{"pageNumber":"70","pageRowStart":"1725","pageSize":"25","recordCount":10957,"records":[{"id":70216464,"text":"70216464 - 2019 - A shallow rift basin segmented in space and time: The southern San Luis Basin, Rio Grande rift, northern New Mexico, U.S.A.","interactions":[],"lastModifiedDate":"2020-11-20T14:11:15.783736","indexId":"70216464","displayToPublicDate":"2019-12-01T07:59:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3310,"text":"Rocky Mountain Geology","active":true,"publicationSubtype":{"id":10}},"title":"A shallow rift basin segmented in space and time: The southern San Luis Basin, Rio Grande rift, northern New Mexico, U.S.A.","docAbstract":"

Interpretation of gravity, magnetotelluric, and aeromagnetic data in conjunction with geologic constraints reveals details of basin geometry, thickness, and spatiotemporal evolution of the southern San Luis Basin, one of the major basins of the northern Rio Grande rift. Spatial variations of low-density basin-fill thickness are estimated primarily using a 3D gravity inversion method that improves on previous modeling efforts by separating the effects of the low-density basin fill from the effects of pre-rift rocks. The basin is found to be significantly narrower—and more complex in the subsurface—than indicated or implied by previous modeling efforts. The basin is also estimated to be significantly shallower than previously estimated. Five distinct subbasins are recognized within the broader southern San Luis Basin. The oldest and shallowest subbasin is the Las Mesitas graben along the northwestern basin margin, formed during the Oligocene transition from Southern Rocky Mountain volcanic field magmatism to rifting. In this subbasin, sediments are estimated to reach a maximum thickness of ~400 m within a north–south elongated structural depression. Other subbasins that likely initially developed during the Miocene are the dominant tectonic features in the southern San Luis Basin. This includes the Tres Orejas subbasin, which formed in the southwestern portion of the basin by the Embudo fault zone and a hypothesized fault zone along its western margin. This subbasin reaches a maximum thickness of ~2 km, as indicated by magnetotelluric and gravity modeling. The Sunshine Valley, Questa, and Taos subbasins occupy the eastern part of the southern San Luis Basin. The southern Sangre de Cristo fault zone is the dominant tectonic feature that controlled their development after ~20 Ma. The east-down Gorge fault zone controlled the western margins of significant parts of these eastern subbasins, although much of the Taos subbasin may be superimposed on the Tres Orejas subbasin. Maximum low-density basin-fill thicknesses are estimated to be 1.2 km for the Sunshine Valley subbasin, 800 m for the Questa subbasin, and 1.8 km for the Taos subbasin. Subbasin-forming tectonic activity along the Gorge fault zone and within the Tres Orejas subbasin ceased by the end of the development of the largely Pliocene Taos Plateau volcanic field. After that, rift-related subsidence became more narrowly centered on the eastern margin of the basin, controlled mainly by the linked Embudo and southern Sangre de Cristo fault zones.

","language":"English","publisher":"Rocky Mountain Geology","doi":"10.24872/rmgjournal.54.2.97","usgsCitation":"Drenth, B.J., Grauch, V.J., Turner, K.J., Rodriguez, B.D., Thompson, R., and Bauer, P.W., 2019, A shallow rift basin segmented in space and time: The southern San Luis Basin, Rio Grande rift, northern New Mexico, U.S.A.: Rocky Mountain Geology, v. 54, no. 2, p. 97-131, https://doi.org/10.24872/rmgjournal.54.2.97.","productDescription":"35 p.","startPage":"97","endPage":"131","ipdsId":"IP-104797","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":459077,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.24872/rmgjournal.54.2.97","text":"Publisher Index Page"},{"id":380645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"San Luis Basin, Rio Grande rift","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.45751953125,\n 35.817813158696616\n ],\n [\n -104.78759765625,\n 35.817813158696616\n ],\n [\n -104.78759765625,\n 37.01132594307015\n ],\n [\n -106.45751953125,\n 37.01132594307015\n ],\n [\n -106.45751953125,\n 35.817813158696616\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grauch, V. J. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":152256,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":805197,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805198,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":805199,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bauer, Paul W.","contributorId":145562,"corporation":false,"usgs":false,"family":"Bauer","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":16150,"text":"New Mexico Bureau of Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":805200,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217620,"text":"70217620 - 2019 - A shrubbier future: Forest transformation in the eastern Jemez Mountains","interactions":[],"lastModifiedDate":"2021-01-25T15:25:03.465327","indexId":"70217620","displayToPublicDate":"2019-11-30T09:24:16","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"A shrubbier future: Forest transformation in the eastern Jemez Mountains","docAbstract":"

No abstract available.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Fire ghosts","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","usgsCitation":"Allen, C.D., 2019, A shrubbier future: Forest transformation in the eastern Jemez Mountains, chap. of Fire ghosts, p. 85-88.","productDescription":"4 p.","startPage":"85","endPage":"88","ipdsId":"IP-109025","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":382546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.875,\n 35.715298012125295\n ],\n [\n -106.31469726562499,\n 35.715298012125295\n ],\n [\n -106.31469726562499,\n 36.37485644939407\n ],\n [\n -106.875,\n 36.37485644939407\n ],\n [\n -106.875,\n 35.715298012125295\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":808921,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70214574,"text":"70214574 - 2019 - Wave-current interaction between Hurricane Matthew wave fields and the Gulf Stream","interactions":[],"lastModifiedDate":"2020-09-30T14:08:22.311228","indexId":"70214574","displayToPublicDate":"2019-11-29T09:03:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2426,"text":"Journal of Physical Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Wave-current interaction between Hurricane Matthew wave fields and the Gulf Stream","docAbstract":"Hurricanes interact with the Gulf Stream in the South Atlantic Bight (SAB) through a wide variety of processes, which are crucial to understand for prediction of open-ocean and coastal hazards during storms. However, it remains unclear how waves are modified by large-scale ocean currents under storm conditions, when waves are aligned with the storm-driven circulation and tightly coupled to the overlying wind field. Hurricane Matthew (2016) impacted the US southeast coast, causing extensive coastal change due to large waves and elevated water levels. The hurricane traveled on the continental shelf parallel to the SAB coastline, with the right side of the hurricane directly over the Gulf Stream. Using the Coupled Ocean Atmosphere Wave Sediment Transport Modeling System, we investigate wave-current interaction between Hurricane Matthew and the Gulf Stream. The model simulates ocean currents and waves over a grid encompassing the US east coast, with varied coupling of the hydrodynamic and wave components to isolate the effect of the currents on the waves, and the effect of the Gulf Stream relative to storm-driven circulation. The Gulf Stream modifies the direction of the storm-driven currents beneath the right side of the hurricane. Waves transitioned from following currents that result in wave lengthening, through negative current gradients that result in wave steepening and dissipation. Wave-current interaction over the Gulf Stream modified maximum coastal total water levels, and changed incident wave directions at the coast by up to 20°, with strong implications for the morphodynamic response and stability of the coast to the hurricane.","language":"English","publisher":"American Meteorology Society","doi":"10.1175/JPO-D-19-0124.1","usgsCitation":"Hegermiller, C., Warner, J., Olabarrieta, M., and Sherwood, C.R., 2019, Wave-current interaction between Hurricane Matthew wave fields and the Gulf Stream: Journal of Physical Oceanography, v. 49, no. 11, p. 2883-2900, https://doi.org/10.1175/JPO-D-19-0124.1.","productDescription":"18 p.","startPage":"2883","endPage":"2900","ipdsId":"IP-109198","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459087,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jpo-d-19-0124.1","text":"Publisher Index Page"},{"id":378900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"East Coast, Gulf Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.12109375,\n 16.97274101999902\n ],\n [\n -78.046875,\n 24.5271348225978\n ],\n [\n -73.47656249999999,\n 36.1733569352216\n ],\n [\n -65.390625,\n 44.213709909702054\n ],\n [\n -68.73046875,\n 46.07323062540835\n ],\n [\n -80.85937499999999,\n 34.016241889667015\n ],\n [\n -92.63671875,\n 32.24997445586331\n ],\n [\n -101.77734374999999,\n 25.799891182088334\n ],\n [\n -97.3828125,\n 19.145168196205297\n ],\n [\n -90.17578124999999,\n 16.29905101458183\n ],\n [\n -89.12109375,\n 16.97274101999902\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hegermiller, Christie 0000-0002-6383-7508","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":241895,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":true,"id":800130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":800131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":211373,"corporation":false,"usgs":false,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":800132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":800133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211034,"text":"70211034 - 2019 - The 2018 update of the US National Seismic Hazard Model: Overview of model and implications","interactions":[],"lastModifiedDate":"2020-07-13T12:34:13.1599","indexId":"70211034","displayToPublicDate":"2019-11-28T15:52:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 update of the US National Seismic Hazard Model: Overview of model and implications","docAbstract":"

During 2017–2018, the National Seismic Hazard Model for the conterminous United States was updated as follows: (1) an updated seismicity catalog was incorporated, which includes new earthquakes that occurred from 2013 to 2017; (2) in the central and eastern United States (CEUS), new ground motion models were updated that incorporate updated median estimates, modified assessments of the associated epistemic uncertainties and aleatory variabilities, and new soil amplification factors; (3) in the western United States (WUS), amplified shaking estimates of long-period ground motions at sites overlying deep sedimentary basins in the Los Angeles, San Francisco, Seattle, and Salt Lake City areas were incorporated; and (4) in the conterminous United States, seismic hazard is calculated for 22 periods (from 0.01 to 10 s) and 8 uniform VS30 maps (ranging from 1500 to 150 m/s). We also include a description of updated computer codes and modeling details. Results show increased ground shaking in many (but not all) locations across the CEUS (up to ~30%), as well as near the four urban areas overlying deep sedimentary basins in the WUS (up to ~50%). Due to population growth and these increased hazard estimates, more people live or work in areas of high or moderate seismic hazard than ever before, leading to higher risk of undesirable consequences from forecasted future ground shaking.

