{"pageNumber":"391","pageRowStart":"9750","pageSize":"25","recordCount":40804,"records":[{"id":70196033,"text":"70196033 - 2018 - Overcoming equifinality: Leveraging long time series for stream metabolism estimation","interactions":[],"lastModifiedDate":"2020-09-02T13:05:49.378881","indexId":"70196033","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Overcoming equifinality: Leveraging long time series for stream metabolism estimation","docAbstract":"

The foundational ecosystem processes of gross primary production (GPP) and ecosystem respiration (ER) cannot be measured directly but can be modeled in aquatic ecosystems from subdaily patterns of oxygen (O2) concentrations. Because rivers and streams constantly exchange O2 with the atmosphere, models must either use empirical estimates of the gas exchange rate coefficient (K600) or solve for all three parameters (GPP, ER, and K600) simultaneously. Empirical measurements of K600 require substantial field work and can still be inaccurate. Three-parameter models have suffered from equifinality, where good fits to O2 data are achieved by many different parameter values, some unrealistic. We developed a new three-parameter, multiday model that ensures similar values for K600 among days with similar physical conditions (e.g., discharge). Our new model overcomes the equifinality problem by (1) flexibly relating K600 to discharge while permitting moderate daily deviations and (2) avoiding the oft-violated assumption that residuals in O2 predictions are uncorrelated. We implemented this hierarchical state-space model and several competitor models in an open-source R package, streamMetabolizer. We then tested the models against both simulated and field data. Our new model reduces error by as much as 70% in daily estimates of K600, GPP, and ER. Further, accuracy benefits of multiday data sets require as few as 3 days of data. This approach facilitates more accurate metabolism estimates for more streams and days, enabling researchers to better quantify carbon fluxes, compare streams by their metabolic regimes, and investigate controls on aquatic activity.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JG004140","usgsCitation":"Appling, A.P., Hall, R., Yackulic, C.B., and Arroita, M., 2018, Overcoming equifinality: Leveraging long time series for stream metabolism estimation: Journal of Geophysical Research: Biogeosciences, v. 123, no. 2, p. 624-645, https://doi.org/10.1002/2017JG004140.","productDescription":"22 p.","startPage":"624","endPage":"645","ipdsId":"IP-089889","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468966,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jg004140","text":"Publisher Index Page"},{"id":352520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0e6","contributors":{"authors":[{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":731078,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Robert O. Jr.","contributorId":145459,"corporation":false,"usgs":false,"family":"Hall","given":"Robert O.","suffix":"Jr.","affiliations":[{"id":16121,"text":"Uni. of Wyoming, Department of Zoology and Physiology","active":true,"usgs":false}],"preferred":false,"id":731079,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arroita, Maite 0000-0001-8754-7604","orcid":"https://orcid.org/0000-0001-8754-7604","contributorId":203307,"corporation":false,"usgs":false,"family":"Arroita","given":"Maite","email":"","affiliations":[{"id":36597,"text":"Flathead Lake Biological Station, University of Montana; University of the Basque Country","active":true,"usgs":false}],"preferred":false,"id":731081,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195695,"text":"70195695 - 2018 - Spatial and spectral interpolation of ground-motion intensity measure observations","interactions":[],"lastModifiedDate":"2018-08-08T15:52:47","indexId":"70195695","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and spectral interpolation of ground-motion intensity measure observations","docAbstract":"

Following a significant earthquake, ground‐motion observations are available for a limited set of locations and intensity measures (IMs). Typically, however, it is desirable to know the ground motions for additional IMs and at locations where observations are unavailable. Various interpolation methods are available, but because IMs or their logarithms are normally distributed, spatially correlated, and correlated with each other at a given location, it is possible to apply the conditional multivariate normal (MVN) distribution to the problem of estimating unobserved IMs. In this article, we review the MVN and its application to general estimation problems, and then apply the MVN to the specific problem of ground‐motion IM interpolation. In particular, we present (1) a formulation of the MVN for the simultaneous interpolation of IMs across space and IM type (most commonly, spectral response at different oscillator periods) and (2) the inclusion of uncertain observation data in the MVN formulation. These techniques, in combination with modern empirical ground‐motion models and correlation functions, provide a flexible framework for estimating a variety of IMs at arbitrary locations.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170201","usgsCitation":"Worden, C., Thompson, E.M., Baker, J.W., Bradley, B.A., Luco, N., and Wald, D.J., 2018, Spatial and spectral interpolation of ground-motion intensity measure observations: Bulletin of the Seismological Society of America, v. 108, no. 2, p. 866-875, https://doi.org/10.1785/0120170201.","productDescription":"10 p.","startPage":"866","endPage":"875","ipdsId":"IP-092580","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":352117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"108","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-13","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0f0","contributors":{"authors":[{"text":"Worden, Charles 0000-0003-1181-685X cbworden@usgs.gov","orcid":"https://orcid.org/0000-0003-1181-685X","contributorId":152042,"corporation":false,"usgs":true,"family":"Worden","given":"Charles","email":"cbworden@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":146592,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":729736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, Jack W.","contributorId":115861,"corporation":false,"usgs":false,"family":"Baker","given":"Jack","email":"","middleInitial":"W.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":729737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradley, Brendon A.","contributorId":202814,"corporation":false,"usgs":false,"family":"Bradley","given":"Brendon","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":729738,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729739,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":741992,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196797,"text":"70196797 - 2018 - AMModels: An R package for storing models, data, and metadata to facilitate adaptive management","interactions":[],"lastModifiedDate":"2018-05-01T15:52:43","indexId":"70196797","displayToPublicDate":"2018-02-28T00:00:00","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}},"title":"AMModels: An R package for storing models, data, and metadata to facilitate adaptive management","docAbstract":"

Agencies are increasingly called upon to implement their natural resource management programs within an adaptive management (AM) framework. This article provides the background and motivation for the R package, AMModels. AMModels was developed under R version 3.2.2. The overall goal of AMModels is simple: To codify knowledge in the form of models and to store it, along with models generated from numerous analyses and datasets that may come our way, so that it can be used or recalled in the future. AMModels facilitates this process by storing all models and datasets in a single object that can be saved to an .RData file and routinely augmented to track changes in knowledge through time. Through this process, AMModels allows the capture, development, sharing, and use of knowledge that may help organizations achieve their mission. While AMModels was designed to facilitate adaptive management, its utility is far more general. Many R packages exist for creating and summarizing models, but to our knowledge, AMModels is the only package dedicated not to the mechanics of analysis but to organizing analysis inputs, analysis outputs, and preserving descriptive metadata. We anticipate that this package will assist users hoping to preserve the key elements of an analysis so they may be more confidently revisited at a later date.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0188966","usgsCitation":"Donovan, T.M., and Katz, J., 2018, AMModels: An R package for storing models, data, and metadata to facilitate adaptive management: PLoS ONE, v. 13, no. 2, p. 1-57, https://doi.org/10.1371/journal.pone.0188966.","productDescription":"e0188966; 57","startPage":"1","endPage":"57","ipdsId":"IP-081371","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":461013,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0188966","text":"Publisher Index Page"},{"id":353899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0e4","contributors":{"authors":[{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katz, Jonathan","contributorId":8370,"corporation":false,"usgs":true,"family":"Katz","given":"Jonathan","affiliations":[],"preferred":false,"id":734478,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195754,"text":"70195754 - 2018 - Future southcentral US wildfire probability due to climate change","interactions":[],"lastModifiedDate":"2018-03-26T13:47:27","indexId":"70195754","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1246,"text":"Climate Change","onlineIssn":"1573-1480","printIssn":"0165-0009","active":true,"publicationSubtype":{"id":10}},"title":"Future southcentral US wildfire probability due to climate change","docAbstract":"

Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. In this paper, we present projections of future fire probability for the southcentral USA using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM). Future fire probability is projected to both increase and decrease across the study region of Oklahoma, New Mexico, and Texas. Among all end-of-century projections, change in fire probabilities (CFPs) range from − 51 to + 240%. Greatest absolute increases in fire probability are shown for areas within the range of approximately 75 to 160 cm mean annual precipitation (MAP), regardless of climate model. Although fire is likely to become more frequent across the southcentral USA, spatial patterns may remain similar unless significant increases in precipitation occur, whereby more extensive areas with increased fire probability are predicted. Perhaps one of the most important results is illumination of climate changes where fire probability response (+, −) may deviate (i.e., tipping points). Fire regimes of southcentral US ecosystems occur in a geographic transition zone from reactant- to reaction-limited conditions, potentially making them uniquely responsive to different scenarios of temperature and precipitation changes. Identification and description of these conditions may help anticipate fire regime changes that will affect human health, agriculture, species conservation, and nutrient and water cycling.

","language":"English","publisher":"Springer","doi":"10.1007/s10584-018-2156-8","usgsCitation":"Stambaugh, M.C., Guyette, R.P., Stroh, E.D., Struckhoff, M.A., and Whittier, J.B., 2018, Future southcentral US wildfire probability due to climate change: Climate Change, v. 147, no. 3-4, p. 617-631, https://doi.org/10.1007/s10584-018-2156-8.","productDescription":"15 p.","startPage":"617","endPage":"631","ipdsId":"IP-088702","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":352124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","issue":"3-4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-26","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0ea","contributors":{"authors":[{"text":"Stambaugh, Michael C.","contributorId":202826,"corporation":false,"usgs":false,"family":"Stambaugh","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":13706,"text":"University of Missouri-Columbia","active":true,"usgs":false}],"preferred":false,"id":729793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guyette, Richard P.","contributorId":176595,"corporation":false,"usgs":false,"family":"Guyette","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":729794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stroh, Esther D. 0000-0003-4291-4647 estroh@usgs.gov","orcid":"https://orcid.org/0000-0003-4291-4647","contributorId":2813,"corporation":false,"usgs":true,"family":"Stroh","given":"Esther","email":"estroh@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":729792,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Struckhoff, Matthew A. 0000-0002-4911-9956 mstruckhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-4911-9956","contributorId":2095,"corporation":false,"usgs":true,"family":"Struckhoff","given":"Matthew","email":"mstruckhoff@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":729795,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whittier, Joanna B.","contributorId":53151,"corporation":false,"usgs":false,"family":"Whittier","given":"Joanna","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":729801,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195565,"text":"ofr20181029 - 2018 - Suspended-sediment transport from the Green-Duwamish River to the Lower Duwamish Waterway, Seattle, Washington, 2013–17","interactions":[],"lastModifiedDate":"2018-03-01T11:06:55","indexId":"ofr20181029","displayToPublicDate":"2018-02-28T00:00:00","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":"2018-1029","title":"Suspended-sediment transport from the Green-Duwamish River to the Lower Duwamish Waterway, Seattle, Washington, 2013–17","docAbstract":"

