The Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) imaged two newly formed impact craters on the South Polar Layered Deposits (SPLD) of Mars in 2018 and 2020. These two new craters, the first detected on the SPLD, measure ∼17 m and ∼48 m in diameter. Follow-up observations were conducted with the High Resolution Imaging Science Experiment (HiRISE), showing seasonal and interannual changes, and providing stereo coverage for the production of digital terrain models (DTMs). Mars Climate Sounder (MCS) data were obtained over the region of these new impacts, giving surface temperature information for the time interval before and after the impacts were detected. Taken together, the optical and infrared observations of these sites reveal craters largely consistent with the morphologies of other small, dated impact craters on Mars, and crater ejecta patterns that suggest a more dust/regolith-dominated upper few meters of the SPLD in contrast to mid-latitude buried ice and lobate debris aprons (LDAs). This supports previous conclusions that the SPLD may have an upper surface depleted in water ice relative to the North PLDs, possibly the result of a widespread deflation event.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2024.115977","usgsCitation":"Landis, M., Dundas, C., McEwen, A.S., Daubar, I.J., Hayne, P.O., Byrne, S., Sutton, S.S., Rangarajan, V.G., Tornabene, L.L., Britton, A., and Herkenhoff, K., 2024, New, dated small impacts on the South Polar Layered Deposits (SPLD), Mars, and implications for shallow subsurface properties: Icarus, v. 419, 115977, 14 p., https://doi.org/10.1016/j.icarus.2024.115977.","productDescription":"115977, 14 p.","ipdsId":"IP-153796","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":486917,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.icarus.2024.115977","text":"Publisher Index Page"},{"id":432996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"419","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Landis, Margaret E.","contributorId":176713,"corporation":false,"usgs":false,"family":"Landis","given":"Margaret E.","affiliations":[{"id":25655,"text":"Lunar and Planetary Laboratory, 1629 E. University Blvd., The University of Arizona, Tucson, AZ 85721, United States","active":true,"usgs":false}],"preferred":false,"id":911218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dundas, Colin M. 0000-0003-2343-7224","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":237028,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":911219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daubar, Ingrid J.","contributorId":204233,"corporation":false,"usgs":false,"family":"Daubar","given":"Ingrid","email":"","middleInitial":"J.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":911221,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hayne, Paul O.","contributorId":174125,"corporation":false,"usgs":false,"family":"Hayne","given":"Paul","email":"","middleInitial":"O.","affiliations":[{"id":27365,"text":"NASA Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":911222,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byrne, Shane","contributorId":53513,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911223,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sutton, Sarah S.","contributorId":203706,"corporation":false,"usgs":false,"family":"Sutton","given":"Sarah","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911224,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rangarajan, Vidhya Ganesh","contributorId":303377,"corporation":false,"usgs":false,"family":"Rangarajan","given":"Vidhya","email":"","middleInitial":"Ganesh","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911225,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tornabene, Livio L.","contributorId":203691,"corporation":false,"usgs":false,"family":"Tornabene","given":"Livio","email":"","middleInitial":"L.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911226,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Britton, Andrew","contributorId":343481,"corporation":false,"usgs":false,"family":"Britton","given":"Andrew","email":"","affiliations":[{"id":82100,"text":"Jacobs/NASA Johnson Space Center","active":true,"usgs":false}],"preferred":false,"id":911227,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":206170,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":911228,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70257650,"text":"70257650 - 2024 - Novel quantitative methods to enable multispectral identification of high-purity water ice exposures on Mars using High Resolution Imaging Science Experiment (HiRISE) images","interactions":[],"lastModifiedDate":"2024-08-21T13:50:08.297937","indexId":"70257650","displayToPublicDate":"2024-07-17T08:48:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Novel quantitative methods to enable multispectral identification of high-purity water ice exposures on Mars using High Resolution Imaging Science Experiment (HiRISE) images","docAbstract":"Reliable detection and characterization of water ice on the Martian surface is pivotal to not only understand its present and past climate, but to also provide valuable information on in-situ resource availability and distribution for future human exploration missions. Ice-rich features are currently identified with visible/near-IR (VNIR), thermal IR and radar data. However, their coarse spatial scale sometimes limits confident characterization of small (i.e., meter-scale) icy exposures resulting from recent activity like new impacts. Water ice bearing materials possess weaker spectral characteristics at wavelengths shorter than ∼1030 nm that may be resolved by VNIR imaging instruments like the High Resolution Imaging Science Experiment (HiRISE) and the Colour and Stereo Surface Imaging System (CaSSIS). Our study assesses the spectral capability of HiRISE colour observations to help distinguish high purity water ice exposures from ice-poor materials. We report detailed methodologies for reliable colour characterization of icy surface using unfiltered HiRISE images. We present the first quantitative approach to uniquely characterize high-purity ice-rich materials through spectral shape and spectral parameterization methods at high spatial resolution (∼50 cm/pixel). We also present three spectral parameters to aid detection of pure water ice features, while also providing statistical constraints to enable a quantitative interpretation scheme. Our methods are observed to work well in characterizing and separating ice-rich features uniquely from ice-poor and ferrous materials. However, we do observe that these methods have a lower grain size detection limit of ∼250–300 μm, and may not be able to uniquely separate frosts from ground ice exposures. We also apply these methods to better constrain the composition of bright materials exposed by recent impacts identified in previous surveys, where substantial evidence for ice-bearing materials was previously unavailable. Overall, our work proposes HiRISE colour-based methods as a novel approach for high-resolution multispectral characterization of ice-rich features on the Martian surface, which is of particular value since the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has ceased operations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2023.115849","usgsCitation":"Rangarajan, V.G., Tornabene, L.L., Osinski, G.R., Dundas, C., Beyer, R.A., Herkenhoff, K., Byrne, S., Heyd, R., Seelos, F.P., Munaretto, G., and Dapremont, A., 2024, Novel quantitative methods to enable multispectral identification of high-purity water ice exposures on Mars using High Resolution Imaging Science Experiment (HiRISE) images: Icarus, v. 419, 115849, 16 p., https://doi.org/10.1016/j.icarus.2023.115849.","productDescription":"115849, 16 p.","ipdsId":"IP-154753","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":432995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"419","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rangarajan, Vidhya Ganesh","contributorId":303377,"corporation":false,"usgs":false,"family":"Rangarajan","given":"Vidhya","email":"","middleInitial":"Ganesh","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tornabene, Livio L.","contributorId":203691,"corporation":false,"usgs":false,"family":"Tornabene","given":"Livio","email":"","middleInitial":"L.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osinski, G. R.","contributorId":343477,"corporation":false,"usgs":false,"family":"Osinski","given":"G.","email":"","middleInitial":"R.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dundas, Colin M. 0000-0003-2343-7224","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":237028,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":911210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beyer, Ross A.","contributorId":204235,"corporation":false,"usgs":false,"family":"Beyer","given":"Ross","email":"","middleInitial":"A.","affiliations":[{"id":36890,"text":"Sagan Center at the SETI Institute and NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":911211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":206170,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":911212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Byrne, Shane","contributorId":53513,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Heyd, Rodney","contributorId":210542,"corporation":false,"usgs":false,"family":"Heyd","given":"Rodney","email":"","affiliations":[],"preferred":false,"id":911214,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Seelos, Frank P.","contributorId":203692,"corporation":false,"usgs":false,"family":"Seelos","given":"Frank","email":"","middleInitial":"P.","affiliations":[{"id":36691,"text":"JHU APL","active":true,"usgs":false}],"preferred":false,"id":911215,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Munaretto, G.","contributorId":343479,"corporation":false,"usgs":false,"family":"Munaretto","given":"G.","email":"","affiliations":[{"id":82097,"text":"INAF Osservatorio Astronomico di Padova","active":true,"usgs":false}],"preferred":false,"id":911216,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dapremont, Angela","contributorId":343480,"corporation":false,"usgs":false,"family":"Dapremont","given":"Angela","email":"","affiliations":[{"id":82098,"text":"Johns Hopkins University Applied Physics Lab","active":true,"usgs":false}],"preferred":false,"id":911217,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70257666,"text":"70257666 - 2024 - Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics","interactions":[],"lastModifiedDate":"2024-08-21T13:34:18.045457","indexId":"70257666","displayToPublicDate":"2024-07-17T08:25:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics","docAbstract":"Invasive dreissenid mussels (Dreissena polymorpha and Dreissena rostriformis bugensis) have altered Great Lakes ecosystems through a multitude of effects on benthic habitats, food web structure, and nutrient cycling. This study explores whether spatially continuous geographic data of environmental factors can be utilized to predict Dreissena spp. spatial distributions on a lake-wide scale. Categorical variables were also assessed for significant relationships with Dreissena spp. biomass. Point observations from the 2017 Lake Huron benthic survey under the Cooperative Science and Monitoring Initiative (CSMI) were utilized for in situ measurements of dreissenid presence and biomass at 119 sites across Lake Huron. Basin, bathymetric zone, and tributary influence were found to have statistically significant relationships to dreissenid biomass. A boosted regression tree (BRT) model (ROC score 0.707) was developed to spatially predict dreissenid presence probability across Lake Huron from six environmental explanatory variables: April, May, and October chlorophyll, June dissolved organic carbon, January bottom temperature, and May bottom temperature. The importance of food availability and bottom temperature illuminated relationships between dreissenid mussels and periods of benthic-pelagic mixing in the spring and fall seasons. Future models could be improved through advancements in survey technology for improved geographic characterization of mussel habitat characteristics and environmental constraints.