Hydrologically significant flow and storage of water occur in macropores and fractures that are only partially filled. To accommodate such processes in flow models, we propose a three-domain framework. Two of the domains correspond to water flow and water storage in a fracture-facial region, in addition to the third domain of matrix water. The fracture-facial region, typically within a fraction of a millimeter of the fracture wall, includes a flowing phase whose fullness is determined by the availability and flux of preferentially flowing water, and a static storage portion whose fullness is determined by the local matric potential. The flow domain can be modeled with the source-responsive preferential flow model, and the roughness-storage domain can be modeled with capillary relations applied on the fracture-facial area. The matrix domain is treated using traditional unsaturated flow theory. We tested the model with application to the hydrology of the Chalk formation in southern England, coherently linking hydrologic information including recharge estimates, streamflow, water table fluctuation, imaging by electron microscopy, and surface roughness. The quantitative consistency of the three-domain matrix-microcavity-film model with this body of diverse data supports the hypothesized distinctions and active mechanisms of the three domains and establishes the usefulness of this framework.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Fluid dynamics in complex fractured-porous systems","language":"English","publisher":"Wiley","doi":"10.1002/9781118877517.ch12","usgsCitation":"Nimmo, J.R., and Malek-Mohammadi, S., 2015, Quantifying water flow and retention in an unsaturated fracture-facial domain, chap. of Fluid dynamics in complex fractured-porous systems, p. 169-182, https://doi.org/10.1002/9781118877517.ch12.","productDescription":"14 p.","startPage":"169","endPage":"182","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054366","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":324559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-12","publicationStatus":"PW","scienceBaseUri":"57739fb5e4b07657d1a90d33","contributors":{"authors":[{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":580104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malek-Mohammadi, Siamak","contributorId":149944,"corporation":false,"usgs":false,"family":"Malek-Mohammadi","given":"Siamak","email":"","affiliations":[{"id":17862,"text":"Bradley University","active":true,"usgs":false}],"preferred":false,"id":580105,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70147324,"text":"sir20155059 - 2015 - Water levels and water quality in the Mississippi River Valley alluvial aquifer in eastern Arkansas, 2012","interactions":[],"lastModifiedDate":"2015-06-11T15:47:35","indexId":"sir20155059","displayToPublicDate":"2015-06-11T15:30:00","publicationYear":"2015","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":"2015-5059","title":"Water levels and water quality in the Mississippi River Valley alluvial aquifer in eastern Arkansas, 2012","docAbstract":"During the spring of 2012, the U.S. Geological Survey, in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey, measured water levels in 342 wells completed in the Mississippi River Valley alluvial aquifer in eastern Arkansas. The Arkansas Natural Resources Commission measured water levels in 11 wells, and the U.S. Department of Agriculture-Natural Resources Conservation Service measured water levels in 239 wells completed in the alluvial aquifer and provided these data to the Arkansas Natural Resources Commission. In 2010, estimated water withdrawals from the alluvial aquifer in Arkansas totaled about 7,592 million gallons per day. Withdrawals more than doubled between 1985 and 2010, about a 115-percent increase.
\nThe regional direction of groundwater flow is generally to the south and east except where flow is affected by groundwater withdrawals. East of Crowleys Ridge, water flows from north to south along Crowleys Ridge and northeast to southwest along the Mississippi River. West of Crowleys Ridge, water flows from northeast to southwest along Crowleys Ridge from Clay County to Craighead County. From Craighead County to Monroe County, a depression redirects groundwater flow from all directions. A depression in Arkansas, Lonoke, and Prairie Counties alters groundwater flow from all directions. South of the Arkansas River, the flow is towards the southeast, except near depressions in Lincoln and Desha Counties and Desha and Chicot Counties where flow is towards the depression. In 2012, the lowest water-level altitude was 73 feet (ft) in Arkansas County. The highest water-level altitude was 288 ft in northeastern Clay County on the western side of Crowleys Ridge.
\nThe 2012 potentiomentric-surface map shows eight depressions, two large depressions and six small depressions. One large depression begins in southeastern Arkansas County, at the Arkansas and Desha County line, extends north into Prairie County, west into Lonoke County, and east into the westernmost part of Monroe County. The area in Lonoke, Prairie, and White Counties in the northwestern half of the depression has a water-level altitude measurement of 90 ft and has expanded into the northern third of Prairie County.
\nThe 2012 potentiometric-surface map shows a general north-south depression with the southern end in central Monroe County through western Lee, St. Francis, Cross, Poinsett, and Craighead Counties and eastern Woodruff and Jackson Counties. There are two deeper areas in this depression, one at the Monroe and Lee County line, with a low water-level altitude measurement of 123 ft, and the second in Poinsett County, with a low water-level altitude measurement of 113 ft. The six small depressions are located in northern Ashley County, in southern Desha and northern Chicot Counties, in eastern Lincoln and western Chicot Counties, at the Arkansas and Desha County line, in northern Phillips County, and in southeastern Greene County.
\nA map showing the difference in water levels was constructed using 541 differences in water levels measured during 2008 and 2012. The difference in measured water levels from 2008 to 2012 ranged from -27.4 ft to 18.7 ft, with a mean of -1.0 ft. The largest decline of -27.4 ft occurred in Lonoke County, and the largest rise of 18.7 ft occurred in Prairie County. Four areas were predominated by declines—west of Crowleys Ridge from Greene County south to Lee County, including Lawrence and southern Woodruff Counties; east of Crowleys Ridge from Clay County south to Poinsett County and Mississippi County; Lonoke and Jefferson Counties; and Ashley, Chicot, Desha, and Drew Counties. Three areas are predominated by rises in measured water levels—east of Crowleys Ridge in Crittenden, Cross, Lee, and St. Francis Counties; Jackson and northern Woodruff Counties; and Arkansas, Monroe, Phillips, Prairie, and White Counties.
\nLong-term water-level changes were evaluated using hydrographs from 319 wells in the alluvial aquifer for the period from 1988 to 2012. The annual rise or decline in water level for the entire study area was -0.45 feet per year (ft/yr) with a range from -2.08 to 0.84 ft/yr. Arkansas County had two different rates of annual decline for the two hydrographs shown, about 0.97 ft/yr and about 0.26 ft/yr.
\nIn Craighead, Cross, Lee, Poinsett, and St. Francis Counties, water levels are declining at a greater rate in areas west of Crowleys Ridge than in areas east of Crowleys Ridge. Two hydrographs are shown in each of Craighead, Cross, Lee, Poinsett, and St. Francis Counties, one on the west side of Crowleys Ridge and one on the east side of Crowleys Ridge. The hydrographs west of Crowleys Ridge have annual water-level declines from -0.91 to -1.24 ft/yr. The hydrographs east of Crowleys Ridge have annual water-level declines from -0.07 to -0.40 ft/yr. The mean county annual water-level declines for these counties range from -0.55 to -0.87 ft/yr.
\nWater samples were collected in the summer of 2012 from142 wells completed in the alluvial aquifer and measured onsite for specific conductance, temperature, and pH. Samples were collected from 94 wells for dissolved chloride analysis. Specific conductance ranged from 91 microsiemens per centimeter at 25 degrees Celsius (μS/cm at 25 °C) in Drew County to 984 μS/cm at 25 °C in Monroe County. The mean specific conductance was 547 μS/cm at 25 °C. Temperature ranged from 18.1 degrees Celsius (°C) in Crittenden County to 22.4 °C in Prairie County. The mean temperature was 22.1 °C. The pH ranged from 8.3 in Randolph County to 6.2 in Drew County and had a median of 7.3. Dissolved chloride concentrations ranged from 3.34 milligrams per liter (mg/L) in Randolph County to 182 mg/L in Lincoln County. The mean chloride concentration was 27.6 mg/L.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155059","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey","usgsCitation":"Schrader, T.P., 2015, Water levels and water quality in the Mississippi River Valley alluvial aquifer in eastern Arkansas, 2012: U.S. Geological Survey Scientific Investigations Report 2015-5059, Report: iv, 63 p.; 2 Plates: 15.0 x 19.0 inches, https://doi.org/10.3133/sir20155059.","productDescription":"Report: iv, 63 p.; 2 Plates: 15.0 x 19.0 inches","numberOfPages":"70","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2008-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-056983","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":301158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155059.jpg"},{"id":301144,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5059/"},{"id":301154,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5059/pdf/sir2015-5059.pdf","text":"Report","size":"1.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301155,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2015/5059/downloads/sir2015-5059-pl1.pdf","text":"Plate 1","size":"1.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 1"},{"id":301156,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2015/5059/downloads/sir2015-5059-pl2.pdf","text":"Plate 2","size":"1.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 2"}],"projection":"Universal Transverse Mercator projection, zone 15","datum":"North American Datum of 1927","country":"United States","state":"Arkansas","otherGeospatial":"Mississippi River Valley alluvial aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.06954956054688,\n 33.00808767987181\n ],\n [\n -92.14302062988281,\n 33.09786930351166\n ],\n [\n -92.12928771972656,\n 33.20824398778792\n ],\n [\n -91.97479248046875,\n 33.30987251398259\n ],\n [\n -91.99058532714844,\n 33.39762556684172\n ],\n [\n -91.73103332519531,\n 33.395332495793745\n ],\n [\n -91.95419311523436,\n 34.09588492955209\n ],\n [\n -92.18490600585938,\n 34.49354133080471\n ],\n [\n -92.25151062011719,\n 34.74330519389396\n ],\n [\n -92.00637817382812,\n 35.068783155653904\n ],\n [\n -91.48521423339844,\n 35.44053326772722\n ],\n [\n -91.62940979003906,\n 35.753756674845675\n ],\n [\n -91.24832153320312,\n 35.888493789015975\n ],\n [\n -91.07734680175781,\n 36.12789245231783\n ],\n [\n -90.78140258789062,\n 36.49804547361385\n ],\n [\n -90.15037536621094,\n 36.49804547361385\n ],\n [\n -90.06179809570312,\n 36.37817351148144\n ],\n [\n -90.06317138671875,\n 36.295204533693536\n ],\n [\n -90.37353515625,\n 35.99578538642032\n ],\n [\n -89.73358154296875,\n 36.005784428799934\n ],\n [\n -89.63607788085938,\n 35.905736972317364\n ],\n [\n -89.91897583007811,\n 35.51881428123057\n ],\n [\n -90.098876953125,\n 35.33977430038646\n ],\n [\n -90.1153564453125,\n 35.110921809704756\n ],\n [\n -90.560302734375,\n 34.58347505599177\n ],\n [\n -90.582275390625,\n 34.420504880133834\n ],\n [\n -90.9283447265625,\n 34.129994745824746\n ],\n [\n -90.9063720703125,\n 34.02990029603907\n ],\n [\n -91.1920166015625,\n 33.4955977448657\n ],\n [\n -91.0821533203125,\n 33.463525475613785\n ],\n [\n -91.0601806640625,\n 33.250172902093894\n ],\n [\n -91.175537109375,\n 33.00405687168934\n ],\n [\n -92.06954956054688,\n 33.00808767987181\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557aa31ae4b0c350d7b9a969","contributors":{"authors":[{"text":"Schrader, Tony P. tpschrad@usgs.gov","contributorId":3027,"corporation":false,"usgs":true,"family":"Schrader","given":"Tony","email":"tpschrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548520,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70160110,"text":"70160110 - 2015 - Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data","interactions":[],"lastModifiedDate":"2015-12-11T15:27:53","indexId":"70160110","displayToPublicDate":"2015-06-10T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data","docAbstract":"Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%–15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model’s lack of fit.
