{"pageNumber":"259","pageRowStart":"6450","pageSize":"25","recordCount":68827,"records":[{"id":70208795,"text":"70208795 - 2020 - Coal biomethanation potential of various ranks from Pakistan: A possible alternative energy source","interactions":[],"lastModifiedDate":"2020-03-02T06:54:26","indexId":"70208795","displayToPublicDate":"2020-01-20T06:49:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Coal biomethanation potential of various ranks from Pakistan: A possible alternative energy source","docAbstract":"The present study investigated the possibility of microbial transformations of coal to gas (biogasification) as an alternative to conventional coal mining because this approach has the potential to be less expensive, cleaner, and providinge greater access to deeper coal resources. Biogasification is often associated with low rank coal such as lignite and subbituminous coal that hasve produced enough coalbed methane to be commercially viable in the United States and Australia. However, little work has been done to analyze the potential of biogasification in higher rank coal. For this purpose, bioassay using a wetland-derived consortium, and a coal-derived consortium were used to analyze coal samples from Pakistan belonging to different ranks (lignite to semi-anthracite). Among all samples a low volatile bituminous coal produced the maximum methane 34.95 µmol CH4/g coal with the wetland-derived microbial consortium, followed by subbituminous coal (30.18 µmol CH4/g coal). Lower methane levels were recorded with the coal-derived consortium, with subbituminous coal yielding the highest concentration (25.1 µmol CH4/g coal). Methane levels appeared to be increasing on the last measurement indicating the coal-derived consortium was slower than the wetland-derived consortium but could still catalyze biogasification in higher rank coals. Quantitative polymerase chain reaction analysis for mcrA functional genes suggested indicated that the microbial community members that produce methane (methanogens) varied during the incubations. Energy conversion efficiency of different strategies (other biological and underground coal gasification processes) was also compared and discussed. This study was the first to compare bioassay using consortia of microbes non-indigenous and indigenous to coal and indicate the potential of biogasification from many different coalbeds across Pakistan.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jclepro.2020.120177","usgsCitation":"Malik, A.Y., Ishtiaq Ali, M., Jamal, A., Farooq, U., Khatoon, N., Orem, W.H., Barnhart, E.P., SanFilipo, J., He, H., and Huang, Z., 2020, Coal biomethanation potential of various ranks from Pakistan: A possible alternative energy source, v. 255, 120177, 11 p., https://doi.org/10.1016/j.jclepro.2020.120177.","productDescription":"120177, 11 p.","ipdsId":"IP-104161","costCenters":[{"id":5050,"text":"WY-MT Water Science 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Land‐use and climate change are significantly affecting stream ecosystems, yet understanding of their long‐term impacts is hindered by the few studies that have simultaneously investigated their interaction and high variability among future projections. We modeled possible effects of a suite of 2030, 2060, and 2090 land‐use and climate scenarios on the condition of 70,772 small streams in the Chesapeake Bay watershed, United States. The Chesapeake Basin‐wide Index of Biotic Integrity, a benthic macroinvertebrate multimetric index, was used to represent stream condition. Land‐use scenarios included four Special Report on Emissions Scenarios (A1B, A2, B1, and B2) representing a range of potential landscape futures. Future climate scenarios included quartiles of future climate changes from downscaled Coupled Model Intercomparison Project ‐ Phase 5 (CMIP5) and a watershed‐wide uniform scenario (Lynch2016). We employed random forests analysis to model individual and combined effects of land‐use and climate change on stream conditions. Individual scenarios suggest that by 2090, watershed‐wide conditions may exhibit anywhere from large degradations (e.g., scenarios A1B, A2, and the CMIP5 25th percentile) to small degradations (e.g., scenarios B1, B2, and Lynch2016). Combined land‐use and climate change scenarios highlighted their interaction and predicted, by 2090, watershed‐wide degradation in 16.2% (A2 CMIP5 25th percentile) to 1.0% (B2 Lynch2016) of stream kilometers. A goal for the Chesapeake Bay watershed is to restore 10% of stream kilometers over a 2008 baseline; our results suggest meeting and sustaining this goal until 2090 may require improvement in 11.0%–26.2% of stream kilometers, dependent on land‐use and climate scenario. These results highlight inherent variability among scenarios and the resultant uncertainty of predicted conditions, which reinforces the need to incorporate multiple scenarios of both land‐use (e.g., development, agriculture, etc.) and climate change in future studies to encapsulate the range of potential future conditions.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14961","usgsCitation":"Maloney, K.O., Krause, K.P., Buchanan, C., Hay, L., McCabe, G.J., Smith, Z.M., Sohl, T.L., and Young, J.A., 2020, Disentangling the potential effects of land-use and climate change on stream conditions: Global Change Biology, v. 26, no. 4, p. 2251-2269, https://doi.org/10.1111/gcb.14961.","productDescription":"19 p.","startPage":"2251","endPage":"2269","ipdsId":"IP-108922","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":458096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.14961","text":"Publisher Index Page"},{"id":377365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New York, Pennsylvania, 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M.","contributorId":214279,"corporation":false,"usgs":false,"family":"Smith","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":795760,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sohl, Terry L. 0000-0002-9771-4231 sohl@usgs.gov","orcid":"https://orcid.org/0000-0002-9771-4231","contributorId":648,"corporation":false,"usgs":true,"family":"Sohl","given":"Terry","email":"sohl@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":795761,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":795762,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70208295,"text":"70208295 - 2020 - Daily stream samples reveal highly complex pesticide occurrence and potential toxicity to aquatic life","interactions":[],"lastModifiedDate":"2021-06-01T17:26:43.193631","indexId":"70208295","displayToPublicDate":"2020-01-18T12:47:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Daily stream samples reveal highly complex pesticide occurrence and potential toxicity to aquatic life","docAbstract":"

Transient, acutely toxic concentrations of pesticides in streams can go undetected by fixed-interval sampling programs. Here we compare temporal patterns in occurrence of current-use pesticides in daily composite samples to those in weekly composite and weekly discrete samples of surface water from 14 small stream sites. Samples were collected over 10–14 weeks at 7 stream sites in each of the Midwestern and Southeastern United States. Samples were analyzed for over 200 pesticides and degradates by direct aqueous injection liquid chromatography with tandem mass spectrometry. Nearly 2 and 3 times as many unique pesticides were detected in daily samples as in weekly composite and weekly discrete samples, respectively. Based on exceedances of acute-invertebrate benchmarks (AIB) and(or) a Pesticide Toxicity Index (PTI) >1, potential acute-invertebrate toxicity was predicted at 11 of 14 sites from the results for daily composite samples, but was predicted for only 3 sites from weekly composites and for no sites from weekly discrete samples. Insecticides were responsible for most of the potential invertebrate toxicity, occurred transiently, and frequently were missed by the weekly discrete and composite samples. The number of days with benthic-invertebrate PTI ≥0.1 in daily composite samples was inversely related to Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness at the sites. The results of the study indicate that short-term, potentially toxic peaks in pesticides frequently are missed by weekly discrete sampling, and that such peaks may contribute to degradation of invertebrate community condition in small streams. Weekly composite samples underestimated maximum concentrations and potential acute-invertebrate toxicity, but to a lesser degree than weekly discrete samples, and provided a reasonable approximation of the 90th percentile total concentrations of herbicides, insecticides, and fungicides, suggesting that weekly composite sampling may be a compromise between assessment needs and cost.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.136795","usgsCitation":"Norman, J.E., Mahler, B., Nowell, L.H., Van Metre, P.C., Sandstrom, M.W., Corbin, M.A., Qian, Y., Pankow, J.F., Luo, W., Fitzgerald, N.B., Asher, W.E., and McWhirter, K.J., 2020, Daily stream samples reveal highly complex pesticide occurrence and potential toxicity to aquatic life: Science of the Total Environment, v. 715, 136795, 13 p., https://doi.org/10.1016/j.scitotenv.2020.136795.","productDescription":"136795, 13 p.","ipdsId":"IP-101574","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"links":[{"id":458098,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.136795","text":"Publisher Index Page"},{"id":437156,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N2A3LS","text":"USGS data release","linkHelpText":"Pesticides in Daily and Weekly Water Samples from the NAWQA Midwest and Southeast Stream Quality Assessments (2013-2014)"},{"id":371960,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ja/70208295/coverthb.jpg"}],"volume":"715","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Julia E. 0000-0002-2820-6225 jnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-2820-6225","contributorId":3832,"corporation":false,"usgs":true,"family":"Norman","given":"Julia","email":"jnorman@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":781299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":781297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":781298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sandstrom, Mark W. 0000-0003-0006-5675 sandstro@usgs.gov","orcid":"https://orcid.org/0000-0003-0006-5675","contributorId":706,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Mark","email":"sandstro@usgs.gov","middleInitial":"W.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":true,"id":781306,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corbin, Mark A.","contributorId":222126,"corporation":false,"usgs":false,"family":"Corbin","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":781300,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Qian, Yaorong","contributorId":176739,"corporation":false,"usgs":false,"family":"Qian","given":"Yaorong","email":"","affiliations":[],"preferred":false,"id":781301,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pankow, James F. 0000-0002-8602-9159","orcid":"https://orcid.org/0000-0002-8602-9159","contributorId":222127,"corporation":false,"usgs":false,"family":"Pankow","given":"James","email":"","middleInitial":"F.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":781302,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Luo, Wentai 0000-0003-3421-4958","orcid":"https://orcid.org/0000-0003-3421-4958","contributorId":222128,"corporation":false,"usgs":false,"family":"Luo","given":"Wentai","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":781303,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fitzgerald, Nicholas B.","contributorId":222131,"corporation":false,"usgs":false,"family":"Fitzgerald","given":"Nicholas","email":"","middleInitial":"B.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":781307,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Asher, William E.","contributorId":222129,"corporation":false,"usgs":false,"family":"Asher","given":"William","email":"","middleInitial":"E.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":781304,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McWhirter, Kevin J.","contributorId":222130,"corporation":false,"usgs":false,"family":"McWhirter","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":781305,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70229397,"text":"70229397 - 2020 - Effect of environmental factors on the movement of Rainbow Trout in the Deerfield Reservoir System","interactions":[],"lastModifiedDate":"2022-03-11T17:11:48.638861","indexId":"70229397","displayToPublicDate":"2020-01-18T09:49:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10384,"text":"Journal of FisheriesSciences.com","active":true,"publicationSubtype":{"id":10}},"title":"Effect of environmental factors on the movement of Rainbow Trout in the Deerfield Reservoir System","docAbstract":"

Spawning movements and the factors affecting those movements are often of interest to fisheries managers and biologists. The objective of this study was to examine the influence of environmental factors on the movements of an adfluvial Rainbow Trout Oncorhynchus mykiss population in the Black Hills, South Dakota. Three unique strains of hatchery-reared Rainbow Trout and resident Rainbow Trout were implanted with passive integrated transponder (PIT) tags and movements between Deerfield Reservoir and the Castle Creek tributary system were monitored from August, 2010-July, 2011. Initial adfluvial movements of Rainbow Trout were detected using a stationary PIT tag reader deployed near the mouth of Castle Creek. Multiple linear regressions were used to model the relationship between PIT tagged Rainbow Trout movement and water temperature, photoperiod, and discharge. Using Akaike’s information criterion (AIC) to compare models, discharge was the top supported model explaining variation in Rainbow Trout movement. Additionally, models containing temperature and photoperiod were also supported. Supported models only explained moderate levels of variation (<23%) in Rainbow Trout movement. Understanding how environmental variables affect the movement patterns of this unique population is essential in determining the proper management strategy for the Deerfield Reservoir system.