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2024.102369","usgsCitation":"Morrison, J.M., Esselman, P.C., Riseng, C.M., Elgin, A.K., and Rowe, M.D., 2024, Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics: Journal of Great Lakes Research, v. 50, no. 4, 102369, 11 p., https://doi.org/10.1016/j.jglr.2024.102369.","productDescription":"102369, 11 p.","ipdsId":"IP-138355","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":432994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.7705078125,\n 45.81348649679973\n ],\n [\n -84.4189453125,\n 45.5679096098613\n ],\n [\n -83.81469726562499,\n 45.390735154248894\n ],\n [\n -83.507080078125,\n 45.166547157856016\n ],\n [\n -83.38623046875,\n 44.73892994307368\n ],\n [\n -83.507080078125,\n 44.315987905196906\n ],\n [\n -83.9794921875,\n 44.02442151965934\n ],\n [\n -83.95751953125,\n 43.59630591596548\n ],\n [\n -83.60595703125,\n 43.61221676817573\n ],\n [\n -82.891845703125,\n 44.05601169578525\n ],\n [\n -82.46337890625,\n 42.94838139765314\n ],\n [\n -81.705322265625,\n 43.37311218382002\n ],\n [\n -81.683349609375,\n 44.11125397357155\n ],\n [\n -81.134033203125,\n 44.61393394730626\n ],\n [\n -81.49658203125,\n 45.205263456162385\n ],\n [\n -81.024169921875,\n 44.629573191951046\n ],\n [\n -79.95849609375,\n 44.41024041296011\n ],\n [\n -79.903564453125,\n 44.77793589631623\n ],\n [\n -79.56298828125,\n 44.72332018895825\n ],\n [\n -80.145263671875,\n 45.56021795715051\n ],\n [\n -80.804443359375,\n 46.03510927947334\n ],\n [\n -81.58447265624999,\n 46.18743678432541\n ],\n [\n -82.63916015625,\n 46.255846818480315\n ],\n [\n -84.122314453125,\n 46.39998810407942\n ],\n [\n -83.81469726562499,\n 46.17983040759436\n ],\n [\n -83.8916015625,\n 46.126556302418514\n ],\n [\n -83.968505859375,\n 45.98169518512228\n ],\n [\n -84.6826171875,\n 46.11132565729796\n ],\n [\n -84.7705078125,\n 45.81348649679973\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Morrison, Jennifer M. 0000-0003-4460-7843 jmmorrison@usgs.gov","orcid":"https://orcid.org/0000-0003-4460-7843","contributorId":4903,"corporation":false,"usgs":true,"family":"Morrison","given":"Jennifer","email":"jmmorrison@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":911325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esselman, Peter C. 0000-0002-0085-903X pesselman@usgs.gov","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":5965,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter","email":"pesselman@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":911326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riseng, Catherine M.","contributorId":30144,"corporation":false,"usgs":true,"family":"Riseng","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":911327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elgin, Ashley K.","contributorId":216170,"corporation":false,"usgs":false,"family":"Elgin","given":"Ashley","email":"","middleInitial":"K.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":911328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowe, Mark D.","contributorId":303683,"corporation":false,"usgs":false,"family":"Rowe","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":65877,"text":"4NOAA Great Lakes Environmental Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":911329,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248840,"text":"70248840 - 2024 - Paramyxoviruses of fish","interactions":[],"lastModifiedDate":"2025-01-31T17:00:01.704109","indexId":"70248840","displayToPublicDate":"2024-07-16T10:58:50","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"19","title":"Paramyxoviruses of fish","docAbstract":"The first fish paramyxovirus was isolated from normal adult Chinook salmon returning to a coastal hatchery in Oregon in the fall of 1982. Subsequently, the virus was isolated from other stocks of adult Chinook salmon and one stock of adult coho salmon in California, Oregon, Washington, and Alaska, leading to its designation as the Pacific salmon paramyxovirus (PsaPV). The slow-growing virus can be isolated from tissues and ovarian fluids of healthy adult fish returning to spawn and apparently causes no clinical signs of disease or mortality. In 1995 a different and widely disseminated paramyxovirus was isolated from farmed Atlantic salmon in Norway and was designated as Atlantic salmon paramyxovirus (AsaPV). Although this virus caused no disease or mortality when injected into juvenile Atlantic salmon, AsaPV has been associated with proliferative gill inflammation in sea-reared yearling fish; however, additional infectious agents may be involved in the etiology of the condition. Sequence analysis of PsaPV and AsaPV isolates using the polymerase gene established their placement in the family Paramyxoviridae and has shown the two viruses to be closely related but sufficiently different from each other and from other known paramyxoviruses to represent a new genus within the family. The viruses can be diagnosed by isolation in cell culture with final confirmation by molecular methods. Other paramyxovirus-like agents have been observed or isolated from rainbow trout in Germany, from seabream in Japan associated with epithelial necrosis, from turbot in Spain associated with erythrocytic inclusion bodies and buccal/opercular hemorrhaging and from koi and common carp associated with gill necrosis in the European Union.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Aquaculture virology (second edition)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-323-91169-6.00030-3","usgsCitation":"Meyers, T.R., and Batts, W.N., 2024, Paramyxoviruses of fish, chap. 19 of Aquaculture virology (second edition), p. 307-314, https://doi.org/10.1016/B978-0-323-91169-6.00030-3.","productDescription":"8 p.","startPage":"307","endPage":"314","ipdsId":"IP-133807","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":481559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Meyers, Ted R.","contributorId":202026,"corporation":false,"usgs":false,"family":"Meyers","given":"Ted","email":"","middleInitial":"R.","affiliations":[{"id":36327,"text":"Alaska Department of Fish and Game, Division of Commercial Fisheries, 1255 W. 8th Street Juneau, AK 99802, USA","active":true,"usgs":false}],"preferred":false,"id":883848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Batts, William N. 0000-0002-6469-9004 bbatts@usgs.gov","orcid":"https://orcid.org/0000-0002-6469-9004","contributorId":3815,"corporation":false,"usgs":true,"family":"Batts","given":"William","email":"bbatts@usgs.gov","middleInitial":"N.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":883849,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70248841,"text":"70248841 - 2024 - Hepeviruses of aquatic organisms","interactions":[],"lastModifiedDate":"2025-01-31T16:54:09.033107","indexId":"70248841","displayToPublicDate":"2024-07-16T10:53:19","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"29","title":"Hepeviruses of aquatic organisms","docAbstract":"Originally reported in California, the cutthroat trout virus (CTV) has now been isolated from nine species of salmonids in North America. Early work focused on the replication and physical characteristics of the virus, but 20 years later was determined to be most closely related to the hepatitis E virus. The small genome is positive-sense, single-stranded RNA similar to other members of the family Hepeviridae, which now contains its own genus Piscihepevirus with two distinct genotypes, CTV-1 and CTV-2. While CTV has not been associated with acute disease in fish, the virus could form persistently infected cell cultures that may aid research in treating hepatitis E-like viruses affecting humans or other animals. Interestingly, trout exposed to CTV were protected for about a month against subsequent exposure to the infectious hematopoietic necrosis virus. Replicating agents suspected to be CTV can be confirmed by polymerase chain reaction (PCR), quantitative PCR, and sequencing. Other unclassified hepeviruses detected in fish using viral metagenomics include Wenling fish hepevirus, Wenling moray eel hepevirus, Murray–Darling carp hepevirus, and eastern mosquitofish hepevirus. The family Hepeviridae has been placed in the order Hepevirales together with the family Matonaviridae (rubella virus), with member viruses having amino acid homology in the helicase and replicase regions of the nonstructural proteins. In addition, using next-generation sequencing, a hepe-like sequence was characterized in diseased giant freshwater prawn Macrobrachium rosenbergii and named Crustacea hepe-like virus 1. Thus the family Hepeviridae continues to expand among aquatic animal hosts.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Aquaculture virology (second edition)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-323-91169-6.00025-X","usgsCitation":"Batts, W.N., 2024, Hepeviruses of aquatic organisms, chap. 29 of Aquaculture virology (second edition), p. 509-514, https://doi.org/10.1016/B978-0-323-91169-6.00025-X.","productDescription":"6 p.","startPage":"509","endPage":"514","ipdsId":"IP-133853","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":481557,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Kibenge, Frederick S. B.","contributorId":173300,"corporation":false,"usgs":false,"family":"Kibenge","given":"Frederick","email":"","middleInitial":"S. B.","affiliations":[],"preferred":false,"id":925877,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Godoy, Marcos","contributorId":173301,"corporation":false,"usgs":false,"family":"Godoy","given":"Marcos","email":"","affiliations":[],"preferred":false,"id":925878,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Batts, William N. 0000-0002-6469-9004 bbatts@usgs.gov","orcid":"https://orcid.org/0000-0002-6469-9004","contributorId":3815,"corporation":false,"usgs":true,"family":"Batts","given":"William","email":"bbatts@usgs.gov","middleInitial":"N.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":883850,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70263545,"text":"70263545 - 2024 - Slip rate for the Rose Canyon fault through San Diego, California, based on analysis of GPS data: Evidence for a potential Rose Canyon–San Miguel-Vallecitos fault connection?","interactions":[],"lastModifiedDate":"2025-02-13T16:56:38.677011","indexId":"70263545","displayToPublicDate":"2024-07-16T10:52:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Slip rate for the Rose Canyon fault through San Diego, California, based on analysis of GPS data: Evidence for a potential Rose Canyon–San Miguel-Vallecitos fault connection?","docAbstract":"The Rose Canyon fault is the southern extension of the larger Newport–Inglewood–Rose Canyon fault system, which represents a major structural boundary in the Inner Continental Borderland (ICB) offshore of southern California. Ten to fifteen percent of total plate boundary motion in southern California is thought to be accommodated by the faults of the ICB, but the exact distribution of slip is uncertain. With an onshore segment, the Rose Canyon fault offers an opportunity to measure the slip rate using traditional geodetic methods. In this study, we use Global Positioning System (GPS) surface velocities from a combined campaign and continuous GPS network to constrain elastic models of the Rose Canyon fault. We then compare the observed surface velocities with proposed conceptual models of regional fault connections that facilitate the transfer of slip into the Rose Canyon fault to assess how well the observations are explained by the models. The results of elastic half‐space models suggest that the Rose Canyon fault may be slipping toward the higher end of geologic estimates, with the preferred model indicating a slip rate of 2.4 ± 0.5 mm/yr. Although limited in terms of near‐fault benchmarks, we find an improved model fit using an asymmetrical elastic half‐space model and a higher slip rate, suggesting a potential rheological contrast across the Rose Canyon fault, similar to observations from the northern Newport–Inglewood fault segments. Observed GPS surface velocities, background seismicity, and gravity anomalies south of San Diego Bay point toward a more easterly trace for the Rose Canyon fault, suggesting a possible connection with the San Miguel–Vallecitos fault system. Such a connection could increase the potential rupture lengths of future earthquakes and have important consequences for regional seismic hazards.