This map product contains a map sheet at 1:1,506,000 scale that shows the geology of the Nepenthes Planum region of Mars, which is located between the cratered highlands that dominate the southern hemisphere and the less-cratered sedimentary plains that dominate the northern hemisphere. The map region contains cone- and mound-shaped landforms as well as lobate materials that are morphologically similar to terrestrial igneous or mud vents and flows. This map is part of an informal series of small-scale (large-area) maps aimed at refining current understanding of the geologic units and structures that make up the highland-to-lowland transition zone. The map base consists of a controlled Thermal Emission Imaging System (THEMIS) daytime infrared image mosaic (100 meters per pixel resolution) supplemented by a Mars Orbiter Laser Altimeter (MOLA) digital elevation model (463 meters per pixel resolution). The map includes a Description of Map Units and a Correlation of Map Units that describes and correlates units identified across the entire map region. The geologic map was assembled using ArcGIS software by Environmental Systems Research Institute (http://www.esri.com). The ArcGIS project, geodatabase, base map, and all map components are included online as supplemental data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3389","usgsCitation":"Skinner, J.A., Jr., and Tanaka, K.L., 2018, Geologic map of the Nepenthes Planum Region, Mars: U.S. Geological Survey Scientific Investigations Map 3389, pamphlet 11 p., scale 1:1,506,000, https://doi.org/10.3133/sim3389.","productDescription":"Map: 45.60 x 38.82 inches; Pamphlet: i, 11 p.; Metadata, Spatial Data; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078987","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":437979,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95837GN","text":"USGS data release","linkHelpText":"Interactive Map: USGS SIM 3389 Geologic Map of the Nepenthes Planum Region, Mars"},{"id":352459,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3389/coverthb.jpg"},{"id":352467,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_gis.zip","text":"GIS Files","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3389"},{"id":352463,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_readme.txt","text":"Read Me","size":"4 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3389"},{"id":352462,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_pamphlet.pdf","text":"Pamphlet","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3389"},{"id":352461,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_mapsheet.pdf","text":"Map","size":"74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3389"},{"id":352460,"rank":2,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_geomap_metadata.xml","size":"7 KB","description":"SIM 3389 Metadata"},{"id":400823,"rank":7,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P95837GN","text":"Interactive map","linkHelpText":"- Geologic map of the Nepenthes Planum Region, Mars, 1:1,506,000, Skinner et al. (2018)"}],"contact":"Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon–climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km2 for the RCP4.5 climate and between 6 and 16 million km2 for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbon varied between 66-Pg C (1015-g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. This assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon–climate feedback.
","language":"English","publisher":"National Academy of Sciences of the United States of America","doi":"10.1073/pnas.1719903115","usgsCitation":"McGuire, A.D., Lawrence, D.M., Koven, C., Clein, J.S., Burke, E.J., Chen, G., Jafarov, E., MacDougall, A.H., Marchenko, S., Nicolsky, D.J., Peng, S., Rinke, A., Ciais, P., Gouttevin, I., Hayes, D.J., Ji, D., Krinner, G., Moore, J., Romanovsky, V., Schadel, C., Schaefer, K., Schuur, E.A., and Zhuang, Q., 2018, Dependence of the evolution of carbon dynamics in the northern permafrost region on the trajectory of climate change: Proceedings of the National Academy of Sciences of the United States of America, v. 115, no. 15, p. 3882-3887, https://doi.org/10.1073/pnas.1719903115.","productDescription":"6 p.","startPage":"3882","endPage":"3887","ipdsId":"IP-092577","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468896,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1719903115","text":"Publisher Index Page"},{"id":354152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"15","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-26","publicationStatus":"PW","scienceBaseUri":"5afee6f7e4b0da30c1bfbfd4","contributors":{"authors":[{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":735188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, David M.","contributorId":105206,"corporation":false,"usgs":false,"family":"Lawrence","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":7166,"text":"Johns Hopkins University Applied Physics Laboratory","active":true,"usgs":false}],"preferred":false,"id":735253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koven, Charles","contributorId":51143,"corporation":false,"usgs":true,"family":"Koven","given":"Charles","affiliations":[],"preferred":false,"id":735254,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clein, Joy S.","contributorId":83697,"corporation":false,"usgs":true,"family":"Clein","given":"Joy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":735255,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burke, Eleanor J.","contributorId":172358,"corporation":false,"usgs":false,"family":"Burke","given":"Eleanor","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":735256,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chen, Guangsheng","contributorId":200153,"corporation":false,"usgs":false,"family":"Chen","given":"Guangsheng","email":"","affiliations":[],"preferred":false,"id":735257,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jafarov, Elchin","contributorId":195182,"corporation":false,"usgs":false,"family":"Jafarov","given":"Elchin","affiliations":[],"preferred":false,"id":735258,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"MacDougall, Andrew H.","contributorId":200165,"corporation":false,"usgs":false,"family":"MacDougall","given":"Andrew","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":735259,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Marchenko, Sergey S.","contributorId":93368,"corporation":false,"usgs":true,"family":"Marchenko","given":"Sergey S.","affiliations":[],"preferred":false,"id":735260,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nicolsky, Dmitry J.","contributorId":83016,"corporation":false,"usgs":true,"family":"Nicolsky","given":"Dmitry","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":735261,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Peng, Shushi","contributorId":172355,"corporation":false,"usgs":false,"family":"Peng","given":"Shushi","email":"","affiliations":[{"id":16636,"text":"CNRS","active":true,"usgs":false}],"preferred":false,"id":735262,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rinke, Annette","contributorId":172352,"corporation":false,"usgs":false,"family":"Rinke","given":"Annette","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":735263,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ciais, Philippe 0000-0001-8560-4943","orcid":"https://orcid.org/0000-0001-8560-4943","contributorId":197934,"corporation":false,"usgs":false,"family":"Ciais","given":"Philippe","email":"","affiliations":[{"id":35082,"text":"LSCE, CEA CNRS UVSQ IPSL, Université Paris Saclay, 91191 Gif sur Yvette, France","active":true,"usgs":false}],"preferred":false,"id":735264,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gouttevin, Isabelle","contributorId":172365,"corporation":false,"usgs":false,"family":"Gouttevin","given":"Isabelle","email":"","affiliations":[{"id":16636,"text":"CNRS","active":true,"usgs":false}],"preferred":false,"id":735265,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hayes, Daniel J.","contributorId":100237,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":735266,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Ji, Duoying","contributorId":172353,"corporation":false,"usgs":false,"family":"Ji","given":"Duoying","email":"","affiliations":[],"preferred":false,"id":735267,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Krinner, Gerhard","contributorId":172367,"corporation":false,"usgs":false,"family":"Krinner","given":"Gerhard","email":"","affiliations":[{"id":16636,"text":"CNRS","active":true,"usgs":false}],"preferred":false,"id":735268,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Moore, John C.","contributorId":152072,"corporation":false,"usgs":false,"family":"Moore","given":"John C.","affiliations":[],"preferred":false,"id":735269,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Romanovsky, Vladimir","contributorId":175208,"corporation":false,"usgs":false,"family":"Romanovsky","given":"Vladimir","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":735270,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Schadel, Christina","contributorId":202385,"corporation":false,"usgs":false,"family":"Schadel","given":"Christina","email":"","affiliations":[{"id":36405,"text":"University of Northern Arizona","active":true,"usgs":false}],"preferred":false,"id":735271,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Schaefer, Kevin","contributorId":63323,"corporation":false,"usgs":true,"family":"Schaefer","given":"Kevin","affiliations":[],"preferred":false,"id":735272,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Schuur, Edward