Federal agencies need credible scientific information to determine the production and value of ecosystem services in an efficient and timely manner. The U.S. Geological Survey addresses this scientific information need through the Sustaining Environmental Capital Initiative project. The project has relied on U.S. Geological Survey expertise related to water, fisheries, advanced modeling, and economics and other social sciences to conduct eight case studies across a range of environment types, including water-based environments, deserts, sagebrush ecosystems, floodplains, and forests. The Sustaining Environmental Capital Initiative also supported the development and expansion of four tools with the intent of adding content and usability for partners’ decision-making needs. The tools are the Natural Value Resource Center, Benefit Transfer Toolkit, Riverine Environmental Flow Decision Support System, and Artificial Intelligence for Ecosystem Services modeling platform.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191117","usgsCitation":"Huber, C., Meldrum, J.R., Schuster, R.M., Ancona, Z.H., Bagstad, K.J., Beck, S.M., Carlisle, D.M., Claggett, P.R., Franco, F., Galbraith, H.S., Haefele, M., Hoelting, K.R., Hogan, D.M., Hopkins, K.G., Kern, T., Lawrence, C.B., Lischka, S., Loomis, J.B., Mueller, J.M., Noe, G.B., Pindilli, E.J., Quay, B., Semmens, D.J., Sinclair, W., Spooner, D.E., Voigt, B., and St. John White, B., 2020, Sustaining Environmental Capital Initiative summary report: U.S. Geological Survey Open-File Report 2019–1117, 23 p., https://doi.org/10.3133/ofr20191117.","productDescription":"v, 23 p.","onlineOnly":"Y","ipdsId":"IP-099772","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":370958,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1117/ofr20191117.pdf","text":"Report","size":"348 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1117"},{"id":370957,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1117/coverthb.jpg"}],"contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Majuro Atoll in the central Pacific has high coastal vulnerability due to low-lying islands, rising sea level, high wave events, eroding shorelines, a dense population center, and limited freshwater resources. Land elevation is the primary geophysical variable that determines exposure to inundation in coastal settings. Accordingly, coastal elevation data (with accuracy information) are critical for assessments of inundation exposure. Previous research has demonstrated the importance of using high-accuracy elevation data and rigorously accounting for uncertainty in inundation assessments. A quantitative analysis of inundation exposure was conducted for Majuro Atoll, including accounting for the cumulative vertical uncertainty from the input digital elevation model (DEM) and datum transformation. The project employed a recently produced and validated DEM derived from structure-from-motion processing of very-high-resolution aerial imagery. Areas subject to marine inundation (direct hydrologic connection to the ocean) and low-lying lands (disconnected hydrologically from the ocean) were mapped and characterized for three inundation levels using deterministic and probabilistic methods. At the highest water level modeled (3.75 ft, or 1.143 m), more than 34% of the atoll study area is likely to be exposed to inundation (68% chance or greater), while more than 20% of the atoll is extremely likely to be exposed (95% chance or greater). The study demonstrates the substantial value of a high-accuracy DEM for assessing inundation exposure of low-relief islands and the enhanced information from accounting for vertical uncertainty.
","language":"English","publisher":"MDPI","doi":"10.3390/rs12010154","usgsCitation":"Gesch, D.B., Palaseanu-Lovejoy, M., Danielson, J.J., Fletcher, C., Kottermair, M., Barbee, M., and Jalandoni, A., 2020, Inundation exposure assessment for Majuro Atoll, Republic of the Marshall Islands using a high-accuracy digital elevation model: Remote Sensing, v. 12, no. 1, Article: 154, 20 p.; Data Release, https://doi.org/10.3390/rs12010154.","productDescription":"Article: 154, 20 p.; Data Release","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":458218,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12010154","text":"Publisher Index Page"},{"id":372951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373335,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5ba9511ee4b08583a5ca09fe","text":"USGS data release","description":"USGS data release","linkHelpText":"Inundation exposure assessment for Majuro Atoll, Republic of the Marshall Islands"}],"country":"Republic of the Marshall Islands","otherGeospatial":"Majuro Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 170.98777770996094,\n 6.976183516197836\n ],\n [\n 171.43203735351562,\n 6.976183516197836\n ],\n [\n 171.43203735351562,\n 7.198319490613516\n ],\n [\n 170.98777770996094,\n 7.198319490613516\n ],\n [\n 170.98777770996094,\n 6.976183516197836\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":784036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":784037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","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":784038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fletcher, Charles","contributorId":192304,"corporation":false,"usgs":false,"family":"Fletcher","given":"Charles","affiliations":[],"preferred":false,"id":784039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kottermair, Maria","contributorId":119958,"corporation":false,"usgs":true,"family":"Kottermair","given":"Maria","email":"","affiliations":[],"preferred":false,"id":784040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barbee, Matthew 0000-0002-8929-7255","orcid":"https://orcid.org/0000-0002-8929-7255","contributorId":196651,"corporation":false,"usgs":false,"family":"Barbee","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":784041,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jalandoni, Andrea 0000-0002-4821-7183","orcid":"https://orcid.org/0000-0002-4821-7183","contributorId":196653,"corporation":false,"usgs":false,"family":"Jalandoni","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":784042,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224539,"text":"70224539 - 2020 - Nest site selection influences cinnamon teal nest survival in Colorado","interactions":[],"lastModifiedDate":"2021-09-27T14:46:51.635435","indexId":"70224539","displayToPublicDate":"2020-01-06T09:40:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Nest site selection influences cinnamon teal nest survival in Colorado","docAbstract":"Nest survival of ducks is partially a function of the spatiotemporal characteristics of the site at which a bird chooses to nest. Nest survival is also a fundamental component of population growth in waterfowl but is relatively unstudied for cinnamon teal (Spatula cyanoptera). We investigated cinnamon teal nest survival in a managed wetland complex in southern Colorado, USA, and assessed nest site selection to determine whether nest site characteristics were adaptive. We monitored 85 nests in 2015–2017 on Monte Vista National Wildlife Refuge, Colorado and did not detect a difference in nest survival across years. Based on nest site selection data from 2017, cinnamon teal selected nest sites characterized by a lower proportion of forbs than available sites. The relationships between habitat characteristics and nest survival were variable. Microhabitat characteristics exhibited only weak effects on nest survival during the laying stage. Nest survival during incubation was negatively related to the proportion of forbs at the nest site and, to a lesser extent, the proportion of grasses. Nest site selection was predictive of future nest survival based on the percent of forbs and grasses around the nest site, suggesting teal select nest locations to benefit reproductive success. These results have the potential to guide local habitat management actions for breeding waterfowl.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21818","usgsCitation":"Kendall, W.L., Setash, C.M., and Olson, D., 2020, Nest site selection influences cinnamon teal nest survival in Colorado: Journal of Wildlife Management, v. 84, no. 3, p. 542-552, https://doi.org/10.1002/jwmg.21818.","productDescription":"11 p.","startPage":"542","endPage":"552","ipdsId":"IP-105687","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":389811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Monte Vista 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 -106.18011474609375,\n 37.45687303762862\n ],\n [\n -106.01394653320312,\n 37.45687303762862\n ],\n [\n -106.01394653320312,\n 37.53477698849112\n ],\n [\n -106.18011474609375,\n 37.53477698849112\n ],\n [\n -106.18011474609375,\n 37.45687303762862\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":823982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Setash, Casey M.","contributorId":265282,"corporation":false,"usgs":false,"family":"Setash","given":"Casey","email":"","middleInitial":"M.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":823983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olson, David","contributorId":265284,"corporation":false,"usgs":false,"family":"Olson","given":"David","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":823984,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70262070,"text":"70262070 - 2020 - Characterization of a Y-specific duplication/insertion of the anti-Mullerian hormone type II receptor gene based on a chromosome-scale genome assembly of yellow perch, Perca flavescens","interactions":[],"lastModifiedDate":"2025-01-10T15:38:58.132616","indexId":"70262070","displayToPublicDate":"2020-01-06T09:23:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Characterization of a Y-specific duplication/insertion of the anti-Mullerian hormone type II receptor gene based on a chromosome-scale genome assembly of yellow perch, Perca flavescens","title":"Characterization of a Y-specific duplication/insertion of the anti-Mullerian hormone type II receptor gene based on a chromosome-scale genome assembly of yellow perch, Perca flavescens","docAbstract":"Yellow perch, Perca flavescens, is an ecologically and economically important species native to a large portion of the northern United States and southern Canada and is also a promising candidate species for aquaculture. However, no yellow perch reference genome has been available to facilitate improvements in both fisheries and aquaculture management practices. By combining Oxford Nanopore Technologies long-reads, 10X Genomics Illumina short linked reads and a chromosome contact map produced with Hi-C, we generated a high-continuity chromosome-scale yellow perch genome assembly of 877.4 Mb. It contains, in agreement with the known diploid chromosome yellow perch count, 24 chromosome-size scaffolds covering 98.8% of the complete assembly (N50 = 37.4 Mb, L50 = 11). We also provide a first characterization of the yellow perch sex determination locus that contains a male-specific duplicate of the anti-Mullerian hormone type II receptor gene (amhr2by) inserted at the proximal end of the Y chromosome (chromosome 9). Using this sex-specific information, we developed a simple PCR genotyping assay which accurately differentiates XY genetic males (amhr2by+) from XX genetic females (amhr2by−). Our high-quality genome assembly is an important genomic resource for future studies on yellow perch ecology, toxicology, fisheries and aquaculture research. In addition, characterization of the amhr2by gene as a candidate sex-determining gene in yellow perch provides a new example of the recurrent implication of the transforming growth factor beta pathway in fish sex determination, and highlights gene duplication as an important genomic mechanism for the emergence of new master sex determination genes.
