It is generally recognized that meeting society's emerging environmental science and management needs will require the marine data community to provide simpler, more effective and more interoperable access to its data. There is broad agreement, as well, that data standards are the bedrock upon which interoperability will be built. The path that would bring the marine data community to agree upon and utilize such standards, however, is often elusive. In this paper we examine the trio of standards 1) netCDF files; 2) the Climate and Forecast (CF) metadata convention; and 3) the OPeNDAP data access protocol. These standards taken together have brought our community a high level of interoperability for \"gridded\" data such as model outputs, satellite products and climatological analyses, and they are gaining rapid acceptance for ocean observations. We will provide an overview of the scope of the contribution that has been made. We then step back from the information technology considerations to examine the community or \"social\" process by which the successes were achieved. We contrast the path by which the World Meteorological Organization (WMO) has advanced the Global Telecommunications System (GTS) - netCDF/CF/OPeNDAP exemplifying a \"bottom up\" standards process whereas GTS is \"top down\". Both of these standards are tales of success at achieving specific purposes, yet each is hampered by technical limitations. These limitations sometimes lead to controversy over whether alternative technological directions should be pursued. Finally we draw general conclusions regarding the factors that affect the success of a standards development effort - the likelihood that an IT standard will meet its design goals and will achieve community-wide acceptance. We believe that a higher level of thoughtful awareness by the scientists, program managers and technology experts of the vital role of standards and the merits of alternative standards processes can help us as a community to reach our interoperability goals faster.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceDate":"September 21-25, 2009","conferenceLocation":"Venice, Italy","language":"English","publisher":"Proceedings of OceanObs’09","doi":"10.5270/OceanObs09.cwp.41","usgsCitation":"Hankin, S.C., Blower, J.D., Carval, T., Casey, K.S., Donlon, C., Lauret, O., Loubrieu, T., Srinivasan, A., Trinanes, J., Godoy, O., Mendelssohn, R., Signell, R.P., de La Beaujardiere, J., Cornillon, P., Blanc, F., Rew, R., and Harlan, J., 2010, NetCDF-CF-OPeNDAP: Standards for ocean data interoperability and object lessons for community data standards processes, in Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society, v. 2, Venice, Italy, September 21-25, 2009, 9 p., https://doi.org/10.5270/OceanObs09.cwp.41.","productDescription":"9 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Modelling the effects of climate change on freshwater fishes requires robust field-based estimates accounting for interactions among multiple factors.2. We used data from an 8-year individual-based study of a wild brook trout (Salvelinus fontinalis) population to test the influence of water temperature on season-specific growth in the context of variation in other environmental (i.e. season, stream flow) or biotic factors (local brook trout biomass density and fish age and size) in West Brook, a third-order stream in western Massachusetts, U.S.A.3. Changes in ambient temperature influenced individual growth rates. In general, higher temperatures were associated with higher growth rates in winter and spring and lower growth rates in summer and autumn. However, the effect of temperature on growth was strongly context-dependent, differing in both magnitude and direction as a function of season, stream flow and fish biomass density.4. We found that stream flow and temperature had strong and complex interactive effects on trout growth. At the coldest temperatures (in winter), high stream flows were associated with reduced trout growth rates. During spring and autumn and in typical summers (when water temperatures were close to growth optima), higher flows were associated with increased growth rates. In addition, the effect of flow at a given temperature (the flow-temperature interaction) differed among seasons.5. Trout density negatively affected growth rate and had strong interactions with temperature in two of four seasons (i.e. spring and summer) with greater negative effects at high temperatures.6. Our study provided robust, integrative field-based estimates of the effects of temperature on growth rates for a species which serves as a model organism for cold-water adapted ectotherms facing the consequences of environmental change. Results of the study strongly suggest that failure to derive season-specific estimates, or to explicitly consider interactions with flow regime and fish density, will seriously compromise our ability to predict the effects of climate change on stream fish growth rates. Further, the concordance we found between empirical observations and likely energetic mechanisms suggests that our general results should be relevant at broader spatial and temporal scales. ?? 