The Green-Duwamish River transports watershed-derived sediment to the Lower Duwamish Waterway Superfund site near Seattle, Washington. Understanding the amount of sediment transported by the river is essential to the bed sediment cleanup process. Turbidity, discharge, suspended-sediment concentration (SSC), and particle-size data were collected by the U.S. Geological Survey (USGS) from February 2013 to January 2017 at the Duwamish River, Washington, within the tidal influence at river kilometer 16.7 (USGS streamgage 12113390; Duwamish River at Golf Course at Tukwila, WA). This report quantifies the timing and magnitude of suspended-sediment transported in the Duwamish River. Regression models were developed between SSC and turbidity and SSC and discharge to estimate 15- minute SSC. Suspended-sediment loads were calculated from the computed SSC and time-series discharge data for every 15-minute interval during the study period. The 2014–16 average annual suspended-sediment load computed was 117,246 tons (106,364 metric tons), of which 73.5 percent or (86,191 tons; 78,191 metric tons) was fine particle (less than 0.0625 millimeter in diameter) suspended sediment. The seasonality of this site is apparent when you divide the year into \"wet\" (October 16– April 15) and \"dry\" (April 16–October 15) seasons. Most (97 percent) of the annual suspended sediment was transported during the wet season, when brief periods of intense precipitation from storms, large releases from the Howard Hanson Dam, or a combination of both were much more frequent.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181029","collaboration":"Prepared in cooperation with the Washington State Department of Ecology","usgsCitation":"Senter, C.A., Conn, K.E., Black, R.W., Peterson, N., Vanderpool-Kimura, A., and Foreman, J.R., 2018, Suspended-sediment transport from the Green-Duwamish River to the Lower Duwamish Waterway, Seattle, Washington, 2013–17: U.S. Geological Survey Open-File Report 2018–1029, 23 p., https://doi.org/10.3133/ofr20181029.","productDescription":"Report: vi, 23 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-092733","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":352133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1029/coverthb.jpg"},{"id":352134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1029/ofr20181029.pdf","text":"Report","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1029"},{"id":352135,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71835Q9","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for turbidity, discharge, and suspended-sediment concentrations and loads, Duwamish River, Tukwila, Washington"}],"country":"United States","state":"Washington","city":"Seattle","otherGeospatial":"Green-Duwamish River, Lower Duwanish Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.39627838134766,\n 47.458272792347074\n ],\n [\n -122.22290039062499,\n 47.458272792347074\n ],\n [\n -122.22290039062499,\n 47.59875528481801\n ],\n [\n -122.39627838134766,\n 47.59875528481801\n ],\n [\n -122.39627838134766,\n 47.458272792347074\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402

","tableOfContents":"","publishedDate":"2018-02-28","noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0f4","contributors":{"authors":[{"text":"Senter, Craig A. 0000-0002-5479-3080 csenter@usgs.gov","orcid":"https://orcid.org/0000-0002-5479-3080","contributorId":150044,"corporation":false,"usgs":true,"family":"Senter","given":"Craig","email":"csenter@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, Kathleen E. 0000-0002-2334-6536 kconn@usgs.gov","orcid":"https://orcid.org/0000-0002-2334-6536","contributorId":3923,"corporation":false,"usgs":true,"family":"Conn","given":"Kathleen E.","email":"kconn@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Black, Robert W. 0000-0002-4748-8213 rwblack@usgs.gov","orcid":"https://orcid.org/0000-0002-4748-8213","contributorId":1820,"corporation":false,"usgs":true,"family":"Black","given":"Robert","email":"rwblack@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Norman 0000-0001-6071-8741 npeterson@usgs.gov","orcid":"https://orcid.org/0000-0001-6071-8741","contributorId":177365,"corporation":false,"usgs":true,"family":"Peterson","given":"Norman","email":"npeterson@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729814,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vanderpool-Kimura, Ann M. 0000-0002-9382-2868 avander@usgs.gov","orcid":"https://orcid.org/0000-0002-9382-2868","contributorId":150042,"corporation":false,"usgs":true,"family":"Vanderpool-Kimura","given":"Ann","email":"avander@usgs.gov","middleInitial":"M.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":729815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foreman, James R. 0000-0003-0535-4580 jforeman@usgs.gov","orcid":"https://orcid.org/0000-0003-0535-4580","contributorId":139319,"corporation":false,"usgs":true,"family":"Foreman","given":"James","email":"jforeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":729816,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195753,"text":"70195753 - 2018 - The geochemistry of loess: Asian and North American deposits compared","interactions":[],"lastModifiedDate":"2018-02-28T11:10:32","indexId":"70195753","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2184,"text":"Journal of Asian Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The geochemistry of loess: Asian and North American deposits compared","docAbstract":"

Loess is widely distributed over Asia and North America and constitutes one of the most important surficial deposits that serve as terrestrial records of the Quaternary. The oldest Pleistocene loess in China is likely ∼2.6 Ma, thus spanning much or all of the Pleistocene. In North America, most loess is no older than the penultimate glacial period, with the exception of Alaska, where the record may go back to ∼3.0 Ma. On both continents, loess deposits date primarily to glacial periods, and interglacial or interstadial periods are represented by paleosols. Both glacial and non-glacial sources of silts that comprise the bulk of loess deposits are found on both continents. Although loess has been considered to be representative of the average upper continental crust, there are regionally distinctive compositions of loess in both Asia and North America. Loess deposits in Asia from Yakutia, Tajikistan, and China have compositionally distinct major element compositions, due to varying abundances of silicate minerals, carbonate minerals, and clay minerals. In North America, loess in the Mississippi River valley, the Great Plains, and Alaska are also distinguishable with regard to major element composition that reflects highly diverse source sediments. Trace element geochemistry (Sc-Th-Zr and the rare earth elements) also shows regional diversity of loess bodies, in both Asia and North America. On both continents, most loess bodies show significant contributions from later-cycle, altered sedimentary rocks, as opposed to direct derivation from igneous rocks. Further, some loess bodies have detectable contributions from mafic igneous rocks as well as major contributions from average, upper-crustal, felsic rocks. Intercalated paleosols in loess sections show geochemical compositions that differ significantly from the underlying loess parent materials. Ratios of soluble-to-insoluble elements show depletions in paleosols due to chemical weathering losses of calcite, dolomite, plagioclase, mica, apatite, and smectite. In Asia and North America, the last interglacial paleosol is more weathered than equivalent modern soils, which could be due either to a climate that was warmer and more humid, a longer period of pedogenesis, or both. In Asia, early Pleistocene loess and paleosols are both more weathered than those from the middle and late Pleistocene, forming prior to a mid-Pleistocene aridification of Asia from uplift of the Tibetan Plateau. Understanding the geochemistry of loess and paleosols can tell us much about past atmospheric circulation, past temperature and moisture regimes, and even tectonic processes.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jseaes.2017.10.032","usgsCitation":"Muhs, D.R., 2018, The geochemistry of loess: Asian and North American deposits compared: Journal of Asian Earth Sciences, v. 155, p. 81-115, https://doi.org/10.1016/j.jseaes.2017.10.032.","productDescription":"35 p.","startPage":"81","endPage":"115","ipdsId":"IP-091000","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":461011,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jseaes.2017.10.032","text":"Publisher Index Page"},{"id":352125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"155","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0ec","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":140288,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel","email":"dmuhs@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":729791,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70194704,"text":"sir20175156 - 2018 - Flood-inundation maps for Cedar Creek at 18th Street at Auburn, Indiana","interactions":[],"lastModifiedDate":"2018-02-27T16:36:54","indexId":"sir20175156","displayToPublicDate":"2018-02-27T12:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5156","title":"Flood-inundation maps for Cedar Creek at 18th Street at Auburn, Indiana","docAbstract":"

Digital flood-inundation maps for a 1.9-mile reach of Cedar Creek at Auburn, Indiana (Ind.), from the First Street bridge, downstream to the streamgage at 18th Street, then ending approximately 1,100 feet (ft) downstream of the Baltimore and Ohio railroad, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science web site at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on Cedar Creek at 18th Street at Auburn, Ind. (station number 04179520). Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps/, although forecasts of flood hydrographs are not available at this site (ABBI3).

Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relation at the Cedar Creek at 18th Street at Auburn, Ind. streamgage and the documented high-water marks from the flood of March 11, 2009. The calibrated hydraulic model was then used to compute seven water-surface profiles for flood stages referenced to the streamgage datum and ranging from 7 ft, or near bankfull, to 13 ft, in 1-foot increments. 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 0.98-ft vertical accuracy and 4.9-ft horizontal resolution) to delineate the area flooded at each water level.

The availability of these maps, along with internet information regarding current stage from the USGS streamgage at Cedar Creek at 18th Street at Auburn, Ind., and stream information from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for postflood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175156","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Fowler, K.K., 2018, Flood-inundation maps for Cedar Creek at 18th Street at Auburn, Indiana: U.S. Geological Survey Scientific Investigations Report 2017–5156, 10 p., https://doi.org/10.3133/sir20175156.","productDescription":"Report: iv, 10 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087585","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":349964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5156/coverthb.jpg"},{"id":351891,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5156/sir20175156.pdf","text":"Report","size":"6.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5156"},{"id":351892,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72806GR","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial Datasets and Surface-Water Hydraulic Model for Cedar Creek at Auburn, Indiana, Flood-inundation Study "}],"country":"United States","state":"Indiana","city":"Auburn","otherGeospatial":"Cedar Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.0667,\n 41.34582213380196\n ],\n [\n -85.0417,\n 41.34582213380196\n ],\n [\n -85.0417,\n 41.37057703323999\n ],\n [\n -85.0667,\n 41.37057703323999\n ],\n [\n -85.0667,\n 41.34582213380196\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278-1996

","tableOfContents":"","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2018-02-27","noUsgsAuthors":false,"publicationDate":"2018-02-27","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0f8","contributors":{"authors":[{"text":"Fowler, Kathleen K. 0000-0002-0107-3848 kkfowler@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3848","contributorId":2439,"corporation":false,"usgs":true,"family":"Fowler","given":"Kathleen","email":"kkfowler@usgs.gov","middleInitial":"K.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":724947,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70195669,"text":"70195669 - 2018 - An analytical framework for estimating aquatic species density from environmental DNA","interactions":[],"lastModifiedDate":"2018-04-02T13:45:27","indexId":"70195669","displayToPublicDate":"2018-02-27T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"An analytical framework for estimating aquatic species density from environmental DNA","docAbstract":"