","language":"English","publisher":"IMed Pub LTD","usgsCitation":"Kientz, J., Davis, J., Chipps, S.R., and Simpson, G., 2020, Effect of environmental factors on the movement of Rainbow Trout in the Deerfield Reservoir System: Journal of FisheriesSciences.com, v. 14, no. 1, p. 1-6.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-124673","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":397026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397024,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fisheriessciences.com/fisheries-aqua/effect-of-environmental-factors-on-the-movement-of-rainbow-trout-in-the-deerfield-reservoir-system.php?aid=26132"}],"country":"United States","state":"South Dakota","otherGeospatial":"Castle Creek, Deerfield Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.8398551940918,\n 44.00158219755276\n ],\n [\n -103.8017463684082,\n 44.00158219755276\n ],\n [\n -103.8017463684082,\n 44.02726038819847\n ],\n [\n -103.8398551940918,\n 44.02726038819847\n ],\n [\n -103.8398551940918,\n 44.00158219755276\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kientz, Jeremy","contributorId":205425,"corporation":false,"usgs":false,"family":"Kientz","given":"Jeremy","email":"","affiliations":[{"id":37104,"text":"South Dakota Department of Game, Fish and Parks","active":true,"usgs":false}],"preferred":false,"id":837832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Jacob L.","contributorId":275831,"corporation":false,"usgs":false,"family":"Davis","given":"Jacob L.","affiliations":[{"id":56698,"text":"South Dakota Department of Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":837833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":837273,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simpson, Gregory","contributorId":288393,"corporation":false,"usgs":false,"family":"Simpson","given":"Gregory","email":"","affiliations":[{"id":56698,"text":"South Dakota Department of Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":837834,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207892,"text":"sim3449 - 2020 - High-resolution airborne geophysical survey of the Shellmound, Mississippi area","interactions":[],"lastModifiedDate":"2022-04-22T20:07:01.788312","indexId":"sim3449","displayToPublicDate":"2020-01-17T16:20:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3449","displayTitle":"High-Resolution Airborne Geophysical Survey of the Shellmound, Mississippi Area","title":"High-resolution airborne geophysical survey of the Shellmound, Mississippi area","docAbstract":"

In late February to early March 2018, the U.S. Geological Survey acquired 2,364 line-kilometers (km) of airborne electromagnetic, magnetic, and radiometric data in the Shellmound, Mississippi study area. The purpose of this survey is to contribute high-resolution information about subsurface geologic structure to inform groundwater models, water resource infrastructure studies, and local decision making. The Shellmound region hosts a managed aquifer recharge (MAR) pilot project, developed by the Agricultural Research Service of the U.S. Department of Agriculture. The MAR pilot project is investigating the use of bank filtration along the Tallahatchie River as a source for recharge in areas of significant groundwater decline. Direct injection into the Mississippi River Valley Alluvial aquifer (MRVA) occurs about 3 km from the extraction gallery. Understanding the structure of the aquifer, including both shallow and deep confining units, is important for the success of this pilot MAR study and may be even more important for potential future large-scale MAR projects and groundwater model development efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3449","usgsCitation":"Burton, B.L., Minsley, B.J., Bloss, B.R., Kress, W.H., Rigby, J.R., and Smith, B.D., 2020, High-resolution airborne geophysical survey of the Shellmound, Mississippi area: U.S. Geological Survey Scientific Investigations Map 3449, 2 sheets, https://doi.org/10.3133/sim3449.","productDescription":"2 Sheets: 28.09 x 21.01 inches and 29.96 x 24.19 inches; Data Release; ReadMe","onlineOnly":"Y","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":399521,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109607.htm"},{"id":371340,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D4EA9W","text":"USGS data release","linkHelpText":"Airborne electromagnetic, magnetic, and radiometric survey, Shellmound, Mississippi, March 2018"},{"id":371339,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3449/sim3449_ReadMe.txt","text":"Read Me","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3449 Read Me"},{"id":371338,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3449/sim3449_sheet2.pdf","text":"Sheet 2—","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3449 Sheet 2","linkHelpText":"High-Resolution Airborne Geophysical Survey of the Shellmound, Mississippi Area"},{"id":371337,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3449/sim3449_sheet1.pdf","text":"Sheet 1—","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3449 Sheet 1","linkHelpText":"High-Resolution Airborne Geophysical Survey of the Shellmound, Mississippi Area"},{"id":371336,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3449/coverthb.jpg"}],"country":"United States","state":"Mississippi","county":"Leflore County","city":"Shellmound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.5333,\n 33.5242\n ],\n [\n -90.1628,\n 33.5242\n ],\n [\n -90.1628,\n 33.8\n ],\n [\n -90.5333,\n 33.8\n ],\n [\n -90.5333,\n 33.5242\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS-973
Denver, CO 80225-0046

","publishedDate":"2020-01-17","noUsgsAuthors":false,"publicationDate":"2020-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Burton, Bethany L. 0000-0001-5011-7862 blburton@usgs.gov","orcid":"https://orcid.org/0000-0001-5011-7862","contributorId":1341,"corporation":false,"usgs":true,"family":"Burton","given":"Bethany L.","email":"blburton@usgs.gov","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":779674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":779675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bloss, Benjamin R. 0000-0002-1678-8571 bbloss@usgs.gov","orcid":"https://orcid.org/0000-0002-1678-8571","contributorId":139981,"corporation":false,"usgs":true,"family":"Bloss","given":"Benjamin","email":"bbloss@usgs.gov","middleInitial":"R.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":779676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kress, Wade H. 0000-0002-6833-028X wkress@usgs.gov","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":1576,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","email":"wkress@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":779677,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rigby, James R. 0000-0002-5611-6307","orcid":"https://orcid.org/0000-0002-5611-6307","contributorId":196374,"corporation":false,"usgs":false,"family":"Rigby","given":"James R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":false,"id":779678,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Bruce D. 0000-0002-1643-2997 bsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":845,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","email":"bsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":779679,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211834,"text":"70211834 - 2020 - Using thermal infrared cameras to detect avian chicks at various distances and vegetative coverages","interactions":[],"lastModifiedDate":"2020-08-07T21:18:11.562582","indexId":"70211834","displayToPublicDate":"2020-01-16T16:15:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Using thermal infrared cameras to detect avian chicks at various distances and vegetative coverages","docAbstract":"

Population monitoring of nesting waterbirds often involves frequent entries into the colony, but alternative methods such as local remotely sensed thermal imaging may help reduce disturbance while providing a cost-effective way to survey breeding populations. Such an approach can have high initial costs, however, which may have reduced the number of studies investigating functionality of paired thermal infrared camera and small unmanned aerial systems. Here, we take the first step of exploring the ability of two thermal infrared cameras to detect an avian chick under varying vegetative cover and distances, preceding field-mounting applications on a small unmanned aerial system. We created seven “bioboxes” to simulate a range of natural vegetation types and densities for a globally important colonial ground-nesting waterbird species, the common tern Sterna hirundo. We placed a juvenile chicken Gallus gallus (surrogate for the locally endangered common tern) in each box, and we tested two market-accessible infrared cameras (produced by FLIR Systems and Infrared Cameras, Inc.) at five elevations using a stationary boom (maximum height = 12 m). We applied computer-based digital thresholding to collected images, identifying pixels meeting one of seven threshold values. The chick was visible from at least one threshold value in 19 and 31 of 35 processed by the FLIR Systems and Infrared Cameras, respectively. Percentage of the chick identified across thresholds was generally highest at lower threshold values and elevations and decreased as elevation and threshold increased; however, the relative importance of each variable changed dramatically across bioboxes and camera types. Ability to detect a chick from processed images generally decreased with increasing elevation, and although we made no quantitative comparisons among boxes, detectability appeared greatest in images from both cameras when little or no vegetation was present. Interestingly, no single threshold value was best for all bioboxes. We observed notable differences between cameras including visual resolution of detected temperature differentials and image processing speed. Results of this controlled study show promise for the use of thermal infrared systems for detecting cryptic species in vegetation. Future research should work to combine thermal infrared and visual sensors with small unmanned aerial systems to test applicability in a mobile field application.

","language":"English","publisher":"Fish and Wildlife Management","doi":"10.3996/072019-JFWM-062","usgsCitation":"Prosser, D., Collier, T., Sullivan, J.D., Dale, K.E., Callahan, C.R., McGowan, P.C., Gaylord, E., Geschke, J.M., Howell, L., Marban, P., and Raman, S., 2020, Using thermal infrared cameras to detect avian chicks at various distances and vegetative coverages: Journal of Fish and Wildlife Management, v. 11, no. 1, p. 245-257, https://doi.org/10.3996/072019-JFWM-062.","productDescription":"13 p.","startPage":"245","endPage":"257","ipdsId":"IP-077752","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458106,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/072019-jfwm-062","text":"Publisher Index Page"},{"id":437159,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97UT9B7","text":"USGS data release","linkHelpText":"Using Thermal Infrared Cameras to Detect Avian Chicks at Various Distances and Vegetative Coverages"},{"id":377208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collier, Tom","contributorId":208436,"corporation":false,"usgs":false,"family":"Collier","given":"Tom","email":"","affiliations":[{"id":37801,"text":"UASbio","active":true,"usgs":false}],"preferred":false,"id":795296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Jeffery D.","contributorId":202910,"corporation":false,"usgs":false,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":795297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dale, Katherine Emily 0000-0002-8544-1571","orcid":"https://orcid.org/0000-0002-8544-1571","contributorId":237786,"corporation":false,"usgs":true,"family":"Dale","given":"Katherine","email":"","middleInitial":"Emily","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":795299,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":795300,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gaylord, Edward","contributorId":237787,"corporation":false,"usgs":false,"family":"Gaylord","given":"Edward","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":795301,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Geschke, Julia M.","contributorId":237788,"corporation":false,"usgs":false,"family":"Geschke","given":"Julia","email":"","middleInitial":"M.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":795302,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Howell, Lucas","contributorId":237789,"corporation":false,"usgs":false,"family":"Howell","given":"Lucas","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":795303,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Marban, Paul R.","contributorId":221168,"corporation":false,"usgs":false,"family":"Marban","given":"Paul R.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":795304,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Raman, Saba","contributorId":237790,"corporation":false,"usgs":false,"family":"Raman","given":"Saba","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":795305,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70207314,"text":"sir20195137 - 2020 - Precipitation, temperature, groundwater-level elevation, streamflow, and potential flood storage trends within the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River basins in Texas through 2017","interactions":[],"lastModifiedDate":"2022-04-25T19:47:32.575058","indexId":"sir20195137","displayToPublicDate":"2020-01-16T15:40:00","publicationYear":"2020","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":"2019-5137","displayTitle":"Precipitation, Temperature, Groundwater-Level Elevation, Streamflow, and Potential Flood Storage Trends Within the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins in Texas Through 2017","title":"Precipitation, temperature, groundwater-level elevation, streamflow, and potential flood storage trends within the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River basins in Texas through 2017","docAbstract":"

The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers (USACE), analyzed streamflow trends and streamflow-related variables through 2017 in seven important water-supply basins to provide information that can help water managers with the USACE and river authorities make future water management decisions. The primary purpose of this report is to document trends in long-term streamflow data at 114 selected USGS streamflow-gaging stations and 36 simulated reservoir-inflow stations in 7 river basins primarily in Texas: Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity. In this report, trends were considered statistically significant if their p-values were less than or equal to 0.05 (p-value ≤0.05). Streamflow data selected for temporal trend analyses included annual minimum streamflow, annual peak streamflow, and streamflow volume. Precipitation, air temperature, and groundwater-level-elevation data were analyzed for trends that may help to explain changes observed in the streamflow statistics. Basins were divided into sections along county lines for precipitation analyses. Streamflow volumes were analyzed for associations with potential flood storage. The potential flood storage, defined as the difference between maximum storage and normal storage, was computed for each dam from the National Inventory of Dams database and accumulated over time based on the completion date of the dam.

