{"pageNumber":"687","pageRowStart":"17150","pageSize":"25","recordCount":184617,"records":[{"id":70263398,"text":"70263398 - 2019 - Comment on “Interpretation of Kappa and fmax  filters as source effect”, by Igor A. Beresnev","interactions":[],"lastModifiedDate":"2025-02-12T16:15:24.114768","indexId":"70263398","displayToPublicDate":"2019-11-12T10:13:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Comment on “Interpretation of Kappa and fmax  filters as source effect”, by Igor A. Beresnev","docAbstract":"Beresnev (2019) advocates the use of an earthquake slip function that produces an ω-2.5 high-frequency falloff of Fourier displacement spectra in the far field, where ω denotes the angular frequency. He argues that the observed high-frequency decay of earthquake spectra can be adequately modeled by this ω-2.5 falloff, without needing to include high frequency attenuation at shallow depth under the site, commonly characterized as fmax or kappa. In his abstract, Beresnev (2019) describes source models with falloffs intermediate between ω-2 and ω-3 as “providing natural high-cut filtering exclusively as a source effect.” In many studies to date, observed spectra are modeled using an ω-2 source spectrum combined with attenuation along the propagation path, including strong attenuation at shallow depths (< 1 km) beneath a site.  It is not clear whether Beresnev (2019) is claiming that path effects (including site attenuation) are unimportant to ground motions or if he is proposing a simple, pragmatic method to fit the high-frequency decay of earthquake spectra.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120190085","usgsCitation":"Frankel, A.D., 2019, Comment on “Interpretation of Kappa and fmax  filters as source effect”, by Igor A. Beresnev: Bulletin of the Seismological Society of America, v. 109, no. 6, p. 2762-2763, https://doi.org/10.1785/0120190085.","productDescription":"2 p.","startPage":"2762","endPage":"2763","ipdsId":"IP-107350","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"109","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926824,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70206715,"text":"70206715 - 2019 - Standardized IMGT nomenclature of salmonidae IGH genes, the paradigm of Atlantic salmon and rainbow trout: From genomics to repertoires","interactions":[],"lastModifiedDate":"2019-11-20T06:20:28","indexId":"70206715","displayToPublicDate":"2019-11-12T07:56:43","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5620,"text":"Frontiers in Immunology","active":true,"publicationSubtype":{"id":10}},"title":"Standardized IMGT nomenclature of salmonidae IGH genes, the paradigm of Atlantic salmon and rainbow trout: From genomics to repertoires","docAbstract":"In teleost fish as in mammals, humoral adaptive immunity is based on B lymphocytes expressing highly diverse immunoglobulins (IG). During B cell differentiation, IG loci are subjected to genomic rearrangements of V, D, and J genes, producing a unique antigen receptor expressed on the surface of each lymphocyte. During the course of an immune response to infections or immunizations, B cell clones specific of epitopes from the immunogen are expanded and activated, leading to production of specific antibodies. Among teleost fish, salmonids comprise key species for aquaculture. Rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar) are especially important from a commercial point of view and have emerged as critical models for fish immunology. The growing interest to capture accurate and comprehensive antibody responses against common pathogens and vaccines has resulted in recent efforts to sequence the IG repertoire in these species. In this context, a unified and standardized nomenclature of salmonid IG heavy chain (IGH) genes is urgently required, to improve accuracy of annotation of adaptive immune receptor repertoire dataset generated by high-throughput sequencing (AIRRseq) and facilitate comparisons between studies and species. Interestingly, the assembly of salmonids IGH genomic sequences is challenging due to the presence of two large size duplicated IGH loci and high numbers of IG genes and pseudogenes. We used data available for Atlantic salmon to establish an IMGT standardized nomenclature of IGH genes in this species and then applied the IMGT rules to the rainbow trout IGH loci to set up a nomenclature, which takes into account the specificities of Salmonid loci. This unique, consistent nomenclature for Salmonid IGH genes was then used to construct IMGT sequence reference directories allowing accurate annotation of AIRRseq data. The complex issues raised by the genetic diversity of salmon and trout strains are discussed in the context of IG repertoire annotation.","language":"English","publisher":"Frontiers","doi":"10.3389/fimmu.2019.02541","usgsCitation":"Magadan, S., Krasnov, A., Hadi-Saljoki, S., Afanasyev, S., Mondot, S., Castro, R., Salinas, I., Sunyer, O., Hansen, J.D., Koop, B.F., Lefranc, M., and Boudinot, P., 2019, Standardized IMGT nomenclature of salmonidae IGH genes, the paradigm of Atlantic salmon and rainbow trout: From genomics to repertoires: Frontiers in Immunology, v. 10, 2541, 16 p., https://doi.org/10.3389/fimmu.2019.02541.","productDescription":"2541, 16 p.","ipdsId":"IP-112719","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":459204,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fimmu.2019.02541","text":"Publisher Index Page"},{"id":369320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Magadan, Susana","contributorId":220717,"corporation":false,"usgs":false,"family":"Magadan","given":"Susana","affiliations":[{"id":40251,"text":"Immunology Laboratory, Biomedical Research Center (CINBIO), University of Vigo, Campus Lagoas Marcosende, Vigo, Spain","active":true,"usgs":false}],"preferred":false,"id":775524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krasnov, Aleksei","contributorId":220718,"corporation":false,"usgs":false,"family":"Krasnov","given":"Aleksei","email":"","affiliations":[{"id":40252,"text":"Nofima AS, Norwegian Institute of Food, Fisheries & Aquaculture Research, Ås, Norway","active":true,"usgs":false}],"preferred":false,"id":775525,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hadi-Saljoki, Saida","contributorId":220719,"corporation":false,"usgs":false,"family":"Hadi-Saljoki","given":"Saida","email":"","affiliations":[{"id":40253,"text":"IMGT, the international ImMunoGeneTics information system (IMGT), Institut de Génétique Humaine, CNRS, University of Montpellier, 34396 Montpellier Cedex 5, France","active":true,"usgs":false}],"preferred":false,"id":775526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Afanasyev, Sergey","contributorId":220720,"corporation":false,"usgs":false,"family":"Afanasyev","given":"Sergey","email":"","affiliations":[{"id":40254,"text":"Sechenov Institute of Evolutionary Physiology and Biochemistry, Saint Petersburg, Russia","active":true,"usgs":false}],"preferred":false,"id":775527,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mondot, Stanislas","contributorId":220721,"corporation":false,"usgs":false,"family":"Mondot","given":"Stanislas","email":"","affiliations":[{"id":40255,"text":"MICALIS, Institut National de la Recherche Agronomique (INRA), Université Paris-Saclay, 78352, Jouy en Josas, France","active":true,"usgs":false}],"preferred":false,"id":775528,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Castro, Rosario","contributorId":220722,"corporation":false,"usgs":false,"family":"Castro","given":"Rosario","email":"","affiliations":[{"id":40256,"text":"Virologie et Immunologie Moleculaires (VIM), Institut National de la Recherche Agronomique (INRA), Universite Paris- Saclay, 78352 Jouy-en-Josas, France","active":true,"usgs":false}],"preferred":false,"id":775529,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Salinas, Irene","contributorId":220723,"corporation":false,"usgs":false,"family":"Salinas","given":"Irene","email":"","affiliations":[{"id":40257,"text":"Department of Biology, Center of Evolutionary and Theoretical Immunology, University of New Mexico, NM, USA","active":true,"usgs":false}],"preferred":false,"id":775530,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sunyer, Oriol","contributorId":220724,"corporation":false,"usgs":false,"family":"Sunyer","given":"Oriol","email":"","affiliations":[{"id":40258,"text":"Pathobiology Department, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, USA","active":true,"usgs":false}],"preferred":false,"id":775531,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hansen, John D. 0000-0002-3006-2734","orcid":"https://orcid.org/0000-0002-3006-2734","contributorId":220725,"corporation":false,"usgs":true,"family":"Hansen","given":"John","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":775532,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Koop, Ben F","contributorId":220726,"corporation":false,"usgs":false,"family":"Koop","given":"Ben","email":"","middleInitial":"F","affiliations":[{"id":40259,"text":"Department of Biology, University of Victoria, Victoria, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":775533,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lefranc, Marie-Paule","contributorId":220727,"corporation":false,"usgs":false,"family":"Lefranc","given":"Marie-Paule","email":"","affiliations":[{"id":40260,"text":"IMGT, the international ImMunoGeneTics information system® (IMGT), Institut de Génétique Humaine, CNRS, University of Montpellier, 34396 Montpellier Cedex 5, France","active":true,"usgs":false}],"preferred":false,"id":775534,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Boudinot, Pierre","contributorId":194698,"corporation":false,"usgs":false,"family":"Boudinot","given":"Pierre","email":"","affiliations":[],"preferred":false,"id":775535,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70206729,"text":"70206729 - 2019 - The importance of natural versus human factors for ecological conditions of streams and rivers","interactions":[],"lastModifiedDate":"2020-01-03T10:36:11","indexId":"70206729","displayToPublicDate":"2019-11-12T07:45:14","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"The importance of natural versus human factors for ecological conditions of streams and rivers","docAbstract":"Streams are influenced by watershed-scale factors, such as climate, geology, topography, hydrology, and soils, which mostly vary naturally among sites, as well as human factors, agriculture and urban development. Thus, natural factors could complicate assessment of human disturbance. In the present study, we use structural equation modeling and data from the 2008-2009 United States National Rivers and Streams Assessment to quantify the relative importance of watershed-scale natural and human factors for in-stream conditions. We hypothesized that biological condition, represented using a diatom multimetric index (MMI), is directly affected by in-stream physicochemical environment, which in turn is regulated by natural and human factors. We evaluated this hypothesis at both national and ecoregion scales to understand how influences vary among regions. We found that direct influences of in-stream environment on diatom MMIs were greater than natural and human factors at the national scale and in all but one ecoregion. Meanwhile, in-stream environments were jointly explained by natural variations in precipitation, base flow index, hydrological stability, % volcanic rock, soil water table depth, and soil depth and by human factors measured as % crops, % other agriculture, and % urban land use. The explained variance of in-stream environment by natural and human factors ranged from 0.30 to 0.75, for which natural factors independently accounted for the largest proportion of explained variance at the national scale and in seven ecoregions. Covariation between natural and human factors accounted for a higher proportion of explained variance of in-stream environment than unique effects of human factors in most ecoregions. Ecoregions with relatively weak effects by human factors had relatively high levels of covariance, high levels of human disturbance, or small ranges in human disturbance. We conclude that accounting for effects of natural factors and their covariation with human factors will be important for accurate ecological assessments.","language":"English","publisher":"Elsevier ","doi":"10.1016/j.scitotenv.2019.135268","usgsCitation":"Tang, T., Stevenson, R.J., and Grace, J., 2019, The importance of natural versus human factors for ecological conditions of streams and rivers: Science of the Total Environment, v. 704, 135268, 13 p., https://doi.org/10.1016/j.scitotenv.2019.135268.","productDescription":"135268, 13 p.","ipdsId":"IP-106891","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":369314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -126.91406249999999,\n              23.885837699862005\n            ],\n            [\n              -67.5,\n              23.885837699862005\n            ],\n            [\n              -67.5,\n              49.38237278700955\n            ],\n            [\n              -126.91406249999999,\n              49.38237278700955\n            ],\n            [\n              -126.91406249999999,\n              23.885837699862005\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"704","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tang, Tao","contributorId":220738,"corporation":false,"usgs":false,"family":"Tang","given":"Tao","email":"","affiliations":[{"id":40263,"text":"State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":775572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevenson, R. Jan","contributorId":139110,"corporation":false,"usgs":false,"family":"Stevenson","given":"R.","email":"","middleInitial":"Jan","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":775573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grace, James 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":220737,"corporation":false,"usgs":true,"family":"Grace","given":"James","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":775571,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70207029,"text":"70207029 - 2019 - Seasonal epilimnetic temperature patterns and trends in a suite of lakes from Wisconsin (USA), Germany and Finland","interactions":[],"lastModifiedDate":"2019-12-03T13:52:41","indexId":"70207029","displayToPublicDate":"2019-11-11T13:49:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal epilimnetic temperature patterns and trends in a suite of lakes from Wisconsin (USA), Germany and Finland","docAbstract":"Epilimnetic temperatures from the early 1980s through 2017 were analyzed for 12 Wisconsin, German and Finnish lakes. Seasonal temperature metrics exhibited large interannual variability with trends differing among regions. In the Wisconsin lakes, only late summer and fall temperatures increased significantly. In the northeastern Germany lakes, temperatures increased in all seasons, but only significantly for some metrics. The Finnish lakes, which spanned the country’s latitude range, exhibited large spring temperature increases influenced by earlier ice-out; summer temperatures also increased significantly, but fall changes were varied. To elucidate longer-term epilimnetic temperature patterns, earlier records from 4 lakes were analyzed. For Lake Mendota (southern Wisconsin), spring and late fall temperatures increased modestly but significantly since 1894; summer temperatures also increased modestly due to a higher frequency of recent summers with warm temperatures and not from new record high temperatures. Trout Lake (northern Wisconsin) exhibited warm temperatures in some summers during the 1930s-1940s similar to warm temperatures in some recent summers. Air-water temperature relationships coupled with long-term regional air temperature data also indicated summer epilimnetic temperatures in the study lakes were likely as warm in the 1930s-1940s as in recent years. Lake data confirmed cooler epilimnetic temperatures occurred in many summers during the 1950s-1980s coincident with intervening cooler air temperatures during this period. Because epilimnetic temperatures have not increased monotonically since 1900, our study supports continued temperature monitoring in lakes with extensive historical data to better understand and project future effects of climate change on lake ecosystems.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/20442041.2019.1637682","usgsCitation":"Lathrop, R.C., Kasprzak, P., Tarvainen, M., Ventela, A., Keskinen, T., Koschel, R., and Robertson, D.M., 2019, Seasonal epilimnetic temperature patterns and trends in a suite of lakes from Wisconsin (USA), Germany and Finland: Inland Waters, v. 9, no. 4, p. 471-488, https://doi.org/10.1080/20442041.2019.1637682.","productDescription":"18 p.","startPage":"471","endPage":"488","ipdsId":"IP-077876","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":459209,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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,{"id":70207143,"text":"70207143 - 2019 - Spatio-temporal variability of human-fire interactions on the Navajo Nation","interactions":[],"lastModifiedDate":"2019-12-09T12:21:55","indexId":"70207143","displayToPublicDate":"2019-11-11T12:21:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Spatio-temporal variability of human-fire interactions on the Navajo Nation","docAbstract":"Unraveling the effects of climate and land-use on historical fire regimes provides important insights into broader human-fire-climate dynamics, which are necessary for ecologically-based forest management. We developed a spatial human land-use model for Navajo Nation forests across which we sampled a network of tree-ring fire history sites to reflect contrasting historical land-use intensity: high human use, primarily in the Chuska Mountains, and low human use, primarily on the central Defiance Plateau. We tested for and compared human- and climate-driven changes in the fire regimes by applying change point detection, regression, and superposed epoch analyses. The historical fire regimes and fire-climate relationships reflect those of similar forests regionally, and are similar between the two Navajo landscapes until the early 1800s. We then determined that a previously identified, localized, early (1830s) decline in fire activity was geographically widespread across higher human use sites. In contrast, fires continued to burn uninterrupted through this period at the lower use sites. Though the 1830s included significantly wet and cold periods that could have contributed to fire regime decline, human factors pose a more spatio-temporally consistent explanation. A rise in Navajo pastoralism in the 1820s-1830s was concentrated seasonally in the heavy use sites. By the 1880s, livestock numbers more than doubled, grazing became far more spatially widespread, and frequent fire regimes of Navajo forests collapsed. The last widespread fire recorded on either landscape was in 1886. In the Chuska Mountains, livestock and fire co-existed for over 50 years between the initial 1832 fire decline and the end of frequent fires after 1886, an exceptional pattern in the western US. Though unique in its timing, character, and spatial dynamics, the collapse of historical fire regimes in Navajo forests contributed to now over a century without frequent surface fire, leaving Navajo forests at risk for large, uncharacteristic high-severity fires.","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.2932","usgsCitation":"Guiterman, C.H., Margolis, E.Q., Baisan, C.H., Falk, D.A., Allen, C.D., and Swetnam, T.W., 2019, Spatio-temporal variability of human-fire interactions on the Navajo Nation: Ecosphere, v. 10, no. 11, e02932, 23 p., https://doi.org/10.1002/ecs2.2932.","productDescription":"e02932, 23 p.","ipdsId":"IP-109701","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":459213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2932","text":"Publisher Index Page"},{"id":370111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","otherGeospatial":"Navajo Nation","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.1324462890625,\n              35.60818490437746\n            ],\n            [\n              -108.30322265624999,\n              35.60818490437746\n            ],\n            [\n              -108.30322265624999,\n              36.8708321556463\n            ],\n            [\n              -110.1324462890625,\n              36.8708321556463\n            ],\n            [\n              -110.1324462890625,\n              35.60818490437746\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Guiterman, Christopher H.","contributorId":190553,"corporation":false,"usgs":false,"family":"Guiterman","given":"Christopher","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":776946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Margolis, Ellis Q. 0000-0002-0595-9005 emargolis@usgs.gov","orcid":"https://orcid.org/0000-0002-0595-9005","contributorId":173538,"corporation":false,"usgs":true,"family":"Margolis","given":"Ellis","email":"emargolis@usgs.gov","middleInitial":"Q.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":776945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baisan, Christopher H.","contributorId":204187,"corporation":false,"usgs":false,"family":"Baisan","given":"Christopher","email":"","middleInitial":"H.","affiliations":[{"id":28236,"text":"Univ of Arizona","active":true,"usgs":false}],"preferred":false,"id":776947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falk, Donald A.","contributorId":197570,"corporation":false,"usgs":false,"family":"Falk","given":"Donald","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":776949,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":776948,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Swetnam, Thomas W.","contributorId":191872,"corporation":false,"usgs":false,"family":"Swetnam","given":"Thomas","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":776950,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70208922,"text":"70208922 - 2019 - A statistical forecasting approach to metapopulation viability analysis","interactions":[],"lastModifiedDate":"2020-03-06T06:36:43","indexId":"70208922","displayToPublicDate":"2019-11-11T06:35:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"A statistical forecasting approach to metapopulation viability analysis","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Conservation of at‐risk species is aided by reliable forecasts of the consequences of environmental change and management actions on population viability. Forecasts from conventional population viability analysis (PVA) are made using a two‐step procedure in which parameters are estimated, or elicited from expert opinion, and then plugged into a stochastic population model without accounting for parameter uncertainty. Recently developed statistical PVAs differ because forecasts are made conditional on models fitted to empirical data. The statistical forecasting approach allows for uncertainty about parameters, but it has rarely been applied in metapopulation contexts where spatially explicit inference is needed about colonization and extinction dynamics and other forms of stochasticity that influence metapopulation viability. We conducted a statistical metapopulation viability analysis (MPVA) using 11&nbsp;yr of data on the federally threatened Chiricahua leopard frog (<i>Lithobates chiricahuensis</i>) to forecast responses to landscape heterogeneity, drought, environmental stochasticity, and management. We evaluated several future environmental scenarios and pond restoration options designed to reduce extinction risk. Forecasts over a 50‐yr time horizon indicated that metapopulation extinction risk was &lt;4% for all scenarios, but uncertainty was high. Without pond restoration, extinction risk is forecasted to be 3.9% (95% CI 0–37%) by year 2066. Restoring six ponds by increasing their hydroperiod reduced extinction risk to &lt;1% and greatly reduced uncertainty (95% CI 0–2%). Our results suggest that managers can mitigate the impacts of drought and environmental stochasticity on metapopulation viability by maintaining ponds that hold water throughout the year and keeping them free of invasive predators. Our study illustrates the utility of the spatially explicit statistical forecasting approach to MPVA in conservation planning efforts.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/eap.2038","usgsCitation":"Howell, P., Hossack, B.R., Muths, E.L., Sigafus, B., Chenevert-Steffler, A., and Chandler, R.B., 2019, A statistical forecasting approach to metapopulation viability analysis: Ecological Applications, v. 30, no. 2, e02038, https://doi.org/10.1002/eap.2038.","productDescription":"e02038","ipdsId":"IP-102677","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":372981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":784028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":784027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":784029,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sigafus, Brent 0000-0002-7422-8927 bsigafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":223082,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent","email":"bsigafus@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":784030,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chenevert-Steffler, A","contributorId":223083,"corporation":false,"usgs":false,"family":"Chenevert-Steffler","given":"A","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":784031,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chandler, Richard B. 0000-0003-4930-2790 rchandler@usgs.gov","orcid":"https://orcid.org/0000-0003-4930-2790","contributorId":187789,"corporation":false,"usgs":false,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B.","affiliations":[{"id":13267,"text":"Warnell School of Forestry and Natural Resources, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":784032,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70206590,"text":"70206590 - 2019 - The complexity of mudstone diagenesis - some insight from the Tøyen Formation, Lower to Middle Ordovician, southern Sweden","interactions":[],"lastModifiedDate":"2019-11-12T06:32:11","indexId":"70206590","displayToPublicDate":"2019-11-09T19:16:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1719,"text":"GFF","active":true,"publicationSubtype":{"id":10}},"title":"The complexity of mudstone diagenesis - some insight from the Tøyen Formation, Lower to Middle Ordovician, southern Sweden","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>The Lower to Middle Ordovician Tøyen Shale in southern Sweden, a biostratigraphically well-dated siliciclastic mudstone unit, shows 18 distinct authigenic cements that include sulfides, carbonates, silicates, clays, and phosphates. Marcasite, sphalerite, galena, and six texturally distinct types of pyrite characterize the sulfides whereas only one type of dolomite and three different generations of calcite are observed in this unit. Quartz, phosphate, and organic matter occur as only one generation each. Authigenic clay minerals are represented by chlorite and kaolinite. The paragenetic sequence of cements is subdivided into the two pre-burial carbonates, succeeded by ten relatively early burial cements, and six late burial cements, the kaolinite being the latest of them all and potentially being of Cretaceous age. Based on textural relationships, the paragenetic sequence of alterations started with dolomite precipitation followed by calcite, and then five different generations of pyrite. All eleven other phases post-date these initial seven cements in the Tøyen Shale.