This 1:100,000-scale geologic map of the South Boston 30’ × 60’ quadrangle, Virginia and North Carolina, provides geologic information for the Piedmont along the I–85 and U.S. Route 58 corridors and in the Roanoke River watershed, which includes the John H. Kerr Reservoir and Lake Gaston. The Raleigh terrane (located on the eastern side of the map) contains Neoproterozoic to early Paleozoic(?) polydeformed, amphibolite-facies gneisses and schists. The Carolina slate belt of the Carolina terrane (located in the central part of the map) contains Neoproterozoic metavolcanic and metasedimentary rocks at greenschist facies. Although locally complicated, the slate-belt structure mapped across the South Boston map area is generally a broad, complex anticlinorium of the Hyco Formation (here called the Chase City anticlinorium) and is flanked to the west and east by synclinoria, which are cored by the overlying Aaron and Virgilina Formations. The western flank of the Carolina terrane (located in the western-central part of the map) contains similar rocks at higher metamorphic grade. This terrane includes epidote-amphibolite-facies to amphibolite-facies gneisses of the Neoproterozoic Country Line complex, which extends north-northeastward across the map. The Milton terrane (located on the western side of the map) contains Ordovician amphibolite-facies metavolcanic and metasedimentary gneisses of the Cunningham complex.
Crosscutting relations and fabrics in mafic to felsic plutonic rocks constrain the timing of Neoproterozoic to late Paleozoic deformations across the Piedmont. In the eastern part of the map, a 5- to 9-kilometer-wide band of tectonic elements that contains two late Paleozoic mylonite zones (Nutbush Creek and Lake Gordon) and syntectonic granite (Buggs Island pluton) separates the Raleigh and Carolina terranes. Amphibolite-facies, infrastructural metaigneous and metasedimentary rocks east of the Lake Gordon mylonite zone are generally assigned to the Raleigh terrane. In the western part of the map area, a 5- to 8-kilometer-wide band of late Paleozoic tectonic elements includes the Hyco and Clover shear zones, syntectonic granitic sheets, and amphibolite-facies gneisses along the western margin of the Carolina terrane at its boundary with the Milton terrane. This band of tectonic elements is also the locus for early Mesozoic extensional faults associated with the early Mesozoic Scottsburg, Randolph, and Roanoke Creek rift basins.
The map shows fluvial terrace deposits of sand and gravel on hills and slopes near the Roanoke and Dan Rivers. The terrace deposits that are highest in altitude are the oldest. Saprolite regolith is spatially associated with geologic source units and is not shown separately on the map.
Mineral resources in the area include gneiss and granite quarried for crushed stone, tungsten-bearing vein deposits of the Hamme district, and copper and gold deposits of the Virgilina district. Surface-water resources are abundant and include rivers, tributaries, the John H. Kerr Reservoir, and Lake Gaston. Groundwater flow is concentrated in saprolite regolith, along fractures in the crystalline bedrock, and along fractures and bedding-plane partings in the Mesozoic rift basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3483","usgsCitation":"Horton, J.W., Jr., Peper, J.D., Burton, W.C., Weems, R.E., and Sacks, P.E., 2022, Geologic map of the South Boston 30' × 60' quadrangle, Virginia and North Carolina: U.S. Geological Survey Scientific Investigations Map 3483, 1 sheet, scale 1:100,000, 46-p. pamphlet, https://doi.org/10.3133/sim3483. [Supersedes USGS Open-File Report 93–244.]","productDescription":"Pamphlet: vi, 46 p.; 1 Sheet: 62.00 x 35.00 inches; Data Release","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112223","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":501889,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112691.htm","linkFileType":{"id":5,"text":"html"}},{"id":396136,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3483/sim3483_map.pdf","text":"Map","size":"38.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3483 map"},{"id":396134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3483/coverthb2.jpg"},{"id":396135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3483/sim3483_pamphlet.pdf","text":"Pamphlet","size":"871 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3483 pamphlet"},{"id":396935,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98AQDR7","text":"USGS data release","linkHelpText":"Database for the Geologic Map of the South Boston 30' × 60' Quadrangle, Virginia and North Carolina"}],"country":"United States","state":"North Carolina, Virginia","otherGeospatial":"South Boston 30 x 60 minute quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79,\n 36.5\n ],\n [\n -78,\n 36.5\n ],\n [\n -78,\n 37\n ],\n [\n -79,\n 37\n ],\n [\n -79,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Florence Bascom Geoscience Center
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Reston, VA 20192
Spring viremia of carp virus (SVCV), is a lethal freshwater pathogen of cyprinid fish, and Cyprinus carpio koi is a primary host species. The virus was initially described in the 1960s after outbreaks occurred in Europe, but a global expansion of SVCV has been ongoing since the late 1990s. Genetic typing of SVCV isolates separates them into 4 genotypes that are correlated with geographic origin: Ia (Asia), Ib and Ic (Eastern Europe), and Id (Central Europe). We compared infectivity and virulence of 8 SVCV strains, including 4 uncharacterized Chinese Ia isolates and representatives of genotypes Ia-d in 2 morphologically distinct varieties of koi: long-fin semi-scaled Beni Kikokuryu koi and short-fin fully scaled Sanke koi. Mortality ranged from 4 to 82% in the Beni Kikokuryu koi and 0 to 94% in the Sanke koi following immersion challenge. Genotype Ia isolates of Asian origin had a wide range in virulence (0-94%). Single isolates representing the European genotypes Ib and Ic were moderately virulent (38-56%). Each virus strain produced similar levels of mortality in both koi breeds, with the exception of the SVCV Id strain that appeared to have both moderate and high virulence phenotypes (60% in Beni Kikokuryu koi vs. 87% in Sanke koi). Overall SVCV strain virulence appeared to be a dominant factor in determining disease outcomes, whereas intraspecies variation, based on koi variety, had less of an impact. This study is the first side-by-side comparison of Chinese SVCV isolates and genotype Ia-d strain virulence in a highly susceptible host.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/dao03650","usgsCitation":"Emmenegger, E.J., Bueren, E.K., Jia, P., Hendrix, N., and Liu, H., 2022, Comparative virulence of spring viremia of carp virus (SVCV) genotypes in two koi varieties: Disease of Aquatic Organisms, v. 148, p. 95-112, https://doi.org/10.3354/dao03650.","productDescription":"18 p.","startPage":"95","endPage":"112","ipdsId":"IP-129753","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":448448,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3354/dao03650","text":"External Repository"},{"id":435920,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WS6Q0M","text":"USGS data release","linkHelpText":"Comparative Virulence of Spring Viremia of Carp Virus (SVCV) Genotypes in Two Koi Varieties"},{"id":398121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"148","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Emmenegger, Eveline J. 0000-0001-5217-6030 eemmenegger@usgs.gov","orcid":"https://orcid.org/0000-0001-5217-6030","contributorId":2434,"corporation":false,"usgs":true,"family":"Emmenegger","given":"Eveline","email":"eemmenegger@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":839551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bueren, Emma K. 