Precipitation and air temperature trends were analyzed for each of the eight climate divisions (High Plains, Trans-Pecos, Low Rolling Hills, Edwards Plateau, North Central Texas, South Central Texas, East Texas, and Upper Coast). Results of precipitation trend analyses indicated moderate upward trends in the Upper Coast and East Texas Climate Divisions analyzed on an annual time step from 1900 through 2017. These two climate divisions are in the eastern and southeastern parts of the State, and they receive more mean annual precipitation (45.88 and 46.09 inches, respectively) than the other climate divisions. The results of air temperature analyses indicated upward trends in annual mean air temperature within all climate divisions, with a mean slope of 0.02 degree Fahrenheit per year, or 1 degree every 50 years.

Within the Brazos River Basin, results of precipitation trend analyses on an annual time step indicated that precipitation amounts are most likely increasing in the lower and middle sections of the basin. Downward trends in annual streamflow and in the ratio of streamflow volume to precipitation volume were indicated at 7 of the 15 stations in the upper sections of the basin. The lower sections of the basin had mostly downward trends in annual minimum streamflow, whereas upward trends in annual minimum streamflow were indicated in the upper sections of the basin. Downward trends in annual peak streamflow were indicated at many of the stations in the upper sections of the basin. At the same seven stations in the upper sections of the basin where there were downward trends in annual streamflow, there were also downward trends in the ratio of streamflow volume to precipitation volume. The data from the same seven stations indicated negative associations between potential flood storage volume and annual streamflow volume and downward trends in the ratio of annual streamflow volume to potential flood storage volume. With the known addition of 13,006,394 acre-feet of potential flood storage between 1900 and 2010 in the subbasins analyzed, streamflow volumes have decreased in the upper sections of the Brazos River Basin.

Within the Colorado River Basin, results of precipitation trend analyses on an annual time step indicated no trends in the basin. Downward trends in annual streamflow were indicated at 16 stations in the upper sections of the basin, whereas no trends in annual streamflow were indicated in the lower section of the basin. In the lower section of the basin, one station that was operated as a continuous streamflow-gaging station through 2017 had a downward trend in annual minimum streamflow, and another station (operated through 2007) had an upward trend in annual minimum streamflow. In the upper sections of the basin, data from seven stations indicated upward trends in annual minimum streamflow, and data from six stations indicated downward trends. Data from 18 stations in the upper sections of the basin indicated downward trends in annual peak streamflow. Thirteen of the 16 stations in the upper sections of the basin with data that indicated downward trends in annual streamflow also have data that indicated downward trends in the ratio of streamflow volume to precipitation volume. Data from the same 13 stations indicated negative associations between potential flood storage volume and annual streamflow volume and downward trends in the ratio of annual streamflow volume to potential flood storage volume. With the known addition of 7,193,147 acre-feet of potential flood storage between 1891 and 2014 in the subbasins analyzed, streamflow volumes have decreased in the upper sections of the Colorado River Basin.

Within the Big Cypress Basin, results of precipitation trend analyses on annual, seasonal, and monthly time steps indicated almost no trends in the basin as defined in this report. However, the annual precipitation p-value only slightly exceeded the p-value threshold for a statistically significant trend. Given the upward trend in precipitation in the East Texas Climate Division, which includes the Big Cypress Basin, and the low p-value for annual precipitation within the basin, precipitation in the basin may be increasing over time. Two annual streamflow trends, one upward and one downward, were in the upper parts of the basin. Data from USGS streamflow-gaging station 07346000 Big Cypress Bayou near Jefferson, Texas, indicated an upward trend in annual minimum streamflow and a downward trend in annual peak streamflow. The station is immediately downstream from Lake O’ the Pines; presumably, minimums have increased because of regulated releases, and annual peaks have decreased because of storage from the lake for flood control. Despite the known addition of 2,737,154 acre-feet of potential flood storage between 1898 and 2011 in the subbasins analyzed, there have not been widespread reductions in streamflow volumes in the Big Cypress Basin, except for within the drainage area for the farthest upstream station on the main stem downstream from Mount Pleasant, Texas.

Within the Guadalupe River Basin, results of precipitation trend analyses on an annual time step indicated an upward trend in the lower section of the basin, but no trends in annual streamflow were indicated in the lower section of the basin. In the upper section of the basin, data from 1 of the 13 stations indicated an upward trend in annual streamflow. Data from 6 of the 13 stations in the upper section of the basin indicated a trend in annual minimum streamflow with 4 upward and 2 downward trends. Data from 2 of the 13 stations in the upper section of the basin indicated downward trends in annual peak streamflow. Despite the known addition of 2,016,534 acre-feet of potential flood storage between 1849 and 2013 in the subbasins analyzed, streamflow volumes have not decreased in the Guadalupe River Basin.

Within the Neches River Basin, results of precipitation trend analyses on an annual time step indicated upward trends in the basin. None of the data from stations analyzed in the Neches River Basin indicated annual trends in streamflow despite upward trends in annual precipitation within the basin. Data from 9 of the 19 stations analyzed in the basin indicated upward trends in annual minimum streamflow. Data from one of the simulated-inflow stations indicated a downward trend in annual minimum streamflow into Sam Rayburn Reservoir. Data from two stations indicated downward trends in annual peak streamflow, and data from one small subbasin indicated an upward trend in annual peak streamflow. Despite the known addition of 4,839,609 acre-feet of potential flood storage between 1888 and 2008 in the subbasins analyzed, there have not been widespread reductions in streamflow volumes in the Neches River Basin.

Within the Sulphur River Basin, results of precipitation trend analyses on an annual time step indicated a moderate upward trend within the basin. Data from only one of the stations, the simulated inflow to Jim Chapman Lake, indicated an annual upward trend in streamflow despite an upward trend in annual precipitation throughout the basin. Data from three of the six stations in the Sulphur River Basin indicated upward trends in annual minimum streamflow, and data from one of the six stations indicated a downward trend in annual peak streamflow. Despite the known addition of 6,933,361 acre-feet of potential flood storage between 1904 and 2006 in the subbasins analyzed, streamflow volumes have not decreased in the Sulphur River Basin.

Within the Trinity River Basin, results of precipitation trend analyses on an annual time step indicated upward trends in most sections of the basin. Data from 8 of the 36 stations analyzed for trends in annual streamflow indicated upward trends, and all 8 stations are in the upper sections of the basin. None of the data from stations in the lower sections of the basin indicated trends in annual streamflow. Data from 16 of the 36 stations indicated upward trends in annual minimum streamflow. Upward trends in annual minimum streamflow could be the result of managed reservoir releases in combination with wastewater treatment plant releases in the large Dallas-Fort Worth metroplex in the upper sections of the basin. All the trends in annual peak streamflow were in the sections of the basin that include the Dallas-Fort Worth metroplex. Data from two stations, one USGS streamflow-gaging station and one simulated-inflow station, indicated upward trends in annual peak streamflow, and data from one streamflow-gaging station indicated a downward trend in annual peak streamflow. Of the basins included in this study, the Trinity River Basin has the second largest amount of potential flood storage of 8,947,349 acre-feet from dams added between 1890 and 2013. Eleven stations in the Trinity River Basin had positive associations between potential flood storage volume and annual streamflow volume, indicating that annual streamflow increases as potential flood storage increases. Data from 7 of the 11 stations also indicated upward trends in annual streamflow. The positive associations may be the result of increases in minimum streamflow, which could be the result of any combination of managed reservoir releases, wastewater treatment plant releases, or increased runoff from urbanized areas, particularly in the urbanized area of the Dallas-Fort Worth metroplex.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195137","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Fort Worth District","usgsCitation":"Harwell, G.R., McDowell, J.S., Gunn, C.L., and Garrett, B.S., 2020, Precipitation, temperature, groundwater-level elevation, streamflow, and potential flood storage trends within the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River basins in Texas through 2017 (ver. 1.1, April 2020): U.S. Geological Survey Scientific Investigations Report 2019–5137, 94 p., https://doi.org/10.3133/sir20195137.","productDescription":"Report: x, 94 p.; 5 Tables; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102896","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":399613,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109606.htm"},{"id":374071,"rank":9,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5137/coverthb2.jpg"},{"id":373986,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5137/versionHist.txt","text":"Version History","size":"1.35 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2019–5137 Version History"},{"id":371261,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table9.xlsx","text":"Table 9—","size":"120 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 9","linkHelpText":"Summary of annual, seasonal, and monthly trends in the ratio of streamflow volume to precipitation volume in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371258,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table7.xlsx","text":"Table 7—","size":"64 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 7","linkHelpText":"Summary of precipitation temporal trends around the time of annual peak streamflow in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371255,"rank":2,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table5.xlsx","text":"Table 5—","size":"80 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 5","linkHelpText":"Summary of annual, seasonal, and monthly associations between precipitation volume and streamflow volume in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371252,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L1F7PT","text":"USGS data release","description":"USGS data release","linkHelpText":"Data used to assess precipitation, temperature, groundwater-level elevation, streamflow, and potential flood storage trends within the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins in Texas through 2017"},{"id":373985,"rank":7,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_v1.1.pdf","text":"Report","size":"20.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5137"},{"id":371259,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table8.xlsx","text":"Table 8—","size":"144 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 8","linkHelpText":"Summary of annual, seasonal, and monthly streamflow volume trends in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371262,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table10.xlsx","text":"Table 10—","size":"48 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 10","linkHelpText":"Summary of trends in annual minimum streamflow and annual peak streamflow and relations between streamflow volume and potential flood storage volume in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"}],"country":"United States","state":"Texas","otherGeospatial":"Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.4667,\n 28.4167\n ],\n [\n -93.0619,\n 28.4167\n ],\n [\n -93.0619,\n 33.6667\n ],\n [\n -101.4667,\n 33.6667\n ],\n [\n -101.4667,\n 28.4167\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: January 2020; Version 1.1: April 2020","contact":"

Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-01-16","revisedDate":"2020-04-16","noUsgsAuthors":false,"publicationDate":"2020-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Harwell, Glenn R. 0000-0003-4265-2296","orcid":"https://orcid.org/0000-0003-4265-2296","contributorId":221295,"corporation":false,"usgs":true,"family":"Harwell","given":"Glenn R.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDowell, Jeremy 0000-0002-8132-9806","orcid":"https://orcid.org/0000-0002-8132-9806","contributorId":221296,"corporation":false,"usgs":true,"family":"McDowell","given":"Jeremy","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gunn-Rosas, Cathina 0000-0002-6633-3735","orcid":"https://orcid.org/0000-0002-6633-3735","contributorId":221298,"corporation":false,"usgs":true,"family":"Gunn-Rosas","given":"Cathina","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garrett, Brett 0000-0003-0132-2426","orcid":"https://orcid.org/0000-0003-0132-2426","contributorId":221297,"corporation":false,"usgs":true,"family":"Garrett","given":"Brett","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777675,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207395,"text":"sir20195140 - 2020 - Seepage investigation of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above El Paso, Texas, 2018","interactions":[],"lastModifiedDate":"2020-01-17T06:36:51","indexId":"sir20195140","displayToPublicDate":"2020-01-16T15:00:00","publicationYear":"2020","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":"2019-5140","displayTitle":"Seepage Investigation of the Rio Grande From Below Leasburg Dam, Leasburg, New Mexico, to Above El Paso, Texas, 2018","title":"Seepage investigation of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above El Paso, Texas, 2018","docAbstract":"

Seepage investigations were conducted periodically by the U.S. Geological Survey (USGS) from 1988 to 1998 and from 2006 to 2015 along a 64-mile reach of the Rio Grande as part of the Mesilla Basin monitoring program. Past studies were conducted during no-flow or low-flow periods. In 2018, a seepage investigation was conducted during April 3–4 along a 62.4-mile study reach, from below Leasburg Dam, Leasburg, New Mexico, to above El Paso, Texas, during a period of high flows due to dam releases of water for irrigation purposes. During this investigation, there was measurable streamflow at 31 of the 41 measurement locations: 22 river sites, 8 inflow sites, and 1 outflow site. Results of the 2018 high-flow seepage investigation are presented in this report.

