Rabies is an ancient disease that is responsible for approximately 59,000 human deaths annually. Bats (Order Chiroptera) are thought to be the original hosts of rabies virus (RABV) and currently account for most rabies cases in wildlife in the Americas. Vaccination is being used to manage rabies in other wildlife reservoirs like fox and raccoon, but no rabies vaccine is available for bats. We previously developed a recombinant raccoonpox virus (RCN) vaccine candidate expressing a mosaic glycoprotein (MoG) gene that protected mice and big brown bats when challenged with RABV. In this study, we developed two new recombinant RCN candidates expressing MoG (RCN-tPA-MoG and RCN-SS-TD-MoG) with the aim of improving RCN-MoG. We assessed and compared in vitro expression, in vivo immunogenicity, and protective efficacy in vaccinated mice challenged intracerebrally with RABV. All three candidates induced significant humoral immune responses, and inoculation with RCN-tPA-MoG or RCN-MoG significantly increased survival after RABV challenge. These results demonstrate the importance of considering molecular elements in the design of vaccines, and that vaccination with either RCN-tPA-MoG or RCN-MoG confers adequate protection from rabies infection, and either may be a sufficient vaccine candidate for bats in future work.
","language":"English","publisher":"MDPI","doi":"10.3390/vaccines9121436","usgsCitation":"Malave, C.M., Lopera-Madrid, J., Medina-Magues, L.G., Rocke, T.E., and Osorio, J., 2021, Impact of molecular modifications on the Immunogenicity and efficacy of recombinant raccoon poxvirus-vectored rabies vaccine candidates in mice: Vaccines, v. 9, no. 12, 1436, 12 p., https://doi.org/10.3390/vaccines9121436.","productDescription":"1436, 12 p.","ipdsId":"IP-134515","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":450089,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/vaccines9121436","text":"Publisher Index Page"},{"id":436104,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IERY9D","text":"USGS data release","linkHelpText":"In vitro expression, immunogenicity, and efficacy data from recombinant raccoon poxvirus-vectored rabies vaccine candidates tested in mice"},{"id":392570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Malave, Carly Marie 0000-0001-6673-737X","orcid":"https://orcid.org/0000-0001-6673-737X","contributorId":269786,"corporation":false,"usgs":true,"family":"Malave","given":"Carly","email":"","middleInitial":"Marie","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":827916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopera-Madrid, Jaime","contributorId":215116,"corporation":false,"usgs":false,"family":"Lopera-Madrid","given":"Jaime","email":"","affiliations":[],"preferred":false,"id":827917,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Medina-Magues, Lex Guillermo","contributorId":269787,"corporation":false,"usgs":false,"family":"Medina-Magues","given":"Lex","email":"","middleInitial":"Guillermo","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":827918,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":827919,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osorio, Jorge E.","contributorId":50392,"corporation":false,"usgs":false,"family":"Osorio","given":"Jorge E.","affiliations":[{"id":13052,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":827920,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226731,"text":"70226731 - 2021 - Reproductive health and endocrine disruption in smallmouth bass (Micropterus dolomieu) from the Lake Erie drainage, Pennsylvania, USA","interactions":[],"lastModifiedDate":"2021-12-08T12:55:37.263109","indexId":"70226731","displayToPublicDate":"2021-12-04T06:51:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Reproductive health and endocrine disruption in smallmouth bass (Micropterus dolomieu) from the Lake Erie drainage, Pennsylvania, USA","docAbstract":"Smallmouth bass Micropterus dolomieu were sampled from three sites within the Lake Erie drainage (Elk Creek, Twentymile Creek, and Misery Bay, an embayment in Presque Isle Bay). Plasma, tissues for histopathological analyses, and liver and testes preserved in RNALater® were sampled from 30 smallmouth bass (of both sexes) at each site. Liver and testes samples were analyzed for transcript abundance with Nanostring nCounter® technology. Evidence of estrogenic endocrine disruption was assessed by the presence and severity of intersex (testicular oocytes; TO) and concentrations of plasma vitellogenin in male fish. Abundance of 17 liver transcripts associated with reproductive function, endocrine activity, and contaminant detoxification pathways and 40 testes transcripts associated with male and female reproductive function, germ cell development, and steroid biosynthesis were also measured. Males with a high rate of TO (87–100%) and plasma vitellogenin were noted at all sites; however, TO severity was greatest at the site with the highest agricultural land cover. Numerous transcripts were differentially regulated among the sites and patterns of transcript abundance were used to better understand potential risk factors for estrogenic endocrine disruption. The results of this study suggest endocrine disruption is prevalent in this region and further research would benefit to identify the types of contaminants that may be associated with the observed biological effects.
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 13.4 billion barrels of oil and 244.4 trillion cubic feet of gas in nine geologic provinces of China.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213051","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Ellis, G.S., Finn, T.M., Le, P.A., Marra, K.R., Leathers-Miller, H.M., and Drake, R.M., II, 2021, Assessment of undiscovered conventional oil and gas resources of China, 2020: U.S. Geological Survey Fact Sheet 2021–3051, 4 p., https://doi.org/10.3133/fs20213051.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-124554","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":392447,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SOH5EN","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-China Assessment Unit Boundaries and Assessment Input Forms"},{"id":392446,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3051/fs20213051.pdf","text":"Report","size":"1.10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021-3051"},{"id":392445,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3051/coverthb.jpg"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 69.9609375,\n 41.77131167976407\n ],\n [\n 77.34374999999999,\n 26.745610382199022\n ],\n [\n 101.953125,\n 19.642587534013032\n ],\n [\n 112.8515625,\n 18.646245142670608\n ],\n [\n 121.28906250000001,\n 20.632784250388028\n ],\n [\n 136.40625,\n 42.293564192170095\n ],\n [\n 136.7578125,\n 54.57206165565852\n ],\n [\n 119.17968749999999,\n 54.77534585936447\n ],\n [\n 106.5234375,\n 46.800059446787316\n ],\n [\n 76.640625,\n 47.27922900257082\n ],\n [\n 69.9609375,\n 41.77131167976407\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Saltwater intrusion and declining water levels have been a water-supply problem in Cape May County, New Jersey, for decades. Cape May County is surrounded by saltwater on three sides. Several communities in the county have only one aquifer from which freshwater withdrawals can be made, and that sole source is threatened by saltwater intrusion and (or) substantial declines in water levels caused by groundwater withdrawals. Growth of the year-round and summer tourism populations have caused water demand for some purveyors to approach the full-allocation withdrawal rates set by the New Jersey Department of Environmental Protection, leading these purveyors to request increases in allocations. Simulated water levels resulting from withdrawals including proposed increases in allocations by four purveyors and a shift of some withdrawals from one aquifer to another by a fifth purveyor were compared to simulated baseline water levels with withdrawals at 2012 full-allocation rates.
The Lower Township Scenario simulates proposed full-allocation withdrawals of 1,079 million gallons per year (Mgal/yr) from the Cohansey aquifer, 211 Mgal/yr (24 percent) higher than the 2012 full allocation withdrawals. Lower Township Scenario simulated water levels are between 2 and 4 feet (ft) lower than those of the shallow-aquifer-system Baseline Scenario simulation in much of Lower Township. The simulated 250-milligrams per liter (mg/L) isochlor is a maximum of 750 ft farther eastward than the simulated position in the shallow-aquifer-system Baseline Scenario, and the isochlor is simulated to be 700 ft from the northwestern-most Lower Township Municipal Utility Authority well at the airport in 2050.
The Wildwood Scenario simulates proposed full-allocation withdrawals of 388 Mgal/yr at the Wildwood Water Utility Rio Grande well field in Middle Township from the Rio Grande water-bearing zone (upper Kirkwood Formation) and 776 Mgal/yr from the Atlantic City 800-foot sand (lower Kirkwood Formation). Simulated water levels in the Atlantic City 800-foot sand near the well field are 30–55 ft lower than in the deep-aquifer-system Baseline Scenario, more than 15 ft lower south and west of Cape May Court House, and 5–10 ft lower between Cape May Court House and Woodbine and Upper Township.
The Avalon Scenario simulates proposed full-allocation withdrawals from the Atlantic City 800-foot sand in Avalon Borough of 495 Mgal/yr, which is 141 Mgal/yr (40 percent) higher than the 2012 full-allocation withdrawals. The Cape May Court House Scenario simulates proposed full-allocation withdrawals near Cape May Court House from the Atlantic City 800-foot sand of 495 Mgal/yr, which is 150 Mgal/yr (64 percent) higher than 2012 full-allocation withdrawals. The Strathmere Scenario simulates proposed full-allocation withdrawals in Strathmere from the Atlantic City 800-foot sand of 30 Mgal/yr, which is 11 Mgal/yr (58 percent) higher than 2012 full-allocation withdrawals. All three of these scenarios generally show simulated water levels to be less than 10 ft lower compared to the deep-aquifer-system Baseline Scenario.
