Deep-sea coral and sponge ecosystems are widespread throughout most of Alaska’s marine waters. In some places, such as the central and western Aleutian Islands, deep-sea coral and sponge resources can be extremely diverse and may rank among the most abundant deep-sea coral and sponge communities in the world. Many different species of fishes and invertebrates are associated with deep-sea coral and sponge communities in Alaska. Because of their biology, these benthic invertebrates are potentially impacted by climate change and ocean acidification. Deepsea coral and sponge ecosystems are also vulnerable to the effects of commercial fishing activities. Because of the size and scope of Alaska’s continental shelf and slope, the vast majority of the area has not been visually surveyed for deep-sea corals and sponges. NOAA’s Deep Sea Coral Research and Technology Program (DSCRTP) sponsored a field research program in the Alaska region between 2012–2015, referred to hereafter as the Alaska Initiative. The priorities for Alaska were derived from ongoing data needs and objectives identified by the DSCRTP, the North Pacific Fishery Management Council (NPFMC), and Essential Fish Habitat-Environmental Impact Statement (EFH-EIS) process.
This report presents the results of 15 projects conducted using DSCRTP funds from 2012-2015. Three of the projects conducted as part of the Alaska deep-sea coral and sponge initiative included dedicated at-sea cruises and fieldwork spread across multiple years. These projects were the eastern Gulf of Alaska Primnoa pacifica study, the Aleutian Islands mapping study, and the Gulf of Alaska fish productivity study. In all, there were nine separate research cruises carried out with a total of 109 at-sea days conducting research. The remaining projects either used data and samples collected by the three major fieldwork projects or were piggy-backed onto existing research programs at the Alaska Fisheries Science Center (AFSC).
","language":"English","publisher":"National Oceanic and Atmospheric Administration","usgsCitation":"Rooper, C., Stone, R.P., Etnoyer, P., Conrath, C., Reynolds, J., Greene, H.G., Williams, B., Salgado, E., Morrison, C.L., Waller, R.G., and Demopoulos, A.W., 2017, Deep-sea coral research and technology program: Alaska deep-sea coral and sponge initiative final report: NOAA Technical Memorandum NMFS-OHC-2, x, 65 p.","productDescription":"x, 65 p.","numberOfPages":"80","ipdsId":"IP-090361","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":345710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":345701,"type":{"id":11,"text":"Document"},"url":"https://spo.nmfs.noaa.gov/sites/default/files/TM-OHC-2-FINAL.pdf"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ba43b6e4b091459a56299f","contributors":{"authors":[{"text":"Rooper, Chris","contributorId":196431,"corporation":false,"usgs":false,"family":"Rooper","given":"Chris","affiliations":[],"preferred":false,"id":710321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Robert P.","contributorId":190569,"corporation":false,"usgs":false,"family":"Stone","given":"Robert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":710322,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Etnoyer, Peter","contributorId":196432,"corporation":false,"usgs":false,"family":"Etnoyer","given":"Peter","affiliations":[],"preferred":false,"id":710323,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrath, Christina","contributorId":196433,"corporation":false,"usgs":false,"family":"Conrath","given":"Christina","email":"","affiliations":[],"preferred":false,"id":710324,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reynolds, Jennifer","contributorId":196434,"corporation":false,"usgs":false,"family":"Reynolds","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":710325,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greene, H. Gary","contributorId":139063,"corporation":false,"usgs":false,"family":"Greene","given":"H.","email":"","middleInitial":"Gary","affiliations":[{"id":12639,"text":"Moss Landing Marine Labs","active":true,"usgs":false}],"preferred":false,"id":710326,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williams, Branwen","contributorId":152572,"corporation":false,"usgs":false,"family":"Williams","given":"Branwen","email":"","affiliations":[],"preferred":false,"id":710327,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Salgado, Enrique","contributorId":196435,"corporation":false,"usgs":false,"family":"Salgado","given":"Enrique","email":"","affiliations":[],"preferred":false,"id":710328,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Morrison, Cheryl L. 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":146488,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":710320,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Waller, Rhian G.","contributorId":195852,"corporation":false,"usgs":false,"family":"Waller","given":"Rhian","email":"","middleInitial":"G.","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":710329,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":196216,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":710330,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70188026,"text":"sir20175047 - 2017 - Loads and yields of deicing compounds and total phosphorus in the Cambridge drinking-water source area, Massachusetts, water years 2009–15","interactions":[],"lastModifiedDate":"2022-11-02T14:10:12.709223","indexId":"sir20175047","displayToPublicDate":"2017-09-12T12:00:00","publicationYear":"2017","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":"2017-5047","title":"Loads and yields of deicing compounds and total phosphorus in the Cambridge drinking-water source area, Massachusetts, water years 2009–15","docAbstract":"The source water area for the drinking-water supply of the city of Cambridge, Massachusetts, encompasses major transportation corridors, as well as large areas of light industrial, commercial, and residential land use. Because of the large amount of roadway in the drinking-water source area, the Cambridge water supply is affected by the usage of deicing compounds and by other constituents that are flushed from such impervious areas. The U.S. Geological Survey (USGS) has monitored surface-water quality in the Cambridge Reservoir and Stony Brook Reservoir Basins, which compose the drinking-water source area, since 1997 (water year 1998) through continuous monitoring and the collection of stream-flow samples.
In a study conducted by the USGS, in cooperation with the City of Cambridge Water Department, concentrations and loads of calcium (Ca), chloride (Cl), magnesium (Mg), sodium (Na), and sulfate (SO4) were estimated from continuous records of specific conductance and streamflow for streams and tributaries at 10 continuous water-quality monitoring stations. These data were used to characterize current (2015) water-quality conditions, estimate loads and yields, and describe trends in Cl and Na in the tributaries and main-stem streams in the Cambridge Reservoir and Stony Brook Reservoir Basins. These data also were used to describe how stream-water quality is related to various basin characteristics and provide information to guide future management of the drinking-water source area.
Water samples from 2009–15 were analyzed for physical properties and concentrations of Ca, Cl, Mg, Na, potassium (K), SO4, and total phosphorus (TP). Values of physical properties and constituent concentrations varied widely, particularly in composite samples of stormflow from tributaries that have high percentages of constructed impervious areas. Median concentrations of Ca, Cl, Mg, Na, and K in samples collected from the tributaries in the Cambridge Reservoir Basin (27.2, 273, 4.7, 154.5, and 2.8 milligrams per liter (mg/L), respectively) were higher than those for the Stony Brook Reservoir Basin (22.2, 128, 4.3, 77.1, and 2.5, respectively). Differences between tributary samples for concentrations of Cl and Na were related to the percentage of developed land and constructed impervious area in the drinking-water source area. Median concentrations of SO4 in samples collected from the tributaries in the Cambridge Reservoir Basin (10.7 mg/L) were lower than those for the Stony Brook Reservoir Basin (18.0 mg/L).
Concentrations of dissolved Cl and Na in samples and those concentrations estimated from continuous records of specific conductance (particularly during base flow) often were greater than the U.S. Environmental Protection Agency (EPA) secondary drinking-water standard for Cl (250 mg/L), the chronic aquatic-life guideline for Cl (230 mg/L), and the Massachusetts Department of Environmental Protection drinking-water guideline for Na (20 mg/L). Concentrations of TP (range from 0.008 to 0.69 mg/L in all subbasins) in tributary samples did not differ substantially between the Cambridge Reservoir and Stony Brook Reservoir Basins. About one-half of the concentrations of TP in samples collected during water years 2013–15 exceeded the EPA proposed reference concentration of 0.024 mg/L.
For most tributaries, about 70 percent of the annual loads of Ca, Cl, Mg, Na, and SO4 were associated with base flow. Concentrations of major ions were negatively correlated with streamflow, indicating that these constituents were diluted during stormflow and tend to increase during the summer when streamflow is low. In contrast, between 57 and 92 percent of the annual load for TP was transported during stormflows.
Mean annual yields of Ca, Cl, Mg, Na, and SO4 in the drinking-water source area were 13, 75, 2.6, 40, and 6.9 metric tons per square kilometer, respectively, for water years 2009–15. The mean annual yield of TP in the drinking-water source area for water years 2013–15 was 0.012 metric tons per square kilometer. Yields for major ions and TP were highest in tributary subbasins adjacent to Interstate 95.