2010 Blackwell Publishing Ltd.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1111/j.1365-2427.2010.02430.x","issn":"00465070","usgsCitation":"Xu, C., Letcher, B., and Nislow, K., 2010, Context-specific influence of water temperature on brook trout growth rates in the field: Freshwater Biology, v. 55, no. 11, p. 2253-2264, https://doi.org/10.1111/j.1365-2427.2010.02430.x.","startPage":"2253","endPage":"2264","numberOfPages":"12","costCenters":[],"links":[{"id":217925,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2427.2010.02430.x"},{"id":245898,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"11","noUsgsAuthors":false,"publicationDate":"2010-05-13","publicationStatus":"PW","scienceBaseUri":"5059fa4de4b0c8380cd4da2a","contributors":{"authors":[{"text":"Xu, C.","contributorId":9781,"corporation":false,"usgs":true,"family":"Xu","given":"C.","email":"","affiliations":[],"preferred":false,"id":462106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Letcher, B. 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The two major issues are: 1) over sampling of sand transport caused by “mining” of sand due to the flow disturbance induced by the presence of the sampler and 2) clogging of the mesh bag with sand particles reducing the hydraulic efficiency of the sampler. Indirect measurement methods hold promise in that unlike direct methods, no transport-altering flow disturbance near the bed occurs. The bedform velocimetry method utilizes a measure of the bedform geometry and the speed of bedform translation to estimate the bedload transport through mass balance. The bedform velocimetry method is readily applied for the estimation of bedload transport in large sand-bed rivers so long as prominent bedforms are present and the streamflow discharge is steady for long enough to provide sufficient bedform translation between the successive bathymetric data sets. Bedform velocimetry in small sandbed rivers is often problematic due to rapid variation within the hydrograph. The bottom-track bias feature of the acoustic Doppler current profiler (ADCP) has been utilized to accurately estimate the virtual velocities of sand-bed rivers. Coupling measurement of the virtual velocity with an accurate determination of the active depth of the streambed sediment movement is another method to measure bedload transport, which will be termed the “virtual velocity” method. Much research remains to develop methods and determine accuracy of the virtual velocity method in small sand-bed rivers.
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We developed an approach to quantify subdaily flow variation for multiple sites across a large watershed to assess the potential impacts of different dam operations (flood control, run-of-river hydropower and peaking hydropower) on natural communities. We used hourly flow data over a 9-year period from 30 stream gages throughout the Connecticut River basin to calculate four metrics of subdaily flow variation and to compare sites downstream of dams with unregulated sites. Our objectives were to (1) determine the temporal scale of data needed to characterize subdaily variability; (2) compare the frequency of days with high subdaily flow variation downstream of dams and unregulated sites; (3) analyse the magnitude of subdaily variation at all sites and (4) identify individual sites that had subdaily variation significantly higher than unregulated locations. We found that estimates of flow variability based on daily mean flow data were not sufficient to characterize subdaily flow patterns. Alteration of subdaily flows was evident in the number of days natural ranges of variability were exceeded, rather than in the magnitude of subdaily variation, suggesting that all rivers may exhibit highly variable subdaily flows, but altered rivers exhibit this variability more frequently. Peaking hydropower facilities had the most highly altered subdaily flows; however, we observed significantly altered ranges of subdaily variability downstream of some flood-control and run-of-river hydropower dams. 