Widespread deployment of carbon capture and storage (CCS) is likely necessary to be able to satisfy baseload electricity demand, to maintain diversity in the energy mix, and to achieve climate and other objectives at the lowest cost. If all of the carbon dioxide (CO2) emissions from stationary sources (such as fossil-fuel burning power plants, and other industrial plants) in the United States needed to be captured and stored, it could be possible to store only a small fraction of this CO2 in oil and natural gas reservoirs, including as a result of CO2 utilization for enhanced oil recovery. The vast majority would have to be stored in saline-filled reservoirs (Dahowski et al., 2005). Given a lack of long-term commercial-scale CCS projects, there is considerable uncertainty in the risks, dynamic capacity, and their cost implications for geologic storage of CO2. Pressure buildup in the storage reservoir is expected to be a primary source of risk associated with CO2 storage, and could severely limit CO2 injection rates (dynamic storage capacities). Most cost estimates for commercial-scale deployment of CCS estimate CO2 storage costs under assumed availability of a theoretical capacity to store tens, hundreds, or even thousands of gigatons of CO2, without considering geologic heterogeneities, pressure limitations, or the time dimension. This could lead to underestimation of the costs of CO2 storage (Anderson, 2017). This paper considers the impacts of pressure limitations and geologic heterogeneity on the dynamic CO2 storage capacity and storage (injection) costs. In the U.S. Geological Survey (USGS)’s National Assessment of Geologic CO2 Storage Resources (USGS, 2013), the mean estimate of the theoretical storage capacity in the Mount Simon Sandstone was about 94 billion metric tons of CO2. However, our results suggest that the pressure-limited capacity after 50 years of injection could be only about 4% of the theoretical geologic storage capacity in this formation. Because this is far less than emissions of CO2 from stationary sources in the region around the Mount Simon Sandstone, the costs to accommodate the potential annual demand for CO2 storage in this formation could be significantly greater than current estimates. Our results could have implications for how long and to what extent decision makers can expect to be able to deploy CCS before transitioning to other low- or zero-carbon energy technologies.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"35th USAEE/IAEE North American Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"USAEE","usgsCitation":"Anderson, S.T., and Jahediesfanjani, H., 2017, Case study - Dynamic pressure-limited capacity and costs of CO2 storage in the Mount Simon sandstone, in 35th USAEE/IAEE North American Conference, 2 p.","productDescription":"2 p.","ipdsId":"IP-088967","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":349751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349543,"type":{"id":15,"text":"Index Page"},"url":"https://www.usaee.org/USAEE2017/program_concurrent.aspx#3"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf8e4b06e28e9c22a3e","contributors":{"authors":[{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jahediesfanjani, Hossein 0000-0001-6281-5166","orcid":"https://orcid.org/0000-0001-6281-5166","contributorId":201000,"corporation":false,"usgs":false,"family":"Jahediesfanjani","given":"Hossein","affiliations":[],"preferred":false,"id":724051,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194437,"text":"ofr20171155 - 2017 - Cobalt—Styles of deposits and the search for primary deposits","interactions":[],"lastModifiedDate":"2018-11-19T11:35:29","indexId":"ofr20171155","displayToPublicDate":"2017-11-30T17:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1155","title":"Cobalt—Styles of deposits and the search for primary deposits","docAbstract":"Cobalt (Co) is a potentially critical mineral. The vast majority of cobalt is a byproduct of copper and (or) nickel production. Cobalt is increasingly used in magnets and rechargeable batteries. More than 50 percent of primary cobalt production is from the Central African Copperbelt. The Central African Copperbelt is the only sedimentary rock-hosted stratiform copper district that contains significant cobalt. Its presence may indicate significant mafic-ultramafic rocks in the local basement. The balance of primary cobalt production is from magmatic nickel-copper and nickel laterite deposits. Cobalt is present in several carbonate-hosted lead-zinc and copper districts. It is also variably present in Besshi-type volcanogenic massive sulfide and siliciclastic sedimentary rock-hosted deposits in back arc and rift environments associated with mafic-ultramafic rocks. Metasedimentary cobalt-copper-gold deposits (such as Blackbird, Idaho), iron oxide-copper-gold deposits, and the five-element vein deposits (such as Cobalt, Ontario) contain different amounts of cobalt. None of these deposit types show direct links to mafic-ultramafic rocks; the deposits may result from crustal-scale hydrothermal systems capable of leaching and transporting cobalt from great depths. Hydrothermal deposits associated with ultramafic rocks, typified by the Bou Azzer district of Morocco, represent another type of primary cobalt deposit.
In the United States, exploration for cobalt deposits may focus on magmatic nickel-copper deposits in the Archean and Proterozoic rocks of the Midwest and the east coast (Pennsylvania) and younger mafic rocks in southeastern and southern Alaska; also, possibly basement rocks in southeastern Missouri. Other potential exploration targets include—
Office of the Associate Director for Energy and Minerals
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 102
Reston, VA 20192
Bear Lake in North Muskegon, Michigan, is listed as part of the Muskegon Lake area of concern as designated by the U.S. Environmental Protection Agency. This area of concern was designated as a result of eutrophication and beneficial use impairments. On the northeast end of Bear Lake, two man-made retention ponds (Willbrandt Pond East and Willbrandt Pond West), formerly used for celery farming, may contribute nutrients to Bear Lake. Willbrandt Ponds (East and West) were previously muck fields that were actively used for celery farming from the early 1900s until 2002. The restoration and reconnection of the Willbrandt Ponds into Bear Lake prompted concerns of groundwater nutrient loading into Bear Lake. Studies done by the State of Michigan and Grand Valley State University revised initial internal phosphorus load estimates and indicated an imbalance in the phosphorus budget in Bear Lake. From June through November 2015, the U.S. Geological Survey (USGS) did an investigative study to quantify the load of nutrients from shallow groundwater around the Willbrandt Ponds in an effort to update the phosphorus budget to Bear Lake. Seven sampling locations were established, including five shallow groundwater wells and two surface-water sites, in the Willbrandt pond study area and Bear Lake. A total of 12 nutrient samples and discrete water-level measurements were collected from each site from June through November 2015. Continuous water-level data were recorded for both surface-water monitoring locations for the entire sampling period.
Water-level data indicated that Willbrandt Pond West had the highest average water-level elevation of all sites monitored, which indicated the general direction of flux is from Willbrandt Pond West to Bear Lake. Nutrient and chloride loading from Willbrandt Pond West to Bear Lake was calculated using two distinct methods: Dupuit and direct seepage methods. Shallow groundwater loading calculations were determined by using groundwater levels to first determine a flux of shallow groundwater, then nutrient concentrations to determine a load. It was determined that Willbrandt Pond East and Willbrandt Pond West contributed between 2 to 4 percent of the total annual phosphorus load to Bear Lake by way of shallow groundwater flow. Annual loads calculated for other constituents include orthophosphate (40–100 pounds per year [lb P/yr]), total nitrogen (200–830 lb/yr), chloride (12,700–32,100 lb/yr), and ammonia (130–670 lb N/yr). Study results indicated that mean groundwater and surface-water nutrient concentrations calculated in this study were higher than reported Michigan statewide values. The data collected in this study allow understanding of groundwater nutrient loading into Bear Lake in an effort to help inform future restoration and management decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175092","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Totten, A.R., Maurer, J.A., and Duris, J.W., 2017, Groundwater flux and nutrient loading in the northeast section of Bear Lake, Muskegon County, Michigan, 2015: U.S. Geological Survey Scientific Investigations Report 2017–5092, 16 p., https://doi.org/10.3133/sir20175092.","productDescription":"v, 16 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074168","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":349260,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73J3BVJ","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater Seepage Measurements in Northeast Section of Bear Lake, Muskegon County, Michigan, October 2015"},{"id":349259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5092/sir20175092.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5092"},{"id":349258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5092/coverthb.jpg"}],"country":"United States","state":"Michigan","county":"Muskegon County","otherGeospatial":"Bear Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.27194404602051,\n 43.25970598443754\n ],\n [\n -86.25323295593262,\n 43.25970598443754\n ],\n [\n -86.25323295593262,\n 43.27145609469072\n ],\n [\n -86.27194404602051,\n 43.27145609469072\n ],\n [\n -86.27194404602051,\n 43.25970598443754\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
6520 Mercantile Way
Suite 5
Lansing, MI 48911
