limnology and Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"A simple technique for continuous measurement of time-variable gas transfer in surface waters","docAbstract":"Mass balance models of dissolved gases in streams, lakes, and rivers serve as the basis for estimating wholeecosystem rates for various biogeochemical processes. Rates of gas exchange between water and the atmosphere are important and error-prone components of these models. Here we present a simple and efficient modification of the SF6 gas tracer approach that can be used concurrently while collecting other dissolved gas samples for dissolved gas mass balance studies in streams. It consists of continuously metering SF6-saturated water directly into the stream at a low rate of flow. This approach has advantages over pulse injection of aqueous solutions or bubbling large amounts of SF6 into the stream. By adding the SF6 as a saturated solution, we minimize the possibility that other dissolved gas measurements are affected by sparging and/or bubble injecta. Because the SF6 is added continuously we have a record of changing gas transfer velocity (GTV) that is contemporaneous with the sampling of other nonconservative ambient dissolved gases. Over a single diel period, a 30% variation in GTV was observed in a second-order stream (Sugar Creek, Indiana, USA). The changing GTV could be attributed in part to changes in temperature and windspeed that occurred on hourly to diel timescales.","language":"English","publisher":"ASLO","doi":"10.4319/lom.2009.7.185","usgsCitation":"Tobias, C., Bohlke, J., Harvey, J.W., and Busenberg, E., 2009, A simple technique for continuous measurement of time-variable gas transfer in surface waters: Limnology and Oceanography: Methods, v. 7, p. 185-195, https://doi.org/10.4319/lom.2009.7.185.","productDescription":"11 p.","startPage":"185","endPage":"195","ipdsId":"IP-004332","costCenters":[{"id":146,"text":"Branch of Regional Research-Eastern Region","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":270737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"7","noUsgsAuthors":false,"publicationDate":"2009-02-12","publicationStatus":"PW","scienceBaseUri":"51653860e4b077fa94dadf5b","contributors":{"authors":[{"text":"Tobias, Craig R.","contributorId":23410,"corporation":false,"usgs":false,"family":"Tobias","given":"Craig R.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":473392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, John Karl 0000-0001-5693-6455","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":84641,"corporation":false,"usgs":true,"family":"Bohlke","given":"John Karl","affiliations":[],"preferred":false,"id":473393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":473390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Busenberg, Eurybiades ebusenbe@usgs.gov","contributorId":2271,"corporation":false,"usgs":true,"family":"Busenberg","given":"Eurybiades","email":"ebusenbe@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":473391,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043368,"text":"70043368 - 2009 - Geochemical Evolution of Great Salt Lake, Utah, USA","interactions":[],"lastModifiedDate":"2013-03-10T11:46:29","indexId":"70043368","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":866,"text":"Aquatic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical Evolution of Great Salt Lake, Utah, USA","docAbstract":"\"The Great Salt Lake (GSL) of Utah, USA, is the largest saline lake in North\nAmerica, and its brines are some of the most concentrated anywhere in the world. The lake\noccupies a closed basin system whose chemistry reflects solute inputs from the weathering\nof a diverse suite of rocks in its drainage basin. GSL is the remnant of a much larger\nlacustrine body, Lake Bonneville, and it has a long history of carbonate deposition. Inflow\nto the lake is from three major rivers that drain mountain ranges to the east and empty into\nthe southern arm of the lake, from precipitation directly on the lake, and from minor\ngroundwater inflow. Outflow is by evaporation. The greatest solute inputs are from calcium\nbicarbonate river waters mixed with sodium chloride-type springs and groundwaters. Prior\nto 1930 the lake concentration inversely tracked lake volume, which reflected climatic\nvariation in the drainage, but since then salt precipitation and re-solution, primarily halite\nand mirabilite, have periodically modified lake-brine chemistry through density stratification\nand compositional differentiation. In addition, construction of a railway causeway\nhas restricted circulation, nearly isolating the northern from the southern part of the lake,\nleading to halite precipitation in the north. These and other conditions have created brine\ndifferentiation, mixing, and fractional precipitation of salts as major factors in solute\nevolution. Pore fluids and diagenetic reactions have been identified as important sources\nand especially sinks for CaCO3, Mg, and K in the lake, depending on the concentration\ngradient and clays.\"","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Aquatic Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10498-008-9047-y","usgsCitation":"Jones, B.F., Naftz, D.L., Spencer, R.J., and Oviatt, C., 2009, Geochemical Evolution of Great Salt Lake, Utah, USA: Aquatic Geochemistry, v. 15, no. 1-2, p. 95-121, https://doi.org/10.1007/s10498-008-9047-y.","startPage":"95","endPage":"121","numberOfPages":"26","ipdsId":"IP-010605","costCenters":[{"id":146,"text":"Branch of Regional Research-Eastern Region","active":false,"usgs":true}],"links":[{"id":269005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269003,"type":{"id":11,"text":"Document"},"url":"https://water.usgs.gov/nrp/proj.bib/Publications/2009/jones_naftz_etal_2009.pdf"},{"id":269004,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10498-008-9047-y"}],"country":"United States","volume":"15","issue":"1-2","noUsgsAuthors":false,"publicationDate":"2008-12-02","publicationStatus":"PW","scienceBaseUri":"53cd5ab0e4b0b290850f9888","contributors":{"authors":[{"text":"Jones, Blair F. bfjones@usgs.gov","contributorId":2784,"corporation":false,"usgs":true,"family":"Jones","given":"Blair","email":"bfjones@usgs.gov","middleInitial":"F.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":473472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Naftz, David L. 0000-0003-1130-6892 dlnaftz@usgs.gov","orcid":"https://orcid.org/0000-0003-1130-6892","contributorId":1041,"corporation":false,"usgs":true,"family":"Naftz","given":"David","email":"dlnaftz@usgs.gov","middleInitial":"L.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spencer, Ronald J.","contributorId":62480,"corporation":false,"usgs":true,"family":"Spencer","given":"Ronald","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":473474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oviatt, Charles G.","contributorId":13503,"corporation":false,"usgs":true,"family":"Oviatt","given":"Charles G.","affiliations":[],"preferred":false,"id":473473,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042435,"text":"70042435 - 2009 - Effects of Groundwater Development on Uranium: Central Valley, California, USA","interactions":[],"lastModifiedDate":"2013-04-09T19:34:21","indexId":"70042435","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Effects of Groundwater Development on Uranium: Central Valley, California, USA","docAbstract":"Uranium (U) concentrations in groundwater in several parts of the eastern San Joaquin Valley, California, have exceeded federal and state drinking water standards during the last 20 years. The San Joaquin Valley is located within the Central Valley of California and is one of the most productive agricultural areas in the world. Increased irrigation and pumping associated with agricultural and urban development during the last 100 years have changed the chemistry and magnitude of groundwater recharge, and increased the rate of downward groundwater movement. Strong correlations between U and bicarbonate suggest that U is leached from shallow sediments by high bicarbonate water, consistent with findings of previous work in Modesto, California. Summer irrigation of crops in agricultural areas and, to lesser extent, of landscape plants and grasses in urban areas, has increased Pco2 concentrations in the soil zone and caused higher temperature and salinity of groundwater recharge. Coupled with groundwater pumping, this process, as evidenced by increasing bicarbonate concentrations in groundwater over the last 100 years, has caused shallow, young groundwater with high U concentrations to migrate to deeper parts of the groundwater system that are tapped by public-supply wells. Continued downward migration of U-affected groundwater and expansion of urban centers into agricultural areas will likely be associated with increased U concentrations in public-supply wells. The results from this study illustrate the potential longterm effects of groundwater development and irrigation-supported agriculture on water quality in arid and semiarid regions around the world.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1745-6584.2009.00635.x","usgsCitation":"Jurgens, B., Fram, M.S., Belitz, K., Burow, K.R., and Landon, M.K., 2009, Effects of Groundwater Development on Uranium: Central Valley, California, USA: Ground Water, v. 48, no. 6, p. 913-928, https://doi.org/10.1111/j.1745-6584.2009.00635.x.","startPage":"913","endPage":"928","numberOfPages":"16","ipdsId":"IP-006319","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":270746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270744,"type":{"id":11,"text":"Document"},"url":"https://oh.water.usgs.gov/tanc/pubs/Jurgens&Others_2009.pdf"},{"id":270745,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2009.00635.x"}],"country":"United States","state":"California","volume":"48","issue":"6","noUsgsAuthors":false,"publicationDate":"2010-11-03","publicationStatus":"PW","scienceBaseUri":"5165386ae4b077fa94dadf9c","contributors":{"authors":[{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":1503,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant C.","email":"bjurgens@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":471521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":471519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burow, Karen R. 0000-0001-6006-6667 krburow@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-6667","contributorId":1504,"corporation":false,"usgs":true,"family":"Burow","given":"Karen","email":"krburow@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471518,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70168687,"text":"70168687 - 2009 - Sensitivity of the carbon cycle in the Arctic to climate change","interactions":[],"lastModifiedDate":"2016-02-24T14:20:52","indexId":"70168687","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity of the carbon cycle in the Arctic to climate change","docAbstract":"<p><span>The recent warming in the Arctic is affecting a broad spectrum of physical, ecological, and human/cultural systems that may be irreversible on century time scales and have the potential to cause rapid changes in the earth system. The response of the carbon cycle of the Arctic to changes in climate is a major issue of global concern, yet there has not been a comprehensive review of the status of the contemporary carbon cycle of the Arctic and its response to climate change. This review is designed to clarify key uncertainties and vulnerabilities in the response of the carbon cycle of the Arctic to ongoing climatic change. While it is clear that there are substantial stocks of carbon in the Arctic, there are also significant uncertainties associated with the magnitude of organic matter stocks contained in permafrost and the storage of methane hydrates beneath both subterranean and submerged permafrost of the Arctic. In the context of the global carbon cycle, this review demonstrates that the Arctic plays an important role in the global dynamics of both CO</span><span>2</span><span>&nbsp;and CH</span><span>4</span><span>. Studies suggest that the Arctic has been a sink for atmospheric CO</span><span>2</span><span>&nbsp;of between 0 and 0.8 Pg C/yr in recent decades, which is between 0% and 25% of the global net land/ocean flux during the 1990s. The Arctic is a substantial source of CH</span><span>4</span><span>&nbsp;to the atmosphere (between 32 and 112 Tg CH</span><span>4</span><span>/yr), primarily because of the large area of wetlands throughout the region. Analyses to date indicate that the sensitivity of the carbon cycle of the Arctic during the remainder of the 21st century is highly uncertain. To improve the capability to assess the sensitivity of the carbon cycle of the Arctic to projected climate change, we recommend that (1) integrated regional studies be conducted to link observations of carbon dynamics to the processes that are likely to influence those dynamics, and (2) the understanding gained from these integrated studies be incorporated into both uncoupled and fully coupled carbon&ndash;climate modeling efforts.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1890/08-2025.1","usgsCitation":"McGuire, A., Anderson, L.G., Christensen, T.R., Dallimore, S., Guo, L., Hayes, D.J., Heimann, M., Lorenson, T., Macdonald, R.W., and Roulet, N., 2009, Sensitivity of the carbon cycle in the Arctic to climate change: Ecological Monographs, v. 79, no. 4, p. 523-555, https://doi.org/10.1890/08-2025.1.","productDescription":"33 p.","startPage":"523","endPage":"555","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-011579","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":476013,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/08-2025.1","text":"Publisher Index Page"},{"id":318367,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"79","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56cee27de4b015c306ec5f0a","contributors":{"authors":[{"text":"McGuire, A. David","contributorId":18494,"corporation":false,"usgs":true,"family":"McGuire","given":"A. David","affiliations":[],"preferred":false,"id":621265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Leif G.","contributorId":166856,"corporation":false,"usgs":false,"family":"Anderson","given":"Leif","email":"","middleInitial":"G.","affiliations":[{"id":12695,"text":"University of Gothenburg","active":true,"usgs":false}],"preferred":false,"id":621298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Torben R.","contributorId":11946,"corporation":false,"usgs":true,"family":"Christensen","given":"Torben","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":621299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dallimore, Scott","contributorId":85503,"corporation":false,"usgs":true,"family":"Dallimore","given":"Scott","affiliations":[],"preferred":false,"id":621300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guo, Laodong","contributorId":70401,"corporation":false,"usgs":true,"family":"Guo","given":"Laodong","affiliations":[],"preferred":false,"id":621301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayes, Daniel J.","contributorId":100237,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":621302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heimann, Martin","contributorId":76497,"corporation":false,"usgs":true,"family":"Heimann","given":"Martin","affiliations":[],"preferred":false,"id":621303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lorenson, T.D. tlorenson@usgs.gov","contributorId":2622,"corporation":false,"usgs":true,"family":"Lorenson","given":"T.D.","email":"tlorenson@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":621304,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Macdonald, Robie W.","contributorId":167171,"corporation":false,"usgs":false,"family":"Macdonald","given":"Robie","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":621305,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Roulet, Nigel","contributorId":46253,"corporation":false,"usgs":true,"family":"Roulet","given":"Nigel","affiliations":[],"preferred":false,"id":621306,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70043242,"text":"70043242 - 2009 - Declining global per capita agricultural production and warming oceans threaten food security","interactions":[],"lastModifiedDate":"2013-04-09T19:28:04","indexId":"70043242","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1683,"text":"Food Security","active":true,"publicationSubtype":{"id":10}},"title":"Declining global per capita agricultural production and warming oceans threaten food security","docAbstract":"Despite accelerating globalization, most people still eat food that is grown locally. Developing countries with weak purchasing power tend to import as little food as possible from global markets, suffering consumption deficits during times of high prices or production declines. Local agricultural production, therefore, is critical to both food security and economic development among the rural poor. The level of local agricultural production, in turn, will be determined by the amount and quality of arable land, the amount and quality of agricultural inputs (fertilizer, seeds, pesticides, etc.), as well as farm-related technology, practices and policies. This paper discusses several emerging threats to global and regional food security, including declining yield gains that are failing to keep up with population increases, and warming in the tropical Indian Ocean and its impact on rainfall. If yields continue to grow more slowly than per capita harvested area, parts of Africa, Asia and Central and Southern America will experience substantial declines in per capita cereal production. Global per capita cereal production will potentially decline by 14% between 2008 and 2030. Climate change is likely to further affect food production, particularly in regions that have very low yields due to lack of technology. Drought, caused by anthropogenic warming in the Indian and Pacific Oceans, may also reduce 21st century food availability in some countries by disrupting moisture transports and bringing down dry air over crop growing areas. The impacts of these circulation changes over Asia remain uncertain. For Africa, however, Indian Ocean warming appears to have already reduced rainfall during the main growing season along the eastern edge of tropical Africa, from southern Somalia to northern parts of the Republic of South Africa. Through a combination of quantitative modeling of food balances and an examination of climate change, this study presents an analysis of emerging threats to global food security.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Food Security","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s12571-009-0026-y","usgsCitation":"Funk, C.C., and Brown, M.E., 2009, Declining global per capita agricultural production and warming oceans threaten food security: Food Security, v. 1, no. 3, p. 271-289, https://doi.org/10.1007/s12571-009-0026-y.","startPage":"271","endPage":"289","ipdsId":"IP-010410","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":476020,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12571-009-0026-y","text":"Publisher Index Page"},{"id":270740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270738,"type":{"id":11,"text":"Document"},"url":"https://link.springer.com/content/pdf/10.1007%2Fs12571-009-0026-y"},{"id":270739,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12571-009-0026-y"}],"country":"United States","volume":"1","issue":"3","noUsgsAuthors":false,"publicationDate":"2009-07-25","publicationStatus":"PW","scienceBaseUri":"51653869e4b077fa94dadf98","contributors":{"authors":[{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":473234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Molly E.","contributorId":62490,"corporation":false,"usgs":true,"family":"Brown","given":"Molly","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":473235,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70042758,"text":"70042758 - 2009 - Transport of tritium contamination to the atmosphere in an arid environment","interactions":[],"lastModifiedDate":"2018-10-03T10:15:42","indexId":"70042758","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Transport of tritium contamination to the atmosphere in an arid environment","docAbstract":"<p>Soil–plant–atmosphere interactions strongly influence water movement in desert unsaturated zones, but little is known about how such interactions affect atmospheric release of subsurface water-borne contaminants. This 2-yr study, performed at the U.S. Geological Survey's Amargosa Desert Research Site in southern Nevada, quantified the magnitude and spatiotemporal variability of tritium (3H) transport from the shallow unsaturated zone to the atmosphere adjacent to a low-level radioactive waste (LLRW) facility. Tritium fluxes were calculated as the product of 3H concentrations in water vapor and respective evaporation and transpiration water-vapor fluxes. Quarterly measured 3H concentrations in soil water vapor and in leaf water of the dominant creosote-bush [<i>Larrea tridentat</i>a (DC.) Coville] were spatially extrapolated and temporally interpolated to develop daily maps of contamination across the 0.76-km2 study area. Maximum plant and root-zone soil concentrations (4200 and 8700 Bq L−1, respectively) were measured 25 m from the LLRW facility boundary. Continuous evaporation was estimated using a Priestley–Taylor model and transpiration was computed as the difference between measured eddy-covariance evapotranspiration and estimated evaporation. The mean evaporation/transpiration ratio was 3:1. Tritium released from the study area ranged from 0.12 to 12 μg d−1 and totaled 1.5 mg (8.2 × 1010 Bq) over 2 yr. Tritium flux variability was driven spatially by proximity to 3H source areas and temporally by changes in 3H concentrations and in the partitioning between evaporation and transpiration. Evapotranspiration removed and limited penetration of precipitation beneath native vegetation and fostered upward movement and release of 3H from below the root zone.