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If this applies also to earthquake fault zones, then the analysis of rupture processes is simplified inasmuch as the slip rates depend only on the local yield stress and are independent of factors specific to a particular event, including the distribution of slip in space and time. We test this hypothesis by first using it to develop an expression for radiated energy that depends primarily on the seismic moment and the maximum slip rate. From laboratory results, the maximum slip rate for any crustal earthquake, as well as various stress parameters including the yield stress, can be determined based on its seismic moment and the maximum slip within its rupture zone. After finding that our new equation for radiated energy works well for laboratory stick-slip friction experiments, we used it to estimate radiated energies for five earthquakes with magnitudes near 2 that were induced in a deep gold mine, an M 2.1 repeating earthquake near the San Andreas Fault Observatory at Depth (SAFOD) site and seven major earthquakes in California and found good agreement with energies estimated independently from spectra of local and regional ground-motion data. Estimates of yield stress for the earthquakes in our study range from 12 MPa to 122 MPa with a median of 64 MPa. The lowest value was estimated for the 2004 M 6 Parkfield, California, earthquake whereas the nearby M 2.1 repeating earthquake, as recorded in the SAFOD pilot hole, showed a more typical yield stress of 64 MPa.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1785/0120100043","issn":"00371106","usgsCitation":"McGarr, A., Fletcher, J.B., Boettcher, M., Beeler, N., and Boatwright, J., 2010, Laboratory-based maximum slip rates in earthquake rupture zones and radiated energy: Bulletin of the Seismological Society of America, v. 100, no. 6, p. 3250-3260, https://doi.org/10.1785/0120100043.","startPage":"3250","endPage":"3260","numberOfPages":"11","costCenters":[],"links":[{"id":246108,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218124,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120100043"}],"volume":"100","issue":"6","noUsgsAuthors":false,"publicationDate":"2010-12-06","publicationStatus":"PW","scienceBaseUri":"505a4123e4b0c8380cd65319","contributors":{"authors":[{"text":"McGarr, Art 0000-0001-9769-4093","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":43491,"corporation":false,"usgs":true,"family":"McGarr","given":"Art","affiliations":[],"preferred":false,"id":461561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fletcher, Joe B.","contributorId":8850,"corporation":false,"usgs":true,"family":"Fletcher","given":"Joe","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":461559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boettcher, M.","contributorId":28828,"corporation":false,"usgs":true,"family":"Boettcher","given":"M.","email":"","affiliations":[],"preferred":false,"id":461560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beeler, N.","contributorId":69753,"corporation":false,"usgs":true,"family":"Beeler","given":"N.","email":"","affiliations":[],"preferred":false,"id":461562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boatwright, J.","contributorId":87297,"corporation":false,"usgs":true,"family":"Boatwright","given":"J.","email":"","affiliations":[],"preferred":false,"id":461563,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227364,"text":"70227364 - 2010 - Identification of plant species by using high spatial and spectral resolution thermal infrared (8.0–13.5 μm) imagery","interactions":[],"lastModifiedDate":"2022-01-11T14:30:07.62028","indexId":"70227364","displayToPublicDate":"2009-10-29T08:25:56","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9944,"text":"Remote Sensing of the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Identification of plant species by using high spatial and spectral resolution thermal infrared (8.0–13.5 μm) imagery","docAbstract":"High spatial and spectral resolution thermal infrared imagery (8.0–13.5 μm) from the SEBASS airborne sensor was used to analyze and map tree canopy spectral features at the State Arboretum of Virginia, near Boyce, Virginia. Fifty tree species were analyzed and about half were directly identified with varying degrees of success on the basis of spectral matched filtering that utilized laboratory-measured leaf spectra as the target signatures. Spectral averages of pixels extracted from SEBASS emissivity data compared favorably with laboratory spectra of leaves collected from individual tree species. Best results were obtained from species having relatively strong spectral contrast, wide and flat leaves, closed planophile canopies, and/or large canopy areas. Tree species having small leaves or unfavorable leaf orientations showed spectral attenuation likely resulting from cavity blackbody effects. Increased spatial resolution and better image calibration and atmospheric correction might lead to further improvements in thermal infrared plant species identification.