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,{"id":70196490,"text":"70196490 - 2018 - Survey of beaver-related restoration practices in rangeland streams of the western USA","interactions":[],"lastModifiedDate":"2018-04-11T14:33:27","indexId":"70196490","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Survey of beaver-related restoration practices in rangeland streams of the western USA","docAbstract":"<p><span>Poor condition of many streams and concerns about future droughts in the arid and semi-arid western USA have motivated novel restoration strategies aimed at accelerating recovery and increasing water resources. Translocation of beavers into formerly occupied habitats, restoration activities encouraging beaver recolonization, and instream structures mimicking the effects of beaver dams are restoration alternatives that have recently gained popularity because of their potential socioeconomic and ecological benefits. However, beaver dams and dam-like structures also harbor a history of social conflict. Hence, we identified a need to assess the use of beaver-related restoration projects in western rangelands to increase awareness and&nbsp;accountability, and identify gaps in scientific knowledge. We inventoried 97 projects implemented by 32 organizations, most in the last 10 years. We found that beaver-related stream restoration projects undertaken mostly involved the relocation of nuisance beavers. The most common goal was to store water, either with beaver dams or artificial structures. Beavers were often moved without regard to genetics, disease, or potential conflicts with nearby landowners. Few projects included post-implementation monitoring or planned for longer term issues, such as what happens when beavers abandon a site or when beaver dams or structures breach. Human dimensions were rarely considered and water rights and other issues were mostly unresolved or addressed through ad-hoc agreements. We conclude that the practice and implementation of beaver-related restoration has outpaced research on its efficacy and best practices. Further scientific research is necessary, especially research that informs the establishment of clear guidelines for best practices.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00267-017-0957-6","usgsCitation":"Pilliod, D.S., Rohde, A., Charnley, S., Davee, R.R., Dunham, J.B., Gosnell, H., Grant, G., Hausner, M.B., Huntington, J., and Nash, C., 2018, Survey of beaver-related restoration practices in rangeland streams of the western USA: Environmental Management, v. 61, no. 1, p. 58-68, https://doi.org/10.1007/s00267-017-0957-6.","productDescription":"11 p.","startPage":"58","endPage":"68","ipdsId":"IP-085356","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":438038,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90GAYBK","text":"USGS data release","linkHelpText":"Beaver-related Stream Restoration Projects in Western Rangelands"},{"id":353330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -125.0244140625,\n              37.055177106660814\n            ],\n            [\n              -104.0185546875,\n              37.055177106660814\n            ],\n            [\n              -104.0185546875,\n              49.06666839558117\n            ],\n            [\n              -125.0244140625,\n              49.06666839558117\n            ],\n            [\n              -125.0244140625,\n              37.055177106660814\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"61","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma 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University","active":true,"usgs":false}],"preferred":false,"id":733203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Charnley, Susan","contributorId":169897,"corporation":false,"usgs":false,"family":"Charnley","given":"Susan","email":"","affiliations":[{"id":25613,"text":"Pacific Northwest Research Station, USDA Forest Service.","active":true,"usgs":false}],"preferred":false,"id":733204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davee, Rachael R","contributorId":204144,"corporation":false,"usgs":false,"family":"Davee","given":"Rachael","email":"","middleInitial":"R","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":733205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":733206,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gosnell, Hannah","contributorId":192214,"corporation":false,"usgs":false,"family":"Gosnell","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":733207,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grant, Gordon E.","contributorId":30881,"corporation":false,"usgs":false,"family":"Grant","given":"Gordon E.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":733208,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hausner, Mark B.","contributorId":204145,"corporation":false,"usgs":false,"family":"Hausner","given":"Mark","email":"","middleInitial":"B.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":733209,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huntington, Justin L.","contributorId":31279,"corporation":false,"usgs":true,"family":"Huntington","given":"Justin L.","affiliations":[],"preferred":false,"id":733239,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nash, Caroline","contributorId":204146,"corporation":false,"usgs":false,"family":"Nash","given":"Caroline","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":733210,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70197788,"text":"70197788 - 2018 - Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States","interactions":[],"lastModifiedDate":"2018-06-20T10:54:13","indexId":"70197788","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3568,"text":"The Leading Edge","active":true,"publicationSubtype":{"id":10}},"title":"Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States","docAbstract":"<p><span>Probabilistic seismic hazard analysis (PSHA) characterizes ground-motion hazard from earthquakes. Typically, the time horizon of a PSHA forecast is long, but in response to induced seismicity related to hydrocarbon development, the USGS developed one-year PSHA models. In this paper, we present a display of the variability in USGS hazard curves due to epistemic uncertainty in its informed submodel using a simple bootstrapping approach. We find that variability is highest in low-seismicity areas. On the other hand, areas of high seismic hazard, such as the New Madrid seismic zone or Oklahoma, exhibit relatively lower variability simply because of more available data and a better understanding of the seismicity. Comparing areas of high hazard, New Madrid, which has a history of large naturally occurring earthquakes, has lower forecast variability than Oklahoma, where the hazard is driven mainly by suspected induced earthquakes since 2009. Overall, the mean hazard obtained from bootstrapping is close to the published model, and variability increased in the 2017 one-year model relative to the 2016 model. Comparing the relative variations caused by individual logic-tree branches, we find that the highest hazard variation (as measured by the 95% confidence interval of bootstrapping samples) in the final model is associated with different ground-motion models and maximum magnitudes used in the logic tree, while the variability due to the smoothing distance is minimal. It should be pointed out that this study is not looking at the uncertainty in the hazard in general, but only as it is represented in the USGS one-year models.</span><span></span></p>","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/tle37020141a1.1","usgsCitation":"Mousavi, S.M., Beroza, G.C., and Hoover, S.M., 2018, Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States: The Leading Edge, v. 37, no. 2, p. 141a1-141a9, https://doi.org/10.1190/tle37020141a1.1.","productDescription":"9 p.","startPage":"141a1","endPage":"141a9","ipdsId":"IP-093220","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":355202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115,\n              25\n            ],\n            [\n              -65,\n              25\n            ],\n            [\n              -65,\n              50\n            ],\n            [\n              -115,\n              50\n            ],\n            [\n              -115,\n              25\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"37","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e5d3e4b060350a15d21c","contributors":{"authors":[{"text":"Mousavi, S. Mostafa","contributorId":205790,"corporation":false,"usgs":false,"family":"Mousavi","given":"S.","email":"","middleInitial":"Mostafa","affiliations":[{"id":37167,"text":"Department of Geophysics, Stanford University, Stanford, CA","active":true,"usgs":false}],"preferred":false,"id":738494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":738495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoover, Susan M. 0000-0002-8682-6668 shoover@usgs.gov","orcid":"https://orcid.org/0000-0002-8682-6668","contributorId":5715,"corporation":false,"usgs":true,"family":"Hoover","given":"Susan","email":"shoover@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738496,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196067,"text":"70196067 - 2018 - A tool for efficient, model-independent management optimization under uncertainty","interactions":[],"lastModifiedDate":"2018-03-15T15:57:07","indexId":"70196067","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A tool for efficient, model-independent management optimization under uncertainty","docAbstract":"<p><span>To fill a need for risk-based environmental management optimization, we have developed PESTPP-OPT, a model-independent tool for resource management optimization under uncertainty. PESTPP-OPT solves a sequential linear programming (SLP) problem and also implements (optional) efficient, “on-the-fly” (without user intervention) first-order, second-moment (FOSM) uncertainty techniques to estimate model-derived constraint uncertainty. Combined with a user-specified risk value, the constraint uncertainty estimates are used to form chance-constraints for the SLP solution process, so that any optimal solution includes contributions from model input and observation uncertainty. In this way, a “single answer” that includes uncertainty is yielded from the modeling analysis. PESTPP-OPT uses the familiar PEST/PEST++ model interface protocols, which makes it widely applicable to many modeling analyses. The use of PESTPP-OPT is demonstrated with a synthetic, integrated surface-water/groundwater model. The function and implications of chance constraints for this synthetic model are discussed.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2017.11.019","usgsCitation":"White, J.T., Fienen, M.N., Barlow, P.M., and Welter, D., 2018, A tool for efficient, model-independent management optimization under uncertainty: Environmental Modelling and Software, v. 100, p. 213-221, https://doi.org/10.1016/j.envsoft.2017.11.019.","productDescription":"9 p.","startPage":"213","endPage":"221","ipdsId":"IP-090477","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":352580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee742e4b0da30c1bfc1f1","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":171511,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","middleInitial":"N.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Paul M. 0000-0003-4247-6456 pbarlow@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6456","contributorId":1200,"corporation":false,"usgs":true,"family":"Barlow","given":"Paul","email":"pbarlow@usgs.gov","middleInitial":"M.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":731193,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Welter, Dave E.","contributorId":203342,"corporation":false,"usgs":false,"family":"Welter","given":"Dave E.","affiliations":[{"id":36603,"text":"SFWMD","active":true,"usgs":false}],"preferred":false,"id":731194,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196893,"text":"70196893 - 2018 - Vertical self-sorting behavior in juvenile Chinook salmon (Oncorhynchus tshawytscha): evidence for family differences and variation in growth and morphology","interactions":[],"lastModifiedDate":"2018-05-17T15:37:23","indexId":"70196893","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Vertical self-sorting behavior in juvenile Chinook salmon (Oncorhynchus tshawytscha): evidence for family differences and variation in growth and morphology","docAbstract":"<p><span>Life history variation is fundamental to the evolution of Pacific salmon and their persistence under variable conditions. We discovered that Chinook salmon sort themselves into surface- and bottom-oriented groups in tanks within days after exogenous feeding. We hypothesised that this behaviour is correlated with subsequent differences in body morphology and growth (as measured by final length and mass) observed later in life. We found consistent morphological differences between surface and bottom phenotypes. Furthermore, we found that surface and bottom orientation within each group is maintained for at least one year after the phenotypes were separated. These surface and bottom phenotypes are expressed across genetic stocks, brood years, and laboratories and we show that the proportion of surface- and bottom-oriented offspring also differed among families. Importantly, feed delivery location did not affect morphology or growth, and the surface fish were longer than bottom fish at the end of the rearing experiment. The body shape of the former correlates with wild individuals that rear in mainstem habitats and migrate in the fall as subyearlings and the latter resemble those that remain in the upper tributaries and migrate as yearling spring migrants. Our findings suggest that early self-sorting behaviour may have a genetic basis and be correlated with other phenotypic traits that are important indicators for juvenile migration timing.