</p>","language":"English","publisher":"Soil Science Society of America","doi":"10.2136/vzj2008.0022","usgsCitation":"Garcia, C.A., Andraski, B.J., Johnson, M.J., Stonestrom, D.A., Michel, R.L., Cooper, C., and Wheatcraft, S., 2009, Transport of tritium contamination to the atmosphere in an arid environment: Vadose Zone Journal, v. 8, no. 2, p. 450-461, https://doi.org/10.2136/vzj2008.0022.","productDescription":"12 p.","startPage":"450","endPage":"461","ipdsId":"IP-004355","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":270866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"8","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd798ae4b0b2908510ce60","contributors":{"authors":[{"text":"Garcia, C. Amanda 0000-0003-3776-3565 cgarcia@usgs.gov","orcid":"https://orcid.org/0000-0003-3776-3565","contributorId":1899,"corporation":false,"usgs":true,"family":"Garcia","given":"C.","email":"cgarcia@usgs.gov","middleInitial":"Amanda","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andraski, Brian J. 0000-0002-2086-0417 andraski@usgs.gov","orcid":"https://orcid.org/0000-0002-2086-0417","contributorId":168800,"corporation":false,"usgs":true,"family":"Andraski","given":"Brian","email":"andraski@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":472176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Michael J. johnsonm@usgs.gov","contributorId":2282,"corporation":false,"usgs":true,"family":"Johnson","given":"Michael","email":"johnsonm@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":472180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stonestrom, David A. 0000-0001-7883-3385 dastones@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-3385","contributorId":2280,"corporation":false,"usgs":true,"family":"Stonestrom","given":"David","email":"dastones@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":472179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Michel, Robert L. rlmichel@usgs.gov","contributorId":823,"corporation":false,"usgs":true,"family":"Michel","given":"Robert","email":"rlmichel@usgs.gov","middleInitial":"L.","affiliations":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"preferred":true,"id":472177,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cooper, C.A.","contributorId":67316,"corporation":false,"usgs":true,"family":"Cooper","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":472182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wheatcraft, S.W.","contributorId":15427,"corporation":false,"usgs":true,"family":"Wheatcraft","given":"S.W.","email":"","affiliations":[],"preferred":false,"id":472181,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70043493,"text":"70043493 - 2009 - Lysimetric Evaluation of Simplified Surface Energy Balance Approach in the Texas High Plains","interactions":[],"lastModifiedDate":"2013-04-07T21:40:33","indexId":"70043493","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":833,"text":"Applied Engineering in Agriculture","active":true,"publicationSubtype":{"id":10}},"title":"Lysimetric Evaluation of Simplified Surface Energy Balance Approach in the Texas High Plains","docAbstract":"Numerous energy balance (EB) algorithms have been developed to make use of remote sensing data to estimate evapotranspiration (ET) regionally. However, most EB models are complex to use and efforts are being made to simplify procedures mainly through the scaling of reference ET. The Simplified Surface Energy Balance (SSEB) is one such method. This approach has never been evaluated using measured ET data. In this study, the SSEB approach was applied to fourteen Landsat TM images covering a major portion of the Southern High Plains that were acquired during 2006 and 2007 cropping seasons. Performance of the SSEB was evaluated by comparing estimated ET with measured daily ET from four large monolithic lysimeters at the USDA-ARS Conservation and Production Research Laboratory, Bushland, Texas. Statistical evaluation of results indicated that the SSEB accounted for 84% of the variability in the measured ET values with a slope and intercept of 0.75 and 1.1 mm d-1, respectively. Considering the minimal amount of ancillary data required and excellent performance in predicting daily ET, the SSEB approach is a promising tool for mapping ET in the semiarid Texas High Plains and in other parts of the world with similar hydro-climatic conditions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Engineering in Agriculture","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisherLocation":"Reston, VA","usgsCitation":"Senay, G.B., Gowda, P., Howell, T., and Marek, T., 2009, Lysimetric Evaluation of Simplified Surface Energy Balance Approach in the Texas High Plains: Applied Engineering in Agriculture, v. 25, no. 5, p. 665-669.","startPage":"665","endPage":"669","ipdsId":"IP-021547","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270643,"type":{"id":11,"text":"Document"},"url":"https://naldc.nal.usda.gov/download/37867/PDF"}],"country":"United States","volume":"25","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5162956ee4b0c25842758cff","contributors":{"authors":[{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gowda, P.H.","contributorId":63652,"corporation":false,"usgs":true,"family":"Gowda","given":"P.H.","email":"","affiliations":[],"preferred":false,"id":473708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howell, T.A.","contributorId":57694,"corporation":false,"usgs":true,"family":"Howell","given":"T.A.","affiliations":[],"preferred":false,"id":473707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marek, T.H.","contributorId":38815,"corporation":false,"usgs":true,"family":"Marek","given":"T.H.","email":"","affiliations":[],"preferred":false,"id":473706,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043798,"text":"70043798 - 2009 - Potential Inundation due to Rising Sea Levels in the San Francisco Bay Region","interactions":[],"lastModifiedDate":"2013-03-10T12:11:38","indexId":"70043798","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"CEC-500-2009-023-D","title":"Potential Inundation due to Rising Sea Levels in the San Francisco Bay Region","docAbstract":"An increase in the rate of sea level rise is one of the primary impacts of projected global climate change. To assess potential inundation associated with a continued acceleration of sea level rise, the highest resolution elevation data available were assembled from various sources and mosaicked to cover the land surfaces of the San Francisco Bay region. Next, to quantify high water levels throughout the bay, a hydrodynamic model of the San Francisco Estuary was driven by a projection of hourly water levels at the Presidio. This projection was based on a combination of climate model outputs and empirical models and incorporates astronomical, storm surge, El Niño, and long-term sea level rise influences. \n\nBased on the resulting data, maps of areas vulnerable to inundation were produced, corresponding to specific amounts of sea level rise and recurrence intervals. These maps portray areas where inundation will likely be an increasing concern. In the North Bay, wetland survival and developed fill areas are at risk. In Central and South bays, a key feature is the bay-ward periphery of developed areas that would be newly vulnerable to inundation. Nearly all municipalities adjacent to South Bay face this risk to some degree. For the Bay as a whole, as early as 2050 under this scenario, the one-year peak event nearly equals the 100-year peak event in 2000. Maps of vulnerable areas are presented and some implications discussed.","language":"English","publisher":"California Climate Change Center","publisherLocation":"Sacramento,CA","usgsCitation":"Knowles, N., 2009, Potential Inundation due to Rising Sea Levels in the San Francisco Bay Region (Draft Paper), i-viii, 21 p.","productDescription":"i-viii, 21 p.","numberOfPages":"33","ipdsId":"IP-010404","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"links":[{"id":269021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269020,"type":{"id":11,"text":"Document"},"url":"https://www.energy.ca.gov/2009publications/CEC-500-2009-023/CEC-500-2009-023-D.PDF"}],"country":"United States","state":"California","edition":"Draft Paper","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd6bfbe4b0b29085104463","contributors":{"authors":[{"text":"Knowles, Noah 0000-0001-5652-1049 nknowles@usgs.gov","orcid":"https://orcid.org/0000-0001-5652-1049","contributorId":1380,"corporation":false,"usgs":true,"family":"Knowles","given":"Noah","email":"nknowles@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":474244,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70042388,"text":"70042388 - 2009 - Multi-scale measurements and modeling of denitrification in streams with varying flow and nitrate concentration in the upper Mississippi River basin, USA","interactions":[],"lastModifiedDate":"2018-10-05T09:50:25","indexId":"70042388","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale measurements and modeling of denitrification in streams with varying flow and nitrate concentration in the upper Mississippi River basin, USA","docAbstract":"<p><span>Denitrification is an important net sink for NO</span><sub>3</sub><sup>−</sup><span> in streams, but direct measurements are limited and in situ controlling factors are not well known. We measured denitrification at multiple scales over a range of flow conditions and NO</span><sub>3</sub><sup>−</sup><span> concentrations in streams draining agricultural land in the upper Mississippi River basin. Comparisons of reach-scale measurements (in-stream mass transport and tracer tests) with local-scale in situ measurements (pore-water profiles, benthic chambers) and laboratory data (sediment core microcosms) gave evidence for heterogeneity in factors affecting benthic denitrification both temporally (e.g., seasonal variation in NO</span><sub>3</sub><sup>−</sup><span> concentrations and loads, flood-related disruption and re-growth of benthic communities and organic deposits) and spatially (e.g., local stream morphology and sediment characteristics). When expressed as vertical denitrification flux per unit area of streambed (</span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span>, in μmol&nbsp;N&nbsp;m</span><sup>−2</sup><span>&nbsp;h</span><sup>−1</sup><span>), results of different methods for a given set of conditions commonly were in agreement within a factor of 2–3. At approximately constant temperature (~20&nbsp;±&nbsp;4°C) and