","language":"English","publisher":"Wiley","doi":"10.1111/1755-0998.13133","usgsCitation":"Feron, R., Zahm, M., Cabau, C., Klopp, C., Roques, C., Bouchez, O., Eché, C., Valière, S., Donnadieu, C., Haffray, P., Bestin, A., Morvezen, R., Acoloque, H., Euclide, P.T., Wen, M., Jouano, E., Schartl, M., Postlethwait, J., Schraidt, C., Christie, M.R., Larson, W., Herpin, A., and Guiguen, Y., 2020, Characterization of a Y-specific duplication/insertion of the anti-Mullerian hormone type II receptor gene based on a chromosome-scale genome assembly of yellow perch, Perca flavescens: Molecular Ecology Resources, v. 20, no. 2, p. 531-543, https://doi.org/10.1111/1755-0998.13133.","productDescription":"13 p.","startPage":"531","endPage":"543","ipdsId":"IP-110009","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467306,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.inrae.fr/hal-02623895","text":"External 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France","active":true,"usgs":false}],"preferred":false,"id":922957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klopp, Christophe","contributorId":348127,"corporation":false,"usgs":false,"family":"Klopp","given":"Christophe","affiliations":[],"preferred":false,"id":922981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roques, Céline","contributorId":348120,"corporation":false,"usgs":false,"family":"Roques","given":"Céline","affiliations":[{"id":37303,"text":"INRA, France","active":true,"usgs":false}],"preferred":false,"id":922958,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bouchez, Olivier","contributorId":348121,"corporation":false,"usgs":false,"family":"Bouchez","given":"Olivier","affiliations":[{"id":37303,"text":"INRA, France","active":true,"usgs":false}],"preferred":false,"id":922959,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eché, 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0000-0002-1212-0435","orcid":"https://orcid.org/0000-0002-1212-0435","contributorId":236838,"corporation":false,"usgs":false,"family":"Euclide","given":"Peter","email":"","middleInitial":"T.","affiliations":[{"id":47551,"text":"University of Wisconsin- Stevens Point","active":true,"usgs":false}],"preferred":false,"id":922987,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wen, Ming","contributorId":348130,"corporation":false,"usgs":false,"family":"Wen","given":"Ming","affiliations":[],"preferred":false,"id":922988,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Jouano, Elodie","contributorId":348131,"corporation":false,"usgs":false,"family":"Jouano","given":"Elodie","affiliations":[],"preferred":false,"id":922989,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Schartl, Manfred","contributorId":348132,"corporation":false,"usgs":false,"family":"Schartl","given":"Manfred","affiliations":[],"preferred":false,"id":922990,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Postlethwait, John","contributorId":348133,"corporation":false,"usgs":false,"family":"Postlethwait","given":"John","affiliations":[],"preferred":false,"id":922991,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Schraidt, Claire","contributorId":311102,"corporation":false,"usgs":false,"family":"Schraidt","given":"Claire","email":"","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":922992,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Christie, Mark R.","contributorId":191035,"corporation":false,"usgs":false,"family":"Christie","given":"Mark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":922993,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Larson, Wesley 0000-0003-4473-3401 wlarson@usgs.gov","orcid":"https://orcid.org/0000-0003-4473-3401","contributorId":199509,"corporation":false,"usgs":true,"family":"Larson","given":"Wesley","email":"wlarson@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922954,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Herpin, Amaury","contributorId":348134,"corporation":false,"usgs":false,"family":"Herpin","given":"Amaury","affiliations":[],"preferred":false,"id":922994,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Guiguen, Yann","contributorId":348135,"corporation":false,"usgs":false,"family":"Guiguen","given":"Yann","affiliations":[],"preferred":false,"id":922995,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70237847,"text":"70237847 - 2020 - Mariana serpentinite mud volcanism exhumes subducted seamount materials: Implications for the origin of life","interactions":[],"lastModifiedDate":"2022-10-26T13:51:19.512083","indexId":"70237847","displayToPublicDate":"2020-01-06T06:36:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3047,"text":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Mariana serpentinite mud volcanism exhumes subducted seamount materials: Implications for the origin of life","docAbstract":"The subduction of seamounts and ridge features at convergent plate boundaries plays an important role in the deformation of the overriding plate and influences geochemical cycling and associated biological processes. Active serpentinization of forearc mantle and serpentinite mud volcanism on the Mariana forearc (between the trench and active volcanic arc) provides windows on subduction processes. Here, we present (1) the first observation of an extensive exposure of an undeformed Cretaceous seamount currently being subducted at the Mariana Trench inner slope; (2) vertical deformation of the forearc region related to subduction of Pacific Plate seamounts and thickened crust; (3) recovered Ocean Drilling Program and International Ocean Discovery Program cores of serpentinite mudflows that confirm exhumation of various Pacific Plate lithologies, including subducted reef limestone; (4) petrologic, geochemical and paleontological data from the cores that show that Pacific Plate seamount exhumation covers greater spatial and temporal extents; (5) the inference that microbial communities associated with serpentinite mud volcanism may also be exhumed from the subducted plate seafloor and/or seamounts; and (6) the implications for effects of these processes with regard to evolution of life.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsta.2018.0425","usgsCitation":"Fryer, P., Wheat, C.G., Williams, T., Johnson, K., Kelley, C., Albers, E., Kurz, W., Shervais, J., Ryan, J., Bekins, B.A., Debret, B., Deng, J., Dong, Y., Eickenbusch, P., Frery, E., Ichiyama, Y., Johnston, R., Kevorkian, R., Magalhaes, V., Mantovanelli, S., Menapace, W., Menzies, C.D., Michibayashi, K., Moyer, C., Mullane, K., Park, J., Price, R., Sissmann, O., Suzuki, S., Takai, K., Walter, B., Zhang, R., Amon, D., Glickson, D., and Pomponi, S., 2020, Mariana serpentinite mud volcanism exhumes subducted seamount materials: Implications for the origin of life: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, v. 378, no. 2165, 20180425, 28 p., https://doi.org/10.1098/rsta.2018.0425.","productDescription":"20180425, 28 p.","ipdsId":"IP-110449","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":458227,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsta.2018.0425","text":"Publisher Index Page"},{"id":408749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"378","issue":"2165","noUsgsAuthors":false,"publicationDate":"2020-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Fryer, Patricia","contributorId":298539,"corporation":false,"usgs":false,"family":"Fryer","given":"Patricia","email":"","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":855844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wheat, C. 