Environmental DNA (eDNA) surveys are appealing options for monitoring aquatic biodiversity. While factors affecting eDNA persistence, capture and amplification have been heavily studied, watershed-scale surveys of fish communities and our confidence in such need further exploration.
We characterized fish eDNA compositions using rapid, low-volume filtering with replicate and control samples scaled for a single Illumina MiSeq flow cell, using the mitochondrial 12S ribosomal RNA locus for taxonomic profiling. Our goals were to determine: (1) spatiotemporal variation in eDNA abundance, (2) the filtrate needed to achieve strong sequencing libraries, (3) the taxonomic resolution of 12S ribosomal sequences in the study environment, (4) the portion of the expected fish community detectable by 12S sequencing, (5) biases in species recovery, (6) correlations between eDNA compositions and catch per unit effort (CPUE) and (7) the extent that eDNA profiles reflect major watershed features. Our bioinformatic approach included (1) estimation of sequencing error from unambiguous mappings and simulation of taxonomic assignment error under various mapping criteria; (2) binning of species based on inferred assignment error rather than by taxonomic rank; and (3) visualization of mismatch distributions to facilitate discovery of distinct haplotypes attributed to the same reference. Our approach was implemented within the St. Regis River, NY, USA, which supports tribal and recreational fisheries and has been a target of restoration activities. We used a large record of St. Regis-specific observations to validate our assignments.
We found that 300 mL drawn through 25-mm cellulose nitrate filters yielded greater than 5 ng/µL DNA at most sites in summer, which was an approximate threshold for generating strong sequencing libraries in our hands. Using inferred sequence error rates, we binned 12S references for 110 species on a state checklist into 85 single-species bins and seven multispecies bins. Of 48 bins observed by capture survey in the St. Regis, we detected eDNA consistent with 40, with an additional four detections flagged as potential contaminants. Sixteen unobserved species detected by eDNA ranged from plausible to implausible based on distributional data, whereas six observed species had no 12S reference sequence. Summed log-ratio compositions of eDNA-detected taxa correlated with log(CPUE) (Pearson’s R = 0.655, P < 0.001). Shifts in eDNA composition of several taxa and a genotypic shift in channel catfish (Ictalurus punctatus) coincided with the Hogansburg Dam, NY, USA. In summary, a simple filtering apparatus operated by field crews without prior expertise gave useful summaries of eDNA composition with minimal evidence of field contamination. 12S sequencing achieved useful taxonomic resolution despite the short marker length, and data exploration with standard bioinformatic tools clarified taxonomic uncertainty and sources of error.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.10539","usgsCitation":"Cornman, R.S., McKenna, J.E., and Fike, J., 2021, Composition and distribution of fish environmental DNA in an Adirondack watershed: PeerJ, v. 9, e10539, 34 p., https://doi.org/10.7717/peerj.10539.","productDescription":"e10539, 34 p.","ipdsId":"IP-121794","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":453296,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.10539","text":"Publisher Index Page"},{"id":436485,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EEOAZK","text":"USGS data release","linkHelpText":"Taxonomic composition of environmental DNA acquired by filtration from the St. Regis River, New York"},{"id":383691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"St. Regis River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.135498046875,\n 44.23732831822538\n ],\n [\n -74.4873046875,\n 44.23732831822538\n ],\n [\n -74.4873046875,\n 44.98034238084973\n ],\n [\n -75.135498046875,\n 44.98034238084973\n ],\n [\n -75.135498046875,\n 44.23732831822538\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":811096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":195894,"corporation":false,"usgs":true,"family":"McKenna","given":"James","suffix":"Jr.","email":"jemckenna@usgs.gov","middleInitial":"E.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":811097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":811098,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228938,"text":"70228938 - 2021 - Feral horse space use and genetic characteristics from fecal DNA","interactions":[],"lastModifiedDate":"2022-02-24T16:18:13.590708","indexId":"70228938","displayToPublicDate":"2021-02-26T10:13:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Feral horse space use and genetic characteristics from fecal DNA","docAbstract":"Feral horses (Equus ferus caballus) in the western United States are managed by the Bureau of Land Management (BLM) and United States Forest Service in designated areas on public lands with a goal of maintaining populations in balance with multiple uses of the landscape. Small, isolated populations can be at risk of extirpation from stochastic events and deleterious genetic effects resulting from inbreeding and reduced heterozygosity. The genetic diversity of feral horse herds is periodically monitored using blood or hair samples collected during management gathers (i.e., occasions when the herd is rounded up). We conducted a study to examine genetic characteristics of the feral horse population at the BLM Little Book Cliffs Herd Management Area (HMA) in Colorado, USA, using non-invasively collected fecal samples. Additionally, we explored whether genotypes could be used to document space use and potential sub-population development. We used a random sampling scheme, walking transects in sampling areas covering most of the HMA to find and collect fecal samples of all ages, except those that were deteriorating. We collected >1,800 fecal samples from across the study area in May, August, and October 2014. We then identified unique individuals using a suite of microsatellite loci. Our estimates of genetic diversity from fecal samples were higher than those reported from blood and hair samples taken during recent horse gathers, likely because our sample size and spatial distribution was larger. Genotypes revealed that some individuals were found only in certain parts of the study area and at a higher proportion than random; thus, they could be considered residents in those sampling areas. Using discriminant function analyses, we detected 5 genetic groups in the sample population, but these did not correspond to individuals in specific parts of the study area. Our results support the use of fecal DNA to augment direct observations of horse presence and could be used to detect habitat use and areas of high density. Non-invasive techniques such as fecal DNA sampling can help managers decide whether new individuals need to be translocated to a closed population to maintain genetic diversity without the human safety and animal welfare concerns associated with gathers and invasive techniques.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21974","usgsCitation":"King, S.R., Schoenecker, K., Fike, J., and Oyler-McCance, S.J., 2021, Feral horse space use and genetic characteristics from fecal DNA: Journal of Wildlife Management, v. 85, no. 6, p. 1074-1083, https://doi.org/10.1002/jwmg.21974.","productDescription":"10 p.","startPage":"1074","endPage":"1083","ipdsId":"IP-117792","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":396428,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Little Book Cliffs Horse Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.51608276367188,\n 39.112480879079556\n ],\n [\n -108.33274841308594,\n 39.112480879079556\n ],\n [\n -108.33274841308594,\n 39.29498546816049\n ],\n [\n -108.51608276367188,\n 39.29498546816049\n ],\n [\n -108.51608276367188,\n 39.112480879079556\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"King, Sarah R. B. 0000-0002-9316-7488","orcid":"https://orcid.org/0000-0002-9316-7488","contributorId":280063,"corporation":false,"usgs":false,"family":"King","given":"Sarah","email":"","middleInitial":"R. B.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":835970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835973,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220257,"text":"70220257 - 2021 - Status of Cisco in Lake Superior in 2017","interactions":[],"lastModifiedDate":"2021-04-29T13:25:58.497396","indexId":"70220257","displayToPublicDate":"2021-02-26T08:22:45","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Status of Cisco in Lake Superior in 2017","docAbstract":"This report describes the status of fish species and their habitat in Lake Superior during the reporting period of 2012-2016 in response to achievement of fish community objectives (FCOs) established by fishery managers for the lake. The overarching goal for the FCOs continued to be met as the fish community remained diverse, self-regulating, dominated by indigenous species, and able to support sustainable fisheries, although further rehabilitation of certain fish is required. The Lake Superior Lakewide Action and Management Plan classified all habitat indicators for Lake Superior as good. Primary production and zooplankton abundance were stable during the reporting period and unchanged from the two previous reporting periods, indicating the lower food web is healthy. Abundance of the invertebrates Mysis diluviana and Diporeia spp. were stable during the reporting period, and Diporeia spp. density exceeded target levels defined in the Great Lakes Water Quality Agreement. Lake Whitefish (Coregonus clupeaformis) abundance was lower than during the previous reporting period but was within the FCO target. Abundance