The U.S. Geological Survey anchored a sediment trap in the northern Gulf of Mexico in January 2008 to collect seasonal time-series data on the flux and assemblage composition of live planktic foraminifers. This report provides an update of the previous time-series data to include continuous results from January 2013 through May 2014. Ten taxa constituted ~95 percent of both the 2013 and 2014 assemblages: Globigerinoides ruber (pink and white varieties), Globigerinoides sacculifer, Globigerina calida, Globigerinella aequilateralis, Globorotalia menardii group [The Gt. menardii group includes Gt. menardii, Gt. tumida, and Gt. ungulata], Orbulina universa, Globorotalia truncatulinoides, Pulleniatina spp., and Neogloboquadrina dutertrei. In 2013, the mean daily flux was 177 tests per square meter per day (m−2 day−1), with maximum fluxes of >1,200 tests m−2 day−1 during the middle of February and minimum fluxes of <13 tests m−2 day−1 during the beginning of November. In 2014, the mean daily flux was 189 tests m−2 day−1, with maximum fluxes of >900 tests m−2 day−1 at the end of January and minimum fluxes of <30 tests m−2 day−1 at the beginning of January. Globorotalia truncatulinoides showed a clear preference for the winter, consistent with data from 2008 to 2012. Globigerinoides ruber (white) flux data for 2012 (average 23 tests m−2 day−1) were consistent with data from 2011 (average 30 tests m−2 day−1) and 2010 (average 29 tests m−2 day−1) and showed a steady threefold increase since 2009 (average 11 tests m−2 day−1) and a tenfold increase from the 2008 flux (3 tests m−2 day−1). The flux data from 2013 (average 15 tests m−2 day−1) and 2014 (average 8 tests m−2 day−1) showed decline from the previous 3 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161115","usgsCitation":"Reynolds, C.E., and Richey, J.N., 2016, Seasonal flux and assemblage composition of planktic foraminifera from the northern Gulf of Mexico, 2008–14: U.S. Geological Survey Open-File Report 2016–1115, 14 p., https://dx.doi.org/10.3133/ofr20161115.","productDescription":"Report: iv, 14 p.; Table","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073887","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":325709,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1115/ofr20161115_table1.xls","text":"Planktic Foraminiferal Flux ","size":"264 KB xls","description":"OFR 2016-1115"},{"id":325708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ofr/2016/1115/ofr20161115.pdf","text":"Report","size":"962 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1115"},{"id":325707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1115/coverthb.jpg"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
At Gale crater, Mars, ChemCam acquired its first laser-induced breakdown spectroscopy (LIBS) target on Sol 13 of the landed portion of the mission (a Sol is a Mars day). Up to Sol 800, more than 188 000 LIBS spectra were acquired on more than 5800 points distributed over about 650 individual targets. We present a comprehensive review of ChemCam scientific accomplishments during that period, together with a focus on the lessons learned from the first use of LIBS in space. For data processing, we describe new tools that had to be developed to account for the uniqueness of Mars data. With regard to chemistry, we present a summary of the composition range measured on Mars for major-element oxides (SiO2, TiO2, Al2O3, FeOT, MgO, CaO, Na2O, K2O) based on various multivariate models, with associated precisions. ChemCam also observed H, and the non-metallic elements C, O, P, and S, which are usually difficult to quantify with LIBS. F and Cl are observed through their molecular lines. We discuss the most relevant LIBS lines for detection of minor and trace elements (Li, Rb, Sr, Ba, Cr, Mn, Ni, and Zn). These results were obtained thanks to comprehensive ground reference datasets, which are set to mimic the expected mineralogy and chemistry on Mars. With regard to the first use of LIBS in space, we analyze and quantify, often for the first time, each of the advantages of using stand-off LIBS in space: no sample preparation, analysis within its petrological context, dust removal, sub-millimeter scale investigation, multi-point analysis, the ability to carry out statistical surveys and whole-rock analyses, and rapid data acquisition. We conclude with a discussion of ChemCam performance to survey the geochemistry of Mars, and its valuable support of decisions about selecting where and whether to make observations with more time and resource-intensive tools in the rover's instrument suite. In the end, we present a bird's-eye view of the many scientific results: discovery of felsic Noachian crust, first observation of hydrated soil, discovery of manganese-rich coatings and fracture fills indicating strong oxidation potential in Mars' early atmosphere, characterization of soils by grain size, and wide scale mapping of sedimentary strata, conglomerates, and diagenetic materials.
Boreal soils play an important role in the global carbon cycle owing to the large amount of carbon stored within this northern region. To understand how carbon and nitrogen storage varied among different ecosystems, a vegetation gradient was established in the Bonanza Creek Long Term Ecological Research (LTER) site, located in interior Alaska. The ecosystems represented are a black spruce (Picea mariana)–feather moss (for example, Hylocomium sp.) forest ecosystem, a shrub-dominated ecosystem, a tussock-grass-dominated ecosystem, a sedge-dominated ecosystem, and a rich fen ecosystem. Here, we report the physical, chemical, and descriptive properties for the soil cores collected at these sites. These data have been used to calculate carbon and nitrogen accumulation rates on a long-term (decadal and century) basis (Manies and others, in press).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161034","usgsCitation":"Manies, K.L., Harden, J.W., Fuller, C.C., Xu, Xiaomei, and McGeehin, J.P., 2016, Soil data for a vegetation gradient located at Bonanza Creek Long Term Ecological Research Site, interior Alaska: U.S. Geological Survey Open-File Report 2016–1034, 10 p., https://dx.doi.org/10.3133/ofr20161034.","productDescription":"Report: iv, 10 p.; Data Files","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072809","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":325710,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1034/coverthb.jpg"},{"id":325738,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1034/ofr20161034_appendix.zip","text":"Data Files","size":"120 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1034"},{"id":325737,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1034/ofr20161034.pdf","text":"Report","size":"393 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1034"}],"contact":"Contact Information
Soil Carbon Research - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 962
Menlo Park, CA 94025
http://carbon.wr.usgs.gov/
http://carbon.wr.usgs.gov/people.html
A detailed inventory of irrigated crop acreage is not available at the level of resolution needed to accurately estimate agricultural water use or to project future water demands in many Florida counties. A detailed digital map and summary of irrigated acreage during the 2015 growing season was developed for 13 of the 15 counties that compose the Suwannee River Water Management District. The irrigated areas were delineated using land-use data, orthoimagery, and information obtained from the water management district consumptive water-use permits that were then field verified between May and November of 2015. Selected attribute data were collected for the irrigated areas, including crop type, primary water source, and type of irrigation system. Results indicate that an estimated 113,134 acres were either irrigated or had potential for irrigation in all or part of the 13 counties within the Suwannee River Water Management District during 2015. This estimate includes 108,870 acres of field-verified, irrigated crops and 4,264 acres of irrigated land observed as (1) idle (with an irrigation system visible but no crop present at the time of the field-verification visit), (2) acres that could not be verified during field visits, or (3) acres that were located on publicly owned research lands.
\nOf the total field-verified crops, 83,721 acres were field crops; 20,962 acres were vegetable crops (sometimes referred to as row crops); 3,089 acres were in tree nurseries, ornamentals, and sod production; and 1,098 acres were fruit crops. Specific irrigated crops included 32,468 acres of corn (primarily for silage); 28,170 acres of peanuts; and 10,331 acres of hay. About 40 percent of the vegetable acreage (8,340 acres) was double cropped (planted with both a spring and a fall crop on the same field). Beans, carrots, and watermelons were the most commonly grown vegetable crops in these 13 counties in 2015.
\nSprinkler irrigation systems including center pivots, portable or traveling guns, and permanent or solid overhead fixtures accounted for nearly 91 percent (102,874 acres) of the total irrigated acreage in the Suwannee River Water Management District, whereas microirrigation systems including drip irrigation accounted for 9 percent (10,260 acres) of the irrigated acreage. A total of 1,466 center pivots were observed during field verification in 2015 and accounted for 93,093 irrigated acres (which represents 82 percent of the total irrigated acreage). Most center pivots were in use at the time of the field verification, although about 3 percent appeared idle. No flood irrigation systems were observed during field verification in 2015. Overall, groundwater was used to irrigate nearly all of the field-verified acreage (99.8 percent). Dairy wastewater effluent was used on many fields during 2015; however, a quantitative estimate of acreage using effluent could not be determined.
\nIrrigated cropland totaled 26,927 acres in Suwannee County; 16,511 acres in Madison County; 14,862 acres in Hamilton County; and 14,155 acres in Gilchrist County; these four counties accounted for nearly two-thirds (64 percent) of the acres irrigated within the Suwannee River Water Management District during 2015. Corn (primarily for silage) and peanuts were the primary irrigated crops, accounting for 48, 70, and 71 percent, respectively, of the total irrigated acreage in Suwannee, Madison, and Gilchrist Counties; vegetables accounted for 52 percent of the total irrigated acres in Hamilton County. Other counties with substantial irrigated acreage included Levy (10,122 acres), Alachua (9,547 acres), and Lafayette (8,110 acres); these three counties, combined with Suwannee, Madison, Hamilton, and Gilchrist Counties, accounted for 88 percent of the irrigated acreage in the Suwannee River Water Management District.