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Deborah","contributorId":298570,"corporation":false,"usgs":false,"family":"Glickson","given":"Deborah","email":"","affiliations":[],"preferred":false,"id":855899,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Pomponi, Shirley","contributorId":289153,"corporation":false,"usgs":false,"family":"Pomponi","given":"Shirley","email":"","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":855900,"contributorType":{"id":1,"text":"Authors"},"rank":35}]}} ,{"id":70261995,"text":"70261995 - 2020 - Seismic character and progression of explosive activity during the 2016-2017 eruption of Bogoslof volcano, Alaska","interactions":[],"lastModifiedDate":"2025-01-08T14:52:22.557026","indexId":"70261995","displayToPublicDate":"2020-01-06T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Seismic character and progression of explosive activity during the 2016-2017 eruption of Bogoslof volcano, Alaska","docAbstract":"Bogoslof volcano, in the central Aleutian arc, experienced a major eruption between December 2016 and August 2017 that was characterized by explosive activity (VEI 2 to 3) and the extrusion of lava domes. The Alaska Volcano Observatory tracked the activity in real-time using seismicity observed on distant stations as well as infrasound, lightning, satellite data, and occasional visual observations. In this study we measure the duration of seismic signals associated with individual explosive events to track their progression during the two explosive phases of the eruption. Seismic recordings of Bogoslof explosions show complex waveforms that suggest both individual explosive events as well as sequences of several explosions separated by lower amplitude tremor. The lack of local seismic monitoring (stations at distances of 1 to 15 km distance) unfortunately limit our ability to closely observe seismicity and to interpret changing conditions at the vent such as position, presence of a lava dome or plug, and the role of seawater associated with the eruption. We use the rate of explosive activity, seismic waveform character, and repose time between explosions to infer the conditions within the conduit.","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-019-1343-4","usgsCitation":"Searcy, C., and Power, J., 2020, Seismic character and progression of explosive activity during the 2016-2017 eruption of Bogoslof volcano, Alaska: Bulletin of Volcanology, v. 82, 12, 15 p., https://doi.org/10.1007/s00445-019-1343-4.","productDescription":"12, 15 p.","ipdsId":"IP-107037","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":465874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.05541389523495,\n 53.94243302102879\n ],\n [\n -168.05541389523495,\n 53.92208824366685\n ],\n [\n -168.01832898316061,\n 53.92208824366685\n ],\n [\n -168.01832898316061,\n 53.94243302102879\n ],\n [\n -168.05541389523495,\n 53.94243302102879\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Searcy, Cheryl 0000-0002-9474-5745","orcid":"https://orcid.org/0000-0002-9474-5745","contributorId":243217,"corporation":false,"usgs":true,"family":"Searcy","given":"Cheryl","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Power, John 0000-0002-7233-4398","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":215240,"corporation":false,"usgs":true,"family":"Power","given":"John","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922600,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211340,"text":"70211340 - 2020 - Using conceptual models to relate multiparameter satellite data to subsurface volcanic processes in Latin America","interactions":[],"lastModifiedDate":"2020-09-01T13:54:44.456524","indexId":"70211340","displayToPublicDate":"2020-01-05T10:07:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Using conceptual models to relate multiparameter satellite data to subsurface volcanic processes in Latin America","docAbstract":"Satellite data have been extensively used to identify volcanic behavior. However, the physical subsurface processes causing any individual manifestation of activity can be ambiguous. We propose a classification scheme for the cause of unrest that simultaneously considers three multiparameter satellite observations. The scheme is based on characteristics of the volcanic system (open, closed, and eruptive) and unrest mechanisms (intrusion, evolution, and withdrawal) occurring at shallow depths in the volcanic system. We applied these models to satellite observations acquired at 47 of the most active volcanoes in Latin America. Of the volcanoes studied, 44 had a robust enough dataset for classification and were clustered into 4 groups and 10 subgroups with common behavioral characteristics. By identifying that these volcanoes can be clustered into a number of groupings significantly less than the number of volcanoes, we have demonstrated that commonalities in behavior patterns exist among diverse volcanic systems. Identifying volcanoes with similar characteristics underpins the use of past observations at one volcano to forecast activity at another and diverges from typical volcanic groupings, which are focused on geologic parameters (i.e., composition, volcano type, and tectonic setting). Based on satellite data alone, we have identified preeruptive intrusion prior to 15 eruptions at 12 different volcanoes, magma evolution prior to 18 eruptions at 13 volcanoes, and magma withdrawal at 3 eruptions and 3 volcanoes. Improvements to the spatial and temporal resolution are needed to make these relations robust. This classification scheme provides a framework for future automated clustering of volcanoes.
Turbidites embedded in lacustrine sediment sequences are commonly used to reconstruct regional flood or earthquake histories. A critical step for this method to be successful is that turbidites and their trigger mechanisms are determined unambiguously. The latter is particularly challenging for prehistoric proglacial lake records in high-seismicity settings where both earthquake-generated and flood-generated turbidites interrupt the background varved sedimentation. This calls for a new method to allow efficient and objective identification and classification of turbidites. This study examined turbidites in five long (9 to 17 m) sediment cores from Eklutna Lake, a proglacial lake in south-central Alaska, using standard core logging and grain-size data. A novel statistical approach is presented, in which varve-thickness distributions were first analyzed to objectively identify the thickest turbidites and distinguish them from background sedimentation. For each turbidite, a selection of variables were then measured, including: basal grain-size, thickness, magnetic susceptibility and spectrophotometric variables. Triggering mechanisms were discriminated by a combination of principal component analysis and clustering, and by calibration with historical events. Using this approach, a 2250 year long lake-wide event stratigraphy was constructed, with 94 prehistoric events, including 24 earthquake and 70 flood events. Basal grain-size and thickness variables turn out to be the most effective proxies for discrimination. This statistical approach is a powerful and new method to identify turbidites and their triggering mechanisms in long prehistoric sediment records. It opens up new prospects for palaeoseismological, palaeohydrological and palaeoclimate studies in proglacial lakes worldwide.