Net seepage gain or loss was computed for each subreach (the interval between two adjacent measurement locations along the river) by subtracting the streamflow measured at the upstream location from the streamflow measured at the closest downstream location and then subtracting any inflow to the river within the subreach. An estimated gain or loss was determined to be meaningful if it exceeded the cumulative measurement uncertainty associated with the net seepage computation. During this investigation, streamflow on the main stem of the Rio Grande ranged from 577 to 1,000 cubic feet per second (ft3/s). Nine subreaches were found to have meaningful net seepage gain or loss, four gaining subreaches and five losing subreaches. Because of high cumulative uncertainty (plus or minus 111.3 ft3/s) relative to the calculated cumulative loss (−57.7 ft3/s) over the entire study reach, no meaningful gain or loss was determined in this study. Like all of the previous USGS seepage studies on this reach of the Rio Grande, this study reported a net seepage loss, and the magnitude of that loss was within the range of historical values.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195140","collaboration":"Prepared in cooperation with the Bureau of Reclamation, New Mexico Office of the State Engineer, City of Las Cruces Utilities, New Mexico Interstate Stream Commission, New Mexico State University, and the Elephant Butte Irrigation District","usgsCitation":"Ball, G.P., Robertson, A.J., and Medina Morales, K., 2020, Seepage investigation of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above El Paso, Texas, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5140, 16 p., https://doi.org/10.3133/sir20195140.","productDescription":"iv, 16 p.","onlineOnly":"Y","ipdsId":"IP-109490","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":371305,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5140/sir20195140.pdf","text":"Report","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5140"},{"id":371304,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5140/coverthb.jpg"}],"country":"United States","state":"Texas, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.787109375,\n 31.475524020001806\n ],\n [\n -105.71044921875,\n 31.175209828310845\n ],\n [\n -105.875244140625,\n 31.512995857454676\n ],\n [\n -106.69921875,\n 32.82421110161336\n ],\n [\n -106.44653320312499,\n 34.07996230865873\n ],\n [\n -107.127685546875,\n 34.1890858311724\n ],\n [\n -107.567138671875,\n 33.58716733904656\n ],\n [\n -107.611083984375,\n 33.091541548655215\n ],\n [\n -106.787109375,\n 31.475524020001806\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd.
Albuquerque, NM 87113

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-01-16","noUsgsAuthors":false,"publicationDate":"2020-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ball, Grady P. 0000-0003-3030-055X","orcid":"https://orcid.org/0000-0003-3030-055X","contributorId":221343,"corporation":false,"usgs":true,"family":"Ball","given":"Grady","email":"","middleInitial":"P.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Andrew J. 0000-0003-2130-0347 ajrobert@usgs.gov","orcid":"https://orcid.org/0000-0003-2130-0347","contributorId":4129,"corporation":false,"usgs":true,"family":"Robertson","given":"Andrew","email":"ajrobert@usgs.gov","middleInitial":"J.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morales, Karen Medina","contributorId":221344,"corporation":false,"usgs":false,"family":"Morales","given":"Karen","email":"","middleInitial":"Medina","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":777898,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228356,"text":"70228356 - 2020 - Use of underwater videography to quantify conditions utilized by endangered Moapa Dace While spawning","interactions":[],"lastModifiedDate":"2022-02-09T18:06:42.187099","indexId":"70228356","displayToPublicDate":"2020-01-16T11:58:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Use of underwater videography to quantify conditions utilized by endangered Moapa Dace While spawning","docAbstract":"

Advances in underwater camera technology provide an affordable means to quantify the environmental conditions under which fish spawn. This information is important for investigating spawning ecology, managing habitat, or providing information for captive breeding programs. We deployed 12 modified security cameras underwater to identify environmental conditions related to the spawning behavior of the critically endangered Moapa Dace Moapa coriacea, a Mojave Desert stream-dwelling cyprinid that had never been observed spawning and that had fallen to a low of 459 individual fish 4 years prior to this study. Camera sites were selected systematically along the stream to represent the variety of conditions available. We divided the field of view in front of each camera into a grid, and we estimated both the available environment and the habitat over which Moapa Dace showed spawning behavior. From over 4,000 10-min video clips that were randomly selected for analysis, 13 spawning events were identified. Using nonparametric contingency table analyses, we found that Moapa Dace selected depths between 30 and 34 cm, water velocities between 0.11 and 0.17 m/s, cobble substrate, and overhead instream cover. Although the recorded sample size of spawning events was small (13), our sample represents a large proportion of events given that the world's entire population of Moapa Dace at the time was approximately 650 fish distributed over multiple kilometers of stream length. Environmental conditions identified by this study were replicated in laboratory facilities to successfully propagate Moapa Dace for the first time in captivity. These propagation methods are now used in a management setting by the Nevada Department of Wildlife to maintain a captive population of this rare fish. Camera methods can be effective in helping to identify spawning conditions where water clarity is sufficient.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10356","usgsCitation":"Ruggirello, J.E., Bonar, S.A., Feuerbacher, O.G., and Simons, L.H., 2020, Use of underwater videography to quantify conditions utilized by endangered Moapa Dace While spawning: North American Journal of Fisheries Management, v. 40, no. 1, p. 17-28, https://doi.org/10.1002/nafm.10356.","productDescription":"12 p.","startPage":"17","endPage":"28","ipdsId":"IP-110930","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Plumer Stream, Warm Springs area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.74601745605469,\n 36.696502641380036\n ],\n [\n -114.66361999511719,\n 36.696502641380036\n ],\n [\n -114.66361999511719,\n 36.74108512094412\n ],\n [\n -114.74601745605469,\n 36.74108512094412\n ],\n [\n -114.74601745605469,\n 36.696502641380036\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruggirello, Jack E.","contributorId":30526,"corporation":false,"usgs":true,"family":"Ruggirello","given":"Jack","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":833924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feuerbacher, Olin G.","contributorId":275282,"corporation":false,"usgs":false,"family":"Feuerbacher","given":"Olin","email":"","middleInitial":"G.","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":833925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simons, Lee H.","contributorId":264621,"corporation":false,"usgs":false,"family":"Simons","given":"Lee","email":"","middleInitial":"H.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":833926,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217320,"text":"70217320 - 2020 - Effects of elevated sea levels and waves on southern California estuaries during the 2015–2016 El Niño","interactions":[],"lastModifiedDate":"2021-01-18T13:14:55.631177","indexId":"70217320","displayToPublicDate":"2020-01-16T07:11:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Effects of elevated sea levels and waves on southern California estuaries during the 2015–2016 El Niño","docAbstract":"

The 2015–2016 El Niño provided insight into how low-inflow estuaries might respond to future climate regimes, including high sea levels and more intense waves. High waves and water levels coupled with low rainfall along the Southern California coastline provided the opportunity to examine how extreme ocean forcing impacts estuaries independently from fluvial events. From November 2015 to April 2016, water levels were measured in 13 Southern California estuaries, including both intermittently closed and perennially open estuaries with varying watershed size, urban development, and management practices. Elevated ocean water levels caused raised water levels and prolonged inundation in all of the estuaries studied. Water levels inside perennially open estuaries mirrored ocean water levels, while those inside intermittently closed estuaries (ICEs) exhibited enhanced higher-high water levels during large waves, and tides were truncated at low tides due to a wave-built sand sill at the mouth, resulting in elevated detided water levels. ICEs closed when sufficient wave-driven sand accretion formed a barrier berm across the mouth separating the estuary from the ocean, the height of which can be estimated using estuarine lower-low water levels. During the 2015–2016 El Niño, a greater number of Southern California ICEs closed than during a typical year and ICEs that close annually experienced longer than normal closures. Overall, sill accretion and wave exposure were important contributing factors to individual estuarine response to ocean conditions. Understanding how estuaries respond to increased sea levels and waves and the factors that influence closures will help managers develop appropriate adaptation strategies.

","language":"English","publisher":"Springer","doi":"10.1007/s12237-019-00676-1","usgsCitation":"Harvey, M., Giddings, S.N., Stein, E.D., Crooks, J.A., Whitcraft, C., Gallien, T.W., Largier, J.L., Tiefenthaler, L., Meltzer, H., Pawlak, G., Thorne, K., Johnston, K., Ambrose, R.F., Schroeter, S.C., Page, H.M., and Elwany, H., 2020, Effects of elevated sea levels and waves on southern California estuaries during the 2015–2016 El Niño: Estuaries and Coasts, v. 43, p. 256-271, https://doi.org/10.1007/s12237-019-00676-1.","productDescription":"16 p.","startPage":"256","endPage":"271","ipdsId":"IP-107281","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458116,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-019-00676-1","text":"Publisher Index 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-120.0750732421875,\n 34.79125047210742\n ],\n [\n -120.61889648437501,\n 34.52918706954935\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","noUsgsAuthors":false,"publicationDate":"2020-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Madeleine","contributorId":247782,"corporation":false,"usgs":false,"family":"Harvey","given":"Madeleine","email":"","affiliations":[{"id":38724,"text":"Scripps Institution of Oceanography, University of California San Diego","active":true,"usgs":false}],"preferred":false,"id":808342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Giddings, Sarah N","contributorId":247783,"corporation":false,"usgs":false,"family":"Giddings","given":"Sarah","email":"","middleInitial":"N","affiliations":[{"id":38724,"text":"Scripps Institution of Oceanography, University of California San Diego","active":true,"usgs":false}],"preferred":false,"id":808343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stein, Eric 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Center","active":true,"usgs":true}],"preferred":true,"id":808352,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Johnston, Karina","contributorId":247792,"corporation":false,"usgs":false,"family":"Johnston","given":"Karina","email":"","affiliations":[{"id":49654,"text":"The Bay Foundation","active":true,"usgs":false}],"preferred":false,"id":808353,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ambrose, Richard F.","contributorId":174708,"corporation":false,"usgs":false,"family":"Ambrose","given":"Richard","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":808354,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Schroeter, Stephen C","contributorId":247794,"corporation":false,"usgs":false,"family":"Schroeter","given":"Stephen","email":"","middleInitial":"C","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":808355,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Page, Henry M.","contributorId":219352,"corporation":false,"usgs":false,"family":"Page","given":"Henry","email":"","middleInitial":"M.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":808356,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Elwany, Hany","contributorId":247795,"corporation":false,"usgs":false,"family":"Elwany","given":"Hany","email":"","affiliations":[{"id":49656,"text":"Coastal Environments","active":true,"usgs":false}],"preferred":false,"id":808357,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70228899,"text":"70228899 - 2020 - An agricultural water use package for MODFLOW and GSFLOW","interactions":[],"lastModifiedDate":"2022-02-23T12:45:47.212533","indexId":"70228899","displayToPublicDate":"2020-01-16T06:43:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7599,"text":"Environmental Modeling and Software","active":true,"publicationSubtype":{"id":10}},"title":"An agricultural water use package for MODFLOW and GSFLOW","docAbstract":"

The Agricultural Water Use (AG) Package was developed for simulating demand-driven and supply-constrained agricultural water use in MODFLOW and GSFLOW models. The AG Package uses pre-existing hydrologic simulation provided by MODFLOW and GSFLOW. Three options are available for simulating water use for agriculture: (1) user-specified demands, (2) demands determined by a user-specified irrigation trigger value that is compared to the ratio of the simulated actual to potential evapotranspiration (ET), and (3) demands determined by minimizing the difference between potential and actual ET. The latter two approaches use energy and soil-water balance to determine crop-water demands. Irrigation withdrawals are diverted into canals and routed to fields using the MODFLOW SFR Package, or irrigation water is provided/supplemented by groundwater. Combined with MODFLOW or GSFLOW, the AG Package can simulate dynamic water use by agriculture in developed basins while providing flexibility to represent a range of irrigation practices.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2019.104617","usgsCitation":"Niswonger, R.G., 2020, An agricultural water use package for MODFLOW and GSFLOW: Environmental Modeling and Software, v. 125, 104617, 16 p., https://doi.org/10.1016/j.envsoft.2019.104617.","productDescription":"104617, 16 p.","ipdsId":"IP-109425","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":458119,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2019.104617","text":"Publisher Index Page"},{"id":396332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":197892,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":835828,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70207962,"text":"70207962 - 2020 - Extreme mortality and reproductive failure of common murres resulting from the northeast Pacific marine heatwave of 2014-2016","interactions":[],"lastModifiedDate":"2023-06-23T14:25:48.582192","indexId":"70207962","displayToPublicDate":"2020-01-15T13:49:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Extreme mortality and reproductive failure of common murres resulting from the northeast Pacific marine heatwave of 2014-2016","docAbstract":"