\nThe irrigated acreage that was field verified in 2015 for the 13 counties in the Suwannee River Water Management District (113,134 acres) is about 6 percent higher than the estimated acreage published by the U.S. Department of Agriculture (107,217 acres) for 2012; however, this 2012 value represents acreage for the entire portion of all 13 counties, not just the Suwannee River Water Management District portion. Differences between the 2015 field-verified acreage totals and those published by the U.S. Department of Agriculture for 2012 may occur because (1) irrigated acreage for some specific crops increased or decreased substantially during the 3-year interval due to commodity prices or economic changes, (2) calculated field-verified irrigated acreage may be an overestimate because irrigation was assumed if an irrigation system was present and therefore the acreage was counted as irrigated, when in fact that may not have been the case as some farmers may not have used their irrigation systems during this growing period even if they had a crop in the field, or (3) the amount of irrigated acreages published by the U.S. Department of Agriculture for selected crops may be underestimated in some cases.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161111","collaboration":"Prepared in cooperation with the Florida Department of Agriculture and Consumer Services and the Suwannee River Water Management District","usgsCitation":"Marella, R.L., Dixon, J.F., and Berry, D.R., 2016, Agricultural irrigated land-use inventory for the counties in the Suwannee River Water Management District in Florida, 2015: U.S. Geological Survey Open-File Report 2016–1111, 18 p., https://dx.doi.org/10.3133/ofr20161111.","productDescription":"Report: 18 p.; Appendixes: 1-2; Data Release","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-071711","costCenters":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"links":[{"id":438580,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NK3C4V","text":"USGS data release","linkHelpText":"Map, Data, and GIS Files Pertaining to the Agricultural Irrigated Land-use Inventory for the Counties in the Suwannee River Water Management District, 2015"},{"id":325761,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1111/ofr20161111_appendix1.pdf","text":"Appendix 1","size":"9.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1111 Appendix 1"},{"id":325760,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1111/ofr20161111.pdf","text":"Report","size":"1.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1111"},{"id":325762,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1111/ofr20161111_appendix2.xlsx","text":"Appendix 2","size":"216 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016–1111 Appendix 2"},{"id":325763,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7NK3C4V","text":"USGS data release - GIS Data and Tables Pertaining to the Agricultural Irrigated Land-use Inventory for the Counties in the Suwannee River Water Management District, 2015","description":"USGS data release"},{"id":325759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1111/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Suwannee River Water Management District","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.0673828125,\n 30.680439786468128\n ],\n [\n -82.3974609375,\n 30.58117925738696\n ],\n [\n -82.3974609375,\n 30.164126343161097\n ],\n [\n -82.0513916015625,\n 30.149877316442065\n ],\n [\n -82.034912109375,\n 29.3965337391284\n ],\n [\n -82.7435302734375,\n 28.96489485992114\n ],\n [\n -83.0621337890625,\n 29.14736383122664\n ],\n [\n -83.408203125,\n 29.53522956294847\n ],\n [\n -83.583984375,\n 29.783449456820605\n ],\n [\n -84.0838623046875,\n 30.102365696412445\n ],\n [\n -84.0673828125,\n 30.680439786468128\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
12703 Research Parkway
Orlando, FL 32826
Efficient and responsible management of water resources relies on accurate streamflow records. However, many watersheds are ungaged, limiting the ability to assess and understand local hydrology. Several tools have been developed to alleviate this data scarcity, but few provide continuous daily streamflow records at individual streamgages within an entire region. Building on the history of hydrologic mapping, ordinary kriging was extended to predict daily streamflow time series on a regional basis. Pooling parameters to estimate a single, time-invariant characterization of spatial semivariance structure is shown to produce accurate reproduction of streamflow. This approach is contrasted with a time-varying series of variograms, representing the temporal evolution and behavior of the spatial semivariance structure. Furthermore, the ordinary kriging approach is shown to produce more accurate time series than more common, single-index hydrologic transfers. A comparison between topological kriging and ordinary kriging is less definitive, showing the ordinary kriging approach to be significantly inferior in terms of Nash–Sutcliffe model efficiencies while maintaining significantly superior performance measured by root mean squared errors. Given the similarity of performance and the computational efficiency of ordinary kriging, it is concluded that ordinary kriging is useful for first-order approximation of daily streamflow time series in ungaged watersheds.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/hess-20-2721-2016","usgsCitation":"Farmer, W.H., 2016, Ordinary kriging as a tool to estimate historical daily streamflow records: Hydrology and Earth System Sciences, v. 20, no. 7, p. 2721-2735, https://doi.org/10.5194/hess-20-2721-2016.","productDescription":"15 p.","startPage":"2721","endPage":"2735","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070177","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470714,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-20-2721-2016","text":"Publisher Index Page"},{"id":325769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-12","publicationStatus":"PW","scienceBaseUri":"579b1e9fe4b0589fa1c951cc","contributors":{"authors":[{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":643738,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70175058,"text":"70175058 - 2016 - Evaluation of leaf removal as a means to reduce nutrient concentrations and loads in urban stormwater","interactions":[],"lastModifiedDate":"2016-07-28T09:50:40","indexId":"70175058","displayToPublicDate":"2016-07-28T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of leaf removal as a means to reduce nutrient concentrations and loads in urban stormwater","docAbstract":"While the sources of nutrients to urban stormwater are many, the primary contributor is often organic detritus, especially in areas with dense overhead tree canopy. One way to remove organic detritus before it becomes entrained in runoff is to implement a city-wide leaf collection and street cleaning program. Improving our knowledge of the potential reduction of nutrients to stormwater through removal of leaves and other organic detritus on streets could help tailor more targeted municipal leaf collection programs. This study characterized an upper ideal limit in reductions of total and dissolved forms of phosphorus and nitrogen in stormwater through implementation of a municipal leaf collection and street cleaning program in Madison, WI, USA. Additional measures were taken to remove leaf litter from street surfaces prior to precipitation events.
\nLoads of total and dissolved phosphorus were reduced by 84 and 83% (p < 0.05), and total and dissolved nitrogen by 74 and 71% (p < 0.05) with an active leaf removal program. Without leaf removal, 56% of the annual total phosphorus yield (winter excluded) was due to leaf litter in the fall compared to 16% with leaf removal. Despite significant reductions in load, total nitrogen showed only minor changes in fall yields without and with leaf removal at 19 and 16%, respectively. The majority of nutrient concentrations were in the dissolved fraction making source control through leaf removal one of the few treatment options available to environmental managers when reducing the amount of dissolved nutrients in stormwater runoff. Subsequently, the efficiency, frequency, and timing of leaf removal and street cleaning are the primary factors to consider when developing a leaf management program.
\n\n
Vast improvements in sequencing technology have made it practical to simultaneously sequence millions of nucleotides distributed across the genome, opening the door for genomic studies in virtually any species. Ornithological research stands to benefit in three substantial ways. First, genomic methods enhance our ability to parse and simultaneously analyze both neutral and non-neutral genomic regions, thus providing insight into adaptive evolution and divergence. Second, the sheer quantity of sequence data generated by current sequencing platforms allows increased precision and resolution in analyses. Third, high-throughput sequencing can benefit applications that focus on a small number of loci that are otherwise prohibitively expensive, time-consuming, and technically difficult using traditional sequencing methods. These advances have improved our ability to understand evolutionary processes like speciation and local adaptation, but they also offer many practical applications in the fields of population ecology, migration tracking, conservation planning, diet analyses, and disease ecology. This review provides a guide for field ornithologists interested in incorporating genomic approaches into their research program, with an emphasis on techniques related to ecology and conservation. We present a general overview of contemporary genomic approaches and methods, as well as important considerations when selecting a genomic technique. We also discuss research questions that are likely to benefit from utilizing high-throughput sequencing instruments, highlighting select examples from recent avian studies.
