Most extant giant gartersnake (Thamnophis gigas) populations persist in an agro-ecosystem dominated by rice, which serves as a surrogate to the expansive marshes lost to flood control projects and development of the Great Central Valley of California. Knowledge of how giant gartersnakes use the rice agricultural landscape, including how they respond to fallowing, idling, or crop rotations, would greatly benefit conservation of giant gartersnakes by informing more snake-friendly land and water management practices. We studied adult giant gartersnakes at 11 sites in the rice-growing regions of the Sacramento Valley during an extended drought in California to evaluate their response to differences in water availability at the site and individual levels. Although our study indicated that giant gartersnakes make little use of rice fields themselves, and avoid cultivated rice relative to its availability on the landscape, rice is a crucial component of the modern landscape for giant gartersnakes. Giant gartersnakes are strongly associated with the canals that supply water to and drain water from rice fields; these canals provide much more stable habitat than rice fields because they maintain water longer and support marsh-like conditions for most of the giant gartersnake active season. Nonetheless, our results suggest that maintaining canals without neighboring rice fields would be detrimental to giant gartersnake populations, with decreases in giant gartersnake survival rates associated with less rice production in the surrounding landscape. Increased productivity of prey populations, dispersion of potential predators across a larger landscape, and a more secure water supply are just some of the mechanisms by which rice fields might benefit giant gartersnakes in adjacent canals. Results indicate that identifying how rice benefits giant gartersnakes in canals and the extent to which the rice agro-ecosystem could provide these benefits when rice is fallowed would inform the use of water for other purposes without harm to giant gartersnakes. Our study also suggests that without such understanding, maintaining rice and associated canals in the Sacramento Valley is critical for the sustainability of giant gartersnake populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171141","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Reyes, G.A., Halstead, B.J., Rose, J.P., Ersan, J.S.M., Jordan, A.C., Essert, A.M., Fouts, K.J., Fulton, A.M., Gustafson, K.B., Wack, R.F., Wylie, G.D., and Casazza, M.L., 2017, Behavioral response of giant gartersnakes (Thamnophis gigas) to the relative availability of aquatic habitat on the landscape: U.S. Geological Survey Open-File Report 2017-1141, 134 p., https://doi.org/10.3133/ofr20171141.","productDescription":"vi, 134 p.","numberOfPages":"144","onlineOnly":"Y","ipdsId":"IP-086237","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":348951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1141/coverthb.jpg"},{"id":348952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1141/ofr20171141.pdf","text":"Report","size":"9.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1141"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.42340087890624,\n 38.62116234642254\n ],\n [\n -121.36596679687499,\n 38.62116234642254\n ],\n [\n -121.36596679687499,\n 39.605688178320804\n ],\n [\n -122.42340087890624,\n 39.605688178320804\n ],\n [\n -122.42340087890624,\n 38.62116234642254\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive
East Sacramento, California 95819
The Alaskan population of Emperor Geese (Chen canagica) nests on the Yukon–Kuskokwim Delta in western Alaska. Numbers of Emperor Geese in Alaska declined from the 1960s to the mid-1980s and since then, their numbers have slowly increased. Low statistical power of microsatellite loci developed in other waterfowl species and used in previous studies of Emperor Geese are unable to confidently assign individual identity. Microsatellite loci for Emperor Goose were therefore developed using shotgun amplification and next-generation sequencing technology. Forty-one microsatellite loci were screened and 14 were found to be polymorphic in Emperor Geese. Only six markers – a combination of four novel loci and two loci developed in other waterfowl species – are needed to identify an individual from among the Alaskan Emperor Goose population. Genetic markers for identifying sex in Emperor Geese were also developed. The 14 novel variable loci and 15 monomorphic loci were screened for polymorphism in four other Arctic-nesting goose species, Black Brant (Branta bernicla nigricans), Greater White-fronted (Anser albifrons), Canada (B. canadensis) and Cackling (B. hutchinsii) Goose. Emperor Goose exhibited the smallest average number of alleles (3.3) and the lowest expected heterozygosity (0.467). Greater White-fronted Geese exhibited the highest average number of alleles (4.7) and Cackling Geese the highest expected heterozygosity (0.599). Six of the monomorphic loci were variable and able to be characterised in the other goose species assayed, a predicted outcome of reverse ascertainment bias. These findings fail to support the hypothesis of ascertainment bias due to selection of microsatellite markers.
","language":"English","publisher":"Ingenta Connect","doi":"10.3184/175815617X14969254461396","usgsCitation":"Gravley, M.C., Sage, G.K., Schmutz, J.A., and Talbot, S.L., 2017, Development of microsatellite loci exhibiting reverse ascertainment bias and a sexing marker for use in Emperor Geese (Chen canagica): Avian Biology Research, v. 10, no. 4, p. 201-210, https://doi.org/10.3184/175815617X14969254461396.","productDescription":"10 p.","startPage":"201","endPage":"210","ipdsId":"IP-083205","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438147,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71V5C4S","text":"USGS data release","linkHelpText":"DNA Microsatellite and Sex Identification Markers for Emperor Goose (Chen canagica) and Cross-Species Amplification of Microsatellites in Select Goose Species, Alaska 2016"},{"id":349005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon–Kuskokwim Delta","volume":"10","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-01","publicationStatus":"PW","scienceBaseUri":"5a60fb0fe4b06e28e9c22b86","contributors":{"authors":[{"text":"Gravley, Megan C. 0000-0002-4947-0236 mgravley@usgs.gov","orcid":"https://orcid.org/0000-0002-4947-0236","contributorId":202812,"corporation":false,"usgs":true,"family":"Gravley","given":"Megan","email":"mgravley@usgs.gov","middleInitial":"C.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":722455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":722457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":722456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":722454,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191499,"text":"70191499 - 2017 - Enhanced Arctic amplification began at the Mid-Brunhes Event 430,000 years ago","interactions":[],"lastModifiedDate":"2017-11-15T10:10:03","indexId":"70191499","displayToPublicDate":"2017-11-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Enhanced Arctic amplification began at the Mid-Brunhes Event 430,000 years ago","docAbstract":"Arctic Ocean temperatures influence ecosystems, sea ice, species diversity, biogeochemical cycling, seafloor methane stability, deep-sea circulation, and CO2 cycling. Today's Arctic Ocean and surrounding regions are undergoing climatic changes often attributed to \"Arctic amplification\" - that is, amplified warming in Arctic regions due to sea-ice loss and other processes, relative to global mean temperature. However, the long-term evolution of Arctic amplification is poorly constrained due to lack of continuous sediment proxy records of Arctic Ocean temperature, sea ice cover and circulation. Here we present reconstructions of Arctic Ocean intermediate depth water (AIW) temperatures and sea-ice cover spanning the last ~ 1.5 million years (Ma) of orbitally-paced glacial/interglacial cycles (GIC). Using Mg/Ca paleothermometry of the ostracode Krithe and sea-ice planktic and benthic indicator species, we suggest that the Mid-Brunhes Event (MBE), a major climate transition ~ 400-350 ka, involved fundamental changes in AIW temperature and sea-ice variability. Enhanced Arctic amplification at the MBE suggests a major climate threshold was reached at ~ 400 ka involving Atlantic Meridional Overturning Circulation (AMOC), inflowing warm Atlantic Layer water, ice sheet, sea-ice and ice-shelf feedbacks, and sensitivity to higher post-MBE interglacial CO2 concentrations.