0000-0002-5738-3917","orcid":"https://orcid.org/0000-0002-5738-3917","contributorId":289657,"corporation":false,"usgs":false,"family":"Bueren","given":"Emma","email":"","middleInitial":"K.","affiliations":[{"id":62212,"text":"Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061","active":true,"usgs":false}],"preferred":false,"id":839552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jia, Peng","contributorId":191750,"corporation":false,"usgs":false,"family":"Jia","given":"Peng","email":"","affiliations":[],"preferred":false,"id":839553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hendrix, Noble","contributorId":289658,"corporation":false,"usgs":false,"family":"Hendrix","given":"Noble","email":"","affiliations":[{"id":62214,"text":"QEDA Consulting, 4007 Densmore Ave N, Seattle, WA 98103, USA","active":true,"usgs":false}],"preferred":false,"id":839554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liu, Hong","contributorId":191763,"corporation":false,"usgs":false,"family":"Liu","given":"Hong","email":"","affiliations":[],"preferred":false,"id":839555,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229768,"text":"70229768 - 2022 - Inherit the kingdom or storm the castle? Breeding strategies in a social carnivore","interactions":[],"lastModifiedDate":"2022-03-17T14:59:55.730675","indexId":"70229768","displayToPublicDate":"2022-03-17T09:54:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1589,"text":"Ethology","active":true,"publicationSubtype":{"id":10}},"title":"Inherit the kingdom or storm the castle? Breeding strategies in a social carnivore","docAbstract":"Breeding opportunities are inherently limited for animals that live and breed in groups. Turnover in breeding positions can have marked effects on groups of cooperative breeders, particularly social carnivores. We generally know little about how breeding vacancies are filled in social carnivores and what factors might influence an individual's ability to successfully fill a vacancy. I used a long-term (11 years) genetic dataset from gray wolves to ask whether breeding vacancies were filled by individuals from within groups or by adoptees (i.e., adult animals immigrating into the group) from outside the group. Males were three times more likely than females to be adopted into breeding positions outside their group. Females typically inherited breeding positions within their natal groups (80%, n = 20), while males obtained breeding positions outside their group (76%, n = 17). Group size did not influence whether a breeding vacancy was filled by an adoptee or inherited by an individual from within the group. Prior to adoption, genetic relatedness was 30% higher in groups when females were adopted into breeding positions compared to when they inherited breeding positions from within groups. Thus, genetic relatedness within groups appears to play a role in whether females are adopted into groups or not. Because of their strong reliance on dispersal to secure a breeding position, male wolves appear to be the couriers of genetic diversity in populations of gray wolves. Many states in the United States have recently implemented hunting and trapping seasons for gray wolves. If dispersing male wolves are disproportionately harvested, genetic connectivity and diversity in populations may be affected.
The sea lamprey (Petromyzon marinus) is an invasive species in the Great Lakes and the focus of a large control and assessment program. Current assessment methods provide information on the census size of spawning adult sea lamprey in a small number of streams, but information characterizing reproductive success of spawning adults is rarely available. We used RAD-capture sequencing to genotype single nucleotide polymorphism (SNP) loci for ~1600 sea lamprey larvae collected from three streams in northern Michigan (Black Mallard, Pigeon, and Ocqueoc Rivers). Larval genotypes were used to reconstruct family pedigrees, which were combined with Gaussian mixture analyses to identify larval age classes for estimation of spawning population size. Two complementary estimates of effective breeding size (Nb), as well as the extrapolated minimum number of spawners (Ns), were also generated for each cohort. Reconstructed pedigrees highlighted inaccuracies of cohort assignments from traditionally used mixture analyses. However, combining genotype-based pedigree information with length-at-age assignment of cohort membership greatly improved cohort identification accuracy. Population estimates across all three streams sampled in this study indicate a small number of successfully spawning adults when barriers were in operation, implying that barriers limited adult spawning numbers but were not completely effective at blocking access to spawning habitats. Thus, the large numbers of larvae present in sampled systems were a poor indicator of spawning adult abundance. Overall, pedigree-based Nb and Ns estimates provide a promising and rapid assessment tool for sea lamprey and other species.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.13364","usgsCitation":"Weise, E.M., Scribner, K.T., Adams, J.V., Boeberitz, O., Jubar, A.K., Bravener, G., Johnson, N.S., and Robinson, J.D., 2022, Pedigree analysis and estimates of effective breeding size characterize sea lamprey reproductive biology: Evolutionary Applications, v. 15, no. 3, p. 484-500, https://doi.org/10.1111/eva.13364.","productDescription":"17 p.","startPage":"484","endPage":"500","ipdsId":"IP-130783","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":448450,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/eva.13364","text":"External Repository"},{"id":397235,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Black Mallard River, Ocqueoc River, Pigeon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.48211669921875,\n 45.408092022812276\n ],\n [\n -84.21501159667969,\n 45.408092022812276\n ],\n [\n -84.21501159667969,\n 45.6716438522655\n ],\n [\n -84.48211669921875,\n 45.6716438522655\n ],\n [\n -84.48211669921875,\n 45.408092022812276\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Weise, Ellen M.","contributorId":288846,"corporation":false,"usgs":false,"family":"Weise","given":"Ellen","email":"","middleInitial":"M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":838310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scribner, Kim T.","contributorId":146113,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim","email":"","middleInitial":"T.","affiliations":[{"id":135,"text":"Biological Resources Division","active":false,"usgs":true},{"id":16582,"text":"Department of Fisheries and Wildlife and Department of Zoology, 480 Wilson Rd. 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":838311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":838312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boeberitz, Olivia","contributorId":288848,"corporation":false,"usgs":false,"family":"Boeberitz","given":"Olivia","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":838313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jubar, Aaron K.","contributorId":150999,"corporation":false,"usgs":false,"family":"Jubar","given":"Aaron","email":"","middleInitial":"K.","affiliations":[{"id":18161,"text":"US Fish and Wildlife Service, Lundington Biological Station","active":true,"usgs":false}],"preferred":false,"id":838314,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bravener, Gale","contributorId":150995,"corporation":false,"usgs":false,"family":"Bravener","given":"Gale","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":838315,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":597,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":838316,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Robinson, John D.","contributorId":288851,"corporation":false,"usgs":false,"family":"Robinson","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":838317,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70230003,"text":"70230003 - 2022 - Special Issue on PFAS","interactions":[],"lastModifiedDate":"2022-03-23T14:28:50.591852","indexId":"70230003","displayToPublicDate":"2022-03-17T09:24:48","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":10522,"text":"GeoHEALTH–USGS Newsletter","active":true,"publicationSubtype":{"id":30}},"title":"Special Issue on PFAS","docAbstract":"No abstract available.