with minimal benthic disturbance, our aggregated data indicated an overall positive relation between </span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span> (~0–4,000&nbsp;μmol&nbsp;N&nbsp;m</span><sup>−2</sup><span>&nbsp;h</span><sup>−1</sup><span>) and stream NO</span><sub>3</sub><sup>−</sup><span>concentration (~20–1,100&nbsp;μmol&nbsp;L</span><sup>−1</sup><span>) representing seasonal variation from spring high flow (high NO</span><sub>3</sub><sup>−</sup><span>) to late summer low flow (low NO</span><sub>3</sub><sup>−</sup><span>). The temporal dependence of </span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span> on NO</span><sub>3</sub><sup>−</sup><span>was less than first-order and could be described about equally well with power-law or saturation equations (e.g., for the unweighted dataset, </span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span>&nbsp;≈26&nbsp;*&nbsp;[NO</span><sub>3</sub><sup>−</sup><span>]</span><sup>0.44</sup><span> or </span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span>≈640&nbsp;*&nbsp;[NO</span><sub>3</sub><sup>−</sup><span>]/[180&nbsp;+&nbsp;NO</span><sub>3</sub><sup>−</sup><span>]; for a partially weighted dataset, </span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span>&nbsp;≈14&nbsp;*&nbsp;[NO</span><sub>3</sub><sup>−</sup><span>]</span><sup>0.54</sup><span> or </span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span>&nbsp;≈700&nbsp;*&nbsp;[NO</span><sub>3</sub><sup>−</sup><span>]/[320&nbsp;+&nbsp;NO</span><sub>3</sub><sup>−</sup><span>]). Similar parameters were derived from a recent spatial comparison of stream denitrification extending to lower NO</span><sub>3</sub><sup>−</sup><span> concentrations (LINX2), and from the combined dataset from both studies over 3 orders of magnitude in NO</span><sub>3</sub><sup>−</sup><span>concentration. Hypothetical models based on our results illustrate: (1) </span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span> was inversely related to denitrification rate constant (</span><i class=\"EmphasisTypeItalic \">k</i><span>1</span><sub>denit</sub><span>, in day</span><sup>−1</sup><span>) and vertical transfer velocity (</span><i class=\"EmphasisTypeItalic \">v</i><sub>f,denit</sub><span>, in m day</span><sup>−1</sup><span>) at seasonal and possibly event time scales; (2) although </span><i class=\"EmphasisTypeItalic \">k</i><span>1</span><sub>denit</sub><span> was relatively large at low flow (low NO</span><sub>3</sub><sup>−</sup><span>), its impact on annual loads was relatively small because higher concentrations and loads at high flow were not fully compensated by increases in </span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span>; and (3) although NO</span><sub>3</sub><sup>−</sup><span> assimilation and denitrification were linked through production of organic reactants, rates of NO</span><sub>3</sub><sup>−</sup><span> loss by these processes may have been partially decoupled by changes in flow and sediment transport. Whereas </span><i class=\"EmphasisTypeItalic \">k</i><span>1</span><sub>denit</sub><span> and </span><i class=\"EmphasisTypeItalic \">v</i><sub>f,denit</sub><span> are linked implicitly with stream depth, NO</span><sub>3</sub><sup>−</sup><span> concentration, and(or) NO</span><sub>3</sub><sup>−</sup><span> load, estimates of </span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span> may be related more directly to field factors (including NO</span><sub>3</sub><sup>−</sup><span> concentration) affecting denitrification rates in benthic sediments. Regional regressions and simulations of benthic denitrification in stream networks might be improved by including a non-linear relation between </span><i class=\"EmphasisTypeItalic \">U</i><sub>denit</sub><span> and stream NO</span><sub>3</sub><sup>−</sup><span>concentration and accounting for temporal variation.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10533-008-9282-8","usgsCitation":"Bohlke, J., Antweiler, R.C., Harvey, J.W., Laursen, A.E., Smith, L.K., Smith, R.L., and Voytek, M.A., 2009, Multi-scale measurements and modeling of denitrification in streams with varying flow and nitrate concentration in the upper Mississippi River basin, USA: Biogeochemistry, v. 93, no. 1, p. 117-141, https://doi.org/10.1007/s10533-008-9282-8.","productDescription":"24 p.","startPage":"117","endPage":"141","ipdsId":"IP-008428","costCenters":[{"id":146,"text":"Branch of Regional Research-Eastern Region","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":476016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10533-008-9282-8","text":"Publisher Index Page"},{"id":270742,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10533-008-9282-8"},{"id":270743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"1","noUsgsAuthors":false,"publicationDate":"2009-01-13","publicationStatus":"PW","scienceBaseUri":"5165386ce4b077fa94dadfc3","contributors":{"authors":[{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":471448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Antweiler, Ronald C. 0000-0001-5652-6034 antweil@usgs.gov","orcid":"https://orcid.org/0000-0001-5652-6034","contributorId":1481,"corporation":false,"usgs":true,"family":"Antweiler","given":"Ronald","email":"antweil@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":471444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":471446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laursen, Andrew E.","contributorId":99783,"corporation":false,"usgs":true,"family":"Laursen","given":"Andrew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":471450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Lesley K.","contributorId":82657,"corporation":false,"usgs":true,"family":"Smith","given":"Lesley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":471447,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Richard L. 0000-0002-3829-0125 rlsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-3829-0125","contributorId":1592,"corporation":false,"usgs":true,"family":"Smith","given":"Richard","email":"rlsmith@usgs.gov","middleInitial":"L.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":471445,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Voytek, Mary A.","contributorId":91943,"corporation":false,"usgs":true,"family":"Voytek","given":"Mary","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471449,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70161856,"text":"70161856 - 2009 - 2008 Spawning Cisco Investigations in the Canadian Waters of Lake Superior","interactions":[],"lastModifiedDate":"2016-06-23T14:48:40","indexId":"70161856","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"2008 Spawning Cisco Investigations in the Canadian Waters of Lake Superior","docAbstract":"<p>The Great Lakes Science Center of the United States Geological Survey (USGS) is working cooperatively with the Ontario Ministry of Natural Resources (OMNR) on a threeyear study to develop standard procedures for acoustic and midwater trawl (AC-MT) assessments of spawning cisco Coregonus artedi that the OMNR can carry forward as a management activity. In year two (2008), we conducted an AC-MT survey of the northern shore from Nipigon Bay to Thunder Bay. Spawning-cisco (&gt; 250 mm total length) densities were lowest near Nipigon Bay (&lt;10/ha), moderate in and around Black Bay (15- 30/ha), and highest in Thunder Bay (118/ha). Rainbow smelt Osmerus mordax densities were highest in Nipigon (2,179/ha) and Black (3,219/ha) bays, and lowest in Thunder Bay (961/ha). We combined our AC-MT survey results with commercial catch records to estimate exploitation fractions of female cisco in Thunder Bay during the 2008 fishery at 4% for ages 1-5, 8.7% for ages 6-12, and 4.4% for ages &ge; 13. Lake Superior fishery managers recently recommended that annual exploitation of adult female lake cisco be kept below 10-15%. Recruitment of cisco since 2003 has been low and there is a strong probability the Thunder Bay stock will decline into the future. Using a simple population dynamics approach we estimated that if the current total allowable catch (TAC) quota is held constant, exploitation fractions could exceed 10% by 2010 and 15% by 2011. Our 2008 collections suggested the survey of Black Bay was likely conducted before all spawners had returned there to spawn. Our data also suggested that cisco collected in Black Bay and east of this site in mid-November may be from the same stock. During November 2009 we will attempt to get better definition of the area occupied by cisco around Black Bay and also determine when surveys should be conducted at this location.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70161856","usgsCitation":"Yule, D., Addison, P.A., Evrard, L.M., Cullis, K.I., and Cholwek, G.A., 2009, 2008 Spawning Cisco Investigations in the Canadian Waters of Lake Superior, 47 p., https://doi.org/10.3133/70161856.","productDescription":"47 p.","numberOfPages":"47","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-014726","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":324306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":313995,"type":{"id":11,"text":"Document"},"url":"https://www.glsc.usgs.gov/products/reports/1970178148"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576d082ce4b07657d1a37543","contributors":{"authors":[{"text":"Yule, Daniel 0000-0002-0117-5115 dyule@usgs.gov","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":139532,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","email":"dyule@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":587943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Addison, Peter A.","contributorId":105987,"corporation":false,"usgs":true,"family":"Addison","given":"Peter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":587947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evrard, Lori M. 0000-0001-8582-5818 levrard@usgs.gov","orcid":"https://orcid.org/0000-0001-8582-5818","contributorId":2720,"corporation":false,"usgs":true,"family":"Evrard","given":"Lori","email":"levrard@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":587945,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cullis, Ken I.","contributorId":150786,"corporation":false,"usgs":false,"family":"Cullis","given":"Ken","email":"","middleInitial":"I.","affiliations":[{"id":13173,"text":"Ontario Ministry of Natural Resources, Upper Great Lakes Management Unit","active":true,"usgs":false}],"preferred":false,"id":587948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cholwek, Gary A. gcholwek@usgs.gov","contributorId":2719,"corporation":false,"usgs":true,"family":"Cholwek","given":"Gary","email":"gcholwek@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":587944,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209246,"text":"70209246 - 2009 - Deglaciation in the southeastern Laurentide Sector and the Hudson