</p></div></div>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/11035897.2018.1525620","usgsCitation":"Egenhoff, S., Fishman, N., Lowers, H.A., and Ahlberg, P., 2019, The complexity of mudstone diagenesis - some insight from the Tøyen Formation, Lower to Middle Ordovician, southern Sweden: GFF, v. 141, no. 1, p. 54-67, https://doi.org/10.1080/11035897.2018.1525620.","productDescription":"14 p.","startPage":"54","endPage":"67","ipdsId":"IP-098019","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":369117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Sweden","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              12.381591796875,\n              56.601838481314694\n            ],\n            [\n              12.678222656249998,\n              55.78892895389262\n            ],\n            [\n              12.930908203125,\n              55.30413773740139\n            ],\n            [\n              14.084472656249998,\n              55.25407706707272\n            ],\n            [\n              15.051269531249998,\n              55.45394132943307\n            ],\n            [\n              15.413818359374998,\n              55.91842985630817\n            ],\n            [\n              14.7216796875,\n              56.47462805805594\n            ],\n            [\n              13.765869140624998,\n              56.69847410813164\n            ],\n            [\n              12.359619140624998,\n              56.9809114245448\n            ],\n            [\n              12.381591796875,\n              56.601838481314694\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"141","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Egenhoff, Sven","contributorId":195466,"corporation":false,"usgs":false,"family":"Egenhoff","given":"Sven","affiliations":[],"preferred":false,"id":775056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fishman, Neil","contributorId":145906,"corporation":false,"usgs":false,"family":"Fishman","given":"Neil","affiliations":[{"id":16290,"text":"Hess Corporation, Houston, Texas, USA","active":true,"usgs":false}],"preferred":false,"id":775057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":775055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ahlberg, Per","contributorId":195467,"corporation":false,"usgs":false,"family":"Ahlberg","given":"Per","email":"","affiliations":[],"preferred":false,"id":775058,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70206605,"text":"70206605 - 2019 - Temporal variation in genetic structure within the threatened spectacled eider","interactions":[],"lastModifiedDate":"2020-02-25T08:05:47","indexId":"70206605","displayToPublicDate":"2019-11-09T12:52:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Temporal variation in genetic structure within the threatened spectacled eider","docAbstract":"We examined the genetic structure of the threatened spectacled eider 14–18 years after the initial assessment to evaluate the influence of population recovery on diversity.  Concordant with the initial assessment, spectacled eiders were highly structured at mitochondrial (mt) DNA and lacked differentiation at microsatellite loci.  The degree and spatial pattern of structure has changed at mtDNA; a 33.0–40.3% reduction in overall FST and ΦST, respectively, and a marked reduction in pairwise FST (-83.1 to -91.4%) among Alaska sites.  Reduction in genetic structure is suggestive of increased female dispersal within Alaska.  These findings highlight the importance of reevaluating genetic diversity as species recover from declines as microevolutionary and demographic processes are dynamic and continually shape associations among populations.","language":"English","publisher":"Taylor & Francis","doi":"10.1007/s10592-019-01234-9","usgsCitation":"Sonsthagen, S.A., Haughey, C., Sexson, M.G., Solovyeva, D.V., Petersen, M.R., and Powell, A., 2019, Temporal variation in genetic structure within the threatened spectacled eider: Conservation Genetics, v. 21, p. 175-179, https://doi.org/10.1007/s10592-019-01234-9.","productDescription":"5 p.","startPage":"175","endPage":"179","ipdsId":"IP-108224","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":437284,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F8DV8O","text":"USGS data release","linkHelpText":"Spectacled Eider (Somateria fischeri) Microsatellite and Mitochondrial DNA Data, 2014-2018, Alaska and Russia"},{"id":369170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -140.44921875,\n              60.75915950226991\n            ],\n            [\n              -140.44921875,\n              70.1403642720717\n            ],\n            [\n              -153.80859375,\n              71.41317683396566\n            ],\n            [\n              -160.3125,\n              71.01695975726373\n            ],\n            [\n              -165.58593749999997,\n              68.78414378041504\n            ],\n            [\n              -167.87109375,\n              65.44000165965534\n            ],\n       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0000-0002-4846-6008","orcid":"https://orcid.org/0000-0002-4846-6008","contributorId":220547,"corporation":false,"usgs":true,"family":"Haughey","given":"Christy","email":"","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":775149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sexson, Matthew G. 0000-0002-1078-0835 msexson@usgs.gov","orcid":"https://orcid.org/0000-0002-1078-0835","contributorId":5544,"corporation":false,"usgs":true,"family":"Sexson","given":"Matthew","email":"msexson@usgs.gov","middleInitial":"G.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":775150,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solovyeva, Diana V","contributorId":216257,"corporation":false,"usgs":false,"family":"Solovyeva","given":"Diana","email":"","middleInitial":"V","affiliations":[{"id":39381,"text":"Institute of Biological problems of the North","active":true,"usgs":false}],"preferred":false,"id":775151,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petersen, Margaret R. 0000-0001-6082-3189 mrpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-6082-3189","contributorId":167729,"corporation":false,"usgs":true,"family":"Petersen","given":"Margaret","email":"mrpetersen@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":775152,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Powell, Abby 0000-0002-9783-134X abby_powell@usgs.gov","orcid":"https://orcid.org/0000-0002-9783-134X","contributorId":176843,"corporation":false,"usgs":true,"family":"Powell","given":"Abby","email":"abby_powell@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":775153,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70215185,"text":"70215185 - 2019 - Within-group relatedness and patterns of reproductive sharing and cooperation in the tropical chestnut-crested yuhina","interactions":[],"lastModifiedDate":"2020-10-09T14:04:56.61404","indexId":"70215185","displayToPublicDate":"2019-11-09T09:00:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":770,"text":"Animal Behaviour","active":true,"publicationSubtype":{"id":10}},"title":"Within-group relatedness and patterns of reproductive sharing and cooperation in the tropical chestnut-crested yuhina","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">In cooperatively breeding animals, genetic relatedness among group members often determines the extent of reproductive sharing, cooperation and competition within a group. Studies of species for which cooperative behaviour is not entirely based on kinship are key for understanding the benefits favouring the evolution and maintenance of cooperative breeding among nonrelatives. In the cooperatively breeding chestnut-crested yuhina,<span>&nbsp;</span><i>Yuhina everetti</i>, a songbird endemic to Borneo, we tested whether unrelated helpers are more likely to gain parentage than are related helpers consistent with the hypothesis that inbreeding risk constrains reproduction by related helpers. We also examined whether related or unrelated helpers provision broods more because of differences in their potential indirect or direct fitness benefits of helping. Kin structure of breeding groups (breeding pair and up to eight helpers of both sexes, median&nbsp;=&nbsp;2 helpers, 96% of 57 pairs had helpers) based on genetic analysis was mixed; 48% of 76 breeder/helper dyads were first-order (26%) or second-order (22%) relatives of one or both members of the breeding pair, and 52% were nonrelatives. Only unrelated male and female helpers gained parentage, and helpers did not differ in their provisioning rate according to their relatedness to the broods. We documented quasi-parasitism or co-breeding by female helpers in 14% of 29 broods and extrapair paternity by male helpers in 21% of 47 broods. This rate of extrapair paternity is relatively high among the few tropical species examined but fit with predictions for mixed-kin groups where inbreeding is avoided. These findings support the emerging pattern for cooperative breeding in birds with mixed-kin groups, wherein unrelated helpers are more likely to gain parentage than are related helpers and helping effort is not necessarily predicted by kinship.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.anbehav.2019.10.007","usgsCitation":"Kaiser, S.A., Martin, T.E., Oteyza, J.C., Danner, J.E., Armstad, C.E., and Fleischer, R.C., 2019, Within-group relatedness and patterns of reproductive sharing and cooperation in the tropical chestnut-crested yuhina: Animal Behaviour, v. 158, p. 89-99, https://doi.org/10.1016/j.anbehav.2019.10.007.","productDescription":"11 p.","startPage":"89","endPage":"99","ipdsId":"IP-107207","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":459217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.anbehav.2019.10.007","text":"Publisher Index Page"},{"id":379274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"158","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kaiser, Sara A.","contributorId":203454,"corporation":false,"usgs":false,"family":"Kaiser","given":"Sara","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":801088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":801089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oteyza, Juan C.","contributorId":166761,"corporation":false,"usgs":false,"family":"Oteyza","given":"Juan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":801090,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danner, Julie E.","contributorId":242912,"corporation":false,"usgs":false,"family":"Danner","given":"Julie","email":"","middleInitial":"E.","affiliations":[{"id":48577,"text":"wash zoo","active":true,"usgs":false}],"preferred":false,"id":801091,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Armstad, Connor E.","contributorId":201088,"corporation":false,"usgs":false,"family":"Armstad","given":"Connor","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":801092,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fleischer, Robert C.","contributorId":127479,"corporation":false,"usgs":false,"family":"Fleischer","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":801093,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70206904,"text":"70206904 - 2019 - Simple metrics predict salt-marsh sediment fluxes","interactions":[],"lastModifiedDate":"2019-12-03T10:10:25","indexId":"70206904","displayToPublicDate":"2019-11-09T08:35:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Simple metrics predict salt-marsh sediment fluxes","docAbstract":"The growth (or decay) of salt marshes depends on suspended-sediment flux into and out of the marsh. Suspended-sediment concentration (SSC) is a key element of the flux, and SSC-based metrics reflect the long-term sediment-flux trajectories of a variety of salt marshes. One metric, the flood–ebb SSC differential, correlates with area-normalized sediment flux and can indicate salt-marsh resilience over months to years. We hypothesize that these metrics may be relevant over shorter time periods. With data from 13 salt-marsh channels, we show that sediment flux direction and magnitude can be inferred from SSC differential over a wide range of timescales. Furthermore, in settings characterized by a standing tidal wave, the water-level gradient can be used instead of velocity to compute the SSC differential, enabling less-intensive measurements that capture fundamental sediment-flux parameters. Distilling the sediment-flux trajectory into simple metrics improves sediment-budget assessment, drives geomorphic model development, and clarifies field observations.