Black shales of the Late Devonian to Early Mississippian Bakken Formation are characterized by high concentrations of organic carbon and the hyper-enrichment (> 500 to 1000s of mg/kg) of V and Zn. Deposition of black shales resulted from shallow seafloor depths that promoted rapid development of euxinic conditions. Vanadium hyper-enrichments, which are unknown in modern environments, are likely the result of very high levels of dissolved H2S (~ 10 mM) in bottom waters or sediments. Because modern hyper-enrichments of Zn are documented only in Framvaren Fjord (Norway), it is likely that the biogeochemical trigger responsible for Zn hyper-enrichment in Framvaren Fjord was also present in the Bakken basin. With Framvaren Fjord as an analogue, we propose a causal link between the activity of phototrophic sulfide oxidizing bacteria, related to the development of photic-zone euxinia, and the hyper-enrichment of Zn in black shales of the Bakken Formation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2017.01.026","usgsCitation":"Scott, C., Slack, J.F., and Kelley, K.D., 2017, The hyper-enrichment of V and Zn in black shales of the Late Devonian-Early Mississippian Bakken Formation (USA): Chemical Geology, v. 452, p. 24-33, https://doi.org/10.1016/j.chemgeo.2017.01.026.","productDescription":"10 p.","startPage":"24","endPage":"33","ipdsId":"IP-078833","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":461343,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2017.01.026","text":"Publisher Index Page"},{"id":349501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Manitoba, Montana, North Dakota, Saskatchewan, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 43\n ],\n [\n -96,\n 43\n ],\n [\n -96,\n 50\n ],\n [\n -108,\n 50\n ],\n [\n -108,\n 43\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"452","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fafce4b06e28e9c22a87","contributors":{"authors":[{"text":"Scott, Clint 0000-0003-2778-2711 clintonscott@usgs.gov","orcid":"https://orcid.org/0000-0003-2778-2711","contributorId":5332,"corporation":false,"usgs":true,"family":"Scott","given":"Clint","email":"clintonscott@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":724013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, Karen Duttweiler 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":192758,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"Duttweiler","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724014,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194476,"text":"70194476 - 2017 - Bacterial sulfur disproportionation constrains timing of neoproterozoic oxygenation","interactions":[],"lastModifiedDate":"2017-11-29T10:25:30","indexId":"70194476","displayToPublicDate":"2017-11-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Bacterial sulfur disproportionation constrains timing of neoproterozoic oxygenation","docAbstract":"Various geochemical records suggest that atmospheric O2 increased in the Ediacaran (635–541 Ma), broadly coincident with the emergence and diversification of large animals and increasing marine ecosystem complexity. Furthermore, geochemical proxies indicate that seawater sulfate levels rose at this time too, which has been hypothesized to reflect increased sulfide oxidation in marine sediments caused by sediment mixing of the newly evolved macrofauna. However, the exact timing of oxygenation is not yet understood, and there are claims for significant oxygenation prior to the Ediacaran. Furthermore, recent evidence suggests that physical mixing of sediments did not become important until the late Silurian. Here we report a multiple sulfur isotope record from a ca. 835–630 Ma succession from Svalbard, further supported by data from Proterozoic strata in Canada, Australia, Russia, and the United States, in order to investigate the timing of oxygenation. We present isotopic evidence for onset of globally significant bacterial sulfur disproportionation and reoxidative sulfur cycling following the 635 Ma Marinoan glaciation. Widespread sulfide oxidation helps to explain the observed first-order increase in seawater sulfate concentration from the earliest Ediacaran to the Precambrian-Cambrian boundary by reducing the amount of sulfur buried as pyrite. Expansion of reoxidative sulfur cycling to a global scale also indicates increasing environmental O2 levels. Thus, our data suggest that increasing atmospheric O2 levels may have played a role in the emergence of the Ediacaran macrofauna and increasing marine ecosystem complexity.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G38602.1","usgsCitation":"Kunzmann, M., Bui, T.H., Crockford, P.W., Halverson, G.P., Scott, C., Lyons, T.W., and Wing, B.A., 2017, Bacterial sulfur disproportionation constrains timing of neoproterozoic oxygenation: Geology, v. 45, no. 3, p. 207-210, https://doi.org/10.1130/G38602.1.","productDescription":"4 p.","startPage":"207","endPage":"210","ipdsId":"IP-076614","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":349503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia, Canada, Russia, United States","volume":"45","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-01","publicationStatus":"PW","scienceBaseUri":"5a60fafce4b06e28e9c22a8a","contributors":{"authors":[{"text":"Kunzmann, Marcus","contributorId":200984,"corporation":false,"usgs":false,"family":"Kunzmann","given":"Marcus","email":"","affiliations":[],"preferred":false,"id":724006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bui, Thi Hao","contributorId":200985,"corporation":false,"usgs":false,"family":"Bui","given":"Thi","email":"","middleInitial":"Hao","affiliations":[],"preferred":false,"id":724007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crockford, Peter W.","contributorId":200986,"corporation":false,"usgs":false,"family":"Crockford","given":"Peter","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":724008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Halverson, Galen P.","contributorId":200987,"corporation":false,"usgs":false,"family":"Halverson","given":"Galen","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":724009,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scott, Clint 0000-0003-2778-2711 clintonscott@usgs.gov","orcid":"https://orcid.org/0000-0003-2778-2711","contributorId":5332,"corporation":false,"usgs":true,"family":"Scott","given":"Clint","email":"clintonscott@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lyons, Timothy W.","contributorId":196850,"corporation":false,"usgs":false,"family":"Lyons","given":"Timothy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":724010,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wing, Boswell A.","contributorId":200989,"corporation":false,"usgs":false,"family":"Wing","given":"Boswell","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724011,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70194483,"text":"70194483 - 2017 - Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States","interactions":[],"lastModifiedDate":"2022-04-22T16:02:15.153901","indexId":"70194483","displayToPublicDate":"2017-11-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States","docAbstract":"Evapotranspiration (ET) is a key component of the hydrologic cycle, accounting for ~70% of precipitation in the conterminous U.S. (CONUS), but it has been a challenge to predict accurately across different spatio-temporal scales. The increasing availability of remotely sensed data has led to significant advances in the frequency and spatial resolution of ET estimates, derived from energy balance principles with variables such as temperature used to estimate surface latent heat flux. Although remote sensing methods excel at depicting spatial and temporal variability, estimation of ET independently of other water budget components can lead to inconsistency with other budget terms. Methods that rely on ground-based data better constrain long-term ET, but are unable to provide the same temporal resolution. Here we combine long-term ET estimates from a water-balance approach with the SSEBop (operational Simplified Surface Energy Balance) remote sensing-based ET product for 2000–2015. We test the new combined method, the original SSEBop product, and another remote sensing ET product (MOD16) against monthly measurements from 119 flux towers. The new product showed advantages especially in non-irrigated areas where the new method showed a coefficient of determination R2 of 0.44, compared to 0.41 for SSEBop or 0.35 for MOD16. The resulting monthly data set will be a useful, unique contribution to ET estimation, due to its combination of remote sensing-based variability and ground-based long-term water balance constraints.
","language":"English","publisher":"MDPI","doi":"10.3390/rs9121181","usgsCitation":"Reitz, M., Senay, G., and Sanford, W.E., 2017, Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States: Remote Sensing, v. 9, no. 12, 1181, 17 p.; Data release, https://doi.org/10.3390/rs9121181.","productDescription":"1181, 17 p.; Data release","ipdsId":"IP-090961","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469292,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9121181","text":"Publisher Index Page"},{"id":349568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397955,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QC02FK","text":"USGS data 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\"}}]}","volume":"9","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-29","publicationStatus":"PW","scienceBaseUri":"5a60fafbe4b06e28e9c22a82","contributors":{"authors":[{"text":"Reitz, Meredith 0000-0001-9519-6103 mreitz@usgs.gov","orcid":"https://orcid.org/0000-0001-9519-6103","contributorId":196694,"corporation":false,"usgs":true,"family":"Reitz","given":"Meredith","email":"mreitz@usgs.gov","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":724058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":724059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":724060,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194335,"text":"70194335 - 2017 - A swath across the great divide: Kelp forests across the Samalga Pass biogeographic break","interactions":[],"lastModifiedDate":"2017-11-29T09:56:13","indexId":"70194335","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"A swath across the great divide: Kelp forests across the Samalga Pass biogeographic break","docAbstract":"Biogeographic breaks are often described as locations where a large number of species reach their geographic range limits. Samalga Pass, in the eastern Aleutian Archipelago, is a known biogeographic break for the spatial distribution of several species of offshore-pelagic communities, including numerous species of cold-water corals, zooplankton, fish, marine mammals, and seabirds. However, it remains unclear whether Samalga Pass also serves as a biogeographic break for nearshore benthic communities. The occurrence of biogeographic breaks across multiple habitats has not often been described. In this study, we examined if the biogeographic break for offshore-pelagic communities applies to nearshore kelp forests. To examine whether Samalga Pass serves as a biogeographic break for kelp forest communities, this study compared abundance, biomass and percent bottom cover of species associated with kelp forests on either side of the pass. We observed marked differences in kelp forest community structure, with some species reaching their geographic range limits on the opposing sides of the pass. In particular, the habitat-forming kelp Nereocystis luetkeana, and the predatory sea stars Pycnopodia helianthoides and Orthasterias koehleri all occurred on the eastern side of Samalga Pass but were not observed west of the pass. In contrast, the sea star Leptasterias camtschatica dispar was observed only on the western side of the pass. We also observed differences in overall abundance and biomass of numerous associated fish, invertebrate and macroalgal species on opposing sides of the pass. We conclude that Samalga Pass is important biogeographic break for kelp forest communities in the Aleutian Archipelago and may demark the geographic range limits of several ecologically important species.","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2017.06.007","usgsCitation":"Konar, B.H., Edwards, M.S., Bland, A., Metzger, J., Ravelo, A., Traiger, S., and Weitzman, B., 2017, A swath across the great divide: Kelp forests across the Samalga Pass biogeographic break: Continental Shelf Research, v. 143, p. 78-88, https://doi.org/10.1016/j.csr.2017.06.007.","productDescription":"11 p.","startPage":"78","endPage":"88","ipdsId":"IP-082946","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":469296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2017.06.007","text":"Publisher Index Page"},{"id":349445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Archipelago, Samalga Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -177.5390625,\n 49.26780455063753\n ],\n [\n -159.521484375,\n 49.26780455063753\n ],\n [\n -159.521484375,\n 56.48676175249086\n ],\n [\n -177.5390625,\n 56.48676175249086\n ],\n [\n -177.5390625,\n 49.26780455063753\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"143","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ae1","contributors":{"authors":[{"text":"Konar, Brenda H. 