The Combined Scenario simulates proposed full-allocation withdrawals, including increased withdrawals from the Atlantic City 800-foot sand in all four locations—the Rio Grande well field, Avalon, Cape May Court House, and Strathmere. Water levels from the Combined Scenario are 40–65 ft lower than those from the deep-aquifer-system Baseline Scenario near the Wildwood Water Utility Rio Grande well field, 15–40 ft lower south of Dennis Township, and 5–15 ft lower in much of the rest of Cape May County.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205052","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Carleton, G.B., 2021, Simulation of potential water allocation changes, Cape May County, New Jersey: U.S. Geological Survey Scientific Investigations Report 2020–5052, 39 p., https://doi.org/10.3133/sir20205052.","productDescription":"Report: vi, 39 p.; Data Release","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044323","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":392461,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20205052/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":392262,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5052/sir20205052.XML"},{"id":392260,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KC1PGV","text":"USGS data release","linkHelpText":"SEAWAT, MODFLOW-2000, and SHARP models used to simulate potential water-allocation changes, Cape May County, New Jersey"},{"id":392261,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5052/images/"},{"id":392259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5052/sir20205052.pdf","text":"Report","size":"4.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5052"},{"id":392258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5052/coverthb.jpg"}],"country":"United States","state":"New Jersey","county":"Cape May County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.99404907226562,\n 38.92843409820933\n ],\n [\n -74.91439819335938,\n 38.91133881927712\n ],\n [\n -74.82376098632812,\n 38.92629741358616\n ],\n [\n -74.77844238281249,\n 38.9807627650163\n ],\n [\n -74.74925994873047,\n 39.041319605445445\n ],\n [\n -74.95010375976561,\n 39.0882354732187\n ],\n [\n -74.99404907226562,\n 38.92843409820933\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The gut microbiota may modulate the disposition and toxicity of environmental contaminants within a host but, conversely, contaminants may also impact gut bacteria. Such contaminant-gut microbial connections, which could lead to alteration of host health, remain poorly known and are rarely studied in free-ranging wildlife. The polar bear (Ursus maritimus) is a long-lived, wide-ranging apex predator that feeds on a variety of high trophic position seal and cetacean species and, as such, is exposed to among the highest levels of biomagnifying contaminants of all Arctic species. Here, we investigate associations between mercury (THg; a key Arctic contaminant), diet, and the diversity and composition of the gut microbiota of polar bears inhabiting the southern Beaufort Sea, while accounting for host sex, age class and body condition. Bacterial diversity was negatively associated with seal consumption and mercury, a pattern seen for both Shannon and Inverse Simpson alpha diversity indices (adjusted R2 = 0.35, F1,18 = 8.00, P = 0.013 and adjusted R2 = 0.26, F1,18 = 6.04, P = 0.027, respectively). No association was found with sex, age class or body condition of polar bears. Bacteria known to either be involved in THg methylation or considered to be highly contaminant resistant, including Lactobacillales, Bacillales and Aeromonadales, were significantly more abundant in individuals that had higher THg concentrations. Conversely, individuals with higher THg concentrations showed a significantly lower abundance of Bacteroidales, a bacterial order that typically plays an important role in supporting host immune function by stimulating intraepithelial lymphocytes within the epithelial barrier. These associations between diet-acquired mercury and microbiota illustrate a potentially overlooked outcome of mercury accumulation in polar bears.
This article reviews the status of knowledge gaps and co-production process challenges that impede coastal flood hazard resilience planning in communities of northwestern Alaska, where threat levels are high. Discussion focuses on the state of knowledge arising after preparation of the 2019 IPCC Special Report on the Ocean and Cryosphere in a Changing Climate and highlights prospects to address urgent needs. The intent is to identify some key steps necessary to advance the integration of relevant multidisciplinary observations with flood modeling and infrastructure mapping to co-produce new online hazard and risk assessment tools that inform local community planning and improve science collaboration among Federal, state, and regional partners for enhanced pre-storm preparations and post-storm recovery, including partial or complete relocation. By focusing coastal data integration for delivery of priority geospatial hazard map products through a consistent yet customized approach to adaptation planning, the broad collaborative effort in Alaska may yield a path of stakeholder service delivery that can be applied to many Arctic communities and other vulnerable regions of the world.
From October 1, 1999, through September 30, 2009, water-quality samples were collected, and discharge was measured at 13 streamgages within the Catskill and Delaware watersheds of the New York City water supply system. The Catskill and Delaware watersheds supply about 90 percent of the water needed by 9 million customers. On average, 59 water-quality samples were collected at each station during each year of the study and analyzed for major ions and nutrients. At six stations, suspended-sediment samples were collected during 2001–09, and turbidity samples were collected during 2003–09. Surficial geology exerted a strong influence on the water quality of streams in the region. Stations in the Cannonsville Reservoir watershed, which has a high percentage of glacial till, had circumneutral stream water, whereas stations in the Neversink Reservoir watershed, which has a high percentage of sedimentary bedrock outcrops, had acidic stream water. All stations showed significant decreases in stream water sulfate concentrations during the study period; however, only the most acidic watersheds showed decreases in hydrogen-ion concentration. Two of the most acidic stations, East Branch Neversink River northeast of Denning and Rondout Creek above Red Brook at Peekamoose also had significant decreasing trends in inorganic monomeric aluminum concentrations, a form of aluminum that is toxic to some aquatic biota at concentrations greater than 0.05 milligram per liter. Three stations in the Neversink Reservoir watershed had inorganic monomeric aluminum concentrations that commonly exceeded 0.05 milligram per liter during the study period. At the West Branch Neversink River at Winnisook Lake near Frost Valley station concentrations of inorganic monomeric aluminum exceeded 0.3 milligram per liter at the beginning of the study, but never exceeded that level during the last 2 water years of the study. The East Branch Neversink River northeast of Denning and Rondout Creek above Red Brook at Peekamoose stations also showed decreases in inorganic monomeric aluminum concentrations during the study. The reduction in inorganic monomeric aluminum concentrations were the result of reductions in stream acidity. The reductions in stream acidity were driven by reductions in sulfate concentrations in precipitation in response to emission regulations included in title IV of the Clean Air Act Amendments of 1990 (42 USC §7651).
Results indicated increasing trends in sodium and chloride concentrations for all stations with high road density relative to other stations included in the study, which could be a future water-quality concern in the region. The Town Brook watershed southeast of Hobart, the only study watershed that contained dairy farms, had a significant decreasing trend in total dissolved phosphorus concentration that may have been a result of agricultural best management practices implemented on farms by the Watershed Agricultural Program. The watershed with the second highest total phosphorus and total dissolved phosphorus concentrations was a completely forested, but previously agricultural, watershed (Town Brook tributary southeast of Hobart) that had not been actively farmed in about 80 years. The phosphorus concentrations at the Town Brook tributary southeast of Hobart station indicated that previously agricultural watersheds may continue to leach phosphorus to streams for many decades after farming has ceased.
At six of the study watersheds, samples of suspended-sediment and turbidity were also collected. The watersheds with the highest suspended-sediment concentrations and turbidity also had the strongest relations between discharge and suspended-sediment concentrations. In general, the relations between discharge and turbidity were not as strong as the relations between discharge and suspended-sediment concentrations. Results indicated strong relations between suspended-sediment concentrations and turbidity levels at each station; however, relations were less strong in the agricultural watersheds. Suspended-sediment concentrations appeared to decrease at the Stony Clove Creek below Ox Clove at Chichester station following a stream stabilization project completed during the study period. However, we were unable to directly attribute the decrease to the stabilization project; there were many complicating variables that made a direct attribution difficult, such as a series of large storms shortly after the stabilization project was completed and differences in flow conditions before and after the project. However, the results have led to additional monitoring within the watershed specifically designed to determine the effectiveness of stream stabilization projects for reducing suspended-sediment concentrations and turbidity in the upper Esopus Creek watershed, the primary source of water to the Ashokan Reservoir. Water quality in the Catskill and Delaware watersheds is generally improving, and although sodium and chloride concentrations increased at some of the stations from 1999 to 2009, the concentrations in 2009 were still well below U.S. Environmental Protection Agency drinking water standards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205049","collaboration":"Prepared in cooperation with New York City Department of Environmental Protection and the U.S. Environmental Protection Agency","usgsCitation":"McHale, M.R., Siemion, J., and Murdoch, P.S., 2021, The water quality of selected streams in the Catskill and Delaware water-supply watersheds in New York, 1999–2009: U.S. Geological Survey Scientific Investigations Report 2020–5049, 48 p., https://doi.org/10.3133/sir20205049.","productDescription":"viii, 48 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060224","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":392036,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20205049/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":391750,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5049/sir20205049.XML"},{"id":391749,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5049/images/"},{"id":391748,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5049/sir20205049.pdf","text":"Report","size":"6.70 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5049"},{"id":391747,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5049/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Catskill Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.16845703125001,\n 41.672911819602085\n ],\n [\n -73.93798828125,\n 41.672911819602085\n ],\n [\n -73.93798828125,\n 42.43156587257916\n ],\n [\n -75.16845703125001,\n 42.43156587257916\n ],\n [\n -75.16845703125001,\n 41.672911819602085\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Responsible stewardship of native fish populations and riparian plants in the Meduxnekeag River watershed in northeastern Maine is a high priority for the Houlton Band of Maliseet Indians. Understanding the potential changes in hydrology and water temperature as a result of climate change is important to this priority for evaluating future habitat conditions in the watershed. This report, prepared in cooperation with the Houlton Band of Maliseet Indians, documents and presents the results of a model using the Precipitation-Runoff Modeling System (PRMS), a hydrologic model designed to provide streamflow and water temperature simulations under predicted changes in precipitation and air temperature during the next century.