","language":"English","publisher":"Springer","doi":"10.1038/s41598-017-13821-2","usgsCitation":"Cronin, T.M., Dwyer, G.S., Caverly, E., Farmer, J., DeNinno, L., Rodriguez-Lazaro, J., and Gemery, L., 2017, Enhanced Arctic amplification began at the Mid-Brunhes Event 430,000 years ago: Scientific Reports, v. 7, 14475; 6 p., https://doi.org/10.1038/s41598-017-13821-2.","productDescription":"14475; 6 p.","ipdsId":"IP-083962","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469313,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-017-13821-2","text":"Publisher Index Page"},{"id":348868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Ocean","volume":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-03","publicationStatus":"PW","scienceBaseUri":"5a60fb11e4b06e28e9c22bbc","contributors":{"authors":[{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":712449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dwyer, Gary S.","contributorId":197070,"corporation":false,"usgs":false,"family":"Dwyer","given":"Gary","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":712450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caverly, Emma","contributorId":197071,"corporation":false,"usgs":false,"family":"Caverly","given":"Emma","affiliations":[],"preferred":false,"id":712451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farmer, Jesse","contributorId":197072,"corporation":false,"usgs":false,"family":"Farmer","given":"Jesse","affiliations":[],"preferred":false,"id":712452,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeNinno, Lauren H.","contributorId":197073,"corporation":false,"usgs":false,"family":"DeNinno","given":"Lauren H.","affiliations":[],"preferred":false,"id":712453,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rodriguez-Lazaro, Julio","contributorId":197074,"corporation":false,"usgs":false,"family":"Rodriguez-Lazaro","given":"Julio","email":"","affiliations":[],"preferred":false,"id":712454,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gemery, Laura 0000-0003-1966-8732 lgemery@usgs.gov","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":5402,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","email":"lgemery@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":722116,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70193736,"text":"70193736 - 2017 - Stormwater management network effectiveness and implications for urban watershed function: A critical review","interactions":[],"lastModifiedDate":"2017-11-17T08:53:58","indexId":"70193736","displayToPublicDate":"2017-11-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Stormwater management network effectiveness and implications for urban watershed function: A critical review","docAbstract":"Deleterious effects of urban stormwater are widely recognized. In several countries, regulations have been put into place to improve the conditions of receiving water bodies, but planning and engineering of stormwater control is typically carried out at smaller scales. Quantifying cumulative effectiveness of many stormwater control measures on a watershed scale is critical to understanding how small-scale practices translate to urban river health. We review 100 empirical and modelling studies of stormwater management effectiveness at the watershed scale in diverse physiographic settings. Effects of networks with stormwater control measures (SCMs) that promote infiltration and harvest have been more intensively studied than have detention-based SCM networks. Studies of peak flows and flow volumes are common, whereas baseflow, groundwater recharge, and evapotranspiration have received comparatively little attention. Export of nutrients and suspended sediments have been the primary water quality focus in the United States, whereas metals, particularly those associated with sediments, have received greater attention in Europe and Australia. Often, quantifying cumulative effects of stormwater management is complicated by needing to separate its signal from the signal of urbanization itself, innate watershed characteristics that lead to a range of hydrologic and water quality responses, and the varying functions of multiple types of SCMs. Biases in geographic distribution of study areas, and size and impervious surface cover of watersheds studied also limit our understanding of responses. We propose hysteretic trajectories for how watershed function responds to increasing imperviousness and stormwater management. Even where impervious area is treated with SCMs, watershed function may not be restored to its predevelopment condition because of the lack of treatment of all stormwater generated from impervious surfaces; non-additive effects of individual SCMs; and persistence of urban effects beyond impervious surfaces. In most cases, pollutant load decreases largely result from run-off reductions rather than lowered solute or particulate concentrations. Understanding interactions between natural and built landscapes, including stormwater management strategies, is critical for successfully managing detrimental impacts of stormwater at the watershed scale.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11347","usgsCitation":"Jefferson, A.J., Bhaskar, A.S., Hopkins, K.G., Fanelli, R.M., Avellaneda, P.M., and McMillan, S., 2017, Stormwater management network effectiveness and implications for urban watershed function: A critical review: Hydrological Processes, v. 31, no. 23, p. 4056-4080, https://doi.org/10.1002/hyp.11347.","productDescription":"25 p.","startPage":"4056","endPage":"4080","ipdsId":"IP-085363","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":349019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia, China, United States","otherGeospatial":"Europe","volume":"31","issue":"23","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-03","publicationStatus":"PW","scienceBaseUri":"5a60fb11e4b06e28e9c22ba8","contributors":{"authors":[{"text":"Jefferson, Anne J.","contributorId":199823,"corporation":false,"usgs":false,"family":"Jefferson","given":"Anne","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":720118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bhaskar, Aditi S.","contributorId":199824,"corporation":false,"usgs":false,"family":"Bhaskar","given":"Aditi","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":720119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":720117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fanelli, Rosemary M. 0000-0002-0874-1925 rfanelli@usgs.gov","orcid":"https://orcid.org/0000-0002-0874-1925","contributorId":199822,"corporation":false,"usgs":true,"family":"Fanelli","given":"Rosemary","email":"rfanelli@usgs.gov","middleInitial":"M.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":720116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Avellaneda, Pedro M.","contributorId":199825,"corporation":false,"usgs":false,"family":"Avellaneda","given":"Pedro","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":720120,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McMillan, Sara K.","contributorId":197089,"corporation":false,"usgs":false,"family":"McMillan","given":"Sara K.","affiliations":[],"preferred":false,"id":720121,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192446,"text":"70192446 - 2017 - Comparing catchment hydrologic response to a regional storm using specific conductivity sensors","interactions":[],"lastModifiedDate":"2018-03-27T14:04:10","indexId":"70192446","displayToPublicDate":"2017-11-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Comparing catchment hydrologic response to a regional storm using specific conductivity sensors","docAbstract":"A better understanding of stormwater generation and solute sources is needed to improve the protection of aquatic ecosystems, infrastructure, and human health from large runoff events. Much of our understanding of water and solutes produced during stormflow comes from studies of individual, small headwater catchments. This study compared many different types of catchments during a single large event to help isolate landscape controls on streamwater and solute generation, including human-impacted land cover. We used a distributed network of specific electrical conductivity sensors to trace storm response during the post-tropical cyclone Sandy event of October 2012 at 29 catchments across the state of New Hampshire. A citizen science sensor network, Lotic Volunteer for Temperature, Electrical Conductivity, and Stage, provided a unique opportunity to investigate high-temporal resolution stream behavior at a broad spatial scale. Three storm response metrics were analyzed in this study: (a) fraction of new water contributing to the hydrograph; (b) presence of first flush (mobilization of solutes during the beginning of the rain event); and (c) magnitude of first flush. We compared new water and first flush to 64 predictor attributes related to land cover, soil, topography, and precipitation. The new water fraction was positively correlated with low and medium intensity development in the catchment and riparian buffers and with the precipitation from a rain event 9 days prior to Sandy. The presence of first flush was most closely related (positively) to soil organic matter. Magnitude of first flush was not strongly related to any of the catchment variables. Our results highlight the potentially important role of human landscape modification in runoff generation at multiple spatial scales and the lack of a clear role in solute flushing. Further development of regional-scale in situ sensor networks will provide better understanding of stormflow and solute generation across a wide range of landscape conditions.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11091","usgsCitation":"Inserillo, A., Green, M., Shanley, J.B., and Boyer, J., 2017, Comparing catchment hydrologic response to a regional storm using specific conductivity sensors: Hydrological Processes, v. 31, no. 5, p. 1074-1085, https://doi.org/10.1002/hyp.11091.","productDescription":"12 p.","startPage":"1074","endPage":"1085","ipdsId":"IP-076898","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":348888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":715879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyer, Joseph","contributorId":198377,"corporation":false,"usgs":false,"family":"Boyer","given":"Joseph","affiliations":[],"preferred":false,"id":715882,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191896,"text":"70191896 - 2017 - Investigating the influence of nitrate nitrogen on post-smolt Atlantic salmon Salmo salar reproductive physiology in water recirculation aquaculture systems","interactions":[],"lastModifiedDate":"2018-03-28T10:58:06","indexId":"70191896","displayToPublicDate":"2017-11-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":852,"text":"Aquacultural Engineering","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Investigating the influence of nitrate nitrogen on post-smolt Atlantic salmon Salmo salar reproductive physiology in water recirculation aquaculture systems","title":"Investigating the influence of nitrate nitrogen on post-smolt Atlantic salmon Salmo salar reproductive physiology in water recirculation aquaculture systems","docAbstract":"A major issue affecting land-based, closed containment Atlantic salmon Salmo salar growout production in water recirculation aquaculture systems (RAS) is precocious male maturation, which can negatively impact factors such as feed conversion, fillet yield, and product quality. Along with other water quality parameters, elevated nitrate nitrogen (NO3-N) has been shown to influence the reproductive development and endogenous sex steroid production in a number of aquatic animal species, including Atlantic salmon. We sought to determine whether elevated NO3-N in RAS can influence early maturation in post-smolt Atlantic salmon in an 8-month trial in replicated freshwater RAS. Post-smolt Atlantic salmon (102 ± 1 g) were stocked into six RAS, with three RAS randomly selected for dosing with high NO3-N (99 ± 1 mg/L) and three RAS set for low NO3-N (10 ± 0 mg/L). At 2-, 4-, 6-, and 8-months post-stocking, 5 fish were randomly sampled from each RAS, gonadosomatic index(GSI) data were collected, and plasma was sampled for 11-ketotestosterone(11-KT) quantification. At 4- and 8-months post-stocking, samples of culture tank and spring water (used as “makeup” or replacement water) were collected and tested for a suite of 42 hormonally active compounds using liquid chromatography/mass spectrometry, as well as for estrogenicity using the bioluminescent yeast estrogen screen (BLYES) reporter system. Finally, at 8-months post-stocking 8–9 salmon were sampled from each RAS for blood gas and chemistry analyses, and multiple organ tissues were sampled for histopathology evaluation. Overall, sexually mature males were highly prevalent in both NO3-N treatment groups by study’s end, and there did not appear to be an effect of NO3-N on male maturation prevalence based on grilse identification, GSI, and 11-KT results, indicating that other culture parameters likely instigated early maturation. No important differences were noted between treatment groups for whole blood gas and chemistry parameters, and no significant tissue changes were noted on histopathology. No hormones, hormone conjugates, or mycotoxins were detected in any water samples; phytoestrogens were generally detected at low levels but were unrelated to NO3-N treatment. Finally, low-level estrogenicity was detected in RAS water, but a NO3-N treatment effect could not be determined. The major findings of this study are i) the NO3-N treatments did not appear to be related to the observed male maturation, and ii) the majority of hormonally active compounds were not detectable in RAS water.