{"pageNumber":"1017","pageRowStart":"25400","pageSize":"25","recordCount":184689,"records":[{"id":70192168,"text":"70192168 - 2017 - Ca isotopic geochemistry of an Antarctic aquatic system","interactions":[],"lastModifiedDate":"2017-11-06T13:21:59","indexId":"70192168","displayToPublicDate":"2017-02-01T00:00:00","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":"Ca isotopic geochemistry of an Antarctic aquatic system","docAbstract":"<p><span>The McMurdo Dry Valleys, Antarctica, are a polar desert ecosystem. The hydrologic system of the dry valleys is linked to climate with ephemeral streams that flow from glacial melt during the austral summer. Past climate variations have strongly influenced the closed-basin, chemically stratified lakes on the valley floor. Results of previous work point to important roles for both in-stream processes (e.g., mineral weathering, precipitation and dissolution of salts) and in-lake processes (e.g., mixing with paleo-seawater and calcite precipitation) in determining the geochemistry of these lakes. These processes have a significant influence on calcium (Ca) biogeochemistry in this aquatic ecosystem, and thus variations in Ca stable isotope compositions of the waters can aid in validating the importance of these processes. We have analyzed the Ca stable isotope compositions of streams and lakes in the McMurdo Dry Valleys. The results validate the important roles of weathering of aluminosilicate minerals and/or CaCO</span><sub>3</sub><span><span>&nbsp;</span>in the hyporheic zone of the streams, and mixing of lake surface water with paleo-seawater and precipitation of Ca-salts during cryo-concentration events to form the deep lake waters. The lakes in the McMurdo Dry Valleys evolved following different geochemical pathways, evidenced by their unique, nonsystematic Ca isotope signatures.</span></p>","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL071169","usgsCitation":"Lyons, W.B., Bullen, T.D., and Welch, K.A., 2017, Ca isotopic geochemistry of an Antarctic aquatic system: Geophysical Research Letters, v. 44, no. 2, p. 882-891, https://doi.org/10.1002/2016GL071169.","productDescription":"10 p.","startPage":"882","endPage":"891","ipdsId":"IP-082104","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470087,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl071169","text":"Publisher Index Page"},{"id":348277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, McMurdo Dry Valleys","volume":"44","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-16","publicationStatus":"PW","scienceBaseUri":"5a07e93ee4b09af898c8cc09","contributors":{"authors":[{"text":"Lyons, W. Berry","contributorId":193456,"corporation":false,"usgs":false,"family":"Lyons","given":"W.","email":"","middleInitial":"Berry","affiliations":[],"preferred":false,"id":714524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bullen, Thomas D. 0000-0003-2281-1691 tdbullen@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-1691","contributorId":1969,"corporation":false,"usgs":true,"family":"Bullen","given":"Thomas","email":"tdbullen@usgs.gov","middleInitial":"D.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":714523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welch, Kathleen A.","contributorId":197891,"corporation":false,"usgs":false,"family":"Welch","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":714525,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193455,"text":"70193455 - 2017 - Annual changes in seasonal river water temperatures in the eastern and western United States","interactions":[],"lastModifiedDate":"2021-06-04T15:52:04.210872","indexId":"70193455","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Annual changes in seasonal river water temperatures in the eastern and western United States","docAbstract":"<p><span>Changes in river water temperatures are anticipated to have direct effects on thermal habitat and fish population vital rates, and therefore, understanding temporal trends in water temperatures may be necessary for predicting changes in thermal habitat and how species might respond to such changes. However, many investigations into trends in water temperatures use regression methods that assume long-term monotonic changes in temperature, when in fact changes are likely to be nonmonotonic. Therefore, our objective was to highlight the need and provide an example of an analytical method to better quantify the short-term, nonmonotonic temporal changes in thermal habitat that are likely necessary to determine the effects of changing thermal conditions on fish populations and communities. To achieve this objective, this study uses Bayesian dynamic linear models (DLMs) to examine seasonal trends in river water temperatures from sites located in the eastern and western United States, regions that have dramatically different riverine habitats and fish communities. We estimated the annual rate of change in water temperature and found little evidence of seasonal changes in water temperatures in the eastern U.S. We found more evidence of warming for river sites located in the western U.S., particularly during the fall and winter seasons. Use of DLMs provided a more detailed view of temporal dynamics in river thermal habitat compared to more traditional methods by quantifying year-to-year changes and associated uncertainty, providing managers with the information needed to adapt decision making to short-term changes in habitat conditions that may be necessary for conserving aquatic resources in the face of a changing climate.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w9020090","usgsCitation":"Wagner, T., Midway, S.R., Whittier, J.B., DeWeber, J.T., and Paukert, C.P., 2017, Annual changes in seasonal river water temperatures in the eastern and western United States: Water, v. 9, no. 2, 90; 13 p., https://doi.org/10.3390/w9020090.","productDescription":"90; 13 p.","ipdsId":"IP-071167","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470084,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w9020090","text":"Publisher Index Page"},{"id":348596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.6650390625,\n              36.914764288955936\n            ],\n            [\n              -106.58935546875,\n              36.914764288955936\n            ],\n            [\n              -106.58935546875,\n              40.97989806962013\n            ],\n            [\n              -111.6650390625,\n              40.97989806962013\n            ],\n            [\n              -111.6650390625,\n              36.914764288955936\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.4638671875,\n              37.33522435930639\n            ],\n            [\n              -74.37744140625,\n              37.33522435930639\n            ],\n            [\n              -74.37744140625,\n              42.391008609205045\n            ],\n            [\n              -80.4638671875,\n              42.391008609205045\n            ],\n            [\n              -80.4638671875,\n              37.33522435930639\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-04","publicationStatus":"PW","scienceBaseUri":"5a06c8d1e4b09af898c8614a","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Midway, Stephen R.","contributorId":172159,"corporation":false,"usgs":false,"family":"Midway","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":721645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whittier, Joanna B.","contributorId":53151,"corporation":false,"usgs":false,"family":"Whittier","given":"Joanna","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":721646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeWeber, Jefferson T.","contributorId":199675,"corporation":false,"usgs":false,"family":"DeWeber","given":"Jefferson","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":721647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paukert, Craig P. 0000-0002-9369-8545 cpaukert@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":147821,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","email":"cpaukert@usgs.gov","middleInitial":"P.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":719127,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193472,"text":"70193472 - 2017 - Factors influencing detection of the federally endangered Diamond Darter Crystallaria cincotta: Implications for long-term monitoring strategies","interactions":[],"lastModifiedDate":"2017-11-10T18:32:18","indexId":"70193472","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5153,"text":"The American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing detection of the federally endangered Diamond Darter Crystallaria cincotta: Implications for long-term monitoring strategies","docAbstract":"<p><span>Population monitoring is an essential component of endangered species recovery programs. The federally endangered Diamond Darter&nbsp;</span><i><i>Crystallaria cincotta</i></i><span><span>&nbsp;</span>is in need of an effective monitoring design to improve our understanding of its distribution and track population trends. Because of their small size, cryptic coloration, and nocturnal behavior, along with limitations associated with current sampling methods, individuals are difficult to detect at known occupied sites. Therefore, research is needed to determine if survey efforts can be improved by increasing probability of individual detection. The primary objective of this study was to determine if there are seasonal and diel patterns in Diamond Darter detectability during population surveys. In addition to temporal factors, we also assessed five habitat variables that might influence individual detection. We used<span>&nbsp;</span></span><i>N</i><span>-mixture models to estimate site abundances and relationships between covariates and individual detectability and ranked models using Akaike's information criteria. During 2015 three known occupied sites were sampled 15 times each between May and Oct. The best supported model included water temperature as a quadratic function influencing individual detectability, with temperatures around 22 C resulting in the highest detection probability. Detection probability when surveying at the optimal temperature was approximately 6% and 7.5% greater than when surveying at 16 C and 29 C, respectively. Time of Night and day of year were not strong predictors of Diamond Darter detectability. The results of this study will allow researchers and agencies to maximize detection probability when surveying populations, resulting in greater monitoring efficiency and likely more precise abundance estimates.</span></p>","language":"English","doi":"10.1674/0003-0031-178.1.123","usgsCitation":"Rizzo, A.A., Brown, D., Welsh, S., and Thompson, P., 2017, Factors influencing detection of the federally endangered Diamond Darter Crystallaria cincotta: Implications for long-term monitoring strategies: The American Midland Naturalist, v. 178, no. 1, p. 123-131, https://doi.org/10.1674/0003-0031-178.1.123.","productDescription":"9 p.","startPage":"123","endPage":"131","ipdsId":"IP-079169","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"178","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8d1e4b09af898c86146","contributors":{"authors":[{"text":"Rizzo, Austin A.","contributorId":191439,"corporation":false,"usgs":false,"family":"Rizzo","given":"Austin","email":"","middleInitial":"A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":721636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Donald J.","contributorId":191568,"corporation":false,"usgs":false,"family":"Brown","given":"Donald J.