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230278","usgsCitation":"Singleton, D.M., Maloney, J., Agnew, D., and Rockwell, T., 2024, Slip rate for the Rose Canyon fault through San Diego, California, based on analysis of GPS data: Evidence for a potential Rose Canyon–San Miguel-Vallecitos fault connection?: Bulletin of the Seismological Society of America, v. 114, no. 5, p. 2751-2766, https://doi.org/10.1785/0120230278.","productDescription":"16 p.","startPage":"2751","endPage":"2766","ipdsId":"IP-149537","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.03132304321895,\n 32.37326157121886\n ],\n [\n -114.89786575651428,\n 32.75462583665147\n ],\n [\n -114.93333927794629,\n 33.64921849858126\n ],\n [\n -118.29120454417611,\n 35.815309260323346\n ],\n [\n -121.93695511034596,\n 35.53619205111963\n ],\n [\n -121.70925414240213,\n 34.55709712444637\n ],\n [\n -118.03132304321895,\n 32.37326157121886\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"114","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Singleton, Drake Moore 0000-0001-5346-0623","orcid":"https://orcid.org/0000-0001-5346-0623","contributorId":261207,"corporation":false,"usgs":true,"family":"Singleton","given":"Drake","email":"","middleInitial":"Moore","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":927318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maloney, Jillian","contributorId":304141,"corporation":false,"usgs":false,"family":"Maloney","given":"Jillian","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":927319,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agnew, Duncan 0000-0002-2360-7783","orcid":"https://orcid.org/0000-0002-2360-7783","contributorId":178605,"corporation":false,"usgs":false,"family":"Agnew","given":"Duncan","email":"","affiliations":[],"preferred":false,"id":927320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rockwell, Thomas","contributorId":175454,"corporation":false,"usgs":false,"family":"Rockwell","given":"Thomas","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":927321,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255731,"text":"ofr20241012 - 2024 - Report of the River Master of the Delaware River for the period December 1, 2015 - November 30, 2016","interactions":[],"lastModifiedDate":"2026-01-29T17:08:39.677727","indexId":"ofr20241012","displayToPublicDate":"2024-07-16T09:09:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1012","displayTitle":"Report of the River Master of the Delaware River for the Period December 1, 2015–November 30, 2016","title":"Report of the River Master of the Delaware River for the period December 1, 2015 - November 30, 2016","docAbstract":"A Decree of the Supreme Court of the United States, entered June 7, 1954 (New Jersey v. New York, 347 U.S. 995), established the position of Delaware River Master within the U.S. Geological Survey. In addition, the Decree authorizes the diversion of water from the Delaware River Basin and requires compensating releases from reservoirs owned by New York City to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master provide reports to the Court not less frequently than annually. This report is the 63rd annual report of the River Master of the Delaware River. The report covers the 2016 River Master report year, which is the period from December 1, 2015, to November 30, 2016.
During the report year, precipitation in the upper Delaware River Basin was 38.6 inches or 87 percent of the long-term average. Combined storage remained high (above 80 percent of combined capacity) for much of the year and did not decline below 80 percent of combined capacity until August 2016. The lowest combined storage was 106.406 billion gallons or 39 percent of combined capacity on November 28, 2016. Delaware River Basin Commission Resolution 2016–07 necessitated a basinwide drought watch on November 23, 2016. The drought watch continued through the remainder of the 2016 report year. Delaware River Master operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program. New York City and New Jersey fully complied with the terms of the Decree and, during drought watch conditions, with the Delaware River Basin Commission Resolution 2016–07 terms. Diversions from the Delaware River Basin by New York City and New Jersey fully complied with the Decree. The reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey, on 126 days during the report year. Interim Excess Release Quantity and conservation releases, designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs, were also made during the report year.
Water quality in the Delaware River estuary between the streamgages at Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at several locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241012","isbn":"978-1-4113-4551-5","usgsCitation":"Russell, K.L., Andrews, W.J., DiFrenna, V.J., Norris, J.M., and Mason, R.R., Jr., 2024, Report of the River Master of the Delaware River for the period December 1, 2015–November 30, 2016: U.S. Geological Survey Open-File Report 2024–1012, 105 p., https://doi.org/10.3133/ofr20241012.","productDescription":"xi, 105 p.","numberOfPages":"105","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-144909","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":430729,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1012/images/"},{"id":430728,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1012/ofr20241012.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1012 XML"},{"id":499229,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117124.htm","linkFileType":{"id":5,"text":"html"}},{"id":430727,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241012/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1012 HTML"},{"id":430725,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1012/coverthb.jpg"},{"id":430726,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1012/ofr20241012.pdf","text":"Report","size":"9.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1012 PDF"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76,\n 40\n ],\n [\n -74,\n 40\n ],\n [\n -74,\n 42.5\n ],\n [\n -76,\n 42.5\n ],\n [\n -76,\n 40\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Delaware River Master
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Mississippi has a dispersed population of nearly three million residents in an area of approximately 48,400 square miles and has a favorable climate for agriculture, with abundant precipitation and minimal extreme temperatures. The topography consists mostly of low hills and lowland plains, with the highest elevation about 800 feet above sea level. An exception is the nearly flat Mississippi Alluvial Plain, or “Delta,” in the northwestern part of the State. Agriculture and forestry are Mississippi’s major industries. With 65 percent of its area forested, the State is one of the country’s top producers of lumber and wood-related products. In addition to agriculture and forest resources management, other important economic activities are infrastructure and construction management, flood risk management, and water supply and quality assessment. High-quality elevation data can help to support these activities. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
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\"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey
MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Animal movement is a fundamental mechanism that shapes communities and ecosystems. Ungulates alter the ecosystems they inhabit and understanding their movements and distribution is critical for linking habitat with population dynamics. Predation risk has been shown to strongly influence ungulate movement patterns, such that ungulates may select habitat where predation risk is lower (refugia), adjust movement rates, temporal patterns, or selection of cover variables in areas with greater predation risk. We evaluated potential predation avoidance behavior in a population of plains bison inhabiting the north rim of Grand Canyon National Park (GRCA) and adjacent Kaibab National Forest (KNF). The KNF has year-round hunting managed by Arizona Game and Fish Department, whereas hunting is not allowed in GRCA. Human-maintained water sources on the KNF are particularly important resources for bison wherein they may be exposed to higher predation risk to access these resources. We used 2-h GPS locations for three years from 31 bison (n = 9 males; n = 22 females), and integrative step selection analysis to test four hypotheses about the potential for bison to reduce their risk from human predation by avoiding areas of high predation risk; moving faster in areas with high predation risk; entering high-risk areas at night when risk is reduced; and entering high-risk areas in habitats that provide cover (coniferous forest). The highest performing model indicated bison movement was 1.3 times faster per 2-h step interval than in areas with no hunting across all vegetation classes (coniferous forest, shrub, quaking aspen, grass-forb meadow) and across all topography classes (valley, slope, ridge). Bison moved more slowly in grass-forb meadows than all other vegetation types, and in valleys relative to slopes and ridges. Several radio-collared individuals had no GPS locations in KNF for the duration of the study. Bison avoided predation risk using two strategies: moving faster while in the KNF, and fully avoiding high-risk areas by remaining within GRCA. Management that manipulates or reduces timing of hunting seasons may reduce perceived predation risk and encourage bison to distribute into the KNF and across a broader range of available habitat.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4909","usgsCitation":"Salganek, S., Schoenecker, K., and Terwilliger, M., 2024, Using integrated step selection to determine effects of predation risk on bison habitat selection and movement: Ecosphere, v. 15, no. 7, e4909, 16 p., https://doi.org/10.1002/ecs2.4909.","productDescription":"e4909, 16 p.","ipdsId":"IP-148082","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":492488,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4909","text":"Publisher Index Page"},{"id":492199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","county":"Coconino County","otherGeospatial":"Kaibab Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.68098786953385,\n 36.999074018413296\n ],\n [\n -112.68098786953385,\n 35.85596339767277\n ],\n [\n -111.67893358079623,\n 35.85596339767277\n ],\n [\n -111.67893358079623,\n 36.999074018413296\n ],\n [\n -112.68098786953385,\n 36.999074018413296\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Salganek, Skye","contributorId":357945,"corporation":false,"usgs":false,"family":"Salganek","given":"Skye","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":942896,"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":942897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terwilliger, Miranda L.N.","contributorId":357947,"corporation":false,"usgs":false,"family":"Terwilliger","given":"Miranda L.N.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":942898,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256181,"text":"70256181 - 2024 - Modeling the potential habitat gained by planting sagebrush in burned landscapes","interactions":[],"lastModifiedDate":"2024-08-01T18:09:27.139004","indexId":"70256181","displayToPublicDate":"2024-07-15T07:03:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18016,"text":"Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the potential habitat gained by planting sagebrush in burned landscapes","docAbstract":"Many revegetation projects are intended to benefit wildlife species. Yet, there are few a priori evaluations that assess the potential efficiency of restoration actions in recovering wildlife habitats. We developed a spatial vegetation–habitat recovery model to gauge the degree to which field planting strategies could be expected to recover multi-factor habitat conditions for wildlife following wildfires. We simulated a wildfire footprint, multiple sagebrush (Artemisia spp.) planting scenarios, and tracked projected vegetation growth for 15 years post-fire. We used a vegetation transition framework to track and estimate the degree to which revegetation could accelerate habitat restoration for a Greater sage-grouse (Centrocercus) population within the Great Basin, western United States. We assessed the amount of habitat 15 years post-fire to estimate the degree to which revegetation could be expected to accelerate habitat restoration. Our results highlight a potential disconnect between the expansive areas required by wide-ranging wildlife such as sage-grouse and the relatively small areas that planting treatments have created. Habitat restorations and planting strategies that are intended to benefit sage-grouse may only speed up localized habitat restoration. This study provides an example of how linked revegetation–habitat modeling approaches can scope the expected return on restoration investment for habitat improvements and support the strategic use of limited restoration resources.