To estimate streamflows and water temperature in the Meduxnekeag River watershed, a PRMS model was developed and calibrated. By using the calibrated PRMS model, simulations were made for projected scenarios of 0, 5, 10, and 15 percent increases in precipitation and for increases in air temperature of 0.0, 3.6, 7.0, and 10.4 degrees Fahrenheit (°F). The increases in precipitation and temperature were applied to all the daily input values uniformly. These scenarios were based upon the results from 30 climate change models summarized in the National Climate Change Viewer. Streamflows and water temperatures modeled for different climate scenarios were compared with streamflows and water temperatures modeled with unadjusted climate inputs.
Overall, streamflow increased with increasing precipitation and decreased with increasing air temperature. Water temperature increased with increasing air temperature. At the outlet of the studied Meduxnekeag River watershed, with both a 15 percent increase in precipitation and a 10.4 °F increase in air temperature, the mean annual streamflow increased by 17 percent from 489 cubic feet per second (ft3/s) to 572 ft3/s, and the mean annual maximum streamflow decreased by 8.3 percent from 3,870 ft3/s to 3,550 ft3/s. At the same location and under the same scenario, the mean annual water temperature increased by 17.5 percent from 47.4 °F to 55.7 °F.
Significant changes in mean monthly streamflows were found with increasing air temperature. The PRMS model results showed that when air temperature was increased, there was an increase in mean monthly streamflow during the winter months and a decrease in mean monthly streamflow during the spring months. In addition, with a 10.4 °F increase in the air temperature, the month with the greatest monthly streamflow changed from April to December. In addition, the PRMS model estimated that the mean annual maximum snowpack in snow water equivalent for the watershed would decrease from 7.67 inches to 1.26 inches, and the mean annual date of the maximum snowpack would change from March 21 to January 28 with a 15 percent increase in precipitation and a 10.4 °F increase in air temperature.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215104","collaboration":"Prepared in cooperation with the Houlton Band of Maliseet Indians","usgsCitation":"Bjerklie, D.M., and Olson, S.A., 2021, Simulating the effects of climate-related changes to air temperature and precipitation on streamflow and water temperature in the Meduxnekeag River watershed, Maine: U.S. Geological Survey Scientific Investigations Report 2021–5104, 35 p., https://doi.org/10.3133/sir20215104.","productDescription":"Report: vi, 35 p.; Data Release","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123224","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":392380,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215104/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":392032,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5104/sir20215104.XML"},{"id":392030,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EB4H6H","text":"USGS data release","linkHelpText":"Data for simulating the effects of air temperature and precipitation changes on streamflow and water temperature in the Meduxnekeag River watershed, Maine"},{"id":392029,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5104/sir20215104.pdf","text":"Report","size":"20.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5104"},{"id":392031,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5104/images/"},{"id":392028,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5104/coverthb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Meduxnekeag River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.302001953125,\n 45.92154267288144\n ],\n [\n -67.78289794921875,\n 45.92154267288144\n ],\n [\n -67.78289794921875,\n 46.26913887119721\n ],\n [\n -68.302001953125,\n 46.26913887119721\n ],\n [\n -68.302001953125,\n 45.92154267288144\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
No abstract available.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Loope, K., DeSha, J.N., Lawson, G., and Hunter, E.A., 2021, Gopherus polyphemus (Gopher Tortoise). Twinning: Herpetological Review, v. 52, no. 4, p. 846-847.","productDescription":"2 p.","startPage":"846","endPage":"847","ipdsId":"IP-132345","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480718,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ssarherps.org/herpetological-review-pdfs/","linkFileType":{"id":5,"text":"html"}},{"id":482518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Loope, Kevin J.","contributorId":288536,"corporation":false,"usgs":false,"family":"Loope","given":"Kevin J.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":924336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeSha, J. Nicole","contributorId":343344,"corporation":false,"usgs":false,"family":"DeSha","given":"J.","email":"","middleInitial":"Nicole","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":924337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawson, Garrett R.","contributorId":349495,"corporation":false,"usgs":false,"family":"Lawson","given":"Garrett R.","affiliations":[{"id":7113,"text":"private citizen","active":true,"usgs":false}],"preferred":false,"id":924338,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924335,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226652,"text":"sir20215133 - 2021 - Streambed scour of salmon (Oncorhynchus spp.) redds in the Sauk River, Northwestern Washington","interactions":[],"lastModifiedDate":"2021-12-03T00:21:45.583067","indexId":"sir20215133","displayToPublicDate":"2021-12-01T16:17:54","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5133","displayTitle":"Streambed Scour of Salmon (Oncorhynchus spp.) Redds in the Sauk River, Northwestern Washington","title":"Streambed scour of salmon (Oncorhynchus spp.) redds in the Sauk River, Northwestern Washington","docAbstract":"The autumn and winter flood season of western Washington coincides with the incubation period of many Pacific salmon (Onchorhynchus spp.) populations. During this period, salmon embryos incubating within gravel nests called “redds” are vulnerable to mobilization of surrounding sediment during floods. As overlying sediment is transported downstream, the vertical position of the streambed can be lowered, a process termed streambed scour; thus developing salmon embryos may be destroyed resulting in decreasing egg-to-fry survival rates. The Sauk River, which drains a 1,900 km2 (733.5 mi2) area of the central Cascade Range of Washington State, provides spawning and rearing habitat for several species of Pacific salmon including Chinook salmon (O. tshawytscha), which were listed as threatened under the Endangered Species Act (ESA) in 1999. In order to assess the hydrologic conditions when streambed scour and concomitant geomorphic changes occur, accelerometer scour monitors (ASMs), which record the time when streambed scour lowers the streambed to the level of salmon egg pockets, were deployed in two geomorphically different reaches of the Sauk River to monitor scour during water year 2018. Nineteen ASMs were deployed in an upstream reach, which was largely confined by valley walls with vegetated, stable banks and low channel-migration rates near the confluence of the Sauk and White Chuck Rivers. Twelve additional ASMs were deployed in a downstream reach within an unconfined valley with unvegetated, unstable banks and high channel-migration rates between the town of Darrington and the confluence of the Sauk and Suiattle Rivers. During the ASM deployment, discharge measured at the U.S. Geological Survey (USGS) streamgage Sauk River above White Chuck River, near Darrington, Washington (12186000), peaked at 479 m3/s (16,900 ft3/s) with an estimated 0.18 probability of annual exceedance (5.7-year recurrence interval). During the flood season, large-scale geomorphic changes, including channel migration and bar deposition, were measured at the downstream reach, but only minimal geomorphic changes were measured at the upstream reach. ASMs deployed at the downstream reach were not recovered after the flood season and total scour depth was presumed to have exceeded ASM anchor depth. At the upstream reach, 7 of the 19 deployed ASMs were recovered after the flood season and all recovered ASMs recorded scour at discharges that equaled or exceeded 204 m3/s (7,210 ft3/s). The remaining 12 ASMs deployed at the upstream reach were not recovered and total scour depth was presumed to have exceeded ASM anchor depth. Collectively, this analysis enhances the ability of fisheries managers to forecast egg-to-fry survival rates of salmonids by determining the hydrologic conditions at which scour at the level of salmon redds initiates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215133","collaboration":"Prepared in cooperation with the Sauk-Suiattle Indian Tribe","usgsCitation":"Gendaszek, A.S., 2021, Streambed scour of salmon (Oncorhynchus spp.) redds in the Sauk River, Northwestern Washington: U.S. Geological Survey Scientific Investigations Report 2021–5133, 19 p., https://doi.org/10.3133/sir20215133.","productDescription":"Report: iv, 19 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-124695","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":392362,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95KOMTC","text":"USGS data release","description":"USGS data release.","linkHelpText":"Accelerometer scour monitor data on the Sauk River, Washington, Water Year 2018"},{"id":392360,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5133/coverthb.jpg"},{"id":392361,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5133/sir20215133.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5133"}],"country":"United States","state":"Washington","otherGeospatial":"Sauk River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.80816650390625,\n 48.31060120649363\n ],\n [\n -121.36871337890625,\n 48.31060120649363\n ],\n [\n -121.36871337890625,\n 48.6927734325279\n ],\n [\n -121.80816650390625,\n 48.6927734325279\n ],\n [\n -121.80816650390625,\n 48.31060120649363\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
This study addresses the characteristics, potential hazards, and both eruptive and non-eruptive role of water at selected volcanic crater lakes in Alaska. Crater lakes are an important feature of some stratovolcanoes in Alaska. Of the volcanoes in the state with known Holocene eruptive activity, about one third have summit crater lakes. Also included are two volcanoes with small caldera lakes (Katmai, Kaguyak). The lakes play an important but not well studied role in influencing eruptive behavior and pose some significant hydrologic hazards. Floods from crater lakes in Alaska are evaluated by estimating maximum potential crater lake water volumes and peak outflow discharge with a dam-break model. Some recent eruptions and hydrologic events that involved crater lakes also are reviewed. The large volumes of water potentially hosted by crater lakes in Alaska indicate that significant flowage hazards resulting from catastrophic breaching of crater rims are possible. Estimates of maximum peak flood discharge associated with breaching of lake-filled craters derived from dam-break modeling indicate that flood magnitudes could be as large as 103–106 m3/s if summit crater lakes drain rapidly when at maximum volume. Many of the Alaska crater lakes discussed are situated in hydrothermally altered craters characterized by complex assemblages of stratified unconsolidated volcaniclastic deposits, in a region known for large magnitude (>M7) earthquakes. Although there are only a few historical examples of eruptions involving crater lakes in Alaska, these provide noteworthy examples of the role of external water in cooling pyroclastic deposits, acidic crater-lake drainage, and water-related hazards such as lahars and base surge.