","language":"English","publisher":"Sage","doi":"10.1177/8755293019878199","usgsCitation":"Petersen, M.D., Shumway, A., Powers, P.M., Mueller, C., Moschetti, M.P., Frankel, A.D., Rezaeian, S., McNamara, D.E., Luco, N., Boyd, O.S., Rukstales, K.S., Jaiswal, K.S., Thompson, E.M., Hoover, S.M., Clayton, B., Field, E., and Zeng, Y., 2019, The 2018 update of the US National Seismic Hazard Model: Overview of model and implications: Earthquake Spectra, v. 36, no. 1, p. 5-41, https://doi.org/10.1177/8755293019878199.","productDescription":"37 p.","startPage":"5","endPage":"41","ipdsId":"IP-109680","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":437273,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RQMREV","text":"USGS data release","linkHelpText":"Data Release for Additional Period and Site Class Data for the 2018 National Seismic Hazard Model for the Conterminous United States (ver. 1.1, February 2020)"},{"id":437272,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WT5OVB","text":"USGS data release","linkHelpText":"Data Release for 2018 Update of the U.S. National Seismic Hazard Model"},{"id":376269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n 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Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5117","displayTitle":"Groundwater-Flow Model and Analysis of Groundwater and Surface-Water Interactions for the Big Sioux Aquifer, Sioux Falls, South Dakota","title":"Groundwater-flow model and analysis of groundwater and surface-water interactions for the Big Sioux aquifer, Sioux Falls, South Dakota","docAbstract":"

The city of Sioux Falls, in southeastern South Dakota, is the largest city in South Dakota. The U.S. Geological Survey (USGS), in cooperation with the city of Sioux Falls, completed a groundwater-flow model to use for improving the understanding of groundwater-flow processes, estimating hydrogeologic properties, and analyzing groundwater and surface-water interactions for the Big Sioux aquifer in the model area.

The model area includes the Big Sioux aquifer and the underlying hydrogeologic units from Dell Rapids, South Dakota, to the confluence of the Big Sioux River and the outlet of the Sioux Falls Diversion Channel in eastern Sioux Falls, S. Dak. The Big Sioux aquifer is the primary aquifer in the model area and the focus of the groundwater-flow model. The Big Sioux River is the largest stream in the model area and is in hydraulic connection with the Big Sioux aquifer.

A conceptual model for the area was constructed and includes a characterization of the hydrogeologic framework, analysis and construction of potentiometric surfaces, and summary of estimated water budget components in the model area. The primary hydrogeologic units in the model area consist of (1) the Big Sioux aquifer, (2) a glacial till confining unit, and (3) bedrock aquifers (Split Rock Creek and Sioux Quartzite aquifers). Sources of groundwater recharge included infiltration of precipitation, stream seepage, and groundwater exchanges among the hydraulically connected Big Sioux aquifer, glacial till confining unit, and bedrock aquifers. Groundwater losses included evapotranspiration, groundwater discharge to streams, and groundwater withdrawal to supply water-use needs.

A numerical groundwater-flow model (numerical model) was constructed and was used to simulate all aspects of the conceptual model for predevelopment (steady-state) and time-varying (transient) monthly conditions for 1950–2017. The numerical model was constructed using the USGS modular hydrologic simulation program, MODFLOW–6, and was calibrated using the Parameter ESTimation software, PEST++.

The transient numerical model was calibrated for steady-state and transient monthly conditions for 1950–2017. Calibration targets were observations of hydraulic head, changes in hydraulic head, monthly mean streamflow (as a rate), and cumulative monthly stream discharge (as a volume). Parameters adjusted during model calibration were horizontal and vertical hydraulic conductivity, specific storage, specific yield, recharge and evapotranspiration multipliers, and streambed hydraulic conductivity. Horizontal and vertical hydraulic conductivity were estimated at pilot points distributed within the model area; specific storage and specific yield were assigned to uniform values in each layer in the model area; recharge and evapotranspiration multipliers were assigned uniformly for every stress period in the numerical model; and streambed hydraulic conductivity values were assigned uniformly between stream confluences.

The final calibrated parameter values of horizontal and vertical hydraulic conductivity, specific yield, specific storage, streambed hydraulic conductivity, recharge, and evapotranspiration were considered reasonable for the hydrogeologic materials and conditions in the model area for 1950–2017.

Overall, simulated hydraulic head altitudes had a linear regression coefficient of determination (R2) of 0.48. Hydraulic head altitude residuals for the glacial till confining unit and bedrock aquifers were typically greater in magnitude when compared to residuals in the Big Sioux aquifer, but simulated hydraulic head altitudes in the Big Sioux aquifer compared favorably with mean observed hydraulic head altitudes and had a linear regression R2 of 0.93.

Simulated streamflow hydrographs matched the general trends of observed increases and decreases in streamflow for USGS streamgages 06482000 (Big Sioux River at Sioux Falls, S. Dak.) and 06482020 (Big Sioux River at North Cliff Avenue at Sioux Falls, S. Dak.), but larger streamflows were overestimated at the first streamgage and underestimated at the second streamgage. The numerical model reasonably estimated cumulative monthly stream discharge for the first 10–15 years of available streamflow records at both USGS streamgages. After the first 10–15 years of available streamflow record, cumulative monthly stream discharge was closely estimated for USGS streamgage 06482000 and underestimated at USGS streamgage 06482020.

Composite sensitivities without regularization were calculated by PEST++ for the calibrated numerical model parameters and were averaged by parameter group. The parameter group with the highest mean composite sensitivity was the recharge multiplier parameter group.

Model simplifications, assumptions, and limitations were necessary for construction of the conceptual and numerical models and for calibration efficiency. Spatial simplification of hydraulic properties could cause the numerical model to misrepresent reactions to changes in localized stresses, such as additional demands for groundwater withdrawal. The numerical model was temporally discretized into monthly periods and required scaling daily rates into representative monthly rates for model input and calibration targets. Based on the comparison between the observed and simulated groundwater levels, monthly mean streamflow and cumulative monthly stream discharge, and general groundwater distribution and flow, the numerical model favorably simulated the flow in the Big Sioux aquifer.

Eventual capture was calculated in the model area using a steady-state numerical groundwater-flow model. The eventual capture map shows areas of higher streamflow capture adjacent to the Big Sioux River north of the city of Sioux Falls and along the lower part of the Sioux Falls Diversion Channel, and areas of lower streamflow capture along aquifer boundaries and near the southern Sioux Quartzite barrier.

The timing of capture was determined using a transient numerical groundwater-flow model to determine the likely captured water sources for 30 years of groundwater withdrawal at three hypothetical wells using three continuous withdrawal rates (112.5, 450.0, and 900.0 gallons per minute). Supply for all three hypothetical wells became capture-dominated after only a short period of continuous withdrawal. Capture stabilized after about 10–15 years for well A, and after 20–25 years for well B, and after about 10–15 years for well C.

The groundwater-flow model is a suitable tool to use for improving the understanding of groundwater-flow processes, estimating hydrogeologic properties, and analyzing groundwater and surface-water interactions for the Big Sioux aquifer near Sioux Falls, S. Dak. The numerical model can be used to simulate hydrologic scenarios, advance understanding of groundwater budgets, compute system response to stress, and determine likely sources of water supplied to wells.

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Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-11-27","noUsgsAuthors":false,"publicationDate":"2019-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Kyle W. 0000-0002-8723-0110","orcid":"https://orcid.org/0000-0002-8723-0110","contributorId":201549,"corporation":false,"usgs":true,"family":"Davis","given":"Kyle W.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eldridge, William G. 0000-0002-3562-728X","orcid":"https://orcid.org/0000-0002-3562-728X","contributorId":208529,"corporation":false,"usgs":true,"family":"Eldridge","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773378,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valder, Joshua F. 0000-0003-3733-8868 jvalder@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-8868","contributorId":139256,"corporation":false,"usgs":true,"family":"Valder","given":"Joshua","email":"jvalder@usgs.gov","middleInitial":"F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":773380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valseth, Kristen J. 0000-0003-4257-6094","orcid":"https://orcid.org/0000-0003-4257-6094","contributorId":203447,"corporation":false,"usgs":true,"family":"Valseth","given":"Kristen","email":"","middleInitial":"J.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773381,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207442,"text":"70207442 - 2019 - Holocene earthquake history and slip rate of the southern Teton fault, Wyoming, USA","interactions":[],"lastModifiedDate":"2020-07-09T14:28:34.224535","indexId":"70207442","displayToPublicDate":"2019-11-21T13:12:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Holocene earthquake history and slip rate of the southern Teton fault, Wyoming, USA","docAbstract":"The 72-km-long Teton normal fault bounds the eastern base of the Teton Range in northwestern Wyoming, USA. Although geomorphic surfaces along the fault record latest Pleistocene to Holocene fault movement, the postglacial earthquake history of the fault has remained enigmatic. We excavated a paleoseismic trench at the Buffalo Bowl site along the southernmost part of the fault to determine its Holocene rupture history and slip rate. At the site, ∼6.3 m of displacement postdates an early Holocene (ca. 10.5 ka) alluvial-fan surface. We document evidence of three surface-faulting earthquakes based on packages of scarp-derived colluvium that postdate the alluvial-fan units. Bayesian modeling of radiocarbon and luminescence ages yields earthquake times of ca. 9.9 ka, ca. 7.1 ka, and ca. 4.6 ka, forming the longest, most complete paleoseismic record of the Teton fault. We integrate these data with a displaced deglacial surface 4 km NE at Granite Canyon to calculate a postglacial to mid-Holocene (14.4−4.6 ka) slip rate of ∼1.1 mm/yr. Our analysis also suggests that the postglacial to early Holocene (14.4−9.9 ka) slip rate exceeds the Holocene (9.9−4.6 ka) rate by a factor of ∼2 (maximum of 3); however, a uniform rate for the fault is possible considering the 95% slip-rate errors. The ∼5 k.y. elapsed time since the last rupture of the southernmost Teton fault implies a current slip deficit of ∼4−5 m, which is possibly explained by spatially/temporally incomplete paleoseismic data, irregular earthquake recurrence, and/or variable per-event displacement. Our study emphasizes the importance of minimizing slip-rate uncertainties by integrating paleoseismic and geomorphic data sets and capturing multiple earthquake cycles.","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35363.1","usgsCitation":"DuRoss, C., Gold, R.D., Briggs, R.W., Delano, J.E., Ostenaa, D.A., Zellman, M., Cholewinski, N., Wittke, S., and Mahan, S.A., 2019, Holocene earthquake history and slip rate of the southern Teton fault, Wyoming, USA: Geological Society of America Bulletin, v. 132, no. 7-8, p. 1566-1586, https://doi.org/10.1130/B35363.1.","productDescription":"21 p.","startPage":"1566","endPage":"1586","ipdsId":"IP-111318","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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A.","contributorId":39467,"corporation":false,"usgs":false,"family":"Ostenaa","given":"Dean","email":"","middleInitial":"A.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":778055,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zellman, Mark","contributorId":167020,"corporation":false,"usgs":false,"family":"Zellman","given":"Mark","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":778056,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cholewinski, Nicole","contributorId":221401,"corporation":false,"usgs":false,"family":"Cholewinski","given":"Nicole","email":"","affiliations":[{"id":40365,"text":"GEI Consultants","active":true,"usgs":false}],"preferred":false,"id":778057,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wittke, 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2019","interactions":[],"lastModifiedDate":"2019-11-21T12:57:42","indexId":"ofr20191129","displayToPublicDate":"2019-11-20T16:32:35","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1129","displayTitle":"Peak Streamflow and Stages at Selected Streamgages on the Arkansas River in Oklahoma and Arkansas, May to June 2019","title":"Peak streamflow and stages at selected streamgages on the Arkansas River in Oklahoma and Arkansas, May to June 2019","docAbstract":"