A.G.","contributorId":50026,"corporation":false,"usgs":true,"family":"Schuur","given":"Edward","email":"","middleInitial":"A.G.","affiliations":[],"preferred":false,"id":735273,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Zhuang, Qianlai","contributorId":101975,"corporation":false,"usgs":true,"family":"Zhuang","given":"Qianlai","affiliations":[],"preferred":false,"id":735274,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70196192,"text":"70196192 - 2018 - Drivers of solar radiation variability in the McMurdo Dry Valleys, Antarctica","interactions":[],"lastModifiedDate":"2018-04-02T13:38:04","indexId":"70196192","displayToPublicDate":"2018-03-26T00:00:00","publicationYear":"2018","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":"Drivers of solar radiation variability in the McMurdo Dry Valleys, Antarctica","docAbstract":"Annually averaged solar radiation in the McMurdo Dry Valleys, Antarctica has varied by over 20 W m−2 during the past three decades; however, the drivers of this variability are unknown. Because small differences in radiation are important to water availability and ecosystem functioning in polar deserts, determining the causes are important to predictions of future desert processes. We examine the potential drivers of solar variability and systematically eliminate all but stratospheric sulfur dioxide. We argue that increases in stratospheric sulfur dioxide increase stratospheric aerosol optical depth and decrease solar intensity. Because of the polar location of the McMurdo Dry Valleys (77–78°S) and relatively long solar ray path through the stratosphere, terrestrial solar intensity is sensitive to small differences in stratospheric transmissivity. Important sources of sulfur dioxide include natural (wildfires and volcanic eruptions) and anthropogenic emission.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-018-23390-7","usgsCitation":"Obryk, M., Fountain, A.G., Doran, P., Lyons, B., and Eastman, R., 2018, Drivers of solar radiation variability in the McMurdo Dry Valleys, Antarctica: Scientific Reports, v. 8, no. 1, Article number: 5002; 7 p., https://doi.org/10.1038/s41598-018-23390-7.","productDescription":"Article number: 5002; 7 p.","ipdsId":"IP-086694","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468895,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-23390-7","text":"Publisher Index Page"},{"id":352761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":352746,"type":{"id":15,"text":"Index Page"},"url":"https://www.nature.com/articles/s41598-018-23390-7"}],"otherGeospatial":"McMurdo Dry Valleys, Antarctica","volume":"8","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-22","publicationStatus":"PW","scienceBaseUri":"5afee6f8e4b0da30c1bfbfe4","contributors":{"authors":[{"text":"Obryk, Maciej K. 0000-0002-8182-8656","orcid":"https://orcid.org/0000-0002-8182-8656","contributorId":203477,"corporation":false,"usgs":true,"family":"Obryk","given":"Maciej","middleInitial":"K.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":731594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fountain, Andrew G.","contributorId":10410,"corporation":false,"usgs":false,"family":"Fountain","given":"Andrew","email":"","middleInitial":"G.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":731595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doran, Peter","contributorId":203478,"corporation":false,"usgs":false,"family":"Doran","given":"Peter","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":731596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, Berry","contributorId":203479,"corporation":false,"usgs":false,"family":"Lyons","given":"Berry","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":731597,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eastman, Ryan","contributorId":203480,"corporation":false,"usgs":false,"family":"Eastman","given":"Ryan","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":731598,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217814,"text":"70217814 - 2018 - Combining multiphase groundwater flow and slope stability models to assess stratovolcano flank collapse in the Cascade Range","interactions":[],"lastModifiedDate":"2021-02-04T14:03:53.275399","indexId":"70217814","displayToPublicDate":"2018-03-25T08:00:39","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6453,"text":"Journal of Geophysical Research Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Combining multiphase groundwater flow and slope stability models to assess stratovolcano flank collapse in the Cascade Range","docAbstract":"Hydrothermal alteration can create low‐permeability zones, potentially resulting in elevated pore‐fluid pressures, within a volcanic edifice. Strength reduction by rock alteration and high pore‐fluid pressures have been suggested as a mechanism for edifice flank instability. Here we combine numerical models of multiphase heat transport and groundwater flow with a slope‐stability code that incorporates three‐dimensional distributions of strength and pore‐water pressure to address the following questions: (1) What permeability distributions and contrasts produce elevated pore‐fluid pressures in a stratovolcano? (2) What are the effects of these elevated pressures on flank stability? (3) Finally, what are the effects of magma intrusion on potential flank failure in an edifice? Simulation results show that under a range of plausible parameters, water tables in a stratovolcano can be elevated or perched. These elevated water tables result in universally lower stability (lower factor of safety) compared with equivalent dry edifices, indicating a higher likelihood of flank collapse. Low‐permeability (<1 × 10−17 m2) layers such as altered pyroclastic deposits or breccias can result in locally saturated regions (perched water) and lower factors of safety near the ground surface but may actually reduce liquid water saturation and pore pressures in the core of the edifice and thus may favor small, shallow collapses over larger, deeper collapses. Magma intrusion into the base of the edifice increases pore‐fluid pressures and decreases the factor of safety. However, the shear strength of edifice rocks also exerts a significant control on stability, so both mechanical properties and pore‐fluid pressures are important for stability assessments.
Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Program’s Priority Basin Project assesses the quality of groundwater resources used for drinking water supply and increases public access to groundwater-quality information. In the Mokelumne, Cosumnes, and American River Watersheds of the Sierra Nevada, many rural households rely on private wells for their drinking-water supplies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181047","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Fram, M.S., and Shelton, J.L., 2018, Groundwater quality in the Mokelumne, Cosumnes, and American River Watersheds, Sierra Nevada, California: U.S. Geological Survey Open-File Report 2018-1047, 4 p., https://doi.org/10.3133/ofr20181047.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-094012","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437981,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78G8JXP","text":"USGS data release","linkHelpText":"GROUNDWATER-QUALITY DATA IN THE MOKELUMNE, COSUMNES, AND AMERICAN RIVER WATERSHEDS SHALLOW AQUIFER STUDY UNIT, 2016-2017: RESULTS FROM THE CALIFORNIA GAMA PRIORITY BASIN PROJECT"},{"id":352749,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1047/coverthb.jpg"},{"id":352750,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1047/ofr20181047_.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1047"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.25,\n 38.18314846626173\n ],\n [\n -120,\n 38.18314846626173\n ],\n [\n -120,\n 39.35341418045878\n ],\n [\n -121.25,\n 39.35341418045878\n ],\n [\n -121.25,\n 38.18314846626173\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"California Water Science Center
California GAMA
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
In the Colorado Front Range (USA), disturbance history dictates stream planform. Undisturbed, old-growth streams have multiple channels and large amounts of wood and depositional habitat. Disturbed streams (wildfires and logging < 200 years ago) are single-channeled with mostly erosional habitat. We tested how these opposing stream states influenced organic matter, benthic macroinvertebrate secondary production, emerging aquatic insect flux, and riparian spider biomass. Organic matter and macroinvertebrate production did not differ among sites per unit area (m−2), but values were 2 ×–21 × higher in undisturbed reaches per unit of stream valley (m−1 valley) because total stream area was higher in undisturbed reaches. Insect emergence was similar among streams at the per unit area and per unit of stream valley. However, rescaling insect emergence to per meter of stream bank showed that the emerging insect biomass reaching the stream bank was lower in undisturbed sites because multi-channel reaches had 3 × more stream bank than single-channel reaches. Riparian spider biomass followed the same pattern as emerging aquatic insects, and we attribute this to bottom-up limitation caused by the multi-channeled undisturbed sites diluting prey quantity (emerging insects) reaching the stream bank (riparian spider habitat). These results show that historic landscape disturbances continue to influence stream and riparian communities in the Colorado Front Range. However, these legacy effects are only weakly influencing habitat-specific function and instead are primarily influencing stream–riparian community productivity by dictating both stream planform (total stream area, total stream bank length) and the proportional distribution of specific habitat types (pools vs riffles).