","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-16-49.1","usgsCitation":"Oyler-McCance, S.J., Oh, K., Langin, K., and Aldridge, C.L., 2016, A field ornithologist’s guide to genomics: Practical considerations for ecology and conservation: The Auk, v. 133, no. 4, p. 626-648, https://doi.org/10.1642/AUK-16-49.1.","productDescription":"23 p.","startPage":"626","endPage":"648","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073441","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470718,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1642/auk-16-49.1","text":"Publisher Index Page"},{"id":325765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"133","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"579b1e9de4b0589fa1c951b7","contributors":{"authors":[{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":643771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oh, Kevin koh@usgs.gov","contributorId":173215,"corporation":false,"usgs":true,"family":"Oh","given":"Kevin","email":"koh@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":643772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langin, Kathryn klangin@usgs.gov","contributorId":173216,"corporation":false,"usgs":true,"family":"Langin","given":"Kathryn","email":"klangin@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":643773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":643774,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168414,"text":"sir20155179 - 2016 - Quantifying the eroded volume of mercury-contaminated sediment using terrestrial laser scanning at Stocking Flat, Deer Creek, Nevada County, California, 2010–13","interactions":[],"lastModifiedDate":"2016-07-28T11:38:03","indexId":"sir20155179","displayToPublicDate":"2016-07-28T10:15:00","publicationYear":"2016","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":"2015-5179","title":"Quantifying the eroded volume of mercury-contaminated sediment using terrestrial laser scanning at Stocking Flat, Deer Creek, Nevada County, California, 2010–13","docAbstract":"High-resolution ground-based light detection and ranging (lidar), also known as terrestrial laser scanning, was used to quantify the volume of mercury-contaminated sediment eroded from a stream cutbank at Stocking Flat along Deer Creek in the Sierra Nevada foothills, about 3 kilometers west of Nevada City, California. Terrestrial laser scanning was used to collect sub-centimeter, three-dimensional images of the complex cutbank surface, which could not be mapped non-destructively or in sufficient detail with traditional surveying techniques.
The stream cutbank, which is approximately 50 meters long and 8 meters high, was surveyed on four occasions: December 1, 2010; January 20, 2011; May 12, 2011; and February 4, 2013. Volumetric changes were determined between the sequential, three-dimensional lidar surveys. Volume was calculated by two methods, and the average value is reported. Between the first and second surveys (December 1, 2010, to January 20, 2011), a volume of 143 plus or minus 15 cubic meters of sediment was eroded from the cutbank and mobilized by Deer Creek. Between the second and third surveys (January 20, 2011, to May 12, 2011), a volume of 207 plus or minus 24 cubic meters of sediment was eroded from the cutbank and mobilized by the stream. Total volumetric change during the winter and spring of 2010–11 was 350 plus or minus 28 cubic meters. Between the third and fourth surveys (May 12, 2011, to February 4, 2013), the differencing of the three-dimensional lidar data indicated that a volume of 18 plus or minus 10 cubic meters of sediment was eroded from the cutbank. The total volume of sediment eroded from the cutbank between the first and fourth surveys was 368 plus or minus 30 cubic meters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155179","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Howle, J.F., Alpers, C.N., Bawden, G.W., and Bond, Sandra, 2016, Quantifying the eroded volume of mercury-contaminated sediment using terrestrial laser scanning at Stocking Flat, Deer Creek, Nevada County, California, 2010–13: U.S. Geological Survey Scientific Investigations Report 2015–5179, 23 p., https://dx.doi.org/10.3133/sir20155179.","productDescription":"vi, 23 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-043568","costCenters":[{"id":154,"text":"California Water Science 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California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
http://ca.water.usgs.gov
The microscopic organisms of the Everglades include numerous prokaryotic organisms, including the eubacteria, such as the cyanobacteria and non-photosynthetic bacteria, as well as several eukaryotic algae and protozoa that form the base of the food web. This report is part 1 in a series of reports that describe microscopic organisms encountered during the examination of several hundred samples collected in the southern Everglades. Part 1 describes the cyanobacteria and includes a suite of images and the most current taxonomic treatment of each taxon. The majority of the images are of live organisms, allowing their true color to be represented. A number of potential new species are illustrated; however, corroborating evidence from a genetic analysis of the morphological characteristics is needed to confirm these designations as new species. Part 1 also includes images of eubacteria that resemble cyanobacteria. Additional parts of the report on microscopic organisms of the Everglades are currently underway, such as the green algae and diatoms. The report also serves as the basis for a taxonomic image database that will provide a digital record of the Everglades microscopic flora and fauna. It is anticipated that these images will facilitate current and future ecological studies on the Everglades, such as understanding food-web dynamics, sediment formation and accumulation, the effects of nutrients and flow, and climate change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161114","usgsCitation":"Rosen, B.H., and Mareš, Jan, Catalog of microscopic organisms of the Everglades, Part 1—The cyanobacteria: U.S. Geological Survey Open-File Report 2016–1114, 108 p., https://dx.doi.org/10.3133/ofr20161114.","productDescription":"Report: x,108 p.","startPage":"1","endPage":"108","numberOfPages":"122","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073349","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":325624,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1114/ofr20161114.pdf","text":"Report","size":"31.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1114"},{"id":325610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1114/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.68359375,\n 25.12539261151203\n ],\n [\n -80.958251953125,\n 25.085598897064777\n ],\n [\n -81.2164306640625,\n 25.199970890386023\n ],\n [\n -81.2274169921875,\n 25.44823489808649\n ],\n [\n -81.375732421875,\n 25.681137335685307\n ],\n [\n -81.7987060546875,\n 25.913585416189797\n ],\n [\n -81.8316650390625,\n 26.091321632191132\n ],\n [\n -81.551513671875,\n 26.254009699865737\n ],\n [\n -81.1614990234375,\n 26.298339726417737\n ],\n [\n -81.0296630859375,\n 26.401710528707707\n ],\n [\n -80.9417724609375,\n 26.519735305660795\n ],\n [\n -80.584716796875,\n 26.45090222367262\n ],\n [\n -80.5023193359375,\n 26.59343927024179\n ],\n [\n -80.4473876953125,\n 26.672004547729433\n ],\n [\n -80.57373046875,\n 26.848578525873275\n ],\n [\n -80.5902099609375,\n 27.103143960595734\n ],\n [\n -80.33203125,\n 27.108033801463115\n ],\n [\n -80.22766113281249,\n 27.103143960595734\n ],\n [\n -80.0518798828125,\n 27.024877476307523\n ],\n [\n -79.9639892578125,\n 26.632728662035912\n ],\n [\n -79.9749755859375,\n 26.170229047478472\n ],\n [\n -80.09033203125,\n 25.750424835909385\n ],\n [\n -80.15625,\n 25.329131707091477\n ],\n [\n -80.68359375,\n 25.12539261151203\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
Information concerning the availability, use, and quality of water in Livingston Parish, Louisiana, is critical for proper water-resource management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163048","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., and Prakken, L.B., 2016, Water resources of Livingston Parish, Louisiana: U.S. Geological Survey Fact Sheet 2016–3048, 6 p., https://dx.doi.org/10.3133/fs20163048. 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Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
Information concerning the availability, use, and quality of water in St. Helena Parish, Louisiana, is critical for proper water-resource management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163047","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., and Prakken, L.B., 2016, Water resources of St. Helena Parish, Louisiana: U.S. Geological Survey Fact Sheet 2016–3047, 6 p., https://dx.doi.org/10.3133/fs20163047. ","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065607","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":325681,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3047/coverthb.jpg"},{"id":325682,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3047/fs20163047.pdf","text":"Fact Sheet","size":"1.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3047"}],"country":"United States","state":"Louisiana","county":"St. Helena Parish","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-90.5669,31],[-90.5672,30.8864],[-90.5673,30.8795],[-90.5668,30.8763],[-90.5668,30.869],[-90.568,30.768],[-90.5668,30.7301],[-90.5664,30.7241],[-90.5676,30.6652],[-90.5704,30.6501],[-90.6033,30.6499],[-90.6156,30.65],[-90.9104,30.6506],[-90.9099,30.6525],[-90.9088,30.657],[-90.9024,30.6629],[-90.9013,30.6638],[-90.8932,30.6743],[-90.8863,30.6775],[-90.882,30.6779],[-90.8773,30.6788],[-90.8767,30.6797],[-90.8777,30.6834],[-90.8788,30.6866],[-90.875,30.6902],[-90.8697,30.6911],[-90.8676,30.6929],[-90.866,30.6952],[-90.8638,30.6961],[-90.8569,30.6979],[-90.8532,30.6983],[-90.8495,30.7001],[-90.851,30.7024],[-90.8521,30.7038],[-90.8515,30.7061],[-90.8489,30.7065],[-90.8457,30.7088],[-90.8451,30.7124],[-90.8462,30.7143],[-90.8477,30.7198],[-90.8461,30.7211],[-90.8434,30.7229],[-90.8413,30.7234],[-90.8407,30.7266],[-90.8418,30.7325],[-90.846,30.7362],[-90.8502,30.7417],[-90.8523,30.744],[-90.8512,30.75],[-90.8479,30.7563],[-90.8447,30.7623],[-90.8436,30.7641],[-90.8404,30.7732],[-90.8419,30.7782],[-90.8419,30.7869],[-90.8423,30.7906],[-90.8434,30.7933],[-90.8396,30.797],[-90.8385,30.8024],[-90.839,30.8066],[-90.8379,30.8102],[-90.8347,30.8166],[-90.8352,30.8193],[-90.8378,30.8207],[-90.8405,30.8248],[-90.8421,30.8271],[-90.8447,30.8308],[-90.8457,30.8335],[-90.8468,30.8372],[-90.8425,30.8427],[-90.8414,30.8449],[-90.8424,30.8486],[-90.8493,30.8505],[-90.853,30.8528],[-90.8551,30.856],[-90.8577,30.8629],[-90.8598,30.8679],[-90.8598,30.8743],[-90.856,30.8761],[-90.8528,30.8788],[-90.8491,30.8825],[-90.8484,30.8962],[-90.8505,30.8985],[-90.8532,30.9012],[-90.8553,30.9053],[-90.852,30.9108],[-90.8541,30.9186],[-90.8572,30.9309],[-90.8588,30.9355],[-90.8619,30.9451],[-90.8565,30.9515],[-90.8506,30.9565],[-90.8474,30.9597],[-90.8458,30.9619],[-90.843,30.9747],[-90.8435,30.9839],[-90.8386,30.9916],[-90.829,30.9947],[-90.8268,30.9992],[-90.8124,30.9992],[-90.5669,31]]]},\"properties\":{\"name\":\"Saint Helena\",\"state\":\"LA\"}}]}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
