The dramatic loss of glacial mass in low latitudes is causing shifts in downstream water availability and use during the driest months of the year. The world’s largest concentration of tropical glaciers lies in the Cordillera Blanca range of Peru, where glacial runoff is declining and regional stresses are emerging over water resources. Throughout the Cordillera Blanca, groundwater inputs from alpine meadow–talus complexes, locally known as pampas, supply proglacial streams with up to 80% of their flow during the region’s dry season. Structural knowledge of the pampa aquifers is needed to estimate their drainable groundwater storage capacity and residence time, to elucidate the role and importance of alpine groundwater storage in the regional water budget of the Cordillera Blanca. To understand the structure of these proglacial aquifers, multiple near-surface geophysical methods were implemented in a proglacial valley near dense networks of spring-fed tributaries. Geophysical results and borehole logs suggest groundwater is stored in a confined aquifer composed of buried talus deposits overlain by lacustrine clay, while deeper portions of the unit, 10–15 m in depth, are relatively clay-free and more hydraulically conductive. Based on these findings and assumptions of aquifer porosity, the pampas of the Callejon de Huaylas may store from 0.006 to 0.02 km3 of groundwater. Furthermore, these findings suggest that the talus aquifers of the Cordillera Blanca were formed in proglacial lakes, followed by infilling with fine lacustrine sediments that confine lower units and allow for groundwater discharge to springs via macropores and preferential flow.
Waterfowl are the natural hosts of avian influenza virus (AIV), and through migration spread the virus worldwide. Most AIVs carried by wild waterfowl are low pathogenic strains; however, Goose/Guangdong/1996 lineage clade 2.3.4.4 H5 highly pathogenic (HP) AIV now appears to be endemic in wild birds in much of the Eastern Hemisphere. Most research efforts studying AIV pathogenicity in waterfowl thus far have been directed toward dabbling ducks. In order to better understand the role of diving ducks in AIV ecology, we previously characterized the pathogenesis of clade 2.3.4.4 H5 HPAIV in lesser scaup (Aythya affinis). In an effort to further elucidate AIV infection in diving ducks, the relative susceptibility and pathogenesis of two North American lineage H7 HPAIV isolates from the most recent outbreaks in the United States was investigated. Lesser scaup were inoculated with either A/turkey/IN/1403-1/2016 H7N8 or A/chicken/TN/17-007147-2/2017 H7N9 HPAIV by the intranasal route. The approximate 50% bird infectious dose (BID50) of the H7N8 isolate was determined to be 103 50% egg infectious doses (EID50), and the BID50 of the H7N9 isolate was determined to be <102 EID50, indicating some variation in adaptation between the two isolates. No mortality or clinical disease was observed in either group except for elevated body temperatures at 2 and 4 days postinoculation (DPI). Virus shedding was detected up to 14 DPI from both groups, and there was a trend for shedding to have a longer duration and at higher titer levels from the cloacal route. These results demonstrate that lesser scaup are susceptible to both H7 lineages of HPAIV, and similar to dabbling duck species, they shed virus for long periods relative to gallinaceous birds and don't present with clinical disease.
In 2015, the U.S. Geological Survey (USGS) entered into a cooperative agreement with the North Carolina Department of Transportation (NCDOT) to develop a North Carolina-enhanced variation of the national Stochastic Empirical Loading and Dilution Model (SELDM) with available North Carolina-specific streamflow and water-quality data and to demonstrate use of the model by documenting selected simulation scenarios. The USGS developed the national SELDM in cooperation with the Federal Highway Administration (FHWA) to provide the tools and techniques necessary for performing stormwater-quality simulations. SELDM uses a stochastic mass-balance approach to estimate combinations of flows, concentrations, and loads of stormwater constituents from the site of interest (often a highway catchment; nonhighway areas, such as a large impervious area at a shopping center complex, also can be used) and the basin upstream from the stormwater outfall to assess the risk for adverse effects of runoff. SELDM also can be used to simulate the effectiveness of volume reduction, hydrograph extension, and water-quality concentration reductions by stormwater best management practices (BMPs), which are designed to help mitigate the effects of runoff on receiving water bodies.
Some of the statistical inputs needed for the North Carolina-enhanced SELDM were either calculated or augmented using local or regional data from North Carolina. Streamflow statistics used by SELDM were determined for 266 streamgages across North Carolina on the basis of data available through the 2015 water year. Recession ratio statistics used for triangular hydrographs were also developed for 30 streamgages across the State. The NCDOT identified previous research reports on highway-runoff and BMP studies in North Carolina for review of potential data addition to the national FHWA Highway-Runoff Database (HRDB). Following USGS review of these data, a total of 25,087 event mean concentration values and 1,140 storm events for 39 highway-runoff sites and 195 analytes were uploaded to the national HRDB from six North Carolina highway-runoff research reports and a recent USGS bridge deck runoff study. Using data for 27 streamgages in North Carolina, a total of 57 water-quality transport curves were developed for seven constituents for use in simulating water-quality conditions in the upstream basin. Performance data for three BMPs (bioretention, grass strip or swale, and wetland channel) from NCDOT research data were incorporated into the North Carolina-enhanced SELDM for volume-reduction statistics, including the effectiveness of treating four water-quality constituents (total suspended solids, total nitrogen, total phosphorus, nitrate plus nitrite) and turbidity.
Simulations using the North Carolina-enhanced SELDM are presented for two hypothetical upstream basins in the Piedmont ecoregion and one hypothetical highway site to demonstrate how simulations can be used to provide risk-based information about potential effects of stormwater runoff on downstream water quality and the potential for mitigating those risks by using BMPs. The first group of simulations explores the stochastic variability in dilution factors (the ratio of the highway runoff to the total downstream stormflow) for a hypothetical Piedmont rural creek having drainage areas ranging from 1 to 100 square miles. The second group of simulations examines dilution factors based on variations in precipitation, streamflow, and recession ratios for two hypothetical Piedmont upstream basins (rural and urban) where the drainage area was held constant at 25 square miles. These simulations indicate the sensitivity of results to variations in each of the three variables. The third group of simulations examines the effects of varied concentrations in the upstream basin on water-quality conditions downstream from the highway crossing. Variations in upstream water-quality conditions for three constituents (suspended sediment concentration, total nitrogen, and total phosphorus) are based on water-quality transport curves selected from among the 57 curves developed as part of this study to represent low-, medium-, and high-concentration statistics. Simulations completed for this third group also examine the potential effects of grass swale and bioretention BMP treatment on total nitrogen and total phosphorus concentrations in highway runoff. The BMP performance data from the NCDOT research reports were applied in this group of simulations.
The stochastic mass-balance approach used in SELDM analyses and simulations provides a strong tool for engineers and water-resource managers to use in exploring a wide range of possible hydrologic and water-quality inputs and their effects on downstream water quality. The results of this study can not only aid engineers and managers in planning for potential adverse effects of runoff at site-specific locations, they can also help the USGS and other Federal and State agencies with oversight responsibilities in stormwater-quality issues to continue gathering data on potential water-quality effects in receiving streams.
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U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
California faces unprecedented challenges presented by shifting weather patterns that are defining a “new normal.” The result has been extreme weather events, prolonged drought, flooding, and debris flows. These conditions drive severe tree mortality, increase wildfire occurrence and intensity, reduce water availability, and hasten subsidence in groundwater basins. Collectively, these challenges threaten public safety, compromise infrastructure, and adversely impact the economic well-being of California's citizens. Critical applications that address these issues depend on light detection and ranging (lidar) data that provide a highly detailed, three-dimensional (3D) model of the Earth’s surface. The U.S. Geological Survey 3D Elevation Program works in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage to meet the needs of California and the Nation.