Temporal trends in mean annual concentrations for Cl and Na were not significant for water years 1998‒2015 (period of record by the USGS) for the outlet of the Cambridge Reservoir and for the main stem of Stony Brook downstream from the reservoir. Median values of base-flow concentrations of TP at three stations were higher for samples collected during base-flow conditions during water years 2005–7 than for samples collected during water years 2013–15. However, the results were not significant for statistical tests between concentrations in samples collected during storms for the same periods, indicating that the quality of stormwater remains similar.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175047","collaboration":"Prepared in cooperation with Cambridge [Massachusetts] Water Department","productDescription":"x, 52 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-078822","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":345074,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5047/sir20175047.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5047"},{"id":345073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5047/coverthb.jpg"}],"country":"United States","state":"Massachusetts","city":"Cambridge","otherGeospatial":"Cambridge Reservoir and Stony Brook Reservoir basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.3167,\n 42.433\n ],\n [\n -71.3167,\n 42.333\n ],\n [\n -71.133,\n 42.333\n ],\n [\n -71.133,\n 42.433\n ],\n [\n -71.3167,\n 42.433\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
In 2016, the U.S. Fish and Wildlife Service, U.S. Geological Survey, and U.S. Army Corps of Engineers undertook a field study in the Chicago Sanitary and Ship Canal near Romeoville, Illinois to determine the influence of tow transit on the efficacy of the Electric Dispersal Barrier System (EDBS) in preventing the passage of juvenile fish (total length < 100 millimeters (mm)). Dual-frequency identification sonar data showed that large schools of juvenile fish (mean school size of 120 fish; n = 19) moved upstream and crossed the electric field of an array in the EDBS concurrent with downstream-bound (downbound) loaded tows in 89.5% of trials. Smaller schools of juvenile fish (mean school size of 98 fish; n = 15) moved downstream and crossed the electric field of an array in the EDBS concurrent with upstream-bound (upbound) loaded tows in 73.3% of trials. Observed fish passages through the EDBS were always opposite to the direction of tow movement, and not associated with propeller wash. These schools were not observed to breach the EDBS in the absence of a tow and showed no signs of incapacitation in the barrier during tow passage. Loaded tows transiting the EDBS create a return current of water flowing between the tow and the canal wall that typically travels opposite the direction of tow movement, and cause a decrease in the voltage gradient of the barrier of up to 88%. Return currents and decreases in voltage gradients induced by tow passage likely contributed to the observed fish passage through the EDBS. The efficacy of the EDBS in preventing the passage of small, wild fish is compromised while tows are moving across the barrier system. In particular, downbound tows moving through the EDBS create a pathway for the upstream movement of small fish, and therefore may increase the risk of transfer of invasive fishes from the Mississippi River Basin to the Great Lakes Basin.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2017.08.013","usgsCitation":"Davis, J.J., LeRoy, J., Shanks, M.R., Jackson, P.R., Engel, F.L., Murphy, E.A., Baxter, C.L., McInerney, M.K., and Barkowski, N.A., 2017, Effects of tow transit on the efficacy of the Chicago Sanitary and Ship Canal Electric Dispersal Barrier System: Journal of Great Lakes Research, v. 43, no. 6, p. 1119-1131, https://doi.org/10.1016/j.jglr.2017.08.013.","productDescription":"13 p.","startPage":"1119","endPage":"1131","ipdsId":"IP-086419","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":469530,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2017.08.013","text":"Publisher Index Page"},{"id":345662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","city":"Romeoville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.06166410446166,\n 41.64078396644512\n ],\n [\n -88.05765151977539,\n 41.64078396644512\n ],\n [\n -88.05765151977539,\n 41.648192108560146\n ],\n [\n -88.06166410446166,\n 41.648192108560146\n ],\n [\n -88.06166410446166,\n 41.64078396644512\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59b8f219e4b08b1644e0aeaf","contributors":{"authors":[{"text":"Davis, Jeremiah J.","contributorId":150963,"corporation":false,"usgs":false,"family":"Davis","given":"Jeremiah","email":"","middleInitial":"J.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":710181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LeRoy, Jessica Z. jleroy@usgs.gov","contributorId":174538,"corporation":false,"usgs":true,"family":"LeRoy","given":"Jessica Z.","email":"jleroy@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":710178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanks, Matthew R.","contributorId":196367,"corporation":false,"usgs":false,"family":"Shanks","given":"Matthew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":710182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Patrick Ryan","contributorId":34043,"corporation":false,"usgs":true,"family":"Jackson","given":"Patrick","email":"","middleInitial":"Ryan","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":710179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Engel, Frank L. 0000-0002-4253-2625 fengel@usgs.gov","orcid":"https://orcid.org/0000-0002-4253-2625","contributorId":5463,"corporation":false,"usgs":true,"family":"Engel","given":"Frank","email":"fengel@usgs.gov","middleInitial":"L.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710180,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Elizabeth A. 0000-0002-8939-7678 emurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-8939-7678","contributorId":196368,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth","email":"emurphy@usgs.gov","middleInitial":"A.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710183,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Baxter, Carey L.","contributorId":196369,"corporation":false,"usgs":false,"family":"Baxter","given":"Carey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":710184,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McInerney, Michael K.","contributorId":196370,"corporation":false,"usgs":false,"family":"McInerney","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":710185,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barkowski, Nicholas A.","contributorId":196371,"corporation":false,"usgs":false,"family":"Barkowski","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":710186,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70190634,"text":"70190634 - 2017 - Behavior of a wave-driven buoyant surface jet on a coral reef","interactions":[],"lastModifiedDate":"2017-09-12T09:41:31","indexId":"70190634","displayToPublicDate":"2017-09-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Behavior of a wave-driven buoyant surface jet on a coral reef","docAbstract":"A wave-driven surface buoyant jet exiting a coral reef was studied in order to quantify the amount of water re-entrained over the reef crest. Both moored observations and Lagrangian drifters were used to study the fate of the buoyant jet. To investigate in detail the effects of buoyancy and along-shore flow variations, we developed an idealized numerical model of the system. Consistent with previous work, the ratio of along-shore velocity to jet-velocity and the jet internal Froude number were found to be important determinants of the fate of the jet. In the absence of buoyancy, the entrainment of fluid at the reef crest, creates a significant amount of retention, keeping 60% of water in the reef system. However, when the jet is lighter than the ambient ocean-water, the net effect of buoyancy is to enhance the separation of the jet from shore, leading to a greater export of reef water. Matching observations, our modeling predicts that buoyancy limits retention to 30% of the jet flow for conditions existing on the Moorea reef. Overall, the combination of observations and modeling we present here shows that reef-ocean temperature gradients can play an important role in reef-ocean exchanges.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016JC011729","usgsCitation":"Herdman, L.M., Hench, J.L., Fringer, O., and Monismith, S.G., 2017, Behavior of a wave-driven buoyant surface jet on a coral reef: Journal of Geophysical Research C: Oceans, v. 122, no. 5, p. 4088-4109, https://doi.org/10.1002/2016JC011729.","productDescription":"22 p.","startPage":"4088","endPage":"4109","ipdsId":"IP-079726","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":345632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Moorea Reef","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -151.0400390625,\n -18.17716879354469\n ],\n [\n -148.5791015625,\n -18.17716879354469\n ],\n [\n -148.5791015625,\n -16.983248530690656\n ],\n [\n -151.0400390625,\n -16.983248530690656\n ],\n [\n -151.0400390625,\n -18.17716879354469\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-16","publicationStatus":"PW","scienceBaseUri":"59b8f21ce4b08b1644e0aecd","contributors":{"authors":[{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710053,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hench, James L.","contributorId":196320,"corporation":false,"usgs":false,"family":"Hench","given":"James","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":710054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fringer, Oliver","contributorId":196321,"corporation":false,"usgs":false,"family":"Fringer","given":"Oliver","affiliations":[],"preferred":false,"id":710055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monismith, Stephen G.","contributorId":196322,"corporation":false,"usgs":false,"family":"Monismith","given":"Stephen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":710056,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190696,"text":"70190696 - 2017 - Temporal variation in survival and recovery rates of lesser scaup: A response","interactions":[],"lastModifiedDate":"2017-11-27T13:04:14","indexId":"70190696","displayToPublicDate":"2017-09-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Temporal variation in survival and recovery rates of lesser scaup: A response","docAbstract":"We recently analyzed long-term (1951–2011) continental band-recovery data from lesser scaup (Aythya affinis) and demonstrated that harvest rates declined through time, but annual survival rates exhibited no such trends; moreover, annual harvest and survival rates were uncorrelated for all age-sex classes. We therefore concluded that declining fecundity was most likely responsible for recent population declines, rather than changes in harvest or survival. Lindberg et al. (2017) critiqued our conclusions, arguing that we did little more than fail to reject a null hypothesis of compensatory mortality, postulated ecologically unrealistic changes in fecundity, and failed to give sufficient consideration to additive harvest mortality. Herein, we re-summarize our original evidence indicating that harvest has been compensatory, or at most weakly additive, and demonstrate that our analysis had sufficient power to detect strongly additive mortality if it occurred. We further demonstrate that our conclusions were not confounded by population size, band loss, or individual heterogeneity, as suggested by Lindberg et al. (2017), and we provide additional support for our conjecture that low fecundity played a major role in declining scaup populations during 1983–2006. We therefore reiterate our original management recommendations: given low harvest rates and lack of demonstrable effect on scaup survival, harvest regulations could return to more liberal frameworks, and waterfowl biologists should work together to continue banding lesser scaup and use these data to explore alternative hypotheses to identify the true ecological causes of population change, given that it is unlikely to be excessive harvest.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21315","usgsCitation":"Arnold, T.W., Afton, A.D., Anteau, M.J., Koons, D.N., and Nicolai, C.A., 2017, Temporal variation in survival and recovery rates of lesser scaup: A response: Journal of Wildlife Management, v. 81, no. 7, p. 1142-1148, https://doi.org/10.1002/jwmg.21315.","productDescription":"7 p.","startPage":"1142","endPage":"1148","ipdsId":"IP-086063","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":345670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","issue":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-28","publicationStatus":"PW","scienceBaseUri":"59b8f218e4b08b1644e0aeac","contributors":{"authors":[{"text":"Arnold, Todd W.","contributorId":36058,"corporation":false,"usgs":false,"family":"Arnold","given":"Todd","email":"","middleInitial":"W.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":710191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Afton, Alan D. 0000-0002-0436-8588 aafton@usgs.gov","orcid":"https://orcid.org/0000-0002-0436-8588","contributorId":139582,"corporation":false,"usgs":false,"family":"Afton","given":"Alan","email":"aafton@usgs.gov","middleInitial":"D.","affiliations":[{"id":368,"text":"Louisiana Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":710192,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":710190,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koons, David N.","contributorId":28137,"corporation":false,"usgs":false,"family":"Koons","given":"David","email":"","middleInitial":"N.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":710193,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nicolai, Chris A.","contributorId":196372,"corporation":false,"usgs":false,"family":"Nicolai","given":"Chris","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":710194,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190665,"text":"70190665 - 2017 - A hydrologic drying bias in water-resource impact analyses of anthropogenic climate change","interactions":[],"lastModifiedDate":"2017-09-12T08:59:58","indexId":"70190665","displayToPublicDate":"2017-09-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"A hydrologic drying bias in water-resource impact analyses of anthropogenic climate change","docAbstract":"For water-resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration (Ep) as inputs. Because Ep is not a climate-model output, an intermediary model of Ep must be introduced to connect the climate model to the hydrologic model. Several Ep methods are used. The suitability of each can be assessed by noting a credible Ep method for offline analyses should be able to reproduce climate models’ ACC-driven changes in actual evapotranspiration in regions and seasons of negligible water stress (Ew). We quantified this ability for seven commonly used Ep methods and for a simple proportionality with available energy (“energy-only” method). With the exception of the energy-only method, all methods tend to overestimate substantially the increase in Ep associated with ACC. In an offline hydrologic model, the Ep-change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC-induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water-resource impact analyses.
