{"pageNumber":"894","pageRowStart":"22325","pageSize":"25","recordCount":165521,"records":[{"id":70194379,"text":"70194379 - 2017 - Application of synthetic scenarios to address water resource concerns: A management-guided case study from the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2017-11-28T10:18:24","indexId":"70194379","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5567,"text":"Climate Services","active":true,"publicationSubtype":{"id":10}},"title":"Application of synthetic scenarios to address water resource concerns: A management-guided case study from the Upper Colorado River Basin","docAbstract":"Water managers are increasingly interested in better understanding and planning for projected resource impacts from climate change. In this management-guided study, we use a very large suite of synthetic climate scenarios in a statistical modeling framework to simultaneously evaluate how (1) average temperature and precipitation changes, (2) initial basin conditions, and (3) temporal characteristics of the input climate data influence water-year flow in the Upper Colorado River. The results here suggest that existing studies may underestimate the degree of uncertainty in future streamflow, particularly under moderate temperature and precipitation changes. However, we also find that the relative severity of future flow projections within a given climate scenario can be estimated with simple metrics that characterize the input climate data and basin conditions. These results suggest that simple testing, like the analyses presented in this paper, may be helpful in understanding differences between existing studies or in identifying specific conditions for physically based mechanistic modeling. Both options could reduce overall cost and improve the efficiency of conducting climate change impacts studies.","language":"English","publisher":"Elsevier","doi":"10.1016/j.cliser.2017.10.003","usgsCitation":"McAfee, S., Pederson, G.T., Woodhouse, C.A., and McCabe, G.J., 2017, Application of synthetic scenarios to address water resource concerns: A management-guided case study from the Upper Colorado River Basin: Climate Services, v. 8, p. 26-35, https://doi.org/10.1016/j.cliser.2017.10.003.","productDescription":"10 p.","startPage":"26","endPage":"35","ipdsId":"IP-086422","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":469299,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cliser.2017.10.003","text":"Publisher Index Page"},{"id":349418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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             43.389081939117496\n            ],\n            [\n              -110.89599609375,\n              42.87596410238256\n            ],\n            [\n              -110.85205078124999,\n              41.78769700539063\n            ],\n            [\n              -110.74218749999999,\n              41.27780646738183\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faffe4b06e28e9c22acb","contributors":{"authors":[{"text":"McAfee, Stephanie A.","contributorId":167115,"corporation":false,"usgs":false,"family":"McAfee","given":"Stephanie A.","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":723594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":723593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":723595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":723596,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70194354,"text":"70194354 - 2017 - Solid-phase arsenic speciation in aquifer sediments: A micro-X-ray absorption spectroscopy approach for quantifying trace-level speciation","interactions":[],"lastModifiedDate":"2018-11-26T09:39:13","indexId":"70194354","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Solid-phase arsenic speciation in aquifer sediments: A micro-X-ray absorption spectroscopy approach for quantifying trace-level speciation","docAbstract":"e of this research is to identify the solid-phase sources and geochemical mechanisms of release of As in aquifers of the Des Moines Lobe glacial advance. The overarching concept is that conditions present at the aquifer-aquitard interfaces promote a suite of geochemical reactions leading to mineral alteration and release of As to groundwater. A microprobe X-ray absorption spectroscopy (lXAS) approach is developed and applied to rotosonic drill core samples to identify the solid-phase speciation of As in aquifer, aquitard, and aquifer-aquitard interface sediments. This approach addresses the low solid-phase As concentrations, as well as the fine-scale physical and chemical heterogeneity of the sediments. The spectroscopy data are analyzed using novel cosine-distance and correlation-distance hierarchical clustering for Fe 1s and As 1s lXAS datasets. The solid-phase Fe and As speciation is then interpreted using sediment and well-water chemical data to propose solid-phase As reservoirs and release mechanisms. The results confirm that in two of the three locations studied, the glacial sediment forming the aquitard is the source of As to the aquifer sediments. The results are consistent with three different As release mechanisms: (1) desorption from Fe (oxyhydr)oxides, (2) reductive dissolution of Fe (oxyhydr)oxides, and (3) oxidative dissolution of Fe sulfides. The findings confirm that glacial sediments at the interface between aquifer and aquitard are geochemically active zones for As. The diversity of As release mechanisms is consistent with the geographic heterogeneity observed in the distribution of elevated-As wells.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2017.05.018","usgsCitation":"Nicholas, S.L., Erickson, M., Woodruff, L.G., Knaeble, A.R., Marcus, M.A., Lynch, J.K., and Toner, B.M., 2017, Solid-phase arsenic speciation in aquifer sediments: A micro-X-ray absorption spectroscopy approach for quantifying trace-level speciation: Geochimica et Cosmochimica Acta, v. 211, p. 228-255, https://doi.org/10.1016/j.gca.2017.05.018.","productDescription":"28 p.","startPage":"228","endPage":"255","ipdsId":"IP-081306","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":469295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2017.05.018","text":"Publisher Index Page"},{"id":349424,"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              -98.87695312499999,\n              41.57436130598913\n            ],\n            [\n              -89.384765625,\n              41.57436130598913\n            ],\n            [\n              -89.384765625,\n              50.51342652633956\n            ],\n            [\n              -98.87695312499999,\n              50.51342652633956\n            ],\n            [\n              -98.87695312499999,\n              41.57436130598913\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"211","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faffe4b06e28e9c22ad1","contributors":{"authors":[{"text":"Nicholas, Sarah L.","contributorId":200812,"corporation":false,"usgs":false,"family":"Nicholas","given":"Sarah","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":723435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knaeble, Alan R.","contributorId":200813,"corporation":false,"usgs":false,"family":"Knaeble","given":"Alan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":723437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marcus, Matthew A.","contributorId":200814,"corporation":false,"usgs":false,"family":"Marcus","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":723438,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynch, Joshua K.","contributorId":200815,"corporation":false,"usgs":false,"family":"Lynch","given":"Joshua","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":723439,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Toner, Brandy M.","contributorId":200816,"corporation":false,"usgs":false,"family":"Toner","given":"Brandy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723440,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194372,"text":"70194372 - 2017 - Factors influencing uptake of sylvatic plague vaccine baits by prairie dogs","interactions":[],"lastModifiedDate":"2023-06-21T15:23:53.765649","indexId":"70194372","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1443,"text":"EcoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing uptake of sylvatic plague vaccine baits by prairie dogs","docAbstract":"Sylvatic plague vaccine (SPV) is a virally vectored bait-delivered vaccine expressing Yersinia pestis antigens that can protect prairie dogs (Cynomys spp.) from plague and has potential utility as a management tool. In a large-scale 3-year field trial, SPV-laden baits containing the biomarker rhodamine B (used to determine bait consumption) were distributed annually at a rate of approximately 100–125 baits/hectare along transects at 58 plots encompassing the geographic ranges of four species of prairie dogs. We assessed site- and individual-level factors related to bait uptake in prairie dogs to determine which were associated with bait uptake rates. Overall bait uptake for 7820 prairie dogs sampled was 70% (95% C.I. 69.9–72.0). Factors influencing bait uptake rates by prairie dogs varied by species, however, in general, heavier animals had greater bait uptake rates. Vegetation quality and day of baiting influenced this relationship for black-tailed, Gunnison’s, and Utah prairie dogs. For these species, baiting later in the season, when normalized difference vegetation indices (a measure of green vegetation density) are lower, improves bait uptake by smaller animals. Consideration of these factors can aid in the development of species-specific SPV baiting strategies that maximize bait uptake and subsequent immunization of prairie dogs against plague.","language":"English","publisher":"Springer","doi":"10.1007/s10393-017-1294-1","usgsCitation":"Abbott, R.C., Russell, R.E., Richgels, K., Tripp, D.W., Matchett, M.R., Biggins, D.E., and Rocke, T.E., 2017, Factors influencing uptake of sylvatic plague vaccine baits by prairie dogs: EcoHealth, v. 15, no. 1, p. 12-22, https://doi.org/10.1007/s10393-017-1294-1.","productDescription":"11 p.; Data Release","startPage":"12","endPage":"22","ipdsId":"IP-089024","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":349421,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418296,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X92968"}],"volume":"15","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-20","publicationStatus":"PW","scienceBaseUri":"5a60faffe4b06e28e9c22acf","contributors":{"authors":[{"text":"Abbott, Rachel C. 0000-0003-4820-9295 rabbott@usgs.gov","orcid":"https://orcid.org/0000-0003-4820-9295","contributorId":1183,"corporation":false,"usgs":true,"family":"Abbott","given":"Rachel","email":"rabbott@usgs.gov","middleInitial":"C.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":723547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":723548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richgels, Katherine 0000-0003-2834-9477 krichgels@usgs.gov","orcid":"https://orcid.org/0000-0003-2834-9477","contributorId":167016,"corporation":false,"usgs":true,"family":"Richgels","given":"Katherine","email":"krichgels@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":723549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tripp, Daniel W.","contributorId":17910,"corporation":false,"usgs":false,"family":"Tripp","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":13449,"text":"Colorado Division of Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":723552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matchett, Marc R.","contributorId":193409,"corporation":false,"usgs":false,"family":"Matchett","given":"Marc","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":723553,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":723550,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":723551,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194393,"text":"70194393 - 2017 - Estimating rupture distances without a rupture","interactions":[],"lastModifiedDate":"2017-11-28T10:09:35","indexId":"70194393","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","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":"Estimating rupture distances without a rupture","docAbstract":"Most ground motion prediction equations (GMPEs) require distances that are defined relative to a rupture model, such as the distance to the surface projection of the rupture (RJB) or the closest distance to the rupture plane (RRUP). There are a number of situations in which GMPEs are used where it is either necessary or advantageous to derive rupture distances from point-source distance metrics, such as hypocentral (RHYP) or epicentral (REPI) distance. For ShakeMap, it is necessary to provide an estimate of the shaking levels for events without rupture models, and before rupture models are available for events that eventually do have rupture models. In probabilistic seismic hazard analysis, it is often convenient to use point-source distances for gridded seismicity sources, particularly if a preferred orientation is unknown. This avoids the computationally cumbersome task of computing rupture-based distances for virtual rupture planes across all strikes and dips for each source. We derive average rupture distances conditioned on REPI, magnitude, and (optionally) back azimuth, for a variety of assumed seismological constraints. Additionally, we derive adjustment factors for GMPE standard deviations that reflect the added uncertainty in the ground motion estimation when point-source distances are used to estimate rupture distances.