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\"}}]}","edition":"Version 1.1; Revised June 24, 2019","contact":"Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
3D Elevation Program
Email: 3DEP@usgs.gov
This report presents revised results for four parameters reported for suspended-sediment samples that were collected in the lower Mississippi-Atchafalaya River Basin as part of a cooperative program between the U.S. Army Corps of Engineers, Mississippi Valley Division, New Orleans District and the U.S. Geological Survey (USGS). The cooperative program has been active since 1973 at seven sites: two sites on the main stem of the Mississippi River, three sites on the Atchafalaya River, one site on the Old River Outflow Channel, and one site on the lower Red River above the confluence with the Old River Outflow Channel. The four parameters—suspended-sediment concentration, percent by mass of the sediment that passes through a 0.063-millimeter (US 230) sieve, instantaneous stream discharge, and instantaneous suspended-sediment discharge—reported for 2,895 samples have been modified to reflect the findings of a full review of the cooperative program, which was initiated by both agencies in January 2015. The revised results are for samples collected from October 1989 through February 2015. Ninety-four percent of the revised values for suspended-sediment concentration are lower than their corresponding original reported values, indicating that less suspended sediment moves through the lower Mississippi River system than was previously reported. For example, the median revised instantaneous suspended-sediment discharge at the Mississippi River at Tarbert Landing, Miss. (USGS station 07295100), was 315,000 short tons per day, compared to 378,000 short tons per day as originally reported. At the Atchafalaya River at Simmesport, La. (USGS station 07381490), the median revised suspended-sediment discharge was 105,000 short tons per day, compared to 143,000 short tons per day as originally reported. The systematic downward revision in instantaneous suspended-sediment discharge values was due to a systematic downward revision in the suspended fine (less than 0.063 millimeter) sediment concentration. The effect of the revision on the suspended-sand concentration and instantaneous suspended-sand discharge was weaker. Any model of sediment load or transport processes in the basin that uses data from the affected samples should be reevaluated on the basis of the revised results.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185147","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, New Orleans District","usgsCitation":"Norton, K.K., Olsen, L.D., Baumann, T.E., Simmons, L.B., Clark, A.P., Demcheck, D.K., and Johnson, M., 2019, Revisions to suspended-sediment concentration, percent smaller than 0.063 millimeter, and instantaneous suspended-sediment discharge reported for a cooperative program between the U.S. Geological Survey and the U.S. Army Corps of Engineers in the lower Mississippi-Atchafalaya River Basin, October 1989 to February 2015: U.S. Geological Survey Scientific Investigations Report 2018–5147, 232 p., https://doi.org/10.3133/sir20185147.","productDescription":"Report: x, 232 p.; Data Release","numberOfPages":"246","onlineOnly":"N","ipdsId":"IP-088529","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":363738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5147/coverthb.jpg"},{"id":363739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5147/sir20185147.pdf","text":"Report","size":"7.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5147"},{"id":363740,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K936GW","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Revised Data and Supporting Information for Seven Sites located on the Lower Mississippi and Atchafalaya Rivers sampled as part of a cooperative sediment program with the U.S. Army Corps of Engineers, October 1989 through February 2015"}],"country":"United States","otherGeospatial":"Lower Mississippi basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.830936,29.164113 ], [ -91.830936,32.428085 ], [ -89.918735,32.428085 ], [ -89.918735,29.164113 ], [ -91.830936,29.164113 ] ] ] } } ] }","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park Drive
Nashville, TN 37211
The primary mission of the U.S. Geological Survey (USGS) Water Mission Area is to collect and disseminate reliable, impartial, and timely information needed to understand the water resources of the Nation, including data on streamflow, groundwater, water quality, water use, and availability. Management of data throughout the entire data lifecycle is necessary to meet the mission and maintain the USGS reputation of producing high-quality data as the Nation’s primary earth-science information agency. This document describes the data management procedures of the USGS Washington Water Science Center, including responsibilities of staff and workflow procedures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191049","usgsCitation":"Conn, K.E., Mastin, M.C., Long, A.J., Dinicola, R.S., and Barton, C., 2019, Data management plan for the U.S. Geological Survey Washington Water Science Center : U.S. Geological Survey Open-File Report 2019-1049, 23 p., https://doi.org/10.3133/ofr20191049.","productDescription":"Report: iv, 23 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-104277","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":363807,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1049/coverthb.jpg"},{"id":363808,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1049/ofr20191049.pdf","text":"Report","size":"573 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1049"}],"country":"United States","state":"Washington","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
We investigated the morphology, biostratigraphy, shell stable isotope composition and paleogeography of the common Arctic benthic foraminifera, Cassidulina teretis (Tappan 1951) (sometimes assigned to Islandiella (Nørvang 1958), for application to Quaternary paleoceanography. Cassidulina teretis, which has been studied by several generations of Arctic foraminiferal specialists, is used in Arctic Ocean paleoceanographic reconstructions based on foraminiferal assemblages and, increasingly, isotope shell chemistry. Here we review its modern and fossil distribution including discussions of its taxonomy, ecology, biostratigraphy and shell chemistry. Cassidulina teretis Tappan 1951, originally described from the Gubik Formation, northern Alaska coastal plain, has variability in test size, apertural morphology and development of an umbilical boss representing intra- and inter-population differences across the Arctic and subarctic in modern, Quaternary and Pliocene assemblages. Nonetheless, our studies and those previously published lead us to conclude that populations from the Arctic Ocean represent a single species proposed by Tappan as Cassidulina teretis. Its modern distribution is mainly 200 to 1000 m water depth, often living within the core of the relatively warm Atlantic Layer. However, shallower occurrences suggest other factors, such as food supply, are also critical to its ecology. The Holocene distribution of Cassidulina teretis in the Beaufort Sea boundary indicate millennial-scale changes in relative abundance related to changing Atlantic Layer influence, sea-ice cover, surface productivity and food availability. There are extremely large changes in its abundance during the last deglacial interval on the Yermak Plateau, Barents Sea slope and the Laptev Sea reflecting rapid ocean changes during the Bølling-Allerød, Younger Dryas, and Preboreal. Similarly, C. teretis abundance changes during the last 300,000 years allow us to use it, at least regionally, as a useful biostratigraphic marker. The stable isotopic composition of Cassidulina teretis tests holds promise for establishing an isotope stratigraphy across the Arctic Ocean and perhaps also in the Nordic Seas, off Iceland and in the northern North Atlantic Ocean, once disequilibrium values and offsets from other Arctic benthic species are more firmly established.