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10641-017-0702-2","usgsCitation":"Unrein, J.R., Billman, E., Cogliati, K.M., Chitwood, R.S., Noakes, D.L., and Schreck, C.B., 2018, Vertical self-sorting behavior in juvenile Chinook salmon (Oncorhynchus tshawytscha): evidence for family differences and variation in growth and morphology: Environmental Biology of Fishes, v. 101, no. 2, p. 341-353, https://doi.org/10.1007/s10641-017-0702-2.","productDescription":"13 p.","startPage":"341","endPage":"353","ipdsId":"IP-066132","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"101","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-02","publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1c9","contributors":{"authors":[{"text":"Unrein, Julia R.","contributorId":172777,"corporation":false,"usgs":false,"family":"Unrein","given":"Julia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":735726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Billman, E.J.","contributorId":172038,"corporation":false,"usgs":false,"family":"Billman","given":"E.J.","email":"","affiliations":[],"preferred":false,"id":735727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cogliati, Karen M.","contributorId":200086,"corporation":false,"usgs":false,"family":"Cogliati","given":"Karen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chitwood, Rob S.","contributorId":172779,"corporation":false,"usgs":false,"family":"Chitwood","given":"Rob","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":735729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noakes, David L. G.","contributorId":195116,"corporation":false,"usgs":false,"family":"Noakes","given":"David","email":"","middleInitial":"L. G.","affiliations":[],"preferred":false,"id":735730,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734925,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70195454,"text":"70195454 - 2018 - Planetary dune workshop expands to include subaqueous processes","interactions":[],"lastModifiedDate":"2018-03-22T10:36:22","indexId":"70195454","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3879,"text":"Eos, Earth and Space Science News","active":true,"publicationSubtype":{"id":10}},"title":"Planetary dune workshop expands to include subaqueous processes","docAbstract":"<p><span>Dune-like structures appear in the depths of Earth’s oceans, across its landscapes, and in the extremities of the solar system beyond. Dunes rise up under the thick dense atmosphere of Venus, and they have been found under the almost unimaginably ephemeral atmosphere of a comet.</span></p>","conferenceTitle":"The Fifth International Planetary Dunes Workshop: From the Bottom of the Oceans to the Outer Limits of the Solar System","conferenceDate":"May 16-19, 2017","conferenceLocation":"St. George, UT","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018EO092783","usgsCitation":"Titus, T.N., Bryant, G., and Rubin, D.M., 2018, Planetary dune workshop expands to include subaqueous processes: Eos, Earth and Space Science News, v. 99, HTML, https://doi.org/10.1029/2018EO092783.","productDescription":"HTML","ipdsId":"IP-088713","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":469074,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018eo092783","text":"Publisher Index Page"},{"id":351705,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee743e4b0da30c1bfc201","contributors":{"authors":[{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":728680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bryant, Gerald","contributorId":202524,"corporation":false,"usgs":false,"family":"Bryant","given":"Gerald","email":"","affiliations":[{"id":36471,"text":"Dixie State University","active":true,"usgs":false}],"preferred":false,"id":728681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubin, David M. 0000-0003-1169-1452 drubin@usgs.gov","orcid":"https://orcid.org/0000-0003-1169-1452","contributorId":3159,"corporation":false,"usgs":true,"family":"Rubin","given":"David","email":"drubin@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":728682,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196629,"text":"70196629 - 2018 - Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA","interactions":[],"lastModifiedDate":"2018-04-23T10:01:33","indexId":"70196629","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1718,"text":"GCB Bioenergy","active":true,"publicationSubtype":{"id":10}},"title":"Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA","docAbstract":"<p><span>Switchgrass (</span><i>Panicum virgatum</i><span>) has been evaluated as one potential source for cellulosic biofuel feedstocks. Planting switchgrass in marginal croplands and waterway buffers can reduce soil erosion, improve water quality, and improve regional ecosystem services (i.e. it serves as a potential carbon sink). In previous studies, we mapped high risk marginal croplands and highly erodible cropland buffers that are potentially suitable for switchgrass development, which would improve ecosystem services and minimally impact food production. In this study, we advance our previous study results and integrate future crop expansion information to develop a switchgrass biofuel potential ensemble map for current and future croplands in eastern Nebraska. The switchgrass biomass productivity and carbon benefits (i.e. NEP: net ecosystem production) for the identified biofuel potential ensemble areas were quantified. The future scenario‐based (‘A1B’) land use and land cover map for 2050, the US Geological Survey crop type and Compound Topographic Index (CTI) maps, and long‐term (1981–2010) averaged annual precipitation data were used to identify future crop expansion regions that are suitable for switchgrass development. Results show that 2528&nbsp;km</span><sup>2</sup><span><span>&nbsp;</span>of future crop expansion regions (~3.6% of the study area) are potentially suitable for switchgrass development. The total estimated biofuel potential ensemble area (including cropland buffers, marginal croplands, and future crop expansion regions) is 4232&nbsp;km</span><sup>2</sup><span><span>&nbsp;</span>(~6% of the study area), potentially producing 3.52 million metric tons of switchgrass biomass per year. Converting biofuel ensemble regions to switchgrass leads to potential carbon sinks (the total NEP for biofuel potential areas is 0.45 million metric tons C) and is environmentally sustainable. Results from this study improve our understanding of environmental conditions and ecosystem services of current and future cropland systems in eastern Nebraska and provide useful information to land managers to make land use decisions regarding switchgrass development.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcbb.12468","usgsCitation":"Gu, Y., and Wylie, B., 2018, Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA: GCB Bioenergy, v. 10, no. 2, p. 76-83, https://doi.org/10.1111/gcbb.12468.","productDescription":"8 p.","startPage":"76","endPage":"83","ipdsId":"IP-087756","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469053,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcbb.12468","text":"Publisher Index Page"},{"id":353641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -99.1845703125,\n              40.01078714046552\n            ],\n            [\n              -95.30639648437499,\n              40.01078714046552\n            ],\n            [\n              -95.30639648437499,\n              42.99661231842139\n            ],\n            [\n              -99.1845703125,\n              42.99661231842139\n            ],\n            [\n              -99.1845703125,\n              40.01078714046552\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-12","publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1d7","contributors":{"authors":[{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":139586,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":733834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":197161,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce K.","email":"wylie@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":733835,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196116,"text":"70196116 - 2018 - Radium mobility and the age of groundwater in public-drinking-water supplies from the Cambrian-Ordovician aquifer system, north-central USA","interactions":[],"lastModifiedDate":"2018-03-21T10:03:13","indexId":"70196116","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Radium mobility and the age of groundwater in public-drinking-water supplies from the Cambrian-Ordovician aquifer system, north-central USA","docAbstract":"<p><span>High radium (Ra) concentrations in potable portions of the Cambrian-Ordovician (C-O) aquifer system were investigated using water-quality data and environmental tracers (</span><sup>3</sup><span>H,<span>&nbsp;</span></span><sup>3</sup><span>He</span><sub>trit</sub><span>, SF</span><sub>6</sub><span>,<span>&nbsp;</span></span><sup>14</sup><span>C and<span>&nbsp;</span></span><sup>4</sup><span>He</span><sub>rad</sub><span>) of groundwater age from 80 public-supply wells (PSWs). Groundwater ages were estimated by calibration of tracers to lumped parameter models and ranged from modern (&lt;50&nbsp;yr) in upgradient, regionally unconfined areas to ancient (&gt;1 Myr) in the most downgradient, confined portions of the potable system. More than 80 and 40 percent of mean groundwater ages were older than 1000 and 50,000&nbsp;yr, respectively. Anoxic, Fe-reducing conditions and increased mineralization develop with time in the aquifer system and mobilize Ra into solution resulting in the frequent occurrence of combined Ra (Ra</span><sub>c</sub><span>&nbsp;=&nbsp;</span><sup>226</sup><span>Ra +<span>&nbsp;</span></span><sup>228</sup><span>Ra) at concentrations exceeding the USEPA MCL of 185 mBq/L (5&nbsp;pCi/L). The distribution of the three Ra isotopes comprising total Ra (Ra</span><sub>t</sub><span>&nbsp;=&nbsp;</span><sup>224</sup><span>Ra +<span>&nbsp;</span></span><sup>226</sup><span>Ra +<span>&nbsp;</span></span><sup>228</sup><span>Ra) differed across the aquifer system. The concentrations of<span>&nbsp;</span></span><sup>224</sup><span>Ra and<span>&nbsp;</span></span><sup>228</sup><span>Ra were strongly correlated and comprised a larger proportion of the Ra</span><sub>t</sub><span><span>&nbsp;</span>concentration in samples from the regionally unconfined area, where arkosic sandstones provide an enhanced source for progeny from the<span>&nbsp;</span></span><sup>232</sup><span>Th&nbsp;decay series.<span>&nbsp;</span></span><sup>226</sup><span>Ra comprised a larger proportion of the Ra</span><sub>t</sub><span>concentration in samples from downgradient confined regions. Concentrations of Ra</span><sub>t</sub><span><span>&nbsp;</span>were significantly greater in samples from the regionally confined area of the aquifer system because of the increase in<span>&nbsp;</span></span><sup>226</sup><span>Ra concentrations there as compared to the regionally unconfined area.<span>&nbsp;</span></span><sup>226</sup><span>Ra distribution coefficients decreased substantially with anoxic conditions and increasing ionic strength of groundwater (mineralization), indicating that Ra is mobilized to solution from solid phases of the aquifer as adsorption capacity is diminished. The amount of<span>&nbsp;</span></span><sup>226</sup><span>Ra released from solid phases by alpha-recoil mechanisms and retained in solution increases relative to the amount of Ra sequestered by adsorption processes or co-precipitation with barite as adsorption capacity and the concentration of Ba decreases. Although<span>&nbsp;</span></span><sup>226</sup><span>Ra occurred at concentrations greater than<span>&nbsp;</span></span><sup>224</sup><span>Ra or<span>&nbsp;</span></span><sup>228</sup><span>Ra, the ingestion exposure risk was greater for<span>&nbsp;</span></span><sup>228</sup><span>Ra owing to its greater toxicity. In addition,<span>&nbsp;</span></span><sup>224</sup><span>Ra added substantial alpha-particle radioactivity to potable samples from the C-O aquifer system. Thus, monitoring for Ra isotopes and gross-alpha-activity (GAA) is important in upgradient, regionally unconfined areas as downgradient, and GAA measurements made within 72&nbsp;h of sample collection would best capture alpha-particle radiation from the short-lived<span>&nbsp;</span></span><sup>224</sup><span>Ra.