Recent data are lacking to assess whether impairments still exist at four of Wisconsin’s largest Lake Michigan harbors that were designated as Areas of Concern (AOCs) in the late 1980s due to sediment contamination and multiple Beneficial Use Impairments (BUIs), such as those affecting benthos (macroinvertebrates) and plankton (zooplankton and phytoplankton) communities. During three seasonal sampling events (“seasons”) in May through August 2012, the U.S. Geological Survey collected sediment benthos and water plankton at the four AOCs as well as six less-degraded non-AOCs along the western Lake Michigan shoreline to assess whether AOC communities were degraded in comparison to non-AOC communities. The four AOCs are the Lower Menominee River, the Lower Green Bay and Fox River, the Sheboygan River, and the Milwaukee Estuary. Due to their size and complexity, multiple locations or “subsites” were sampled within the Lower Green Bay and Fox River AOC (Lower Green Bay, the Fox River near Allouez, and the Fox River near De Pere) and within the Milwaukee Estuary AOC (the Milwaukee River, the Menomonee River, and the Milwaukee Harbor) and single locations were sampled at the other AOCs and non-AOCs. The six non-AOCs are the Escanaba River in Michigan, and the Oconto River, Ahnapee River, Kewaunee River, Manitowoc River, and Root River in Wisconsin. Benthos samples were collected by using Hester-Dendy artificial substrates deployed for 30 days and by using a dredge sampler; zooplankton were collected by net and phytoplankton by whole-water sampler. Except for the Lower Green Bay and Milwaukee Harbor locations, communities at each AOC were compared to all non-AOCs as a group and to paired non-AOCs using taxa relative abundances and metrics, including richness, diversity, and an Index of Biotic Integrity (IBI, for Hester-Dendy samples only). Benthos samples collected during one or more seasons were rated as degraded for at least one metric at all AOCs. In the Milwaukee Estuary, benthos richness was lower in the Milwaukee River subsite spring and summer samples and in the Menomonee River subsite spring sample relative to the paired non-AOCs. Benthos diversity and IBIs at the Menomonee River subsite and IBIs at the Milwaukee River subsite and Sheboygan River were significantly lower than at all non-AOCs as a group across all seasons and therefore were rated as degraded. In addition, IBIs at the Lower Menominee River were significantly lower than those at the paired non-AOCs during all seasons and were therefore rated degraded. Benthos at both Fox River subsites and the Milwaukee River subsite were significantly different from their paired non-AOCs during all three seasons, based on a comparison of the relative abundances of taxa using multivariate testing. Metrics for plankton at AOCs were not significantly lower than those at the paired or group non-AOCs during all seasons; however, zooplankton richness in spring at the Sheboygan River and in fall at the Menomonee River subsite was rated as degraded in comparison to paired non-AOCs. Also, zooplankton richness in fall at the Fox River near Allouez subsite and in spring at the Milwaukee River subsite was rated degraded overall because values were lower than at all non-AOCs as a group and lower than at the paired non-AOCs. Zooplankton diversity in fall at the Fox River near Allouez subsite and the Lower Menominee River was rated degraded in comparison to paired non-AOC comparison sites. Zooplankton communities at the Fox River near Allouez subsite were significantly different from the paired non-AOCs when multivariate comparisons were made without rotifers other than A. priodonta. Overall, benthos and zooplankton BUIs remained at the AOCs in 2012 but no AOCs with a phytoplankton BUI were rated degraded in comparison to non-AOCs. The use of a multiple ecological measures, structural and functional, and multiple statistical analyses, biological metrics and multivariate statistics, provided assessments that defined 2012 status of communities relative to less-impaired non-AOCs in the Great Lakes area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165090","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources and the U.S. Environmental Protection Agency—Great Lakes National Program Office","usgsCitation":"Scudder Eikenberry, B.C., Bell, A.H., Templar, H.A., and Burns, D.J., 2016, Comparison of benthos and plankton for selected Areas of Concern and non-Areas of Concern in Western Lake Michigan Rivers and Harbors in 2012: U.S. Geological Survey Scientific Investigations Report 2016–5090, 28 p., https://dx.doi.org/10.3133/sir20165090.","productDescription":"vi, 38 p.","startPage":"1","endPage":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071418","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":325585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5090/sir20165090.pdf","text":"Report","size":"1.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5090"},{"id":325584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5090/coverthb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.4951171875,\n 41.713930073371294\n ],\n [\n -87.703857421875,\n 42.19596877629178\n ],\n [\n -87.73681640625,\n 42.391008609205045\n ],\n [\n -87.747802734375,\n 42.80346172417078\n ],\n [\n -87.81372070312499,\n 43.004647127794435\n ],\n [\n -87.791748046875,\n 43.46089378008257\n ],\n [\n -87.60498046875,\n 43.82660134505384\n ],\n [\n -87.615966796875,\n 44.03232064275084\n ],\n [\n -87.440185546875,\n 44.32384807250689\n ],\n [\n -87.396240234375,\n 44.61393394730626\n ],\n [\n -87.29736328125,\n 44.77793589631623\n ],\n [\n -87.528076171875,\n 44.879228141635274\n ],\n [\n -87.84530639648436,\n 44.621265367781014\n ],\n [\n -87.86453247070312,\n 44.621265367781014\n ],\n [\n -87.91706085205078,\n 44.57848569904532\n ],\n [\n -87.91053771972656,\n 44.56870306646167\n ],\n [\n -87.96066284179688,\n 44.535429806668404\n ],\n [\n -87.99671173095703,\n 44.54497334861026\n ],\n [\n -88.341064453125,\n 44.68427737181225\n ],\n [\n -88.450927734375,\n 44.89479576469787\n ],\n [\n -88.08837890625,\n 44.98811302615805\n ],\n [\n -87.890625,\n 45.10454630976873\n ],\n [\n -87.264404296875,\n 45.259422036351694\n ],\n [\n -87.57202148437499,\n 45.62940492064501\n ],\n [\n -87.066650390625,\n 45.706179285330855\n ],\n [\n -86.9677734375,\n 46.263442671779885\n ],\n [\n -87.4951171875,\n 46.430285240839964\n ],\n [\n -87.9345703125,\n 46.61171462536894\n ],\n [\n -88.3740234375,\n 46.64189395892874\n ],\n [\n -88.70361328125,\n 46.61171462536894\n ],\n [\n -88.604736328125,\n 46.31658418182218\n ],\n [\n -89.18701171875,\n 46.20264638061019\n ],\n [\n -89.154052734375,\n 45.96642454131025\n ],\n [\n -89.09912109375,\n 45.775186183521036\n ],\n [\n -89.02221679687499,\n 45.60635207711834\n ],\n [\n -89.12109375,\n 45.38301927899065\n ],\n [\n -89.176025390625,\n 45.1433047394883\n ],\n [\n -89.20898437499999,\n 44.88701247981298\n ],\n [\n -89.47265625,\n 44.42593442145313\n ],\n [\n -90.054931640625,\n 43.82660134505384\n ],\n [\n -89.527587890625,\n 43.48481212891603\n ],\n [\n -88.846435546875,\n 43.52465500687185\n ],\n [\n -88.494873046875,\n 43.39706523932025\n ],\n [\n -88.39599609375,\n 42.98857645832184\n ],\n [\n -87.4951171875,\n 41.713930073371294\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
http://wi.water.usgs.gov
Despite control efforts, human schistosomiasis remains prevalent throughout Africa, Asia, and South America. The global schistosomiasis burden has changed little since the new anthelmintic drug, praziquantel, promised widespread control.
\nWe evaluated large-scale schistosomiasis control attempts over the past century and across the globe by identifying factors that predict control program success: snail control (e.g., molluscicides or biological control), mass drug administrations (MDA) with praziquantel, or a combined strategy using both. For data, we compiled historical information on control tactics and their quantitative outcomes for all 83 countries and territories in which: (i) schistosomiasis was allegedly endemic during the 20th century, and (ii) schistosomiasis remains endemic, or (iii) schistosomiasis has been \"eliminated,\" or is \"no longer endemic,\" or transmission has been interrupted.
\nWidespread snail control reduced prevalence by 92 ± 5% (N = 19) vs. 37 ± 7% (N = 29) for programs using little or no snail control. In addition, ecological, economic, and political factors contributed to schistosomiasis elimination. For instance, snail control was most common and widespread in wealthier countries and when control began earlier in the 20th century.