","language":"English","publisher":"American Water Resources Asssociation","doi":"10.1111/1752-1688.12538","usgsCitation":"Milly, P., and Dunne, K.A., 2017, A hydrologic drying bias in water-resource impact analyses of anthropogenic climate change: Journal of the American Water Resources Association, v. 53, no. 4, p. 822-838, https://doi.org/10.1111/1752-1688.12538.","productDescription":"17 p.","startPage":"822","endPage":"838","ipdsId":"IP-084657","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":345630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-26","publicationStatus":"PW","scienceBaseUri":"59b8f21be4b08b1644e0aec3","contributors":{"authors":[{"text":"Milly, Paul 0000-0003-4389-3130 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3130","contributorId":196325,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","affiliations":[],"preferred":true,"id":710069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunne, Krista A. kadunne@usgs.gov","contributorId":3936,"corporation":false,"usgs":true,"family":"Dunne","given":"Krista","email":"kadunne@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":710070,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190506,"text":"ofr20171109 - 2017 - Bathymetric survey of the Cayuga Inlet flood-control channel and selected tributaries in Ithaca, New York, 2016","interactions":[],"lastModifiedDate":"2017-09-08T16:46:32","indexId":"ofr20171109","displayToPublicDate":"2017-09-08T17:30:00","publicationYear":"2017","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":"2017-1109","title":"Bathymetric survey of the Cayuga Inlet flood-control channel and selected tributaries in Ithaca, New York, 2016","docAbstract":"From July 14 to July 20, 2016, the U.S. Geological Survey, in cooperation with the City of Ithaca, New York, and the New York State Department of State, surveyed the bathymetry of the Cayuga Inlet flood-control channel and the mouths of selected tributaries to Cayuga Inlet and Cayuga Lake in Ithaca, N.Y. The flood-control channel, built by the U.S. Army Corps of Engineers between 1965 and 1970, was designed to convey flood flows from the Cayuga Inlet watershed through the City of Ithaca and minimize possible flood damages. Since that time, the channel has infrequently been maintained by dredging, and sediment accumulation and resultant shoaling have greatly decreased the conveyance of the channel and its navigational capability.
U.S. Geological Survey personnel collected bathymetric data by using an acoustic Doppler current profiler. The survey produced a dense dataset of water depths that were converted to bottom elevations. These elevations were then used to generate a geographic information system bathymetric surface. The bathymetric data and resultant bathymetric surface show the current condition of the channel and provide the information that governmental agencies charged with maintaining the Cayuga Inlet for flood-control and navigational purposes need to make informed decisions regarding future maintenance measures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171109","collaboration":"Prepared in cooperation with the City of Ithaca, New York, and the New York State Department of State","usgsCitation":"Wernly, J.F., Nystrom, E.A., and Coon, W.F., 2017, Bathymetric survey of the Cayuga Inlet flood-control channel and selected tributaries in Ithaca, New York, 2016: U.S. Geological Survey Open-File Report 2017–1109, 9 p., https://doi.org/10.3133/ofr20171109.","productDescription":"Report: v, 9 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-080379","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":438218,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K935NQ","text":"USGS data release","linkHelpText":"Geospatial dataset of bathymetric survey of the Cayuga Inlet flood-control channel and selected tributaries in Ithaca, New York, 2016"},{"id":345569,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1109/coverthb.jpg"},{"id":345570,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1109/ofr20171109.pdf","text":"Report","size":"1.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1109"},{"id":345572,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7K935NQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial dataset of bathymetric survey of the Cayuga Inlet flood-control channel and selected tributaries, Ithaca, N.Y., 2016"}],"country":"United States","state":"New York","city":"Ithaca","otherGeospatial":"Cayuga Inlet Flood-Control Channel ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.52423858642578,\n 42.42586409208738\n ],\n [\n -76.48801803588867,\n 42.42586409208738\n ],\n [\n -76.48801803588867,\n 42.46437270371863\n ],\n [\n -76.52423858642578,\n 42.46437270371863\n ],\n [\n -76.52423858642578,\n 42.42586409208738\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
30 Brown Road
Ithaca, NY 14850
Terrestrial and aquatic ecosystems provide valuable services to humans and are a source of clean water, energy, raw materials, and productive soils. The Nation’s food supply is more secure because of wildlife. For example, native pollinators enhance agricultural crops, and insect-eating bats provide pest control services worth billions of dollars to farmers annually. Fish and wildlife are also vital to a vibrant outdoor recreation and tourism industry. Recreational activities, such as hunting, shooting, boating, and angling, generated \\$1.1 billion in excise taxes paid to State wildlife agencies in 2017. National parks, wildlife refuges, and monuments accounted for $35 billion in economic output and 318,000 jobs nationwide in 2016. Additional economic benefits are generated from the use and enjoyment of wildlife in State-owned lands and waters.
Although the United States is rich in natural resources, human activity continues to place new pressures on fish and wildlife and the habitats they rely on. The United States became the world’s top producer of petroleum and natural gas products in 2012, surpassing Russia’s natural gas production levels in 2009 and Saudi Arabia’s petroleum production in 2013. The U.S. Energy Information Administration projects that the demand for liquid fuel, natural gas, and renewable energy will show strong growth in the next 20 years. Wind energy has demonstrated consistent growth since 2007 with now more than 53,000 wind turbines contributing to power grids in 41 States, Guam, and Puerto Rico. Solar energy has seen rapid growth since 2013 and made up nearly one-third of the total electricity generation additions in 2016. Yet as our Nation works to advance energy security and sustain wildlife, some conflicts have surfaced. Impacts of an expanding energy infrastructure include fragmentation and loss of habitat as well as mortality of birds, bats, fish, and other animals from interactions with energy generation facilities. Because energy development can often occur in wildlife habitats, ecological science can help guide project siting and operational decisions to areas that present the lowest risk to wildlife and energy developers.
To address these challenges and make the most of new opportunities, the U.S. Geological Survey is producing innovative science to develop workable solutions that can help sustain wildlife and the habitat they rely upon, while allowing informed development.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1435","isbn":"978-1-4113-4169-2","usgsCitation":"Khalil, Mona, ed., 2017, U.S. Geological Survey—Energy and wildlife research annual report for 2017: U.S. Geological Survey Circular 1435, 91 p., https://doi.org/10.3133/cir1435.","productDescription":"iv, 91 p.","numberOfPages":"100","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088712","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":345415,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1435/coverthb2.jpg"},{"id":345416,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1435/circ1435.pdf","text":"Report","size":"23.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIRC 1435"}],"contact":"Energy and Wildlife Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Mail Stop 301
Reston, VA 20192
Federal, State, and local agencies and organizations have expressed concerns regarding the detrimental effects of excessive sediment transport on aquatic resources and endangered species populations in the upper Little Tennessee River and some of its tributaries. In addition, the storage volume of Lake Emory, which is necessary for flood control and power generation, has been depleted by sediment deposition. To help address these concerns, a 2-year study was conducted in the upper Little Tennessee River Basin to characterize the ambient suspended-sediment concentrations and suspended-sediment loads upstream and downstream from Lake Emory in Franklin, North Carolina. The study was conducted by the U.S. Geological Survey in cooperation with Duke Energy. Suspended-sediment samples were collected periodically, and time series of stage and turbidity data were measured from December 2013 to January 2016 upstream and downstream from Lake Emory. The stage data were used to compute time-series streamflow. Suspended-sediment samples, along with time-series streamflow and turbidity data, were used to develop regression models that were used to estimate time-series suspended-sediment concentrations for the 2014 and 2015 calendar years. These concentrations, along with streamflow data, were used to compute suspended-sediment loads. Selected suspended-sediment samples were collected for analysis of particle-size distribution, with emphasis on high-flow events. Bed-load samples were also collected upstream from Lake Emory.
The estimated annual suspended-sediment loads (yields) for the upstream site for the 2014 and 2015 calendar years were 27,000 short tons (92 short tons per square mile) and 63,300 short tons (215 short tons per square mile), respectively. The annual suspended-sediment loads (yields) for the downstream site for 2014 and 2015 were 24,200 short tons (75 short tons per square mile) and 94,300 short tons (292 short tons per square mile), respectively. Overall, the suspended-sediment load at the downstream site was about 28,300 short tons greater than the upstream site over the study period.