","language":"English","publisher":"IEEE","publisherLocation":"New York","doi":"10.1109/TGRS.2015.2425916","issn":"01962892","usgsCitation":"Junttila, V., Kauranne, T., Finley, A., and Bradford, J.B., 2015, Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data: IEEE Transactions on Geoscience and Remote Sensing, v. 53, no. 10, p. 5600-5612, https://doi.org/10.1109/TGRS.2015.2425916.","productDescription":"13 p.","startPage":"5600","endPage":"5612","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043945","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":312193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312171,"type":{"id":15,"text":"Index Page"},"url":"https://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7108001"}],"volume":"53","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566c01ebe4b09cfe53ca5aee","contributors":{"authors":[{"text":"Junttila, Virpi","contributorId":103547,"corporation":false,"usgs":true,"family":"Junttila","given":"Virpi","email":"","affiliations":[],"preferred":false,"id":581932,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauranne, Tuomo","contributorId":75037,"corporation":false,"usgs":true,"family":"Kauranne","given":"Tuomo","email":"","affiliations":[],"preferred":false,"id":581931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finley, Andrew O.","contributorId":70666,"corporation":false,"usgs":true,"family":"Finley","given":"Andrew O.","affiliations":[],"preferred":false,"id":581930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":581929,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148420,"text":"sim3330 - 2015 - Bathymetric survey of Lake Calumet, Cook County, Illinois","interactions":[],"lastModifiedDate":"2015-09-04T09:24:52","indexId":"sim3330","displayToPublicDate":"2015-06-10T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3330","title":"Bathymetric survey of Lake Calumet, Cook County, Illinois","docAbstract":"The U.S. Geological Survey collected bathymetric data in Lake Calumet and a portion of the Calumet River in the vicinity of Lake Calumet to produce a bathymetric map. The bathymetric survey was made over 3 days (July 26, September 11, and November 7, 2012). Lake Calumet has become a focus area for Asian carp rapid-response efforts by state and federal agencies, and very little bathymetric data existed prior to this survey. This bathymetric survey provides data for a variety of scientific and engineering studies of the area; for example, hydraulic modeling of water and sediment transport from Lake Calumet to the Calumet River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3330","collaboration":"Prepared in cooperation with the Great Lakes Restoration Initiative","usgsCitation":"Duncker, J.J., Johnson, K.K., and Sharpe, J.B., 2015, Bathymetric survey of Lake Calumet, Cook County, Illinois: U.S. Geological Survey Scientific Investigations Map 3330, 1 sheet, https://doi.org/10.3133/sim3330.","productDescription":"1 sheet","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-042792","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":301134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3330.jpg"},{"id":301132,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3330/"},{"id":301133,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3330/pdf/sim3330.pdf","text":"SIM 3330","size":"80 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Illinois","county":"Cook County","otherGeospatial":"Lake Calumet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.60068893432617,\n 41.66284553398066\n ],\n [\n -87.60068893432617,\n 41.687912152121875\n ],\n [\n -87.57777214050293,\n 41.687912152121875\n ],\n [\n -87.57777214050293,\n 41.66284553398066\n ],\n [\n -87.60068893432617,\n 41.66284553398066\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557951afe4b032353cc173ef","contributors":{"authors":[{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Kevin K. 0000-0003-2703-5994 johnsonk@usgs.gov","orcid":"https://orcid.org/0000-0003-2703-5994","contributorId":4220,"corporation":false,"usgs":true,"family":"Johnson","given":"Kevin","email":"johnsonk@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharpe, Jennifer B. 0000-0002-5192-7848 jbsharpe@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-7848","contributorId":2825,"corporation":false,"usgs":true,"family":"Sharpe","given":"Jennifer","email":"jbsharpe@usgs.gov","middleInitial":"B.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548120,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70147198,"text":"sir20155062 - 2015 - Estimated water use in Arkansas, 2010","interactions":[],"lastModifiedDate":"2015-06-10T14:41:58","indexId":"sir20155062","displayToPublicDate":"2015-06-10T14:30:00","publicationYear":"2015","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":"2015-5062","title":"Estimated water use in Arkansas, 2010","docAbstract":"The Arkansas Natural Resources Commission (ANRC) conducts an annual inventory of reported groundwater and surface-water withdrawals in Arkansas in cooperation with the U.S. Geological Survey (USGS). This report describes withdrawals from groundwater and surface-water resources in Arkansas for 2010. The report compiles withdrawals by county for 10 categories of water use—public supply, domestic (self-supplied), commercial (self-supplied), industrial (self-supplied), mining, livestock, aquaculture, irrigation, duck (hunting) clubs, and thermoelectric power generation. Water-use trends in Arkansas from 1965 to 2010 and sources of groundwater withdrawals also are described.
\nDuring 2010, total withdrawals from groundwater and surface-water sources in Arkansas were 11,300 million gallons per day (Mgal/d). Of the total withdrawn, about 69 percent (7,790 Mgal/d) was from groundwater. Public-supply systems served about 94 percent of Arkansas’ population. Public-supply total withdrawals were 429 Mgal/d, with about 69 percent from surface-water sources. The statewide average of per capita residential use from public-supply systems was about 155 gallons per day (gal/d). The domestic (self-supplied) water use was 12.8 Mgal/d. Total commercial (self-supplied) water use was 11.7 Mgal/d. Total industrial (self-supplied) water use was 276 Mgal/d. Total mining water use was 44.3 Mgal/d. Total livestock water use was 39.0 Mgal/d. Total aquaculture water use was 268 Mgal/d. Irrigation water use totaled 8,720 Mgal/d. Total duck (hunting) club water use was 216 Mgal/d. Total thermoelectric power water use was 1,540 Mgal/d.
\nThe three water-use categories with the largest withdrawals and their effects on total water use were examined. Total water use in Arkansas has increased about 428 percent between 1965 and 2010. Total groundwater use increased about 533 percent and total surface-water use increased about 289 percent. Since about 2000, total water use in Arkansas has plateaued, peaking in 2005. The plateauing of total water use is the result of decreasing surface-water use in the irrigation, thermoelectric power, and public-supply categories offsetting the continuing increases in groundwater use in the irrigation category. An examination of total water use and irrigation water-use changes over time demonstrates the increasing dominance of groundwater withdrawals for irrigation on Arkansas’ total water use. Total irrigation water use in Arkansas between 1965 and 2010 has increased about 652 percent. Withdrawals for thermoelectric power water use in Arkansas have continuously accounted for about half of the State’s total surface-water use for the period 1965–2010. Thermoelectric power water use in Arkansas between 1965 and 2010 increased 264 percent. The percent of Arkansas’ population served by public water suppliers has continued to increase while the percentage of the State’s total water use withdrawn by public water suppliers has remained relatively constant. Public-supply water use in Arkansas between 1965 and 2010 increased about 238 percent. Regardless of continuing increases in population, since about 2000, total public-supply water use in Arkansas has plateaued at about 425 Mgal/d.
\nGroundwater withdrawals comprised about 69 percent of the total amount of water used in Arkansas in 2010. Four aquifers in Arkansas account for more than 99 percent of the total groundwater withdrawals. The aquifers in deposits of Quaternary age supplied about 97 percent of all groundwater withdrawals. The Sparta-Memphis aquifer supplied about 2.5 percent of all groundwater withdrawals, the Wilcox aquifer supplied about 0.5 percent of all groundwater withdrawals, and the Paleozoic aquifer supplied about 0.3 percent of all groundwater withdrawals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155062","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission","usgsCitation":"Pugh, A., and Holland, T.W., 2015, Estimated water use in Arkansas, 2010: U.S. Geological Survey Scientific Investigations Report 2015-5062, v, 33 p., https://doi.org/10.3133/sir20155062.","productDescription":"v, 33 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-056330","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":301135,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5062/"},{"id":301136,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5062/pdf/sir2015-5062.pdf","text":"Report","size":"4.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155062.jpg"}],"country":"United States","state":"Arkansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.04296874999999,\n 33.02248191961359\n ],\n [\n -91.1480712890625,\n 33.0178760185549\n ],\n [\n -91.0601806640625,\n 33.426856918285004\n ],\n [\n -91.1810302734375,\n 33.56428403679499\n ],\n [\n -90.7745361328125,\n 34.29353023058858\n ],\n [\n -90.5767822265625,\n 34.43862840686652\n ],\n [\n -90.5328369140625,\n 34.642247047768535\n ],\n [\n -90.2581787109375,\n 34.939985151560435\n ],\n [\n -90.274658203125,\n 35.02999636902566\n ],\n [\n -90.08239746093749,\n 35.232159412017154\n ],\n [\n -90.1043701171875,\n 35.429344044107154\n ],\n [\n -89.6484375,\n 35.91129848822746\n ],\n [\n -89.7418212890625,\n 35.99578538642032\n ],\n [\n -90.3680419921875,\n 36.00467348670187\n ],\n [\n -90.3131103515625,\n 36.115690180653395\n ],\n [\n -90.0604248046875,\n 36.301845303684345\n ],\n [\n -90.076904296875,\n 36.40359962073253\n ],\n [\n -90.13732910156249,\n 36.43012234551576\n ],\n [\n -90.164794921875,\n 36.49638952000399\n ],\n [\n -94.61975097656249,\n 36.49638952000399\n ],\n [\n -94.43298339843749,\n 35.392408576059616\n ],\n [\n -94.48516845703125,\n 33.637489243170826\n ],\n [\n -94.38629150390624,\n 33.55055114384406\n ],\n [\n -94.0704345703125,\n 33.57572644624357\n ],\n [\n -94.04296874999999,\n 33.5459730276919\n ],\n [\n -94.04296874999999,\n 33.02248191961359\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557951b0e4b032353cc173f1","contributors":{"authors":[{"text":"Pugh, Aaron L. apugh@usgs.gov","contributorId":2480,"corporation":false,"usgs":true,"family":"Pugh","given":"Aaron L.","email":"apugh@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holland, Terrance W.","contributorId":45754,"corporation":false,"usgs":true,"family":"Holland","given":"Terrance","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":545722,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155002,"text":"70155002 - 2015 - Organic carbon burial in lakes and reservoirs of the conterminous United States","interactions":[],"lastModifiedDate":"2018-08-09T12:49:27","indexId":"70155002","displayToPublicDate":"2015-06-10T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Organic carbon burial in lakes and reservoirs of the conterminous United States","docAbstract":"Organic carbon (OC) burial in lacustrine sediments represents an important sink in the global carbon cycle; however, large-scale OC burial rates are poorly constrained, primarily because of the sparseness of available data sets. Here we present an analysis of OC burial rates in water bodies of the conterminous U.S. (CONUS) that takes advantage of recently developed national-scale data sets on reservoir sedimentation rates, sediment OC concentrations, lake OC burial rates, and water body distributions. We relate these data to basin characteristics and land use in a geostatistical analysis to develop an empirical model of OC burial in water bodies of the CONUS. Our results indicate that CONUS water bodies sequester 20.8 (95% CI: 9.4–65.8) Tg C yr–1, and spatial patterns in OC burial are strongly influenced by water body type, size, and abundance; land use; and soil and vegetation characteristics in surrounding areas. Carbon burial is greatest in the central and southeastern regions of the CONUS, where cultivation and an abundance of small water bodies enhance accumulation of sediment and OC in aquatic environments.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/acs.est.5b00373","usgsCitation":"Clow, D.W., Stackpoole, S.M., Verdin, K.L., Butman, D.E., Zhu, Z., Krabbenhoft, D.P., and Striegl, R.G., 2015, Organic carbon burial in lakes and reservoirs of the conterminous United States: Environmental Science & Technology, v. 49, no. 13, p. 7614-7622, https://doi.org/10.1021/acs.est.5b00373.","productDescription":"9 p.","startPage":"7614","endPage":"7622","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064948","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":305957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}\n","volume":"49","issue":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-22","publicationStatus":"PW","scienceBaseUri":"55b361b5e4b09a3b01b5dab1","chorus":{"doi":"10.1021/acs.est.5b00373","url":"http://dx.doi.org/10.1021/acs.est.5b00373","publisher":"American Chemical Society (ACS)","authors":"Clow David W., Stackpoole Sarah M., Verdin Kristine L., Butman David E., Zhu Zhiliang, Krabbenhoft David P., Striegl Robert G.","journalName":"Environmental Science & Technology","publicationDate":"7/7/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science 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0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":200,"text":"Coop Res Unit 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quadrangle, San Diego County, California","docAbstract":"The Julian 7.5' quadrangle lies within the Jurassic-Cretaceous Peninsular Ranges batholith of southern California and Baja California. Four granitic plutonic units and one gabbroic unit, most comprising a number of individual plutons, have been mapped in the Julian quadrangle and informal names have been assigned. The formal name Cuyamaca Gabbro has been retained. In addition to these plutonic units, metasedimentary and minor metavolcanic rocks occur in steeply dipping tabular bodies, or screens, within and between plutons.