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL083819","usgsCitation":"Nowacki, D.J., and Ganju, N., 2019, Simple metrics predict salt-marsh sediment fluxes: Geophysical Research Letters, v. 46, no. 12, p. 12250-12257, https://doi.org/10.1029/2019GL083819.","productDescription":"8 p.","startPage":"12250","endPage":"12257","ipdsId":"IP-108546","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459220,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gl083819","text":"Publisher Index Page"},{"id":437285,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91L4A75","text":"USGS data release","linkHelpText":"Suspended-sediment concentration data from water samples collected in 2016-17 in Grand Bay, Alabama and Mississippi"},{"id":369696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Nowacki, Daniel J. 0000-0002-7015-3710 dnowacki@usgs.gov","orcid":"https://orcid.org/0000-0002-7015-3710","contributorId":174586,"corporation":false,"usgs":true,"family":"Nowacki","given":"Daniel","email":"dnowacki@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":776199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":776200,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70207176,"text":"70207176 - 2019 - Estimating the value of mangrove leaf litter in sesarmid crab diets: The importance of fractionation factors","interactions":[],"lastModifiedDate":"2020-08-05T13:56:58.389158","indexId":"70207176","displayToPublicDate":"2019-11-08T15:16:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1106,"text":"Bulletin of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the value of mangrove leaf litter in sesarmid crab diets: The importance of fractionation factors","docAbstract":"<p><span>Sesarmid crabs play an important role in organic matter and carbon cycling of mangrove forests. Visual observations and gut content studies have verified that sesarmid crabs are feeding on mangrove leaves, yet stable isotopes of carbon and nitrogen (</span><sup>13</sup><span>C and&nbsp;</span><sup>15</sup><span>N) have indicated that leaf litter is not assimilated as a food source. Sesarmid crabs tend to be much more enriched in&nbsp;</span><sup>13</sup><span>C than leaf litter (0.9‰ – 11.6‰) and have C values that are often more like microphytobenthos (MPB). General&nbsp;</span><sup>13</sup><span>C trophic enrichment factors (TEF; 0.1‰ – 0.5‰) suggest crabs feed more heavily on MPB. Field and laboratory-based evidence reveal that general&nbsp;</span><sup>13</sup><span>C TEF for crabs feeding on mangrove leaves may be incorrect and much greater than 0.1‰ – 0.5‰. A food web study conducted annually over 2 yrs revealed a shift in the δ</span><sup>13</sup><span>C and δ</span><sup>15</sup><span>N of&nbsp;</span><i>Parasesarma</i><span>&nbsp;sp. crabs similar to mangrove leaves also sampled. This suggested&nbsp;</span><i>Parasesarma</i><span>&nbsp;sp. may be feeding more heavily on mangrove leaves than previously reported despite crabs being 4.4‰ – 11.6‰ more enriched in&nbsp;</span><sup>13</sup><span>C than mangrove leaves. A laboratory feeding study confirmed that average&nbsp;</span><sup>13</sup><span>C TEF between&nbsp;</span><i>Parasesarma</i><span>&nbsp;sp. and decayed&nbsp;</span><i>Rhizophora</i><span>&nbsp;sp. leaves was 3.3‰ (SE 0.5). The Stable Isotope Analysis in R package (SIAR) used with our TEF and the general 0.5‰&nbsp;</span><sup>13</sup><span>C TEF revealed that published TEFs may underestimate mangrove leaf contributions to sesarmid crab diets on average by 33.3% (SE 0.1) and overestimate MPB and epiphytic algal contributions by 31.3% (SE 0.1). Food web studies in mangroves and other ecosystems will continue to inaccurately identify important food resources or food web structures unless more accurate and species-specific isotope fractionation values are determined.</span></p>","language":"English","publisher":"Ingenta Connect","doi":"10.5343/bms.2019.0026","usgsCitation":"MacKenzie, R., Cormier, N., and Demopoulos, A., 2019, Estimating the value of mangrove leaf litter in sesarmid crab diets: The importance of fractionation factors: Bulletin of Marine Science, v. 96, no. 3, p. 501-520, https://doi.org/10.5343/bms.2019.0026.","productDescription":"20 p.","startPage":"501","endPage":"520","ipdsId":"IP-108875","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":459223,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5343/bms.2019.0026","text":"Publisher Index Page"},{"id":370189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"MacKenzie, R.A.","contributorId":221146,"corporation":false,"usgs":false,"family":"MacKenzie","given":"R.A.","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":777154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cormier, N. 0000-0003-2453-9900","orcid":"https://orcid.org/0000-0003-2453-9900","contributorId":221147,"corporation":false,"usgs":false,"family":"Cormier","given":"N.","affiliations":[{"id":16788,"text":"Macquarie University","active":true,"usgs":false}],"preferred":false,"id":777155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":221145,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":777153,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70207443,"text":"70207443 - 2019 - Variable normal-fault rupture behavior, northern Lost River fault zone, Idaho, USA","interactions":[],"lastModifiedDate":"2020-12-18T21:19:55.06454","indexId":"70207443","displayToPublicDate":"2019-11-08T13:09:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Variable normal-fault rupture behavior, northern Lost River fault zone, Idaho, USA","docAbstract":"The 1983 Mw 6.9 Borah Peak earthquake generated ∼36 km of surface rupture along the Thousand Springs and Warm Springs sections of the Lost River fault zone (LRFZ, Idaho, USA). Although the rupture is a well-studied example of multisegment surface faulting, ambiguity remains regarding the degree to which a bedrock ridge and branch fault at the Willow Creek Hills influenced rupture progress. To explore the 1983 rupture in the context of the structural complexity, we reconstruct the spatial distribution of surface displacements for the northern 16 km of the 1983 rupture and prehistoric ruptures in the same reach of the LRFZ using 252 vertical-separation measurements made from high-resolution (5–10-cm-pixel) digital surface models. Our results suggest the 1983 Warm Springs rupture had an average vertical displacement of ∼0.3–0.4 m and released ∼6% of the seismic moment estimated for the Borah Peak earthquake and <12% of the moment accumulated on the Warm Springs section since its last prehistoric earthquake. The 1983 Warm Springs rupture is best described as the moderate-displacement continuation of primary rupture from the Thousand Springs section into and through a zone of structural complexity. Historical and prehistoric displacements show that the Willow Creek Hills have impeded some, but not all ruptures. We speculate that rupture termination or penetration is controlled by the history of LRFZ moment release, displacement, and rupture direction. Our results inform the interpretation of paleoseismic data from near zones of normal-fault structural complexity and demonstrate that these zones may modulate rather than impede rupture displacement.","language":"English","publisher":"GeoScienceWorld","doi":"10.1130/GES02096.1","usgsCitation":"DuRoss, C., Bunds, M.P., Gold, R.D., Briggs, R.W., Reitman, N.G., Personius, S., and Toke, N.A., 2019, Variable normal-fault rupture behavior, northern Lost River fault zone, Idaho, USA: Geosphere, v. 15, no. 6, p. 1869-1892, https://doi.org/10.1130/GES02096.1.","productDescription":"24 p.","startPage":"1869","endPage":"1892","ipdsId":"IP-108215","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":459224,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02096.1","text":"Publisher Index 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 \"}}]}","volume":"15","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunds, Michael P.","contributorId":221403,"corporation":false,"usgs":false,"family":"Bunds","given":"Michael","email":"","middleInitial":"P.","affiliations":[{"id":40367,"text":"Utah Valley University","active":true,"usgs":false}],"preferred":false,"id":778061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778063,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reitman, Nadine G. 0000-0002-6730-2682 nreitman@usgs.gov","orcid":"https://orcid.org/0000-0002-6730-2682","contributorId":5816,"corporation":false,"usgs":true,"family":"Reitman","given":"Nadine","email":"nreitman@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778064,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Personius, Stephen 0000-0001-8347-7370 personius@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-7370","contributorId":150055,"corporation":false,"usgs":true,"family":"Personius","given":"Stephen","email":"personius@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778065,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Toke, Nathan A.","contributorId":221404,"corporation":false,"usgs":false,"family":"Toke","given":"Nathan","email":"","middleInitial":"A.","affiliations":[{"id":40367,"text":"Utah Valley University","active":true,"usgs":false}],"preferred":false,"id":778066,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70206424,"text":"fs20193069 - 2019 - Naturally occurring uranium in groundwater in northeastern Washington State","interactions":[],"lastModifiedDate":"2020-11-19T16:53:13.660054","indexId":"fs20193069","displayToPublicDate":"2019-11-08T12:31:53","publicationYear":"2019","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":"2019-3069","displayTitle":"Naturally Occurring Uranium in Groundwater in Northeastern Washington State","title":"Naturally occurring uranium in groundwater in northeastern Washington State","docAbstract":"<p>Uranium is a radioactive element (radionuclide) that occurs naturally in rock, soil, and water, usually in low concentrations. Radionuclides are unstable atoms with excess energy and as radionuclides decay, they emit radiation. The uranium decay sequence also includes other radionuclides of concern such as radium and radon. This fact sheet addresses naturally occurring uranium in groundwater in northeastern Washington.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193069","usgsCitation":"Kahle, S.C., 2019, Naturally occurring uranium in groundwater in northeastern Washington State: U.S. Geological Survey Fact Sheet 2019–3069, 4 p., https://doi.org/10.3133/fs20193069.","productDescription":"4 p.","ipdsId":"IP-109656","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":380610,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://wim.usgs.gov/geonarrative/uraniumgw/","text":"USGS geo-narrative —","description":"USGS Geo-Narrative","linkHelpText":"Naturally occurring uranium in groundwater in northeastern Washington State"},{"id":369098,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3069/fs20193069.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3069"},{"id":369097,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3069/coverthb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.01538085937499,\n              48.96579381461063\n            ],\n            [\n              -120.684814453125,\n              49.001843917978526\n            ],\n            [\n              -120.59692382812499,\n              46.77749276376827\n            ],\n            [\n              -117.05932617187499,\n              46.76996843356982\n            ],\n            [\n              -117.01538085937499,\n              48.96579381461063\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_wa@usgs.gov\" data-mce-href=\"mailto:dc_wa@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/wa-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/wa-water\">Washington Water Science Center</a><br>U.S. Geological Survey<br>934 Broadway, Suite 300, Tacoma, Washington 98402</p>","tableOfContents":"<ul><li>What is uranium?</li><li>Why is uranium in drinking water a concern?</li><li>Why is it important to test my drinking water?</li><li>Why does uranium occur in groundwater in northeastern Washington?</li><li>What levels of uranium have been found in area wells?</li><li>What else could we learn?</li><li>Where can I find more information?</li><li>References</li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2019-11-08","noUsgsAuthors":false,"publicationDate":"2019-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Kahle, Sue C. 0000-0003-1262-4446 sckahle@usgs.gov","orcid":"https://orcid.org/0000-0003-1262-4446","contributorId":3096,"corporation":false,"usgs":true,"family":"Kahle","given":"Sue","email":"sckahle@usgs.gov","middleInitial":"C.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":774500,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70216028,"text":"70216028 - 2019 - Weed-suppressive bacteria fail to control bromus tectorum under field conditions","interactions":[],"lastModifiedDate":"2020-11-13T20:46:16.444746","indexId":"70216028","displayToPublicDate":"2019-11-08T11:43:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Weed-suppressive bacteria fail to control bromus tectorum under field conditions","docAbstract":"<p><span>The exotic winter annual grass&nbsp;</span><i>Bromus tectorum</i><span>&nbsp;L. (downy brome or cheatgrass) infests millions of hectares of western rangelands. Weed-suppressive bacteria (ACK55 and D7 strains of&nbsp;</span><i>Pseudomonas fluorescens</i><span>&nbsp;Migula 1895) have been shown to reduce&nbsp;</span><i>B.&nbsp;tectorum</i><span>&nbsp;populations in eastern Washington. Unfortunately, outside of Washington, little is known about the efficacy of these or other weed-suppressive bacteria. We used Petri-plate and plant-soil bioassays to test effects of ACK55 and D7 on&nbsp;</span><i>B.&nbsp;tectorum</i><span>&nbsp;from Montana and Wyoming. We also tested effects of ACK55 on&nbsp;</span><i>B.&nbsp;tectorum</i><span>&nbsp;at six field sites in Montana and one in Wyoming.&nbsp;</span><i>P.&nbsp;fluorescens</i><span>&nbsp;reduced&nbsp;</span><i>B.&nbsp;tectorum</i><span>&nbsp;germination and root and shoot lengths in Petri-plates but had no effect on plants during growth chamber plant-soil bioassays or field experiments.&nbsp;</span><i>Bromus arvensis</i><span>&nbsp;L. (field brome or Japanese brome), a species similar to&nbsp;</span><i>B.&nbsp;tectorum,</i><span>&nbsp;was prevalent at two of our sites, and ACK55 was ineffective against&nbsp;</span><i>B.&nbsp;arvensis</i><span>&nbsp;as well. Our findings contribute to a growing body of evidence that the ACK55 and D7 strains of&nbsp;</span><i>P.&nbsp;fluorescens</i><span>&nbsp;are not reliable tools for controlling&nbsp;</span><i>B.&nbsp;tectorum</i><span>&nbsp;in the Northern Great Plains, Central Rocky Mountains, and elsewhere.