As expected, high-flow events (the top 5 percent of daily mean flows) accounted for the majority of the sediment load; 80 percent at the upstream site and 90 percent at the downstream site. A similar relation between turbidity (the top 5 percent of daily mean turbidity) and high loads was also noted. In general, when instantaneous streamflows at the upstream site exceeded 5,000 cubic feet per second, increased daily loads were computed at the downstream site. During low to moderate flows, estimated suspended-sediment loads were lower at the downstream site when compared to the upstream site, which suggests that sediment deposition may be occurring in the intervening reach during those conditions. During the high-flow events, the estimated suspended-sediment loads were higher at the downstream site; however, it is impossible to say with certainty whether the increase in loading was due to scouring of lake sediment, contributions from the additional source area, model error, or a combination of one or more of these factors. The computed loads for a one-week period (December 24–31, 2015), during which the two largest high-flow events of the study period occurred, were approximately 52 percent of the 2015 annual sediment load (36 percent of 2-year load) at the upstream site and approximately 72 percent of the 2015 annual sediment load (57 percent of 2-year load) at the downstream site. Six bedload samples were collected during three events; two high-flow events and one base-flow event. The contribution of bedload to the total sediment load was determined to be insignificant for sampled flows. In general, streamflows for long-term streamgages in the study area were below normal for the majority of the study period; however, flows during the last 3 months of the study period were above normal, including the extreme events during the last week of the study period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175081","collaboration":"Prepared in cooperation with Duke Energy","usgsCitation":"Huffman, B.A., Hazell, W.F., and Oblinger, C.J., 2017, Characterization of sediment transport upstream and downstream from Lake Emory on the Little Tennessee River near Franklin, North Carolina, 2014–15: U.S. Geological Survey Scientific Investigations Report 2017–5081, 30 p., https://doi.org/10.3133/sir20175081.","productDescription":"vii, 30 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081883","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":345379,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5081/sir20175081.pdf","text":"Report","size":"5.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5081"},{"id":345378,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5081/coverthb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Lake Emory; 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U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
We investigated how visitor-use affects water quality in wilderness in Yosemite National Park. During the summers of 2012–2014, we collected and analyzed surface-water samples for water-quality indicators, including fecal indicator bacteria Escherichia coli, nutrients (nitrogen, phosphorus, carbon), suspended sediment concentration, pharmaceuticals, and hormones. Samples were collected upstream and downstream from different types of visitor use at weekly to biweekly intervals and during summer storms. We conducted a park-wide synoptic sampling campaign during summer 2014, and sampled upstream and downstream from meadows to evaluate the mitigating effect of meadows on water quality. At pack stock stream crossings, Escherichia coli concentrations were greater downstream from crossings than upstream (median downstream increase in Escherichia coli of three colony forming units 100 mL−1), with the greatest increases occurring during storms (median downstream increase in Escherichia coli of 32 CFU 100 mL−1). At backpacker use sites, hormones, and pharmaceuticals (e.g., insect repellent) were detected at downstream sites, and Escherichia coli concentrations were greater at downstream sites (median downstream increase in Escherichia coli of 1 CFU 100 mL−1). Differences in water quality downstream vs. upstream from meadows grazed by pack stock were not detectable for most water-quality indicators, however, Escherichia coli concentrations decreased downstream, suggesting entrapment and die-off of fecal indicator bacteria in meadows. Our results indicate that under current-use levels pack stock trail use and backpacker use are associated with detectable, but relatively minor, effects on water quality, which are most pronounced during storms.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-017-0899-z","usgsCitation":"Forrester, H., Clow, D.W., Roche, J.W., Heyvaert, A., and Battaglin, W.A., 2017, Effects of backpacker use, pack stock trail use, and pack stock grazing on water-quality indicators, including nutrients, E. coli, hormones, and pharmaceuticals, in Yosemite National Park, USA: Environmental Management, v. 60, no. 3, p. 526-543, https://doi.org/10.1007/s00267-017-0899-z.","productDescription":"18 p.","startPage":"526","endPage":"543","ipdsId":"IP-087033","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":345522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.44335937499999,\n 37.738141282210385\n ],\n [\n -119.25041198730469,\n 37.738141282210385\n ],\n [\n -119.25041198730469,\n 37.93282521519654\n ],\n [\n -119.44335937499999,\n 37.93282521519654\n ],\n [\n -119.44335937499999,\n 37.738141282210385\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"60","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-08","publicationStatus":"PW","scienceBaseUri":"59b1092ee4b020cdf7d8d9b7","contributors":{"authors":[{"text":"Forrester, Harrison","contributorId":21084,"corporation":false,"usgs":true,"family":"Forrester","given":"Harrison","affiliations":[],"preferred":false,"id":709672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roche, James W.","contributorId":178800,"corporation":false,"usgs":false,"family":"Roche","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":709674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heyvaert, Alan","contributorId":145509,"corporation":false,"usgs":false,"family":"Heyvaert","given":"Alan","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":709675,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Battaglin, William A. 0000-0001-7287-7096 wbattagl@usgs.gov","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":1527,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","email":"wbattagl@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709673,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189477,"text":"sir20175049 - 2017 - A field study of selected U.S. Geological Survey analytical methods for measuring pesticides in filtered stream water, June - September 2012","interactions":[],"lastModifiedDate":"2021-05-27T13:41:53.681826","indexId":"sir20175049","displayToPublicDate":"2017-09-06T00:00:00","publicationYear":"2017","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":"2017-5049","title":"A field study of selected U.S. Geological Survey analytical methods for measuring pesticides in filtered stream water, June - September 2012","docAbstract":"U.S. Geological Survey monitoring programs extensively used two analytical methods, gas chromatography/mass spectrometry and liquid chromatography/mass spectrometry, to measure pesticides in filtered water samples during 1992–2012. In October 2012, the monitoring programs began using direct aqueous-injection liquid chromatography tandem mass spectrometry as a new analytical method for pesticides. The change in analytical methods, however, has the potential to inadvertently introduce bias in analysis of datasets that span the change.
A field study was designed to document performance of the new method in a variety of stream-water matrices and to quantify any potential changes in measurement bias or variability that could be attributed to changes in analytical methods. The goals of the field study were to (1) summarize performance (bias and variability of pesticide recovery) of the new method in a variety of stream-water matrices; (2) compare performance of the new method in laboratory blank water (laboratory reagent spikes) to that in a variety of stream-water matrices; (3) compare performance (analytical recovery) of the new method to that of the old methods in a variety of stream-water matrices; (4) compare pesticide detections and concentrations measured by the new method to those of the old methods in a variety of stream-water matrices; (5) compare contamination measured by field blank water samples in old and new methods; (6) summarize the variability of pesticide detections and concentrations measured by the new method in field duplicate water samples; and (7) identify matrix characteristics of environmental water samples that adversely influence the performance of the new method. Stream-water samples and a variety of field quality-control samples were collected at 48 sites in the U.S. Geological Survey monitoring networks during June–September 2012. Stream sites were located across the United States and included sites in agricultural and urban land-use settings, as well as sites on major rivers.
The results of the field study identified several challenges for the analysis and interpretation of data analyzed by both old and new methods, particularly when data span the change in methods and are combined for analysis of temporal trends in water quality. The main challenges identified are large (greater than 30 percent), statistically significant differences in analytical recovery, detection capability, and (or) measured concentrations for selected pesticides. These challenges are documented and discussed, but specific guidance or statistical methods to resolve these differences in methods are beyond the scope of the report. The results of the field study indicate that the implications of the change in analytical methods must be assessed individually for each pesticide and method.
Understanding the possible causes of the systematic differences in concentrations between methods that remain after recovery adjustment might be necessary to determine how to account for the differences in data analysis. Because recoveries for each method are independently determined from separate reference standards and spiking solutions, the differences might be due to an error in one of the reference standards or solutions or some other basic aspect of standard procedure in the analytical process. Further investigation of the possible causes is needed, which will lead to specific decisions on how to compensate for these differences in concentrations in data analysis. In the event that further investigations do not provide insight into the causes of systematic differences in concentrations between methods, the authors recommend continuing to collect and analyze paired environmental water samples by both old and new methods. This effort should be targeted to seasons, sites, and expected concentrations to supplement those concentrations already assessed and to compare the ongoing analytical recovery of old and new methods to those observed in the summer and fall of 2012.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175049","usgsCitation":"Martin, J.D., Norman, J.E., Sandstrom, M.W., and Rose, C.E., 2017, A field study of selected U.S. Geological Survey analytical methods for measuring pesticides in filtered stream water, June–September 2012: U.S. Geological Survey Scientific Investigations Report 2017–5049, 106 p., https://doi.org/10.3133/sir20175049.","productDescription":"Report: viii, 106 p.; 7 Appendixes; Data Release","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071831","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"links":[{"id":345500,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5049/sir20175049_appendix2to8.zip","text":"Appendixes 2–8","size":"1.49 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2017–5049 Appendixes 2–8"},{"id":345494,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5049/sir20175049_appendix8.pdf","text":"Appendix 8","size":"95 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5049 Appendix 8"},{"id":345493,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5049/sir20175049_appendix7.pdf","text":"Appendix 7","size":"108 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5049 Appendix 7"},{"id":345488,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5049/sir20175049_appendix2.pdf","text":"Appendix 2","size":"207 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5049 Appendix 2"},{"id":345442,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5049/sir20175049.pdf","text":"Report","size":"4.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5049"},{"id":345441,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5049/coverthb.jpg"},{"id":345492,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5049/sir20175049_appendix6.pdf","text":"Appendix 6","size":"153 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5049 Appendix 6"},{"id":345491,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5049/sir20175049_appendix5.pdf","text":"Appendix 5","size":"233 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5049 Appendix 5"},{"id":345490,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5049/sir20175049_appendix4.pdf","text":"Appendix 4","size":"363 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5049 Appendix 4"},{"id":345489,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5049/sir20175049_appendix3.pdf","text":"Appendix 3","size":"570 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5049 Appendix 3"},{"id":345443,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RB732P","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data Sets for the Report Entitled, \"A field study of selected U.S. Geological Survey analytical methods for measuring pesticides in filtered stream water, June - September 2012 (Scientific Investigations Report SIR-2017-5049)\""}],"country":"United States","contact":"National Water-Quality Assessment Project
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278
In this study, we measured the concentrations of 65 flame retardants in water samples from five Lake Michigan tributaries. These flame retardants included organophosphate esters (OPEs), brominated flame retardants (BFRs), and Dechlorane-related compounds. A total of 59 samples, including both the particulate and the dissolved phases, were collected from the Grand, Kalamazoo, Saint Joseph, and Lower Fox rivers and from the Indiana Harbor and Ship Canal (IHSC) in 2015. OPEs were the most abundant among the targeted compounds with geometric mean concentrations ranging from 20 to 54 ng/L; OPE concentrations were comparable among the five tributaries. BFR concentrations were about 1 ng/L, and the most-abundant compounds were bis(2-ethylhexyl) tetrabromophthalate, 2-ethylhexyl 2,3,4,5-tetrabromobenzoate, and decabromodiphenyl ether. The highest BFR concentrations were measured in either the IHSC or the Saint Joseph River. The dechlorane-related compounds were detected at low concentrations (<1 pg/L). The fraction of target compounds in the particulate phase relative to the dissolved phase varied by chemical and tended to increase with their octanol–water partition coefficient. The chemical loading from all the five tributaries into Lake Michigan were <10 kg/year for the BFRs and about 500 kg/year for the OPEs.