of lean, siscowet, and humper forms of Lake Trout (Salvelinus namaycush) remained stable at levels seen in previous reporting periods. The FCO for non-indigenous salmonids was met as Chinook Salmon (Oncorhynchus tshawytscha), Coho Salmon (O. kisutch), and steelhead/Rainbow Trout (O. mykiss) were being sustained by natural reproduction, and their abundance remained stable or increased from previous reporting periods. The FCO for Walleye (Sander vitreus) was not met, although populations showed signs of improvement since the previous reporting period. The fish community in littoral areas and embayments continued to be diverse and composed mostly of indigenous species. No new invasive species were found in Lake Superior during the reporting period. Degraded embayment and tributary habitats continued to prevent achievement of the FCOs for Brook Trout (S. fontinalis) and Lake Sturgeon (Acipenser fulvescens). Barriers created for hydroelectric generation either blocked Lake Sturgeon from historically important spawning grounds or reduced stream flows necessary for its reproduction. In tributaries without man-made barriers, Lake Sturgeon was relatively abundant and appeared healthy. Attainment of the FCOs for Brook Trout and Lake Sturgeon will be challenging and can only be attained through development of large-scale management actions like those implemented for Lake Trout rehabilitation and Sea Lamprey (Petromyzon marinus) control. Sea Lamprey-control expenditures doubled in 2016 from past levels and should result in suppression of the population closer to its FCO after 2016. The prey-fish FCO appears to have been met, but biomass of nearly all prey-fish species declined from that reported for the previous reporting period and has been on a downward trajectory since 2000. Predation by Lake Trout is probably to blame for the declining biomass of prey fish. Poor recruitment by Cisco (C. artedi) over the last 15 years is exacerbating the declines in prey-fish biomass because Lake Trout must compensate for the loss of Cisco by consuming other, less-abundant prey fish.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The state of Lake Superior ecosystem in 2017","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Goldsworthy, C., and Yule, D.L., 2021, Status of Cisco in Lake Superior in 2017, 4 p.","productDescription":"4 p.","startPage":"29","endPage":"32","ipdsId":"IP-122168","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":385390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385372,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/pubs/SpecialPubs/Sp21_02.pdf"}],"country":"Canada, United States","otherGeospatial":"Lake 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Cory","contributorId":257723,"corporation":false,"usgs":false,"family":"Goldsworthy","given":"Cory","email":"","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":814914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yule, Daniel L. 0000-0002-0117-5115","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":248693,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":814915,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218480,"text":"70218480 - 2021 - The contribution of water radiolysis to marine sedimentary life","interactions":[],"lastModifiedDate":"2021-03-01T14:24:40.886787","indexId":"70218480","displayToPublicDate":"2021-02-26T08:22:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"The contribution of water radiolysis to marine sedimentary life","docAbstract":"Water radiolysis continuously produces H2 and oxidized chemicals in wet sediment and rock. Radiolytic H2 has been identified as the primary electron donor (food) for microorganisms in continental aquifers kilometers below Earth’s surface. Radiolytic products may also be significant for sustaining life in subseafloor sediment and subsurface environments of other planets. However, the extent to which most subsurface ecosystems rely on radiolytic products has been poorly constrained, due to incomplete understanding of radiolytic chemical yields in natural environments. Here we show that all common marine sediment types catalyse radiolytic H2 production, amplifying yields by up to 27X relative to pure water. In electron equivalents, the global rate of radiolytic H2 production in marine sediment appears to be 1-2% of the global organic flux to the seafloor. However, most organic matter is consumed at or near the seafloor, whereas radiolytic H2 is produced at all sediment depths. Comparison of radiolytic H2 consumption rates to organic oxidation rates suggests that water radiolysis is the principal source of biologically accessible energy for microbial communities in marine sediment older than a few million years. Where water permeates similarly catalytic material on other worlds, life may also be sustained by water radiolysis.
Nitrogen (N) and phosphorus (P) inputs throughout the Mississippi/Atchafalaya River Basin (MARB) have been linked to the Gulf of Mexico hypoxia and water‐quality problems throughout the MARB. To describe N and P loading throughout the MARB, SPAtially Referenced Regression On Watershed attributes (SPARROW) models were previously developed based on nutrient inputs and management similar to 1992 and 2002. In this study, refined SPARROW models were developed with higher resolution basin delineation, updated (2012) source inputs, improved calibration (load) targets, and additional statistical techniques than used in the previous SPARROW models. Based on the refined models, consistent with past models, N and P loads/yields were the highest from the central part of the MARB (Corn Belt) and along the Mississippi River. Agricultural activities remained the most important N and P source, but more so for N because its input, which could now be distinguished from atmospheric deposition, could be estimated. Natural loss of P from geologic material throughout the MARB was an important source, contributing about 23% of the total P from the MARB, and resulted in specific areas, such as Kentucky and Tennessee, being larger sources of P than previously estimated. This information can help managers decide where efforts will have the largest effects (highest ranked areas) on reducing nutrient loading to the Gulf hypoxia and what are the most important sources of N and P in these areas.
No abstract available.
","language":"English","publisher":"Solutions Journal","usgsCitation":"Fox, M., and Bagstad, K.J., 2021, Book review: \"Replacing GDP by 2030: Towards a common language for the well-being and sustainability community\" by Rutger Hoekstra: Solutions Journal.","ipdsId":"IP-125619","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":383709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383703,"type":{"id":15,"text":"Index Page"},"url":"https://thesolutionsjournal.com/2021/02/26/a-review-of-replacing-gdp-by-2030-towards-a-common-language-for-the-well-being-and-sustainability-community-by-rutger-hoekstra/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fox, Mairi-Jane 0000-0001-9395-058X","orcid":"https://orcid.org/0000-0001-9395-058X","contributorId":248829,"corporation":false,"usgs":false,"family":"Fox","given":"Mairi-Jane","email":"","affiliations":[{"id":50031,"text":"Regis University","active":true,"usgs":false}],"preferred":false,"id":811222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":811223,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70229045,"text":"70229045 - 2021 - Carcass deposition to suppress invasive lake trout causes differential mortality of two common benthic invertebrates in Yellowstone Lake","interactions":[],"lastModifiedDate":"2022-02-28T16:17:00.9896","indexId":"70229045","displayToPublicDate":"2021-02-25T09:56:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5004,"text":"Fundamental and Applied Limnology","active":true,"publicationSubtype":{"id":10}},"title":"Carcass deposition to suppress invasive lake trout causes differential mortality of two common benthic invertebrates in Yellowstone Lake","docAbstract":"Invasive species require management to mitigate their harmful effects on native biodiversity and ecosystem processes. However, such management can also have negative, unintended consequences on non-target taxa, ecosystem processes, and food web dynamics. In Yellowstone Lake, invasive lake trout (Salvelinus namaycush) have caused a decline in the native Yellowstone cutthroat trout (Oncorhynchus clarkii bouvieri) population. To suppress the invader, lake trout carcasses are deposited on the species’ spawning sites, causing embryo mortality by reducing dissolved oxygen as they decay. The non-target effects of carcass treatment are unknown, but benthic invertebrates may be sensitive to reductions in dissolved oxygen. Benthic invertebrate taxa have varying hypoxia tolerances; caddisflies (Trichoptera, family Limnephilidae) are hypoxia sensitive while amphipods Gammarus lacustris and Hyallela azteca are hypoxia tolerant. Both are widespread and abundant in Yellowstone Lake and comprise a large proportion of fish diets, so changes in their abundances could alter food web dynamics. We conducted an in situ experiment to determine if carcass deposition causes mortality in these two taxa of benthic invertebrates. The probability of mortality for caddisflies was 3.15 times higher in carcass treatments as compared to controls, while amphipod mortality did not change in response to carcass treatment. Amphipods, which contribute most significantly to fish diets, are unlikely to be reduced in response to carcass deposition, which is confined to a small fraction of the lake where lake trout spawn, limiting the possibility for lake-wide effects. We conclude that carcass deposition is unlikely to alter the availability of invertebrates as a food source for fish in Yellowstone Lake.
