A study was conducted during June–October 2020 to evaluate factors affecting the migration success of adult sockeye salmon (Oncorhynchus nerka) in the Yakima River, Washington. A total of 144 adult sockeye salmon were tagged and released during the study. Most fish (112 fish) were collected, tagged with passive integrated transponder (PIT), and released at the mouth of the Yakima River. The remaining fish were tagged with a radio transmitter and PIT tag: 13 fish were collected, tagged, and released at Prosser Dam; 13 fish were collected and tagged at Prosser Dam, transported downstream, and released at the mouth of the Yakima River; and 6 fish were collected, tagged, and released at the mouth of the Yakima River. Radio-tagged fish released at Prosser Dam initially moved upstream and spread out in the river reach between Prosser and Sunnyside Dams, but all fish stopped moving and several transmitters were recovered. Detection records and temperature data from recovered transmitters were the basis for inferring that avian predators consumed at least 6 of the 13 fish. Fifteen of the 19 radio-tagged sockeye salmon released at the mouth of the Yakima River moved upstream in the Columbia River and were detected at Johnson Island in the Hanford Reach, or at Priest Rapids Dam. Two of these fish, tagged on August 7, eventually moved back downstream and entered the Yakima River when water temperatures in the lower Yakima River were 16–18 degrees Celsius (°C). One fish moved upstream to Sunnyside Dam where its tag was later recovered. The other fish moved farther upstream and was detected at Prosser Dam, but eventually moved downstream and its tag was recovered near Benton City, Washington. None of the recovered tags were found near a carcass. More than one-half of the sockeye salmon that were collected, tagged, and released at the mouth of the Yakima River were subsequently detected, and the greatest proportion of fish from groups released during June, July, and August entered the Yakima River. This finding suggests that adult sockeye salmon are present at the mouth of the Yakima River throughout the summer. Detection records for tagged fish at monitoring sites located near cool water inputs in the lower Yakima River suggest that sockeye salmon do not spend a substantial amount of time at these locations. Fish count data at Prosser Dam fish ladders showed that sockeye salmon had a bi-modal pattern of upstream migration with peaks in late June/early July and September when water temperature in the lower Yakima River was 20 °C or less. Sixty-one percent of PIT-tagged sockeye salmon detected at Prosser Dam were eventually collected at the adult fish trapping facility at Roza Dam where fish are collected and transported upstream to Cle Elum Reservoir. These data, in conjunction with results from other studies, suggest that a substantial proportion of Yakima River sockeye salmon fail to arrive at Roza Dam. Additional research will be required to better understand factors affecting Yakima River sockeye salmon.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211075","collaboration":"Prepared in cooperation with Bureau of Reclamation, Yakama Nation Fisheries, and Washington Department of Fish and Wildlife","usgsCitation":"Kock, T.J., Hansen, A.C., Evans, S.D., Visser, R., Saluskin, B., Matala, A., and Hoffarth, P., 2021, Evaluation of factors affecting migration success of adult sockeye salmon (Oncorhynchus nerka) in the Yakima River, Washington, 2020: U.S. Geological Survey Open-File Report 2021–1075, 30 p., https://doi.org/10.3133/ofr20211075.","productDescription":"vi, 30 p.","onlineOnly":"Y","ipdsId":"IP-128700","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":387441,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1075/ofr20211075.pdf","text":"Report","size":"5.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1075"},{"id":387440,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1075/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Yakima River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.8770751953125,\n 45.96642454131025\n ],\n [\n -118.67431640625,\n 45.96642454131025\n ],\n [\n -118.67431640625,\n 46.916503267244835\n ],\n [\n -120.8770751953125,\n 46.916503267244835\n ],\n [\n -120.8770751953125,\n 45.96642454131025\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
1. Migratory waterfowl facilitate long distance dispersal of zoonotic pathogens and are increasingly recognized as contributing to the geographic spread of avian influenza viruses (AIV). AIV are globally distributed and have the potential to produce highly contagious poultry disease, economically impact both large-scale and backyard poultry producers, and raise the specter of epidemics and pandemics in human populations.