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":721637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":721638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Patricia A. pathompson@usgs.gov","contributorId":5249,"corporation":false,"usgs":true,"family":"Thompson","given":"Patricia A.","email":"pathompson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":721639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192900,"text":"70192900 - 2017 - A land data assimilation system for sub-Saharan Africa food and water security applications","interactions":[],"lastModifiedDate":"2017-10-30T15:06:03","indexId":"70192900","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"A land data assimilation system for sub-Saharan Africa food and water security applications","docAbstract":"<p><span>Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/sdata.2017.12","usgsCitation":"McNally, A., Arsenault, K., Kumar, S., Shukla, S., Peterson, P., Wang, S., Funk, C., Peters-Lidard, C., and Verdin, J., 2017, A land data assimilation system for sub-Saharan Africa food and water security applications: Scientific Data, v. 4, p. 1-19, https://doi.org/10.1038/sdata.2017.12.","productDescription":"Article number 170012; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-077287","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470090,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/sdata.2017.12","text":"Publisher Index Page"},{"id":347730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-14","publicationStatus":"PW","scienceBaseUri":"59f83a39e4b063d5d30980f3","contributors":{"authors":[{"text":"McNally, Amy","contributorId":145810,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","email":"","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":717321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arsenault, Kristi","contributorId":198836,"corporation":false,"usgs":false,"family":"Arsenault","given":"Kristi","affiliations":[],"preferred":false,"id":717322,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumar, Sujay","contributorId":198837,"corporation":false,"usgs":false,"family":"Kumar","given":"Sujay","email":"","affiliations":[],"preferred":false,"id":717323,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shukla, Shraddhanand","contributorId":145841,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16255,"text":"Climate Hazards Group University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":717324,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peterson, Pete","contributorId":192379,"corporation":false,"usgs":false,"family":"Peterson","given":"Pete","affiliations":[],"preferred":false,"id":717325,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Shugong","contributorId":198838,"corporation":false,"usgs":false,"family":"Wang","given":"Shugong","email":"","affiliations":[],"preferred":false,"id":717326,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":717320,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Peters-Lidard, Christa","contributorId":198839,"corporation":false,"usgs":false,"family":"Peters-Lidard","given":"Christa","email":"","affiliations":[],"preferred":false,"id":717327,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Verdin, James 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":145830,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717328,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70189149,"text":"70189149 - 2017 - Paleoseismic potential of sublacustrine landslide records in a high-seismicity setting (south-central Alaska)","interactions":[],"lastModifiedDate":"2023-11-08T15:51:27.424228","indexId":"70189149","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Paleoseismic potential of sublacustrine landslide records in a high-seismicity setting (south-central Alaska)","docAbstract":"<p><span>Sublacustrine landslide stratigraphy is considered useful for quantitative&nbsp;paleoseismology&nbsp;in low-seismicity settings. However, as the recharging of underwater slopes with sediments is one of the factors that governs the recurrence of slope failures, it is not clear if landslide deposits can provide continuous paleoseismic records in settings of frequent strong shaking. To test this, we selected three lakes in south-central Alaska that experienced a strong historical megathrust earthquake (the 1964 M</span><sub><i>w</i></sub><span>9.2 Great Alaska Earthquake) and exhibit high&nbsp;sedimentation rates&nbsp;in their main basins (0.2</span><span>&nbsp;</span><span>cm</span><span>&nbsp;</span><span>yr</span><sup>−&nbsp;1</sup><span>–1.0</span><span>&nbsp;</span><span>cm</span><span>&nbsp;</span><span>yr</span><sup>−&nbsp;1</sup><span>). We present high-resolution reflection&nbsp;seismic data&nbsp;(3.5</span><span>&nbsp;</span><span>kHz) and&nbsp;radionuclide&nbsp;data from&nbsp;sediment cores&nbsp;in order to investigate factors that control the establishment of a reliable landslide record.&nbsp;Seismic stratigraphy&nbsp;analysis reveals the presence of several landslide deposits in the lacustrine sedimentary infill. Most of these landslide deposits can be attributed to specific landslide events, as multiple landslide deposits sourced from different lacustrine slopes occur on a single stratigraphic horizon. We identify numerous events in the lakes: Eklutna Lake proximal basin (14 events), Eklutna Lake distal basin (8 events), Skilak Lake (7 events) and Kenai Lake (7 events). The most recent event in each basin corresponds to the historic 1964 megathrust earthquake. All events are characterized by multiple landslide deposits, which hints at a regional trigger mechanism, such as an earthquake (the synchronicity criterion). This means that the landslide record in each basin represents a record of past seismic events. Based on extrapolation of sedimentation rates derived from radionuclide dating, we roughly estimate a mean&nbsp;recurrence interval&nbsp;in the Eklutna Lake proximal basin, Eklutna Lake distal basin, Skilak Lake and Kenai Lake, at ~</span><span>&nbsp;</span><span>250</span><span>&nbsp;</span><span>yrs., ~</span><span>&nbsp;</span><span>450</span><span>&nbsp;</span><span>yrs., ~</span><span>&nbsp;</span><span>900</span><span>&nbsp;</span><span>yrs. and ~</span><span>&nbsp;</span><span>450</span><span>&nbsp;</span><span>yrs., respectively. This distinct difference in recording can be explained by variations in preconditioning factors like slope angle, slope recharging (sedimentation rate) and the sediment source area: faster slope recharging and a predominance of delta and&nbsp;alluvial fan&nbsp;failures, increase the sensitivity and lower the intensity threshold for slope instability. Also, the&nbsp;seismotectonic&nbsp;setting of the lakes has to be taken into account. This study demonstrates that sublacustrine landslides in several Alaskan lakes can be used as reliable recorders of strong earthquake shaking, when a multi-lake approach is used, and can enhance the temporal and spatial resolution of the paleoseismic record of south-central Alaska.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2016.05.004","usgsCitation":"Praet, N., Moernaut, J., Van Daele, M., Boes, E., Haeussler, P.J., Strupler, M., Schmidt, S., Loso, M.G., and De Batist, M., 2017, Paleoseismic potential of sublacustrine landslide records in a high-seismicity setting (south-central Alaska): Marine Geology, v. 384, p. 103-119, https://doi.org/10.1016/j.margeo.2016.05.004.","productDescription":"17 p.","startPage":"103","endPage":"119","ipdsId":"IP-073802","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":489654,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GK6YZG","text":"USGS data release","linkHelpText":"Gridded Data from Multibeam Bathymetric Surveys of Eklutna, Kenai, and Skilak Lakes, Alaska"},{"id":470106,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2016.05.004","text":"Publisher Index Page"},{"id":343261,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kenai Peninsula","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -153.5009765625,\n              59.108308258604964\n            ],\n            [\n              -147.48046875,\n              59.108308258604964\n            ],\n            [\n    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Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":703164,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Strupler, Michael","contributorId":194087,"corporation":false,"usgs":false,"family":"Strupler","given":"Michael","email":"","affiliations":[],"preferred":false,"id":703169,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, Sabine","contributorId":194088,"corporation":false,"usgs":false,"family":"Schmidt","given":"Sabine","email":"","affiliations":[],"preferred":false,"id":703170,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Loso, Michael G.","contributorId":146361,"corporation":false,"usgs":false,"family":"Loso","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":703171,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"De Batist, Marc 0000-0002-1625-2080","orcid":"https://orcid.org/0000-0002-1625-2080","contributorId":194089,"corporation":false,"usgs":false,"family":"De Batist","given":"Marc","email":"","affiliations":[],"preferred":false,"id":703172,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70191538,"text":"70191538 - 2017 - Compartmentalization of the Coso East Flank geothermal field imaged by 3-D full-tensor MT inversion","interactions":[],"lastModifiedDate":"2017-10-17T11:10:13","indexId":"70191538","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Compartmentalization of the Coso East Flank geothermal field imaged by 3-D full-tensor MT inversion","docAbstract":"<p><span>Previous magnetotelluric (MT) studies of the high-temperature Coso geothermal system in California identified a subvertical feature of low resistivity (2–5&nbsp;Ohm m) and appreciable lateral extent (&gt;1&nbsp;km) in the producing zone of the East Flank field. However, these models could not reproduce gross 3-D effects in the recorded data. We perform 3-D full-tensor inversion and retrieve a resistivity model that out-performs previous 2-D and 3-D off-diagonal models in terms of its fit to the complete 3-D MT data set as well as the degree of modelling bias. Inclusion of secondary&nbsp;</span><i>Z</i><sub><i>xx</i></sub><span><span>&nbsp;</span>and<span>&nbsp;</span></span><i>Z</i><sub><i>yy</i></sub><span><span>&nbsp;</span>data components leads to a robust east-dip (60†) to the previously identified conductive East Flank reservoir feature, which correlates strongly with recently mapped surface faults, downhole well temperatures, 3-D seismic reflection data, and local microseismicity. We perform synthetic forward modelling to test the best-fit dip of this conductor using the response at a nearby MT station. We interpret the dipping conductor as a fractured and fluidized compartment, which is structurally controlled by an unmapped blind East Flank fault zone.