About 62,000 dead or dying common murres (Uria aalge), the trophically dominant fish-eating seabird of the North Pacific, washed ashore between summer 2015 and spring 2016 on beaches from California to Alaska. Most birds were severely emaciated and, so far, no evidence for anything other than starvation was found to explain this mass mortality. Three-quarters of murres were found in the Gulf of Alaska and the remainder along the West Coast. Studies show that only a fraction of birds that die at sea typically wash ashore, and we estimate that total mortality approached 1 million birds. About two-thirds of murres killed were adults, a substantial blow to breeding populations. Additionally, 22 complete reproductive failures were observed at multiple colonies region-wide during (2015) and after (2016–2017) the mass mortality event. Die-offs and breeding failures occur sporadically in murres, but the magnitude, duration and spatial extent of this die-off, associated with multi-colony and multi-year reproductive failures, is unprecedented and astonishing. These events co-occurred with the most powerful marine heatwave on record that persisted through 2014–2016 and created an enormous volume of ocean water (the “Blob”) from California to Alaska with temperatures that exceeded average by 2–3 standard deviations. Other studies indicate that this prolonged heatwave reduced phytoplankton biomass and restructured zooplankton communities in favor of lower-calorie species, while it simultaneously increased metabolically driven food demands of ectothermic forage fish. In response, forage fish quality and quantity diminished. Similarly, large ectothermic groundfish were thought to have increased their demand for forage fish, resulting in greater top-predator demands for diminished forage fish resources. We hypothesize that these bottom-up and top-down forces created an “ectothermic vise” on forage species leading to their system-wide scarcity and resulting in mass mortality of murres and many other fish, bird and mammal species in the region during 2014–2017.

","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0226087","usgsCitation":"Piatt, J.F., Parrish, J.K., Renner, H.M., Schoen, S.K., Jones, T., Arimitsu, M.L., Kuletz, K.J., Bodenstein, B., Garcia-Reyes, M., Duerr, R., Corcoran, R., Kaler, R., McChesney, G.J., Golightly, R.T., Coletti, H.A., Suryan, R., Burgess, H.K., Lindsey, J., Lindquist, K., Warzybok, P., Jahncke, J., Roletto, J., and Sydeman, W., 2020, Extreme mortality and reproductive failure of common murres resulting from the northeast Pacific marine heatwave of 2014-2016: PLoS ONE, no. 15, e0226087, 32 p.; Data release, https://doi.org/10.1371/journal.pone.0226087.","productDescription":"e0226087, 32 p.; Data release","ipdsId":"IP-102890","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":458122,"rank":4,"type":{"id":40,"text":"Open Access Publisher 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The San Antonio Reservoir is a large water storage facility in Alameda County, California, and is a major component of the Hetch Hetchy Regional Water System (RWS). The RWS is a water-supply system owned and operated by the San Francisco Public Utilities Commission (SFPUC) and provides water for about 2.7 million people in the San Francisco, Santa Clara, Alameda, and San Mateo Counties. The San Antonio Reservoir is one of two RWS reservoirs in Alameda County and the third largest of the RWS reservoirs in the San Francisco Bay Area. The reservoir was formed by the James H. Turner Dam, which was completed in 1965. At the time of construction, the reservoir was estimated to have 50,500 acre-feet (acre-ft) of storage capacity. That early estimate was based on a 1963 pre-construction topographic map, which was drawn from aerial photographs. The capacity of the reservoir was later surveyed in 1994 and 2000. These two later surveys did not include the upper 18 feet (ft) of the reservoir, which represents roughly 30 percent of the overall storage volume. To determine the storage capacity and provide updated stage-capacity curves up to the spillway, the U.S. Geological Survey, in cooperation with the SFPUC, surveyed the bathymetry and shoreline of the reservoir in April 2018.

The bathymetric survey was performed by making depth soundings using a boat-mounted, multibeam echosounder. At the time of the survey, the water level was between 13 and 14 ft below the spillway elevation. To measure capacity between the water line up to the spillway elevation, topography along most of the shoreline was surveyed from the boat using a terrestrial Light Detection and Ranging (LiDAR) scanner and in other areas by using ground-survey techniques. Location during bathymetric and topographic data collection was determined using a Global Navigation Satellite System-Real Time Network system. Vertical profiles of sound speed were collected periodically. The sound-speed profiles were used to spatially and temporally adjust the sound-speed calculations used to determine depth from the soundings. Approximately 125 kilometers (78 miles) of transects with a total of about 560 million depth soundings and topographic LiDAR points were collected (about 160 per square meter). In addition, approximately 500 topographic survey points were collected in shallow, wadable areas and on land near the upper reservoir area using a Global Navigation Satellite System receiver attached to a fixed length survey rod. Depth soundings, terrestrial LiDAR points, topographic survey points, and a digitized shoreline were merged and interpolated to generate a digital elevation model (DEM) of the reservoir. Gridded elevation data extracted from the DEM were then tabulated to determine total reservoir capacity and create reservoir stage-surface area and stage-storage capacity tables.

Results of the reservoir capacity analysis indicated that the reservoir has 53,266 (plus or minus 140) acre-ft of storage capacity, which is an increase of 2,766 acre-ft (or 5.5 percent) greater than the original 1965 estimate; the increase is likely due to improved survey methods. Also, at the time of this 2018 survey, Intake #1 (the lowest intake) was not in operation. Intake #1 is estimated to be buried approximately 10 ft below the bed, whereas Intake #2 is about 20 ft above the bed. There are five intakes at different elevation levels; however, when consecutive lower intakes become inoperable due to sedimentation, the live storage capacity (capacity available for use) is reduced. At the time of this survey, the remaining live storage (above Intake #2) was approximately 52,363 acre-ft.

The 2018 stage-capacity curve was compared to the original 1965 stage-capacity curve. Although overall, the changes indicate an increase in storage capacity, the change in volume at 372.7 ft North American Vertical Datum of 1988 (370 ft National Geodetic Vertical Datum of 1929, NGVD 29) shows a decrease of 733 acre-ft (the elevation of 370 ft NGVD 29 was used because it is the lowest elevation available for the 1965 stage-capacity curves). This finding agrees with the observed accumulation of sediment over Intake #1. That volume was converted to an annual sediment yield of 0.35 acre-ft per square mile (or 165 cubic meters per square kilometer), which is of the same order of magnitude as that found in other watersheds for the Coast Ranges in California. A decrease of 733 acre-ft between 1965 and 2018 thus represents a loss of 1.5 percent of the overall storage capacity in the reservoir. The updated stage-surface area and stage-capacity tables provided in this report and online (https://doi.org/10.5066/P9KC9DU8) can be used by the SFPUC to improve reservoir operations and serve as an accurate baseline to monitor bathymetric changes in the future.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195151","collaboration":"Prepared in cooperation with the San Francisco Public Utilities Commission","usgsCitation":"Marineau, M.D., Wright, S.A, and Lopez, J.V., 2020, Storage capacity and sedimentation characteristics of the San Antonio Reservoir, California, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5151, 34 p., https://doi.org/10.3133/sir20195151.","productDescription":"Report: vi, 34 p.; Data Release","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-105258","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":399623,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109595.htm"},{"id":371223,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KC9DU8","linkHelpText":"Bathymetry, Stage-Area, and Stage-Volume Tables for the San Antonio Reservoir, California, 2018"},{"id":371222,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5151/sir20195151.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5151"},{"id":371221,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5151/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Antonio Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.81846618652345,\n 37.596415965954684\n ],\n [\n -121.85348510742188,\n 37.57138553454929\n ],\n [\n -121.841983795166,\n 37.565262680889965\n ],\n [\n -121.8335723876953,\n 37.56186087804736\n ],\n [\n -121.82378768920898,\n 37.5711134184077\n ],\n [\n -121.81726455688477,\n 37.582541440297746\n ],\n [\n -121.80301666259766,\n 37.5814531328266\n ],\n [\n -121.80473327636719,\n 37.59083926161267\n ],\n [\n -121.81846618652345,\n 37.596415965954684\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"

","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2020-01-15","noUsgsAuthors":false,"publicationDate":"2020-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":779408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":779409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez, Joan V. 0000-0003-4477-7025 jvlopez@usgs.gov","orcid":"https://orcid.org/0000-0003-4477-7025","contributorId":221656,"corporation":false,"usgs":true,"family":"Lopez","given":"Joan","email":"jvlopez@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":779410,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224972,"text":"70224972 - 2020 - Estimation of nonlinear water-quality trends in high-frequency monitoring data","interactions":[],"lastModifiedDate":"2021-10-11T13:02:50.792784","indexId":"70224972","displayToPublicDate":"2020-01-15T07:58:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Estimation of nonlinear water-quality trends in high-frequency monitoring data","docAbstract":"

Recent advances in high-frequency water-quality sensors have enabled direct measurements of physical and chemical attributes in rivers and streams nearly continuously. Water-quality trends can be used to identify important watershed-scale changes driven by natural and anthropogenic influences. Statistical methods to estimate trends using high-frequency data are lacking. To address this gap, an evaluation of the generalized additive model (GAM) approach to test for trends in high-frequency data was conducted. Our proposed framework includes methods for handling serial correlation, trend estimation and slope-change detection, and trend interpretation at arithmetic scale for log-transformed variables. Water-temperature and turbidity data, representing two analytes with different temporal patterns, collected from the James River at Cartersville, Virginia, USA, were chosen for this analysis. Results indicated that the model, including flow, season, time covariates, and interaction between flow and season performed well for both analytes. The same model structure was applied to specific conductance data, collected from a small highly urbanized watershed, with satisfactory model performance. The water temperature GAM results indicated that the significant decreasing-then-increasing patterns after 2012 were mainly driven by air temperature changes. The turbidity trend was not significant over time. The specific conductance results showed a consistently upward trend over the last decade due to ever-increasing urbanization in the small watershed. This study suggests that the GAM method has great potential as a useful tool for trend analysis on high-frequency data, and for informing watershed managers of hydro-climatic and human influences on water quality by detecting crucial signal variation over time.

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Atmospheric dust can influence biogeochemical cycles, accelerate snowmelt, and affect air, water quality, and human health. Yet, the bulk of atmospherically transported material remains poorly quantified in terms of total mass fluxes and composition. This lack of information stems in part from the challenges associated with measuring dust deposition. Here we report on the design and efficacy of a new dry deposition sampler (Dry Deposition Sampling Unit (DSU)) and method that quantifies the gravitational flux of dust particles. The sampler can be used alone or within existing networks such as those employed by the National Atmospheric Deposition Program (NADP). Because the samplers are deployed sterile and the use of water to remove trapped dust is not required, this method allows for the recovery of unaltered dry material suitable for subsequent chemical and microbiological analyses. The samplers were tested in the laboratory and at 15 field sites in the western United States. With respect to material retention, sampler performance far exceeded commonly used methods. Retrieval efficiency was >97% in all trials and the sampler effectively preserved grain size distributions during wind exposure experiments. Field tests indicated favorable comparisons to dust-on-snow measurement across sites (r2 0.70, p < 0.05) and within sites to co-located aerosol data (r2 0.57–0.99, p < 0.05). The inclusion of dust deposition and composition monitoring into existing networks increases spatial and temporal understanding of the atmospheric transport on materials and substantively furthers knowledge of the effects of dust on terrestrial ecosystems and human exposure to dust and associated deleterious compounds.