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2021.751216","usgsCitation":"Waythomas, C.F., 2021, Selected crater and small caldera lakes in Alaska: Characteristics and hazards: Frontiers in Earth Science, v. 9, 751216, 23 p., https://doi.org/10.3389/feart.2021.751216.","productDescription":"751216, 23 p.","ipdsId":"IP-132664","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467219,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2021.751216","text":"Publisher Index Page"},{"id":463360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -142.4292614840023,\n 61.7867815706897\n ],\n [\n -179,\n 61.7867815706897\n ],\n [\n -179,\n 49.606118935666444\n ],\n [\n -144.99994877731635,\n 56.83072738947416\n ],\n [\n -142.4292614840023,\n 61.7867815706897\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2022-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917093,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70226845,"text":"70226845 - 2021 - A characterization of deep-sea coral and sponge communities along the California and Oregon coast using a remotely operated vehicle on the EXPRESS 2018 expedition","interactions":[],"lastModifiedDate":"2022-01-20T17:47:27.706118","indexId":"70226845","displayToPublicDate":"2021-12-01T11:47:06","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5134,"text":"NOAA Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"NMFS-SWFSC 657","title":"A characterization of deep-sea coral and sponge communities along the California and Oregon coast using a remotely operated vehicle on the EXPRESS 2018 expedition","docAbstract":"Deep-sea coral and sponge (DSCS) communities serve as essential fish habitats (EFH) by providing shelter and nursery habitat, increasing diversity, and increasing prey availability (Freese and Wing, 2003; Bright, 2007; Baillon et al., 2012; Henderson et al., 2020). Threats to these long-lived, fragile organisms from bottom contact fishing gear, potential offshore renewable energy development, and ocean warming and acidification have increased the need for DSCS research along the U.S. West Coast (Gomez et al., 2018; Salgado et al., 2018; Yoklavich, et al., 2018; Gugliotti et al., 2019). The focus of these studies has varied from species distribution and abundance (Yoklavich and Love, 2005; Tissot et al., 2006) to developing and validating predictive distribution models (Huff et al., 2013; Rooper et al., 2017; Kreidler, 2020) to finding medicinal uses for corals and sponges (Essack et al., 2011; Shrestha et al., 2018). Due to the vast area of unexplored seafloor within the U.S. exclusive economic zone (EEZ; 200 nautical miles off the coast) and the technological requirements and expanse of deep-sea research, there is still much to learn about the distributions and biology of DSCS. This information is critical to resource managers for effective conservation and management of DSCS habitats. Protections are provided by the Pacific Fishery Management Council (PFMC) designation of groundfish EFH conservation areas (EFHCA) and the National Marine Sanctuaries Act (NMSA). Areas designated as EFHCA are closed to bottom trawl fishing to protect and preserve seafloor habitats. Recently the PFMC adopted Amendment 28 to the Groundfish Fishery Management Plan (GFMP; Pacific Fishery Management Council, 2019) which modified EFHCAs by closing new areas identified as vulnerable and reopening areas deemed not vulnerable. The NMSA prohibits bottom disturbance from certain activities within areas designated as national marine sanctuaries, such as oil and gas exploration or extraction, cable laying, and other forms of seabed alteration or construction that disturb benthic communities. \n\nNOAA’s Deep-Sea Coral and Research Technology Program (DSCRTP) began a 4-yr funding initiative for the U.S. West Coast in 2017. The goals of the West Coast Deep-Sea Coral Initiative (WCDSCI) were to: 1) gather baseline information on areas subject to fishing regulation changes prior to the implementation of Amendment 28; 2) improve our understanding of known DSCS bycatch “hot spots”; and 3) explore and assess DSCS resources within NOAA National Marine Sanctuaries with emphasis on areas of sanctuary resource protection and management concerns. During the first year of the program, a research cruise was developed to survey the West Coast from Oregon to California studying the DSCS ecosystems in priority areas. The 31-day expedition (9 Oct – 8 Nov, 2018) was launched from the NOAA Ship Bell M. Shimada, beginning in Newport, OR and ending in San Diego, CA. \n\nThe science team assembled for this cruise were members of the EXpanding Pacific Research and Exploration of Submerged Systems (EXPRESS) campaign, which brings together researchers from federal and nonfederal institutions to collaborate on scientific expeditions targeting the deepwater areas off California, Oregon, and Washington. EXPRESS supports researchers leveraging funding, resources, personnel, and expertise to accomplish more science than would have been possible by a single entity alone. The 2018 coastwide expedition included research partners from National Marine Fisheries Service (NMFS) Southwest Fisheries Science Center (SWFSC) and Northwest Fisheries Science Center (NWFSC), National Ocean Service (Channel Islands, Cordell Bank, Greater Farallones, and Monterey Bay National Marine Sanctuaries), Bureau of Ocean Energy Management (BOEM), U.S. Geological Survey (USGS), and Monterey Bay Aquarium Research Institute (MBARI). \n\nResearch objectives for the cruise were to:\n\n1) Collect DSCS baseline information at 10 of the EFHCA sites undergoing protection modifications by the Pacific Fishery Management Council.\n\n2) Collect DSCS and fish data at previously unexplored sites within West Coast National Marine Sanctuaries.\n\n3) Revisit a subset of previously surveyed sites to document if changes in DCSC have occurred over time.\n\n4) Collect information to validate BOEM supported cross-shelf habitat suitability models for DSCS.\n\n5) Collect samples to help in identifying (and understanding) West Coast DSCS and expand use of new technologies (ROV, AUV, and environmental DNA [eDNA]).\n\n6) Collect water samples for coastwide eDNA, nutrient, and carbon chemistry studies.","language":"English","publisher":"NOAA","doi":"10.25923/sd6f-j739","usgsCitation":"Laidig, T., Watters, D., Prouty, N.G., Everett, M., Duncan, L., Clarke, L., Caldow, C., and Demopoulos, A., 2021, A characterization of deep-sea coral and sponge communities along the California and Oregon coast using a remotely operated vehicle on the EXPRESS 2018 expedition: NOAA Technical Memorandum NMFS-SWFSC 657, 122 p., https://doi.org/10.25923/sd6f-j739.","productDescription":"122 p.","ipdsId":"IP-134460","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":394597,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.01318359375001,\n 34.288991865037524\n ],\n [\n -120.498046875,\n 34.288991865037524\n ],\n [\n -120.498046875,\n 46.08847179577592\n ],\n [\n -126.01318359375001,\n 46.08847179577592\n ],\n [\n -126.01318359375001,\n 34.288991865037524\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Laidig, Tom","contributorId":270131,"corporation":false,"usgs":false,"family":"Laidig","given":"Tom","email":"","affiliations":[{"id":56090,"text":"NOAA Fisheries, SWFSC, Fisheries Ecology Division, Santa Cruz, CA","active":true,"usgs":false}],"preferred":false,"id":828462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watters, Diana","contributorId":270132,"corporation":false,"usgs":false,"family":"Watters","given":"Diana","email":"","affiliations":[{"id":56090,"text":"NOAA Fisheries, SWFSC, Fisheries Ecology Division, Santa Cruz, CA","active":true,"usgs":false}],"preferred":false,"id":828463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":828464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Everett, Meredith","contributorId":270133,"corporation":false,"usgs":false,"family":"Everett","given":"Meredith","email":"","affiliations":[{"id":56092,"text":"NOAA Fisheries, NWFSC, Seattle WA","active":true,"usgs":false}],"preferred":false,"id":828465,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duncan, Lizzie","contributorId":270134,"corporation":false,"usgs":false,"family":"Duncan","given":"Lizzie","email":"","affiliations":[{"id":56094,"text":"NOAA, NOS, Channel Islands National Marine Sanctuary, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":828466,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clarke, Liz","contributorId":270135,"corporation":false,"usgs":false,"family":"Clarke","given":"Liz","email":"","affiliations":[{"id":56092,"text":"NOAA Fisheries, NWFSC, Seattle WA","active":true,"usgs":false}],"preferred":false,"id":828467,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Caldow, Chris","contributorId":270136,"corporation":false,"usgs":false,"family":"Caldow","given":"Chris","affiliations":[{"id":56094,"text":"NOAA, NOS, Channel Islands National Marine Sanctuary, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":828468,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":222185,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":828469,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70225624,"text":"70225624 - 2021 - Invasive carp population modeling to support an adaptive management framework","interactions":[],"lastModifiedDate":"2024-03-21T16:31:40.616244","indexId":"70225624","displayToPublicDate":"2021-12-01T11:29:33","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":9543,"text":"Interim Summary Report","active":true,"publicationSubtype":{"id":3}},"title":"Invasive carp population modeling to support an adaptive management framework","docAbstract":"No abstract available.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Interim summary report: Invasive carp monitoring and response plan 2021","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Asian Carp Regional Coordinating Committee","usgsCitation":"Erickson, R.A., 2021, Invasive carp population modeling to support an adaptive management framework: Interim Summary Report, 4 p.","productDescription":"4 p.","startPage":"132","endPage":"135","ipdsId":"IP-129312","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":426839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391072,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://invasivecarp.us/PlansReports.html"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":825981,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70226621,"text":"ofr20211078 - 2021 - Quantification of metal loading using tracer dilution and instantaneous synoptic sampling and importance of diel cycling in Leavenworth Creek, Clear Creek County, Colorado, 2012","interactions":[],"lastModifiedDate":"2021-12-16T21:16:26.305379","indexId":"ofr20211078","displayToPublicDate":"2021-12-01T11:10:00","publicationYear":"2021","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":"2021-1078","displayTitle":"Quantification of Metal Loading Using Tracer Dilution and Instantaneous Synoptic Sampling and Importance of Diel Cycling in Leavenworth Creek, Clear Creek County, Colorado, 2012","title":"Quantification of metal loading using tracer dilution and instantaneous synoptic sampling and importance of diel cycling in Leavenworth Creek, Clear Creek County, Colorado, 2012","docAbstract":"Leavenworth Creek, a tributary of South Clear Creek and Clear Creek near Georgetown, Colorado, contains copper, lead, and zinc at concentrations close to or in excess of aquatic-life standards. In the summer of 2012, the U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Forest Service and the Colorado Division of Reclamation, Mining and Safety, conducted monitoring to (1) quantify the effects of diel cycling and perform synoptic sampling in a way to minimize those effects, (2) separate “point” or distinct single tributaries or sources of load from diffuse load sources along the study reach to aid remediation planning, and (3) quantify metal loading from transmountain diversion of water from Peru Creek through the Vidler Tunnel into Leavenworth Creek. The study included monitoring for diel cycles in June 2012 and diel and synoptic sampling in August 2012 along an approximately 2-kilometer stream reach. Synoptic samples were collected at 26 stream and 35 inflow, tributary, mine waste seep, and mine tunnel sites from August 28 to 30, 2012.