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3764","usgsCitation":"Chambert, T., Pilliod, D.S., Goldberg, C.S., Doi, H., and Takahara, T., 2018, An analytical framework for estimating aquatic species density from environmental DNA: Ecology and Evolution, v. 8, no. 6, p. 3468-3477, https://doi.org/10.1002/ece3.3764.","productDescription":"10 p.","startPage":"3468","endPage":"3477","ipdsId":"IP-079053","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468971,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3764","text":"Publisher Index Page"},{"id":352059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-25","publicationStatus":"PW","scienceBaseUri":"5afee716e4b0da30c1bfc106","contributors":{"authors":[{"text":"Chambert, Thierry 0000-0002-9450-9080 tchambert@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-9080","contributorId":191979,"corporation":false,"usgs":false,"family":"Chambert","given":"Thierry","email":"tchambert@usgs.gov","affiliations":[],"preferred":false,"id":729620,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":149254,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","email":"dpilliod@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":729619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldberg, Caren S.","contributorId":76879,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","email":"","middleInitial":"S.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":729621,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doi, Hideyuki","contributorId":202789,"corporation":false,"usgs":false,"family":"Doi","given":"Hideyuki","email":"","affiliations":[{"id":36527,"text":"University of Hyogo","active":true,"usgs":false}],"preferred":false,"id":729622,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Takahara, Teruhiko","contributorId":176873,"corporation":false,"usgs":false,"family":"Takahara","given":"Teruhiko","email":"","affiliations":[],"preferred":false,"id":729623,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195710,"text":"ofr20181028 - 2018 - Effects of the proposed California WaterFix North Delta Diversion on flow reversals and entrainment of juvenile Chinook salmon (Oncorhynchus tshawytscha) into Georgiana Slough and the Delta Cross Channel, northern California","interactions":[],"lastModifiedDate":"2018-02-28T10:43:13","indexId":"ofr20181028","displayToPublicDate":"2018-02-27T00:00:00","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":"2018-1028","displayTitle":"Effects of the proposed California WaterFix North Delta Diversion on flow reversals and entrainment of juvenile Chinook salmon (Oncorhynchus tshawytscha) into Georgiana Slough and the Delta Cross Channel, northern California","title":"Effects of the proposed California WaterFix North Delta Diversion on flow reversals and entrainment of juvenile Chinook salmon (Oncorhynchus tshawytscha) into Georgiana Slough and the Delta Cross Channel, northern California","docAbstract":"

The California Department of Water Resources and Bureau of Reclamation propose new water intake facilities on the Sacramento River in northern California that would convey some of the water for export to areas south of the Sacramento-San Joaquin River Delta (hereinafter referred to as the Delta) through tunnels rather than through the Delta. The collection of water intakes, tunnels, pumping facilities, associated structures, and proposed operations are collectively referred to as California WaterFix. The water intake facilities, hereinafter referred to as the North Delta Diversion (NDD), are proposed to be located on the Sacramento River downstream of the city of Sacramento and upstream of the first major river junction where Sutter Slough branches from the Sacramento River. The NDD can divert a maximum discharge of 9,000 cubic feet per second (ft3/s) from the Sacramento River, which reduces the amount of Sacramento River inflow into the Delta.

In this report, we conducted three analyses to investigate the effect of the NDD and its proposed operation on entrainment of juvenile Chinook salmon (Oncorhynchus tshawytscha) into Georgiana Slough and the Delta Cross Channel (DCC). Fish that enter the interior Delta (the network of channels to the south of the Sacramento River) through Georgiana Slough and the DCC survive at lower rates than fish that use other migration routes (Sacramento River, Sutter Slough, and Steamboat Slough). Therefore, fisheries managers were concerned about the extent to which operation of the NDD would increase the proportion of the population entering the interior Delta, which, all else being equal, would lower overall survival through the Delta by increasing the fraction of the population subject to lower survival rates. Operation of the NDD would reduce flow in the Sacramento River, which has the potential to increase the magnitude and duration of reverse flows of the Sacramento River downstream of Georgiana Slough.

In the first analysis, we evaluate the effect of the NDD bypass rules on flow reversals of the Sacramento River downstream of Georgiana Slough. The NDD bypass rules are a set of operational criteria designed to minimize upstream transport of fish into Georgiana Slough and the DCC, and were developed based on previous studies showing that the magnitude and duration of flow reversals increase the proportion of fish entering Georgiana Slough and the DCC. We estimated the frequency and duration of reverse-flow conditions of the Sacramento River downstream of Georgiana Slough under each of the prescribed minimum bypass flows described in the NDD bypass rules. To accommodate adaptive levels of protection during different times of year when juvenile salmon are migrating through the Delta, the NDD bypass rules prescribe a series of minimum allowable bypass flows that vary depending on (1) month of the year, and (2) progressively decreasing levels of protection following a pulse flow event.

We determined that the NDD bypass rules increased the frequency and duration of reverse flows of the Sacramento River downstream of Georgiana Slough, with the magnitude of increase varying among scenarios. Constant low-level pumping, the most protective bypass rule that limits diversion to 10 percent of the maximum diversion and is implemented following a pulse-flow event, led to the smallest increase in frequency and duration of flow reversals. In contrast, we found that some scenarios led to sizeable increases in the fraction of the day with reverse flow. The conditions under which the proportion of the day with reverse flow can increase by greater than or equal to 10 percentage points between October and June, when juvenile salmon are present in the Delta, include October–November bypass rules and level-3 post-pulse operations during December–June. These conditions would be expected to increase the proportion of juvenile salmon entering the interior Delta through Georgiana Slough.

In the second analysis, we assessed bias in Delta Simulation Model 2 (DSM2) flow predictions at the junction of the Sacramento River, DCC, and Georgiana Slough. Because DSM2 was being used to simulate California WaterFix operations, understanding the extent of bias relative to USGS streamgages was important since fish routing models were based on flow data at streamgages. We determined that river flow predicted by DSM2 was biased for Georgiana Slough and the Sacramento River. Therefore, for subsequent analysis, we bias-corrected the DSM2 flow predictions using measured stream flows as predictor variables.

In the third analysis, we evaluated the effect of the NDD on the daily probability of fish entering Georgiana Slough and the DCC. We applied an existing model to predict entrainment from 15-minute flow simulations for an 82-year time series of flows simulated by DSM2 under the Proposed Action (PA), where the North Delta Diversion is implemented under California WaterFix, and the No Action Alternative (NAA), where the diversion is not implemented. To estimate the daily fraction of fish entering each river channel, entrainment probabilities were averaged over each day. To evaluate the two scenarios, we then compared mean annual entrainment probabilities by month, water year classification, and three different assumed run timings. Overall, the probability of remaining in the Sacramento River was lower under the PA scenario, but the magnitude of the difference was small (3/s. At flows greater than 41,000 ft3/s, we hypothesize that entrainment into the interior Delta is relatively constant, which would have caused little difference between scenarios at higher flows.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181028","collaboration":"Prepared in cooperation with National Atmospheric and Oceanic Administration, National Marine Fisheries Service","usgsCitation":"Perry, R.W., Romine, J.G., Pope, A.C., and Evans, S.D., 2018, Effects of the proposed California WaterFix North\nDelta Diversion on flow reversals and entrainment of juvenile Chinook salmon (Oncorhynchus tshawytscha) into\nGeorgiana Slough and the Delta Cross Channel, northern California: U.S. Geological Survey Open File Report\n2018-1028, 46 p., https://doi.org/10.3133/ofr20181028.","productDescription":"vi, 46 p.","onlineOnly":"Y","ipdsId":"IP-077416","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":352094,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1028/ofr20181028.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1028"},{"id":352093,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1028/coverthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.53127670288086,\n 38.22449353550286\n ],\n [\n -121.49771690368652,\n 38.22449353550286\n ],\n [\n -121.49771690368652,\n 38.26466948704442\n ],\n [\n -121.53127670288086,\n 38.26466948704442\n ],\n [\n -121.53127670288086,\n 38.22449353550286\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115

","tableOfContents":"","publishedDate":"2018-02-27","noUsgsAuthors":false,"publicationDate":"2018-02-27","publicationStatus":"PW","scienceBaseUri":"5afee715e4b0da30c1bfc0fc","contributors":{"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":729763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":729764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Adam C. 0000-0002-7253-2247 apope@usgs.gov","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":5664,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","email":"apope@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":729765,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, Scott D. 0000-0003-0452-7726 sdevans@usgs.gov","orcid":"https://orcid.org/0000-0003-0452-7726","contributorId":4408,"corporation":false,"usgs":true,"family":"Evans","given":"Scott","email":"sdevans@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":729766,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195674,"text":"70195674 - 2018 - Surrounding land cover types as predictors of palustrine wetland vegetation quality in conterminous USA","interactions":[],"lastModifiedDate":"2018-02-27T09:51:12","indexId":"70195674","displayToPublicDate":"2018-02-27T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Surrounding land cover types as predictors of palustrine wetland vegetation quality in conterminous USA","docAbstract":"

The loss of wetland habitats and their often-unique biological communities is a major environmental concern. We examined vegetation data obtained from 380 wetlands sampled in a statistical survey of wetlands in the USA. Our goal was to identify which surrounding land cover types best predict two indices of vegetation quality in wetlands at the regional scale. We considered palustrine wetlands in four regions (Coastal Plains, North Central East, Interior Plains, and West) in which the dominant vegetation was emergent, forested, or scrub-shrub. For each wetland, we calculated weighted proportions of eight land cover types surrounding the area in which vegetation was assessed, in four zones radiating from the edge of the assessment area to 2 km. Using Akaike's Information Criterion, we determined the best 1-, 2- and 3-predictor models of the two indices, using the weighted proportions of the land cover types as potential predictors. Mean values of the two indices were generally higher in the North Central East and Coastal Plains than the other regions for forested and emergent wetlands. In nearly all cases, the best predictors of the indices were not the dominant surrounding land cover types. Overall, proportions of forest (positive effect) and agriculture (negative effect) surrounding the assessment area were the best predictors of the two indices. One or both of these variables were included as predictors in 65 of the 72 models supported by the data. Wetlands surrounding the assessment area had a positive effect on the indices, and ranked third (33%) among the predictors included in supported models. Development had a negative effect on the indices and was included in only 28% of supported models. These results can be used to develop regional management plans for wetlands, such as creating forest buffers around wetlands, or to conserve zones between wetlands to increase habitat connectivity.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.11.107","usgsCitation":"Stapanian, M.A., Gara, B., and Schumacher, W., 2018, Surrounding land cover types as predictors of palustrine wetland vegetation quality in conterminous USA: Science of the Total Environment, v. 619-620, p. 366-375, https://doi.org/10.1016/j.scitotenv.2017.11.107.","productDescription":"10 p.","startPage":"366","endPage":"375","ipdsId":"IP-088234","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":352053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}\n\n\n","volume":"619-620","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee715e4b0da30c1bfc102","contributors":{"authors":[{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":729637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gara, Brian","contributorId":52061,"corporation":false,"usgs":true,"family":"Gara","given":"Brian","affiliations":[],"preferred":false,"id":729638,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schumacher, William","contributorId":150060,"corporation":false,"usgs":false,"family":"Schumacher","given":"William","email":"","affiliations":[{"id":17898,"text":"Ohio Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":729639,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195621,"text":"70195621 - 2018 - Rayleigh and S wave tomography constraints on subduction termination and lithospheric foundering in central California","interactions":[],"lastModifiedDate":"2018-02-26T12:31:26","indexId":"70195621","displayToPublicDate":"2018-02-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Rayleigh and S wave tomography constraints on subduction termination and lithospheric foundering in central California","docAbstract":"