As much as 22 inches of rain fell in Oklahoma in May 2019, resulting in historic flooding along the Arkansas River in Oklahoma and Arkansas. The flooding along the Arkansas River and its tributaries that began in May continued into June 2019. Peaks of record were measured at 12 U.S. Geological Survey (USGS) streamgages on various streams in eastern and northeastern Oklahoma. This report documents the peak streamflows and stages for seven selected streamgages along the Arkansas River in Oklahoma and Arkansas. Most of the flood peaks occurred from May 26 to June 4, 2019. The historic flooding caused homes to fall into the river as a result of bank erosion, forced some towns to be evacuated, and resulted in the highest flood depths in Tulsa, Oklahoma, since 1986. Along the Arkansas River, peak streamflows were recorded at six of the seven selected USGS streamgages, with the seventh streamgage on the Arkansas River having the second highest peak of record at that site since regulation began.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191129","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency and the U.S. Army Corps of Engineers","usgsCitation":"Lewis, J.M., and Trevisan, A.R., 2019, Peak streamflow and stages at selected streamgages on the Arkansas River in Oklahoma and Arkansas, May to June 2019: U.S. Geological Survey Open-File Report 2019–1129, 10 p., https://doi.org/10.3133/ofr20191129.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-112483","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":369335,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1129/ofr20191129.pdf","text":"Report","size":"4.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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\"}}]}","contact":"

Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-11-20","noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Lewis, Jason M. 0000-0001-5337-1890 jmlewis@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1890","contributorId":3854,"corporation":false,"usgs":true,"family":"Lewis","given":"Jason","email":"jmlewis@usgs.gov","middleInitial":"M.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":774902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trevisan, A.R. 0000-0002-7295-145X","orcid":"https://orcid.org/0000-0002-7295-145X","contributorId":220399,"corporation":false,"usgs":true,"family":"Trevisan","given":"A.R.","email":"","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":774903,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215266,"text":"70215266 - 2019 - Phenotypic plasticity or a reproductive dead end? Primnoa pacifica (Cnidaria: Alcyonacea) in the southeastern Alaska region","interactions":[],"lastModifiedDate":"2020-10-15T13:25:55.053368","indexId":"70215266","displayToPublicDate":"2019-11-20T09:08:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Phenotypic plasticity or a reproductive dead end? Primnoa pacifica (Cnidaria: Alcyonacea) in the southeastern Alaska region","title":"Phenotypic plasticity or a reproductive dead end? Primnoa pacifica (Cnidaria: Alcyonacea) in the southeastern Alaska region","docAbstract":"

Red tree corals (Primnoa pacifica) are abundant in the eastern Gulf of Alaska, from the glacial fjords of Southeast Alaska where they emerge to as shallow as 6 m, to the continental shelf edge and seamounts where they are more commonly found at depths greater than 150 – 500 m. This keystone species forms large thickets, creating habitat for many associated species, including economically valuable fishes and crabs, and so are important benthic suspension feeders in this region. Though the reproductive periodicity of this species was reported in 2014 from a shallow fjord (Tracy Arm), this study examined reproductive ecologies from 8 sites – two within Glacier Bay National Park and Preserve, three on the continental shelf edge, one within Endicott Arm (Holkham Bay) and two time points from the Tracy Arm (Holkham Bay) study. Male reproductive traits were similar at all sites but there were distinct differences in oogenesis. Though per polyp fecundity mostly showed no significant difference between sites, there was a non-significant trend of increasing number of oocytes with depth. In addition, the average oocyte size from Tracy Arm (the shallowest site) was 105 μm, whereas from Shutter Ridge (one of the deepest sites) the average size was 309 μm. Moreover, the maximum oocyte size at Endicott Arm was 221 μm and at Tracy Arm was 802 μm (both shallow sites), whereas at Dixon Entrance (a deep site) it was 2120 μm, a difference not usually observed within a single species. We propose two theories to explain the observed differences, (a) this species shows great phenotypic plasticity in reproductive ecology, adjusting to different environmental variables based on energetic need and potentially demonstrating micro-evolution; or (b) the fjord sites are at a reproductive dead end, with the stress of shallow-water conditions effectively preventing gametogenesis reaching full potential and likely limiting successful reproductive events from occurring, at least on a regular basis.

","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2019.00709","usgsCitation":"Waller, R.G., Stone, R.P., Rice, L., Johnstone, J., Rossin, A.M., Hartill, E., Feehan, K., and Morrison, C., 2019, Phenotypic plasticity or a reproductive dead end? Primnoa pacifica (Cnidaria: Alcyonacea) in the southeastern Alaska region: Frontiers in Marine Science, v. 6, 709, 14 p., https://doi.org/10.3389/fmars.2019.00709.","productDescription":"709, 14 p.","ipdsId":"IP-109052","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":459144,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2019.00709","text":"Publisher Index Page"},{"id":379359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -142.20703125,\n 54.470037612805754\n ],\n [\n -128.671875,\n 54.470037612805754\n ],\n [\n -128.671875,\n 60.50052541051131\n ],\n [\n -142.20703125,\n 60.50052541051131\n ],\n [\n -142.20703125,\n 54.470037612805754\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Waller, Rhian G.","contributorId":195852,"corporation":false,"usgs":false,"family":"Waller","given":"Rhian","email":"","middleInitial":"G.","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":801391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Robert P.","contributorId":190569,"corporation":false,"usgs":false,"family":"Stone","given":"Robert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":801392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rice, Lauren","contributorId":243033,"corporation":false,"usgs":false,"family":"Rice","given":"Lauren","email":"","affiliations":[{"id":48620,"text":"Darling Marine Center, University of Maine and Oregon Institute of Marine Biology, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":801393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnstone, Julia","contributorId":243034,"corporation":false,"usgs":false,"family":"Johnstone","given":"Julia","email":"","affiliations":[{"id":48621,"text":"Darling Marine Center, University of Maine","active":true,"usgs":false}],"preferred":false,"id":801394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rossin, Ashley M.","contributorId":243035,"corporation":false,"usgs":false,"family":"Rossin","given":"Ashley","email":"","middleInitial":"M.","affiliations":[{"id":48622,"text":"Darling Marine Center, University of Maine and University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":801395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hartill, Elise","contributorId":243036,"corporation":false,"usgs":false,"family":"Hartill","given":"Elise","email":"","affiliations":[{"id":48621,"text":"Darling Marine Center, University of Maine","active":true,"usgs":false}],"preferred":false,"id":801396,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Feehan, Keri","contributorId":243037,"corporation":false,"usgs":false,"family":"Feehan","given":"Keri","email":"","affiliations":[{"id":48621,"text":"Darling Marine Center, University of Maine","active":true,"usgs":false}],"preferred":false,"id":801397,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morrison, Cheryl 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":202644,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":801398,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70206053,"text":"sim3444 - 2019 - Potentiometric surface of groundwater-level altitudes near the planned Highway 270 bypass, east of Hot Springs, Arkansas, July–August 2017","interactions":[],"lastModifiedDate":"2019-11-19T17:19:14","indexId":"sim3444","displayToPublicDate":"2019-11-19T13:49:10","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3444","displayTitle":"Potentiometric Surface of Groundwater-Level Altitudes Near the Planned Highway 270 Bypass, East of Hot Springs, Arkansas, July–August 2017","title":"Potentiometric surface of groundwater-level altitudes near the planned Highway 270 bypass, east of Hot Springs, Arkansas, July–August 2017","docAbstract":"

The Ouachita Mountains aquifer system potentiometric-surface map is one component of the Hot Springs Bypass Groundwater Monitoring Project. The potentiometric-surface map provides a baseline assessment of shallow groundwater levels and flow directions before the construction of the Arkansas Department of Transportation planned extension of the Highway 270 bypass, east of Hot Springs, Arkansas. The map provides data regarding status of groundwater levels and potential effects on the recharge area in the Hot Springs National Park and to groundwater that supplies water to domestic users near the Highway 270 bypass.

Groundwater levels from 66 wells were measured in July–August 2017. Fifty nine of the 66 groundwater-level altitudes measured, along with select surface-water features and springs, were used to construct the Ouachita Mountains aquifer system potentiometric-surface map. The potentiometric surface, a two-dimensional representation, shows groundwater-level altitudes ranging from a maximum of 766 ft above the North American Vertical Datum of 1988 (NAVD 88) to a minimum of 443 ft NAVD 88. The spring altitudes on the potentiometric-surface map range from 534 ft to 927 ft above NAVD 88. The study area, located in the Ouachita Mountains physiographic section of the Ouachita physiographic province, comprises narrow valleys and high ridges of Stanley Shale, Hot Springs Sandstone, Arkansas Novaculite, Missouri Mountain-Polk Creek Shale, and Bigfork Chert. The highest groundwater-level altitudes observed were in the Hot Springs Sandstone, Arkansas Novaculite, and Missouri Mountain-Polk Creek Shale. The springs discharge in outcrop areas of the Stanley Shale, Bigfork Chert, and Arkansas novaculite. The planned Highway 270 bypass will cut across ridges and valleys comprising these formations and, very importantly, across areas with elevations above 660 ft above NAVD 88 that define the hot springs recharge zone.