","language":"English","publisher":"MDPI","doi":"10.3390/conservation4030024","usgsCitation":"Heinrichs, J., O’Donnell, M.S., Orning, E.K., Pyke, D.A., Ricca, M.A., Coates, P.S., and Aldridge, C.L., 2024, Modeling the potential habitat gained by planting sagebrush in burned landscapes: Conservation, v. 4, no. 3, p. 364-377, https://doi.org/10.3390/conservation4030024.","productDescription":"14 p.","startPage":"364","endPage":"377","ipdsId":"IP-110620","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":439279,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/conservation4030024","text":"Publisher Index Page"},{"id":434928,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S4WHHV","text":"USGS data release","linkHelpText":"veg_sim: Modeling Greater sage-grouse habitat suitability 15-years post simulated fire event and sagebrush transplanting (2015-2030)"},{"id":431438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.21272893162755,\n 42.005085754708546\n ],\n [\n -117.21272893162755,\n 40.091378407222805\n ],\n [\n -113.98274846287774,\n 40.091378407222805\n ],\n [\n -113.98274846287774,\n 42.005085754708546\n ],\n [\n -117.21272893162755,\n 42.005085754708546\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Heinrichs, Julie A. 0000-0001-7733-5034","orcid":"https://orcid.org/0000-0001-7733-5034","contributorId":240888,"corporation":false,"usgs":false,"family":"Heinrichs","given":"Julie A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":907004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":907005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orning, Elizabeth Kari 0000-0002-1376-729X","orcid":"https://orcid.org/0000-0002-1376-729X","contributorId":315548,"corporation":false,"usgs":true,"family":"Orning","given":"Elizabeth","email":"","middleInitial":"Kari","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":907006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":907007,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":907059,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":907060,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":907008,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256026,"text":"70256026 - 2024 - Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall","interactions":[],"lastModifiedDate":"2024-07-16T11:45:30.466723","indexId":"70256026","displayToPublicDate":"2024-07-15T06:38:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall","docAbstract":"Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24 h lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9 January 2018 debris-flow event in Montecito, California, USA. When the observed debris-flow volumes were used to drive the probabilistic forecast model, analysis of the simulated inundation probabilities demonstrates that the model is both reliable and sharp. In the fully predictive model, however, in which debris-flow likelihood and volume were computed from the atmospheric model ensemble's predictions of peak 15 min rainfall intensity, I15, the model generally under-forecasted the inundation area. The observed peak I15 lies in the upper tail of the atmospheric model ensemble spread; thus a large fraction of ensemble members forecast lower I15 than observed. Using these I15 values as input to the inundation model resulted in lower-than-observed flow volumes which translated into under-forecasting of the inundation area. Even so, approximately 94 % of the observed inundated area was forecast to have an inundation probability greater than 1 %, demonstrating that the observed extent of inundation was generally captured within the range of outcomes predicted by the model. Sensitivity analyses indicate that debris-flow volume and two parameters associated with debris-flow mobility exert significant influence on inundation predictions, but reducing uncertainty in postfire debris-flow volume predictions will have the largest impact on reducing inundation outcome uncertainty. This study represents a first step toward a near-real-time hazard assessment product that includes probabilistic estimates of debris-flow inundation and provides guidance for future improvements to this and similar model frameworks by identifying key sources of uncertainty.
Volcanic unrest and eruptions are associated with surface deformation and landscape change that can be detected, characterized, and tracked via remote sensing measurements. Subsurface processes, including magma accumulation, withdrawal, and transport, can cause displacements at the surface that are best tracked at subaerial volcanoes with interferometric synthetic aperture radar (InSAR) and Global Navigation Satellite System (GNSS) measurements, although non-volcanic activity, like hydrothermal and tectonic sources, can complicate interpretations. Surface change is often associated with the emplacement of volcanic deposits, which modify the landscape and can experience post-emplacement deformation or morphological changes over time. Measurement of surface topography at volcanoes via remote means is a particularly important capability, given the control that topography exerts on many volcanic hazards and the potential for topographic change measurements to provide information about eruption rates. A much broader set of tools is available to investigate surface change at volcanoes, including not only InSAR and GNSS, but also synthetic aperture radar amplitude data, visible imagery, and lidar, acquired from airborne, ground-based, and satellite platforms. These data can also be used to identify instability of volcanic flanks and even have potential for use in detecting airborne ash plumes. Although hidden from traditional airborne and space-based remote sensing, deformation and surface change associated with submarine volcanism can be investigated with pressure sensors and bathymetric measurements—the below-water remote sensing analogs of GNSS and InSAR, respectively.