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2017.11.002","usgsCitation":"Stackelberg, P.E., Szabo, Z., and Jurgens, B., 2018, Radium mobility and the age of groundwater in public-drinking-water supplies from the Cambrian-Ordovician aquifer system, north-central USA: Applied Geochemistry, v. 89, p. 34-48, https://doi.org/10.1016/j.apgeochem.2017.11.002.","productDescription":"15 p.","startPage":"34","endPage":"48","ipdsId":"IP-084578","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":469075,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2017.11.002","text":"Publisher Index Page"},{"id":438031,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BR8QP0","text":"USGS data release","linkHelpText":"Data for Radium Mobility and the Age of Groundwater in Public-drinking-water Supplies from the Cambrian-Ordovician Aquifer System, North-Central USA"},{"id":352683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.82275390625,\n              38.54816542304656\n            ],\n            [\n              -84.462890625,\n              38.54816542304656\n            ],\n            [\n              -84.462890625,\n              46.66451741754235\n            ],\n            [\n              -95.82275390625,\n              46.66451741754235\n            ],\n            [\n              -95.82275390625,\n              38.54816542304656\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"89","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee742e4b0da30c1bfc1ef","contributors":{"authors":[{"text":"Stackelberg, Paul E. 0000-0002-1818-355X pestack@usgs.gov","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":1069,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","email":"pestack@usgs.gov","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":2240,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":731427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":1503,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant C.","email":"bjurgens@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":731428,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192339,"text":"70192339 - 2018 - An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions","interactions":[],"lastModifiedDate":"2018-04-02T13:53:09","indexId":"70192339","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1191,"text":"Cartography and Geographic Information Science","active":true,"publicationSubtype":{"id":10}},"title":"An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions","docAbstract":"<p><span>This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10&nbsp;m. This research demonstrates the utility of open source tools with parallel computing support for extracting connected drainage network patterns and handling depressions in 30 subbasins distributed across humid, dry, and transitional climate regions and in terrain conditions exhibiting a range of slopes. Special attention is given to low-slope terrain, where network connectivity is preserved by generating synthetic stream channels through lake and waterbody polygons. Conflation analysis compares the extracted streams with a 1:24,000-scale National Hydrography Dataset flowline network and shows that similarities are greatest for second- and higher-order tributaries.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15230406.2017.1337524","usgsCitation":"Stanislawski, L.V., Survila, K., Wendel, J., Liu, Y., and Buttenfield, B., 2018, An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions: Cartography and Geographic Information Science, v. 45, no. 4, p. 319-328, https://doi.org/10.1080/15230406.2017.1337524.","productDescription":"10 p.","startPage":"319","endPage":"328","ipdsId":"IP-077833","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":350964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-04","publicationStatus":"PW","scienceBaseUri":"5a7586d8e4b00f54eb1d81f2","contributors":{"authors":[{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":715438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Survila, Kornelijus 0000-0003-4851-6084","orcid":"https://orcid.org/0000-0003-4851-6084","contributorId":196791,"corporation":false,"usgs":false,"family":"Survila","given":"Kornelijus","email":"","affiliations":[],"preferred":false,"id":715439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wendel, Jeffrey 0000-0003-0294-0250 jwendel@usgs.gov","orcid":"https://orcid.org/0000-0003-0294-0250","contributorId":196792,"corporation":false,"usgs":true,"family":"Wendel","given":"Jeffrey","email":"jwendel@usgs.gov","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":715441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Yan 0000-0003-2298-4728","orcid":"https://orcid.org/0000-0003-2298-4728","contributorId":196790,"corporation":false,"usgs":false,"family":"Liu","given":"Yan","email":"","affiliations":[],"preferred":false,"id":715442,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buttenfield, Barbara P.","contributorId":145538,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":715440,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196845,"text":"70196845 - 2018 - Estimating wetland connectivity to streams in the Prairie Pothole Region: An isotopic and remote sensing approach","interactions":[],"lastModifiedDate":"2018-05-04T10:36:11","indexId":"70196845","displayToPublicDate":"2018-02-01T00:00:00","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":"Estimating wetland connectivity to streams in the Prairie Pothole Region: An isotopic and remote sensing approach","docAbstract":"<p><span>Understanding hydrologic connectivity between wetlands and perennial streams is critical to understanding the reliance of stream flow on inputs from wetlands. We used the isotopic evaporation signal in water and remote sensing to examine wetland‐stream hydrologic connectivity within the Pipestem Creek watershed, North Dakota, a watershed dominated by prairie‐pothole wetlands. Pipestem Creek exhibited an evaporated‐water signal that had approximately half the isotopic‐enrichment signal found in most evaporatively enriched prairie‐pothole wetlands. Groundwater adjacent to Pipestem Creek had isotopic values that indicated recharge from winter precipitation and had no significant evaporative enrichment, indicating that enriched surface water did not contribute significantly to groundwater discharging into Pipestem Creek. The estimated surface water area necessary to generate the evaporation signal within Pipestem Creek was highly dynamic, varied primarily with the amount of discharge, and was typically greater than the immediate Pipestem Creek surface water area, indicating that surficial flow from wetlands contributed to stream flow throughout the summer. We propose a dynamic range of spilling thresholds for prairie‐pothole wetlands across the watershed allowing for wetland inputs even during low‐flow periods. Combining Landsat estimates with the isotopic approach allowed determination of potential (Landsat) and actual (isotope) contributing areas in wetland‐dominated systems. This combined approach can give insights into the changes in location and magnitude of surface water and groundwater pathways over time. This approach can be used in other areas where evaporation from wetlands results in a sufficient evaporative isotopic signal.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2017WR021016","usgsCitation":"Brooks, J.R., Mushet, D.M., Vanderhoof, M.K., Leibowitz, S.G., Christensen, J.R., Neff, B., Rosenberry, D.O., Rugh, W.D., and Alexander, L., 2018, Estimating wetland connectivity to streams in the Prairie Pothole Region: An isotopic and remote sensing approach: Water Resources Research, v. 54, no. 2, p. 955-977, https://doi.org/10.1002/2017WR021016.","productDescription":"23 p.","startPage":"955","endPage":"977","ipdsId":"IP-086197","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469082,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5903587","text":"Publisher Index Page"},{"id":353957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","volume":"54","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-09","publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1cb","contributors":{"authors":[{"text":"Brooks, J. R.","contributorId":204685,"corporation":false,"usgs":false,"family":"Brooks","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":36973,"text":"U.S. EPA, National Health and Environmental Effects Res Lab, Western Ecology Division, Corvallis, OR","active":true,"usgs":false}],"preferred":false,"id":734681,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":734680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":734682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leibowitz, Scott G.","contributorId":156432,"corporation":false,"usgs":false,"family":"Leibowitz","given":"Scott","email":"","middleInitial":"G.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":734686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, J. R.","contributorId":204686,"corporation":false,"usgs":false,"family":"Christensen","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":36974,"text":"U.S. Environmental Protection Agency, National Exposure Research Laboratory, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":734684,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neff, Brian 0000-0003-3718-7350 bneff@usgs.gov","orcid":"https://orcid.org/0000-0003-3718-7350","contributorId":198885,"corporation":false,"usgs":true,"family":"Neff","given":"Brian","email":"bneff@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":734685,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":734687,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rugh, W. D.","contributorId":204687,"corporation":false,"usgs":false,"family":"Rugh","given":"W.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":734688,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Alexander, L.C.","contributorId":204056,"corporation":false,"usgs":false,"family":"Alexander","given":"L.C.","email":"","affiliations":[{"id":36812,"text":"U.S. EPA, Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":734689,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70196961,"text":"70196961 - 2018 - Nonbreeding home‐range size and survival of lesser prairie‐chickens","interactions":[],"lastModifiedDate":"2018-05-15T16:56:19","indexId":"70196961","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Nonbreeding home‐range size and survival of lesser prairie‐chickens","docAbstract":"<p><span>The lesser prairie‐chicken (</span><i>Tympanuchus pallidicinctus</i><span>), a species of conservation concern with uncertain regulatory status, has experienced population declines over the past century. Most research on lesser prairie‐chickens has focused on the breeding season, with little research conducted during the nonbreeding season, a period that exerts a strong influence on demography in other upland game birds. We trapped lesser prairie‐chickens on leks and marked them with either global positioning system (GPS) satellite or very high frequency (VHF) transmitters to estimate survival and home‐range size during the nonbreeding season. We monitored 119 marked lesser prairie‐chickens in 3 study areas in Kansas, USA, from 16 September to 14 March in 2013, 2014, and 2015. We estimated home‐range size using Brownian Bridge movement models (GPS transmitters) and fixed kernel density estimators (VHF transmitters), and female survival using Kaplan–Meier known‐fate models. Average home‐range size did not differ between sexes. Estimated home‐range size was 3 times greater for individuals fitted with GPS satellite transmitters (</span><img class=\"section_image\" src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/2c179701-0c60-4087-af50-64559b0fd382/jwmg21390-math-0005.png\" alt=\"urn:x-wiley:14381656:media:jwmg21390:jwmg21390-math-0005\" data-mce-src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/2c179701-0c60-4087-af50-64559b0fd382/jwmg21390-math-0005.png\"><span> = 997 ha) than those with VHF transmitters (</span><img class=\"section_image\" src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/cc4a0e9f-303f-46fa-be8a-d33cc178cb68/jwmg21390-math-0006.png\" alt=\"urn:x-wiley:14381656:media:jwmg21390:jwmg21390-math-0006\" data-mce-src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/cc4a0e9f-303f-46fa-be8a-d33cc178cb68/jwmg21390-math-0006.png\"><span> = 286 ha), likely a result of the temporal resolution of the different transmitters. Home‐range size of GPS‐marked birds increased 2.8 times relative to the breeding season and varied by study area and year. Home‐range size was smaller in the 2013–2014 nonbreeding season (</span><img class=\"section_image\" src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/a0f30e98-ec64-4508-b33d-1542b38220ab/jwmg21390-math-0007.png\" alt=\"urn:x-wiley:14381656:media:jwmg21390:jwmg21390-math-0007\" data-mce-src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/a0f30e98-ec64-4508-b33d-1542b38220ab/jwmg21390-math-0007.png\"><span> = 495 ha) than the following 2 nonbreeding seasons (</span><img class=\"section_image\" src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/c03a4caf-700f-42dd-bf54-a854ed5a9525/jwmg21390-math-0008.png\" alt=\"urn:x-wiley:14381656:media:jwmg21390:jwmg21390-math-0008\" data-mce-src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/c03a4caf-700f-42dd-bf54-a854ed5a9525/jwmg21390-math-0008.png\"><span> = 1,290 ha and<span>&nbsp;</span></span><img class=\"section_image\" src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/dce88549-9369-4fd1-bf50-79ba36e8f234/jwmg21390-math-0009.png\" alt=\"urn:x-wiley:14381656:media:jwmg21390:jwmg21390-math-0009\" data-mce-src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/dce88549-9369-4fd1-bf50-79ba36e8f234/jwmg21390-math-0009.png\"><span> = 1,158 ha), corresponding with drought conditions of 2013, which were alleviated in following years. Female survival (</span><img class=\"section_image\" src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/0ec2e8c9-c112-4a67-9a9a-7760150fcb5c/jwmg21390-math-0010.png\" alt=\"urn:x-wiley:14381656:media:jwmg21390:jwmg21390-math-0010\" data-mce-src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/0ec2e8c9-c112-4a67-9a9a-7760150fcb5c/jwmg21390-math-0010.png\"><span>) was high relative to breeding season estimates, and did not differ by study area or year (</span><img class=\"section_image\" src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/f668f7c3-5042-40ca-90d1-23a4855bd972/jwmg21390-math-0011.png\" alt=\"urn:x-wiley:14381656:media:jwmg21390:jwmg21390-math-0011\" data-mce-src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/f668f7c3-5042-40ca-90d1-23a4855bd972/jwmg21390-math-0011.png\"><span> = 0.73 ± 0.04 [SE]). Future management could remain focused on the breeding season because nonbreeding survival was 39–44% greater than the previous breeding season; however, considerations of total space needs would benefit lesser prairie‐chickens by accounting for the greater spatial requirements during the nonbreeding season.