\nJurassic plutons in the Julian quadrangle underwent synkinematic metamorphism with the result that plutonic contacts and foliation are concordant with those in the surrounding metamorphosed country rocks. Foliation in Jurassic plutons consists of the planar orientation of recrystallized mineral grains and aggregates; deformation textures include augen gneiss, mylonitic gneiss, and mylonite. Structural studies indicate that a significant part of this deformation took place in the Cretaceous and, therefore, the regional foliation in this part of the batholith clearly postdates intrusion of many Cretaceous plutons.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr9416","usgsCitation":"Todd, V., 2015, Geologic map of the Julian 7.5' quadrangle, San Diego County, California: U.S. Geological Survey Open-File Report 94-16, Pamphlet: ii, 18 p.; 1 Plate: 31.99 × 32.00 inches; Readme; Metadata; Database; Shapefile, https://doi.org/10.3133/ofr9416.","productDescription":"Pamphlet: ii, 18 p.; 1 Plate: 31.99 × 32.00 inches; Readme; Metadata; Database; Shapefile","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":301129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr9416.jpg"},{"id":398355,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_103698.htm"},{"id":301122,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/1994/0016/downloads/ofr94-16_readme.txt","text":"Readme","linkFileType":{"id":2,"text":"txt"},"description":"Readme"},{"id":301121,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/1994/0016/pdf/ofr94-16_map.pdf","text":"Map","linkFileType":{"id":1,"text":"pdf"},"description":"Map"},{"id":301120,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/1994/0016/pdf/ofr94-16_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"Pamphlet"},{"id":301119,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/1994/0016/"},{"id":301128,"rank":10,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/1994/0016/downloads/topo_base_Julian.tif","text":"Julian 7.5' quadrangle topographic map","description":"Julian 7.5' quadrangle topographic map"},{"id":301127,"rank":9,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/1994/0016/downloads/Julian.style","text":"ESRI Styles","description":"ESRI Styles"},{"id":301126,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/1994/0016/downloads/ofr94-16_shape.zip","text":"Shapefile","linkFileType":{"id":6,"text":"zip"},"description":"Shapefile"},{"id":301125,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/1994/0016/downloads/ofr94-16_database.zip","text":"Database","linkFileType":{"id":6,"text":"zip"},"description":"Database","linkHelpText":"ESRI ArcGIS 10.2 File Geodatabase"},{"id":301124,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/1994/0016/downloads/ofr94-16_metadata.xml","text":"Metadata","description":"Metadata"},{"id":301123,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/1994/0016/downloads/ofr94-16_metadata.txt","text":"Metadata","linkFileType":{"id":2,"text":"txt"},"description":"Metadata"}],"country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Julian quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.72973632812499,\n 32.95797741405952\n ],\n [\n -116.72973632812499,\n 33.17664043594348\n ],\n [\n -116.51550292968749,\n 33.17664043594348\n ],\n [\n -116.51550292968749,\n 32.95797741405952\n ],\n [\n -116.72973632812499,\n 32.95797741405952\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557951b2e4b032353cc173f5","contributors":{"authors":[{"text":"Todd, Victoria R.","contributorId":87544,"corporation":false,"usgs":true,"family":"Todd","given":"Victoria R.","affiliations":[],"preferred":false,"id":511721,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70156781,"text":"70156781 - 2015 - Methylmercury bioaccumulation in stream food webs declines with increasing primary production","interactions":[],"lastModifiedDate":"2018-08-09T12:47:50","indexId":"70156781","displayToPublicDate":"2015-06-10T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Methylmercury bioaccumulation in stream food webs declines with increasing primary production","docAbstract":"Opposing hypotheses posit that increasing primary productivity should result in either greater or lesser contaminant accumulation in stream food webs. We conducted an experiment to evaluate primary productivity effects on MeHg accumulation in stream consumers. We varied light for 16 artificial streams creating a productivity gradient (oxygen production =0.048–0.71 mg O2 L–1 d–1) among streams. Two-level food webs were established consisting of phytoplankton/filter feeding clam, periphyton/grazing snail, and leaves/shredding amphipod (Hyalella azteca). Phytoplankton and periphyton biomass, along with MeHg removal from the water column, increased significantly with productivity, but MeHg concentrations in these primary producers declined. Methylmercury concentrations in clams and snails also declined with productivity, and consumer concentrations were strongly correlated with MeHg concentrations in primary producers. Heterotroph biomass on leaves, MeHg in leaves, and MeHg in Hyalella were unrelated to stream productivity. Our results support the hypothesis that contaminant bioaccumulation declines with stream primary production via the mechanism of bloom dilution (MeHg burden per cell decreases in algal blooms), extending patterns of contaminant accumulation documented in lakes to lotic systems.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/acs.est.5b00911","usgsCitation":"Walters, D., D.F. Raikow, C.R. Hammerschmidt, Mehling, M., Kovach, A., and J.T. Oris, 2015, Methylmercury bioaccumulation in stream food webs declines with increasing primary production: Environmental Science & Technology, v. 49, no. 13, p. 7762-7769, https://doi.org/10.1021/acs.est.5b00911.","productDescription":"8 p.","startPage":"7762","endPage":"7769","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063132","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":307717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-10","publicationStatus":"PW","scienceBaseUri":"55e57ab1e4b05561fa2086a9","contributors":{"authors":[{"text":"Walters, David 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":147135,"corporation":false,"usgs":true,"family":"Walters","given":"David","email":"waltersd@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":570516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D.F. Raikow","contributorId":147136,"corporation":false,"usgs":false,"family":"D.F. Raikow","affiliations":[{"id":7237,"text":"NPS, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":570517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"C.R. Hammerschmidt","contributorId":147137,"corporation":false,"usgs":false,"family":"C.R. Hammerschmidt","affiliations":[{"id":13420,"text":"Wright State Univ.","active":true,"usgs":false}],"preferred":false,"id":570518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mehling, M.G.","contributorId":147138,"corporation":false,"usgs":false,"family":"Mehling","given":"M.G.","email":"","affiliations":[{"id":16790,"text":"Chatham Univ.","active":true,"usgs":false}],"preferred":false,"id":570519,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kovach, A.","contributorId":147139,"corporation":false,"usgs":false,"family":"Kovach","given":"A.","email":"","affiliations":[{"id":16791,"text":"GEI","active":true,"usgs":false}],"preferred":false,"id":570520,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"J.T. Oris","contributorId":147140,"corporation":false,"usgs":false,"family":"J.T. Oris","affiliations":[{"id":16792,"text":"Miami Univ.","active":true,"usgs":false}],"preferred":false,"id":570521,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70148492,"text":"70148492 - 2015 - Survival and growth of invasive Indo-Pacific lionfish at low salinities","interactions":[],"lastModifiedDate":"2015-06-10T10:50:15","indexId":"70148492","displayToPublicDate":"2015-06-10T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Survival and growth of invasive Indo-Pacific lionfish at low salinities","docAbstract":"Invasive Indo-Pacific lionfish [Pterois volitans (Linnaeus, 1758) and P. miles (Bennett, 1828)] are now established throughout the Western North Atlantic. Several studies have documented negative effects of lionfish on marine fauna including significant changes to reef fish community composition. Established populations of lionfish have been documented in several estuaries, and there is concern that the species may invade other low-salinity environments where they could potentially affect native fauna. To gain a better understanding of their low-salinity tolerance, we exposed lionfish to four salinities [5, 10, 20 and 34 (control)]. No lionfish mortality was observed at salinities of 34, 20 or 10, but all fish died at salinity = 5 within 12 days. Lionfish survived for at least a month at a salinity of 10 and an average of about a week at 5. Fish started the experiment at an average mass of 127.9 g, which increased at a rate of 0.55 g per day while they were alive, regardless of salinity treatment. Our research indicated lionfish can survive salinities down to 5 for short periods and thus may penetrate and persist in a variety of estuarine habitats. Further study is needed on effects of salinity levels on early life stages (eggs, larvae).
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre (REABIC)","doi":"10.3391/ai.2015.10.3.08","usgsCitation":"Schofield, P., Huge, D.H., Rezek, T.C., Slone, D., and Morris, J.A., 2015, Survival and growth of invasive Indo-Pacific lionfish at low salinities: Aquatic Invasions, v. 10, no. 3, p. 333-337, https://doi.org/10.3391/ai.2015.10.3.08.","productDescription":"5 p.","startPage":"333","endPage":"337","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054610","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472023,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2015.10.3.08","text":"Publisher Index Page"},{"id":301118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557951b3e4b032353cc173fd","contributors":{"authors":[{"text":"Schofield, Pamela J. 0000-0002-8752-2797 pschofield@usgs.gov","orcid":"https://orcid.org/0000-0002-8752-2797","contributorId":138883,"corporation":false,"usgs":true,"family":"Schofield","given":"Pamela J.","email":"pschofield@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":548412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huge, Dane H. dhuge@usgs.gov","contributorId":4314,"corporation":false,"usgs":true,"family":"Huge","given":"Dane","email":"dhuge@usgs.gov","middleInitial":"H.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":548413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rezek, Troy C.","contributorId":141095,"corporation":false,"usgs":false,"family":"Rezek","given":"Troy","email":"","middleInitial":"C.","affiliations":[{"id":13676,"text":"National Oceanic and Atmospheric Administration, National Ocean Service, National Centers for Coastal Ocean Science, 101 Pivers Island Road, Beaufort, North Carolina 28516, USA","active":true,"usgs":false}],"preferred":false,"id":548414,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Slone, Daniel H. 0000-0002-9903-9727 dslone@usgs.gov","orcid":"https://orcid.org/0000-0002-9903-9727","contributorId":140621,"corporation":false,"usgs":true,"family":"Slone","given":"Daniel H.","email":"dslone@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":548416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morris, James A. Jr.","contributorId":141096,"corporation":false,"usgs":false,"family":"Morris","given":"James","suffix":"Jr.","email":"","middleInitial":"A.","affiliations":[{"id":13676,"text":"National Oceanic and Atmospheric Administration, National Ocean Service, National Centers for Coastal Ocean Science, 101 Pivers Island Road, Beaufort, North Carolina 28516, USA","active":true,"usgs":false}],"preferred":false,"id":548415,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148526,"text":"70148526 - 2015 - Evolution of Mars’ Northern Polar Seasonal CO2 deposits: variations in surface brightness and bulk density","interactions":[],"lastModifiedDate":"2015-08-17T15:19:01","indexId":"70148526","displayToPublicDate":"2015-06-10T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Evolution of Mars’ Northern Polar Seasonal CO2 deposits: variations in surface brightness and bulk density","docAbstract":"Small scale variations of seasonal ice are explored at different geomorphic units on the Northern Polar Seasonal Cap (NPSC). We use seasonal rock shadow measurements, combined with visible and thermal observations, to calculate density over time. The coupling of volume density and albedo allows us to determine the microphysical state of the seasonal CO2 ice. We find two distinct endmembers across the NPSC: 1) Snow deposits may anneal to form an overlying slab layer that fractures. These low density deposits maintain relatively constant densities over springtime. 2) Porous slab deposits likely anneal rapidly in early spring and fracture in late spring. These high density deposits dramatically increase in density over time. The endmembers appear to be correlated with latitude.