","language":"English","publisher":"Schweizerbart Science Publishers","doi":"10.1127/fal/2020/1352","usgsCitation":"Briggs, M., Albertson, L.K., Lujan, D., Tronstad, L., Glassic, H., Guy, C.S., and Koel, T., 2021, Carcass deposition to suppress invasive lake trout causes differential mortality of two common benthic invertebrates in Yellowstone Lake: Fundamental and Applied Limnology, v. 194, no. 4, p. 285-295, https://doi.org/10.1127/fal/2020/1352.","productDescription":"11 p.","startPage":"285","endPage":"295","ipdsId":"IP-120668","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":396560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n 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R.","contributorId":286901,"corporation":false,"usgs":false,"family":"Lujan","given":"Dominique R.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":836354,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tronstad, Lusha M.","contributorId":224819,"corporation":false,"usgs":false,"family":"Tronstad","given":"Lusha M.","affiliations":[{"id":40947,"text":"Wyoming Natural Diversity Database, University of Wyoming, Laramie, WY, USA","active":true,"usgs":false}],"preferred":false,"id":836355,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glassic, Hayley C.","contributorId":278613,"corporation":false,"usgs":false,"family":"Glassic","given":"Hayley C.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":836356,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":836351,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Koel, Todd M.","contributorId":270657,"corporation":false,"usgs":false,"family":"Koel","given":"Todd M.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":836357,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223894,"text":"70223894 - 2021 - Analytical validation of two RT-qPCR tests and detection of spring viremia of carp virus (SVCV) in persistently infected koi Cyprinus carpio","interactions":[],"lastModifiedDate":"2021-12-07T16:35:07.874608","indexId":"70223894","displayToPublicDate":"2021-02-25T09:31:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Analytical validation of two RT-qPCR tests and detection of spring viremia of carp virus (SVCV) in persistently infected koi Cyprinus carpio","title":"Analytical validation of two RT-qPCR tests and detection of spring viremia of carp virus (SVCV) in persistently infected koi Cyprinus carpio","docAbstract":"Spring viremia of carp virus (SVCV) ia a carp sprivivirus and a member of the genus Sprivivirus within the family Rhabdoviridae. The virus is the etiological agent of spring viremia of carp, a disease of cyprinid species including koi Cyprinus carpio L. and notifiable to the World Organisation for Animal Health. The goal of this study was to explore hypotheses regarding inter-genogroup (Ia to Id) SVCV infection dynamics in juvenile koi and contemporaneously create new reverse-transcription quantitative PCR (RT-qPCR) assays and validate their analytical sensitivity, specificity (ASp) and repeatability for diagnostic detection of SVCV. RT-qPCR diagnostic tests targeting the SVCV nucleoprotein (Q2N) or glycoprotein (Q1G) nucleotides were pan-specific for isolates typed to SVCV genogroups Ia to Id. The Q2N test had broader ASp than Q1G because Q1G did not detect SVCV isolate 20120450 and Q2N displayed occasional detection of pike fry sprivivirus isolate V76. Neither test cross-reacted with other rhabdoviruses, infectious pancreatic necrosis virus or co-localizing cyprinid herpesvirus 3. Both tests were sensitive with observed 50% limits of detection of 3 plasmid copies and high repeatability. Test analysis of koi immersed in SVCV showed that the virus could be detected for at least 167 d following exposure and that titer, prevalence, replicative rate and persistence in koi were correlated significantly with virus virulence. In this context, high virulence SVCV isolates were more prevalent, reached higher titers quicker and persisted in koi for longer periods of time relative to moderate and low virulence isolates.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/dao03564","usgsCitation":"Clouthier, S.C., Schroeder, T., Bueren, E., Anderson, E., and Emmenegger, E., 2021, Analytical validation of two RT-qPCR tests and detection of spring viremia of carp virus (SVCV) in persistently infected koi Cyprinus carpio: Diseases of Aquatic Organisms, v. 143, p. 169-188, https://doi.org/10.3354/dao03564.","productDescription":"20 p.","startPage":"169","endPage":"188","ipdsId":"IP-119270","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":453304,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/dao03564","text":"Publisher Index Page"},{"id":389150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clouthier, Sharon C","contributorId":265646,"corporation":false,"usgs":false,"family":"Clouthier","given":"Sharon","email":"","middleInitial":"C","affiliations":[{"id":54748,"text":"Fisheries & Oceans Canada, Freshwater Institute, Winnipeg, Manitoba R3T 2N6, Canada","active":true,"usgs":false}],"preferred":false,"id":823160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schroeder, Tamara","contributorId":265647,"corporation":false,"usgs":false,"family":"Schroeder","given":"Tamara","email":"","affiliations":[{"id":54748,"text":"Fisheries & Oceans Canada, Freshwater Institute, Winnipeg, Manitoba R3T 2N6, Canada","active":true,"usgs":false}],"preferred":false,"id":823161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bueren, Emma K","contributorId":265648,"corporation":false,"usgs":false,"family":"Bueren","given":"Emma K","affiliations":[{"id":54749,"text":"Department of Biological Sciences, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, 24061 USA","active":true,"usgs":false}],"preferred":false,"id":823162,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Eric D.","contributorId":213888,"corporation":false,"usgs":false,"family":"Anderson","given":"Eric D.","affiliations":[{"id":38922,"text":"Maine BioTek Inc., Winterport, ME 04496, USA","active":true,"usgs":false}],"preferred":false,"id":823163,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Emmenegger, Eveline 0000-0001-5217-6030","orcid":"https://orcid.org/0000-0001-5217-6030","contributorId":265649,"corporation":false,"usgs":false,"family":"Emmenegger","given":"Eveline","affiliations":[{"id":54750,"text":"Western Fisheries Research Center","active":true,"usgs":false}],"preferred":false,"id":823164,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261909,"text":"70261909 - 2021 - Eruption of compositionally heterogeneous andesites from a complex storage region during the 2006 eruption of Augustine Volcano","interactions":[],"lastModifiedDate":"2025-01-02T15:01:27.2945","indexId":"70261909","displayToPublicDate":"2021-02-25T08:55:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Eruption of compositionally heterogeneous andesites from a complex storage region during the 2006 eruption of Augustine Volcano","docAbstract":"Despite the common occurrence of heterogeneous andesitic eruptions, few studies have investigated the compositional effects on microlite crystallization and vesiculation in co-erupted natural samples. In 2006, Augustine Volcano erupted compositionally heterogeneous andesites that range from 56.4 to 63.3 wt% SiO2 and include two endmember lithologic groups: low-silica andesite (LSA) and high-silica andesite (HSA). Textural and compositional differences between LSA and HSA end members are explored for two discrete, sequential vulcanian explosions from January 17 (event 9) and 27 (event 10), 2006. Groundmass glass compositions of pyroclasts within LSA and HSA compositional suites are not colinear and do not correlate with plagioclase microlite crystallinities, indicating eruption from multiple isolated shallow magma reservoirs with various pressure-temperature pathways. HSA pyroclasts have lower crystallinities, 0.02–0.24, than most LSA pyroclasts, 0.16–0.39, demonstrating the influence of composition on crystallinity. Additionally, microlite textural and groundmass glass compositional differences exist between consecutive vulcanian explosions. The event 9 deposits have a typical bimodal density distribution and groundmass glass compositions range from 65 to 78 wt% SiO2. Plagioclase microlite number densities (MNV) are 104.6–6.4 mm−3 and crystallinities are 0.02 to 0.28, similar to products from other andesitic vulcanian eruptions. Deposits from the early phase of event 10 have a bimodal density distribution and contain a high proportion of LSA pyroclasts, similar to event 9. Groundmass glass compositions range from 72 to 79 wt% SiO2 and plagioclase MNV are 105.9–6.3 mm−3, forming narrower ranges compared to event 9. A transition occurred during the later phase of event 10 to a unimodal density distribution, a more homogeneous groundmass glass composition, 75–78 wt% SiO2, a higher proportion of HSA pyroclasts, and the highest MNV of 105.9–6.7 mm−3. We interpret this shift to reflect eruption from reservoir depths around 4–6 km and the cessation of pre-eruptive magma staging in the upper conduit, transitioning the eruption to continuous and effusive phases. Attention to heterogeneous andesitic erupted products reveals additional details about heterogeneous shallow magma storage, variable upper conduit magma staging, and a range of pressure-temperature paths prior to fragmentation.