<span>&nbsp;</span></span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21390","usgsCitation":"Robinson, S.G., Haukos, D.A., Plumb, R.T., Lautenbach, J.M., Sullins, D.S., Kraft, J.D., Lautenbach, J.D., Hagen, C.A., and Pitman, J.C., 2018, Nonbreeding home‐range size and survival of lesser prairie‐chickens: Journal of Wildlife Management, v. 82, no. 2, p. 413-423, https://doi.org/10.1002/jwmg.21390.","productDescription":"11 p.","startPage":"413","endPage":"423","ipdsId":"IP-087792","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21390","text":"Publisher Index Page"},{"id":354202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","county":"Clark County, Comanche County, Gove County, Kiowa County, Logan County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0135,37.3849],[-99.0008,37.3849],[-99.0005,37.0008],[-99.4004,37.0001],[-99.4516,37],[-99.5399,36.9998],[-100.0009,36.9985],[-100.0024,36.9985],[-100.0902,36.9983],[-100.0898,37.3855],[-100.106,37.3862],[-100.1068,37.4751],[-99.5557,37.4689],[-99.5584,37.7354],[-99.0142,37.7339],[-99.0136,37.471],[-99.0135,37.3849]]],[[[-100.7201,39.1338],[-100.7005,39.1333],[-100.6086,39.1335],[-100.589,39.1329],[-100.497,39.1331],[-100.4775,39.1329],[-100.3867,39.1325],[-100.3689,39.1328],[-100.2757,39.1319],[-100.2585,39.1321],[-100.1642,39.1321],[-100.1488,39.1318],[-100.1543,38.6966],[-100.2481,38.6976],[-100.4687,38.6988],[-100.5772,38.6997],[-100.5973,38.7003],[-100.6882,38.7037],[-100.8168,38.7032],[-101.1293,38.7001],[-101.485,38.7002],[-101.4779,39.1339],[-101.3913,39.1345],[-101.3669,39.1342],[-101.2791,39.1344],[-101.2548,39.1345],[-101.1664,39.1346],[-101.1438,39.1342],[-101.0554,39.1346],[-101.0334,39.1346],[-100.9444,39.1342],[-100.8323,39.1336],[-100.8121,39.133],[-100.7201,39.1338]]]]},\"properties\":{\"name\":\"Clark\",\"state\":\"KS\"}}]}","volume":"82","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-27","publicationStatus":"PW","scienceBaseUri":"5afee73fe4b0da30c1bfc1c7","contributors":{"authors":[{"text":"Robinson, Samantha G.","contributorId":172786,"corporation":false,"usgs":false,"family":"Robinson","given":"Samantha","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":735457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":735146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plumb, Reid T.","contributorId":172787,"corporation":false,"usgs":false,"family":"Plumb","given":"Reid","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":735458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lautenbach, Joseph M.","contributorId":172788,"corporation":false,"usgs":false,"family":"Lautenbach","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735459,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullins, Daniel S.","contributorId":166689,"corporation":false,"usgs":false,"family":"Sullins","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":735460,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kraft, John D.","contributorId":172789,"corporation":false,"usgs":false,"family":"Kraft","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":735461,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lautenbach, Jonathan D.","contributorId":172790,"corporation":false,"usgs":false,"family":"Lautenbach","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":735462,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hagen, Christian A.","contributorId":177795,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":735463,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pitman, James C.","contributorId":40529,"corporation":false,"usgs":true,"family":"Pitman","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":735464,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70194986,"text":"70194986 - 2018 - Modulators of mercury risk to wildlife and humans in the context of rapid global change","interactions":[],"lastModifiedDate":"2018-02-05T15:27:15","indexId":"70194986","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":698,"text":"Ambio","active":true,"publicationSubtype":{"id":10}},"title":"Modulators of mercury risk to wildlife and humans in the context of rapid global change","docAbstract":"<p><span>Environmental mercury (Hg) contamination is an urgent global health threat. The complexity of Hg in the environment can hinder accurate determination of ecological and human health risks, particularly within the context of the rapid global changes that are altering many ecological processes, socioeconomic patterns, and other factors like infectious disease incidence, which can affect Hg exposures and health outcomes. However, the success of global Hg-reduction efforts depends on accurate assessments of their effectiveness in reducing health risks. In this paper, we examine the role that key extrinsic and intrinsic drivers play on several aspects of Hg risk to humans and organisms in the environment. We do so within three key domains of ecological and human health risk. First, we examine how extrinsic global change drivers influence pathways of Hg bioaccumulation and biomagnification through food webs. Next, we describe how extrinsic socioeconomic drivers at a global scale, and intrinsic individual-level drivers, influence human Hg exposure. Finally, we address how the adverse health effects of Hg in humans and wildlife are modulated by a range of extrinsic and intrinsic drivers within the context of rapid global change. Incorporating components of these three domains into research and monitoring will facilitate a more holistic understanding of how ecological and societal drivers interact to influence Hg health risks.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s13280-017-1011-x","usgsCitation":"Eagles-Smith, C.A., Silbergeld, E.K., Basu, N., Bustamante, P., Diaz-Barriga, F., Hopkins, W., Kidd, K.A., and Nyland, J.F., 2018, Modulators of mercury risk to wildlife and humans in the context of rapid global change: Ambio, v. 47, no. 2, p. 170-197, https://doi.org/10.1007/s13280-017-1011-x.","productDescription":"18 p.","startPage":"170","endPage":"197","ipdsId":"IP-091232","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469066,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13280-017-1011-x","text":"Publisher Index Page"},{"id":350886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-31","publicationStatus":"PW","scienceBaseUri":"5a74357fe4b0a9a2e9e25c82","contributors":{"authors":[{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":726364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Silbergeld, Ellen K.","contributorId":201550,"corporation":false,"usgs":false,"family":"Silbergeld","given":"Ellen","email":"","middleInitial":"K.","affiliations":[{"id":13508,"text":"Johns Hopkins Bloomberg School of Public health","active":true,"usgs":false}],"preferred":false,"id":726365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Basu, Niladri","contributorId":60085,"corporation":false,"usgs":false,"family":"Basu","given":"Niladri","email":"","affiliations":[],"preferred":false,"id":726366,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bustamante, Paco","contributorId":201551,"corporation":false,"usgs":false,"family":"Bustamante","given":"Paco","email":"","affiliations":[{"id":36199,"text":"La Rochelle University","active":true,"usgs":false}],"preferred":false,"id":726367,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diaz-Barriga, Fernando","contributorId":201552,"corporation":false,"usgs":false,"family":"Diaz-Barriga","given":"Fernando","email":"","affiliations":[{"id":36200,"text":"Universidad Autónoma de San Luis Potosí","active":true,"usgs":false}],"preferred":false,"id":726368,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hopkins, William A.","contributorId":201553,"corporation":false,"usgs":false,"family":"Hopkins","given":"William A.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":726369,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kidd, Karen A.","contributorId":201554,"corporation":false,"usgs":false,"family":"Kidd","given":"Karen","email":"","middleInitial":"A.","affiliations":[{"id":25502,"text":"McMaster University","active":true,"usgs":false}],"preferred":false,"id":726370,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nyland, Jennifer F.","contributorId":201555,"corporation":false,"usgs":false,"family":"Nyland","given":"Jennifer","email":"","middleInitial":"F.","affiliations":[{"id":36201,"text":"Salisbury University","active":true,"usgs":false}],"preferred":false,"id":726371,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70194983,"text":"70194983 - 2018 - Limited contribution of ancient methane to surface waters of the U.S. Beaufort Sea shelf","interactions":[],"lastModifiedDate":"2018-02-01T11:47:29","indexId":"70194983","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Limited contribution of ancient methane to surface waters of the U.S. Beaufort Sea shelf","docAbstract":"<p><span>In response to warming climate, methane can be released to Arctic Ocean sediment and waters from thawing subsea permafrost and decomposing methane hydrates. However, it is unknown whether methane derived from this sediment storehouse of frozen ancient carbon reaches the atmosphere. We quantified the fraction of methane derived from ancient sources in shelf waters of the U.S. Beaufort Sea, a region that has both permafrost and methane hydrates and is experiencing significant warming. Although the radiocarbon-methane analyses indicate that ancient carbon is being mobilized and emitted as methane into shelf bottom waters, surprisingly, we find that methane in surface waters is principally derived from modern-aged carbon. We report that at and beyond approximately the 30-m isobath, ancient sources that dominate in deep waters contribute, at most, 10 ± 3% of the surface water methane. These results suggest that even if there is a heightened liberation of ancient carbon–sourced methane as climate change proceeds, oceanic oxidation and dispersion processes can strongly limit its emission to the atmosphere.</span></p>","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.aao4842","usgsCitation":"Sparrow, K.J., Kessler, J.D., Southon, J.R., Garcia-Tigreros, F., Schreiner, K.M., Ruppel, C.D., Miller, J.B., Lehman, S.J., and Xu, X., 2018, Limited contribution of ancient methane to surface waters of the U.S. Beaufort Sea shelf: Science Advances, v. 4, no. 1, eaao4842; 7 p., https://doi.org/10.1126/sciadv.aao4842.","productDescription":"eaao4842; 7 p.","ipdsId":"IP-091258","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aao4842","text":"Publisher Index Page"},{"id":350888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"1","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a743580e4b0a9a2e9e25c86","contributors":{"authors":[{"text":"Sparrow, Katy J.","contributorId":201537,"corporation":false,"usgs":false,"family":"Sparrow","given":"Katy","email":"","middleInitial":"J.","affiliations":[{"id":36190,"text":"Department of Earth and Environmental Sciences, University of Rochester, Rochester, New York, USA","active":true,"usgs":false}],"preferred":false,"id":726338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kessler, John D. 0000-0003-1097-6800","orcid":"https://orcid.org/0000-0003-1097-6800","contributorId":184241,"corporation":false,"usgs":false,"family":"Kessler","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":726339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Southon, John R.","contributorId":201538,"corporation":false,"usgs":false,"family":"Southon","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":36191,"text":"Keck Carbon Cycle AMS Laboratory, Department of Earth System Science, University of California Irvine, Irvine, California, USA.","active":true,"usgs":false}],"preferred":false,"id":726340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia-Tigreros, Fenix 0000-0001-8694-9046","orcid":"https://orcid.org/0000-0001-8694-9046","contributorId":194744,"corporation":false,"usgs":false,"family":"Garcia-Tigreros","given":"Fenix","email":"","affiliations":[],"preferred":false,"id":726341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schreiner, Kathryn