","language":"English","publisher":"Micro Press","usgsCitation":"Cronin, T.M., Seidenstein, J., Keller, K., McDougall-Reid, K., Reufer, A., and Gemery, L., 2019, The benthic foraminifera cassidulina from the Arctic Ocean: Application to paleoceanography and biostratigraphy: Micropaleontology, v. 65, no. 2, p. 105-125.","productDescription":"21 p.","startPage":"105","endPage":"125","ipdsId":"IP-097014","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":385640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385617,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org/microaccess/micropaleontology/issue-347/article-2119"}],"volume":"65","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":815570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seidenstein, Julia","contributorId":243162,"corporation":false,"usgs":false,"family":"Seidenstein","given":"Julia","affiliations":[],"preferred":false,"id":815571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keller, Katherine 0000-0001-6915-5455","orcid":"https://orcid.org/0000-0001-6915-5455","contributorId":218048,"corporation":false,"usgs":false,"family":"Keller","given":"Katherine","email":"","affiliations":[{"id":39732,"text":"Natural Systems Analysts, Harvard University","active":true,"usgs":false}],"preferred":false,"id":815572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDougall-Reid, Kristin 0000-0002-8788-3664","orcid":"https://orcid.org/0000-0002-8788-3664","contributorId":216211,"corporation":false,"usgs":true,"family":"McDougall-Reid","given":"Kristin","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":815573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reufer, Ana","contributorId":258025,"corporation":false,"usgs":false,"family":"Reufer","given":"Ana","email":"","affiliations":[{"id":16809,"text":"James Madison University","active":true,"usgs":false}],"preferred":false,"id":815574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gemery, Laura 0000-0003-1966-8732 lgemery@usgs.gov","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":5402,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","email":"lgemery@usgs.gov","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":815645,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208535,"text":"70208535 - 2019 - Characterization of the exoskeleton of the Antarctic king crab Paralomis birsteini","interactions":[],"lastModifiedDate":"2020-02-14T06:43:48","indexId":"70208535","displayToPublicDate":"2019-05-14T06:42:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2104,"text":"Invertebrate Biology","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of the exoskeleton of the Antarctic king crab Paralomis birsteini","docAbstract":"Ocean acidification is projected to inhibit the biogenic production of calcium-carbonate skeletons in marine organisms. Antarctic waters represent a natural environment in which to examine the long-term effects of carbonate undersaturation on calcification in marine predators. King crabs (Decapoda: Anomura: Lithodidae), which currently inhabit the undersaturated environment of the continental slope off Antarctica, are potential invasives on the Antarctic shelf as oceanic temperatures rise. Here, we describe the chemical, physical, and mechanical properties of the exoskeleton of the deep-water Antarctic lithodid Paralomis birsteini and compare our measurements with two decapod species from shallow water at lower latitudes: Cancer borealis (Brachyura: Cancridae) and Callinectes sapidus (Brachyura: Portunidae). Paralomis birsteini deposit proportionally more calcium carbonate in their predatory chelae than their protective carapaces, compared with the other two crab species. When exoskeleton thickness and microhardness were compared between the chelae and carapace, the magnitude of the difference between these body regions was significantly greater in P. birsteini than in the other species tested. Hence, there appeared to be a greater disparity in P. birsteini in overall investment in calcium-carbonate structures among regions of the exoskeleton. The imperatives of prey consumption and predator avoidance may be influencing the deposition of calcium to different parts of the exoskeleton in lithodids living in an environment undersaturated with respect to calcium carbonate.","language":"English","publisher":"Wiley","doi":"10.1111/ivb.12246","usgsCitation":"Steffel, B.V., Smith, K.E., Dickinson, G.H., Flannery, J.A., Baran, K.A., Rosen, M.N., Mcclintock, J.B., and Aronson, R.B., 2019, Characterization of the exoskeleton of the Antarctic king crab Paralomis birsteini: Invertebrate Biology, v. 138, no. 2, e12246, https://doi.org/10.1111/ivb.12246.","productDescription":"e12246","ipdsId":"IP-104563","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467618,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ivb.12246","text":"Publisher Index Page"},{"id":372334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"138","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Steffel, Brittan V.","contributorId":222496,"corporation":false,"usgs":false,"family":"Steffel","given":"Brittan","email":"","middleInitial":"V.","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":782323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Kathryn E.","contributorId":222497,"corporation":false,"usgs":false,"family":"Smith","given":"Kathryn","email":"","middleInitial":"E.","affiliations":[{"id":17840,"text":"University of Exeter","active":true,"usgs":false}],"preferred":false,"id":782324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickinson, Gary H.","contributorId":222498,"corporation":false,"usgs":false,"family":"Dickinson","given":"Gary","email":"","middleInitial":"H.","affiliations":[{"id":33872,"text":"The College of New Jersey","active":true,"usgs":false}],"preferred":false,"id":782325,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flannery, Jennifer A. 0000-0002-1692-2662 jflannery@usgs.gov","orcid":"https://orcid.org/0000-0002-1692-2662","contributorId":4317,"corporation":false,"usgs":true,"family":"Flannery","given":"Jennifer","email":"jflannery@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":782322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baran, Kerstin A.","contributorId":222499,"corporation":false,"usgs":false,"family":"Baran","given":"Kerstin","email":"","middleInitial":"A.","affiliations":[{"id":40552,"text":"University of Alabama at Birmingham","active":true,"usgs":false}],"preferred":false,"id":782326,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosen, Miranda N.","contributorId":222500,"corporation":false,"usgs":false,"family":"Rosen","given":"Miranda","email":"","middleInitial":"N.","affiliations":[{"id":33872,"text":"The College of New Jersey","active":true,"usgs":false}],"preferred":false,"id":782327,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mcclintock, James B.","contributorId":141011,"corporation":false,"usgs":false,"family":"Mcclintock","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":13651,"text":"University of Alabama-Birmingham","active":true,"usgs":false}],"preferred":false,"id":782328,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Aronson, Richard B. 0000-0003-0383-3844","orcid":"https://orcid.org/0000-0003-0383-3844","contributorId":212695,"corporation":false,"usgs":false,"family":"Aronson","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":782329,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203436,"text":"70203436 - 2019 - Hydrologic lag effects on wetland greenhouse gas fluxes","interactions":[],"lastModifiedDate":"2019-05-14T11:48:57","indexId":"70203436","displayToPublicDate":"2019-05-14T05:48:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5634,"text":"Atmosphere","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic lag effects on wetland greenhouse gas fluxes","docAbstract":"Hydrologic margins of wetlands are narrow, transient zones between inundated and dry areas. As water levels fluctuate, the dynamic hydrology at margins may impact wetland greenhouse gas (GHG) fluxes that are sensitive to soil saturation. The Prairie Pothole Region of North America consists of millions of seasonally-ponded wetlands that are ideal for studying hydrologic transition states. Using a long-term GHG database with biweekly flux measurements from 88 seasonal wetlands, we categorized each sample event into wet to wet (W→W), dry to wet (D→W), dry to dry (D→D), or wet to dry (W→D) hydrologic states based on the presence or absence of ponded water from the previous and current event. Fluxes of methane were 5-times lower in the D→W compared to W→W states, indicating a lag ‘ramp-up’ period following ponding. Nitrous oxide fluxes were highest in the W→D state and accounted for 20% of total emissions despite accounting for only 5.2% of wetland surface area during the growing season. Fluxes of carbon dioxide were unaffected by transitions, indicating a rapid acclimation to current conditions by respiring organisms. Results of this study highlight how seasonal drying and re-wetting impact GHGs