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2019.07.006","usgsCitation":"Reinhart, K.O., Carlson, C.H., Feris, K.P., Germino, M., Jandreau, C.J., Lazarus, B., Mangold, J.M., Pellatz, D.W., Ramsey, P., Rinella, M.J., and Valliant, M., 2019, Weed-suppressive bacteria fail to control bromus tectorum under field conditions: Rangeland Ecology & Management, v. 73, no. 6, p. 760-765, https://doi.org/10.1016/j.rama.2019.07.006.","productDescription":"6 p.","startPage":"760","endPage":"765","ipdsId":"IP-107524","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":459227,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://scholarworks.montana.edu/xmlui/handle/1/17109","text":"Publisher Index Page"},{"id":380083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Reinhart, Kurt O","contributorId":244337,"corporation":false,"usgs":false,"family":"Reinhart","given":"Kurt","email":"","middleInitial":"O","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":803805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Chris H","contributorId":244338,"corporation":false,"usgs":false,"family":"Carlson","given":"Chris","email":"","middleInitial":"H","affiliations":[{"id":48895,"text":"Missoula Parks and Recreation","active":true,"usgs":false}],"preferred":false,"id":803806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feris, Kevin P","contributorId":244339,"corporation":false,"usgs":false,"family":"Feris","given":"Kevin","email":"","middleInitial":"P","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":803807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Germino, Matthew 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":218007,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":803808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jandreau, Clancy J","contributorId":244340,"corporation":false,"usgs":false,"family":"Jandreau","given":"Clancy","email":"","middleInitial":"J","affiliations":[{"id":48895,"text":"Missoula Parks and Recreation","active":true,"usgs":false}],"preferred":false,"id":803809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lazarus, Brynne E. 0000-0002-6352-486X","orcid":"https://orcid.org/0000-0002-6352-486X","contributorId":242732,"corporation":false,"usgs":true,"family":"Lazarus","given":"Brynne E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":803810,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mangold, Jane M.","contributorId":224964,"corporation":false,"usgs":false,"family":"Mangold","given":"Jane","email":"","middleInitial":"M.","affiliations":[{"id":41008,"text":"Montana State University, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":803811,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pellatz, Dave W","contributorId":244341,"corporation":false,"usgs":false,"family":"Pellatz","given":"Dave","email":"","middleInitial":"W","affiliations":[{"id":48896,"text":"Thunder Basin Grasslands Prairie Ecosystem Association","active":true,"usgs":false}],"preferred":false,"id":803812,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ramsey, Philip","contributorId":244342,"corporation":false,"usgs":false,"family":"Ramsey","given":"Philip","email":"","affiliations":[{"id":48897,"text":"MPG Ranch","active":true,"usgs":false}],"preferred":false,"id":803813,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rinella, Matthew J.","contributorId":172336,"corporation":false,"usgs":false,"family":"Rinella","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":803814,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Valliant, Morgan","contributorId":244343,"corporation":false,"usgs":false,"family":"Valliant","given":"Morgan","email":"","affiliations":[{"id":48895,"text":"Missoula Parks and Recreation","active":true,"usgs":false}],"preferred":false,"id":803815,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70187332,"text":"pp1824CC - 2019 - Geology and assessment of undiscovered oil and gas resources of the Lomonosov-Makarov Province, 2008","interactions":[{"subject":{"id":70187332,"text":"pp1824CC - 2019 - Geology and assessment of undiscovered oil and gas resources of the Lomonosov-Makarov Province, 2008","indexId":"pp1824CC","publicationYear":"2019","noYear":false,"chapter":"CC","displayTitle":"Geology and Assessment of Undiscovered Oil and Gas Resources of the Lomonosov-Makarov Province, 2008","title":"Geology and assessment of undiscovered oil and gas resources of the Lomonosov-Makarov Province, 2008"},"predicate":"IS_PART_OF","object":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"id":1}],"isPartOf":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"lastModifiedDate":"2024-06-26T14:26:08.421738","indexId":"pp1824CC","displayToPublicDate":"2019-11-08T09:16:16","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1824","chapter":"CC","displayTitle":"Geology and Assessment of Undiscovered Oil and Gas Resources of the Lomonosov-Makarov Province, 2008","title":"Geology and assessment of undiscovered oil and gas resources of the Lomonosov-Makarov Province, 2008","docAbstract":"<p>The Lomonosov-Makarov Province lies in the central Arctic Ocean and encompasses the northern part of the oceanic Amerasia Basin (Makarov and Podvodnikov Basins) and the adjoining Lomonosov Ridge and Siberian continental margins. The Amerasia Basin is thought to have been created in the Jurassic and Early Cretaceous by rotational rifting of the Alaska-Siberia margin away from the Canada margin about a pivot point in the Mackenzie Delta and an associated continental-scale transform fault along the Lomonosov Ridge. The province is bounded on the south by the Cretaceous Alpha-Mendeleev Ridge, an undersea ridge composed of plume-type volcanic rocks that obliquely crosses the Amerasia Basin, dividing it into northern and southern parts. The thickest passive-margin succession in the province lies along the Siberian margin, where sediments thin from a maximum thickness along the continental margin to less than 2 km in the basin. The northern part of the province consists of the Lomonosov Ridge, which was rifted away from the Eurasia Plate in the Paleocene during formation of the oceanic Eurasia Basin, creating an isolated, narrow, submerged, but high-standing microcontinent. This part of the province contains sediments that were shed from the Eurasia Plate in the Mesozoic and covered by pelagic and hemipelagic sediments in the Cenozoic, creating depositional successions with thicknesses ranging from about 1 to more than 5 km.</p><p>This tectonic framework provides the basis for division of the province into four assessment units (AUs), including (1) Lomonosov Ridge AU, (2) Makarov Basin Margin AU, (3) Siberian Passive Margin AU, and (4) Makarov Basin AU. The Lomonosov Ridge and Makarov Basin Margin AUs compose a displaced part of the Cretaceous shelf and slope, respectively, of the Eurasia continental margin with a covering drape of pelagic Cenozoic sediments. The Siberian Passive Margin and Makarov Basin AUs represent the slope of the Siberian continental margin and adjoining basin plain deposits, respectively, deposited on oceanic crust of the northern Amerasia Basin. All of the AUs are entirely submarine and covered by the polar icecap, and consequently have not been explored for petroleum. Petroleum source rock units considered in the assessment of the province are mostly hypothetical, and include Triassic and Jurassic platformal marine shale units on the Lomonosov Ridge, and province-wide Lower Cretaceous synrift, Lower and Upper Cretaceous postrift, and Paleogene organic-rich shale intervals. The most prospective reservoirs and traps are envisioned to include base-of-slope turbidite-fan complexes, slope channels and basins, extensional and growth fault structures, and other stratigraphic, structural, and composite trap features typically present on clastic-dominated continental passive margins. Because of concerns about reservoir quality in the Makarov Basin AU and the detrimental effect of Paleocene rifting in the Lomonosov Ridge AU, these units were not quantitatively assessed, as they were judged to have less than 10 percent probability of containing at least one accumulation of hydrocarbons equal to or greater than 50 million barrels of oil equivalent (MMBOE). The mean volumes of undiscovered resources for the Makarov Basin Margin AU are estimated to be 0.12 billion barrels of oil and 0.74 trillion cubic feet of nonassociated gas, whereas the undiscovered resources for the Siberian Passive Margin AU are estimated to be ~1 billion barrels of oil and 4.7 trillion cubic feet of nonassociated gas.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824CC","usgsCitation":"Moore, T.E., Bird, K.J., and Pitman, J.K., 2019, Geology and assessment of undiscovered oil and gas resources of the Lomonosov-Makarov Province, 2008, chap. CC <i>of</i> Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 43 p., https://doi.org/10.3133/pp1824cc.","productDescription":"Report: vii, 43 p.; 4 Appendixes","numberOfPages":"43","additionalOnlineFiles":"Y","ipdsId":"IP-021705","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":368983,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/cc/pp1824cc_appx4.xls","text":"Appendix 4","size":"40 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter CC","linkHelpText":"- Input data for Siberian Passive Margin Assessment Unit"},{"id":368982,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/cc/pp1824cc_appx3.xls","text":"Appendix 3","size":"40 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter CC","linkHelpText":"- Input data for Podvodnikov-Makarov Basin Assessment Unit"},{"id":368981,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/cc/pp1824cc_appx2.xls","text":"Appendix 2","size":"40 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter CC","linkHelpText":"- Input data for Makarov Basin Margin Assessment Unit"},{"id":368980,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/cc/pp1824cc_appx1.xls","text":"Appendix 1","size":"40 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter CC","linkHelpText":"- Input data for Lomonosov Ridge Assessment Unit"},{"id":368979,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/cc/pp1824cc.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter CC"},{"id":368978,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/cc/coverthb.jpg"}],"otherGeospatial":"Lomonosov-Makarov Province","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg/employee-directory\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg/employee-directory\">Contact Information</a>,<br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center—Menlo Park</a><br><a href=\"https://usgs.gov\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>345 Middlefield Road<br>Menlo Park, CA 94025-3591<br>FAX 650-329-4936</p>","tableOfContents":"<p></p><ul><li>Abstract</li><li>Introduction</li><li>Lomonosov-Makarov Province Description</li><li>Assessment Units</li><li>Summary of Assessment Results</li><li>Acknowledgments</li><li>References Cited</li><li>Appendixes</li></ul><p></p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-11-08","noUsgsAuthors":false,"publicationDate":"2019-11-08","publicationStatus":"PW","contributors":{"editors":[{"text":"Moore, Thomas E. 0000-0002-0878-0457 tmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-0878-0457","contributorId":127538,"corporation":false,"usgs":true,"family":"Moore","given":"Thomas","email":"tmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":774779,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Gautier, Donald L. gautier@usgs.gov","contributorId":1310,"corporation":false,"usgs":true,"family":"Gautier","given":"Donald","email":"gautier@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":774780,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Moore, Thomas E. 0000-0002-0878-0457 tmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-0878-0457","contributorId":127538,"corporation":false,"usgs":true,"family":"Moore","given":"Thomas","email":"tmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":693504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bird, Kenneth J. kbird@usgs.gov","contributorId":1015,"corporation":false,"usgs":true,"family":"Bird","given":"Kenneth","email":"kbird@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":693503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":693505,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70211849,"text":"70211849 - 2019 - Process-guided deep learning predictions of lake water temperature","interactions":[],"lastModifiedDate":"2020-08-10T13:36:45.068234","indexId":"70211849","displayToPublicDate":"2019-11-08T08:26:04","publicationYear":"2019","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":"Process-guided deep learning predictions of lake water temperature","docAbstract":"<p><span>The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools. Hybrid models that integrate theory with state‐of‐the art empirical techniques have the potential to improve predictions while remaining true to physical laws. This paper evaluates the Process‐Guided Deep Learning (PGDL) hybrid modeling framework with a use‐case of predicting depth‐specific lake water temperatures. The PGDL model has three primary components: a deep learning model with temporal awareness (long short‐term memory recurrence), theory‐based feedback (model penalties for violating conversation of energy), and model pretraining to initialize the network with synthetic data (water temperature predictions from a process‐based model). In situ water temperatures were used to train the PGDL model, a deep learning (DL) model, and a process‐based (PB) model. Model performance was evaluated in various conditions, including when training data were sparse and when predictions were made outside of the range in the training data set. The PGDL model performance (as measured by root‐mean‐square error (RMSE)) was superior to DL and PB for two detailed study lakes, but only when pretraining data included greater variability than the training period. The PGDL model also performed well when extended to 68 lakes, with a median RMSE of 1.65 °C during the test period (DL: 1.78 °C, PB: 2.03 °C; in a small number of lakes PB or DL models were more accurate). This case‐study demonstrates that integrating scientific knowledge into deep learning tools shows promise for improving predictions of many important environmental variables.