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-01431-2","usgsCitation":"Benage, M.C., Wright, H.M., and Coombs, M.L., 2021, Eruption of compositionally heterogeneous andesites from a complex storage region during the 2006 eruption of Augustine Volcano: Bulletin of Volcanology, v. 83, 17; 23 p., https://doi.org/10.1007/s00445-020-01431-2.","productDescription":"17; 23 p.","ipdsId":"IP-123502","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":465608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Augustine Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -153.51368537912168,\n 59.40176810974776\n ],\n [\n -153.51368537912168,\n 59.322048642759654\n ],\n [\n -153.36796855048897,\n 59.322048642759654\n ],\n [\n -153.36796855048897,\n 59.40176810974776\n ],\n [\n -153.51368537912168,\n 59.40176810974776\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"83","noUsgsAuthors":false,"publicationDate":"2021-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Benage, Mary Catherine 0000-0002-8793-7722","orcid":"https://orcid.org/0000-0002-8793-7722","contributorId":336948,"corporation":false,"usgs":true,"family":"Benage","given":"Mary","email":"","middleInitial":"Catherine","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922248,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70234266,"text":"70234266 - 2021 - Subducting oceanic basement roughness impacts on upper plate tectonic structure and a backstop splay fault zone activated in the southern Kodiak aftershock region of the Mw 9.2, 1964 megathrust rupture, Alaska","interactions":[],"lastModifiedDate":"2022-08-05T13:32:23.783492","indexId":"70234266","displayToPublicDate":"2021-02-25T08:25:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Subducting oceanic basement roughness impacts on upper plate tectonic structure and a backstop splay fault zone activated in the southern Kodiak aftershock region of the Mw 9.2, 1964 megathrust rupture, Alaska","docAbstract":"In 1964, the Alaska margin ruptured in a giant Mw 9.2 megathrust earthquake, the 2nd largest during worldwide instrumental recording. The coseismic slip and aftershock region offshore Kodiak Island was surveyed in 1977 – 1981 to understand the region’s tectonics. We re-processed multichannel seismic (MCS) field data using current standard Kirchhoff depth migration and/or MCS traveltime tomography. Further surveys in 1994 added P-wave velocity structure from wide-angle seismic lines and multibeam bathymetry. Published regional gravity, backscatter, and earthquake compilations also became available at this time.
Beneath the trench, rough oceanic crust is covered by ~3 to 5 km thick sediment. Sediment on the subducting plate modulates the plate interface relief. The accreted prism’s imbricate thrust faults have a complex P-wave velocity structure. Landward, an accelerated increase in P-wave velocities is marked by a backstop splay fault zone (BSFZ) that marks a transition from the prism to the higher rigidity rock beneath the middle and upper slope. Structures associated with this feature may indicate fluid flow. Further upslope, another fault extends >100 km along-strike across the middle slope. Erosion from subducting seamounts leaves embayments in the frontal prism.
Plate interface roughness varies along the subduction zone. Beneath the lower and middle slope, 2.5 D plate interface images show modest relief whereas the oceanic basement image is rougher. The 1964 earthquake slip maximum coincides with the leading/landward flank of a subducting seamount and the BSFZ. The BSFZ is a potentially active structure and should be considered in tsunami hazard assessments.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02275.1","usgsCitation":"Krabbenhoeft, A., von Huene, R.E., Miller, J.J., and Klaeschen, D., 2021, Subducting oceanic basement roughness impacts on upper plate tectonic structure and a backstop splay fault zone activated in the southern Kodiak aftershock region of the Mw 9.2, 1964 megathrust rupture, Alaska: Geosphere, v. 17, no. 2, p. 409-437, https://doi.org/10.1130/GES02275.1.","productDescription":"29 p.","startPage":"409","endPage":"437","ipdsId":"IP-118908","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":453307,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02275.1","text":"Publisher Index Page"},{"id":404873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kodiak Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.96240234375,\n 55.29788360510556\n ],\n [\n -150.46875,\n 55.29788360510556\n ],\n [\n -150.46875,\n 56.49889156789072\n ],\n [\n -153.96240234375,\n 56.49889156789072\n ],\n [\n -153.96240234375,\n 55.29788360510556\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Krabbenhoeft, Anne","contributorId":208084,"corporation":false,"usgs":false,"family":"Krabbenhoeft","given":"Anne","email":"","affiliations":[{"id":37708,"text":"GEOMAR Helmholtz Center for Ocean Research Kiel, Wischhofstr. 1-3, 24148 Kiel, Germany","active":true,"usgs":false}],"preferred":false,"id":848365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"von Huene, Roland E. 0000-0003-1301-3866 rvonhuene@usgs.gov","orcid":"https://orcid.org/0000-0003-1301-3866","contributorId":191070,"corporation":false,"usgs":true,"family":"von Huene","given":"Roland","email":"rvonhuene@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":848366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, John J. 0000-0002-9098-0967 jmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-0967","contributorId":3785,"corporation":false,"usgs":true,"family":"Miller","given":"John","email":"jmiller@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":848367,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaeschen, Dirk","contributorId":198022,"corporation":false,"usgs":false,"family":"Klaeschen","given":"Dirk","email":"","affiliations":[],"preferred":false,"id":848368,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218452,"text":"70218452 - 2021 - Implications of historical and contemporary processes on genetic differentiation of a declining boreal songbird: The rusty blackbird","interactions":[],"lastModifiedDate":"2021-02-26T14:05:43.154105","indexId":"70218452","displayToPublicDate":"2021-02-25T08:01:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Implications of historical and contemporary processes on genetic differentiation of a declining boreal songbird: The rusty blackbird","docAbstract":"First-order dynamic occupancy models (FODOMs) are a class of state-space model in which the true state (occurrence) is observed imperfectly. An important assumption of FODOMs is that site dynamics only depend on the current state and that variations in dynamic processes are adequately captured with covariates or random effects. However, it is often difficult to understand and/or measure the covariates that generate ecological data, which are typically spatiotemporally correlated. Consequently, the non-independent error structure of correlated data causes underestimation of parameter uncertainty and poor ecological inference. Here, we extend the FODOM framework with a second-order Markov process to accommodate site memory when covariates are not available. Our modeling framework can be used to make reliable inference about site occupancy, colonization, extinction, turnover, and detection probabilities. We present a series of simulations to illustrate the data requirements and model performance. We then applied our modeling framework to 13 yr of data from an amphibian community in southern Arizona, USA. In this analysis, we found residual temporal autocorrelation of population processes for most species, even after accounting for long-term drought dynamics. Our approach represents a valuable advance in obtaining inference on population dynamics, especially as they relate to metapopulations.