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquaeng.2016.09.003","usgsCitation":"Good, C., Davidson, J., Iwanowicz, L.R., Meyer, M.T., Dietze, J.E., Kolpin, D.W., Marancik, D., Birkett, J., Williams, C., and Summerfelt, S.T., 2017, Investigating the influence of nitrate nitrogen on post-smolt Atlantic salmon Salmo salar reproductive physiology in water recirculation aquaculture systems: Aquacultural Engineering, v. 78, no. Part A, p. 2-8, https://doi.org/10.1016/j.aquaeng.2016.09.003.","productDescription":"7 p.","startPage":"2","endPage":"8","ipdsId":"IP-076818","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":469312,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aquaeng.2016.09.003","text":"Publisher Index Page"},{"id":348872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"Part A","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb11e4b06e28e9c22bb3","contributors":{"authors":[{"text":"Good, Christopher","contributorId":200359,"corporation":false,"usgs":false,"family":"Good","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":713569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davidson, John","contributorId":197473,"corporation":false,"usgs":false,"family":"Davidson","given":"John","affiliations":[],"preferred":false,"id":713571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":190787,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":713575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":713567,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dietze, Julie E. 0000-0002-5936-5739 juliec@usgs.gov","orcid":"https://orcid.org/0000-0002-5936-5739","contributorId":3939,"corporation":false,"usgs":true,"family":"Dietze","given":"Julie","email":"juliec@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":713568,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713576,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marancik, David","contributorId":197474,"corporation":false,"usgs":false,"family":"Marancik","given":"David","email":"","affiliations":[],"preferred":false,"id":713572,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Birkett, Jill","contributorId":197477,"corporation":false,"usgs":false,"family":"Birkett","given":"Jill","email":"","affiliations":[],"preferred":false,"id":713577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Williams, Christina","contributorId":197475,"corporation":false,"usgs":false,"family":"Williams","given":"Christina","email":"","affiliations":[],"preferred":false,"id":713573,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Summerfelt, Steven T.","contributorId":192709,"corporation":false,"usgs":false,"family":"Summerfelt","given":"Steven","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":713574,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70194507,"text":"70194507 - 2017 - Monitoring gas and heat emissions at Norris Geyser Basin, Yellowstone National Park, USA based on a combined eddy covariance and Multi-GAS approach","interactions":[],"lastModifiedDate":"2019-02-18T11:22:55","indexId":"70194507","displayToPublicDate":"2017-11-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring gas and heat emissions at Norris Geyser Basin, Yellowstone National Park, USA based on a combined eddy covariance and Multi-GAS approach","docAbstract":"We quantified gas and heat emissions in an acid-sulfate, vapor-dominated area (0.04-km2) of Norris Geyser Basin, located just north of the 0.63 Ma Yellowstone Caldera and near an area of anomalous uplift. From 14 May to 3 October 2016, an eddy covariance system measured half-hourly CO2, H2O and sensible (H) and latent (LE) heat fluxes and a Multi-GAS instrument measured (1 Hz frequency) atmospheric H2O, CO2 and H2S volumetric mixing ratios. We also measured soil CO2 fluxes using the accumulation chamber method and temperature profiles on a grid and collected fumarole gas samples for geochemical analysis. Eddy covariance CO2 fluxes ranged from − 56 to 885 g m− 2 d− 1. Using wavelet analysis, average daily eddy covariance CO2 fluxes were locally correlated with average daily environmental parameters on several-day to monthly time scales. Estimates of CO2emission rate from the study area ranged from 8.6 t d− 1 based on eddy covariance measurements to 9.8 t d− 1 based on accumulation chamber measurements. Eddy covariance water vapor fluxes ranged from 1178 to 24,600 g m− 2 d− 1. Nighttime H and LEwere considered representative of hydrothermal heat fluxes and ranged from 4 to 183 and 38 to 504 W m− 2, respectively. The total hydrothermal heat emission rate (H + LE + radiant) estimated for the study area was 11.6 MW and LE contributed 69% of the output. The mean ± standard deviation of H2O, CO2 and H2S mixing ratios measured by the Multi-GAS system were 9.3 ± 3.1 parts per thousand, 467 ± 61 ppmv, and 0.5 ± 0.6 ppmv, respectively, and variations in the gas compositions were strongly correlated with diurnal variations in environmental parameters (wind speed and direction, atmospheric temperature). After removing ambient H2O and CO2, the observed variations in the Multi-GAS data could be explained by the mixing of relatively H2O-CO2-H2S-rich fumarole gases with CO2-rich and H2O-H2S-poor soil gases. The fumarole H2O/CO2 and CO2/H2S end member ratios (101.7 and 27.1, respectively, on average) were invariant during the measurement period and fell within the range of values measured in direct fumarole gas samples. The soil gas H2O/CO2end member ratios (~ 15–30) were variable and low relative to the fumarole end member, likely resulting from water vapor loss during cooling and condensation in the shallow subsurface, whereas the CO2/H2S end member ratio was high (~ 160), presumably related to transport of CO2-dominated soil gas emissions mixed with trace fumarolic emissions to the Multi-GAS station. Nighttime eddy covariance ratios of H2O to CO2 flux were typically between the soil gas and fumarole end member H2O/CO2 ratios defined by Multi-GAS measurements. Overall, the combined eddy covariance and Multi-GAS approach provides a powerful tool for quasi-continuous measurements of gas and heat emissions for improved volcano-hydrothermal monitoring.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.10.001","usgsCitation":"Lewicki, J.L., Kelly, P.J., Bergfeld, D., Vaughan, R., and Lowenstern, J.B., 2017, Monitoring gas and heat emissions at Norris Geyser Basin, Yellowstone National Park, USA based on a combined eddy covariance and Multi-GAS approach: Journal of Volcanology and Geothermal Research, v. 347, p. 312-326, https://doi.org/10.1016/j.jvolgeores.2017.10.001.","productDescription":"15 p.","startPage":"312","endPage":"326","ipdsId":"IP-088820","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":349628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Norris Geyser Basin, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.72776794433592,\n 44.71642860567541\n ],\n [\n -110.6945514678955,\n 44.71642860567541\n ],\n [\n -110.6945514678955,\n 44.742222087511614\n ],\n [\n -110.72776794433592,\n 44.742222087511614\n ],\n [\n -110.72776794433592,\n 44.71642860567541\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"347","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb10e4b06e28e9c22b9e","contributors":{"authors":[{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":724170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":724171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergfeld, Deborah 0000-0003-4570-7627 dbergfel@usgs.gov","orcid":"https://orcid.org/0000-0003-4570-7627","contributorId":152531,"corporation":false,"usgs":true,"family":"Bergfeld","given":"Deborah","email":"dbergfel@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":724172,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vaughan, R. Greg gvaughan@usgs.gov","contributorId":200796,"corporation":false,"usgs":true,"family":"Vaughan","given":"R. Greg","email":"gvaughan@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":false,"id":724173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowenstern, Jacob B. 0000-0003-0464-7779 jlwnstrn@usgs.gov","orcid":"https://orcid.org/0000-0003-0464-7779","contributorId":2755,"corporation":false,"usgs":true,"family":"Lowenstern","given":"Jacob","email":"jlwnstrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":724174,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189972,"text":"ofr20171088 - 2017 - Virginia flow-ecology modeling results—An initial assessment of flow reduction effects on aquatic biota","interactions":[],"lastModifiedDate":"2017-11-14T12:14:48","indexId":"ofr20171088","displayToPublicDate":"2017-11-14T10:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1088","title":"Virginia flow-ecology modeling results—An initial assessment of flow reduction effects on aquatic biota","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Virginia Department of Environmental Quality (DEQ), reviewed a previously compiled set of linear regression models to assess their utility in defining the response of the aquatic biological community to streamflow depletion.
As part of the 2012 Virginia Healthy Watersheds Initiative (HWI) study conducted by Tetra Tech, Inc., for the U.S. Environmental Protection Agency (EPA) and Virginia DEQ, a database with computed values of 72 hydrologic metrics, or indicators of hydrologic alteration (IHA), 37 fish metrics, and 64 benthic invertebrate metrics was compiled and quality assured. Hydrologic alteration was represented by simulation of streamflow record for a pre-water-withdrawal condition (baseline) without dams or developed land, compared to the simulated recent-flow condition (2008 withdrawal simulation) including dams and altered landscape to calculate a percent alteration of flow. Biological samples representing the existing populations represent a range of alteration in the biological community today.
For this study, all 72 IHA metrics, which included more than 7,272 linear regression models, were considered. This extensive dataset provided the opportunity for hypothesis testing and prioritization of flow-ecology relations that have the potential to explain the effect(s) of hydrologic alteration on biological metrics in Virginia streams.