\nSnail control has been the most effective way to reduce schistosomiasis prevalence. Despite evidence that snail control leads to long-term disease reduction and elimination, most current schistosomiasis control efforts emphasize MDA using praziquantel over snail control. Combining drug-based control programs with affordable snail control seems the best strategy for eliminating schistosomiasis.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pntd.0004794","usgsCitation":"Sokolow, S.H., Wood, C., Jones, I.J., Swartz, S.J., Lopez, M., Hsieh, M.H., Lafferty, K.D., Kuris, A.M., Rickards, C., and De Leo, G.A., 2016, Global assessment of schistosomiasis control over the past century shows targeting the snail intermediate host works best: PLoS Neglected Tropical Diseases, v. 10, no. 7, e0004794; 19 p., https://doi.org/10.1371/journal.pntd.0004794.","productDescription":"e0004794; 19 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073942","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470730,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pntd.0004794","text":"Publisher Index Page"},{"id":325604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-21","publicationStatus":"PW","scienceBaseUri":"57972a21e4b021cadec86f1d","contributors":{"authors":[{"text":"Sokolow, Susanne H.","contributorId":52503,"corporation":false,"usgs":false,"family":"Sokolow","given":"Susanne","email":"","middleInitial":"H.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":643408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Chelsea L.","contributorId":36866,"corporation":false,"usgs":true,"family":"Wood","given":"Chelsea L.","affiliations":[],"preferred":false,"id":643409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Isabel J.","contributorId":173135,"corporation":false,"usgs":false,"family":"Jones","given":"Isabel","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":643410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swartz, Scott J.","contributorId":173136,"corporation":false,"usgs":false,"family":"Swartz","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":643411,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopez, Melina","contributorId":173137,"corporation":false,"usgs":false,"family":"Lopez","given":"Melina","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":643412,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hsieh, Michael H.","contributorId":146317,"corporation":false,"usgs":false,"family":"Hsieh","given":"Michael","email":"","middleInitial":"H.","affiliations":[{"id":16665,"text":"Stanford University; Biomedical Research Institute; Children's National Health System; The George Washington University","active":true,"usgs":false}],"preferred":false,"id":643413,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":643407,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kuris, Armand M.","contributorId":54332,"corporation":false,"usgs":true,"family":"Kuris","given":"Armand","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":643414,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rickards, Chloe","contributorId":173138,"corporation":false,"usgs":false,"family":"Rickards","given":"Chloe","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":643415,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"De Leo, Giulio A.","contributorId":146323,"corporation":false,"usgs":false,"family":"De Leo","given":"Giulio","email":"","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":643416,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70174823,"text":"fs20163049 - 2016 - Water resources of Tangipahoa Parish, Louisiana","interactions":[],"lastModifiedDate":"2016-09-27T09:31:30","indexId":"fs20163049","displayToPublicDate":"2016-07-25T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3049","title":"Water resources of Tangipahoa Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in Tangipahoa Parish, Louisiana, is critical for proper water-resource management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163049","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., and Prakken, L.B., 2016, Water resources of Tangipahoa Parish, Louisiana: U.S. Geological Survey Fact Sheet 2016–3049, 6 p., https://dx.doi.org/10.3133/fs20163049.","productDescription":"6 p.","startPage":"1","endPage":"6","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065604","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":325340,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3049/coverthb.jpg"},{"id":325595,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3049/fs20163049.pdf","text":"Fact Sheet","size":"2.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3049"}],"country":"United States","state":"Louisiana","county":"Tangipahoa Parish","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-90.3482,31.0012],[-90.3477,30.9949],[-90.3468,30.9058],[-90.3346,30.9048],[-90.3347,30.9016],[-90.3298,30.902],[-90.33,30.891],[-90.3167,30.8913],[-90.3168,30.8813],[-90.3159,30.8748],[-90.3159,30.8703],[-90.3139,30.8643],[-90.3097,30.8574],[-90.3013,30.8509],[-90.2992,30.8472],[-90.2971,30.8445],[-90.2956,30.8385],[-90.2936,30.8316],[-90.2926,30.828],[-90.2917,30.8134],[-90.2939,30.8079],[-90.2913,30.8033],[-90.2861,30.7987],[-90.2809,30.7936],[-90.2794,30.7812],[-90.2768,30.7775],[-90.2731,30.7757],[-90.2716,30.7738],[-90.2663,30.7674],[-90.2648,30.7655],[-90.2637,30.7623],[-90.2651,30.7413],[-90.2636,30.7372],[-90.2615,30.7339],[-90.2578,30.7321],[-90.2552,30.7284],[-90.2553,30.7224],[-90.2554,30.7174],[-90.256,30.7124],[-90.2567,30.7024],[-90.2515,30.6936],[-90.2495,30.6863],[-90.2485,30.6799],[-90.2491,30.6758],[-90.2508,30.6698],[-90.2525,30.6657],[-90.2525,30.6612],[-90.2521,30.657],[-90.25,30.652],[-90.2458,30.6469],[-90.2448,30.6428],[-90.2444,30.6391],[-90.2461,30.6323],[-90.2467,30.5925],[-90.2458,30.577],[-90.2444,30.5299],[-90.2442,30.5093],[-90.2443,30.5061],[-90.2443,30.5038],[-90.2433,30.2247],[-90.2776,30.2306],[-90.2972,30.294],[-90.312,30.2955],[-90.3199,30.2988],[-90.3337,30.2953],[-90.349,30.2973],[-90.3629,30.2905],[-90.373,30.2833],[-90.3841,30.2871],[-90.3915,30.2849],[-90.4016,30.2854],[-90.42,30.2902],[-90.4316,30.2958],[-90.4426,30.3046],[-90.475,30.3365],[-90.476,30.3401],[-90.4738,30.3438],[-90.4759,30.3507],[-90.48,30.3585],[-90.4896,30.3554],[-90.4884,30.3631],[-90.4921,30.3664],[-90.5027,30.3624],[-90.5043,30.3637],[-90.5026,30.3692],[-90.5009,30.3779],[-90.5019,30.3848],[-90.504,30.3871],[-90.5077,30.3885],[-90.5114,30.3913],[-90.5119,30.3954],[-90.5123,30.3986],[-90.5134,30.4018],[-90.5155,30.4041],[-90.5175,30.4069],[-90.5186,30.4105],[-90.5196,30.4124],[-90.5254,30.4174],[-90.5301,30.4179],[-90.5343,30.4212],[-90.539,30.4244],[-90.5427,30.4277],[-90.5459,30.4304],[-90.5468,30.4378],[-90.5468,30.4423],[-90.5457,30.4469],[-90.5478,30.4492],[-90.5499,30.4515],[-90.5503,30.4588],[-90.5502,30.4657],[-90.5528,30.4698],[-90.5549,30.4749],[-90.5554,30.4785],[-90.559,30.4845],[-90.567,30.4869],[-90.5671,30.5239],[-90.567,30.5317],[-90.5674,30.6313],[-90.5704,30.6501],[-90.5676,30.6652],[-90.5664,30.7241],[-90.5668,30.7301],[-90.568,30.768],[-90.5668,30.869],[-90.5668,30.8763],[-90.5673,30.8795],[-90.5672,30.8864],[-90.5669,31],[-90.5502,31],[-90.5048,31.0003],[-90.3482,31.0012]]]},\"properties\":{\"name\":\"Tangipahoa\",\"state\":\"LA\"}}]}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2016-07-25","noUsgsAuthors":false,"publicationDate":"2016-07-25","publicationStatus":"PW","scienceBaseUri":"57972a21e4b021cadec86f21","contributors":{"authors":[{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prakken, Lawrence B. lprakken@usgs.gov","contributorId":139067,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","email":"lprakken@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":643479,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170934,"text":"sir20165051 - 2016 - Evaluation of National Atmospheric Deposition Program measurements for colocated sites CO89 and CO98 at Rocky Mountain National Park, water years 2010–14","interactions":[],"lastModifiedDate":"2016-07-25T09:15:52","indexId":"sir20165051","displayToPublicDate":"2016-07-22T16:00:00","publicationYear":"2016","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":"2016-5051","title":"Evaluation of National Atmospheric Deposition Program measurements for colocated sites CO89 and CO98 at Rocky Mountain National Park, water years 2010–14","docAbstract":"
Atmospheric wet-deposition monitoring in Rocky Mountain National Park included precipitation depth and aqueous chemical measurements at colocated National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites CO89 and CO98 (Loch Vale) during water years 2010–14 (study period). The colocated sites were separated by approximately 6.5 meters horizontally and 0.5 meter in elevation, in accordance with NADP siting criteria. Assessment of the 5-year record of colocated data is intended to inform man-agement decisions pertaining to the achievement of nitrogen deposition reduction goals of the Rocky Mountain National Park Nitrogen Deposition Reduction Plan.