This potentiometric-surface map defines the status of the shallow groundwater potentiometric surface near the Highway 270 bypass prior to initiation of construction activities. A post-construction potentiometric map is planned. It must be noted that shallow groundwater levels are also subject to climatic effects including changes in amount and timing of precipitation and changes in temperature.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3444","collaboration":"Prepared in cooperation with the Arkansas Department of Transportation and the National Park Service","usgsCitation":"Nottmeier, A.M., and Hays, P.D., 2019, Potentiometric surface of groundwater-level altitudes near the planned Highway 270 bypass, east of Hot Springs, Arkansas, July–August 2017: U.S. Geological Survey Scientific Investigations Map 3444, 13 p., 1 sheet, https://doi.org/10.3133/sim3444.","productDescription":"Pamphlet: v, 13 p.; Sheet: 22 x 28 inches; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092242","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":369331,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TD9WK0","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Datasets of the Potentiometric Surface of Groundwater-Level Altitudes Near the Planned Highway 270 Bypass, East of Hot Springs, Arkansas, July–August 2017"},{"id":369328,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3444/coverthb.jpg"},{"id":369329,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3444/sim3444.pdf","text":"Sheet ","size":"2.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3444 ","linkHelpText":"– Potentiometric-surface map for the Ouachita Mountains aquifer, July–August 2017"},{"id":369330,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3444/sim3444_pamphlet.pdf","text":"Pamphlet","size":"3.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3444 Pamphlet"}],"country":"United States","state":"Arkansas","county":"Garland County","city":"Hot Springs","otherGeospatial":"Highway 270 Bypass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.01935195922852,\n 34.50542493789137\n ],\n [\n -92.94931411743164,\n 34.50542493789137\n ],\n [\n -92.94931411743164,\n 34.5710371883746\n ],\n [\n -93.01935195922852,\n 34.5710371883746\n ],\n [\n -93.01935195922852,\n 34.50542493789137\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-11-19","noUsgsAuthors":false,"publicationDate":"2019-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Nottmeier, Anna M. 0000-0002-0205-0955 anottmeier@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-0955","contributorId":5283,"corporation":false,"usgs":true,"family":"Nottmeier","given":"Anna","email":"anottmeier@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hays, Phillip D. 0000-0001-5491-9272 pdhays@usgs.gov","orcid":"https://orcid.org/0000-0001-5491-9272","contributorId":4145,"corporation":false,"usgs":true,"family":"Hays","given":"Phillip","email":"pdhays@usgs.gov","middleInitial":"D.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773430,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208703,"text":"70208703 - 2019 - Heterogeneity in hyporheic flow, pore water chemistry, and microbial community composition in an alpine streambed","interactions":[],"lastModifiedDate":"2020-02-25T12:27:59","indexId":"70208703","displayToPublicDate":"2019-11-19T12:25:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Heterogeneity in hyporheic flow, pore water chemistry, and microbial community composition in an alpine streambed","docAbstract":"The hyporheic zone, where surface water and groundwater mix, is an important microbial habitat where biogeochemical reactions influence water quality. We show that spatial variability in hyporheic flow in the East River near Crested Butte, Colorado, drives heterogeneity in streambed geochemical conditions and microbial community assemblages, but the diversity of assemblages remains nearly constant throughout the reach. In July 2018, we collected approximately 100 pore water samples at 20 cm depth and analyzed them for anions, cations, dissolved organic carbon, dissolved organic matter (DOM) quality, and basic water quality parameters. Vertical hydraulic head gradients were also measured to assess the potential for upward or downward flow, and heat tracing was used to quantify vertical flux rates at a subset of locations. We found that regions of the streambed that are more groundwater-dominated contain less dissolved oxygen, higher concentrations of reduced metals, and more microbially-processed, recalcitrant DOM, while more surface water-dominated locations contain higher dissolved oxygen concentrations and terrestrially-derived, labile DOM. 16S rRNA gene sequencing of extracted DNA revealed that microbial community composition varies with geochemical gradients related to hyporheic flow. These findings provide a better understanding of hyporheic controls on streambed biogeochemistry during the baseflow season, which is expected to lengthen with climate change in alpine watersheds due to earlier snowmelt onset and reduced snowpack.","language":"English","publisher":"Wiley","doi":"10.1029/2019JG005226","usgsCitation":"Nelson, A., Sawyer, A., Gabor, R., Saup, C., Bryant, S., Harris, K., Briggs, M.A., Williams, K., and Wilkins, M.J., 2019, Heterogeneity in hyporheic flow, pore water chemistry, and microbial community composition in an alpine streambed: Journal of Geophysical Research: Biogeosciences, v. 124, no. 11, p. 3465-3478, https://doi.org/10.1029/2019JG005226.","productDescription":"14 p.","startPage":"3465","endPage":"3478","ipdsId":"IP-113191","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":459156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Improved model regionalization and prediction uncertainties using hierarchical Bayesian methods","docAbstract":"

The precise estimation of process effects in hydrological models requires applying models to large scales with extensive spatial variability in controlling factors. Despite progress in large‐scale applications of hydrological models in conterminous United States (CONUS) river basins, spatial constraints in model parameters have prevented the interbasin sharing of data, complicating quantification of process effects and limiting the accuracy of model predictions and uncertainties. Hierarchical Bayesian methods enable data sharing between basins and the identification of the causes of model uncertainties, which can improve model accuracy and interpretability; however, computational inefficiencies have been an obstacle to their large‐scale application. We used a new generation of Bayesian methods to develop a hierarchical version of a previous hybrid (statistical‐mechanistic) SPAtially Referenced Regression On Watershed attributes model of long‐term mean annual streamflow in the CONUS. We identified hierarchical (regional) variations in model coefficients and uncertainties and evaluated their effects on model accuracy and interpretability across diverse environments in 16 major CONUS regions. Hierarchical coefficients significantly improved spatial accuracy of model predictions, with the largest improvements in humid eastern regions, where uncertainties were approximately one third of those in arid western regions. Half of the coefficients varied regionally, with the largest variations in coefficients associated with water losses in streams and reservoirs. Our unraveling of the causes of model uncertainties identified a small latent process component of runoff that varies inversely with river size in most CONUS regions. Our study advances the use of hierarchical Bayesian methods to improve the predictive capabilities of hydrological models.

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gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":213621,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory","email":"gschwarz@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":800905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":800906,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70207116,"text":"70207116 - 2019 - Using stream-side groundwater discharge for geochemical exploration in mountainous terrain","interactions":[],"lastModifiedDate":"2019-12-07T09:27:29","indexId":"70207116","displayToPublicDate":"2019-11-14T09:24:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Using stream-side groundwater discharge for geochemical exploration in mountainous terrain","docAbstract":"Groundwater chemistry has been predominantly used in geochemical exploration studies to identify mineralized targets concealed under transported cover in areas with gentle topography. Another potentially valuable ap-plication that has received little attention is using groundwater chemistry to identify deposits concealed within mountain ridges. A number of geochemical exploration studies have employed surface water chemistry in hilly and mountainous terrain and have demonstrated mixed success. However, groundwater chemistry is potentially a more refined and powerful tool because groundwater sample locations can be selected to target a specific hillslope zone, whereas surface water integrates the geochemical signature of the entire watershed area above the sample site. In this study, we propose an approach that utilizes shallow groundwater samples collected from near-stream, hand-installed sampling points. We tested this approach in Handcart Gulch, an unmined catchment in the Montezuma Mining District, Colorado, USA, where previous studies suggested the possible presence of a concealed mineral occurrence. Seventeen near-stream mini-boreholes were drilled in a stream-parallel 3.3-km-long transect to depths of ~2 m in ferricrete (iron-oxide cemented colluvium and alluvium) using a handheld rock-coring drill. Groundwater in the mini-boreholes was sampled for major and trace element chemistry, as well as environmental tracers including stable water isotopes, dissolved noble gases, helium isotopes, and tritium, to identify possible variations in groundwater age and recharge conditions/sources. Chemistry data delineate a well-defined 900-m-wide zone of elevated SO4, Cu, and other metal concentrations on the east side of the stream. In this zone, Cu concentrations up to 2670 μg/L are 1–3 orders of magnitude greater than concentrations in upstream and downstream areas. Environmental tracer data show no corresponding anomalies in groundwater age or recharge conditions/sources within the zone, suggesting that the source of the elevated metals is a change in bedrock mineralogy as opposed to other hydrologic factors. The groundwater samples therefore successfully identify and refine the location of a potential concealed high-Cu mineral occurrence in the watershed, de-monstrating that near-stream groundwater discharge may be a valuable medium for geochemical exploration in mountainous areas.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2019.106415","usgsCitation":"Manning, A.H., Morrison, J.M., Wanty, R., and Mills, C., 2019, Using stream-side groundwater discharge for geochemical exploration in mountainous terrain: Journal of Geochemical Exploration, v. 209, 106415, https://doi.org/10.1016/j.gexplo.2019.106415.","productDescription":"106415","ipdsId":"IP-109321","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":459186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70206055,"text":"ofr20191119 - 2019 - Detailed Lithologic Logs from Auger Holes in southern Charleston County, southwestern Dorchester County, and eastern Colleton County, South Carolina","interactions":[],"lastModifiedDate":"2019-11-07T13:30:32","indexId":"ofr20191119","displayToPublicDate":"2019-11-07T13:30:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1119","displayTitle":"Detailed Lithologic Logs from Auger Holes in Southern Charleston County, Southwestern Dorchester County, and Eastern Colleton County, South Carolina","title":"Detailed Lithologic Logs from Auger Holes in southern Charleston County, southwestern Dorchester County, and eastern Colleton County, South Carolina","docAbstract":"

The lithologic logs described in this open-file report are from holes augered in the South Carolina Low Country in parts of Charleston, Dorchester, and Colleton Counties from 1998 through 2010. Lithologic units described here include not only surficial Pleistocene units but also subsurface stratigraphic units ranging as far back in age as late Eocene. This region comprises the southernmost and westernmost portions of the area included in the 1:100,000 Charleston region geologic map, which lies east of 80°30′ west and south of 33°15′ north. Logs of the remainder of that map area were published prior to the release of that map. The present report completes the lithologic log record from which the 1:100,000 Charleston region geologic map largely was compiled.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191119","collaboration":"Prepared in cooperation with the South Carolina Geological Survey","usgsCitation":"Weems, R.E., and Lewis, W.C., 2019, Detailed lithologic logs from auger holes in southern Charleston County, southwestern Dorchester County, and eastern Colleton County, South Carolina: U.S. Geological Survey Open-File Report 2019–1119, 129 p., https://doi.org/10.3133/ofr20191119.","productDescription":"iv, 129 p.","numberOfPages":"136","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-105009","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":368507,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1119/coverthb2.jpg"},{"id":369044,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1119/ofr20191119.pdf","text":"Report","size":"2.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1119"}],"country":"United States","state":"South Carolina","county":"Charleston County, Colleton County, Dorchester County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.8758544921875,\n 32.20350534542368\n ],\n [\n -79.8870849609375,\n 32.20350534542368\n ],\n [\n -79.8870849609375,\n 33.02248191961359\n ],\n [\n -80.8758544921875,\n 33.02248191961359\n ],\n [\n -80.8758544921875,\n 32.20350534542368\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Florence Bascom Geoscience Center
U.S. Geological Survey
MS 926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-11-07","noUsgsAuthors":false,"publicationDate":"2019-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Weems, Robert E. 0000-0002-1907-7804 rweems@usgs.gov","orcid":"https://orcid.org/0000-0002-1907-7804","contributorId":2663,"corporation":false,"usgs":true,"family":"Weems","given":"Robert","email":"rweems@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":773435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewis, William C.","contributorId":192890,"corporation":false,"usgs":false,"family":"Lewis","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":773436,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70212493,"text":"70212493 - 2019 - Overview, chronology, and impacts of the 2016–2017 eruption of Bogoslof volcano, Alaska","interactions":[],"lastModifiedDate":"2020-08-18T17:20:45.396543","indexId":"70212493","displayToPublicDate":"2019-11-05T12:15:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Overview, chronology, and impacts of the 2016–2017 eruption of Bogoslof volcano, Alaska","docAbstract":"

The 2016–2017 eruption of Bogoslof volcano, a back-arc shallow submarine volcano in Alaska’s Aleutian arc, began in December 2016 and included 70 explosive events and at least two episodes of subaerial dome building. Because the volcano had no local monitoring stations during the eruption, a combination of distant seismic stations, regional infrasound sensors, lightning detection, a variety of satellite data and observer reports, and a field visit in 2018, were used to recreate the events that occurred during the nine-month eruption. Following precursory seismicity that started in September 2016, the eruption began in December 2016 with a series of explosive events that persisted through mid-March 2017. After a 6-week hiatus, activity resumed on May 17 and lasted through the end of August 2017 and consisted of additional explosions and two short-lived subaerial lava domes that formed in June and August. For most of the eruption, Bogoslof’s vent was submerged in shallow seawater, though during several of the longer events a subaerial edifice grew, and the vent migrated above sea level resulting in more ash-rich volcanic clouds. Eruptive products, geophysical signals, and eruptive style are all broadly consistent with vulcanian activity where slow magma ascent led to repetitive dome or plug formation, overpressurization in the upper conduit, and sudden release during short-lived explosions. Infiltration of seawater may have prohibited large domes from forming especially in the first half of the eruption when explosions were closely spaced in time. The largest four explosions in the sequence occurred after inter-event times of 10 days or more. Three events produced ashfall on nearby communities and mariners east and south of Bogoslof and the eruption resulted in dozens of flight cancelations and flight diversions around the volcano and its ash clouds.