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170174","usgsCitation":"Thompson, E.M., and Worden, C., 2017, Estimating rupture distances without a rupture: Bulletin of the Seismological Society of America, v. 10, no. 10, p. 1-9, https://doi.org/10.1785/0120170174.","productDescription":"9 p.","startPage":"1","endPage":"9","ipdsId":"IP-090953","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":438144,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VH5M0W","text":"USGS data release","linkHelpText":"Point-source to finite-fault distance conversions"},{"id":349417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-21","publicationStatus":"PW","scienceBaseUri":"5a60faffe4b06e28e9c22ac8","contributors":{"authors":[{"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":723673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":723674,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70194429,"text":"70194429 - 2017 - The value of information for woodland management: Updating a state–transition model","interactions":[],"lastModifiedDate":"2017-11-29T09:54:21","indexId":"70194429","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"The value of information for woodland management: Updating a state–transition model","docAbstract":"Value of information (VOI) analyses reveal the expected benefit of reducing uncertainty to a decision maker. Most ecological VOI analyses have focused on population models rarely addressing more complex community models. We performed a VOI analysis for a complex state–transition model of Box-Ironbark Forest and Woodland management. With three management alternatives (limited harvest/firewood removal (HF), ecological thinning (ET), and no management), managing the system optimally (for 150 yr) with the original information would, on average, increase the amount of forest in a desirable state from 19% to 35% (a 16-percentage point increase). Resolving all uncertainty would, on average, increase the final percentage to 42% (a 19-percentage point increase). However, only resolving the uncertainty for a single parameter was worth almost two-thirds the value of resolving all uncertainty. We found the VOI to depend on the number of management options, increasing as the management flexibility increased. Our analyses show it is more cost-effective to monitor low-density regrowth forest than other states and more cost-effective to experiment with the no-management alternative than the other management alternatives. Importantly, the most cost-effective strategies did not include either the most desired forest states or the least understood management strategy, ET. This implies that managers cannot just rely on intuition to tell them where the most VOI will lie, as critical uncertainties in a complex system are sometimes cryptic.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1998","usgsCitation":"Morris, W.K., Runge, M.C., and Vesk, P.A., 2017, The value of information for woodland management: Updating a state–transition model: Ecosphere, v. 8, no. 11, p. 1-12, https://doi.org/10.1002/ecs2.1998.","productDescription":"e01998; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-082196","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469297,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1998","text":"Publisher Index Page"},{"id":349416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","state":"Victoria","volume":"8","issue":"11","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-16","publicationStatus":"PW","scienceBaseUri":"5a60faffe4b06e28e9c22ac5","contributors":{"authors":[{"text":"Morris, William K.","contributorId":200890,"corporation":false,"usgs":false,"family":"Morris","given":"William","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":723739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":723738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vesk, Peter A.","contributorId":200891,"corporation":false,"usgs":false,"family":"Vesk","given":"Peter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":723740,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194432,"text":"70194432 - 2017 - Determining fine-scale use and movement patterns of diving bird species in federal waters of the Mid-Atlantic United States using satellite telemetry","interactions":[],"lastModifiedDate":"2018-02-06T12:39:35","indexId":"70194432","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesNumber":"BOEM 2017-069","title":"Determining fine-scale use and movement patterns of diving bird species in federal waters of the Mid-Atlantic United States using satellite telemetry","docAbstract":"Offshore wind energy development in the United States is projected to expand in the upcoming decades to meet growing energy demands and reduce fossil fuel emissions. There is particular interest in commercial offshore wind development within Federal waters (i.e., > 3 nautical miles from shore) of the mid-Atlantic. In order to understand the potential for adverse effects on marine birds in this area, information on distribution and behavior (e.g., flight pathways, timing, etc.) is required for a broad suite of species. In areas where offshore wind development is likely to occur, such information can be used to identify high use areas during critical life stages, which can inform the siting of offshore facilities. It can also be used to provide baseline data for understanding broad changes in distributions that occur after offshore wind developments are constructed in a specific area.","language":"English","publisher":"U.S. Department of the Interior, Bureau of Ocean Energy Management","usgsCitation":"Spiegel, C., Berlin, A., Gilbert, A., Gray, C., Montevecchi, W., Stenhouse, I., Ford, S., Olsen, G.H., Fiely, J., Savoy, L., Goodale, M.W., and Burke, C., 2017, Determining fine-scale use and movement patterns of diving bird species in federal waters of the Mid-Atlantic United States using satellite telemetry, xxix, 260 p.","productDescription":"xxix, 260 p.","ipdsId":"IP-088069","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":349413,"type":{"id":15,"text":"Index 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Alicia 0000-0002-5275-3077 aberlin@usgs.gov","orcid":"https://orcid.org/0000-0002-5275-3077","contributorId":168416,"corporation":false,"usgs":true,"family":"Berlin","given":"Alicia","email":"aberlin@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":723754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilbert, Andrew","contributorId":194560,"corporation":false,"usgs":false,"family":"Gilbert","given":"Andrew","affiliations":[],"preferred":false,"id":723756,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gray, Carrie E.","contributorId":127669,"corporation":false,"usgs":false,"family":"Gray","given":"Carrie E.","affiliations":[{"id":25572,"text":"University of Maine, Orono","active":true,"usgs":false},{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 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golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":723761,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fiely, Jonathan","contributorId":200905,"corporation":false,"usgs":false,"family":"Fiely","given":"Jonathan","email":"","affiliations":[],"preferred":false,"id":723762,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Savoy, Lucas","contributorId":171896,"corporation":false,"usgs":false,"family":"Savoy","given":"Lucas","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":723763,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Goodale, M. Wing","contributorId":200906,"corporation":false,"usgs":false,"family":"Goodale","given":"M.","email":"","middleInitial":"Wing","affiliations":[],"preferred":false,"id":723764,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Burke, Chantelle","contributorId":200907,"corporation":false,"usgs":false,"family":"Burke","given":"Chantelle","email":"","affiliations":[],"preferred":false,"id":723765,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70194439,"text":"70194439 - 2017 - Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States","interactions":[],"lastModifiedDate":"2017-11-28T11:46:05","indexId":"70194439","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","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":"Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States","docAbstract":"Drinking water treatment plants rely on purification of contaminated source waters to provide communities with potable water. One group of possible contaminants are enteric viruses. Measurement of viral quantities in environmental water systems are often performed using polymerase chain reaction (PCR) or quantitative PCR (qPCR). However, true values may be underestimated due to challenges involved in a multi-step viral concentration process and due to PCR inhibition. In this study, water samples were concentrated from 25 drinking water treatment plants (DWTPs) across the US to study the occurrence of enteric viruses in source water and removal after treatment. The five different types of viruses studied were adenovirus, norovirus GI, norovirus GII, enterovirus, and polyomavirus. Quantitative PCR was performed on all samples to determine presence or absence of these viruses in each sample. Ten DWTPs showed presence of one or more viruses in source water, with four DWTPs having treated drinking water testing positive. Furthermore, PCR inhibition was assessed for each sample using an exogenous amplification control, which indicated that all of the DWTP samples, including source and treated water samples, had some level of inhibition, confirming that inhibition plays an important role in PCR based assessments of environmental samples. PCR inhibition measurements, viral recovery, and other assessments were\nincorporated into a Bayesian model to more accurately determine viral load in both source and treated water. Results of the Bayesian model indicated that viruses are present in source water and treated water. By using a Bayesian framework that incorporates inhibition, as well as many other parameters that affect viral detection, this study offers an approach for more accurately estimating the occurrence of viral pathogens in environmental waters.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.10.267","usgsCitation":"Varughese, E.A., Brinkman, N., Anneken, E.M., Cashdollar, J.S., Fout, G., Furlong, E.T., Kolpin, D.W., Glassmeyer, S.T., and Keely, S.P., 2017, Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States: Science of the Total Environment, v. 619-620, p. 1330-1339, https://doi.org/10.1016/j.scitotenv.2017.10.267.","productDescription":"10 p.","startPage":"1330","endPage":"1339","ipdsId":"IP-089619","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":469298,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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,{"id":70194335,"text":"70194335 - 2017 - A swath across the great divide: Kelp forests across the Samalga Pass biogeographic break","interactions":[],"lastModifiedDate":"2017-11-29T09:56:13","indexId":"70194335","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"A swath across the great divide: Kelp forests across the Samalga Pass biogeographic break","docAbstract":"Biogeographic breaks are often described as locations where a large number of species reach their geographic range limits. Samalga Pass, in the eastern Aleutian Archipelago, is a known biogeographic break for the spatial distribution of several species of offshore-pelagic communities, including numerous species of cold-water corals, zooplankton, fish, marine mammals, and seabirds. However, it remains unclear whether Samalga Pass also serves as a biogeographic break for nearshore benthic communities. The occurrence of biogeographic breaks across multiple habitats has not often been described. In this study, we examined if the biogeographic break for offshore-pelagic communities applies to nearshore kelp forests. To examine whether Samalga Pass serves as a biogeographic break for kelp forest communities, this study compared abundance, biomass and percent bottom cover of species associated with kelp forests on either side of the pass. We observed marked differences in kelp forest community structure, with some species reaching their geographic range limits on the opposing sides of the pass. In particular, the habitat-forming kelp Nereocystis luetkeana, and the predatory sea stars Pycnopodia helianthoides and Orthasterias koehleri all occurred on the eastern side of Samalga Pass but were not observed west of the pass. In contrast, the sea star Leptasterias camtschatica dispar was observed only on the western side of the pass. We also observed differences in overall abundance and biomass of numerous