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2014JE004706","usgsCitation":"Mount, C.P., and Titus, T.N., 2015, Evolution of Mars’ Northern Polar Seasonal CO2 deposits: variations in surface brightness and bulk density: Journal of Geophysical Research E: Planets, v. 120, no. 7, p. 1252-1266, https://doi.org/10.1002/2014JE004706.","productDescription":"15 p.","startPage":"1252","endPage":"1266","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057802","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":301194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-07","publicationStatus":"PW","scienceBaseUri":"557c02c9e4b023124e8edf11","chorus":{"doi":"10.1002/2014je004706","url":"http://dx.doi.org/10.1002/2014je004706","publisher":"Wiley-Blackwell","authors":"Mount Christopher P., Titus Timothy N.","journalName":"Journal of Geophysical Research: Planets","publicationDate":"7/2015"},"contributors":{"authors":[{"text":"Mount, Christopher P. cmount@usgs.gov","contributorId":4794,"corporation":false,"usgs":true,"family":"Mount","given":"Christopher","email":"cmount@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":548512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":548511,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148495,"text":"70148495 - 2015 - The influence of prefire tree growth and crown condition on postfire mortality of sugar pine following prescribed fire in Sequoia National Park","interactions":[],"lastModifiedDate":"2015-06-11T10:27:58","indexId":"70148495","displayToPublicDate":"2015-06-10T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1170,"text":"Canadian Journal of Forest Research","active":true,"publicationSubtype":{"id":10}},"title":"The influence of prefire tree growth and crown condition on postfire mortality of sugar pine following prescribed fire in Sequoia National Park","docAbstract":"Tree mortality is a vital component of forest management in the context of prescribed fires; however, few studies have examined the effect of prefire tree health on postfire mortality. This is especially relevant for sugar pine (Pinus lambertiana Douglas), a species experiencing population declines due to a suite of anthropogenic factors. Using data from an old-growth mixed-conifer forest in Sequoia National Park, we evaluated the effects of fire, tree size, prefire radial growth, and crown condition on postfire mortality. Models based only on tree size and measures of fire damage were compared with models that included tree size, fire damage, and prefire tree health (e.g., measures of prefire tree radial growth or crown condition). Immediately following the fire, the inclusion of different metrics of prefire tree health produced variable improvements over the models that included only tree size and measures of fire damage, as models that included measures of crown condition performed better than fire-only models, but models that included measures of prefire radial growth did not perform better. However, 5 years following the fire, sugar pine mortality was best predicted by models that included measures of both fire damage and prefire tree health, specifically, diameter at breast height (DBH, 1.37 m), crown scorch, 30-year mean growth, and the number of sharp declines in growth over a 30-year period. This suggests that factors that influence prefire tree health (e.g., drought, competition, pathogens, etc.) may partially determine postfire mortality, especially when accounting for delayed mortality following fire.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfr-2014-0449","usgsCitation":"Nesmith, J.C., Das, A., O’Hara, K.L., and van Mantgem, P.J., 2015, The influence of prefire tree growth and crown condition on postfire mortality of sugar pine following prescribed fire in Sequoia National Park: Canadian Journal of Forest Research, v. 45, p. 910-919, https://doi.org/10.1139/cjfr-2014-0449.","productDescription":"10 p.","startPage":"910","endPage":"919","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030332","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":301116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sequoia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.92288208007812,\n 36.33614694088851\n ],\n [\n -118.92288208007812,\n 36.677230602346214\n ],\n [\n -118.6083984375,\n 36.677230602346214\n ],\n [\n -118.6083984375,\n 36.33614694088851\n ],\n [\n -118.92288208007812,\n 36.33614694088851\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557951b5e4b032353cc17401","contributors":{"authors":[{"text":"Nesmith, Jonathan C. B.","contributorId":88618,"corporation":false,"usgs":true,"family":"Nesmith","given":"Jonathan","email":"","middleInitial":"C. B.","affiliations":[],"preferred":false,"id":548429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Das, Adrian J. 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":3842,"corporation":false,"usgs":true,"family":"Das","given":"Adrian J.","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":548428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Hara, Kevin L.","contributorId":9923,"corporation":false,"usgs":true,"family":"O’Hara","given":"Kevin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":548430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422 pvanmantgem@usgs.gov","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":2838,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip","email":"pvanmantgem@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":548427,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148506,"text":"70148506 - 2015 - Application of Bayesian Networks to hindcast barrier island morphodynamics","interactions":[],"lastModifiedDate":"2015-06-10T10:19:06","indexId":"70148506","displayToPublicDate":"2015-06-10T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Application of Bayesian Networks to hindcast barrier island morphodynamics","docAbstract":"Prediction of coastal vulnerability is of increasing concern to policy makers, coastal managers and other stakeholders. Coastal regions and barrier islands along the Atlantic and Gulf coasts are subject to frequent, large storms, whose waves and storm surge can dramatically alter beach morphology, threaten infrastructure, and impact local economies. Given that precise forecasts of regional hazards are challenging, because of the complex interactions between processes on many scales, a range of probable geomorphic change in response to storm conditions is often more helpful than deterministic predictions. Site-specific probabilistic models of coastal change are reliable because they are formulated with observations so that local factors, of potentially high influence, are inherent in the model. The development and use of predictive tools such as Bayesian Networks in response to future storms has the potential to better inform management decisions and hazard preparation in coastal communities. We present several Bayesian Networks designed to hindcast distinct morphologic changes attributable to the Nor'Ida storm of 2009, at Fire Island, New York. Model predictions are informed with historical system behavior, initial morphologic conditions, and a parameterized treatment of wave climate.
\nWe refine a preliminary Bayesian Network by 1) increasing model experience through additional observations, 2) including anthropogenic modification history, and 3) replacing parameterized wave impact values with maximum run-up elevation. Further, we develop and train a pair of generalized models with an additional dataset encompassing a different storm event, which expands the observations beyond our hindcast objective. We compare the skill of the generalized models against the Nor'Ida specific model formulation, balancing the reduced skill with an expectation of increased transferability. Results of Nor'Ida hindcasts ranged in skill from 0.37 to 0.51 and accuracy of 65.0 to 81.9%.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2015.04.006","usgsCitation":"Wilson, K.E., Adams, P.N., Hapke, C.J., Lentz, E., and Brenner, O.T., 2015, Application of Bayesian Networks to hindcast barrier island morphodynamics: Coastal Engineering, v. 102, p. 30-43, https://doi.org/10.1016/j.coastaleng.2015.04.006.","productDescription":"14 p.","startPage":"30","endPage":"43","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059455","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":301114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.34884643554688,\n 40.63688312646408\n ],\n [\n -73.32824707031249,\n 40.60873982383701\n ],\n [\n -73.20602416992188,\n 40.622291783092706\n ],\n [\n -73.00140380859375,\n 40.67126439151552\n ],\n [\n -72.82562255859375,\n 40.73581157695217\n ],\n [\n -72.69653320312499,\n 40.7701418259051\n ],\n [\n -72.71438598632812,\n 40.791979118109566\n ],\n [\n -72.80364990234375,\n 40.76494141246851\n ],\n [\n -72.88467407226562,\n 40.74101426921151\n ],\n [\n -72.94097900390625,\n 40.724364221722716\n ],\n [\n -73.01101684570312,\n 40.69834018178775\n ],\n [\n -73.05084228515625,\n 40.67959657544238\n ],\n [\n -73.14285278320312,\n 40.6629311662891\n ],\n [\n -73.23486328124999,\n 40.64521960545374\n ],\n [\n -73.30078125,\n 40.6410514961004\n ],\n [\n -73.34884643554688,\n 40.63688312646408\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557951aee4b032353cc173ed","contributors":{"authors":[{"text":"Wilson, Kathleen E. kwilson@usgs.gov","contributorId":5788,"corporation":false,"usgs":true,"family":"Wilson","given":"Kathleen","email":"kwilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":548489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Peter N.","contributorId":64361,"corporation":false,"usgs":true,"family":"Adams","given":"Peter","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":548491,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":548490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lentz, Erika E. elentz@usgs.gov","contributorId":141129,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika E.","email":"elentz@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":548492,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brenner, Owen T. 0000-0002-1588-721X obrenner@usgs.gov","orcid":"https://orcid.org/0000-0002-1588-721X","contributorId":4933,"corporation":false,"usgs":true,"family":"Brenner","given":"Owen","email":"obrenner@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":548493,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148505,"text":"70148505 - 2015 - The importance of range edges for an irruptive species during extreme weather events","interactions":[],"lastModifiedDate":"2015-06-10T10:26:17","indexId":"70148505","displayToPublicDate":"2015-06-10T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The importance of range edges for an irruptive species during extreme weather events","docAbstract":"Threats to wildlife species from extreme events, such as droughts, are predicted to increase in frequency and magnitude with climate change. Extreme events can cause mortality and community-level changes, but for some mobile species, movement away from areas affected may be a viable option.
\nWe examined the effect of extreme weather on spatial patterns of abundance for an irruptive grassland bird species, the Dickcissel (Spiza americana).
\nWe calculated route-level annual abundances and abundance anomalies from 1980 to 2012 from North American Breeding Bird Survey data, and classified the Dickcissel’s range into core and edge regions using these abundances. We then compared abundances in the core and edge regions to the standardized precipitation evapotranspiration index, a measure of drought, in linear regressions.
\nWe found that Dickcissel irruptions in the northern range edges were related to drought conditions in the range core, potentially a consequence of birds being ‘pushed’ to the range edge when weather was unsuitable. Specifically, Dickcissels moved into refuge sites containing a high proportion of cultivated crops, with higher vegetation greenness, than those areas they leave during drought years.
\nIn a changing climate where more frequent extreme weather may be more common, conservation strategies for weather-sensitive species may require consideration of habitat in the edges of species’ ranges, even though non-core areas may be unoccupied in ‘normal’ years. Our results highlight the conservation importance of range edges in providing refuge from extreme events, such as drought, and climate change.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-015-0212-6","usgsCitation":"Bateman, B.L., Pidgeon, A.M., Radeloff, V.C., Allstadt, A.J., Akcakaya, H.R., Thogmartin, W.E., Vavrus, S.J., and Heglund, P., 2015, The importance of range edges for an irruptive species during extreme weather events: Landscape Ecology, v. 30, no. 6, p. 1095-1110, https://doi.org/10.1007/s10980-015-0212-6.","productDescription":"16 p.","startPage":"1095","endPage":"1110","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059595","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":301115,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-16","publicationStatus":"PW","scienceBaseUri":"557951b4e4b032353cc173ff","contributors":{"authors":[{"text":"Bateman, Brooke L.","contributorId":141122,"corporation":false,"usgs":false,"family":"Bateman","given":"Brooke","email":"","middleInitial":"L.","affiliations":[{"id":13679,"text":"SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":548482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pidgeon, Anna M.","contributorId":141123,"corporation":false,"usgs":false,"family":"Pidgeon","given":"Anna","email":"","middleInitial":"M.","affiliations":[{"id":13679,"text":"SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":548483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Radeloff, Volker C.","contributorId":141124,"corporation":false,"usgs":false,"family":"Radeloff","given":"Volker","email":"","middleInitial":"C.","affiliations":[{"id":13679,"text":"SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":548484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allstadt, Andrew J.","contributorId":141125,"corporation":false,"usgs":false,"family":"Allstadt","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":13679,"text":"SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":548485,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Akcakaya, H. Resit","contributorId":141126,"corporation":false,"usgs":false,"family":"Akcakaya","given":"H.","email":"","middleInitial":"Resit","affiliations":[{"id":13680,"text":"Department of Ecology and Evolution, Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":548486,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":548481,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vavrus, Stephen J.","contributorId":141127,"corporation":false,"usgs":false,"family":"Vavrus","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":13681,"text":"Center for Climate Research, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":548487,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Heglund, Patricia J.","contributorId":141128,"corporation":false,"usgs":false,"family":"Heglund","given":"Patricia J.