","language":"English","publisher":"Springer","doi":"10.1007/s00442-018-4106-6","usgsCitation":"Venarsky, M.P., Walters, D.M., Hall, R., Livers, B., and Wohl, E., 2018, Shifting stream planform state decreases stream productivity yet increases riparian animal production: Oecologia, v. 187, no. 1, p. 167-180, https://doi.org/10.1007/s00442-018-4106-6.","productDescription":"14 p.","startPage":"167","endPage":"180","ipdsId":"IP-087083","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":352745,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"187","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-06","publicationStatus":"PW","scienceBaseUri":"5afee6f8e4b0da30c1bfbfee","contributors":{"authors":[{"text":"Venarsky, Michael P.","contributorId":203472,"corporation":false,"usgs":false,"family":"Venarsky","given":"Michael","email":"","middleInitial":"P.","affiliations":[{"id":7117,"text":"Griffith University","active":true,"usgs":false}],"preferred":false,"id":731587,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walters, David M. 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":140992,"corporation":false,"usgs":true,"family":"Walters","given":"David","email":"waltersd@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":731586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Robert O. Jr.","contributorId":104182,"corporation":false,"usgs":true,"family":"Hall","given":"Robert O.","suffix":"Jr.","affiliations":[],"preferred":false,"id":731588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Livers, Bridget","contributorId":203474,"corporation":false,"usgs":false,"family":"Livers","given":"Bridget","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":731589,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wohl, Ellen 0000-0001-7435-5013","orcid":"https://orcid.org/0000-0001-7435-5013","contributorId":194945,"corporation":false,"usgs":false,"family":"Wohl","given":"Ellen","affiliations":[],"preferred":false,"id":731590,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196186,"text":"70196186 - 2018 - The role of frozen soil in groundwater discharge predictions for warming alpine watersheds","interactions":[],"lastModifiedDate":"2018-04-27T16:38:29","indexId":"70196186","displayToPublicDate":"2018-03-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The role of frozen soil in groundwater discharge predictions for warming alpine watersheds","docAbstract":"Climate warming may alter the quantity and timing of groundwater discharge to streams in high alpine watersheds due to changes in the timing of the duration of seasonal freezing in the subsurface and snowmelt recharge. It is imperative to understand the effects of seasonal freezing and recharge on groundwater discharge to streams in warming alpine watersheds as streamflow originating from these watersheds is a critical water resource for downstream users. This study evaluates how climate warming may alter groundwater discharge due to changes in seasonally frozen ground and snowmelt using a 2‐D coupled flow and heat transport model with freeze and thaw capabilities for variably saturated media. The model is applied to a representative snowmelt‐dominated watershed in the Rocky Mountains of central Colorado, USA, with snowmelt time series reconstructed from a 12 year data set of hydrometeorological records and satellite‐derived snow covered area. Model analyses indicate that the duration of seasonal freezing in the subsurface controls groundwater discharge to streams, while snowmelt timing controls groundwater discharge to hillslope faces. Climate warming causes changes to subsurface ice content and duration, rerouting groundwater flow paths but not altering the total magnitude of future groundwater discharge outside of the bounds of hydrologic parameter uncertainties. These findings suggest that frozen soil routines play an important role for predicting the future location of groundwater discharge in watersheds underlain by seasonally frozen ground.
","language":"English","publisher":"AGU","doi":"10.1002/2017WR022098","usgsCitation":"Evans, S.G., Ge, S., Voss, C.I., and Molotch, N.P., 2018, The role of frozen soil in groundwater discharge predictions for warming alpine watersheds: Water Resources Research, v. 54, no. 3, p. 1599-1615, https://doi.org/10.1002/2017WR022098.","productDescription":"17 p.","startPage":"1599","endPage":"1615","ipdsId":"IP-093839","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":468898,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr022098","text":"Publisher Index Page"},{"id":352744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.64702033996582,\n 40.03182061333687\n ],\n [\n -105.57663917541504,\n 40.03182061333687\n ],\n [\n -105.57663917541504,\n 40.05902304741144\n ],\n [\n -105.64702033996582,\n 40.05902304741144\n ],\n [\n -105.64702033996582,\n 40.03182061333687\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-07","publicationStatus":"PW","scienceBaseUri":"5afee6f8e4b0da30c1bfbff2","contributors":{"authors":[{"text":"Evans, Sarah G.","contributorId":203464,"corporation":false,"usgs":false,"family":"Evans","given":"Sarah","email":"","middleInitial":"G.","affiliations":[{"id":36626,"text":"Appalachian State University","active":true,"usgs":false}],"preferred":false,"id":731568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ge, Shemin","contributorId":203465,"corporation":false,"usgs":false,"family":"Ge","given":"Shemin","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":731569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":731567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Molotch, Noah P. 0000-0003-4733-8060","orcid":"https://orcid.org/0000-0003-4733-8060","contributorId":203466,"corporation":false,"usgs":false,"family":"Molotch","given":"Noah","email":"","middleInitial":"P.","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":731570,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196187,"text":"70196187 - 2018 - Functional group, biomass, and climate change effects on ecological drought in semiarid grasslands","interactions":[],"lastModifiedDate":"2020-09-01T14:12:00.758312","indexId":"70196187","displayToPublicDate":"2018-03-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Functional group, biomass, and climate change effects on ecological drought in semiarid grasslands","docAbstract":"Water relations in plant communities are influenced both by contrasting functional groups (grasses, shrubs) and by climate change via complex effects on interception, uptake and transpiration. We modelled the effects of functional group replacement and biomass increase, both of which can be outcomes of invasion and vegetation management, and climate change on ecological drought (soil water potential below which photosynthesis stops) in 340 semiarid grassland sites over 30‐year periods. Relative to control vegetation (climate and site‐determined mixes of functional groups), the frequency and duration of drought were increased by shrubs and decreased by annual grasses. The rankings of shrubs, control vegetation, and annual grasses in terms of drought effects were generally consistent in current and future climates, suggesting that current differences among functional groups on drought effects predict future differences. Climate change accompanied by experimentally‐increased biomass (i.e. the effects of invasions that increase community biomass, or management that increases productivity through fertilization or respite from grazing) increased drought frequency and duration, and advanced drought onset. Our results suggest that the replacement of perennial temperate semiarid grasslands by shrubs, or increased biomass, can increase ecological drought both in current and future climates.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JG004173","usgsCitation":"Wilson, S.D., Schlaepfer, D., Bradford, J.B., Lauenroth, W.K., Duniway, M.C., Hall, S.A., Jamiyansharav, K., Jia, G., Lkhagva, A., Munson, S.M., Pyke, D.A., and Tietjen, B., 2018, Functional group, biomass, and climate change effects on ecological drought in semiarid grasslands: Journal of Geophysical Research G: Biogeosciences, v. 123, no. 3, p. 1072-1085, https://doi.org/10.1002/2017JG004173.","productDescription":"14 p.","startPage":"1072","endPage":"1085","ipdsId":"IP-093452","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468900,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jg004173","text":"Publisher Index Page"},{"id":352743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-25","publicationStatus":"PW","scienceBaseUri":"5afee6f8e4b0da30c1bfbff0","contributors":{"authors":[{"text":"Wilson, Scott D.","contributorId":181519,"corporation":false,"usgs":false,"family":"Wilson","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":731572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":731573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731574,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":731575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731576,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, Sonia A.","contributorId":181518,"corporation":false,"usgs":false,"family":"Hall","given":"Sonia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":731577,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jamiyansharav, Khishigbayar","contributorId":181522,"corporation":false,"usgs":false,"family":"Jamiyansharav","given":"Khishigbayar","email":"","affiliations":[],"preferred":false,"id":731578,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jia, Gensuo","contributorId":181520,"corporation":false,"usgs":false,"family":"Jia","given":"Gensuo","email":"","affiliations":[],"preferred":false,"id":731579,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lkhagva, Ariuntsetseg","contributorId":181521,"corporation":false,"usgs":false,"family":"Lkhagva","given":"Ariuntsetseg","email":"","affiliations":[],"preferred":false,"id":731580,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731581,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":731571,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tietjen, Britta","contributorId":181517,"corporation":false,"usgs":false,"family":"Tietjen","given":"Britta","email":"","affiliations":[],"preferred":false,"id":731582,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70196196,"text":"70196196 - 2018 - Managing an invasive corallimorph at Palmyra Atoll National Wildlife Refuge, Line Islands, Central Pacific","interactions":[],"lastModifiedDate":"2023-06-23T14:37:13.701765","indexId":"70196196","displayToPublicDate":"2018-03-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Managing an invasive corallimorph at Palmyra Atoll National Wildlife Refuge, Line Islands, Central Pacific","docAbstract":"In 2007, a phase shift from corals to corallimorpharians (CM) centered around a shipwreck was documented at Palmyra Atoll, Line Islands. Subsequent surveys revealed CM to be overgrowing the reef benthos, including corals and coralline algae, potentially placing coral ecosystems in the atoll at risk. This prompted the U.S. Fish and Wildlife Service, the lead management agency of the atoll, to remove the shipwreck. Subsequent surveys showed reductions in CM around the ship impact site. We explain patterns of spread of the CM in terms of both life history and local currents and show with a pilot study that pulverized bleach may be an effective tool to eradicate CM on a local scale. If applied strategically, particularly in heavily infested (> 66% cover) areas, active intervention such as this could be an effective management tool to reduce CM impact on localized areas and decrease colonization rate of remaining reefs. This is the first documentation of the response of an invasive cnidarian to shipwreck removal. While this was a singular event in Palmyra, the spatial and temporal patterns of this invasion and the eradications lessons described herein, are useful for anticipating and controlling similar situations elsewhere.