2. Because migratory waterfowl behavior varies across multiple spatial and temporal scales, the timing and distribution of wild bird AIV introductions to poultry are also heterogeneous in time and space. To help reduce economic impacts to the poultry industry and enable poultry producers to better anticipate when and where poultry outbreaks may occur, it is critically important to consider the movement ecology of the waterfowl species transporting and transmitting AIV.
3. We used telemetry for a geographically widespread and common AIV host, blue-winged teal (Spatula discors; BWTE), to model reservoir host movement states with respect to backyard and commercial poultry facilities in the United States. Our modeling framework enabled us to estimate wild bird proximity to poultry facilities while concurrently assessing the influence of poultry facilities on BWTE movement state transition. Our primary objective was to estimate the likelihood of duck and poultry overlap by estimating when and where BWTE were geographically closest to poultry.
4. Synthesis and applications. Migratory waterfowl facilitate dispersal of the avian influenza viruses that cause highly contagious poultry disease. Movement analysis of blue-winged teal indicates that spatio-temporal overlap between wild birds and poultry facilities varies by season, the poultry type produced (e.g., turkey, chicken), and if the facility is a commercial or backyard operation. These findings are broadly applicable to disease ecology research and can be applied by poultry producers to improve bio-security, enhance poultry management, and prioritize disease surveillance efforts.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13963","usgsCitation":"Humphreys, J.M., Douglas, D.C., Ramey, A.M., Mullinax, J.M., Soos, C., Link, P.T., Walther, P., and Prosser, D., 2021, The spatial-temporal relationship of blue-winged teal to domestic poultry: Movement state modeling of a highly mobile avian influenza host: Journal of Applied Ecology, v. 58, no. 10, p. 2040-2052, https://doi.org/10.1111/1365-2664.13963.","productDescription":"13 p.","startPage":"2040","endPage":"2052","ipdsId":"IP-118863","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":451405,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13963","text":"Publisher Index Page"},{"id":387599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-08-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Humphreys, John M.","contributorId":217932,"corporation":false,"usgs":false,"family":"Humphreys","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":820044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":820046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":820045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mullinax, Jennifer M.","contributorId":221170,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":820047,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soos, Catherine","contributorId":177909,"corporation":false,"usgs":false,"family":"Soos","given":"Catherine","email":"","affiliations":[],"preferred":false,"id":820048,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Link, Paul T.","contributorId":53611,"corporation":false,"usgs":false,"family":"Link","given":"Paul","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":820049,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walther, Patrick","contributorId":213915,"corporation":false,"usgs":false,"family":"Walther","given":"Patrick","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":820050,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":820051,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223494,"text":"70223494 - 2021 - Water–rock interaction and the concentrations of major, trace, and rare earth elements in hydrocarbon-associated produced waters of the United States","interactions":[],"lastModifiedDate":"2024-09-16T16:35:32.635392","indexId":"70223494","displayToPublicDate":"2021-07-26T07:46:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9161,"text":"Environmental Science: Processes & Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Water–rock interaction and the concentrations of major, trace, and rare earth elements in hydrocarbon-associated produced waters of the United States","docAbstract":"Studies of co-produced waters from hydrocarbon extraction across multiple energy-producing basins have generally focused on major ions or a few select tracers, and studies that examine trace elements and involve laboratory experiments have generally been basin specific. Here, new perspective is sought through a broad analysis of concentration data for 26 elements from three hydrocarbon well types using the U.S. Geological Survey National Produced Waters Geochemical Database (v2.3). Those data are compared to leachates (water, hydrochloric acid, and artificial brine) from 12 energy-resource related shales from across the United States. Both lower pH and higher ionic strength were associated with greater concentrations of many trace elements in produced waters. However, individual effects were difficult to distinguish because higher ionic strengths drive decreases in pH. Water–rock interactions in the leaching experiments generally replicated produced water concentrations for trace elements including Al, As, Cd, Co, Cu, Mo, Ni, Pb, Sb, Si, and Zn. Enhanced middle rare earth element (REE) mobilization relative to shale REE content occurred with low pH leachates. Produced water concentrations of Li, Sr, and Ba were not replicated by the leaching experiments. Patterns of high Li, Sr, and Ba concentrations and ratios relative to other elements across produced waters types indicate controls on these elements in many settings related to pore space pools of salts, brines, and ion-exchange sites affected by diagenetic processes. The size of those pools is diluted and masked by other water–rock interaction processes at the water–rock ratios necessitated by laboratory experiments. The results broadly link water–rock interaction processes and environmental patterns across a wide variety of produced waters and host formations and thus provide context for trace element data from other environmental and laboratory studies of such waters.