0000-0002-8998-1612","orcid":"https://orcid.org/0000-0002-8998-1612","contributorId":200787,"corporation":false,"usgs":false,"family":"Konar","given":"Brenda","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":723339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Matthew S.","contributorId":200788,"corporation":false,"usgs":false,"family":"Edwards","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":723340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bland, Aaron","contributorId":200789,"corporation":false,"usgs":false,"family":"Bland","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":723341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Metzger, Jacob","contributorId":200790,"corporation":false,"usgs":false,"family":"Metzger","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":723342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ravelo, Alexandra","contributorId":200791,"corporation":false,"usgs":false,"family":"Ravelo","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":723343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Traiger, Sarah","contributorId":200792,"corporation":false,"usgs":false,"family":"Traiger","given":"Sarah","affiliations":[],"preferred":false,"id":723344,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weitzman, Ben P. 0000-0001-7559-3654 bweitzman@usgs.gov","orcid":"https://orcid.org/0000-0001-7559-3654","contributorId":5123,"corporation":false,"usgs":true,"family":"Weitzman","given":"Ben P.","email":"bweitzman@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":723338,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70194343,"text":"70194343 - 2017 - Exploration of diffuse and discrete sources of acid mine drainage to a headwater mountain stream in Colorado, USA","interactions":[],"lastModifiedDate":"2017-11-28T11:00:53","indexId":"70194343","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2745,"text":"Mine Water and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Exploration of diffuse and discrete sources of acid mine drainage to a headwater mountain stream in Colorado, USA","docAbstract":"We investigated the impact of acid mine drainage (AMD) contamination from the Minnesota Mine, an inactive gold and silver mine, on Lion Creek, a headwater mountain stream near Empire, Colorado. The objective was to map the sources of AMD contamination, including discrete sources visible at the surface and diffuse inputs that were not readily apparent. This was achieved using geochemical sampling, in-stream and in-seep fluid electrical conductivity (EC) logging, and electrical resistivity imaging (ERI) of the subsurface. The low pH of the AMD-impacted water correlated to high fluid EC values that served as a target for the ERI. From ERI, we identified two likely sources of diffuse contamination entering the stream: (1) the subsurface extent of two seepage faces visible on the surface, and (2) rainfall runoff washing salts deposited on the streambank and in a tailings pile on the east bank of Lion Creek. Additionally, rainfall leaching through the tailings pile is a potential diffuse source of contamination if the subsurface beneath the tailings pile is hydraulically connected with the stream. In-stream fluid EC was lowest when stream discharge was highest in early summer and then increased throughout the summer as stream discharge decreased, indicating that the concentration of dissolved solids in the stream is largely controlled by mixing of groundwater and snowmelt. Total dissolved solids (TDS) load is greatest in early summer and displays a large diel signal. Identification of diffuse sources and variability in TDS load through time should allow for more targeted remediation options.","language":"English","publisher":"Springer Berlin Heidelberg","doi":"10.1007/s10230-017-0452-6","usgsCitation":"Johnston, A., Runkel, R.L., Navarre-Sitchler, A., and Singha, K., 2017, Exploration of diffuse and discrete sources of acid mine drainage to a headwater mountain stream in Colorado, USA: Mine Water and the Environment, v. 36, no. 4, p. 463-478, https://doi.org/10.1007/s10230-017-0452-6.","productDescription":"16 p.","startPage":"463","endPage":"478","ipdsId":"IP-077543","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":349427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Empire","otherGeospatial":"Lion Creek","volume":"36","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-29","publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ada","contributors":{"authors":[{"text":"Johnston, Allison","contributorId":200808,"corporation":false,"usgs":false,"family":"Johnston","given":"Allison","email":"","affiliations":[],"preferred":false,"id":723380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Navarre-Sitchler, Alexis","contributorId":190441,"corporation":false,"usgs":false,"family":"Navarre-Sitchler","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":723381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini","contributorId":76733,"corporation":false,"usgs":true,"family":"Singha","given":"Kamini","affiliations":[],"preferred":false,"id":723382,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194341,"text":"70194341 - 2017 - Regionalizing indicators for marine ecosystems: Bering Sea–Aleutian Island seabirds, climate, and competitors","interactions":[],"lastModifiedDate":"2017-11-28T11:11:23","indexId":"70194341","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Regionalizing indicators for marine ecosystems: Bering Sea–Aleutian Island seabirds, climate, and competitors","docAbstract":"Seabirds are thought to be reliable, real-time indicators of forage fish availability and the climatic and\r\nbiotic factors affecting pelagic food webs in marine ecosystems. In this study, we tested the hypothesis\r\nthat temporal trends and interannual variability in seabird indicators reflect simultaneously occurring\r\nbottom-up (climatic) and competitor (pink salmon) forcing of food webs. To test this hypothesis, we\r\nderived multivariate seabird indicators for the Bering Sea–Aleutian Island (BSAI) ecosystem and related\r\nthem to physical and biological conditions known to affect pelagic food webs in the ecosystem. We\r\nexamined covariance in the breeding biology of congeneric pelagic gulls (kittiwakes Rissa tridactyla and\r\nR. brevirostris) andauks (murres Uria aalge and U. lomvia), all of whichare abundant and well-studiedinthe\r\nBSAI. At the large ecosystem scale, kittiwake and murre breeding success and phenology (hatch dates)\r\ncovaried among congeners, so data could be combined using multivariate techniques, but patterns of\r\nresponsedifferedsubstantially betweenthe genera.Whiledata fromall sites (n = 5)inthe ecosystemcould\r\nbe combined, the south eastern Bering Sea shelf colonies (St. George, St. Paul, and Cape Peirce) provided\r\nthe strongest loadings on indicators, and hence had the strongest influence on modes of variability. The\r\nkittiwake breeding success mode of variability, dominated by biennial variation, was significantly related\r\nto both climatic factors and potential competitor interactions. The murre indicator mode was interannual\r\nand only weakly related to the climatic factors measured. The kittiwake phenology indicator mode of\r\nvariability showed multi-year periods (“stanzas”) of late or early breeding, while the murre phenology\r\nindicator showed a trend towards earlier timing. Ocean climate relationships with the kittiwake breeding\r\nsuccess indicator suggestthat early-season (winter–spring) environmental conditions and the abundance\r\nof pink salmon affect the pelagic food webs that support these seabirds in the BSAI ecosystem.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2017.03.013","usgsCitation":"Sydeman, W., Thompson, S.A., Piatt, J.F., García-Reyes, M., Zador, S., Williams, J.C., Romano, M., and Renner, H., 2017, Regionalizing indicators for marine ecosystems: Bering Sea–Aleutian Island seabirds, climate, and competitors: Ecological Indicators, v. 78, p. 458-469, https://doi.org/10.1016/j.ecolind.2017.03.013.","productDescription":"12 p.","startPage":"458","endPage":"469","ipdsId":"IP-063143","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":349429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Islands, Bering Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -188.7890625,\n 50.3454604086048\n ],\n [\n -156.88476562499997,\n 50.3454604086048\n ],\n [\n -156.88476562499997,\n 60.54377524118842\n ],\n [\n -188.7890625,\n 60.54377524118842\n ],\n [\n -188.7890625,\n 50.3454604086048\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ade","contributors":{"authors":[{"text":"Sydeman, William J.","contributorId":172574,"corporation":false,"usgs":false,"family":"Sydeman","given":"William J.","affiliations":[],"preferred":false,"id":723371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Sarah Ann","contributorId":198394,"corporation":false,"usgs":false,"family":"Thompson","given":"Sarah","email":"","middleInitial":"Ann","affiliations":[],"preferred":false,"id":723372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":723370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"García-Reyes, Marisol","contributorId":200914,"corporation":false,"usgs":false,"family":"García-Reyes","given":"Marisol","affiliations":[],"preferred":false,"id":723373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zador, Stephani","contributorId":60992,"corporation":false,"usgs":false,"family":"Zador","given":"Stephani","affiliations":[],"preferred":false,"id":723374,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Jeffrey C.","contributorId":126882,"corporation":false,"usgs":false,"family":"Williams","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":723375,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Romano, Marc","contributorId":200806,"corporation":false,"usgs":false,"family":"Romano","given":"Marc","affiliations":[],"preferred":false,"id":723376,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Renner, Heather","contributorId":200807,"corporation":false,"usgs":false,"family":"Renner","given":"Heather","affiliations":[],"preferred":false,"id":723377,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70194354,"text":"70194354 - 2017 - Solid-phase arsenic speciation in aquifer sediments: A micro-X-ray absorption spectroscopy approach for quantifying trace-level speciation","interactions":[],"lastModifiedDate":"2018-11-26T09:39:13","indexId":"70194354","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Solid-phase arsenic speciation in aquifer sediments: A micro-X-ray absorption spectroscopy approach for quantifying trace-level speciation","docAbstract":"e of this research is to identify the solid-phase sources and geochemical mechanisms of release of As in aquifers of the Des Moines Lobe glacial advance. The overarching concept is that conditions present at the aquifer-aquitard interfaces promote a suite of geochemical reactions leading to mineral alteration and release of As to groundwater. A microprobe X-ray absorption spectroscopy (lXAS) approach is developed and applied to rotosonic drill core samples to identify the solid-phase speciation of As in aquifer, aquitard, and aquifer-aquitard interface sediments. This approach addresses the low solid-phase As concentrations, as well as the fine-scale physical and chemical heterogeneity of the sediments. The spectroscopy data are analyzed using novel cosine-distance and correlation-distance hierarchical clustering for Fe 1s and As 1s lXAS datasets. The solid-phase Fe and As speciation is then interpreted using sediment and well-water chemical data to propose solid-phase As reservoirs and release mechanisms. The results confirm that in two of the three locations studied, the glacial sediment forming the aquitard is the source of As to the aquifer sediments. The results are consistent with three different As release mechanisms: (1) desorption from Fe (oxyhydr)oxides, (2) reductive dissolution of Fe (oxyhydr)oxides, and (3) oxidative dissolution of Fe sulfides. The findings confirm that glacial sediments at the interface between aquifer and aquitard are geochemically active zones for As. The diversity of As release mechanisms is consistent with the geographic heterogeneity observed in the distribution of elevated-As wells.