","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Iwanowicz, D.D., 2022, Special Issue on PFAS: GeoHEALTH–USGS Newsletter, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-139302","costCenters":[{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":397458,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397457,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/geohealth-usgs/geohealth-usgs-special-issue-pfas"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":838627,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70229808,"text":"70229808 - 2022 - Temporal greenness trends in stable natural land cover and relationships with climatic variability across the conterminous United States","interactions":[],"lastModifiedDate":"2022-03-17T13:30:53.219328","indexId":"70229808","displayToPublicDate":"2022-03-17T08:23:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Temporal greenness trends in stable natural land cover and relationships with climatic variability across the conterminous United States","docAbstract":"Assessment of temporal trends in vegetation greenness and related influences aids understanding of recent change in terrestrial ecosystems and feedbacks from weather, climate, and environment. We analyzed 1-km normalized difference vegetation index (NDVI) timeseries data (1989–2016) derived from the Advanced Very High Resolution Radiometer (AVHRR) and developed growing season time-integrated NDVI (GS-TIN) for estimating seasonal vegetation activity across stable natural land cover in the conterminous United States (CONUS). After removing areas from analysis that had experienced land cover conversion or modification, we conducted a monotonic trend analysis on the GS-TIN timeseries and found that significant positive temporal trends occurred over 35% of the area, while significant negative trends were observed over only 3.5%. Positive trends were prevalent in the forested lands of the eastern third of CONUS and far northwest, as well as in grasslands in the north central plains. We observed negative and nonsignificant trends mainly in the shrublands and grasslands across the northwest, southwest, and west central plains. To understand the relationship of climate variability with these temporal trends, we conducted partial and multiple correlation analyses on GS-TIN, growing season temperature, and water-year precipitation timeseries. The GS-TIN trends in northern forests were positively correlated with temperature. The GS-TIN trends in the central and western shrublands and grasslands were negatively correlated with temperature and positively correlated with precipitation. Our results revealed spatial patterns in vegetation greenness trends for different stable natural vegetation types across CONUS, enhancing understanding gained from prior studies based on coarser 8-km AVHRR data.","language":"English","publisher":"American Meteorological Society","doi":"10.1175/EI-D-21-0018.1","usgsCitation":"Ji, L., and Brown, J.F., 2022, Temporal greenness trends in stable natural land cover and relationships with climatic variability across the conterminous United States: Earth Interactions, v. 26, no. 1, p. 66-83, https://doi.org/10.1175/EI-D-21-0018.1.","productDescription":"18 p.","startPage":"66","endPage":"83","ipdsId":"IP-112507","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":448451,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/ei-d-21-0018.1","text":"Publisher Index 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lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":139587,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":838423,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":838424,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236084,"text":"70236084 - 2022 - Regional-scale liquefaction analyses","interactions":[],"lastModifiedDate":"2022-08-30T10:53:02.18042","indexId":"70236084","displayToPublicDate":"2022-03-17T08:19:53","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Regional-scale liquefaction analyses","docAbstract":"Regional-scale liquefaction hazard analyses are necessary for resilience planning and prioritization of seismic upgrades for critical distributed infrastructure such as levees, pipelines, roadways, and electrical transmission facilities. Two approaches are often considered for liquefaction hazard analysis of distributed infrastructure: (1) conventional, site-specific probe or borehole-based analyses, which do not quantify the uncertainty between investigation locations; or (2) surface geology-based analyses, which often neglect localized geotechnical properties and include a great amount of uncertainty. We describe an analytical method to unify the disparate site-specific and deposit-scale approaches using Gaussian processes. We use borehole data to produce spatial fields of random variables for liquefaction triggering analyses, such as groundwater elevation, soil texture classification, penetration resistance, and cyclic resistance ratio that converge to the site-specific uncertainty at sampling locations but also quantify the uncertainty in-between sampling locations. We demonstrate the effectiveness of Gaussian process models for regional-scale liquefaction hazard analyses in two example studies in Washington state and California, US.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geo-Congress 2022: Geophysical and earthquake engineering and soil dynamics","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Geo-Congress 2022","conferenceDate":"March 20-23, 2022","conferenceLocation":"Charlotte, NC","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/9780784484043.039","usgsCitation":"Greenfield, M.W., and Grant, A.R., 2022, Regional-scale liquefaction analyses, in Geo-Congress 2022: Geophysical and earthquake engineering and soil dynamics, Charlotte, NC, March 20-23, 2022, p. 401-410, https://doi.org/10.1061/9780784484043.039.","productDescription":"10 p.","startPage":"401","endPage":"410","ipdsId":"IP-130480","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":405788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Greenfield, Michael W.","contributorId":267916,"corporation":false,"usgs":false,"family":"Greenfield","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":40903,"text":"Greenfield Geotechnical, Portland, OR","active":true,"usgs":false}],"preferred":false,"id":849956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":849957,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70241061,"text":"70241061 - 2022 - Volcanic unrest at Nevados de Chillán (Southern Andean Volcanic Zone) from January 2019 to November 2020, imaged by DInSAR","interactions":[],"lastModifiedDate":"2023-03-08T13:10:50.779908","indexId":"70241061","displayToPublicDate":"2022-03-17T07:02:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Volcanic unrest at Nevados de Chillán (Southern Andean Volcanic Zone) from January 2019 to November 2020, imaged by DInSAR","docAbstract":"The volcanic complex of Nevados de Chillán, located in the Southern Volcanic Zone (SVZ) of the Andes, has been active for the past 640 ± 20 ka. Its volcanic activity includes dome forming eruptions, explosive events, and lava flows. The most recent eruption cycle started in January 2016. We employ DInSAR time-series from Sentinel-1 data to investigate the unrest episode from January 2019 to November 2020. Two distinct periods of unrest are recognized in the time series. The first period (from January to October 2019) coincides with explosive events, dome growth inside the active crater, and a decrease in seismic activity but does not present a significant deformation. The second period (October 2019 to November 2020) is characterized by a displacement towards the sensor's line-of-sight of 100–120 mm. The observed surface deformation is compatible with an inflation source approximately 1.5 km south-southwest of the present active vent, at 5.5 ± 0.5 km depth from the surface, and with a volume change of 0.044 ± 0.014 km3. The most likely explanation for the observed inflation of Nevados de Chillan is the intrusion of magma in a reservoir feeding the current eruption cycle.
Field and laboratory studies of the 1959 Kīlauea Iki lava lake have provided insight into differentiation processes in mafic magma chambers. This paper explores how partially molten basaltic mushes responded to unloading as a consequence of drilling. Most holes drilled from 1967 to 1979 terminated in a melt-rich internal differentiate with a sharp crust-melt interface. These interfaces were not stable, so the boreholes were backfilled by melt-rich (<5% crystal) ooze. This process, with melt ascent rates of 1.3–4.2 m/s, occurred within minutes of intersecting the bodies, mimicking volcanic eruptions, albeit on a small scale.
One borehole (KI79-1), which did not encounter such a discontinuity, was backfilled over a period of 16 days by upward flow of crystal-rich mushes rather than melt-rich ooze. The first interval of ooze recovered had undergone extensive internal differentiation. Its most conspicuous feature was production of melt-rich layers by lateral migration of interstitial melt from the wallrock into the rising crystal-rich mush. In addition, two smaller-scale processes occurred within the rising mush: segregation of melt into discrete blebs within the rising mush column and aggregation of groundmass crystals into crystal-rich clumps formed adjacent to coarser olivine crystals. The upper parts of the ooze are enriched in melt relative to deeper samples, which suggests that the melt blebs rose relative to their olivine-rich matrix. Similar melt blebs and crystal-rich clumps are observed in naturally occurring diapiric bodies within the lava lake. These processes appear to be intrinsic to the upwelling of narrow cylindrical mush bodies whether constrained within a borehole (like the oozes) or unconstrained (as were the diapirs in the lava lake).