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Network stakeholders often inquire about the importance of sites and their locations when discussing funding and monitoring design. Support vector machines (SVMs) can be useful by their assigning each monitoring site as either a support or nonsupport vector. A potentiometric surface was created from synthetic data and 800 random observation locations (sites) as an analog to a groundwater-level network. Using generalized additive models for potentiometric surface prediction, simulations show that a subsample of support vectors from the 800 sites will out perform random samples of sample size equaling the support vector count. Support vector percentages from simulation quantify the recurrence that SVMs assign each site as a support vector, and these percentages in turn measure site importance. An example application of support vector percentages identifies important monitoring sites needed to regionalize the 0.1 annual exceedance probability peak streamflow. The results indicate that 152 of 283 streamgages with support vector percentages equalling 100 percent have not operated since about 2000 and generally have much smaller drainage areas than the greater streamgage network in Texas. The drainage area disparity is an indication of historical imbalance in peak streamflow data acquisition from various stream sizes in Texas.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.124522","collaboration":"","usgsCitation":"Asquith, W.H., 2020, The use of support vectors from support vector machines for hydrometeorologic monitoring network analyses: Journal of Hydrology, v. 583, 124522, 10 p., https://doi.org/10.1016/j.jhydrol.2019.124522.","productDescription":"124522, 10 p.","ipdsId":"IP-104552","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":374045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"583","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787258,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70208149,"text":"70208149 - 2020 - Soil surface elevation dynamics in a mangrove-to-marsh ecotone characterized by vegetation shifts","interactions":[],"lastModifiedDate":"2020-02-25T08:17:01","indexId":"70208149","displayToPublicDate":"2020-01-13T17:56:17","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Soil surface elevation dynamics in a mangrove-to-marsh ecotone characterized by vegetation shifts","docAbstract":"Mangrove forest encroachment into coastal marsh habitats has been described in subtropical regions worldwide in recent decades. To better understand how soil processes may influence vegetation change, we studied soil surface elevation change, accretion rates, and soil subsurface change across a coastal salinity gradient in Florida, USA, an area with documented mangrove encroachment into saline marshes. Our aim was to identify if variations in the soil variables studied exist and to document any associated vegetation shifts. We used surface elevation tables and marker horizons to document the soil variables over 5 years in a mangrove-to-marsh transition zone or ecotone. Study sites were located in three marsh types (brackish, salt, and transition) and in riverine mangrove forests. Mangrove forest sites had significantly higher accretion rates than marsh sites and were the only locations where elevation gain occurred. Significant loss in surface elevation occurred at transition and salt marsh sites. Transition marshes, which had a significantly higher rate of shallow subsidence compared to other wetland types, appear to be most vulnerable to submergence or to a shift to mangrove forest. Submergence can result in herbaceous vegetation mortality and conversion to open water, with severe implications to the quantity and quality of wetland services provided.","language":"English","publisher":"Springer","doi":"10.1007/s10750-019-04170-4","usgsCitation":"Howard, R.J., From, A., Krauss, K.W., Andres, K.D., Cormier, N., Allain, L.K., and Savarese, M., 2020, Soil surface elevation dynamics in a mangrove-to-marsh ecotone characterized by vegetation shifts: Hydrobiologia, v. 847, p. 1087-1106, https://doi.org/10.1007/s10750-019-04170-4.","productDescription":"20 p.","startPage":"1087","endPage":"1106","ipdsId":"IP-098005","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":437162,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XZYJ2X","text":"USGS data release","linkHelpText":"Soil surface elevation dynamics in a mangrove-to-marsh ecotone characterized by vegetation shifts"},{"id":371740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Ten Thousand Islands National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.64421081542969,\n 25.99014369697799\n ],\n [\n -81.64627075195312,\n 25.978416223326267\n ],\n [\n -81.63528442382812,\n 25.97471256755186\n ],\n [\n -81.65382385253906,\n 25.919761316197402\n ],\n [\n -81.64833068847656,\n 25.884554354339247\n ],\n [\n -81.62910461425781,\n 25.888878582127084\n ],\n [\n -81.63116455078124,\n 25.904320959711665\n ],\n [\n -81.61331176757812,\n 25.903703303407667\n ],\n [\n -81.61674499511719,\n 25.890114046690094\n ],\n [\n -81.55357360839842,\n 25.890114046690094\n ],\n [\n -81.55082702636719,\n 25.80669119147928\n ],\n [\n 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]\n}","volume":"847","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Howard, Rebecca J. 0000-0001-7264-4364 howardr@usgs.gov","orcid":"https://orcid.org/0000-0001-7264-4364","contributorId":2429,"corporation":false,"usgs":true,"family":"Howard","given":"Rebecca","email":"howardr@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":780716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"From, Andrew 0000-0002-6543-2627 froma@usgs.gov","orcid":"https://orcid.org/0000-0002-6543-2627","contributorId":169668,"corporation":false,"usgs":true,"family":"From","given":"Andrew","email":"froma@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":780717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":780718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andres, Kimberly D.","contributorId":221924,"corporation":false,"usgs":false,"family":"Andres","given":"Kimberly","email":"","middleInitial":"D.","affiliations":[{"id":40458,"text":"Florida Gulf Coast University","active":true,"usgs":false}],"preferred":false,"id":780719,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cormier, Nicole 0000-0003-2453-9900 cormiern@usgs.gov","orcid":"https://orcid.org/0000-0003-2453-9900","contributorId":4262,"corporation":false,"usgs":true,"family":"Cormier","given":"Nicole","email":"cormiern@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":780720,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allain, Larry K. 0000-0002-7717-9761 allainl@usgs.gov","orcid":"https://orcid.org/0000-0002-7717-9761","contributorId":2414,"corporation":false,"usgs":true,"family":"Allain","given":"Larry","email":"allainl@usgs.gov","middleInitial":"K.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":780721,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Savarese, Michael","contributorId":221927,"corporation":false,"usgs":false,"family":"Savarese","given":"Michael","email":"","affiliations":[{"id":40458,"text":"Florida Gulf Coast University","active":true,"usgs":false}],"preferred":false,"id":780722,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70211824,"text":"70211824 - 2020 - Pulsed flow-through auto-feeding beaker systems for the laboratory culture of juvenile freshwater mussels","interactions":[],"lastModifiedDate":"2020-08-10T12:37:20.374625","indexId":"70211824","displayToPublicDate":"2020-01-13T17:06:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":853,"text":"Aquaculture","active":true,"publicationSubtype":{"id":10}},"title":"Pulsed flow-through auto-feeding beaker systems for the laboratory culture of juvenile freshwater mussels","docAbstract":"

Newly metamorphosed freshwater mussels are small and delicate, so that captive laboratory culture presents challenges for handling; for maintenance of suitable microhabitat, water quality, and food; and for avoidance of competitors and predators. To address these challenges, a new pulsed flow-through auto-feeding beaker system was developed for culturing juvenile mussels. In this system, groups of mussels were maintained in 300- to 1000-mL beakers with a thin layer of sand substrate. The water in the beakers was static except for pulses that were delivered every 1 or 2 h and that displaced about half of the water in each beaker per water cycle. A peristaltic pump delivered food to multiple mixing cells where the water was automatically mixed with food just before the water delivery. In testing this approach, newly metamorphosed mussels of 4 species were cultured in the system for 84 to 357 d. The sand and beakers were replaced weekly. Survival was high (>85% at day 84) for Lampsilis siliquoidea and Villosa iris, but relatively lower for Anodonta californiensis (29% at day 155) and Margaritifera falcata (23% at day 357). Growth rate ranged among the 4 species from 27 to 60 μm/d, with the slowest rate for M. falcata and fastest for A. californiensis. Overall, the new pulsed flow-through auto-feeding beaker system improved survival and growth of juvenile mussels versus other methods previously tested. Additionally, a simplified system for the water and food delivery was developed with a single mixing cell. The use of both systems indicate that they are suitable for laboratory experiments and for captive culture of juvenile mussels.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquaculture.2020.734959","usgsCitation":"Kunz, J.L., Brunson, E., Barnhart, M., Glidewell, E.A., Wang, N., and Ingersoll, C.G., 2020, Pulsed flow-through auto-feeding beaker systems for the laboratory culture of juvenile freshwater mussels: Aquaculture, v. 520, 734959, 8 p., https://doi.org/10.1016/j.aquaculture.2020.734959.","productDescription":"734959, 8 p.","ipdsId":"IP-113839","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":437163,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P989BFTB","text":"USGS data release","linkHelpText":"Survival and growth of juvenile freshwater mussels in a flow-through auto-feeding system"},{"id":377215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"520","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":795248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brunson, Eric 0000-0001-6624-0902","orcid":"https://orcid.org/0000-0001-6624-0902","contributorId":201761,"corporation":false,"usgs":true,"family":"Brunson","given":"Eric","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":795251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnhart, M. Christopher","contributorId":189301,"corporation":false,"usgs":false,"family":"Barnhart","given":"M. Christopher","affiliations":[],"preferred":false,"id":795250,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glidewell, Elizabeth A.","contributorId":189302,"corporation":false,"usgs":false,"family":"Glidewell","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":795252,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":795249,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":795253,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208025,"text":"70208025 - 2020 - A round-robin evaluation of the repeatability and reproducibility of environmental DNA assays for dreissenid mussels","interactions":[],"lastModifiedDate":"2020-10-28T15:09:08.954274","indexId":"70208025","displayToPublicDate":"2020-01-13T16:41:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"A round-robin evaluation of the repeatability and reproducibility of environmental DNA assays for dreissenid mussels","docAbstract":"

Resource managers may be hesitant to make decisions based on environmental (e)DNA results alone since eDNA is an indirect method of species detection. One way to reduce the uncertainty of eDNA is to identify laboratory‐based protocols that ensure repeatable and reproducible results. We conducted a double‐blind round‐robin analysis of probe‐based assays for DNA of dreissenid (Dreissena spp.) mussels, which are prolific aquatic invaders that can cause significant economic and ecological impacts. DNA extract from water samples spiked with known amounts of dreissenid DNA and from water samples collected from waters with and without dreissenids were analyzed by four independent research laboratories. We used results to calculate detection repeatability within laboratories and assays, detection reproducibility among laboratories and assays, and estimated dreissenid DNA copy number precision and accuracy. Laboratory and assay repeatability and reproducibility of detection results were high, 91% and 92%, respectively. The estimated copy numbers were neither precise nor accurate for samples spiked with <773 gene copies. These results suggest that eDNA surveillance of dreissenid mussels, using the protocols evaluated herein, can generate reliable detection data for decision‐making. However, managers should be cautious about using the quantitative information often associated with eDNA detections, especially when DNA is at lower abundance. Our results provide strong support that eDNA has the potential to provide repeatable and reproducible evidence under varying laboratory conditions and for different sample water chemistries. This is reassuring since the demand for eDNA surveillance is widespread and number of laboratories that process eDNA samples is growing steadily.