The forage maturation hypothesis (FMH) states that energy intake for ungulates is maximised when forage biomass is at intermediate levels. Nevertheless, metabolic allometry and different digestive systems suggest that resource selection should vary across ungulate species. By combining GPS relocations with remotely sensed data on forage characteristics and surface water, we quantified the effect of body size and digestive system in determining movements of 30 populations of hindgut fermenters (equids) and ruminants across biomes. Selection for intermediate forage biomass was negatively related to body size, regardless of digestive system. Selection for proximity to surface water was stronger for equids relative to ruminants, regardless of body size. To be more generalisable, we suggest that the FMH explicitly incorporate contingencies in body size and digestive system, with small-bodied ruminants selecting more strongly for potential energy intake, and hindgut fermenters selecting more strongly for surface water.
We studied biotic ligand model (BLM) predictions of toxicity of nickel (Ni) and zinc (Zn) in natural waters from Illinois and Minnesota USA which had combinations of pH, hardness, and dissolved organic carbon (DOC) more extreme than 99.7% of waters in a nationwide database. We conducted 7-d chronic tests with Ceriodaphnia dubia, and 96-hr acute test and 14-d chronic tests with Neocloeon triangulifer, and estimated LC50s and EC20s for both species. Toxicity of Ni and Zn to both species differed among test waters by factors from 8 (Zn tests with C. dubia) to 35 (Zn tests with N. triangulifer). For both species and metals, tests with Minnesota waters (low pH and hardness, high DOC) showed lower toxicity than Illinois waters (high pH, high hardness, low DOC). Recalibration of the Ni BLM to be more responsive to pH-related changes improved predictions of Ni toxicity, especially for C. dubia. We compared several input data scenarios for the Zn BLM, which generally had minor effects on Model Performance Scores (MPS). A scenario that included inputs of modeled dissolved inorganic carbon and measured Al and Fe(III) produced highest MPS values for tests with both C. dubia and N. triangulifer. Overall, the BLM framework successfully modeled variation in toxicity for both Zn and Ni across wide ranges of water chemistry in tests with both standard and novel test organisms.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.5178","usgsCitation":"Besser, J.M., Ivey, C.D., Steevens, J.A., Cleveland, D.M., Soucek, D.J., Dickinson, A., Van Genderen, E.J., Ryan, A.C., Schlekat, C.E., Garman, E., Middleton, E., and Santore, R.C., 2021, Modeling the bioavailability of nickel and zinc to Ceriodaphnia dubia and Neocloeon triangulifer in toxicity tests with Natural Waters: Environmental Toxicology and Chemistry, v. 40, no. 11, p. 3049-3062, https://doi.org/10.1002/etc.5178.","productDescription":"14 p.","startPage":"3049","endPage":"3062","ipdsId":"IP-124650","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":436265,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GWJRF3","text":"USGS data release","linkHelpText":"Survival, growth and reproduction of C. dubia and N. triangulifer to nickel and zinc exposure in natural waters"},{"id":388396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Minnesota","otherGeospatial":"Keeley Creek, Spoon Creek, Spring Creek, St. Louis River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.2080078125,\n 47.100044694025215\n ],\n [\n -91.23046875,\n 47.100044694025215\n ],\n [\n -91.23046875,\n 48.1367666796927\n ],\n [\n -93.2080078125,\n 48.1367666796927\n ],\n [\n -93.2080078125,\n 47.100044694025215\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.8681640625,\n 40.38002840251183\n ],\n [\n -87.5390625,\n 40.38002840251183\n ],\n [\n -87.5390625,\n 41.541477666790286\n ],\n [\n -89.8681640625,\n 41.541477666790286\n ],\n [\n -89.8681640625,\n 40.38002840251183\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":821744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":821745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":821746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":821747,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soucek, David