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1696-1","usgsCitation":"Work, T.M., Aeby, G.S., Neal, B.P., Price, N.N., Conklin, E., and Pollock, A., 2018, Managing an invasive corallimorph at Palmyra Atoll National Wildlife Refuge, Line Islands, Central Pacific: Biological Invasions, v. 20, no. 8, p. 2197-2208, https://doi.org/10.1007/s10530-018-1696-1.","productDescription":"12 p.","startPage":"2197","endPage":"2208","ipdsId":"IP-091119","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":468899,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-018-1696-1","text":"Publisher Index Page"},{"id":352753,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418363,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95PE2S5","text":"USGS data release","description":"USGS data release","linkHelpText":"Corallimorph Invasion Palmyra: Data"}],"country":"United States","otherGeospatial":"Palmyra Atoll National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.1194076538086,\n 5.859889863069604\n ],\n [\n -162.03529357910156,\n 5.859889863069604\n ],\n [\n -162.03529357910156,\n 5.89813976783302\n ],\n [\n -162.1194076538086,\n 5.89813976783302\n ],\n [\n -162.1194076538086,\n 5.859889863069604\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"8","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-23","publicationStatus":"PW","scienceBaseUri":"5afee6f8e4b0da30c1bfbfec","contributors":{"authors":[{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":731634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aeby, Greta S.","contributorId":64783,"corporation":false,"usgs":false,"family":"Aeby","given":"Greta","email":"","middleInitial":"S.","affiliations":[{"id":13394,"text":"Hawai‘i Institute of Marine Biology","active":true,"usgs":false}],"preferred":false,"id":731635,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neal, Benjamin P.","contributorId":203493,"corporation":false,"usgs":false,"family":"Neal","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[{"id":36632,"text":"Bigelow Laboratory for Ocean Sciences, 60 Bigelow Dr, East Boothbay, ME 04544, USA","active":true,"usgs":false}],"preferred":false,"id":731636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Price, Nichole N.","contributorId":203494,"corporation":false,"usgs":false,"family":"Price","given":"Nichole","email":"","middleInitial":"N.","affiliations":[{"id":36632,"text":"Bigelow Laboratory for Ocean Sciences, 60 Bigelow Dr, East Boothbay, ME 04544, USA","active":true,"usgs":false}],"preferred":false,"id":731637,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conklin, Eric","contributorId":203495,"corporation":false,"usgs":false,"family":"Conklin","given":"Eric","email":"","affiliations":[{"id":36633,"text":"The Nature Conservancy-Hawaii, 923 Nuuanu Ave, Honolulu, HI 96817, USA","active":true,"usgs":false}],"preferred":false,"id":731639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pollock, Amanda","contributorId":150244,"corporation":false,"usgs":false,"family":"Pollock","given":"Amanda","email":"","affiliations":[{"id":17945,"text":"U.S. Fish and Wildlife Service, Pacific Islands Refuge and Monuments","active":true,"usgs":false}],"preferred":false,"id":731638,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196012,"text":"ofr20171165 - 2018 - The sedimentological characteristics and geochronology of the marshes of Dauphin Island, Alabama","interactions":[],"lastModifiedDate":"2025-05-13T16:24:00.938754","indexId":"ofr20171165","displayToPublicDate":"2018-03-22T13:45:00","publicationYear":"2018","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":"2017-1165","title":"The sedimentological characteristics and geochronology of the marshes of Dauphin Island, Alabama","docAbstract":"In August 2015, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 11 push cores from the marshes of Dauphin Island and Little Dauphin Island, Alabama. Sample site environments included high marshes, low salt marshes, and salt flats, and varied in distance from the shoreline. The sampling efforts were part of a larger study to assess the feasibility and sustainability of proposed restoration efforts for Dauphin Island, Alabama, and to identify trends in shoreline erosion and accretion. The data presented in this publication can provide a basis for assessing organic and inorganic sediment accumulation rates and temporal changes in accumulation rates over multiple decades at multiple locations across the island. This study was funded by the National Fish and Wildlife Foundation, via the Gulf Environmental Benefit Fund. This report serves as an archive for the sedimentological and geochemical data derived from the marsh cores. Downloadable data are available and include Microsoft Excel spreadsheets (.xlsx), comma-separated values (.csv) text files, JPEG files, and formal Federal Geographic Data Committee metadata in a U.S. Geological Survey data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171165","usgsCitation":"Ellis, A.M., Smith, C.G., and Marot, M.E., 2018, The sedimentological characteristics and geochronology of the marshes of Dauphin Island, Alabama: U.S. Geological Survey Open-File Report 2017–1165, https://doi.org/10.3133/ofr20171165.","productDescription":"HTML Document; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085345","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":352515,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1165/index.html","text":"Report HTML"},{"id":352514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1165/coverthb.jpg"},{"id":352516,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VM49J0","text":"USGS data release","description":"USGS data release","linkHelpText":"The Sedimentological Characteristics and Geochronology of the Marshes of Dauphin Island, Alabama"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.20854187011719,\n 30.221101852485987\n ],\n [\n -88.06709289550781,\n 30.221101852485987\n ],\n [\n -88.06709289550781,\n 30.282491622409413\n ],\n [\n -88.20854187011719,\n 30.282491622409413\n ],\n [\n -88.20854187011719,\n 30.221101852485987\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
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600 4th Street South
St. Petersburg, FL 33701
No abstract available.
","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Pearl, A., Laramie, M., Baldwin, C., Rohrback, J., Dietz, B., and McDaniel, M., 2018, The Chief Joseph Hatchery Program spring Chinook 2018 annual report, ix, 74 p.","productDescription":"ix, 74 p.","numberOfPages":"111","ipdsId":"IP-130467","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":402530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":402529,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.cct-fnw.com/reports"}],"country":"United States","state":"Washington","otherGeospatial":"Chief Joseph Dam, Okanogan River Subbasin, Columbia River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.27008056640624,\n 47.9696977140649\n ],\n [\n -119.00665283203124,\n 47.9696977140649\n ],\n [\n -119.00665283203124,\n 48.98922934818294\n ],\n [\n -120.27008056640624,\n 48.98922934818294\n ],\n [\n -120.27008056640624,\n 47.9696977140649\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pearl, Andrea","contributorId":178154,"corporation":false,"usgs":false,"family":"Pearl","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":844928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laramie, Matthew 0000-0001-7820-2583 mlaramie@usgs.gov","orcid":"https://orcid.org/0000-0001-7820-2583","contributorId":152532,"corporation":false,"usgs":true,"family":"Laramie","given":"Matthew","email":"mlaramie@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, Casey","contributorId":178155,"corporation":false,"usgs":false,"family":"Baldwin","given":"Casey","affiliations":[],"preferred":false,"id":844930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rohrback, John","contributorId":178156,"corporation":false,"usgs":false,"family":"Rohrback","given":"John","email":"","affiliations":[],"preferred":false,"id":844931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dietz, Brian","contributorId":222733,"corporation":false,"usgs":false,"family":"Dietz","given":"Brian","email":"","affiliations":[{"id":27988,"text":"Colville Confederated Tribes","active":true,"usgs":false}],"preferred":false,"id":844932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDaniel, Matt","contributorId":292519,"corporation":false,"usgs":false,"family":"McDaniel","given":"Matt","email":"","affiliations":[{"id":62929,"text":"Colville Confederate Tribes","active":true,"usgs":false}],"preferred":false,"id":844933,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70194780,"text":"sir20175159 - 2018 - Model methodology for estimating pesticide concentration extremes based on sparse monitoring data","interactions":[],"lastModifiedDate":"2018-03-22T15:35:37","indexId":"sir20175159","displayToPublicDate":"2018-03-22T00:00:00","publicationYear":"2018","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":"2017-5159","title":"Model methodology for estimating pesticide concentration extremes based on sparse monitoring data","docAbstract":"This report describes a new methodology for using sparse (weekly or less frequent observations) and potentially highly censored pesticide monitoring data to simulate daily pesticide concentrations and associated quantities used for acute and chronic exposure assessments, such as the annual maximum daily concentration. The new methodology is based on a statistical model that expresses log-transformed daily pesticide concentration in terms of a seasonal wave, flow-related variability, long-term trend, and serially correlated errors. Methods are described for estimating the model parameters, generating conditional simulations of daily pesticide concentration given sparse (weekly or less frequent) and potentially highly censored observations, and estimating concentration extremes based on the conditional simulations. The model can be applied to datasets with as few as 3 years of record, as few as 30 total observations, and as few as 10 uncensored observations. The model was applied to atrazine, carbaryl, chlorpyrifos, and fipronil data for U.S. Geological Survey pesticide sampling sites with sufficient data for applying the model. A total of 112 sites were analyzed for atrazine, 38 for carbaryl, 34 for chlorpyrifos, and 33 for fipronil. The results are summarized in this report; and, R functions, described in this report and provided in an accompanying model archive, can be used to fit the model parameters and generate conditional simulations of daily concentrations for use in investigations involving pesticide exposure risk and uncertainty.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175159","collaboration":"National Water Quality Program","usgsCitation":"Vecchia, A.V., 2018, Model methodology for estimating pesticide concentration extremes based on sparse monitoring data: U.S. Geological Survey Scientific Investigations Report 2017–5159, 47 p., https://doi.org/10.3133/sir20175159.","productDescription":"Report: viii, 47 p.; Appendix; Data release","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090885","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":352536,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NV9H50","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data Files to Support SEAWAVE-QEX Model for Simulating Concentrations of Selected Pesticides in the Continental United States, 1992–2012"},{"id":352529,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/science/mission-areas/water/national-water-quality-program?qt-programs_l2_landing_page=0#qt-programs_l2_landing_page","text":"National Water Quality Program"},{"id":352528,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5159/downloads/","text":"Model Archive","description":"SIR 2017–5159 Model Archive"},{"id":352526,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5159/coverthb.jpg"},{"id":352527,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5159/sir20175159.pdf","text":"Report","size":"2.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5159"}],"contact":"Director, Dakota Water Science Center, North Dakota Office