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":548488,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70148501,"text":"70148501 - 2015 - Lake Ontario water quality during the 2003 and 2008 intensive field years and comparison with long-term trends","interactions":[],"lastModifiedDate":"2017-10-20T11:06:34","indexId":"70148501","displayToPublicDate":"2015-06-10T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":865,"text":"Aquatic Ecosystem Health & Management","active":true,"publicationSubtype":{"id":10}},"title":"Lake Ontario water quality during the 2003 and 2008 intensive field years and comparison with long-term trends","docAbstract":"Phosphorus loading declined between the 1970s and the 1990s, leading to oligotrophication of the offshore waters of Lake Ontario during that time period. Using lake-wide data from the intensive field years of 2003 and 2008 and from available long-term data sets on several trophic state indicators (total phosphorus [TP], soluble reactive silica [SRSi], chlorophyll a and Secchi disc transparency [SDT]), we tested the hypothesis that oligotrophication of the offshore waters of Lake Ontario has continued in the 2000s. Significant differences between 2003 and 2008 include higher spring (April) TP, SRSi, and SDT in 2008, lower summer (July–August) SDT in 2008, higher summer chlorophyll a in 2008, and lower fall (September) TP, SRSi, and chlorophyll a in 2008. The decline in SRSi from spring to summer was greater in 2008 than in 2003. Change point and regression analyses on the long-term data revealed no trend in spring TP since 1996, in summer chlorophyll a since 1994, in spring SDT since 1998, in spring SRSi or SRSi decline from spring to summer since 1999, or in summer SDT since 2001. Neither the comparison of the 2003 and 2008 surveys nor the analysis of the long-term data supported our hypothesis of continued oligotrophication of the offshore of Lake Ontario in the 2000s.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/14634988.2015.1000787","usgsCitation":"Holeck, K., Rudstam, L.G., Watkins, J., Luckey, F.J., Lantry, J.R., Lantry, B.F., Trometer, E.S., Koops, M., and Johnson, T.B., 2015, Lake Ontario water quality during the 2003 and 2008 intensive field years and comparison with long-term trends: Aquatic Ecosystem Health & Management, v. 18, no. 1, p. 7-17, https://doi.org/10.1080/14634988.2015.1000787.","productDescription":"11 p.","startPage":"7","endPage":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057587","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":301109,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.85412597656249,\n 43.257205668363206\n ],\n [\n -79.31579589843749,\n 43.185152509372955\n ],\n [\n -79.090576171875,\n 43.25320494908846\n ],\n [\n -78.5302734375,\n 43.369119087738554\n ],\n [\n -78.057861328125,\n 43.37311218382002\n ],\n [\n -77.71728515624999,\n 43.329173667843904\n ],\n [\n -77.5634765625,\n 43.213183300738876\n ],\n [\n -77.3492431640625,\n 43.265206318396025\n ],\n [\n -77.0965576171875,\n 43.28520334369384\n ],\n [\n -76.893310546875,\n 43.25320494908846\n ],\n [\n -76.7010498046875,\n 43.33316939281735\n ],\n [\n -76.387939453125,\n 43.52465500687185\n ],\n [\n -76.201171875,\n 43.52863784832998\n ],\n [\n -76.1572265625,\n 43.691707903073805\n ],\n [\n -76.22863769531249,\n 43.84245116699036\n ],\n [\n -76.124267578125,\n 43.93350594453702\n ],\n [\n -76.0198974609375,\n 44.000717834282774\n ],\n [\n -76.1517333984375,\n 44.08758502824518\n ],\n [\n -76.2890625,\n 44.08363928284644\n ],\n [\n -76.3055419921875,\n 44.13885576756881\n ],\n [\n -76.00341796875,\n 44.308126684886126\n ],\n [\n -75.83862304687499,\n 44.457309801319305\n ],\n [\n -75.926513671875,\n 44.50434127765394\n ],\n [\n -76.13525390624999,\n 44.731125592643274\n ],\n [\n -76.497802734375,\n 44.731125592643274\n ],\n [\n -76.695556640625,\n 44.731125592643274\n ],\n [\n -76.761474609375,\n 44.63739123445585\n ],\n [\n -76.541748046875,\n 44.308126684886126\n ],\n [\n -76.728515625,\n 44.18220395771566\n ],\n [\n -77.431640625,\n 44.213709909702054\n ],\n [\n -77.662353515625,\n 44.040218713142146\n ],\n [\n -78.134765625,\n 44.000717834282774\n ],\n [\n -78.804931640625,\n 43.9058083561574\n ],\n [\n -79.134521484375,\n 43.8503744993026\n ],\n [\n -79.508056640625,\n 43.6599240747891\n ],\n [\n -79.73876953125,\n 43.476840397778915\n ],\n [\n -79.903564453125,\n 43.25320494908846\n ],\n [\n -79.85412597656249,\n 43.257205668363206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557951b3e4b032353cc173f9","contributors":{"authors":[{"text":"Holeck, K. 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J.","contributorId":141110,"corporation":false,"usgs":false,"family":"Luckey","given":"F.","email":"","middleInitial":"J.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":548462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lantry, J. R.","contributorId":141111,"corporation":false,"usgs":false,"family":"Lantry","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":548464,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":548458,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Trometer, E. S.","contributorId":141112,"corporation":false,"usgs":false,"family":"Trometer","given":"E.","email":"","middleInitial":"S.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":548465,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koops, M. A.","contributorId":141113,"corporation":false,"usgs":false,"family":"Koops","given":"M. A.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":548466,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnson, Terry B.","contributorId":115694,"corporation":false,"usgs":true,"family":"Johnson","given":"Terry","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":548467,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70148497,"text":"70148497 - 2015 - Sea lamprey mark type, marking rate, and parasite-host relationships for lake trout and other species in Lake Ontario","interactions":[],"lastModifiedDate":"2020-09-24T19:15:05.343424","indexId":"70148497","displayToPublicDate":"2015-06-10T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Sea lamprey mark type, marking rate, and parasite-host relationships for lake trout and other species in Lake Ontario","docAbstract":"We examined how attack frequency by sea lampreys on fishes in Lake Ontario varied in response to sea lamprey abundance and preferred host abundance (lake trout > 433 mm). For this analysis we used two gill net assessment surveys, one angler creel survey, three salmonid spawning run datasets, one adult sea lamprey assessment, and a bottom trawl assessment of dead lake trout. The frequency of fresh sea lamprey marks observed on lake trout from assessment surveys was strongly related to the frequency of sea lamprey attacks observed on salmon and trout from the creel survey and spawning migrations. Attack frequencies on all salmonids examined were related to the ratio between the abundances of adult sea lampreys and lake trout. Reanalysis of the susceptibility to sea lamprey attack for lake trout strains stocked into Lake Ontario reaffirmed that Lake Superior strain lake trout were among the most and Seneca Lake strain among the least susceptible and that Lewis Lake strain lake trout were even more susceptible than the Superior strain. Seasonal attack frequencies indicated that as the number of observed sea lamprey attacks decreased during June–September, the ratio of healing to fresh marks also decreased. Simulation of the ratios of healing to fresh marks indicated that increased lethality of attacks by growing sea lampreys contributed to the decline in the ratios and supported laboratory studies about wound healing duration.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2014.12.013","usgsCitation":"Lantry, B.F., Adams, J.V., Christie, G., Schaner, T., Bowlby, J., Keir, M., Lantry, J., Sullivan, P., Bishop, D., Treska, T., and Morrison, B., 2015, Sea lamprey mark type, marking rate, and parasite-host relationships for lake trout and other species in Lake Ontario: Journal of Great Lakes Research, v. 41, no. 1, p. 266-279, https://doi.org/10.1016/j.jglr.2014.12.013.","productDescription":"14 p.","startPage":"266","endPage":"279","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053444","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":301113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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]\n}","volume":"41","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557951b3e4b032353cc173fb","contributors":{"authors":[{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":548494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":548495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christie, Gavin","contributorId":14778,"corporation":false,"usgs":true,"family":"Christie","given":"Gavin","affiliations":[],"preferred":false,"id":548496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schaner, Teodore","contributorId":141099,"corporation":false,"usgs":false,"family":"Schaner","given":"Teodore","email":"","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":548497,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowlby, James","contributorId":141100,"corporation":false,"usgs":false,"family":"Bowlby","given":"James","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":548498,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keir, Michael","contributorId":141101,"corporation":false,"usgs":false,"family":"Keir","given":"Michael","affiliations":[{"id":6779,"text":"Environment Canada, Burlington, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":548499,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lantry, Jana","contributorId":141102,"corporation":false,"usgs":false,"family":"Lantry","given":"Jana","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":548500,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sullivan, Paul","contributorId":141103,"corporation":false,"usgs":false,"family":"Sullivan","given":"Paul","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":548501,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bishop, Daniel","contributorId":141104,"corporation":false,"usgs":false,"family":"Bishop","given":"Daniel","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":548502,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Treska, Ted","contributorId":141105,"corporation":false,"usgs":false,"family":"Treska","given":"Ted","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":548503,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Morrison, Bruce","contributorId":141106,"corporation":false,"usgs":false,"family":"Morrison","given":"Bruce","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":548504,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70142463,"text":"ds925 - 2015 - Hydrogeologic data and water-quality data from a thick unsaturated zone at a proposed wastewater-treatment facility site, Yucca Valley, San Bernardino County, California, 2008-11","interactions":[],"lastModifiedDate":"2015-06-10T09:04:49","indexId":"ds925","displayToPublicDate":"2015-06-10T09:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"925","title":"Hydrogeologic data and water-quality data from a thick unsaturated zone at a proposed wastewater-treatment facility site, Yucca Valley, San Bernardino County, California, 2008-11","docAbstract":"The Hi-Desert Water District, in the community of Yucca Valley, California, is considering constructing a wastewater-treatment facility and using the reclaimed water to recharge the aquifer system through surface spreading. The Hi-Desert Water District is concerned with possible effects of this recharge on water quality in the underlying groundwater system; therefore, an unsaturated-zone monitoring site was constructed by the U.S. Geological Survey (USGS) to characterize the unsaturated zone, monitor a pilot-scale recharge test, and, ultimately, to monitor the flow of reclaimed water to the water table once the treatment facility is constructed.
\nIn June and July 2008, a borehole (YVUZ-5) was drilled by the USGS through the unsaturated zone in the vicinity of the proposed wastewater-treatment facility site by using an overburden drilling method. In addition to a variety of unsaturated-zone instrumentation, an observation well screened near the water table was installed in the borehole. The drilling procedures, lithologic and geophysical data, construction details, physical properties of unsaturated alluvial deposits, and instrumentation installed in YVUZ-5 are described in this report. Core material was analyzed for bulk-density, porosity, effective porosity, volumetric water content, residual water content, saturation, effective saturation, matric-potential, and saturated hydraulic conductivity. Concentrations of soluble anions, including bromide, chloride, fluoride, sulfate, nitrate, nitrite, phosphate, and orthophosphate, in unsaturated-zone sediment and dissolved in unsaturated-zone water were determined by analyzing water extracted from drill-cutting material. A 0.1-acre pilot-scale infiltration pond was constructed in the vicinity of YVUZ-5. Water was applied to the pond over a period of about 8 months and allowed to infiltrate into the underlying unsaturated zone. Data were collected on chemical and isotopic composition of the groundwater, unsaturated-zone water, and infiltration pond water before, during, and after infiltration of water from the constructed pond. Selected drill cuttings and core samples collected during drilling were analyzed for the presence or absence of denitrifying and nitrate-reducing bacteria.