The crust and upper mantle structure of central California have been modified by subduction termination, growth of the San Andreas plate boundary fault system, and small-scale upper mantle convection since the early Miocene. Here we investigate the contributions of these processes to the creation of the Isabella Anomaly, which is a high seismic velocity volume in the upper mantle. There are two types of hypotheses for its origin. One is that it is the foundered mafic lower crust and mantle lithosphere of the southern Sierra Nevada batholith. The alternative suggests that it is a fossil slab connected to the Monterey microplate. A dense broadband seismic transect was deployed from the coast to the western Sierra Nevada to fill in the least sampled areas above the Isabella Anomaly, and regional-scale Rayleigh and S wave tomography are used to evaluate the two hypotheses. New shear velocity (Vs) tomography images a high-velocity anomaly beneath coastal California that is sub-horizontal at depths of ∼40–80 km. East of the San Andreas Fault a continuous extension of the high-velocity anomaly dips east and is located beneath the Sierra Nevada at ∼150–200 km depth. The western position of the Isabella Anomaly in the uppermost mantle is inconsistent with earlier interpretations that the Isabella Anomaly is connected to actively foundering foothills lower crust. Based on the new Vs images, we interpret that the Isabella Anomaly is not the dense destabilized root of the Sierra Nevada, but rather a remnant of Miocene subduction termination that is translating north beneath the central San Andreas Fault. Our results support the occurrence of localized lithospheric foundering beneath the high elevation eastern Sierra Nevada, where we find a lower crustal low Vs layer consistent with a small amount of partial melt. The high elevations relative to crust thickness and lower crustal low Vs zone are consistent with geological inferences that lithospheric foundering drove uplift and a ∼3–4 Ma pulse of basaltic magmatism.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2018.02.009","usgsCitation":"Jiang, C., Schmandt, B., Hansen, S.M., Dougherty, S.L., Clayton, R.W., Farrell, J., and Lin, F., 2018, Rayleigh and S wave tomography constraints on subduction termination and lithospheric foundering in central California: Earth and Planetary Science Letters, v. 488, p. 14-26, https://doi.org/10.1016/j.epsl.2018.02.009.","productDescription":"13 p.","startPage":"14","endPage":"26","ipdsId":"IP-090395","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468974,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.caltech.edu/CaltechAUTHORS:20180221-090936349","text":"External Repository"},{"id":352018,"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 -124,\n 32\n ],\n [\n -114,\n 32\n ],\n [\n -114,\n 39\n ],\n [\n -124,\n 39\n ],\n [\n -124,\n 32\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"488","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee717e4b0da30c1bfc112","contributors":{"authors":[{"text":"Jiang, Chengxin","contributorId":202749,"corporation":false,"usgs":false,"family":"Jiang","given":"Chengxin","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":729435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmandt, Brandon","contributorId":202750,"corporation":false,"usgs":false,"family":"Schmandt","given":"Brandon","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":729436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Steven M.","contributorId":202751,"corporation":false,"usgs":false,"family":"Hansen","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":729437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dougherty, Sara L. 0000-0002-5327-3286 sdougherty@usgs.gov","orcid":"https://orcid.org/0000-0002-5327-3286","contributorId":191210,"corporation":false,"usgs":true,"family":"Dougherty","given":"Sara","email":"sdougherty@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":729434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clayton, Robert W.","contributorId":202752,"corporation":false,"usgs":false,"family":"Clayton","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":729438,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Farrell, Jamie","contributorId":175477,"corporation":false,"usgs":false,"family":"Farrell","given":"Jamie","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":729439,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lin, Fan-Chi","contributorId":175478,"corporation":false,"usgs":false,"family":"Lin","given":"Fan-Chi","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":729440,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70122872,"text":"sir20145168 - 2018 - Spatially distributed groundwater recharge estimated using a water-budget model for the Island of Maui, Hawai`i, 1978–2007","interactions":[],"lastModifiedDate":"2019-10-04T07:23:44","indexId":"sir20145168","displayToPublicDate":"2018-02-26T00:00:00","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":"2014-5168","title":"Spatially distributed groundwater recharge estimated using a water-budget model for the Island of Maui, Hawai`i, 1978–2007","docAbstract":"

Demand for freshwater on the Island of Maui is expected to grow. To evaluate the availability of fresh groundwater, estimates of groundwater recharge are needed. A water-budget model with a daily computation interval was developed and used to estimate the spatial distribution of recharge on Maui for average climate conditions (1978–2007 rainfall and 2010 land cover) and for drought conditions (1998–2002 rainfall and 2010 land cover). For average climate conditions, mean annual recharge for Maui is about 1,309 million gallons per day, or about 44 percent of precipitation (rainfall and fog interception). Recharge for average climate conditions is about 39 percent of total water inflow consisting of precipitation, irrigation, septic leachate, and seepage from reservoirs and cesspools. Most recharge occurs on the wet, windward slopes of Haleakalā and on the wet, uplands of West Maui Mountain. Dry, coastal areas generally have low recharge. In the dry isthmus, however, irrigated fields have greater recharge than nearby unirrigated areas. For drought conditions, mean annual recharge for Maui is about 1,010 million gallons per day, which is 23 percent less than recharge for average climate conditions. For individual aquifer-system areas used for groundwater management, recharge for drought conditions is about 8 to 51 percent less than recharge for average climate conditions. The spatial distribution of rainfall is the primary factor determining spatially distributed recharge estimates for most areas on Maui. In wet areas, recharge estimates are also sensitive to water-budget parameters that are related to runoff, fog interception, and forest-canopy evaporation. In dry areas, recharge estimates are most sensitive to irrigated crop areas and parameters related to evapotranspiration.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145168","collaboration":"Prepared in cooperation with the County of Maui Department of Water Supply and the State of Hawai‘i Commission on Water Resource Management","usgsCitation":"Johnson, A.G., Engott, J.A., Bassiouni, Maoya, and Rotzoll, Kolja, 2018, Spatially distributed groundwater recharge estimated using a water-budget model for the Island of Maui, Hawai`i, 1978–2007 (ver. 2.0, February 2018): U.S. Geological Survey Scientific Investigations Report 2014–5168, 53 p., https://doi.org/10.3133/sir20145168.","productDescription":"Report: v, 53 p.; Data Release","numberOfPages":"64","ipdsId":"IP-036379","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":351916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5168/pdf/sir20145168.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2014-5168"},{"id":351915,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2014/5168/images/coverthb.jpg"},{"id":351918,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/get/5a0f91bee4b09af898d09be6","linkHelpText":"Mean annual water-budget components for the Island of Maui, Hawaii, for average climate conditions, 1978-2007 rainfall and 2010 land cover (version 2.0)"},{"id":351917,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5168/sir20145168_versionhist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2014-5168"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.73507690429688,\n 20.56208154725951\n ],\n [\n -155.972900390625,\n 20.56208154725951\n ],\n [\n -155.972900390625,\n 21.042209507614245\n ],\n [\n -156.73507690429688,\n 21.042209507614245\n ],\n [\n -156.73507690429688,\n 20.56208154725951\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted December 14, 2014; Version 2.0: February 26, 2018","contact":"

Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2014-12-14","revisedDate":"2018-02-26","noUsgsAuthors":false,"publicationDate":"2014-12-14","publicationStatus":"PW","scienceBaseUri":"5459eaa4e4b009f8aec9701e","contributors":{"authors":[{"text":"Johnson, Adam G. 0000-0003-2448-5746 ajohnson@usgs.gov","orcid":"https://orcid.org/0000-0003-2448-5746","contributorId":4752,"corporation":false,"usgs":true,"family":"Johnson","given":"Adam","email":"ajohnson@usgs.gov","middleInitial":"G.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engott, John A. 0000-0003-1889-4519 jaengott@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-4519","contributorId":1142,"corporation":false,"usgs":true,"family":"Engott","given":"John","email":"jaengott@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729356,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bassiouni, Maoya 0000-0001-5795-9894","orcid":"https://orcid.org/0000-0001-5795-9894","contributorId":197780,"corporation":false,"usgs":true,"family":"Bassiouni","given":"Maoya","affiliations":[],"preferred":false,"id":729357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rotzoll, Kolja 0000-0002-5910-888X","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":201087,"corporation":false,"usgs":false,"family":"Rotzoll","given":"Kolja","affiliations":[],"preferred":false,"id":729358,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222584,"text":"70222584 - 2018 - Rare long-distance dispersal of the Island Night Lizard, Xantusia riversiana, maintains high diversity in a fragmented environment","interactions":[],"lastModifiedDate":"2021-08-05T21:06:33.373807","indexId":"70222584","displayToPublicDate":"2018-02-24T15:59:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Rare long-distance dispersal of the Island Night Lizard, Xantusia riversiana, maintains high diversity in a fragmented environment","title":"Rare long-distance dispersal of the Island Night Lizard, Xantusia riversiana, maintains high diversity in a fragmented environment","docAbstract":"

The Island Night Lizard (Xantusia riversiana) is endemic to three of the Channel Islands off the coast of California, USA. Introduced species such as goats, sheep, and cats have profoundly affected the fauna and flora of the islands for over 150 years, but most of these non-native species have been recently removed. We measured the distribution of genetic diversity in Island Night Lizards across San Nicolas Island using DNA microsatellites to assess the impacts of historical habitat change on effective population size, gene flow, and population divergence; to provide baseline data for future monitoring of genetic diversity; and to provide recommendations to inform the restoration of degraded habitat. Despite a history of profound anthropogenic habitat disturbance, genetic diversity was high within sites, and there was no evidence of population bottlenecks. Divergence between sites was extraordinarily high, as expected for this sedentary species. Landscape resistance modeling using circuit theory showed that unsuitable habitat is relatively permeable to gene flow compared to suitable habitat, and yet populations separated by very short geographic distances remain genetically distinct. We found no evidence of a need for short-term intervention such as artificial translocations to maintain genetic diversity. Instead, we suggest that management should focus on maintaining, improving, and increasing habitat, especially in creating patches of habitat to link existing sites.