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
This report describes (1) work done between January 2015 and May 2017 as part of the U.S. Geological Survey (USGS) hexavalent chromium, Cr(VI), background study and (2) the summative-scale approach to be used to estimate the extent of anthropogenic (man-made) Cr(VI) and background Cr(VI) concentrations near the Pacific Gas and Electric Company (PG&E) natural gas compressor station in Hinkley, California. Most of the field work for the study was completed by May 2017. The summative-scale approach and calculation of Cr(VI) background were not well-defined at the time the USGS proposal for the background Cr(VI) study was prepared but have since been refined as a result of data collected as part of this study. The proposed summative scale consists of multiple items, formulated as questions to be answered at each sampled well. Questions that compose the summative scale were developed to address geologic, hydrologic, and geochemical constraints on Cr(VI) within the study area. Each question requires a binary (yes or no) answer. A score of 1 will be assigned for an answer that represents data consistent with anthropogenic Cr(VI); a score of –1 will be assigned for an answer that represents data inconsistent with anthropogenic Cr(VI). The areal extent of anthropogenic Cr(VI) estimated from the summative-scale analyses will be compared with the areal extent of anthropogenic Cr(VI) estimated on the basis of numerical groundwater flow model results, along with particle-tracking analyses. On the basis of these combined results, background Cr(VI) values will be estimated for “Mojave-type” deposits, and other deposits, in different parts of the study area outside the summative-scale mapped extent of anthropogenic Cr(VI).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181045","collaboration":"Prepared in cooperation with the Lahontan Regional Water Quality Control Board and the State Water Resources Control Board","usgsCitation":"Izbicki, J.A., and Groover, K., 2018, Natural and man-made hexavalent chromium, Cr(VI), in groundwater near a mapped plume, Hinkley, California—study progress as of May 2017, and a summative-scale approach to estimate background Cr(VI) concentrations: U.S. Geological Survey Open-File Report 2018–1045, 28 p., https://doi.org/10.3133/ofr20181045.","productDescription":"vi, 28 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-095489","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":352720,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1045/ofr20181045.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1045"},{"id":352719,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1045/coverthb.jpg"}],"country":"United States","state":"California","city":"Hinkley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.2333,\n 34.8667\n ],\n [\n -117.0667,\n 34.8667\n ],\n [\n -117.0667,\n 35.0333\n ],\n [\n -117.2333,\n 35.0333\n ],\n [\n -117.2333,\n 34.8667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
Unique responses to climate change can occur across intraspecific levels, resulting in individualistic adaptation or movement patterns among populations within a given species. Thus, the need to model potential responses among genetically distinct populations within a species is increasingly recognized. However, predictive models of future distributions are regularly fit at the species level, often because intraspecific variation is unknown or is identified only within limited sample locations. In this study, we considered the role of intraspecific variation to shape the geographic distribution of ponderosa pine (Pinus ponderosa), an ecologically and economically important tree species in North America. Morphological and genetic variation across the distribution of ponderosa pine suggest the need to model intraspecific populations: the two varieties (var. ponderosa and var. scopulorum) and several haplotype groups within each variety have been shown to occupy unique climatic niches, suggesting populations have distinct evolutionary lineages adapted to different environmental conditions. We utilized a recently-available, geographically-widespread dataset of intraspecific variation (haplotypes) for ponderosa pine and a recently-devised lineage distance modeling approach to derive additional, likely intraspecific occurrence locations. We confirmed the relative uniqueness of each haplotype-climate relationship using a niche-overlap analysis, and developed ecological niche models (ENMs) to project the distribution for two varieties and eight haplotypes under future climate forecasts. Future projections of haplotype niche distributions generally revealed greater potential range loss than predicted for the varieties. This difference may reflect intraspecific responses of distinct evolutionary lineages. However, directional trends are generally consistent across intraspecific levels, and include a loss of distributional area and an upward shift in elevation. Our results demonstrate the utility in modeling intraspecific response to changing climate and they inform management and conservation strategies, by identifying haplotypes and geographic areas that may be most at risk, or most secure, under projected climate change.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/sysbio/syy017","usgsCitation":"Maguire, K.C., Shinneman, D.J., Potter, K.M., and Hipkins, V.D., 2018, Intraspecific niche models for ponderosa pine (Pinus ponderosa) suggest potential variability in population-level response to climate change: Systematic Biology, v. 67, no. 6, p. 965-978, https://doi.org/10.1093/sysbio/syy017.","productDescription":"14 p.","startPage":"965","endPage":"978","ipdsId":"IP-088076","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468902,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/sysbio/syy017","text":"Publisher Index Page"},{"id":352679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"67","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5afee6f9e4b0da30c1bfc000","contributors":{"authors":[{"text":"Maguire, Kaitlin C. 0000-0001-8193-2384","orcid":"https://orcid.org/0000-0001-8193-2384","contributorId":203419,"corporation":false,"usgs":true,"family":"Maguire","given":"Kaitlin","email":"","middleInitial":"C.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":731442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":731443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Potter, Kevin M.","contributorId":167660,"corporation":false,"usgs":false,"family":"Potter","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":24794,"text":"Department of Forestry and Environmental Resources, North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":731444,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hipkins, Valerie D.","contributorId":167661,"corporation":false,"usgs":false,"family":"Hipkins","given":"Valerie","email":"","middleInitial":"D.","affiliations":[{"id":24795,"text":"National Forest Genetics Laboratory, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":731445,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196147,"text":"sim3393 - 2018 - Delineation of the hydrogeologic framework of the Big Sioux aquifer near Sioux Falls, South Dakota, using airborne electromagnetic data","interactions":[],"lastModifiedDate":"2018-09-25T08:02:09","indexId":"sim3393","displayToPublicDate":"2018-03-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3393","title":"Delineation of the hydrogeologic framework of the Big Sioux aquifer near Sioux Falls, South Dakota, using airborne electromagnetic data","docAbstract":"The U.S. Geological Survey, in cooperation with the City of Sioux Falls, South Dakota, began developing a groundwater-flow model of the Big Sioux aquifer in 2014 that will enable the City to make more informed water management decisions, such as delineation of areas of the greatest specific yield, which is crucial for locating municipal wells. Innovative tools are being evaluated as part of this study that can improve the delineation of the hydrogeologic framework of the aquifer for use in development of a groundwater-flow model, and the approach could have transfer value for similar hydrogeologic settings. The first step in developing a groundwater-flow model is determining the hydrogeologic framework (vertical and horizontal extents of the aquifer), which typically is determined by interpreting geologic information from drillers’ logs and surficial geology maps. However, well and borehole data only provide hydrogeologic information for a single location; conversely, nearly continuous geophysical data are collected along flight lines using airborne electromagnetic (AEM) surveys. These electromagnetic data are collected every 3 meters along a flight line (on average) and subsequently can be related to hydrogeologic properties. AEM data, coupled with and constrained by well and borehole data, can substantially improve the accuracy of aquifer hydrogeologic framework delineations and result in better groundwater-flow models.
AEM data were acquired using the Resolve frequency-domain AEM system to map the Big Sioux aquifer in the region of the city of Sioux Falls. The survey acquired more than 870 line-kilometers of AEM data over a total area of about 145 square kilometers, primarily over the flood plain of the Big Sioux River between the cities of Dell Rapids and Sioux Falls. The U.S. Geological Survey inverted the survey data to generate resistivity-depth sections that were used in two-dimensional maps and in three-dimensional volumetric visualizations of the Earth resistivity distribution. Contact lines were drawn using a geographic information system to delineate interpreted geologic stratigraphy. The contact lines were converted to points and then interpolated into a raster surface. The methods used to develop elevation and depth maps of the hydrogeologic framework of the Big Sioux aquifer are described herein.