","language":"English","publisher":"International Association of Sedimentologists","doi":"10.1111/sed.12703","usgsCitation":"Praet, N., Van Daele, M., Collart, T., Moernaut, J., Vandekerkhove, E., Kempf, P., Haeussler, P., and De Batist, M., 2020, Turbidite stratigraphy in proglacial lakes: Deciphering trigger mechanisms using a statistical approach: Sedimentology, v. 67, no. 5, p. 2332-2359, https://doi.org/10.1111/sed.12703.","productDescription":"28 p.","startPage":"2332","endPage":"2359","ipdsId":"IP-112553","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":382465,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Eklutna Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.2,\n 61.1667\n ],\n [\n -148.85,\n 61.1667\n ],\n [\n -148.85,\n 61.45\n ],\n [\n -149.2,\n 61.45\n ],\n [\n -149.2,\n 61.1667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Praet, Nore","contributorId":194083,"corporation":false,"usgs":false,"family":"Praet","given":"Nore","email":"","affiliations":[],"preferred":false,"id":808647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Daele, Maarten 0000-0002-8530-4438","orcid":"https://orcid.org/0000-0002-8530-4438","contributorId":194085,"corporation":false,"usgs":false,"family":"Van Daele","given":"Maarten","email":"","affiliations":[{"id":27279,"text":"Department of Geology and Soil Science, Ghent University, Ghent, Belgium","active":true,"usgs":false}],"preferred":false,"id":808687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collart, Tim","contributorId":248240,"corporation":false,"usgs":false,"family":"Collart","given":"Tim","email":"","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":808648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moernaut, J.","contributorId":238170,"corporation":false,"usgs":false,"family":"Moernaut","given":"J.","affiliations":[{"id":47707,"text":"Institute of Geology, University of Innsbruck, Austria","active":true,"usgs":false}],"preferred":false,"id":808649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandekerkhove, Elke 0000-0002-6184-2709","orcid":"https://orcid.org/0000-0002-6184-2709","contributorId":248243,"corporation":false,"usgs":false,"family":"Vandekerkhove","given":"Elke","email":"","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":808650,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kempf, P.","contributorId":248246,"corporation":false,"usgs":false,"family":"Kempf","given":"P.","email":"","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":808651,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":808652,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"De Batist, M.","contributorId":248249,"corporation":false,"usgs":false,"family":"De Batist","given":"M.","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":808653,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70208124,"text":"70208124 - 2020 - Dermal denticle assemblages in coral reef sediments correlate with conventional shark surveys","interactions":[],"lastModifiedDate":"2020-03-11T14:31:21","indexId":"70208124","displayToPublicDate":"2020-01-04T15:55:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Dermal denticle assemblages in coral reef sediments correlate with conventional shark surveys","docAbstract":"1. It is challenging to assess long-term trends in mobile, long-lived, and relatively rare species such as sharks. Despite ongoing declines in many coastal shark populations, conventional surveys might be too fleeting and too recent to describe population trends over decades to millennia. Placing recent shark declines into historical context should improve management efforts as well as our understanding of past ecosystem dynamics.
2. A new paleoecological approach for surveying shark abundance on coral reefs is to quantify dermal denticle assemblages preserved in sediments. This approach assumes that denticle accumulation rates correlate with shark abundances. Here, we test this assumption by comparing the denticle record in surface sediments to three conventional shark survey methods at Palmyra Atoll, Line Islands, central Pacific Ocean, where shark density is high and spatially heterogeneous.
3. We generally found a significant positive correlation between denticle accumulation rates and shark abundances derived from underwater visual census, baited remote underwater video, and hook and line surveys.
4. Denticle accumulation rates reflected shark abundances, suggesting that denticle assemblages can preserve a signal of time-averaged shark abundance in low-energy coral reef environments. We offer suggestions for applying this tool to measure shark abundance over long timescales in other contexts.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13346","usgsCitation":"Dillon, E.M., Lafferty, K.D., McCauley, D.J., Bradley, D., Norris, R.D., Caselle, J.E., DiRenzo, G.V., Gardner, J.P., and O’Dea, A., 2020, Dermal denticle assemblages in coral reef sediments correlate with conventional shark surveys: Methods in Ecology and Evolution, v. 11, no. 3, p. 362-375, https://doi.org/10.1111/2041-210X.13346.","productDescription":"14 p.","startPage":"362","endPage":"375","ipdsId":"IP-113704","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458233,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13346","text":"Publisher Index Page"},{"id":371661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Palmyra Atoll Fish and Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.17605590820312,\n 5.840763926791161\n ],\n [\n -161.97898864746094,\n 5.840763926791161\n ],\n [\n -161.97898864746094,\n 5.919995673041826\n ],\n [\n -162.17605590820312,\n 5.919995673041826\n ],\n [\n -162.17605590820312,\n 5.840763926791161\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Dillon, Erin M.","contributorId":221878,"corporation":false,"usgs":false,"family":"Dillon","given":"Erin","email":"","middleInitial":"M.","affiliations":[{"id":34029,"text":"U.C. 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San Diego","active":true,"usgs":false}],"preferred":false,"id":780611,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caselle, Jennifer E.","contributorId":127450,"corporation":false,"usgs":false,"family":"Caselle","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":780612,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DiRenzo, Graziella V.","contributorId":192177,"corporation":false,"usgs":false,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":780613,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gardner, Jonathan P.A.","contributorId":221882,"corporation":false,"usgs":false,"family":"Gardner","given":"Jonathan","email":"","middleInitial":"P.A.","affiliations":[{"id":40453,"text":"Victoria University, NZ","active":true,"usgs":false}],"preferred":false,"id":780614,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"O’Dea, Aaron","contributorId":174330,"corporation":false,"usgs":false,"family":"O’Dea","given":"Aaron","email":"","affiliations":[{"id":27419,"text":"Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Balboa, Republic of Panama","active":true,"usgs":false}],"preferred":false,"id":780615,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70216735,"text":"70216735 - 2020 - Wetland water-management may influence mercury bioaccumulation in songbirds and ducks at a mercury hotspot","interactions":[],"lastModifiedDate":"2020-12-03T14:02:51.380232","indexId":"70216735","displayToPublicDate":"2020-01-04T08:00:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Wetland water-management may influence mercury bioaccumulation in songbirds and ducks at a mercury hotspot","docAbstract":"Mercury is a persistent, biomagnifying contaminant that can cause negative behavioral, immunological, and reproductive effects in wildlife and human populations. We examined the role of wetland water-management on mercury bioaccumulation in songbirds and ducks at Kellys Slough National Wildlife Refuge Complex, near Grand Forks, North Dakota USA. We assessed mercury concentrations in blood of wetland-foraging songbirds (80 common yellowthroats [Geothlypis trichas] and 14 Nelson’s sparrows [Ammospiza nelsoni]) and eggs of upland-nesting ducks (28 gadwall [Mareca strepera], 19 blue-winged teal [Spatula discors], and 13 northern shoveler [S. clypeta]) across four wetland water-management classifications. Nelson’s sparrow blood mercury concentrations were elevated (mean: 1.00 µg/g ww; 95% CL: 0.76–1.31) and similar to those reported 6 years previously. Mercury in songbird blood and duck eggs varied among wetland water-management classifications. Songbirds and ducks had 67% and 49% lower mercury concentrations, respectively, when occupying wetlands that were drawn down with water flow compared to individuals occupying isolated-depressional wetlands with no outflow. Additionally, songbirds within impounded and partially drawn-down wetland units with water flow had mercury concentrations that were 26–28% lower, respectively, than individuals within isolated-depressional wetlands with no outflow. Our results confirm that mercury concentrations in songbirds at Kellys Slough continue to be elevated and suggest that water-management could be an important tool for wetland managers to reduce bioaccumulation of mercury in birds.