The most striking behavior observed during repeated reentry of KI79-1 was a sharp change in rheology during the second and third re-entries of the borehole. The shift in behavior observed was that the oozes rose up the borehole, with ascent rates of 1.0–1.7 m/s, which are comparable to the rates of the crystal-poor oozes from melt-rich internal differentiates. These oozes contain more melt than the original core at equivalent depths, presumably because melt moved relative to crystals down the pressure gradient created by the open borehole. Groundmass textures in these inflated mushes show erosion of crystal outlines, especially of grain-to-grain contacts between different phases, so that the tenuous crystalline network observed in the original core samples was replaced by rounded crystals in continuous melt at crystallinities of 55–65 vol%. The transition from stable coherent mush to inflatable mush occurred at 25–28 vol% melt. This behavior appears similar to certain types of reactive transport observed in other studies.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36248.1","usgsCitation":"Helz, R.L., 2022, Melt surges, flow differentiation, and remobilization of crystal-rich mushes in response to unloading: Observations from Kīlauea Iki lava lake, Hawaii: GSA Bulletin, v. 134, no. 11-12, p. 3123-3141, https://doi.org/10.1130/B36248.1.","productDescription":"9 p.","startPage":"3123","endPage":"3141","ipdsId":"IP-121979","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":448456,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b36248.1","text":"Publisher Index Page"},{"id":404990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Iki lava lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.45654296875,\n 19.134789188332523\n ],\n [\n -155.006103515625,\n 19.134789188332523\n ],\n [\n -155.006103515625,\n 19.482128945320483\n ],\n [\n -155.45654296875,\n 19.482128945320483\n ],\n [\n -155.45654296875,\n 19.134789188332523\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"134","issue":"11-12","noUsgsAuthors":false,"publicationDate":"2022-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Helz, Rosalind L. 0000-0003-1550-0684 rhelz@usgs.gov","orcid":"https://orcid.org/0000-0003-1550-0684","contributorId":1952,"corporation":false,"usgs":true,"family":"Helz","given":"Rosalind","email":"rhelz@usgs.gov","middleInitial":"L.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":848574,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239283,"text":"70239283 - 2022 - Using ensemble data assimilation to estimate transient hydrologic exchange flow under highly dynamic flow conditions","interactions":[],"lastModifiedDate":"2023-01-06T12:40:06.995804","indexId":"70239283","displayToPublicDate":"2022-03-17T06:34:22","publicationYear":"2022","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":"Using ensemble data assimilation to estimate transient hydrologic exchange flow under highly dynamic flow conditions","docAbstract":"Quantifying dynamic hydrologic exchange flows (HEFs) within river corridors that experience high-frequency flow variations caused by dam regulations is important for understanding the biogeochemical processes at the river water and groundwater interfaces. Heat has been widely used as a tracer to infer steady-state flow velocities through analytical solutions of heat transport defined by the diurnal temperature signals. Under sub-daily dynamic flow conditions, however, such analytical solutions are not applicable due to the violation of their fundamental assumptions. In this study, we developed a data assimilation-based approach to estimate the sub-daily flux under highly dynamic flow conditions using multi-depth temperature observations at a 5-min resolution. If the hydraulic gradient is measured, Darcy's law was used to calculate the flux with permeability estimated from temperature responses below the riverbed. Otherwise, flux was estimated directly by assimilating multi-depth temperature data at 1- or 2-hr time intervals assuming one-dimensional flow and heat transport governing equation. By comparing estimated fluxes with model-generated synthetic truth, we demonstrated that both schemes have robust performance in estimating fluxes under highly dynamic flow conditions. This data assimilation-based flux estimation method was able to capture the vertical sub-daily fluxes using multi-depth high-resolution temperature data alone, even in the presence of multi-dimensional flow. This approach has been successfully applied to real field temperature data collected at the Hanford site, which experiences highly dynamic HEFs. Our study shows the promise of adopting distributed 1-D temperature monitoring to capture spatial and temporal exchange dynamics in river corridors at a watershed scale or beyond.
Missouri, one of only two States that borders eight different States, lies in the heart of the United States. Distinguished by its farm fields and forests, substantial rivers and lakes, and cities filled with culture and industry, the “Show Me State” has abundant beauty and a long history of connecting the East and the West. The Pony Express, Oregon Trail, Santa Fe Trail, and California Trail all began in Missouri.
The land and the people of Missouri contribute to its resiliency. Landsat data provide important tools for Missourians to protect their landscapes and waterways and enhance their economy under a variety of circumstances, from fast-arising natural disasters to longer-term environmental phenomena.
Here are several ways that Landsat data benefit Missouri.
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The estuarine habitat mosaic supports the reproduction, growth, and survival of resident and migratory fish species by providing a diverse portfolio of unique habitats with varying physical and biological features. Global climate change is expected to result in increasing temperatures, rising sea levels, and changes in riverine hydrology, which will have profound effects on the extent and composition of the estuarine habitat mosaic and its associated nursery quality for juvenile fish. We used a spatially explicit bioenergetics model to assess how different climate change scenarios might affect juvenile salmon growth rate potential relative to present day conditions in the Nisqually River Delta, WA, USA. The model indicated that prey-rich habitats such as emergent salt marshes and eelgrass meadows were most likely to facilitate growth, and that reductions in their areal extent and accessibility could have severe consequences for salmon. For instance, unmitigated sea-level rise halved the predicted extent of low- and high-elevation emergent salt marsh, leading to a 30% reduction in end-of-season weights. Increasing water temperatures compounded these effects during the late spring and summer such that the average daily growth rate of an individual fish decreased by an additional 5–50% when compared to the effects of sea-level rise alone. Lethal temperatures (> 24 °C) were infrequently observed, but they were more likely to occur during summer low tides in the mudflat and eelgrass habitats when accessibility to prey-rich marsh was minimal, thereby limiting foraging capacity and the availability of thermal refugia. Our findings indicate that, barring the enactment of targeted management strategies, rising tidal levels and increasing ocean temperatures may reduce the quality of the estuarine habitat mosaic for out-migrating salmon and other sensitive fish species.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-021-01003-3","usgsCitation":"Davis, M.J., Woo, I., Ellings, C.S., Hodgson, S., Beauchamp, D., Nakai, G., and De La Cruz, S.E., 2022, A climate-mediated shift in the estuarine habitat mosaic limits prey availability and reduces nursery quality for juvenile salmon: Estuaries and Coasts, v. 45, p. 1445-1464, https://doi.org/10.1007/s12237-021-01003-3.","productDescription":"20 p.","startPage":"1445","endPage":"1464","ipdsId":"IP-129415","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":397156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta, Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7385711669922,\n 47.06731569299121\n ],\n [\n -122.73273468017578,\n 47.067900315766245\n ],\n [\n -122.71350860595702,\n 47.06836800936954\n ],\n [\n -122.69496917724608,\n 47.07526601334617\n ],\n [\n -122.67488479614258,\n 47.08239690925263\n ],\n [\n -122.67454147338866,\n 47.11172875008271\n ],\n [\n -122.73822784423828,\n 47.11137826571562\n ],\n [\n -122.7385711669922,\n 47.06731569299121\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationDate":"2021-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":838145,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":838146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellings, Christopher