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggw408","usgsCitation":"Lindsey, N.J., Kaven, J., Davatzes, N.C., and Newman, G.A., 2017, Compartmentalization of the Coso East Flank geothermal field imaged by 3-D full-tensor MT inversion: Geophysical Journal International, v. 208, no. 2, p. 652-662, https://doi.org/10.1093/gji/ggw408.","productDescription":"11 p.","startPage":"652","endPage":"662","ipdsId":"IP-073610","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470088,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggw408","text":"Publisher Index Page"},{"id":346680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Coso Range","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.8,\n              36\n            ],\n            [\n              -117.725,\n              36\n            ],\n            [\n              -117.725,\n              36.075\n            ],\n            [\n              -117.8,\n              36.075\n            ],\n            [\n              -117.8,\n              36\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"208","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-05","publicationStatus":"PW","scienceBaseUri":"59e71692e4b05fe04cd331b1","contributors":{"authors":[{"text":"Lindsey, Nathaniel J.","contributorId":197138,"corporation":false,"usgs":false,"family":"Lindsey","given":"Nathaniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712679,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaven, J. Ole 0000-0003-2625-2786 okaven@usgs.gov","orcid":"https://orcid.org/0000-0003-2625-2786","contributorId":3993,"corporation":false,"usgs":true,"family":"Kaven","given":"J. Ole","email":"okaven@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":712678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davatzes, Nicholas C.","contributorId":138855,"corporation":false,"usgs":false,"family":"Davatzes","given":"Nicholas","email":"","middleInitial":"C.","affiliations":[{"id":12547,"text":"Temple University","active":true,"usgs":false}],"preferred":false,"id":712680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Newman, Gregory A.","contributorId":197140,"corporation":false,"usgs":false,"family":"Newman","given":"Gregory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712681,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193019,"text":"70193019 - 2017 - Fish and invertebrate flow-biology relationships to support the determination of ecological flows for North Carolina","interactions":[],"lastModifiedDate":"2017-11-21T13:54:05","indexId":"70193019","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Fish and invertebrate flow-biology relationships to support the determination of ecological flows for North Carolina","docAbstract":"<p><span>A method was developed to characterize fish and invertebrate responses to flow alteration in the state of North Carolina. This method involved using 80th percentile linear quantile regressions to relate six flow metrics to the diversity of riffle-run fish and benthic Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness. All twelve flow-biology relationships were found to be significant, with both benthos and fish showing negative responses to ecodeficits and reductions in flow. The responses of benthic richness to reduced flows were consistent and generally greater than that of fish diversity. However, the riffle-run fish guild showed the greatest reductions in diversity in response to summer ecodeficits. The directional consistency and differential seasonal sensitivities of fish and invertebrates to reductions in flow highlight the need to consider seasonality when managing flows. In addition, all relationships were linear, and therefore do not provide clear thresholds to support ecological flow determinations and flow prescriptions to prevent the degradation of fish and invertebrate communities in North Carolina rivers and streams. A method of setting ecological flows based on the magnitude of change in biological condition that is acceptable to society is explored.</span></p>","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12497","usgsCitation":"Phelan, J., Cuffney, T.F., Patterson, L.A., Eddy, M., Dykes, R., Pearsall, S., Goudreau, C., Mead, J., and Tarver, F., 2017, Fish and invertebrate flow-biology relationships to support the determination of ecological flows for North Carolina: Journal of the American Water Resources Association, v. 53, no. 1, p. 42-55, https://doi.org/10.1111/1752-1688.12497.","productDescription":"14 p.","startPage":"42","endPage":"55","ipdsId":"IP-077299","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":349217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North 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Carolina\",\"nation\":\"USA  \"}}]}","volume":"53","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-10","publicationStatus":"PW","scienceBaseUri":"5a60fc26e4b06e28e9c23b11","contributors":{"authors":[{"text":"Phelan, Jennifer","contributorId":198940,"corporation":false,"usgs":false,"family":"Phelan","given":"Jennifer","affiliations":[],"preferred":false,"id":717667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cuffney, Thomas F. 0000-0003-1164-5560 tcuffney@usgs.gov","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":517,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"tcuffney@usgs.gov","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patterson, Lauren A.","contributorId":177289,"corporation":false,"usgs":false,"family":"Patterson","given":"Lauren","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":717668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eddy, Michele","contributorId":198941,"corporation":false,"usgs":false,"family":"Eddy","given":"Michele","email":"","affiliations":[],"preferred":false,"id":717669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dykes, Robert","contributorId":198942,"corporation":false,"usgs":false,"family":"Dykes","given":"Robert","email":"","affiliations":[],"preferred":false,"id":717670,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pearsall, Sam","contributorId":198943,"corporation":false,"usgs":false,"family":"Pearsall","given":"Sam","email":"","affiliations":[],"preferred":false,"id":717671,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goudreau, Chris","contributorId":198944,"corporation":false,"usgs":false,"family":"Goudreau","given":"Chris","email":"","affiliations":[],"preferred":false,"id":717672,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mead, Jim","contributorId":198945,"corporation":false,"usgs":false,"family":"Mead","given":"Jim","affiliations":[],"preferred":false,"id":717673,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tarver, Fred","contributorId":198946,"corporation":false,"usgs":false,"family":"Tarver","given":"Fred","email":"","affiliations":[],"preferred":false,"id":717674,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70192944,"text":"70192944 - 2017 - Temporal expansion of annual crop classification layers for the CONUS using the C5 decision tree classifier","interactions":[],"lastModifiedDate":"2017-10-30T15:00:45","indexId":"70192944","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3251,"text":"Remote Sensing Letters","active":true,"publicationSubtype":{"id":10}},"title":"Temporal expansion of annual crop classification layers for the CONUS using the C5 decision tree classifier","docAbstract":"<p><span>Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008 to 2013. In this investigation, we sought to contribute to the availability of consistent CONUS crop cover maps by extending temporal coverage of the NASS CDL archive back eight additional years to 2000 by creating annual NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million records to train a classification tree algorithm and develop a crop classification model (CCM). The model was used to create crop cover maps for the CONUS for years 2000–2013 at 250&nbsp;m spatial resolution. The CCM and the maps for years 2008–2013 were assessed for accuracy relative to resampled NASS CDLs. The CCM performed well against a withheld test data set with a model prediction accuracy of over 90%. The assessment of the crop cover maps indicated that the model performed well spatially, placing crop cover pixels within their known domains; however, the model did show a bias towards the ‘Other’ crop cover class, which caused frequent misclassifications of pixels around the periphery of large crop cover patch clusters and of pixels that form small, sparsely dispersed crop cover patches.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/2150704X.2016.1271469","usgsCitation":"Friesz, A.M., Wylie, B., and Howard, D.M., 2017, Temporal expansion of annual crop classification layers for the CONUS using the C5 decision tree classifier: Remote Sensing Letters, v. 8, no. 4, p. 389-398, https://doi.org/10.1080/2150704X.2016.1271469.","productDescription":"10 p.","startPage":"389","endPage":"398","ipdsId":"IP-075490","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":347729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-03","publicationStatus":"PW","scienceBaseUri":"59f83a38e4b063d5d30980ef","contributors":{"authors":[{"text":"Friesz, Aaron M. 0000-0003-4096-3824 afriesz@usgs.gov","orcid":"https://orcid.org/0000-0003-4096-3824","contributorId":5943,"corporation":false,"usgs":true,"family":"Friesz","given":"Aaron","email":"afriesz@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":197161,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce K.","email":"wylie@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":717394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howard, Daniel M. 0000-0002-7563-7538 danny.howard.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":197063,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel","email":"danny.howard.ctr@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":717393,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70182759,"text":"70182759 - 2017 - Nationwide reconnaissance of contaminants of emerging concern in source and treated drinking waters of the United States: Pharmaceuticals","interactions":[],"lastModifiedDate":"2019-08-20T08:46:57","indexId":"70182759","displayToPublicDate":"2017-02-01T00:00:00","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":"Nationwide reconnaissance of contaminants of emerging concern in source and treated drinking waters of the United States: Pharmaceuticals","docAbstract":"Mobile and persistent chemicals that are present in urban wastewater, such as pharmaceuticals, may survive\non-site ormunicipal wastewater treatment and post-discharge environmental processes. These pharmaceuticals\nhave the potential to reach surface and groundwaters, essential drinking-water sources. A joint, two-phase U.S.\nGeological Survey-U.S. Environmental Protection Agency study examined source and treated waters from 25\ndrinking-water treatment plants from across the United States. Treatment plants that had probable wastewater\ninputs to their source waters were selected to assess the prevalence of pharmaceuticals in such source waters,\nand to identify which pharmaceuticals persist through drinking-water treatment. All samples were analyzed\nfor 24 pharmaceuticals in Phase I and for 118 in Phase II.\nIn Phase I, 11 pharmaceuticals were detected in all source-water samples, with amaximumof nine pharmaceuticals\ndetected in any one sample. The median number of pharmaceuticals for all 25 samples was five.\nQuantifiable pharmaceutical detections were fewer, with a maximum of five pharmaceuticals in any one\nsample and a median for all samples of two. In Phase II, 47 different pharmaceuticals were detected in all\nsource-water samples, with a maximum of 41 pharmaceuticals detected in any one sample. The median\nnumber of pharmaceuticals for all 25 samples was eight. For 37 quantifiable pharmaceuticals in Phase II,\nmedian concentrations in source water were below 113 ng/L.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.128","usgsCitation":"Furlong, E.T., Batt, A.L., Glassmeyer, S.T., Noriega, M.C., Kolpin, D.W., Mash, H., and Schenck, K.M., 2017, Nationwide reconnaissance of contaminants of emerging concern in source and treated drinking waters of the United States: Pharmaceuticals: Science of the Total Environment, v. 579, p. 1629-1642, https://doi.org/10.1016/j.scitotenv.2016.03.128.","productDescription":"14 p. ","startPage":"1629","endPage":"1642","ipdsId":"IP-066272","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"links":[{"id":470097,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://europepmc.org/articles/pmc7017633","text":"External Repository"},{"id":336327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"579","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b69a3ee4b01ccd54ff3f7e","contributors":{"authors":[{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":673614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Batt, Angela L.","contributorId":184134,"corporation":false,"usgs":false,"family":"Batt","given":"Angela","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":673615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glassmeyer, Susan T.","contributorId":184135,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":673616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noriega, Mary C. mnoriega@usgs.gov","contributorId":2553,"corporation":false,"usgs":true,"family":"Noriega","given":"Mary","email":"mnoriega@usgs.gov","middleInitial":"C.