associated fish, invertebrate and macroalgal species on opposing sides of the pass. We conclude that Samalga Pass is important biogeographic break for kelp forest communities in the Aleutian Archipelago and may demark the geographic range limits of several ecologically important species.","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2017.06.007","usgsCitation":"Konar, B.H., Edwards, M.S., Bland, A., Metzger, J., Ravelo, A., Traiger, S., and Weitzman, B., 2017, A swath across the great divide: Kelp forests across the Samalga Pass biogeographic break: Continental Shelf Research, v. 143, p. 78-88, https://doi.org/10.1016/j.csr.2017.06.007.","productDescription":"11 p.","startPage":"78","endPage":"88","ipdsId":"IP-082946","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":469296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2017.06.007","text":"Publisher Index Page"},{"id":349445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Archipelago, Samalga Pass","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -177.5390625,\n              49.26780455063753\n            ],\n            [\n              -159.521484375,\n              49.26780455063753\n            ],\n            [\n              -159.521484375,\n              56.48676175249086\n            ],\n            [\n              -177.5390625,\n              56.48676175249086\n            ],\n            [\n              -177.5390625,\n              49.26780455063753\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"143","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ae1","contributors":{"authors":[{"text":"Konar, Brenda H. 0000-0002-8998-1612","orcid":"https://orcid.org/0000-0002-8998-1612","contributorId":200787,"corporation":false,"usgs":false,"family":"Konar","given":"Brenda","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":723339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Matthew S.","contributorId":200788,"corporation":false,"usgs":false,"family":"Edwards","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":723340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bland, Aaron","contributorId":200789,"corporation":false,"usgs":false,"family":"Bland","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":723341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Metzger, Jacob","contributorId":200790,"corporation":false,"usgs":false,"family":"Metzger","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":723342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ravelo, Alexandra","contributorId":200791,"corporation":false,"usgs":false,"family":"Ravelo","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":723343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Traiger, Sarah","contributorId":200792,"corporation":false,"usgs":false,"family":"Traiger","given":"Sarah","affiliations":[],"preferred":false,"id":723344,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weitzman, Ben P. 0000-0001-7559-3654 bweitzman@usgs.gov","orcid":"https://orcid.org/0000-0001-7559-3654","contributorId":5123,"corporation":false,"usgs":true,"family":"Weitzman","given":"Ben P.","email":"bweitzman@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":723338,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70193317,"text":"tm12A2 - 2017 - PRISM software—Processing and review interface for strong-motion data","interactions":[],"lastModifiedDate":"2017-11-28T16:07:31","indexId":"tm12A2","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"12-A2","title":"PRISM software—Processing and review interface for strong-motion data","docAbstract":"Rapidly available and accurate ground-motion acceleration time series (seismic recordings) and derived data products are essential to quickly providing scientific and engineering analysis and advice after an earthquake. To meet this need, the U.S. Geological Survey National Strong Motion Project has developed a software package called PRISM (Processing and Review Interface for Strong-Motion data). PRISM automatically processes strong-motion acceleration records, producing compatible acceleration, velocity, and displacement time series; acceleration, velocity, and displacement response spectra; Fourier amplitude spectra; and standard earthquake-intensity measures. PRISM is intended to be used by strong-motion seismic networks, as well as by earthquake engineers and seismologists.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm12A2","usgsCitation":"Jones, J.M., Kalkan, Erol, Stephens, C.D., and Ng, Peter, 2017, PRISM software—Processing and review interface for strong-motion data: U.S. Geological Survey Techniques and Methods, book 12, chap. A2, 4 p., https://doi.org/10.3133/tm12A2.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-090364","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":349454,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/12a2/tm12a2.pdf","text":"Report","size":"850 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 12-A2"},{"id":349453,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/12a2/coverthb.jpg"}],"publicComments":"This report is Chapter 2 of Section A in USGS Techniques and Methods Book 12.","contact":"<p><a href=\"https://earthquake.usgs.gov/contactus/menlo/menloloc.php\" data-mce-href=\"https://earthquake.usgs.gov/contactus/menlo/menloloc.php\">Director</a>,<a href=\"https://earthquake.usgs.gov/contactus/menlo/\" target=\"_blank\" data-mce-href=\"https://earthquake.usgs.gov/contactus/menlo/\"><br>USGS Earthquake Science Center<br></a><a href=\"https://usgs.gov/\" target=\"_blank\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>345 Middlefield Road&nbsp;<br>Mail Stop 977&nbsp;<br>Menlo Park, CA 94025</p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-11-28","noUsgsAuthors":false,"publicationDate":"2017-11-28","publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ae5","contributors":{"authors":[{"text":"Jones, Jeanne M. 0000-0001-7549-9270 jmjones@usgs.gov","orcid":"https://orcid.org/0000-0001-7549-9270","contributorId":4676,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","email":"jmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":718665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":718664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stephens, Christopher D. 0000-0003-0858-3709 cdstephens@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-3709","contributorId":2788,"corporation":false,"usgs":true,"family":"Stephens","given":"Christopher","email":"cdstephens@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":718666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ng, Peter 0000-0001-8509-5544 png@usgs.gov","orcid":"https://orcid.org/0000-0001-8509-5544","contributorId":3317,"corporation":false,"usgs":true,"family":"Ng","given":"Peter","email":"png@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":718667,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70194341,"text":"70194341 - 2017 - Regionalizing indicators for marine ecosystems: Bering Sea–Aleutian Island seabirds, climate, and competitors","interactions":[],"lastModifiedDate":"2017-11-28T11:11:23","indexId":"70194341","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Regionalizing indicators for marine ecosystems: Bering Sea–Aleutian Island seabirds, climate, and competitors","docAbstract":"Seabirds are thought to be reliable, real-time indicators of forage fish availability and the climatic and\r\nbiotic factors affecting pelagic food webs in marine ecosystems. In this study, we tested the hypothesis\r\nthat temporal trends and interannual variability in seabird indicators reflect simultaneously occurring\r\nbottom-up (climatic) and competitor (pink salmon) forcing of food webs. To test this hypothesis, we\r\nderived multivariate seabird indicators for the Bering Sea–Aleutian Island (BSAI) ecosystem and related\r\nthem to physical and biological conditions known to affect pelagic food webs in the ecosystem. We\r\nexamined covariance in the breeding biology of congeneric pelagic gulls (kittiwakes Rissa tridactyla and\r\nR. brevirostris) andauks (murres Uria aalge and U. lomvia), all of whichare abundant and well-studiedinthe\r\nBSAI. At the large ecosystem scale, kittiwake and murre breeding success and phenology (hatch dates)\r\ncovaried among congeners, so data could be combined using multivariate techniques, but patterns of\r\nresponsedifferedsubstantially betweenthe genera.Whiledata fromall sites (n = 5)inthe ecosystemcould\r\nbe combined, the south eastern Bering Sea shelf colonies (St. George, St. Paul, and Cape Peirce) provided\r\nthe strongest loadings on indicators, and hence had the strongest influence on modes of variability. The\r\nkittiwake breeding success mode of variability, dominated by biennial variation, was significantly related\r\nto both climatic factors and potential competitor interactions. The murre indicator mode was interannual\r\nand only weakly related to the climatic factors measured. The kittiwake phenology indicator mode of\r\nvariability showed multi-year periods (“stanzas”) of late or early breeding, while the murre phenology\r\nindicator showed a trend towards earlier timing. Ocean climate relationships with the kittiwake breeding\r\nsuccess indicator suggestthat early-season (winter–spring) environmental conditions and the abundance\r\nof pink salmon affect the pelagic food webs that support these seabirds in the BSAI ecosystem.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2017.03.013","usgsCitation":"Sydeman, W., Thompson, S.A., Piatt, J.F., García-Reyes, M., Zador, S., Williams, J.C., Romano, M., and Renner, H., 2017, Regionalizing indicators for marine ecosystems: Bering Sea–Aleutian Island seabirds, climate, and competitors: Ecological Indicators, v. 78, p. 458-469, https://doi.org/10.1016/j.ecolind.2017.03.013.","productDescription":"12 p.","startPage":"458","endPage":"469","ipdsId":"IP-063143","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":349429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Islands, Bering Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -188.7890625,\n              50.3454604086048\n            ],\n            [\n              -156.88476562499997,\n              50.3454604086048\n            ],\n            [\n              -156.88476562499997,\n              60.54377524118842\n            ],\n            [\n              -188.7890625,\n              60.54377524118842\n            ],\n            [\n              -188.7890625,\n              50.3454604086048\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"78","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ade","contributors":{"authors":[{"text":"Sydeman, William J.","contributorId":172574,"corporation":false,"usgs":false,"family":"Sydeman","given":"William J.","affiliations":[],"preferred":false,"id":723371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Sarah Ann","contributorId":198394,"corporation":false,"usgs":false,"family":"Thompson","given":"Sarah","email":"","middleInitial":"Ann","affiliations":[],"preferred":false,"id":723372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":723370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"García-Reyes, Marisol","contributorId":200914,"corporation":false,"usgs":false,"family":"García-Reyes","given":"Marisol","affiliations":[],"preferred":false,"id":723373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zador, Stephani","contributorId":60992,"corporation":false,"usgs":false,"family":"Zador","given":"Stephani","affiliations":[],"preferred":false,"id":723374,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Jeffrey C.","contributorId":126882,"corporation":false,"usgs":false,"family":"Williams","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":723375,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Romano, Marc","contributorId":200806,"corporation":false,"usgs":false,"family":"Romano","given":"Marc","affiliations":[],"preferred":false,"id":723376,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Renner, Heather","contributorId":200807,"corporation":false,"usgs":false,"family":"Renner","given":"Heather","affiliations":[],"preferred":false,"id":723377,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70194343,"text":"70194343 - 2017 - Exploration of diffuse and discrete sources of acid mine drainage to a headwater mountain stream in Colorado, USA","interactions":[],"lastModifiedDate":"2017-11-28T11:00:53","indexId":"70194343","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2745,"text":"Mine Water and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Exploration of diffuse and discrete sources of acid mine drainage to a headwater mountain stream in Colorado, USA","docAbstract":"We investigated the impact of acid mine drainage (AMD) contamination from the Minnesota Mine, an inactive gold and silver mine, on Lion Creek, a headwater mountain stream near Empire, Colorado. The objective was to map the sources of AMD contamination, including discrete sources visible at the surface and diffuse inputs that were not readily apparent. This was achieved using geochemical sampling, in-stream and in-seep fluid electrical conductivity (EC) logging, and electrical resistivity imaging (ERI) of the subsurface. The low pH of the AMD-impacted water correlated to high fluid EC values that served as a target for the ERI. From ERI, we identified two likely sources of diffuse contamination entering the stream: (1) the subsurface extent of two seepage faces visible on the surface, and (2) rainfall runoff washing salts deposited on the streambank and in a tailings pile on the east bank of Lion Creek. Additionally, rainfall leaching through the tailings pile is a potential diffuse source of contamination if the subsurface beneath the tailings pile is hydraulically connected with the stream. In-stream fluid EC was lowest when stream discharge was highest in early summer and then increased throughout the summer as stream discharge decreased, indicating that the concentration of dissolved solids in the stream is largely controlled by mixing of groundwater and snowmelt. Total dissolved solids (TDS) load is greatest in early summer and displays a large diel signal. Identification of diffuse sources and variability in TDS load through time should allow for more targeted remediation options.","language":"English","publisher":"Springer Berlin Heidelberg","doi":"10.1007/s10230-017-0452-6","usgsCitation":"Johnston, A., Runkel, R.L., Navarre-Sitchler, A., and Singha, K., 2017, Exploration of diffuse and discrete sources of acid mine drainage to a headwater mountain stream in Colorado, USA: Mine Water and the Environment, v. 36, no. 4, p. 463-478, https://doi.org/10.1007/s10230-017-0452-6.","productDescription":"16 p.","startPage":"463","endPage":"478","ipdsId":"IP-077543","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":349427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Empire","otherGeospatial":"Lion Creek","volume":"36","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-29","publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ada","contributors":{"authors":[{"text":"Johnston, Allison","contributorId":200808,"corporation":false,"usgs":false,"family":"Johnston","given":"Allison","email":"","affiliations":[],"preferred":false,"id":723380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Navarre-Sitchler, Alexis","contributorId":190441,"corporation":false,"usgs":false,"family":"Navarre-Sitchler","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":723381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini","contributorId":76733,"corporation":false,"usgs":true,"family":"Singha","given":"Kamini","affiliations":[],"preferred":false,"id":723382,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70194352,"text":"70194352 - 2017 - Spatially explicit dynamic N-mixture models","interactions":[],"lastModifiedDate":"2017-11-28T10:51:21","indexId":"70194352","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Spatially explicit dynamic N-mixture models","docAbstract":"Knowledge of demographic parameters such as survival, reproduction, emigration, and immigration is essential to understand metapopulation dynamics. Traditionally the estimation of these demographic parameters requires intensive data from marked animals. The development of dynamic N-mixture models makes it possible to estimate demographic parameters from count data of unmarked animals, but the original dynamic N-mixture model does not distinguish emigration and immigration from survival and reproduction, limiting its ability to explain important metapopulation processes such as movement among local populations. In this study we developed a spatially explicit dynamic N-mixture model that estimates survival, reproduction, emigration, local population size, and detection probability from count data under the assumption that movement only occurs among adjacent habitat patches. Simulation studies showed that the inference of our model depends on detection probability, local population size, and the implementation of robust sampling design. Our model provides reliable estimates of survival, reproduction, and emigration when detection probability is high, regardless of local population size or the type of sampling design. When detection probability is low, however, our model only provides reliable estimates of survival, reproduction, and emigration when local population size is moderate to high and robust sampling design is used. A sensitivity analysis showed that our model is robust against the violation of the assumption that movement only occurs among adjacent habitat patches, suggesting wide applications of this model. Our model can be used to improve our understanding of metapopulation dynamics based on count data that are relatively easy to collect in many systems.","language":"English","doi":"10.1007/s10144-017-0600-7","usgsCitation":"Zhao, Q., Royle, A., and Boomer, G., 2017, Spatially explicit dynamic N-mixture models: Population Ecology, v. 59, no. 4, p. 293-300, https://doi.org/10.1007/s10144-017-0600-7.","productDescription":"8 p.","startPage":"293","endPage":"300","ipdsId":"IP-090072","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":349425,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-20","publicationStatus":"PW","scienceBaseUri":"5a60faffe4b06e28e9c22ad4","contributors":{"authors":[{"text":"Zhao, Qing","contributorId":174370,"corporation":false,"usgs":false,"family":"Zhao","given":"Qing","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":723793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":723432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boomer, G. Scott","contributorId":84603,"corporation":false,"usgs":true,"family":"Boomer","given":"G. Scott","affiliations":[],"preferred":false,"id":723794,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70190241,"text":"70190241 - 2017 - Geologic characterization of the hydrocarbon resource potential of the Upper Cretaceous Tuscaloosa marine shale in Mississippi and Louisiana, U.S.A.","interactions":[],"lastModifiedDate":"2018-07-23T16:57:10","indexId":"70190241","displayToPublicDate":"2017-11-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Geologic characterization of the hydrocarbon resource potential of the Upper Cretaceous Tuscaloosa marine shale in Mississippi and Louisiana, U.S.A.","docAbstract":"Recent oil production from the Upper Cretaceous Tuscaloosa marine shale (TMS) has elevated the formation, previously assessed by the USGS in 2011 as part of the Eagle Ford Group, to its own distinct assessment unit for an upcoming assessment.  Geologic characterization in preparation for the 2017 assessment has included the analysis of rock samples and produced oils, and the interpretation of well logs and biostratigraphic data.  Results include new mapped extents of the reservoir, which reaches a maximum thickness of almost 500 feet in southern Mississippi and central Louisiana, and geochemical interpretations which support a self-sourced origin for  high gravity (36-48 API) low sulfur oil.  Programmed pyrolysis and petrography indicate the TMS contains dominantly Type III gas-prone kerogen with some Type II oil-prone kerogen present in the most organic-rich samples.  TMS samples contain an average of 47 weight percent total clays, had organic carbon content which ranged from 0.14 to 4.0 weight percent, and had a thermal maturity of 0.57 to 0.99 percent vitrinite reflectance in the productive area.  These characteristics were the same for the TMS within an area defined as a “high resistivity zone” and outside of it.  These results will be integral to the planned USGS assessment of the TMS.","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":" Gulf Coast Association of Geological Societies Transactions","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"67th annual GCAGS convention and 64th annual GCSSEPM meeting","conferenceDate":"November 1-3, 2017","conferenceLocation":"San Antonio, TX","language":"English","publisher":"Gulf Coast Association of Geological Societies","usgsCitation":"Enomoto, C.B., Hackley, P.C., Valentine, B.J., Rouse, W.A., Dulong, F.T., Lohr, C., and Hatcherian, J.J., 2017, Geologic characterization of the hydrocarbon resource potential of the Upper Cretaceous Tuscaloosa marine shale in Mississippi and Louisiana, U.S.A., <i>in</i>  Gulf Coast Association of Geological Societies Transactions, v. 67, San Antonio, TX, November 1-3, 2017, p. 95-109.","productDescription":"15 p.","startPage":"95","endPage":"109","ipdsId":"IP-085680","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":355938,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355937,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.gcags.org/exploreanddiscover/2017/00193_enomoto_et_al.pdf","text":"Index Page"}],"otherGeospatial":"Tuscaloosa Marine Shale","volume":"67","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc54ee4b0f5d57878eb0f","contributors":{"authors":[{"text":"Enomoto, Catherine B. 0000-0002-4119-1953 cenomoto@usgs.gov","orcid":"https://orcid.org/0000-0002-4119-1953","contributorId":2126,"corporation":false,"usgs":true,"family":"Enomoto","given":"Catherine","email":"cenomoto@usgs.gov","middleInitial":"B.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":708100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":708101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":708102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rouse, William A. 0000-0002-0790-370X wrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0790-370X","contributorId":4172,"corporation":false,"usgs":true,"family":"Rouse","given":"William","email":"wrouse@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":708103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dulong, Frank T. 0000-0001-7388-647X fdulong@usgs.gov","orcid":"https://orcid.org/0000-0001-7388-647X","contributorId":650,"corporation":false,"usgs":true,"family":"Dulong","given":"Frank","email":"fdulong@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":708104,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lohr, Celeste D. 0000-0001-6287-9047 clohr@usgs.gov","orcid":"https://orcid.org/0000-0001-6287-9047","contributorId":3866,"corporation":false,"usgs":true,"family":"Lohr","given":"Celeste D.","email":"clohr@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":708105,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":708106,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194137,"text":"70194137 - 2017 - Feral goats and sheep","interactions":[],"lastModifiedDate":"2018-01-03T13:07:11","indexId":"70194137","displayToPublicDate":"2017-11-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Feral goats and sheep","docAbstract":"<p>No abstract available.<br></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecology and management of terrestrial vertebrate invasive species in the United States","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","isbn":"9781498704823","usgsCitation":"Hess, S.C., Van Vuren, D.H., and Witmer, G.W., 2017, Feral goats and sheep, chap. <i>of</i> Ecology and management of terrestrial vertebrate invasive species in the United States, p. 287-307.","productDescription":"21 p.","startPage":"287","endPage":"307","ipdsId":"IP-074343","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":348942,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcpress.com/Ecology-and-Management-of-Terrestrial-Vertebrate-Invasive-Species-in-the/Pitt-Beasley-Witmer/p/book/9781498704823"},{"id":349309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb01e4b06e28e9c22aeb","contributors":{"editors":[{"text":"Pitt, William C.","contributorId":34355,"corporation":false,"usgs":false,"family":"Pitt","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":723397,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beasley, James","contributorId":172814,"corporation":false,"usgs":false,"family":"Beasley","given":"James","affiliations":[{"id":27094,"text":"University of Georgia, Savannah River Ecology Laboratory, Warnell School of Forestry and Natural Resources, PO Drawer E, Aiken, SC 29802","active":true,"usgs":false}],"preferred":false,"id":723398,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Witmer, Gary W.","contributorId":200434,"corporation":false,"usgs":false,"family":"Witmer","given":"Gary","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":723399,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Hess, Steve C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":150366,"corporation":false,"usgs":true,"family":"Hess","given":"Steve","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":722317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Vuren, Dirk H.","contributorId":200433,"corporation":false,"usgs":false,"family":"Van Vuren","given":"Dirk","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":722318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Witmer, Gary W.","contributorId":200434,"corporation":false,"usgs":false,"family":"Witmer","given":"Gary","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":722319,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194193,"text":"70194193 - 2017 - Concepts: Integrating population survey data from different spatial scales, sampling methods, and species","interactions":[],"lastModifiedDate":"2017-11-25T12:35:54","indexId":"70194193","displayToPublicDate":"2017-11-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Concepts: Integrating population survey data from different spatial scales, sampling methods, and species","docAbstract":"Conservationists and managers are continually under pressure from the public, the media, and political policy makers to provide “tiger numbers,” not just for protected reserves, but also for large spatial scales, including landscapes, regions, states, nations, and even globally. Estimating the abundance of tigers within relatively small areas (e.g., protected reserves) is becoming increasingly tractable (see Chaps. 