Natal dispersal is assumed to be a particularly risky movement behavior as individuals transfer, often long distances, from birth site to site of potential first reproduction. Though, because this behavior persists in populations, it is assumed that dispersal increases the fitness of individuals despite the potential for increased risk of mortality. The extent of dispersal risk, however, has rarely been tested, especially for large mammals. Therefore, we aimed to test the relationship between dispersal and survival for both males and females in a large herbivore. Using a radio-transmittered sample of 398 juvenile male and 276 juvenile female white-tailed deer (Odocoileus virginianus), we compared survival rates of dispersers and non-dispersers. We predicted that dispersing deer would experience greater overall mortality than philopatric deer due to direct transfer-related risks (e.g., vehicular collision), indirect immigration-related mortality attributable to colonization of unfamiliar habitat, and increased over-winter mortality associated with energetic costs of movement and unfamiliarity with recently colonized habitat. For both male and female yearlings, survival rates of dispersers (male = 49.9%, female = 64.0%) did not differ from non-dispersers (male = 51.6%, female = 70.7%). Only two individuals (both female) were killed by vehicular collision during transfer, and over-winter survival patterns were similar between the two groups. Although dispersal movement likely incurs energetic costs on dispersers, these costs do not necessarily translate to decreased survival. In many species, including white-tailed deer, dispersal is likely condition-dependent, such that larger and healthier individuals are more likely to disperse; therefore, costs associated with dispersal are more likely to be borne successfully by those individuals that do disperse. Whether low-risk dispersal of large mammals is the rule or the exception will require additional research. Further, future research is needed to evaluate non-survival fitness-related costs and benefits of dispersal (e.g., increased reproductive opportunities for dispersers).
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7227","usgsCitation":"Long, E., Diefenbach, D.R., Lutz, C., Wallingford, B., and Rosenberry, C., 2021, Risky movements? Natal dispersal does not decrease survival of a large herbivore: Ecology and Evolution, v. 11, no. 6, p. 2731-2740, https://doi.org/10.1002/ece3.7227.","productDescription":"10 p.","startPage":"2731","endPage":"2740","ipdsId":"IP-118210","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":453313,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7227","text":"Publisher Index Page"},{"id":395944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"11","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Long, Eric S.","contributorId":276215,"corporation":false,"usgs":false,"family":"Long","given":"Eric S.","affiliations":[{"id":56939,"text":"Seattle Pacific University","active":true,"usgs":false}],"preferred":false,"id":834669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lutz, Clayton L.","contributorId":276216,"corporation":false,"usgs":false,"family":"Lutz","given":"Clayton L.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallingford, Bret D.","contributorId":276217,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret D.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosenberry, Christopher S.","contributorId":276218,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834672,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217179,"text":"mcs2021 - 2021 - Mineral commodity summaries 2021","interactions":[],"lastModifiedDate":"2021-02-24T19:30:12.316619","indexId":"mcs2021","displayToPublicDate":"2021-02-24T14:35:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"seriesTitle":{"id":368,"text":"Mineral Commodity Summaries","active":false,"publicationSubtype":{"id":6}},"displayTitle":"Mineral Commodity Summaries 2021","title":"Mineral commodity summaries 2021","docAbstract":"Each mineral commodity chapter of the 2021 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production and resources. The MCS is the earliest comprehensive source of 2020 mineral production data for the world. More than 90 individual minerals and materials are covered by 2-page synopses.
For mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the 2-page synopsis.
Abbreviations and units of measure and definitions of selected terms used in the report are in Appendix A and Appendix B, respectively. Reserves and resources information is in Appendix C, which includes “Part A—Resource and Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is in Appendix D.
The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2021 are welcomed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/mcs2021","usgsCitation":"U.S. Geological Survey, 2021, Mineral commodity summaries 2021: U.S. Geological Survey, 200 p., https://doi.org/10.3133/mcs2021.","productDescription":"200 p.","numberOfPages":"200","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-125100","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":382519,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/periodicals/mcs2021/coverthb.jpg"},{"id":382587,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/periodicals/mcs2021/mcs2021.pdf","text":"Report","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"MCS 2021"},{"id":382588,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/centers/nmic/mineral-commodity-summaries","text":"Mineral Commodity Summaries Prior to 2021"},{"id":382589,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/centers/nmic/commodity-statistics-and-information","text":"Commodity Statistics and Information"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Steady-state numerical groundwater-flow models were constructed for the islands of Kaua‘i, O‘ahu, and Maui to enable quantification of the hydrologic consequences of withdrawals and other stresses that can place limits on groundwater availability. The volcanic aquifers of Hawai‘i supply nearly all drinking water for the islands’ residents, freshwater for diverse industries, and natural discharge to springs, streams, and nearshore areas that support ecosystems, cultural practices, aesthetics, and recreation. Increases in groundwater withdrawal and changes in climate can cause water-table depression, saltwater rise, and reduction of natural groundwater discharge—all of which can limit fresh groundwater availability. The numerical models described in this report are designed to quantify these consequences. Separate models were created for each island using MODFLOW-2005 with the Seawater Intrusion package, which allows simulation of freshwater and saltwater in ocean-island aquifers. Calibration resulted in models that generally replicate observed water-level, stream base-flow, and spring-flow data, and simulate groundwater-flow directions and fresh groundwater thicknesses that are consistent with conceptual models. The calibrated models use hydraulic properties that are consistent with the ranges reported in previous studies. The models show that the relative distribution of fresh groundwater discharge to the ocean, streams, and springs and withdrawals for human use differ substantially among the three islands studied here. These differences indicate that consequences that limit the availability of fresh groundwater for human use are likely to differ among the three islands.