J. 0000-0002-7741-0193","orcid":"https://orcid.org/0000-0002-7741-0193","contributorId":224591,"corporation":false,"usgs":false,"family":"Soucek","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":40897,"text":"Illinois Natural History Survey, University of Illinois, Urbana-Champaign, IL","active":true,"usgs":false}],"preferred":false,"id":821748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dickinson, Amy","contributorId":224592,"corporation":false,"usgs":false,"family":"Dickinson","given":"Amy","email":"","affiliations":[{"id":40897,"text":"Illinois Natural History Survey, University of Illinois, Urbana-Champaign, IL","active":true,"usgs":false}],"preferred":false,"id":821749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Genderen, Eric J.","contributorId":264611,"corporation":false,"usgs":false,"family":"Van Genderen","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":54515,"text":"International Zinc Association, Durham NC","active":true,"usgs":false}],"preferred":false,"id":821750,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ryan, Adam C.","contributorId":175564,"corporation":false,"usgs":false,"family":"Ryan","given":"Adam","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":821751,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schlekat, Chris E.","contributorId":264612,"corporation":false,"usgs":false,"family":"Schlekat","given":"Chris","email":"","middleInitial":"E.","affiliations":[{"id":54516,"text":"NiPERA Inc, Durham NC","active":true,"usgs":false}],"preferred":false,"id":821752,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Garman, Emily R.","contributorId":264613,"corporation":false,"usgs":false,"family":"Garman","given":"Emily R.","affiliations":[{"id":54516,"text":"NiPERA Inc, Durham NC","active":true,"usgs":false}],"preferred":false,"id":821753,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Middleton, Elizabeth 0000-0002-4775-2774","orcid":"https://orcid.org/0000-0002-4775-2774","contributorId":264614,"corporation":false,"usgs":false,"family":"Middleton","given":"Elizabeth","email":"","affiliations":[{"id":54516,"text":"NiPERA Inc, Durham NC","active":true,"usgs":false}],"preferred":false,"id":821754,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Santore, Robert C.","contributorId":202449,"corporation":false,"usgs":false,"family":"Santore","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":36447,"text":"Windward Environmental LLC, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":821755,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70221896,"text":"sir20215026 - 2021 - Hydrogeology of the Susquehanna River valley-fill aquifer system in the towns of Conklin and Kirkwood, Broome County, New York","interactions":[],"lastModifiedDate":"2024-06-26T19:36:08.52945","indexId":"sir20215026","displayToPublicDate":"2021-07-23T10:10:00","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":"2021-5026","displayTitle":"Hydrogeology of the Susquehanna River Valley-Fill Aquifer System in the Towns of Conklin and Kirkwood, Broome County, New York","title":"Hydrogeology of the Susquehanna River valley-fill aquifer system in the towns of Conklin and Kirkwood, Broome County, New York","docAbstract":"The hydrogeology of the Susquehanna River valley-fill aquifer system and adjacent areas in south-central Broome County, New York, was investigated in cooperation with the New York State Department of Environmental Conservation. The study area encompasses roughly 55.5 square miles and includes the towns of Conklin and Kirkwood. Multiple small, perhaps discontinuous, valley-fill aquifers of unknown extent and hydraulic interconnection underlie the Susquehanna River valley from easternmost Binghamton south to Riverside, New York, near the Pennsylvania border. The hydrogeologic framework of these aquifers is described in this report on the basis of existing descriptions of surficial materials, especially those related to deglaciation, and subsurface data extracted from well and boring logs. A compilation of surficial geology, the descriptions of the spatial distribution of confined and unconfined aquifers, hydrogeologic sections, and well locations is provided as an oversized map plate and in a U.S. Geological Survey data release.