The final AEM interpreted aquifer thickness ranged from 0 to 31 meters with an average thickness of 12.8 meters. The estimated total volume of the aquifer was 1,060,000,000 cubic meters based on the assumption that the top of the aquifer is the land-surface elevation. A simple calculation of the volume (length times width times height) of a previous delineation of the aquifer estimated the aquifer volume at 378,000,000 cubic meters; thus, the estimation based on AEM data is more than twice the previous estimate. The depth to top of Sioux Quartzite, which ranged in depth from 0 to 90 meters, also was delineated from the AEM data.
Director, Dakota Water Science Center, South Dakota Office
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
Negative relationships between dissolved organic carbon (DOC) concentration and fish productivity have been reported from correlative studies across lakes, but to date there have not been experimental tests of these relationships. We increased the DOC concentration in a lake by 3.4 mg L-1, using a before-after control-impact (BACI) design, to quantify the effects on the productivity and population structure of Largemouth Bass (Micropterus salmoides). Greater DOC reduced the volume of the epilimnion, the preferred habitat of Largemouth Bass, resulting in increased bass density. The likelihood that adult bass had empty diets decreased despite this increase in bass density; diet composition also changed. There was no apparent change in bass growth or condition. Overall, there was no net change in Largemouth Bass productivity. However, changes in YOY and juvenile recruitment and feeding success suggest the possibility that future effects could occur. Our results are the first to examine the effects of an increase in DOC on fish productivity through a five-year temporal lens, which demonstrates that the relationship between DOC and fish productivity is multi-dimensional and complex.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2017-0283","usgsCitation":"Koizumi, S., Craig, N., Zwart, J., Kelly, P.T., Ziegler, J.P., Weidel, B., Jones, S.E., and Solomon, C.T., 2018, Experimental whole-lake dissolved organic carbon increase alters fish diet and density but not growth or productivity: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 11, p. 1859-1867, https://doi.org/10.1139/cjfas-2017-0283.","productDescription":"9 p.","startPage":"1859","endPage":"1867","ipdsId":"IP-090537","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":501085,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/89189","text":"External Repository"},{"id":352686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"11","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6fae4b0da30c1bfc008","contributors":{"authors":[{"text":"Koizumi, Shuntaro","contributorId":203399,"corporation":false,"usgs":false,"family":"Koizumi","given":"Shuntaro","email":"","affiliations":[{"id":36610,"text":"McGill","active":true,"usgs":false}],"preferred":false,"id":731391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Craig, Nicola","contributorId":150803,"corporation":false,"usgs":false,"family":"Craig","given":"Nicola","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":731392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":731393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelly, Patrick T.","contributorId":193577,"corporation":false,"usgs":false,"family":"Kelly","given":"Patrick","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":731394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ziegler, Jacob P.","contributorId":196715,"corporation":false,"usgs":false,"family":"Ziegler","given":"Jacob","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":731395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":731390,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Stuart E.","contributorId":203400,"corporation":false,"usgs":false,"family":"Jones","given":"Stuart","email":"","middleInitial":"E.","affiliations":[{"id":36611,"text":"Notre Dame","active":true,"usgs":false}],"preferred":false,"id":731396,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":731397,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196125,"text":"70196125 - 2018 - Developing Foram-AMBI for biomonitoring in the Mediterranean: Species assignments to ecological categories","interactions":[],"lastModifiedDate":"2018-03-21T09:34:04","indexId":"70196125","displayToPublicDate":"2018-03-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2673,"text":"Marine Micropaleontology","active":true,"publicationSubtype":{"id":10}},"title":"Developing Foram-AMBI for biomonitoring in the Mediterranean: Species assignments to ecological categories","docAbstract":"Most environmental bio-monitoring methods using the species composition of marine faunas define the Ecological Quality Status of soft bottom ecosystems based on the relative proportions of species assigned to a limited number of ecological categories. In this study we analyse the distribution patterns of benthic foraminifera in the Mediterranean as a function of organic carbon gradients on the basis of 15 publications and assign the individual species to five ecological categories. Our categories (of sensitive, indifferent and 3rd, 2nd and 1st order opportunists) are very similar to the ecological categories commonly used for macrofauna, but show some minor differences. In the 15 analysed publications, we considered the numerical data of 493 taxa, of which 199 could be assigned. In all 79 taxa were classified as sensitive, 60 as indifferent, 46 as 3rd order, 12 as 2nd order and 2 as 1st order opportunists. The remaining 294 taxa are all accessory, and will only marginally contribute to biotic indices based on relative species proportions. In this paper we wanted also to explain the methodology we used for these species assignments, paying particular attention to all complications and problems encountered. We think that the species list proposed here will constitute a highly useful tool for foraminiferal bio-monitoring of soft bottoms in the Mediterranean Sea, which can be used in different ecological indices (Foram-AMBI and similar methods). With additional information becoming available in the next few years, it will be possible to expand the list, and, if necessary, to apply some minor corrections. As a next step, we intend to test this species list using several biotic indices, in a number of independent data sets, as soon as these will become available.
To evaluate the effect of fish growth on mercury (Hg) and polychlorinated biphenyl (PCB) bioaccumulation, a non–steady‐state toxicokinetic model, combined with a Wisconsin bioenergetics model, was developed to simulate Hg and PCB bioaccumulation in bluegill (Lepomis macrochirus). The model was validated by comparing observed with predicted Hg and PCB 180 concentrations across 5 age classes from 5 different waterbodies across North America. The non–steady‐state model generated accurate predictions for Hg and PCB bioaccumulation in 3 of 5 waterbodies: Apsey Lake (ON, Canada), Sharbot Lake (ON, Canada), and Stonelick Lake (OH, USA). The poor performance of the model for the Detroit River (MI, USA/ON, Canada) and Lake Hartwell (GA/SC, USA), which are 2 well‐known contaminated sites with possibly high heterogeneity in spatial contamination, was attributed to changes in feeding behavior and/or prey contamination. Model simulations indicate that growth dilution is a major component of contaminant bioaccumulation patterns in fish, especially during early life stages, and was predicted to be more important for hydrophobic PCBs than for Hg. Simulations that considered tissue‐specific growth provided some improvement in model performance particularly for PCBs in fish populations that exhibited changes in their whole‐body lipid content with age. Higher variation in lipid growth compared with that of lean dry protein was also observed between different bluegill populations, which partially explains the greater variation in PCB bioaccumulation slopes compared with Hg across sampling sites.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4114","usgsCitation":"Li, J., Haffner, G.D., Patterson, G., Walters, D., Burtnyk, M.D., and Drouillard, K.G., 2018, Importance of growth rate on mercury and polychlorinated biphenyl bioaccumulation in fish: Environmental Toxicology and Chemistry, v. 37, no. 6, p. 1655-1667, https://doi.org/10.1002/etc.4114.","productDescription":"13 p.","startPage":"1655","endPage":"1667","ipdsId":"IP-090841","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":352682,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-19","publicationStatus":"PW","scienceBaseUri":"5afee6fae4b0da30c1bfc002","contributors":{"authors":[{"text":"Li, Jiajia","contributorId":203411,"corporation":false,"usgs":false,"family":"Li","given":"Jiajia","email":"","affiliations":[{"id":36613,"text":"U. Windsor","active":true,"usgs":false}],"preferred":false,"id":731430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haffner, G. Douglas","contributorId":203414,"corporation":false,"usgs":false,"family":"Haffner","given":"G.","email":"","middleInitial":"Douglas","affiliations":[{"id":36613,"text":"U. Windsor","active":true,"usgs":false}],"preferred":false,"id":731433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patterson, Gordon","contributorId":203412,"corporation":false,"usgs":false,"family":"Patterson","given":"Gordon","email":"","affiliations":[{"id":36614,"text":"Michigan Tech","active":true,"usgs":false}],"preferred":false,"id":731431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, David M. 