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2017.05.018","usgsCitation":"Nicholas, S.L., Erickson, M., Woodruff, L.G., Knaeble, A.R., Marcus, M.A., Lynch, J.K., and Toner, B.M., 2017, Solid-phase arsenic speciation in aquifer sediments: A micro-X-ray absorption spectroscopy approach for quantifying trace-level speciation: Geochimica et Cosmochimica Acta, v. 211, p. 228-255, https://doi.org/10.1016/j.gca.2017.05.018.","productDescription":"28 p.","startPage":"228","endPage":"255","ipdsId":"IP-081306","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":469295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2017.05.018","text":"Publisher Index Page"},{"id":349424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.87695312499999,\n 41.57436130598913\n ],\n [\n -89.384765625,\n 41.57436130598913\n ],\n [\n -89.384765625,\n 50.51342652633956\n ],\n [\n -98.87695312499999,\n 50.51342652633956\n ],\n [\n -98.87695312499999,\n 41.57436130598913\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"211","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faffe4b06e28e9c22ad1","contributors":{"authors":[{"text":"Nicholas, Sarah L.","contributorId":200812,"corporation":false,"usgs":false,"family":"Nicholas","given":"Sarah","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":723435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knaeble, Alan R.","contributorId":200813,"corporation":false,"usgs":false,"family":"Knaeble","given":"Alan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":723437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marcus, Matthew A.","contributorId":200814,"corporation":false,"usgs":false,"family":"Marcus","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":723438,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynch, Joshua K.","contributorId":200815,"corporation":false,"usgs":false,"family":"Lynch","given":"Joshua","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":723439,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Toner, Brandy M.","contributorId":200816,"corporation":false,"usgs":false,"family":"Toner","given":"Brandy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723440,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70188289,"text":"ofr20171052 - 2017 - Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina","interactions":[],"lastModifiedDate":"2024-03-04T18:57:59.926401","indexId":"ofr20171052","displayToPublicDate":"2017-11-22T07:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1052","title":"Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina","docAbstract":"Mattamuskeet National Wildlife Refuge (MNWR) offers a mix of open water, marsh, forest, and cropland habitats on 20,307 hectares in coastal North Carolina. In 1934, Federal legislation (Executive Order 6924) established MNWR to benefit wintering waterfowl and other migratory bird species. On an annual basis, the refuge staff decide how to manage 14 impoundments to benefit not only waterfowl during the nonbreeding season, but also shorebirds during fall and spring migration. In making these decisions, the challenge is to select a portfolio, or collection, of management actions for the impoundments that optimizes use by the three groups of birds while respecting budget constraints. In this study, a decision support tool was developed for these annual management decisions.
Within the decision framework, there are three different management objectives: shorebird-use days during fall and spring migrations, and waterfowl-use days during the nonbreeding season. Sixteen potential management actions were identified for impoundments; each action represents a combination of hydroperiod and vegetation manipulation. Example hydroperiods include semi-permanent and seasonal drawdowns, and vegetation manipulations include mechanical-chemical treatment, burning, disking, and no action. Expert elicitation was used to build a Bayesian Belief Network (BBN) model that predicts shorebird- and waterfowl-use days for each potential management action. The BBN was parameterized for a representative impoundment, MI-9, and predictions were re-scaled for this impoundment to predict outcomes at other impoundments on the basis of size. Parameter estimates in the BBN model can be updated using observations from ongoing monitoring that is part of the Integrated Waterbird Management and Monitoring (IWMM) program.
The optimal portfolio of management actions depends on the importance, that is, weights, assigned to the three objectives, as well as the budget. Five scenarios with a variety of objective weights and budgets were developed. Given the large number of possible portfolios (1614), a heuristic genetic algorithm was used to identify a management action portfolio that maximized use-day objectives while respecting budget constraints. The genetic algorithm identified a portfolio of management actions for each of the five scenarios, enabling refuge staff to explore the sensitivity of their management decisions to objective weights and budget constraints.
The decision framework developed here provides a transparent, defensible, and testable foundation for decision making at MNWR. The BBN model explicitly structures and parameterizes a mental model previously used by an expert to assign management actions to the impoundments. With ongoing IWMM monitoring, predictions from the model can be tested, and model parameters updated, to reflect empirical observations. This framework is intended to be a living document that can be updated to reflect changes in the decision context (for example, new objectives or constraints, or new models to compete with the current BBN model). Rather than a mandate to refuge staff, this framework is intended to be a decision support tool; tool outputs can become part of the deliberations of refuge staff when making difficult management decisions for multiple objectives.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171052","usgsCitation":"Tavernia, B.G., Stanton, J.D., and Lyons, J.E., 2017, Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina: U.S. Geological Survey Open-File Report 2017–1052, 43 p., https://doi.org/10.3133/ofr20171052.","productDescription":"vii, 43 p.","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074603","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":348384,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1052/coverthb.jpg"},{"id":348385,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1052/ofr20171052.pdf","text":"Report","size":"9.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1052"}],"country":"United States","state":"North Carolina","otherGeospatial":"Mattamuskeet National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.36459350585938,\n 35.42262976362149\n ],\n [\n -76.03363037109374,\n 35.42262976362149\n ],\n [\n -76.03363037109374,\n 35.59031875398378\n ],\n [\n -76.36459350585938,\n 35.59031875398378\n ],\n [\n -76.36459350585938,\n 35.42262976362149\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road, Ste 4039
Laurel, MD 20708
Subspecies relationships within the peregrine falcon (Falco peregrinus) have been long debated because of the polytypic nature of melanin-based plumage characteristics used in subspecies designations and potential differentiation of local subpopulations due to philopatry. In North America, understanding the evolutionary relationships among subspecies may have been further complicated by the introduction of captive bred peregrines originating from non-native stock, as part of recovery efforts associated with mid 20th century population declines resulting from organochloride pollution. Alaska hosts all three nominal subspecies of North American peregrine falcons–F. p. tundrius, anatum, and pealei–for which distributions in Alaska are broadly associated with nesting locales within Arctic, boreal, and south coastal maritime habitats, respectively. Unlike elsewhere, populations of peregrine falcon in Alaska were not augmented by captive-bred birds during the late 20th century recovery efforts. Population genetic differentiation analyses of peregrine populations in Alaska, based on sequence data from the mitochondrial DNA control region and fragment data from microsatellite loci, failed to uncover genetic distinction between populations of peregrines occupying Arctic and boreal Alaskan locales. However, the maritime subspecies, pealei, was genetically differentiated from Arctic and boreal populations, and substructured into eastern and western populations. Levels of interpopulational gene flow between anatum and tundrius were generally higher than between pealei and either anatum or tundrius. Estimates based on both marker types revealed gene flow between augmented Canadian populations and unaugmented Alaskan populations. While we make no attempt at formal taxonomic revision, our data suggest that peregrine falcons occupying habitats in Alaska and the North Pacific coast of North America belong to two distinct regional groupings–a coastal grouping (pealei) and a boreal/Arctic grouping (currently anatum and tundrius)–each comprised of discrete populations that are variously intra-regionally connected.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0188185","usgsCitation":"Talbot, S.L., Sage, G.K., Sonsthagen, S.A., Gravley, M.C., Swem, T., Williams, J.C., Longmire, J.L., Ambrose, S., Flamme, M.J., Lewis, S.B., Phillips, L.M., Anderson, C., and White, C., 2017, Intraspecific evolutionary relationships among peregrine falcons in western North American high latitudes: PLoS ONE, v. 12, no. 11, p. 1-25, https://doi.org/10.1371/journal.pone.0188185.","productDescription":"e0188185; 25 p.","startPage":"1","endPage":"25","ipdsId":"IP-070365","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469305,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0188185","text":"Publisher Index Page"},{"id":438145,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F18WV0","text":"USGS data release","linkHelpText":"Peregrine Falcon (Falco peregrinus) mtDNA and Microsatellite Genetic Data, Alaska, Canada and Russia, 1880-2012"},{"id":349123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, 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 -180.17578125,\n 50.17689812200107\n ],\n [\n -99.84374999999999,\n 50.17689812200107\n ],\n [\n -99.84374999999999,\n 72.0739114882038\n ],\n [\n -180.17578125,\n 72.0739114882038\n ],\n [\n -180.17578125,\n 50.17689812200107\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-17","publicationStatus":"PW","scienceBaseUri":"5a60fb0de4b06e28e9c22b69","contributors":{"authors":[{"text":"Talbot, Sandra L. 0000-0002-3312-7214 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ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":722724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gravley, Megan C. 0000-0002-4947-0236 mgravley@usgs.gov","orcid":"https://orcid.org/0000-0002-4947-0236","contributorId":202812,"corporation":false,"usgs":true,"family":"Gravley","given":"Megan","email":"mgravley@usgs.gov","middleInitial":"C.