In June 2012, temperature, dissolved oxygen, and pH showed strong diel signals at two sites in Leavenworth Creek, with temperature and pH having minimum values near dawn and maximum values during the afternoon and dissolved oxygen having maximum values in the early morning and minimum values in late afternoon. Concentrations of zinc, cadmium, cobalt, manganese, and yttrium showed strong diel fluctuations at both sites with minimum concentrations during daytime and maximum concentrations during nighttime. Because of these diel cycles, all stream sites were sampled during synoptic sampling at 1200 hours on August 30, 2012. During synoptic sampling from August 28 to 30, 2012, zinc showed maximum concentrations at nighttime and minimum concentrations at midday and diel variation ranged from 26 to 33 percent.
Inflows from the Wilcox Tunnel and Waldorf seep area were the greatest source of zinc load to the stream (about 45 percent), and a left-bank inflow in the dispersed tailings area was the greatest source of lead (about 45 percent) and manganese (about 25 percent) loads to the stream, and a secondary source for zinc (about 40 percent). Copper load was almost equally divided (about 35 percent) between these two sources. Diffuse loading, likely from left-bank sources, was evident for copper, lead, manganese, and zinc in the stream reach from approximately 800 to 1,200 meters, and for copper, lead, and, to a lesser extent, manganese in the reach containing left-bank dispersed tailings (from approximately 1,300 to 1,800 meters). The load values reported herein are minimum estimates because the stream synoptic samples were collected at 1200 hours when positively charged elements, including copper, lead, manganese, and zinc, have minimum concentrations. Diel patterns measured for zinc during the synoptic sampling indicate maximum daily zinc loads were as much as 33 percent greater than those measured at 1200 hours on August 30, 2012.
Transmountain diversion of water through Vidler Tunnel negatively affects water quality in Leavenworth Creek as indicated by much greater metal loads and concentrations and a visually evident mixing zone where Vidler Tunnel water joins Leavenworth Creek when diversion is active compared to when it is not.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20211078","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Forest Service and the Colorado Division of Reclamation, Mining and Safety","usgsCitation":"Walton-Day, K., Runkel, R.L., Smith, C.D., and Kimball, B.A., 2021, Quantification of metal loading using tracer dilution and instantaneous synoptic sampling and importance of diel cycling in Leavenworth Creek, Clear Creek County, Colorado, 2012: U.S. Geological Survey Open-File Report 2021–1078, 37 p., https://doi.org/10.3133/ofr20211078.","productDescription":"Report: viii, 37 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-102543","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":392247,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGC2V4","text":"USGS data release","linkHelpText":"Stream discharge, sodium, bromide, and specific conductance data for stream and hyporheic zone samples affected by injection of sodium bromide tracer, Leavenworth Creek, Clear Creek County, Colorado, August 2012"},{"id":392246,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1078/ofr20211078.pdf","text":"Report","size":"5.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1078"},{"id":392245,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1078/coverthb.jpg"}],"country":"United States","state":"Colorado","county":"Clear Creek County","otherGeospatial":"Leavenworth Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.86219787597655,\n 39.595371402863655\n ],\n [\n -105.69602966308594,\n 39.595371402863655\n ],\n [\n -105.69602966308594,\n 39.71405356154611\n ],\n [\n -105.86219787597655,\n 39.71405356154611\n ],\n [\n -105.86219787597655,\n 39.595371402863655\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
The South Loup River in central Nebraska has been impaired by bacteria since at least 2004, which has resulted in the river not meeting its intended use as a recreational waterway. As part of a strategy for reducing the bacterial load in the river, the U.S. Geological Survey, in cooperation with the Lower Loup Natural Resources District, made continuous estimates of Escherichia coli (E. coli) and nutrient concentrations during seasonal monitoring at the South Loup River at Saint Michael, Nebraska, during 2017–18. Continuous turbidity data were collected from mid-April through October in 2017 and 2018 and were paired with 35 co-occurring discrete water samples that were analyzed for E. coli, nutrients, and suspended solids. Surrogate models relating the discrete concentrations to the continuous turbidity data were developed using ordinary-least-squares regression and were evaluated for model performance and uncertainty. Although the model assumptions were met for E. coli, the imprecision of the E. coli model was considerably higher than the other constituents, probably because of measurement imprecision and greater sensitivity to environmental factors. Once the models were developed, the turbidity data were used to predict continuous constituent concentrations and corresponding prediction intervals, which were made available online as part of the U.S. Geological Survey National Water Information System database. It is expected that results from these models will provide stakeholders with an understanding of constituent concentrations during the 2017–18 monitoring period and the results will also provide a good reference point for any future comparisons.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215120","collaboration":"Prepared in cooperation with the Lower Loup Natural Resources District","usgsCitation":"Rus, D.L., and Densmore, B.K., 2021, Continuous turbidity data used to compute constituent concentrations in the South Loup River, Nebraska, 2017–18: U.S. Geological Survey Scientific Investigations Report 2021–5120, 10 p., https://doi.org/10.3133/sir20215120.","productDescription":"Report: vi, 10 p.; 2 Datasets","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-127801","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":392236,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5120/coverthb.jpg"},{"id":392237,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5120/sir20215120.pdf","text":"Report","size":"1.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5120"},{"id":392238,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://www.waterqualitydata.us/","text":"National Water Quality Monitoring Council website and digital data","linkHelpText":"— Water quality portal"},{"id":392239,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Nebraska","otherGeospatial":"South Loup River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.667724609375,\n 40.93841495689795\n ],\n [\n -98.2177734375,\n 40.93841495689795\n ],\n [\n -98.2177734375,\n 42.02481360781777\n ],\n [\n -100.667724609375,\n 42.02481360781777\n ],\n [\n -100.667724609375,\n 40.93841495689795\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
No abstract available.