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\"}}]}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond VA 23228
This report describes a compilation of existing water-quality data associated with groundwater resources originating from abandoned underground coal mines in West Virginia. Data were compiled from multiple sources for the purpose of understanding the suitability of groundwater from abandoned underground coal mines for public supply, industrial, agricultural, and other uses. This compilation includes data collected for multiple individual studies conducted from July 13, 1973 through September 7, 2016. Analytical methods varied by the time period of data collection and requirements of the independent studies.This project identified 770 water-quality samples from 294 sites that could be attributed to abandoned underground coal mine aquifers originating from multiple coal seams in West Virginia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1069","collaboration":"Prepared in cooperation with the West Virginia Department of Environmental Protection Division of Water and Waste Management","usgsCitation":"McAdoo, M.A., and Kozar M.D., 2017, Groundwater-quality data associated with abandoned underground coal mine aquifers in West Virginia, 1973-2016: Compilation of existing data from multiple sources: U.S. Geological Survey Data Series 1069, 7 p., https://doi.org/10.3133/ds1069.","productDescription":"Report: iv, 7 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088916","costCenters":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":438150,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TM78C5","text":"USGS data release","linkHelpText":"Site and Groundwater-Quality Sample Data for Abandoned 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Virginia\",\"nation\":\"USA \"}}]}","contact":"Director, West Virginia Water Science Center
U.S. Geological Survey
11 Dunbar Street
Charleston, WV 25301
The United States (U.S.) has faced major environmental changes in recent decades, including agricultural intensification and urban expansion, as well as changes in atmospheric deposition and climate—all of which may influence eutrophication of freshwaters. However, it is unclear whether or how water quality in lakes across diverse ecological settings has responded to environmental change. We quantified water quality trends in 2913 lakes using nutrient and chlorophyll (Chl) observations from the Lake Multi-Scaled Geospatial and Temporal Database of the Northeast U.S. (LAGOS-NE), a collection of preexisting lake data mostly from state agencies. LAGOS-NE was used to quantify whether lake water quality has changed from 1990 to 2013, and whether lake-specific or regional geophysical factors were related to the observed changes. We modeled change through time using hierarchical linear models for total nitrogen (TN), total phosphorus (TP), stoichiometry (TN:TP), and Chl. Both the slopes (percent change per year) and intercepts (value in 1990) were allowed to vary by lake and region. Across all lakes, TN declined at a rate of 1.1% year−1, while TP, TN:TP, and Chl did not change. A minority (7%–16%) of individual lakes had changing nutrients, stoichiometry, or Chl. Of those lakes that changed, we found differences in the geospatial variables that were most related to the observed change in the response variables. For example, TN and TN:TP trends were related to region-level drivers associated with atmospheric deposition of N; TP trends were related to both lake and region-level drivers associated with climate and land use; and Chl trends were found in regions with high air temperature at the beginning of the study period. We conclude that despite large environmental change and management efforts over recent decades, water quality of lakes in the Midwest and Northeast U.S. has not overwhelmingly degraded or improved.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13810","usgsCitation":"Oliver, S., Collins, S.M., Soranno, P.A., Wagner, T., Stanley, E.H., Jones, J., Stow, C., and Lottig, N.R., 2017, Unexpected stasis in a changing world: Lake nutrient and chlorophyll trends since 1990: Global Change Biology, v. 23, no. 12, p. 5455-5467, https://doi.org/10.1111/gcb.13810.","productDescription":"13 p.","startPage":"5455","endPage":"5467","ipdsId":"IP-081858","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469318,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.13810","text":"Publisher Index Page"},{"id":348839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"23","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-23","publicationStatus":"PW","scienceBaseUri":"5a60fb13e4b06e28e9c22be5","contributors":{"authors":[{"text":"Oliver, Samantha K.","contributorId":169273,"corporation":false,"usgs":false,"family":"Oliver","given":"Samantha K.","affiliations":[],"preferred":false,"id":719279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collins, Sarah M.","contributorId":172181,"corporation":false,"usgs":false,"family":"Collins","given":"Sarah","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":719280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":719281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":719278,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":719282,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, John R.","contributorId":48459,"corporation":false,"usgs":false,"family":"Jones","given":"John R.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":719283,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stow, Craig A.","contributorId":49733,"corporation":false,"usgs":true,"family":"Stow","given":"Craig A.","affiliations":[],"preferred":false,"id":719284,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lottig, Noah R.","contributorId":172031,"corporation":false,"usgs":false,"family":"Lottig","given":"Noah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":719285,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70193727,"text":"fs20173083 - 2017 - Streamflow conditions along Soldier Creek, Northeast Kansas","interactions":[],"lastModifiedDate":"2017-11-14T11:08:04","indexId":"fs20173083","displayToPublicDate":"2017-11-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3083","title":"Streamflow conditions along Soldier Creek, Northeast Kansas","docAbstract":"The availability of adequate water to meet the present (2017) and future needs of humans, fish, and wildlife is a fundamental issue for the Prairie Band Potawatomi Nation in northeast Kansas. Because Soldier Creek flows through the Prairie Band Potawatomi Nation Reservation, it is an important tribal resource. An understanding of historical Soldier Creek streamflow conditions is required for the effective management of tribal water resources, including drought contingency planning. Historical data for six selected U.S. Geological Survey (USGS) streamgages along Soldier Creek were used in an assessment of streamflow characteristics and trends by Juracek (2017). Streamflow data for the period of record at each streamgage were used to compute annual mean streamflow, annual mean base flow, mean monthly flow, annual peak flow, and annual minimum flow. Results of the assessment are summarized in this fact sheet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173083","usgsCitation":"Juracek, K.E., 2017, Streamflow conditions along Soldier Creek, Northeast Kansas: U.S. Geological Survey Fact Sheet 2017–3083, 4 p., https://doi.org/10.3133/fs20173083.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-091639","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":348318,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3083/coverthb.jpg"},{"id":348319,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3083/fs20173083.pdf","text":"Report","size":"3.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3083"},{"id":348320,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20175061","text":"SIR 2017–5061","description":"SIR 2017–5061","linkHelpText":"Streamflow characteristics and trends along Soldier Creek, Northeast Kansas"}],"country":"United States","state":"Kansas","otherGeospatial":"Soldier Creek Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.0040283203125,\n 39.08210619353512\n ],\n [\n -95.60440063476562,\n 39.08210619353512\n ],\n [\n -95.60440063476562,\n 39.67019926771586\n ],\n [\n -96.0040283203125,\n 39.67019926771586\n ],\n [\n -96.0040283203125,\n 39.08210619353512\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
Context
Efficient restoration of longitudinal river connectivity relies on barrier mitigation prioritization tools that incorporate stream network spatial structure to maximize ecological benefits given limited resources. Typically, ecological benefits of barrier mitigation are measured using proxies such as the amount of accessible riverine habitat.
Objectives
We developed an optimization approach for barrier mitigation planning which directly incorporates the ecology of managed taxa, and applied it to an urbanizing salmon-bearing watershed in Alaska.
Methods
A novel river connectivity metric that exploits information on the distribution and movement of managed taxon was embedded into a barrier prioritization framework to identify optimal mitigation actions given limited restoration budgets. The value of ecological information on managed taxa was estimated by comparing costs to achieve restoration targets across alternative barrier prioritization approaches.
Results
Barrier mitigation solutions informed by life history information outperformed those using only river connectivity proxies, demonstrating high value of ecological information for watershed restoration. In our study area, information on salmon ecology was typically valued at 0.8–1.2 M USD in costs savings to achieve a given benefit level relative to solutions derived only from stream network information, equating to 16–28% of the restoration budget.
Conclusions
Investing in ecological studies may achieve win–win outcomes of improved understanding of aquatic ecology and greater watershed restoration efficiency.
Simultaneous assessment of sediment chemistry, sediment toxicity, and macroinvertebrate communities can provide multiple lines of evidence when investigating relations between sediment contaminants and ecological degradation. These three measures were evaluated at 99 wadable stream sites across 11 states in the Midwestern United States during the summer of 2013 to assess sediment pollution across a large agricultural landscape. This evaluation considers an extensive suite of sediment chemistry totaling 274 analytes (polycyclic aromatic hydrocarbons, organochlorine compounds, polychlorinated biphenyls, polybrominated diphenyl ethers, trace elements, and current-use pesticides) and a mixture assessment based on the ratios of detected compounds to available effects-based benchmarks. The sediments were tested for toxicity with the amphipod Hyalella azteca (28-d exposure), the midge Chironomus dilutus (10-d), and, at a few sites, with the freshwater mussel Lampsilis siliquoidea (28-d). Sediment concentrations, normalized to organic carbon content, infrequently exceeded benchmarks for aquatic health, which was generally consistent with low rates of observed toxicity. However, the benchmark-based mixture score and the pyrethroid insecticide bifenthrin were significantly related to observed sediment toxicity. The sediment mixture score and bifenthrin were also significant predictors of the upper limits of several univariate measures of the macroinvertebrate community (EPT percent, MMI (Macroinvertebrate Multimetric Index) Score, Ephemeroptera and Trichoptera richness) using quantile regression. Multivariate pattern matching (Mantel-like tests) of macroinvertebrate species per site to identified contaminant metrics and sediment toxicity also indicate that the sediment mixture score and bifenthrin have weak, albeit significant, influence on the observed invertebrate community composition. Together, these three lines of evidence (toxicity tests, univariate metrics, and multivariate community analysis) suggest that elevated contaminant concentrations in sediments, in particular bifenthrin, is limiting macroinvertebrate communities in several of these Midwest streams.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.05.035","usgsCitation":"Moran, P.W., Nowell, L.H., Kemble, N.E., Mahler, B., Waite, I.R., and Van Metre, P., 2017, Influence of sediment chemistry and sediment toxicity on macroinvertebrate communities across 99 wadable streams of the Midwestern USA: Science of the Total Environment, v. 599-600, p. 1469-1478, https://doi.org/10.1016/j.scitotenv.2017.05.035.","productDescription":"10 p.","startPage":"1469","endPage":"1478","ipdsId":"IP-087012","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":461347,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2017.05.035","text":"Publisher Index Page"},{"id":348701,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"599-600","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb15e4b06e28e9c22c12","contributors":{"authors":[{"text":"Moran, Patrick W. 0000-0002-2002-3539 pwmoran@usgs.gov","orcid":"https://orcid.org/0000-0002-2002-3539","contributorId":489,"corporation":false,"usgs":true,"family":"Moran","given":"Patrick","email":"pwmoran@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717030,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kemble, Nile E. 0000-0002-3608-0538 nkemble@usgs.gov","orcid":"https://orcid.org/0000-0002-3608-0538","contributorId":2626,"corporation":false,"usgs":true,"family":"Kemble","given":"Nile","email":"nkemble@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":717031,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717032,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717033,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Metre, Peter C. 0000-0001-7564-9814 pcvanmet@usgs.gov","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":197363,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":false,"id":717034,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193967,"text":"70193967 - 2017 - A three-dimensional mapping of the ocean based on environmental data","interactions":[],"lastModifiedDate":"2018-01-19T17:59:46","indexId":"70193967","displayToPublicDate":"2017-11-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2929,"text":"Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"A three-dimensional mapping of the ocean based on environmental data","docAbstract":"The existence, sources, distribution, circulation, and physicochemical nature of macroscale oceanic water bodies have long been a focus of oceanographic inquiry. Building on that work, this paper describes an objectively derived and globally comprehensive set of 37 distinct volumetric region units, called ecological marine units (EMUs). They are constructed on a regularly spaced ocean point-mesh grid, from sea surface to seafloor, and attributed with data from the 2013 World Ocean Atlas version 2. The point attribute data are the means of the decadal averages from a 57-year climatology of six physical and chemical environment parameters (temperature, salinity, dissolved oxygen, nitrate, phosphate, and silicate). The database includes over 52 million points that depict the global ocean in x, y, and z dimensions. The point data were statistically clustered to define the 37 EMUs, which represent physically and chemically distinct water volumes based on spatial variation in the six marine environmental characteristics used. The aspatial clustering to produce the 37 EMUs did not include point location or depth as a determinant, yet strong geographic and vertical separation was observed. Twenty-two of the 37 EMUs are globally or regionally extensive, and account for 99% of the ocean volume, while the remaining 15 are smaller and shallower, and occur around coastal features. We assessed the vertical distribution of EMUs in the water column and placed them into classical depth zones representing epipelagic (0 m to 200 m), mesopelagic (200 m to 1,000 m), bathypelagic (1,000 m to 4,000 m) and abyssopelagic (>4,000 m) layers. The mapping and characterization of the EMUs represent a new spatial framework for organizing and understanding the physical, chemical, and ultimately biological properties and processes of oceanic water bodies. The EMUs are an initial objective partitioning of the ocean using long-term historical average data, and could be extended in the future by adding new classification variables and by introducing functionality to develop time-specific EMU distribution maps. The EMUs are an open-access resource, and as both a standardized geographic framework and a baseline physicochemical characterization of the oceanic environment, they are intended to be useful for disturbance assessments, ecosystem accounting exercises, conservation priority setting, and marine protected area network design, along with other research and management applications.