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":673620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":673619,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mash, Heath","contributorId":184088,"corporation":false,"usgs":false,"family":"Mash","given":"Heath","affiliations":[],"preferred":false,"id":673617,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schenck, Kathleen M.","contributorId":184136,"corporation":false,"usgs":false,"family":"Schenck","given":"Kathleen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":673618,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70182798,"text":"70182798 - 2017 - Dynamic strains for earthquake source characterization","interactions":[],"lastModifiedDate":"2017-03-01T14:26:59","indexId":"70182798","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic strains for earthquake source characterization","docAbstract":"Strainmeters measure elastodynamic deformation associated with earthquakes over a broad frequency band, with detection characteristics that complement traditional instrumentation, but they are commonly used to study slow transient deformation along active faults and at subduction zones, for example. Here, we analyze dynamic strains at Plate Boundary Observatory (PBO) borehole strainmeters (BSM) associated with 146 local and regional earthquakes from 2004–2014, with magnitudes from M 4.5 to 7.2. We find that peak values in seismic strain can be predicted from a general regression against distance and magnitude, with improvements in accuracy gained by accounting for biases associated with site–station effects and source–path effects, the latter exhibiting the strongest influence on the regression coefficients. To account for the influence of these biases in a general way, we include crustal‐type classifications from the CRUST1.0 global velocity model, which demonstrates that high‐frequency strain data from the PBO BSM network carry information on crustal structure and fault mechanics: earthquakes nucleating offshore on the Blanco fracture zone, for example, generate consistently lower dynamic strains than earthquakes around the Sierra Nevada microplate and in the Salton trough. Finally, we test our dynamic strain prediction equations on the 2011 M 9 Tohoku‐Oki earthquake, specifically continuous strain records derived from triangulation of 137 high‐rate Global Navigation Satellite System Earth Observation Network stations in Japan. Moment magnitudes inferred from these data and the strain model are in agreement when Global Positioning System subnetworks are unaffected by spatial aliasing.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160155","usgsCitation":"Barbour, A., and Crowell, B.W., 2017, Dynamic strains for earthquake source characterization: Seismological Research Letters, v. 88, no. 2A, p. 354-370, https://doi.org/10.1785/0220160155.","productDescription":"17 p. ","startPage":"354","endPage":"370","ipdsId":"IP-076502","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":336775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336351,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1785/0220160155"}],"volume":"88","issue":"2A","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-01","publicationStatus":"PW","scienceBaseUri":"58b7eba1e4b01ccd5500bad5","contributors":{"authors":[{"text":"Barbour, Andrew J. 0000-0002-6890-2452 abarbour@usgs.gov","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":140443,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew J.","email":"abarbour@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":673788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crowell, Brendan W.","contributorId":184207,"corporation":false,"usgs":false,"family":"Crowell","given":"Brendan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":673789,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192623,"text":"70192623 - 2017 - An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics","interactions":[],"lastModifiedDate":"2018-05-13T12:10:31","indexId":"70192623","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics","docAbstract":"<p><span>Ecological invasions and colonizations occur dynamically through space and time. Estimating the distribution and abundance of colonizing species is critical for efficient management or conservation. We describe a statistical framework for simultaneously estimating spatiotemporal occupancy and abundance dynamics of a colonizing species. Our method accounts for several issues that are common when modeling spatiotemporal ecological data including multiple levels of detection probability, multiple data sources, and computational limitations that occur when making fine-scale inference over a large spatiotemporal domain. We apply the model to estimate the colonization dynamics of sea otters (</span><i>Enhydra lutris</i><span>) in Glacier Bay, in southeastern Alaska.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1643","usgsCitation":"Williams, P.J., Hooten, M., Womble, J.N., Esslinger, G.G., Bower, M., and Hefley, T.J., 2017, An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics: Ecology, v. 98, no. 2, p. 328-336, https://doi.org/10.1002/ecy.1643.","productDescription":"9 p.","startPage":"328","endPage":"336","ipdsId":"IP-076210","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":461769,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.1643","text":"Publisher Index Page"},{"id":348565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-04","publicationStatus":"PW","scienceBaseUri":"5a06c8d2e4b09af898c8614e","contributors":{"authors":[{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":721553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":716573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Womble, Jamie N.","contributorId":198631,"corporation":false,"usgs":false,"family":"Womble","given":"Jamie","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":721554,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esslinger, George G. 0000-0002-3459-0083 gesslinger@usgs.gov","orcid":"https://orcid.org/0000-0002-3459-0083","contributorId":131009,"corporation":false,"usgs":true,"family":"Esslinger","given":"George","email":"gesslinger@usgs.gov","middleInitial":"G.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":721555,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bower, Michael R.","contributorId":44787,"corporation":false,"usgs":true,"family":"Bower","given":"Michael R.","affiliations":[],"preferred":false,"id":721556,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hefley, Trevor J.","contributorId":147146,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","email":"","middleInitial":"J.","affiliations":[{"id":16796,"text":"Dept Fish, Wildlife & Cons Biol, Colorado St Univ, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":721557,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70186026,"text":"70186026 - 2017 - Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010)","interactions":[],"lastModifiedDate":"2017-03-30T12:02:00","indexId":"70186026","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010)","docAbstract":"<p><span>Quantifying changes in the cover of river-floodplain systems can provide important insights into the processes that structure these landscapes as well as the potential consequences to the ecosystem services they provide. We examined net changes in 13 different aquatic and floodplain land cover classes using photo interpreted maps of the navigable portions of the Upper Mississippi River (UMR, above the confluence with the Ohio River) and Illinois River from 1989 to 2000 and from 2000 to 2010. We detected net decreases in vegetated aquatic area in nearly all river reaches from 1989 to 2000. The only river reaches that experienced a subsequent recovery of vegetated aquatic area from 2000 to 2010 were located in the northern portion of the UMR (above navigation pool 14) and two reaches in the Illinois River. Changes on the floodplain were dominated by urban development, which increased in nearly every river reach studied from 1989 to 2000. Agricultural lands declined in most river reaches from 2000 to 2010. The loss of agricultural land cover in the northern UMR was accompanied by increases in forest cover, whereas in the lower UMR and Illinois River, declines in agriculture were accompanied by increases in forest and shallow marsh communities. The changes in aquatic vegetation occupied between 5 and 20% of the total aquatic area and are likely associated with previously reported regional improvements in water clarity, while smaller (1–15% of the total floodplain area) changes in anthropogenic land cover types on the floodplain are likely driven by broad-scale socio-economic conditions.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10661-017-5774-0","usgsCitation":"De Jager, N.R., and Rohweder, J.J., 2017, Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010): Environmental Monitoring and Assessment, v. 189, p. 1-14, https://doi.org/10.1007/s10661-017-5774-0.","productDescription":"Article 77; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-078207","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":338819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Illinois River, Upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.31787109374999,\n              36.914764288955936\n            ],\n            [\n              -87.47314453125,\n              36.914764288955936\n            ],\n            [\n              -87.47314453125,\n              44.94924926661153\n            ],\n            [\n              -93.31787109374999,\n              44.94924926661153\n            ],\n            [\n              -93.31787109374999,\n              36.914764288955936\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"189","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-24","publicationStatus":"PW","scienceBaseUri":"58de194ee4b02ff32c699c9d","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rohweder, Jason J. jrohweder@usgs.gov","contributorId":460,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":687383,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70184967,"text":"70184967 - 2017 - Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (<i>Myocastor coypus</i>)","interactions":[],"lastModifiedDate":"2017-03-15T12:07:21","indexId":"70184967","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (<i>Myocastor coypus</i>)","docAbstract":"<p><span>Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (</span><i><span class=\"tn\"><span class=\"genus\">Myocastor</span> <span class=\"species\">coypus</span></span></i><span> [Molina, 1782]), we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (</span><abbr id=\"ABBRID0EMF\" title=\"global circulation model\">GCM</abbr><span>) predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among </span><abbr id=\"ABBRID0EUF\" title=\"global climate projections\">GCMs</abbr><span>, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.</span></p>","language":"English","publisher":"Pensoft","doi":"10.3897/neobiota.32.8884","usgsCitation":"Jarnevich, C.S., Young, N.E., Sheffels, T.R., Carter, J., Systma, M.D., and Talbert, C., 2017, Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (<i>Myocastor coypus</i>): NeoBiota, v. 32, p. 107-125, https://doi.org/10.3897/neobiota.32.8884.","productDescription":"19 p.","startPage":"107","endPage":"125","ipdsId":"IP-065118","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.32.8884","text":"Publisher Index Page"},{"id":337613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-04","publicationStatus":"PW","scienceBaseUri":"58ca52cce4b0849ce97c869a","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":683741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Nicholas E.","contributorId":189060,"corporation":false,"usgs":false,"family":"Young","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":683742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheffels, Trevor R.","contributorId":140176,"corporation":false,"usgs":false,"family":"Sheffels","given":"Trevor","email":"","middleInitial":"R.