\nWater levels in the observation well ranged from about 367 to 370 feet below land surface during the period of the study. Measured saturated hydraulic conductivity of core material ranged from 2.1 to 11.0 feet per day. Average vertical infiltration rates in the pilot-scale infiltration pond ranged from 0.7 to 2.4 feet per day. Both denitrifying and nitrate-reducing bacteria were present in drill cutting material in most probable numbers ranging from below detection limits to 2,400,000 for denitrifying and to 93,000 for nitrate-reducing bacteria.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds925","collaboration":"Prepared in cooperation with the Hi-Desert Water District","usgsCitation":"O’Leary, D., Clark, D.A., and Izbicki, J., 2015, Hydrogeologic data and water-quality data from a thick unsaturated zone at a proposed wastewater-treatment facility site, Yucca Valley, San Bernardino County, California, 2008-11: U.S. Geological Survey Data Series 925, x, 68 p., https://doi.org/10.3133/ds925.","productDescription":"x, 68 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2008-06-01","temporalEnd":"2011-12-31","ipdsId":"IP-010954","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":301106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds925.jpg"},{"id":301105,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0925/pdf/ds925.pdf","text":"Report","size":"4.3 MB","description":"Report"},{"id":301103,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0925/"}],"country":"United States","state":"California","county":"San Bernardino County","otherGeospatial":"Yucca Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.4121627807617,\n 34.13511003175254\n ],\n [\n -116.40117645263673,\n 34.13979877188829\n ],\n [\n -116.39173507690428,\n 34.14164577990677\n ],\n [\n -116.38074874877931,\n 34.14235615685566\n ],\n [\n -116.37662887573241,\n 34.14406103716462\n ],\n [\n -116.37096405029297,\n 34.14420310897081\n ],\n [\n -116.36392593383789,\n 34.14292445411448\n ],\n [\n -116.36341094970702,\n 34.12388441525915\n ],\n [\n -116.36787414550781,\n 34.117205176698675\n ],\n [\n -116.36959075927736,\n 34.11024115351507\n ],\n [\n -116.36924743652344,\n 34.10498222546687\n ],\n [\n -116.36804580688475,\n 34.093468295940426\n ],\n [\n -116.36838912963867,\n 34.08550713253843\n ],\n [\n -116.38675689697266,\n 34.082094976194774\n ],\n [\n -116.40289306640624,\n 34.08323237692003\n ],\n [\n -116.40907287597656,\n 34.09034078531726\n ],\n [\n -116.42829895019531,\n 34.10000726293642\n ],\n [\n -116.4466667175293,\n 34.10341869733246\n ],\n [\n -116.46091461181639,\n 34.10498222546687\n ],\n [\n -116.46915435791016,\n 34.10810919505794\n ],\n [\n -116.4712142944336,\n 34.11663670650332\n ],\n [\n -116.46486282348631,\n 34.120189582533065\n ],\n [\n -116.46142959594725,\n 34.12331598996403\n ],\n [\n -116.45421981811522,\n 34.12502125438493\n ],\n [\n -116.43945693969727,\n 34.128715875972134\n ],\n [\n -116.4224624633789,\n 34.13042103147612\n ],\n [\n -116.41422271728514,\n 34.133831239293684\n ],\n [\n -116.4121627807617,\n 34.13511003175254\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557951b2e4b032353cc173f7","contributors":{"authors":[{"text":"O’Leary, David 0000-0001-9888-1739 doleary@usgs.gov","orcid":"https://orcid.org/0000-0001-9888-1739","contributorId":139900,"corporation":false,"usgs":true,"family":"O’Leary","given":"David","email":"doleary@usgs.gov","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Dennis A. daclark@usgs.gov","contributorId":1477,"corporation":false,"usgs":true,"family":"Clark","given":"Dennis","email":"daclark@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":548434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":1375,"corporation":false,"usgs":true,"family":"Izbicki","given":"John A.","email":"jaizbick@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":548436,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70154933,"text":"70154933 - 2015 - Restoration of oyster reefs in an estuarine lake: population dynamics and shell accretion","interactions":[],"lastModifiedDate":"2017-07-20T14:07:27","indexId":"70154933","displayToPublicDate":"2015-06-10T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Restoration of oyster reefs in an estuarine lake: population dynamics and shell accretion","docAbstract":"Restoration activities inherently depend on understanding the spatial and temporal variation in basic demographic rates of the species of interest. For species that modify and maintain their own habitat such as the eastern oyster Crassostrea virginica, understanding demographic rates and their impacts on population and habitat success are crucial to ensuring restoration success. We measured oyster recruitment, density, size distribution, biomass, mortality and Perkinsus marinus infection intensity quarterly for 3 yr on shallow intertidal reefs created with shell cultch in March 2009. All reefs were located within Sister Lake, LA. Reefs were placed in pairs at 3 different locations within the lake; pairs were placed in low and medium energy sites within each location. Restored reefs placed within close proximity (<8 km) experienced very different development trajectories; there was high inter-site and inter-annual variation in recruitment and mortality of oysters, with only slight variation in growth curves. Despite this high variation in population dynamics, all reefs supported dense oyster populations (728 ± 102 ind. m-2) and high live oyster biomass (>14.6 kg m-2) at the end of 3 yr. Shell accretion, on average, exceeded estimated rates required to keep pace with local subsidence and shell loss. Variation in recruitment, growth and survival drives local site-specific population success, which highlights the need to understand local water quality, hydrodynamics, and metapopulation dynamics when planning restoration.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps11198","usgsCitation":"Casas, S.M., La Peyre, J.F., and La Peyre, M., 2015, Restoration of oyster reefs in an estuarine lake: population dynamics and shell accretion: Marine Ecology Progress Series, v. 524, p. 171-184, https://doi.org/10.3354/meps11198.","productDescription":"14 p.","startPage":"171","endPage":"184","ipdsId":"IP-057172","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":472024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps11198","text":"Publisher Index Page"},{"id":344146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Sister Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.00250244140624,\n 29.165053325564653\n ],\n [\n -90.79479217529297,\n 29.165053325564653\n ],\n [\n -90.79479217529297,\n 29.284602230535242\n ],\n [\n -91.00250244140624,\n 29.284602230535242\n ],\n [\n -91.00250244140624,\n 29.165053325564653\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"524","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5971c1c4e4b0ec1a4885dae0","contributors":{"authors":[{"text":"Casas, Sandra M.","contributorId":145452,"corporation":false,"usgs":false,"family":"Casas","given":"Sandra","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":705871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"La Peyre, Jerome F.","contributorId":34697,"corporation":false,"usgs":true,"family":"La Peyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":705872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":79375,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan","email":"mlapeyre@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564379,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189621,"text":"70189621 - 2015 - Surface monitoring of microseismicity at the Decatur, Illinois, CO2 sequestration demonstration site","interactions":[],"lastModifiedDate":"2019-06-03T13:25:10","indexId":"70189621","displayToPublicDate":"2015-06-10T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Surface monitoring of microseismicity at the Decatur, Illinois, CO2 sequestration demonstration site","docAbstract":"Sequestration of CO2 into subsurface reservoirs can play an important role in limiting future emission of CO2 into the atmosphere (e.g., Benson and Cole, 2008). For geologic sequestration to become a viable option to reduce greenhouse gas emissions, large-volume injection of supercritical CO2 into deep sedimentary formations is required. These formations offer large pore volumes and good pore connectivity and are abundant (Bachu, 2003; U.S. Geological Survey Geologic Carbon Dioxide Storage Resources Assessment Team, 2013). However, hazards associated with injection of CO2 into deep formations require evaluation before widespread sequestration can be adopted safely (Zoback and Gorelick, 2012). One of these hazards is the potential to induce seismicity on pre-existing faults or fractures. If these faults or fractures are large and critically stressed, seismic events can occur with magnitudes large enough to pose a hazard to surface installations and, possibly more critical, the seal integrity of the cap rock.
The Decatur, Illinois, carbon capture and storage (CCS) demonstration site is the first, and to date, only CCS project in the United States that injects a large volume of supercritical CO2 into a regionally extensive, undisturbed saline formation. The first phase of the Decatur CCS project was completed in November 2014 after injecting a million metric tons of supercritical CO2 over three years. This phase was led by the Illinois State Geological Survey (ISGS) and included seismic monitoring using deep borehole sensors, with a few sensors installed within the injection horizon. Although the deep borehole network provides a more comprehensive seismic catalog than is presented in this paper, these deep data are not publicly available. We contend that for monitoring induced microseismicity as a possible seismic hazard and to elucidate the general patterns of microseismicity, the U.S. Geological Survey (USGS) surface and shallow borehole network described below provides an adequate event detection threshold.
The formation targeted for injection is the Mount Simon Sandstone, which is laterally extensive, has high porosity and permeability and has the potential to host future CCS projects due to its favorable hydrologic characteristics and proximity to industrial sources of CO2 (Birkholzer and Zhou, 2009). At Decatur, CO2, a byproduct of ethanol production at the Archer Daniels Midland (ADM) facility, is compressed to supercritical state and injected at 2.1 km depth into the 460 m thick Mount Simon Sandstone. This sandstone has varying properties, ranging from the lower, fine- to coarse-grained sandstone with high permeability and porosity, to the middle and upper Mount Simon, which consist of planar, cross-bedded layers of varied permeability and porosity (Leetaru and Freiburg, 2014). The changes in permeability and porosity within the Mount Simon Sandstone, due to depositional and diagenetic differences, create horizontal baffles, which inhibit vertical flow and restrict the injected CO2 to remain near the injection horizon (Bowen et al., 2011). The lowest portion of the Mount Simon Sandstone overlying the Precambrian rhyolite basement is the Pre-Mount Simon interval, generally < 15 m in thickness and composed of fine- to medium-grain size sandstone that is highly deformed (Leetaru and Freiburg, 2014). The basement rhyolite has a clayrich matrix and is fractured, with significant alterations within the fractures. The primary sealing cap rock is the Eau Claire Formation, a 100–150 m thick unit at a depth of roughly 1.69 km (Leetaru and Freiburg, 2014). The Maquoketa Shale Group and the New Albany Shale serve as secondary and tertiary seals at shallower depths of ∼820 and ∼650 m, respectively.
The ISGS managed the Illinois Basin–Decatur Project (IBDP), a three-year project beginning in November 2011, during which carbon dioxide was injected at a rate of ∼1000 metric tons per day until November 2014 (Finley et al., 2011, 2013). ADM manages the Illinois Industrial CCS (ICCS) project, which will inject ∼3000 metric tons/day into a second injection well starting in the summer of 2015.
The USGS began monitoring microseismicity with a 13- station seismic network at Decatur in July 2013 (Fig. 1). This network provides good detection capabilities and azimuthal (focal sphere) coverage for microseismicity with moment magnitudes (Mw) above about −0:5. Here, we report on 19 months of microseismicity monitoring at the Decatur CO2 sequestration site, which permits a detailed look at the evolution and character of injection-induced seismicity.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220150062","usgsCitation":"Kaven, J., Hickman, S.H., McGarr, A.F., and Ellsworth, W.L., 2015, Surface monitoring of microseismicity at the Decatur, Illinois, CO2 sequestration demonstration site: Seismological Research Letters, v. 86, no. 4, p. 1096-1101, https://doi.org/10.1785/0220150062.","productDescription":"6 p. ","startPage":"1096","endPage":"1101","ipdsId":"IP-064149","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","city":"Decatur","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.09088134765625,\n 39.706130149279325\n ],\n [\n -88.78326416015625,\n 39.706130149279325\n ],\n [\n -88.78326416015625,\n 39.9634381223102\n ],\n [\n -89.09088134765625,\n 39.9634381223102\n ],\n [\n -89.09088134765625,\n 39.706130149279325\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"86","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-10","publicationStatus":"PW","scienceBaseUri":"59706fb9e4b0d1f9f065a8c5","contributors":{"authors":[{"text":"Kaven, J. Ole 0000-0003-2625-2786 okaven@usgs.gov","orcid":"https://orcid.org/0000-0003-2625-2786","contributorId":3993,"corporation":false,"usgs":true,"family":"Kaven","given":"J. Ole","email":"okaven@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hickman, Stephen H. 0000-0003-2075-9615 hickman@usgs.gov","orcid":"https://orcid.org/0000-0003-2075-9615","contributorId":2705,"corporation":false,"usgs":true,"family":"Hickman","given":"Stephen","email":"hickman@usgs.gov","middleInitial":"H.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGarr, Arthur F. 0000-0001-9769-4093 mcgarr@usgs.gov","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":3178,"corporation":false,"usgs":true,"family":"McGarr","given":"Arthur","email":"mcgarr@usgs.gov","middleInitial":"F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellsworth, William L. ellsworth@usgs.gov","contributorId":787,"corporation":false,"usgs":true,"family":"Ellsworth","given":"William","email":"ellsworth@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705469,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70147007,"text":"sir20155058 - 2015 - Water-quality trends in the Scituate reservoir drainage area, Rhode Island, 1983-2012","interactions":[],"lastModifiedDate":"2015-06-09T14:49:52","indexId":"sir20155058","displayToPublicDate":"2015-06-09T16:00:00","publicationYear":"2015","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":"2015-5058","title":"Water-quality trends in the Scituate reservoir drainage area, Rhode Island, 1983-2012","docAbstract":"The Scituate Reservoir is the primary source of drinking water for more than 60 percent of the population of Rhode Island. Water-quality and streamflow data collected at 37 surface-water monitoring stations in the Scituate Reservoir drainage area, Rhode Island, from October 2001 through September 2012, water years (WYs) 2002-12, were analyzed to determine water-quality conditions and constituent loads in the drainage area. Trends in water quality, including physical properties and concentrations of constituents, were investigated for the same period and for a longer period from October 1982 through September 2012 (WYs 1983-2012). Water samples were collected and analyzed by the Providence Water Supply Board, the agency that manages the Scituate Reservoir. Streamflow data were collected by the U.S. Geological Survey. Median values and other summary statistics for pH, color, turbidity, alkalinity, chloride, nitrite, nitrate, total coliform bacteria, Escherichia coli (E. coli), and orthophosphate were calculated for WYs 2003-12 for all 37 monitoring stations. Instantaneous loads and yields (loads per unit area) of total coliform bacteria and E. coli, chloride, nitrite, nitrate, and orthophosphate were calculated for all sampling dates during WYs 2003-12 for 23 monitoring stations with streamflow data. Values of physical properties and concentrations of constituents were compared with State and Federal water-quality standards and guidelines and were related to streamflow, land-use characteristics, varying classes of timber operations, and impervious surface areas.