The freshwater salinization syndrome (FSS), a concomitant watershed-scale increase in salinity, alkalinity, and major-cation and trace-metal concentrations, over recent decades, has been described for major rivers draining extensive urban areas, yet few studies have evaluated temporal and spatial FSS variations, or causal factors, at the subwatershed scale in mixed-use landscapes. This study examines the potential influence of land-use practices and wastewater treatment plant (WWTP) effluent on the export of major ions and trace metals from the mixed-use East Branch Brandywine Creek watershed in southeastern Pennsylvania, during the 2019 water year. Separate analysis of baseflow and stormflow subsets revealed similar correlations among land-use characteristics and streamwater chemistry. Positive associations between percent impervious surface cover, which ranged from 1.26 % to 21.9 % for the 13 sites sampled, and concentrations of Ca2+, Mg2+, Na+, and Cl− are consistent with road-salt driven reverse cation exchange and weathering of the built environment. The relative volume of upstream WWTP was correlated with Cu and Zn, which may be derived in part from corroded water-conveyance infrastructure; chloride to sulfate mass ratios (CSMR) ranged from ~6.3 to ~7.7× the 0.5 threshold indicating serious corrosivity potential. Observed exceedances of U.S. Environmental Protection Agency Na+ and Cl− drinking water and aquatic life criteria occurred in winter months. Finally, correlations between percent cultivated cropland and As and Pb concentrations may be explained by the persistence of agricultural pesticides that had been used historically. Study results contribute to the understanding of FSS solute origin, fate, and transport in mixed-use watersheds, particularly those in road salt-affected regions. Study results also emphasize the complexity of trace-metal source attribution and explore the potential for FSS solutes to affect human health, aquatic life, and infrastructure.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2024.174266","usgsCitation":"Marks, N.K., Cravotta, C., Rossi, M.L., Silva, C., Kremer, P., and Goldsmith, S.T., 2024, Exploring spatial and temporal symptoms of the freshwater salinization syndrome in a rural to urban watershed: Science of the Total Environment, v. 947, 174266, 17 p., https://doi.org/10.1016/j.scitotenv.2024.174266.","productDescription":"174266, 17 p.","ipdsId":"IP-154332","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":466983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2024.174266","text":"Publisher Index Page"},{"id":464716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"East Branch Brandywine Creek watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.83342045572547,\n 40.01916009274666\n ],\n [\n -75.72337369661636,\n 39.97446847844611\n ],\n [\n -75.66768738477772,\n 39.96227478065106\n ],\n [\n -75.61332693750671,\n 40.00088069477613\n ],\n [\n -75.6106752083719,\n 40.09425729037662\n ],\n [\n -75.62260798947986,\n 40.11555358035895\n ],\n [\n -75.71011505094027,\n 40.1621792980624\n ],\n [\n -75.83474632029366,\n 40.14090269654602\n ],\n [\n -75.8519825596717,\n 40.078027071145215\n ],\n [\n -75.84535323683392,\n 40.05570674139187\n ],\n [\n -75.83342045572547,\n 40.01916009274666\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"947","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marks, Nicole K.","contributorId":346882,"corporation":false,"usgs":false,"family":"Marks","given":"Nicole","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":920112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":258816,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rossi, Marissa Lee 0000-0003-2341-0312","orcid":"https://orcid.org/0000-0003-2341-0312","contributorId":310430,"corporation":false,"usgs":true,"family":"Rossi","given":"Marissa","email":"","middleInitial":"Lee","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Silva, Camila","contributorId":346883,"corporation":false,"usgs":false,"family":"Silva","given":"Camila","email":"","affiliations":[],"preferred":false,"id":920115,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kremer, Peleg","contributorId":296521,"corporation":false,"usgs":false,"family":"Kremer","given":"Peleg","email":"","affiliations":[{"id":12766,"text":"Villanova University","active":true,"usgs":false}],"preferred":false,"id":920116,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goldsmith, Steven T.","contributorId":193458,"corporation":false,"usgs":false,"family":"Goldsmith","given":"Steven","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":920117,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256033,"text":"70256033 - 2024 - Palaeontological signatures of the Anthropocene are distinct from those of previous epochs","interactions":[],"lastModifiedDate":"2024-07-16T11:56:38.958876","indexId":"70256033","displayToPublicDate":"2024-07-13T06:54:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14252,"text":"Earth Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Palaeontological signatures of the Anthropocene are distinct from those of previous epochs","docAbstract":"The “Great Acceleration” beginning in the mid-20th century provides the causal mechanism of the Anthropocene, which has been proposed as a new epoch of geological time beginning in 1952 CE. Here we identify key parameters and their diagnostic palaeontological signals of the Anthropocene, including the rapid breakdown of discrete biogeographical ranges for marine and terrestrial species, rapid changes to ecologies resulting from climate change and ecological degradation, the spread of exotic foodstuffs beyond their ecological range, and the accumulation of reconfigured forest materials such as medium density fibreboard (MDF) all being symptoms of the Great Acceleration. We show: 1) how Anthropocene successions in North America, South America, Africa, Oceania, Europe, and Asia can be correlated using palaeontological signatures of highly invasive species and changes to ecologies that demonstrate the growing interconnectivity of human systems; 2) how the unique depositional settings of landfills may concentrate the remains of organisms far beyond their geographical range of environmental tolerance; and 3) how a range of settings may preserve a long-lived, unique palaeontological record within post-mid-20th century deposits. Collectively these changes provide a global palaeontological signature that is distinct from all past records of deep-time biotic change, including those of the Holocene.
Des Moines Water Works (DMWW) is a regional municipal water utility that provides residential and commercial water resources to about 600,000 customers in Des Moines, Iowa, and surrounding municipalities in central Iowa. DMWW has identified a need for increased water supply and is exploring the potential for expanding groundwater production capabilities in the Des Moines River alluvial aquifer, where it operates two radial collector wells (RCWs). The U.S. Geological Survey, in cooperation with DMWW, completed a study of the Des Moines River alluvial aquifer and interactions of the RCWs with the aquifer; no previously published model has included the existing well locations, which is the focus of this model. A conceptual and numerical groundwater flow model have been developed to characterize the Des Moines River alluvial aquifer under existing conditions, to simulate water levels observed in the RCWs, and to provide publicly accessible hydrologic data and research that advance understanding of the regional hydrologic system and can potentially be used in the future to evaluate groundwater production scenarios. Model performance was assessed by comparing observed and simulated groundwater levels that included water level elevations, water level changes, water level inequality observations, surface water streamflow, and change in surface water volume from upstream to downstream. Water table elevation in the aquifer layers is on average slightly overestimated with average absolute value error less than 1.5 meters at both RCWs and less than 2.5 meters for all observation wells in the alluvial aquifer layers. The model also accurately simulated water tables greater than the RCW design minimum (a water level threshold at which RCW pumping is reduced) in all timesteps for which water level observation data existed. Water table elevation error was higher in other model layers that were not the focus of the study, and the model did not accurately match streamflow targets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245059","collaboration":"Prepared in cooperation with Des Moines Water Works","usgsCitation":"Bristow, E.L., and Davis, K.W., 2024, Groundwater flow model for the Des Moines River alluvial aquifer near Des Moines, Iowa: U.S. Geological Survey Scientific Investigations Report 2024–5059, 47 p., https://doi.org/10.3133/sir20245059.","productDescription":"Report: ix, 47 p.; 3 Data Releases; 1 Dataset","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154246","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":430905,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5059/sir20245059.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5059"},{"id":430904,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5059/coverthb.jpg"},{"id":430906,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5059/sir20245059.XML"},{"id":430907,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5059/images/"},{"id":430908,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245059/full"},{"id":430909,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":430910,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13ZDDVY","text":"USGS data release","linkHelpText":"MODFLOW 6 groundwater flow model for the Des Moines River alluvial aquifer near Des Moines, Iowa"},{"id":430911,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B9AVKJ","text":"USGS data release","linkHelpText":"Geophysical data collected in the Des Moines River, Beaver Creek, and the Des Moines River floodplain, Des Moines, Iowa, 2018"},{"id":430912,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F3CKLC","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater levels in the Des Moines River alluvial aquifer near Des Moines, Iowa"},{"id":499480,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117123.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Iowa","city":"Des Moines","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.75578446475713,\n 41.70743368403336\n ],\n [\n -93.75578446475713,\n 41.53433869670215\n ],\n [\n -93.54349781702975,\n 41.53433869670215\n ],\n [\n -93.54349781702975,\n 41.70743368403336\n ],\n [\n -93.75578446475713,\n 41.70743368403336\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
Accelerated sea-level rise is an existential threat to coastal wetlands, but the timing and extent of wetland drowning are debated. Recent data syntheses have clarified future relative sea-level rise exposure and sensitivity thresholds for drowning. Here, we integrate these advances to estimate when and where rising sea levels could cross thresholds for initiating wetland drowning across the conterminous United States. Our results show that there is much spatial variation in relative sea-level rise rates, which impacts the potential timing and extent of wetlands crossing thresholds. High rates of relative sea-level rise along wetland-rich parts of the Gulf of Mexico and Atlantic coasts highlight areas where wetlands are already drowning or could begin to drown within decades, including large wetland landscapes within the Mississippi River delta, Greater Everglades, Chesapeake Bay, Texas, Georgia, and the Carolinas. Collectively, our results underscore the need to prepare for transformative coastal change.
Emerging infectious diseases with zoonotic potential often have complex socioecological dynamics and limited ecological data, requiring integration of epidemiological modeling with surveillance. Although our understanding of SARS-CoV-2 has advanced considerably since its detection in late 2019, the factors influencing its introduction and transmission in wildlife hosts, particularly white-tailed deer (Odocoileus virginianus), remain poorly understood. We use a Susceptible-Infected-Recovered-Susceptible epidemiological model to investigate the spillover risk and transmission dynamics of SARS-CoV-2 in wild and captive white-tailed deer populations across various simulated scenarios. We found that captive scenarios pose a higher risk of SARS-CoV-2 introduction from humans into deer herds and subsequent transmission among deer, compared to wild herds. However, even in wild herds, the transmission risk is often substantial enough to sustain infections. Furthermore, we demonstrate that the strength of introduction from humans influences outbreak characteristics only to a certain extent. Transmission among deer was frequently sufficient for widespread outbreaks in deer populations, regardless of the initial level of introduction. We also explore the potential for fence line interactions between captive and wild deer to elevate outbreak metrics in wild herds that have the lowest risk of introduction and sustained transmission. Our results indicate that SARS-CoV-2 could be introduced and maintained in deer herds across a range of circumstances based on testing a range of introduction and transmission risks in various captive and wild scenarios. Our approach and findings will aid One Health strategies that mitigate persistent SARS-CoV-2 outbreaks in white-tailed deer populations and potential spillback to humans.
The 2-aminoethanol salt of niclosamide (2′,5-dichloro-4′-nitrosalicylanilide) is a pesticide known as Bayluscide that is used in conjunction with TFM (4-nitro-3-[trifluoromethyl]phenol), also known as 3-trifluoromethyl-4-nitrophenol) to treat tributaries to the Great Lakes infested with invasive parasitic Petromyzon marinus (sea lamprey). Adding 0.5 to 2 percent Bayluscide with TFM can substantially reduce the amount of TFM required to achieve effective control. Currently, an emulsifiable concentrate (EC) formulation of Bayluscide is used in combination with TFM during some stream treatments completed by the Great Lakes Fishery Commission’s binational sea lamprey control program. The Bayluscide EC formulation is highly effective; however, it degrades application tubing, adheres to application equipment, and raises concerns for worker safety because of the solvent in the formulation, N-methyl-2-pyrrolidone.