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":683743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@usgs.gov","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":683744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Systma, Mark D.","contributorId":140177,"corporation":false,"usgs":false,"family":"Systma","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":13401,"text":"Portland State University, Portland Oregon","active":true,"usgs":false}],"preferred":false,"id":683745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbert, Colin 0000-0002-9505-1876 talbertc@usgs.gov","orcid":"https://orcid.org/0000-0002-9505-1876","contributorId":181913,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":683746,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70187165,"text":"70187165 - 2017 - Tracer-based characterization of hyporheic exchange and benthic biolayers in streams","interactions":[],"lastModifiedDate":"2017-04-25T15:20:57","indexId":"70187165","displayToPublicDate":"2017-02-01T00:00:00","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":"Tracer-based characterization of hyporheic exchange and benthic biolayers in streams","docAbstract":"<p><span>Shallow benthic biolayers at the top of the streambed are believed to be places of enhanced biogeochemical turnover within the hyporheic zone. They can be investigated by reactive stream tracer tests with tracer recordings in the streambed and in the stream channel. Common in-stream measurements of such reactive tracers cannot localize where the processing primarily takes place, whereas isolated vertical depth profiles of solutes within the hyporheic zone are usually not representative of the entire stream. We present results of a tracer test where we injected the conservative tracer bromide together with the reactive tracer resazurin into a third-order stream and combined the recording of in-stream breakthrough curves with multidepth sampling of the hyporheic zone at several locations. The transformation of resazurin was used as an indicator of metabolism, and high-reactivity zones were identified from depth profiles. The results from our subsurface analysis indicate that the potential for tracer transformation (i.e., the reaction rate constant) varied with depth in the hyporheic zone. This highlights the importance of the benthic biolayer, which we found to be on average 2 cm thick in this study, ranging from one third to one half of the full depth of the hyporheic zone. The reach-scale approach integrated the effects of processes along the reach length, isolating hyporheic processes relevant for whole-stream chemistry and estimating effective reaction rates.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016WR019393","usgsCitation":"Knapp, J., Gonzalez-Pinzon, R., Drummond, J.D., Larsen, L., Cirpka, O.A., and Harvey, J.W., 2017, Tracer-based characterization of hyporheic exchange and benthic biolayers in streams: Water Resources Research, v. 53, no. 2, p. 1575-1594, https://doi.org/10.1002/2016WR019393.","productDescription":"20 p.","startPage":"1575","endPage":"1594","ipdsId":"IP-080169","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr019393","text":"Publisher Index Page"},{"id":340374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-21","publicationStatus":"PW","scienceBaseUri":"59006062e4b0e85db3a5ddd1","contributors":{"authors":[{"text":"Knapp, Julia L.A.","contributorId":191389,"corporation":false,"usgs":false,"family":"Knapp","given":"Julia L.A.","affiliations":[],"preferred":false,"id":692887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonzalez-Pinzon, Ricardo","contributorId":191362,"corporation":false,"usgs":false,"family":"Gonzalez-Pinzon","given":"Ricardo","email":"","affiliations":[],"preferred":false,"id":692888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drummond, Jennifer D.","contributorId":191390,"corporation":false,"usgs":false,"family":"Drummond","given":"Jennifer","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":692889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Laurel G.","contributorId":191391,"corporation":false,"usgs":false,"family":"Larsen","given":"Laurel G.","affiliations":[],"preferred":false,"id":692890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cirpka, Olaf A.","contributorId":191392,"corporation":false,"usgs":false,"family":"Cirpka","given":"Olaf","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":692891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":692886,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70188375,"text":"70188375 - 2017 - Multi-year microbial source tracking study characterizing fecal contamination in an urban watershed","interactions":[],"lastModifiedDate":"2017-06-07T14:04:58","indexId":"70188375","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3711,"text":"Water Environment Research","active":true,"publicationSubtype":{"id":10}},"title":"Multi-year microbial source tracking study characterizing fecal contamination in an urban watershed","docAbstract":"<p><span>Microbiological and hydrological data were used to rank tributary stream contributions of bacteria to the Little Blue River in Independence, Missouri. Concentrations, loadings and yields of </span><i>E. coli</i><span> and microbial source tracking (MST) markers, were characterized during base flow and storm events in five subbasins within Independence, as well as sources entering and leaving the city through the river. The </span><i>E. coli</i><span> water quality threshold was exceeded in 29% of base-flow and 89% of storm-event samples. The total contribution of </span><i>E. coli</i><span> and MST markers from tributaries within Independence to the Little Blue River, regardless of streamflow, did not significantly increase the median concentrations leaving the city. Daily loads and yields of </span><i>E. coli</i><span> and MST markers were used to rank the subbasins according to their contribution of each constituent to the river. The ranking methodology used in this study may prove useful in prioritizing remediation in the different subbasins.</span></p>","language":"English","publisher":"Water Environment Federation","doi":"10.2175/106143016X14798353399412","collaboration":"City of Independence, Missouri Water Pollution Control Station","usgsCitation":"Bushon, R.N., Brady, A.M., Christensen, E.D., and Stelzer, E.A., 2017, Multi-year microbial source tracking study characterizing fecal contamination in an urban watershed: Water Environment Research, v. 89, no. 2, p. 127-143, https://doi.org/10.2175/106143016X14798353399412.","productDescription":"17 p.","startPage":"127","endPage":"143","ipdsId":"IP-069132","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":342249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","city":"Independence","otherGeospatial":"Little Blue 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,{"id":70195839,"text":"70195839 - 2017 - Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States","interactions":[],"lastModifiedDate":"2018-03-06T11:11:17","indexId":"70195839","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States","docAbstract":"<p><span>A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere–ocean general circulation models (AOGCMs; CCSM4, HadGEM2-CC, MIROC5, and MRI-CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET-BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern United States are anticipated to increase evapotranspiration across all sites, although invoking CO</span><sub>2</sub><span><span>&nbsp;</span>effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce-fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snow packs, longer growing seasons, and associated water deficits. Considering future CO</span><sub>2</sub><span>effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern United States. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrological responses to climate change.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13444","usgsCitation":"Pourmokhtarian, A., Driscoll, C.T., Campbell, J.L., Hayhoe, K., Stoner, A., Adams, M.B., Burns, D., Fernandez, I., Mitchell, M.J., and Shanley, J.B., 2017, Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States: Global Change Biology, v. 23, no. 2, p. 840-856, https://doi.org/10.1111/gcb.13444.","productDescription":"17 p.","startPage":"840","endPage":"856","ipdsId":"IP-077080","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":352254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-25","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4ba","contributors":{"authors":[{"text":"Pourmokhtarian, Afshin","contributorId":202944,"corporation":false,"usgs":false,"family":"Pourmokhtarian","given":"Afshin","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":730243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Charles T.","contributorId":167460,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":730244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, John L.","contributorId":178410,"corporation":false,"usgs":false,"family":"Campbell","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":730245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayhoe, Katharine","contributorId":149192,"corporation":false,"usgs":false,"family":"Hayhoe","given":"Katharine","email":"","affiliations":[{"id":17667,"text":"Climate Science Center, Texas Tech University, Lubbock, Texas, United States","active":true,"usgs":false}],"preferred":false,"id":730246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stoner, Anne M. K.","contributorId":202945,"corporation":false,"usgs":false,"family":"Stoner","given":"Anne M. K.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":730247,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Mary Beth","contributorId":150354,"corporation":false,"usgs":false,"family":"Adams","given":"Mary","email":"","middleInitial":"Beth","affiliations":[],"preferred":false,"id":730248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":730242,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fernandez, Ivan","contributorId":178215,"corporation":false,"usgs":false,"family":"Fernandez","given":"Ivan","affiliations":[],"preferred":false,"id":730249,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mitchell, Myron J.","contributorId":73734,"corporation":false,"usgs":true,"family":"Mitchell","given":"Myron","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":730250,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730241,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70189714,"text":"70189714 - 2017 - Development and utilization of USGS ShakeCast for rapid post-earthquake assessment of critical facilities and infrastructure","interactions":[],"lastModifiedDate":"2017-07-21T11:50:56","indexId":"70189714","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Development and utilization of USGS ShakeCast for rapid post-earthquake assessment of critical facilities and infrastructure","docAbstract":"<p><span>The ShakeCast system is an openly available, near real-time post-earthquake information management system. ShakeCast is widely used by public and private emergency planners and responders, lifeline utility operators and transportation engineers to automatically receive and process ShakeMap products for situational awareness, inspection priority, or damage assessment of their own infrastructure or building portfolios. The success of ShakeCast to date and its broad, critical-user base mandates improved software usability and functionality, including improved engineering-based damage and loss functions. In order to make the software more accessible to novice users—while still utilizing advanced users’ technical and engineering background—we have developed a “ShakeCast Workbook”, a well documented, Excel spreadsheet-based user interface that allows users to input notification and inventory data and export XML files requisite for operating the ShakeCast system. Users will be able to select structure based on a minimum set of user-specified facility (building location, size, height, use, construction age, etc.). “Expert” users will be able to import user-modified structural response properties into facility inventory associated with the HAZUS Advanced Engineering Building Modules (AEBM). The goal of the ShakeCast system is to provide simplified real-time potential impact and inspection metrics (i.e., green, yellow, orange and red priority ratings) to allow users to institute customized earthquake response protocols. Previously, fragilities were approximated using individual ShakeMap intensity measures (IMs, specifically PGA and 0.3 and 1s spectral accelerations) for each facility but we are now performing capacity-spectrum damage state calculations using a more robust characterization of spectral deamnd.We are also developing methods for the direct import of ShakeMap’s multi-period spectra in lieu of the assumed three-domain design spectrum (at 0.3s for constant acceleration; 1s or 3s for constant velocity and constant displacement at very long response periods). As part of ongoing ShakeCast research and development, we will also explore the use of ShakeMap IM uncertainty estimates and evaluate the assumption of employing multiple response spectral damping values rather than the single 5%-damped value currently employed. Developing and incorporating advanced fragility assignments into the ShakeCast Workbook requires related software modifications and database improvements; these enhancements are part of an extensive rewrite of the ShakeCast application.