Valley – 15,000 Years of vegetational and climate history","interactions":[],"lastModifiedDate":"2020-03-27T06:33:39","indexId":"70209246","displayToPublicDate":"2009-12-31T11:57:37","publicationYear":"2009","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Deglaciation in the southeastern Laurentide Sector and the Hudson Valley – 15,000 Years of vegetational and climate history","docAbstract":"<p>In this field trip, we provide a review of the significant controversy concerning the timing of deglaciation in the Hudson and Wallkill Valleys. We outline the differences in methodology and chronology with a circular route throughout the Hudson and Wallkill valleys. We begin the trip at Lake Mohonk near New Paltz led by Kirsten Menking and Dorothy Peteet, then continue to the “black dirt” region of the Wallkill Valley where John Rayburn has contributed a new GIS model of deglaciation in the Wallkill Valley and Guy Robinson will review the history of fossil mammals, including mammoths. From this point we travel southeast to a rare exposure of glaciolacustrine beds on the west side of the Huson River, described by Byron Stone and John Rayburn, and on to Croton Marsh at Croton Point, New York where Dorothy Peteet will review the marsh histories of the region. </p><p>A recent review of literature relating to the last glacial recession in the Hudson Valley indicates that the timing of de - glaciation is very controversial (Peteet et al., 2006; Peteet, in review; Balco et al., 2006; Balco et al., 2009; Schaefer, 2007). Some questions to consider: </p><p>1) How does timing of new lake basal dates at the margin of the ice (Staten Island) compare with sites to the north and inland (ie. Mohonk)? </p><p>2) What is the vegetational history of the region and how does it compare with Deevey’s classical southern New England stratigraphy? </p><p>3) What is the latest model of the deglaciation of the Wallkill Valley? </p><p>4) What have the Hudson marshes added to our understanding of the vegetation and landscape history, particularly in the last few millennia?</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Field trip guidebook: New York State Geological Association 81st annual meeting, September 25-27, 2009","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"New York State Geological Association 81st annual meeting","conferenceDate":"September 25-27, 2009","conferenceLocation":"New Paltz, NY","language":"English","publisher":"New York State Geological Association","usgsCitation":"Peteet, D.M., Rayburn, J., Menking, K.M., Robinson, G., and Stone, B.D., 2009, Deglaciation in the southeastern Laurentide Sector and the Hudson Valley – 15,000 Years of vegetational and climate history, <i>in</i> Field trip guidebook: New York State Geological Association 81st annual meeting, September 25-27, 2009, New Paltz, NY, September 25-27, 2009, p. 4.1-4.18.","productDescription":"18 p.","startPage":"4.1","endPage":"4.18","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":373516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373515,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nysga-online.net/guidebooks/1925-2018/"}],"country":"United States","state":"New York","city":" New Paltz","otherGeospatial":"Croton Point, Hudson Valley, Lake Mohonk, Wallkill Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.51751708984375,\n              41.062786068733026\n            ],\n            [\n              -73.68804931640625,\n              41.062786068733026\n            ],\n            [\n              -73.68804931640625,\n              42.256983603767466\n            ],\n            [\n              -74.51751708984375,\n              42.256983603767466\n            ],\n            [\n              -74.51751708984375,\n              41.062786068733026\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peteet, Dorothy M. 0000-0003-3029-7506","orcid":"https://orcid.org/0000-0003-3029-7506","contributorId":147523,"corporation":false,"usgs":false,"family":"Peteet","given":"Dorothy","email":"","middleInitial":"M.","affiliations":[{"id":16858,"text":"Goddard Institute","active":true,"usgs":false}],"preferred":false,"id":785540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rayburn, John","contributorId":223595,"corporation":false,"usgs":false,"family":"Rayburn","given":"John","email":"","affiliations":[],"preferred":false,"id":785541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Menking, Kirsten M.","contributorId":53564,"corporation":false,"usgs":true,"family":"Menking","given":"Kirsten","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":785542,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robinson, Guy","contributorId":223596,"corporation":false,"usgs":false,"family":"Robinson","given":"Guy","email":"","affiliations":[],"preferred":false,"id":785543,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stone, Byron D. 0000-0001-6092-0798 bdstone@usgs.gov","orcid":"https://orcid.org/0000-0001-6092-0798","contributorId":1702,"corporation":false,"usgs":true,"family":"Stone","given":"Byron","email":"bdstone@usgs.gov","middleInitial":"D.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":785544,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226921,"text":"70226921 - 2009 - Discussion on remote sensing for aquatic monitoring","interactions":[],"lastModifiedDate":"2021-12-21T15:16:35.814809","indexId":"70226921","displayToPublicDate":"2009-12-31T09:11:12","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":9957,"text":"PNAMP Special Publication","active":true,"publicationSubtype":{"id":4}},"chapter":"12","title":"Discussion on remote sensing for aquatic monitoring","docAbstract":"<p>The special session on Remote Sensing for Aquatic Resource Monitoring concluded with an expert panel discussion. Panel members were Jennifer Bountry (hydraulic engineer, Bureau of Reclamation), Mimi D’Iorio (GIS analyst and database manager, National Oceanic and Atmospheric Administration), Russ Faux (president, Watershed Sciences, Inc.), Steve Lanigan (team leader, Aquatic and Riparian Effectiveness Monitoring Program, U.S. Forest Service), and Amar Nayegandhi (computer scientist, Jacobs Technology, contracted to U.S. Geological Survey). The panel was moderated by Ralph Haugerud (geologist, U.S. Geological Survey) and there were significant contributions from the audience. The dialogue is summarized below in question and answer format. This summary is followed by discussion of what we learned in the course of the special session and identification of some next steps for the Pacific Northwest aquatic monitoring community. </p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"PNAMP special publication: Remote sensing applications for aquatic resource monitoring","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Pacific Northwest Aquatic Monitoring Partnership in association with Puget Sound Region of the American Society for Photogrammetry and Remote Sensing","collaboration":".","usgsCitation":"Haugerud, R.A., 2009, Discussion on remote sensing for aquatic monitoring: PNAMP Special Publication, 8 p.","productDescription":"8 p.","startPage":"93","endPage":"100","ipdsId":"IP-013019","costCenters":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":393179,"type":{"id":15,"text":"Index Page"},"url":"https://www.pnamp.org/document/10344"},{"id":393191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haugerud, Ralph A. 0000-0001-7302-4351","orcid":"https://orcid.org/0000-0001-7302-4351","contributorId":204669,"corporation":false,"usgs":true,"family":"Haugerud","given":"Ralph","email":"","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":828798,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70189932,"text":"70189932 - 2009 - Advanced Tools for River Science: EAARL and MD_SWMS: Chapter 3","interactions":[],"lastModifiedDate":"2017-08-01T15:45:30","indexId":"70189932","displayToPublicDate":"2009-12-31T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Advanced Tools for River Science: EAARL and MD_SWMS: Chapter 3","docAbstract":"Disruption of flow regimes and sediment supplies, induced by anthropogenic or climatic factors, can produce dramatic alterations in river form, vegetation patterns, and associated habitat conditions. To improve habitat in these fluvial systems, resource managers may choose from a variety of treatments including flow and/or sediment prescriptions, vegetation management, or engineered approaches. Monitoring protocols developed to assess the morphologic response of these treatments require techniques that can measure topographic changes above and below the water surface efficiently, accurately, and in a standardized, cost-effective manner. Similarly, modeling of flow, sediment transport, habitat, and channel evolution requires characterization of river morphology for model input and verification. Recent developments by the U.S. Geological Survey with regard to both remotely sensed methods (the Experimental Advanced Airborne Research LiDAR; EAARL) and computational modeling software (the Multi-Dimensional Surface-Water Modeling System; MD_SWMS) have produced advanced tools for spatially explicit monitoring and modeling in aquatic environments. In this paper, we present a pilot study conducted along the Platte River, Nebraska, that demonstrates the combined use of these river science tools.","largerWorkTitle":"PNAMP Special Publication: Remote Sensing Applications for Aquatic Resource Monitoring","conferenceTitle":"2008 American Society for Photogrammetry and Remote Sensing Annual Meeting: PNAMP Special Session","conferenceDate":"April 28, 2008-May 2, 2008","conferenceLocation":"Portland, OR","language":"English","usgsCitation":"Kinzel, P.J., 2009, Advanced Tools for River Science: EAARL and MD_SWMS: Chapter 3, 10 p.","productDescription":"10 p.","startPage":"17","endPage":"26","ipdsId":"IP-010843","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":344426,"type":{"id":15,"text":"Index Page"},"url":"https://www.pnamp.org/document/2550"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59819317e4b0e2f5d463b7b7","contributors":{"authors":[{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":706801,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70189840,"text":"70189840 - 2009 - Constraints on the stress state of the San Andreas fault with analysis based on core and cuttings from SAFOD drilling phases 1 and 2","interactions":[],"lastModifiedDate":"2021-03-31T15:09:15.833172","indexId":"70189840","displayToPublicDate":"2009-12-31T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7514,"text":"Journal of Geophysical Research - Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Constraints on the stress state of the San Andreas fault with analysis based on core and cuttings from SAFOD drilling phases 1 and 2","docAbstract":"<p><span>Analysis of field data has led different investigators to conclude