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":722734,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swem, Ted","contributorId":200583,"corporation":false,"usgs":false,"family":"Swem","given":"Ted","affiliations":[],"preferred":false,"id":722725,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Jeffrey C.","contributorId":126882,"corporation":false,"usgs":false,"family":"Williams","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":722726,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Longmire, Jonathan L.","contributorId":35845,"corporation":false,"usgs":false,"family":"Longmire","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":722727,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ambrose, Skip","contributorId":200584,"corporation":false,"usgs":false,"family":"Ambrose","given":"Skip","email":"","affiliations":[],"preferred":false,"id":722728,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Flamme, Melanie J.","contributorId":200585,"corporation":false,"usgs":false,"family":"Flamme","given":"Melanie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":722729,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lewis, Stephen B.","contributorId":200586,"corporation":false,"usgs":false,"family":"Lewis","given":"Stephen","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":722730,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Phillips, Laura M.","contributorId":49497,"corporation":false,"usgs":false,"family":"Phillips","given":"Laura","email":"","middleInitial":"M.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":722731,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Anderson, Clifford","contributorId":200587,"corporation":false,"usgs":false,"family":"Anderson","given":"Clifford","email":"","affiliations":[],"preferred":false,"id":722732,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"White, Clayton M","contributorId":200588,"corporation":false,"usgs":false,"family":"White","given":"Clayton M","affiliations":[],"preferred":false,"id":722733,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70194144,"text":"70194144 - 2017 - Persistent shoreline shape induced from offshore geologic framework: Effects of shoreface connected ridges","interactions":[],"lastModifiedDate":"2017-12-19T16:33:38","indexId":"70194144","displayToPublicDate":"2017-11-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Persistent shoreline shape induced from offshore geologic framework: Effects of shoreface connected ridges","docAbstract":"Mechanisms relating offshore geologic framework to shoreline evolution are determined through geologic investigations, oceanographic deployments, and numerical modeling. Analysis of shoreline positions from the past 50 years along Fire Island, New York, a 50 km long barrier island, demonstrates a persistent undulating shape along the western half of the island. The shelf offshore of these persistent undulations is characterized with shoreface-connected sand ridges (SFCR) of a similar alongshore length scale, leading to a hypothesis that the ridges control the shoreline shape through the modification of flow. To evaluate this, a hydrodynamic model was configured to start with the US East Coast and scale down to resolve the Fire Island nearshore. The model was validated using observations along western Fire Island and buoy data, and used to compute waves, currents and sediment fluxes. To isolate the influence of the SFCR on the generation of the persistent shoreline shape, simulations were performed with a linearized nearshore bathymetry to remove alongshore transport gradients associated with shoreline shape. The model accurately predicts the scale and variation of the alongshore transport that would generate the persistent shoreline undulations. In one location, however, the ridge crest connects to the nearshore and leads to an offshore-directed transport that produces a difference in the shoreline shape. This qualitatively supports the hypothesized effect of cross-shore fluxes on coastal evolution. Alongshore flows in the nearshore during a representative storm are driven by wave breaking, vortex force, advection and pressure gradient, all of which are affected by the SFCR.
","language":"English","publisher":"AGU","doi":"10.1002/2017JC012808","usgsCitation":"Safak, I., List, J.H., Warner, J., and Schwab, W.C., 2017, Persistent shoreline shape induced from offshore geologic framework: Effects of shoreface connected ridges: Journal of Geophysical Research C: Oceans, v. 122, no. 11, p. 8721-8738, https://doi.org/10.1002/2017JC012808.","productDescription":"18 p.","startPage":"8721","endPage":"8738","ipdsId":"IP-082366","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469311,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hdl.handle.net/1912/9472","text":"Publisher Index Page"},{"id":349010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.33099365234375,\n 40.588928169693745\n ],\n [\n -72.35321044921875,\n 40.588928169693745\n ],\n [\n -72.35321044921875,\n 40.865756786006806\n ],\n [\n -73.33099365234375,\n 40.865756786006806\n ],\n [\n -73.33099365234375,\n 40.588928169693745\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"11","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-15","publicationStatus":"PW","scienceBaseUri":"5a60fb0fe4b06e28e9c22b8e","contributors":{"authors":[{"text":"Safak, Ilgar 0000-0001-7675-0770 isafak@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-0770","contributorId":5522,"corporation":false,"usgs":true,"family":"Safak","given":"Ilgar","email":"isafak@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"List, Jeffrey H. 0000-0001-8594-2491 jlist@usgs.gov","orcid":"https://orcid.org/0000-0001-8594-2491","contributorId":174581,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":722351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722352,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191327,"text":"sir20175105 - 2017 - Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015","interactions":[],"lastModifiedDate":"2018-11-19T10:10:32","indexId":"sir20175105","displayToPublicDate":"2017-11-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5105","title":"Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015","docAbstract":"Sediment management is a challenge faced by reservoir managers who have several potential options, including dredging, for mitigation of storage capacity lost to sedimentation. As sediment is removed from reservoir storage, potential use of the sediment for socioeconomic or ecological benefit could potentially defray some costs of its removal. Rivers that transport a sandy sediment load will deposit the sand load along a reservoir-headwaters reach where the current of the river slackens progressively as its bed approaches and then descends below the reservoir water level. Given a rare combination of factors, a reservoir deposit of alluvial sand has potential to be suitable for use as proppant for hydraulic fracturing in unconventional oil and gas development. In 2015, the U.S. Geological Survey began a program of researching potential sources of proppant sand from reservoirs, with an initial focus on the Missouri River subbasins that receive sand loads from the Nebraska Sand Hills. This report documents the methods and results of assessments of the suitability of river delta sediment as proppant for a pilot study area in the delta headwaters of Lewis and Clark Lake, Nebraska and South Dakota. Results from surface-geophysical surveys of electrical resistivity guided borings to collect 3.7-meter long cores at 25 sites on delta sandbars using the direct-push method to recover duplicate, 3.8-centimeter-diameter cores in April 2015. In addition, the U.S. Geological Survey collected samples of upstream sand sources in the lower Niobrara River valley.
At the laboratory, samples were dried, weighed, washed, dried, and weighed again. Exploratory analysis of natural sand for determining its suitability as a proppant involved application of a modified subset of the standard protocols known as American Petroleum Institute (API) Recommended Practice (RP) 19C. The RP19C methods were not intended for exploration-stage evaluation of raw materials. Results for the washed samples are not directly applicable to evaluations of suitability for use as fracture sand because, except for particle-size distribution, the API-recommended practices for assessing proppant properties (sphericity, roundness, bulk density, and crush resistance) require testing of specific proppant size classes. An optical imaging particle-size analyzer was used to make measurements of particle-size distribution and particle shape. Measured samples were sieved to separate the dominant-size fraction, and the separated subsample was further tested for roundness, sphericity, bulk density, and crush resistance.
For the bulk washed samples collected from the Missouri River delta, the geometric mean size averaged 0.27 millimeters (mm), 80 percent of the samples were predominantly sand in the API 40/70 size class, and 17 percent were predominantly sand in the API 70/140 size class. Distributions of geometric mean size among the four sandbar complexes were similar, but samples collected from sandbar complex B were slightly coarser sand than those from the other three complexes. The average geometric mean sizes among the four sandbar complexes ranged only from 0.26 to 0.30 mm. For 22 main-stem sampling locations along the lower Niobrara River, geometric mean size averaged 0.26 mm, an average of 61 percent was sand in the API 40/70 size class, and 28 percent was sand in the API 70/140 size class. Average composition for lower Niobrara River samples was 48 percent medium sand, 37 percent fine sand, and about 7 percent each very fine sand and coarse sand fractions. On average, samples were moderately well sorted.
Particle shape and strength were assessed for the dominant-size class of each sample. For proppant strength, crush resistance was tested at a predetermined level of stress (34.5 megapascals [MPa], or 5,000 pounds-force per square inch). To meet the API minimum requirement for proppant, after the crush test not more than 10 percent of the tested sample should be finer than the precrush dominant-size class. For particle shape, all samples surpassed the recommended minimum criteria for sphericity and roundness, with most samples being well-rounded.
For proppant strength, of 57 crush-resistance tested Missouri River delta samples of 40/70-sized sand, 23 (40 percent) were interpreted as meeting the minimum criterion at 34.5 MPa, or 5,000 pounds-force per square inch. Of 12 tested samples of 70/140-sized sand, 9 (75 percent) of the Missouri River delta samples had less than 10 percent fines by volume following crush testing, achieving the minimum criterion at 34.5 MPa. Crush resistance for delta samples was strongest at sandbar complex A, where 67 percent of tested samples met the 10-percent fines criterion at the 34.5-MPa threshold. This frequency was higher than was indicated by samples from sandbar complexes B, C, and D that had rates of 50, 46, and 42 percent, respectively. The group of sandbar complex A samples also contained the largest percentages of samples dominated by the API 70/140 size class, which overall had a higher percentage of samples meeting the minimum criterion compared to samples dominated by coarser size classes; however, samples from sandbar complex A that had the API 40/70 size class tested also had a higher rate for meeting the minimum criterion (57 percent) than did samples from sandbar complexes B, C, and D (50, 43, and 40 percent, respectively).
For samples collected along the lower Niobrara River, of the 25 tested samples of 40/70-sized sand, 9 samples passed the API minimum criterion at 34.5 MPa, but only 3 samples passed the more-stringent criterion of 8 percent postcrush fines. All four tested samples of 70/140 sand passed the minimum criterion at 34.5 MPa, with postcrush fines percentage of at most 4.1 percent.