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 16th World Conference on Earthquake Engineering","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"16th World Conference on Earthquake Engineering","language":"English","publisher":"16th World Conference on Earthquake Engineering","usgsCitation":"Wald, D.J., Lin, K., Kircher, C.A., Jaiswal, K.S., Luco, N., Turner, L., and Slosky, D., 2017, Development and utilization of USGS ShakeCast for rapid post-earthquake assessment of critical facilities and infrastructure, <i>in</i> Proceedings of the 16th World Conference on Earthquake Engineering.","ipdsId":"IP-080219","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":344164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":344163,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://usgs.github.io/shakecast/2017_16WCEE.html"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"597312aae4b0ec1a488718d7","contributors":{"authors":[{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lin, Kuo-wan 0000-0002-7520-8151 klin@usgs.gov","orcid":"https://orcid.org/0000-0002-7520-8151","contributorId":1539,"corporation":false,"usgs":true,"family":"Lin","given":"Kuo-wan","email":"klin@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kircher, C. A.","contributorId":194952,"corporation":false,"usgs":false,"family":"Kircher","given":"C.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":705901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705906,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Turner, L.","contributorId":194953,"corporation":false,"usgs":false,"family":"Turner","given":"L.","email":"","affiliations":[],"preferred":false,"id":705902,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slosky, Daniel 0000-0001-7407-3606 dslosky@usgs.gov","orcid":"https://orcid.org/0000-0001-7407-3606","contributorId":194954,"corporation":false,"usgs":true,"family":"Slosky","given":"Daniel","email":"dslosky@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705903,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70182152,"text":"70182152 - 2017 - Identifying movement patterns and spawning areas of Lake Trout in Yellowstone Lake","interactions":[],"lastModifiedDate":"2017-02-20T12:07:16","indexId":"70182152","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3802,"text":"Yellowstone Science","active":true,"publicationSubtype":{"id":10}},"title":"Identifying movement patterns and spawning areas of Lake Trout in Yellowstone Lake","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"National Park Service","usgsCitation":"Gresswell, R.E., Heredia, N.A., Romine, J.G., Gutowsky, L.F., Sandstrom, P.T., Parsley, M.J., Bigelow, P.E., Suski, C.D., and Ertel, B.D., 2017, Identifying movement patterns and spawning areas of Lake Trout in Yellowstone Lake: Yellowstone Science, v. 25, no. 1, p. 66-69.","productDescription":"4 p.","startPage":"66","endPage":"69","ipdsId":"IP-075220","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":335839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335798,"type":{"id":15,"text":"Index Page"},"url":"https://www.nps.gov/yell/learn/yellowstone-science.htm"}],"volume":"25","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ac0e2de4b0ce4410e7d5f4","contributors":{"authors":[{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":152031,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":669807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heredia, Nicholas A.","contributorId":181858,"corporation":false,"usgs":false,"family":"Heredia","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":669808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":669809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gutowsky, Lee F. G.","contributorId":181859,"corporation":false,"usgs":false,"family":"Gutowsky","given":"Lee","email":"","middleInitial":"F. G.","affiliations":[],"preferred":false,"id":669810,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sandstrom, Phillip T.","contributorId":181860,"corporation":false,"usgs":false,"family":"Sandstrom","given":"Phillip","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":669812,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parsley, Michael J. 0000-0003-0097-6364 mparsley@usgs.gov","orcid":"https://orcid.org/0000-0003-0097-6364","contributorId":2608,"corporation":false,"usgs":true,"family":"Parsley","given":"Michael","email":"mparsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":669811,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bigelow, Patricia E.","contributorId":181861,"corporation":false,"usgs":false,"family":"Bigelow","given":"Patricia","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":669813,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Suski, C. D.","contributorId":181862,"corporation":false,"usgs":false,"family":"Suski","given":"C.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":669814,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ertel, Brian D.","contributorId":181863,"corporation":false,"usgs":false,"family":"Ertel","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":669815,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70188352,"text":"70188352 - 2017 - Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California","interactions":[],"lastModifiedDate":"2018-03-16T11:29:21","indexId":"70188352","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California","docAbstract":"<p><span>Previously reported whole-rock δ</span><sup>18</sup><span>O values (5.6–7.8‰) for primitive quaternary mafic lavas from the southernmost Cascades (SMC) are often elevated (up to 1‰) relative to δ</span><sup>18</sup><span>O values expected for mafic magmas in equilibrium with mantle peridotite. Olivine, clinopyroxene, and plagioclase crystals were separated from 29 geochemically well-characterized mafic lavas for δ</span><sup>18</sup><span>O measurements by laser fluorination to assess modification of the mantle sources by ancient and modern subducted components. Oxygen isotope values of olivine phenocrysts in calc-alkaline lavas and contemporaneous high alumina olivine tholeiitic (HAOT) lavas generally exceed depleted mantle olivine values (~4.9–5.3‰). Modern addition of up to 6 wt% slab-derived fluid from Gorda serpentinized peridotite dehydration (~15‰) or chlorite dehydration (~10‰) within the serpentinized peridotite can provide the<span>&nbsp;</span></span><sup>18</sup><span>O enrichment detected in olivine phenocrysts (δ</span><sup>18</sup><span>O</span><sub>olivine</sub><span><span>&nbsp;</span>= 5.3–6.3‰) in calc-alkaline mafic lavas, and elevate<span>&nbsp;</span></span><sup>18</sup><span>O in overlying mantle lithosphere, as well. Specifically, although HAOT δ</span><sup>18</sup><span>O</span><sub>olivine</sub><span><span>&nbsp;</span>values (5.5–5.7‰) may reflect partial melting in heterogeneous<span>&nbsp;</span></span><sup>18</sup><span>O enriched mantle source domains that developed during multiple subduction events associated with terrane accretion (e.g., &lt;1 wt% of ~15‰ materials), an additional<span>&nbsp;</span></span><sup>18</sup><span>O enrichment of up to 2 wt% of 10–15‰ slab-derived hydrous fluids might be accommodated. The calc-alkaline primitive magmas appear to have experienced a continuous range of open system processes, which operate in the mantle and during rapid magma ascent to eruption, and occasionally post quench. Textural relationships and geochemistry of these lava samples are consistent with blends of mafic phenocrysts and degassed melts in varying states of<span>&nbsp;</span></span><sup>18</sup><span>O disequilibrium. In lenses of accumulated melt within peridotite near the base of the crust, coexisting olivine and clinopyroxene δ</span><sup>18</sup><span>O values probably are not at isotopic equilibrium because fluids introduced into the system perturbed the δ</span><sup>18</sup><span>O</span><sub>melt</sub><span><span>&nbsp;</span>values. A “sudden” melt extraction event interrupts<span>&nbsp;</span></span><sup>18</sup><span>O equilibration in phenocrysts and poorly mixed melt(s). Rapid ascent of volatile oversaturated primitive mafic magma through the crust appears to be accompanied by devolatilization and crystallization of anorthite-rich plagioclase with elevated δ</span><sup>18</sup><span>O</span><sub>plag</sub><span><span>&nbsp;</span>values. The (Sr/P)</span><sub>N</sub><span><span>&nbsp;</span>values for the whole rock geochemistry are consistent with a<span>&nbsp;</span></span><sup>87</sup><span>Sr/</span><sup>86</sup><span>Sr ~0.7027 slab-derived fluid addition into the infertile peridotite source of magmas, and melt devolatilization is recorded in the mixture of disequilibrium δ</span><sup>18</sup><span>O values for the constituent phases of lavas. Morbidity of the Gorda Plate as it undergoes intense deformation from the spreading ridge to the trench is likely a key factor to developing the carrying capacity of hydrous fluids and mineral phases in the slab subducting into the SMC mantle.