</span></p>","language":"English","publisher":"Wiley","doi":"10.1029/2019WR024922","usgsCitation":"Read, J.S., Jia, X., Willard, J., Appling, A.P., Zwart, J.A., Oliver, S.K., Karpatne, A., Hansen, G., Hanson, P.C., Watkins, W., Steinbach, M., and Kumar, V., 2019, Process-guided deep learning predictions of lake water temperature: Water Resources Research, v. 55, no. 11, p. 9173-9190, https://doi.org/10.1029/2019WR024922.","productDescription":"28 p.","startPage":"9173","endPage":"9190","ipdsId":"IP-104941","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":459230,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2019wr024922","text":"External 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,{"id":70205777,"text":"ofr20191113 - 2019 - Full Equations Model Graphical Data Inspector (FEQ–GDI) user guide","interactions":[],"lastModifiedDate":"2019-11-12T06:12:57","indexId":"ofr20191113","displayToPublicDate":"2019-11-07T15:32:54","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1113","displayTitle":"Full Equations Model Graphical Data Inspector (FEQ–GDI) User Guide","title":"Full Equations Model Graphical Data Inspector (FEQ–GDI) user guide","docAbstract":"<p>The Full Equations Model Graphical Data Inspector (FEQ–GDI) is a menu-driven utility program that enables users to visualize and check the geometric and hydraulic properties of channel cross sections, selected control structures, and stream profiles in the input files for the Full Equations (FEQ) Model and the Full Equations Utilities (FEQUTL) Model. The FEQ Model is a computer program for the simulation of one-dimensional, unsteady flow in open channels and through control structures using the full, dynamic equations of motion. The input to FEQ Model includes the output from the FEQUTL Model, which computes tables relating the hydraulic properties of channel cross sections and control structures to depth, flow, and (or) other specified parameters. FEQ–GDI can be used to help users quickly detect anomalies in the data that may indicate errors in the input files.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191113","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Department","usgsCitation":"Ern, J.L., Ortel, T., Ishii, A.L., and Bera, M., 2019, Full Equations Model Graphical Data Inspector (FEQ–GDI) user guide: U.S. Geological Survey Open-File Report 2019–1113, 11 p., https://doi.org/10.3133/ofr20191113.","productDescription":"iv, 11 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-111050","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":369032,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1113/coverthb.jpg"},{"id":369033,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1113/ofr20191113.pdf","text":"Report","size":"4.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1113"}],"contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/cm-water\" href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a> <br>U.S. Geological Survey<br>405 North Goodwin <br>Urbana, IL 61801</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Full Equations Model Graphical Data Inspector Description</li><li>Program Requirements and Installation</li><li>Development</li><li>Summary</li><li>References Cited</li><li>Figures</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-11-07","noUsgsAuthors":false,"publicationDate":"2019-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Ern, Jessica L.","contributorId":219461,"corporation":false,"usgs":false,"family":"Ern","given":"Jessica","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":772306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ortel, Terry 0000-0001-9647-4259","orcid":"https://orcid.org/0000-0001-9647-4259","contributorId":204651,"corporation":false,"usgs":true,"family":"Ortel","given":"Terry","email":"","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ishii, Audrey L. alishii@usgs.gov","contributorId":219460,"corporation":false,"usgs":false,"family":"Ishii","given":"Audrey","email":"alishii@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":772305,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bera, Maitreyee 0000-0002-3968-1961 mbera@usgs.gov","orcid":"https://orcid.org/0000-0002-3968-1961","contributorId":5450,"corporation":false,"usgs":true,"family":"Bera","given":"Maitreyee","email":"mbera@usgs.gov","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772303,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70206055,"text":"ofr20191119 - 2019 - Detailed Lithologic Logs from Auger Holes in southern Charleston County, southwestern Dorchester County, and eastern Colleton County, South Carolina","interactions":[],"lastModifiedDate":"2019-11-07T13:30:32","indexId":"ofr20191119","displayToPublicDate":"2019-11-07T13:30:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1119","displayTitle":"Detailed Lithologic Logs from Auger Holes in Southern Charleston County, Southwestern Dorchester County, and Eastern Colleton County, South Carolina","title":"Detailed Lithologic Logs from Auger Holes in southern Charleston County, southwestern Dorchester County, and eastern Colleton County, South Carolina","docAbstract":"<p>The lithologic logs described in this open-file report are from holes augered in the South Carolina Low Country in parts of Charleston, Dorchester, and Colleton Counties from 1998 through 2010. Lithologic units described here include not only surficial Pleistocene units but also subsurface stratigraphic units ranging as far back in age as late Eocene. This region comprises the southernmost and westernmost portions of the area included in the 1:100,000 Charleston region geologic map, which lies east of 80°30′ west and south of 33°15′ north. Logs of the remainder of that map area were published prior to the release of that map. The present report completes the lithologic log record from which the 1:100,000 Charleston region geologic map largely was compiled.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191119","collaboration":"Prepared in cooperation with the South Carolina Geological Survey","usgsCitation":"Weems, R.E., and Lewis, W.C., 2019, Detailed lithologic logs from auger holes in southern Charleston County, southwestern Dorchester County, and eastern Colleton County, South Carolina: U.S. Geological Survey Open-File Report 2019–1119, 129 p., https://doi.org/10.3133/ofr20191119.","productDescription":"iv, 129 p.","numberOfPages":"136","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-105009","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":368507,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1119/coverthb2.jpg"},{"id":369044,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1119/ofr20191119.pdf","text":"Report","size":"2.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1119"}],"country":"United States","state":"South Carolina","county":"Charleston County, Colleton County, Dorchester County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.8758544921875,\n              32.20350534542368\n            ],\n            [\n              -79.8870849609375,\n              32.20350534542368\n            ],\n            [\n              -79.8870849609375,\n              33.02248191961359\n            ],\n            [\n              -80.8758544921875,\n              33.02248191961359\n            ],\n            [\n              -80.8758544921875,\n              32.20350534542368\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/fbgc\" data-mce-href=\"https://www.usgs.gov/centers/fbgc\">Florence Bascom Geoscience Center</a><br>U.S. Geological Survey<br>MS 926A National Center<br>12201 Sunrise Valley Drive<br>Reston, VA 20192<br></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Introduction</li><li>Methods</li><li>Stratigraphy</li><li>Structural Geology</li><li>Hydrogeology</li><li>References Cited</li><li>Appendix 1. Locality Descriptions and Detailed Lithologic Logs</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-11-07","noUsgsAuthors":false,"publicationDate":"2019-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Weems, Robert E. 0000-0002-1907-7804 rweems@usgs.gov","orcid":"https://orcid.org/0000-0002-1907-7804","contributorId":2663,"corporation":false,"usgs":true,"family":"Weems","given":"Robert","email":"rweems@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":773435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewis, William C.","contributorId":192890,"corporation":false,"usgs":false,"family":"Lewis","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":773436,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70206811,"text":"70206811 - 2019 - Nutritional status of honey bee (Apis mellifera L.) workers across an agricultural land-use gradient","interactions":[],"lastModifiedDate":"2020-12-18T14:47:25.967296","indexId":"70206811","displayToPublicDate":"2019-11-07T10:20:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Nutritional status of honey bee (<i>Apis mellifera</i> L.) workers across an agricultural land-use gradient","title":"Nutritional status of honey bee (Apis mellifera L.) workers across an agricultural land-use gradient","docAbstract":"Land use and habitat quality have emerged as critical factors influencing the health, productivity, and survival of honey bee colonies.  However, characterization of the mechanistic relationship between differential land-use conditions and ultimate outcomes for honey bee colonies has been elusive. We assessed the physiological health of individual worker honey bees in colonies stationed across a gradient of agricultural land use to ask whether indicators of nutritional physiology including glycogen, total sugar, lipids, and protein were associated with land-use conditions over the growing season and colony population size the subsequent spring during almond pollination.  Across the observed land-use gradient, we found that September lipid levels related to growing-season land use, with honey bees from apiaries surrounded by more favorable land covers such as grassland, pasture, conservation land, and fallow fields having greater lipid reserves.  Further, we observed a significant effect of total protein during September on population size of colonies during almond pollination the following February.  We demonstrate and discuss the utility of quantifying nutritional biomarkers to infer land-use quality and predict colony population size.","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-52485-y","usgsCitation":"Smart, M., Otto, C., and Lundgren, J.G., 2019, Nutritional status of honey bee (Apis mellifera L.) workers across an agricultural land-use gradient: Scientific Reports, v. 9, 16252, 10 p., https://doi.org/10.1038/s41598-019-52485-y.","productDescription":"16252, 10 p.","ipdsId":"IP-103496","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":459233,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-52485-y","text":"Publisher Index Page"},{"id":437287,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NND336","text":"USGS data release","linkHelpText":"Nutritional physiology of honey bee (Apis mellifera L.) workers across an agricultural land use gradient dataset"},{"id":369458,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Smart, Matthew 0000-0003-0711-3035","orcid":"https://orcid.org/0000-0003-0711-3035","contributorId":220827,"corporation":false,"usgs":true,"family":"Smart","given":"Matthew","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":775842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":775843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lundgren, Jonathan G.","contributorId":220828,"corporation":false,"usgs":false,"family":"Lundgren","given":"Jonathan","email":"","middleInitial":"G.","affiliations":[{"id":40282,"text":"Ecdysis Foundation","active":true,"usgs":false}],"preferred":false,"id":775844,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70215782,"text":"70215782 - 2019 - Soil aggregates as a source of dissolved organic carbon to streams: An experimental study on the effect of solution chemistry on water extractable carbon","interactions":[],"lastModifiedDate":"2020-10-29T14:32:59.149073","indexId":"70215782","displayToPublicDate":"2019-11-07T09:26:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Soil aggregates as a source of dissolved organic carbon to streams: An experimental study on the effect of solution chemistry on water extractable carbon","docAbstract":"<div class=\"JournalAbstract\"><p>Over the past two decades, headwater streams of the northern hemisphere have shown increased amounts of dissolved organic carbon (DOC), coinciding with decreased acid deposition. The exact nature of the mechanistic link between precipitation composition and stream water DOC is still widely debated in the literature. We hypothesize that soil aggregates are the main source of stream water DOC and that DOC release is greater in organic rich, riparian soils vs. hillslope soils. To test these hypotheses, we collected soils from two main landscape positions (hillslope and riparian zones) from the acid-impacted Sleepers River Research Watershed in northeastern Vermont. We performed aqueous soil extracts with solutions of different ionic strength (IS) and composition to simulate changes in soil solution. We monitored dynamic changes in soil particle size, aggregate architecture and composition, leachate DOC concentrations, dissolved organic matter (DOM) characteristics by fluorescence spectroscopy and trends in bioavailability. In low IS solutions, extractable DOC concentrations were significantly higher, particle size (by laser diffraction) was significantly smaller and organic material was separated from mineral particles in scanning electron microscope observations. Furthermore, higher DOC concentrations were found in Na<sup>+</sup><span>&nbsp;</span>compared to Ca<sup>2+</sup><span>&nbsp;</span>solutions of the same IS. These effects are attributed to aggregate dispersion due to expanding diffuse double layers in decreased IS solutions and to decreased bridging by divalent cations. Landscape position impacted quality but not quantity of released DOC. Overall, these results indicate that soil aggregates might be one important link between Critical Zone inputs (i.e., precipitation) and exports in streams.