For two reaches of the lower Niobrara River, where hydraulic sorting was energized artificially by the hydraulic head drop at and immediately downstream from Spencer Dam, suitability of channel deposits for potential use as fracture sand was confirmed by test results. All reach A washed samples were well-rounded and had sphericity scores above 0.65, and samples for 80 percent of sampled locations met the crush-resistance criterion at the 34.5-MPa stress level. A conservative lower-bound estimate of sand volume in the reach A deposits was about 86,000 cubic meters. All reach B samples were well-rounded but sphericity averaged 0.63, a little less than the average for upstream reaches A and SP. All four samples tested passed the crush-resistance test at 34.5 MPa. Of three reach B sandbars, two had no more than 3 percent fines after the crush test, surpassing more stringent criteria for crush resistance that accept a maximum of 6 percent fines following the crush test for the API 70/140 size class.
Relative to the crush-resistance test results for the API 40/70 size fraction of two samples of mine output from Loup River settling-basin dredge spoils near Genoa, Nebr., four of five reach A sample locations compared favorably. The four samples had increases in fines composition of 1.6–5.9 percentage points, whereas fines in the two mine-output samples increased by an average 6.8 percentage points.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175105","collaboration":"Prepared in cooperation with Midwest Region Initiative on Natural Sources of Fracture Sand","usgsCitation":"Zelt, R.B., Hobza, C.M., Burton, B.L., Schaepe, N.J., and Piatak, Nadine, 2017, Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015: U.S. Geological Survey Scientific Investigations Report 2017–5105, 51 p., https://doi.org/10.3133/sir20175105.","productDescription":"Report: viii, 51 p.; Tables: 4; Data Release","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077776","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":348988,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5105"},{"id":348987,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5105/coverthb2.jpg"},{"id":348989,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table4.xlsx","text":"Table 4","size":"38.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 4"},{"id":348990,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table5.xlsx","text":"Table 5","size":"26.6 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 5"},{"id":348991,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table6.xlsx","text":"Table 6","size":"70.8 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 6"},{"id":348992,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table9.xlsx","text":"Table 9","size":"75.0","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 9"},{"id":348993,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79W0CQB","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Streambed sediment data for Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015"}],"country":"United States","state":"Nebraska, South Dakota","otherGeospatial":"Missouri River, Niobrara River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.75,\n 42.5\n ],\n [\n -97.45,\n 42.5\n ],\n [\n -97.45,\n 43\n ],\n [\n -98.75,\n 43\n ],\n [\n -98.75,\n 42.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Long-term research programs can benefit from early and periodic evaluation of their ability to meet stated objectives. In particular, consideration of the spatial allocation of effort is key. We sampled 4 species of stream salamanders intensively for 2 years (2010–2011) in the Chesapeake and Ohio Canal National Historical Park, Maryland, USA to evaluate alternative distributions of sampling locations within stream networks, and then evaluated via simulation the ability of multiple survey designs to detect declines in occupancy and to estimate dynamic parameters (colonization, extinction) over 5 years for 2 species. We expected that fine-scale microhabitat variables (e.g., cobble, detritus) would be the strongest determinants of occupancy for each of the 4 species; however, we found greater support for all species for models including variables describing position within the stream network, stream size, or stream microhabitat. A monitoring design focused on headwater sections had greater power to detect changes in occupancy and the dynamic parameters in each of 3 scenarios for the dusky salamander (Desmognathus fuscus) and red salamander (Pseudotriton ruber). Results for transect length were more variable, but across all species and scenarios, 25-m transects are most suitable as a balance between maximizing detection probability and describing colonization and extinction. These results inform sampling design and provide a general framework for setting appropriate goals, effort, and duration in the initial planning stages of research programs on stream salamanders in the eastern United States.
We summarize the distribution, ecology, threats, and conservation status of Faxonius marchandi (Hobbs, 1948), the Mammoth Spring crayfish, a limited-range endemic species to the Spring River drainage of Missouri and Arkansas, USA. The species is known from 51 locations on lower-order perennial and intermittent streams in only the eastern portion of the drainage. Faxonius marchandi is found in larger rocky substrates in shallower, slower-velocity habitats of well-buffered, mineral-rich streams. The invading alien crayfish Faxonius neglectus chaenodactylus (Williams, 1952) is the most likely threat to F. marchandi. These compiled data should serve as a baseline for future comparison, and facilitate discussion about future management, conservation, and research efforts.
","language":"English","publisher":"The Crustacean Society","doi":"10.1093/jcbiol/rux075","usgsCitation":"DiStefano, R.J., Magoulick, D.D., Flinders, C., and Imhoff, E., 2017, Conservation status of an imperiled crayfish, Faxonius marchandi Hobbs, 1948 (Decapoda: Cambaridae): Journal of Conservation Biology, v. 37, no. 5, p. 529-534, https://doi.org/10.1093/jcbiol/rux075.","productDescription":"6 p.","startPage":"529","endPage":"534","ipdsId":"IP-087504","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469333,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jcbiol/rux075","text":"Publisher Index Page"},{"id":348532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri","otherGeospatial":"Spring River","volume":"37","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-23","publicationStatus":"PW","scienceBaseUri":"5a05771be4b09af898c7085c","contributors":{"authors":[{"text":"DiStefano, Robert J.","contributorId":178202,"corporation":false,"usgs":false,"family":"DiStefano","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":720613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flinders, C.A.","contributorId":6257,"corporation":false,"usgs":true,"family":"Flinders","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":721426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Imhoff, Emily M.","contributorId":145444,"corporation":false,"usgs":false,"family":"Imhoff","given":"Emily M.","affiliations":[],"preferred":false,"id":721427,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193726,"text":"ofr20171144 - 2017 - Acoustic tag detections of green sturgeon in the Columbia River and Coos Bay estuaries, Washington and Oregon, 2010–11","interactions":[],"lastModifiedDate":"2017-11-08T17:33:23","indexId":"ofr20171144","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1144","title":"Acoustic tag detections of green sturgeon in the Columbia River and Coos Bay estuaries, Washington and Oregon, 2010–11","docAbstract":"The Columbia River, in Washington and Oregon, and Coos Bay, in Oregon, are economically important shipping channels that are inhabited by several fishes protected under the Endangered Species Act (ESA). Maintenance of shipping channels involves dredge operations to maintain sufficient in-channel depths to allow large ships to navigate the waterways safely. Fishes entrained by dredge equipment often die or experience delayed mortality. Other potential negative effects of dredging include increased turbidity, reductions in prey resources, and the release of harmful contaminants from the dredged sediments. One species of concern is the ESA-listed green sturgeon (Acipenser medirostris; Southern Distinct Population Segment). In this study, we used acoustic telemetry to identify habitat use, arrival and departure timing, and the extent of upstream migration of green sturgeon in the Columbia River and Coos Bay to help inform dredge operations to minimize potential take of green sturgeon. Autonomous acoustic receivers were deployed in Coos Bay from the mouth to river kilometer (rkm) 21.6 from October 2009 through October 2010. In the Columbia River Estuary, receivers were deployed between the mouth and rkm 37.8 from April to November in 2010 and 2011. A total of 29 subadult and adult green sturgeon were tagged with temperature and pressure sensor tags and released during the study, primarily in Willapa Bay and Grays Harbor, Washington, and the Klamath River, Oregon. Green sturgeon detected during the study but released by other researchers also were included in the study.
The number of tagged green sturgeon detected in the two estuaries differed markedly. In Coos Bay, only one green sturgeon was detected for about 2 hours near the estuary mouth. In the Columbia River Estuary, 9 green sturgeon were detected in 2010 and 10 fish were detected in 2011. Green sturgeon entered the Columbia River from May through October during both years, with the greatest numbers of fish being present in August and September. One green sturgeon was detected at the uppermost receiver station (rkm 37.8), but overall, the number of fish detected upriver decreased rapidly with distance from the estuary mouth. Residence times of fish that were only detected in the lower 4.8 rkm generally were less than 24 hours, but fish detected farther upriver had a median residence time greater than 10 days. Green sturgeon were widely dispersed among channel and non-channel habitats in the lower estuary in 2010. In 2011, the fish were more concentrated near the estuary mouth. The intensity of use, measured as the total number of fish detections at each station, generally was greatest from Point Ellice (rkm 20.1) to Rice Island (rkm 33.0) in channel and shallow shoal areas, and lowest at the stations west of Point Ellice with the exception of the area near the entrance to the Ilwaco Channel.