The data at site CO98 met NADP completeness criteria for the first time in 29 years of operation in 2011 and then again in 2012. During the study period, data at site CO89 met completeness criteria in 2012. Median weekly relative precipitation-depth differences between sites CO89 and CO98 ranged from 0 to 0.25 millimeter during the study period. Median weekly absolute percent differences in sample volume ranged from 5 to 10 percent. Median relative concentration differences for weekly ammonium (NH4+) and nitrate (NO3-) concentrations were near the NADP Central Analytical Laboratory’s method detection limits and thus were considered small. Absolute percent differences for water-year 2010–14 precipitation-weighted mean concentrations of NH4+, NO3-, and inorganic nitrogen (Ninorg) ranged from 0.0 to 25.7 percent. Absolute percent differences for water-year 2010–14 NH4+, NO3-, and Ninorg deposition ranged from 2.1 to 18.9 percent, 3.3 to 24.5 percent, and 0.3 to 17.4 percent, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165051","usgsCitation":"Wetherbee, G.A., 2016, Evaluation of National Atmospheric Deposition Program measurements for colocated sites CO89 and CO98 at Rocky Mountain National Park, water years 2010–14: U.S. Geological Survey Scientific Investigations Report 2016–5051, 32 p., https://dx.doi.org/10.3133/sir20165051.","productDescription":"vi, 32 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073496","costCenters":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"links":[{"id":325482,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5051/sir20165051.pdf","text":"Report","size":"16.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5051"},{"id":325481,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5051/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountain National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.5,\n 39.5\n ],\n [\n -104.5,\n 41\n ],\n [\n -106,\n 41\n ],\n [\n -106,\n 39.5\n ],\n [\n -104.5,\n 39.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, USGS Branch of Quality Systems
Box 25046, Mail Stop 401
Denver, CO 80225
Degradation of aquatic habitats has motivated construction and research on the use of artificial reefs to enhance production of fish populations. However, reefs are often poorly planned, reef design characteristics are not evaluated, and reef assessments are short-term. We constructed 29 reefs in Thunder Bay, Lake Huron, in 2010 and 2011 to mitigate for degradation of a putative lake trout spawning reef. Reefs were designed to evaluate lake trout preferences for height, orientation, and size, and were compared with two degraded natural reefs and a high-quality natural reef (East Reef). Eggs and fry were sampled on each reef for five years post-construction, and movements of 40 tagged lake trout were tracked during three spawning seasons using acoustic telemetry. Numbers of adults and spawning on the constructed reefs were initially low, but increased significantly over the five years, while remaining consistent on East Reef. Adult density, egg deposition, and fry catch were not related to reef height or orientation of the constructed reefs, but were related to reef size and adjacency to East Reef. Adult lake trout visited and spawned on all except the smallest constructed reefs. Of the metrics used to evaluate the reefs, acoustic telemetry produced the most valuable and consistent data, including fine-scale examination of lake trout movements relative to individual reefs. Telemetry data, supplemented with diver observations, identified several previously unknown natural spawning sites, including the high-use portions of East Reef. Reef construction has increased the capacity for fry production in Thunder Bay without apparently decreasing the use of the natural reef. Results of this project emphasize the importance of multi-year reef assessment, use of multiple assessment methods, and comparison of reef characteristics when developing artificial reef projects. Specific guidelines for construction of reefs focused on enhancing lake trout spawning are suggested.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2016.06.012","usgsCitation":"Marsden, J., Binder, T., Johnson, J., He, J., Dingledine, N., Adams, J., Johnson, N.S., Buchinger, T.J., and Krueger, C., 2016, Five-year evaluation of habitat remediation in Thunder Bay, Lake Huron: Comparison of constructed reef characteristics that attract spawning lake trout: Fisheries Research, v. 183, p. 275-286, https://doi.org/10.1016/j.fishres.2016.06.012.","productDescription":"12 p.","startPage":"275","endPage":"286","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075570","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":470736,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2016.06.012","text":"Publisher Index Page"},{"id":325531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Huron, Thunder Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.583984375,\n 44.74380712723563\n ],\n [\n -83.583984375,\n 45.12974228438219\n ],\n [\n -82.99209594726562,\n 45.12974228438219\n ],\n [\n -82.99209594726562,\n 44.74380712723563\n ],\n [\n -83.583984375,\n 44.74380712723563\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"183","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57933616e4b0eb1ce79e8bb5","contributors":{"authors":[{"text":"Marsden, J. Ellen","contributorId":10367,"corporation":false,"usgs":true,"family":"Marsden","given":"J. Ellen","affiliations":[],"preferred":false,"id":643170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Binder, Thomas R.","contributorId":21093,"corporation":false,"usgs":true,"family":"Binder","given":"Thomas R.","affiliations":[],"preferred":false,"id":643171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, James","contributorId":173063,"corporation":false,"usgs":false,"family":"Johnson","given":"James","email":"","affiliations":[],"preferred":false,"id":643172,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"He, Ji","contributorId":172649,"corporation":false,"usgs":false,"family":"He","given":"Ji","affiliations":[],"preferred":false,"id":643173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dingledine, Natalie","contributorId":173064,"corporation":false,"usgs":false,"family":"Dingledine","given":"Natalie","email":"","affiliations":[],"preferred":false,"id":643174,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Janice","contributorId":173065,"corporation":false,"usgs":false,"family":"Adams","given":"Janice","email":"","affiliations":[],"preferred":false,"id":643175,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":597,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":643176,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Buchinger, Tyler J.","contributorId":40508,"corporation":false,"usgs":true,"family":"Buchinger","given":"Tyler","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":643177,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Krueger, Charles C.","contributorId":73131,"corporation":false,"usgs":true,"family":"Krueger","given":"Charles C.","affiliations":[],"preferred":false,"id":643178,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70174925,"text":"70174925 - 2016 - The logic of comparative life history studies for estimating key parameters, with a focus on natural mortality rate","interactions":[],"lastModifiedDate":"2017-05-04T10:03:52","indexId":"70174925","displayToPublicDate":"2016-07-22T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1936,"text":"ICES Journal of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"The logic of comparative life history studies for estimating key parameters, with a focus on natural mortality rate","docAbstract":"There are a number of key parameters in population dynamics that are difficult to estimate, such as natural mortality rate, intrinsic rate of population growth, and stock-recruitment relationships. Often, these parameters of a stock are, or can be, estimated indirectly on the basis of comparative life history studies. That is, the relationship between a difficult to estimate parameter and life history correlates is examined over a wide variety of species in order to develop predictive equations. The form of these equations may be derived from life history theory or simply be suggested by exploratory data analysis. Similarly, population characteristics such as potential yield can be estimated by making use of a relationship between the population parameter and bio-chemico–physical characteristics of the ecosystem. Surprisingly, little work has been done to evaluate how well these indirect estimators work and, in fact, there is little guidance on how to conduct comparative life history studies and how to evaluate them. We consider five issues arising in such studies: (i) the parameters of interest may be ill-defined idealizations of the real world, (ii) true values of the parameters are not known for any species, (iii) selecting data based on the quality of the estimates can introduce a host of problems, (iv) the estimates that are available for comparison constitute a non-random sample of species from an ill-defined population of species of interest, and (v) the hierarchical nature of the data (e.g. stocks within species within genera within families, etc., with multiple observations at each level) warrants consideration. We discuss how these issues can be handled and how they shape the kinds of questions that can be asked of a database of life history studies.