\nTributaries in the Scituate Reservoir drainage area for WYs 2003-12 were slightly acidic (median pH of all stations equal to 6.1) and contained low median concentrations of chloride (22 milligrams per liter [mg/L]), nitrate (0.01 mg/L as nitrogen), nitrite (0.001 mg/L as nitrogen), and orthophosphate (0.02 milligrams per liter as phosphorus [mg/L as P]). Turbidity and alkalinity values also were low with medians of 0.57 nephelometric turbidity units and 5.1 mg/L as calcium carbonate, respectively. Total coliform bacteria and E. coli were detected in most samples from all stations, but median concentrations were generally low-43 colony-forming units per 100 milliliters (mL) and 15 colony-forming units per 100 milliliters, respectively.
\nMedian values of several physical properties and median concentrations of several constituents correlated positively with the percentages of developed land and negatively with the percentages of forest cover in the drainage areas above the monitoring stations. Median concentrations of chloride correlated positively with the percentages of impervious land use in the subbasins of monitoring stations, likely reflecting the effects of deicing compounds applied to roadways during winter maintenance. Median concentrations of alkalinity also correlated positively with the percentage of impervious land use, which may be related to the deterioration of fabricated structures containing calcium carbonate. Median values of color correlated positively with the percentage of wetland area in the subbasins of monitoring stations, reflecting the natural sources of color in tributaries. Streamflows were negatively correlated with turbidity and concentrations of total coliform bacteria and E. coli, possibly reflecting seasonal patterns in which relatively high values of these properties and constituents occur during warmer low-flow conditions late in the water year. Similar seasonal patterns were observed for pH, alkalinity, and color. Negative correlations between concentrations of chloride and streamflow also were significant, indicating that deicing salts from roadways and other impervious surfaces that lack direct connection to the tributaries are likely infiltrating to the groundwater and discharging to some of the tributaries late in the water year. While salt-laden runoff directly enters some of the tributaries at roadway crossings, most of the roadway runoff infiltrates into the adjacent berms throughout the drainage area. Statistically significant correlations were not identified between various degrees of tree-canopy reduction caused by timber operations in the subbasins and median values or concentrations of water-quality properties.
\nLoads and yields of chloride, nitrate, nitrite, orthophosphate, and bacteria varied at monitoring stations in the Scituate Reservoir drainage area in WYs 2003-12. Loads generally were greater at stations in the Barden Reservoir and the Regulating Reservoir Subbasins that have larger drainage areas than in subbasins with smaller drainage areas. Subbasin yields of fecal-indicator bacteria and orthophosphate generally were largest in the Westconnaug Reservoir Subbasin, and subbasin yields for chloride, nitrate, and nitrite were largest in the Moswansicut Reservoir Subbasin in the northeastern part of the drainage area.
\nUpward trends in pH were identified for nearly half of the monitoring stations for WYs 1983-2012 and may reflect regional reductions in acid precipitation. Many upward trends in alkalinity also were identified for both the WYs 1983-2012 and for WYs 2003-12 periods and are likely related to the natural weathering of structures containing concrete or, in some cases, the application of lime or fertilizers on agriculture lands. Significant trends in chloride concentrations at most stations during WYs 1983-2012 were upward; however, results for WYs 2003-12 substantiate few significant upward trends and, in a few cases, downward trends were identified in several tributary drainage areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155058","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2015, Water-quality trends in the Scituate reservoir drainage area, Rhode Island, 1983-2012: U.S. Geological Survey Scientific Investigations Report 2015-5058, viii, 56 p., https://doi.org/10.3133/sir20155058.","productDescription":"viii, 56 p.","numberOfPages":"70","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"1983-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-045415","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":301097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155058.jpg"},{"id":301094,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5058/"},{"id":301095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5058/pdf/sir2015-5058.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5058 Report"},{"id":301096,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5058/attachments/sir2015-5058_appendix.xlsx","text":"Appendix 1","size":"700 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5058 Appendix 1","linkHelpText":"Values for water-quality data collected by the Providence Water Supply Board at 37 monitoring stations in the Scituate Reservoir drainage area, water years 1983–2012."}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.79290771484375,\n 41.72623044860004\n ],\n [\n -71.8011474609375,\n 41.937019660425264\n ],\n [\n -71.54296874999999,\n 41.937019660425264\n ],\n [\n -71.553955078125,\n 41.734429390721\n ],\n [\n -71.79290771484375,\n 41.72623044860004\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55780020e4b032353cbeb6b7","contributors":{"authors":[{"text":"Smith, Kirk P. 0000-0003-0269-474X kpsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-474X","contributorId":1516,"corporation":false,"usgs":true,"family":"Smith","given":"Kirk","email":"kpsmith@usgs.gov","middleInitial":"P.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545577,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148001,"text":"ofr20151085 - 2015 - Simulation of nitrogen attenuation in a subterranean estuary, representative of the southern coast of Cape Cod, Massachusetts","interactions":[],"lastModifiedDate":"2015-06-09T14:59:54","indexId":"ofr20151085","displayToPublicDate":"2015-06-09T15:00:00","publicationYear":"2015","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":"2015-1085","title":"Simulation of nitrogen attenuation in a subterranean estuary, representative of the southern coast of Cape Cod, Massachusetts","docAbstract":"A two-dimensional model was developed by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, to assess flow and chemical reaction associated with groundwater discharge through the subterranean estuary representative of coastal salt ponds of southern Cape Cod. The model simulated both the freshwater and saltwater flow systems and accounted for density-dependent flow, tidal fluctuation, and chemical reactivity among oxygen, dissolved organic carbon, nitrate, and ammonia. Not previously incorporated into one model, the interaction of these effects can now be simulated in the subterranean estuary context.
\nAn analysis of the flow system under mean-tide conditions was conducted first to provide the initial conditions for a subsequent analysis that included the effects of tidal fluctuations. Tidal fluctuations were simulated with a repeated couplet that represented a high tide-low tide sequence and alternating locations of head-dependent flux boundaries placed along the simulated seabed, above and below the levels of the respective high and low tides.
\nBoundary conditions for chemical species included nitrate in recharge, and oxygen and organic matter (including organic nitrogen) in infiltrating solutions of head-dependent boundaries. Reaction chemistry was limited to oxidative degradation of organic matter (including remineralization of ammonia) with oxygen or nitrate as electron acceptors and nitrification of ammonia in the presence of oxygen.
\nSimulations using the SEAWAT-2000 computer program resulted in two mixing zones-between freshwater and saltwater in a deep saltwater wedge and in an intertidal salt zone, which results from tidal fluctuation. The mixing zones are the principal locations where nitrogen attenuation reactions occurred-between organic matter in the saltwater zones of the aquifer and nitrate in the freshwater zone.
\nIn mean-tide PHT3D model simulations, 15 percent of nitrogen that is recharged was attenuated because of reaction with dissolved organic matter, a denitrification reaction that reduces nitrate to nitrogen gas. When a fluctuating tide was simulated, the amount of recharged nitrogen that was denitrified increased to 20 percent.
\nChemical reaction was controlled by the rate of mixing of freshwater and saltwater, which contained the reactants nitrate and dissolved organic matter, respectively, necessary for nitrogen attenuation reactions to take place. Reaction occurred in both the deep saltwater wedge and in an increased denitrification. However, mixing may also have been enhanced partly by numerical dispersion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151085","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Colman, J.A., Carlson, C.S., and Robinson, C., 2015, Simulation of nitrogen attenuation in a subterranean estuary, representative of the southern coast of Cape Cod, Massachusetts: U.S. Geological Survey Open-File Report 2015-1085, vi, 30 p., https://doi.org/10.3133/ofr20151085.","productDescription":"vi, 30 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056161","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":301100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151085.jpg"},{"id":301098,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1085/"},{"id":301099,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1085/pdf/ofr2015-1085.pdf","text":"Report","size":"3.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2015-1085 Report"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.5377197265625,\n 41.80203073088394\n ],\n [\n -70.477294921875,\n 41.77131167976407\n ],\n [\n -70.29052734375,\n 41.73852846935917\n ],\n [\n -70.235595703125,\n 41.74467659677642\n ],\n [\n -70.191650390625,\n 41.76106872528616\n ],\n [\n -70.02685546875,\n 41.79384042311992\n ],\n [\n -70.01312255859375,\n 41.87365126992505\n ],\n [\n -70.0762939453125,\n 41.89205502378826\n ],\n [\n -70.0872802734375,\n 41.98807738309159\n ],\n 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jacolman@usgs.gov","orcid":"https://orcid.org/0000-0001-9327-0779","contributorId":2098,"corporation":false,"usgs":true,"family":"Colman","given":"John","email":"jacolman@usgs.gov","middleInitial":"A.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Carl S. 0000-0001-7142-3519 cscarlso@usgs.gov","orcid":"https://orcid.org/0000-0001-7142-3519","contributorId":1694,"corporation":false,"usgs":true,"family":"Carlson","given":"Carl","email":"cscarlso@usgs.gov","middleInitial":"S.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robinson, C.","contributorId":70586,"corporation":false,"usgs":true,"family":"Robinson","given":"C.","affiliations":[],"preferred":false,"id":548417,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148471,"text":"sir20155045 - 2015 - Hydrologic model of the Modesto Region, California, 1960-2004","interactions":[],"lastModifiedDate":"2015-06-09T08:50:49","indexId":"sir20155045","displayToPublicDate":"2015-06-09T10:00:00","publicationYear":"2015","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":"2015-5045","title":"Hydrologic model of the Modesto Region, California, 1960-2004","docAbstract":"Strategies for managing water supplies and groundwater quality in the Modesto region of the eastern San Joaquin Valley, California, are being formulated and evaluated by the Stanislaus and Tuolumne Rivers Groundwater Basin Association. Management issues and goals in the basin include an area in the lower part of the basin that requires drainage of the shallow water table to sustain agriculture, intra- and inter-basin migration of poor-quality groundwater, and efficient management of surface and groundwater supplies. To aid in the evaluation of water-management strategies, the U.S. Geological Survey and the Stanislaus and Tuolumne Rivers Groundwater Basin Association have developed a hydrologic model that simulates monthly groundwater and surface-water flow as governed by aquifer-system properties, annual and seasonal variations in climate, surface-water flow and availability, water use, and land use. The model was constructed by using the U.S. Geological Survey groundwater-modeling software MODFLOW-OWHM with the Farm Process.
\nAvailable measurements of groundwater pumped for municipal, irrigation, and drainage purposes are specified in the model, as are deliveries of surface water. Private irrigation pumping and recharge associated with agricultural land use were estimated by using the Farm Process in MODFLOW-OWHM, which simulates landscape processes associated with irrigated agriculture and other land uses. The distribution of hydraulic conductivity in the aquifer system was constrained by using data from more than 3,500 drillers' logs. The model was calibrated to 4,061 measured groundwater levels in 109 wells and 2,739 mean monthly surface-water flows measured at 6 streamgages during 1960-2004 by using a semi-automated method of parameter estimation.
\nThe model fit to groundwater levels was good, with an absolute mean residual of 0.8 feet; 74 percent of simulated heads were within 10 feet of those observed. The model fit to streamflow was biased low, but reasonable overall; the absolute mean residual of streamflow was 780 cubic feet per second, and 68 percent of simulated streamflows were within 500 cubic feet per second of observed. Hydrographs both of groundwater levels and streamflow indicated overall an acceptable fit to observed trends.
\nSimulated private agricultural pumpage ranged from about 780,000 to 1,380,000 acre-feet per year and averaged about 1,000,000 acre-feet per year from 1960 to 2004. Simulated deep percolation, or groundwater recharge from precipitation and irrigation, varied with climate and land use from about 1,100,000 to 1,700,000 acre-feet per year, averaging 1,360,000 acre-feet per year. Key limitations of the model with respect to estimating these large components of the water budget are the uncertainty associated with actual irrigation deliveries and irrigation efficiencies and the lack of metered data for private agricultural groundwater pumping. Different assumptions with respect to irrigation deliveries and efficiencies, and other model input, would result in different estimates of private agricultural groundwater use.