Residential households are one of the principal consumers of groundwater in the study area. Approximately half of these households are served by public water-supply systems that obtain water from wells, chiefly from highly productive but small and likely discontinuous surficial deposits of sand and gravel, while others obtain water from sand-and-gravel aquifers beneath till and (or) fine-grained lacustrine deposits, and a few from bedrock. Residents outside the public-supply service areas rely on private wells. In till-mantled upland areas, nearly all private wells tap bedrock. Water-resource potential is likely greatest north of Kirkwood Center, New York, where the valley is narrowest, and local aquifers are in thick stratified glacial deposits. Well yields are highest in this part of the valley, and the local aquifer system is likely replenished through induced infiltration from the Susquehanna River and numerous small tributaries. The area between Langdon and Kirkwood is filled with a mixture of stratified and unstratified glacial sediments and contains one high-yield well. This area likely has moderate water-resource potential, but limited well data make this difficult to verify. Well yields from suitable stratified glacial sediments generally decrease southward toward Riverside, New York.
Characterizing potential groundwater resources is also helpful for prioritizing source-water-protection efforts. Water resources throughout New York are at risk of contamination from commercial and industrial surface activities. As in many valley areas throughout the Susquehanna River watershed in south-central New York, valley wells with depths greater than roughly 100 to 150 feet are susceptible to contamination by naturally occurring saltwater and methane. New York currently has a moratorium on hydraulic fracturing, but the study area is underlain by rocks suitable for unconventional methods of gas production that would likely be initiated if the moratorium were to be lifted.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215026","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Van Hoesen, J.G., Heisig, P.M., and Fisher, S.R., 2021, Hydrogeology of the Susquehanna River valley-fill aquifer system in the towns of Conklin and Kirkwood, Broome County, New York: U.S. Geological Survey Scientific Investigations Report 2021–5026, 29 p., 1 pl., https://doi.org/10.3133/sir20215026.","productDescription":"Report: vii, 29 p.; 1 Plate 30.25 x 31.25 inches; Data Release","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118763","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":387155,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2021/5026/sir20215026_plate1.pdf","text":"Plate 1","size":"1.82 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Detailed aquifer mapping of the Susquehanna River valley in south-central Broome County, towns of Conklin and Kirkwood, New York"},{"id":387154,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O1EAV7","text":"USGS data release","linkHelpText":"Digital datasets for the hydrogeology of the Susquehanna River Valley in south-central Broome County, towns of Conklin and Kirkwood, New York"},{"id":387153,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5026/sir20215026.pdf","text":"Report","size":"8.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5026"},{"id":387152,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5026/coverthb2.jpg"}],"country":"United States","state":"New York","county":"Broome County","otherGeospatial":"Susquehanna River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.91690063476561,\n 42.001345689029755\n ],\n [\n -75.74970245361328,\n 42.001345689029755\n ],\n [\n -75.74970245361328,\n 42.08803181932636\n ],\n [\n -75.91690063476561,\n 42.08803181932636\n ],\n [\n -75.91690063476561,\n 42.001345689029755\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
Forest management guidelines are designed to protect water quality from unintended effects of land use changes such as timber harvest, mining, or forest road construction. Although streams that periodically cease to flow (nonperennial) drain the majority of forested areas, these streams are not consistently included in forest management guidelines. This paper reviews management guidelines for nonperennial (intermittent and ephemeral) streams draining temperate forests in the continental U.S., evaluates potential impacts of land use activities on ecosystem services provided by these streams, and identifies information needed to incorporate nonperennial streams into water quality protection practices. For federally administered lands, national management guidance is deliberately nonprescriptive, deferring to regional and forest-level recommendations for both perennial and nonperennial streams. Most state guidelines recommend riparian management zone (RMZ) protection for perennial streams (48/50 states) and intermittent streams (45/50 states), but only Alaska and West Virginia require RMZs around ephemeral streams. Based on the National Hydrography Dataset, an average of 58% of forested land area in the U.S. drains to nonperennial headwater streams, making these stream types the most common connectors between forested lands and the aquatic system. Land uses that modify flow regimes in these streams can affect sediment and organic matter transport and distribution, stream temperature dynamics, and biogeochemical processing. Nonperennial streams also provide material subsidies to downstream waters and serve as temporary habitats for some aquatic species. However, limited research has examined how forest land uses affect ecosystem services and biota in these streams. Therefore we highlight a set of key questions about nonperennial streams in forests, not the least of which is simply understanding where headwater stream channels are located and associated patterns of flow duration. Although many questions remain, we also note where recent advances in data collection, modeling and process-level research provide opportunities to resolve uncertainties around nonperennial streams in forested landscapes of the continental U.S.