","language":"English","publisher":"Wiley","doi":"10.1002/edn3.68","usgsCitation":"Sepulveda, A.J., Hutchins, P.R., Jackson, C., Ostberg, C.O., Laramie, M., Amberg, J., Counihan, T., Hoegh, A.B., and Pilliod, D.S., 2020, A round-robin evaluation of the repeatability and reproducibility of environmental DNA assays for dreissenid mussels: Environmental DNA, v. 2, no. 4, p. 446-459, https://doi.org/10.1002/edn3.68.","productDescription":"14 p.","startPage":"446","endPage":"459","ipdsId":"IP-111602","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":458141,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.68","text":"Publisher Index Page"},{"id":437164,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NMZZNP","text":"USGS data release","linkHelpText":"PCR results from dreissenid mussel round robin assay analyses, 2018-2019"},{"id":371541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Montana, Nevada, New York, Oregon, Washington, Wisconsin, Wyoming","otherGeospatial":"Columbia River, Jackson Lake, Lake Mead, Lake Michigan, San Justo Reservoir, Seneca Lake, Yellowstone River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.6708984375,\n 42.16340342422401\n ],\n [\n -86.8359375,\n 42.16340342422401\n ],\n [\n -86.8359375,\n 44.809121700077355\n ],\n [\n -87.6708984375,\n 44.809121700077355\n ],\n [\n -87.6708984375,\n 42.16340342422401\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.92248535156249,\n 36.005784428799934\n ],\n [\n 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phutchins@usgs.gov","orcid":"https://orcid.org/0000-0001-5232-0821","contributorId":198337,"corporation":false,"usgs":true,"family":"Hutchins","given":"Patrick","email":"phutchins@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":780181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Craig 0000-0003-4023-0276 cjackson@usgs.gov","orcid":"https://orcid.org/0000-0003-4023-0276","contributorId":192276,"corporation":false,"usgs":true,"family":"Jackson","given":"Craig","email":"cjackson@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":780182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ostberg, Carl O. 0000-0003-1479-8458","orcid":"https://orcid.org/0000-0003-1479-8458","contributorId":220731,"corporation":false,"usgs":true,"family":"Ostberg","given":"Carl","middleInitial":"O.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":780183,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laramie, Matthew 0000-0001-7820-2583 mlaramie@usgs.gov","orcid":"https://orcid.org/0000-0001-7820-2583","contributorId":152532,"corporation":false,"usgs":true,"family":"Laramie","given":"Matthew","email":"mlaramie@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":780184,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":780185,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Counihan, Timothy D. 0000-0003-4967-6514","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":207532,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":780186,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hoegh, Andrew B.","contributorId":166684,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":12694,"text":"Virginia 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Invasive species represent a threat to aquatic ecosystems globally; however, impacts can be heterogenous across systems. Documented impacts of invasive zebra mussels (Dreissena polymorpha) and spiny water fleas (Bythotrephes cederströmii; hereafter Bythotrephes) on native fishes are variable and context dependent across locations and time periods. Here, we use a hierarchical Bayesian analysis of a 35-year dataset on two fish species from 9 lakes to demonstrate that early life growth of ecologically important fishes are influenced by these aquatic invasive species. Walleye (Sander vitreus) in their first year of life grew more slowly in the presence of either invader after correcting for temperature (measured by degree days), and were on average 12 or 14% smaller at the end of their first summer following invasion by Bythotrephes or zebra mussels, respectively. Yellow perch (Perca flavescens) growth was less affected by invasion. Yellow perch on average grew more slowly in their first year of life following invasion by zebra mussels, although this effect was not statistically distinguishable from zero. Early life growth of both walleye and yellow perch was less tightly coupled to degree days in invaded systems, as demonstrated by increased variance surrounding the degree day-length relationship. Smaller first-year size is related to walleye survival and recruitment to later life stages and has important implications for lake food webs and fisheries management. Future research quantifying effects of zebra mussels and Bythotrephes on other population-level processes and across a wider gradient of lake types is needed to understand the mechanisms driving observed changes in walleye growth.

","language":"English","publisher":"Springer","doi":"10.1007/s10530-020-02198-5","usgsCitation":"Ahrenstorff, T.D., Hansen, G., Bethke, B.J., Dumke, J., Hirsch, J., Kovalenko, K., LeDuc, J., Maki, R.P., Rantala, H., and Wagner, T., 2020, Walleye growth declines following zebra mussel and Bythotrephes invasion: Biological Invasions, v. 22, p. 1481-1495, https://doi.org/10.1007/s10530-020-02198-5.","productDescription":"15 p.","startPage":"1481","endPage":"1495","ipdsId":"IP-110055","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":458143,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-020-02198-5","text":"Publisher Index Page"},{"id":395656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.91015624999999,\n 45.398449976304086\n ],\n [\n -89.736328125,\n 45.398449976304086\n ],\n [\n -89.736328125,\n 49.03786794532644\n ],\n [\n -97.91015624999999,\n 49.03786794532644\n ],\n [\n -97.91015624999999,\n 45.398449976304086\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","noUsgsAuthors":false,"publicationDate":"2020-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahrenstorff, Tyler D.","contributorId":275045,"corporation":false,"usgs":false,"family":"Ahrenstorff","given":"Tyler","email":"","middleInitial":"D.","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":833604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Gretchen J. A.","contributorId":275043,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen J. A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":833603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bethke, Bethany J.","contributorId":275047,"corporation":false,"usgs":false,"family":"Bethke","given":"Bethany","email":"","middleInitial":"J.","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":833605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dumke, Josh","contributorId":275049,"corporation":false,"usgs":false,"family":"Dumke","given":"Josh","email":"","affiliations":[{"id":18006,"text":"University of Minnesota Duluth","active":true,"usgs":false}],"preferred":false,"id":833606,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hirsch, Jodie","contributorId":275051,"corporation":false,"usgs":false,"family":"Hirsch","given":"Jodie","email":"","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":833607,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kovalenko, Katya E.","contributorId":275052,"corporation":false,"usgs":false,"family":"Kovalenko","given":"Katya E.","affiliations":[{"id":18006,"text":"University of Minnesota Duluth","active":true,"usgs":false}],"preferred":false,"id":833608,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LeDuc, Jaime F.","contributorId":275056,"corporation":false,"usgs":false,"family":"LeDuc","given":"Jaime F.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":833609,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Maki, Ryan P","contributorId":275061,"corporation":false,"usgs":false,"family":"Maki","given":"Ryan","email":"","middleInitial":"P","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":833610,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rantala, Heidi","contributorId":275065,"corporation":false,"usgs":false,"family":"Rantala","given":"Heidi","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":833611,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833602,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70208001,"text":"70208001 - 2020 - Mercury and selenium concentrations in fishes of the Upper Colorado River Basin, southwestern United States: A retrospective assessment","interactions":[],"lastModifiedDate":"2020-01-23T06:22:49","indexId":"70208001","displayToPublicDate":"2020-01-13T06:18:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Mercury and selenium concentrations in fishes of the Upper Colorado River Basin, southwestern United States: A retrospective assessment","docAbstract":"Mercury (Hg) and selenium (Se) are contaminants of concern for fish in the Upper Colorado River Basin (UCRB). We explored Hg and Se in fish tissues (2,324 individuals) collected over 50 years (1962–2011) from the UCRB. Samples include native and non-native fish collected from lotic waterbodies spanning 7 major tributaries to the Colorado River. There was little variation of total mercury (THg) in fish assemblages basin-wide and only 13% (272/1959) of individual fish samples exceeded the fish health benchmark (0.27 μg THg/g ww). Most THg exceedances were observed in the White-Yampa tributary whereas the San Juan had the lowest mean THg concentration. Risks associated with THg are species specific with exceedances dominated by Colorado Pikeminnow (mean = 0.38 and standard error ± 0.08 μg THg/g ww) and Roundtail Chub (0.24 ± 0.06 μg THg/g ww). For Se, 48% (827/1720) of all individuals exceeded the fish health benchmark (5.1 μg Se/g dw). The Gunnison river had the most individual exceedances of the Se benchmark (74%) whereas the Dirty Devil had the fewest. We identified that species of management concern accumulate THg and Se to levels above risk thresholds and that fishes of the White-Yampa (THg) and Gunnison (Se) rivers are at the greatest risk in the UCRB.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0226824","usgsCitation":"Day, N.K., Schmidt, T.S., Roberts, J., Osmundson, B., Willacker, J., and Eagles-Smith, C., 2020, Mercury and selenium concentrations in fishes of the Upper Colorado River Basin, southwestern United States: A retrospective assessment: PLoS ONE, v. 15, no. 1, e0226824, https://doi.org/10.1371/journal.pone.0226824.","productDescription":"e0226824","ipdsId":"IP-100771","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":458151,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0226824","text":"Publisher Index Page"},{"id":437167,"rank":0,"type":{"id":30,"text":"Data 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0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":780101,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208449,"text":"70208449 - 2020 - Effects of montane watershed development on vulnerability of domestic groundwater supply during drought","interactions":[],"lastModifiedDate":"2020-02-10T18:22:15","indexId":"70208449","displayToPublicDate":"2020-01-11T18:13:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of montane watershed development on vulnerability of domestic groundwater supply during drought","docAbstract":"Climate change is expected to reduce recharge to montane aquifers in the western United States, but it is unclear how this will impact groundwater resources in watersheds where intensive surface-water development has disrupted the natural hydrologic regime. To better understand sources of recharge and associated vulnerabilities of groundwater supply in this setting, we made a detailed geochemical survey of domestic wells finished in fractured bedrock throughout the Yuba and Bear River watersheds (Sierra Nevada foothills, northern California)during historic drought (2015–2016). Stable isotopes of water and noble gas recharge temperatures closely tracked atmospheric lapse rates across a broad elevation gradient (100–2000 m), indicating groundwater inputs are dominated by local precipitation that rapidly recharges fractured bedrock during the winter wet-season. However, nearly one-quarter of wells had water isotopes that were fractionated by evaporation and warm recharge temperatures, indicative of mixing with dry-season recharge by surface water. Monte Carlo mixing models suggest evaporation-impacted groundwater samples are mixtures of local rain with an average of 28% ± 13% from diverted surface water that can recharge bedrock aquifers during the dry-season by either irrigation return flow or seepage from extensive distribution infrastructure. Wells that received recharge subsidies from diverted surface water had elevated levels of nitrate and coliform bacteria compared to those replenished exclusively by local precipitation,\nwhich are more vulnerable to supply shortage during drought. It is important to consider the impacts of increased surface-water development on the quantity and quality of groundwater recharge in rapidly developing montane watersheds.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.124567","usgsCitation":"Levy, Z., Fram, M.S., Faulkner, K., Alpers, C.N., Soltero, E.M., and Taylor, K.A., 2020, Effects of montane watershed development on vulnerability of domestic groundwater supply during drought: Journal of Hydrology, v. 583, 124567, 18 p., https://doi.org/10.1016/j.jhydrol.2020.124567.","productDescription":"124567, 18 p.","ipdsId":"IP-107517","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":458154,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2020.124567","text":"Publisher Index Page"},{"id":437168,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YETK9P","text":"USGS data release","linkHelpText":"Dissolved Noble Gas Concentrations and Modeled Recharge Temperatures for Groundwater from Northern Sierra Nevada Foothills Shallow Aquifer Assessment Study Units, 2015-2017: Results from the California GAMA Priority Basin Project"},{"id":372204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bear River watershed, Yuba River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.2451171875,\n 38.86323626888358\n ],\n [\n -120.13275146484374,\n 38.86323626888358\n ],\n [\n -120.13275146484374,\n 39.85282948915942\n ],\n [\n -121.2451171875,\n 39.85282948915942\n ],\n [\n -121.2451171875,\n 38.86323626888358\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"583","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Levy, Zeno F. 0000-0003-4580-2309","orcid":"https://orcid.org/0000-0003-4580-2309","contributorId":222340,"corporation":false,"usgs":true,"family":"Levy","given":"Zeno","middleInitial":"F.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faulkner, Kirsten 0000-0003-1628-2877","orcid":"https://orcid.org/0000-0003-1628-2877","contributorId":222341,"corporation":false,"usgs":true,"family":"Faulkner","given":"Kirsten","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781923,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soltero, Evelyn M","contributorId":222342,"corporation":false,"usgs":false,"family":"Soltero","given":"Evelyn","email":"","middleInitial":"M","affiliations":[{"id":40530,"text":"All About Wells","active":true,"usgs":false}],"preferred":false,"id":781924,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Taylor, Kimberly A. 0000-0002-0095-6403 ktaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-0095-6403","contributorId":1601,"corporation":false,"usgs":true,"family":"Taylor","given":"Kimberly","email":"ktaylor@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781925,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208357,"text":"70208357 - 2020 - Phosphorus, nitrogen and dissolved organic carbon fluxes from sediments in freshwater rivermouths entering Green Bay (Lake Michigan; USA)","interactions":[],"lastModifiedDate":"2020-02-05T16:05:31","indexId":"70208357","displayToPublicDate":"2020-01-10T15:56:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Phosphorus, nitrogen and dissolved organic carbon fluxes from sediments in freshwater rivermouths entering Green Bay (Lake Michigan; USA)","docAbstract":"