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2019.00172","usgsCitation":"Cincotta, M.M., Perdrial, J.N., Shavitz, A., Libenson, A., Landsman, M., Perdrial, N., Armfield, J., Adler, T., and Shanley, J.B., 2019, Soil aggregates as a source of dissolved organic carbon to streams: An experimental study on the effect of solution chemistry on water extractable carbon: Frontiers in Environmental Science, v. 7, 172, 14 p., https://doi.org/10.3389/fenvs.2019.00172.","productDescription":"172, 14 p.","ipdsId":"IP-106555","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":459236,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2019.00172","text":"Publisher Index Page"},{"id":379915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Sleepers River Research Watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.17468261718749,\n              44.268804788566165\n            ],\n            [\n              -71.6033935546875,\n              44.268804788566165\n            ],\n            [\n              -71.6033935546875,\n              44.5435052132082\n            ],\n            [\n              -72.17468261718749,\n              44.5435052132082\n            ],\n            [\n              -72.17468261718749,\n              44.268804788566165\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","noUsgsAuthors":false,"publicationDate":"2019-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Cincotta, Malayika M.","contributorId":244151,"corporation":false,"usgs":false,"family":"Cincotta","given":"Malayika","email":"","middleInitial":"M.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":803435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perdrial, Julia N.","contributorId":177340,"corporation":false,"usgs":false,"family":"Perdrial","given":"Julia","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":803436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shavitz, Aaron","contributorId":244152,"corporation":false,"usgs":false,"family":"Shavitz","given":"Aaron","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":803437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Libenson, Arianna","contributorId":244153,"corporation":false,"usgs":false,"family":"Libenson","given":"Arianna","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":803438,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landsman, Maxwell","contributorId":244154,"corporation":false,"usgs":false,"family":"Landsman","given":"Maxwell","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":803439,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perdrial, Nicolas","contributorId":198718,"corporation":false,"usgs":false,"family":"Perdrial","given":"Nicolas","email":"","affiliations":[],"preferred":false,"id":803440,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Armfield, Jesse","contributorId":244155,"corporation":false,"usgs":false,"family":"Armfield","given":"Jesse","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":803441,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Adler, Thomas","contributorId":244156,"corporation":false,"usgs":false,"family":"Adler","given":"Thomas","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":803442,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803443,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70220400,"text":"70220400 - 2019 - 300,000 yr history of water-table fluctuations at Wind Cave, South Dakota, USA—Scale, timing, and groundwater mixing in the Madison Aquifer","interactions":[],"lastModifiedDate":"2021-05-11T11:56:33.042551","indexId":"70220400","displayToPublicDate":"2019-11-07T06:51:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"300,000 yr history of water-table fluctuations at Wind Cave, South Dakota, USA—Scale, timing, and groundwater mixing in the Madison Aquifer","docAbstract":"<p>Deposits of calcite coating the lower passages of Wind Cave in the southern Black Hills of South Dakota were precipitated under phreatic conditions. Data from samples associated with a new cave survey and hydrologic studies indicate that past water tables within Wind Cave reached a maximum height of 45 m above modern levels but were mostly confined to 25 m or less. Uranium-series ages for basal layers deposited on weathered wall rock indicate subaerial conditions in this part of the cave persisted between 1000 and 300 ka. Ages and elevations of wall coatings and cave rafts establish a 300,000 yr paleohydrograph indicating that water-table highstands occurred during interglacial or interstadial-to-early glacial periods and lowstands occurred during full-glacial and stadial episodes.</p><p>Isotopes of Sr, U, C, and O from dated calcite samples were obtained to evaluate potential shifts in paleo-groundwater composition. For comparison, Sr and U isotopic compositions were determined for modern groundwater from 18 sites previously classified into five hydrogeologic domains. Isotope data for different domains tend to cluster in separate fields, although several fields overlap. Compositions of Calcite Lake (informal name) water reflect modern recharge to shallow aquifers. In contrast, speleothem data indicate that paleo-groundwater highstands were not supported by increased infiltration associated with local recharge, or by upwelling from deeper Proterozoic sources. Instead, cave water was similar to deeper, warmer groundwater from the Madison Aquifer discharging at modern artesian springs flanking the southern Black Hills. Highstands were likely influenced by large-scale hydraulic processes associated with recharge to the Madison Aquifer under the Laurentide ice sheet on the northeast side of the Williston Basin, causing increased hydrostatic pressures in confined aquifers on the south side of the basin.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35312.1","usgsCitation":"Paces, J.B., Palmer, M.V., Palmer, A.N., Long, A.J., and Emmons, M.P., 2019, 300,000 yr history of water-table fluctuations at Wind Cave, South Dakota, USA—Scale, timing, and groundwater mixing in the Madison Aquifer: GSA Bulletin, v. 132, no. 7-8, p. 1447-1468, https://doi.org/10.1130/B35312.1.","productDescription":"22 p.","startPage":"1447","endPage":"1468","ipdsId":"IP-102435","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":385560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"South Dakota","city":"Rapid City, Hot Springs","otherGeospatial":"southern Black Hills","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.029541015625,\n              42.98857645832184\n            ],\n            [\n              -103.095703125,\n              42.98857645832184\n            ],\n            [\n              -103.095703125,\n              44.33956524809713\n            ],\n            [\n              -104.029541015625,\n              44.33956524809713\n            ],\n            [\n              -104.029541015625,\n              42.98857645832184\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"132","issue":"7-8","noUsgsAuthors":false,"publicationDate":"2019-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":215864,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":815425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmer, Margaret V.","contributorId":257970,"corporation":false,"usgs":false,"family":"Palmer","given":"Margaret","email":"","middleInitial":"V.","affiliations":[{"id":52191,"text":"State University of New York, Oneonta","active":true,"usgs":false}],"preferred":false,"id":815426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmer, Arthur N. 0000-0002-2770-0053","orcid":"https://orcid.org/0000-0002-2770-0053","contributorId":257971,"corporation":false,"usgs":false,"family":"Palmer","given":"Arthur","email":"","middleInitial":"N.","affiliations":[{"id":52191,"text":"State University of New York, Oneonta","active":true,"usgs":false}],"preferred":false,"id":815427,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Long, Andrew J. 0000-0001-7385-8081 ajlong@usgs.gov","orcid":"https://orcid.org/0000-0001-7385-8081","contributorId":989,"corporation":false,"usgs":true,"family":"Long","given":"Andrew","email":"ajlong@usgs.gov","middleInitial":"J.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815428,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Emmons, Matthew P. 0000-0002-3429-396X memmons@usgs.gov","orcid":"https://orcid.org/0000-0002-3429-396X","contributorId":5023,"corporation":false,"usgs":true,"family":"Emmons","given":"Matthew","email":"memmons@usgs.gov","middleInitial":"P.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":815429,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70206838,"text":"70206838 - 2019 - Protracted multipulse emplacement of a post-resurgent pluton: The case of Platoro caldera complex (Southern Rocky Mountain volcanic field, Colorado)","interactions":[],"lastModifiedDate":"2020-01-03T10:46:18","indexId":"70206838","displayToPublicDate":"2019-11-07T06:44:18","publicationYear":"2019","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":"Protracted multipulse emplacement of a post-resurgent pluton: The case of Platoro caldera complex (Southern Rocky Mountain volcanic field, Colorado)","docAbstract":"Many eroded calderas expose associated postcollapse plutons, but detailed fieldwork‐supported\nstudies have rarely focused on the internal structure that can contribute to understanding of emplacement dynamics. The Alamosa River monzonite pluton is a postcollapse intrusion at the Platoro caldera complex that erupted six large ignimbrites between 30.2 and 28.8 Ma in the Southern Rocky Mountains volcanic field. Magnetic fabrics in this intrusion indicate the pulsed emplacement of a vertically extensive pluton. The magmatic pulses are documented by three concentric domains of magnetic foliations elongated in ~NE‐SW direction, corresponding to structural trends at the Platoro caldera complex and preexisting regional structures. As no evidence for deformation of wall rocks and the adjacent resurgent block has been identified, we interpret the Alamosa River pluton as a postresurgent intrusion. The space‐opening process\ninvolved magmatic stoping and small‐scale magma wedging. New SHRIMP‐RG U/Pb zircon dates (28.98 ±0.18, 27.42 ± 0.35, and 27.32 ± 0.38 Ma) suggest a magmatic lifespan of ~1.7 My for the Alamosa River pluton. Our results indicate that postcaldera magmatism includes pulsed and protracted activity from large intracaldera resurgent plutons to smaller postresurgent stocks and sheeted complexes. As demonstrated by the Alamosa River pluton, some intrusions are emplaced shortly after collapse and resurgence, but postcaldera volcano‐plutonic systems may remain active for several million years or more. We also suggest that subvolcanic magma bodies may be assembled incrementally and that the record of early composite magma lenses preserved as magma wedges are later obliterated by convective flowage and crystallization.","language":"English","publisher":"Wiley","doi":"10.1029/2019GC008477","usgsCitation":"Tomek, F., Gilmer, A.K., Petronis, M.S., Lipman, P.W., and Foucher, M.S., 2019, Protracted multipulse emplacement of a post-resurgent pluton: The case of Platoro caldera complex (Southern Rocky Mountain volcanic field, Colorado): Geochemistry, Geophysics, Geosystems, v. 20, no. 11, p. 5225-5250, https://doi.org/10.1029/2019GC008477.","productDescription":"26 p.","startPage":"5225","endPage":"5250","ipdsId":"IP-108672","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":369518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Southern Rocky Mountain Volcanic Field","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108,\n              40\n            ],\n            [\n              -104,\n              40\n            ],\n            [\n              -104,\n              36\n            ],\n            [\n              -108,\n              36\n            ],\n            [\n              -108,\n              40\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Tomek, Filip 0000-0002-1040-0193","orcid":"https://orcid.org/0000-0002-1040-0193","contributorId":220856,"corporation":false,"usgs":false,"family":"Tomek","given":"Filip","email":"","affiliations":[{"id":40285,"text":"Czech Academy of Sciences, Institute of Geology","active":true,"usgs":false}],"preferred":false,"id":776003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":776002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petronis, M. S.","contributorId":220857,"corporation":false,"usgs":false,"family":"Petronis","given":"M.","email":"","middleInitial":"S.","affiliations":[{"id":40286,"text":"Environmental Geology, Natural Resources Management Department, New Mexico Highlands University","active":true,"usgs":false}],"preferred":false,"id":776004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lipman, Peter W. 0000-0001-9175-6118","orcid":"https://orcid.org/0000-0001-9175-6118","contributorId":203612,"corporation":false,"usgs":true,"family":"Lipman","given":"Peter","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":776005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foucher, M. S. 0000-0001-7840-7298","orcid":"https://orcid.org/0000-0001-7840-7298","contributorId":220858,"corporation":false,"usgs":false,"family":"Foucher","given":"M.","email":"","middleInitial":"S.","affiliations":[{"id":40287,"text":"Department of Geological and Mining Engineering and Sciences, Michigan Technological University","active":true,"usgs":false}],"preferred":false,"id":776006,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70206606,"text":"70206606 - 2019 - Phytoplankton community and algal toxicity at a recurring bloom in Sullivan Bay, Kabetogama Lake, Minnesota, USA","interactions":[],"lastModifiedDate":"2019-11-13T12:49:22","indexId":"70206606","displayToPublicDate":"2019-11-06T12:41:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Phytoplankton community and algal toxicity at a recurring bloom in Sullivan Bay, Kabetogama Lake, Minnesota, USA","docAbstract":"Kabetogama Lake in Voyageurs National Park, Minnesota, USA suffers from recurring late summer algal blooms that often contain toxin-producing cyanobacteria. Previous research identified the toxin microcystin in blooms, but we wanted to better understand how the algal and cyanobacterial community changed throughout an open water season and how changes in community structure were related to toxin production. Therefore, we sampled one recurring bloom location throughout the entire open water season. The uniqueness of this study is the absence of urban and agricultural nutrient sources, the remote location, and the collection of samples before any visible blooms were present. Through quantitative polymerase chain reaction (qPCR), we discovered that toxin-forming cyanobacteria were