S.","contributorId":149343,"corporation":false,"usgs":false,"family":"Ellings","given":"Christopher","email":"","middleInitial":"S.","affiliations":[{"id":17711,"text":"Dep't Natural Resources, Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":838147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hodgson, Sayre","contributorId":172121,"corporation":false,"usgs":false,"family":"Hodgson","given":"Sayre","email":"","affiliations":[{"id":26985,"text":"Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":838148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":838149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nakai, Glynnis","contributorId":172123,"corporation":false,"usgs":false,"family":"Nakai","given":"Glynnis","email":"","affiliations":[{"id":26986,"text":"US Fish and Wildlife Service, Nisqually Nat'l Wildlife Refuge, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":838150,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":838151,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230233,"text":"70230233 - 2022 - Urban landcover differentially drives day and nighttime air temperature across a semi-arid city","interactions":[],"lastModifiedDate":"2022-04-06T14:45:12.0395","indexId":"70230233","displayToPublicDate":"2022-03-16T09:52:13","publicationYear":"2022","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":"Urban landcover differentially drives day and nighttime air temperature across a semi-arid city","docAbstract":"Semi-arid urban environments are undergoing an increase in both average air temperatures and in the frequency and intensity of extreme heat events. Within cities, different composition and densities of urban landcovers (ULC) influence local air temperatures, either mitigating or increasing heat. Currently, understanding how combinations of ULC influence air temperature at the block to neighborhood scale is necessary for heat mitigation plans, and yet limited due to the complexities integrating high-resolution ULC with spatial and temporally high-resolution microclimate data. We quantify how ULC influences air temperature at 60 m resolution for day and nighttime climate normals and extreme heat conditions by integrating microclimate sensor data sensor and high-resolution (1 m2) ULC for Denver, Colorado's urban core. We derive ULC drivers of air temperature using a structural equation model, then use a random forest algorithm to predict air temperatures for 30-year climate normals and an extreme heat condition. We find that, in conjunction with other ULC, urban tree canopy reduces daytime air temperatures (−0.026 °C per % cover), and the combination of impervious surfaces and buildings increases daytime air temperature (0.021 °C per % cover). Compared to daytime hours, nighttime irrigated turf temperature cooling effects are increased from being non-significant to −0.022 °C per % cover, while tree canopy effects are reduced from −0.026 °C during the day to −0.016 °C at night. Overall, ULC drives ~17% and 25% of local air temperature during the day and night, respectively. ULC influence on daytime air temperatures is altered in extreme heat events, both depending on the ULC type and time of day. Our findings inform urban planners seeking to identify potential hot and cool spots within a semi-arid city and mitigate high urban air temperatures through using ULC within larger urban climate mitigation strategies.
Groundwater/surface-water (GW/SW) exchange and hyporheic processes are topics receiving increasing attention from the hydrologic community. Hydraulic, chemical, temperature, geophysical, and remote sensing methods are used to achieve various goals (e.g., inference of GW/SW exchange, mapping of bed materials, etc.), but the application of these methods is constrained by site conditions such as water depth, specific conductance, bed material, and other factors. Researchers and environmental professionals working on GW/SW problems come from diverse fields and rarely have expertise in all available field methods; hence there is a need for guidance to design field campaigns and select methods that both contribute to study goals and are likely to work under site-specific conditions. Here, we present the spreadsheet-based GW/SW-Method Selection Tool (GW/SW-MST) to help practitioners identify methods for use in GW/SW and hyporheic studies. The GW/SW-MST is a Microsoft Excel-based decision support tool in which the user selects answers to questions about GW/SW-related study goals and site parameters and characteristics. Based on user input, the tool indicates which methods from a toolbox of 32 methods could potentially contribute to achieving the specified goals at the site described.
","language":"English","publisher":"National Groundwater Association (NGWA)","doi":"10.1111/gwat.13194","usgsCitation":"Hammett, S., Day-Lewis, F., Trottier, B.R., Barlow, P.M., Briggs, M., Delin, G.N., Harvey, J., Johnson, C., Lane, J., Rosenberry, D., and Werkema, D.D., 2022, GW/SW-MST: A groundwater/surface-water method selection tool: Groundwater, v. 60, no. 6, p. 784-791, https://doi.org/10.1111/gwat.13194.","productDescription":"8 p.","startPage":"784","endPage":"791","ipdsId":"IP-128682","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":448467,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9477975","text":"Publisher Index Page"},{"id":435922,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YFJALF","text":"USGS data release","linkHelpText":"GW/SW-MST: A Groundwater/Surface-Water Method Selection Tool"},{"id":401640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Hammett, Steven 0000-0002-6051-966X","orcid":"https://orcid.org/0000-0002-6051-966X","contributorId":292207,"corporation":false,"usgs":false,"family":"Hammett","given":"Steven","email":"","affiliations":[{"id":38050,"text":"Contractor","active":true,"usgs":false}],"preferred":false,"id":844072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":844073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Trottier, Brett Russell 0000-0002-6148-0875","orcid":"https://orcid.org/0000-0002-6148-0875","contributorId":291383,"corporation":false,"usgs":true,"family":"Trottier","given":"Brett","email":"","middleInitial":"Russell","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":844080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barlow, Paul M. 0000-0003-4247-6456 pbarlow@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6456","contributorId":1200,"corporation":false,"usgs":true,"family":"Barlow","given":"Paul","email":"pbarlow@usgs.gov","middleInitial":"M.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":844074,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":844075,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delin, Geoffrey N. 0000-0001-7991-6158","orcid":"https://orcid.org/0000-0001-7991-6158","contributorId":224981,"corporation":false,"usgs":true,"family":"Delin","given":"Geoffrey","email":"","middleInitial":"N.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":844076,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":844077,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Carole D. 0000-0001-6941-1578","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":245365,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":844082,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":844078,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rosenberry, D.O. 0000-0003-0681-5641","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":38500,"corporation":false,"usgs":true,"family":"Rosenberry","given":"D.O.","affiliations":[],"preferred":true,"id":844079,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":844081,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70229727,"text":"70229727 - 2022 - Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?","interactions":[],"lastModifiedDate":"2022-03-16T14:42:57.642502","indexId":"70229727","displayToPublicDate":"2022-03-16T09:29:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?","docAbstract":"Climate change is expected to increase fire activity, which has the potential to accelerate climate-induced shifts in species composition and distribution in the boreal-temperate ecotone. Wildfire can kill resident trees, and thus provide establishment opportunities for migrating tree species. However, the role of fire size and its interactions with tree species with varied life-history attributes in driving climate-induced shifts is not understood. Future fire regimes could be characterized by many small fires or a few large fires. Large and small fires create and regulate distinct burn patterns, which may influence tree-species responses and post-fire successional trajectories. Here we investigated the effects of future fire-regime variability on the boreal-temperate ecotone of northeastern China under climate change using a coupled forest dynamic model (LANDIS