","language":"English","publisher":"ACS","doi":"10.1021/acs.est.7b01294","usgsCitation":"Guo, J., Romanak, K., Westenbroek, S.M., Hites, R.A., and Venier, M., 2017, Current-use flame retardants in the water of Lake Michigan tributaries: Environmental Science & Technology, v. 51, no. 17, p. 9960-9969, https://doi.org/10.1021/acs.est.7b01294.","productDescription":"10 p.","startPage":"9960","endPage":"9969","ipdsId":"IP-087256","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":345526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","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 -88.165283203125,\n 41.335575973123916\n ],\n [\n -85.946044921875,\n 41.335575973123916\n ],\n [\n -85.946044921875,\n 44.66083904265621\n ],\n [\n -88.165283203125,\n 44.66083904265621\n ],\n [\n -88.165283203125,\n 41.335575973123916\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"17","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-17","publicationStatus":"PW","scienceBaseUri":"59b1092fe4b020cdf7d8d9c0","contributors":{"authors":[{"text":"Guo, Jiehong","contributorId":191232,"corporation":false,"usgs":false,"family":"Guo","given":"Jiehong","email":"","affiliations":[],"preferred":false,"id":709633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romanak, Kevin","contributorId":191234,"corporation":false,"usgs":false,"family":"Romanak","given":"Kevin","affiliations":[],"preferred":false,"id":709634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westenbroek, Stephen M. 0000-0002-6284-8643 smwesten@usgs.gov","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":2210,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen","email":"smwesten@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hites, Ronald A.","contributorId":191235,"corporation":false,"usgs":false,"family":"Hites","given":"Ronald","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":709635,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Venier, Marta","contributorId":191233,"corporation":false,"usgs":false,"family":"Venier","given":"Marta","email":"","affiliations":[],"preferred":false,"id":709636,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190547,"text":"70190547 - 2017 - Climate, wildfire, and erosion ensemble foretells more sediment in western USA watersheds","interactions":[],"lastModifiedDate":"2017-10-02T12:47:15","indexId":"70190547","displayToPublicDate":"2017-09-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Climate, wildfire, and erosion ensemble foretells more sediment in western USA watersheds","docAbstract":"The area burned annually by wildfires is expected to increase worldwide due to climate change. Burned areas increase soil erosion rates within watersheds, which can increase sedimentation in downstream rivers and reservoirs. However, which watersheds will be impacted by future wildfires is largely unknown. Using an ensemble of climate, fire, and erosion models, we show that post-fire sedimentation is projected to increase for nearly nine-tenths of watersheds by > 10% and for more than one-third of watersheds by > 100% by the 2041 to 2050 decade in the western USA. The projected increases are statistically significant for more than eight-tenths of the watersheds. In the western USA, many human communities rely on water from rivers and reservoirs that originates in watersheds where sedimentation is projected to increase. Increased sedimentation could negatively impact water supply and quality for some communities, in addition to affecting stream channel stability and aquatic ecosystems.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL073979","usgsCitation":"Sankey, J.B., Kreitler, J.R., Hawbaker, T., McVay, J.L., Miller, M., Mueller, E.R., Vaillant, N.M., Lowe, S., and Sankey, T.T., 2017, Climate, wildfire, and erosion ensemble foretells more sediment in western USA watersheds: Geophysical Research Letters, v. 44, no. 17, p. 8884-8892, https://doi.org/10.1002/2017GL073979.","productDescription":"9 p.","startPage":"8884","endPage":"8892","ipdsId":"IP-073012","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":438223,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BV7DS8","text":"USGS data release","linkHelpText":"Climate, Wildfire, and Erosion Data, Western US"},{"id":345524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"17","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-07","publicationStatus":"PW","scienceBaseUri":"59b1092ee4b020cdf7d8d9b3","contributors":{"authors":[{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":709726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":709727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":196234,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[],"preferred":true,"id":709728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McVay, Jason L.","contributorId":196235,"corporation":false,"usgs":false,"family":"McVay","given":"Jason","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":709729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Mary Ellen","contributorId":196236,"corporation":false,"usgs":false,"family":"Miller","given":"Mary Ellen","affiliations":[],"preferred":false,"id":709730,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mueller, Erich R. 0000-0001-8202-154X emueller@usgs.gov","orcid":"https://orcid.org/0000-0001-8202-154X","contributorId":4930,"corporation":false,"usgs":true,"family":"Mueller","given":"Erich","email":"emueller@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":709734,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vaillant, Nicole M.","contributorId":196237,"corporation":false,"usgs":false,"family":"Vaillant","given":"Nicole","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":709731,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lowe, Scott E.","contributorId":196238,"corporation":false,"usgs":false,"family":"Lowe","given":"Scott E.","affiliations":[],"preferred":false,"id":709732,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":709733,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70190509,"text":"70190509 - 2017 - East African weathering dynamics controlled by vegetation-climate feedbacks","interactions":[],"lastModifiedDate":"2017-09-05T13:25:07","indexId":"70190509","displayToPublicDate":"2017-09-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"East African weathering dynamics controlled by vegetation-climate feedbacks","docAbstract":"Tropical weathering has important linkages to global biogeochemistry and landscape evolution in the East African rift. We disentangle the influences of climate and terrestrial vegetation on chemical weathering intensity and erosion at Lake Malawi using a long sediment record. Fossil pollen, microcharcoal, particle size, and mineralogy data affirm that the detrital clays accumulating in deep water within the lake are controlled by feedbacks between climate and hinterland forest composition. Particle-size patterns are also best explained by vegetation, through feedbacks with lake levels, wildfires, and erosion. We develop a new source-to-sink framework that links lacustrine sedimentation to hinterland vegetation in tropical rifts. Our analysis suggests that climate-vegetation interactions and their coupling to weathering/erosion could threaten future food security and has implications for accurately predicting petroleum play elements in continental rift basins.
","language":"English","publisher":"The Geological Society of America","doi":"10.1130/G38938.1","usgsCitation":"Ivory, S., McGlue, M.M., Ellis, G.S., Boehlke, A., Lézine, A., Vincens, A., and Cohen, A.S., 2017, East African weathering dynamics controlled by vegetation-climate feedbacks: Geology, v. 45, no. 9, p. 823-826, https://doi.org/10.1130/G38938.1.","productDescription":"4 p.","startPage":"823","endPage":"826","ipdsId":"IP-072975","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469540,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/632127","text":"External Repository"},{"id":345463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Malawi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 32.947998046875,\n -14.955399325942619\n ],\n [\n 36.046142578125,\n -14.955399325942619\n ],\n [\n 36.046142578125,\n -9.091248585779377\n ],\n [\n 32.947998046875,\n -9.091248585779377\n ],\n [\n 32.947998046875,\n -14.955399325942619\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-26","publicationStatus":"PW","scienceBaseUri":"59afb79ae4b0e9bde1351125","contributors":{"authors":[{"text":"Ivory, Sarah J.","contributorId":138493,"corporation":false,"usgs":false,"family":"Ivory","given":"Sarah J.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":709510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGlue, Michael M. mmcglue@usgs.gov","contributorId":4091,"corporation":false,"usgs":true,"family":"McGlue","given":"Michael","email":"mmcglue@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":709511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Geoffrey S. 0000-0003-4519-3320 gsellis@usgs.gov","orcid":"https://orcid.org/0000-0003-4519-3320","contributorId":1058,"corporation":false,"usgs":true,"family":"Ellis","given":"Geoffrey","email":"gsellis@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":709509,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boehlke, Adam 0000-0003-4980-431X aboehlke@usgs.gov","orcid":"https://orcid.org/0000-0003-4980-431X","contributorId":3470,"corporation":false,"usgs":true,"family":"Boehlke","given":"Adam","email":"aboehlke@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":709512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lézine, Anne-Marie","contributorId":196162,"corporation":false,"usgs":false,"family":"Lézine","given":"Anne-Marie","affiliations":[],"preferred":false,"id":709513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vincens, Annie","contributorId":138497,"corporation":false,"usgs":false,"family":"Vincens","given":"Annie","affiliations":[{"id":12427,"text":"CEREGE, CNRS, Aix-en-Provence, France","active":true,"usgs":false}],"preferred":false,"id":709514,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cohen, Andrew S.","contributorId":138496,"corporation":false,"usgs":false,"family":"Cohen","given":"Andrew","email":"","middleInitial":"S.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":709515,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189630,"text":"sir20165139B - 2017 - Simulation and assessment of groundwater flow and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2003 through 2013: Chapter B of Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","interactions":[{"subject":{"id":70189630,"text":"sir20165139B - 2017 - Simulation and assessment of groundwater flow and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2003 through 2013: Chapter B of Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","indexId":"sir20165139B","publicationYear":"2017","noYear":false,"chapter":"B","displayTitle":"Simulation and assessment of groundwater flow and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2003 through 2013: Chapter B of Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","title":"Simulation and assessment of groundwater flow and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2003 through 2013: Chapter B of Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015"},"predicate":"IS_PART_OF","object":{"id":70177056,"text":"sir20165139 - 2016 - Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","indexId":"sir20165139","publicationYear":"2016","noYear":false,"title":"Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015"},"id":1}],"isPartOf":{"id":70177056,"text":"sir20165139 - 2016 - Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","indexId":"sir20165139","publicationYear":"2016","noYear":false,"title":"Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015"},"lastModifiedDate":"2017-09-06T09:28:03","indexId":"sir20165139B","displayToPublicDate":"2017-09-05T00:00:00","publicationYear":"2017","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":"2016-5139","chapter":"B","displayTitle":"Simulation and assessment of groundwater flow and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2003 through 2013: Chapter B of Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","title":"Simulation and assessment of groundwater flow and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2003 through 2013: Chapter B of Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","docAbstract":"Water levels during 2003 through 2013 were less than mean water levels for the period 1925–2013 for several lakes in the northeast Twin Cities Metropolitan Area in Minnesota. Previous periods of low lake-water levels generally were correlated with periods with less than mean precipitation. Increases in groundwater withdrawals and land-use changes have brought into question whether or not recent (2003–13) lake-water-level declines are solely caused by decreases in precipitation. A thorough understanding of groundwater and surface-water exchanges was needed to assess the effect of water-management decisions on lake-water levels. To address this need, the U.S. Geological Survey, in cooperation with the Metropolitan Council and the Minnesota Department of Health, developed and calibrated a three-dimensional, steady-state groundwater-flow model representing 2003–13 mean hydrologic conditions to assess groundwater and lake-water exchanges, and the effects of groundwater withdrawals and precipitation on water levels of 96 lakes in the northeast Twin Cities Metropolitan Area.