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205126","usgsCitation":"Izuka, S.K., Rotzoll, K., and Nishikawa, T., 2021, Volcanic Aquifers of Hawai‘i—Construction and calibration of numerical models for assessing groundwater availability on Kaua‘i, O‘ahu, and Maui: U.S. Geological Survey Scientific Investigations Report 2020-5126, 63 p., https://doi.org/10.3133/sir20205126.","productDescription":"Report: viii, 63 p.; Data Release","numberOfPages":"63","ipdsId":"IP-071367","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":383611,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5126/covrthb.jpg"},{"id":383612,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5126/sir20205126.pdf","text":"Report","size":"53 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":383613,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K4DK2P","linkHelpText":"MODFLOW-2005 and SWI2 models for assessing groundwater availability in volcanic aquifers on Kaua‘i, O‘ahu, and Maui, Hawai‘i"},{"id":416444,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20155164","text":"Scientific Investigations Report 2015-5164","description":"Izuka, S.K., Engott, J.A., Rotzoll, Kolja, Bassiouni, Maoya, Johnson, A.G., Miller, L.D., and Mair, Alan, 2018, Volcanic aquifers of Hawai‘i—Hydrogeology, water budgets, and conceptual models (ver. 2.0, March 2018): U.S. Geological Survey Scientific Investigations Report 2015-5164, 158 p., https://doi.org/10.3133/sir20155164.","linkHelpText":"- Volcanic Aquifers of Hawai‘i—Hydrogeology, Water budgets, and Conceptual Models"},{"id":416445,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1876","text":"Professional Paper 1876","description":"Izuka, S.K., and Rotzoll, K., 2023, Volcanic aquifers of Hawaiʻi—Contributions to assessing groundwater availability on Kauaʻi, Oʻahu, and Maui: U.S. Geological Survey Professional Paper 1876, 100 p., https://doi.org/10.3133/pp1876.","linkHelpText":"- Volcanic Aquifers of Hawai‘i—Contributions to Assessing Groundwater Availability on Kaua‘i, O‘ahu, and Maui"},{"id":417944,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20233010","text":"Fact Sheet 2023-3010","description":"Izuka, S.K., and Rotzoll, K., 2023, Availability of groundwater from the volcanic aquifers of the Hawaiian Islands: U.S. Geological Survey Fact Sheet 2023-3010, 4 p., https://doi.org/10.3133/fs20233010.","linkHelpText":"- Availability of Groundwater from the Volcanic Aquifers of the Hawaiian Islands"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kaua'i, Maui, O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.73095703125,\n 20.57365332356332\n ],\n [\n -155.90423583984375,\n 20.57365332356332\n ],\n [\n -155.90423583984375,\n 21.04861794324536\n ],\n [\n -156.73095703125,\n 21.04861794324536\n ],\n [\n -156.73095703125,\n 20.57365332356332\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.33221435546875,\n 21.235622362422877\n ],\n [\n -157.62359619140625,\n 21.235622362422877\n ],\n [\n -157.62359619140625,\n 21.72505868324388\n ],\n [\n -158.33221435546875,\n 21.72505868324388\n ],\n [\n -158.33221435546875,\n 21.235622362422877\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.85931396484375,\n 21.830906665069758\n ],\n [\n -159.22622680664062,\n 21.830906665069758\n ],\n [\n -159.22622680664062,\n 22.264951388846296\n ],\n [\n -159.85931396484375,\n 22.264951388846296\n ],\n [\n -159.85931396484375,\n 21.830906665069758\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
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Honolulu, HI 96818
Multispectral remote sensing data acquired by the Landsat 8 Operational Land Imager (OLI) sensor were analyzed using a new, automated technique to generate a map of exposed mineral and vegetation groups in the western San Juan Mountains, Colo., and the Four Corners Region of the United States. Band ratio results were combined into displayed mineral and vegetation groups using Boolean algebra. New analysis logic has been implemented to exploit the coastal aerosol band in Landsat 8 OLI data and identify concentrations of iron sulfate minerals. These may indicate the presence of near-surface pyrite, which can be a potential nonpoint source of acid rock drainage. Zoned occurrences of iron sulfate minerals in areas surrounding and down gradient of known sources of pyrite have been mapped using this technique. They show high correlation with occurrences of jarosite-bearing mineral assemblages, as mapped using airborne imaging spectrometer data and supporting field verification surveys. Mapping the occurrence of iron sulfate minerals produced by the weathering and oxidation of pyrite in exposed hydrothermally altered rocks can also provide an important indicator of the genetic environment of alteration and the associated mineral deposit type. The automated analysis methodology is being employed to rapidly and cost-effectively generate maps of large regions of the United States in support of U.S. Geological Survey mineral resource and mineral-environmental assessments. This map, which includes the ERDAS IMAGINE thematic raster format in the data release, has been attributed by pixel value with mineral and vegetation group classification data, which can be queried in most image processing and GIS software packages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3466","usgsCitation":"Rockwell, B.W., Gnesda, W.R., and Hofstra, A.H., 2021, Improved automated identification and mapping of iron sulfate minerals, other mineral groups, and vegetation using Landsat 8 Operational Land Imager data, San Juan Mountains, Colorado, and Four Corners Region: U.S. Geological Survey Scientific Investigations Map 3466, 1 sheet, scale 1:325,000, 37-p. pamphlet, https://doi.org/10.3133/sim3466.","productDescription":"Pamphlet: v, 37 p.; 1 Sheet: 38.72 x 37.71 inches; 2 Data Releases: Read Me","onlineOnly":"Y","ipdsId":"IP-079681","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":382731,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ONOKKX","text":"USGS data release","linkHelpText":"Digital map of iron sulfate minerals, other mineral groups, and vegetation of the San Juan Mountains, Colorado, and Four Corners Region derived from automated analysis of Landsat 8 satellite data"},{"id":383537,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BYV5H4","text":"USGS data release","linkHelpText":"Digital map of iron sulfate minerals, other mineral groups, and vegetation of the western United States derived from automated analysis of Landsat 8 satellite data"},{"id":382727,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3466/coverthb2.jpg"},{"id":382729,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3466/sim3466_sheet1.pdf","text":"Sheet 1. Improved Automated Identification and Mapping of Iron Sulfate Minerals, Other Mineral Groups, and Vegetation using Landsat 8 Operational Land Imager Data, San Juan Mountains, Colorado, and Four Corners Region","size":"34.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3466 map sheet","linkHelpText":"Download file and view it in Adobe Acrobat DC or Adobe Reader DC to access interactive layers."},{"id":382728,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3466/sim3466_pamphlet.pdf","text":"Report","size":"2.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3466 pamphlet"},{"id":382730,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3466/ReadMe.txt","text":"Read Me","size":"12.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3466 map read me file"}],"country":"United States","state":"Colorado, Utah","otherGeospatial":"Four Corners region, San Juan Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.4737548828125,\n 36.70365959719456\n ],\n [\n -106.2872314453125,\n 38.50948995925553\n ],\n [\n -109.039306640625,\n 39.10022600175347\n ],\n [\n -110.31372070312499,\n 36.87522650673951\n ],\n [\n -107.4737548828125,\n 36.70365959719456\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS-973
Denver, CO 80225-0046
The ongoing global pandemic caused by coronavirus disease has once again demonstrated the role of the family Coronaviridae in causing human disease outbreaks. Because severe acute respiratory syndrome coronavirus 2 was first detected in December 2019, information on its tropism, host range, and clinical manifestations in animals is limited. Given the limited information, data from other coronaviruses might be useful for informing scientific inquiry, risk assessment, and decision-making. We reviewed endemic and emerging infections of alphacoronaviruses and betacoronaviruses in wildlife, livestock, and companion animals and provide information on the receptor use, known hosts, and clinical signs associated with each host for 15 coronaviruses detected in humans and animals. This information can be used to guide implementation of a One Health approach that involves human health, animal health, environmental, and other relevant partners in developing strategies for preparedness, response, and control to current and future coronavirus disease threats.