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":4444,"corporation":false,"usgs":true,"family":"Walters","given":"David M.","email":"waltersd@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":731429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burtnyk, Michael D.","contributorId":203413,"corporation":false,"usgs":false,"family":"Burtnyk","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":36615,"text":"CH2M Hill","active":true,"usgs":false}],"preferred":false,"id":731432,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drouillard, Ken G.","contributorId":127334,"corporation":false,"usgs":false,"family":"Drouillard","given":"Ken","email":"","middleInitial":"G.","affiliations":[{"id":6778,"text":"University of Windsor, Windsor, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":731434,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196115,"text":"70196115 - 2018 - Annual variation in polychlorinated biphenyl (PCB) exposure in tree swallow (Tachycineta bicolor) eggs and nestlings at Great Lakes Restoration Initiative (GLRI) study sites","interactions":[],"lastModifiedDate":"2022-04-04T20:43:36.748088","indexId":"70196115","displayToPublicDate":"2018-03-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Annual variation in polychlorinated biphenyl (PCB) exposure in tree swallow (Tachycineta bicolor) eggs and nestlings at Great Lakes Restoration Initiative (GLRI) study sites","title":"Annual variation in polychlorinated biphenyl (PCB) exposure in tree swallow (Tachycineta bicolor) eggs and nestlings at Great Lakes Restoration Initiative (GLRI) study sites","docAbstract":"Tree swallow (Tachycineta bicolor) eggs and nestlings were collected from 16 sites across the Great Lakes to quantify normal annual variation in total polychlorinated biphenyl (PCB) exposure and to validate the sample size choice in earlier work. A sample size of five eggs or five nestlings per site was adequate to quantify exposure to PCBs in tree swallows given the current exposure levels and variation. There was no difference in PCB exposure in two randomly selected sets of five eggs collected in the same year, but analyzed in different years. Additionally, there was only modest annual variation in exposure, with between 69% (nestlings) and 73% (eggs) of sites having no differences between years. There was a tendency, both statistically and qualitatively, for there to be less exposure in the second year compared to the first year.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-018-6617-3","usgsCitation":"Custer, C.M., Custer, T.W., Dummer, P.M., Goldberg, D., and Franson, J.C., 2018, Annual variation in polychlorinated biphenyl (PCB) exposure in tree swallow (Tachycineta bicolor) eggs and nestlings at Great Lakes Restoration Initiative (GLRI) study sites: Environmental Monitoring and Assessment, v. 190, p. 1-7, https://doi.org/10.1007/s10661-018-6617-3.","productDescription":"Article 227; 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-090193","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":352684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.21923828124999,\n 41.244772343082076\n ],\n [\n -78.7060546875,\n 41.244772343082076\n ],\n [\n -78.7060546875,\n 46.86019101567027\n ],\n [\n -92.21923828124999,\n 46.86019101567027\n ],\n [\n -92.21923828124999,\n 41.244772343082076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"190","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-17","publicationStatus":"PW","scienceBaseUri":"5afee6fae4b0da30c1bfc004","contributors":{"authors":[{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":731421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Custer, Thomas W. 0000-0003-3170-6519 tcuster@usgs.gov","orcid":"https://orcid.org/0000-0003-3170-6519","contributorId":2835,"corporation":false,"usgs":true,"family":"Custer","given":"Thomas","email":"tcuster@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":731422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dummer, Paul M. 0000-0002-2055-9480 pdummer@usgs.gov","orcid":"https://orcid.org/0000-0002-2055-9480","contributorId":3015,"corporation":false,"usgs":true,"family":"Dummer","given":"Paul","email":"pdummer@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":731423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldberg, Diana R. 0000-0001-8540-8512","orcid":"https://orcid.org/0000-0001-8540-8512","contributorId":82252,"corporation":false,"usgs":true,"family":"Goldberg","given":"Diana R.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":731424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Franson, J. Christian 0000-0002-0251-4238 jfranson@usgs.gov","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":177499,"corporation":false,"usgs":true,"family":"Franson","given":"J.","email":"jfranson@usgs.gov","middleInitial":"Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":731425,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196112,"text":"70196112 - 2018 - Tributyltin: Advancing the science on assessing endocrine disruption with an unconventional endocrine-disrupting compound","interactions":[],"lastModifiedDate":"2018-09-04T09:16:33","indexId":"70196112","displayToPublicDate":"2018-03-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Tributyltin: Advancing the science on assessing endocrine disruption with an unconventional endocrine-disrupting compound","docAbstract":"Tributyltin (TBT) has been recognized as an endocrine disrupting chemical (EDC) for several decades. However, only in the last decade, was its primary endocrine mechanism of action (MeOA) elucidated—interactions with the nuclear retinoid-X receptor (RXR), peroxisome proliferator-activated receptor γ (PPARγ), and their heterodimers. This molecular initiating event (MIE) alters a range of reproductive, developmental, and metabolic pathways at the organism level. It is noteworthy that a variety of MeOAs have been proposed over the years for the observed endocrine-type effects of TBT; however, convincing data for the MIE was provided only recently and now several researchers have confirmed and refined the information on this MeOA. One of the most important lessons learned from years of research on TBT concerns apparent species sensitivity. Several aspects such as the rates of uptake and elimination, chemical potency, and metabolic capacity are all important for identifying the most sensitive species for a given chemical, including EDCs. For TBT, much of this was discovered by trial and error, hence important relationships and important sensitive taxa were not identified until several decades after its introduction to the environment. As recognized for many years, TBT-induced responses are known to occur at very low concentrations for molluscs, a fact that has more recently also been observed in fish species. This review explores the MeOA and effects of TBT in different species (aquatic molluscs and other invertebrates, fish, amphibians, birds, and mammals) according to the OECD Conceptual Framework for Endocrine Disruptor Testing and Assessment (CFEDTA). The information gathered on biological effects that are relevant for populations of aquatic animals was used to construct Species Sensitivity Distributions (SSDs) based on No Observed Effect Concentrations (NOECs) and Lowest Observed Effect Concentrations (LOECs). Fish appear at the lower end of these distributions, showing that they are as sensitive as molluscs, and for some species, even more sensitive. Concentrations in the range of 1 ng/L for water exposure (10 ng/g for whole-body burden) have been shown to elicit endocrine-type responses, whereas mortality occurs at water concentrations ten times higher. Current screening and assessment methodologies as compiled in the OECD CFEDTA are able to identify TBT as a potent endocrine disruptor with a high environmental risk for the original use pattern. If those approaches had been available when TBT was introduced to the market, it is likely that its use would have been regulated sooner, thus avoiding the detrimental effects on marine gastropod populations and communities as documented over several decades.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reviews of environmental contamination and toxicology Volume 245","language":"English","publisher":"Springer","doi":"10.1007/398_2017_8","usgsCitation":"Lagadic, L., Katsiadaki, I., Biever, R.C., Guiney, P., Karouna-Renier, N., Schwarz, T., and Meador, J., 2018, Tributyltin: Advancing the science on assessing endocrine disruption with an unconventional endocrine-disrupting compound, chap. of Reviews of environmental contamination and toxicology Volume 245, v. 245, p. 65-127, https://doi.org/10.1007/398_2017_8.","productDescription":"63 p.","startPage":"65","endPage":"127","ipdsId":"IP-075961","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":352685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"245","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-09","publicationStatus":"PW","scienceBaseUri":"5afee6fae4b0da30c1bfc006","contributors":{"authors":[{"text":"Lagadic, Laurent","contributorId":200679,"corporation":false,"usgs":false,"family":"Lagadic","given":"Laurent","email":"","affiliations":[],"preferred":false,"id":731400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katsiadaki, Ioanna","contributorId":200653,"corporation":false,"usgs":false,"family":"Katsiadaki","given":"Ioanna","email":"","affiliations":[],"preferred":false,"id":731401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biever, Ronald C.","contributorId":200660,"corporation":false,"usgs":false,"family":"Biever","given":"Ronald","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":731402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guiney, Patrick","contributorId":193148,"corporation":false,"usgs":false,"family":"Guiney","given":"Patrick","affiliations":[],"preferred":false,"id":731403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":200983,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":731399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwarz, Tamar","contributorId":200733,"corporation":false,"usgs":false,"family":"Schwarz","given":"Tamar","email":"","affiliations":[],"preferred":false,"id":731404,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meador, James P.","contributorId":174075,"corporation":false,"usgs":false,"family":"Meador","given":"James P.","affiliations":[],"preferred":false,"id":731405,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195978,"text":"sir20185006 - 2018 - Nitrogen concentrations and loads for the Connecticut River at Middle Haddam, Connecticut, computed with the use of autosampling and continuous measurements of water quality for water years 2009 to 2014","interactions":[],"lastModifiedDate":"2018-03-21T15:01:13","indexId":"sir20185006","displayToPublicDate":"2018-03-20T16:00:00","publicationYear":"2018","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":"2018-5006","title":"Nitrogen concentrations and loads for the Connecticut River at Middle Haddam, Connecticut, computed with the use of autosampling and continuous measurements of water quality for water years 2009 to 2014","docAbstract":"The daily and annual loads of nitrate plus nitrite and total nitrogen for the Connecticut River at Middle Haddam, Connecticut, were determined for water years 2009 to 2014. The analysis was done with a combination of methods, which included a predefined rating curve method for nitrate plus nitrite and total nitrogen for water years 2009 to 2011 and a custom rating curve method that included sensor measurements of nitrate plus nitrite nitrogen concentration and turbidity along with mean daily flow to determine total nitrogen loads for water years 2011 to 2014. Instantaneous concentrations of total nitrogen were estimated through the use of a regression model based on sensor measurements at 15-minute intervals of nitrate plus nitrite nitrogen and turbidity for water years 2011 to 2014.