","language":"English","publisher":"Oxford Journals","doi":"10.1093/icesjms/fsw089","usgsCitation":"Hoenig, J., Then, A.Y., Babcock, E.A., Hall, N.G., Hewitt, D.A., and Hesp, S.A., 2016, The logic of comparative life history studies for estimating key parameters, with a focus on natural mortality rate: ICES Journal of Marine Science, v. 73, no. 10, p. 2453-2467, https://doi.org/10.1093/icesjms/fsw089.","productDescription":"15 p.","startPage":"2453","endPage":"2467","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069001","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":470738,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/icesjms/fsw089","text":"Publisher Index Page"},{"id":325530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"10","noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"57933619e4b0eb1ce79e8bc3","contributors":{"authors":[{"text":"Hoenig, John M","contributorId":58211,"corporation":false,"usgs":true,"family":"Hoenig","given":"John M","affiliations":[],"preferred":false,"id":643164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Then, Amy Y.-H.","contributorId":173060,"corporation":false,"usgs":false,"family":"Then","given":"Amy","email":"","middleInitial":"Y.-H.","affiliations":[],"preferred":false,"id":643165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Babcock, Elizabeth A.","contributorId":173061,"corporation":false,"usgs":false,"family":"Babcock","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":643166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hall, Norman G.","contributorId":76245,"corporation":false,"usgs":true,"family":"Hall","given":"Norman","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":643167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":643168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hesp, Sybrand A.","contributorId":173062,"corporation":false,"usgs":false,"family":"Hesp","given":"Sybrand","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":643169,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174203,"text":"ofr20161090 - 2016 - Hurricane Sandy washover deposits on southern Long Beach Island, New Jersey","interactions":[],"lastModifiedDate":"2016-08-08T09:05:49","indexId":"ofr20161090","displayToPublicDate":"2016-07-22T11:00:00","publicationYear":"2016","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":"2016-1090","title":"Hurricane Sandy washover deposits on southern Long Beach Island, New Jersey","docAbstract":"Sedimentologic and topographic data from Hurricane Sandy washover deposits were collected from southern Long Beach Island, New Jersey, in order to document changes to the barrier-island beaches, dunes, and coastal wetlands caused by Hurricane Sandy and subsequent storm events. These data will provide a baseline dataset for use in future coastal change descriptive and predictive studies and assessments. The data presented here were collected as part of the U.S. Geological Survey’s Barrier Island and Estuarine Wetland Physical Change Assessment Project (http://coastal.er.usgs.gov/sandy-wetland-assessment/), which aims to assess ecological and societal vulnerability that results from long- and short-term physical changes to barrier islands and coastal wetlands. This report describes data that were collected in April 2015, approximately 2½ years after Hurricane Sandy’s landfall on October 29, 2012. During the field campaign, washover deposits were photographed and described, and sediment cores, sediment samples, and surface-elevation data were collected. Data collected during this study, including sample locations and elevations, core photographs, computed tomography scans, descriptive core logs, sediment grain-size data, and accompanying Federal Geographic Data Committee metadata, are available in the associated U.S. Geological Survey data release (Bishop and others, 2016; http://dx.doi.org/10.5066/F7PK0D7S).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161090","collaboration":"Barrier Island and Estuarine Wetland Physical Change Assessment Project","usgsCitation":"Bishop, J.M., Richmond, B.R., Zaremba, N.J., Lunghino, B.D., and Kane, H.K., 2016, Hurricane Sandy washover deposits on southern Long Beach Island, New Jersey: U.S. Geological Survey Open-File Report 2016–1090, 14 p., https://dx.doi.org/10.3133/ofr20161090.","productDescription":"Report: vi, 21 p.; Data Release","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073323","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":324814,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1090/ofr20161090.pdf","text":"Report","size":"5.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1090"},{"id":324813,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1090/coverthb.jpg"},{"id":324815,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7PK0D7S","text":"USGS data release - Hurricane Sandy washover deposit data from southern Long Beach Island, New Jersey: Grain-size, elevations, and graphic core logs"}],"country":"United States","state":"New Jersey","otherGeospatial":"Long Beach Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.30912017822266,\n 39.504305605954634\n ],\n [\n -74.3060302734375,\n 39.49874248613119\n ],\n [\n -74.29779052734375,\n 39.49635815560969\n ],\n [\n -74.27684783935547,\n 39.504305605954634\n ],\n [\n -74.26380157470702,\n 39.52072745681898\n ],\n [\n -74.2620849609375,\n 39.526288816558626\n ],\n [\n -74.26654815673828,\n 39.53502719632629\n ],\n [\n -74.2730712890625,\n 39.53449762886045\n ],\n [\n -74.28062438964844,\n 39.526818446639844\n ],\n [\n -74.29847717285156,\n 39.51675478434244\n ],\n [\n -74.30912017822266,\n 39.504305605954634\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in South San Francisco Bay, California. This report includes data collected by U.S. Geological Survey (USGS) scientists for the period from January 2015 to December 2015. These data are appended to long-term datasets extending back to 1974, and serve as the basis for the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.
\nFollowing significant reductions in the late 1980s, silver (Ag) and copper (Cu) concentrations in sediment and M. petalum appear to have stabilized. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2015, concentrations of Ag and Cu in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. In M. petalum, all observed elements showed annual maxima in January–February and minima in April, except for Zn, which was lowest in December. In sediments, annual maxima also occurred in January–February, and minima were measured in June and September. In 2015, metal concentrations in both sediments and clam tissue were among the lowest on record. This record suggests that regional-scale factors now largely control sedimentary and bioavailable concentrations of Ag and Cu, as well as other elements of regulatory interest, at the Palo Alto site.
\nAnalyses of the benthic community structure at the same mudflat over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of M. petalum shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2015), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2015. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed an increase in dominance, concurrent with the decrease in Ag and Cu concentrations, and in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 abundance in 2015. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like M. petalum. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or to anoxia. The reproductive mode of most species present in 2015 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous (live-birth) species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2015 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161118","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Crauder, Jeff, Parchaso, Francis, Stewart, Robin, Turner, Mathew, Hornberger, M.I., and Luoma, S.N., 2016, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015: U.S. Geological Survey Open-File Report 2016–1118, 78 p., https://dx.doi.org/10.3133/ofr20161118.","productDescription":"vii, 78 p.","numberOfPages":"87","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076608","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":416191,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":416190,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416189,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416188,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181107","text":"Open-File Report 2018-1107","linkHelpText":"- Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017"},{"id":416187,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171135","text":"Open-File Report 2017-1135","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016"},{"id":325514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1118/coverthb.jpg"},{"id":325515,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1118/ofr20161118.pdf","text":"Report","size":"4.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1118"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.14530944824217,\n 37.40452830389465\n ],\n [\n -122.14530944824217,\n 37.52443079581378\n ],\n [\n -121.91871643066406,\n 37.52443079581378\n ],\n [\n -121.91871643066406,\n 37.40452830389465\n ],\n [\n -122.14530944824217,\n 37.40452830389465\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NRP staff
National Research Program
U.S. Geological Survey
345 Middlefield Road, MS-435
Menlo Park, CA 94025
http://water.usgs.gov/nrp/
Environmental tracers (noble gases, tritium, industrial gases, stable isotopes, and radio-carbon) and hydrogeology were interpreted to determine groundwater transit-time distribution and calculate mean transit time (MTT) with lumped parameter modeling at 19 large springs distributed throughout the Upper Colorado River Basin (UCRB), USA. The predictive value of the MTT to evaluate the pattern and timing of groundwater response to hydraulic stress (i.e., vulnerability) is examined by a statistical analysis of MTT, historical spring discharge records, and the Palmer Hydrological Drought Index. MTTs of the springs range from 10 to 15,000 years and 90 % of the cumulative discharge-weighted travel-time distribution falls within the range of 2−10,000 years. Historical variability in discharge was assessed as the ratio of 10–90 % flow-exceedance (R 10/90%) and ranged from 2.8 to 1.1 for select springs with available discharge data. The lag-time (i.e., delay in discharge response to drought conditions) was determined by cross-correlation analysis and ranged from 0.5 to 6 years for the same select springs. Springs with shorter MTTs (<80 years) statistically correlate with larger discharge variations and faster responses to drought, indicating MTT can be used for estimating the relative magnitude and timing of groundwater response. Results indicate that groundwater discharge to streams in the UCRB will likely respond on the order of years to climate variation and increasing groundwater withdrawals.
","language":"English","publisher":"International Association of Hydrogeologists","doi":"10.1007/s10040-016-1440-9","usgsCitation":"Solder, J.E., Stolp, B.J., Heilweil, V.M., and Susong, D.D., 2016, Characterization of mean transit time at large springs in the Upper Colorado River Basin, USA: A tool for assessing groundwater discharge vulnerability: Hydrogeology Journal, v. 24, no. 8, p. 2017-2033, https://doi.org/10.1007/s10040-016-1440-9.","productDescription":"17 p.","startPage":"2017","endPage":"2033","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075897","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":325907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","volume":"24","issue":"8","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-20","publicationStatus":"PW","scienceBaseUri":"57a1c42de4b006cb45552bfb","contributors":{"authors":[{"text":"Solder, John E. 0000-0002-0660-3326 jsolder@usgs.gov","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":171916,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"jsolder@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":639086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stolp, Bernard J. 0000-0003-3803-1497 bjstolp@usgs.gov","orcid":"https://orcid.org/0000-0003-3803-1497","contributorId":963,"corporation":false,"usgs":true,"family":"Stolp","given":"Bernard","email":"bjstolp@usgs.gov","middleInitial":"J.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":639088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heilweil, Victor M. heilweil@usgs.gov","contributorId":837,"corporation":false,"usgs":true,"family":"Heilweil","given":"Victor","email":"heilweil@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":639087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Susong, David D. ddsusong@usgs.gov","contributorId":1040,"corporation":false,"usgs":true,"family":"Susong","given":"David","email":"ddsusong@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":639089,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174821,"text":"sir20165100 - 2016 - Water-quality trends and constituent-transport analysis for selected sampling sites in the Milltown Reservoir/Clark Fork River Superfund Site in the upper Clark Fork Basin, Montana, water years 1996–2015","interactions":[],"lastModifiedDate":"2016-07-20T11:54:23","indexId":"sir20165100","displayToPublicDate":"2016-07-20T00:00:00","publicationYear":"2016","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":"2016-5100","title":"Water-quality trends and constituent-transport analysis for selected sampling sites in the Milltown Reservoir/Clark Fork River Superfund Site in the upper Clark Fork Basin, Montana, water years 1996–2015","docAbstract":"During the extended history of mining in the upper Clark Fork Basin in Montana, large amounts of waste materials enriched with metallic contaminants (cadmium, copper, lead, and zinc) and the metalloid trace element arsenic were generated from mining operations near Butte and milling and smelting operations near Anaconda. Extensive deposition of mining wastes in the Silver Bow Creek and Clark Fork channels and flood plains had substantial effects on water quality. Federal Superfund remediation activities in the upper Clark Fork Basin began in 1983 and have included substantial remediation near Butte and removal of the former Milltown Dam near Missoula. To aid in evaluating the effects of remediation activities on water quality, the U.S. Geological Survey began collecting streamflow and water-quality data in the upper Clark Fork Basin in the 1980s.