We collaborated with a pesticide formulation company to develop a Bayluscide 20-percent suspension concentrate (SC) formulation as a potential replacement for the Bayluscide 20-percent EC formulation. The 20-percent SC formulation was specifically developed using inert ingredients approved for use by the U.S. Environmental Protection Agency and the Health Canada Pest Management Regulatory Agency. Although approved for use, the inclusion of a small quantity of an antimicrobial in the formulation warranted evaluating the toxicological profile to sea lamprey and select nontarget fish species. We evaluated and compared the toxicity of the 20-percent SC formulation to the 20-percent EC formulation using continuous-flow diluter systems and larval sea lamprey and select cold-, cool-, and warm-water fish as test animals. Our results demonstrate comparable toxicological profiles between the two formulations with the 20-percent SC formulation being slightly less toxic to the nontarget species evaluated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241037","usgsCitation":"Luoma, J.A., Schueller, J.R., Schloesser, N.A., Kirkeeng, C.A., and Wolfe, S.L., 2024, Comparative toxicity of emulsifiable concentrate and suspension concentrate formulations of 2′,5-dichloro-4′-nitrosalicylanilide ethanolamine salt: U.S. Geological Survey Open-File Report 2024–1037, 10 p., https://doi.org/10.3133/ofr20241037.","productDescription":"Report: vii, 10 p.; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-161507","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":430974,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1473X4B","text":"USGS data release","linkHelpText":"Data and code release—Comparative toxicity of emulsifiable concentrate and suspension concentrate formulations of 2′,5-dichloro-4′-nitrosalicylanilide ethanolamine salt"},{"id":430973,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241037/full"},{"id":430971,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1037/ofr20241037.XML"},{"id":430969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1037/coverthb.jpg"},{"id":430970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1037/ofr20241037.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1037"},{"id":430972,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1037/images/"}],"contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
International Ocean Discovery Program (IODP) Expedition 374 sailed to the Ross Sea in 2018 to reconstruct paleoenvironments, track the history of key water masses, and assess model simulations that show warm-water incursions from the Southern Ocean led to the loss of marine-based Antarctic ice sheets during past interglacials. IODP Site U1523 (water depth 828 m) is located at the continental shelf break, northeast of Pennell Bank on the southeastern flank of Iselin Bank, where it lies beneath the Antarctic Slope Current (ASC). This site is sensitive to warm-water incursions from the Ross Sea Gyre and modified Circumpolar Deep Water (mCDW) today and during times of past warming climate. Multiple incursions of subpolar or temperate planktic foraminifera taxa occurred at Site U1523 after 3.8 Ma and prior to ∼ 1.82 Ma. Many of these warm-water taxa incursions likely represent interglacials of the latest Early Pliocene and Early Pleistocene, including Marine Isotope Stage (MIS) Gi7 to Gi3 (∼ 3.72–3.65 Ma), and Early Pleistocene MIS 91 or 90 (∼ 2.34–2.32 Ma) and MIS 77–67 (∼ 2.03–1.83 Ma) and suggest warmer-than-present conditions and less ice cover in the Ross Sea. However, a moderately resolved age model based on four key events prohibits us from precisely correlating with Marine Isotope Stages established by the LR04 Stack; therefore, these correlations are best estimates. Diatom-rich intervals during the latest Pliocene at Site U1523 include evidence of anomalously warm conditions based on the presence of subtropical and temperate planktic foraminiferal species in what likely correlates with interglacial MIS G17 (∼ 2.95 Ma), and a second interval that likely correlates with MIS KM3 (∼ 3.16 Ma) of the mid-Piacenzian Warm Period. Collectively, these multiple incursions of warmer-water planktic foraminifera provide evidence for polar amplification during super-interglacials of the Pliocene and Early Pleistocene. Higher abundances of planktic and benthic foraminifera during the Mid- to Late Pleistocene associated with interglacials of the MIS 37–31 interval (∼ 1.23–1.07 Ma), MIS 25 (∼ 0.95 Ma), MIS 15 (∼ 0.60 Ma), and MIS 6–5e transition (∼ 0.133–0.126 Ma) also indicate a reduced ice shelf and relatively warm conditions, including multiple warmer interglacials during the Mid-Pleistocene Transition (MPT). A decrease in sedimentation rate after ∼ 1.78 Ma is followed by a major change in benthic foraminiferal biofacies marked by a decrease in Globocassidulina subglobosa and a decrease in mud (< 63 µm) after ∼ 1.5 Ma. Subsequent dominance of Trifarina earlandi biofacies beginning during MIS 15 (∼ 600 ka) indicate progressive strengthening of the Antarctic Slope Current along the shelf edge of the Ross Sea during the mid to Late Pleistocene. A sharp increase in foraminiferal fragmentation after the MPT (∼ 900 ka) and variable abundances of T. earlandi indicate higher productivity, a stronger but variable ASC during interglacials, and/or corrosive waters, suggesting changes in water masses entering (mCDW) and exiting (High Salinity Shelf Water or Dense Shelf Water) the Ross Sea since the MPT.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/jm-43-211-2024","usgsCitation":"Seidenstein, J.L., Leckie, R., McKay, R., De Santis, L., Harwood, D., and IODP Expedition 374 Scientists, 2024, Pliocene–Pleistocene warm-water incursions and water mass changes on the Ross Sea continental shelf (Antarctica) based on foraminifera from IODP Expedition 374: Journal of Micropalaeontology, v. 43, no. 2, p. 211-238, https://doi.org/10.5194/jm-43-211-2024.","productDescription":"28 p.","startPage":"211","endPage":"238","ipdsId":"IP-154696","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":488299,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/jm-43-211-2024","text":"Publisher Index Page"},{"id":483338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Ross Ice Shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -179.9,\n -70\n ],\n [\n -179.9,\n -78\n ],\n [\n -150,\n -78\n ],\n [\n -150,\n -70\n ],\n [\n -179.9,\n -70\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 170,\n -70\n ],\n [\n 170,\n -78\n ],\n [\n 179.9,\n -78\n ],\n [\n 179.9,\n -70\n ],\n [\n 170,\n -70\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"43","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Seidenstein, Julia Lynn 0000-0002-0585-1977","orcid":"https://orcid.org/0000-0002-0585-1977","contributorId":290625,"corporation":false,"usgs":true,"family":"Seidenstein","given":"Julia","email":"","middleInitial":"Lynn","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":930738,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leckie, R. Mark","contributorId":352312,"corporation":false,"usgs":false,"family":"Leckie","given":"R. Mark","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":930739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKay, Robert","contributorId":9546,"corporation":false,"usgs":true,"family":"McKay","given":"Robert","affiliations":[],"preferred":false,"id":930752,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"De Santis, L.","contributorId":96471,"corporation":false,"usgs":true,"family":"De Santis","given":"L.","email":"","affiliations":[],"preferred":false,"id":930753,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harwood, David","contributorId":352313,"corporation":false,"usgs":false,"family":"Harwood","given":"David","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":930740,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"IODP Expedition 374 Scientists","contributorId":352319,"corporation":true,"usgs":false,"organization":"IODP Expedition 374 Scientists","id":930754,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261605,"text":"70261605 - 2024 - Silver Chub spawning confirmed in the Maumee River, a tributary of Lake Erie","interactions":[],"lastModifiedDate":"2024-12-17T14:54:10.639043","indexId":"70261605","displayToPublicDate":"2024-07-11T08:49:35","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Silver Chub spawning confirmed in the Maumee River, a tributary of Lake Erie","docAbstract":"Biodiversity is declining due to invasive species and other factors that can affect individual species differently. Silver Chub Macrhybopsis storeriana are declining in their native range, and their conservation status in the Great Lakes ranges from secure to possibly extirpated. Lake Erie once supported a large Silver Chub population until it crashed in the 1950s. Additionally, the spawning behavior and reproductive guild of Silver Chub in Lake Erie is unknown. Our objective was to document Silver Chub spawning in the Maumee River, a Lake Erie tributary.
Invasive Grass Carp Ctenopharyngodon idella are known to spawn in the Maumee River during high-flow events from May to July, and the University of Toledo and U.S. Geological Survey regularly sample the lower 24 km for early life stages using paired bongo nets. Contents from paired bongo nets are returned to the laboratory for processing, and a subset of potential Grass Carp eggs are sent for genetic analysis.
On June 8, 2022, several potential Grass Carp eggs were captured at two sites on the Maumee River during a high-flow event. Fifteen potential Grass Carp eggs were sent for genetic analysis, and DNA sequencing revealed that six of these eggs were Silver Chub.