9 and 10), but doing so for larger spatial scales still presents a formidable challenge. Those who seek “tiger numbers” are often not satisfied by estimates of tiger occupancy alone, regardless of the reliability of the estimates (see Chaps. 4 and 5). As a result, wherever tiger conservation efforts are underway, either substantially or nominally, scientists and managers are frequently asked to provide putative large-scale tiger numbers based either on a total count or on an extrapolation of some sort (see Chaps. 1 and 2).","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Methods for monitoring tiger and prey populations","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-981-10-5436-5_12","usgsCitation":"Dorazio, R., Delampady, M., Dey, S., and Gopalaswamy, A.M., 2017, Concepts: Integrating population survey data from different spatial scales, sampling methods, and species, chap. <i>of</i> Methods for monitoring tiger and prey populations, p. 247-254, https://doi.org/10.1007/978-981-10-5436-5_12.","productDescription":"8 p.","startPage":"247","endPage":"254","ipdsId":"IP-083543","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":349308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-28","publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ae8","contributors":{"editors":[{"text":"Karanth, K. Ullas","contributorId":192144,"corporation":false,"usgs":false,"family":"Karanth","given":"K.","email":"","middleInitial":"Ullas","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":723395,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Nichols, James D. jnichols@usgs.gov","contributorId":139087,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":723396,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Dorazio, Robert 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":172151,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":722588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Delampady, Mohan","contributorId":200532,"corporation":false,"usgs":false,"family":"Delampady","given":"Mohan","email":"","affiliations":[{"id":35775,"text":"Indian Statistical Institute, Bangalore, India","active":true,"usgs":false}],"preferred":false,"id":722589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dey, Soumen","contributorId":200534,"corporation":false,"usgs":false,"family":"Dey","given":"Soumen","email":"","affiliations":[{"id":35775,"text":"Indian Statistical Institute, Bangalore, India","active":true,"usgs":false}],"preferred":false,"id":722591,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gopalaswamy, Arjun M.","contributorId":199394,"corporation":false,"usgs":false,"family":"Gopalaswamy","given":"Arjun","email":"","middleInitial":"M.","affiliations":[{"id":20302,"text":"Univeristy of Oxford","active":true,"usgs":false},{"id":35775,"text":"Indian Statistical Institute, Bangalore, India","active":true,"usgs":false}],"preferred":false,"id":722592,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70194008,"text":"70194008 - 2017 - Advancing mangrove macroecology","interactions":[],"lastModifiedDate":"2017-11-25T12:53:09","indexId":"70194008","displayToPublicDate":"2017-11-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"11","title":"Advancing mangrove macroecology","docAbstract":"Mangrove forests provide a wide range of ecosystem services to society, yet they are among the most anthropogenically impacted coastal ecosystems in the world. In this chapter, we discuss and provide examples for how macroecology can advance our understanding of mangrove ecosystems. Macroecology is broadly defined as a discipline that uses statistical analyses to investigate large-scale, universal patterns in the distribution, abundance, diversity, and organization of species and ecosystems, including the scaling of ecological processes and structural and functional relationships. Macroecological methods can be used to advance our understanding of how non-linear responses in natural systems can be triggered by human impacts at local, regional, and global scales. Although macroecology has the potential to gain knowledge on universal patterns and processes that govern mangrove ecosystems, the application of macroecological methods to mangroves has historically been limited by constraints in data quality and availability. Here we provide examples that include evaluations of the variation in mangrove forest ecosystem structure and function in relation to macroclimatic drivers (e.g., temperature and rainfall regimes) and climate change. Additional examples include work focused upon the continental distribution of aboveground net primary productivity and carbon storage, which are rapidly advancing research areas. These examples demonstrate the value of a macroecological perspective for the understanding of global- and regional-scale effects of both changing environmental conditions and management actions on ecosystem structure, function, and the supply of goods and services. We also present current trends in mangrove modeling approaches and their potential utility to test hypotheses about mangrove structural and functional properties. Given the gap in relevant experimental work at the regional scale, we also discuss the potential use of mangrove restoration and rehabilitation projects as macroecological studies that advance the critical selection and conservation of ecosystem services when managing mangrove resources. Future work to further incorporate macroecology into mangrove research will require a concerted effort by research groups and institutions to launch research initiatives and synthesize data collected across broad biogeographic regions.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mangrove ecosystems: A global biogeographic perspective","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-62206-4_11","isbn":"978-3-319-62204-0","usgsCitation":"Rivera-Monroy, V.H., Osland, M.J., Day, J.W., Ray, S., Rovai, A.S., Day, R.H., and Mukherjee, J., 2017, Advancing mangrove macroecology, chap. 11 <i>of</i> Mangrove ecosystems: A global biogeographic perspective, p. 347-381, https://doi.org/10.1007/978-3-319-62206-4_11.","productDescription":"35 p.","startPage":"347","endPage":"381","ipdsId":"IP-086590","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":349310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-04","publicationStatus":"PW","scienceBaseUri":"5a60fb01e4b06e28e9c22aed","contributors":{"editors":[{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":723400,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lee, Shing Yip","contributorId":39694,"corporation":false,"usgs":false,"family":"Lee","given":"Shing","email":"","middleInitial":"Yip","affiliations":[{"id":13193,"text":"School of Environment, Griffith University","active":true,"usgs":false}],"preferred":false,"id":723401,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Kristensen, Erik","contributorId":24034,"corporation":false,"usgs":false,"family":"Kristensen","given":"Erik","email":"","affiliations":[{"id":35818,"text":"University of Southern Denmark","active":true,"usgs":false}],"preferred":false,"id":723402,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Twilley, Robert R.","contributorId":34585,"corporation":false,"usgs":false,"family":"Twilley","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":723403,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":721915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":721914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day, John W.","contributorId":200323,"corporation":false,"usgs":false,"family":"Day","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":721916,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ray, Santanu","contributorId":200324,"corporation":false,"usgs":false,"family":"Ray","given":"Santanu","email":"","affiliations":[{"id":35743,"text":"Visva-Bharati University","active":true,"usgs":false}],"preferred":false,"id":721917,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rovai, Andre S.","contributorId":167671,"corporation":false,"usgs":false,"family":"Rovai","given":"Andre","email":"","middleInitial":"S.","affiliations":[{"id":24801,"text":"Federal University of Santa Catarina, Dept. Ecology and Zoology, Brazil","active":true,"usgs":false}],"preferred":false,"id":721918,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Day, Richard H. 0000-0002-5959-7054 dayr@usgs.gov","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":2427,"corporation":false,"usgs":true,"family":"Day","given":"Richard","email":"dayr@usgs.gov","middleInitial":"H.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":721919,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mukherjee, Joyita","contributorId":200325,"corporation":false,"usgs":false,"family":"Mukherjee","given":"Joyita","email":"","affiliations":[{"id":35743,"text":"Visva-Bharati University","active":true,"usgs":false}],"preferred":false,"id":721920,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70236753,"text":"70236753 - 2017 - Discriminating between natural vs induced seismicity from long-term deformation history of intraplate faults","interactions":[],"lastModifiedDate":"2022-09-19T15:19:31.845284","indexId":"70236753","displayToPublicDate":"2017-11-24T10:08:28","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Discriminating between natural vs induced seismicity from long-term deformation history of intraplate faults","docAbstract":"To assess whether recent seismicity is induced by human activity or is of natural origin, we analyze fault displacements on high-resolution seismic reflection profiles for two regions in the central United States (CUS): the Fort Worth Basin (FWB) of Texas, and the northern Mississippi embayment (NME). Since 2009 earthquake activity in the CUS has increased dramatically, and numerous publications suggest that this increase is primarily due to induced earthquakes caused by deep-well injection of wastewater, both flowback water from hydrofracturing operations and produced water accompanying hydrocarbon production. Alternatively, some argue that these earthquakes are natural, and that the seismicity increase is a normal variation that occurs over millions of years. Our analysis shows that within the NME, faults deform both Quaternary alluvium and underlying sediments dating from Paleozoic through Tertiary, with displacement increasing with geologic unit age, documenting a long history of natural activity. In the FWB, a region of ongoing wastewater injection, basement faults show deformation of the Proterozoic and Paleozoic units, but little or no deformation of younger strata. Specifically, vertical displacements in the post-Pennsylvanian formations, if any, are below the resolution (~15 m) of the seismic data, far less than expected had these faults accumulated deformation over millions of years. Our results support the assertion that recent FWB earthquakes are of induced origin; this conclusion is entirely independent of analyses correlating seismicity and wastewater injection practices. To our knowledge this is the first study to discriminate natural and induced seismicity using classical structural geology analysis techniques.","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.1701593","usgsCitation":"Magnani, M.B., Blanpied, M.L., DeShon, H.R., and Hornbach, M., 2017, Discriminating between natural vs induced seismicity from long-term deformation history of intraplate faults: Science Advances, v. 3, no. 11, e1701593, 12 p., https://doi.org/10.1126/sciadv.1701593.","productDescription":"e1701593, 12 p.","ipdsId":"IP-090248","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"links":[{"id":469300,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.1701593","text":"Publisher Index Page"},{"id":406969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70188289,"text":"ofr20171052 - 2017 - Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina","interactions":[],"lastModifiedDate":"2024-03-04T18:57:59.926401","indexId":"ofr20171052","displayToPublicDate":"2017-11-22T07:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1052","title":"Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina","docAbstract":"<p>Mattamuskeet National Wildlife Refuge (MNWR) offers a mix of open water, marsh, forest, and cropland habitats on 20,307 hectares in coastal North Carolina. In 1934, Federal legislation (Executive Order 6924) established MNWR to benefit wintering waterfowl and other migratory bird species. On an annual basis, the refuge staff decide how to manage 14 impoundments to benefit not only waterfowl during the nonbreeding season, but also shorebirds during fall and spring migration. In making these decisions, the challenge is to select a portfolio, or collection, of management actions for the impoundments that optimizes use by the three groups of birds while respecting budget constraints. In this study, a decision support tool was developed for these annual management decisions.