","language":"English","publisher":"Centers for Disease Control and Prevention","doi":"10.3201/eid2704.203945","usgsCitation":"Ghai, R.R., Carpenter, A., Liew, A.Y., Martin, K.B., Herring, M.K., Gerber, S.I., Hall, A.J., Sleeman, J.M., VonDobschuetz, S., and Barton Behravesh, C., 2021, Animal reservoirs and hosts for emerging alphacoronaviruses and betacoronaviruses: Emerging Infectious Diseases, v. 27, no. 4, p. 1015-1022, https://doi.org/10.3201/eid2704.203945.","productDescription":"8 p.","startPage":"1015","endPage":"1022","ipdsId":"IP-122283","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":453316,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3201/eid2704.203945","text":"Publisher Index Page"},{"id":383698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ghai, Ria R.","contributorId":252886,"corporation":false,"usgs":false,"family":"Ghai","given":"Ria","email":"","middleInitial":"R.","affiliations":[{"id":50460,"text":"U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States (","active":true,"usgs":false}],"preferred":false,"id":811067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carpenter, Ann","contributorId":252887,"corporation":false,"usgs":false,"family":"Carpenter","given":"Ann","email":"","affiliations":[{"id":50461,"text":"U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States","active":true,"usgs":false}],"preferred":false,"id":811068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liew, Amanda Y.","contributorId":252889,"corporation":false,"usgs":false,"family":"Liew","given":"Amanda","email":"","middleInitial":"Y.","affiliations":[{"id":50461,"text":"U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States","active":true,"usgs":false}],"preferred":false,"id":811070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Krystalyn B.","contributorId":252890,"corporation":false,"usgs":false,"family":"Martin","given":"Krystalyn","email":"","middleInitial":"B.","affiliations":[{"id":50461,"text":"U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States","active":true,"usgs":false}],"preferred":false,"id":811071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herring, Meghan K.","contributorId":252888,"corporation":false,"usgs":false,"family":"Herring","given":"Meghan","email":"","middleInitial":"K.","affiliations":[{"id":50461,"text":"U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States","active":true,"usgs":false}],"preferred":false,"id":811069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gerber, Susan I.","contributorId":252891,"corporation":false,"usgs":false,"family":"Gerber","given":"Susan","email":"","middleInitial":"I.","affiliations":[{"id":50461,"text":"U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States","active":true,"usgs":false}],"preferred":false,"id":811072,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hall, Aron J.","contributorId":252892,"corporation":false,"usgs":false,"family":"Hall","given":"Aron","email":"","middleInitial":"J.","affiliations":[{"id":50461,"text":"U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States","active":true,"usgs":false}],"preferred":false,"id":811073,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":811074,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"VonDobschuetz, Sophie","contributorId":252893,"corporation":false,"usgs":false,"family":"VonDobschuetz","given":"Sophie","email":"","affiliations":[{"id":50462,"text":"Food and Agriculture Organization of the United Nations, Rome,","active":true,"usgs":false}],"preferred":false,"id":811075,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Barton Behravesh, Casey","contributorId":252894,"corporation":false,"usgs":false,"family":"Barton Behravesh","given":"Casey","email":"","affiliations":[{"id":50461,"text":"U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States","active":true,"usgs":false}],"preferred":false,"id":811076,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70228856,"text":"70228856 - 2021 - Epizootic plague in prairie dogs: Correlates and control with deltamethrin","interactions":[],"lastModifiedDate":"2022-02-23T16:49:58.836667","indexId":"70228856","displayToPublicDate":"2021-02-24T10:37:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3675,"text":"Vector-Borne and Zoonotic Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Epizootic plague in prairie dogs: Correlates and control with deltamethrin","docAbstract":"The plague bacterium, Yersinia pestis, is a generalist pathogen of flea (Siphonaptera) vectors and mammalian hosts. In colonies of prairie dogs (PDs, Cynomys spp.), Y. pestis causes occasional epizootics, killing ≥90% of PDs within weeks to several months. We evaluated the effectiveness of deltamethrin, a pyrethroid insecticide, as a tool for preventing plague epizootics among three PD species. Specifically, we studied PD population growth on paired plots treated with deltamethrin for flea control or left untreated as baselines. We also evaluated PD population growth relative to flea abundance and PD density. All epizootics occurred on nontreated plots. Epizootics occurred on plots with very low PD densities as well as high densities. Mean population change, assessed by comparing visual counts of PDs in years before and during epizootics, was +88% for treated plots and −97% for nontreated plots. For comparison, an experimental oral vaccine against plague had an average change in population index or estimate during epizootics of −69% on vaccine plots compared with −83% for associated nontreated (placebo) plots. In our study and on plots not treated with deltamethrin, PD population growth was negatively correlated with flea abundance in the year before the epizootic, lending support to the hypothesis that flea abundance plays a critical role in plague transmission under natural conditions. Generally speaking, deltamethrin is a highly effective tool for plague management on PD colonies. That said, continued study is needed to refine deltamethrin treatments and to develop a more integrated strategy for plague management.
","language":"English","publisher":"Mary Ann Liebert Inc.","doi":"10.1089/vbz.2020.2684","usgsCitation":"Biggins, D.E., Godbey, J.L., and Eads, D.A., 2021, Epizootic plague in prairie dogs: Correlates and control with deltamethrin: Vector-Borne and Zoonotic Diseases, v. 21, no. 3, p. 172-178, https://doi.org/10.1089/vbz.2020.2684.","productDescription":"7 p.","startPage":"172","endPage":"178","ipdsId":"IP-120505","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":436488,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99IBB3N","text":"USGS data release","linkHelpText":"Data on prairie dog densities, flea abundance, and plague epizootics in Montana and Utah, USA"},{"id":396358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Godbey, Jerry L. godbeyj@usgs.gov","contributorId":5121,"corporation":false,"usgs":true,"family":"Godbey","given":"Jerry","email":"godbeyj@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":835711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":835712,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218469,"text":"70218469 - 2021 - Geochemical advances in Arctic Alaska oil typing - North Slope oil correlation and charge history","interactions":[],"lastModifiedDate":"2021-04-16T13:57:53.669361","indexId":"70218469","displayToPublicDate":"2021-02-24T10:34:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical advances in Arctic Alaska oil typing - North Slope oil correlation and charge history","docAbstract":"The Arctic Alaska petroleum province is geologically and geochemically complex. Mixed hydrocarbon charge from multiple source rocks and/or levels of thermal maturity is common within an individual oil pool. Biomarker and chemometric statistical analyses were used to correlate twenty-nine oils to five oil families derived from: (1) Triassic Shublik Formation (calcareous organofacies), (2) Triassic Shublik Formation (shaly organofacies), (3) Jurassic Kingak Shale, (4) Cretaceous shale (pebble shale unit and Hue Shale), and (5) Paleogene shale (Canning Formation). Age-diagnostic and source-related oil biomarker parameters establish clear genetic relationships between the normal oil-window components and their putative source designations. However, application of diamondoid analyses reveals mixed-oil accumulations with postmature charge contributions (diamondoid-rich and biomarker-poor) in many oils.
Most sampled reservoirs contain a predominant charge derived from a single oil-window source plus a minor contribution from one or more higher maturity source(s). Variations in source organofacies also are recognized in the Shublik, Kingak, and Cretaceous oil families. In some cases, oils from multiple pools within a single field display relatively homogeneous geochemical profiles, suggesting a common source and migration pathway. For example, oil from the significant Pikka discovery is inferred to originate mainly from the calcareous Shublik Formation. In other cases, variability among oils from multiple pools within a single field (e.g., Milne Point, Colville River, and Northstar) likely indicates a more complex source, migration, and charge history. Results may be useful for anticipating the composition of oil charge in stratigraphic traps with low-permeability sandstone reservoirs, where oil gravity and other chemical parameters may influence economic viability.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2020.104878","usgsCitation":"Botterell, P.J., Houseknecht, D.W., Lillis, P.G., Barbanti, S.M., Dahl, J.E., and Moldowan, J.M., 2021, Geochemical advances in Arctic Alaska oil typing - North Slope oil correlation and charge history: Marine and Petroleum Geology, v. 127, 104878, 23 p., https://doi.org/10.1016/j.marpetgeo.2020.104878.","productDescription":"104878, 23 p.","ipdsId":"IP-120847","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":467255,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1774068","text":"External Repository"},{"id":436489,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91VS1I8","text":"USGS data release","linkHelpText":"Geochemical Advances in Arctic Alaska Oil Typing - North Slope Oil Correlation and Charge History"},{"id":383692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.1923828125,\n 68.12248241161676\n ],\n [\n -141.0205078125,\n 68.12248241161676\n ],\n [\n -141.0205078125,\n 71.96538769913127\n ],\n [\n -157.1923828125,\n 71.96538769913127\n ],\n [\n -157.1923828125,\n 68.12248241161676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Botterell, Palma J. 0000-0001-7140-0915 pjarboe@usgs.gov","orcid":"https://orcid.org/0000-0001-7140-0915","contributorId":5805,"corporation":false,"usgs":true,"family":"Botterell","given":"Palma","email":"pjarboe@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":811090,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":811091,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lillis, Paul G. 0000-0002-7508-1699 plillis@usgs.gov","orcid":"https://orcid.org/0000-0002-7508-1699","contributorId":1817,"corporation":false,"usgs":true,"family":"Lillis","given":"Paul","email":"plillis@usgs.gov","middleInitial":"G.