PRO) and ecosystem process model (LINKAGES). We simulated fire regimes using the LANDIS PRO fire module. We designed two fire scenarios (frequent, small fires and infrequent, large fires) to represent different fire regimes in terms of fire size. Results showed fire-catalyzed, climate-induced transitions from boreal to pioneer and temperate forest communities. Frequent, small fires resulted in 13% and 23% higher increases in pioneer and temperate species respectively, relative to infrequent, large fires. Therefore, species composition shifts were faster following frequent, small fires than infrequent, large fires. The results can help policymakers and forest managers determine tradeoffs among strategies to mitigate or adapt to climate change under altered fire regimes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2022.120131","usgsCitation":"Xu, W., He, H.S., Huang, C., Duan, S., Hawbaker, T., Henne, P., Liang, Y., and Zhu, Z., 2022, Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?: Forest Ecology and Management, v. 510, p. 1-10, https://doi.org/10.1016/j.foreco.2022.120131.","productDescription":"120131, 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-130289","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":448469,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2022.120131","text":"Publisher Index Page"},{"id":435923,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YREDMC","text":"USGS data 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phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838114,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liang, Yu","contributorId":145642,"corporation":false,"usgs":false,"family":"Liang","given":"Yu","affiliations":[],"preferred":false,"id":838115,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5055,"text":"Land Change 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was initially proposed to retrieve the site amplification function and its resonance frequencies produced by unconsolidated sediments overlying high-velocity bedrock. Presently, MHVSR measurements are predominantly conducted to obtain an estimate of the fundamental site frequency at sites where a strong subsurface impedance contrast exists. Of the earthquake site characterization methods presented in this special issue, the MHVSR method is the furthest behind in terms of consensus towards standardized guidelines and commercial use. The greatest challenges to an international standardization of MHVSR acquisition and analysis are (1) the what — the underlying composition of the microtremor wavefield is site-dependent, and thus, the appropriate theoretical (forward) model for inversion is still debated; and (2) the how — many factors and options are involved in the data acquisition, processing, and interpretation stages. This paper reviews briefly a historical development of the MHVSR technique and the physical basis of an MHVSR (the what). We then summarize recommendations for MHVSR acquisition and analysis (the how). Specific sections address MHVSR interpretation and uncertainty assessment.
","language":"English","publisher":"Springer","doi":"10.1007/s10950-021-10062-9","usgsCitation":"Molnar, S., Sirohey, A., Assaf, J., Bard, P., Castellaro, C., Cornou, C., Cox, B., Guillier, B., Hassani, B., Kawase, H., Matsushima, S., Sánchez-Sesma, F., and Yong, A., 2022, A review of the microtremor horizontal-to-vertical spectral ratio (MHVSR) method: Journal of Seismology, v. 26, p. 653-685, https://doi.org/10.1007/s10950-021-10062-9.","productDescription":"33 p.","startPage":"653","endPage":"685","ipdsId":"IP-127918","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":448472,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10950-021-10062-9","text":"Publisher Index Page"},{"id":406138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2022-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Molnar, S.","contributorId":203574,"corporation":false,"usgs":false,"family":"Molnar","given":"S.","email":"","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":850685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sirohey, A.","contributorId":296125,"corporation":false,"usgs":false,"family":"Sirohey","given":"A.","email":"","affiliations":[],"preferred":false,"id":850686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Assaf, J.","contributorId":296126,"corporation":false,"usgs":false,"family":"Assaf","given":"J.","email":"","affiliations":[],"preferred":false,"id":850708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bard, P.-Y.","contributorId":296110,"corporation":false,"usgs":false,"family":"Bard","given":"P.-Y.","email":"","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":850687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castellaro, C.","contributorId":296111,"corporation":false,"usgs":false,"family":"Castellaro","given":"C.","email":"","affiliations":[{"id":63993,"text":"Alma Mater Studiorum Università di Bologna","active":true,"usgs":false}],"preferred":false,"id":850688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cornou, C.","contributorId":296112,"corporation":false,"usgs":false,"family":"Cornou","given":"C.","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":850689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cox, B.","contributorId":296113,"corporation":false,"usgs":false,"family":"Cox","given":"B.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":850690,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Guillier, B.","contributorId":296114,"corporation":false,"usgs":false,"family":"Guillier","given":"B.","email":"","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":850691,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hassani, B.","contributorId":296115,"corporation":false,"usgs":false,"family":"Hassani","given":"B.","email":"","affiliations":[{"id":37568,"text":"BC Hydro","active":true,"usgs":false}],"preferred":false,"id":850692,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kawase, H.","contributorId":296116,"corporation":false,"usgs":false,"family":"Kawase","given":"H.","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":850693,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Matsushima, S.","contributorId":296117,"corporation":false,"usgs":false,"family":"Matsushima","given":"S.","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":850694,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sánchez-Sesma, F. J.","contributorId":296118,"corporation":false,"usgs":false,"family":"Sánchez-Sesma","given":"F. J.","affiliations":[{"id":25354,"text":"Universidad Nacional Autónoma de México","active":true,"usgs":false}],"preferred":false,"id":850695,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850696,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70236346,"text":"70236346 - 2022 - A review of near-surface QS estimation methods using active and passive sources","interactions":[],"lastModifiedDate":"2022-09-02T14:12:47.588487","indexId":"70236346","displayToPublicDate":"2022-03-16T09:10:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2453,"text":"Journal of Seismology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A review of near-surface QS estimation methods using active and passive sources","title":"A review of near-surface QS estimation methods using active and passive sources","docAbstract":"Seismic attenuation and the associated quality factor (Q) have long been studied in various sub-disciplines of seismology, ranging from observational and engineering seismology to near-surface geophysics and soil/rock dynamics with particular emphasis on geotechnical earthquake engineering and engineering seismology. Within the broader framework of seismic site characterization, various experimental techniques have been adopted over the years to measure the near-surface shear-wave quality factor (QS). Common methods include active- and passive-source recording techniques performed at the free surface of soil deposits and within boreholes, as well as laboratory tests. This paper intends to provide an in-depth review of what Q is and, in particular, how QS is estimated in the current practice. After motivating the importance of this parameter in seismology, we proceed by recalling various theoretical definitions of Q and its measurement through laboratory tests, considering various deformation modes, most notably QP and QS. We next provide a review of the literature on QS estimation methods that use data from surface and borehole sensor recordings. We distinguish between active- and passive-source approaches, along with their pros and cons, as well as the state-of-the-practice and state-of-the-art. Finally, we summarize the phenomena associated with the high-frequency shear-wave attenuation factor (kappa) and its relation to Q, as well as other lesser-known attenuation parameters.