Sensor tag data indicated that the deeper South and North Channel habitats (bottom depth ≥10 m) were used, as were the more shallow sandy shoal, shoreline, and bay habitats (bottom depth <10 m). Median fish depths among fish and receiver locations ranged from 2.5 to 28.2 m below water surface (bws) and water temperatures ranged from 9.1 to 22.0 °C during late May through mid-October. In the deeper channel habitat, near the Ilwaco Channel, fish inhabited water with median temperatures ranging from 11.4 to 16.7 °C, whereas east of Point Ellice, predominantly in shallow non-channel habitats, fish inhabited water with median temperatures ranging from about 17.0 to 21.0 °C.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171144","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hansel, H.C., Romine, J.G., and Perry, R.W., 2017, Acoustic tag detections of green sturgeon in the Columbia River and Coos Bay estuaries, Washington and Oregon, 2010–11: U.S. Geological Survey Open-File Report 2017-1144, 30 p., https://doi.org/10.3133/ofr20171144.","productDescription":"vi, 30 p.","onlineOnly":"Y","ipdsId":"IP-088817","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":348413,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1144/ofr20171144.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1144"},{"id":348412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1144/coverthb.jpg"}],"country":"United States","state":"Oregon","city":"Astoria","otherGeospatial":"Coos Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.36283111572264,\n 43.33067209551502\n ],\n [\n -124.12696838378908,\n 43.33067209551502\n ],\n [\n -124.12696838378908,\n 43.476591264232674\n ],\n [\n -124.36283111572264,\n 43.476591264232674\n ],\n [\n -124.36283111572264,\n 43.33067209551502\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.09263610839842,\n 46.14416148780093\n ],\n [\n -123.61129760742186,\n 46.14416148780093\n ],\n [\n -123.61129760742186,\n 46.32559414426375\n ],\n [\n -124.09263610839842,\n 46.32559414426375\n ],\n [\n -124.09263610839842,\n 46.14416148780093\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
We present a Dynamic Energy Budget (DEB) model for the eastern oyster, Crassostrea virginica, which enables the inclusion of salinity as a third environmental variable, on top of the standard foodr and temperature variables. Salinity changes have various effects on the physiology of oysters, potentially altering filtration and respiration rates, and ultimately impacting growth, reproduction and mortality. We tested different hypotheses as to how to include these effects in a DEB model for C. virginica. Specifically, we tested two potential mechanisms to explain changes in oyster shell growth (cm), tissue dry weight (g) and gonad dry weight (g) when salinity moves away from the ideal range: 1) a negative effect on filtration rate and 2) an additional somatic maintenance cost. Comparative simulations of shell growth, dry tissue biomass and dry gonad weight in two monitored sites in coastal Louisiana experiencing salinity from 0 to 28 were statistically analyzed to determine the best hypothesis. Model parameters were estimated through the covariation method, using literature data and a set of specifically designed ecophysiological experiments. The model was validated through independent field studies in estuaries along the northern Gulf of Mexico. Our results suggest that salinity impacts C. virginica’s energy budget predominantly through effects on filtration rate. With an overwhelming number of environmental factors impacting organisms, and increasing exposure to novel and extreme conditions, the mechanistic nature of the DEB model with its ability to incorporate more than the standard food and temperature variables provides a powerful tool to verify hypotheses and predict individual organism performance across a range of conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2017.09.003","usgsCitation":"Lavaud, R., LaPeyre, M.K., Casas, S.M., Bacher, C., and La Peyre, J.F., 2017, Integrating the effects of salinity on the physiology of the eastern oyster, Crassostrea virginica, in the northern Gulf of Mexico through a Dynamic Energy Budget model: Ecological Modelling, v. 363, p. 221-233, https://doi.org/10.1016/j.ecolmodel.2017.09.003.","productDescription":"13 p.","startPage":"221","endPage":"233","ipdsId":"IP-086164","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.140625,\n 24.367113562651262\n ],\n [\n -79.189453125,\n 24.367113562651262\n ],\n [\n -79.189453125,\n 33.063924198120645\n ],\n [\n -99.140625,\n 33.063924198120645\n ],\n [\n -99.140625,\n 24.367113562651262\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"363","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425aee4b0dc0b45b452f1","contributors":{"authors":[{"text":"Lavaud, Romain","contributorId":200114,"corporation":false,"usgs":false,"family":"Lavaud","given":"Romain","email":"","affiliations":[],"preferred":false,"id":721040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":720625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casas, Sandra M.","contributorId":145452,"corporation":false,"usgs":false,"family":"Casas","given":"Sandra","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bacher, C.","contributorId":69742,"corporation":false,"usgs":true,"family":"Bacher","given":"C.","email":"","affiliations":[],"preferred":false,"id":721042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, Jerome F.","contributorId":34697,"corporation":false,"usgs":true,"family":"La Peyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":721043,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193830,"text":"70193830 - 2017 - Diet composition and provisioning rates of nestlings determine reproductive success in a subtropical seabird","interactions":[],"lastModifiedDate":"2017-11-08T11:16:08","indexId":"70193830","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Diet composition and provisioning rates of nestlings determine reproductive success in a subtropical seabird","docAbstract":"Understanding how both quality and quantity of prey affect the population dynamics of marine predators is a crucial step toward predicting the effects of environmental perturbations on population-level processes. The Junk Food Hypothesis, which posits that energetic content of prey species may influence reproductive capacity of marine top predators regardless of prey availability, has been proposed as a mechanism by which changes in prey populations could affect predator populations in high latitude systems; however, support for this hypothesis has been inconsistent across studies, and further data are needed to elucidate variation in the relative importance of prey quantity and quality, both among predator species and across ecological systems. We tested the relative importance of prey quantity and quality to nestling survival in the eastern brown pelican Pelecanus occidentalis carolinensis across 9 breeding colonies in the northern Gulf of Mexico that varied in underlying availability of a key prey resource, the Gulf menhaden Brevoortia patronus. Both feeding frequency and meal mass were significantly correlated to energy provisioning rates and nestling survival, while energy density of meals had little effect on either metric. Compared to previous results from cold-water systems, we found lower and less variable energy densities (4.4 kJ g-1, vs. 5.2 to 6.5 kJ g-1 in other studies) and lipid content (9% dry mass, vs. 16 to 23% in other studies) of common prey items. While Gulf menhaden was the most common prey species at all colonies, the proportion of menhaden fed to nestlings varied and was not strongly correlated to fledging success. We conclude that quantity rather than quality of prey, particularly small schooling fish, is the main driver of brown pelican reproductive success in this system, and that environmental perturbations affecting biomass, distribution, and abundance of forage fish could substantially affect brown pelican reproductive success.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps12301","usgsCitation":"Lamb, J.S., Jodice, P.G., and Satge, Y.G., 2017, Diet composition and provisioning rates of nestlings determine reproductive success in a subtropical seabird: Marine Ecology Progress Series, v. 581, p. 149-164, https://doi.org/10.3354/meps12301.","productDescription":"16 p.","startPage":"149","endPage":"164","ipdsId":"IP-083227","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469338,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps12301","text":"Publisher Index Page"},{"id":438155,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R78D6J","text":"USGS data release","linkHelpText":"Composition of diet of juvenile Brown Pelican in the northern Gulf of Mexico (2013-2015)"},{"id":348429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.525390625,\n 25.403584973186703\n ],\n [\n -81.38671875,\n 25.403584973186703\n ],\n [\n -81.38671875,\n 30.826780904779774\n ],\n [\n -98.525390625,\n 30.826780904779774\n ],\n [\n -98.525390625,\n 25.403584973186703\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"581","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425aee4b0dc0b45b452f4","contributors":{"authors":[{"text":"Lamb, Juliet S. 0000-0003-0358-3240","orcid":"https://orcid.org/0000-0003-0358-3240","contributorId":198059,"corporation":false,"usgs":false,"family":"Lamb","given":"Juliet","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":721086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":200009,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":720623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Satge, Yvan G.","contributorId":200132,"corporation":false,"usgs":false,"family":"Satge","given":"Yvan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":721087,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193565,"text":"70193565 - 2017 - Increased hurricane frequency near Florida during Younger Dryas Atlantic Meridional Overturning Circulation slowdown ","interactions":[],"lastModifiedDate":"2017-11-06T11:40:48","indexId":"70193565","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Increased hurricane frequency near Florida during Younger Dryas Atlantic Meridional Overturning Circulation slowdown ","docAbstract":"The risk posed by intensification of North Atlantic hurricane activity remains controversial, in part due to a lack of available storm proxy records that extend beyond the relatively stable climates of the late Holocene. Here we present a record of storm-triggered turbidite deposition offshore the Dry Tortugas, south Florida, USA, that spans abrupt transitions in North Atlantic sea-surface temperature and Atlantic Meridional Overturning Circulation (AMOC) during the Younger Dryas (12.9–11.7 ka). Despite potentially hostile conditions for cyclogenesis in the tropical North Atlantic at that time, our record and numerical experiments suggest that strong hurricanes may have regularly affected Florida. Less severe surface cooling at mid-latitudes (∼20°–40°N) than across much of the tropical North Atlantic (∼10°–20°N) in response to AMOC reduction may best explain strong hurricane activity during the Younger Dryas near the Dry Tortugas and possibly along the entire southeastern coast of the United States.","language":"English","publisher":"Geological Society of America","doi":"10.1130/G39270.1","usgsCitation":"Toomey, M., Korty, R.L., Donnelly, J.P., van Hengstum, P.J., and Curry, W.B., 2017, Increased hurricane frequency near Florida during Younger Dryas Atlantic Meridional Overturning Circulation slowdown : Geology, v. 45, no. 11, p. 1047-1050, https://doi.org/10.1130/G39270.1.","productDescription":"4 p.","startPage":"1047","endPage":"1050","ipdsId":"IP-089873","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469347,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/9392","text":"External Repository"},{"id":348262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas","volume":"45","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-05","publicationStatus":"PW","scienceBaseUri":"5a07e849e4b09af898c8cb36","contributors":{"authors":[{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@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":719374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Korty, Robert L.","contributorId":199535,"corporation":false,"usgs":false,"family":"Korty","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":719375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donnelly, Jeffrey P.","contributorId":192783,"corporation":false,"usgs":false,"family":"Donnelly","given":"Jeffrey","email":"","middleInitial":"P.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":719376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Hengstum, Peter J.","contributorId":199536,"corporation":false,"usgs":false,"family":"van Hengstum","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":719377,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curry, William B.","contributorId":199537,"corporation":false,"usgs":false,"family":"Curry","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":16634,"text":"Bermuda Institute of Ocean Sciences","active":true,"usgs":false}],"preferred":false,"id":719378,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200597,"text":"70200597 - 2017 - Transgressive-regressive cycles in the metalliferous, oil-shale-bearing Heath Formation (Upper Mississippian), central Montana","interactions":[],"lastModifiedDate":"2018-10-24T16:27:54","indexId":"70200597","displayToPublicDate":"2017-11-01T16:27:46","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Transgressive-regressive cycles in the metalliferous, oil-shale-bearing Heath Formation (Upper Mississippian), central Montana","docAbstract":"The Upper Mississippian Heath Formation, which accumulated in the Big Snowy Trough of central Montana, has been known for three decades to contain mudrocks highly enriched in Zn, V, Mo, Ni and other metals, and source rocks for oil. The unit has more recently been recognized as a prospective tight oil play. Here we present petrographic, paleontologic, geochemical, and carbon and sulfur isotope data on seven continuous drill cores spanning ≤146 m of immature to marginally mature strata in order to improve understanding of the depositional setting of the Heath.