","language":"English","publisher":"The Oceanography Society","doi":"10.5670/oceanog.2017.116","usgsCitation":"Sayre, R., Wright, D.J., Breyer, S.P., Butler, K., Van Graafeiland, K., Costello, M.J., Harris, P.T., Goodin, K., Guinotte, J.M., Basher, Z., Kavanaugh, M.T., Halpin, P.N., Monaco, M.E., Cressie, N., Aniello, P., Frye, C., and Stephens, D., 2017, A three-dimensional mapping of the ocean based on environmental data: Oceanography, v. 30, no. 1, p. 90-103, https://doi.org/10.5670/oceanog.2017.116.","productDescription":"14 p.","startPage":"90","endPage":"103","ipdsId":"IP-082069","costCenters":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true}],"links":[{"id":461345,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5670/oceanog.2017.116","text":"Publisher Index Page"},{"id":348684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb14e4b06e28e9c22bf1","contributors":{"authors":[{"text":"Sayre, Roger 0000-0001-6703-7105 rsayre@usgs.gov","orcid":"https://orcid.org/0000-0001-6703-7105","contributorId":191629,"corporation":false,"usgs":true,"family":"Sayre","given":"Roger","email":"rsayre@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true}],"preferred":true,"id":721752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Dawn J.","contributorId":191639,"corporation":false,"usgs":false,"family":"Wright","given":"Dawn","email":"","middleInitial":"J.","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":721753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breyer, Sean P.","contributorId":191634,"corporation":false,"usgs":false,"family":"Breyer","given":"Sean","email":"","middleInitial":"P.","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":721754,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butler, Kevin","contributorId":200270,"corporation":false,"usgs":false,"family":"Butler","given":"Kevin","email":"","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":721755,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Graafeiland, Keith","contributorId":200271,"corporation":false,"usgs":false,"family":"Van Graafeiland","given":"Keith","email":"","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":721756,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costello, Mark John","contributorId":146661,"corporation":false,"usgs":false,"family":"Costello","given":"Mark","email":"","middleInitial":"John","affiliations":[{"id":13376,"text":"The University of Auckland","active":true,"usgs":false}],"preferred":false,"id":721757,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harris, Peter T.","contributorId":200273,"corporation":false,"usgs":false,"family":"Harris","given":"Peter","email":"","middleInitial":"T.","affiliations":[{"id":35732,"text":"GRID-Arendal","active":true,"usgs":false}],"preferred":false,"id":721758,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goodin, Kathleen","contributorId":200274,"corporation":false,"usgs":false,"family":"Goodin","given":"Kathleen","affiliations":[{"id":17658,"text":"NatureServe","active":true,"usgs":false}],"preferred":false,"id":721759,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Guinotte, John M.","contributorId":200275,"corporation":false,"usgs":false,"family":"Guinotte","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":721760,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Basher, Zeenatul 0000-0002-6439-8324 zbasher@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-8324","contributorId":48118,"corporation":false,"usgs":true,"family":"Basher","given":"Zeenatul","email":"zbasher@usgs.gov","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":false,"id":721761,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kavanaugh, Maria T.","contributorId":200277,"corporation":false,"usgs":false,"family":"Kavanaugh","given":"Maria","email":"","middleInitial":"T.","affiliations":[{"id":13294,"text":"Woods Hole Oceanographic Institute","active":true,"usgs":false}],"preferred":false,"id":721762,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Halpin, Patrick N.","contributorId":200278,"corporation":false,"usgs":false,"family":"Halpin","given":"Patrick","email":"","middleInitial":"N.","affiliations":[{"id":12868,"text":"Nicholas School of the Environment, Duke University, Durham, NC, USA","active":true,"usgs":false}],"preferred":false,"id":721763,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Monaco, Mark E.","contributorId":200279,"corporation":false,"usgs":false,"family":"Monaco","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":721764,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cressie, Noel","contributorId":200280,"corporation":false,"usgs":false,"family":"Cressie","given":"Noel","email":"","affiliations":[{"id":16754,"text":"University of Wollongong, Australia","active":true,"usgs":false}],"preferred":false,"id":721765,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Aniello, Peter","contributorId":200281,"corporation":false,"usgs":false,"family":"Aniello","given":"Peter","email":"","affiliations":[{"id":34829,"text":"Sandia National Laboratories","active":true,"usgs":false}],"preferred":false,"id":721766,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Frye, Charles","contributorId":200282,"corporation":false,"usgs":false,"family":"Frye","given":"Charles","email":"","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":721767,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stephens, Drew","contributorId":200283,"corporation":false,"usgs":false,"family":"Stephens","given":"Drew","email":"","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":721768,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70193073,"text":"sir20175127 - 2017 - Flood-inundation maps for North Fork Salt Creek at Nashville, Indiana","interactions":[],"lastModifiedDate":"2017-11-14T11:17:30","indexId":"sir20175127","displayToPublicDate":"2017-11-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5127","title":"Flood-inundation maps for North Fork Salt Creek at Nashville, Indiana","docAbstract":"Digital flood-inundation maps for a 3.2-mile reach of North Fork Salt Creek at Nashville, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding that correspond to selected water levels (stages) at the North Fork Salt Creek at Nashville, Ind., streamgage (USGS station number 03371650). Real-time stages at this streamgage may be obtained from the USGS National Water Information System at http://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also shows observed USGS stages at the same site as the USGS streamgage (NWS site NFSI3).
Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current (2015) stage-discharge rating at the USGS streamgage 03371650, North Fork Salt Creek at Nashville, Ind. The hydraulic model was then used to compute 12 water-surface profiles for flood stages at 1-foot (ft) intervals, except for the highest profile of 22.9 ft, referenced to the streamgage datum ranging from 12.0 ft (the NWS “action stage”) to 22.9 ft, which is the highest stage of the current (2015) USGS stage-discharge rating curve and 1.9 ft higher than the NWS “major flood stage.” The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.98-ft vertical accuracy and 4.9-ft horizontal resolution) to delineate the area flooded at each stage.