","language":"English","publisher":"Springer","doi":"10.1007/s10592-018-1055-x","usgsCitation":"O’Donnell, R.P., Drost, C.A., Fellers, G.M., Crabb, B.A., and Mock, K., 2018, Rare long-distance dispersal of the Island Night Lizard, Xantusia riversiana, maintains high diversity in a fragmented environment: Conservation Genetics, v. 19, p. 803-814, https://doi.org/10.1007/s10592-018-1055-x.","productDescription":"12 p.","startPage":"803","endPage":"814","ipdsId":"IP-081802","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":387727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.42962646484374,\n 33.23007250637392\n ],\n [\n -119.46086883544922,\n 33.258211766248415\n ],\n [\n -119.50000762939452,\n 33.27285208252106\n ],\n [\n -119.52953338623045,\n 33.28691595686207\n ],\n [\n -119.5528793334961,\n 33.28146288679663\n ],\n [\n -119.56523895263673,\n 33.27514838003839\n ],\n [\n -119.58103179931642,\n 33.28117587367123\n ],\n [\n -119.57210540771484,\n 33.24902443255544\n ],\n [\n -119.54635620117188,\n 33.23122122490653\n ],\n [\n -119.50035095214844,\n 33.216861158847486\n ],\n [\n -119.47048187255858,\n 33.21226543987183\n ],\n [\n -119.44061279296875,\n 33.215712251730736\n ],\n [\n -119.42962646484374,\n 33.23007250637392\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2018-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"O’Donnell, Ryan P. 0000-0002-8710-7956 rodonnell@usgs.gov","orcid":"https://orcid.org/0000-0002-8710-7956","contributorId":4657,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Ryan","email":"rodonnell@usgs.gov","middleInitial":"P.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":820644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":820645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fellers, Gary M. 0000-0003-4092-0285 gary_fellers@usgs.gov","orcid":"https://orcid.org/0000-0003-4092-0285","contributorId":3150,"corporation":false,"usgs":true,"family":"Fellers","given":"Gary","email":"gary_fellers@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":820646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crabb, Benjamin A.","contributorId":261781,"corporation":false,"usgs":false,"family":"Crabb","given":"Benjamin","email":"","middleInitial":"A.","affiliations":[{"id":53015,"text":"Remote Sensing/Geographic Information Systems Laboratory, College of Natural Resources, 5275 Old Main Hill, Utah State University, Logan, UT 84322-5275","active":true,"usgs":false}],"preferred":false,"id":820647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mock, Karen E.","contributorId":261782,"corporation":false,"usgs":false,"family":"Mock","given":"Karen E.","affiliations":[{"id":53016,"text":"Wildland Resources Department, 5230 Old Main Hill, Utah State University, Logan, UT 84322-5230","active":true,"usgs":false}],"preferred":false,"id":820648,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195632,"text":"70195632 - 2018 - Waterbird habitat in California's Central Valley basins under climate, urbanization, and water management scenarios","interactions":[],"lastModifiedDate":"2018-06-04T16:12:05","indexId":"70195632","displayToPublicDate":"2018-02-24T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Waterbird habitat in California's Central Valley basins under climate, urbanization, and water management scenarios","docAbstract":"California's Central Valley provides critical, but threatened habitat and food resources for migrating and wintering waterfowl, shorebirds, and other waterbirds. The Central Valley is comprised of nine basins that were defined by the Central Valley Joint Venture (CVJV) to assist in conservation planning. Basins vary in composition and extent of habitats, which primarily include croplands and wetlands that rely on water supplies shared with other competing human and environmental uses. Changes in climate, urban development, and water supply management are uncertain and could reduce future availability of water supplies supporting waterbird habitats and limit effectiveness of wetland restoration planned by the CVJV to support wintering waterbirds. We modeled 17 plausible scenarios including combinations of three climate projections, three urbanization rates, and five water supply management options to promote agricultural and urban water uses, with and without wetland restoration. Our research examines the reduction in quantity and quality of habitats during the fall migration-wintering period by basin under each scenario, and the efficacy of planned wetland restoration to compensate reductions in flooded areas of wetland habitats. Scenario combinations of projected climate, urbanization, and water supply management options reduced availability of flooded cropland and wetland habitats during fall-winter and degraded the quality of seasonal wetlands (i.e., summer-irrigation for improved forage production), though the extent and frequency of impacts varied by basin. Planned wetland restoration may substantially compensate for scenario-related effects on wetland habitats in each basin. However, results indicate that Colusa, Butte, Sutter, San Joaquin, and Tulare Basins may require additional conservation to support summer-irrigation of seasonal wetlands and winter-flooding of cropland habitats. Still further conservation may be required to provide sufficient areas of flooded seasonal and semi-permanent wetlands in San Joaquin and Tulare Basins during fall-winter. The main objective of this research is to provide decision-support for achieving waterbird conservation goals in the valley and to inform CVJV's regional conservation planning.","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/122016-JFWM-095","usgsCitation":"Matchett, E., and Fleskes, J.P., 2018, Waterbird habitat in California's Central Valley basins under climate, urbanization, and water management scenarios: Journal of Fish and Wildlife Management, v. 9, no. 1, p. 75-94, https://doi.org/10.3996/122016-JFWM-095.","productDescription":"20 p.","startPage":"75","endPage":"94","ipdsId":"IP-080053","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468975,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/122016-jfwm-095","text":"Publisher Index Page"},{"id":438003,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NV9GDQ","text":"USGS data release","linkHelpText":"Recent historical and projected (years 2006-99) areas (km2) of managed, flooded habitats used by waterbirds overwintering in Central Valley, California basins for 17 climate, urbanization, and water management scenarios"},{"id":351987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","volume":"9","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-17","publicationStatus":"PW","scienceBaseUri":"5afee718e4b0da30c1bfc11c","contributors":{"authors":[{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":729491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":177154,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":729490,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195636,"text":"70195636 - 2018 - Enhanced invertebrate prey production following estuarine restoration supports foraging for multiple species of juvenile salmonids (Oncorhynchus spp.)","interactions":[],"lastModifiedDate":"2021-08-12T16:45:02.037993","indexId":"70195636","displayToPublicDate":"2018-02-24T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Enhanced invertebrate prey production following estuarine restoration supports foraging for multiple species of juvenile salmonids (Oncorhynchus spp.)","title":"Enhanced invertebrate prey production following estuarine restoration supports foraging for multiple species of juvenile salmonids (Oncorhynchus spp.)","docAbstract":"

Estuaries provide crucial foraging resources and nursery habitat for threatened populations of anadromous salmon. As such, there has been a global undertaking to restore habitat and tidal processes in modified estuaries. The foraging capacity of these ecosystems to support various species of out-migrating juvenile salmon can be quantified by monitoring benthic, terrestrial, and pelagic invertebrate prey communities. Here, we present notable trends in the availability of invertebrate prey at several sites within a restoring large river delta in Puget Sound, Washington, U.S.A. Three years after the system was returned to tidal influence, we observed substantial additions to amphipod, copepod, and cumacean abundances in newly accessible marsh channels (from 0 to roughly 5,000–75,000 individuals/m2). In the restoration area, terrestrial invertebrate colonization was dependent upon vegetative cover, with dipteran and hymenopteran biomass increasing 3-fold between 1 and 3 years post-restoration. While the overall biodiversity within the restoration area was lower than in the reference marsh, estimated biomass was comparable to or greater than that found within the other study sites. This additional prey biomass likely provided foraging benefits for juvenile Chinook, chum, and coho salmon. Primary physical drivers differed for benthic, terrestrial, and pelagic invertebrates, and these invertebrate communities are expected to respond differentially depending on organic matter exchange and vegetative colonization. Restoring estuaries may take decades to meet certain success criteria, but our study demonstrates rapid enhancements in foraging resources understood to be used for estuary-dependent wildlife.