and demonstrate the importance of hydrologic transitions on total wetland GHG balance.","language":"English","publisher":"MDPI","doi":"10.3390/atmos10050269","usgsCitation":"Tangen, B., and Bansal, S., 2019, Hydrologic lag effects on wetland greenhouse gas fluxes: Atmosphere, v. 10, no. 5, 13 p., https://doi.org/10.3390/atmos10050269.","productDescription":"13 p.","ipdsId":"IP-106999","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467619,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/atmos10050269","text":"Publisher Index Page"},{"id":437463,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KS6QG2","text":"USGS data release","linkHelpText":"Soil properties and greenhouse gas fluxes of Prairie Pothole Region wetlands: a comprehensive data release"},{"id":363763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":762701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":762702,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204006,"text":"70204006 - 2019 - Groundwater quality of a public supply aquifer in proximity to oil development, Fruitvale Oil Field, Bakersfield, California","interactions":[],"lastModifiedDate":"2019-06-26T16:03:51","indexId":"70204006","displayToPublicDate":"2019-05-13T15:51:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater quality of a public supply aquifer in proximity to oil development, Fruitvale Oil Field, Bakersfield, California","docAbstract":"Due to concerns over the effects of oil production activities on groundwater quality in California, chemical, isotopic, dissolved gas and age-dating tracers were analyzed in samples collected from public-supply wells and produced-water sites in the Fruitvale oil field (FVOF). A combination of newly collected and historical data was used to determine whether oil formation fluids have mixed with groundwater used for public supply and what the potential pathways for the migration of oil formation fluids into groundwater may be. Stable isotopes of water (δ2H and δ18O) and age dating (3H, 3Hetrit, SF6 and 14C) tracers in groundwater samples were consistent with the Kern River being the main source of recharge to aquifers. The distribution of major ion concentrations and pH with distance from the Kern River indicate that natural processes were the primary controls on groundwater salinity. Two of 14 groundwater samples had δ13C-DIC values (−2.4 to +1.9 per mil) consistent with mixtures of <1 to about 9 percent oil-field water. Concentrations of TDS in groundwater samples were generally much lower (129–1,200 milligrams per liter (mg/l), median 216 mg/l) than produced water samples (586–24,930 mg/l, median 2,717 mg/l), suggesting that any mixing of oil-field water with groundwater has not significantly affected groundwater salinity. Trace concentrations of thermogenic methane were detected in three groundwater samples that did not have dissolved inorganic or isotopic indicators consistent with mixing of oil-field water, suggesting that stray gases may have migrated from the subsurface via preferential pathways such as leaky well bores into groundwater aquifers. Low concentrations of petroleum hydrocarbons were detected in samples that also contained anthropogenic VOCs and components of post- and pre-1950s recharge, indicating that petroleum hydrocarbons could have come from subsurface and/or surface sources. Overall, the results of this study indicated that groundwater currently used for public supply in the FVOF was of good quality with little, if any, effects from oil production activities. This may be due in part to the relatively rapid flushing of the aquifer system by recharge from the Kern River.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2019.05.003","usgsCitation":"Wright, M., McMahon, P.B., Landon, M.K., and Kulongoski, J.T., 2019, Groundwater quality of a public supply aquifer in proximity to oil development, Fruitvale Oil Field, Bakersfield, California: Applied Geochemistry, v. 106, p. 82-95, https://doi.org/10.1016/j.apgeochem.2019.05.003.","productDescription":"14 p.","startPage":"82","endPage":"95","ipdsId":"IP-093942","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":467620,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2019.05.003","text":"Publisher Index Page"},{"id":365096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Bakersfield","otherGeospatial":"Fruitvale Oil Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.57107543945311,\n 35.17493084974928\n ],\n [\n -119.57107543945311,\n 35.17493084974928\n ],\n [\n -119.57107543945311,\n 35.17493084974928\n ],\n [\n -119.57107543945311,\n 35.17493084974928\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.00115966796875,\n 35.48890875085949\n ],\n [\n -119.04373168945314,\n 35.48541438776276\n ],\n [\n -119.0478515625,\n 35.48275857019274\n ],\n [\n -119.04870986938477,\n 35.46808010116232\n ],\n [\n -119.04029846191405,\n 35.46108941215697\n ],\n [\n -119.02072906494142,\n 35.44724605551148\n ],\n [\n -119.02072906494142,\n 35.44221151715641\n ],\n [\n -119.01643753051758,\n 35.43941441533686\n ],\n [\n -119.01163101196289,\n 35.436617216330966\n ],\n [\n -119.00922775268555,\n 35.42878454211113\n ],\n [\n -119.01884078979492,\n 35.42374884923695\n ],\n [\n -119.01248931884766,\n 35.411018333025666\n ],\n [\n -119.00871276855467,\n 35.40682101870289\n ],\n [\n -118.98828506469725,\n 35.41003897923532\n ],\n [\n -118.96957397460938,\n 35.41269719754907\n ],\n [\n -118.96322250366211,\n 35.42290953648285\n ],\n [\n -118.94914627075195,\n 35.43395978725954\n ],\n [\n -118.9460563659668,\n 35.44235136969617\n ],\n [\n -118.95429611206056,\n 35.453259119161764\n ],\n [\n -118.9621925354004,\n 35.46808010116232\n ],\n [\n -118.97283554077148,\n 35.474930386870035\n ],\n [\n -118.99686813354491,\n 35.485833719356805\n ],\n [\n -119.00115966796875,\n 35.48890875085949\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wright, Michael 0000-0003-0653-6466 mtwright@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":151031,"corporation":false,"usgs":true,"family":"Wright","given":"Michael","email":"mtwright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765172,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202335,"text":"ofr20191016 - 2019 - Analysis for agreement of the Northern Gulf of Mexico topobathymetric digital elevation model with 3-Dimensional Elevation Program 1/3 arc-second digital elevation models","interactions":[],"lastModifiedDate":"2019-05-14T11:43:13","indexId":"ofr20191016","displayToPublicDate":"2019-05-13T11:35:20","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":"2019-1016","displayTitle":"Analysis for Agreement of the Northern Gulf of Mexico Topobathymetric Digital Elevation Model with 3-Dimensional Elevation Program 1/3 Arc-Second Digital Elevation Models","title":"Analysis for agreement of the Northern Gulf of Mexico topobathymetric digital elevation model with 3-Dimensional Elevation Program 1/3 arc-second digital elevation models","docAbstract":"Topographical differencing and edge-matching analyses were used to evaluate agreement of the Coastal National Elevation Database Applications Project’s Northern Gulf of Mexico topobathymetric digital elevation model (TBDEM) with The National Map 3-Dimensional Elevation Program (3DEP) 1/3 arc-second digital elevation models (DEMs). In addition to topographic map products provided through the National Geospatial Program, the model integrates bathymetric and topobathymetric datasets for three-dimensional (3D) mapping of rivers, lakes, and bays in the upland and intertidal wetlands to offshore environments in coastal zones from the border between Texas and Louisiana to east of Mobile Bay, Alabama.
Contoured elevation differences between the Northern Gulf of Mexico TBDEM and the 3DEP 1/3 arc-second DEMs indicate that 85 percent of elevation data in the Northern Gulf of Mexico TBDEM agree (no difference for contoured elevations) between 95 and 100 percent with 3DEP 1/3 arc-second DEMs. Edge matching differences between adjacent Northern Gulf of Mexico TBDEM source projects or between the TBDEM and 3DEP DEMs indicate most seams between integrated and 3DEP DEMs are smooth. Where seams did not match, most differences were in the range of tenths to hundredths of a meter. Valid differences that are greater than plus or minus 2 meters in areas of bathymetric data are found in the Mississippi River, Atchafalaya River, Lower Atchafalaya River, Wax Lake Pass channel, the Vermilion Bay bathymetric datasets, and where topobathymetric datasets are integrated in the model. Areas with positive or negative outlier difference elevations seem to be a result of site conditions that affect light detection and ranging (lidar) waveform return signals, misclassification of surface features, or possibly because of interpolation required to develop a smooth elevation surface. Results of this analysis provide information to help understand model parameters and agreement of the Northern Gulf of Mexico TBDEM developed using different data types from different sources with The National Map 3DEP DEMs.