","language":"English","publisher":"Springer","doi":"10.1007/s00445-019-1322-9","usgsCitation":"Coombs, M.L., Wallace, K.L., Cameron, C., Lyons, J.J., Wech, A., Angeli, K.M., and Cervelli, P., 2019, Overview, chronology, and impacts of the 2016–2017 eruption of Bogoslof volcano, Alaska: Bulletin of Volcanology, v. 81, 62, 23 p., https://doi.org/10.1007/s00445-019-1322-9.","productDescription":"62, 23 p.","ipdsId":"IP-107331","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":377621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -169.573974609375,\n 52.859180945520826\n ],\n [\n -165.9869384765625,\n 52.859180945520826\n ],\n [\n -165.9869384765625,\n 54.559322587438636\n ],\n [\n -169.573974609375,\n 54.559322587438636\n ],\n [\n -169.573974609375,\n 52.859180945520826\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","noUsgsAuthors":false,"publicationDate":"2019-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":796572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":796573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cameron, Cheryl","contributorId":139951,"corporation":false,"usgs":false,"family":"Cameron","given":"Cheryl","affiliations":[{"id":13214,"text":"State of Alaska, Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":796574,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":796575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":796576,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Angeli, Kim M. 0000-0003-2427-3241 kangeli@usgs.gov","orcid":"https://orcid.org/0000-0003-2427-3241","contributorId":238809,"corporation":false,"usgs":true,"family":"Angeli","given":"Kim","email":"kangeli@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":796577,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cervelli, Peter 0000-0001-6765-1009","orcid":"https://orcid.org/0000-0001-6765-1009","contributorId":215619,"corporation":false,"usgs":true,"family":"Cervelli","given":"Peter","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":796578,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205412,"text":"ofr20191103 - 2019 - Optimization of salt marsh management at the Rhode Island National Wildlife Refuge Complex through use of structured decision making","interactions":[],"lastModifiedDate":"2024-03-04T18:41:42.763901","indexId":"ofr20191103","displayToPublicDate":"2019-10-31T13:10:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1103","displayTitle":"Optimization of Salt Marsh Management at the Rhode Island National Wildlife Refuge Complex Through Use of Structured Decision Making","title":"Optimization of salt marsh management at the Rhode Island National Wildlife Refuge Complex through use of structured decision making","docAbstract":"

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing salt marsh management decisions at the Rhode Island National Wildlife Refuge Complex. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of nine salt marsh management units within the refuge complex and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per salt marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $150,000, but that further expenditures may yield diminishing return on investment. Management actions in optimal portfolios at total costs less than $150,000 included digging runnels (by hand or machine) on the marsh surface to improve drainage in eight management units, applying sediment to the marsh surface (thin layer deposition) in one management unit, constructing islands for use by tidal marsh obligate birds in two management units, and controlling Phragmites australis in one management unit. The management benefits were derived from expected improvements in the capacity for marsh elevation to keep pace with sea-level rise and increases in numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds. The prototype presented here provides a framework for decision making at the Rhode Island National Wildlife Refuge Complex that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191103","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., and Ernst, N.T., 2019, Optimization of salt marsh management at the Rhode Island National Wildlife Refuge Complex through use of structured decision making: U.S. Geological Survey Open-File Report 2019–1103, 39 p., https://doi.org/10.3133/ofr20191103.","productDescription":"vi, 39 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-102061","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":368643,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1103/ofr20191103.pdf","text":"Report","size":"3.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1103"},{"id":368642,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1103/coverthb.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Rhode Island National Wildlife Refuge Complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.57524108886719,\n 41.3757780692323\n ],\n [\n -71.42074584960938,\n 41.3757780692323\n ],\n [\n -71.42074584960938,\n 41.49674964110098\n ],\n [\n -71.57524108886719,\n 41.49674964110098\n ],\n [\n -71.57524108886719,\n 41.3757780692323\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708-4039

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2019-10-31","noUsgsAuthors":false,"publicationDate":"2019-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Neckles, Hilary A. 0000-0002-5662-2314 hneckles@usgs.gov","orcid":"https://orcid.org/0000-0002-5662-2314","contributorId":3821,"corporation":false,"usgs":true,"family":"Neckles","given":"Hilary","email":"hneckles@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":771083,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":214392,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":771084,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagel, Jessica L. 0000-0002-4437-0324 jnagel@usgs.gov","orcid":"https://orcid.org/0000-0002-4437-0324","contributorId":3976,"corporation":false,"usgs":true,"family":"Nagel","given":"Jessica","email":"jnagel@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":771085,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adamowicz, Susan C.","contributorId":174712,"corporation":false,"usgs":false,"family":"Adamowicz","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":true,"id":771086,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mikula, Toni","contributorId":208473,"corporation":false,"usgs":false,"family":"Mikula","given":"Toni","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":771087,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ernst, Nicholas T.","contributorId":219029,"corporation":false,"usgs":false,"family":"Ernst","given":"Nicholas","email":"","middleInitial":"T.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":771088,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70215270,"text":"70215270 - 2019 - Coseismic slip and early afterslip of the M6.0 August 24, 2014 South Napa, California, earthquake","interactions":[],"lastModifiedDate":"2020-10-14T13:29:10.31605","indexId":"70215270","displayToPublicDate":"2019-10-31T08:26:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Coseismic slip and early afterslip of the M6.0 August 24, 2014 South Napa, California, earthquake","docAbstract":"

We employ strong motion seismograms and static offsets from the Global Positioning System, Interferometric Synthetic Aperture Radar, and other measurements in order to derive a coseismic slip and afterslip model of the M6.0 24 August 2014 South Napa earthquake. This earthquake ruptured an ∼13‐km‐long portion of the West Napa fault with predominantly right‐lateral strike slip. In the kinematic seismic slip inversions, we couple the coseismic slip and afterslip distributions by requiring both distributions to involve right‐lateral strike slip with positive amplitude, with the net static slip being the sum of the two. We consider several candidate fault geometries: a first involving two steeply east dipping fault planes that reach Earth's surface at the western surface trace (STW), where most surface rupture was observed, a second involving a steeply west dipping plane that also reaches Earth's surface at the STW, and a third involving a combination of two variably west dipping planes constrained to pass through the locus of postseismic seismicity located ∼1 km west of the STW. The data are best fit using the model of two east dipping fault planes, with coseismic slip up to ∼1.2 m on a dominant shallow asperity about 10 km north of the hypocenter and on deeper asperities on the southern part of the rupture. Afterslip up to 1 m is concentrated along the southern part of the rupture at depths \"urn:x-wiley:jgrb:media:jgrb53820:jgrb53820-math-0001\"5 km, consistent with surface observations of afterslip. Seismic moments associated with coseismic slip and afterslip are 1.13×1018 N m (Mw 6.00) and 3.64×1017 N m, respectively.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JB018470","usgsCitation":"Pollitz, F., Murray, J.R., Minson, S.E., Wicks, C.W., Svarc, J.L., and Brooks, B.A., 2019, Coseismic slip and early afterslip of the M6.0 August 24, 2014 South Napa, California, earthquake: Journal of Geophysical Research, v. 124, no. 11, p. 11728-11747, https://doi.org/10.1029/2019JB018470.","productDescription":"20 p.","startPage":"11728","endPage":"11747","ipdsId":"IP-109539","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":379354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"South Napa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.61566162109375,\n 38.002655740556705\n ],\n [\n -121.91253662109376,\n 38.002655740556705\n ],\n [\n -121.91253662109376,\n 38.44498466889473\n ],\n [\n -122.61566162109375,\n 38.44498466889473\n ],\n [\n -122.61566162109375,\n 38.002655740556705\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"11","noUsgsAuthors":false,"publicationDate":"2019-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":801417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":801418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":801419,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wicks, Charles W. Jr. 0000-0002-0809-1328 cwicks@usgs.gov","orcid":"https://orcid.org/0000-0002-0809-1328","contributorId":127701,"corporation":false,"usgs":true,"family":"Wicks","given":"Charles","suffix":"Jr.","email":"cwicks@usgs.gov","middleInitial":"W.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":801420,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Svarc, Jerry L. 0000-0002-2802-4528","orcid":"https://orcid.org/0000-0002-2802-4528","contributorId":212736,"corporation":false,"usgs":true,"family":"Svarc","given":"Jerry","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":801421,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brooks, Benjamin A. 0000-0001-7954-6281 bbrooks@usgs.gov","orcid":"https://orcid.org/0000-0001-7954-6281","contributorId":5237,"corporation":false,"usgs":true,"family":"Brooks","given":"Benjamin","email":"bbrooks@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":801422,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227655,"text":"70227655 - 2019 - Tropical cyclones alter short-term activity patterns of a coastal seabird","interactions":[],"lastModifiedDate":"2022-01-25T14:21:45.013504","indexId":"70227655","displayToPublicDate":"2019-10-28T08:16:16","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Tropical cyclones alter short-term activity patterns of a coastal seabird","docAbstract":"

Background

Mobile organisms in marine environments are expected to modify their behavior in response to external stressors. Among environmental drivers of animal movement are long-term climatic indices influencing organism distribution and short-term meteorological events anticipated to alter acute movement behavior. However, few studies exist documenting the response of vagile species to meteorological anomalies in coastal and marine systems.