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plan","interactions":[],"lastModifiedDate":"2021-08-09T13:40:23.125976","indexId":"70222612","displayToPublicDate":"2021-07-23T08:27:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5021,"text":"Environments","active":true,"publicationSubtype":{"id":10}},"title":"Applying biodiversity metrics as surrogates to a habitat conservation plan","docAbstract":"Unabated urbanization has led to environmental degradation and subsequent biodiversity loss across the globe. As an outcome of unmitigated land use, multi-jurisdictional agencies have developed land use plans that attempt to protect threatened or endangered species across selected areas by which some trade-offs between harm to species and additional conservation approaches are allowed among the partnering organizations. Typical conservation plans can be created to focus on single or multiple species, and although they may protect a species or groups of species, they may not account for biodiversity or its protection across the given area. We applied an approach that clustered deductive habitat models for terrestrial vertebrates into metrics that serve as surrogates for biodiversity and relate to ecosystem services. In order to evaluate this process, we collaborated with the partnering agencies who are creating a Multi-Species Habitat Conservation Plan in southern California and compared it to the entire Mojave Desert Ecoregion. We focused on total terrestrial vertebrate species richness and taxon groupings representing amphibians, birds, mammals, and reptiles, and two special status species using the Normalized Index of Biodiversity (NIB). The conservation planning area had a lower NIB and was less species rich than the Mojave Desert Ecoregion, but the Mojave River riparian corridor had a higher NIB and was more species-rich, and while taxon analysis varied across the geographies, this pattern generally held. Additionally, we analyzed desert tortoise (Gopherus agassizii) and desert kit fox (Vulpes macrotis arsipus) as umbrella species and determined that both species are associated with increased NIB and large numbers of species for the conservation area. Our process provided the ability to incorporate value-added surrogate information into a formal land use planning process and used a metric, NIB, which allowed comparison of the various planning areas and geographic units. Although this process has been applied to Apple Valley, CA, and other geographies within the U.S., the approach has practical application for other global biodiversity initiatives.
","language":"English","publisher":"MDPI","doi":"10.3390/environments8080069","usgsCitation":"Boykin, K.G., Kepner, W.G., and McKerrow, A., 2021, Applying biodiversity metrics as surrogates to a habitat conservation plan: Environments, v. 8, no. 8, 69, 19 p., https://doi.org/10.3390/environments8080069.","productDescription":"69, 19 p.","ipdsId":"IP-128000","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":451420,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/environments8080069","text":"Publisher Index Page"},{"id":387777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County","otherGeospatial":"Apple Valley Multi-Species Habitat Conservation Plan Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.28666667,\n 34.73750000\n ],\n [\n -116.95666667,\n 34.73750000\n ],\n [\n -116.95666667,\n 34.37194444\n ],\n [\n -117.28666667,\n 34.37194444\n ],\n [\n -117.28666667,\n 34.73750000\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Boykin, Kenneth G. 0000-0001-6381-0463","orcid":"https://orcid.org/0000-0001-6381-0463","contributorId":43651,"corporation":false,"usgs":false,"family":"Boykin","given":"Kenneth","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":820747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kepner, William G.","contributorId":261909,"corporation":false,"usgs":false,"family":"Kepner","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":13226,"text":"U.S. Environmental Protection Agency, Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":820748,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":820749,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223505,"text":"70223505 - 2021 - Interlaboratory comparison of SARS-CoV2 molecular detection assays in use by U.S. veterinary diagnostic laboratories","interactions":[],"lastModifiedDate":"2021-11-01T15:59:00.301607","indexId":"70223505","displayToPublicDate":"2021-07-23T08:21:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2492,"text":"Journal of Veterinary Diagnostic Investigation","active":true,"publicationSubtype":{"id":10}},"title":"Interlaboratory comparison of SARS-CoV2 molecular detection assays in use by U.S. veterinary diagnostic laboratories","docAbstract":"The continued search for intermediate hosts and potential reservoirs for SARS-CoV2 makes it clear that animal surveillance is critical in outbreak response and prevention. Real-time RT-PCR assays for SARS-CoV2 detection can easily