</p><p>Within the decision framework, there are three different management objectives: shorebird-use days during fall and spring migrations, and waterfowl-use days during the nonbreeding season. Sixteen potential management actions were identified for impoundments; each action represents a combination of hydroperiod and vegetation manipulation. Example hydroperiods include semi-permanent and seasonal drawdowns, and vegetation manipulations include mechanical-chemical treatment, burning, disking, and no action. Expert elicitation was used to build a Bayesian Belief Network (BBN) model that predicts shorebird- and waterfowl-use days for each potential management action. The BBN was parameterized for a representative impoundment, MI-9, and predictions were re-scaled for this impoundment to predict outcomes at other impoundments on the basis of size. Parameter estimates in the BBN model can be updated using observations from ongoing monitoring that is part of the Integrated Waterbird Management and Monitoring (IWMM) program.</p><p>The optimal portfolio of management actions depends on the importance, that is, weights, assigned to the three objectives, as well as the budget. Five scenarios with a variety of objective weights and budgets were developed. Given the large number of possible portfolios (16<sup>14</sup>), a heuristic genetic algorithm was used to identify a management action portfolio that maximized use-day objectives while respecting budget constraints. The genetic algorithm identified a portfolio of management actions for each of the five scenarios, enabling refuge staff to explore the sensitivity of their management decisions to objective weights and budget constraints.</p><p>The decision framework developed here provides a transparent, defensible, and testable foundation for decision making at MNWR. The BBN model explicitly structures and parameterizes a mental model previously used by an expert to assign management actions to the impoundments. With ongoing IWMM monitoring, predictions from the model can be tested, and model parameters updated, to reflect empirical observations. This framework is intended to be a living document that can be updated to reflect changes in the decision context (for example, new objectives or constraints, or new models to compete with the current BBN model). Rather than a mandate to refuge staff, this framework is intended to be a decision support tool; tool outputs can become part of the deliberations of refuge staff when making difficult management decisions for multiple objectives.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171052","usgsCitation":"Tavernia, B.G., Stanton, J.D., and Lyons, J.E., 2017, Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina: U.S. Geological Survey Open-File Report 2017–1052, 43 p., https://doi.org/10.3133/ofr20171052.","productDescription":"vii, 43 p.","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074603","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":348384,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1052/coverthb.jpg"},{"id":348385,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1052/ofr20171052.pdf","text":"Report","size":"9.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1052"}],"country":"United States","state":"North Carolina","otherGeospatial":"Mattamuskeet National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.36459350585938,\n              35.42262976362149\n            ],\n            [\n              -76.03363037109374,\n              35.42262976362149\n            ],\n            [\n              -76.03363037109374,\n              35.59031875398378\n            ],\n            [\n              -76.36459350585938,\n              35.59031875398378\n            ],\n            [\n              -76.36459350585938,\n              35.42262976362149\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eesc\" data-mce-href=\"https://www.usgs.gov/centers/eesc\">Eastern Ecological Science Center</a><br>U.S. Geological Survey <br>12100 Beech Forest Road, Ste 4039<br>Laurel, MD 20708</p>","tableOfContents":"<ul><li>Abstract&nbsp;</li><li>Introduction</li><li>Purpose and Scope</li><li>Objectives</li><li>Alternatives</li><li>Predictive Models</li><li>Tradeoffs Using Portfolio Analysis</li><li>Future Changes to the Decision Framework</li><li>References Cited</li><li>Appendix 1.&nbsp;Glossary of Hydroperiod Terms</li><li>Appendix 2.&nbsp;Waterfowl Habitat Modeling</li><li>Appendix 3. Building Predictive Models with Expert Judgment&nbsp;</li><li>Appendix 4.&nbsp;Expert Elicitation of Conditional Probability Tables</li><li>Appendix 5.&nbsp;Bird-Use Day Estimates</li><li>Appendix 6.&nbsp;Genetic Algorithm Approach to Portfolio Analysis&nbsp;</li><li>Appendix 7.&nbsp;Management Action Costs</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2017-11-22","noUsgsAuthors":false,"publicationDate":"2017-11-22","publicationStatus":"PW","scienceBaseUri":"5a60fb01e4b06e28e9c22af0","contributors":{"authors":[{"text":"Tavernia, Brian G. btavernia@usgs.gov","contributorId":5876,"corporation":false,"usgs":true,"family":"Tavernia","given":"Brian G.","email":"btavernia@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":720952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanton, John D.","contributorId":145798,"corporation":false,"usgs":false,"family":"Stanton","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":720953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, James E. 0000-0002-9810-8751 jelyons@usgs.gov","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":177546,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"jelyons@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":697140,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192099,"text":"sir20175126 - 2017 - Macroinvertebrate communities evaluated prior to and following a channel restoration project in Silver Creek, Blaine County, Idaho, 2001-16","interactions":[],"lastModifiedDate":"2017-11-28T12:27:48","indexId":"sir20175126","displayToPublicDate":"2017-11-22T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5126","title":"Macroinvertebrate communities evaluated prior to and following a channel restoration project in Silver Creek, Blaine County, Idaho, 2001-16","docAbstract":"<p class=\"p1\">The U.S. Geological Survey, in cooperation with Blaine County and The Nature Conservancy, evaluated the status of macroinvertebrate communities prior to and following a channel restoration project in Silver Creek, Blaine County, Idaho. The objective of the evaluation was to determine whether 2014 remediation efforts to restore natural channel conditions in an impounded area of Silver Creek caused declines in local macroinvertebrate communities. Starting in 2001 and ending in 2016, macroinvertebrates were sampled every 3 years at two long-term trend sites and sampled seasonally (spring, summer, and autumn) in 2013, 2015, and 2016 at seven synoptic sites. Trend-site communities were collected from natural stream-bottom substrates to represent locally established macroinvertebrate assemblages. Synoptic site communities were sampled using artificial (multi-plate) substrates to represent recently colonized (4–6 weeks) assemblages. Statistical summaries of spatial and temporal patterns in macroinvertebrate taxonomic composition at both trend and synoptic sites were completed.</p><p class=\"p1\">The potential effect of the restoration project on resident macroinvertebrate populations was determined by comparing the following community assemblage metrics:</p><ol class=\"ol1\"><li class=\"li2\">Total taxonomic richness (taxa richness);</li><li class=\"li2\">Total macroinvertebrate abundance (total abundance);</li><li class=\"li2\">Ephemeroptera, Plecoptera, Trichoptera (EPT) richness;</li><li class=\"li2\">EPT abundance;</li><li class=\"li2\">Simpson’s diversity; and</li><li class=\"li3\">Simpson’s evenness for periods prior to and following restoration.</li></ol><p class=\"p5\">A significant decrease in one or more metric values in the period following stream channel restoration was the basis for determining impairment to the macroinvertebrate communities in Silver Creek.</p><p class=\"p5\">Comparison of pre-restoration (2001–13) and post‑restoration (2016) macroinvertebrate community composition at trend sites determined that no significant decreases occurred in any metric parameter for communities sampled in 2016. Taxa and EPT richness of colonized assemblages at synoptic sites increased significantly from pre-restoration in 2013 to post-restoration in 2015 and 2016. Similarly, total and EPT abundances at synoptic sites showed non-significant increases from 2013 to 2015 and 2016. Significant seasonal differences in macroinvertebrate assemblages were apparent at synoptic site locations and likely reflected typical life-history patterns of increased insect emergence and development in the late spring and early summer months. Taxa and EPT richness were each significantly higher in spring and summer than in autumn, and total abundances were significantly higher in spring than in summer and autumn. No significant differences in community diversity or evenness of colonized communities were noted at synoptic site locations between pre- and post-restoration years or among seasons. Select community-metric results from the trend- and synoptic<span class=\"s2\">‑</span>site sampling indicated that the Silver Creek restoration effort in 2014 did not result in a significant decline in resident macroinvertebrate communities.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175126","collaboration":"Prepared in cooperation with Blaine County and The Nature Conservancy","usgsCitation":"MacCoy, D.E., and Short, T.M., Macroinvertebrate communities evaluated prior to and following a channel restoration project in Silver Creek, Blaine County, Idaho, 2001-16: U.S. Geological Survey Scientific Investigations Report 2017-5126, 25 p., https://doi.org/10.3133/sir20175126.","productDescription":"Report: vi, 25 p.; Appendixes A-B","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-046209","costCenters":[{"id":343,"text":"Idaho Water Science 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href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, <a href=\"http://id.water.usgs.gov\" target=\"blank\" data-mce-href=\"http://id.water.usgs.gov\">Idaho Water Science Center</a><br> U.S. Geological Survey<br> 230 Collins Road Boise, Idaho 83702</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Hydrology, Water Quality, and Macroinvertebrates at Trend and Synoptic Sites<br></li><li>Hydrology, Water Quality, and Macroinvertebrate Evaluation<br></li><li>Summary and Conclusions<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendixes A–B<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-11-22","noUsgsAuthors":false,"publicationDate":"2017-11-22","publicationStatus":"PW","scienceBaseUri":"5a60fb01e4b06e28e9c22afd","contributors":{"authors":[{"text":"MacCoy, Dorene E. 0000-0001-6810-4728 demaccoy@usgs.gov","orcid":"https://orcid.org/0000-0001-6810-4728","contributorId":948,"corporation":false,"usgs":true,"family":"MacCoy","given":"Dorene","email":"demaccoy@usgs.gov","middleInitial":"E.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Short, Terry M. 0000-0001-9941-4593 tmshort@usgs.gov","orcid":"https://orcid.org/0000-0001-9941-4593","contributorId":1718,"corporation":false,"usgs":true,"family":"Short","given":"Terry","email":"tmshort@usgs.gov","middleInitial":"M.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":714229,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70194265,"text":"70194265 - 2017 - Imaging shear strength along subduction faults","interactions":[],"lastModifiedDate":"2018-01-05T13:57:56","indexId":"70194265","displayToPublicDate":"2017-11-22T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Imaging shear strength along subduction faults","docAbstract":"<p><span>Subduction faults accumulate stress during long periods of time and release this stress suddenly, during earthquakes, when it reaches a threshold. This threshold, the shear strength, controls the occurrence and magnitude of earthquakes. We consider a 3-D model to derive an analytical expression for how the shear strength depends on the fault geometry, the convergence obliquity, frictional properties, and the stress field orientation. We then use estimates of these different parameters in Japan to infer the distribution of shear strength along a subduction fault. We show that the 2011&nbsp;</span><i>M</i><sub><i>w</i></sub><span>9.0 Tohoku earthquake ruptured a fault portion characterized by unusually small variations in static shear strength. This observation is consistent with the hypothesis that large earthquakes preferentially rupture regions with relatively homogeneous shear strength. With increasing constraints on the different parameters at play, our approach could, in the future, help identify favorable locations for large earthquakes.