M.","contributorId":201540,"corporation":false,"usgs":false,"family":"Schreiner","given":"Kathryn","email":"","middleInitial":"M.","affiliations":[{"id":36192,"text":"Large Lakes Observatory, University of Minnesota Duluth, Duluth, Minnesota, USA.","active":true,"usgs":false}],"preferred":false,"id":726342,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":195778,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn","email":"cruppel@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":726337,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, John B.","contributorId":37304,"corporation":false,"usgs":true,"family":"Miller","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":726343,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lehman, Scott J.","contributorId":201559,"corporation":false,"usgs":false,"family":"Lehman","given":"Scott","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":726344,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Xu, Xiaomei","contributorId":32055,"corporation":false,"usgs":true,"family":"Xu","given":"Xiaomei","affiliations":[],"preferred":false,"id":726345,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70194989,"text":"70194989 - 2018 - Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model","interactions":[],"lastModifiedDate":"2018-02-02T10:29:37","indexId":"70194989","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model","docAbstract":"<p><span>Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO</span><sub>2</sub><span>concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085–2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO</span><sub>2</sub><span>, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO</span><sub>2</sub><span><span>&nbsp;</span>concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO</span><sub>2</sub><span><span>&nbsp;</span>concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of  ∼  70 % relative to the baseline scenario, due to elevated CO</span><sub>2</sub><span><span>&nbsp;</span>concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha</span><sup>−1</sup><span><span>&nbsp;</span>in nitrate yield relative to the watershed with a lower percent of croplands as a result of increased export of nitrate derived from fertilizer. The watershed dominated by poorly drained soils showed increased nitrate removal due do enhanced denitrification compared to the watershed dominated by well-drained soils. Our findings suggest that increased implementation of conservation practices would be necessary for this region to mitigate increased nitrate loads associated with predicted changes in future climate.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-22-689-2018","usgsCitation":"Lee, S., Yeo, I., Sadeghi, A.M., McCarty, G.W., Hively, W., Lang, M.W., and Sharifi, A., 2018, Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model: Hydrology and Earth System Sciences, v. 22, p. 689-708, https://doi.org/10.5194/hess-22-689-2018.","productDescription":"10 p.","startPage":"689","endPage":"708","ipdsId":"IP-090233","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-689-2018","text":"Publisher Index Page"},{"id":350956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Greensboro Watershed, Tuckahoe Creek Watershed","volume":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-25","publicationStatus":"PW","scienceBaseUri":"5a7586d6e4b00f54eb1d81d4","contributors":{"authors":[{"text":"Lee, Sangchul","contributorId":201237,"corporation":false,"usgs":false,"family":"Lee","given":"Sangchul","email":"","affiliations":[],"preferred":false,"id":726400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeo, In-Young","contributorId":131145,"corporation":false,"usgs":false,"family":"Yeo","given":"In-Young","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":726402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sadeghi, Ali M.","contributorId":131147,"corporation":false,"usgs":false,"family":"Sadeghi","given":"Ali","email":"","middleInitial":"M.","affiliations":[{"id":7262,"text":"USDA-ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705","active":true,"usgs":false}],"preferred":false,"id":726401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":726403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hively, Wells whively@usgs.gov","contributorId":201563,"corporation":false,"usgs":true,"family":"Hively","given":"Wells","email":"whively@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":726399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":726404,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sharifi, Amir","contributorId":201564,"corporation":false,"usgs":false,"family":"Sharifi","given":"Amir","email":"","affiliations":[{"id":18168,"text":"USDA ARS","active":true,"usgs":false}],"preferred":false,"id":726405,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70195024,"text":"70195024 - 2018 - The northern pike, a prized native but disastrous invasive: Chapter 14","interactions":[],"lastModifiedDate":"2018-02-13T14:45:43","indexId":"70195024","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The northern pike, a prized native but disastrous invasive: Chapter 14","docAbstract":"<p><span>As the chapters in this book describe, the northern pike Esox lucius Linneaus, 1758 is a fascinating fish that plays an important ecological role in structuring aquatic communities (chapter 8), has the capacity to aid lake restoration efforts (chapter 11), and contributes substantially to local economies, both as a highlysought after sport fish (chapter 12) and as a commercial fishing resource (chapter 13). However, despite the magnificent attributes of this fish, there is another side to its story. Specifically, what happens when northern pike, a highly efficient predator, becomes established outside its natural range? To explore this question, this chapter will investigate observed consequences from many locations where northern pike (hereafter referred to as “pike”) have been introduced and discuss potential reasons why pike, under the right circumstances, can be considered an invasive species.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Biology and ecology of pike","language":"English","publisher":"CRC Press","isbn":"9781482262902","usgsCitation":"Rutz, D., Massengill, R.L., Sepulveda, A.J., and Dunker, K.J., 2018, The northern pike, a prized native but disastrous invasive: Chapter 14, chap. <i>of</i> Biology and ecology of pike, 43 p.","productDescription":"43 p.","ipdsId":"IP-081440","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":350996,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcpress.com/Biology-and-Ecology-of-Pike/Skov-Nilsson/p/book/9781482262902"},{"id":351546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee743e4b0da30c1bfc20b","contributors":{"authors":[{"text":"Rutz, David","contributorId":201636,"corporation":false,"usgs":false,"family":"Rutz","given":"David","affiliations":[{"id":36220,"text":"Alaska Department of Fish & Game","active":true,"usgs":false}],"preferred":false,"id":726631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Massengill, Robert L.","contributorId":174630,"corporation":false,"usgs":false,"family":"Massengill","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":726630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":726628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunker, Kristine J.","contributorId":38864,"corporation":false,"usgs":false,"family":"Dunker","given":"Kristine","email":"","middleInitial":"J.","affiliations":[{"id":6770,"text":"Alaska Department of Fish & Game, Division of Commercial Fish, Soldotna, AK 99669","active":true,"usgs":false}],"preferred":false,"id":726629,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70194981,"text":"70194981 - 2018 - Environmental DNA (eDNA): A tool for quantifying the abundant but elusive round goby (Neogobius melanostomus)","interactions":[],"lastModifiedDate":"2018-02-01T12:47:52","indexId":"70194981","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Environmental DNA (eDNA): A tool for quantifying the abundant but elusive round goby (<i>Neogobius melanostomus</i>)","title":"Environmental DNA (eDNA): A tool for quantifying the abundant but elusive round goby (Neogobius melanostomus)","docAbstract":"<p><span>Environmental DNA (eDNA) is revolutionizing biodiversity monitoring, occupancy estimates, and real-time detections of invasive species. In the Great Lakes, the round goby (</span><i>Neogobius melanostomus</i><span>), an invasive benthic fish from the Black Sea, has spread to encompass all five lakes and many tributaries, outcompeting or consuming native species; however, estimates of round goby abundance are confounded by behavior and habitat preference, which impact reliable methods for estimating their population. By integrating eDNA into round goby monitoring, improved estimates of biomass may be obtainable. We conducted mesocosm experiments to estimate rates of goby DNA shedding and decay. Further, we compared eDNA with several methods of traditional field sampling to compare its use as an alternative/complementary monitoring method. Environmental DNA decay was comparable to other fish species, and first-order decay was lower at 12°C (k = 0.043) than at 19°C (k = 0.058). Round goby eDNA was routinely detected in known invaded sites of Lake Michigan and its tributaries (range log</span><sub>10</sub><span><span>&nbsp;</span>4.8–6.2 CN/L), but not upstream of an artificial fish barrier. Traditional techniques (mark-recapture, seining, trapping) in Lakes Michigan and Huron resulted in fewer, more variable detections than eDNA, but trapping and eDNA were correlated (Pearson R = 0.87). Additional field testing will help correlate round goby abundance with eDNA, providing insight on its role as a prey fish and its impact on food webs.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0191720","usgsCitation":"Nevers, M., Byappanahalli, M., Morris, C.C., Shively, D., Przybyla-Kelly, K., Spoljaric, A., Dickey, J., and Roseman, E.F., 2018, Environmental DNA (eDNA): A tool for quantifying the abundant but elusive round goby (Neogobius melanostomus): PLoS ONE, v. 13, no. 1, p. 1-22, https://doi.org/10.1371/journal.pone.0191720.","productDescription":"e0191720; 22 p.","startPage":"1","endPage":"22","ipdsId":"IP-091049","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469070,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0191720","text":"Publisher Index Page"},{"id":350891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350889,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GH9H6F","text":"USGS data release","linkHelpText":"Round goby eDNA survey, evaluation, and laboratory data in Lakes Michigan and Huron 2016-2017"}],"country":"United States","otherGeospatial":"Lake Huron, Lake Michigan ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.48098754882812,\n              44.864629668602866\n            ],\n            [\n              -83.19808959960936,\n              44.864629668602866\n            ],\n            [\n              -83.19808959960936,\n              45.091944150432724\n            ],\n            [\n              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PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-22","publicationStatus":"PW","scienceBaseUri":"5a743581e4b0a9a2e9e25c8a","contributors":{"authors":[{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":726326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":726327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Charles C.","contributorId":201532,"corporation":false,"usgs":false,"family":"Morris","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":726328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shively, Dawn 0000-0002-6119-924X dshively@usgs.gov","orcid":"https://orcid.org/0000-0002-6119-924X","contributorId":201533,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":726329,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Przybyla-Kelly, Katarzyna 0000-0001-9168-3545 kprzybyla-kelly@usgs.gov","orcid":"https://orcid.org/0000-0001-9168-3545","contributorId":201534,"corporation":false,"usgs":true,"family":"Przybyla-Kelly","given":"Katarzyna","email":"kprzybyla-kelly@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":726330,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spoljaric, Ashley M.","contributorId":201535,"corporation":false,"usgs":false,"family":"Spoljaric","given":"Ashley M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":726331,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dickey, Joshua","contributorId":201536,"corporation":false,"usgs":false,"family":"Dickey","given":"Joshua","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":726332,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roseman, Edward F. 0000-0002-5315-9838 eroseman@usgs.gov","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":168428,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward","email":"eroseman@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":726333,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70194987,"text":"70194987 - 2018 - Determinants of Pseudogymnoascus destructans within bat hibernacula: Implications for surveillance and management of white-nose syndrome","interactions":[],"lastModifiedDate":"2023-06-30T14:48:58.619547","indexId":"70194987","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Determinants of <i>Pseudogymnoascus destructans</i> within bat hibernacula: Implications for surveillance and management of white-nose syndrome","title":"Determinants of Pseudogymnoascus destructans within bat hibernacula: Implications for surveillance and management of white-nose syndrome","docAbstract":"<ol id=\"jpe13070-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li>Fungal diseases are an emerging global problem affecting human health, food security and biodiversity. Ability of many fungal pathogens to persist within environmental reservoirs can increase extinction risks for host species and presents challenges for disease control. Understanding factors that regulate pathogen spread and persistence in these reservoirs is critical for effective disease management.