be adapted to different host species. U.S. veterinary diagnostic laboratories have used the CDC assays or other national reference laboratory methods to test animal samples. However, these methods have only been evaluated using internal validation protocols. To help the laboratories evaluate their SARS-CoV2 test methods, an interlaboratory comparison (ILC) was performed in collaboration with multiple organizations. Forty-four sets of 19 blind-coded RNA samples in Tris-EDTA (TE) buffer or PrimeStore transport medium were shipped to 42 laboratories. Results were analyzed according to the principles of the International Organization for Standardization (ISO) 16140-2:2016 standard. Qualitative assessment of PrimeStore samples revealed that, in approximately two-thirds of the laboratories, the limit of detection with a probability of 0.95 (LOD95) for detecting the RNA was ≤20 copies per PCR reaction, close to the theoretical LOD of 3 copies per reaction. This level of sensitivity is not expected in clinical samples because of additional factors, such as sample collection, transport, and extraction of RNA from the clinical matrix. Quantitative assessment of Ct values indicated that reproducibility standard deviations for testing the RNA with assays reported as N1 were slightly lower than those for N2, and they were higher for the RNA in PrimeStore medium than those in TE buffer. Analyst experience and the use of either a singleplex or multiplex PCR also affected the quantitative ILC test results.
The Line Islands volcanic chain in the central Pacific Ocean exhibits many characteristics of a hotspot-generated seamount chain; however, the lack of a predictable age progression has stymied previous models for the origin of this feature. We combined plate-tectonic reconstructions with seamount age dates and available geochemistry to develop a new model that involves multiple melt regions and multiple melt delivery styles to explain the spatial and temporal history of the Line Islands system. Our model identifies a new melt source region (Larson melt region at ~17°S, ~125°W) that contributed to the formation of the Line Islands, as well as the Mid-Pacific Mountains and possibly the Pukapuka Ridge.
In recent decades, feral horse (Equus caballus; horse) populations increased in sagebrush (Artimesia spp.) ecosystems, especially within the Great Basin, to the point of exceeding maximum appropriate management levels (AMLmax), which were set by land administrators to balance resource use by feral horses, livestock, and wildlife. Concomitantly, greater sage-grouse (Centrocercus urophasianus; sage-grouse) are sagebrush obligates that have experienced population declines within these same arid environments as a result of steady and continued loss of seasonal habitats. Although a strong body of research indicates that overabundant populations of horses degrade sagebrush ecosystems, empirical evidence linking horse abundance to sage-grouse population dynamics is missing. Within a Bayesian framework, we employed state-space models to estimate population rate of change (λ) using 15 years (2005–2019) of count surveys of male sage-grouse at traditional breeding grounds (i.e., leks) as a function of horse abundance relative to AMLmax and other environmental covariates (e.g., wildfire, precipitation, % sagebrush cover). Additionally, we employed a post hoc impact-control design to validate existing AMLmax values as related to sage-grouse population responses, and to help control for environmental stochasticity and broad-scale oscillations in sage-grouse abundance. On average, for every 50% increase in horse abundance over AMLmax, our model predicted an annual decline in sage-grouse abundance by 2.6%. Horse abundance at or below AMLmax coincided with sage-grouse λ estimates that were consistent with trends at non-horse areas elsewhere in the study region. Thus, AMLmax, as a whole, appeared to be set adequately in preventing adverse effects to sage-grouse populations. Results indicated 76%, 97%, and >99% probability of sage-grouse population decline relative to controls when horse numbers are 2, 2.5, and ≥3 times over AMLmax, respectively. As of 2019, horse herds exceeded AMLmax in Nevada, USA, by >4 times on average across all horse management areas. If feral horse populations continue to grow at current rates unabated, model projections indicate sage-grouse populations will be reduced within horse-occupied areas by >70.0% by 2034 (15-year projection), on average compared to 21.2% estimated for control sites. A monitoring framework that improves on estimating horse abundance and identifying responses of sage-grouse and other key indicator species (plant and animal) would be beneficial to guide management decisions that promote co-occurrence of horses with sensitive wildlife and livestock within landscapes subjected to multiple uses. Published 2021. This article is a U.S. Government work and is in the public domain in the USA. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.