Methods

Here we examined the movements of Eastern brown pelicans (Pelecanus occidentalis carolinensis) in the South Atlantic Bight in response to the passage of three separate hurricane events in 2 years. Pelicans (n = 32) were tracked with GPS satellite transmitters from four colonies in coastal South Carolina, USA, for the entirety of at least one storm event. An Expectation Maximization binary Clustering algorithm was used to discretize pelican behavioral states, which were pooled into ‘active’ versus ‘inactive’ states. Multinomial logistic regression was used to assess behavioral state probabilities in relation to changes in barometric pressure and wind velocity.

Results

Individual pelicans were more likely to remain inactive during tropical cyclone passage compared to baseline conditions generally, although responses varied by hurricane. When inactive, pelicans tended to seek shelter using local geomorphological features along the coastline such as barrier islands and estuarine systems.

Conclusions

Our telemetry data showed that large subtropical seabirds such as pelicans may mitigate risk associated with spatially-extensive meteorological events by decreasing daily movements. Sheltering may be related to changes in barometric pressure and wind velocity, and represents a strategy common to several other classes of marine vertebrate predators for increasing survival probabilities.

","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-019-0178-0","usgsCitation":"Wilkinson, B.P., Satge, Y.G., Lamb, J.S., and Jodice, P.G., 2019, Tropical cyclones alter short-term activity patterns of a coastal seabird: Movement Ecology, v. 7, 30, 11 p., https://doi.org/10.1186/s40462-019-0178-0.","productDescription":"30, 11 p.","ipdsId":"IP-108429","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":459342,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-019-0178-0","text":"Publisher Index Page"},{"id":437290,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D5IP0G","text":"USGS data release","linkHelpText":"Movement ecology of Brown Pelican in the South Atlantic Bight, 2017-2019"},{"id":394817,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.5947265625,\n 25.839449402063185\n ],\n [\n -75.6298828125,\n 25.839449402063185\n ],\n [\n -75.6298828125,\n 35.88905007936091\n ],\n [\n -84.5947265625,\n 35.88905007936091\n ],\n [\n -84.5947265625,\n 25.839449402063185\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","noUsgsAuthors":false,"publicationDate":"2019-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilkinson, B. P.","contributorId":272128,"corporation":false,"usgs":false,"family":"Wilkinson","given":"B.","email":"","middleInitial":"P.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":831568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Satge, Y. G.","contributorId":272129,"corporation":false,"usgs":false,"family":"Satge","given":"Y.","email":"","middleInitial":"G.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":831569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamb, J. S.","contributorId":272130,"corporation":false,"usgs":false,"family":"Lamb","given":"J.","email":"","middleInitial":"S.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":831570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":831571,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204747,"text":"sim3437 - 2019 - Three-dimensional geologic map of the southern Carson Sink, Nevada, including the Fallon FORGE area","interactions":[],"lastModifiedDate":"2019-10-25T15:53:06","indexId":"sim3437","displayToPublicDate":"2019-10-25T10:17:17","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3437","displayTitle":"Three-Dimensional Geologic Map of the Southern Carson Sink, Nevada, Including the Fallon FORGE area","title":"Three-dimensional geologic map of the southern Carson Sink, Nevada, including the Fallon FORGE area","docAbstract":"

The three-dimensional (3–D) geologic map characterizes the subsurface in the southern Carson Sink region. We created the 3–D map by integrating the results from seismic-reflection, potential-field-geophysical, and lithologic well-logging inves­tigations completed in and around the Fallon FORGE site as part of the U.S. Department of Energy Frontier Observatory for Research in Geothermal Energy (FORGE) initiative from 2015–2018. The FORGE initiative was part of an effort to develop the technologies, techniques, and knowledge needed to make enhanced geothermal systems a commercially viable electricity-generation option for the United States. Geo­logic units and structures mapped during the Fallon FORGE study, which particularly focused on the Mesozoic basement, were extrapolated to create the 3–D map of the southern Carson Sink area. The 3–D map area is 10 km wide along the east-west and north-south axes and extends 2.5 km below sea level, ~3.7 km below the land surface. Views of the map include horizontal and vertical sections and oblique perspective views from several angles. We describe the geologic units and structures and dis­cuss the methods used to integrate the geologic and geophysical information in a 3–D geologic interpretation. We provide digital data for elements of the map, such as individual 3–D fault and stratigraphic surfaces and surface-fault traces. Input data are available from various data repositories through cited web links. A brief movie displaying the 3–D map is available at https://doi.org/10.3133/sim3437.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3437","usgsCitation":"Siler, D.L., Faulds, J.E., Glen, J.M.G., Hinz, N.H., Witter, J.B., Blake, K., Queen, J., and Fortuna, M., 2019, Three-dimensional geologic map of the southern Carson Sink, Nevada, including the Fallon FORGE area: U.S. Geological Survey Scientific Investigations Map 3437, pamphlet 22 p., https://doi.org/10.3133/sim3437.","productDescription":"Pamphlet: iv, 22 p.; Map, 46.35 x 39 inches; Video; Database; Metadata; Readme","numberOfPages":"22","additionalOnlineFiles":"Y","ipdsId":"IP-100960","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":368577,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3437/coverthb.jpg"},{"id":368582,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3437/sim3437_metadata.zip","size":"20 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3437"},{"id":368583,"rank":7,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3437/sim3437_readme.docx","size":"20 KB docx","description":"SIM 3437"},{"id":368578,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3437/sim3437_pamphlet.pdf","text":"Pamphlet","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3437"},{"id":368579,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3437/sim3437_map.pdf","text":"Map","size":"8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3437"},{"id":368580,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sim/3437/sim3437_3dmap_1080.mp4","text":"3-Dimensional Map Video","size":"30 MB mp4","description":"SIM 3437"},{"id":368581,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3437/sim3437_database.zip","size":"600 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3437"}],"country":"United States","state":"Nevada","otherGeospatial":"Southern Carson Sink, Fallon FORGE area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.20989990234374,\n 39.12153746241925\n ],\n [\n -118.08380126953125,\n 39.12153746241925\n ],\n [\n -118.08380126953125,\n 40.264856517201856\n ],\n [\n -119.20989990234374,\n 40.264856517201856\n ],\n [\n -119.20989990234374,\n 39.12153746241925\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936

","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-10-25","noUsgsAuthors":false,"publicationDate":"2019-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":768286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faulds, James E.","contributorId":218085,"corporation":false,"usgs":false,"family":"Faulds","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":39739,"text":"Nevada Bureau of Mines and Geology, University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":768287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":773857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hinz, Nicholas H.","contributorId":218086,"corporation":false,"usgs":false,"family":"Hinz","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":39739,"text":"Nevada Bureau of Mines and Geology, University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":768289,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Witter, Jeffrey B. 0000-0002-1357-1481","orcid":"https://orcid.org/0000-0002-1357-1481","contributorId":211948,"corporation":false,"usgs":false,"family":"Witter","given":"Jeffrey","email":"","middleInitial":"B.","affiliations":[{"id":38365,"text":"Innovate Geothermal Ltd.","active":true,"usgs":false}],"preferred":false,"id":768290,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blake, Kelly","contributorId":203950,"corporation":false,"usgs":false,"family":"Blake","given":"Kelly","email":"","affiliations":[{"id":36772,"text":"U.S. Dept of the Navy","active":true,"usgs":false}],"preferred":false,"id":768291,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"John Queen","contributorId":218087,"corporation":false,"usgs":false,"family":"John Queen","affiliations":[{"id":39740,"text":"HiQ Geophysical","active":true,"usgs":false}],"preferred":false,"id":768292,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fortuna, Mark","contributorId":218088,"corporation":false,"usgs":false,"family":"Fortuna","given":"Mark","email":"","affiliations":[{"id":39741,"text":"MAF Seismic","active":true,"usgs":false}],"preferred":false,"id":768293,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70266159,"text":"70266159 - 2019 - Oyster reefs in northern Gulf of Mexico estuaries harbor diverse fish and decapod crustacean assemblages: A meta-synthesis","interactions":[],"lastModifiedDate":"2025-04-29T14:31:34.117524","indexId":"70266159","displayToPublicDate":"2019-10-25T09:25:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Oyster reefs in northern Gulf of Mexico estuaries harbor diverse fish and decapod crustacean assemblages: A meta-synthesis","docAbstract":"