Inclusion of bathymetric and topobathymetric data types in the 3DEP aligns with the mission to respond to growing needs for a wide range of three-dimensional representations of the Nation and supports the U.S. Geological Survey strategy for developing a National Terrain Model to provide hydrographic and elevation data that extend the elevation surface below water bodies. The 3D Nation Requirements and Benefits Study sponsored by the U.S. Geological Survey and National Oceanic and Atmospheric Administration to assess local to regional Tribal, State, and Federal technical requirements, needs, and benefits for using topographic and bathymetric 3DEP elevation data will be used to help develop and refine future program alternatives for 3D elevation data that include a category for bathymetry and topobathymetry. At the time of this report (2019), 3DEP acquisition is specific to topographic lidar that meets lidar DEM specifications and which requires surface-water feature areas to be hydroflattened. Cataloging bathymetric and topobathymetric DEMs as part of the 3DEP will require new specifications for acoustic, lidar, merged acoustic and lidar, and possibly other bathymetric and topobathymetric survey data types.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191016","usgsCitation":"Miller-Corbett, C., 2019, Analysis for agreement of the Northern Gulf of Mexico topobathymetric digital elevation model with 3-Dimensional Elevation Program 1/3 arc-second digital elevation models: U.S. Geological Survey Open-File Report 2019–1016, 44 p., https://doi.org/10.3133/ofr20191016.","productDescription":"vi, 43 p.","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-081383","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"links":[{"id":363655,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1016/ofr20191016.pdf","text":"Report","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1016"},{"id":363654,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1016/coverthb.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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.48193359375,\n 28.43971381702788\n ],\n [\n -84.13330078125,\n 28.43971381702788\n ],\n [\n -84.13330078125,\n 31.39115752282472\n ],\n [\n -96.48193359375,\n 31.39115752282472\n ],\n [\n -96.48193359375,\n 28.43971381702788\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
1. Hotspot analysis is a commonly used method in ecology and conservation to identify areas of high biodiversity or conservation concern. However, delineating and mapping hotspots is subjective and various approaches can lead to different conclusions with regard to the classification of particular areas as hotspots, complicating long-term conservation planning and implementation efforts.
2. We present a comparative analysis of recent approaches for identifying waterbird hotspots, with the goal of developing insights about the appropriate use of these methods. We selected four commonly used measures to identify persistent areas of high use: kernel density estimation, Getis-Ord Gi*, hotspot persistence, and hotspots conditional on presence, which represent the range of quantitative hotspot estimation approaches used in waterbird analyses. We applied each of the methods to aerial survey waterbird count data collected in the Great Lakes from 2012-2014 using a 5 km2 grid. For each approach, we identified areas of high use for seven species/species groups and then compared the results across all methods.
3. Our results indicate that formal hotspot analysis frameworks do not always lead to the same conclusions. The kernel density and Getis-Ord Gi* methods yielded the most similar results across all species analyzed. We found that these two models can differ substantially from the hotspot persistence and hotspots conditional on presence estimation approaches, which were not consistently similar to one another. The hotspot persistence approach differed most significantly from the other methods but is the only method to explicitly account for temporal variation.
4. We recommend considering the ecological question and scale of any conservation or management activities prior to designing survey methodologies. Deciding the appropriate definition and scale for analysis is critical for interpretation of hotspot analysis results. Combining methods using an integrative approach, either within a single analysis or post-hoc, could lead to greater consistency in the identification of waterbird hotspots.
","language":"English","publisher":"British Ecological society","doi":"10.1111/2041-210X.13209","usgsCitation":"Sussman, A.L., Gardner, B., Adams, E.M., Salas, L., Kenow, K.P., Luukkonen, D.R., Monfils, M.J., Mueller, W.P., Williams, K.A., Leduc-Lapierre, M., and Zipkin, E.F., 2019, A comparative analysis of common methods to identify waterbird hotspots: Methods in Ecology and Evolution, v. 10, no. 9, p. 1454-1468, https://doi.org/10.1111/2041-210X.13209.","productDescription":"15 p.","startPage":"1454","endPage":"1468","ipdsId":"IP-091670","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467621,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13209","text":"Publisher Index Page"},{"id":367534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie, Lake Huron, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.76953125,\n 41.21172151054787\n ],\n [\n -78.75,\n 41.21172151054787\n ],\n [\n -78.75,\n 46.164614496897094\n ],\n [\n -88.76953125,\n 46.164614496897094\n ],\n [\n -88.76953125,\n 41.21172151054787\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"9","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Sussman, Allison L.","contributorId":219074,"corporation":false,"usgs":false,"family":"Sussman","given":"Allison","email":"","middleInitial":"L.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":771216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":771217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Evan M.","contributorId":139994,"corporation":false,"usgs":false,"family":"Adams","given":"Evan","email":"","middleInitial":"M.","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":771218,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salas, Leo","contributorId":219075,"corporation":false,"usgs":false,"family":"Salas","given":"Leo","email":"","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":771219,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kenow, Kevin P. 0000-0002-3062-5197 kkenow@usgs.gov","orcid":"https://orcid.org/0000-0002-3062-5197","contributorId":3339,"corporation":false,"usgs":true,"family":"Kenow","given":"Kevin","email":"kkenow@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":771215,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luukkonen, David R.","contributorId":219076,"corporation":false,"usgs":false,"family":"Luukkonen","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":771220,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Monfils, Michael J.","contributorId":219077,"corporation":false,"usgs":false,"family":"Monfils","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":39957,"text":"Michigan State University Extension","active":true,"usgs":false}],"preferred":false,"id":771221,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mueller, William P.","contributorId":219078,"corporation":false,"usgs":false,"family":"Mueller","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":39958,"text":"Western Great Lakes Bird and Bat Observatory","active":true,"usgs":false}],"preferred":false,"id":771222,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Williams, Kate A.","contributorId":219079,"corporation":false,"usgs":false,"family":"Williams","given":"Kate","email":"","middleInitial":"A.","affiliations":[{"id":37436,"text":"Biodiversity Research Institute","active":true,"usgs":false}],"preferred":false,"id":771223,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Leduc-Lapierre, Michelle","contributorId":219080,"corporation":false,"usgs":false,"family":"Leduc-Lapierre","given":"Michelle","email":"","affiliations":[{"id":13509,"text":"Great Lakes Commission","active":true,"usgs":false}],"preferred":false,"id":771224,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zipkin, Elise F. 0000-0003-4155-6139","orcid":"https://orcid.org/0000-0003-4155-6139","contributorId":192755,"corporation":false,"usgs":false,"family":"Zipkin","given":"Elise","email":"","middleInitial":"F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":771225,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70210223,"text":"70210223 - 2019 - Microbial assemblages reflect environmental heterogeneity in alpine streams","interactions":[],"lastModifiedDate":"2020-05-21T14:23:46.94455","indexId":"70210223","displayToPublicDate":"2019-05-11T09:20:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Microbial assemblages reflect environmental heterogeneity in alpine streams","docAbstract":"Alpine streams are dynamic habitats harboring substantial biodiversity across small spatial extents. The diversity of alpine stream biota is largely reflective of environmental heterogeneity stemming from varying hydrological sources. Globally, alpine stream diversity is under threat as meltwater sources recede and stream conditions become increasingly homogeneous. Much attention has been devoted to macroinvertebrate diversity