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2017GL075501","usgsCitation":"Bletery, Q., Thomas, A.M., Rempel, A.W., and Hardebeck, J.L., 2017, Imaging shear strength along subduction faults: Geophysical Research Letters, v. 44, no. 22, p. 11329-11339, https://doi.org/10.1002/2017GL075501.","productDescription":"11 p.","startPage":"11329","endPage":"11339","ipdsId":"IP-088563","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469302,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gl075501","text":"Publisher Index Page"},{"id":349290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"22","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-18","publicationStatus":"PW","scienceBaseUri":"5a60fb01e4b06e28e9c22afb","contributors":{"authors":[{"text":"Bletery, Quentin","contributorId":200640,"corporation":false,"usgs":false,"family":"Bletery","given":"Quentin","email":"","affiliations":[],"preferred":false,"id":722955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Amanda M.","contributorId":200641,"corporation":false,"usgs":false,"family":"Thomas","given":"Amanda","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":722956,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rempel, Alan W.","contributorId":200642,"corporation":false,"usgs":false,"family":"Rempel","given":"Alan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":722957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":722954,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70194319,"text":"70194319 - 2017 - Wildlife governance in the 21st century—Will sustainable use endure?","interactions":[],"lastModifiedDate":"2018-01-05T13:59:54","indexId":"70194319","displayToPublicDate":"2017-11-22T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Wildlife governance in the 21st century—Will sustainable use endure?","docAbstract":"<p><span>In light of the trajectory of wildlife governance in the United States, the future of sustainable use of wildlife is a topic of substantial interest in the wildlife conservation community. We examine sustainable-use principles with respect to “good governance” considerations and public trust administration principles to assess how sustainable use might fare in the 21st century. We conclude that sustainable-use principles are compatible with recently articulated wildlife governance principles and could serve to mitigate broad values and norm shifts in American society that affect social acceptability of particular uses. Wildlife governance principles emphasize inclusive discourse among diverse wildlife interests, which could minimize isolated exchanges among cliques of like-minded people pursuing their ambitions without seeking opportunity for sharing or understanding diverse views. Aligning governance practices with wildlife governance principles can help avoid such isolation. In summary, sustainable use of wildlife is likely to endure as long as society 1) believes the long-term sustainability of wildlife is not jeopardized, and 2) accepts practices associated with such use as legitimate. These are 2 criteria needing constant attention.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/wsb.830","usgsCitation":"Decker, D.J., Organ, J.F., Forstchen, A., Jacobson, C.A., Siemer, W.F., Smith, C.A., Lederle, P.E., and Schiavone, M.V., 2017, Wildlife governance in the 21st century—Will sustainable use endure?: Wildlife Society Bulletin, v. 41, no. 4, p. 821-826, https://doi.org/10.1002/wsb.830.","productDescription":"6 p.","startPage":"821","endPage":"826","ipdsId":"IP-082502","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500043,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/1420e061002e4e428616d6877820f1fd","text":"External Repository"},{"id":349266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-15","publicationStatus":"PW","scienceBaseUri":"5a60fb01e4b06e28e9c22af7","contributors":{"authors":[{"text":"Decker, Daniel J.","contributorId":114044,"corporation":false,"usgs":true,"family":"Decker","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":723283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Organ, John F. 0000-0002-0959-0639 jorgan@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-0639","contributorId":189047,"corporation":false,"usgs":true,"family":"Organ","given":"John","email":"jorgan@usgs.gov","middleInitial":"F.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":723268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forstchen, Ann","contributorId":166904,"corporation":false,"usgs":false,"family":"Forstchen","given":"Ann","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":723284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacobson, Cynthia A.","contributorId":200767,"corporation":false,"usgs":false,"family":"Jacobson","given":"Cynthia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":723285,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Siemer, William F.","contributorId":192551,"corporation":false,"usgs":false,"family":"Siemer","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":723286,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Christian A.","contributorId":200768,"corporation":false,"usgs":false,"family":"Smith","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":723287,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lederle, Patrick E.","contributorId":200769,"corporation":false,"usgs":false,"family":"Lederle","given":"Patrick","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":723288,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schiavone, Michael V.","contributorId":30064,"corporation":false,"usgs":false,"family":"Schiavone","given":"Michael","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":723289,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70170194,"text":"pp1824X - 2017 - Geology and assessment of undiscovered oil and gas resources of the Zyryanka Basin Province, 2008","interactions":[{"subject":{"id":70170194,"text":"pp1824X - 2017 - Geology and assessment of undiscovered oil and gas resources of the Zyryanka Basin Province, 2008","indexId":"pp1824X","publicationYear":"2017","noYear":false,"chapter":"X","title":"Geology and assessment of undiscovered oil and gas resources of the Zyryanka Basin Province, 2008"},"predicate":"IS_PART_OF","object":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"id":1}],"isPartOf":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"lastModifiedDate":"2024-06-26T13:56:40.207223","indexId":"pp1824X","displayToPublicDate":"2017-11-22T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1824","chapter":"X","title":"Geology and assessment of undiscovered oil and gas resources of the Zyryanka Basin Province, 2008","docAbstract":"<p><span>The U.S. Geological Survey (USGS) recently assessed the potential for undiscovered oil and gas resources of the Zyryanka Basin Province as part of the 2008 USGS Circum-Arctic Resource Appraisal program. The province is in the Russian Federation and is situated on the Omolon superterrane of the Kolyma block. The one assessment unit (AU) that was defined for this study, called the Zyryanka Basin AU, which coincides with the province, was assessed for undiscovered, technically recoverable, conventional resources. The estimated mean volumes of undiscovered resources in the Zyryanka Basin Province are ~72 million barrels of crude oil, 2,282 billion cubic feet of natural gas, and 61 million barrels of natural-gas liquids. About 66 percent of the study area and undiscovered petroleum resources are north of the Arctic Circle.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824X","usgsCitation":"Klett, T.R., and Pitman, J.K., 2017, Geology and assessment of undiscovered oil and gas resources of the Zyryanka Basin Province, 2008, chap. X <i>of</i> Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 11 p., https://doi.org/10.3133/pp1824X.","productDescription":"Report: vi, 11 p.; Appendix","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-050992","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":349289,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/x/pp1824x_appx.xls","text":"Appendix 1","size":"50 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter X","linkHelpText":"- Input Data for the Zyryanka Basin Assessment Unit"},{"id":349287,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/x/coverthb.jpg"},{"id":349288,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/x/pp1824_x.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter X"}],"country":"Russia","otherGeospatial":"Zyryanka Basin Province","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              142,\n              64\n            ],\n            [\n              153,\n              64\n            ],\n            [\n              153,\n              69\n            ],\n            [\n              142,\n              69\n            ],\n            [\n              142,\n              64\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg/employee-directory\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg/employee-directory\">Contact Information</a>,&nbsp;<a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center—Menlo Park</a><br><a href=\"https://usgs.gov\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>345 Middlefield Road<br>Menlo Park, CA 94025-3591<br>FAX 650-329-4936</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Zyryanka Basin Province<br></li><li>Petroleum Occurrence<br></li><li>Tectono-Stratigraphic Evolution<br></li><li>Petroleum-System Elements<br></li><li>Assessment Unit<br></li><li>Assessment Results<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-11-22","noUsgsAuthors":false,"publicationDate":"2017-11-22","publicationStatus":"PW","scienceBaseUri":"5a60fb02e4b06e28e9c22b00","contributors":{"editors":[{"text":"Moore, Thomas E. 0000-0002-0878-0457","orcid":"https://orcid.org/0000-0002-0878-0457","contributorId":85592,"corporation":false,"usgs":true,"family":"Moore","given":"Thomas E.","affiliations":[],"preferred":false,"id":723336,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Gautier, D. L.","contributorId":69996,"corporation":false,"usgs":true,"family":"Gautier","given":"D.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723337,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Klett, Timothy R. 0000-0001-9779-1168 tklett@usgs.gov","orcid":"https://orcid.org/0000-0001-9779-1168","contributorId":150416,"corporation":false,"usgs":true,"family":"Klett","given":"Timothy","email":"tklett@usgs.gov","middleInitial":"R.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":626354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":626355,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170191,"text":"pp1824V - 2017 - Geology and assessment of undiscovered oil and gas resources of the Lena-Vilyui Basin Province, 2008","interactions":[{"subject":{"id":70170191,"text":"pp1824V - 2017 - Geology and assessment of undiscovered oil and gas resources of the Lena-Vilyui Basin Province, 2008","indexId":"pp1824V","publicationYear":"2017","noYear":false,"chapter":"V","title":"Geology and assessment of undiscovered oil and gas resources of the Lena-Vilyui Basin Province, 2008"},"predicate":"IS_PART_OF","object":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"id":1}],"isPartOf":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"lastModifiedDate":"2024-06-26T14:03:27.382883","indexId":"pp1824V","displayToPublicDate":"2017-11-22T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1824","chapter":"V","title":"Geology and assessment of undiscovered oil and gas resources of the Lena-Vilyui Basin Province, 2008","docAbstract":"<p><span>The U.S. Geological Survey (USGS) recently assessed the potential for undiscovered oil and gas resources of the Lena-Vilyui Basin Province, north of the Arctic Circle, as part of the Circum-Arctic Resource Appraisal program. The province is in the Russian Federation and is situated between the Verkhoyansk fold-and-thrust belt and the Siberian craton. The one assessment unit (AU) defined for this study—the Northern Priverkhoyansk Foredeep AU—was assessed for undiscovered, technically recoverable resources. The estimated mean volumes of undiscovered resources for the Northern Priverkhoyansk Foredeep in the Lena-Vilyui Basin Province are ~400 million barrels of crude oil, 1.3 trillion cubic feet of natural gas, and 40 million barrels of natural-gas liquids, practically all (99.49 percent) of which is north of the Arctic Circle.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824V","usgsCitation":"Klett, T.R., and Pitman, J.K., 2017, Geology and assessment of undiscovered oil and gas resources of the Lena-Vilyui Basin Province, 2008, chap. V <i>of</i> Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 17 p., https://doi.org/10.3133/pp1824V.","productDescription":"Report: vii, 17 p.; Appendix","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-050989","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":349279,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/v/coverthb.jpg"},{"id":349292,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/v/pp1824v_appx.xls","text":"Appendix 1","size":"49 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter V","linkHelpText":"- Input Data for the Northern Priverkhoyansk Foredeep Assessment Unit"},{"id":349280,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/v/pp1824v.