Lake-water budgets for the calibrated groundwater-flow model indicated that groundwater is flowing into lakes in the northeast Twin Cities Metropolitan Area and lakes are providing water to underlying aquifers. Lake-water outflow to the simulated groundwater system was a major outflow component for Big Marine Lake, Lake Elmo, Snail Lake, and White Bear Lake, accounting for 45 to 64 percent of the total outflows from the lakes. Evaporation and transpiration from the lake surface ranged from 19 to 52 percent of the total outflow from the four lakes. Groundwater withdrawals and precipitation were varied from the 2003‒13 mean values used in the calibrated model (30-percent changes in groundwater withdrawals and 5-percent changes in precipitation) for hypothetical scenarios to assess the effects of groundwater withdrawals and precipitation on water budgets and levels in Big Marine Lake, Snail Lake, and White Bear Lake. Simulated lake-water levels and budgets for Snail Lake and White Bear Lake were affected by 30-percent changes in groundwater withdrawals and 5-percent changes in precipitation in the area, whereas the water level in Big Marine Lake was mainly affected by 5-percent precipitation changes. The effects of groundwater withdrawals on the lake-water levels depend on the number of wells and amount of withdrawals from wells near the lakes. Although lake-water levels are sensitive to precipitation changes, increases in groundwater withdrawals during dry periods exacerbate lake-water level declines. The calibrated, groundwater-flow model is a tool that water-resources managers can use to address future water management issues in the northeast Twin Cities Metropolitan Area.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015 (Scientific Investigations Report 2016–5139)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165139B","collaboration":"Prepared in cooperation with the Metropolitan Council and Minnesota Department of Health","usgsCitation":"Jones, P.M., Roth, J.L., Trost, J.J., Christenson, C.A., Diekoff, A.L., and Erickson, M.L., 2017, Simulation and assessment of groundwater flow and groundwater and surface-water exchanges in lakes in the northeast Twin Cities Metropolitan Area, Minnesota, 2003 through 2013: U.S. Geological Survey Scientific Investigations Report 2016–5139–B, 88 p., https://doi.org/10.3133/sir20165139B.","productDescription":"Report: xi, 88 p.; Tables 3 and 8; Data Release","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081793","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":345436,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5139/b/sir20165139B.pdf","text":"Report","size":"14.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5139–B"},{"id":345437,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5139/b/sir20165139B_table3.xlsx","text":"Table 3","size":"41.5 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5139–B Table 3"},{"id":345438,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5139/b/sir20165139B_table8.pdf","text":"Table 8","size":"197 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5139–B Table 8"},{"id":345435,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5139/b/coverthb.jpg"},{"id":345440,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7445JRM","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model used to simulate and assess the groundwater flow and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2003 through 2013"}],"country":"United States","state":"Minnesota","city":"Minneapolis, Saint Paul","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.833984375,\n 43.79488907226601\n ],\n [\n -91.658935546875,\n 43.79488907226601\n ],\n [\n -91.658935546875,\n 46.08085173686784\n ],\n [\n -94.833984375,\n 46.08085173686784\n ],\n [\n -94.833984375,\n 43.79488907226601\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
Major floods adversely affect water quality through surface runoff, groundwater discharge, and damage to municipal water infrastructure. Despite their importance, it can be difficult to assess the effects of floods on streamwater chemistry because of challenges collecting samples and the absence of baseline data. This study documents water quality during the September 2013 extreme flood in the South Platte River, Colorado, USA. Weekly time-series water samples were collected from 3 urban source waters (municipal tap water, streamwater, and wastewater treatment facility effluent) under normal-flow and flood conditions. In addition, water samples were collected during the flood at 5 locations along the South Platte River and from 7 tributaries along the Colorado Front Range. Samples were analyzed for 54 major and trace elements. Specific chemical tracers, representing different natural and anthropogenic sources and geochemical behaviors, were used to compare streamwater composition before and during the flood. The results differentiate hydrological processes that affected water quality: (1) in the upper watershed, runoff diluted most dissolved constituents, (2) in the urban corridor and lower watershed, runoff mobilized soluble constituents accumulated on the landscape and contributed to stream loading, and (3) flood-induced groundwater discharge mobilized soluble constituents stored in the vadose zone.
","language":"English","publisher":"ACS","doi":"10.1021/acs.est.7b01767","usgsCitation":"Barber, L.B., Paschke, S.S., Battaglin, W.A., Douville, C., Fitzgerald, K.C., Keefe, S.H., Roth, D.A., and Vajda, A.M., 2017, Effects of an extreme flood on trace elements in river water—From urban stream to major river basin: Environmental Science & Technology, v. 51, no. 18, p. 10344-10356, https://doi.org/10.1021/acs.est.7b01767.","productDescription":"13 p.","startPage":"10344","endPage":"10356","ipdsId":"IP-080742","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":438226,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76Q1VCC","text":"USGS data release","linkHelpText":"Major, trace, and rare earth element concentration measured in water samples collected during the September 2013 Colorado South Platte River flood"},{"id":345459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"South Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.5,\n 38\n ],\n [\n -102,\n 38\n ],\n [\n -102,\n 41\n ],\n [\n -105.5,\n 41\n ],\n [\n -105.5,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"18","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-01","publicationStatus":"PW","scienceBaseUri":"59afb79be4b0e9bde1351127","contributors":{"authors":[{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":709501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paschke, Suzanne S. 0000-0002-3471-4242 spaschke@usgs.gov","orcid":"https://orcid.org/0000-0002-3471-4242","contributorId":1347,"corporation":false,"usgs":true,"family":"Paschke","given":"Suzanne","email":"spaschke@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Battaglin, William A. 0000-0001-7287-7096 wbattagl@usgs.gov","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":1527,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","email":"wbattagl@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Douville, Chris","contributorId":179191,"corporation":false,"usgs":false,"family":"Douville","given":"Chris","email":"","affiliations":[],"preferred":false,"id":709504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzgerald, Kevin C. kcfitzgerald@usgs.gov","contributorId":5534,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Kevin","email":"kcfitzgerald@usgs.gov","middleInitial":"C.","affiliations":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"preferred":true,"id":709505,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keefe, Steffanie H. 0000-0002-3805-6101 shkeefe@usgs.gov","orcid":"https://orcid.org/0000-0002-3805-6101","contributorId":2843,"corporation":false,"usgs":true,"family":"Keefe","given":"Steffanie","email":"shkeefe@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":709506,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roth, David A. 0000-0002-7515-3533 daroth@usgs.gov","orcid":"https://orcid.org/0000-0002-7515-3533","contributorId":2340,"corporation":false,"usgs":true,"family":"Roth","given":"David","email":"daroth@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":709507,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vajda, Alan M.","contributorId":179189,"corporation":false,"usgs":false,"family":"Vajda","given":"Alan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":709508,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70190483,"text":"70190483 - 2017 - Experimental observations on the decay of environmental DNA from bighead and silver carps","interactions":[],"lastModifiedDate":"2017-09-05T09:18:52","indexId":"70190483","displayToPublicDate":"2017-09-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Experimental observations on the decay of environmental DNA from bighead and silver carps","docAbstract":"Interest in the field of environmental DNA (eDNA) is growing rapidly and eDNA surveys are becoming an important consideration for aquatic resource managers dealing with invasive species. However, in order for eDNA monitoring to mature as a research and management tool, there are several critical knowledge gaps that must be filled. One such gap is the fate of eDNA materials in the aquatic environment. Understanding the environmental factors that influence the decay of eDNA and how these factors impact detection probabilities over time and space could have significant implications for eDNA survey design and data interpretation. Here we experimentally explore decay of eDNA associated with bighead carp (Hypophthalmichthys nobilis) biological waste collected from an aquaculture filtration system and with sperm collected from captive silver carp (H. molitrix), and how decay may be influenced by differing levels of water turbulence, temperature, microbial load, and pH. We found that the decay patterns of eDNA associated with both H. nobilis biological waste and H. molitrix milt significantly fit monophasic exponential decay curves. Secondly, we observed that the highest temperature we tested resulted in a decay half-life as much as 5.5× more rapid than the lowest temperature we tested. When we suppressed microbial loads in eDNA samples, we observed that overall losses of eDNA were reduced by about 2.5×. When we amended eDNA samples with pond water the half-life of eDNA was reduced by about 2.25×, despite relatively little apparent increase in the overall microbial load. This pattern indicated that species constituency of the microbial community, in addition to microbial load, might play a critical role in eDNA degradation. A shift in pH from 6.5 to 8.0 in the samples resulted in a 1.6× reduction in eDNA halflife. Water turbulence in our study had no apparent effect on eDNA decay. When we combined different temperature, pH, and microbial load treatments to create a rapid decay condition and a slow decay condition, and tracked eDNA decay over 91 days, we observed a 5.0× greater loss of eDNA by Day 5 under rapid decay conditions than under slow decay conditions. At the end of the trials, the differences in eDNA loss between the rapid decay and baseline and slow decay conditions were 0.1× and 3.3×, respectively. Our results strongly demonstrate the potential for environmental factors to influence eDNA fate and, thus, the interpretation of eDNA survey results.