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2009.09.019","usgsCitation":"Ribeiro da Luz, B., and Crowley, J.K., 2010, Identification of plant species by using high spatial and spectral resolution thermal infrared (8.0–13.5 μm) imagery: Remote Sensing of the Environment, v. 114, no. 2, p. 404-413, https://doi.org/10.1016/j.rse.2009.09.019.","productDescription":"10 p.","startPage":"404","endPage":"413","costCenters":[],"links":[{"id":394180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"114","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ribeiro da Luz, Beatriz bribeirodaluz@usgs.gov","contributorId":3260,"corporation":false,"usgs":true,"family":"Ribeiro da Luz","given":"Beatriz","email":"bribeirodaluz@usgs.gov","affiliations":[],"preferred":true,"id":830600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crowley, James K.","contributorId":10928,"corporation":false,"usgs":true,"family":"Crowley","given":"James","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":830601,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208549,"text":"70208549 - 2010 - Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States","interactions":[],"lastModifiedDate":"2020-02-20T10:07:26","indexId":"70208549","displayToPublicDate":"2009-09-19T13:25:32","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States","docAbstract":"Since January 2008, the U.S. Department of Interior / U.S. Geological Survey have been providing free terrain-corrected (Level 1T) Landsat Enhanced Thematic Mapper Plus (ETM+) data via the Internet, currently for acquisitions with less than 40% cloud cover. With this rich dataset, temporally composited, mosaics of the conterminous United States (CONUS) were generated on a monthly, seasonal, and annual basis using 6521 ETM+ acquisitions from December 2007 to November 2008. The composited mosaics are designed to provide consistent Landsat data that can be used to derive land cover and geo-physical and bio-physical products for detailed regional assessments of land-cover dynamics and to study Earth system functioning. The data layers in the composited mosaics are defined at 30 m and include top of atmosphere (TOA) reflectance, TOA brightness temperature, TOA normalized difference vegetation index (NDVI), the date each composited pixel was acquired on, per-band radiometric saturation status, cloud mask values, and the number of acquisitions considered in the compositing period. Reduced spatial resolution browse imagery, and top of atmosphere 30 m reflectance time series extracted from the monthly composites, capture the expected land surface phenological change, and illustrate the potential of the composited mosaic data for terrestrial monitoring at high spatial resolution. The composited mosaics are available in 501 tiles of 5000 × 5000 30 m pixels in the Albers equal area projection and are downloadable at http://landsat.usgs.gov/WELD.php. The research described in this paper demonstrates the potential of Landsat data processing to provide a consistent, long-term, large-area, data record.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2009.08.011","usgsCitation":"Roy, D.P., Ju, J., Kline, K.L., Scaramuzza, P.L., Kovalskyy, V., Hansen, M., Loveland, T., Vermote, E., and Zhang, C., 2010, Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States: Remote Sensing of Environment, v. 114, no. 1, p. 35-49, https://doi.org/10.1016/j.rse.2009.08.011.","productDescription":"15 p.","startPage":"35","endPage":"49","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":502478,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":372351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": 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Streamflow was measured or estimated by the USGS following standard methods at 23 streamflow-gaging stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2002 (October 1, 2001 to September 30, 2002). Water-quality samples were also collected at 35 of 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2002 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2002.\r\n\r\nThe largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 12.6 cubic feet per second (ft3/s) to the reservoir during WY 2002. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.14 to 8.1 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 534,000 kilograms (kg) of sodium and 851,000 kg of chloride to the Scituate Reservoir during WY 2002; sodium and chloride yields for the tributaries ranged from 2,900 to 40,200 kilograms per square mile (kg/mi2) and from 4,200 to 68,200 kg/mi2, respectively.\r\n\r\nAt the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 16.8 milligrams per liter (mg/L), median nitrate concentration was 0.02 mg/L as N, median nitrite concentration was 0.002 mg/L as N, median orthophosphate concentration was 0.03 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 22 and 14 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrate, nitrite, orthophosphate and total coliform and E. coli bacteria were 21 kg/d (12 kg/d/mi2), 0.04 kg/d (0.014 kg/d/mi2), 0.005 kg/d (0.002 kg/d/mi2), 0.08 kg/d (0.035 kg/d/mi2), and 370 million colony forming units per day (CFUx106/d) (120 CFUx106/d/ mi2) and 300 CFUx106/d (75 CFUx106/d/mi2), respectively.