that the San Andreas Fault (SAF) has either anomalously low frictional sliding strength (</span><i>μ</i><span>&nbsp;&lt; 0.2) or strength consistent with standard laboratory tests (</span><i>μ</i><span>&nbsp;&gt; 0.6). Arguments for the apparent weakness of the SAF generally hinge on conceptual models involving intrinsically weak gouge or elevated pore pressure within the fault zone. Some models assert that weak gouge and/or high pore pressure exist under static conditions while others consider strength loss or fluid pressure increase due to rapid coseismic fault slip. The present paper is composed of three parts. First, we develop generalized equations, based on and consistent with the Rice (1992) fault zone model to relate stress orientation and magnitude to depth‐dependent coefficient of friction and pore pressure. Second, we present temperature‐ and pressure‐dependent friction measurements from wet illite‐rich fault gouge extracted from San Andreas Fault Observatory at Depth (SAFOD) phase 1 core samples and from weak minerals associated with the San Andreas Fault. Third, we reevaluate the state of stress on the San Andreas Fault in light of new constraints imposed by SAFOD borehole data. Pure talc (</span><i>μ</i><span>≈0.1) had the lowest strength considered and was sufficiently weak to satisfy weak fault heat flow and stress orientation constraints with hydrostatic pore pressure. Other fault gouges showed a systematic increase in strength with increasing temperature and pressure. In this case, heat flow and stress orientation constraints would require elevated pore pressure and, in some cases, fault zone pore pressure in excess of vertical stress.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2008JB005883","usgsCitation":"Tembe, C., Lockner, D.A., and Wong, T., 2009, Constraints on the stress state of the San Andreas fault with analysis based on core and cuttings from SAFOD drilling phases 1 and 2: Journal of Geophysical Research - Solid Earth, v. 114, no. B11, B11401, 21 p., https://doi.org/10.1029/2008JB005883.","productDescription":"B11401, 21 p.","ipdsId":"IP-011888","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":476031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2008jb005883","text":"Publisher Index Page"},{"id":344400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -125.068359375,\n              41.11246878918088\n            ],\n            [\n              -124.69482421875,\n              40.49709237269567\n            ],\n            [\n              -124.4091796875,\n              40.111688665595956\n            ],\n            [\n              -124.21142578125,\n              39.45316112807394\n            ],\n            [\n              -123.55224609375,\n              38.151837403006766\n            ],\n            [\n              -123.37646484374999,\n              37.56199695314352\n            ],\n            [\n              -122.1240234375,\n              36.19109202182454\n            ],\n            [\n              -120.9375,\n              34.19817309627726\n            ],\n            [\n              -118.63037109375,\n              33.65120829920497\n            ],\n            [\n              -118.05908203124999,\n              33.37641235124676\n            ],\n            [\n              -117.35595703124999,\n              32.47269502206151\n            ],\n            [\n              -114.488525390625,\n              32.722598604044066\n            ],\n            [\n              -115.37841796874999,\n              34.43409789359469\n            ],\n            [\n              -117.61962890624999,\n              36.527294814546245\n            ],\n            [\n              -120.76171875,\n              39.52099229357195\n            ],\n            [\n              -122.89306640624999,\n              41.57436130598913\n            ],\n            [\n              -123.837890625,\n              41.343824581185686\n            ],\n            [\n              -125.068359375,\n              41.11246878918088\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"114","issue":"B11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2009-11-05","publicationStatus":"PW","scienceBaseUri":"597afba8e4b0a38ca2750b6c","contributors":{"authors":[{"text":"Tembe, Cheryl","contributorId":195205,"corporation":false,"usgs":false,"family":"Tembe","given":"Cheryl","email":"","affiliations":[],"preferred":false,"id":706521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706520,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wong, Teng-fong","contributorId":195206,"corporation":false,"usgs":false,"family":"Wong","given":"Teng-fong","email":"","affiliations":[],"preferred":false,"id":706522,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70003503,"text":"70003503 - 2009 - Population dynamics of long-tailed ducks breeding on the Yukon-Kuskokwim Delta, Alaska","interactions":[],"lastModifiedDate":"2023-08-09T16:40:55.530327","indexId":"70003503","displayToPublicDate":"2009-12-31T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":894,"text":"Arctic","active":true,"publicationSubtype":{"id":10}},"title":"Population dynamics of long-tailed ducks breeding on the Yukon-Kuskokwim Delta, Alaska","docAbstract":"Population estimates for long-tailed ducks in North America have declined by nearly 50% over the past 30 years. Life history and population dynamics of this species are difficult to ascertain, because the birds nest at low densities across a broad range of habitat types. Between 1991 and 2004, we collected information on productivity and survival of long-tailed ducks at three locations on the Yukon-Kuskokwim Delta. Clutch size averaged 7.1 eggs, and nesting success averaged 30%. Duckling survival to 30 days old averaged 10% but was highly variable among years, ranging from 0% to 25%. Apparent annual survival of adult females based on mark-recapture of nesting females was estimated at 74%. We combined these estimates of survival and productivity into a matrix-based population model, which predicted an annual population decline of 19%. Elasticities indicated that population growth rate (&lambda;) was most sensitive to changes in adult female survival. Further, the relatively high sensitivity of &lambda; to duckling survival suggests that low duckling survival may be a bottleneck to productivity in some years. These data represent the first attempt to synthesize a population model for this species. Although our analyses were hampered by the small sample sizes inherent in studying a dispersed nesting species, our model provides a basis for management actions and can be enhanced as additional data become available.","language":"English","publisher":"Arctic Institute of North America","doi":"10.14430/arctic131","usgsCitation":"Schamber, J.L., Flint, P.L., Grand, J., Wilson, H.M., and Morse, J.A., 2009, Population dynamics of long-tailed ducks breeding on the Yukon-Kuskokwim Delta, Alaska: Arctic, v. 62, no. 2, p. 190-200, https://doi.org/10.14430/arctic131.","productDescription":"11 p.","startPage":"190","endPage":"200","temporalStart":"1991-01-01","temporalEnd":"2004-12-31","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":489809,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14430/arctic131","text":"Publisher Index Page"},{"id":419660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon-Kuskokwin Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -161.58644631128854,\n              63.49574914683663\n            ],\n            [\n              -166.02212168061303,\n              63.49574914683663\n            ],\n            [\n              -166.02212168061303,\n              59.74690004761109\n            ],\n            [\n              -161.58644631128854,\n              59.74690004761109\n            ],\n            [\n              -161.58644631128854,\n              63.49574914683663\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"62","issue":"2","noUsgsAuthors":false,"publicationDate":"2009-09-11","publicationStatus":"PW","scienceBaseUri":"4f4e4ad6e4b07f02db684064","contributors":{"authors":[{"text":"Schamber, Jason L.","contributorId":72512,"corporation":false,"usgs":true,"family":"Schamber","given":"Jason","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":347557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":347553,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grand, J. Barry","contributorId":61950,"corporation":false,"usgs":true,"family":"Grand","given":"J. Barry","affiliations":[],"preferred":false,"id":347555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Heather M.","contributorId":37056,"corporation":false,"usgs":false,"family":"Wilson","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":13236,"text":"U.S. Fish and Wildlife Service, Migratory Bird Management","active":true,"usgs":false}],"preferred":false,"id":347554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morse, Julie A.","contributorId":63939,"corporation":false,"usgs":true,"family":"Morse","given":"Julie","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":347556,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70191429,"text":"70191429 - 2009 - Comparing a quasi-3D to a full 3D nearshore circulation model: SHORECIRC and ROMS","interactions":[],"lastModifiedDate":"2017-10-11T13:55:52","indexId":"70191429","displayToPublicDate":"2009-12-31T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Comparing a quasi-3D to a full 3D nearshore circulation model: SHORECIRC and ROMS","docAbstract":"<p><span>Predictions of nearshore and surf zone processes are important for determining coastal circulation, impacts of storms, navigation, and recreational safety. Numerical modeling of these systems facilitates advancements in our understanding of coastal changes and can provide predictive capabilities for resource managers. There exists many nearshore coastal circulation models, however they are mostly limited or typically only applied as depth integrated models. SHORECIRC is an established surf zone circulation model that is quasi-3D to allow the effect of the variability in the vertical structure of the currents while maintaining the computational advantage of a 2DH model. Here we compare SHORECIRC to ROMS, a fully 3D ocean circulation model which now includes a three dimensional formulation for the wave-driven flows. We compare the models with three different test applications for: (i) spectral waves approaching a plane beach with an oblique angle of incidence; (ii) monochromatic waves driving longshore currents in a laboratory basin; and (iii) monochromatic waves on a barred beach with rip channels in a laboratory basin. Results identify that the models are very similar for the depth integrated flows and qualitatively consistent for the vertically varying components. The differences are primarily the result of the vertically varying radiation stress utilized by ROMS and the utilization of long wave theory for the radiation stress formulation in vertical varying momentum balance by SHORECIRC. The quasi-3D model is faster, however the applicability of the fully 3D model allows it to extend over a broader range of processes, temporal, and spatial scales.