","language":"English","publisher":"The Denver Well Logging Society","usgsCitation":"Lagesse, J.H., 2021, The Denver Well Logging Society December 2021 Newsletter: From the VP - Technology: Denver Well Drilling Society Newsletter, no. December 2021, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-135539","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":394393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394392,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://dwls.spwla.org/2021-12-Newsletter.html"}],"issue":"December 2021","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lagesse, Jenny H. 0000-0002-3541-4751","orcid":"https://orcid.org/0000-0002-3541-4751","contributorId":248367,"corporation":false,"usgs":true,"family":"Lagesse","given":"Jenny","email":"","middleInitial":"H.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":830056,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70257015,"text":"70257015 - 2021 - Assessing cormorant populations and association with fish stocking in Texas","interactions":[],"lastModifiedDate":"2024-09-05T15:57:28.619342","indexId":"70257015","displayToPublicDate":"2021-12-01T10:54:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1137,"text":"Bulletin of the Texas Ornithological Society","active":true,"publicationSubtype":{"id":10}},"title":"Assessing cormorant populations and association with fish stocking in Texas","docAbstract":"—Double-Crested Cormorants (Nannopterum auritum) and Neotropic Cormorants (Nannopterum brasilianum) are thought to be expanding their populations across Texas. This expansion is cause for a concern for both fish stocking and fisheries management in public waters. To examine the historic and current populations and distributions of cormorants, we first evaluated the temporal and spatial patterns of cormorants in Texas. Also, because cormorants are thought to depredate public fisheries, we conducted a small observational field study to assess cormorant presence and behavior at lakes relative to fish stocking. We compiled Christmas Bird Count (CBC) data for both species over a period of fifty years (1970 to 2019). We assessed changes in detection rates at CBCs among years as evidence of population trends during the winter, and changes in distance from the Gulf Coast of CBCs reporting cormorants for evidence of changes in distribution. Our results suggest that winter populations of Double-Crested Cormorants are relatively stable, with no meaningful change in distribution. In contrast, Neotropic Cormorants appear to be both increasing in number and expanding their range. Our assessment of cormorant abundance and behavior at stocked and unstocked lakes from December through February revealed a significant difference in detections among the stocked lakes during pre- and post-stocking but no significant difference among the control lakes.
","language":"English","publisher":"Texas Ornithological Society","usgsCitation":"Morris, S.A., Boal, C.W., and Patino, R., 2021, Assessing cormorant populations and association with fish stocking in Texas: Bulletin of the Texas Ornithological Society, v. 54, no. 1-2, p. 1-8.","productDescription":"8 p.","startPage":"1","endPage":"8","ipdsId":"IP-135215","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432308,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://texasbirds.org/publications/bulletin-of-the-texas-ornithological-society/"},{"id":433509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"54","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Morris, Sophie A.","contributorId":341918,"corporation":false,"usgs":false,"family":"Morris","given":"Sophie","email":"","middleInitial":"A.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":909160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":909159,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patino, Reynaldo 0000-0002-4831-8400 r.patino@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-8400","contributorId":2311,"corporation":false,"usgs":true,"family":"Patino","given":"Reynaldo","email":"r.patino@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":909161,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70226877,"text":"70226877 - 2021 - Data-driven prospectivity modelling of sediment-hosted mineral systems","interactions":[],"lastModifiedDate":"2025-06-18T15:48:21.907004","indexId":"70226877","displayToPublicDate":"2021-12-01T10:42:21","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Data-driven prospectivity modelling of sediment-hosted mineral systems","docAbstract":"Mississippi Valley-type (MVT) and clastic-dominated (CD) deposits are important sources for Zn, Pb, Ag, and Cd as well as the critical elements Ga, Ge, In, and Sb. However, mapping the drivers, sources, pathways, and traps of MVT and CD deposits within the much larger and mostly unmineralized sedimentary basins remain some of the least understood aspects of these mineral systems. Herein we address those knowledge gaps by integrating public geoscience datasets from Canada, the United States of America, and Australia using a discrete global grid system to map the continent-scale footprints of MVT and CD deposits.","conferenceTitle":"Mineral Prospectivity and Exploration Targeting – MinProXT 2021 Webinar","conferenceDate":"October 12-13 & 26-27, 2021","language":"English","publisher":"Geological Survey of Finland","collaboration":"Geological Survey of Canada and Geoscience Australia","usgsCitation":"Lawley, C.J., McCafferty, A.E., Graham, G.E., Gadd, M.G., Huston, D.L., Kelley, K.D., Czarnota, K., Paradis, S., Peter, J.M., Hayward, N., Barlow, M., Emsbo, P., Coyan, J.A., and San Juan, C.A., 2021, Data-driven prospectivity modelling of sediment-hosted mineral systems, Mineral Prospectivity and Exploration Targeting – MinProXT 2021 Webinar, October 12-13 & 26-27, 2021, p. 67-70.","productDescription":"4 p.","startPage":"67","endPage":"70","ipdsId":"IP-131337","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":490924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":490923,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.gtk.fi/en/minproxt-2021-webinar/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationDate":"2021-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Lawley, Christopher J.M. 0000-0001-6877-0675","orcid":"https://orcid.org/0000-0001-6877-0675","contributorId":328598,"corporation":false,"usgs":false,"family":"Lawley","given":"Christopher","email":"","middleInitial":"J.M.","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":828577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCafferty, Anne E. 0000-0001-5574-9201 anne@usgs.gov","orcid":"https://orcid.org/0000-0001-5574-9201","contributorId":1120,"corporation":false,"usgs":true,"family":"McCafferty","given":"Anne","email":"anne@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":828578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":828579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gadd, Michael G.","contributorId":270171,"corporation":false,"usgs":false,"family":"Gadd","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":828580,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huston, David L.","contributorId":67139,"corporation":false,"usgs":true,"family":"Huston","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":828581,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelley, Karen D. 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":179012,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":828582,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Czarnota, Karol","contributorId":270196,"corporation":false,"usgs":false,"family":"Czarnota","given":"Karol","email":"","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":828584,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paradis, Suzanne","contributorId":31666,"corporation":false,"usgs":true,"family":"Paradis","given":"Suzanne","email":"","affiliations":[],"preferred":false,"id":828585,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Peter, Jan M.","contributorId":270175,"corporation":false,"usgs":false,"family":"Peter","given":"Jan","email":"","middleInitial":"M.","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":828586,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hayward, Nathan","contributorId":270177,"corporation":false,"usgs":false,"family":"Hayward","given":"Nathan","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":828587,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Barlow, Mike","contributorId":270179,"corporation":false,"usgs":false,"family":"Barlow","given":"Mike","email":"","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":828588,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Emsbo, Poul 0000-0001-9421-201X pemsbo@usgs.gov","orcid":"https://orcid.org/0000-0001-9421-201X","contributorId":997,"corporation":false,"usgs":true,"family":"Emsbo","given":"Poul","email":"pemsbo@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":828583,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Coyan, Joshua A. 0000-0002-8450-7364 jcoyan@usgs.gov","orcid":"https://orcid.org/0000-0002-8450-7364","contributorId":197481,"corporation":false,"usgs":true,"family":"Coyan","given":"Joshua","email":"jcoyan@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":828589,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"San Juan, Carma A. 0000-0002-9151-1919 csanjuan@usgs.gov","orcid":"https://orcid.org/0000-0002-9151-1919","contributorId":1146,"corporation":false,"usgs":true,"family":"San Juan","given":"Carma","email":"csanjuan@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":828590,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70224955,"text":"70224955 - 2021 - Exploring basin-scale relations and unsupervised classification to quantify and automate the definition of assessment units in USGS continuous oil and gas resource assessments","interactions":[],"lastModifiedDate":"2025-06-17T15:42:06.522652","indexId":"70224955","displayToPublicDate":"2021-12-01T10:34:26","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Exploring basin-scale relations and unsupervised classification to quantify and automate the definition of assessment units in USGS continuous oil and gas resource assessments","docAbstract":"The U.S. Geological Survey (USGS) assesses potential for undiscovered, technically recoverable oil and gas resources in priority geologic provinces and quantifies resource volume estimates within subdivisions called assessment units (AUs). AU boundaries are defined by USGS geologists using quantitative and qualitative geologic information. Variables contained in IHS Markit’s well and production databases can quantify and/or function as proxies for many of the qualitative, boundary-defining variables. This research explores a new approach to determine AU boundaries and the potential to automate their definition, using data analytics and machine learning algorithms on key, qualitative variables within the IHS Markit databases. Well and production data from the U.S. onshore Gulf Coast region for the Upper Cretaceous Eagle Ford Group and Austin Chalk are used in this analysis because each is relatively geologically uniform in Texas and both have recently been assessed by the USGS. The Eagle Ford is an example of an in situ continuous oil and gas accumulation, and the overlying Austin Chalk is an example of a combined conventional and continuous resource, sourced from the underlying Eagle Ford. Wellspecific values were extracted or calculated from data in IHS Markit’s well and production databases for depth to top and base of the formations, formation thickness, bottom-hole temperature, temperature gradient, temperature at base of formation, cumulative oil and gas production values, barrels of oil equivalent, oil and gas gravities, mud weights from initial well test, depth pressure ratio, and excess pressure. A raster for each variable was interpolated using the natural neighbor technique from the spatial analyst toolbox in ArcGIS. Rasters were then transformed using minimum-maximum scaling, which rescales the distribution to the range of 0–1. Clustering was completed using the iso cluster unsupervised classification tool on the normalized rasters. Raster cell groupings from two to ten were explored, with initial results demonstrating that four to six classes return the most differentiable groups, with depth to formation, oil gravity, pressure, and temperature variables containing the greatest between-group differences. Modeled clusters have spatial similarities to the geologically defined AUs, with indication that temperature and pressure are the most fundamental to AU definition. Input from geologists will remain crucial for further dividing clusters and defining final AUs, since AUs are defined by both qualitative and quantitative information; however, this research documents promising cluster modeling results for the automation of initial AU definitions.