Transitional areas between ecosystem types are often active biogeochemically due to resource limitation changes. Lotic-to-lentic transitions in freshwaters appear active biogeochemically, but few studies have directly measured nutrient processing rates to assess whether processing within the rivermouth is important for load estimates or the local communities. We measured oxic fluxes of inorganic nitrogen and phosphorus and dissolved organic carbon (DOC) from sediments in two rivermouths of Green Bay (Lake Michigan, USA). Soluble reactive phosphorus (SRP) flux was positive in most cases (overall mean 1.74 mg SRP m− 2 day− 1), as was ammonium (NH4) flux (40.6 mg NH4 m− 2 day− 1). Partial least square regression (PLSR) indicated a latent variable associated with both sediment [loosely bound phosphorus (P), iron bound P, organic content] and water column properties [temperature, DOC:dissolved inorganic nitrogen (DIN) and DOC:SRP ratios (negatively)] that was moderately associated with variation in SRP flux. PLSR analysis also indicated several sediment characteristics were moderately related to NH4 flux, especially organic content, density (negative), and porosity. Flux of nitrates/nitrites (NOX) and DOC were positively associated with the water column concentrations of NOX and DOC and qualitative estimates of the labile, non-humic types of DOC. In early summer, water column NOX and DOC concentrations were high and labile DOC may have fueled denitrification, resulting in net flux into sediments of both NOX and DOC. By late summer, water column NOX and DOC were very low and both these constituents were fluxing out of sediments into the water column. Based on our estimates for the entire period from April through September, rivermouth sediments were a net source of SRP and DIN, with a DIN:SRP ratio of ~ 44 and a NH4:NOX > 1. We estimated that the sediments in the Fox rivermouth probably contributed a small proportion of the total Fox River load during the growing season 2016 (< 5%), but at times may have contributed as much as 14% of the daily load. Despite the small size of the Fox rivermouth (< 0.5% of the watershed area), these results indicate that at times sediments can contribute substantially to the overall delivery of nitrogen and phosphorus to the nearshore zone.

","language":"English","publisher":"Springer Nature Switzerland AG","doi":"10.1007/s10533-020-00635-0","usgsCitation":"Larson, J.H., James, W.F., Fitzpatrick, F.A., Frost, P.C., Evans, M.A., Reneau, P., and Xenopoulos, M.A., 2020, Phosphorus, nitrogen and dissolved organic carbon fluxes from sediments in freshwater rivermouths entering Green Bay (Lake Michigan; USA): Biogeochemistry, v. 147, p. 179-197, https://doi.org/10.1007/s10533-020-00635-0.","productDescription":"19 p.","startPage":"179","endPage":"197","ipdsId":"IP-101349","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437171,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LVTWS8","text":"USGS data release","linkHelpText":"Data from 92 sediment incubation experiments using sediments collected from the Fox and Duck rivermouths (adjacent to Green Bay, Lake Michigan; 2016 data)"},{"id":437170,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P995SMVW","text":"USGS data release","linkHelpText":"\tR Code to analyze data from sediment incubation experiments (Fox and Duck Rivermouths; 2016)"},{"id":372096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Green Bay","otherGeospatial":"Duck Creek, Fox River, Green Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.077392578125,\n 44.44162421758805\n ],\n [\n -87.99121856689453,\n 44.44162421758805\n ],\n [\n -87.99121856689453,\n 44.57873024377564\n ],\n [\n -88.077392578125,\n 44.57873024377564\n ],\n [\n -88.077392578125,\n 44.44162421758805\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"147","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":781554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"James, William F.","contributorId":213265,"corporation":false,"usgs":false,"family":"James","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":38729,"text":"University of Wisconsin-Stout","active":true,"usgs":false}],"preferred":false,"id":781555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075 fafitzpa@usgs.gov","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":196543,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"fafitzpa@usgs.gov","middleInitial":"A.","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":false,"id":781556,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frost, Paul C.","contributorId":138628,"corporation":false,"usgs":false,"family":"Frost","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON CA","active":true,"usgs":false}],"preferred":false,"id":781557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":149358,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":781558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reneau, Paul C.","contributorId":222219,"corporation":false,"usgs":false,"family":"Reneau","given":"Paul C.","affiliations":[{"id":40507,"text":"former employee, Wisconsin Water Science Center","active":true,"usgs":false}],"preferred":false,"id":781559,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xenopoulos, Marguerite A.","contributorId":138629,"corporation":false,"usgs":false,"family":"Xenopoulos","given":"Marguerite","email":"","middleInitial":"A.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON CA","active":true,"usgs":false}],"preferred":false,"id":781560,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208629,"text":"70208629 - 2020 - Seasonal drivers of chemical and hydrological patterns in roadside infiltration-based green infrastructure","interactions":[],"lastModifiedDate":"2020-02-21T10:40:13","indexId":"70208629","displayToPublicDate":"2020-01-10T10:29:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal drivers of chemical and hydrological patterns in roadside infiltration-based green infrastructure","docAbstract":"

Infiltration-based green infrastructure has become a popular means of reducing stormwater hazards in urban areas. However, the long-term effects of green infrastructure on the geochemistry of roadside environments are poorly defined, particularly given the considerable roadside legacy metal contamination from historic industrial activity and vehicle emissions (e.g., Pb). Most current research on green infrastructure geochemistry is restricted to time periods of less than a year or limited sets of chemical species. This further limits our understanding of systems that evolve over time and are subject to seasonal variability. Between 2016 and 2018, two infiltration trenches in Pittsburgh, PA, were monitored to determine infiltration rates and dissolved nutrient and metal content. The trench water was analyzed to characterize seasonal patterns in both trench function and chemistry. Shifting patterns in infiltration rate and geochemical activity show trends corresponding with seasonal changes. Trench function is dependent on the local water table, with the highest infiltration rates occurring when evapotranspiration is active and groundwater elevation is low. Two seasonal chemical patterns were identified. The first is driven by road salt application in the winter and interaction of the salt pulse increase Pb and Cu concentrations. The second is driven by the formation of summer reducing environments that increase dissolved Fe and Mn. These findings suggest that chemical and hydrological activity in infiltration-based green infrastructure varies seasonally and may remobilize legacy contamination.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.136503","usgsCitation":"Mullins, A.R., Bain, D.J., Pfeil McCullough, E., Hopkins, K.G., Lavin, S., and Copeland, E., 2020, Seasonal drivers of chemical and hydrological patterns in roadside infiltration-based green infrastructure: Science of the Total Environment, v. 714, 136503, 9 p., https://doi.org/10.1016/j.scitotenv.2020.136503.","productDescription":"136503, 9 p.","ipdsId":"IP-107782","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":372502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","city":"Pittsburgh","otherGeospatial":"Schenley Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.95034217834473,\n 40.428067577817366\n ],\n [\n -79.93197441101074,\n 40.428067577817366\n ],\n [\n -79.93197441101074,\n 40.4415907903353\n ],\n [\n -79.95034217834473,\n 40.4415907903353\n ],\n [\n -79.95034217834473,\n 40.428067577817366\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"714","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mullins, Angela R.","contributorId":222657,"corporation":false,"usgs":false,"family":"Mullins","given":"Angela","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":782814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bain, Daniel J 0000-0003-1979-7016","orcid":"https://orcid.org/0000-0003-1979-7016","contributorId":197634,"corporation":false,"usgs":true,"family":"Bain","given":"Daniel","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":782815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pfeil McCullough, Erin","contributorId":222658,"corporation":false,"usgs":false,"family":"Pfeil McCullough","given":"Erin","email":"","affiliations":[],"preferred":false,"id":782816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lavin, S.","contributorId":107127,"corporation":false,"usgs":true,"family":"Lavin","given":"S.","email":"","affiliations":[],"preferred":false,"id":782818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Copeland, Erin","contributorId":222659,"corporation":false,"usgs":false,"family":"Copeland","given":"Erin","email":"","affiliations":[],"preferred":false,"id":782819,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209414,"text":"70209414 - 2020 - Calcite precipitation in Lake Powell reduces alkalinity and total salt loading to the Lower Colorado River Basin","interactions":[],"lastModifiedDate":"2020-08-04T13:59:38.294865","indexId":"70209414","displayToPublicDate":"2020-01-10T08:25:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Calcite precipitation in Lake Powell reduces alkalinity and total salt loading to the Lower Colorado River Basin","docAbstract":"

Reservoirs can retain and transform carbon, nitrogen, phosphorus, and silica, but less is known about their effects on other biogeochemically relevant solutes. The salinization of freshwater ecosystems is a growing concern in many regions, and the role of reservoirs in salinity transport is an important research frontier. Here, we examine how a large desert southwest reservoir, Lake Powell, has altered the downstream transport of total dissolved solids (TDSs) as well as the dominant cations and anions comprising the TDS pool (\"urn:x-wiley:00243590:media:lno11399:lno11399-math-0001\", \"urn:x-wiley:00243590:media:lno11399:lno11399-math-0002\", and Ca2+). Average downstream TDS concentrations have declined significantly since river impoundment and seasonal fluctuations in TDS concentrations have become more modulated, but year to year variation in TDS concentrations has remained similar. While some of the reductions in TDS concentration can be attributed to watershed management, we find that Lake Powell retains about 10% of the TDS loaded to the system (1991 Mg TDS d−1). Much of this retention is occurring in the forms of calcium and bicarbonate, likely via calcite precipitation, and is equivalent to an average burial of 522 mg C m−2 d−1, thus reducing the alkalinity of downstream water. Flow‐weighted modeling suggests that, in the absence of Lake Powell, downstream salinity limits would be surpassed at the outflow to Lake Powell 41% of the time (vs. 0% of the time currently). Understanding the dominant mechanisms regulating solute transport through the reservoir is important given the relevance for downstream drinking water and irrigation concerns, biogeochemical cycling, and the high potential for reduced flows in the future.

","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.11399","usgsCitation":"Deemer, B., Stets, E.G., and Yackulic, C.B., 2020, Calcite precipitation in Lake Powell reduces alkalinity and total salt loading to the Lower Colorado River Basin: Limnology and Oceanography, v. 65, no. 7, p. 1439-1455, https://doi.org/10.1002/lno.11399.","productDescription":"17 p.","startPage":"1439","endPage":"1455","ipdsId":"IP-112663","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437173,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A9P44R","text":"USGS data release","linkHelpText":"Calcium, magnesium and total dissolved solids data as well as modeled salinity and mass balance estimates for Lake Powell, 1952-2017"},{"id":373749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Lower Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.4228515625,\n 36.87962060502676\n ],\n [\n -109.3798828125,\n 35.02999636902566\n ],\n [\n -104.765625,\n 35.639441068973944\n ],\n [\n -104.19433593749999,\n 37.996162679728116\n ],\n [\n -104.4580078125,\n 40.74725696280421\n ],\n [\n -107.5341796875,\n 43.42100882994726\n ],\n [\n -110.56640625,\n 43.739352079154706\n ],\n [\n -112.54394531249999,\n 43.58039085560784\n ],\n [\n -113.115234375,\n 41.672911819602085\n ],\n [\n -112.412109375,\n 40.3130432088809\n ],\n [\n -112.1484375,\n 39.13006024213511\n ],\n [\n -112.8955078125,\n 37.61423141542417\n ],\n [\n -113.4228515625,\n 36.87962060502676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":786378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":786379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":786380,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}