</li><li>White-nose syndrome (WNS) is a disease of hibernating bats caused by<span>&nbsp;</span><i>Pseudogymnoascus destructans</i><span>&nbsp;</span>(<i>Pd</i>), a fungus that establishes persistent environmental reservoirs within bat hibernacula, which contribute to seasonal disease transmission dynamics in bats. However, host and environmental factors influencing distribution of<span>&nbsp;</span><i>Pd</i>within these reservoirs are unknown.</li><li>We used model selection on longitudinally collected field data to test multiple hypotheses describing presence–absence and abundance of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>in environmental substrates and on bats within hibernacula at different stages of WNS.</li><li>First detection of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>in the environment lagged up to 1&nbsp;year after first detection on bats within that hibernaculum. Once detected, the probability of detecting<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>within environmental samples from a hibernaculum increased over time and was higher in sediment compared to wall surfaces. Temperature had marginal effects on the distribution of<span>&nbsp;</span><i>Pd</i>. For bats, prevalence and abundance of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>were highest on<span>&nbsp;</span><i>Myotis lucifugus</i><span>&nbsp;</span>and on bats with visible signs of WNS.</li><li><i>Synthesis and applications</i>. Our results indicate that distribution of<span>&nbsp;</span><i>Pseudogymnoascus destructans</i><span>&nbsp;</span>(<i>Pd</i>) within a hibernaculum is driven primarily by bats with delayed establishment of environmental reservoirs. Thus, collection of samples from<span>&nbsp;</span><i>Myotis lucifugus</i>, or from sediment if bats cannot be sampled, should be prioritized to improve detection probabilities for<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>surveillance. Long-term persistence of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>in sediment suggests that disease management for white-nose syndrome should address risks of sustained transmission from environmental reservoirs.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13070","usgsCitation":"Verant, M.L., Bohuski, E.A., Richgels, K.L., Olival, K.J., Epstein, J.H., and Blehert, D.S., 2018, Determinants of Pseudogymnoascus destructans within bat hibernacula: Implications for surveillance and management of white-nose syndrome: Journal of Applied Ecology, v. 55, no. 2, p. 820-829, https://doi.org/10.1111/1365-2664.13070.","productDescription":"10 p.","startPage":"820","endPage":"829","ipdsId":"IP-078933","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":469050,"rank":3,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5877478","text":"External Repository"},{"id":350885,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418657,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77D2SP5","text":"USGS data release","description":"USGS data release","linkHelpText":"Determinants of Pseudogymnoascus destructans within bat hibernacula: data"}],"volume":"55","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-15","publicationStatus":"PW","scienceBaseUri":"5a74357fe4b0a9a2e9e25c7d","contributors":{"authors":[{"text":"Verant, Michelle L.","contributorId":201556,"corporation":false,"usgs":false,"family":"Verant","given":"Michelle","email":"","middleInitial":"L.","affiliations":[{"id":36202,"text":"School of Veterinary Medicine, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":726377,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohuski, Elizabeth A. 0000-0001-8061-2151 ebohuski@usgs.gov","orcid":"https://orcid.org/0000-0001-8061-2151","contributorId":5890,"corporation":false,"usgs":true,"family":"Bohuski","given":"Elizabeth","email":"ebohuski@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":726378,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richgels, Katherine L. D. 0000-0003-2834-9477 krichgels@usgs.gov","orcid":"https://orcid.org/0000-0003-2834-9477","contributorId":151205,"corporation":false,"usgs":true,"family":"Richgels","given":"Katherine","email":"krichgels@usgs.gov","middleInitial":"L. D.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":726379,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olival, Kevin J.","contributorId":143712,"corporation":false,"usgs":false,"family":"Olival","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":7118,"text":"EcoHealth Alliance","active":true,"usgs":false}],"preferred":false,"id":726380,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Epstein, Jonathan H.","contributorId":201557,"corporation":false,"usgs":false,"family":"Epstein","given":"Jonathan","email":"","middleInitial":"H.","affiliations":[{"id":36203,"text":"Ecohealth Alliamce","active":true,"usgs":false}],"preferred":false,"id":726381,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":140397,"corporation":false,"usgs":true,"family":"Blehert","given":"David","email":"dblehert@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":726376,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70194932,"text":"70194932 - 2018 - Mineral commodity summaries 2018","interactions":[],"lastModifiedDate":"2018-06-08T09:10:46","indexId":"70194932","displayToPublicDate":"2018-01-31T15:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"seriesTitle":{"id":368,"text":"Mineral Commodity Summaries","active":false,"publicationSubtype":{"id":6}},"title":"Mineral commodity summaries 2018","docAbstract":"<p>This report is the earliest Government publication to furnish estimates covering 2017 nonfuel mineral industry data. Data sheets contain information on the domestic industry structure, Government programs, tariffs, and 5-year salient statistics for more than 90 individual minerals and materials.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70194932","usgsCitation":"U.S. Geological Survey, 2018, Mineral commodity summaries 2018: U.S. Geological Survey, 200 p., https://doi.org/10.3133/70194932.","productDescription":"200 p.","numberOfPages":"204","ipdsId":"IP-094560","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":350834,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/graphics/minerals-commodity-2018.jpg"},{"id":350835,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/","text":"Mineral Commodity Summaries Index Page","linkFileType":{"id":5,"text":"html"},"description":"Link to page with all USGS Mineral Commodities Summaries"}],"contact":"<p>Director, <a href=\"https://minerals.usgs.gov/minerals/\" data-mce-href=\"https://minerals.usgs.gov/minerals/\">National Minerals Information Center</a><br> U.S. Geological Survey<br> 12201 Sunrise Valley Drive<br> 988 National Center<br> Reston, VA 20192<br> Email: <a href=\"mailto:nmicrecordsmgt@usgs.gov\" data-mce-href=\"mailto:nmicrecordsmgt@usgs.gov\">nmicrecordsmgt@usgs.gov</a></p>","publishedDate":"2018-01-31","noUsgsAuthors":false,"publicationDate":"2018-01-31","publicationStatus":"PW","scienceBaseUri":"5a72e3e5e4b0a9a2e9e08ea5","contributors":{"authors":[{"text":"Ober, Joyce A. 0000-0003-1608-5611 jober@usgs.gov","orcid":"https://orcid.org/0000-0003-1608-5611","contributorId":394,"corporation":false,"usgs":true,"family":"Ober","given":"Joyce","email":"jober@usgs.gov","middleInitial":"A.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":726241,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70194887,"text":"sir20185011 - 2018 - Flood-inundation maps for the Withlacoochee River From Skipper Bridge Road to St. Augustine Road, within the City of Valdosta, Georgia, and Lowndes County, Georgia","interactions":[],"lastModifiedDate":"2018-06-11T09:26:02","indexId":"sir20185011","displayToPublicDate":"2018-01-31T10:00:00","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":"2018-5011","title":"Flood-inundation maps for the Withlacoochee River From Skipper Bridge Road to St. Augustine Road, within the City of Valdosta, Georgia, and Lowndes County, Georgia","docAbstract":"<p>Digital flood-inundation maps for a 12.6-mile reach of the Withlacoochee River from Skipper Bridge Road to St. Augustine Road (Georgia State Route 133) were developed to depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey (USGS) streamgage at Withlacoochee River at Skipper Bridge Road, near Bemiss, Ga. (023177483). Real-time stage information from this streamgage can be used with these maps to estimate near real-time areas of inundation. The forecasted peak-stage information for the USGS streamgage at Withlacoochee River at Skipper Bridge Road, near Bemiss, Ga. (023177483), can be used in conjunction with the maps developed for this study to show predicted areas of flood inundation.</p><p>A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers Hydrologic Engineer-ing Center’s River Analysis System (HEC–RAS) software for the Withlacoochee River and was used to compute flood profiles for a 12.6-mile reach of the Withlacoochee River. The hydraulic model was then used to simulate 23 water-surface profiles at 1.0-foot (ft) intervals at the Withlacoochee River near the Bemiss streamgage. The profiles ranged from the National Weather Service action stage of 10.7 ft, which is 131.0 ft above the North American Vertical Datum of 1988 (NAVD 88), to a stage of 32.7 ft, which is 153.0 ft above NAVD 88. The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging (lidar) data having a 4.0-ft horizontal resolution—to delineate the area flooded at each 1.0-ft interval of stream stage.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185011","collaboration":"Prepared in cooperation with the City of Valdosta, Georgia, and Lowndes County, Georgia","usgsCitation":"Musser, J.W., 2018, Flood-inundation maps for the Withlacoochee River from Skipper Bridge Road to St. Augustine Road, within the City of Valdosta, Georgia, and Lowndes County, Georgia: U.S. Geological Survey Scientific Investigations Report 2018–5011, 15 p., https://doi.org/10.3133/sir20185011.","productDescription":"Report: viii, 18 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087876","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":350785,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5011/coverthb.jpg"},{"id":350787,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71N809J","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood-inundation area for the Withlacoochee River in Lowndes County, Georgia from Skipper Bridge Road to St. Augustine Road"},{"id":350786,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5011/sir20185011.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5011"}],"country":"United States","state":"Georgia","county":"Lowndes County","city":"Valdosta","otherGeospatial":"Withlacoochee 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href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director</a><a>, </a><a href=\"https://www.usgs.gov/centers/sa-water\" data-mce-href=\"https://www.usgs.gov/centers/sa-water\">South Atlantic Water Science Center</a><br> U.S. Geological Survey<br> 720 Gracern Road<br> Columbia, SC 29210</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract&nbsp;</li><li>Introduction</li><li>Constructing Water-Surface Profiles</li><li>Flood-Inundation Mapping</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2018-01-31","noUsgsAuthors":false,"publicationDate":"2018-01-31","publicationStatus":"PW","scienceBaseUri":"5a72e3e6e4b0a9a2e9e08eb0","contributors":{"authors":[{"text":"Musser, Jonathan W. 0000-0002-3543-0807 jwmusser@usgs.gov","orcid":"https://orcid.org/0000-0002-3543-0807","contributorId":2266,"corporation":false,"usgs":true,"family":"Musser","given":"Jonathan","email":"jwmusser@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":726163,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70189140,"text":"ofr20171085 - 2018 - Evaluation of the Radar Stage Sensor manufactured by Forest Technology Systems—Results of laboratory and field testing","interactions":[],"lastModifiedDate":"2018-02-01T10:37:53","indexId":"ofr20171085","displayToPublicDate":"2018-01-31T00:00:00","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":"2017-1085","title":"Evaluation of the Radar Stage Sensor manufactured by Forest Technology Systems—Results of laboratory and field testing","docAbstract":"<p>Two identical Radar Stage Sensors from Forest Technology Systems were evaluated to determine if they are suitable for U.S. Geological Survey (USGS) hydrologic data collection. The sensors were evaluated in laboratory conditions to evaluate the distance accuracy of the sensor over the manufacturer’s specified operating temperatures and distance to water ranges. Laboratory results were compared to the manufacturer’s accuracy specification of ±0.007 foot (ft) and the USGS Office of Surface Water (OSW) policy requirement that water-level sensors have a measurement uncertainty of no more than 0.01 ft or 0.20 percent of the indicated reading. Both of the sensors tested were within the OSW policy requirement in both laboratory tests and within the manufacturer’s specification in the distance to water test over tested distances from 3 to 15 ft. In the temperature chamber test, both sensors were within the manufacturer’s specification for more than 90 percent of the data points collected over a temperature range of –40 to +60 degrees Celsius at a fixed distance of 8 ft. One sensor was subjected to an SDI-12 communication test, which it passed. A field test was conducted on one sensor at a USGS field site near Landon, Mississippi, from February 5 to March 29, 2016. Water-level measurements made by the radar during the field test were in agreement with those made by the Sutron Accubar Constant Flow Bubble Gauge.