in alpine headwaters, yet to fully understand the breadth of climate change threats, a more thorough accounting of microbial diversity is needed. We characterized microbial diversity (specifically Bacteria and Archaea) of 13 streams in two disjunct Rocky Mountain subranges through 16S rRNA gene sequencing. Our study encompassed the spectrum of alpine stream sources (glaciers, snowfields, subterranean ice, and groundwater) and three microhabitats (ice, biofilms, and streamwater). We observed no difference in regional (γ) diversity between subranges but substantial differences in diversity among (β) stream types and microhabitats. Within‐stream (α) diversity was highest in groundwater‐fed springs, lowest in glacier‐fed streams, and positively correlated with water temperature for both streamwater and biofilm assemblages. We identified an underappreciated alpine stream type—the icy seep—that are fed by subterranean ice, exhibit cold temperatures (summer mean <2°C), moderate bed stability, and relatively high conductivity. Icy seeps will likely be important for combatting biodiversity losses as they contain similar microbial assemblages to streams fed by surface ice yet may be buffered against climate change by insulating debris cover. Our results show that the patterns of microbial diversity support an ominous trend for alpine stream biodiversity; as meltwater sources decline, stream communities will become more diverse locally, but regional diversity will be lost. Icy seeps, however, represent a source of optimism for the future of biodiversity in these imperiled ecosystems.","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14683","usgsCitation":"Hotaling, S., Foley, M., Zeglin, L., Finn, D.S., Tronstad, L., Giersch, J.J., Muhlfeld, C.C., and Weisrock, D.W., 2019, Microbial assemblages reflect environmental heterogeneity in alpine streams: Global Change Biology, v. 25, no. 8, p. 2576-2590, https://doi.org/10.1111/gcb.14683.","productDescription":"15 p.","startPage":"2576","endPage":"2590","ipdsId":"IP-105125","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":374985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.11474609375001,\n 47.07386310181414\n ],\n [\n -112.30224609374999,\n 47.07386310181414\n ],\n [\n -112.30224609374999,\n 49.001843917978526\n ],\n [\n -115.11474609375001,\n 49.001843917978526\n ],\n [\n -115.11474609375001,\n 47.07386310181414\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"8","noUsgsAuthors":false,"publicationDate":"2019-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hotaling, Scott","contributorId":202050,"corporation":false,"usgs":false,"family":"Hotaling","given":"Scott","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":789623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Mary E.","contributorId":224817,"corporation":false,"usgs":false,"family":"Foley","given":"Mary E.","affiliations":[{"id":40945,"text":"Department of Biology, University of Kentucky, Lexington, KY, USA","active":true,"usgs":false}],"preferred":false,"id":789624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zeglin, Lydia","contributorId":224818,"corporation":false,"usgs":false,"family":"Zeglin","given":"Lydia","affiliations":[{"id":40946,"text":"Division of Biology, Kansas State University, Manhattan, KS, USA","active":true,"usgs":false}],"preferred":false,"id":789625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finn, Debra S.","contributorId":198312,"corporation":false,"usgs":false,"family":"Finn","given":"Debra","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":789626,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tronstad, Lusha M.","contributorId":224819,"corporation":false,"usgs":false,"family":"Tronstad","given":"Lusha M.","affiliations":[{"id":40947,"text":"Wyoming Natural Diversity Database, University of Wyoming, Laramie, WY, USA","active":true,"usgs":false}],"preferred":false,"id":789627,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Giersch, J. Joseph 0000-0001-7818-3941 jgiersch@usgs.gov","orcid":"https://orcid.org/0000-0001-7818-3941","contributorId":198074,"corporation":false,"usgs":true,"family":"Giersch","given":"J.","email":"jgiersch@usgs.gov","middleInitial":"Joseph","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789628,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789629,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weisrock, David W.","contributorId":198313,"corporation":false,"usgs":false,"family":"Weisrock","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":789630,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203601,"text":"70203601 - 2019 - Eradication of two non-native cichlid fishes in Miami, Florida (USA)","interactions":[],"lastModifiedDate":"2019-06-12T13:15:57","indexId":"70203601","displayToPublicDate":"2019-05-10T14:52:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Eradication of two non-native cichlid fishes in Miami, Florida (USA)","docAbstract":"The proliferation of non-native fishes in Florida is a serious problem, and new species continue to be introduced to the state. Fishes in the Family Cichlidae have been especially successful colonizers of south Florida freshwater habitats. Herein we report a multi-agency effort to eradicate two non-native cichlid fishes in Miami, Florida (Bay Snook Petenia splendida and Blue Mbuna Labeotropheus fuelleborni). These fishes were removed before they were observed in the extensive, interconnected canal system through which they may have been able to expand throughout south Florida and access protected areas such as Everglades National Park. The study site, Pinecrest Gardens, is important because it contains remnant coastal cypress-strand habitat in an increasingly urbanized landscape that historically provided refuge to native amphidromous fishes and invertebrates. The project took considerable time (3.5 years), and we detail in this report how it evolved from a focus on isolating the non-native fishes and reducing their population sizes to an eradication. Gardens’ staff hydrologically isolated their ponds from nearby waterbodies by plugging a culvert with a solid gate. That provided the interagency team with more time to remove the potential threats. Compromises were made between fish management strategies and the Gardens’ priorities. Hurricane impacts helped shift priorities to more aggressive fish-management strategies. Cooperation among several federal and state agencies, as well as the Gardens, was key to the project’s success. We hope this effort may serve as a model for removing non-native species before they spread into ecosystems where eradication is not practical.","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2019.10.2.06","usgsCitation":"Schofield, P.J., Jelks, H.L., and Gestring, K.B., 2019, Eradication of two non-native cichlid fishes in Miami, Florida (USA): Management of Biological Invasions, v. 10, no. 2, p. 296-310, https://doi.org/10.3391/mbi.2019.10.2.06.","productDescription":"15 p.","startPage":"296","endPage":"310","ipdsId":"IP-097111","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467623,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2019.10.2.06","text":"Publisher Index Page"},{"id":437467,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EWSGZB","text":"USGS data release","linkHelpText":"Removing threats before they spread: Eradication of two non-native fishes in Miami, Florida (USA)"},{"id":364130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Miami-Dade County","city":"Miami","volume":"10","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schofield, Pamela J. 0000-0002-8752-2797 pschofield@usgs.gov","orcid":"https://orcid.org/0000-0002-8752-2797","contributorId":168659,"corporation":false,"usgs":true,"family":"Schofield","given":"Pamela","email":"pschofield@usgs.gov","middleInitial":"J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":763227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jelks, Howard L. 0000-0002-0672-6297 hjelks@usgs.gov","orcid":"https://orcid.org/0000-0002-0672-6297","contributorId":168997,"corporation":false,"usgs":true,"family":"Jelks","given":"Howard","email":"hjelks@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":763228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gestring, Kelly B.","contributorId":210849,"corporation":false,"usgs":false,"family":"Gestring","given":"Kelly","email":"","middleInitial":"B.