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter V"}],"country":"Russia","otherGeospatial":"Lena-Vilyui Basin Province","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              119.5,\n              62\n            ],\n            [\n              138,\n              62\n            ],\n            [\n              138,\n              72\n            ],\n            [\n              119.5,\n              72\n            ],\n            [\n              119.5,\n              62\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg/employee-directory\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg/employee-directory\">Contact Information</a>,&nbsp;<a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center—Menlo Park</a><br><a href=\"https://usgs.gov\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>345 Middlefield Road<br>Menlo Park, CA 94025-3591<br>FAX 650-329-4936</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Province Description<br></li><li>Petroleum Occurrence<br></li><li>Tectonostratigraphic Evolution<br></li><li>Petroleum-System Elements<br></li><li>Assessment Units<br></li><li>Northern Priverkhoyansk Foredeep Assessment Unit<br></li><li>Assessment Results<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-11-22","noUsgsAuthors":false,"publicationDate":"2017-11-22","publicationStatus":"PW","scienceBaseUri":"5a60fb02e4b06e28e9c22b02","contributors":{"editors":[{"text":"Moore, Thomas E. 0000-0002-0878-0457","orcid":"https://orcid.org/0000-0002-0878-0457","contributorId":85592,"corporation":false,"usgs":true,"family":"Moore","given":"Thomas E.","affiliations":[],"preferred":false,"id":723322,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Gautier, D. L.","contributorId":69996,"corporation":false,"usgs":true,"family":"Gautier","given":"D.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723323,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Klett, Timothy R. 0000-0001-9779-1168 tklett@usgs.gov","orcid":"https://orcid.org/0000-0001-9779-1168","contributorId":150416,"corporation":false,"usgs":true,"family":"Klett","given":"Timothy","email":"tklett@usgs.gov","middleInitial":"R.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":626348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":626349,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70199762,"text":"70199762 - 2017 - Estimating discharge and nonpoint source nitrate loading to streams from three end‐member pathways using high‐frequency water quality data","interactions":[],"lastModifiedDate":"2018-09-27T14:15:17","indexId":"70199762","displayToPublicDate":"2017-11-21T13:34:20","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimating discharge and nonpoint source nitrate loading to streams from three end‐member pathways using high‐frequency water quality data","docAbstract":"<p><span>The myriad hydrologic and biogeochemical processes taking place in watersheds occurring across space and time are integrated and reflected in the quantity and quality of water in streams and rivers. Collection of high‐frequency water quality data with sensors in surface waters provides new opportunities to disentangle these processes and quantify sources and transport of water and solutes in the coupled groundwater‐surface water system. A new approach for separating the streamflow hydrograph into three components was developed and coupled with high‐frequency nitrate data to estimate time‐variable nitrate loads from chemically dilute quick flow, chemically concentrated quick flow, and slowflow groundwater end‐member pathways for periods of up to 2 years in a groundwater‐dominated and a quick‐flow‐dominated stream in central Wisconsin, using only streamflow and in‐stream water quality data. The dilute and concentrated quick flow end‐members were distinguished using high‐frequency specific conductance data. Results indicate that dilute quick flow contributed less than 5% of the nitrate load at both sites, whereas 89 ± 8% of the nitrate load at the groundwater‐dominated stream was from slowflow groundwater, and 84 ± 25% of the nitrate load at the quick‐flow‐dominated stream was from concentrated quick flow. Concentrated quick flow nitrate concentrations varied seasonally at both sites, with peak concentrations in the winter that were 2–3 times greater than minimum concentrations during the growing season. Application of this approach provides an opportunity to assess stream vulnerability to nonpoint source nitrate loading and expected stream responses to current or changing conditions and practices in watersheds.</span></p>","language":"English ","publisher":"American Geophysical Union","doi":"10.1002/2017WR021654","usgsCitation":"Miller, M.P., Tesoriero, A.J., Hood, K., Terziotti, S., and Wolock, D.M., 2017, Estimating discharge and nonpoint source nitrate loading to streams from three end‐member pathways using high‐frequency water quality data: Water Resources Research, v. 53, no. 12, p. 10201-10216, https://doi.org/10.1002/2017WR021654.","productDescription":"16 p.","startPage":"10201","endPage":"10216","ipdsId":"IP-091844","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"links":[{"id":469303,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr021654","text":"Publisher Index Page"},{"id":357845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"12","noUsgsAuthors":false,"publicationDate":"2017-12-07","publicationStatus":"PW","scienceBaseUri":"5bc030a6e4b0fc368eb53a0a","contributors":{"authors":[{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tesoriero, Anthony J. 0000-0003-4674-7364 tesorier@usgs.gov","orcid":"https://orcid.org/0000-0003-4674-7364","contributorId":2693,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony","email":"tesorier@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hood, Krista","contributorId":208243,"corporation":false,"usgs":false,"family":"Hood","given":"Krista","email":"","affiliations":[],"preferred":false,"id":746521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Terziotti, Silvia 0000-0003-3559-5844 seterzio@usgs.gov","orcid":"https://orcid.org/0000-0003-3559-5844","contributorId":1613,"corporation":false,"usgs":true,"family":"Terziotti","given":"Silvia","email":"seterzio@usgs.gov","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":746523,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70191222,"text":"sir20175119 - 2017 - The U.S. Geological Survey Peak-Flow File Data Verification Project, 2008–16","interactions":[],"lastModifiedDate":"2017-11-21T15:57:28","indexId":"sir20175119","displayToPublicDate":"2017-11-21T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5119","title":"The U.S. Geological Survey Peak-Flow File Data Verification Project, 2008–16","docAbstract":"<p>Annual peak streamflow (peak flow) at a streamgage is defined as the maximum instantaneous flow in a water year. A water year begins on October 1 and continues through September 30 of the following year; for example, water year 2015 extends from October 1, 2014, through September 30, 2015. The accuracy, characterization, and completeness of the peak streamflow data are critical in determining flood-frequency estimates that are used daily to design water and transportation infrastructure, delineate flood-plain boundaries, and regulate development and utilization of lands throughout the United States and are essential to understanding the implications of climate and land-use change on flooding and high-flow conditions.</p><p>As of November 14, 2016, peak-flow data existed for 27,240 unique streamgages in the United States and its territories. The data, collectively referred to as the “peak-flow file,” are available as part of the U.S. Geological Survey (USGS) public web interface, the National Water Information System, at <a href=\"https://nwis.waterdata.usgs.gov/usa/nwis/peak\" data-mce-href=\"https://nwis.waterdata.usgs.gov/usa/nwis/peak\">https://nwis.waterdata.usgs.gov/usa/nwis/peak</a>. Although the data have been routinely subjected to periodic review by the USGS Office of Surface Water and screening at the USGS Water Science Center level, these data were not reviewed in a national, systematic manner until 2008 when automated scripts were developed and applied to detect potential errors in peak-flow values and their associated dates, gage heights, and peak-flow qualification codes, as well as qualification codes associated with the gage heights. USGS scientists and hydrographers studied the resulting output, accessed basic records and field notes, and corrected observed errors or, more commonly, confirmed existing data as correct.</p><p>This report summarizes the changes in peak-flow file data at a national level, illustrates their nature and causation, and identifies the streamgages affected by these changes. Specifically, the peak-flow data were compared for streamgages with peak flow measured as of November 19, 2008 (before the automated scripts were widely applied) and on November 14, 2016 (after several rounds of corrections). There were 659,332 peak-flow values in the 2008 dataset and 731,965 peak-flow values in the 2016 dataset. When compared to the 2016 dataset, 5,179 (0.79 percent) peak-flow values had changed; 36,506 (5.54 percent) of the peak-flow qualification codes had changed; 1,938 (0.29 percent) peak-flow dates had changed; 18,599 (2.82 percent) of the peak-flow gage heights had changed; and 20,683 (3.14 percent) of the gage-height qualification codes had changed—most as a direct result of the peak-flow file data verification effort led by USGS personnel. The various types of changes are summarized and mapped in this report. In addition to this report, a corresponding USGS data release is provided to identify changes in peak flows at individual streamgages. The data release and the procedures to access the data release are described in this report.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175119","usgsCitation":"Ryberg, K.R., Goree, B.B., Williams-Sether, Tara, and Mason, R.R., Jr., 2017, The U.S. Geological Survey Peak-Flow File Data Verification Project, 2008–16: U.S. Geological Survey Scientific Investigations Report 2017–5119, 61 p., https://doi.org/10.31333/sir20175119.","productDescription":"Report: vii, 63 p.; Appendixes 1-2; Data Release","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068669","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":347884,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GH9G3P","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data documenting the U.S. Geological Survey peak-flow file data 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States\"}}]}","contact":"<p>Director, <a href=\"https://water.usgs.gov/osw\" data-mce-href=\"https://water.usgs.gov/osw\">Office of Surface Water </a><br>U.S. Geological Survey<br>415 National Center <br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Data Representing Peak-Flow File Changes<br></li><li>Types of Errors in the Peak-Flow File<br></li><li>Checks Done on Peak-Flow Values<br></li><li>Checks Done on Gage-Height Values<br></li><li>Peak-Flow File Qualification Codes<br></li><li>Limitations of Peak-Flow File Checks<br></li><li>Comparison Methods<br></li><li>Results of 2008 to 2016 Comparison<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix 1. U.S. Geological Survey Surface Water Branch Technical Memorandum 69.11—Storage and Retrieval System for Annual Peak Discharges<br></li><li>Appendix 2. Code that Produced the Results<br></li><li>Reference Cited</li></ul><p><br data-mce-bogus=\"1\"></p><p><br data-mce-bogus=\"1\"></p>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2017-11-21","noUsgsAuthors":false,"publicationDate":"2017-11-21","publicationStatus":"PW","scienceBaseUri":"5a60fb03e4b06e28e9c22b0a","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goree, Burl B. 0000-0003-3278-0403 bbgoree@usgs.gov","orcid":"https://orcid.org/0000-0003-3278-0403","contributorId":3508,"corporation":false,"usgs":true,"family":"Goree","given":"Burl","email":"bbgoree@usgs.gov","middleInitial":"B.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams-Sether, Tara 0000-0001-6515-9416 tjsether@usgs.gov","orcid":"https://orcid.org/0000-0001-6515-9416","contributorId":152247,"corporation":false,"usgs":true,"family":"Williams-Sether","given":"Tara","email":"tjsether@usgs.gov","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711603,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mason,, Robert R. Jr. 0000-0002-3998-3468 rrmason@usgs.gov","orcid":"https://orcid.org/0000-0002-3998-3468","contributorId":176493,"corporation":false,"usgs":true,"family":"Mason,","given":"Robert R.","suffix":"Jr.","email":"rrmason@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":711601,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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