</p><p>Upon the manufacturer’s release of updated firmware version 1.09, additional SDI-12 and temperature testing was performed to evaluate added SDI-12 functions and verify that performance was unaffected by the update. At this time, an Axiom data logger is required to perform a firmware update on this sensor. The data confirmed the results of the original test. Based on the test results, the Radar Stage Sensor is a suitable choice for USGS hydrologic data collection.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171085","usgsCitation":"Kunkle, G.A., 2018, Evaluation of the Radar Stage Sensor manufactured by Forest Technology Systems—Results of laboratory and field testing: U.S. Geological Survey Open-File Report 2017–1085, 12 p., https://doi.org/10.3133/ofr20171085.","productDescription":"Report: iv, 12 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-083860","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":350803,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71C1VSR","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Evaluation of the Radar Stage Sensor Manufactured by Forest Technology Systems, Incorporated—Results of Laboratory and Field Testing"},{"id":350800,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1085/ofr20171085.pdf","text":"Report","size":"918 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1085"},{"id":350799,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1085/coverthb.jpg"}],"contact":"<p>Chief, <a href=\"https://water.usgs.gov/hif/\" data-mce-href=\"https://water.usgs.gov/hif/\">Hydrologic Instrumentation Facility</a><br>U.S. Geological Survey<br>Building 2101<br>Stennis Space Center, MS 39529</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Description of the Radar Stage Sensor<br></li><li>Methods<br></li><li>Results<br></li><li>Conclusions<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2018-01-31","noUsgsAuthors":false,"publicationDate":"2018-01-31","publicationStatus":"PW","scienceBaseUri":"5a72e3e8e4b0a9a2e9e08ecc","contributors":{"authors":[{"text":"Kunkle, Gerald A. 0000-0002-3700-7746 gkunkle@usgs.gov","orcid":"https://orcid.org/0000-0002-3700-7746","contributorId":194077,"corporation":false,"usgs":true,"family":"Kunkle","given":"Gerald","email":"gkunkle@usgs.gov","middleInitial":"A.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":703141,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70194958,"text":"ofr20181007 - 2018 - Development and release of phenological data products—A case study in compliance with federal open data policy","interactions":[],"lastModifiedDate":"2018-08-10T16:28:37","indexId":"ofr20181007","displayToPublicDate":"2018-01-31T00:00:00","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":"2018-1007","title":"Development and release of phenological data products—A case study in compliance with federal open data policy","docAbstract":"<p><span>In Autumn 2015, USA National Phenology Network (USA-NPN) staff implemented new U.S. Geological Survey (USGS) data-management policies intended to ensure that the results of Federally funded research are made available to the public. The effort aimed both to improve USA-NPN data releases and to provide a model for similar programs within the USGS. This report provides an overview of the steps taken to ensure compliance, following the USGS Science Data Lifecycle, and provides lessons learned about the data-release process for USGS program leaders and data managers.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181007","usgsCitation":"Rosemartin, A., Langseth, M.L., Crimmins, T.M., and Weltzin, J.F., 2018, Development and release of phenological data products—A case study in compliance with federal open data policy: U.S. Geological Survey Open-File Report 2018–1007, 13 p., https://doi.org/10.3133/ofr20181007.","productDescription":"iv, 13 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-090322","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":350850,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1007/coverthb.jpg"},{"id":350851,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1007/ofr20181007.pdf","text":"Report","size":"350 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1007"}],"contact":"<p><a href=\"https://www2.usgs.gov/ecosystems/\" data-mce-href=\"https://www2.usgs.gov/ecosystems/\">Ecosystems Mission Area</a><br><a href=\"https://www.usgs.gov/\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>12201 Sunrise Valley Dr., MS 300<br>Reston, VA 20192<br></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Purpose and Scope<br></li><li>USA-NPN: Data Products for Science and Decisionmaking<br></li><li>The Data-Management Planning Process<br></li><li>Case Study – Historical Annual Spring Indices<br></li><li>Conclusions and Recommendations<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-01-31","noUsgsAuthors":false,"publicationDate":"2018-01-31","publicationStatus":"PW","scienceBaseUri":"5a72e3e7e4b0a9a2e9e08eb7","contributors":{"authors":[{"text":"Rosemartin, Alyssa H.","contributorId":178239,"corporation":false,"usgs":false,"family":"Rosemartin","given":"Alyssa","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":726292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langseth, Madison L. 0000-0002-4472-9106 mlangseth@usgs.gov","orcid":"https://orcid.org/0000-0002-4472-9106","contributorId":149156,"corporation":false,"usgs":true,"family":"Langseth","given":"Madison","email":"mlangseth@usgs.gov","middleInitial":"L.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":726293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crimmins, Theresa","contributorId":103579,"corporation":false,"usgs":false,"family":"Crimmins","given":"Theresa","affiliations":[],"preferred":false,"id":726294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weltzin, Jake F. 0000-0001-8641-6645 jweltzin@usgs.gov","orcid":"https://orcid.org/0000-0001-8641-6645","contributorId":149648,"corporation":false,"usgs":true,"family":"Weltzin","given":"Jake F.","email":"jweltzin@usgs.gov","affiliations":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"preferred":false,"id":726295,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70195000,"text":"70195000 - 2018 - Earthquake potential in California-Nevada implied by correlation of strain rate and seismicity","interactions":[],"lastModifiedDate":"2018-03-19T11:18:53","indexId":"70195000","displayToPublicDate":"2018-01-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake potential in California-Nevada implied by correlation of strain rate and seismicity","docAbstract":"Rock mechanics studies and dynamic earthquake simulations show that patterns of seismicity evolve with time through (1) accumulation phase, (2) localization phase, and (3) rupture phase. We observe a similar pattern of changes in seismicity during the past century across California and Nevada. To quantify these changes, we correlate GPS strain rates with seismicity. Earthquakes of M > 6.5 are collocated with regions of highest strain rates. By contrast, smaller magnitude earthquakes of M ≥ 4 show clear spatiotemporal changes. From 1933 to the late 1980s, earthquakes of M ≥ 4 were more diffused and broadly distributed in both high and low strain rate regions (accumulation phase). From the late 1980s to 2016, earthquakes were more concentrated within the high strain rate areas focused on the major fault strands (localization phase). In the same time period, the rate of M > 6.5 events also increased significantly in the high strain rate areas. The strong correlation between current strain rate and the later period of seismicity indicates that seismicity is closely related to the strain rate. The spatial patterns suggest that before the late 1980s, the strain rate field was also broadly distributed because of the stress shadows from previous large earthquakes. As the deformation field evolved out of the shadow in the late 1980s, strain has refocused on the major fault systems and we are entering a period of increased risk for large earthquakes in California.","language":"English","publisher":"Wiley","doi":"10.1002/2017GL075967","usgsCitation":"Zeng, Y., Petersen, M.D., and Shen, Z., 2018, Earthquake potential in California-Nevada implied by correlation of strain rate and seismicity: Geophysical Research Letters, v. 45, no. 4, p. 1778-1785, https://doi.org/10.1002/2017GL075967.","productDescription":"8 p.","startPage":"1778","endPage":"1785","ipdsId":"IP-090085","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":350943,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-19","publicationStatus":"PW","scienceBaseUri":"5a7586d6e4b00f54eb1d81d7","contributors":{"authors":[{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":726509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":726510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shen, Zheng-Kang","contributorId":145691,"corporation":false,"usgs":false,"family":"Shen","given":"Zheng-Kang","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":726511,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194873,"text":"fs20183003 - 2018 - Missouri StreamStats—A water-resources web application","interactions":[],"lastModifiedDate":"2018-01-31T10:16:10","indexId":"fs20183003","displayToPublicDate":"2018-01-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3003","title":"Missouri StreamStats—A water-resources web application","docAbstract":"<p><span>The U.S.&nbsp;Geological Survey (USGS) maintains and operates more than 8,200&nbsp;continuous streamgages nationwide. Types of data that may be collected, computed, and stored for streamgages include streamgage height (water-surface elevation), streamflow, and water quality. The streamflow data allow scientists and engineers to calculate streamflow statistics, such as the 1-percent annual exceedance probability flood (also known as the 100-year flood), the mean flow, and the 7-day, 10-year low flow, which are used by managers to make informed water resource management decisions, at each streamgage location. Researchers, regulators, and managers also commonly need physical characteristics (basin characteristics) that describe the unique properties of a basin. Common uses for streamflow statistics and basin characteristics include hydraulic design, water-supply management, water-use appropriations, and flood-plain mapping for establishing flood-insurance rates and land-use zones. The USGS periodically publishes reports that update the values of basin characteristics and streamflow statistics at selected gaged locations (locations with streamgages), but these studies usually only update a subset of streamgages, making data retrieval difficult. Additionally, streamflow statistics and basin characteristics are most often needed at ungaged locations (locations without streamgages) for which published streamflow statistics and basin characteristics do not exist. </span></p><p>Missouri StreamStats is a web-based geographic information system that was created by the USGS in cooperation with the Missouri Department of Natural Resources to provide users with access to an assortment of tools that are useful for water-resources planning and management. StreamStats allows users to easily obtain the most recent published streamflow statistics and basin characteristics for streamgage locations and to automatically calculate selected basin characteristics and estimate streamflow statistics at ungaged locations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183003","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Ellis, J.T., 2018, Missouri StreamStats—A water-resources web application: U.S. Geological Survey Fact Sheet 2018–3003, 6 p., https://doi.org/10.3133/fs20183003.","productDescription":"6 p.","onlineOnly":"N","ipdsId":" IP-091212","costCenters":[{"id":396,"text":"Missouri Water Science 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 \"}}]}","contact":"<p><a href=\"mailto: dc_mo@usgs.gov\" data-mce-href=\"mailto: dc_mo@usgs.gov\">Director</a>, <a href=\"https://mo.water.usgs.gov/\" data-mce-href=\"https://mo.water.usgs.gov/\">Missouri Water Science Center</a><br>U.S. Geological Survey <br>1400 Independence