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091041","isbn":"9781411325173","collaboration":"Prepared in cooperation with the Providence Water Supply Board and the Rhode Island Department of Environmental Management","usgsCitation":"Breault, R., 2010, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2002: U.S. Geological Survey Open-File Report 2009-1041, v, 26 p., https://doi.org/10.3133/ofr20091041.","productDescription":"v, 26 p.","temporalStart":"2001-10-01","temporalEnd":"2002-09-30","costCenters":[{"id":544,"text":"Rhode Island Water Science Center","active":false,"usgs":true}],"links":[{"id":126289,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1041.jpg"},{"id":12980,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1041/","linkFileType":{"id":5,"text":"html"}},{"id":388260,"rank":2,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_87194.htm"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir drainage area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.83333333333333,41.7 ], [ -71.83333333333333,41.916666666666664 ], [ -71.53333333333333,41.916666666666664 ], [ -71.53333333333333,41.7 ], [ -71.83333333333333,41.7 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b15e4b07f02db6a4d7e","contributors":{"authors":[{"text":"Breault, Robert F. 0000-0002-2517-407X rbreault@usgs.gov","orcid":"https://orcid.org/0000-0002-2517-407X","contributorId":2219,"corporation":false,"usgs":true,"family":"Breault","given":"Robert F.","email":"rbreault@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":303224,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70230292,"text":"70230292 - 2010 - Mercury sources to Lake Ozette and Lake Dickey: Highly contaminated remote coastal lakes, Washington State, USA","interactions":[],"lastModifiedDate":"2022-04-06T15:25:58.70318","indexId":"70230292","displayToPublicDate":"2009-08-18T10:17:57","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Mercury sources to Lake Ozette and Lake Dickey: Highly contaminated remote coastal lakes, Washington State, USA","docAbstract":"Mercury concentrations in largemouth bass and mercury accumulation rates in age-dated sediment cores were examined at Lake Ozette and Lake Dickey in Washington State. Goals of the study were to compare concentrations in fish tissues at the two lakes with a larger statewide dataset and examine mercury pathways to the lakes. After accounting for fish length, tissue concentrations at the lakes were significantly higher than other Washington State lakes. Wet deposition and historical atmospheric monitoring from the area show no indication of enhanced local or regional deposition. Sediment core records from the lakes indicate rising sedimentation rates coinciding with logging in the lakes’ drainages has greatly increased the net flux of mercury to the waterbodies.
","language":"English","publisher":"Springer Link","doi":"10.1007/s11270-009-0165-y","usgsCitation":"Van Furl, C., Colman, J.A., and Bothner, M., 2010, Mercury sources to Lake Ozette and Lake Dickey: Highly contaminated remote coastal lakes, Washington State, USA: Water, Air, & Soil Pollution, v. 208, p. 275-286, https://doi.org/10.1007/s11270-009-0165-y.","productDescription":"12 p.","startPage":"275","endPage":"286","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":475956,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/3848","text":"External Repository"},{"id":398224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Dickey, Lake Ozette","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.51698303222658,\n 48.09619676148215\n ],\n [\n -124.49501037597655,\n 48.09619676148215\n ],\n [\n -124.49501037597655,\n 48.12553866602599\n ],\n [\n -124.51698303222658,\n 48.12553866602599\n ],\n [\n -124.51698303222658,\n 48.09619676148215\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.67868804931639,\n 48.032871264684964\n ],\n [\n -124.58667755126955,\n 48.032871264684964\n ],\n [\n -124.58667755126955,\n 48.15486381795689\n ],\n [\n -124.67868804931639,\n 48.15486381795689\n ],\n [\n -124.67868804931639,\n 48.032871264684964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"208","noUsgsAuthors":false,"publicationDate":"2009-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Furl, Chad","contributorId":289846,"corporation":false,"usgs":false,"family":"Van Furl","given":"Chad","email":"","affiliations":[],"preferred":false,"id":839889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colman, John A. 0000-0001-9327-0779 jacolman@usgs.gov","orcid":"https://orcid.org/0000-0001-9327-0779","contributorId":2098,"corporation":false,"usgs":true,"family":"Colman","given":"John","email":"jacolman@usgs.gov","middleInitial":"A.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":839890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bothner, Michael H. mbothner@usgs.gov","contributorId":139855,"corporation":false,"usgs":true,"family":"Bothner","given":"Michael H.","email":"mbothner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":839891,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}