</span></p>","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2017-5588","usgsCitation":"Underwood, S.J., and Clynne, M.A., 2017, Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California: American Mineralogist, v. 102, no. 2, p. 251-261, https://doi.org/10.2138/am-2017-5588.","productDescription":"11 p.","startPage":"251","endPage":"261","ipdsId":"IP-075965","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":352601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cascade Range","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.4920654296875,\n              39.9434364619742\n            ],\n            [\n              -120.794677734375,\n              39.9434364619742\n            ],\n            [\n              -120.794677734375,\n              40.990264773996884\n            ],\n            [\n              -122.4920654296875,\n              40.990264773996884\n            ],\n            [\n              -122.4920654296875,\n              39.9434364619742\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"102","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-01","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4be","contributors":{"authors":[{"text":"Underwood, Sandra J.","contributorId":192684,"corporation":false,"usgs":false,"family":"Underwood","given":"Sandra","email":"","middleInitial":"J.","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":697361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":697360,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70190678,"text":"70190678 - 2017 - Integration of genetic and demographic data to assess population risk in a continuously distributed species","interactions":[],"lastModifiedDate":"2018-03-26T14:33:09","indexId":"70190678","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Integration of genetic and demographic data to assess population risk in a continuously distributed species","docAbstract":"<p style=\"\"><span>The identification and demographic assessment of biologically meaningful populations is fundamental to species’ ecology and management. Although genetic tools are used frequently to identify populations, studies often do not incorporate demographic data to understand their respective population trends. We used genetic data to define subpopulations in a continuously distributed species. We assessed demographic independence and variation in population trends across the distribution. Additionally, we identified potential barriers to gene&nbsp;flow among subpopulations. We sampled greater sage-grouse (</span><i class=\"EmphasisTypeItalic \">Centrocercus urophasianus</i><span>) leks from across their range (≈175,000 Km</span><sup>2</sup><span>) in Wyoming and amplified DNA at 14 microsatellite loci for 1761 samples. Subsequently, we assessed population structure in unrelated individuals (</span><i class=\"EmphasisTypeItalic \">n</i><span>&nbsp;=&nbsp;872) by integrating results from multiple Bayesian clustering approaches and used the boundaries to inform our assessment of long-term population trends and lek activity over the period of 1995–2013. We identified four genetic clusters of which two northern ones showed demographic independence from the others. Trends in population size for the northwest subpopulation were statistically different from the other three genetic clusters and the northeast and southwest subpopulations demonstrated a general trend of increasing proportion of inactive leks over time. Population change from 1996 to 2012 suggested population growth in the southern subpopulations and decline, or neutral, change in the northern subpopulations. We suggest that sage-grouse subpopulations in northern Wyoming are at greater risk of extirpation than the southern subpopulations due to smaller census and effective population sizes and higher variability within subpopulations. Our research is an example of incorporating genetic and demographic data and provides guidance on the identification of subpopulations of conservation concern.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10592-016-0885-7","usgsCitation":"Fedy, B., Row, J.R., and Oyler-McCance, S.J., 2017, Integration of genetic and demographic data to assess population risk in a continuously distributed species: Conservation Genetics, v. 18, no. 1, p. 89-104, https://doi.org/10.1007/s10592-016-0885-7.","productDescription":"16 p.","startPage":"89","endPage":"104","ipdsId":"IP-060878","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":345643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"1","noUsgsAuthors":false,"publicationDate":"2016-09-22","publicationStatus":"PW","scienceBaseUri":"59b8f220e4b08b1644e0aeeb","contributors":{"authors":[{"text":"Fedy, Bradley C.","contributorId":40536,"corporation":false,"usgs":true,"family":"Fedy","given":"Bradley C.","affiliations":[],"preferred":false,"id":710146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Row, Jeffery R.","contributorId":178107,"corporation":false,"usgs":false,"family":"Row","given":"Jeffery","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":710147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":710148,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189597,"text":"70189597 - 2017 - Four new species of Eimeria (Apicomplexa: Eimeriidae) from Emoia spp. Skinks (Sauria: Scincidae), from Papua New Guinea and the Insular Pacific","interactions":[],"lastModifiedDate":"2017-07-18T12:03:52","indexId":"70189597","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Four new species of Eimeria (Apicomplexa: Eimeriidae) from Emoia spp. Skinks (Sauria: Scincidae), from Papua New Guinea and the Insular Pacific","docAbstract":"<p><span>Between September and November 1991, 54 adult skinks from 15 species were collected by hand or blowpipe from several localities on Rarotonga, Cook Islands, Ovalau Island, Fiji, and Papua New Guinea (PNG), and their feces were examined for coccidians. Species included 5 seaside skinks (</span><i>Emoia atrocostata</i><span>), 1 Pacific blue-tailed skink (</span><i>Emoia caeroleocauda</i><span>), 2 Fiji slender treeskinks (</span><i>Emoia concolor</i><span>), 15 white-bellied copper-striped skinks (</span><i>Emoia cyanura</i><span>), 1 Bulolo River forest skink (</span><i>Emoia guttata</i><span>), 6 dark-bellied copper-striped skinks (</span><i>Emoia impar</i><span>), 5 Papua five-striped skinks (</span><i>Emoia jakati</i><span>), 2 Papua slender treeskinks (</span><i>Emoia kordoana</i><span>), 3 Papua robust treeskinks (</span><i>Emoia longicauda</i><span>), 1 brown-backed forest skink (</span><i>Emoia loveridgei</i><span>), 3 Papua black-sided skinks (</span><i>Emoia pallidiceps</i><span>), 2 Papua white-spotted skinks (</span><i>Emoia physicae</i><span>), 2 Papua yellow-head skinks (</span><i>Emoia popei</i><span>), 1 Papua brown forest skink (</span><i>Emoia submetallica</i><span>), and 5 Fiji barred treeskinks (</span><i>Emoia trossula</i><span>) Species of<span>&nbsp;</span></span><i>Eimeria</i><span><span>&nbsp;</span>(</span><i>Ei</i><span>.) were detected from these<span>&nbsp;</span></span><i>Emoia</i><span><span>&nbsp;</span>(</span><i>Em</i><span>.) spp. and are described here as new. Oocysts of<span>&nbsp;</span></span><i><i>Eimeria iovai</i></i><span><span>&nbsp;</span>n. sp. from<span>&nbsp;</span></span><i>Em. pallidiceps</i><span><span>&nbsp;</span>from PNG were ellipsoidal with a bilayered wall (L × W) 26.5 × 18.1 μm, with a length/width ratio (L/W) of 1.1. Both micropyle and oocyst residuum were absent, but a fragmented polar granule was present. This eimerian also was found in<span>&nbsp;</span></span><i>Em. atrocostata</i><span><span>&nbsp;</span>from PNG. Oocysts of<span>&nbsp;</span></span><i><i>Eimeria kirkpatricki</i></i><span><span>&nbsp;</span>n. sp. from<span>&nbsp;</span></span><i>Em. atrocostata</i><span><span>&nbsp;</span>from PNG were ellipsoidal with a bilayered wall, 18.6 × 13.5 μm, L/W 1.4. A micropyle and oocyst residuum were absent, but a fragmented polar granule was present. This eimerian was also shared by<span>&nbsp;</span></span><i>Em. cyanura</i><span><span>&nbsp;</span>from the Cook Islands and Fiji,<span>&nbsp;</span></span><i>Em. impar</i><span>from the Cook Islands,<span>&nbsp;</span></span><i>Em. loveridgei</i><span><span>&nbsp;</span>from PNG,<span>&nbsp;</span></span><i>Em. pallidiceps</i><span>from PNG,<span>&nbsp;</span></span><i>Em. popei</i><span><span>&nbsp;</span>from PNG, and<span>&nbsp;</span></span><i>Em. submetallica</i><span><span>&nbsp;</span>from PNG. Oocysts of<span>&nbsp;</span></span><i><i>Eimeria stevejayuptoni</i></i><span><span>&nbsp;</span>n. sp. from<span>&nbsp;</span></span><i>Em. longicauda</i><span>were subspheroidal to ellipsoidal with a bilayered wall, 18.7 × 16.6 μm, L/W 1.1. A micropyle and oocyst residuum were absent, but a fragmented polar granule was present. Oocysts of<span>&nbsp;</span></span><i><i>Eimeria emoia</i></i><span><span>&nbsp;</span>n. sp. from<span>&nbsp;</span></span><i>Em. longicauda</i><span><span>&nbsp;</span>from PNG were cylindroidal with a bilayered wall, 29.2 × 15.7 μm, L/W 1.9. A micropyle and oocyst residuum were absent, but a polar granule was present. These are the first eimerians reported from<span>&nbsp;</span></span><i><i>Emoia</i></i><span><span>&nbsp;</span>spp. and they add to our growing knowledge of the coccidian fauna of scincid lizards of the South Pacific.</span></p>","language":"English","publisher":"American Society of Parasitologists","doi":"10.1645/16-67","usgsCitation":"McAllister, C.T., Duszynski, D.W., Austin, C., and Fisher, R.N., 2017, Four new species of Eimeria (Apicomplexa: Eimeriidae) from Emoia spp. Skinks (Sauria: Scincidae), from Papua New Guinea and the Insular Pacific: Journal of Parasitology, v. 103, no. 1, p. 103-110, https://doi.org/10.1645/16-67.","productDescription":"8 p.","startPage":"103","endPage":"110","ipdsId":"IP-078006","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":343987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Papua New Guinea","otherGeospatial":"Insular Pacific","volume":"103","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596f1e25e4b0d1f9f0640756","contributors":{"authors":[{"text":"McAllister, Chris T.","contributorId":22704,"corporation":false,"usgs":true,"family":"McAllister","given":"Chris","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":705341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duszynski, Donald W.","contributorId":87869,"corporation":false,"usgs":true,"family":"Duszynski","given":"Donald","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":705342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Austin, Christopher C.","contributorId":8772,"corporation":false,"usgs":true,"family":"Austin","given":"Christopher C.","affiliations":[],"preferred":false,"id":705343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705344,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192093,"text":"70192093 - 2017 - Rainfall-runoff of anthropogenic waste indicators from agricultural fields applied with municipal biosolids","interactions":[],"lastModifiedDate":"2021-05-28T14:06:34.304778","indexId":"70192093","displayToPublicDate":"2017-02-01T00:00:00","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":"Rainfall-runoff of anthropogenic waste indicators from agricultural fields applied with municipal biosolids","docAbstract":"<p><span>The presence of anthropogenic contaminants such as antimicrobials, flame-retardants, and plasticizers in runoff from agricultural fields applied with municipal biosolids may pose a potential threat to the environment. This study assesses the potential for rainfall-induced runoff of 69 anthropogenic waste indicators (AWIs), widely found in household and industrial products, from biosolids amended field plots. The agricultural field containing the test plots was treated with biosolids for the first time immediately prior to this study. AWIs present in soil and biosolids were isolated by continuous liquid-liquid extraction and analyzed by full-scan gas chromatography/mass spectrometry. Results for 18 AWIs were not evaluated due to their presence in field blank QC samples, and another 34 did not have sufficient detection frequency in samples to analyze trends in data. A total of 17 AWIs, including 4-nonylphenol, triclosan, and tris(2-butoxyethyl)phosphate, were present in runoff with acceptable data quality and frequency for subsequent interpretation. Runoff samples were collected 5&nbsp;days prior to and 1, 9, and 35&nbsp;days after biosolids application. Of the 17 AWIs considered, 14 were not detected in pre-application samples, or their concentrations were much smaller than in the sample collected one day after application. A range of trends was observed for individual AWI concentrations (typically from 0.1 to 10&nbsp;μg/L) over the course of the study, depending on the combination of partitioning and degradation mechanisms affecting each compound most strongly. Overall, these results indicate that rainfall can mobilize anthropogenic contaminants from biosolids-amended agricultural fields, directly to surface waters and redistribute them to terrestrial sites away from the point of application&nbsp;</span><i>via</i><span><span>&nbsp;</span>runoff. For 14 of 17 compounds examined, the potential for runoff remobilization during rainstorms persists even after three 100-year rainstorm-equivalent simulations and the passage of a month.