A common idea in the discussion of soil carbon processes is that litter decomposition rates and soil carbon stocks are inversely related. To test this overall hypothesis, simultaneous studies were conducted of the relationship of environmental gradients to leaf and wood decomposition, buried cloth decomposition and percent soil organic matter in Taxodium distichum swamps across the Mississippi River Alluvial Valley (MRAV) and northern Gulf of Mexico (GOM) of the US. Decomposition of leaf tissue was 6.2 to 10.9 times faster than wood tissue. Both precipitation and flooding gradients were negatively related to leaf and wood litter decomposition rates based on models developed using Stepwise General Model Selection (MRAV vs. GOM, respectively). Cotton cloth should not be used as a proxy for plant litter without prior testing because cloth responded differently than plant litter to regional environmental gradients in T. distichum swamps. The overall hypothesis was supported in the MRAV because environments with higher precipitation (climate normal) had lower rates of decomposition and higher percent soil organic matter. In the MRAV, higher levels of percent soil organic matter were related to increased 30-year climate normals (30 year averages of precipitation and air temperature comprising southward increasing PrinComp1). Soil organic carbon % in inland vs. coastal T. distichum forests of the MRAV were comparable (range = 1.5% to 26.9% vs. 9.8 to 31.5%, respectively). GOM swamps had lower rates of litter decomposition in more flooded environments. Woody T. distichum detritus had a half-life of up to 300 years in the MRAV, which points to its likely role in the maintenance of inland “teal” soil organic carbon. This unique study can contribute to the discussion of approaches to maintain environments conducive to soil carbon stock maximization.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0226998","usgsCitation":"Middleton, B.A., 2020, Trends of litter decomposition and soil organic matter stocks across forested swamp environments of the southeastern US: PLoS ONE, v. 15, no. 1, e0226998, 23 p., https://doi.org/10.1371/journal.pone.0226998.","productDescription":"e0226998, 23 p.","ipdsId":"IP-085013","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":458237,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0226998","text":"Publisher Index Page"},{"id":371401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Florida, Illinois, Louisiana, Mississippi, Missouri, Texas","otherGeospatial":"Mississippi River Alluvial Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.24218749999999,\n 37.78808138412046\n ],\n [\n -90.17578124999999,\n 37.055177106660814\n ],\n [\n -91.7578125,\n 34.52466147177172\n ],\n [\n -92.5048828125,\n 30.977609093348686\n ],\n [\n -90.2197265625,\n 28.65203063036226\n ],\n [\n -88.9013671875,\n 29.036960648558267\n ],\n [\n -89.20898437499999,\n 29.84064389983441\n ],\n [\n -91.01074218749999,\n 31.203404950917395\n ],\n [\n -88.06640625,\n 37.055177106660814\n ],\n [\n -88.24218749999999,\n 37.78808138412046\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.15234375,\n 29.38217507514529\n ],\n [\n -93.8232421875,\n 29.38217507514529\n ],\n [\n -93.8232421875,\n 31.240985378021307\n ],\n [\n -96.15234375,\n 31.240985378021307\n ],\n [\n -96.15234375,\n 29.38217507514529\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.814453125,\n 29.458731185355344\n ],\n [\n -83.583984375,\n 29.458731185355344\n ],\n [\n -83.583984375,\n 30.56226095049944\n ],\n [\n -84.814453125,\n 30.56226095049944\n ],\n [\n -84.814453125,\n 29.458731185355344\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth A. 0000-0002-1220-2326 middletonb@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":2029,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","email":"middletonb@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":779850,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70208716,"text":"70208716 - 2020 - Formation and prevention of pipe scale from acid mine drainage at Iron Mountain and Leviathan Mines, California, USA","interactions":[],"lastModifiedDate":"2020-02-25T15:17:36","indexId":"70208716","displayToPublicDate":"2020-01-03T15:14:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Formation and prevention of pipe scale from acid mine drainage at Iron Mountain and Leviathan Mines, California, USA","docAbstract":"Pipelines carrying acid mine drainage (AMD) to treatment plants commonly form pipe scale, an Fe(III)-rich precipitate that forms inside the pipelines and requires periodic and costly cleanout and maintenance. Pipelines at Iron Mountain Mine (IMM) and Leviathan Mine (LM) in California carry acidic water from mine sources to a treatment plant and have developed pipe scale. Samples of scale and AMD were collected from both mine sites for mineralogical, microbiological, and chemical analysis. The scale mineralogy was primarily schwertmannite with minor amounts of poorly crystalline goethite. Although the bulk composition of the scale was similar along the length of the pipeline at IMM, the number of iron-oxidizing bacteria and concentrations of associated trace elements decreased along the flow-path inside the pipeline. Laboratory batch experiments with unfiltered AMD from IMM and LM showed that Fe(II) oxidation was driven by microbial activity when the pH was <5. A remediation strategy of decreasing the pH to <2.2 was tested through geochemical modeling and laboratory experiments. These experiments indicated that scale formation could be prevented by decreasing the pH, which could be achieved at IMM by mixing source waters. However, the presence of Fe(III)-rich scale in a pipeline buffers the pH to higher values that may affect the efficacy of this remedial approach.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2020.104521","usgsCitation":"Campbell, K.M., Alpers, C.N., and Nordstrom, D.K., 2020, Formation and prevention of pipe scale from acid mine drainage at Iron Mountain and Leviathan Mines, California, USA: Applied Geochemistry, v. 115, 104521, 14 p. , https://doi.org/10.1016/j.apgeochem.2020.104521.","productDescription":"104521, 14 p. ","ipdsId":"IP-105776","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":458240,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2020.104521","text":"Publisher Index Page"},{"id":372639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Iron Mountain and Leviathan Mines","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.10455322265625,\n 40.065460682065535\n ],\n [\n -122.53875732421875,\n 40.065460682065535\n ],\n [\n -122.53875732421875,\n 40.6723059714534\n ],\n [\n -123.10455322265625,\n 40.6723059714534\n ],\n [\n -123.10455322265625,\n 40.065460682065535\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.16296386718749,\n 38.03078569382294\n ],\n [\n -118.9215087890625,\n 38.03078569382294\n ],\n [\n -118.9215087890625,\n 38.6897975322717\n ],\n [\n -120.16296386718749,\n 38.6897975322717\n ],\n [\n -120.16296386718749,\n 38.03078569382294\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"115","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":783148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":783150,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211922,"text":"70211922 - 2020 - Estimating bedload from suspended load and water discharge in sand bed rivers","interactions":[],"lastModifiedDate":"2020-08-11T20:13:57.981854","indexId":"70211922","displayToPublicDate":"2020-01-03T15:10:09","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimating bedload from suspended load and water discharge in sand bed rivers","docAbstract":"Estimates of fluvial sediment discharge from in situ instruments are an important component of large‐scale sediment budgets that track long‐term geomorphic change. Suspended sediment load can be reliably estimated using acoustic or physical sampling techniques; however, bedload is difficult to measure directly and can consequently be one of the largest sources of uncertainty in estimates of total load. We propose a physically informed predictive empirical model for bedload sand flux as a function of variables that are measured using existing acoustic or physical sampling techniques. This model depends on the assumption that concentration and grain size in suspension are in equilibrium with reach‐averaged boundary conditions. Bayesian inference is used to fit model parameters to data from eight sand‐bed rivers and to simulate bedload flux over the available gage record at one site on the Colorado River in Grand Canyon National Park. We find that the cumulative bedload flux during the 9 year period from 2008 to 2016 was 5% of the cumulative suspended sand load; however, instantaneous bedload flux ranged from as little as 1% of instantaneous suspended sand load to as much as 75% of instantaneous suspended sand load due to fluctuations in flow strength and sediment supply. Changes in bedload flux at a constant discharge are indicative of short‐term sediment supply enrichment and depletion. Long‐term average bedload flux cannot be expected to remain constant in the future as the river adjusts to changes in sediment runoff and the dam‐regulated discharge regime.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR025883","usgsCitation":"Ashley, T., McElroy, B., Buscombe, D., Grams, P.E., and Kaplinski, M., 2020, Estimating bedload from suspended load and water discharge in sand bed rivers: Water Resources Research, v. 56, no. 2, e2019WR025883, 25 p., https://doi.org/10.1029/2019WR025883.","productDescription":"e2019WR025883, 25 p.","ipdsId":"IP-108262","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":458242,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/essoar.10503756.1","text":"External Repository"},{"id":377386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.005126953125,\n 35.71083783530009\n ],\n [\n -111.37390136718749,\n 35.71083783530009\n ],\n [\n -111.37390136718749,\n 36.92793899776678\n ],\n [\n -114.005126953125,\n 36.92793899776678\n ],\n [\n -114.005126953125,\n 35.71083783530009\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Ashley, T.C.","contributorId":238017,"corporation":false,"usgs":false,"family":"Ashley","given":"T.C.","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":795824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McElroy, B.","contributorId":23797,"corporation":false,"usgs":true,"family":"McElroy","given":"B.","email":"","affiliations":[],"preferred":false,"id":795825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buscombe, D.","contributorId":44020,"corporation":false,"usgs":true,"family":"Buscombe","given":"D.","email":"","affiliations":[],"preferred":false,"id":795826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":795827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaplinski, M.","contributorId":31576,"corporation":false,"usgs":true,"family":"Kaplinski","given":"M.","email":"","affiliations":[],"preferred":false,"id":795828,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207677,"text":"fs20193067 - 2020 - U.S. Geological Survey Earthquake Science Center","interactions":[],"lastModifiedDate":"2022-10-31T14:12:08.267675","indexId":"fs20193067","displayToPublicDate":"2020-01-03T11:51:24","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3067","displayTitle":"U.S. Geological Survey Earthquake Science Center","title":"U.S. Geological Survey Earthquake Science Center","docAbstract":"The mission of the U.S. Geological Survey (USGS) Earthquake Science Center is to collect a wide range of data on earthquakes, faults, and crustal deformation; conduct research to increase our understanding of earthquake source processes, occurrence, and effects; and synthesize this knowledge into probabilistic seismic hazard assessments, aftershock forecasts, and ground-shaking scenarios for anticipated major earthquakes. We disseminate these data products, hazard assessments, and research discoveries to scientists, engineers, emergency managers, and the public.