Trend analysis was done on specific conductance, selected trace elements (arsenic, copper, and zinc), and suspended sediment for seven sampling sites in the Milltown Reservoir/Clark Fork River Superfund Site for water years 1996–2015. The most upstream site included in trend analysis is Silver Bow Creek at Warm Springs, Montana (sampling site 8), and the most downstream site is Clark Fork above Missoula, Montana (sampling site 22), which is just downstream from the former Milltown Dam. Water year is the 12-month period from October 1 through September 30 and is designated by the year in which it ends. Trend analysis was done by using a joint time-series model for concentration and streamflow. To provide temporal resolution of changes in water quality, trend analysis was conducted for four sequential 5-year periods: period 1 (water years 1996–2000), period 2 (water years 2001–5), period 3 (water years 2006–10), and period 4 (water years 2011–15). Because of the substantial effect of the intentional breach of Milltown Dam on March 28, 2008, period 3 was subdivided into period 3A (October 1, 2005–March 27, 2008) and period 3B (March 28, 2008–September 30, 2010) for the Clark Fork above Missoula (sampling site 22). Trend results were considered statistically significant when the statistical probability level was less than 0.01.
In conjunction with the trend analysis, estimated normalized constituent loads (hereinafter referred to as “loads”) were calculated and presented within the framework of a constituent-transport analysis to assess the temporal trends in flow-adjusted concentrations (FACs) in the context of sources and transport. The transport analysis allows assessment of temporal changes in relative contributions from upstream source areas to loads transported past each reach outflow.
Trend results indicate that FACs of unfiltered-recoverable copper decreased at the sampling sites from the start of period 1 through the end of period 4; the decreases ranged from large for one sampling site (Silver Bow Creek at Warm Springs [sampling site 8]) to moderate for two sampling sites (Clark Fork near Galen, Montana [sampling site 11] and Clark Fork above Missoula [sampling site 22]) to small for four sampling sites (Clark Fork at Deer Lodge, Montana [sampling site 14], Clark Fork at Goldcreek, Montana [sampling site 16], Clark Fork near Drummond, Montana [sampling site 18], and Clark Fork at Turah Bridge near Bonner, Montana [sampling site 20]). For period 4 (water years 2011–15), the most notable changes indicated for the Milltown Reservoir/Clark Fork River Superfund Site were statistically significant decreases in FACs and loads of unfiltered-recoverable copper for sampling sites 8 and 22. The period 4 changes in FACs of unfiltered-recoverable copper for all other sampling sites were not statistically significant.
Trend results indicate that FACs of unfiltered-recoverable arsenic decreased at the sampling sites from period 1 through period 4 (water years 1996–2015); the decreases ranged from minor (sampling sites 8–20) to small (sampling site 22). For period 4 (water years 2011–15), the most notable changes indicated for the Milltown Reservoir/Clark Fork River Superfund Site were statistically significant decreases in FACs and loads of unfiltered-recoverable arsenic for sampling site 8 and near statistically significant decreases for sampling site 22. The period 4 changes in FACs of unfiltered-recoverable arsenic for all other sampling sites were not statistically significant.
Trend results indicate that FACs of suspended sediment decreased at the sampling sites from period 1 through period 4 (water years 1996–2015); the decreases ranged from moderate (sampling site 8) to small (sampling sites 11–22). For period 4 (water years 2011–15), the changes in FACs of suspended sediment were not statistically significant for any sampling sites.
The reach of the Clark Fork from Galen to Deer Lodge is a large source of metallic contaminants and suspended sediment, which strongly affects downstream transport of those constituents. Mobilization of copper and suspended sediment from flood-plain tailings and the streambed of the Clark Fork and its tributaries within the reach results in a contribution of those constituents that is proportionally much larger than the contribution of streamflow from within the reach. Within the reach from Galen to Deer Lodge, unfiltered-recoverable copper loads increased by a factor of about 4 and suspended-sediment loads increased by a factor of about 5, whereas streamflow increased by a factor of slightly less than 2. For period 4 (water years 2011–15), unfiltered-recoverable copper and suspended-sediment loads sourced from within the reach accounted for about 41 and 14 percent, respectively, of the loads at Clark Fork above Missoula (sampling site 22), whereas streamflow sourced from within the reach accounted for about 4 percent of the streamflow at sampling site 22. During water years 1996–2015, decreases in FACs and loads of unfiltered-recoverable copper and suspended sediment for the reach generally were proportionally smaller than for most other reaches.
Unfiltered-recoverable copper loads sourced within the reaches of the Clark Fork between Deer Lodge and Turah Bridge near Bonner (just upstream from the former Milltown Dam) were proportionally smaller than contributions of streamflow sourced from within the reaches; these reaches contributed proportionally much less to copper loading in the Clark Fork than the reach between Galen and Deer Lodge. Although substantial decreases in FACs and loads of unfiltered-recoverable copper and suspended sediment were indicated for Silver Bow Creek at Warm Springs (sampling site 8), those substantial decreases were not translated to downstream reaches between Deer Lodge and Turah Bridge near Bonner. The effect of the reach of the Clark Fork from Galen to Deer Lodge as a large source of copper and suspended sediment, in combination with little temporal change in those constituents for the reach, contributes to this pattern.
With the removal of the former Milltown Dam in 2008, substantial amounts of contaminated sediments that remained in the Clark Fork channel and flood plain in reach 9 (downstream from Turah Bridge near Bonner) became more available for mobilization and transport than before the dam removal. After the removal of the former Milltown Dam, the Clark Fork above Missoula (sampling site 22) had statistically significant decreases in FACs of unfiltered-recoverable copper in period 3B (March 28, 2008, through water year 2010) that continued in period 4 (water years 2011–15). Also, decreases in FACs of unfiltered-recoverable arsenic and suspended sediment were indicated for period 4 at this site. The decrease in FACs of unfiltered-recoverable copper for sampling site 22 during period 4 was proportionally much larger than the decrease for the Clark Fork at Turah Bridge near Bonner (sampling site 20). Net mobilization of unfiltered-recoverable copper and arsenic from sources within reach 9 are smaller for period 4 than for period 1 when the former Milltown Dam was in place, providing evidence that contaminant source materials have been substantially reduced in reach 9.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165100","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Sando, S.K., and Vecchia, A.V., 2016, Water-quality trends and constituent-transport analysis for selected sampling sites in the Milltown Reservoir/Clark Fork River Superfund Site in the upper Clark Fork Basin, Montana, water years 1996–2015: U.S. Geological Survey Scientific Investigations Report 2016–5100, 82 p., https://dx.doi.org/10.3133/sir20165100.","productDescription":"viii, 82 p.","numberOfPages":"94","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1996-10-01","ipdsId":"IP-074218","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":325351,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5100/coverthb.jpg"},{"id":325352,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5100/sir20165100.pdf","text":"Report","size":"3.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5100"}],"country":"United States","state":"Montana","otherGeospatial":"Upper Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.027099609375,\n 45.706179285330855\n ],\n [\n -114.027099609375,\n 47.517200697839414\n ],\n [\n -112.225341796875,\n 47.517200697839414\n ],\n [\n -112.225341796875,\n 45.706179285330855\n ],\n [\n -114.027099609375,\n 45.706179285330855\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
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Estuarine habitat occupied by Alligator mississippiensis, a primarily freshwater species, is spatially and temporally heterogeneous largely due to a salinity gradient that fluctuates. Using long-term night light survey data, we examined seasonal patterns in alligators’ habitat use by size classes in midstream and downstream estuary zones of Shark River, Everglades National Park, in southern Florida. We observed predominantly large-sized alligators (total length ≥ 1.75 m); observations of alligators in the small size classes (0.5 m ≤ total length < 1.25 m) were rare especially in the higher-salinity downstream zone. The density of alligators in the downstream zone was lower than that of the midstream zone during the dry season when salinity increases due to reduced precipitation. Conversely, the density of the large size alligators was higher in the downstream zone than in the midstream zone during the wet season, likely because of reduced salinity. We also found a significant declining trend over time in the number of alligators in the dry season, which coincides with the reported decline in alligator relative density in southern Florida freshwater wetlands. Our results indicated high adaptability of alligators to the fluctuating habitat conditions. Use of estuaries by alligators is likely driven in part by physiology and possibly by reproductive cycle, and our results supported their opportunistic use of estuary habitat and ontogenetic niche shifts.
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