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2017.8.3.08","usgsCitation":"Lance, R.F., Klymus, K.E., Richter, C.A., Guan, X., Farrington, H.L., Carr, M.R., Thompson, N., Chapman, D., and Baerwaldt, K.L., 2017, Experimental observations on the decay of environmental DNA from bighead and silver carps: Management of Biological Invasions, v. 8, no. 3, p. 343-359, https://doi.org/10.3391/mbi.2017.8.3.08.","productDescription":"17 p.","startPage":"343","endPage":"359","ipdsId":"IP-080386","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":469541,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2017.8.3.08","text":"Publisher Index Page"},{"id":438224,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F769P1","text":"USGS data release","linkHelpText":"Experimental observations on the decay of environmental DNA from bighead and silver carp-Data"},{"id":345452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59afb79be4b0e9bde135112b","contributors":{"authors":[{"text":"Lance, Richard F.","contributorId":176872,"corporation":false,"usgs":false,"family":"Lance","given":"Richard","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":709418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":709419,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richter, Catherine A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":138994,"corporation":false,"usgs":true,"family":"Richter","given":"Catherine","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":709417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guan, Xin","contributorId":196130,"corporation":false,"usgs":false,"family":"Guan","given":"Xin","email":"","affiliations":[],"preferred":false,"id":709420,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Farrington, Heather L.","contributorId":196131,"corporation":false,"usgs":false,"family":"Farrington","given":"Heather","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":709421,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carr, Matthew R.","contributorId":196132,"corporation":false,"usgs":false,"family":"Carr","given":"Matthew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":709422,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thompson, Nathan 0000-0002-1372-6340 nthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-1372-6340","contributorId":196133,"corporation":false,"usgs":true,"family":"Thompson","given":"Nathan","email":"nthompson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":709423,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":709424,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Baerwaldt, Kelly L.","contributorId":196134,"corporation":false,"usgs":false,"family":"Baerwaldt","given":"Kelly","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":709425,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70189964,"text":"sir20175084 - 2017 - Characterization of water quality and suspended sediment during cold-season flows, warm-season flows, and stormflows in the Fountain and Monument Creek watersheds, Colorado, 2007–2015","interactions":[],"lastModifiedDate":"2017-09-05T10:02:12","indexId":"sir20175084","displayToPublicDate":"2017-09-01T16:00:00","publicationYear":"2017","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":"2017-5084","displayTitle":"Characterization of water quality and suspended sediment during cold-season flows, warm-season flows, and stormflows in the Fountain and Monument Creek watersheds, Colorado, 2007–2015","title":"Characterization of water quality and suspended sediment during cold-season flows, warm-season flows, and stormflows in the Fountain and Monument Creek watersheds, Colorado, 2007–2015","docAbstract":"From 2007 through 2015, the U.S. Geological Survey, in cooperation with Colorado Springs City Engineering, conducted a study in the Fountain and Monument Creek watersheds, Colorado, to characterize surface-water quality and suspended-sediment conditions for three different streamflow regimes with an emphasis on characterizing water quality during storm runoff. Data collected during this study were used to evaluate the effects of stormflows and wastewater-treatment effluent discharge on Fountain and Monument Creeks in the Colorado Springs, Colorado, area. Water-quality samples were collected at 2 sites on Upper Fountain Creek, 2 sites on Monument Creek, 3 sites on Lower Fountain Creek, and 13 tributary sites during 3 flow regimes: cold-season flow (November–April), warm-season flow (May–October), and stormflow from 2007 through 2015. During 2015, additional samples were collected and analyzed for Escherichia coli (E. coli) during dry weather conditions at 41 sites, located in E. coli impaired stream reaches, to help identify source areas and scope of the impairment.
Concentrations of E. coli, total arsenic, and dissolved copper, selenium, and zinc in surface-water samples were compared to Colorado in-stream standards. Stormflow concentrations of E. coli frequently exceeded the recreational use standard of 126 colonies per 100 milliliters at main-stem and tributary sites by more than an order of magnitude. Even though median E. coli concentrations in warm-season flow samples were lower than median concentrations in storm-flow samples, the water quality standard for E. coli was still exceeded at most main-stem sites and many tributary sites during warm-season flows. Six samples (three warm-season flow and three stormflow samples) collected from Upper Fountain Creek, upstream from the confluence of Monument Creek, and two stormflow samples collected from Lower Fountain Creek, downstream from the confluence with Monument Creek, exceeded the acute water-quality standard for total arsenic of 50 micrograms per liter. All concentrations of dissolved copper, selenium, and zinc measured in samples were below the water-quality standard.
Concentrations of dissolved nitrate plus nitrite generally increased from upstream to downstream during all flow periods. The largest downstream increase in dissolved nitrate plus nitrite concentration was measured between sites 07103970 and 07104905 on Monument Creek. All but one tributary that drain into Monument Creek between the two sites had higher median nitrate plus nitrite concentrations than the nearest upstream site on Monument Creek, site 07103970 (MoCr_Woodmen). Increases in the concentration of dissolved nitrate plus nitrite were also evident below wastewater treatment plants located on Fountain Creek.
Most stormflow concentrations of dissolved trace elements were smaller than concentrations from cold-season flow or warm-season samples. However, median concentrations of total arsenic, lead, manganese, nickel, and zinc generally were much larger during periods of stormflow than during cold-season flow or warm-season fl. Median concentrations of total arsenic, total copper, total lead, dissolved and total manganese, total nickel, dissolved and total selenium, and dissolved and total zinc concentrations increased from 1.5 to 28.5 times from site 07103700 (FoCr_Manitou) to 07103707 (FoCr_8th) during cold-season and warm-season flows, indicating a large source of trace elements between these two sites. Both of these sites are located on Fountain Creek, upstream from the confluence with Monument Creek.
Median suspended-sediment concentrations and median suspended-sediment loads increased in the downstream direction during all streamflow regimes between Monument Creek sites 07103970 (MoCr_Woodmen) and 07104905 (MoCr_Bijou); however, statistically significant increase (p-value less than 0.05) were only present during warm-season flow and stormflow. Significant increases in median suspended sediment concentrations were measured during cold-season flow and warm-season flow between Upper Fountain Creek site 07103707 (FoCr_8th) and Lower Fountain Creek site 07105500 (FoCr_Nevada) because of inflows from Monument Creek with higher suspended-sediment concentrations. Median suspended-sediment concentrations between sites 07104905 (MoCr_Bijou) and 07105500 (FoCr_Nevada) increased significantly during warm-season flow but showed no significant differences during cold-season flow and stormflow. Significant decreases in median suspended-sediment concentrations were measured between sites 07105500 (FoCr_Nevada) and 07105530 (FoCr_Janitell) during all flow regimes.
Suspended-sediment concentrations, discharges, and yields associated with stormflow were significantly larger than those associated with warm-season flow. Although large spatial variations in suspended-sediment yields occurred during warm-season flows, the suspended-sediment yield associated with stormflow were as much as 1,000 times larger than the suspended-sediment yields that occurred during warm-season flow.
Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225-0046
“Whiting” in oceanography is a term used to describe a sharply defined patch of water that contains high levels of suspended, fine-grained calcium carbonate (CaCO3). Whitings have been reported in many oceanic and lake environments, and recently have been reported in southwest Florida coastal waters. Here, field and laboratory measurements were used to study optical, biological, and chemical properties of whiting waters off southwest Florida. No significant difference was found in chlorophyll a concentrations between whiting and outside waters (non-whiting water), but average particle backscattering coefficients in whiting waters were double those in outside waters, and remote sensing reflectance in whiting waters was higher at all wavelengths (400–700 nm). While other potential causes cannot be completely ruled out, particle composition and biochemical differences between sampled whiting water, contiguous water, and outside water indicate a biologically precipitated mode of whiting formation. Taxonomic examination of marine phytoplankton samples collected during a whiting event revealed a community dominated by autotrophic picoplankton and a small (<10 μm), centric diatom species, identified as Thalassiosira sp. through the use of scanning electron microscopy. Amorphous to fully formed crystals of CaCO3 were observed along the girdle bands of Thalassiosira sp. cells and autotrophic picoplankton cells. Although carbonate parameters differed from whiting and contiguous to outside water, more sampling is needed to determine if these results are statistically significant.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2017.07.017","usgsCitation":"Long, J., Hu, C., Robbins, L.L., Byrne, R.H., Paul, J.H., and Wolny, J.L., 2017, Optical and biochemical properties of a southwest Florida whiting event: Estuarine, Coastal and Shelf Science, v. 196, p. 258-268, https://doi.org/10.1016/j.ecss.2017.07.017.","productDescription":"11 p.","startPage":"258","endPage":"268","ipdsId":"IP-081745","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469545,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2017.07.017","text":"Publisher Index Page"},{"id":356303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","volume":"196","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc5c9e4b0f5d57878eb43","contributors":{"authors":[{"text":"Long, Jacqueline","contributorId":45646,"corporation":false,"usgs":true,"family":"Long","given":"Jacqueline","email":"","affiliations":[],"preferred":false,"id":707109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hu, Chaunmin","contributorId":195445,"corporation":false,"usgs":false,"family":"Hu","given":"Chaunmin","email":"","affiliations":[],"preferred":false,"id":707110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robbins, Lisa L. 0000-0003-3681-1094 lrobbins@usgs.gov","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":422,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","email":"lrobbins@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":707108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Byrne, Robert H.","contributorId":149366,"corporation":false,"usgs":false,"family":"Byrne","given":"Robert","email":"","middleInitial":"H.","affiliations":[{"id":17720,"text":"College of Marine Science USF","active":true,"usgs":false}],"preferred":false,"id":707111,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paul, John H.","contributorId":28183,"corporation":false,"usgs":true,"family":"Paul","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":707112,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wolny, Jennifer L.","contributorId":195447,"corporation":false,"usgs":false,"family":"Wolny","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":707113,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191052,"text":"70191052 - 2017 - The fascinating and complex dynamics of geyser eruptions","interactions":[],"lastModifiedDate":"2017-09-25T11:57:02","indexId":"70191052","displayToPublicDate":"2017-09-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":806,"text":"Annual Review of Earth and Planetary Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The fascinating and complex dynamics of geyser eruptions","docAbstract":"Geysers episodically erupt liquid and vapor. Despite two centuries of scientific study, basic questions persist—why do geysers exist? What determines eruption intervals, durations, and heights? What initiates eruptions? Through monitoring eruption intervals, analyzing geophysical data, taking measurements within geyser conduits, performing numerical simulations, and constructing laboratory models, some of these questions have been addressed. Geysers are uncommon because they require a combination of abundant water recharge, magmatism, and rhyolite flows to supply heat and silica, and large fractures and cavities overlain by low-permeability materials to trap rising multiphase and multicomponent fluids. Eruptions are driven by the conversion of thermal to kinetic energy during decompression. Larger and deeper cavities permit larger eruptions and promote regularity by isolating water from weather variations. The ejection velocity may be limited by the speed of sound of the liquid + vapor mixture.
","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-earth-063016-015605","usgsCitation":"Hurwitz, S., and Manga, M., 2017, The fascinating and complex dynamics of geyser eruptions: Annual Review of Earth and Planetary Sciences, v. 45, p. 31-59, https://doi.org/10.1146/annurev-earth-063016-015605.","productDescription":"29 p.","startPage":"31","endPage":"59","ipdsId":"IP-075214","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469559,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1146/annurev-earth-063016-015605","text":"Publisher Index Page"},{"id":346049,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ca15ade4b017cf314041c0","contributors":{"authors":[{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":711065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manga, Michael","contributorId":145531,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":711066,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194724,"text":"70194724 - 2017 - Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources","interactions":[],"lastModifiedDate":"2017-12-14T12:48:05","indexId":"70194724","displayToPublicDate":"2017-09-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources","docAbstract":"Cyanobacterial harmful algal blooms (cyanoHAB) cause extensive problems in lakes worldwide, including human and ecological health risks, anoxia and fish kills, and taste and odor problems. CyanoHABs are a particular concern in both recreational waters and drinking water sources because of their dense biomass and the risk of exposure to toxins. Successful cyanoHAB assessment using satellites may provide an indicator for human and ecological health protection. In this study, methods were developed to assess the utility of satellite technology for detecting cyanoHAB frequency of occurrence at locations of potential management interest. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was evaluated to prepare for the equivalent series of Sentinel-3 Ocean and Land Colour Imagers (OLCI) launched in 2016 as part of the Copernicus program. Based on the 2012 National Lakes Assessment site evaluation guidelines and National Hydrography Dataset, the continental United States contains 275,897 lakes and reservoirs >1 ha in area. Results from this study show that 5.6% of waterbodies were resolvable by satellites with 300 m single-pixel resolution and 0.7% of waterbodies were resolvable when a three by three pixel (3 × 3-pixel) array was applied based on minimum Euclidian distance from shore. Satellite data were spatially joined to U.S. public water surface intake (PWSI) locations, where single-pixel resolution resolved 57% of the PWSI locations and a 3 × 3-pixel array resolved 33% of the PWSI locations. Recreational and drinking water sources in Florida and Ohio were ranked from 2008 through 2011 by cyanoHAB frequency above the World Health Organization’s (WHO) high threshold for risk of 100,000 cells mL−1. The ranking identified waterbodies with values above the WHO high threshold, where Lake Apopka, FL (99.1%) and Grand Lake St. Marys, OH (83%) had the highest observed bloom frequencies per region. The method presented here may indicate locations with high exposure to cyanoHABs and therefore can be used to assist in prioritizing management resources and actions for recreational and drinking water sources.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2017.04.046","usgsCitation":"Clark, J.M., Schaeffer, B., Darling, J.A., Urquhart, E.A., Johnston, J.M., Ignatius, A.R., Myer, M.H., Loftin, K.A., Werdell, P., and Stumpf, R., 2017, Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources: Ecological Indicators, v. 80, p. 84-95, https://doi.org/10.1016/j.ecolind.2017.04.046.","productDescription":"12 p.","startPage":"84","endPage":"95","ipdsId":"IP-085906","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":469570,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2017.04.046","text":"Publisher Index Page"},{"id":349989,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.715576171875,\n 38.84826438869913\n ],\n [\n -81.265869140625,\n 38.84826438869913\n ],\n [\n -81.265869140625,\n 41.97582726102573\n ],\n [\n -84.715576171875,\n 41.97582726102573\n ],\n [\n -84.715576171875,\n 38.84826438869913\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.232666015625,\n 26.362342068998764\n ],\n [\n -79.95849609375,\n 26.362342068998764\n ],\n [\n -79.95849609375,\n 30.486550842588485\n ],\n [\n -82.232666015625,\n 30.486550842588485\n ],\n [\n -82.232666015625,\n 26.362342068998764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb5be4b06e28e9c22fa2","contributors":{"authors":[{"text":"Clark, John M.","contributorId":201331,"corporation":false,"usgs":false,"family":"Clark","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":725014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaeffer, Blake A.","contributorId":152172,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Blake A.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":725015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Darling, John A.","contributorId":38878,"corporation":false,"usgs":true,"family":"Darling","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":725016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Urquhart, Erin A.","contributorId":201327,"corporation":false,"usgs":false,"family":"Urquhart","given":"Erin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":725017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnston, John M.","contributorId":104318,"corporation":false,"usgs":true,"family":"Johnston","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":725018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ignatius, Amber R. arignatius@usgs.gov","contributorId":3817,"corporation":false,"usgs":true,"family":"Ignatius","given":"Amber","email":"arignatius@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":725019,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Myer, Mark H.","contributorId":201335,"corporation":false,"usgs":false,"family":"Myer","given":"Mark","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":725020,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":725013,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Werdell, P. 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Seagrasses are in decline globally, and monitoring changes in their growth and extent is increasingly valuable to determine impacts from large-scale estuarine restoration and inform blue carbon mapping initiatives. Thus, we examined the efficacy of two remote sensing mapping methods with high-resolution (0.5 m pixel size) color near infrared imagery with ground validation to assess change following major tidal marsh restoration. Automated classification of false color aerial imagery and digitized polygons documented a slight decline in eelgrass area directly after restoration followed by an increase two years later. Classification of sparse and low to medium density eelgrass was confounded in areas with algal cover, however large dense patches of eelgrass were well delineated. Automated classification of aerial imagery from unsupervised and supervised methods provided reasonable accuracies of 73% and hand-digitizing polygons from the same imagery yielded similar results. Visual clues for hand digitizing from the high-resolution imagery provided as reliable a map of dense eelgrass extent as automated image classification. We found that automated classification had no advantages over manual digitization particularly because of the limitations of detecting eelgrass with only three bands of imagery and near infrared.
","language":"English","publisher":"Northwest Scientific Association","doi":"10.3955/046.091.0307","usgsCitation":"Davenport, A.E., Davis, J.D., Woo, I., Grossman, E.E., Barham, J.B., Ellings, C.S., and Takekawa, J.Y., 2017, Comparing automated classification and digitization approaches to detect change in eelgrass bed extent during restoration of a large river delta: Northwest Science, v. 91, no. 3, p. 272-282, https://doi.org/10.3955/046.091.0307.","productDescription":"11 p.","startPage":"272","endPage":"282","ipdsId":"IP-075396","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":345974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually Delta, Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73685455322266,\n 47.07690269678769\n ],\n [\n -122.67866134643553,\n 47.07690269678769\n ],\n [\n -122.67866134643553,\n 47.1075227853425\n ],\n [\n -122.73685455322266,\n 47.1075227853425\n ],\n [\n -122.73685455322266,\n 47.07690269678769\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59c37e3be4b091459a6316ff","contributors":{"authors":[{"text":"Davenport, Anna Elizabeth","contributorId":196608,"corporation":false,"usgs":false,"family":"Davenport","given":"Anna","email":"","middleInitial":"Elizabeth","affiliations":[],"preferred":false,"id":710912,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Jerry D.","contributorId":196609,"corporation":false,"usgs":false,"family":"Davis","given":"Jerry","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":710913,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":710911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":196610,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":710914,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barham, Jesse B.","contributorId":149342,"corporation":false,"usgs":false,"family":"Barham","given":"Jesse","email":"","middleInitial":"B.","affiliations":[{"id":17710,"text":"Nisqually NWR, USFWS, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":710915,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellings, Christopher S.","contributorId":149343,"corporation":false,"usgs":false,"family":"Ellings","given":"Christopher","email":"","middleInitial":"S.","affiliations":[{"id":17711,"text":"Dep't Natural Resources, Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":710916,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":196611,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":710917,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}