With university and State partners, we operate the California Integrated Seismic Network and the Pacific Northwest Seismic Network, as well as geodetic networks throughout the western United States. We also lead the National Strong Motion Project and the ShakeAlert earthquake early warning (EEW) system; house renowned rock mechanics laboratories and deep borehole geophysics facilities; and conduct extensive geophysical, geologic, and paleoseismic investigations along active faults. We are funded primarily by the USGS Earthquake Hazards Program, with additional support from the USGS Volcano Hazards and Energy Resources Programs, other Federal and State agencies, private foundations, and public and private utilities and corporations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193067","usgsCitation":"This publication is available at https://pubs.er.usgs.gov/publication/fs20193067. 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Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, California 94025
Observations from ground-penetrating radar, sediment cores, elevation surveys and aerial imagery are used to understand the development of the Elwha River delta in north-western Washington, USA, which prograded as a result of two dam removals in late 2011. Swash-bar, foreshore and swale depositional elements are recognized within ground-penetrating radar profiles and sediment cores. A model for the growth and development of small mountainous river wave-dominated deltas is proposed based on observation of both the fluvial and deltaic settings. If enough sediment is available in the fluvial system, mouth-bars form after higher than average river discharge events, creating a large platform seaward of the subaqueous delta plain. Swash-bars form concurrently or within a month of mouth-bar deposition as a result of wave action. Fair-weather waves drive swash-bar migration landward and in the direction of littoral drift. The signature of swash-bar welding to the shoreline is landward-dipping reflections, as a result of overwash processes and slipface migration. However, most swash-bars are eroded by the river mouth, as only 10 of the 37 swash-bars that formed between August 2011 and July 2016 survived within the Elwha River delta. The swash-bars that do survive either amalgamate onto the shoreline or an earlier deposited swash-bar, forming a single larger barrier at the delta front. In asymmetrical deltas, the signature of swash-bar welding is more likely to be preserved on the downdrift side of the delta, where formation is more likely and accommodation behind newer swash-bars preserves older deposits. On small mountainous river deltas, welded swash-bars may be more indicative of a large sediment pulse to the system, rather than large hydrological events.
","language":"English","publisher":"Wiley","doi":"10.1111/sed.12702","usgsCitation":"Zurbuchen, J., Simms, A., Warrick, J.A., Miller, I.M., and Ritchie, A., 2020, A model for the growth and development of wave-dominated deltas fed by small mountainous rivers: Insights from the Elwha River delta, Washington: Sedimentology, v. 67, no. 5, p. 2310-2331, https://doi.org/10.1111/sed.12702.","productDescription":"22 p.","startPage":"2310","endPage":"2331","ipdsId":"IP-091098","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/sed.12702","text":"Publisher Index Page"},{"id":483949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.53500604047304,\n 48.153518237078885\n ],\n [\n -123.57618620014911,\n 48.153518237078885\n ],\n [\n -123.57618620014911,\n 48.12519411609762\n ],\n [\n -123.53500604047304,\n 48.12519411609762\n ],\n [\n -123.53500604047304,\n 48.153518237078885\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"67","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Zurbuchen, Julie","contributorId":352837,"corporation":false,"usgs":false,"family":"Zurbuchen","given":"Julie","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":932190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simms, Alexander R.","contributorId":352838,"corporation":false,"usgs":false,"family":"Simms","given":"Alexander R.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":932191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":932193,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ritchie, Andrew C. 0000-0001-5826-9983","orcid":"https://orcid.org/0000-0001-5826-9983","contributorId":333630,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932194,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227661,"text":"70227661 - 2020 - A comparison of Grass Carp population characteristics upstream and downstream of Lock and Dam 19 of the Upper Mississippi River","interactions":[],"lastModifiedDate":"2022-01-25T12:53:00.932275","indexId":"70227661","displayToPublicDate":"2020-01-03T06:48:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of Grass Carp population characteristics upstream and downstream of Lock and Dam 19 of the Upper Mississippi River","docAbstract":"Grass Carp Ctenopharyngodon idella have been intentionally stocked for aquatic vegetation control across the Midwestern United States for several decades. During the 1970s, escapement of Grass Carp into the Missouri River facilitated their naturalization into much of the Mississippi River basin, including the Upper Mississippi River. Lock and Dam 19 (LD19) in Keokuk, Iowa, is a high-head dam that represents a focal point for naturalized Grass Carp management where populations may differ between upstream and downstream pools as result of limited upstream migration, but potential differences between populations have yet to be evaluated to the best of our knowledge. The objective of this study was to compare the relative abundance, size structure, condition, growth, and recruitment variability of Grass Carp collected upstream and downstream of LD19. We sampled Grass Carp monthly (April–October) during 2014 and 2015 from four locations in the Des Moines River (downstream of LD19) and five locations throughout the Skunk, Iowa, and Cedar rivers (upstream of LD19) using boat electrofishing and trammel net sets. We captured 29 Grass Carp upstream of LD19 compared with 179 individuals captured downstream. Trammel nets only captured Grass Carp downstream of LD19; trammel net catch per unit effort upstream of LD19 was low and ranged from 0.0 to 8.0 fish/net lift (mean ± SE = 0.39 ± 0.13). Electrofishing catch per unit effort ranged from 0.0 to 22.7 fish/h (1.49 ± 0.30) and was higher downstream (2.42 ± 0.30) of LD19 than upstream (0.57 ± 0.07). Grass Carp downstream of LD19 tended to be smaller, younger, of lower body condition, had higher mortality rates, and were slower growing compared with those collected upstream and to populations documented in other systems. Understanding and monitoring adult Grass Carp population characteristics upstream and downstream of LD19 is necessary to determine how they may change in response to ongoing harvest efforts for invasive carps in these river reaches.