The availability of these maps, along with information regarding current stage from the USGS streamgage, will provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175127","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Martin, Z.W., 2017, Flood-inundation maps for North Fork Salt Creek at Nashville, Indiana: U.S. Geological Survey Scientific Investigations Report 2017–5127, 10 p., https://doi.org/10.3133/sir20175127.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087895","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":348732,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5127/sir20175127.pdf","text":"Report","size":"1.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5127"},{"id":348733,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VQ316V","text":"USGS data release","description":"USGS Data Release","linkHelpText":"North Fork Salt Creek at Nashville, Indiana, flood-inundation model and GIS data"},{"id":348731,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5127/coverthb.jpg"}],"country":"United States","state":"Indiana","city":"Nashville","otherGeospatial":"North Fork Salt Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.26336097717285,\n 39.190954761524445\n ],\n [\n -86.22027397155762,\n 39.190954761524445\n ],\n [\n -86.22027397155762,\n 39.213036788153914\n ],\n [\n -86.26336097717285,\n 39.213036788153914\n ],\n [\n -86.26336097717285,\n 39.190954761524445\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard,
Indianapolis, IN 46278–1996
Late Quaternary paleoceanographic changes at the Lomonosov Ridge, central Arctic Ocean, were reconstructed from a multicore and gravity core recovered during the 2014 SWERUS-C3 Expedition. Ostracode assemblages dated by accelerator mass spectrometry (AMS) indicate changing sea-ice conditions and warm Atlantic Water (AW)inflow to the Arctic Ocean from ∼50 ka to present. Key taxa used as environmental indicators include Acetabulastoma arcticum (perennial sea ice), Polycopes pp. (variable sea-ice margins, high surface productivity), Krithe hunti (Arctic Ocean deep water), and Rabilimis mirabilis (water mass change/AW inflow). Results indicate periodic seasonally sea-ice-free conditions during Marine Isotope Stage (MIS) 3 (∼57-29 ka), rapid deglacial changes in water mass conditions (15-11 ka), seasonally sea-ice-free conditions during the early Holocene (∼10-7 ka) and perennial sea ice during the late Holocene. Comparisons with faunal records from other cores from the Mendeleev and Lomonosov ridges suggest generally similar patterns, although sea-ice cover during the Last Glacial Maximum may have been less extensive at the new Lomonosov Ridge core site (∼85.15° N, 152° E) than farther north and towards Greenland. The new data provide evidence for abrupt, large-scale shifts in ostracode species depth and geographical distributions during rapid climatic transitions.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-2017-22","usgsCitation":"Gemery, L., Cronin, T.M., Poirier, R.K., Pearce, C., Barrientos, N., O’Regan, M., Johansson, C., Koshurnikov, A., and Jakobsson, M., 2017, Central Arctic Ocean paleoceanography from ∼50 ka to present, on the basis of ostracode faunal assemblages from the SWERUS 2014 expedition : Climate of the Past, v. 13, p. 1473-1489, https://doi.org/10.5194/cp-2017-22.","productDescription":"17 p.","startPage":"1473","endPage":"1489","ipdsId":"IP-084428","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469326,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-2017-22","text":"Publisher Index Page"},{"id":348623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Ocean","volume":"13","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a096bafe4b09af898c94137","contributors":{"authors":[{"text":"Gemery, Laura 0000-0003-1966-8732 lgemery@usgs.gov","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":5402,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","email":"lgemery@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":717636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":717637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poirier, Robert K. rpoirier@usgs.gov","contributorId":5790,"corporation":false,"usgs":true,"family":"Poirier","given":"Robert","email":"rpoirier@usgs.gov","middleInitial":"K.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":717638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearce, Christof","contributorId":197126,"corporation":false,"usgs":false,"family":"Pearce","given":"Christof","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":717639,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barrientos, Natalia","contributorId":197127,"corporation":false,"usgs":false,"family":"Barrientos","given":"Natalia","email":"","affiliations":[{"id":35520,"text":"1Department of Geological Sciences and Bolin Centre for Climate Research, Stockholm University, Stockholm, 10691, Sweden","active":true,"usgs":false},{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":717640,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Regan, Matt","contributorId":197135,"corporation":false,"usgs":false,"family":"O’Regan","given":"Matt","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":717641,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johansson, Carina","contributorId":166871,"corporation":false,"usgs":false,"family":"Johansson","given":"Carina","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":717642,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koshurnikov, Andrey","contributorId":166860,"corporation":false,"usgs":false,"family":"Koshurnikov","given":"Andrey","email":"","affiliations":[{"id":24563,"text":"Tomsk Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":717644,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jakobsson, Martin","contributorId":166854,"corporation":false,"usgs":false,"family":"Jakobsson","given":"Martin","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":717643,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70192972,"text":"70192972 - 2017 - Hydrologic metrics for status-and-trends monitoring in urban and urbanizing watersheds","interactions":[],"lastModifiedDate":"2018-01-05T14:10:23","indexId":"70192972","displayToPublicDate":"2017-11-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic metrics for status-and-trends monitoring in urban and urbanizing watersheds","docAbstract":"Local governmental agencies are increasingly undertaking potentially costly “status-and-trends” monitoring to evaluate the effectiveness of stormwater control measures and land-use planning strategies, or to satisfy regulatory requirements. Little guidance is presently available for such efforts, and so we have explored the application, interpretation, and temporal limitations of well-established hydrologic metrics of runoff changes from urbanization, making use of an unusually long-duration, high-quality data set from the Pacific Northwest (USA) with direct applicability to urban and urbanizing watersheds. Three metrics previously identified for their utility in identifying hydrologic conditions with biological importance that respond to watershed urbanization—TQmean (the fraction of time that flows exceed the mean annual discharge), the Richards-Baker Index (characterizing flashiness relative to the mean discharge), and the annual tally of wet-season day-to-day flow reversals (the total number of days that reverse the prior days’ increasing or decreasing trend)—are all successful in stratifying watersheds across a range of urbanization, as measured by total contributing area of urban development. All metrics respond with statistical significance to multi-decadal trends in urbanization, but none detect trends in watershed-scale urbanization over the course of a single decade. This suggests a minimum period over which dependable trends in hydrologic alteration (or improvement) can be detected with confidence. The metrics also prove less well suited to urbanizing watersheds in a semi-arid climate, with only flow reversals showing a response consistent with prior findings from more humid regions. We also explore the use of stage as a surrogate for discharge in calculating these metrics, recognizing potentially significant agency cost savings in data collection with minimal loss of information. This approach is feasible but cannot be implemented under current data-reporting practices, requiring measurement of water-depth values and preservation of the full precision of the original recorded data. With these caveats, however, hydrologic metrics based on stage should prove as or more useful, at least in the context of status-and-trends monitoring, as those based on subsequent calculations of discharge.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11369","usgsCitation":"Booth, D.B., and Konrad, C.P., 2017, Hydrologic metrics for status-and-trends monitoring in urban and urbanizing watersheds: Hydrological Processes, v. 31, no. 25, p. 4507-4519, https://doi.org/10.1002/hyp.11369.","productDescription":"13 p.","startPage":"4507","endPage":"4519","ipdsId":"IP-090190","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":348629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"25","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-23","publicationStatus":"PW","scienceBaseUri":"5a096bb0e4b09af898c9413d","contributors":{"authors":[{"text":"Booth, Derek B.","contributorId":100873,"corporation":false,"usgs":false,"family":"Booth","given":"Derek","email":"","middleInitial":"B.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":717492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":1716,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717491,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192996,"text":"70192996 - 2017 - Sampling uncharted waters: Examining rearing habitat of larval Longfin Smelt (Spirinchus thaleichthys) in the upper San Francisco Estuary","interactions":[],"lastModifiedDate":"2017-11-12T12:44:02","indexId":"70192996","displayToPublicDate":"2017-11-12T00:00:00","publicationYear":"2017","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}},"displayTitle":"Sampling uncharted waters: Examining rearing habitat of larval Longfin Smelt (Spirinchus thaleichthys) in the upper San Francisco Estuary","title":"Sampling uncharted waters: Examining rearing habitat of larval Longfin Smelt (Spirinchus thaleichthys) in the upper San Francisco Estuary","docAbstract":"The southern-most reproducing Longfin Smelt population occurs in the San Francisco Estuary, California, USA. Long-term monitoring of estuarine habitat for this species has generally only considered deep channels, with little known of the role shallow waters play in supporting their early life stage. To address the need for focused research on shallow-water habitat, a targeted study of Longfin Smelt larvae in littoral habitat was conducted to identify potential rearing habitats during 2013 and 2014. Our study objectives were to (1) determine if larval densities vary between littoral habitats (tidal slough vs. open-water shoal), (2) determine how larval densities in littoral habitats vary with physicochemical and biological attributes, (3) determine if larval densities vary between littoral habitats and long-term monitoring channel collections, and (4) determine what factors predict larval rearing distributions from the long-term monitoring channel collections. Larval densities did not vary between littoral habitats but they did vary between years. Water temperature, salinity, and chlorophyll a were found important in predicting larval densities in littoral habitats. Larval densities do not vary between littoral and channel surveys; however, the analysis based on channel data suggests that Longfin Smelt are hatching and rearing in a much broader region and under higher salinities (∼2–12 psu) than previously recognized. Results of this study indicate that conservation efforts should consider how freshwater flow, habitat, climate, and food webs interact as mechanisms that influence Longfin Smelt recruitment in estuarine environments.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-017-0255-9","usgsCitation":"Grimaldo, L., Feyrer, F.V., Burns, J., and Maniscalco, D., 2017, Sampling uncharted waters: Examining rearing habitat of larval Longfin Smelt (Spirinchus thaleichthys) in the upper San Francisco Estuary: Estuaries and Coasts, v. 40, no. 6, p. 1771-1784, https://doi.org/10.1007/s12237-017-0255-9.","productDescription":"14 p.","startPage":"1771","endPage":"1784","ipdsId":"IP-085099","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":348624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay Estuary","volume":"40","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-17","publicationStatus":"PW","scienceBaseUri":"5a096bb0e4b09af898c9413b","contributors":{"authors":[{"text":"Grimaldo, Lenny","contributorId":10728,"corporation":false,"usgs":false,"family":"Grimaldo","given":"Lenny","email":"","affiliations":[{"id":35724,"text":"ICF, San Francisco, USA","active":true,"usgs":false}],"preferred":false,"id":717561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":178379,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Jillian","contributorId":198892,"corporation":false,"usgs":false,"family":"Burns","given":"Jillian","email":"","affiliations":[{"id":35724,"text":"ICF, San Francisco, USA","active":true,"usgs":false}],"preferred":false,"id":717562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maniscalco, Donna","contributorId":198893,"corporation":false,"usgs":false,"family":"Maniscalco","given":"Donna","email":"","affiliations":[{"id":35725,"text":"ICF, San Jose, USA","active":true,"usgs":false}],"preferred":false,"id":717563,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193273,"text":"70193273 - 2017 - The role of deep-water sedimentary processes in shaping a continental margin: The Northwest Atlantic","interactions":[],"lastModifiedDate":"2017-11-29T16:01:31","indexId":"70193273","displayToPublicDate":"2017-11-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"The role of deep-water sedimentary processes in shaping a continental margin: The Northwest Atlantic","docAbstract":"The tectonic history of a margin dictates its general shape; however, its geomorphology is generally transformed by deep-sea sedimentary processes. The objective of this study is to show the influences of turbidity currents, contour currents and sediment mass failures on the geomorphology of the deep-water northwestern Atlantic margin (NWAM) between Blake Ridge and Hudson Trough, spanning about 32° of latitude and the shelf edge to the abyssal plain. This assessment is based on new multibeam echosounder data, global bathymetric models and sub-surface geophysical information.