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.033","usgsCitation":"Gray, J.L., Borch, T., Furlong, E.T., Davis, J., Yager, T., Yang, Y., and Kolpin, D.W., 2017, Rainfall-runoff of anthropogenic waste indicators from agricultural fields applied with municipal biosolids: Science of the Total Environment, v. 580, p. 83-89, https://doi.org/10.1016/j.scitotenv.2016.03.033.","productDescription":"7 p.","startPage":"83","endPage":"89","ipdsId":"IP-073810","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"links":[{"id":470105,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.033","text":"Publisher Index Page"},{"id":347164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"580","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59eeffaae4b0220bbd988fb9","contributors":{"authors":[{"text":"Gray, James L. 0000-0002-0807-5635 jlgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":1253,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"jlgray@usgs.gov","middleInitial":"L.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":714191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borch, Thomas","contributorId":195631,"corporation":false,"usgs":false,"family":"Borch","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":714192,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714193,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Jessica","contributorId":197745,"corporation":false,"usgs":false,"family":"Davis","given":"Jessica","affiliations":[],"preferred":false,"id":714194,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yager, Tracy tjyager@usgs.gov","contributorId":1881,"corporation":false,"usgs":true,"family":"Yager","given":"Tracy","email":"tjyager@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714195,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yang, Yun-Ya","contributorId":197746,"corporation":false,"usgs":false,"family":"Yang","given":"Yun-Ya","email":"","affiliations":[],"preferred":false,"id":714196,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714197,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70192059,"text":"70192059 - 2017 - Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach","interactions":[],"lastModifiedDate":"2017-10-19T14:44:32","indexId":"70192059","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Assessing conditions influencing the longitudinal distribution of exotic brown trout (<i>Salmo trutta</i>) in a mountain stream: a spatially-explicit modeling approach","title":"Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach","docAbstract":"<p><span>Trout species often segregate along elevational gradients, yet the mechanisms driving this pattern are not fully understood. On the Logan River, Utah, USA, exotic brown trout (</span><i class=\"EmphasisTypeItalic \">Salmo trutta</i><span>) dominate at low elevations but are near-absent from high elevations with native Bonneville cutthroat trout (</span><i class=\"EmphasisTypeItalic \">Onchorhynchus clarkii utah</i><span>). We used a spatially-explicit Bayesian modeling approach to evaluate how abiotic conditions (describing mechanisms related to temperature and physical habitat) as well as propagule pressure explained the distribution of brown trout in this system. Many covariates strongly explained redd abundance based on model performance and coefficient strength, including average annual temperature, average summer temperature, gravel availability, distance from a concentrated stocking area, and anchor ice-impeded distance from a concentrated stocking area. In contrast, covariates that exhibited low performance in models and/or a weak relationship to redd abundance included reach-average water depth, stocking intensity to the reach, average winter temperature, and number of days with anchor ice. Even if climate change creates more suitable summer temperature conditions for brown trout at high elevations, our findings suggest their success may be limited by other conditions. The potential role of anchor ice in limiting movement upstream is compelling considering evidence suggesting anchor ice prevalence on the Logan River has decreased significantly over the last several decades, likely in response to climatic changes. Further experimental and field research is needed to explore the role of anchor ice, spawning gravel availability, and locations of historical stocking in structuring brown trout distributions on the Logan River and elsewhere.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1322-z","usgsCitation":"Meredith, C.S., Budy, P., Hooten, M., and Oliveira Prates, M., 2017, Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach: Biological Invasions, v. 19, no. 2, p. 503-519, https://doi.org/10.1007/s10530-016-1322-z.","productDescription":"17 p.","startPage":"503","endPage":"519","ipdsId":"IP-069503","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Logan River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.8023681640625,\n              41.734941789858006\n            ],\n            [\n              -111.53594970703125,\n              41.734941789858006\n            ],\n            [\n              -111.53594970703125,\n              41.95336258301847\n            ],\n            [\n              -111.8023681640625,\n              41.95336258301847\n            ],\n            [\n              -111.8023681640625,\n              41.734941789858006\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"19","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"59e9b996e4b05fe04cd65cac","contributors":{"authors":[{"text":"Meredith, Christy S.","contributorId":197695,"corporation":false,"usgs":false,"family":"Meredith","given":"Christy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":714105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":714037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":714038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliveira Prates, Marcos","contributorId":197696,"corporation":false,"usgs":false,"family":"Oliveira Prates","given":"Marcos","email":"","affiliations":[],"preferred":false,"id":714106,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192213,"text":"70192213 - 2017 - Tidal triggering of earthquakes suggests poroelastic behavior on the San Andreas Fault","interactions":[],"lastModifiedDate":"2017-10-31T14:57:12","indexId":"70192213","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Tidal triggering of earthquakes suggests poroelastic behavior on the San Andreas Fault","docAbstract":"<p><span>Tidal triggering of earthquakes is hypothesized to provide quantitative information regarding the fault's stress state, poroelastic properties, and may be significant for our understanding of seismic hazard. To date, studies of regional or global earthquake catalogs have had only modest successes in identifying tidal triggering. We posit that the smallest events that may provide additional evidence of triggering go unidentified and thus we developed a technique to improve the identification of very small magnitude events. We identify events applying a method known as inter-station seismic coherence where we prioritize detection and discrimination over characterization. Here we show tidal triggering of earthquakes on the San Andreas Fault. We find the complex interaction of semi-diurnal and fortnightly tidal periods exposes both stress threshold and critical state behavior. Our findings reveal earthquake nucleation processes and pore pressure conditions – properties of faults that are difficult to measure, yet extremely important for characterizing earthquake physics and seismic hazards.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2016.12.014","usgsCitation":"Delorey, A., van der Elst, N., and Johnson, P., 2017, Tidal triggering of earthquakes suggests poroelastic behavior on the San Andreas Fault: Earth and Planetary Science Letters, v. 460, p. 164-170, https://doi.org/10.1016/j.epsl.2016.12.014.","productDescription":"7 p.","startPage":"164","endPage":"170","ipdsId":"IP-068597","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470100,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1341854","text":"Publisher Index Page"},{"id":347908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas Fault","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121,\n              35.5\n            ],\n            [\n              -120,\n              35.5\n            ],\n            [\n              -120,\n              36.4\n            ],\n            [\n              -121,\n              36.4\n            ],\n            [\n              -121,\n              35.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"460","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f98bb8e4b0531197af9ffb","contributors":{"authors":[{"text":"Delorey, Andrew","contributorId":189149,"corporation":false,"usgs":false,"family":"Delorey","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":714833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van der Elst, Nicholas 0000-0002-3812-1153 nvanderelst@usgs.gov","orcid":"https://orcid.org/0000-0002-3812-1153","contributorId":147858,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":714832,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Paul","contributorId":189150,"corporation":false,"usgs":false,"family":"Johnson","given":"Paul","email":"","affiliations":[],"preferred":false,"id":714834,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192403,"text":"70192403 - 2017 - Population genetics and demography unite ecology and evolution","interactions":[],"lastModifiedDate":"2018-03-26T14:21:29","indexId":"70192403","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Population genetics and demography unite ecology and evolution","docAbstract":"<div class=\"abstract svAbstract \" data-etype=\"ab\"><p id=\"spar0005\">The interplay of ecology and evolution has been a rich area of research for decades. A surge of interest in this area was catalyzed by the observation that evolution by natural selection can operate at the same contemporary timescales as ecological dynamics. Specifically, recent eco-evolutionary research focuses on how rapid adaptation influences ecology, and vice versa. Evolution by non-adaptive forces also occurs quickly, with ecological consequences, but understanding the full scope of ecology–evolution (eco–evo) interactions requires explicitly addressing population-level processes – genetic and demographic. We show the strong ecological effects of non-adaptive evolutionary forces and, more broadly, the value of population-level research for gaining a mechanistic understanding of eco–evo interactions. The breadth of eco-evolutionary research should expand to incorporate the breadth of evolution itself.</p></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.tree.2016.12.002","usgsCitation":"Lowe, W.H., Kovach, R., and Allendorf, F.W., 2017, Population genetics and demography unite ecology and evolution: Trends in Ecology and Evolution, v. 32, no. 2, p. 141-152, https://doi.org/10.1016/j.tree.2016.12.002.","productDescription":"12 p.","startPage":"141","endPage":"152","ipdsId":"IP-077980","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":470104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.tree.2016.12.002","text":"Publisher Index Page"},{"id":347385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a6e4b0220bbd9d9f61","contributors":{"authors":[{"text":"Lowe, Winsor H.","contributorId":126722,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor","email":"","middleInitial":"H.","affiliations":[{"id":6577,"text":"University of Montana, Division of Biological Sciences, Missoula, MT, 59812, USA.","active":true,"usgs":false}],"preferred":false,"id":715705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kovach, Ryan 0000-0001-5402-2123 rkovach@usgs.gov","orcid":"https://orcid.org/0000-0001-5402-2123","contributorId":145914,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":715704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allendorf, Fred W.","contributorId":124525,"corporation":false,"usgs":false,"family":"Allendorf","given":"Fred","email":"","middleInitial":"W.","affiliations":[{"id":5084,"text":"Division of Biological Sciences, University of Montana, Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":715706,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}