Limited evidence for spatial patterns of denitrification in tidal freshwater forested wetlands (TFFWs), seemingly due to high spatial variability in the process, is surprising considering the various spatial gradients of its biogeochemical and hydrogeomorphic controls in these ecosystems. Because certain physical environmental gradients may be useful for the prediction of denitrification in TFFWs, we measured denitrification and ecosystem attributes in hummock-hollow microtopography of TFFWs along longitudinal riverine positions (upper, middle, and lower tidal river sites, and nearby upstream nontidal forested floodplains) of the adjoining Pamunkey and Mattaponi Rivers, Virginia. We tested differences by river, site, and plot in denitrification enzyme activity (DEA) and substrate limitations of denitrification potential (DP). The Pamunkey River carries greater river nitrate concentrations, and we found less nitrate limitation of DP and greater soil nitrate in hollows of this river. DEA in tidal hummocks was positively correlated with soil organic matter, nitrogen, and carbon, with the highest rates in lower tidal sites. Hummocks also promoted greater oxygen-controlled substrate limitation of DP, whereby experimental aeration stimulated DP under subsequent inundation more in hummocks than hollows. Additionally, tidal sites had greater DEA than nontidal sites, inferred to be caused by a combination of higher moisture, organic, and nutrient content. Our results indicate that the increasing nitrogen concentrations in these rivers will increase denitrification more on the Mattaponi River by alleviating its greater nitrogen limitation compared to the Pamunkey River, and modification to sedimentation, inundation, or microtopography from sea level rise may alter denitrification gradients in TFFWs and upstream low-elevation nontidal floodplains.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-019-00663-6","usgsCitation":"Korol, A.R., and Noe, G.E., 2020, Patterns of denitrification potential in tidal freshwater forested wetlands, v. 43, no. 2, p. 329-346, https://doi.org/10.1007/s12237-019-00663-6.","productDescription":"18 p.","startPage":"329","endPage":"346","ipdsId":"IP-103254","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":372341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Mattaponi River, Pamunkey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.31903076171875,\n 37.44106442458557\n ],\n [\n -76.76010131835938,\n 37.44106442458557\n ],\n [\n -76.76010131835938,\n 37.86943313301452\n ],\n [\n -77.31903076171875,\n 37.86943313301452\n ],\n [\n -77.31903076171875,\n 37.44106442458557\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Korol, Alicia R.","contributorId":174405,"corporation":false,"usgs":false,"family":"Korol","given":"Alicia","email":"","middleInitial":"R.","affiliations":[{"id":27449,"text":"Department of Environmental Science and Policy, George Mason University, 4400 University Drive, Fairfax, VA, 22030","active":true,"usgs":false}],"preferred":false,"id":782341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":782340,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210786,"text":"70210786 - 2020 - Observations on the May 2019 Joffre Peak landslides, British Columbia","interactions":[],"lastModifiedDate":"2020-06-25T14:39:44.613134","indexId":"70210786","displayToPublicDate":"2020-01-02T09:33:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Observations on the May 2019 Joffre Peak landslides, British Columbia","docAbstract":"Two catastrophic landslides occurred in quick succession on 13 and 16 May 2019, from the north face of Joffre Peak, Cerise Creek, southern Coast Mountains, British Columbia. With headscarps at 2560 m and 2690 m elevation, both began as rock avalanches, rapidly transforming into debris flows along middle Cerise Creek, and finally into debris floods affecting the fan. Beyond the fan margin, a flood surge on Cayoosh Creek reached bankfull and attenuated rapidly downstream; only fine sediment reached Duffey Lake. The toe of the main debris flow deposit reached 4 km from the headscarp, with a travel angle of 0.28; while the debris flood phase reached the fan margin 5.9 km downstream, with a travel angle of 0.22. Photogrammetry indicates the source volume of each event is 2-3 Mm3, with combined volume of 5 Mm3. Lidar differencing, used to assess deposit volume, yielded a similar total result; although error in the depth estimate introduced large error and masks expected increase due to dilation and entrainment. The average velocity of the rock avalanche-debris flow phases, from seismic analysis, was ~25-30 m/s, and the velocity of the 16 May debris flood on the upper fan, from super-elevation and boulder sizes, was 5-10 m/s. The volume of debris deposited on the fan was ~104 m3, 2-orders of magnitude less than the avalanche/debris flow phases. The 13 May landslide was apparently triggered by rapid snowmelt; with debuttressing triggering the 16 May event. While spring 2019 was warm, it wasn’t unusual. It is likely that progressive glacier retreat and permafrost degradation were the conditioning factors; precursor activity was noted at least 1 yr previous; thus, the mountain was primed to fail and average seasonal snowmelt tipped the balance.","language":"English","publisher":"Springer","doi":"10.1007/s10346-019-01332-2","usgsCitation":"Friele, P., Millard, T., Mitchell, A., Allstadt, K.E., Menounos, B., Geertsema, M., and Clague, J.J., 2020, Observations on the May 2019 Joffre Peak landslides, British Columbia: Landslides, v. 17, p. 913-930, https://doi.org/10.1007/s10346-019-01332-2.","productDescription":"18 p.","startPage":"913","endPage":"930","ipdsId":"IP-113348","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":458247,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10346-019-01332-2","text":"Publisher Index Page"},{"id":375915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"British Columbia","otherGeospatial":"Joffre Peak","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.51678466796874,\n 50.31828499756704\n ],\n [\n -122.37945556640624,\n 50.31828499756704\n ],\n [\n -122.37945556640624,\n 50.38181606585463\n ],\n [\n -122.51678466796874,\n 50.38181606585463\n ],\n [\n -122.51678466796874,\n 50.31828499756704\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Friele, Pierre","contributorId":225511,"corporation":false,"usgs":false,"family":"Friele","given":"Pierre","email":"","affiliations":[{"id":41151,"text":"Cordilleran Geoscience","active":true,"usgs":false}],"preferred":false,"id":791407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Millard, Tom","contributorId":225512,"corporation":false,"usgs":false,"family":"Millard","given":"Tom","email":"","affiliations":[{"id":41152,"text":"BC Ministry of Forests Lands Natural Resource Operations and Rural Development (BC FLNRORD), Nanaimo, BC","active":true,"usgs":false}],"preferred":false,"id":791408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, Andrew","contributorId":225513,"corporation":false,"usgs":false,"family":"Mitchell","given":"Andrew","email":"","affiliations":[{"id":41153,"text":"Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":791409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":791410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Menounos, Brian","contributorId":225514,"corporation":false,"usgs":false,"family":"Menounos","given":"Brian","email":"","affiliations":[{"id":41154,"text":"Geography Program and Natural Resources and Environmental Studies Institute, University of Northern British Columbia","active":true,"usgs":false}],"preferred":false,"id":791411,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Geertsema, Marten","contributorId":197464,"corporation":false,"usgs":false,"family":"Geertsema","given":"Marten","email":"","affiliations":[],"preferred":false,"id":791412,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clague, John J.","contributorId":191448,"corporation":false,"usgs":false,"family":"Clague","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":791413,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209596,"text":"70209596 - 2020 - Early goose arrival increases soil nitrogen availability more than an advancing spring in coastal western Alaska","interactions":[],"lastModifiedDate":"2020-09-23T15:39:16.635611","indexId":"70209596","displayToPublicDate":"2020-01-02T07:37:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Early goose arrival increases soil nitrogen availability more than an advancing spring in coastal western Alaska","docAbstract":"An understudied aspect of climate change-induced phenological mismatch is its effect on ecosystem functioning, such as nitrogen (N) cycling. Migratory herbivore arrival time may alter N inputs and plant–herbivore feedbacks, whereas earlier springs are predicted to increase N cycling rates through warmer temperatures. However, the relative importance of these shifts in timing and how they interact to affect N cycling are largely unknown. We conducted a 3-year factorial experiment in coastal western Alaska that simulated different timings of Pacific black brant (Branta bernicla nigricans) arrival (3 weeks early, typical, 3 weeks late, or no-grazing) and the growing season (ca. 3 weeks advanced and ambient) on adsorbed and mobile inorganic (NH4+–N, NO3−–N) and mobile organic N (amino acid) pools. Early grazing increased NH4+–N, NO3−–N, and amino acids by 103%, 119%, and 7%, respectively, whereas late grazing reduced adsorbed NH4+–N and NO3−–N by 16% and 17%, respectively. In comparison, the advanced growing season increased mobile NH4+–N by 26%. The arrival time by geese and the start of the season did not interact to influence soil N availability. While the onset of spring in our system is advancing at twice the rate of migratory goose arrival, earlier goose migration is likely to be more significant than the advances in springs in influencing soil N, although both early goose arrival and advanced springs are likely to increase N availability in the future. This increase in soil N resources can have a lasting impact on plant community composition and productivity in this N-limited ecosystem.