","language":"English","publisher":"Springer","doi":"10.1007/s10950-021-10066-5","usgsCitation":"Parolai, S., Lai, C.G., Dreossi, I., Ktenidou, O., and Yong, A., 2022, A review of near-surface QS estimation methods using active and passive sources: Journal of Seismology, v. 26, p. 823-862, https://doi.org/10.1007/s10950-021-10066-5.","productDescription":"40 p.","startPage":"823","endPage":"862","ipdsId":"IP-132752","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":448475,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10950-021-10066-5","text":"Publisher Index Page"},{"id":406135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2022-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Parolai, Stefano 0000-0002-9084-7488","orcid":"https://orcid.org/0000-0002-9084-7488","contributorId":296105,"corporation":false,"usgs":false,"family":"Parolai","given":"Stefano","email":"","affiliations":[{"id":63989,"text":"Instituto Nazionale di Oceonografia","active":true,"usgs":false}],"preferred":false,"id":850680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lai, Carlo G.","contributorId":296106,"corporation":false,"usgs":false,"family":"Lai","given":"Carlo","email":"","middleInitial":"G.","affiliations":[{"id":63990,"text":"Department of Civil and Architectural Engineering, University of Pavia, Pavia, Italy","active":true,"usgs":false}],"preferred":false,"id":850681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dreossi, Ilaria","contributorId":296107,"corporation":false,"usgs":false,"family":"Dreossi","given":"Ilaria","email":"","affiliations":[{"id":63991,"text":"National Institute of Oceanography and Applied Geophysics – OGS, Udine, Italy","active":true,"usgs":false}],"preferred":false,"id":850682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ktenidou, Olga-Joan","contributorId":271026,"corporation":false,"usgs":false,"family":"Ktenidou","given":"Olga-Joan","email":"","affiliations":[{"id":56255,"text":"National Observatory of Athens","active":true,"usgs":false}],"preferred":false,"id":850683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yong, Alan K. 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":296108,"corporation":false,"usgs":true,"family":"Yong","given":"Alan K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850684,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230023,"text":"70230023 - 2022 - Modeling the dynamics of salt marsh development in coastal land reclamation","interactions":[],"lastModifiedDate":"2022-03-24T14:12:06.779505","indexId":"70230023","displayToPublicDate":"2022-03-16T08:55:46","publicationYear":"2022","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":"Modeling the dynamics of salt marsh development in coastal land reclamation","docAbstract":"The valuable ecosystem services of salt marshes are spurring marsh restoration projects around the world. However, it is difficult to determine the final vegetated area based on physical drivers. Herein, we use a 3D fully coupled vegetation-hydrodynamic-morphological modeling system (COAWST), to simulate the final vegetation cover and the timescale to reach it under various forcing conditions. Marsh development in our simulations can be divided in three distinctive phases: a preparation phase characterized by sediment accumulation in the absence of vegetation, an encroachment phase in which the vegetated area grows, and an adjustment phase in which the vegetated area remains relatively constant while marsh accretes vertically to compensate for sea level rise. Sediment concentration, settling velocity, sea level rise and tidal range each comparably affect equilibrium coverage and timescale in different ways. Our simulations show that the Unvegetated-Vegetated Ratio (UVVR) also relates to sediment budget in marsh development under most conditions.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL095559","usgsCitation":"Xu, Y., Kalra, T., Ganju, N., and Fagherazzi, S., 2022, Modeling the dynamics of salt marsh development in coastal land reclamation: Geophysical Research Letters, v. 49, no. 6, e2021GL095559, 11 p., https://doi.org/10.1029/2021GL095559.","productDescription":"e2021GL095559, 11 p.","ipdsId":"IP-131905","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448480,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021gl095559","text":"External Repository"},{"id":397522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Yiyang","contributorId":289206,"corporation":false,"usgs":false,"family":"Xu","given":"Yiyang","email":"","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":838716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":838781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":838718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fagherazzi, Sergio","contributorId":207153,"corporation":false,"usgs":false,"family":"Fagherazzi","given":"Sergio","email":"","affiliations":[{"id":37465,"text":"Boston University, Earth and Environment, Boston, 02215, USA.","active":true,"usgs":false}],"preferred":false,"id":838719,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239267,"text":"70239267 - 2022 - Average kinship within bighorn sheep populations is associated with connectivity, augmentation, and bottlenecks","interactions":[],"lastModifiedDate":"2023-01-06T14:34:50.408914","indexId":"70239267","displayToPublicDate":"2022-03-16T08:29:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Average kinship within bighorn sheep populations is associated with connectivity, augmentation, and bottlenecks","docAbstract":"Understanding the influence of population attributes on genetic diversity is important to advancement of biological conservation. Because bighorn sheep (Ovis canadensis) populations vary in size and management history, the species provides a unique opportunity to observe the response of average pairwise kinship, inversely related to genetic diversity, to a spectrum of natural and management influences. We estimated average pairwise kinship of bighorn sheep herds and compared estimates with population origin (native/indigenous/extant or reintroduced), historical minimum count, connectivity, and augmentation history, to determine which predictors were the most important. We evaluated 488 bighorn sheep from 19 wild populations with past minimum counts of 16–562 animals, including native and reintroduced populations that received 0–165 animals in augmentations. Using the Illumina High Density Ovine array, we generated a dataset of 7728 single nucleotide polymorphisms and calculated average pairwise kinship for each population. Multiple linear regression analysis determined that connectivity between populations via dispersal, greater number of animals received in augmentations, and greater minimum count were correlated with lower average pairwise kinship at the population level, and whether the population was extant or reintroduced was less important. Thus, our results indicated that genetic isolation of populations can result in increased levels of inbreeding. By determining that natural and human-assisted gene flow were likely the most important influences of average pairwise kinship at the population level, this study can serve as a benchmark for future management of bighorn sheep populations and aid in identifying populations of genetic concern to define priorities for conservation of wild populations.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3972","usgsCitation":"Flesch, E.P., Graves, T., Thomson, J., Proffitt, K., and Garrott, R.A., 2022, Average kinship within bighorn sheep populations is associated with connectivity, augmentation, and bottlenecks: Ecosphere, v. 13, no. 3, e3972, 19 p., https://doi.org/10.1002/ecs2.3972.","productDescription":"e3972, 19 p.","ipdsId":"IP-123033","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":488768,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3972","text":"Publisher Index Page"},{"id":411486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.78094692827673,\n 43.20819189911293\n ],\n [\n -107.87478246478094,\n 43.46432073825207\n ],\n [\n -105.38522276615836,\n 47.31273522708753\n ],\n [\n -106.94850703787552,\n 48.95098006865928\n ],\n [\n -116.04022455322576,\n 48.995371199230505\n ],\n [\n -115.43136405543936,\n 47.5027919613581\n ],\n [\n -114.77745582859464,\n 46.867640242508855\n ],\n [\n -114.42311195285694,\n 46.465058107358715\n ],\n [\n -114.4197823602259,\n 45.56395759707192\n ],\n [\n -113.70839351291886,\n 45.38622209814852\n ],\n [\n -112.22430921762538,\n 44.50809933614741\n ],\n [\n -111.26330199120804,\n 44.53201508738698\n ],\n [\n -110.78094692827673,\n 43.20819189911293\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Flesch, Elizabeth P 0000-0002-7592-8124","orcid":"https://orcid.org/0000-0002-7592-8124","contributorId":222685,"corporation":false,"usgs":false,"family":"Flesch","given":"Elizabeth","email":"","middleInitial":"P","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":860960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":860961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomson, Jennifer 