Annual total nitrogen loads at the Connecticut River at Middle Haddam ranged from 12,900 to 19,200 metric tons, of which about 42 to 49 percent was in the form of nitrate plus nitrite. The mean 95-percent prediction intervals on daily total nitrogen load estimates were smaller from the custom model, which used sensor data, than those calculated by the predefined model.
Annual total nitrogen load estimates at the Connecticut River at Middle Haddam were compared with the upstream load estimates at the Connecticut River at Thompsonville, Conn. Annual gains in total nitrogen loads between the two stations ranged from 3,430 to 6,660 metric tons. These increases between the two stations were attributed to the effects of increased urbanization and to combined annual discharges of 1,540 to 2,090 metric tons of nitrogen from 24 wastewater treatment facilities in the drainage area between the two stations. The contribution of total nitrogen from wastewater discharge between the two stations had declined substantially before the beginning of this study and accounted for from 31 to 52 percent of the gain in nitrogen load between the Thompsonville and Middle Haddam sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185006","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Mullaney, J.R., Martin, J.W., and Morrison, J., 2018, Nitrogen concentrations and loads for the Connecticut River at Middle Haddam, Connecticut, computed with the use of autosampling and continuous measurements of water quality for water years 2009 to 2014: U.S. Geological Survey Scientific Investigations Report 2018–5006, 22 p., https://doi.org/10.3133/sir20185006.","productDescription":"Report: vii, 22 p.; Data release","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091217","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":352399,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5006/sir20185006.pdf","text":"Report","size":"4.79 MB ","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5006"},{"id":352631,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VQ31WT","text":"USGS data release","description":"USGS data release","linkHelpText":"Nitrogen Concentrations and Loads for the Connecticut River at Middle Haddam, Connecticut, Computed With the Use of Autosampling and Continuous Measurements of Water Quality for Water Years 2009 to 2014"},{"id":352409,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5006/coverthb.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Connecticut River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.94097900390625,\n 41.34691753986531\n ],\n [\n -72.18154907226562,\n 41.34691753986531\n ],\n [\n -72.18154907226562,\n 42.04011410708205\n ],\n [\n -72.94097900390625,\n 42.04011410708205\n ],\n [\n -72.94097900390625,\n 41.34691753986531\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
101 Pitkin Street
East Hartford, CT 06108
Assessment of the “Bird or Animal Deformities or Reproductive Problems” Beneficial Use Impairment (BUI) can be accomplished by (1) comparing tissue concentrations to established background and Lowest Observable Effect Level (LOEL) for reproductive effects, or (2) directly measuring reproductive success at Areas of Concern (AOCs) and statistically comparing those rates to minimally impacted reference locations (non-AOCs). Results from recent tree swallow (Tachycineta bicolor) publications were used to evaluate this BUI based on both approaches. For both endpoints, a 95-percent confidence interval (CI) was used to test for significant differences. Additional information on BUIs, AOCs, and the program in general can be found in the Great Lakes Water Quality Agreement (2012).
For the first metric, there are good background and reproductive effect threshold LOELs for tree swallow egg concentrations for polychlorinated biphenyls (PCBs), dioxins and furans (PCDD/Fs), and mercury, as well as, for some other organic and inorganic contaminants. For the second assessment, comparisons were made between AOC and non-AOC sites for reproductive success, which was measured as the daily probability of egg failure and the percentage of eggs laid that hatched. Multistate modeling was used to assess whether there was an association between the daily probability of egg failure and a suite of contaminants, including PCBs, but also whether there was an association with ecological variables, such as female age and date within season. Both of these ecological variables are known to affect hatching success in birds. The objective of this report is to synthesize the previously published information to assist in the assessment of the “Bird or Animal Deformities or Reproductive Problems” BUI at 16 sites within the 5 Wisconsin AOCs (table 1). The logic behind this interpretation is applicable to other AOCs as well.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181032","usgsCitation":"Custer, C.M., Custer, T.W., and Dummer, P.M., 2018, Synthesis of tree swallow (Tachycineta bicolor) data for Beneficial Use Impairment (BUI) assessment at Wisconsin Areas of Concern: U.S. Geological Survey Open-File Report 2018–1032, 8 p., https://doi.org/10.3133/ofr20181032.","productDescription":"iv, 8 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092682","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":352653,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1032/ofr20181032.pdf","text":"Report","size":"111 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1032"},{"id":352652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1032/coverthb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconsin","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Cross, WI 54603
The number of stranding response facilities for marine mammals in the United States has increased over the past two decades, resulting in thousands of rehabilitated marine mammals released back into the wild (Geraci and Lounsbury 2005; Moore et al. 2007; Johnson and Mayer 2015; Simeone et al. 2015). All rehabilitated marine mammals released in the United States must be tagged or marked (50 CFR 216.27) and post-release monitoring is recommended, if not required, for some taxonomic groups. This depends on their release category as determined by a veterinarian in concordance with guidelines established by the National Marine Fisheries Service (NMFS) and the US Fish and Wildlife Service (USFWS; Whaley and Borkowski 2009). Monitoring the fate of released, rehabilitated marine mammals is not only necessary for the validation and refinement of veterinary procedures and treatments, but allows for the recovery of individuals that are unable to adapt to the wild (Whaley and Borkowski 2009). For cases in which rehabilitation is used to enhance small or endangered populations, monitoring the ability of individuals to forage, survive, and ultimately reproduce following release is essential for assessing the conservation value of a given program’s efforts. Post-release monitoring has also been useful in some cases for elucidating poorly understood ranges and habitat use of wild populations (Moore et al. 2007).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"CRC handbook of marine mammal medicine, 3rd edition","language":"English","publisher":"CRC Press : Taylor & Francis Group","usgsCitation":"Lander, M.E., Westgate, A.J., Balmer, B.C., Reid, J.P., Murray, M.J., and Laidre, K.L., 2018, Tagging and tracking, chap. of CRC handbook of marine mammal medicine, 3rd edition, p. 767-798.","productDescription":"32 p.","startPage":"767","endPage":"798","ipdsId":"IP-080536","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":356956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":356309,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/books/9781498796880"}],"edition":"3rd","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2eae4b0702d0e84300a","contributors":{"authors":[{"text":"Lander, Michelle E.","contributorId":206850,"corporation":false,"usgs":false,"family":"Lander","given":"Michelle","email":"","middleInitial":"E.","affiliations":[{"id":37416,"text":"Marine Mammal Laboratory, Alaska Fisheries Science Center, NOAA, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":741940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westgate, Andrew J.","contributorId":206851,"corporation":false,"usgs":false,"family":"Westgate","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":37417,"text":"Dept. of Biology and Marine Biology, University of North Carolina Wilmington, Wilmington, NC","active":true,"usgs":false}],"preferred":false,"id":741941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balmer, Brian C.","contributorId":206853,"corporation":false,"usgs":false,"family":"Balmer","given":"Brian","email":"","middleInitial":"C.","affiliations":[{"id":27926,"text":"NOAA, National Centers for Coastal Ocean Science","active":true,"usgs":false}],"preferred":false,"id":741943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reid, James P. 0000-0002-8497-1132 jreid@usgs.gov","orcid":"https://orcid.org/0000-0002-8497-1132","contributorId":3460,"corporation":false,"usgs":true,"family":"Reid","given":"James","email":"jreid@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":741939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, Michael J.","contributorId":206852,"corporation":false,"usgs":false,"family":"Murray","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":37418,"text":"Monterey Bay Aquarium, Monterey, CA","active":true,"usgs":false}],"preferred":false,"id":741942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Laidre, Kristen L.","contributorId":206854,"corporation":false,"usgs":false,"family":"Laidre","given":"Kristen","email":"","middleInitial":"L.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":741944,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}