Oyster reefs provide habitat for numerous fish and decapod crustacean species that mediate ecosystem functioning and support vibrant fisheries. Recent focus on the restoration of eastern oyster (Crassostrea virginica) reefs stems from this role as a critical ecosystem engineer. Within the shallow estuaries of the northern Gulf of Mexico (nGoM), the eastern oyster is the dominant reef building organism. This study synthesizes data on fish and decapod crustacean occupancy of oyster reefs across nGoM with the goal of providing management and restoration benchmarks, something that is currently lacking for the region. Relevant data from 23 studies were identified, representing data from all five U.S. nGoM states over the last 28 years. Cumulatively, these studies documented over 120,000 individuals from 115 fish and 41 decapod crustacean species. Densities as high as 2,800 ind m−2 were reported, with individual reef assemblages composed of as many as 52 species. Small, cryptic organisms that occupy interstitial spaces within the reefs, and sampled using trays, were found at an average density of 647 and 20 ind m−2 for decapod crustaceans and fishes, respectively. Both groups of organisms were comprised, on average, of 8 species. Larger-bodied fishes captured adjacent to the reef using gill nets were found at an average density of 6 ind m−2, which came from 23 species. Decapod crustaceans sampled with gill nets had a much lower average density, <1 ind m−2, and only contained 2 species. On average, seines captured the greatest number of fish species (n = 33), which were made up of both facultative residents and transients. These data provide general gear-specific benchmarks, based on values currently found in the region, to assist managers in assessing nekton occupancy of oyster reefs, and assessing trends or changes in status of oyster reef associated nekton support. More explicit reef descriptions (e.g., rugosity, height, area, adjacent habitat) would allow for more precise benchmarks as these factors are important in determining nekton assemblages, and sampling efficiency.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2019.00666","usgsCitation":"LaPeyre, M.K., Marshall, D.A., Miller, L., and Humphries, A.T., 2019, Oyster reefs in northern Gulf of Mexico estuaries harbor diverse fish and decapod crustacean assemblages: A meta-synthesis: Frontiers in Marine Science, v. 6, 666, 13 p., https://doi.org/10.3389/fmars.2019.00666.","productDescription":"666, 13 p.","ipdsId":"IP-080466","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":487836,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2019.00666","text":"Publisher Index Page"},{"id":485132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.77507531536082,\n 26.434595440924554\n ],\n [\n -82.36851770898288,\n 29.179744856981316\n ],\n [\n -84.05763771804244,\n 30.18102965026621\n ],\n [\n -86.45906479945596,\n 30.564740988936478\n ],\n [\n -88.96978854642646,\n 30.601009360135762\n ],\n [\n -90.98398001483329,\n 29.849499692049946\n ],\n [\n -93.94726229901573,\n 30.024980309521595\n ],\n [\n -95.54944591403085,\n 29.35885238728197\n ],\n [\n -97.86986826415085,\n 27.75470647893117\n ],\n [\n -97.64835626287109,\n 26.38999825884062\n ],\n [\n -81.77507531536082,\n 26.434595440924554\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2019-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":934765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Danielle Aguilar","contributorId":341509,"corporation":false,"usgs":false,"family":"Marshall","given":"Danielle","email":"","middleInitial":"Aguilar","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":934845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Lindsay","contributorId":353924,"corporation":false,"usgs":false,"family":"Miller","given":"Lindsay","affiliations":[],"preferred":false,"id":934766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Humphries, Austin T.","contributorId":15943,"corporation":false,"usgs":true,"family":"Humphries","given":"Austin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":934767,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207513,"text":"70207513 - 2019 - Lead exposure of red-shouldered hawks during the breeding season in the central Appalachians, USA","interactions":[],"lastModifiedDate":"2019-12-22T13:59:50","indexId":"70207513","displayToPublicDate":"2019-10-23T13:56:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1103,"text":"Bulletin of Environmental Contamination and Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Lead exposure of red-shouldered hawks during the breeding season in the central Appalachians, USA","docAbstract":"Lead is toxic to humans and wildlife. Most studies of lead exposure of raptors focus on the winter, non-breeding season when they scavenge heavily. We evaluated blood lead concentrations (BLCs) of red-shouldered hawks (Buteo lineatus) during the non-scavenging season in the eastern United States. BLCs of 53 of 70 hawks were above the limit of detection ( x¯ = 9.25 µg/dL ± 19.81; ± SD). Adult hawks had higher BLCs ( x¯ = 12.86 µg/dL ± 24.72) than did nestlings ( x¯ = 3.25 µg/dL ± 2.62; p ≤ 0.001, χ2 = 13.2). There was no difference in BLCs of adult hawks among physiographic provinces but there were differences between urban and non-urban settings (p = 0.04, χ2 = 4.2). Soils and invertebrate hawk prey also had quantifiable lead concentrations. Our work shows that red-shouldered hawks are exposed to lead when not scavenging, and suggests pathways by which these birds may be exposed.","language":"English","publisher":"Springer","doi":"10.1007/s00128-019-02732-9","usgsCitation":"Katzner, T., 2019, Lead exposure of red-shouldered hawks during the breeding season in the central Appalachians, USA: Bulletin of Environmental Contamination and Toxicology, v. 103, no. 6, p. 783-788, https://doi.org/10.1007/s00128-019-02732-9.","productDescription":"6 p.","startPage":"783","endPage":"788","ipdsId":"IP-104710","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":370606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Central Appalachians","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.3525390625,\n 35.10193405724606\n ],\n [\n -82.9248046875,\n 34.70549341022544\n ],\n [\n -81.298828125,\n 34.813803317113155\n ],\n [\n -77.2998046875,\n 39.470125122358176\n ],\n [\n -74.70703125,\n 41.409775832009565\n ],\n [\n -75.322265625,\n 42.32606244456202\n ],\n [\n -77.9150390625,\n 42.16340342422401\n ],\n [\n -82.0458984375,\n 39.740986355883564\n ],\n [\n -83.75976562499999,\n 37.92686760148135\n ],\n [\n -86.0009765625,\n 35.99578538642032\n ],\n [\n -86.3525390625,\n 35.10193405724606\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"103","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":778324,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70205398,"text":"sir20195101 - 2019 - Groundwater and surface-water resources near Red Fleet Reservoir, Uintah County, Utah","interactions":[],"lastModifiedDate":"2019-10-23T07:36:10","indexId":"sir20195101","displayToPublicDate":"2019-10-22T15:24:54","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5101","displayTitle":"Groundwater and Surface-Water Resources near Red Fleet Reservoir, Uintah County, Utah","title":"Groundwater and surface-water resources near Red Fleet Reservoir, Uintah County, Utah","docAbstract":"Red Fleet Reservoir in Uintah County, Utah, is an approximately 26,000 acre-foot (acre-ft) on-channel reservoir in the Big Brush Creek drainage on the south slopes of the Uinta Mountains. It is operated primarily for irrigation needs while providing a supplemental drinking-water supply to the Vernal, Utah area. Red Fleet Reservoir, which was operated by the Bureau of Reclamation and the Uintah Water Conservancy District through 2015, began storing water in May 1980. The reservoir is on southward dipping Mesozoic lithologies ranging from Jurassic to Cretaceous in age. The Nugget and Frontier Sandstone aquifers are the targeted units in this investigation, which is to characterize groundwater conditions that exist in each sandstone aquifer and how they interact with Red Fleet Reservoir. Groundwater levels were measured in six wells and one spring in the Nugget Sandstone and the Frontier Sandstone aquifers. Water levels in the Nugget Sandstone aquifer were 35–70 feet above the maximum stage of Red Fleet Reservoir on the west and east banks. Water levels in the Frontier Sandstone aquifer were 15–30 feet below the observed stage of Red Fleet Reservoir on the west bank during the study period.\nA water budget was calculated for Red Fleet Reservoir between May 1980 and December 2015. During this period, 1,050,000 acre-ft of water from Big Brush Creek discharged into the reservoir, while 993,000 acre-ft of water was released downstream of Red Fleet Dam. Total evaporation from May 1980 through December 2015 was about 52,000 acre-ft, while total precipitation over the same period was about 12,000 acre-ft. From May 1980 through December 2015, the total pumped volume of water from the Tyzack Pump Station, at the base of Red Fleet Dam, was about 42,000 acre-ft. Total groundwater discharge to Red Fleet Reservoir from 1980 through 2015 was about 40,000 acre-ft.\nWater was sampled from four wells and from the inflow arm of Red Fleet Reservoir, and analyzed for major-ion chemistry, select trace metals, nutrients, and environmental tracers. Water sampled from the Nugget Sandstone aquifer yielded good-quality water with dissolved-solids concentrations of less than 200 milligram per liter, and no trace elements above the Environmental Protection Agency drinking-water standards. Water sampled from the Frontier Sandstone aquifer yielded poor-quality water with dissolved-solids concentrations of about 2,150 milligrams per liter with trace elements approaching drinking-water standards for arsenic. Dissolved noble gases used to identify recharge elevations and temperatures for groundwater indicate that water in the Nugget Sandstone aquifer likely recharged at a high altitude and low temperature, and not locally because of interaction with Red Fleet Reservoir. The Frontier Sandstone aquifer is likely recharged at low elevation and at temperatures similar to those observed at Red Fleet Reservoir.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195101","collaboration":"Prepared in cooperation with the Uintah Water Conservancy District and the Bureau of Reclamation","usgsCitation":"Marston, T.M., Solder, J.E., and Jones, K.K., 2019, Groundwater and surface-water resources near Red Fleet Reservoir, Uintah County, Utah: U.S. Geological Survey Scientific Investigations Report 2019–5101, 40 p., https://doi.org/10.3133/sir20195101.","productDescription":"vi, 40 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-103710","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":437296,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H7FIEO","text":"USGS data release","linkHelpText":"Lumped parameter models of 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Director, 
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
801-908-5000

","tableOfContents":"