Road <br>Rolla, MO 65401</p>","tableOfContents":"<ul><li>Introduction<br></li><li>User Interface<br></li><li>Streamflow Statistics at Ungaged Locations<br></li><li>Limitations<br></li><li>Future Functionality<br></li><li>Selected References<br></li></ul>","publishedDate":"2018-01-31","noUsgsAuthors":false,"publicationDate":"2018-01-31","publicationStatus":"PW","scienceBaseUri":"5a72e3e7e4b0a9a2e9e08ebd","contributors":{"authors":[{"text":"Ellis, Jarrett T.","contributorId":93050,"corporation":false,"usgs":true,"family":"Ellis","given":"Jarrett T.","affiliations":[{"id":396,"text":"Missouri Water Science 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,{"id":70196246,"text":"70196246 - 2018 - Water stress from high-volume hydraulic fracturing potentially threatens aquatic biodiversity and ecosystem services in Arkansas, United States","interactions":[],"lastModifiedDate":"2018-03-28T12:01:22","indexId":"70196246","displayToPublicDate":"2018-01-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Water stress from high-volume hydraulic fracturing potentially threatens aquatic biodiversity and ecosystem services in Arkansas, United States","docAbstract":"<p><span>Demand for high-volume, short duration water withdrawals could create water stress to aquatic organisms in Fayetteville Shale streams sourced for hydraulic fracturing fluids. We estimated potential water stress using permitted water withdrawal volumes and actual water withdrawals compared to monthly median, low, and high streamflows. Risk for biological stress was considered at 20% of long-term median and 10% of high- and low-flow thresholds. Future well build-out projections estimated potential for continued stress. Most water was permitted from small, free-flowing streams and “frack” ponds (dammed streams). Permitted 12-h pumping volumes exceeded median streamflow at 50% of withdrawal sites in June, when flows were low. Daily water usage, from operator disclosures, compared to median streamflow showed possible water stress in 7–51% of catchments from June–November, respectively. If 100% of produced water was recycled, per-well water use declined by 25%, reducing threshold exceedance by 10%. Future water stress was predicted to occur in fewer catchments important for drinking water and species of conservation concern due to the decline in new well installations and increased use of recycled water. Accessible and precise withdrawal and streamflow data are critical moving forward to assess and mitigate water stress in streams that experience high-volume withdrawals.</span></p>","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.7b03304","usgsCitation":"Entrekin, S., Trainor, A., Saiers, J., Patterson, L., Maloney, K.O., Fargione, J., Kiesecker, J.M., Baruch-Mordo, S., Konschnik, K.E., Wiseman, H., Nicot, J., and Ryan, J.N., 2018, Water stress from high-volume hydraulic fracturing potentially threatens aquatic biodiversity and ecosystem services in Arkansas, United States: Environmental Science & Technology, v. 52, no. 4, p. 2349-2358, https://doi.org/10.1021/acs.est.7b03304.","productDescription":"10 p.","startPage":"2349","endPage":"2358","ipdsId":"IP-079892","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":352824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","volume":"52","issue":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-31","publicationStatus":"PW","scienceBaseUri":"5afee744e4b0da30c1bfc211","contributors":{"authors":[{"text":"Entrekin, Sally","contributorId":147949,"corporation":false,"usgs":false,"family":"Entrekin","given":"Sally","affiliations":[{"id":16964,"text":"University of Central Arkansas","active":true,"usgs":false}],"preferred":false,"id":731854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trainor, Anne","contributorId":191831,"corporation":false,"usgs":false,"family":"Trainor","given":"Anne","affiliations":[],"preferred":false,"id":731855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saiers, James","contributorId":191832,"corporation":false,"usgs":false,"family":"Saiers","given":"James","affiliations":[],"preferred":false,"id":731856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patterson, Lauren","contributorId":203604,"corporation":false,"usgs":false,"family":"Patterson","given":"Lauren","affiliations":[],"preferred":false,"id":731857,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":731858,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fargione, Joseph","contributorId":191828,"corporation":false,"usgs":false,"family":"Fargione","given":"Joseph","affiliations":[],"preferred":false,"id":731859,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kiesecker, Joseph M.","contributorId":146679,"corporation":false,"usgs":false,"family":"Kiesecker","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":731860,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baruch-Mordo, Sharon","contributorId":191830,"corporation":false,"usgs":false,"family":"Baruch-Mordo","given":"Sharon","email":"","affiliations":[],"preferred":false,"id":731861,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Konschnik, Katherine E.","contributorId":191826,"corporation":false,"usgs":false,"family":"Konschnik","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":731862,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wiseman, Hannah","contributorId":191827,"corporation":false,"usgs":false,"family":"Wiseman","given":"Hannah","affiliations":[],"preferred":false,"id":731863,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nicot, Jean-Philippe","contributorId":175575,"corporation":false,"usgs":false,"family":"Nicot","given":"Jean-Philippe","email":"","affiliations":[],"preferred":false,"id":731864,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ryan, Joseph N.","contributorId":54290,"corporation":false,"usgs":false,"family":"Ryan","given":"Joseph","email":"","middleInitial":"N.","affiliations":[{"id":604,"text":"University of Colorado- Boulder","active":false,"usgs":true}],"preferred":false,"id":731865,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70194843,"text":"sim3397 - 2018 - Maps showing predicted probabilities for selected dissolved oxygen and dissolved manganese threshold events in depth zones used by the domestic and public drinking water supply wells, Central Valley, California","interactions":[],"lastModifiedDate":"2018-02-01T10:50:58","indexId":"sim3397","displayToPublicDate":"2018-01-31T00:00:00","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":"3397","title":"Maps showing predicted probabilities for selected dissolved oxygen and dissolved manganese threshold events in depth zones used by the domestic and public drinking water supply wells, Central Valley, California","docAbstract":"<p>The purpose of the prediction grids for selected redox constituents—dissolved oxygen and dissolved manganese—are intended to provide an understanding of groundwater-quality conditions at the domestic and public-supply drinking water depths. The chemical quality of groundwater and the fate of many contaminants is influenced by redox processes in all aquifers, and understanding the redox conditions horizontally and vertically is critical in evaluating groundwater quality. The redox condition of groundwater—whether oxic (oxygen present) or anoxic (oxygen absent)—strongly influences the oxidation state of a chemical in groundwater. The anoxic dissolved oxygen thresholds of &lt;0.5 milligram per liter (mg/L), &lt;1.0 mg/L, and &lt;2.0 mg/L were selected to apply broadly to regional groundwater-quality investigations. Although the presence of dissolved manganese in groundwater indicates strongly reducing (anoxic) groundwater conditions, it is also considered a “nuisance” constituent in drinking water, making drinking water undesirable with respect to taste, staining, or scaling. Three dissolved manganese thresholds, &lt;50 micrograms per liter (µg/L), &lt;150 µg/L, and &lt;300 µg/L, were selected to create predicted probabilities of exceedances in depth zones used by domestic and public-supply water wells. The 50 µg/L event threshold represents the secondary maximum contaminant level (SMCL) benchmark for manganese (U.S. Environmental Protection Agency, 2017; California Division of Drinking Water, 2014), whereas the 300 µg/L event threshold represents the U.S. Geological Survey (USGS) health-based screening level (HBSL) benchmark, used to put measured concentrations of drinking-water contaminants into a human-health context (Toccalino and others, 2014). The 150 µg/L event threshold represents one-half the USGS HBSL. The resultant dissolved oxygen and dissolved manganese prediction grids may be of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to anoxic conditions. Prediction grids for selected redox constituents and thresholds were created by the USGS National Water-Quality Assessment (NAWQA) modeling and mapping team.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3397","usgsCitation":"Rosecrans, C.Z., Nolan, B.T., and Gronberg, J.M., 2018, Maps showing predicted probabilities for selected dissolved oxygen and dissolved manganese threshold events in depth zones used by the domestic and public drinking water supply wells, Central Valley, California: U.S. Geological Survey Scientific Investigations Map 3397, 2 sheets, various scales, https://doi.org/10.3133/sim3397.","productDescription":"2 Sheets: 18.99 x 24.04 inches and 18.99 x 23.75 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-083513","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":350545,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T151S1","linkHelpText":"Probability distribution grids of dissolved oxygen and dissolved manganese concentrations at selected thresholds in drinking water depth zones, Central Valley, California"},{"id":350705,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3397/sim3397_plate1_.pdf","text":"Plate 1","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3397","linkHelpText":" - Spatial Distribution of Predicted Probabilities for Selected Dissolved Oxygen Threshold Events"},{"id":350544,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3397/coverthb_.jpg"},{"id":350706,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3397/sim3397_plate2.pdf","text":"Plate 2","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3397","linkHelpText":" - Spatial Distribution of Predicted Probabilities for Selected Dissolved Manganese Threshold Events"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.354736328125,\n              40.17887331434696\n            ],\n            [\n              -122.2119140625,\n              38.02213147353745\n            ],\n            [\n              -119.46533203125,\n              34.858890491257796\n            ],\n            [\n              -118.54248046874999,\n              34.93097858831627\n            ],\n            [\n              -118.57543945312501,\n              35.29943548054545\n            ],\n            [\n              -118.93798828125,\n              36.465471886798134\n            ],\n            [\n              -119.5751953125,\n              36.94989178681327\n            ],\n            [\n              -120.487060546875,\n              37.70120736474139\n            ],\n            [\n              -120.92651367187499,\n              38.05674222065296\n            ],\n            [\n              -121.11328124999999,\n              38.676933444637925\n            ],\n            [\n              -121.47583007812501,\n              39.39375459224348\n            ],\n            [\n              -121.53076171875,\n              39.64799732373418\n            ],\n            [\n              -121.871337890625,\n              39.977120098439634\n            ],\n            [\n              -122.1240234375,\n              40.212440718286466\n            ],\n            [\n              -122.310791015625,\n              40.212440718286466\n            ],\n            [\n              -122.354736328125,\n              40.17887331434696\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://mail.google.com/mail/?view=cm&amp;fs=1&amp;tf=1&amp;to=dc_ca@usgs.gov\" target=\"_blank\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>, <br><a href=\"http://ca.water.usgs.gov/\" data-mce-href=\"http://ca.water.usgs.gov/\">California Water Science Center</a><br>6000 J Street, Placer Hall<br>Sacramento, CA 95819<br></p>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2018-01-31","noUsgsAuthors":false,"publicationDate":"2018-01-31","publicationStatus":"PW","scienceBaseUri":"5a72e3e8e4b0a9a2e9e08ec5","contributors":{"authors":[{"text":"Rosecrans, Celia Z. 0000-0003-1456-4360 crosecrans@usgs.gov","orcid":"https://orcid.org/0000-0003-1456-4360","contributorId":187542,"corporation":false,"usgs":true,"family":"Rosecrans","given":"Celia","email":"crosecrans@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":725978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":725979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gronberg, JoAnn M. 0000-0003-4822-7434 jmgronbe@usgs.gov","orcid":"https://orcid.org/0000-0003-4822-7434","contributorId":3548,"corporation":false,"usgs":true,"family":"Gronberg","given":"JoAnn","email":"jmgronbe@usgs.gov","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":725980,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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