0000-0003-1921-0975","orcid":"https://orcid.org/0000-0003-1921-0975","contributorId":248418,"corporation":false,"usgs":false,"family":"Thomson","given":"Jennifer","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":860962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Proffitt, Kelly M.","contributorId":275167,"corporation":false,"usgs":false,"family":"Proffitt","given":"Kelly M.","affiliations":[{"id":48627,"text":"mtfwp","active":true,"usgs":false}],"preferred":false,"id":860963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrott, Robert A.","contributorId":171537,"corporation":false,"usgs":false,"family":"Garrott","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":860964,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231194,"text":"70231194 - 2022 - Influence of offshore oil and gas structures on seascape ecological connectivity","interactions":[],"lastModifiedDate":"2022-05-03T12:12:50.95425","indexId":"70231194","displayToPublicDate":"2022-03-16T07:10:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of offshore oil and gas structures on seascape ecological connectivity","docAbstract":"Offshore platforms, subsea pipelines, wells and related fixed structures supporting the oil and gas (O&G) industry are prevalent in oceans across the globe, with many approaching the end of their operational life and requiring decommissioning. Although structures can possess high ecological diversity and productivity, information on how they interact with broader ecological processes remains unclear. Here, we review the current state of knowledge on the role of O&G infrastructure in maintaining, altering or enhancing ecological connectivity with natural marine habitats. There is a paucity of studies on the subject with only 33 papers specifically targeting connectivity and O&G structures, although other studies provide important related information. Evidence for O&G structures facilitating vertical and horizontal seascape connectivity exists for larvae and mobile adult invertebrates, fish and megafauna; including threatened and commercially important species. The degree to which these structures represent a beneficial or detrimental net impact remains unclear, is complex and ultimately needs more research to determine the extent to which natural connectivity networks are conserved, enhanced or disrupted. We discuss the potential impacts of different decommissioning approaches on seascape connectivity and identify, through expert elicitation, critical knowledge gaps that, if addressed, may further inform decision making for the life cycle of O&G infrastructure, with relevance for other industries (e.g. renewables). The most highly ranked critical knowledge gap was a need to understand how O&G structures modify and influence the movement patterns of mobile species and dispersal stages of sessile marine species. Understanding how different decommissioning options affect species survival and movement was also highly ranked, as was understanding the extent to which O&G structures contribute to extending species distributions by providing rest stops, foraging habitat, and stepping stones. These questions could be addressed with further dedicated studies of animal movement in relation to structures using telemetry, molecular techniques and movement models. Our review and these priority questions provide a roadmap for advancing research needed to support evidence-based decision making for decommissioning O&G infrastructure.
Disturbances are a key component of ecological processes in coastal ecosystems. Investigating factors that affect tidal marsh accretion and elevation change is important, largely due to accelerating sea-level rise and the ecological and economic value of wetlands. Sediment accumulation rates, elevation change, and flooding were examined at five marshes along a riverine-tidal gradient in the northern San Francisco Bay-Delta, California, USA during an Atmospheric River storm event in 2017 using Surface Elevation Tables (SETs), feldspar marker horizons (MH), and continuous water-level sensors. Our results showed that localized marsh flooding increased during the storm event, but not evenly across sites. Marsh surface elevation increased the most at the tidal freshwater marsh site in response to the storms, with an average surface elevation gain of 45.6 ± 13.1 mm, and the least at a tidal saline marsh with an average surface elevation gain of 4.0 ± 1.2 mm. A marsh located on the large embayment did not exhibit an immediate response to the storm but had a surface elevation gain of 21.5 ± 13.7 mm 6 months after the storm. During the storm period, marsh distance to the bay was the strongest predictor of elevation change, followed by SET-MH elevations. Conversely, during non-storm periods, SET-MH elevation was a relatively strong predictor of elevation change. Atmospheric Rivers appear to be a major factor affecting short-term spatial and temporal variability in flooding and sedimentation rates in tidal marsh systems. Incorporating information about storms into monitoring could increase our understanding of how episodic storms can impact marshes.
Salmonella enterica serovar Typhimurium is typically considered a host generalist; however, certain isolates are associated with specific hosts and show genetic features of host adaptation. Here, we sequenced 131 S. Typhimurium isolates from wild birds collected in 30 U.S. states during 1978-2019. We found that isolates from broad taxonomic host groups including passerine birds, water birds (Aequornithes), and larids (gulls and terns) represented three distinct lineages and certain S. Typhimurium CRISPR types presented in individual lineages. We also showed that lineages formed by wild bird isolates differed from most isolates originating from domestic animal sources, and genomes from these lineages substantially improved source attribution of Typhimurium genomes to wild birds by a machine learning classifier. Furthermore, virulence gene signatures that differentiated S. Typhimurium from passerines, water birds, and larids were detected. Passerine isolates tended to lack S. Typhimurium-specific virulence plasmids. Isolates from the passerine, water bird, and larid lineages had close genetic relatedness with human clinical isolates, including those from a 2021 U.S. outbreak linked to passerine birds. These observations indicate that S. Typhimurium from wild birds in the United States are likely host-adapted, and the representative genomic dataset examined in this study can improve source prediction and facilitate outbreak investigation.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/aem.01979-21","usgsCitation":"Fu, Y., M’ikanatha, N.M., Lorch, J., Blehert, D.S., Berlowski-Zier, B.M., Whitehouse, C.A., Li, S., Deng, X., Smith, J., Shariat, N.W., Nawrocki, E.M., and Dudley, E.G., 2022, Salmonella enterica serovar Typhimurium from wild birds in the United States represent distinct lineages defined by bird type: Applied and Environmental Microbiology, v. 88, no. 6, e01979-21, 16 p., https://doi.org/10.1128/aem.01979-21.","productDescription":"e01979-21, 16 p.","ipdsId":"IP-131992","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":448497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1128/aem.01979-21","text":"Publisher Index Page"},{"id":397112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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headwater stream permanence estimates from a monthly water balance model in the Pacific Northwest, USA","docAbstract":"Stream permanence classifications (i.e., perennial, intermittent, ephemeral) are a primary consideration to determine stream regulatory status in the United States (U.S.) and are an important indicator of environmental conditions and biodiversity. However, at present, no models or products adequately describe surface water presence for regulatory determinations. We modified the Thornthwaite monthly water balance model (MWBM) with a flow threshold parameter to estimate flow permanence and evaluated the model’s accuracy and precision for more than 1.3 million headwater stream reaches in the U.S. Pacific Northwest (PNW). Stream reaches were assigned to one of eight calibration groups by unsupervised classification based on sensitivity to MWBM parameters. Suitable MWBM parameter sets were identified by comparing modeled stream permanence estimates to surface water presence observations (SWPO). Parameter sets with accuracies > 65% were considered suitable. The MWBM estimated stream permanence with high precision at 40% of reaches, with poor precision at 20% of reaches, and no suitable parameter sets were identified for 40% of reaches. Results highlight the need for increased SWPO collection to improve calibration and assessment of stream permanence models. Additionally, implementation of the MWBM to estimate surface water presence indicates potential for process-based models to predict stream permanence with future development.
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