present before visible blooms and toxins not previously detected in this region (anatoxin-a and saxitoxin) were present, indicating that sampling for additional toxins and sampling earlier in the season may be necessary to assess ecosystems and human health risk.","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-52639-y","usgsCitation":"Christensen, V., Maki, R.P., Stelzer, E., Norland, J.E., and Khan, E., 2019, Phytoplankton community and algal toxicity at a recurring bloom in Sullivan Bay, Kabetogama Lake, Minnesota, USA: Scientific Reports, v. 9, 16129, 11 p., https://doi.org/10.1038/s41598-019-52639-y.","productDescription":"16129, 11 p.","ipdsId":"IP-102539","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":459242,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-52639-y","text":"Publisher Index Page"},{"id":437288,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XO3SGF","text":"USGS data release","linkHelpText":"Phytoplankton enumeration and identification from a recurring algal bloom location in Sullivan Bay, Kabetogama Lake, northern Minnesota, 2016"},{"id":369169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Kabetogama Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.1365966796875,\n              48.39729713260604\n            ],\n            [\n              -92.80288696289062,\n              48.39729713260604\n            ],\n            [\n              -92.80288696289062,\n              48.54752375797609\n            ],\n            [\n              -93.1365966796875,\n              48.54752375797609\n            ],\n            [\n              -93.1365966796875,\n              48.39729713260604\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":775154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maki, Ryan P.","contributorId":177488,"corporation":false,"usgs":false,"family":"Maki","given":"Ryan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":775155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stelzer, Erin A. 0000-0001-7645-7603","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":220549,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":775156,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norland, Jack E.","contributorId":214257,"corporation":false,"usgs":false,"family":"Norland","given":"Jack","email":"","middleInitial":"E.","affiliations":[{"id":39001,"text":"School of Natural Resources Sciences, North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":775158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Khan, Eakalak","contributorId":220550,"corporation":false,"usgs":false,"family":"Khan","given":"Eakalak","email":"","affiliations":[{"id":40182,"text":"University of Nevada Las Vegas","active":true,"usgs":false}],"preferred":false,"id":775157,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70206244,"text":"sir20195124 - 2019 - Updates to the Madison Lake (Minnesota) CE–QUAL–W2 water-quality model for assessing algal community dynamics","interactions":[],"lastModifiedDate":"2019-12-05T09:47:00","indexId":"sir20195124","displayToPublicDate":"2019-11-06T10:02:47","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5124","displayTitle":"Updates to the Madison Lake (Minnesota) CE–QUAL–W2 Water-Quality Model for Assessing Algal Community Dynamics","title":"Updates to the Madison Lake (Minnesota) CE–QUAL–W2 water-quality model for assessing algal community dynamics","docAbstract":"<p>A previously developed CE–QUAL–W2 model for Madison Lake, Minnesota, simulated the algal community dynamics, water quality, and fish habitat suitability of Madison Lake under recent (2014) meteorological conditions. Additionally, this previously developed model simulated the complex interplay between external nutrient loading, internal nutrient loading from sediment release of phosphorus, and the organic matter decomposition of the algal biomass. However, the partitioning of Cyanophyta within the modeling framework was simplified to one group and did not account for how different Cyanophyta populations are affected by light conditions, use of nitrogen, temperature growth ranges, and differences in settling rates. Properly capturing Cyanophyta dynamics is important given the potential risks posed by potential large algal blooms. For example, when Cyanophyta form large blooms, recreational activities can become restricted in certain areas because of thick algal scums or algal mats, in addition to the possible production of a class of toxins, known as cyanotoxins, capable of threatening human health, domestic animals, and wildlife. Therefore, we updated the model to partition the Cyanophyta into a group that fixed nitrogen and a second, more buoyant Cyanophyta group that did not independently fix nitrogen.</p><p>The U.S. Geological Survey, in cooperation with the St. Croix Watershed Research Station (Science Museum of Minnesota) with support from the Environmental and Natural Resources Trust Fund of Minnesota (Legislative-Citizen Commission on Minnesota Resources), updated the Madison Lake CE–QUAL–W2 model to address the shortcomings of simulating Cyanophyta in the previously developed model and better characterize Cyanophyta into two groups. In addition to updating the Cyanophyta group differentiation, the part of the model that handles the simulation of algal community dynamics was updated while preserving model predictive capabilities for nutrients, water temperature, and dissolved oxygen. The calibration and validation of the model was done under recent meteorological conditions with large and persistent Cyanophyta blooms (2014 and 2016).</p><p>Overall, the model simulations predicted the persistently large total phosphorus concentrations in the hypolimnion of Madison Lake and key differences in nutrient concentrations between 2014 and 2016. The Cyanophyta bloom persistence throughout the summer was also simulated by the model in 2014 and 2016, a critical goal of the model update. Finally, monthly total phosphorus budgets were calculated for the updated Madison Lake model for 2014 and 2016.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195124","collaboration":"Prepared in cooperation with the Legislative-Citizen Commission on Minnesota Resources and St. Croix Watershed Research Station—Science Museum of Minnesota","usgsCitation":"Smith, E.A., and Kiesling, R.L., 2019, Updates to the Madison Lake (Minnesota) CE–QUAL–W2 water-quality model for assessing algal community dynamics: U.S. Geological Survey Scientific Investigations Report 2019–5124, 35 p., https://doi.org/10.3133/sir20195124.","productDescription":"Report: viii, 35 p.; Data Release","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-109825","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":368957,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5124/coverthb.jpg"},{"id":368958,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5124/sir20195124.pdf","text":"Report","size":"1.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5124"},{"id":368959,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92YEVPO","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Updated CE–QUAL–W2 water-quality model for Madison Lake, Minnesota (2014 and 2016)"}],"country":"United States","state":"Minnesota","county":"Blue Earth County","otherGeospatial":"Madison Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.82830619812012,\n              44.17063113749022\n            ],\n            [\n              -93.77620697021484,\n              44.17063113749022\n            ],\n            [\n              -93.77620697021484,\n              44.20368152239254\n            ],\n            [\n              -93.82830619812012,\n              44.20368152239254\n            ],\n            [\n              -93.82830619812012,\n              44.17063113749022\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/umid-water\" href=\"https://www.usgs.gov/centers/umid-water\">Upper Midwest Water Science Center</a> <br>U.S. Geological Survey<br>2280 Woodale Drive <br>Mounds View, MN 55112</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods and Data</li><li>Model Calibration and Validation</li><li>Phosphorus Loads</li><li>Model Limitations</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2019-11-06","noUsgsAuthors":false,"publicationDate":"2019-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Erik A. 0000-0001-8434-0798 easmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8434-0798","contributorId":1405,"corporation":false,"usgs":true,"family":"Smith","given":"Erik","email":"easmith@usgs.gov","middleInitial":"A.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773920,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70206419,"text":"sir20195129 - 2019 - The lava flow that came to Hilo—The 1880–81 eruption of Mauna Loa volcano, Island of Hawai‘i","interactions":[],"lastModifiedDate":"2019-11-07T06:37:44","indexId":"sir20195129","displayToPublicDate":"2019-11-06T09:58:24","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5129","displayTitle":"The Lava Flow that Came to Hilo—The 1880–81 Eruption of Mauna Loa Volcano, Island of Hawai‘i","title":"The lava flow that came to Hilo—The 1880–81 eruption of Mauna Loa volcano, Island of Hawai‘i","docAbstract":"<p>The Mauna Loa eruption sequence of 1880–81 consists of two eruptions. The May 1880 eruption in Mokuʻāweoweo at the summit of Mauna Loa lasted just a few days and was followed 6 months later by three lava flows that issued from vents along the Northeast Rift Zone. The November 1880 eruption lasted almost a year and one of its flows nearly reached Hilo Bay.</p><p>Public reaction in Hilo to the advancing lava flow increased as the lava got closer, but a smallpox quarantine prevented travelers and government officials from leaving Honolulu, the government seat of the Hawaiian Kingdom, until July 1881. In the King’s absence, his sister Princess Regent Liliʻuokalani and key officials met in Hilo at the beginning of August to plan a government response. This included the first known plan to use barriers and explosives to divert the lava flow in Hawaiʻi. Fortunately, the lava flow stopped before the plan was enacted; however, both Christian prayer and traditional Hawaiian chants and gifts to the Hawaiian deity Pele were offered in the last few weeks of lava activity.</p><p>Mauna Loa was again restless in 2019 and the time seems optimum to review this and other Mauna Loa flows, in order to be ready for the next lava flow. Should the next flow threaten developed areas, review of past lava flow threats may provide valuable experience on how the public may best be provided with information.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195129","usgsCitation":"Kauahikaua, J., Gaddis, B., Kanahele, K., Hon, K., and Wasser, V., 2019, The lava flow that came to Hilo—The 1880–81 eruption of Mauna Loa volcano, Island of Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2019–5129, 35 p., https://doi.org/10.3133/sir20195129.","productDescription":"iv, 35 p.","onlineOnly":"N","ipdsId":"IP-103587","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":368962,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5129/sir20195129.pdf","text":"Report","size":"70 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5129"},{"id":368961,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5129/coverthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.61241149902344,\n              19.41673522857577\n            ],\n            [\n              -155.55198669433594,\n              19.41673522857577\n            ],\n            [\n              -155.55198669433594,\n              19.50866738207669\n            ],\n            [\n              -155.61241149902344,\n              19.50866738207669\n            ],\n            [\n              -155.61241149902344,\n              19.41673522857577\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://volcanoes.usgs.gov/observatories/hvo/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://volcanoes.usgs.gov/observatories/hvo/\">Hawaiian Volcano Observatory</a><br><a data-mce-href=\"https://usgs.gov/\" href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>1266 Kamehameha Avenue, Suite A-8<br>Hilo, HI 96720</p>","tableOfContents":"<p></p><ul><li>Abstract</li><li>Introduction</li><li>Sources of Eruption Information</li><li>Hilo in 1880</li><li>Pelehonuamea</li><li>Moku‘āweoweo Eruption May 1, 1880</li><li>Northeast Rift Zone Eruption Started November 5, 1880</li><li>When Did the Eruption End?</li><li>Conclusions</li><li>What We Learned from Revisiting the 1880–81 Lava Flow</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix</li></ul><p></p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-11-06","noUsgsAuthors":false,"publicationDate":"2019-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Kauahikaua, James P. 0000-0003-3777-503X jimk@usgs.gov","orcid":"https://orcid.org/0000-0003-3777-503X","contributorId":2146,"corporation":false,"usgs":true,"family":"Kauahikaua","given":"James","email":"jimk@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":774484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaddis, Ben 0000-0001-7280-353X","orcid":"https://orcid.org/0000-0001-7280-353X","contributorId":203453,"corporation":false,"usgs":true,"family":"Gaddis","given":"Ben","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":774488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kanahele, Ku`ulei","contributorId":192259,"corporation":false,"usgs":false,"family":"Kanahele","given":"Ku`ulei","email":"","affiliations":[],"preferred":false,"id":774485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hon, Ken","contributorId":220212,"corporation":false,"usgs":false,"family":"Hon","given":"Ken","email":"","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":774486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wasser, Valerie","contributorId":220213,"corporation":false,"usgs":false,"family":"Wasser","given":"Valerie","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":774487,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
]}