The deep-water NWAM is divided into four broad geomorphologic classifications based on their bathymetric shape: graded, above-grade, stepped and out-of-grade. These shapes were created as a function of the balance between sediment accumulation and removal that in turn were related to sedimentary processes and slope-accommodation. This descriptive method of classifying continental margins, while being non-interpretative, is more informative than the conventional continental shelf, slope and rise classification, and better facilitates interpretation concerning dominant sedimentary processes.
Areas of the margin dominated by turbidity currents and slope by-pass developed graded slopes. If sediments did not by-pass the slope due to accommodation then an above grade or stepped slope resulted. Geostrophic currents created sedimentary bodies of a variety of forms and positions along the NWAM. Detached drifts form linear, above-grade slopes along their crests from the shelf edge to the deep basin. Plastered drifts formed stepped slope profiles. Sediment mass failure has had a variety of consequences on the margin morphology; large mass-failures created out-of-grade profiles, whereas smaller mass failures tended to remain on the slope and formed above-grade profiles at trough-mouth fans, or nearly graded profiles, such as offshore Cape Fear.
An important unresolved question is how populations of coldwater-dependent fishes will respond to rapidly warming water temperatures. For example, the culturally and economically important group, Pacific salmon (Oncorhynchus spp.), experience site-specific thermal regimes during early development that could be disrupted by warming. To test for thermal local adaptation and heritable phenotypic plasticity in Pacific salmon embryos, we measured the developmental rate, survival, and body size at hatching in two populations of sockeye salmon (Oncorhynchus nerka) that overlap in timing of spawning but incubate in contrasting natural thermal regimes. Using a split half-sibling design, we exposed embryos of 10 families from each of two populations to variable and constant thermal regimes. These represented both experienced temperatures by each population, and predicted temperatures under plausible future conditions based on a warming scenario from the downscaled global climate model (MIROC A1B scenario). We did not find evidence of thermal local adaptation during the embryonic stage for developmental rate or survival. Within treatments, populations hatched within 1 day of each other, on average, and amongtreatments, did not differ in survival in response to temperature. We did detect plasticity to temperature; embryos developed 2.5 times longer (189 days) in the coolest regime compared to the warmest regime (74 days). We also detected variation in developmental rates among families within and among temperature regimes, indicating heritable plasticity. Families exhibited a strong positive relationship between thermal variability and phenotypic variability in developmental rate but body length and mass at hatching were largely insensitive to temperature. Overall, our results indicated a lack of thermal local adaptation, but a presence of plasticity in populations experiencing contrasting conditions, as well as family-specific heritable plasticity that could facilitate adaptive change.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13782","usgsCitation":"Sparks, M.M., Westley, P.A., Falke, J.A., and Quinn, T.P., 2017, Thermal adaptation and phenotypic plasticity in a warming world: Insights from common garden experiments on Alaskan sockeye salmon: Global Change Biology, v. 23, no. 12, p. 5203-5217, https://doi.org/10.1111/gcb.13782.","productDescription":"15 p.","startPage":"5203","endPage":"5217","ipdsId":"IP-081151","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-06","publicationStatus":"PW","scienceBaseUri":"5a06c8c5e4b09af898c860d5","contributors":{"authors":[{"text":"Sparks, Morgan M.","contributorId":200252,"corporation":false,"usgs":false,"family":"Sparks","given":"Morgan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westley, Peter A. H.","contributorId":190530,"corporation":false,"usgs":false,"family":"Westley","given":"Peter","email":"","middleInitial":"A. H.","affiliations":[],"preferred":false,"id":721608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quinn, Thomas P.","contributorId":167272,"corporation":false,"usgs":false,"family":"Quinn","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24671,"text":"School of Aquatic and Fsiery Sciences, UW, Box 355020, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":721609,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207059,"text":"70207059 - 2017 - Inland fisheries – Invisible but integral to the UN Sustainable Development Agenda for ending poverty by 2030","interactions":[],"lastModifiedDate":"2019-12-04T15:52:41","indexId":"70207059","displayToPublicDate":"2017-11-09T15:41:54","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1841,"text":"Global Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"Inland fisheries – Invisible but integral to the UN Sustainable Development Agenda for ending poverty by 2030","docAbstract":"The United Nations’ (UN) 2030 Agenda for Sustainable Development defines the formidable challenge of integrating historically separate economic, social, and environmental goals into a unified ‘plan of action for people, planet, and prosperity.’ We highlight the substantial contribution inland fisheries can make towards preventing increased poverty and, in some cases, alleviating poverty (i.e. addressing Sustainable Development Goal [SDG] 1: No Poverty) as an opportunity to inform the next set of development agendas and their associated budgets and priorities. Overlooking the contribution of inland fisheries to poverty prevention and alleviation may undermine the capacity to successfully meet the development goals, especially in rural communities in Low-Income Food-Deficit countries. Inland fisheries are essential for food and economic security as the vast majority are small-scale operations or subsistence, predominantly used by poorer groups. Protecting inland fisheries from diverse threats from other water users and associated sectors requires robust, multi-sectoral, and multinational policies that can be brought about by global initiatives like the SDGs. Without such protection, their vital contribution towards sustainable livelihoods and poverty issues becomes uncertain. Further, integrating inland fisheries into sustainable development frameworks strengthens the likelihood of achieving the UN Agenda for Sustainable Development. In this perspective article, we posit that including inland fisheries in national policy statements and programs can prove beneficial to promoting economic and social growth for the poor, preventing further poverty, and achieving SDG 1 and other SDG targets, especially those related to food security.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloenvcha.2017.10.005","usgsCitation":"Lynch, A., Cowx, I., Fluet-Chouinard, E., Glaser, S.M., Phang, S.C., Beard, T., Bower, S.D., Brooks, J., Bunnell, D.B., Claussen, J., Cooke, S.J., Kao, Y., Lorenzen, K., Myers, B., Reid, A.J., Taylor, J.J., and Youn, S., 2017, Inland fisheries – Invisible but integral to the UN Sustainable Development Agenda for ending poverty by 2030: Global Environmental Change, v. 47, p. 167-173, https://doi.org/10.1016/j.gloenvcha.2017.10.005.","productDescription":"7 p.","startPage":"167","endPage":"173","ipdsId":"IP-085649","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":488850,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hull-repository.worktribe.com/output/529008","text":"External Repository"},{"id":369922,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lynch, Abigail 0000-0001-8449-8392 ajlynch@usgs.gov","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":169460,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","email":"ajlynch@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":776667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cowx, I.G.","contributorId":48794,"corporation":false,"usgs":true,"family":"Cowx","given":"I.G.","email":"","affiliations":[],"preferred":false,"id":776668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fluet-Chouinard, Etienne","contributorId":217392,"corporation":false,"usgs":false,"family":"Fluet-Chouinard","given":"Etienne","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":776669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glaser, S. M.","contributorId":221027,"corporation":false,"usgs":false,"family":"Glaser","given":"S.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":776670,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phang, Sui C.","contributorId":169462,"corporation":false,"usgs":false,"family":"Phang","given":"Sui","email":"","middleInitial":"C.","affiliations":[{"id":6714,"text":"Ohio State University, School of Earth Sciences, Columbus, Ohio, USA","active":true,"usgs":false}],"preferred":false,"id":776671,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beard, T. Douglas Jr. dbeard@usgs.gov","contributorId":150495,"corporation":false,"usgs":true,"family":"Beard","given":"T. Douglas","suffix":"Jr.","email":"dbeard@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":false,"id":776672,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bower, S. D.","contributorId":221028,"corporation":false,"usgs":false,"family":"Bower","given":"S.