This was the first known collection of Silver Chub eggs in a Lake Erie tributary, and our findings indicate that Silver Chub likely belong to the pelagophil reproductive guild. Although Grass Carp and Silver Chub spawn under similar conditions, management actions to control Grass Carp in the Maumee River may be unlikely to affect Silver Chub due to electrofishing settings used in the capture of Grass Carp. The verification of Silver Chub spawning in a Western Erie Basin tributary provides insights into their reproductive biology that could be useful in recovery planning in Lake Erie and throughout the Great Lakes.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.11018","usgsCitation":"Brown, R.E., Mayer, C.M., Thompson, N., Hilling, C.D., Roberts, J., and Richter, C.A., 2024, Silver Chub spawning confirmed in the Maumee River, a tributary of Lake Erie: North American Journal of Fisheries Management, v. 44, no. 4, p. 849-856, https://doi.org/10.1002/nafm.11018.","productDescription":"8 p.","startPage":"849","endPage":"856","ipdsId":"IP-160696","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":466984,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.11018","text":"Publisher Index Page"},{"id":465187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Maumee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.61706918500697,\n 41.58428035547584\n ],\n [\n -83.68677030613738,\n 41.58428035547584\n ],\n [\n -83.68677030613738,\n 41.53713542031409\n ],\n [\n -83.61706918500697,\n 41.53713542031409\n ],\n [\n -83.61706918500697,\n 41.58428035547584\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Ryan E.","contributorId":332137,"corporation":false,"usgs":false,"family":"Brown","given":"Ryan","email":"","middleInitial":"E.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":921167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mayer, Christine M.","contributorId":203271,"corporation":false,"usgs":false,"family":"Mayer","given":"Christine","email":"","middleInitial":"M.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":921168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Nathan 0000-0002-1372-6340 nthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-1372-6340","contributorId":196133,"corporation":false,"usgs":true,"family":"Thompson","given":"Nathan","email":"nthompson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":921169,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hilling, Corbin David 0000-0003-4040-9516","orcid":"https://orcid.org/0000-0003-4040-9516","contributorId":298946,"corporation":false,"usgs":true,"family":"Hilling","given":"Corbin","email":"","middleInitial":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":921170,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":921171,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richter, Catherine A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":138994,"corporation":false,"usgs":true,"family":"Richter","given":"Catherine","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":921172,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256053,"text":"70256053 - 2024 - Sero-epidemiology of Highly Pathogenic Avian Influenza viruses among wild birds in subarctic intercontinental transition zones","interactions":[],"lastModifiedDate":"2024-07-17T13:22:14.276022","indexId":"70256053","displayToPublicDate":"2024-07-11T08:20:23","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18008,"text":"Research Square","active":true,"publicationSubtype":{"id":32}},"title":"Sero-epidemiology of Highly Pathogenic Avian Influenza viruses among wild birds in subarctic intercontinental transition zones","docAbstract":"Background: The geographic expansion and evolution of A/Goose/Guangdong/1/1996(H5N1) (Gs/GD) lineage H5Nx highly pathogenic avian influenza (HPAI) viruses since 1996 have raised awareness of enzootic circulation among migratory birds and the potential for intercontinental transport and spread. Recent Pacific- and Atlantic-route introductions of HPAI to North America were facilitated by avian migration through subarctic zones, specifically Alaska and Iceland. This study aimed to identify recent historical patterns of exposure to HPAI viruses among birds within and migrating through both regions and evaluate how geographic, demographic, and taxonomic differences contribute to exposure risk at two intercontinental staging locations.
Methods: During 2010-2019, blood samples were obtained from captured wild migratory seabirds and waterfowl in Alaska and Iceland. All live birds were released following completion of sampling. Sampling date, species, sampling location, and age class was documented for each bird, and sex was documented when possible. Lentiviral pseudoviruses that express the influenza hemagglutinin surface glycoprotein for H5Nx HPAI and H5 low-pathogenicity avian influenza (LPAI) were constructed for use in serological assays to screen for and quantify titers of antibodies against the latter viruses. Data were analyzed to compare (a) categorical baseline ecological traits between Iceland and Alaska, and (b) ecological traits between birds identified to be seropositive and suggestive/seronegative/fully cross-reactive birds to H5Nx HPAI in Iceland and Alaska. Factors associated with seroreactivity to H5Nx HPAI and H5 LPAI were assessed.
Results:The seroprevalence of HPAI among birds in both locations was 7.3% (112/1526). Findings reveal variability in seroprevalence by year, higher rates of exposure to H5 LPAI than H5Nx HPAI overall, and significantly more seropositive and suggestive exposure of birds to H5Nx HPAI in Alaska as compared to Iceland. Geographic, demographic, and taxonomic differences contribute to exposure risk between Alaska and Iceland. Most tested birds were immuno-naïve to HPAI in both locations, which indicates many migratory birds in the subarctic are susceptible to HPAI infection, demonstrating substantial risk for intercontinental transmission between Asia, Europe, and North America.
Conclusions: Our findings provide further justification for increased viral and serosurveillance in Alaska and Iceland to monitor subarctic movements of migratory birds and intercontinental transmission dynamics of currently circulating and new strains of HPAI globally.
","language":"English","publisher":"Research Square","doi":"10.21203/rs.3.rs-4233804/v2","usgsCitation":"Gass, J.D., Dusek, R.J., Hill, N.J., Borkenhagen, L., Hall, J.S., Hallgrimsson, G.T., Bishop, M., Ramey, A.M., Timothy J. Spivey, Vignisson, S.R., Ragnarsdottir, S.B., Halldorsson, H.P., Jonsson, J.E., Simulynas, A.D., Nutter, F.B., Puryear, W., and Runstadler, J.A., 2024, Sero-epidemiology of Highly Pathogenic Avian Influenza viruses among wild birds in subarctic intercontinental transition zones: Research Square, https://doi.org/10.21203/rs.3.rs-4233804/v2.","productDescription":"27 p.","ipdsId":"IP-165563","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":466985,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.21203/rs.3.rs-4233804/v2","text":"External Repository"},{"id":431127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gass, Jonathon D.","contributorId":340193,"corporation":false,"usgs":false,"family":"Gass","given":"Jonathon","email":"","middleInitial":"D.","affiliations":[{"id":81502,"text":"Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University","active":true,"usgs":false}],"preferred":false,"id":906519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":174374,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":906520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hill, Nichola J.","contributorId":189563,"corporation":false,"usgs":false,"family":"Hill","given":"Nichola","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":906521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borkenhagen, Laura","contributorId":292318,"corporation":false,"usgs":false,"family":"Borkenhagen","given":"Laura","email":"","affiliations":[{"id":62870,"text":"Department of Infectious Disease and Global Health, Tufts University, North Grafton, MA 01536, USA","active":true,"usgs":false}],"preferred":false,"id":906522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":906523,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hallgrimsson, Gunnar Thor","contributorId":298374,"corporation":false,"usgs":false,"family":"Hallgrimsson","given":"Gunnar","email":"","middleInitial":"Thor","affiliations":[{"id":64545,"text":"Institute of Biology, University of Iceland","active":true,"usgs":false}],"preferred":false,"id":906524,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bishop, Mary Anne","contributorId":258847,"corporation":false,"usgs":false,"family":"Bishop","given":"Mary Anne","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":906525,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":906526,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Timothy J. Spivey","contributorId":340194,"corporation":false,"usgs":false,"family":"Timothy J. 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","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20243018","programNote":"National and Global Petroleum Assessment","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Le, P.A., Cicero, A.D., Drake, R.M., II, Ellis, G.S., Finn, T.M., Gardner, M.H., Gelman, S.E., Hearon, J.S., Johnson, B.G., Lagesse, J.H., Leathers-Miller, H.M., Marra, K.R., Timm, K.K., and Young, S.S., 2024, Assessment of undiscovered conventional oil and gas resources of the Black Sea area, 2023: U.S. Geological Survey Fact Sheet 2024–3018, 4 p., https://doi.org/10.3133/fs20243018.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-153353","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":430811,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"http://doi.org/10.5066/P145GOCC","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Black Sea Area: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":430958,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243018/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3018"},{"id":430810,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3018/fs20243018.pdf","text":"Report","size":"808 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3018"},{"id":430809,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3018/coverthb.jpg"},{"id":430900,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3018/images"},{"id":430901,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3018/fs20243018.xml"}],"country":"Bulgaria, Georgia, Moldova, Romania, Russia, Turkey, Ukraine","otherGeospatial":"Black Sea area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 26.73816007269457,\n 47.35313609234342\n ],\n [\n 26.73816007269457,\n 40.266796066832995\n ],\n [\n 42.91550600490609,\n 40.266796066832995\n ],\n [\n 42.91550600490609,\n 47.35313609234342\n ],\n [\n 26.73816007269457,\n 47.35313609234342\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Previous studies have demonstrated that vegetation-generated turbulence can enhance erosion rate and reduce the velocity threshold for erosion of non-cohesive sediment. This study considered whether vegetation-generated turbulence had a similar influence on natural cohesive sediment. Cores were collected from a black mangrove forest with aboveground biomass and exposed to stepwise increases in velocity. Erosion was recorded through suspended sediment concentration. For the same velocity, cores with pneumatophores had elevated turbulent kinetic energy compared to bare cores without pneumatophores. However, the vegetation-generated turbulence did not increase bed stress or the rate of resuspension, relative to bare cores. It was hypothesized that the short time-scale fluctuations associated with vegetation-generated turbulence were not of sufficient duration to break cohesion between grains, explaining why elevated levels of turbulence associated with the pneumatophores had no impact on the erosion threshold or rate.