","language":"English","publisher":"Wiley","doi":"10.1111/rec.12658","usgsCitation":"Woo, I., Davis, M.J., Ellings, C.S., Nakai, G., Takekawa, J.Y., and De La Cruz, S.E., 2018, Enhanced invertebrate prey production following estuarine restoration supports foraging for multiple species of juvenile salmonids (Oncorhynchus spp.): Restoration Ecology, v. 26, no. 5, p. 964-975, https://doi.org/10.1111/rec.12658.","productDescription":"12 p.","startPage":"964","endPage":"975","ipdsId":"IP-083281","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":351982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.72552490234375,\n 47.05562189093551\n ],\n [\n -122.65068054199219,\n 47.05562189093551\n ],\n [\n -122.65068054199219,\n 47.1248118482342\n ],\n [\n -122.72552490234375,\n 47.1248118482342\n ],\n [\n -122.72552490234375,\n 47.05562189093551\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-25","publicationStatus":"PW","scienceBaseUri":"5afee717e4b0da30c1bfc116","contributors":{"authors":[{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":729513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":729517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellings, Christopher S.","contributorId":149343,"corporation":false,"usgs":false,"family":"Ellings","given":"Christopher","email":"","middleInitial":"S.","affiliations":[{"id":17711,"text":"Dep't Natural Resources, Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":729514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nakai, Glynnis","contributorId":172123,"corporation":false,"usgs":false,"family":"Nakai","given":"Glynnis","email":"","affiliations":[{"id":26986,"text":"US Fish and Wildlife Service, Nisqually Nat'l Wildlife Refuge, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":729515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":196611,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":729516,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":729512,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70212485,"text":"70212485 - 2018 - Report of the IAU Working Group on Cartographic Coordinates and Rotational Elements: 2015","interactions":[],"lastModifiedDate":"2020-08-17T15:20:09.571703","indexId":"70212485","displayToPublicDate":"2018-02-23T10:03:07","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1201,"text":"Celestial Mechanics and Dynamical Astronomy","active":true,"publicationSubtype":{"id":10}},"title":"Report of the IAU Working Group on Cartographic Coordinates and Rotational Elements: 2015","docAbstract":"This report continues the practice where the IAU Working Group on Cartographic Coordinates and Rotational Elements revises recommendations regarding those topics for the planets, satellites, minor planets, and comets approximately every three years. The Working Group has now become a “functional working group” of the IAU and its membership is open to anyone interested in participating. We describe the procedure for submitting questions about the recommendations given here or the application of these recommendations for creating a new or updated coordinate system for a given body. Regarding body orientation, the following bodies have been updated: Mercury, based on MESSENGER results; Mars, along with a refined longitude definition; Phobos; Deimos; (1) Ceres; (52) Europa; (243) Ida; (2867) Šteins; Neptune; (134340) Pluto and its satellite Charon; comets 9P/Tempel 1, 19P/Borrelly, 67P/Churyumov-Gerasimenko, and 103P/Hartley 2, noting that such information is valid only between specific epochs. The special challenges related to mapping 67P/Churyumov-Gerasimenko are also discussed. Approximate expressions for the Earth have been removed in order to avoid confusion, and the low precision series expression for the Moon’s orientation has been removed. The previously on-line only recommended orientation model for (4) Vesta is repeated with an explanation of how it was updated. Regarding body shape, text has been included to explain the expected uses of such information, and the relevance of the cited uncertainty information. The size of the Sun has been updated and notation added that the size and the ellipsoidal axes for the Earth and Jupiter have been recommended by an IAU Resolution. The distinction of a reference radius for a body (here, the Moon and Titan) is made between cartographic uses, and for orthoprojection and geophysical uses. The recommended radius for Mercury has been updated based on MESSENGER results. The recommended radius for Titan is returned to its previous value. Size information has been updated for 13 other Saturnian satellites and added for Aegaeon. The sizes of Pluto and Charon have been updated. Size information has been updated for (1) Ceres and given for (16) Psyche and (52) Europa. The size of (25143) Itokawa has been corrected. In addition, the discussion of terminology for the poles (hemispheres) of small bodies has been modified and a discussion on cardinal directions added. Although they continue to be used for planets and their satellites, it is assumed that the planetographic and planetocentric coordinate system definitions do not apply to small bodies. However, planetocentric and planetodetic latitudes and longitudes may be used on such bodies, following the right-hand rule. We repeat our previous recommendations that planning and efforts be made to make controlled cartographic products; newly recommend that common formulations should be used for orientation and size; continue to recommend that a community consensus be developed for the orientation models of Jupiter and Saturn; newly recommend that historical summaries of the coordinate systems for given bodies should be developed, and point out that for planets and satellites planetographic systems have generally been historically preferred over planetocentric systems, and that in cases when planetographic coordinates have been widely used in the past, there is no obvious advantage to switching to the use of planetocentric coordinates. The Working Group also requests community input on the question submitting process, posting of updates to the Working Group website, and on whether recommendations should be made regarding exoplanet coordinate systems.","language":"English","publisher":"Springer","doi":"10.1007/s10569-017-9805-5","usgsCitation":"Archinal, B., Acton, C.H., A’Hearn, M., Conrad, A., Consolmagno, G.J., Duxbury, T., D. Hestroffer, Hilton, J., Kirk, R.L., Klioner, S., McCarthy, D., Meech, K., Oberst, J., Ping, J., Seidelmann, P.K., Tholen, D.J., Thomas, P.C., and Williams, I.P., 2018, Report of the IAU Working Group on Cartographic Coordinates and Rotational Elements: 2015: Celestial Mechanics and Dynamical Astronomy, v. 130, 22, 46 p., https://doi.org/10.1007/s10569-017-9805-5.","productDescription":"22, 46 p.","ipdsId":"IP-090015","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":377575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","noUsgsAuthors":false,"publicationDate":"2018-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Archinal, Brent A. 0000-0002-6654-0742","orcid":"https://orcid.org/0000-0002-6654-0742","contributorId":206341,"corporation":false,"usgs":true,"family":"Archinal","given":"Brent A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":796499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acton, C. H.","contributorId":238761,"corporation":false,"usgs":false,"family":"Acton","given":"C.","email":"","middleInitial":"H.","affiliations":[{"id":47757,"text":"Jet Propulsion Laboratory, Pasadena, CA, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":796500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"A’Hearn, M. F.","contributorId":238762,"corporation":false,"usgs":false,"family":"A’Hearn","given":"M. F.","affiliations":[{"id":47758,"text":"University of Maryland, College Park, MD, U.S.A (deceased)","active":true,"usgs":false}],"preferred":false,"id":796501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrad, A.","contributorId":238763,"corporation":false,"usgs":false,"family":"Conrad","given":"A.","affiliations":[{"id":47759,"text":"Large Binocular Telescope Observatory, University of Arizona, Tucson, AZ, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":796502,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Consolmagno, G. 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L.","contributorId":238767,"corporation":false,"usgs":false,"family":"Hilton","given":"J. L.","affiliations":[{"id":47763,"text":"U.S. Naval Observatory, Washington D.C., U.S.A.","active":true,"usgs":false}],"preferred":false,"id":796506,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":796508,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Klioner, S. A.","contributorId":238769,"corporation":false,"usgs":false,"family":"Klioner","given":"S. A.","affiliations":[{"id":47765,"text":"Technische Universität Dresden, Lohrmann Observatory, Dresden, Germany","active":true,"usgs":false}],"preferred":false,"id":796507,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McCarthy, D.","contributorId":238770,"corporation":false,"usgs":false,"family":"McCarthy","given":"D.","email":"","affiliations":[{"id":47766,"text":"U.S. Naval Observatory (retired), Washington, DC, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":796510,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Meech, K.","contributorId":238771,"corporation":false,"usgs":false,"family":"Meech","given":"K.","affiliations":[{"id":47766,"text":"U.S. Naval Observatory (retired), Washington, DC, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":796511,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Oberst, J.","contributorId":238772,"corporation":false,"usgs":false,"family":"Oberst","given":"J.","affiliations":[{"id":47767,"text":"DLR Berlin Adlershof, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":796512,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ping, J.","contributorId":238773,"corporation":false,"usgs":false,"family":"Ping","given":"J.","email":"","affiliations":[{"id":47768,"text":"Shanghai Astronomical Observatory, Shanghai, China","active":true,"usgs":false}],"preferred":false,"id":796513,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Seidelmann, P. K.","contributorId":238774,"corporation":false,"usgs":false,"family":"Seidelmann","given":"P.","email":"","middleInitial":"K.","affiliations":[{"id":47769,"text":"University of Virginia, Charlottesville, VA, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":796514,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tholen, D. J.","contributorId":238775,"corporation":false,"usgs":false,"family":"Tholen","given":"D.","email":"","middleInitial":"J.","affiliations":[{"id":47770,"text":"University of Hawaii, Honolulu, HI, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":796515,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Thomas, P. C.","contributorId":238776,"corporation":false,"usgs":false,"family":"Thomas","given":"P.","email":"","middleInitial":"C.","affiliations":[{"id":47771,"text":"Cornell University, Ithaca, NY, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":796516,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Williams, I. P.","contributorId":238777,"corporation":false,"usgs":false,"family":"Williams","given":"I.","email":"","middleInitial":"P.","affiliations":[{"id":47772,"text":"Queen Mary, University of London, London, U.K.","active":true,"usgs":false}],"preferred":false,"id":796517,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70195576,"text":"70195576 - 2018 - Temporal stress changes caused by earthquakes: A review","interactions":[],"lastModifiedDate":"2018-03-26T14:17:45","indexId":"70195576","displayToPublicDate":"2018-02-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Temporal stress changes caused by earthquakes: A review","docAbstract":"Earthquakes can change the stress field in the Earth’s lithosphere as they relieve and redistribute stress. Earthquake-induced stress changes have been observed as temporal rotations of the principal stress axes following major earthquakes in a variety of tectonic settings. The stress changes due to the 2011 Mw9.0 Tohoku-Oki, Japan, earthquake were particularly well documented. Earthquake stress rotations can inform our understanding of earthquake physics, most notably addressing the long-standing problem of whether the Earth’s crust at plate boundaries is “strong” or “weak.” Many of the observed stress rotations, including that due to the Tohoku-Oki earthquake, indicate near-complete stress drop in the mainshock. This implies low background differential stress, on the order of earthquake stress drop, supporting the weak crust model. Earthquake stress rotations can also be used to address other important geophysical questions, such as the level of crustal stress heterogeneity and the mechanisms of postseismic stress reloading. The quantitative interpretation of stress rotations is evolving from those based on simple analytical methods to those based on more sophisticated numerical modeling that can capture the spatial-temporal complexity of the earthquake stress changes.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014617","usgsCitation":"Hardebeck, J.L., and Okada, T., 2018, Temporal stress changes caused by earthquakes: A review: Journal of Geophysical Research B: Solid Earth, v. 123, no. 2, p. 1350-1365, https://doi.org/10.1002/2017JB014617.","productDescription":"16 p.","startPage":"1350","endPage":"1365","ipdsId":"IP-088291","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":351902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","volume":"123","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-22","publicationStatus":"PW","scienceBaseUri":"5afee719e4b0da30c1bfc120","contributors":{"authors":[{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780 jhardebeck@usgs.gov","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":841,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"jhardebeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":729341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Okada, Tomomi","contributorId":202692,"corporation":false,"usgs":false,"family":"Okada","given":"Tomomi","email":"","affiliations":[{"id":36517,"text":"Tohoku University","active":true,"usgs":false}],"preferred":false,"id":729342,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187785,"text":"sir20175051 - 2018 - Status and understanding of groundwater quality in the North San Francisco Bay Shallow Aquifer study unit, 2012; California GAMA Priority Basin Project (ver. 1.1, February 2018)","interactions":[],"lastModifiedDate":"2018-02-26T10:42:16","indexId":"sir20175051","displayToPublicDate":"2018-02-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5051","title":"Status and understanding of groundwater quality in the North San Francisco Bay Shallow Aquifer study unit, 2012; California GAMA Priority Basin Project (ver. 1.1, February 2018)","docAbstract":"

Groundwater quality in the North San Francisco Bay Shallow Aquifer study unit (NSF-SA) was investigated as part of the Priority Basin Project of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is in Marin, Mendocino, Napa, Solano, and Sonoma Counties and included two physiographic study areas: the Valleys and Plains area and the surrounding Highlands area. The NSF-SA focused on groundwater resources used for domestic drinking water supply, which generally correspond to shallower parts of aquifer systems than that of groundwater resources used for public drinking water supply in the same area. The assessments characterized the quality of untreated groundwater, not the quality of drinking water.

This study included three components: (1) a status assessment, which characterized the status of the quality of the groundwater resources used for domestic supply for 2012; (2) an understanding assessment, which evaluated the natural and human factors potentially affecting water quality in those resources; and (3) a comparison between the groundwater resources used for domestic supply and those used for public supply.

The status assessment was based on data collected from 71 sites sampled by the U.S. Geological Survey for the GAMA Priority Basin Project in 2012. To provide context, concentrations of constituents measured in groundwater were compared to U.S. Environmental Protection Agency (EPA) and California State Water Resources Control Board Division of Drinking Water regulatory and non-regulatory benchmarks for drinking-water quality. The status assessment used a grid-based method to estimate the proportion of the groundwater resources that has concentrations of water-quality constituents approaching or above benchmark concentrations. This method provides statistically unbiased results at the study-area scale and permits comparisons to other GAMA Priority Basin Project study areas.

In the NSF-SA study unit as a whole, inorganic constituents with human-health benchmarks were detected at high relative concentrations (RCs) in 27 percent of the shallow aquifer system, and inorganic constituents with secondary maximum contaminant levels (SMCL) were detected at high RCs in 24 percent of the system. The inorganic constituents detected at high RCs were arsenic, boron, fluoride, manganese, nitrate, iron, sulfate, and total dissolved solids (TDS). Organic constituents with human-health benchmarks were detected at high RCs in 1 percent of the shallow aquifer system. Of the 148 organic constituents analyzed, 30 constituents were detected, although only 1, chloroform, had a detection frequency greater than 10 percent.

Natural and anthropogenic factors that could affect the groundwater quality were evaluated by using results from statistical testing of associations between constituent concentrations and values of potential explanatory factors. Groundwater age class (modern, mixed, or pre-modern), redox class (oxic or anoxic), aquifer lithology class (metamorphic, sedimentary, or volcanic), and dissolved oxygen concentrations were the explanatory factors that explained distribution patterns of most of the inorganic constituents best. Groundwater classified primarily as pre-modern or mixed in age was associated with higher concentrations of arsenic and fluoride than waters classified as modern. Anoxic or mixed redox conditions were associated with higher concentrations of boron, fluoride, and manganese. Similar patterns of association with explanatory variables were seen for inorganic constituents with aesthetic-based benchmarks detected at high concentrations. Nitrate and perchlorate had higher concentrations in oxic than in the anoxic redox class and were positively correlated with urban land use.