","conferenceTitle":"SEG-AAPG International Meeting for Applied Geoscience & Energy (IMAGE) 2021","conferenceDate":"September 26-October 1, 2021","conferenceLocation":"Denver, CO","language":"English","publisher":"Society of Exploration Geophysicists and the American Association of Petroleum Geologists","usgsCitation":"Shorten, C., Kinney, S.A., and Whidden, K.J., 2021, Exploring basin-scale relations and unsupervised classification to quantify and automate the definition of assessment units in USGS continuous oil and gas resource assessments, SEG-AAPG International Meeting for Applied Geoscience & Energy (IMAGE) 2021, Denver, CO, September 26-October 1, 2021, 10 p.","productDescription":"10 p.","ipdsId":"IP-131669","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":490854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":490853,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/international-meeting-for-applied-geoscience-and-energy/data/2021/7321.htm?q=%2BauthorStrip%3Ashorten","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana, Mississippi, Texas","otherGeospatial":"Upper Cretaceous Eagle Ford Group and Austin Chalk","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101.46300363364126,\n 29.853524579639256\n ],\n [\n -98.79174292446497,\n 26.39154767945162\n ],\n [\n -97.15568801261291,\n 25.692988402953162\n ],\n [\n -96.30476798511874,\n 27.907758438495677\n ],\n [\n -93.26076686296953,\n 29.3771372231364\n ],\n [\n -88.088627576136,\n 28.580800903730534\n ],\n [\n -88.5714936485433,\n 32.46814742644388\n ],\n [\n -94.5985927100297,\n 32.52158667154865\n ],\n [\n -101.46300363364126,\n 29.853524579639256\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shorten, Chilisa Marie 0000-0003-1828-2002","orcid":"https://orcid.org/0000-0003-1828-2002","contributorId":267256,"corporation":false,"usgs":true,"family":"Shorten","given":"Chilisa Marie","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":824843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinney, Scott A. 0000-0001-5008-5813 skinney@usgs.gov","orcid":"https://orcid.org/0000-0001-5008-5813","contributorId":1395,"corporation":false,"usgs":true,"family":"Kinney","given":"Scott","email":"skinney@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":824844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":824845,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229714,"text":"70229714 - 2021 - Effects of sample gear on estuarine nekton assemblage assessments and food web model simulations","interactions":[],"lastModifiedDate":"2022-03-17T13:23:05.511118","indexId":"70229714","displayToPublicDate":"2021-12-01T10:32:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Effects of sample gear on estuarine nekton assemblage assessments and food web model simulations","docAbstract":"Long-term fisheries-independent sampling data inform population status and trends of species-specific biomass and are often used to drive biomass-based food web models such as the Comprehensive Aquatic Systems Model (CASM). Indicators such as total biomass and mean trophic level derived from these data and from CASM outputs inform management and facilitate assessments of on-going and predicted coastal change and restoration activities on fisheries, but rely on consistent sampling to enable comparisons across space and time. Changes in coastal estuarine gradients, combined with the availability of new sampling technologies, highlight a need to assess the potential consequences of changing sampling technologies on fisheries data and the cascading impact on model outputs. In Louisiana, USA, CASM models are used to inform coastal restoration projects, relying on 40 years of fisheries-independent data derived from 50′ seine sampling. However, alternative use of electrofishers as a sampling method has been proposed to replace the seine sampling. In this study, we examine data from concurrent seine and electrofisher sampling in Barataria Basin, Louisiana, and compare biomass, assemblage data and CASM outputs related to species biomass, food web structure and energy cycling. In a paired comparison of data in 2018–2019, the electrofisher captured higher total catch and diversity compared to the seine. The electrofisher samples were dominated by shrimp (grass, white, brown) and larger bodied fish, while seine samples were dominated by smaller-bodied fish (i.e., anchovy, menhaden). Ecosystem indicators derived from running the CASM using biomass data from seine and electrofisher sampling separately in two different simulation exercises provide contrasting results. In Simulation Exercise 1, the use of different datasets (long-term CASM calibration, 2018–2019 seine, 2018–2019 electrofisher) to initialize the CASM biomasses did not result in large or long-running changes in the simulated biomasses over time. In contrast, in Simulation Exercise 2, CASM model outputs using adjusted gear ratios indicated changes in biomass structure when using electrofisher data, with a doubling of total food web biomass due to the increased shrimp count, and a 13% increase in total energy flow through the food web. Conversions based on area and gear efficiency for overall catch may be useful in maintaining the continuity of historical data. However, differences in species-specific catch due to gear selectivity could have large consequences for constructing and calibrating fish and ecosystem models and remain difficult to reconcile. These differences in assemblages, and estimated biomasses for key food web species, suggest careful consideration in changing gears.
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M.","contributorId":220867,"corporation":false,"usgs":false,"family":"Taylor","given":"C.","email":"","middleInitial":"M.","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":838076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watkins, Katherine S.","contributorId":288553,"corporation":false,"usgs":false,"family":"Watkins","given":"Katherine","email":"","middleInitial":"S.","affiliations":[{"id":52096,"text":"Dynamic Solutions, LLC","active":true,"usgs":false}],"preferred":false,"id":838077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kiskaddon, E.","contributorId":276292,"corporation":false,"usgs":false,"family":"Kiskaddon","given":"E.","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":838079,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baustian, M.","contributorId":288555,"corporation":false,"usgs":false,"family":"Baustian","given":"M.","email":"","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":838080,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70242771,"text":"70242771 - 2021 - Supplemental vegetation monitoring plots at Little Bighorn Battlefield National Monument to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","interactions":[],"lastModifiedDate":"2024-03-05T16:44:23.727968","indexId":"70242771","displayToPublicDate":"2021-12-01T10:23:29","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":7577,"text":"Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Supplemental vegetation monitoring plots at Little Bighorn Battlefield National Monument to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","docAbstract":"The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains (NGP) working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.”
The original ABAM model has little information about the effects of the herbicide indaziflam on target invasive annual grasses and other components of the vegetation in conditions like those that frequently occur in ABAM parks (i.e., ungrazed). The purpose of this study is to provide some of that information and therefore accelerate the rate of learning accomplished in the adaptive management cycle.
","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., Richardson, T., and Swanson, D., 2021, Supplemental vegetation monitoring plots at Little Bighorn Battlefield National Monument to accelerate learning of the Annual Brome Adaptive Management (ABAM) model: Annual Report, 5 p.","productDescription":"5 p.","ipdsId":"IP-152073","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415838,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573320","linkFileType":{"id":5,"text":"html"}},{"id":426325,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Little Bighorn Battlefield National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.42780937203189,\n 45.55613907753829\n ],\n [\n -107.41424157476726,\n 45.56297486244455\n ],\n [\n -107.42644541357662,\n 45.57478473659421\n ],\n [\n -107.44274112775177,\n 45.56674424099478\n ],\n [\n -107.44575619381031,\n 45.566543213856875\n ],\n [\n -107.44259755317754,\n 45.56327642203598\n ],\n [\n -107.43943891254428,\n 45.56151730159996\n ],\n [\n -107.4385056778117,\n 45.560763375980855\n ],\n [\n -107.44123359472226,\n 45.55814968884059\n ],\n [\n -107.43814674137612,\n 45.55679253410301\n ],\n [\n -107.43584954818878,\n 45.55789836636245\n ],\n [\n -107.43412665329791,\n 45.56016022820128\n ],\n [\n -107.43218839654568,\n 45.55855180246806\n ],\n [\n -107.43419844058504,\n 45.55593801245129\n ],\n [\n -107.43075265080329,\n 45.555586146818285\n ],\n [\n -107.42780937203189,\n 45.55613907753829\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, Timm","contributorId":334581,"corporation":false,"usgs":false,"family":"Richardson","given":"Timm","email":"","affiliations":[],"preferred":false,"id":895969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swanson, Dan","contributorId":334582,"corporation":false,"usgs":false,"family":"Swanson","given":"Dan","email":"","affiliations":[],"preferred":false,"id":895970,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230205,"text":"70230205 - 2021 - Genomics reveals identity, phenology and population demographics of larval ciscoes (Coregonus artedi, C. hoyi, and C. kiyi) in the Apostle Islands, Lake Superior","interactions":[],"lastModifiedDate":"2022-04-05T15:27:13.158382","indexId":"70230205","displayToPublicDate":"2021-12-01T10:14:06","publicationYear":"2021","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}},"displayTitle":"Genomics reveals identity, phenology and population demographics of larval ciscoes (Coregonus artedi, C. hoyi, and C. kiyi) in the Apostle Islands, Lake Superior","title":"Genomics reveals identity, phenology and population demographics of larval ciscoes (Coregonus artedi, C. hoyi, and C. kiyi) in the Apostle Islands, Lake Superior","docAbstract":"We demonstrate, for the first time, the ability to reliably assign an assemblage of larval coregonines [Salmonidae Coregoninae] to shallow and multiple deepwater species. Larval coregonines from the Apostle Islands, Lake Superior, were genotyped using restriction site-associated DNA sequencing (RADseq) and were assigned to species using reference genotypes from adult corgonines from the same region. Of the 193 genotyped larvae, 101 were assigned as Coregonus artedi (average assignment probability = 97.6%), 57 were assigned as C. kiyi (average assignment probability = 95.5%), and 28 were assigned as C. hoyi (average assignment probability = 89.0%). Coregonus artedi were collected earliest in the season, followed by C. kiyi and then C. hoyi. Estimates of genetic diversity within each species provide a baseline for future monitoring in the Apostle Islands. Our success with species assignment indicates the promise of leveraging genomic data for larval coregonine identification, which could enable assessing and evaluating early life history dynamics and recruitment processes at the species level to the benefit of ongoing coregonine restoration and management efforts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.09.012","usgsCitation":"Lachance, H., Ackiss, A.S., Larson, W., Vinson, M., and Stockwell, J.D., 2021, Genomics reveals identity, phenology and population demographics of larval ciscoes (Coregonus artedi, C. hoyi, and C. kiyi) in the Apostle Islands, Lake Superior: Journal of Great Lakes Research, v. 47, no. 6, p. 1849-1857, https://doi.org/10.1016/j.jglr.2021.09.012.","productDescription":"9 p.","startPage":"1849","endPage":"1857","ipdsId":"IP-127797","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":450101,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2021.09.012","text":"Publisher Index Page"},{"id":398118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Alaska","interactions":[],"lastModifiedDate":"2024-10-29T14:51:56.414934","indexId":"70260126","displayToPublicDate":"2021-12-01T09:47:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7593,"text":"Volcanica","active":true,"publicationSubtype":{"id":10}},"title":"Simultaneous effusive and explosive cinder cone eruptions at Veniaminof Volcano, Alaska","docAbstract":"Historical eruptions of Veniaminof Volcano, Alaska have all occurred at a 300-m-high cinder cone within the icefilled caldera that characterizes the volcano. At least six of nineteen historical eruptions involved simultaneous explosive and effusive activity from separate vents. Eruptions in 1944, 1983–1984, 1993–1994, 2013, 2018 and 2021 included periods of explosive ash-producing Strombolian activity from summit vents and simultaneous nonexplosive effusion of lava from flank vents on either the southern or northeast sides of the cone. A T-junction conduit network is proposed to explain the simultaneous eruptive styles and as a mechanism for gas-magma segregation that must occur to produce the observed activity. Historical eruptions with simultaneous summit and flank activity produced slightly higher rising ash clouds compared to historical eruptions where simultaneous activity did not occur. This could be a consequence of the partitioning of more gas-charged magma into the vertical conduit of a T-junction conduit system.