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":811092,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barbanti, Silvana M. 0000-0001-5682-9764","orcid":"https://orcid.org/0000-0001-5682-9764","contributorId":252899,"corporation":false,"usgs":false,"family":"Barbanti","given":"Silvana","email":"","middleInitial":"M.","affiliations":[{"id":50465,"text":"Biomarker Technologies, Inc.","active":true,"usgs":false}],"preferred":false,"id":811093,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahl, Jeremy E.","contributorId":252900,"corporation":false,"usgs":false,"family":"Dahl","given":"Jeremy","email":"","middleInitial":"E.","affiliations":[{"id":50466,"text":"Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory","active":true,"usgs":false}],"preferred":false,"id":811094,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moldowan, J. Michael","contributorId":252901,"corporation":false,"usgs":false,"family":"Moldowan","given":"J.","email":"","middleInitial":"Michael","affiliations":[{"id":50465,"text":"Biomarker Technologies, Inc.","active":true,"usgs":false}],"preferred":false,"id":811095,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70231742,"text":"70231742 - 2021 - Foreword","interactions":[],"lastModifiedDate":"2022-05-31T15:20:01.121816","indexId":"70231742","displayToPublicDate":"2021-02-24T10:15:29","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Foreword","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Sloth Bear-the Barefoot Bear of Sri Lanka","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Sunway University Press","usgsCitation":"van Manen, F.T., 2021, Foreword, chap. of Sloth Bear-the Barefoot Bear of Sri Lanka, 5 p.","productDescription":"5 p.","ipdsId":"IP-125085","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":401369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":401031,"type":{"id":15,"text":"Index Page"},"url":"https://press.sunway.edu.my/books/sloth-bear"}],"country":"Sri Lanka","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 80.6396484375,\n 5.911116815631734\n ],\n [\n 81.573486328125,\n 6.348056476859364\n ],\n [\n 81.89208984375,\n 6.784625755799487\n ],\n [\n 81.93603515625,\n 7.27529233637217\n ],\n [\n 81.71630859375,\n 7.8089631205593895\n ],\n [\n 81.32080078125,\n 8.602747284770018\n ],\n [\n 80.22216796875,\n 9.871451997300548\n ],\n [\n 79.70581054687499,\n 9.784851250750604\n ],\n [\n 79.617919921875,\n 9.438224391343347\n ],\n [\n 79.6728515625,\n 9.026152779146141\n ],\n [\n 79.903564453125,\n 8.765652867885256\n ],\n [\n 79.727783203125,\n 8.265855052877221\n ],\n [\n 79.661865234375,\n 7.9504368350293735\n ],\n [\n 79.771728515625,\n 6.980954426458497\n ],\n [\n 79.87060546875,\n 6.489983332670651\n ],\n [\n 80.145263671875,\n 5.911116815631734\n ],\n [\n 80.6396484375,\n 5.911116815631734\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":843621,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70247385,"text":"70247385 - 2021 - Airborne dust plumes lofted by dislodged ice blocks at Russell Crater, Mars","interactions":[],"lastModifiedDate":"2023-08-01T14:47:03.083682","indexId":"70247385","displayToPublicDate":"2021-02-24T09:44:33","publicationYear":"2021","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":"Airborne dust plumes lofted by dislodged ice blocks at Russell Crater, Mars","docAbstract":"Linear dune gullies on poleward-facing Martian slopes are enigmatic. Formation by CO2-ice block or snow cornice falls has been proposed based on optical imagery of bright, high-albedo features inside gully channels. Because these features often resemble patchy frost residue rather than three-dimensional blocks, more evidence is needed to support the ice-block formation mechanism. Satellite imagery captured two simultaneous airborne plumes with in-channel sources at the Russell crater megadune, thrust up, and dispersed outward along the path of linear dune gullies. We use spectral data analyses, climatic analyses of bolometric temperatures, and thermal modeling to further develop the mechanistic framework for linear dune gully development. Basal sublimation and CO2 gas venting likely cause CO2-ice-block detachment and falls from gully alcoves in southern early spring, accompanied by ice-block off-gassing and saltation of sands and coarse silts that are redeposited around gully channels, and lofting of sublimation lag (coarse dust/silt) into airborne plumes.
","language":"English","publisher":"Wiley","doi":"10.1029/2020GL091920","usgsCitation":"Dinwiddie, C., and Titus, T.N., 2021, Airborne dust plumes lofted by dislodged ice blocks at Russell Crater, Mars: Geophysical Research Letters, v. 48, no. 6, e2020GL091920, 9 p., https://doi.org/10.1029/2020GL091920.","productDescription":"e2020GL091920, 9 p.","ipdsId":"IP-149099","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":453321,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020gl091920","text":"Publisher Index Page"},{"id":419474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars, Russell Crater","volume":"48","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Dinwiddie, Cynthia L.","contributorId":38880,"corporation":false,"usgs":true,"family":"Dinwiddie","given":"Cynthia L.","affiliations":[],"preferred":false,"id":879399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":879400,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218649,"text":"70218649 - 2021 - Fish Rhabdoviruses (Rhabdoviridae)","interactions":[],"lastModifiedDate":"2021-03-04T14:27:15.795534","indexId":"70218649","displayToPublicDate":"2021-02-24T08:26:40","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Fish Rhabdoviruses (Rhabdoviridae)","docAbstract":"The family Rhabdoviridae currently has 18 genera accepted by the International Committee for Virus Taxonomy (ICTV), and three of those genera contain fish rhabdoviruses. In the genera Novirhabdovirus, Sprivivirus, and Perhabdovirus all viruses infect fish hosts, and there are no fish viruses in any of the other 15 rhabdovirus genera. In the overall phylogeny of the Rhabdoviridae the three fish virus genera are well separated from each other, and the novirhabdovirus genus occupies a position basal to all other genera.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Virology 4th Edition","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","usgsCitation":"Kurath, G., and Stone, D.B., 2021, Fish Rhabdoviruses (Rhabdoviridae), chap. of Encyclopedia of Virology 4th Edition, p. 324-331.","productDescription":"8 p.","startPage":"324","endPage":"331","ipdsId":"IP-105809","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":383825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383804,"type":{"id":15,"text":"Index Page"},"url":"https://www.elsevier.com/books/encyclopedia-of-virology/bamford/978-0-12-814515-9"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kurath, Gael 0000-0003-3294-560X","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":220175,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811276,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, David B.","contributorId":193572,"corporation":false,"usgs":false,"family":"Stone","given":"David","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":811277,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218775,"text":"70218775 - 2021 - Broadening the ecology of fear: Non-lethal effects arise from diverse responses to predation and parasitism","interactions":[],"lastModifiedDate":"2021-03-11T13:36:57.765821","indexId":"70218775","displayToPublicDate":"2021-02-24T07:32:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3173,"text":"Proceedings of the Royal Society B","active":true,"publicationSubtype":{"id":10}},"title":"Broadening the ecology of fear: Non-lethal effects arise from diverse responses to predation and parasitism","docAbstract":"Research on the ‘ecology of fear’ posits that defensive prey responses to avoid predation can cause non-lethal effects across ecological scales. Parasites also elicit defensive responses in hosts with associated non-lethal effects, which raises the longstanding, yet unresolved question of how non-lethal effects of parasites compare with those of predators. We developed a framework for systematically answering this question for all types of predator–prey and host–parasite systems. Our framework reveals likely differences in non-lethal effects not only between predators and parasites, but also between different types of predators and parasites. Trait responses should be strongest towards predators, parasitoids and parasitic castrators, but more numerous and perhaps more frequent for parasites than for predators. In a case study of larval amphibians, whose trait responses to both predators and parasites have been relatively well studied, existing data indicate that individuals generally respond more strongly and proactively to short-term predation risks than to parasitism. Apart from studies using amphibians, there have been few direct comparisons of responses to predation and parasitism, and none have incorporated responses to micropredators, parasitoids or parasitic castrators, or examined their long-term consequences. Addressing these and other data gaps highlighted by our framework can advance the field towards understanding how non-lethal effects impact prey/host population dynamics and shape food webs that contain multiple predator and parasite species.