The unit consists of five third-order transgressive-regressive cycles (C1–C5 from bottom to top) that were deposited during a fluctuating climatic regime. Cycles comprise thinly interbedded gray to black mudrock and carbonate strata capped by either coal, implying a humid climate (C1, C3 and C4), or gypsum, implying more arid conditions (C2); the upper part of C5 is not preserved in our study area. Mfs (maximum flooding surfaces) in C1, C2, C4, and C5 lie within black mudrock beds ~0.5–3-m thick with >10% TOC (total organic carbon), type I and type II kerogen (determined by programmed pyrolysis), high contents of Zn, V, Mo, and other metals, relatively low values of δ13CTOC and δ34Spyrite, and a limited-diversity fauna of locally abundant, thin-shelled pelecypods (Dunbarella? sp.).
The mfs in C2 is within the Cox Ranch oil shale bed, which is known from previous studies to be metalliferous; new analyses reported here show ≤28 wt % TOC, 5140 ppm Zn, 1910 ppm V, 1590 ppm Mo, and 509 ppm Ni. Strata that contain the mfs of C1, C4, and C5 are shown here for the first time to also have high metal contents, with maximum values of 1030–7340 ppm Zn, 446–1980 ppm V, 72–859 ppm Mo, and 221–452 ppm Ni. Cycle C3, which contains more gray mudrock and carbonate beds than the other cycles, has lower TOC (≤4.2 wt %), lower metals, and mainly type III kerogen. Carbonate beds include normal-marine crinoidal mudstone to packstone and lesser (dolo)mudstone with fenestral fabric, peloids, intraclasts, and a euryhaline fauna. Mid-Chesterian (early Serpukhovian) foraminifers in C3, combined with previously published fossil data, suggest that third-order cycles in the Heath Formation were ~1–2 myr in duration. They formed during a time of active block faulting in the Big Snowy Trough and global cooling linked to Gondwanan glaciation.
Tectonic, climatic, and paleogeographic factors shaped the cycles of the Heath Formation. Faunal and geochemical evidence indicate that conditions were most favorable for marine life during C3. Molybdenum concentrations >100 ppm and organic geochemical data suggest euxinic conditions during deposition of the black mudrock in C2, C4, and C5, but the presence of shell beds (1 mm–6-cm thick) within this mudrock requires bottom water with sufficient oxygen to support life, at least periodically. The apparent conflict between the geochemical and paleontologic observations likely reflects the different time scales of these two environmental proxies: 1000s of yrs vs <1–10s of yrs, respectively.
Metal- and organic-rich strata in the Heath Formation formed by slow, condensed sedimentation from periodically anoxic or euxinic bottom waters in a marine basin. Fossil data indicate that anoxia was episodic, perhaps seasonal and/or linked to longer-duration climate shifts. On a millennial time scale, metal enrichments in the Heath reflect a balance between primary productivity that was high enough for oxygen to be consumed by sinking organic matter and oxic seawater inflow that was strong enough to maintain a supply of metals without compromising anoxia. Organic-rich mudrock in the Heath shares intriguing lithologic and geochemical similarities with mudrock in other Middle to Upper Paleozoic units such as the Devonian-Mississippian Bakken Formation and Pennsylvanian cyclothems (e.g., Excello Shale).
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Methow valley is excavated in an exotic terrane of folded Mesozoic sedimentary and volcanic rocks faulted between crystalline blocks. Repeated floods of Columbia River Basalt about 16 Ma drowned a backarc basin to the southeast.\n\nCirques, aretes, and U-shaped hanging troughs brand the Methow, Skagit, and Chelan headwaters. The Late Wisconsin Cordilleran icesheet beveled the alpine topography and deposited drift. Cordilleran ice flowed into the heads of Methow tributaries and overflowed from Skagit tributaries to greatly augment Chelan trough's glacier. Joined Okanogan and Methow ice flowed down Columbia valley and up lower Chelan trough. This tongue met the icesheet tongue flowing southeast down Chelan valley. Successively lower ice-marginal channels and kame terraces show that the icesheet withered away largely by downwasting.\n\nImmense late Wisconsin floods from glacial Lake Missoula occasionally swept the Chelan-Vantage reach of Columbia valley by different routes. The earliest debacles, nearly 19,000 cal yr BP (by radiocarbon methods), raged 335 m deep down the Columbia and built high Pangborn bar at Wenatchee. As Cordilleran ice blocked the northwest of Columbia valley, several giant floods descended Moses Coulee and backflooded up the Columbia. As advancing ice then blocked Moses Coulee, Grand Coulee to Quincy basin became the westmost floodway. From Quincy basin many Missoula floods backflowed 50 km upvalley past Wenatchee 18,000 to 15,500 years ago. Receding ice dammed glacial Lake Columbia centuries more--till it burst about 15,000 years ago. After Glacier Peak ashfall about 13,600 years ago, smaller great flood(s) swept down the Columbia from glacial Lake Kootenay in British Columbia. A cache of huge fluted Clovis points had been laid atop Pangborn bar (East Wenatchee) after the Glacier Peak ashfall. Clovis people came two and a half millennia after the last small Missoula flood, two millennia after the glacial Lake Columbia flood.\n\nThis timing by radiocarbon methods is under review by newer exposure dating--10Be, 26Al, and 36Cl methods.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From the Puget Lowland to east of the Cascade Range—Geologic excursions in the Pacific Northwest: Geological Society of America Field Guide 49","language":"English","publisher":"Geological Society of America","isbn":"978-0-8137-0049-6","usgsCitation":"Waitt, R.B., 2017, Pleistocene glaciers, lakes, and floods in north-central Washington State, chap. of From the Puget Lowland to east of the Cascade Range—Geologic excursions in the Pacific Northwest: Geological Society of America Field Guide 49, p. 175-205.","productDescription":"31 p.","startPage":"175","endPage":"205","ipdsId":"IP-088267","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":349597,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349596,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://rock.geosociety.org/Store/detail.aspx?id=FLD049"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb21e4b06e28e9c22d05","contributors":{"editors":[{"text":"Haugerud, Ralph A. 0000-0001-7302-4351 rhaugerud@usgs.gov","orcid":"https://orcid.org/0000-0001-7302-4351","contributorId":2691,"corporation":false,"usgs":true,"family":"Haugerud","given":"Ralph","email":"rhaugerud@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":724156,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Kelsey, Harvey M.","contributorId":101713,"corporation":false,"usgs":true,"family":"Kelsey","given":"Harvey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":724157,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Waitt, Richard B. 0000-0002-6392-5604 waitt@usgs.gov","orcid":"https://orcid.org/0000-0002-6392-5604","contributorId":2343,"corporation":false,"usgs":true,"family":"Waitt","given":"Richard","email":"waitt@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":723269,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70193779,"text":"70193779 - 2017 - Perspectives on chemical oceanography in the 21st century: Participants of the COME ABOARD Meeting examine aspects of the field in the context of 40 years of DISCO","interactions":[],"lastModifiedDate":"2017-11-06T10:56:13","indexId":"70193779","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2662,"text":"Marine Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Perspectives on chemical oceanography in the 21st century: Participants of the COME ABOARD Meeting examine aspects of the field in the context of 40 years of DISCO","docAbstract":"The questions that chemical oceanographers prioritize over the coming decades, and the methods we use to address these questions, will define our field's contribution to 21st century science. In recognition of this, the U.S. National Science Foundation and National Oceanic and Atmospheric Administration galvanized a community effort (the Chemical Oceanography MEeting: A BOttom-up Approach to Research Directions, or COME ABOARD) to synthesize bottom-up perspectives on selected areas of research in Chemical Oceanography. Representing only a small subset of the community, COME ABOARD participants did not attempt to identify targeted research directions for the field. Instead, we focused on how best to foster diverse research in Chemical Oceanography, placing emphasis on the following themes: strengthening our core chemical skillset; expanding our tools through collaboration with chemists, engineers, and computer scientists; considering new roles for large programs; enhancing interface research through interdisciplinary collaboration; and expanding ocean literacy by engaging with the public. For each theme, COME ABOARD participants reflected on the present state of Chemical Oceanography, where the community hopes to go and why, and actionable pathways to get there. A unifying concept among the discussions was that dissimilar funding structures and metrics of success may be required to accommodate the various levels of readiness and stages of knowledge development found throughout our community. In addition to the science, participants of the concurrent Dissertations Symposium in Chemical Oceanography (DISCO) XXV, a meeting of recent and forthcoming Ph.D. graduates in Chemical Oceanography, provided perspectives on how our field could show leadership in addressing long-standing diversity and early-career challenges that are pervasive throughout science. Here we summarize the COME ABOARD Meeting discussions, providing a synthesis of reflections and perspectives on the field.
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