","language":"English","publisher":"Presses universitaires de Strasbourg","doi":"10.30909/vol.04.02.295307","usgsCitation":"Waythomas, C.F., 2021, Simultaneous effusive and explosive cinder cone eruptions at Veniaminof Volcano, Alaska: Volcanica, v. 4, no. 2, p. 295-307, https://doi.org/10.30909/vol.04.02.295307.","productDescription":"13 p.","startPage":"295","endPage":"307","ipdsId":"IP-123129","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467220,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol.04.02.295307","text":"Publisher Index Page"},{"id":463342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Veniaminof Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -159.61853128517166,\n 56.32013696150028\n ],\n [\n -159.61853128517166,\n 56.00933215264163\n ],\n [\n -159.04223263726425,\n 56.00933215264163\n ],\n [\n -159.04223263726425,\n 56.32013696150028\n ],\n [\n -159.61853128517166,\n 56.32013696150028\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917094,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70241051,"text":"70241051 - 2021 - Inter- and intra-annual effects of lethal removal on common raven abundance in Nevada and California, USA","interactions":[],"lastModifiedDate":"2023-03-08T15:17:43.127372","indexId":"70241051","displayToPublicDate":"2021-12-01T09:10:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13291,"text":"Human–Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Inter- and intra-annual effects of lethal removal on common raven abundance in Nevada and California, USA","docAbstract":"Populations of common ravens (Corvus corax; ravens) have increased rapidly within sagebrush (Artemisia spp.) ecosystems between 1960 and 2020. Although ravens are native to North America, their population densities have expanded to levels that negatively influence the population dynamics of other wildlife species of conservation concern, such as greater sage-grouse (Centrocercus urophasianus) and desert tortoises (Gopherus agassizii). For this reason, lethal removal, such as the application of the avicide DRC-1339, has been used to manage raven numbers at local scales and under certain circumstances. Because the relative effectiveness of DRC-1339 in reducing raven populations densities is not thoroughly understood, we completed 2 case studies using a before-after-control-impact experimental design of density estimates generated from point count data within a Bayesian hierarchical distance sampling framework. Specifically, we analyzed >16,000 point count surveys collected during 2009–2019 and split into 2 study designs covering multiple field sites within the Great Basin region. The first experiment evaluated intra-annual changes in density by comparing before and after treatment time periods within a single breeding season for multiple treatment regions compared to 2 control regions. The other experiment focused on inter-annual differences by comparing time periods across years before and after the onset of annual avicide application for a single treatment region compared to multiple control regions. Our models estimated a 100% probability of decline in density relative to control sites for both the intra- and inter-annual model designs. At treatment sites, expected densities of ravens varied but were reduced by 43% (95% CRI: 33–49%) and 54% (95% CRI: 24–71%) according to intra- and inter-annual analyses, respectively, whereas densities increased by 42% (95% CRI: 27–60%) and 15% (95% CRI: -17 to 58%) at control sites. Although population densities were reduced with treatments, trends indicated that sustained effort would likely be needed to maintain densities at acceptable levels within regions of interest. Effectively reducing the adverse effects of raven populations on other native species likely will depend on a variety of targeted management actions such as improving habitat quality for prey species, possibly reducing ravens’ population density, and treating the cause of increased raven abundance to reduce future carrying capacity and prevent rebounds.
","language":"English","publisher":"Berryman Institute","doi":"10.26077/p79d-en84","usgsCitation":"O’Neil, S.T., Coates, P.S., Brockman, J.C., Jackson, P.J., Spencer, J.O., and Williams, P.J., 2021, Inter- and intra-annual effects of lethal removal on common raven abundance in Nevada and California, USA: Human–Wildlife Interactions, v. 15, no. 3, 20, 16 p., https://doi.org/10.26077/p79d-en84.","productDescription":"20, 16 p.","ipdsId":"IP-130888","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":413856,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.06172324180406,\n 41.791122396069284\n ],\n [\n -120.49545088606604,\n 41.791122396069284\n ],\n [\n -120.49545088606604,\n 37.428574642347996\n ],\n [\n -114.06172324180406,\n 37.428574642347996\n ],\n [\n -114.06172324180406,\n 41.791122396069284\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865865,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":865866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brockman, Julia C.","contributorId":302928,"corporation":false,"usgs":false,"family":"Brockman","given":"Julia","email":"","middleInitial":"C.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":865867,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Pat J.","contributorId":206602,"corporation":false,"usgs":false,"family":"Jackson","given":"Pat","email":"","middleInitial":"J.","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":865868,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spencer, Jack O. Jr.","contributorId":196229,"corporation":false,"usgs":false,"family":"Spencer","given":"Jack","suffix":"Jr.","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":865869,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":865870,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236368,"text":"70236368 - 2021 - Metal accumulation in Lake Michigan prey fish: Influence of ontogeny, trophic position, and habitat","interactions":[],"lastModifiedDate":"2023-09-18T20:50:58.994088","indexId":"70236368","displayToPublicDate":"2021-12-01T09:01:28","publicationYear":"2021","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":"Metal accumulation in Lake Michigan prey fish: Influence of ontogeny, trophic position, and habitat","docAbstract":"Developing an understanding of factors that influence the accumulation and magnification of heavy metals in fish of the Laurentian Great Lakes is central to managing ecosystem and human health. We measured muscle tissue concentrations of heavy metals in Lake Michigan prey fish that vary in habitat use, diet, and trophic position, including alewife, bloater, deepwater sculpin, round goby, rainbow smelt, and slimy sculpin. For each individual, we measured tissue concentrations of four metals (chromium [Cr], copper [Cu], manganese [Mn], and total mercury [THg]), stable isotope ratios for trophic position (δ15N and δ13C), and individual fish attributes (length, mass). Total mercury concentration was positively related to total length and δ15N. Of all species, round goby displayed one of the greatest increases in mercury per unit growth and was most isotopically distinct from other species. Profundal species (bloater, deepwater sculpin, slimy sculpin) had similar high THg tissue concentrations, possibly due to slower growth due to cold temperatures, whereas other species (alewife, round goby, rainbow smelt) showed more variation in THg. In contrast, other metals (Cr, Cu, Mn) had either a negative or no relationship to total length and δ15N, suggesting no bioaccumulation or biomagnification. Potential incorporation of mercury by sportfish may thus be related to species, age, diet, trophic position, and habitat of prey fish. Our findings serve as a foundation for understanding how heavy metals accumulate in Lake Michigan food webs and highlight the continued need for management of metal input and cycling in Lake Michigan.
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