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GL109730","usgsCitation":"Deitrick, A.R., Ralston, D.K., Esposito, C.R., Baustian, M.M., Beltran Burgos, M., Courtois, A.J., and Nepf, H.M., 2024, Vegetation-generated turbulence does not impact the erosion of natural cohesive sediment: Geophysical Research Letters, v. 51, no. 14, e2024GL109730, 10 p., https://doi.org/10.1029/2024GL109730.","productDescription":"e2024GL109730, 10 p.","ipdsId":"IP-157158","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":439285,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gl109730","text":"Publisher Index Page"},{"id":431220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","city":"Port Fourchon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.21841177935528,\n 29.15\n ],\n [\n -90.27,\n 29.15\n ],\n [\n -90.27,\n 29.09003621081129\n ],\n [\n -90.21841177935528,\n 29.09003621081129\n ],\n [\n -90.21841177935528,\n 29.15\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"14","noUsgsAuthors":false,"publicationDate":"2024-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Deitrick, Autumn R.","contributorId":340204,"corporation":false,"usgs":false,"family":"Deitrick","given":"Autumn","email":"","middleInitial":"R.","affiliations":[{"id":81503,"text":"Department of Civil and Environmental Engineering, MIT-WHOI Joint Program in Oceanography/Applied Ocean Science and Engineering, Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":906565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ralston, David K. 0000-0002-0774-3101","orcid":"https://orcid.org/0000-0002-0774-3101","contributorId":195909,"corporation":false,"usgs":false,"family":"Ralston","given":"David","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":906566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esposito, Christopher R.","contributorId":340205,"corporation":false,"usgs":false,"family":"Esposito","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":81504,"text":"The Water Institute","active":true,"usgs":false}],"preferred":false,"id":906567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baustian, Melissa Millman 0000-0003-2467-2533","orcid":"https://orcid.org/0000-0003-2467-2533","contributorId":304015,"corporation":false,"usgs":true,"family":"Baustian","given":"Melissa","email":"","middleInitial":"Millman","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":906568,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beltran Burgos, Maricel","contributorId":340206,"corporation":false,"usgs":false,"family":"Beltran Burgos","given":"Maricel","email":"","affiliations":[{"id":81504,"text":"The Water Institute","active":true,"usgs":false}],"preferred":false,"id":906569,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Courtois, Andrew J.","contributorId":340207,"corporation":false,"usgs":false,"family":"Courtois","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":81504,"text":"The Water Institute","active":true,"usgs":false}],"preferred":false,"id":906570,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nepf, Heidi M.","contributorId":173323,"corporation":false,"usgs":false,"family":"Nepf","given":"Heidi","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":906571,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256416,"text":"70256416 - 2024 - A conceptual framework to assess post-wildfire water quality: State of the science and knowledge gaps","interactions":[],"lastModifiedDate":"2024-08-01T14:20:43.087876","indexId":"70256416","displayToPublicDate":"2024-07-10T09:19:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A conceptual framework to assess post-wildfire water quality: State of the science and knowledge gaps","docAbstract":"Wildfire substantially alters aquatic ecosystems by inducing moderate to catastrophic physical and chemical changes. However, the relations of environmental and watershed variables that drive those effects are complex. We present a Driver-Factor-Stressor-Effect (DFSE) conceptual framework to assess the current state of the science related to post-wildfire water-quality. We reviewed 64 peer-reviewed papers using the DFSE framework to identify drivers, factors, stressors, and effects associated with each study. A total of five drivers were identified and ranked according to their frequency of occurrence in the literature: atmospheric processes > fire characteristics > ecologic processes and characteristics > land surface characteristics > soil characteristics. Commonly reported stressors include increased nutrients, runoff, and sediment transport. Furthermore, although several different factors have been used at least once to explain water-quality effects, relatively few factors outside of precipitation and fire characteristics are frequently studied. We identified several gaps indicating the need for long-term monitoring, multi-factor studies, consideration of organic contaminants, consideration of groundwater, and inclusion of soil characteristics. This assessment expands on other reviews and meta-analyses by exploring causal linkages between influential variables and overall effects in post-wildfire watersheds. Information gathered from our assessment and the framework itself can be used to inform future monitoring plans and as a guide for modeling efforts focused on better understanding specific processes or to mitigate potential risks of post-wildfire water quality.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR036260","usgsCitation":"Elliott, S.M., Hornberger, M.I., Rosenberry, D.O., Frus, R., and Webb, R.M., 2024, A conceptual framework to assess post-wildfire water quality: State of the science and knowledge gaps: Water Resources Research, v. 60, no. 7, e2023WR036260, 20 p.; Data Release, https://doi.org/10.1029/2023WR036260.","productDescription":"e2023WR036260, 20 p.; Data Release","ipdsId":"IP-156361","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":439286,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr036260","text":"Publisher Index Page"},{"id":434931,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97JZOVY","text":"USGS data release","linkHelpText":"Annotated bibliography of 64 papers reviewed and summarized in a conceptual framework to assess post-wildfire water quality"},{"id":432026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":907311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hornberger, Michelle I. 0000-0002-7787-3446 mhornber@usgs.gov","orcid":"https://orcid.org/0000-0002-7787-3446","contributorId":1037,"corporation":false,"usgs":true,"family":"Hornberger","given":"Michelle","email":"mhornber@usgs.gov","middleInitial":"I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":907312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":907313,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frus, Rebecca J. 0000-0002-2435-7202","orcid":"https://orcid.org/0000-0002-2435-7202","contributorId":340187,"corporation":false,"usgs":false,"family":"Frus","given":"Rebecca J.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":907314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":907315,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257502,"text":"70257502 - 2024 - Same streams in a different forest? Investigations of forest harvest legacies and future trajectories across 30 years of stream habitat monitoring on the Tongass National Forest, Alaska","interactions":[],"lastModifiedDate":"2024-09-09T16:16:56.834676","indexId":"70257502","displayToPublicDate":"2024-07-10T09:07:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Same streams in a different forest? Investigations of forest harvest legacies and future trajectories across 30 years of stream habitat monitoring on the Tongass National Forest, Alaska","docAbstract":"The effects of timber harvest practices and climate change have altered forest ecosystems in southeast Alaska. However, quantification of patterns and trends in stream habitats associated with these forests is limited owing to a paucity of data available in remote watersheds. Here, we analyzed a 30-year dataset from southeast Alaska's Tongass National Forest to understand how these factors shape stream habitats. First, we examined differences between broad management classes (i.e., harvested and non-harvested) that have been used to guide stream channel restoration goals. Second, we assessed associations between intrinsic landscape characteristics, watershed management, and timber harvest legacies on aquatic habitat metrics. And third, we examined trends in stream habitat metrics over the duration of the dataset to anticipate future management challenges for these systems. Small effect sizes for some harvest-related predictors suggest that some stream habitat metrics, such as pool densities, are less responsive than others, and management practices such as protecting riparian buffers as well as post-harvest restoration may help conserve fish habitats. Large wood densities increased with time since harvest at sites harvested >50 years ago, indicating that multiple decades of post-harvest forest regrowth may contribute large wood to streams (possibly alder), but that it is not enough time for old-growth trees (e.g., spruce, Picea, or hemlock, Tsuga,), classified as key wood, to develop and be delivered to streams. The declining trend in key wood (i.e., the largest size class of wood) regardless of management history may reflect that pre-harvest legacy old-growth trees are declining along streams, with low replacement. The introduction of wood to maintain complex stream habitats may fill this gap until riparian stands again contribute structural key wood to streams. Trend analyses indicate an increasing spatial extent of undercut banks that may also be influenced by shifting hydrologic regimes under climate change.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0301723","usgsCitation":"Moore, M.J., Flitcroft, R., Tucker, E., Prussian, K.K., and Claeson, S.M., 2024, Same streams in a different forest? Investigations of forest harvest legacies and future trajectories across 30 years of stream habitat monitoring on the Tongass National Forest, Alaska: PLoS ONE, v. 19, no. 7, e0301723, 28 p., https://doi.org/10.1371/journal.pone.0301723.","productDescription":"e0301723, 28 p.","ipdsId":"IP-146418","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439287,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1371/journal.pone.0301723","text":"Publisher Index Page"},{"id":433632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Tongass National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.79598611853271,\n 35.785590501974994\n ],\n [\n -120.79598611853271,\n 35.758103908925094\n ],\n [\n -120.7544854283608,\n 35.758103908925094\n ],\n [\n -120.7544854283608,\n 35.785590501974994\n ],\n [\n -120.79598611853271,\n 35.785590501974994\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -136.02998750758678,\n 57.464783614185876\n ],\n [\n -136.02998750758678,\n 55.846134928392786\n ],\n [\n -133.47293766914498,\n 55.846134928392786\n ],\n [\n -133.47293766914498,\n 57.464783614185876\n ],\n [\n -136.02998750758678,\n 57.464783614185876\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Michael J. 0000-0002-5495-7049","orcid":"https://orcid.org/0000-0002-5495-7049","contributorId":304258,"corporation":false,"usgs":true,"family":"Moore","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910552,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flitcroft, R.","contributorId":342974,"corporation":false,"usgs":false,"family":"Flitcroft","given":"R.","email":"","affiliations":[{"id":81962,"text":"Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":910553,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tucker, E.","contributorId":342975,"corporation":false,"usgs":false,"family":"Tucker","given":"E.","email":"","affiliations":[{"id":81965,"text":"Tongass National Forest","active":true,"usgs":false}],"preferred":false,"id":910554,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prussian, K. K.","contributorId":204860,"corporation":false,"usgs":false,"family":"Prussian","given":"K.","email":"","middleInitial":"K.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":910555,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Claeson, S. M.","contributorId":342976,"corporation":false,"usgs":false,"family":"Claeson","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":81962,"text":"Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":910556,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}