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-019-00472-9","usgsCitation":"Choi, R.T., Beard, K.H., Kelsey, K., Leffler, J., Schmutz, J.A., and Welker, J., 2020, Early goose arrival increases soil nitrogen availability more than an advancing spring in coastal western Alaska: Ecosystems, v. 23, p. 1309-1324, https://doi.org/10.1007/s10021-019-00472-9.","productDescription":"26 p.","startPage":"1309","endPage":"1324","ipdsId":"IP-110431","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":374005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Coastal western Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.37890625,\n 70.61261423801925\n ],\n [\n -162.59765625,\n 70.4367988185464\n ],\n [\n -166.81640625,\n 68.84766505841037\n ],\n [\n -167.6953125,\n 66.51326044311185\n ],\n [\n -167.87109375,\n 64.01449619484472\n ],\n [\n -166.81640625,\n 61.60639637138628\n ],\n [\n -166.11328125,\n 59.62332522313024\n ],\n [\n -160.83984375,\n 57.98480801923985\n ],\n [\n -167.87109375,\n 54.059387886623576\n ],\n [\n -166.9921875,\n 52.696361078274485\n ],\n [\n -151.171875,\n 56.07203547180089\n ],\n [\n -154.3359375,\n 59.712097173322924\n ],\n [\n -158.37890625,\n 70.61261423801925\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Choi, Ryan T.","contributorId":205936,"corporation":false,"usgs":false,"family":"Choi","given":"Ryan","email":"","middleInitial":"T.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":787056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beard, Karen H.","contributorId":205934,"corporation":false,"usgs":false,"family":"Beard","given":"Karen","email":"","middleInitial":"H.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":787057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelsey, Katherine","contributorId":224102,"corporation":false,"usgs":false,"family":"Kelsey","given":"Katherine","email":"","affiliations":[{"id":37194,"text":"University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":787059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leffler, Joshua","contributorId":224101,"corporation":false,"usgs":false,"family":"Leffler","given":"Joshua","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":787058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@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":787060,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Welker, Jeffrey","contributorId":214926,"corporation":false,"usgs":false,"family":"Welker","given":"Jeffrey","affiliations":[{"id":37194,"text":"University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":787061,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70260098,"text":"70260098 - 2020 - Goals and development of the Alaska Volcano Observatory Seismic Network and application to forecasting and detecting volcanic eruptions","interactions":[],"lastModifiedDate":"2024-10-30T22:23:31.538975","indexId":"70260098","displayToPublicDate":"2020-01-02T07:06:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Goals and development of the Alaska Volcano Observatory Seismic Network and application to forecasting and detecting volcanic eruptions","docAbstract":"The Alaska Volcano Observatory (AVO) seismic network has been in operation since 1988 and during this time has grown from 29 to 217 seismic stations providing real-time monitoring of 32 active volcanoes in Alaska, as well as useful data for regional earthquake monitoring. Since 1988, AVO has detected 59 volcanic eruptions at Aleutian arc volcanoes, and 31 of these have been captured by local seismic instrumentation. As part of this monitoring effort, AVO has cataloged more than 120,000 earthquake hypocenters and magnitudes associated with volcanic processes throughout the arc. This high rate of volcanic activity provides an excellent opportunity to study seismicity associated with magmatic and eruptive processes and develop and refine analytical techniques to track volcanic seismicity and warn of hazardous eruptions. The network is currently undergoing an extensive upgrade, replacing aging short-period analog seismometers with digital broadband instruments. These are expected to improve AVO’s seismic capability and further facilitate other geophysical instrumentation such as continuous Global Positioning System receivers, infrasound sensors, and web cams.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190216","usgsCitation":"Power, J., Haney, M.M., Botnick, S.M., Dixon, J.P., Fee, D., Kaufman, M., Ketner, D.M., Lyons, J.J., Parker, T., Paskievitch, J.F., Read, C., Searcy, C., Stihler, S.D., Tepp, G., and Wech, A., 2020, Goals and development of the Alaska Volcano Observatory Seismic Network and application to forecasting and detecting volcanic eruptions: Seismological Research Letters, v. 91, no. 2A, p. 647-659, https://doi.org/10.1785/0220190216.","productDescription":"13 p.","startPage":"647","endPage":"659","ipdsId":"IP-111065","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463242,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"2A","noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Power, John 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To assess potential impacts of climate change on carbonate production in the open ocean, we measured size and weight of planktic foraminifers during the late Pliocene at pCO2atm concentrations comparable to today and global temperatures 2 to 3 °C warmer. Size of all foraminifers was measured at Atlantic Ocean Deep Sea Drilling Project (DSDP) Site 610, Ocean Drilling Program (ODP) Site 999, and Integrated Ocean Drilling Program (IODP) Site U1313. Test size was smaller during the Pliocene than in modern assemblages under the same environmental conditions. During the cold marine isotope stage (MIS) M2, size increased at Site 999, potentially linked to intensified stratification of the surface ocean in response to the closure of the Central American Seaway. At Site U1313, test size tracks the warming throughout the late Pliocene. Size-normalized weight (SNW) of Globigerina bulloides at Site U1313 decreased during warmer temperature intervals. SNW of Globigerinoides ruber (white) at Site 999 displays high-frequency variability not correlated to temperature. Yet during the glacial period within MIS M2, test weight was higher during higher temperatures. Our results support studies in the modern ocean, which challenge the view that carbonate chemistry is the primary driver for calcification. To better understand processes driving changes in SNW, computer tomography was used to quantify calcite to volume ratios. During interglacial periods, lower calcite volume but higher test volume suggests less suitable conditions for calcification. As this signal is not evident in SNW, subtle changes in calcification might not be observed by the weight-based method.
Pacific capelin Mallotus catervarius are planktivorous, small pelagic fish that serve an intermediate trophic role in marine food webs. Due to the lack of a directed fishery or monitoring of capelin in the Northeast Pacific, there is limited information on their distribution and abundance, and how spatio-temporal fluctuations in capelin density affects their availability as prey. To provide information on life history, spatial patterns, and population dynamics of capelin in the Gulf of Alaska (GOA), we modeled distributions of spawning habitat and larval dispersal, and synthesized spatially-indexed data from multiple, independent sources from 1996 to 2016. Potential capelin spawning areas were broadly distributed across the GOA. Models of larval drift show the GOA’s advective circulation patterns disperse capelin larvae over the continental shelf and upper slope, indicating potential connections between spawning areas and observed offshore distributions that are influenced by the location and timing of spawning. Spatial overlap in composite distributions of larval and age-1+ fish was used to identify core areas where capelin consistently occur and concentrate. Capelin primarily occupy shelf waters near the Kodiak Archipelago, and are patchily distributed across the GOA shelf and inshore waters. Interannual variations in abundance along with spatio-temporal differences in density indicates the availability of capelin to predators and monitoring surveys is highly variable in the GOA. We demonstrate that the limitations of individual data series can be compensated for by integrating multiple data sources to monitor fluctuations in distributions and abundance trends of an ecologically important species across a large marine ecosystem.
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