","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2019-10-22","noUsgsAuthors":false,"publicationDate":"2019-10-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Marston, Thomas M. 0000-0003-1053-4172 tmarston@usgs.gov","orcid":"https://orcid.org/0000-0003-1053-4172","contributorId":3272,"corporation":false,"usgs":true,"family":"Marston","given":"Thomas","email":"tmarston@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Solder, John E. 0000-0002-0660-3326 jsolder@usgs.gov","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":171916,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"jsolder@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773391,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Katherine K.","contributorId":219862,"corporation":false,"usgs":true,"family":"Jones","given":"Katherine","email":"","middleInitial":"K.","affiliations":[],"preferred":true,"id":773392,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70206089,"text":"70206089 - 2019 - Assessing plant production responses to climate across water-limited regions using Google Earth Engine","interactions":[],"lastModifiedDate":"2019-10-22T06:32:15","indexId":"70206089","displayToPublicDate":"2019-10-21T13:41:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Assessing plant production responses to climate across water-limited regions using Google Earth Engine","docAbstract":"(Munson) Climate variability and change acting at broad scales can lead to divergent changes in plant production at local scales. Quantifying how production responds to variation in climate at local scales is essential to understand underlying ecological processes and inform land management decision-making, but has historically been limited in spatiotemporal scale based on the use of discrete ground-based measurements or coarse resolution satellite observations. With the advent of cloud-based computing through Google Earth Engine (GEE), production responses to climate can be evaluated across broad landscapes though time at a resolution useful for ecological and land management applications. Here, GEE was employed to synthesize a multi-platform Landsat time series (1988 – 2014) and evaluate relationships between the soil-adjusted vegetation index (a proxy for plant production) and climate across deserts and plant communities of the southwestern U.S. A “climate pivot point” approach was adopted in GEE to assess the trade-off between production responses to increasing wetness and resistances to drought at 30-m resolution. Consistent with a long-term seasonal climate gradient, production was most related to climate variance during the cool-season in the western deserts, during the warm-season in the eastern deserts, and equally related to both seasons within several desert areas. Communities dominated by grasses and deciduous trees displayed large production responses to an increase in wetness and low resistances to water deficit, while shrublands and evergreen woodlands had variable responses and high drought resistances. Production in plant communities that spanned multiple deserts responded differently to seasonal climate variability in each desert. Defining these plant production sensitivities to climate at 30-m resolution in GEE advances forecasts of how long-term climate trajectories may affect carbon storage, wildlife habitat, and the vulnerability of water-limited ecosystems.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2019.111379","collaboration":"None.","usgsCitation":"Bunting, E., Munson, S.M., and Bradford, J., 2019, Assessing plant production responses to climate across water-limited regions using Google Earth Engine: Remote Sensing of Environment, v. 233, p. 1-15, https://doi.org/10.1016/j.rse.2019.111379.","productDescription":"1113792, 15p.","startPage":"1","endPage":"15","ipdsId":"IP-093613","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":459429,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2019.111379","text":"Publisher Index Page"},{"id":437297,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98ZCJBI","text":"USGS data release","linkHelpText":"Dataset for plant production responses to climate across water-limited regions"},{"id":368461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368458,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0034425719303980?via%3Dihub"}],"country":"United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Texas, Utah","otherGeospatial":"Chihuahuan, Colorado Plateau, Great Basin, Mojave, Sonoran ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.09374999999999,\n 41.705728515237524\n ],\n [\n -119.88281249999999,\n 41.376808565702355\n ],\n [\n -120.84960937499999,\n 38.685509760012\n ],\n [\n -115.83984375,\n 35.60371874069731\n ],\n [\n -115.6640625,\n 32.62087018318113\n ],\n [\n -114.78515624999999,\n 32.91648534731439\n ],\n [\n -110.21484375,\n 31.50362930577303\n ],\n [\n -110.56640625,\n 33.797408767572485\n ],\n [\n -113.64257812499999,\n 34.74161249883172\n ],\n [\n -111.70898437499999,\n 35.88905007936091\n ],\n [\n -108.19335937499999,\n 34.08906131584994\n ],\n [\n -105.29296874999999,\n 30.826780904779774\n ],\n [\n -103.0078125,\n 29.305561325527698\n ],\n [\n -102.12890625,\n 30.221101852485987\n ],\n [\n -107.40234375,\n 36.31512514748051\n ],\n [\n -106.5234375,\n 37.50972584293751\n ],\n [\n -107.22656249999999,\n 38.34165619279595\n ],\n [\n -108.80859375,\n 37.23032838760387\n ],\n [\n -108.369140625,\n 41.11246878918088\n ],\n [\n -111.09374999999999,\n 41.705728515237524\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"233","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bunting, Erin L.","contributorId":208169,"corporation":false,"usgs":false,"family":"Bunting","given":"Erin L.","affiliations":[{"id":37758,"text":"Michigan State University, East Lansing, MI USA","active":true,"usgs":false}],"preferred":false,"id":773528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":773527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":773529,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215415,"text":"70215415 - 2019 - Differential effects of temperature and salinity on growth and mortality of oysters (Crassostrea virginica) in Barataria Bay and Breton Sound, Louisiana","interactions":[],"lastModifiedDate":"2020-10-19T19:17:19.843075","indexId":"70215415","displayToPublicDate":"2019-10-19T14:12:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"title":"Differential effects of temperature and salinity on growth and mortality of oysters (Crassostrea virginica) in Barataria Bay and Breton Sound, Louisiana","docAbstract":"Temperature and salinity and their interaction exert a major control on the life cycle of the eastern oyster (Crassostrea virginica), affecting reproduction, development, growth, and mortality. Quantifying specific temperature and salinity relationships on oyster growth and mortality has however proven difficult, with data suggesting potentially region-specific responses. Legacy and recent data from field tray studies from public oyster grounds in Barataria Bay and Breton Sound were used to estimate growth and mortality rates as a function of temperature and salinity. Previous studies conducted in Barataria Bay and Breton Sound reported differences in growth and mortality between the basins. In the present study, environmental conditions were synchronized to compare growth and mortality between basins at similar combinations of temperature and salinity. Results indicate that when temperature and salinity are the same (synchronized), seasonal oyster growth and mortality rates still differ between Barataria Bay and Breton Sound. Given the same salinity and temperature conditions, differences in growth and mortality rates between estuaries may persist due to differences in other environmental conditions (i.e., food quality and composition, hydrology, site history, salinity variation) or localized genetic adaptations to environmental conditions.","language":"English","publisher":"BioOne","doi":"10.2983/035.038.0212","usgsCitation":"Sehlinger, T., Lowe, M., LaPeyre, M.K., and Soniat, T., 2019, Differential effects of temperature and salinity on growth and mortality of oysters (Crassostrea virginica) in Barataria Bay and Breton Sound, Louisiana: Journal of Shellfish Research, v. 38, no. 2, p. 317-326, https://doi.org/10.2983/035.038.0212.","productDescription":"10 p.","startPage":"317","endPage":"326","ipdsId":"IP-105718","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":379528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Lousianna","otherGeospatial":"Barataria Bay and Brenton Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.8349609375,\n 28.714678586705976\n ],\n [\n -89.033203125,\n 28.714678586705976\n ],\n [\n -89.033203125,\n 30.32547125932808\n ],\n [\n -90.8349609375,\n 30.32547125932808\n ],\n [\n -90.8349609375,\n 28.714678586705976\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sehlinger, T.","contributorId":243342,"corporation":false,"usgs":false,"family":"Sehlinger","given":"T.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":802099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, M.R.","contributorId":243343,"corporation":false,"usgs":false,"family":"Lowe","given":"M.R.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":802100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":802101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soniat, T.M.","contributorId":243344,"corporation":false,"usgs":false,"family":"Soniat","given":"T.M.","email":"","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":802102,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215413,"text":"70215413 - 2019 - A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay Case Study","interactions":[],"lastModifiedDate":"2020-10-20T13:24:52.488251","indexId":"70215413","displayToPublicDate":"2019-10-19T14:01:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay Case Study","docAbstract":"Nutrient-reduction efforts have been undertaken in recent decades to mitigate the impacts of eutrophication in coastal and estuarine systems worldwide. To track progress in response to one of these efforts we use Generalized Additive Models (GAMs) to evaluate a diverse suite of water quality constituents over a 32-year period in the Chesapeake Bay, an estuary on the east coast of the United States. Model development included selecting a GAM structure to describe nonlinear seasonally-varying changes over time, incorporating hydrologic variability via either river flow or salinity, and using interventions to model method or laboratory changes suspected to impact data. This approach, transferable to other systems, allows for evaluation of water quality data in a statistically rigorous way, while being suitable for application to many sites and variables. This enables consistent generation of annual updates, while providing a tool for developing insights to a range of management- and research-focused questions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2019.03.027","usgsCitation":"Murphy, R., Perry, E., Harcum, J., and Keisman, J.L., 2019, A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay Case Study: Environmental Modelling & Software, v. 118, 13 p., https://doi.org/10.1016/j.envsoft.2019.03.027.","productDescription":"13 p.","ipdsId":"IP-105288","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":379527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.40966796875,\n 36.756490329505176\n ],\n [\n -75.5419921875,\n 36.756490329505176\n ],\n [\n -75.5419921875,\n 39.57182223734374\n ],\n [\n -77.40966796875,\n 39.57182223734374\n ],\n [\n -77.40966796875,\n 36.756490329505176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Rebecca 0000-0003-3391-1823","orcid":"https://orcid.org/0000-0003-3391-1823","contributorId":199777,"corporation":false,"usgs":false,"family":"Murphy","given":"Rebecca","email":"","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":true,"id":802095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Elgin","contributorId":243340,"corporation":false,"usgs":false,"family":"Perry","given":"Elgin","affiliations":[{"id":48694,"text":"Statistics Consultant","active":true,"usgs":false}],"preferred":false,"id":802096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harcum, Jon","contributorId":243341,"corporation":false,"usgs":false,"family":"Harcum","given":"Jon","email":"","affiliations":[{"id":48695,"text":"Tetra Tech, Inc.","active":true,"usgs":false}],"preferred":false,"id":802097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keisman, Jennifer L. 0000-0001-6808-9193 jkeisman@usgs.gov","orcid":"https://orcid.org/0000-0001-6808-9193","contributorId":198107,"corporation":false,"usgs":true,"family":"Keisman","given":"Jennifer","email":"jkeisman@usgs.gov","middleInitial":"L.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802098,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215411,"text":"70215411 - 2019 - Dextral, normal, and sinistral faulting across the eastern California shear zone-Mina deflection transition, California-Nevada","interactions":[],"lastModifiedDate":"2020-10-20T13:30:40.254733","indexId":"70215411","displayToPublicDate":"2019-10-19T13:35:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Dextral, normal, and sinistral faulting across the eastern California shear zone-Mina deflection transition, California-Nevada","docAbstract":"

Strike-slip faults commonly include extensional and contractional bends and stepovers, whereas rotational stepovers are less common. The Volcanic Tableland, Black Mountain, and River Spring areas (California and Nevada, USA) (hereafter referred to as the VBR region) straddle the transition from the dominantly NW-striking dextral faults that define the northwestern part of the eastern California shear zone into a rotational stepover characterized by dominantly NE-striking sinistral faults that define the southwestern Mina deflection. New detailed geologic mapping, structural studies, and 40Ar/39Ar geochronology across the VBR region allow us to calculate Pliocene to Pleistocene fault slip rates and test predictions for the kinematics of fault slip transfer into this rotational stepover. In the VBR, Mesozoic basement is nonconformably overlain by a Miocene sequence of rhyolite, dacite, and andesite volcanic rocks that yield 40Ar/39Ar ages between 22.878 ± 0.051 Ma and 11.399 ± 0.041 Ma. Miocene rocks are unconformably overlain by an extensive sequence of Pliocene basalt and andesite lava flows and cinder cones that yield 40Ar/39Ar ages between 3.606 ± 0.060 Ma and 2.996 ± 0.027 Ma. The Pliocene sequence is, in turn, unconformably overlain by Quaternary tuffs and sedimentary rocks. This sequence of rocks is cut by NS- to NW-striking normal faults across the Volcanic Tableland that transition northward into NS-striking normal faults across the Black Mountain area and that, in turn, transition northward into NW-striking dextral and NE-striking sinistral faults in the River Spring area. A range of geologic markers were used to measure offset across the faults in the VBR, and combined with the age of the markers, yield minimum ∼EW-extension rates of ∼0.5 mm/yr across the Volcanic Tableland and Black Mountain regions, and minimum NW-dextral slip and NE-sinistral slip rates of ∼0.7 and ∼0.3 mm/yr, respectively, across the River Spring region. In the River Spring area, our preferred minimum dextral slip and sinistral slip rates are 0.8–0.9 mm/yr and 0.7–0.9 mm/yr, respectively. We propose three kinematic fault slip models, two irrotational and one rotational, whereby the VBR region transfers a portion of dextral Owens Valley fault slip northwestward into the Mina deflection. In irrotational model 1, Owens Valley fault slip is partitioned into two components, one northeastward onto the White Mountain fault zone and one northwestward into the Volcanic Tableland. Slip from the two zones is then transferred northward into the southwestern Mina deflection. In irrotational model 2, Owens Valley fault slip is partitioned into three components, with the third component partitioned west-northwest onto the Sierra Nevada frontal fault zone. In the rotational model, predicted sinistral slip rates across the southwestern Mina deflection are at least 115% greater than our observed minimum slip rates, implying our minimum observed rates underestimate true sinistral slip rates. A comparison of summed geologic fault slip rates, parallel to motion of the Sierra Nevada block relative to the central Great Basin, from the Sierra Nevada northeastward across the VBR region and into western Nevada are the same as geodetic rates, if our assumptions about the geologic slip rate across the dextral White Mountain fault zone is correct.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01636.1","usgsCitation":"DeLano, K., Lee, J., Roper, R., and Calvert, A.T., 2019, Dextral, normal, and sinistral faulting across the eastern California shear zone-Mina deflection transition, California-Nevada: Geosphere, v. 15, no. 4, p. 1206-1239, https://doi.org/10.1130/GES01636.1.","productDescription":"34 p.","startPage":"1206","endPage":"1239","ipdsId":"IP-097991","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":459455,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01636.1","text":"Publisher Index Page"},{"id":379525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Eastern California shear 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