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":776673,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brooks, J.L.","contributorId":10759,"corporation":false,"usgs":true,"family":"Brooks","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":776674,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":195888,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","email":"dbunnell@usgs.gov","middleInitial":"B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":776675,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Claussen, Julie","contributorId":150973,"corporation":false,"usgs":false,"family":"Claussen","given":"Julie","affiliations":[{"id":12458,"text":"Illinois Natural History Survey, Lake Michigan Biological Station","active":true,"usgs":false}],"preferred":false,"id":776676,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cooke, S. J.","contributorId":55645,"corporation":false,"usgs":false,"family":"Cooke","given":"S.","email":"","middleInitial":"J.","affiliations":[{"id":16718,"text":"Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada","active":true,"usgs":false}],"preferred":false,"id":776677,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kao, Yu-Chun 0000-0001-5552-909X ykao@usgs.gov","orcid":"https://orcid.org/0000-0001-5552-909X","contributorId":192240,"corporation":false,"usgs":true,"family":"Kao","given":"Yu-Chun","email":"ykao@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":776678,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lorenzen, Kai","contributorId":169476,"corporation":false,"usgs":false,"family":"Lorenzen","given":"Kai","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":776679,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Myers, Bonnie 0000-0002-3170-2633 bjmyers@usgs.gov","orcid":"https://orcid.org/0000-0002-3170-2633","contributorId":176495,"corporation":false,"usgs":true,"family":"Myers","given":"Bonnie","email":"bjmyers@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":776680,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Reid, Andrea J.","contributorId":221029,"corporation":false,"usgs":false,"family":"Reid","given":"Andrea","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":776681,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Taylor, J. J.","contributorId":221030,"corporation":false,"usgs":false,"family":"Taylor","given":"J.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":776682,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Youn, S.","contributorId":221031,"corporation":false,"usgs":false,"family":"Youn","given":"S.","affiliations":[],"preferred":false,"id":776683,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70193809,"text":"70193809 - 2017 - Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection","interactions":[],"lastModifiedDate":"2017-11-09T11:57:32","indexId":"70193809","displayToPublicDate":"2017-11-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection","docAbstract":"Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-21-5443-2017","usgsCitation":"Poole, S., Vis, M., Knight, R., and Seibert, J., 2017, Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection: Hydrology and Earth System Sciences, v. 21, p. 5443-5457, https://doi.org/10.5194/hess-21-5443-2017.","productDescription":"15 p.","startPage":"5443","endPage":"5457","ipdsId":"IP-078840","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":469334,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-21-5443-2017","text":"Publisher Index Page"},{"id":348538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Tennessee River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.549560546875,\n 36.474306755095206\n ],\n [\n -89.40673828124999,\n 36.1290016556965\n ],\n [\n -88.450927734375,\n 34.49750272138159\n ],\n [\n -88.04443359375,\n 34.125447565116126\n ],\n [\n -87.29736328125,\n 34.125447565116126\n ],\n [\n -86.63818359374999,\n 34.11635246997272\n ],\n [\n -85.924072265625,\n 34.30714385628802\n ],\n [\n -85.71533203124999,\n 34.56990638085633\n ],\n [\n -85.60546875,\n 34.93998515156041\n ],\n [\n -84.99023437499999,\n 34.99400375757575\n ],\n [\n -84.57275390624999,\n 34.858890491257796\n ],\n [\n -84.12231445312499,\n 34.867904962568744\n ],\n [\n -83.60595703124999,\n 35.54116627999815\n ],\n [\n -83.03466796874999,\n 35.71975793933433\n ],\n [\n -82.86987304687499,\n 35.90684930677118\n ],\n [\n -82.46337890625,\n 36.01356058518151\n ],\n [\n -81.91406249999999,\n 36.1822249804225\n ],\n [\n -81.94702148437499,\n 36.70365959719453\n ],\n [\n -81.73828125,\n 37.21283151445594\n ],\n [\n -81.771240234375,\n 37.39634613318923\n ],\n [\n -81.990966796875,\n 37.47485808497102\n ],\n [\n -82.24365234375,\n 37.33522435930639\n ],\n [\n -83.34228515624999,\n 36.84446074079561\n ],\n [\n -84.08935546874999,\n 36.76529191711621\n ],\n [\n -84.86938476562499,\n 36.756490329505155\n ],\n [\n -85.62744140624999,\n 36.633162095586556\n ],\n [\n -85.81420898437499,\n 36.27970720524017\n ],\n [\n -86.91284179687499,\n 36.11125252076156\n ],\n [\n -87.50610351562499,\n 36.32397712011264\n ],\n [\n -87.80273437499999,\n 36.712467243386264\n ],\n [\n -88.01147460937499,\n 37.020098201368086\n ],\n [\n -88.2861328125,\n 37.142803443716836\n ],\n [\n -88.51684570312499,\n 37.05517710666079\n ],\n [\n -88.72558593749999,\n 37.10776507118514\n ],\n [\n -89.03320312499999,\n 37.17782559332976\n ],\n [\n -89.18701171874999,\n 37.02886944696474\n ],\n [\n -89.12109375,\n 36.976226784640936\n ],\n [\n -89.28588867187499,\n 36.5449494414832\n ],\n [\n -89.43969726562499,\n 36.55377524336086\n ],\n [\n -89.549560546875,\n 36.474306755095206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-06","publicationStatus":"PW","scienceBaseUri":"5a05771de4b09af898c70868","contributors":{"authors":[{"text":"Poole, Sandra","contributorId":174147,"corporation":false,"usgs":false,"family":"Poole","given":"Sandra","email":"","affiliations":[{"id":27368,"text":"University of Zurich","active":true,"usgs":false}],"preferred":false,"id":720577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vis, Marc","contributorId":174146,"corporation":false,"usgs":false,"family":"Vis","given":"Marc","email":"","affiliations":[{"id":27368,"text":"University of Zurich","active":true,"usgs":false}],"preferred":false,"id":720578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Rodney 0000-0001-9588-0167 rrknight@usgs.gov","orcid":"https://orcid.org/0000-0001-9588-0167","contributorId":152422,"corporation":false,"usgs":true,"family":"Knight","given":"Rodney","email":"rrknight@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":720576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seibert, Jan","contributorId":176322,"corporation":false,"usgs":false,"family":"Seibert","given":"Jan","email":"","affiliations":[],"preferred":false,"id":720579,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193817,"text":"70193817 - 2017 - Windows of susceptibility and consequences of early life exposures to 17β–estradiol on medaka (Oryzias latipes) reproductive success","interactions":[],"lastModifiedDate":"2017-11-10T09:56:53","indexId":"70193817","displayToPublicDate":"2017-11-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Windows of susceptibility and consequences of early life exposures to 17β–estradiol on medaka (Oryzias latipes) reproductive success","docAbstract":"Estrogens and estrogen mimics are commonly found in surface waters and are associated with deleterious effects in fish populations. Impaired fertility and fecundity in fish following chronic exposures to estrogens and estrogen mimics during critical windows in development are well documented. However, information regarding differential reproductive effects of exposure within defined developmental stages remains sparse. In this study, reproductive capacity was assessed in Japanese medaka (Oryzias latipes) after exposure to two concentrations of 17β–estradiol (E2β; 2 ng/L and 50 ng/L) during four distinct stages of development: gonad development, gonad differentiation, development of secondary sex characteristics (SSC) and gametogenesis. Exposure to E2β did not adversely impact survival, hatch success, growth, or genotypic ratios. In contrast, exposure to 50 ng/L E2β during SSC development altered phenotypic ratios and SSC. Exposure to both E2β treatments reduced reproductive capacity (fertility, fecundity) by 7.3–57.4% in adult medaka breeding pairs, with hindrance of SSC development resulting in the largest disruption in breeding capacity (51.6–57.4% decrease) in the high concentration. This study documents differential effects among four critical stages of development and provides insight into factors (window of exposure, exposure concentration and duration of exposure period) contributing to reproductive disruption in fish.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.7b01568","usgsCitation":"Lee Pow, C.S., Tilahun, K., Creech, K., Law, J.M., Cope, W., Kwak, T.J., Rice, J., Aday, D.D., and Kullman, S.W., 2017, Windows of susceptibility and consequences of early life exposures to 17β–estradiol on medaka (Oryzias latipes) reproductive success: Environmental Science & Technology, v. 51, no. 9, p. 5296-5305, https://doi.org/10.1021/acs.est.7b01568.","productDescription":"10 p.","startPage":"5296","endPage":"5305","ipdsId":"IP-086265","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-20","publicationStatus":"PW","scienceBaseUri":"5a05771ce4b09af898c70865","contributors":{"authors":[{"text":"Lee Pow, Crystal S. D.","contributorId":176861,"corporation":false,"usgs":false,"family":"Lee Pow","given":"Crystal","email":"","middleInitial":"S. D.","affiliations":[],"preferred":false,"id":721443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tilahun, Kedamawit","contributorId":200213,"corporation":false,"usgs":false,"family":"Tilahun","given":"Kedamawit","email":"","affiliations":[],"preferred":false,"id":721444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Creech, Kari","contributorId":200214,"corporation":false,"usgs":false,"family":"Creech","given":"Kari","email":"","affiliations":[],"preferred":false,"id":721445,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Law, J. Mac","contributorId":176862,"corporation":false,"usgs":false,"family":"Law","given":"J.","email":"","middleInitial":"Mac","affiliations":[],"preferred":false,"id":721446,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":721447,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720597,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rice, James A.","contributorId":176863,"corporation":false,"usgs":false,"family":"Rice","given":"James A.","affiliations":[],"preferred":false,"id":721448,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Aday, D. Derek","contributorId":176864,"corporation":false,"usgs":false,"family":"Aday","given":"D.","email":"","middleInitial":"Derek","affiliations":[],"preferred":false,"id":721449,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kullman, Seth W.","contributorId":62516,"corporation":false,"usgs":true,"family":"Kullman","given":"Seth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":721450,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}