\nThe simulated exchange between groundwater and surface water was a small percentage of streamflow, typically ranging within a loss or gain of about 2 cubic feet per second per mile. The simulated exchange compared reasonably with limited independent estimates available, but substantial uncertainty is associated with these estimates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155045","collaboration":"Prepared in cooperation with the Stanislaus and Tuolumne Rivers Groundwater Basin Association","usgsCitation":"Phillips, S.P., Rewis, D.L., and Traum, J.A., 2015, Hydrologic model of the Modesto Region, California, 1960-2004: U.S. Geological Survey Scientific Investigations Report 2015-5045, x, 69 p., https://doi.org/10.3133/sir20155045.","productDescription":"x, 69 p.","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-014014","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":301085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155045.jpg"},{"id":301082,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5045/"},{"id":301084,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5045/downloads/sir2015-5045_fig21supplement.xls","text":"Supplement to figure 21","size":"3.1 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5045 Supplement to figure 21"},{"id":301083,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5045/pdf/sir2015-5045.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5045 Report"}],"projection":"Albers equal area conic projection","datum":"North American Datum of 1983","country":"United States","state":"California","otherGeospatial":"Modesto","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.38381958007812,\n 37.56308554496544\n ],\n [\n -121.38381958007812,\n 37.565262680889965\n ],\n [\n -121.34948730468749,\n 37.565262680889965\n ],\n [\n -121.34948730468749,\n 37.56308554496544\n ],\n [\n -121.38381958007812,\n 37.56308554496544\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.33575439453126,\n 37.57505900514994\n ],\n [\n -120.838623046875,\n 37.9051994823157\n ],\n [\n -120.39093017578125,\n 37.470498470798724\n ],\n [\n -120.96633911132812,\n 37.11543110112874\n ],\n [\n -121.33575439453126,\n 37.57505900514994\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5578001de4b032353cbeb6b3","contributors":{"authors":[{"text":"Phillips, Steven P. 0000-0002-5107-868X sphillip@usgs.gov","orcid":"https://orcid.org/0000-0002-5107-868X","contributorId":1506,"corporation":false,"usgs":true,"family":"Phillips","given":"Steven","email":"sphillip@usgs.gov","middleInitial":"P.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rewis, Diane L. dlrewis@usgs.gov","contributorId":1511,"corporation":false,"usgs":true,"family":"Rewis","given":"Diane","email":"dlrewis@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548353,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70154932,"text":"70154932 - 2015 - Effects of oyster harvest activities on Louisiana reef habitat and resident nekton communities","interactions":[],"lastModifiedDate":"2018-02-27T18:16:26","indexId":"70154932","displayToPublicDate":"2015-06-09T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1663,"text":"Fishery Bulletin","printIssn":"0090-0656","active":true,"publicationSubtype":{"id":10}},"title":"Effects of oyster harvest activities on Louisiana reef habitat and resident nekton communities","docAbstract":"Oysters are often cited as “ecosystem engineers” because they modify their environment. Coastal Louisiana contains extensive oyster reef areas that have been harvested for decades, and whether differences in habitat functions exist between those areas and nonharvested reefs is unclear. We compared reef physical structure and resident community metrics between these 2 subtidal reef types. Harvested reefs were more fragmented and had lower densities of live eastern oysters (Crassostrea virginica) and hooked mussels (Ischadium recurvum) than the nonharvested reefs. Stable isotope values (13C and 15N) of dominant nekton species and basal food sources were used to compare food web characteristics. Nonpelagic source contributions and trophic positions of dominant species were slightly elevated at harvested sites. Oyster harvesting appeared to have decreased the number of large oysters and to have increased the percentage of reefs that were nonliving by decreasing water column filtration and benthopelagic coupling. The differences in reef matrix composition, however, had little effect on resident nekton communities. Understanding the thresholds of reef habitat areas, the oyster density or oyster size distribution below which ecosystem services may be compromised, remains key to sustainable management.
","language":"English","publisher":"U.S. National Oceanic and Atmospheric Administration ","doi":"10.7755/FB.113.3.8","usgsCitation":"Beck, S., and LaPeyre, M.K., 2015, Effects of oyster harvest activities on Louisiana reef habitat and resident nekton communities: Fishery Bulletin, v. 113, no. 3, p. 327-340, https://doi.org/10.7755/FB.113.3.8.","productDescription":"14 p.","startPage":"327","endPage":"340","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-039257","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":472025,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7755/fb.113.3.8","text":"Publisher Index Page"},{"id":324972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Calcasieu Lake, Sabine Lake, Sister Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.06494140625,\n 29.036960648558267\n ],\n [\n -94.06494140625,\n 30.221101852485987\n ],\n [\n -90.802001953125,\n 30.221101852485987\n ],\n [\n -90.802001953125,\n 29.036960648558267\n ],\n [\n -94.06494140625,\n 29.036960648558267\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"113","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5780ceb6e4b081161682231e","contributors":{"authors":[{"text":"Beck, Steve","contributorId":172773,"corporation":false,"usgs":false,"family":"Beck","given":"Steve","email":"","affiliations":[{"id":25282,"text":"School of Renewable Natural Resources, Louisiana State University, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":641996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":564378,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70137557,"text":"70137557 - 2015 - Assessment of general health of fishes collected at selected sites in the Great Lakes Basin In 2012","interactions":[],"lastModifiedDate":"2015-11-17T09:45:04","indexId":"70137557","displayToPublicDate":"2015-06-09T09:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesNumber":"112-2015","subseriesTitle":"Cooperator Science Series","title":"Assessment of general health of fishes collected at selected sites in the Great Lakes Basin In 2012","docAbstract":"During the past decade, there has been a substantive increase in the detection of “emerging contaminants”, defined as a new substance, chemical, or metabolite in the environment; or a legacy substance with a newly expanded distribution, altered release, or a newly recognized effect (such as endocrine disruption). Emerging contaminants include substances such as biogenic hormones (human and animal), brominated flame retardants, pharmaceuticals, personal care products, plasticizers, current use pesticides, detergents, and nanoparticles. These contaminants are frequently not regulated or inadequately regulated by state or Federal water quality programs. Information about the toxicity of these substances to fish and wildlife resources is generally limited, compared to more highly regulated contaminants, and some classes have been shown to cause affects (for example feminization of male fish, immunomodulation) that are not evaluated via traditional toxicity testing protocols. As a result, these compounds may pose a substantial, but currently poorly documented threat to aquatic ecosystems. Failure to identify and understand the impacts of these emerging contaminants on fish and wildlife resources may result in deleterious impacts to Great Lakes resources that can result in adverse ecological, economic and recreational consequences.
\nThe U. S. Fish and Wildlife Service received funding through the Great Lakes Restoration Initiative (GLRI) for an Early Warning Program to detect and identify emerging contaminants and to evaluate the effects of these contaminants on fish and wildlife. The U.S. Geological Survey (WV Cooperative Fish and Wildlife Research Unit and National Fish Health Research Laboratory, Leetown Science Center) developed and implemented a biological effects monitoring protocol to assist in this program. Fish collections and measurements of biomarkers of exposure in Fall 2010 and Spring 2011 occurred at individual sites within select Areas of Concern (AOCs). They provided an assessment of the utility of the suite of biomarkers and also identified sites for more in-depth analyses. Selected areas are characterized as areas with known emerging contaminants, sensitive or listed species, areas downstream from municipal wastewater discharges or receiving waters for industrial facilities, and/or areas susceptible to agricultural or urban contamination, or harbors or ports. The results of the 2010- 2011 studies were summarized in Blazer et al. 2014 a, b, c; Braham et al. in review and Blazer et al. in review.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Mazik, P.M., Braham, R., Hahn, C.M., and Blazer, V., 2015, Assessment of general health of fishes collected at selected sites in the Great Lakes Basin In 2012, ii, 26.","productDescription":"ii, 26","numberOfPages":"28","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061682","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":311410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311409,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/singleitem/collection/document/id/2086/rec/1"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.46044921875,\n 40.329795743702064\n ],\n [\n -94.46044921875,\n 50.05008477838258\n ],\n [\n -74.8388671875,\n 50.05008477838258\n ],\n [\n -74.8388671875,\n 40.329795743702064\n ],\n [\n -94.46044921875,\n 40.329795743702064\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564c5dc1e4b0ebfbef0d346b","contributors":{"authors":[{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":537897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Braham, Ryan P.","contributorId":97427,"corporation":false,"usgs":true,"family":"Braham","given":"Ryan P.","affiliations":[],"preferred":false,"id":579980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hahn, Cassidy M. cmhahn@usgs.gov","contributorId":5321,"corporation":false,"usgs":true,"family":"Hahn","given":"Cassidy","email":"cmhahn@usgs.gov","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":579981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blazer, Vicki 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":792,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":579982,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190236,"text":"70190236 - 2015 - Elevational gradient in clutch size of Red-faced Warblers","interactions":[],"lastModifiedDate":"2017-08-18T16:44:42","indexId":"70190236","displayToPublicDate":"2015-06-09T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Elevational gradient in clutch size of Red-faced Warblers","docAbstract":"Our understanding of life history evolution has benefited from debates regarding the underlying causes, and geographic ubiquity, of spatial patterns in avian clutch sizes. Past studies have revealed that birds lay smaller clutch sizes at higher elevation. However, in most previous studies, investigators have failed to adequately control for elevational differences in breeding phenology. To better understand the elevational gradient in avian clutch size, we need to know how clutch size changes across the entire elevational breeding range of a species (i.e., the shape of the relationship between elevation and clutch size), and whether the elevational gradient in clutch size is merely an artifact of elevational gradients in breeding phenology or breeding season length. We examined the relationship between breeding elevation and clutch size of Red-faced Warblers (Cardellina rubrifrons) along a 1000-m elevational gradient in Arizona. Our objectives were to determine how clutch size changed with elevation, and if the relationship between clutch size and elevation merely reflected elevational changes in breeding season length or phenology. The proportion of 5-egg clutches decreased and the proportion of 3- and 4-egg clutches increased non-linearly with increasing elevation, even after controlling for the elevational gradient in nest initiation date. Thus, average clutch size declined across the elevational breeding range of Red-faced Warblers, but this decline was not due to elevational variation in breeding phenology. Timing of breeding changed, but the duration of the breeding season did not change appreciably across the elevational gradient. Hence, elevational differences in breeding season length or breeding phenology cannot explain why Red-faced Warblers (and perhaps other birds) breeding at higher elevations have smaller clutches.
","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12099","usgsCitation":"Dillon, K.G., and Conway, C.J., 2015, Elevational gradient in clutch size of Red-faced Warblers: Journal of Field Ornithology, v. 86, no. 2, p. 163-172, https://doi.org/10.1111/jofo.12099.","productDescription":"10 p.","startPage":"163","endPage":"172","ipdsId":"IP-038160","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":344964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-25","publicationStatus":"PW","scienceBaseUri":"5997fc9de4b0b589267cd218","contributors":{"authors":[{"text":"Dillon, Kristen G.","contributorId":195744,"corporation":false,"usgs":false,"family":"Dillon","given":"Kristen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":708055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":708043,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70048662,"text":"70048662 - 2015 - Mapping wetlands and surface water in the Prairie Pothole Region of North America: Chapter 16","interactions":[],"lastModifiedDate":"2017-03-24T15:41:18","indexId":"70048662","displayToPublicDate":"2015-06-09T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Mapping wetlands and surface water in the Prairie Pothole Region of North America: Chapter 16","docAbstract":"The Prairie Pothole Region (PPR) is one of the most highly productive wetland regions in the world. Prairie Pothole wetlands serve as a primary feeding and breeding habitat for more than one-half of North America’s waterfowl population, as well as a variety of songbirds, waterbirds, shorebirds, and other wildlife. During the last century, extensive land conversions from grassland with wetlands to cultivated cropland and grazed pastureland segmented and reduced wetland habitat. Inventorying and characterizing remaining wetland habitat is critical for the management of wetland ecosystem services. Remote sensing technologies are often utilized for mapping and monitoring wetlands. This chapter presents background specific to the PPR and discusses approaches employed in mapping its wetlands before presenting a case study.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Remote sensing of wetlands: Applications and advances","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","publisherLocation":"Boca Raton, FL","isbn":"9781482237351","usgsCitation":"Rover, J.R., and Mushet, D.M., 2015, Mapping wetlands and surface water in the Prairie Pothole Region of North America: Chapter 16, chap. of Remote sensing of wetlands: Applications and advances, p. 347-368.","productDescription":"22 p.","startPage":"347","endPage":"368","ipdsId":"IP-045855","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":338323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Prairie Pothole Region","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58d63038e4b05ec7991310ed","contributors":{"authors":[{"text":"Rover, Jennifer R. 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":2941,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":518225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":518224,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}