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocemod.2008.09.003","usgsCitation":"Haas, K.A., and Warner, J., 2009, Comparing a quasi-3D to a full 3D nearshore circulation model: SHORECIRC and ROMS: Ocean Modelling, v. 26, no. 1-2, p. 91-103, https://doi.org/10.1016/j.ocemod.2008.09.003.","productDescription":"13 p.","startPage":"91","endPage":"103","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":346507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59df0ae2e4b05fe04ccd3dd9","contributors":{"authors":[{"text":"Haas, Kevin A.","contributorId":78027,"corporation":false,"usgs":true,"family":"Haas","given":"Kevin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":712214,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70168804,"text":"70168804 - 2009 - Nitrogen attenuation of terrestrial carbon cycle response to global environmental factors","interactions":[],"lastModifiedDate":"2016-03-04T13:19:14","indexId":"70168804","displayToPublicDate":"2009-12-30T14:15:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen attenuation of terrestrial carbon cycle response to global environmental factors","docAbstract":"<p>Nitrogen cycle dynamics have the capacity to attenuate the magnitude of global terrestrial carbon sinks and sources driven by CO<sub>2</sub> fertilization and changes in climate. In this study, two versions of the terrestrial carbon and nitrogen cycle components of the Integrated Science Assessment Model (ISAM) are used to evaluate how variation in nitrogen availability influences terrestrial carbon sinks and sources in response to changes over the 20th century in global environmental factors including atmospheric CO<sub>2</sub> concentration, nitrogen inputs, temperature, precipitation and land use. The two versions of ISAM vary in their treatment of nitrogen availability: ISAM-NC has a terrestrial carbon cycle model coupled to a fully dynamic nitrogen cycle while ISAM-C has an identical carbon cycle model but nitrogen availability is always in sufficient supply. Overall, the two versions of the model estimate approximately the same amount of global mean carbon uptake over the 20th century. However, comparisons of results of ISAM-NC relative to ISAM-C reveal that nitrogen dynamics: (1) reduced the 1990s carbon sink associated with increasing atmospheric CO<sub>2</sub> by 0.53 PgC yr<sup>&minus;1</sup> (1 Pg = 1015g), (2) reduced the 1990s carbon source associated with changes in temperature and precipitation of 0.34 PgC yr<sup>&minus;1</sup> in the 1990s, (3) an enhanced sink associated with nitrogen inputs by 0.26 PgC yr<sup>&minus;1</sup>, and (4) enhanced the 1990s carbon source associated with changes in land use by 0.08 PgC yr<sup>&minus;1</sup> in the 1990s. These effects of nitrogen limitation influenced the spatial distribution of the estimated exchange of CO<sub>2</sub> with greater sink activity in high latitudes associated with climate effects and a smaller sink of CO<sub>2</sub> in the southeastern United States caused by N limitation associated with both CO<sub>2</sub> fertilization and forest regrowth. These results indicate that the dynamics of nitrogen availability are important to consider in assessing the spatial distribution and temporal dynamics of terrestrial carbon sources and sinks.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Global Biogeochemical Cycles","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, DC","doi":"10.1029/2009GB003519","usgsCitation":"Jain, A., Yang, X., Kheshgi, H., McGuire, A.D., Post, W., and Kicklighter, D.W., 2009, Nitrogen attenuation of terrestrial carbon cycle response to global environmental factors: Global Biogeochemical Cycles, v. 23, no. 4, 13 p., https://doi.org/10.1029/2009GB003519.","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-019838","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":476037,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2009gb003519","text":"Publisher Index Page"},{"id":318561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2009-12-30","publicationStatus":"PW","scienceBaseUri":"56dabfede4b015c306f84cdd","contributors":{"authors":[{"text":"Jain, A.A.","contributorId":75345,"corporation":false,"usgs":true,"family":"Jain","given":"A.A.","email":"","affiliations":[],"preferred":false,"id":621936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Xiaojuan","contributorId":146256,"corporation":false,"usgs":false,"family":"Yang","given":"Xiaojuan","email":"","affiliations":[{"id":16649,"text":"Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN 37831-6335, USA","active":true,"usgs":false}],"preferred":false,"id":621937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kheshgi, H.","contributorId":54049,"corporation":false,"usgs":true,"family":"Kheshgi","given":"H.","email":"","affiliations":[],"preferred":false,"id":621938,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":621829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Post, W.","contributorId":6155,"corporation":false,"usgs":true,"family":"Post","given":"W.","affiliations":[],"preferred":false,"id":621939,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kicklighter, David W.","contributorId":48872,"corporation":false,"usgs":false,"family":"Kicklighter","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":621940,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":98080,"text":"sir20095260 - 2009 - Evaluation of LiDAR-Acquired Bathymetric and Topographic Data Accuracy in Various Hydrogeomorphic Settings in the Lower Boise River, Southwestern Idaho, 2007","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20095260","displayToPublicDate":"2009-12-30T00:00:00","publicationYear":"2009","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":"2009-5260","title":"Evaluation of LiDAR-Acquired Bathymetric and Topographic Data Accuracy in Various Hydrogeomorphic Settings in the Lower Boise River, Southwestern Idaho, 2007","docAbstract":"Elevation data in riverine environments can be used in various applications for which different levels of accuracy are required. The Experimental Advanced Airborne Research LiDAR (Light Detection and Ranging) - or EAARL - system was used to obtain topographic and bathymetric data along the lower Boise River, southwestern Idaho, for use in hydraulic and habitat modeling. The EAARL data were post-processed into bare earth and bathymetric raster and point datasets.\r\n\r\nConcurrently with the EAARL data collection, real-time kinetic global positioning system and total station ground-survey data were collected in three areas within the lower Boise River basin to assess the accuracy of the EAARL elevation data in different hydrogeomorphic settings. The accuracies of the EAARL-derived elevation data, determined in open, flat terrain, to provide an optimal vertical comparison surface, had root mean square errors ranging from 0.082 to 0.138 m. Accuracies for bank, floodplain, and in-stream bathymetric data had root mean square errors ranging from 0.090 to 0.583 m. The greater root mean square errors for the latter data are the result of high levels of turbidity in the downstream ground-survey area, dense tree canopy, and horizontal location discrepancies between the EAARL and ground-survey data in steeply sloping areas such as riverbanks.\r\n\r\nThe EAARL point to ground-survey comparisons produced results similar to those for the EAARL raster to ground-survey comparisons, indicating that the interpolation of the EAARL points to rasters did not introduce significant additional error. The mean percent error for the wetted cross-sectional areas of the two upstream ground-survey areas was 1 percent. The mean percent error increases to -18 percent if the downstream ground-survey area is included, reflecting the influence of turbidity in that area.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095260","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Skinner, K.D., 2009, Evaluation of LiDAR-Acquired Bathymetric and Topographic Data Accuracy in Various Hydrogeomorphic Settings in the Lower Boise River, Southwestern Idaho, 2007: U.S. Geological Survey Scientific Investigations Report 2009-5260, iv, 13 p., https://doi.org/10.3133/sir20095260.","productDescription":"iv, 13 p.","temporalStart":"2007-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":125866,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5260.jpg"},{"id":13314,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5260/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.25,43.416666666666664 ], [ -117.25,44 ], [ -116,44 ], [ -116,43.416666666666664 ], [ -117.25,43.416666666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a09e4b07f02db5fafeb","contributors":{"authors":[{"text":"Skinner, Kenneth D. 0000-0003-1774-6565 kskinner@usgs.gov","orcid":"https://orcid.org/0000-0003-1774-6565","contributorId":1836,"corporation":false,"usgs":true,"family":"Skinner","given":"Kenneth","email":"kskinner@usgs.gov","middleInitial":"D.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304084,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":98081,"text":"sir20095249 - 2009 - Reconnaissance Assessment of the Potential for Roadside Dry Wells to Affect Water Quality on the Island of Hawai'i","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20095249","displayToPublicDate":"2009-12-30T00:00:00","publicationYear":"2009","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":"2009-5249","title":"Reconnaissance Assessment of the Potential for Roadside Dry Wells to Affect Water Quality on the Island of Hawai'i","docAbstract":"The County of Hawai'i Department of Public Works (DPW) uses dry wells to dispose of stormwater runoff from roads. Recently, concern has been raised that water entering the dry wells may transport contaminants to groundwater and affect the quality of receiving waters. The DPW operates 2,052 dry wells. Compiling an inventory of these dry wells and sorting it on the basis of presence or absence of urbanization in the drainage area, distance between the bottom of the dry well and the water table, and proximity to receiving waters helps identify the dry wells having greatest potential to affect the quality of receiving waters so that future studies or mitigation efforts can focus on a smaller number of dry wells. The drainage areas of some DPW dry wells encompass urbanized areas, which could be a source of contaminants. Some dry wells penetrate close to or through the water table, eliminating or substantially reducing opportunities for contaminant attenuation between the ground surface and water table. Dry wells that have drainage areas that encompass urbanization, penetrate to near the water table, and are near the coast have the highest potential to affect the quality of coastal waters (this study did not consider specific sections of coastline that may be of greater concern than others). Some DPW dry wells, including a few that have drainage areas that encompass urbanization, lie within the areas contributing recharge (ACR) to drinking-water wells. Numerical groundwater modeling studies by previous investigators indicate that water infiltrating those dry wells could eventually be pumped at drinking-water wells. \r\n\r\nDry wells that have a high potential for affecting coastal receiving waters or drinking-water wells can be the focus of studies to further understand the effect of the dry wells on the quality of receiving waters. Possible study approaches include sampling for contaminants at the dry well and receiving water, injecting and monitoring the movement of tracers, and numerical modeling. To fully assess whether dry wells actually pose a significant contamination threat to receiving waters, results from modeling or monitoring must be compared to limits for contaminant concentration at receiving waters. These limits are usually established by the agencies tasked with protecting those waters.