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":763229,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204238,"text":"70204238 - 2019 - A comparison of chlorophyll a values obtained from an autonomous underwater vehicle to satellite-based measures for Lake Michigan","interactions":[],"lastModifiedDate":"2019-08-13T15:39:03","indexId":"70204238","displayToPublicDate":"2019-05-10T10:18:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of chlorophyll a values obtained from an autonomous underwater vehicle to satellite-based measures for Lake Michigan","docAbstract":"Accurate methods to track changes in lake productivity through time and space are critical to fisheries management. Chlorophyll a is the most widely studied proxy for ecosystem primary production, and has been the topic of many studies. The main sources of chlorophyll a measurements are ship-based measures or multi-spectral satellite data. Autonomous underwater vehicles can survey large spatial extents approaching the scale of satellite data, but with the accuracy of ship-based water sampling methods. We use several statistical measures to compare measures of chlorophyll a collected in Lake Michigan with spatiotemporally matched satellite-derived measures of chlorophyll a from the MODIS Aqua multi-spectral sensor using NASA’s OC3 and the Great Lakes Fit algorithms. Our findings show a near one to one relationship between AUV data and both satellite-derived data sets when the AUV data are coarsened to the resolution of the satellite data. A comparison of satellite-based chlorophyll a to AUV-derived chlorophyll summarized in discrete water depth bins suggested that, based on decreasing coefficients of determination, satellite estimates of chlorophyll accounted for the most variability in chlorophyll a concentrations in the upper 10 m of the water column, even though satellite sensors may detect past this depth.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2019.04.003","usgsCitation":"Bennion, D., Warner, D., Esselman, P., Hobson, B., and Kieft, B., 2019, A comparison of chlorophyll a values obtained from an autonomous underwater vehicle to satellite-based measures for Lake Michigan: Journal of Great Lakes Research, v. 45, no. 4, p. 726-734, https://doi.org/10.1016/j.jglr.2019.04.003.","productDescription":"9 p.","startPage":"726","endPage":"734","ipdsId":"IP-096378","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467624,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2019.04.003","text":"Publisher Index Page"},{"id":365575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n 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Center","active":true,"usgs":true}],"preferred":true,"id":766120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, David 0000-0003-4939-5368","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":216543,"corporation":false,"usgs":true,"family":"Warner","given":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":766121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":766122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hobson, Brett","contributorId":216922,"corporation":false,"usgs":false,"family":"Hobson","given":"Brett","email":"","affiliations":[{"id":37324,"text":"Monterey Bay Aquarium Research Institute","active":true,"usgs":false}],"preferred":false,"id":766173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kieft, Brian","contributorId":216923,"corporation":false,"usgs":false,"family":"Kieft","given":"Brian","email":"","affiliations":[{"id":37324,"text":"Monterey Bay Aquarium Research Institute","active":true,"usgs":false}],"preferred":false,"id":766174,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203553,"text":"70203553 - 2019 - Aluminum- and iron-based coagulation for in-situ removal of dissolved organic carbon, disinfection byproducts, mercury and other constituents from agricultural drain water","interactions":[],"lastModifiedDate":"2019-06-18T12:13:56","indexId":"70203553","displayToPublicDate":"2019-05-09T09:52:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Aluminum- and iron-based coagulation for in-situ removal of dissolved organic carbon, disinfection byproducts, mercury and other constituents from agricultural drain water","docAbstract":"Agricultural production on wetland soils can be significant sources of dissolved organic carbon (DOC), disinfection byproduct precursors, mercury and nutrients to downstream water bodies and accelerate land subsidence. Presented as a potential solution for in-situ water quality improvement and land subsidence mitigation, chemically enhanced treatment wetlands (CETWs) were used to leverage both coagulation and wetland processes. In this study, we evaluated the performance of coagulants ferric sulfate (Fe dosing) and polyaluminum chloride (Al dosing) to remove pollutants from agricultural drain water using the coagulation system designed for CETWs. Both coagulation treatments removed over 70% DOC from source waters, resulting in removal efficiencies (mg-DOC removed per mg-metal dosed) of 1 under Al dosing and 0.5 under Fe dosing. Coagulation by both treatments preferentially removed UV254 active compounds compared to the bulk DOC concentration, suggesting coagulation targeted aromatics more effectively. Phosphates and haloacetic acids were also removed more readily, whereas trihalomethanes, dissolved organic nitrogen and filtered mercury species were removed at similar or lower rates than DOC. Dissolved inorganic nitrogen was not amenable to coagulation and removal was not observed. Freundlich, Langmuir and Monod models explained 33% of the variance for Al dosing and 78 – 89% of the variance for Fe dosing. All three models indicated Al dosing had higher removal efficiency and affinity for DOC than Fe dosing under study conditions, but when used to predict maximum removal efficiency there was no cohesiveness between the three models due to different model assumptions. Consideration of fluorescence dissolved organic matter and UV254 as surrogates for DOC concentration showed both were equally suitable before coagulant application, but as surrogates after coagulant application, neither could be deemed more fit as a surrogate since both were shown suitable for different treatment scenarios.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2019.02.015","usgsCitation":"Bachand, S.M., Kraus, T.E., Stern, D., Ling Liang, Y., Horwath, W.R., and Bachand, P.A., 2019, Aluminum- and iron-based coagulation for in-situ removal of dissolved organic carbon, disinfection byproducts, mercury and other constituents from agricultural drain water: Ecological Engineering, v. 134, p. 26-38, https://doi.org/10.1016/j.ecoleng.2019.02.015.","productDescription":"13 p.","startPage":"26","endPage":"38","ipdsId":"IP-099173","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":467627,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2019.02.015","text":"Publisher Index Page"},{"id":364087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"134","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bachand, Sandra M. 0000-0001-5235-9726","orcid":"https://orcid.org/0000-0001-5235-9726","contributorId":207557,"corporation":false,"usgs":false,"family":"Bachand","given":"Sandra","email":"","middleInitial":"M.","affiliations":[{"id":12526,"text":"Bachand & Associates","active":true,"usgs":false}],"preferred":false,"id":763118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stern, Dylan 0000-0001-5676-8711","orcid":"https://orcid.org/0000-0001-5676-8711","contributorId":215742,"corporation":false,"usgs":false,"family":"Stern","given":"Dylan","email":"","affiliations":[{"id":39311,"text":"Delta Stewardship Program, Aquatic Science Program","active":true,"usgs":false}],"preferred":false,"id":763119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ling Liang, Yan 0000-0001-5999-3148","orcid":"https://orcid.org/0000-0001-5999-3148","contributorId":207555,"corporation":false,"usgs":false,"family":"Ling Liang","given":"Yan","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":763120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Horwath, William R. 0000-0003-3707-0697","orcid":"https://orcid.org/0000-0003-3707-0697","contributorId":207560,"corporation":false,"usgs":false,"family":"Horwath","given":"William","email":"","middleInitial":"R.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":763121,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bachand, Philip A. M. 0000-0002-6757-2404","orcid":"https://orcid.org/0000-0002-6757-2404","contributorId":207558,"corporation":false,"usgs":false,"family":"Bachand","given":"Philip","email":"","middleInitial":"A. M.","affiliations":[{"id":12526,"text":"Bachand & Associates","active":true,"usgs":false}],"preferred":false,"id":763122,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70210516,"text":"70210516 - 2019 - Distribution of mineral phases in the Eocene Green River Formation, Piceance Basin, Colorado – Implications for the evolution of Lake Uinta","interactions":[],"lastModifiedDate":"2020-06-08T19:43:39.040549","indexId":"70210516","displayToPublicDate":"2019-05-08T14:38:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2789,"text":"Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Distribution of mineral phases in the Eocene Green River Formation, Piceance Basin, Colorado – Implications for the evolution of Lake Uinta","docAbstract":"The mineralogy of the Eocene Green River Formation in the Piceance Basin, Colorado, has been the subject of numerous studies since the 1920s. Most previous work has focused on the resource potential of these lacustrine mudrocks, which in addition to substantial oil shale potential (in-place resources of 353 billion barrels of synthetic crude oil for rocks yielding at least 25 gallons per ton, GPT), includes nahcolite, a currently utilized soda ash resource, and dawsonite, a potential alternative source of aluminum. Another reason to study the mineralogy in this system is that the geographic and stratigraphic distribution of various authigenic minerals may provide insights into the geochemistry and depositional environment of the long-lived Eocene Lake Uinta. In this study, legacy non-quantitative (presence/absence) X-ray diffraction (XRD) data recently published by the U.S. Geological Survey (USGS) for more than nine-thousand samples collected from thirty coreholes in the Green River Formation, Piceance Basin were examined. These data were used to better define the stratigraphic and paleogeographic extent of a set of indicator minerals (illite, analcime, albite, dawsonite, and nahcolite) within the Piceance Basin lacustrine strata. This set of minerals was selected based on observations from previous work and variability in their occurrence and co-occurrence within the Piceance Basin. The USGS database has been used to (1) construct maps showing geographic variations in mineral occurrences for 14 stratigraphically defined rich and lean oil shale zones; (2) assess co-occurrences of indicator minerals; and (3) compare occurrence results with quantitative XRD datasets collected on Piceance Basin oil shales. Occurrences of many authigenic minerals (analcime, dawsonite, and nahcolite) varied in the lacustrine strata near and around the depocenter, but others, like quartz, dolomite, and feldspar (potassium + undifferentiated), were widely and consistently present (>90% of samples) across the basin. Shifts in the distribution of indicator mineral occurrences generally coincide with changes identified in previous lake history descriptions and indicate that the water chemistry of Lake Uinta varied significantly going from near-shore to the depocenter and through time.","language":"English","publisher":"Rocky Mountain Association of Geologists","doi":"10.31582/rmag.mg.56.2.73","usgsCitation":"Birdwell, J.E., Johnson, R.C., and Brownfield, M.E., 2019, Distribution of mineral phases in the Eocene Green River Formation, Piceance Basin, Colorado – Implications for the evolution of Lake Uinta: Mountain Geologist, v. 56, no. 2, p. 73-141, https://doi.org/10.31582/rmag.mg.56.2.73.","productDescription":"69 p.","startPage":"73","endPage":"141","ipdsId":"IP-102092","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":375424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Piceance Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.072265625,\n 38.54816542304656\n ],\n [\n -106.435546875,\n 38.54816542304656\n ],\n [\n -106.435546875,\n 40.96330795307353\n ],\n [\n -109.072265625,\n 40.96330795307353\n ],\n [\n -109.072265625,\n 38.54816542304656\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-05-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":790489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":790490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":790491,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202744,"text":"ofr20191029 - 2019 - Spatial integration of biological and social objectives to identify priority landscapes for waterfowl habitat conservation","interactions":[],"lastModifiedDate":"2024-03-04T18:47:33.875141","indexId":"ofr20191029","displayToPublicDate":"2019-05-08T12:45:00","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":"2019-1029","displayTitle":"Spatial Integration of Biological and Social Objectives to Identify Priority Landscapes for Waterfowl Habitat Conservation","title":"Spatial integration of biological and social objectives to identify priority landscapes for waterfowl habitat conservation","docAbstract":"Waterfowl population management and habitat conservation compose one of the oldest and most successful adaptive management frameworks in the world. Since its inception, the North American Waterfowl Management Plan (NAWMP) has emphasized strategically targeted conservation investments in regions that most affect waterfowl population dynamics. By 2012, regional conservation had progressively become more science-based and strategic: many migratory bird partnerships had initiated or completed projects on mapping and modeling waterfowl distribution and abundances using geospatial techniques. However, when developing a map depicting and titled “Areas of Greatest Continental Significance to North American Ducks, Geese, and Swans” for the 2012 NAWMP Revision, waterfowl professionals articulated the need for improved decision frameworks and use of consistent datasets for refining large-scale spatial products depicting priority areas for waterfowl and people. This report describes a framework for developing a spatial value model to support the identification of North American geographies of importance to waterfowl during the breeding and non-breeding periods and to resource users who could potentially support (financially and (or) politically) waterfowl habitat conservation. Objectives used to identify priority geographies were determined through a collaborative process of the NAWMP Science Support Team, Priority Landscapes Committee (PLC), and other experts in the fields of waterfowl biology and ecology, environmental science, and human dimensions. ArcGIS Desktop was used as the platform for managing, analyzing, combining and displaying the spatial data as well as producing new data through spatial analysis functions. Thirty-eight spatial layers were developed, and several composite spatially explicit products (maps of North America) were produced based on PLC recommendations. The composite products have extensive similarities to the 2012 NAWMP map depicting areas of greatest continental significance to North American waterfowl. There are also some differences, especially in regions of the high Arctic and in Mexico. These differences between spatial value model maps and the 2012 NAWMP output likely arose from inclusion of social objectives, reduced dependence on expert opinion to generate abundance estimates, lack of population surveys in some regions and availability of expanded survey data in other regions, and use of model-based waterfowl population estimates for some unsurveyed areas.
The structured decision-making framework application in this study is discussed, and the appropriate use of the products and their limitations are outlined. Additionally, options for future improvements are presented by identifying gaps in data collection, waterfowl-habitat association assumptions, and uncertainties related to social objectives. These spatial products are intended for use by national, regional, and province/state level wildlife professionals to aid their decisions in targeting waterfowl habitat conservation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191029","usgsCitation":"Krainyk, A., Lyons, J.E., Brasher, M.G., Humburg, D.D., Soulliere, G.J., Coluccy, J.M., Petrie, M.J., Howerter, D.W., Slattery, S.M., Rice, M.B., and Fuller, J.C., 2019, Spatial integration of biological and social objectives to identify priority landscapes for waterfowl habitat conservation: U.S. Geological Survey Open-File Report 2019–1029, 41 p., https://doi.org/10.3133/ofr20191029.","productDescription":"Document: vii, 41 p.; Additional Report Piece; Data Release","numberOfPages":"53","ipdsId":"IP-100747","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":363506,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L7J5U4","text":"USGS data release","description":"USGS data release","linkHelpText":"Spatial Integration of Biological and Social Objectives to Identify Priority Landscapes for Waterfowl Habitat Conservation"},{"id":363574,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2019/1029/ofr20191029_supplementalinformation.pdf","text":"Supplemental Information","size":"5.41 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":363503,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1029/coverthb2.jpg"},{"id":363504,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1029/ofr20191029.pdf","text":"Report","size":"30.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1029"}],"contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road, Ste 4039
Laurel, MD 20708
Despite their seeming permanence, volcanoes are prone to catastrophic collapse that can affect vast areas in a matter of minutes. Large collapses begin as gigantic landslides that quickly transform to debris avalanches—chaotically tumbling masses of rock debris that can sweep downslope at extremely high velocities, inundating areas far beyond the volcano. Rapid burial by the debris avalanches themselves, associated eruptions and lahars (volcanic mudflows), and inundation by tsunamis triggered when avalanches impact bodies of water can all cause widespread devastation to people and property.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193023","usgsCitation":"Siebert, L., Reid, M.E., Vallance, J.W., and Pierson, T.C., 2019, When volcanoes fall down—Catastrophic collapse and debris avalanches (ver. 1.2, August 2019): U.S. Geological Survey Fact Sheet 2019-3023, 6 p., https://doi.org/10.3133/fs20193023.\n","productDescription":" 6 p.","numberOfPages":"6","ipdsId":"IP-095974","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":363557,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3023/fs20193023_v1.2.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2019-3023"},{"id":364482,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2019/3023/fs20193023_v1.2_versionhist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"Fact Sheet 2019-3023 Version History"},{"id":363556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3023/coverthb.jpg"}],"edition":"Version 1.2: August 2019; Version 1.1: June 2019","contact":"