The NSF-SA water-quality results were compared to those of the GAMA North San Francisco Bay Public-Supply Aquifer study unit (NSF-PA). The NSF-PA was sampled in 2004 and covers much of the same area as the NSF-SA, but focused on the deeper public-supply aquifer system. The comparison of the NSF-PA to the NSF-SA showed that there were more differences between the Valleys and Plains study areas of the two study units than between the Highlands study areas of the two study units. As expected from the shallower depth of wells, the NSF-SA Valleys and Plains study area had a lesser proportion of pre-modern age groundwater and greater proportion of modern age groundwater than the NSF-PA Valleys and Plains study area. In contrast, well depths and groundwater ages were not significantly different between the two Highlands study areas. Arsenic, manganese, and nitrate were present at high RCs, and perchlorate was detected in greater proportions of the NSF-SA Valleys and Plains study area than the NSF-PA Valleys and Plains study area.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175051","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Bennett, G.L., V, 2018, Status and understanding of groundwater quality in the North San Francisco Bay Shallow Aquifer study unit, 2012; California GAMA Priority Basin Project (ver. 1.1, February 2018): U.S. Geological Survey Scientific Investigations Report 2017–5051, 74 p., https://doi.org/10.3133/sir20175051.","productDescription":"Report: x, 74 p.","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-053824","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":344100,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5051/sir20175051_v1.1.pdf","text":"Report","size":"11.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5051 Version 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California Water Science Center
California GAMA
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2017-07-20","revisedDate":"2018-02-23","noUsgsAuthors":false,"publicationDate":"2017-07-20","publicationStatus":"PW","scienceBaseUri":"5971c1c0e4b0ec1a4885dab3","contributors":{"authors":[{"text":"Bennett, George L. V 0000-0002-6239-1604 georbenn@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-1604","contributorId":1373,"corporation":false,"usgs":true,"family":"Bennett","given":"George","suffix":"V","email":"georbenn@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695616,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70195550,"text":"70195550 - 2018 - A floodplain continuum for Atlantic coast rivers of the Southeastern US: Predictable changes in floodplain biota along a river's length","interactions":[],"lastModifiedDate":"2018-02-23T10:51:59","indexId":"70195550","displayToPublicDate":"2018-02-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"A floodplain continuum for Atlantic coast rivers of the Southeastern US: Predictable changes in floodplain biota along a river's length","docAbstract":"

Floodplains are among the world’s economically-most-valuable, environmentally-most-threatened, and yet conceptually-least-understood ecosystems. Drawing on concepts from existing riverine and wetland models, and empirical data from floodplains of Atlantic Coast rivers in the Southeastern US (and elsewhere when possible), we introduce a conceptual model to explain a continuum of longitudinal variation in floodplain ecosystem functions with a particular focus on biotic change. Our hypothesis maintains that major controls on floodplain ecology are either external (ecotonal interactions with uplands or stream/river channels) or internal (wetland-specific functions), and the relative importance of these controls changes progressively from headwater to mid-river to lower-river floodplains. Inputs of water, sediments, nutrients, flora, and fauna from uplands-to-floodplains decrease, while the impacts of wetland biogeochemistry and obligate wetland plants and animals within-floodplains increase, along the length of a river floodplain. Inputs of water, sediment, nutrients, and fauna from river/stream channels to floodplains are greatest mid-river, and lower either up- or down-stream. While the floodplain continuum we develop is regional in scope, we review how aspects may apply more broadly. Management of coupled floodplain-river ecosystems would be improved by accounting for how factors controlling the floodplain ecosystem progressively change along longitudinal riverine gradients.

","language":"English","publisher":"Springer","doi":"10.1007/s13157-017-0983-4","usgsCitation":"Batzer, D.P., Noe, G.E., Lee, L., and Galatowitsch, M., 2018, A floodplain continuum for Atlantic coast rivers of the Southeastern US: Predictable changes in floodplain biota along a river's length: Wetlands, v. 38, no. 1, p. 1-13, https://doi.org/10.1007/s13157-017-0983-4.","productDescription":"13 p.","startPage":"1","endPage":"13","ipdsId":"IP-091974","costCenters":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"links":[{"id":351873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"38","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-04","publicationStatus":"PW","scienceBaseUri":"5afee726e4b0da30c1bfc13c","contributors":{"authors":[{"text":"Batzer, Darold P.","contributorId":202656,"corporation":false,"usgs":false,"family":"Batzer","given":"Darold","email":"","middleInitial":"P.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":729238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":729237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Linda","contributorId":202657,"corporation":false,"usgs":false,"family":"Lee","given":"Linda","affiliations":[{"id":36513,"text":"University of Georgia Savannah River Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":729239,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galatowitsch, Mark","contributorId":202658,"corporation":false,"usgs":false,"family":"Galatowitsch","given":"Mark","email":"","affiliations":[{"id":36514,"text":"Centre College","active":true,"usgs":false}],"preferred":false,"id":729240,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263404,"text":"70263404 - 2018 - Ground-motion models for very-hard rock sites in eastern North America: An update","interactions":[],"lastModifiedDate":"2025-02-10T15:56:51.149178","indexId":"70263404","displayToPublicDate":"2018-02-21T09:53:22","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Ground-motion models for very-hard rock sites in eastern North America: An update","docAbstract":"

The ground‐motion models provided by me to the Next Generation Attenuation‐East (NGA‐East) project in 2015 have been updated by considering three additional Fourier spectra attenuation models and by conducting a mixed‐effect analysis of the residuals between the ground‐motion intensity measures computed from the attenuation models and the data from nine relatively well‐recorded events in eastern North America. On the basis of the period trends of the bias in the residuals and the distance trends of the residuals, I recommend the ground‐motion models developed for these attenuation models, with equal weights: the BCA10D model with 1/R geometrical spreading at all distances, and two modifications of the Atkinson and Boore (2014; referred as AB14) model, with 1/R spreading within 10 km, 1/R1.3 spreading from 10 to 50 km, and 1/√R spreading beyond 50 km.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170218","usgsCitation":"Boore, D., 2018, Ground-motion models for very-hard rock sites in eastern North America: An update: Seismological Research Letters, v. 89, no. 3, p. 1172-1184, https://doi.org/10.1785/0220170218.","productDescription":"13 p.","startPage":"1172","endPage":"1184","ipdsId":"IP-091241","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481867,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"3","noUsgsAuthors":false,"publicationDate":"2018-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Boore, David 0000-0002-8605-9673 boore@usgs.gov","orcid":"https://orcid.org/0000-0002-8605-9673","contributorId":140502,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926869,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70208916,"text":"70208916 - 2018 - Examining the role of unusually warm Indo‐Pacific sea‐surface temperatures in recent African droughts","interactions":[],"lastModifiedDate":"2020-03-05T06:46:48","indexId":"70208916","displayToPublicDate":"2018-02-21T06:42:31","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5939,"text":"Journal of the Royal Meteorological Society","active":true,"publicationSubtype":{"id":10}},"title":"Examining the role of unusually warm Indo‐Pacific sea‐surface temperatures in recent African droughts","docAbstract":"Southern Africa (SA) and eastern Africa (EA) experienced a sequence of severe droughts in December–February (SA DJF) 2015–2016, October–December (EA OND) 2016 and March–April–May 2017 (EA MAM). This sequence contributed to severe food insecurity. While climate variability in these regions is very complex, the goal of this study is to analyse the role played by unusually warm Indo–Pacific SSTs, where unusual is defined as a 1‐in‐6 year event. We use observed sea‐surface temperatures (SST) and satellite–gauge rainfall observations, a 20‐member ensemble of Community Atmospheric Model version 5.1 simulations (CAM5), and a 40‐member ensemble of climate change simulations from the Community Earth Systems Model version 1 (CESM1) Large Ensemble Community Project (LENS) to explore climate conditions associated with warm events identified based on eastern and western Pacific SSTs. Our analysis suggests that strong El Niño's may be followed by warm western Pacific SST conditions, which can lead to conditions conducive to successive and potentially predictable droughts in SA DJF, EA OND and EA MAM. We show that different regions of warm SST are related to recent droughts—SA DJF: Niño 3.4; EA OND: western equatorial Pacific (WEP); and EA MAM: western North Pacific (WNP). For DJF and MAM, respectively, the CAM5 model driven with observed SST and the same model driven within a climate change experiment indicate that warmer El Niño's and WNP events produce more intense atmospheric responses, potentially associated with more severe droughts. OND climate seems to be strongly influenced by the Indian Ocean Dipole, which corresponds with some WEP events. Given global warming, we suggest that the extreme Niño 3.4 and west Pacific SST events responsible for 2015–2017 droughts are likely to reoccur, thus humanitarian agencies should prepare to predict and respond to multi‐year drought and substantial food insecurity in SA and EA.","language":"English","publisher":"Wiley","doi":"10.1002/qj.3266","usgsCitation":"Funk, C., Harrison, L., Shukla, S., Pomposi, C., Galu, G., Korecha, D., Husak, G., Magadzire, T., Davenport, F., Hillbruner, C., Eilerts, G., Zaitchik, B., and Verdin, J., 2018, Examining the role of unusually warm Indo‐Pacific sea‐surface temperatures in recent African droughts: Journal of the Royal Meteorological Society, v. 144, no. S1, p. 360-383, https://doi.org/10.1002/qj.3266.","productDescription":"24 p.","startPage":"360","endPage":"383","ipdsId":"IP-089669","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468980,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/qj.3266","text":"Publisher Index Page"},{"id":372941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 34.80468749999999,\n 27.371767300523047\n ],\n [\n 29.8828125,\n 34.016241889667015\n ],\n [\n 11.25,\n 41.244772343082076\n ],\n [\n -7.3828125,\n 37.996162679728116\n ],\n [\n -18.28125,\n 28.304380682962783\n ],\n [\n -22.148437499999996,\n 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resolution","interactions":[],"lastModifiedDate":"2018-02-28T10:10:34","indexId":"70195533","displayToPublicDate":"2018-02-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":836,"text":"Applied Geography","active":true,"publicationSubtype":{"id":10}},"title":"The sensitivity of ecosystem service models to choices of input data and spatial resolution","docAbstract":"

Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeog.2018.02.005","usgsCitation":"Bagstad, K.J., Cohen, E., Ancona, Z.H., McNulty, S., and Sun, G., 2018, The sensitivity of ecosystem service models to choices of input data and spatial resolution: Applied Geography, v. 93, p. 25-36, https://doi.org/10.1016/j.apgeog.2018.02.005.","productDescription":"12 p.","startPage":"25","endPage":"36","ipdsId":"IP-089975","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":438005,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CR5S92","text":"USGS data release","linkHelpText":"Data Release for The sensitivity of ecosystem service models to choices of input data and spatial resolution"},{"id":351849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Rwanda","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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]\n ]\n },\n \"properties\": {\n \"name\": \"Rwanda\"\n }\n }\n ]\n}","volume":"93","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee728e4b0da30c1bfc146","contributors":{"authors":[{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":729144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cohen, Erika","contributorId":202610,"corporation":false,"usgs":false,"family":"Cohen","given":"Erika","email":"","affiliations":[{"id":36493,"text":"USDA Forest 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Ge","contributorId":145893,"corporation":false,"usgs":false,"family":"Sun","given":"Ge","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":729148,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195518,"text":"70195518 - 2018 - Delineating and identifying long-term changes in the whooping crane (Grus americana) migration corridor","interactions":[],"lastModifiedDate":"2018-02-20T12:46:47","indexId":"70195518","displayToPublicDate":"2018-02-20T00:00:00","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":"Delineating and identifying long-term changes in the whooping crane (Grus americana) migration corridor","title":"Delineating and identifying long-term changes in the whooping crane (Grus americana) migration corridor","docAbstract":"

Defining and identifying changes to seasonal ranges of migratory species is required for effective conservation. Historic sightings of migrating whooping cranes (Grus americana) have served as sole source of information to define a migration corridor in the Great Plains of North America (i.e., Canadian Prairies and United States Great Plains) for this endangered species. We updated this effort using past opportunistic sightings from 1942–2016 (n = 5,055) and more recent (2010–2016) location data from 58 telemetered birds (n = 4,423) to delineate migration corridors that included 50%, 75%, and 95% core areas. All migration corridors were well defined and relatively compact, with the 95% core corridor averaging 294 km wide, although it varied approximately ±40% in width from 170 km in central Texas to 407 km at the international border of the United States and Canada. Based on historic sightings and telemetry locations, we detected easterly movements in locations over time, primarily due to locations west of the median shifting east. This shift occurred from northern Oklahoma to central Saskatchewan at an average rate of 1.2 km/year (0.3–2.8 km/year). Associated with this directional shift was a decrease in distance of locations from the median in the same region averaging -0.7 km/year (-0.3–-1.3 km/year), suggesting a modest narrowing of the migration corridor. Changes in the corridor over the past 8 decades suggest that agencies and organizations interested in recovery of this species may need to modify where conservation and recovery actions occur. Whooping cranes showed apparent plasticity in their migratory behavior, which likely has been necessary for persistence of a wetland-dependent species migrating through the drought-prone Great Plains. Behavioral flexibility will be useful for whooping cranes to continue recovery in a future of uncertain climate and land use changes throughout their annual range.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0192737","usgsCitation":"Pearse, A.T., Rabbe, M., Juliusson, L.M., Bidwell, M.T., Craig-Moore, L., Brandt, D.A., and Harrell, W.C., 2018, Delineating and identifying long-term changes in the whooping crane (Grus americana) migration corridor: PLoS ONE, v. 13, no. 2, p. 1-15, https://doi.org/10.1371/journal.pone.0192737.","productDescription":"e0192737; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-090602","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0192737","text":"Publisher Index Page"},{"id":351820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-15","publicationStatus":"PW","scienceBaseUri":"5afee729e4b0da30c1bfc150","contributors":{"authors":[{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":728990,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rabbe, Matt","contributorId":202597,"corporation":false,"usgs":false,"family":"Rabbe","given":"Matt","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":728991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Juliusson, Lara M.","contributorId":202593,"corporation":false,"usgs":false,"family":"Juliusson","given":"Lara","email":"","middleInitial":"M.","affiliations":[{"id":36490,"text":"USFWS, Lakewood, CO","active":true,"usgs":false}],"preferred":false,"id":728992,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidwell, Mark T.","contributorId":202007,"corporation":false,"usgs":false,"family":"Bidwell","given":"Mark","email":"","middleInitial":"T.","affiliations":[{"id":36318,"text":"CWS","active":true,"usgs":false}],"preferred":false,"id":728993,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Craig-Moore, Lea","contributorId":202595,"corporation":false,"usgs":false,"family":"Craig-Moore","given":"Lea","email":"","affiliations":[{"id":36491,"text":"Environment and Climate Change Canada, Saskatoon, SK","active":true,"usgs":false}],"preferred":false,"id":728994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":728995,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harrell, Wade C.","contributorId":147143,"corporation":false,"usgs":false,"family":"Harrell","given":"Wade","email":"","middleInitial":"C.","affiliations":[{"id":16793,"text":"USFWS, Ecological Services, Austwell, TX","active":true,"usgs":false}],"preferred":false,"id":728996,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195523,"text":"70195523 - 2018 - Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria","interactions":[],"lastModifiedDate":"2018-07-03T11:36:21","indexId":"70195523","displayToPublicDate":"2018-02-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria","docAbstract":"

Rainfall-induced shallow landsliding is a persistent hazard to human life and property. Despite the observed connection between infiltration through the unsaturated zone and shallow landslide initiation, there is considerable uncertainty in how estimates of unsaturated soil-water retention properties affect slope stability assessment. This source of uncertainty is critical to evaluating the utility of physics-based hydrologic modeling as a tool for landslide early warning. We employ a numerical model of variably saturated groundwater flow parameterized with an ensemble of texture-, laboratory-, and field-based estimates of soil-water retention properties for an extensively monitored landslide-prone site in the San Francisco Bay Area, CA, USA. Simulations of soil-water content, pore-water pressure, and the resultant factor of safety show considerable variability across and within these different parameter estimation techniques. In particular, we demonstrate that with the same permeability structure imposed across all simulations, the variability in soil-water retention properties strongly influences predictions of positive pore-water pressure coincident with widespread shallow landsliding. We also find that the ensemble of soil-water retention properties imposes an order-of-magnitude and nearly two-fold variability in seasonal and event-scale landslide susceptibility, respectively. Despite the reduced factor of safety uncertainty during wet conditions, parameters that control the dry end of the soil-water retention function markedly impact the ability of a hydrologic model to capture soil-water content dynamics observed in the field. These results suggest that variability in soil-water retention properties should be considered for objective physics-based simulation of landslide early warning criteria.

","language":"English","publisher":"Springer","doi":"10.1007/s10346-018-0950-z","usgsCitation":"Thomas, M.A., Mirus, B.B., Collins, B.D., Lu, N., and Godt, J.W., 2018, Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria: Landslides, v. 15, no. 7, p. 1265-1277, https://doi.org/10.1007/s10346-018-0950-z.","productDescription":"13 p.","startPage":"1265","endPage":"1277","ipdsId":"IP-089282","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":438007,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7M0449D","text":"USGS data release","linkHelpText":"Field data used to support hydrologic modeling for the U.S. Geological Survey's San Francisco Bay Area "BALT1" landslide monitoring site"},{"id":351832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-12","publicationStatus":"PW","scienceBaseUri":"5afee728e4b0da30c1bfc14a","contributors":{"authors":[{"text":"Thomas, Matthew A.","contributorId":138657,"corporation":false,"usgs":false,"family":"Thomas","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":12482,"text":"Department of Geological and Environmental Sciences, Stanford University, 450 Serra Mall, Building 320, Stanford, California 94305-2115, USA","active":true,"usgs":false}],"preferred":false,"id":729027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":729028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Brian D. bcollins@usgs.gov","contributorId":2406,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":729029,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Ning","contributorId":191360,"corporation":false,"usgs":false,"family":"Lu","given":"Ning","email":"","affiliations":[{"id":12620,"text":"U.S. Army Corp. of Engineers","active":true,"usgs":false}],"preferred":false,"id":729030,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729031,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195500,"text":"70195500 - 2018 - Plateau subduction, intraslab seismicity, and the Denali (Alaska) volcanic gap","interactions":[],"lastModifiedDate":"2018-02-20T10:08:36","indexId":"70195500","displayToPublicDate":"2018-02-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Plateau subduction, intraslab seismicity, and the Denali (Alaska) volcanic gap","docAbstract":"Tectonic tremors in Alaska (USA) are associated with subduction of the Yakutat plateau, but their origins are unclear due to lack of depth constraints. We have processed tremor recordings to extract low-frequency earthquakes (LFEs), and generated a set of six LFE waveform templates via iterative network matched filtering and stacking. The timing of impulsive P (compressional) wave and S (shear) wave arrivals on template waveforms places LFEs at 40–58 km depth, near the upper envelope of intraslab seismicity and immediately updip of increased levels of intraslab seismicity. S waves at near-epicentral distances display polarities consistent with shear slip on the plate boundary. We compare characteristics of LFEs, seismicity, and tectonic structures in central Alaska with those in warm subduction zones, and propose a new model for the region’s unusual intraslab seismicity and the enigmatic Denali volcanic gap (i.e., an area of no volcanism where expected). We argue that fluids in the Yakutat plate are confined to its upper crust, and that shallow subduction leads to hydromechanical conditions at the slab interface in central Alaska akin to those in warm subduction zones where similar LFEs and tremor occur. These conditions lead to fluid expulsion at shallow depths, explaining strike-parallel alignment of tremor occurrence with the Denali volcanic gap. Moreover, the lack of double seismic zone and restriction of deep intraslab seismicity to a persistent low-velocity zone are simple consequences of anhydrous conditions prevailing in the lower crust and upper mantle of the Yakutat plate.","language":"English","publisher":"Geological Society of America","doi":"10.1130/G38867.1","usgsCitation":"Chuang, L.Y., Bostock, M., Wech, A., and Plourde, A., 2018, Plateau subduction, intraslab seismicity, and the Denali (Alaska) volcanic gap: Geology, v. 45, no. 7, p. 647-650, https://doi.org/10.1130/G38867.1.","productDescription":"4 p.","startPage":"647","endPage":"650","ipdsId":"IP-081838","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468986,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2429/64405","text":"External Repository"},{"id":351811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Denali volcanic gap","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -184.39453125,\n 49.95121990866204\n ],\n [\n -137.63671875,\n 49.95121990866204\n ],\n [\n -137.63671875,\n 70.90226826757711\n ],\n [\n -184.39453125,\n 70.90226826757711\n ],\n [\n -184.39453125,\n 49.95121990866204\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-08","publicationStatus":"PW","scienceBaseUri":"5afee72ae4b0da30c1bfc15a","contributors":{"authors":[{"text":"Chuang, Lindsay Yuling","contributorId":173691,"corporation":false,"usgs":false,"family":"Chuang","given":"Lindsay","email":"","middleInitial":"Yuling","affiliations":[{"id":27275,"text":"Department of Earth Sciences, National Taiwan Normal University","active":true,"usgs":false}],"preferred":false,"id":728930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bostock, Michael","contributorId":202572,"corporation":false,"usgs":false,"family":"Bostock","given":"Michael","email":"","affiliations":[{"id":36484,"text":"UBC","active":true,"usgs":false}],"preferred":false,"id":728931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":728929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plourde, Alexandre","contributorId":202573,"corporation":false,"usgs":false,"family":"Plourde","given":"Alexandre","email":"","affiliations":[{"id":36484,"text":"UBC","active":true,"usgs":false}],"preferred":false,"id":728932,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}