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095249","collaboration":"Prepared in cooperation with the County of Hawai'i Department of Public Works","usgsCitation":"Izuka, S.K., Senter, C., and Johnson, A.G., 2009, Reconnaissance Assessment of the Potential for Roadside Dry Wells to Affect Water Quality on the Island of Hawai'i: U.S. Geological Survey Scientific Investigations Report 2009-5249, vi, 56 p., https://doi.org/10.3133/sir20095249.","productDescription":"vi, 56 p.","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":125787,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5249.jpg"},{"id":13315,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5249/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.25,18.5 ], [ -156.25,20.5 ], [ -154.5,20.5 ], [ -154.5,18.5 ], [ -156.25,18.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a51e4b07f02db629e39","contributors":{"authors":[{"text":"Izuka, Scot K. 0000-0002-8758-9414 skizuka@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-9414","contributorId":2645,"corporation":false,"usgs":true,"family":"Izuka","given":"Scot","email":"skizuka@usgs.gov","middleInitial":"K.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senter, Craig A.","contributorId":40310,"corporation":false,"usgs":true,"family":"Senter","given":"Craig A.","affiliations":[],"preferred":false,"id":304087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Adam G. 0000-0003-2448-5746 ajohnson@usgs.gov","orcid":"https://orcid.org/0000-0003-2448-5746","contributorId":4752,"corporation":false,"usgs":true,"family":"Johnson","given":"Adam","email":"ajohnson@usgs.gov","middleInitial":"G.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304086,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":98077,"text":"ofr20091269 - 2009 - Predictive Models of the Hydrological Regime of Unregulated Streams in Arizona","interactions":[],"lastModifiedDate":"2012-02-10T00:11:52","indexId":"ofr20091269","displayToPublicDate":"2009-12-30T00:00:00","publicationYear":"2009","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":"2009-1269","title":"Predictive Models of the Hydrological Regime of Unregulated Streams in Arizona","docAbstract":"Three statistical models were developed by the U.S. Geological Survey in cooperation with the Arizona Department of Environmental Quality to improve the predictability of flow occurrence in unregulated streams throughout Arizona. The models can be used to predict the probabilities of the hydrological regime being one of four categories developed by this investigation: perennial, which has streamflow year-round; nearly perennial, which has streamflow 90 to 99.9 percent of the year; weakly perennial, which has streamflow 80 to 90 percent of the year; or nonperennial, which has streamflow less than 80 percent of the year. The models were developed to assist the Arizona Department of Environmental Quality in selecting sites for participation in the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program. \r\n\r\nOne model was developed for each of the three hydrologic provinces in Arizona - the Plateau Uplands, the Central Highlands, and the Basin and Range Lowlands. The models for predicting the hydrological regime were calibrated using statistical methods and explanatory variables of discharge, drainage-area, altitude, and location data for selected U.S. Geological Survey streamflow-gaging stations and a climate index derived from annual precipitation data. Models were calibrated on the basis of streamflow data from 46 stations for the Plateau Uplands province, 82 stations for the Central Highlands province, and 90 stations for the Basin and Range Lowlands province. \r\n\r\nThe models were developed using classification trees that facilitated the analysis of mixed numeric and factor variables. In all three models, a threshold stream discharge was the initial variable to be considered within the classification tree and was the single most important explanatory variable. If a stream discharge value at a station was below the threshold, then the station record was determined as being nonperennial. If, however, the stream discharge was above the threshold, subsequent decisions were made according to the classification tree and explanatory variables to determine the hydrological regime of the reach as being perennial, nearly perennial, weakly perennial, or nonperennial. Using model calibration data, misclassification rates for each model were 17 percent for the Plateau Uplands, 15 percent for the Central Highlands, and 14 percent for the Basin and Range Lowlands models. The actual misclassification rate may be higher; however, the model has not been field verified for a full error assessment. \r\n\r\nThe calibrated models were used to classify stream reaches for which the Arizona Department of Environmental Quality had collected miscellaneous discharge measurements. A total of 5,080 measurements at 696 sites were routed through the appropriate classification tree to predict the hydrological regime of the reaches in which the measurements were made. The predictions resulted in classification of all stream reaches as perennial or nonperennial; no reaches were predicted as nearly perennial or weakly perennial. The percentages of sites predicted as being perennial and nonperennial, respectively, were 77 and 23 for the Plateau Uplands, 87 and 13 for the Central Highlands, and 76 and 24 for the Basin and Range Lowlands. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091269","collaboration":"Prepared in cooperation with the Arizona Department of Environmental Quality","usgsCitation":"Anning, D.W., and Parker, J.T., 2009, Predictive Models of the Hydrological Regime of Unregulated Streams in Arizona: U.S. Geological Survey Open-File Report 2009-1269, Report: iv, 33 p.; 4 Appendixes, https://doi.org/10.3133/ofr20091269.","productDescription":"Report: iv, 33 p.; 4 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":125775,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1269.jpg"},{"id":13311,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1269/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -115.5,31 ], [ -115.5,38 ], [ -109,38 ], [ -109,31 ], [ -115.5,31 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0ae4b07f02db5fb89c","contributors":{"authors":[{"text":"Anning, David W. dwanning@usgs.gov","contributorId":432,"corporation":false,"usgs":true,"family":"Anning","given":"David","email":"dwanning@usgs.gov","middleInitial":"W.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, John T.C.","contributorId":18766,"corporation":false,"usgs":true,"family":"Parker","given":"John","email":"","middleInitial":"T.C.","affiliations":[],"preferred":false,"id":304080,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":98078,"text":"ofr20091280 - 2009 - Land-cover change in the Lower Mississippi Valley, 1973-2000","interactions":[],"lastModifiedDate":"2017-03-29T13:28:24","indexId":"ofr20091280","displayToPublicDate":"2009-12-30T00:00:00","publicationYear":"2009","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":"2009-1280","title":"Land-cover change in the Lower Mississippi Valley, 1973-2000","docAbstract":"<p>The Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. The project is coordinated by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in conjunction with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA). Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 were processed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into four temporal periods: 1973 to1980, 1980 to 1986, 1986 to 1992, 1992 to 2000 and overall from 1973 to 2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize and evaluate land-cover change using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation.</p><p>The rates of land-cover change were estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images were used to interpret land-cover change. The sample block data then were incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20091280","usgsCitation":"Karstensen, K.A., and Sayler, K., 2009, Land-cover change in the Lower Mississippi Valley, 1973-2000: U.S. Geological Survey Open-File Report 2009-1280, iv, 13 p., https://doi.org/10.3133/ofr20091280.","productDescription":"iv, 13 p.","temporalStart":"1973-01-01","temporalEnd":"2000-12-31","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":383,"text":"Mid-Continent Geographic Science Center","active":true,"usgs":true}],"links":[{"id":338631,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2009/1280/pdf/of2009-1280.pdf"},{"id":125869,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1280.jpg"},{"id":13312,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1280/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95,29 ], [ -95,38 ], [ -87,38 ], [ -87,29 ], [ -95,29 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6ae344","contributors":{"authors":[{"text":"Karstensen, Krista A. kkarstensen@usgs.gov","contributorId":286,"corporation":false,"usgs":true,"family":"Karstensen","given":"Krista","email":"kkarstensen@usgs.gov","middleInitial":"A.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":304081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sayler, Kristi L. 0000-0003-2514-242X sayler@usgs.gov","orcid":"https://orcid.org/0000-0003-2514-242X","contributorId":2988,"corporation":false,"usgs":true,"family":"Sayler","given":"Kristi","email":"sayler@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":304082,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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