Wildfires and invasive species have caused widespread changes in western North America’s shrub-steppe landscapes. The bottom–up consequences of degraded shrublands on predator ecology and demography remain poorly understood. We used a before–after paired design to study whether Golden Eagle (Aquila chrysaetos) diet and nestling survivorship changed following wildfires in southwestern Idaho, USA. We assessed burn extents from 1981 to 2013 and vegetation changes between 1979 (pre-burn) and 2014 (post-burn) within 3 km of Golden Eagle nesting centroids. We measured the frequency and biomass of individual prey, calculated diet diversity indexes, and monitored nestling survivorship at 15 territories in 1971–1981 and 2014–2015. On average, 0.70 of the area within 3 km of nesting centroids burned between 1981 and 2013, and the mean proportion of unburned shrubland decreased from 0.73 in 1979 to 0.22 in 2014. Diets in post-burn years were more diverse and had a lower proportion of some shrub-associated species, such as black-tailed jackrabbits (Lepus californicus) and mountain cottontails (Sylvilagus nuttallii), and a higher proportion of American Coots (Fulica americana), Mallards (Anas platyrhynchos), Piute ground squirrels (Urocitellus mollis), and Rock Pigeons (Columba livia) compared with pre-burn years. A high proportion of waterfowl represented a novel change in Golden Eagle diets, which are typically dominated by mammalian prey. Nestling survivorship was positively associated with the proportion of black-tailed jackrabbits and negatively associated with the proportion of Rock Pigeons in eagle diets. Rock Pigeons are a vector for Trichomonas gallinae, a disease-causing protozoan lethal to young eagles. Nesting attempts were more likely to fail (all young die) in the post-burn period compared with the pre-burn period. Dietary shifts are a common mechanism for predators to cope with landscape change, but shifts away from preferred prey to disease vectors affect nestling survivorship and could lead to population-level effects on productivity.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duab034","usgsCitation":"Heath, J.A., Kochert, M.N., and Steenhof, K., 2021, Golden Eagle dietary shifts following wildfire and shrub loss have negative consequences for nestling survivorship: Ornithological Applications, v. 123, no. 4, duab034, 14 p., https://doi.org/10.1093/ornithapp/duab034.","productDescription":"duab034, 14 p.","ipdsId":"IP-126722","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":451429,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duab034","text":"Publisher Index Page"},{"id":401967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.00439453125,\n 42.61779143282346\n ],\n [\n -114.9169921875,\n 42.61779143282346\n ],\n [\n -114.9169921875,\n 43.77109381775651\n ],\n [\n -117.00439453125,\n 43.77109381775651\n ],\n [\n -117.00439453125,\n 42.61779143282346\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Heath, Julie A.","contributorId":192842,"corporation":false,"usgs":false,"family":"Heath","given":"Julie","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":844412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kochert, Michael N. 0000-0002-4380-3298 mkochert@usgs.gov","orcid":"https://orcid.org/0000-0002-4380-3298","contributorId":3037,"corporation":false,"usgs":true,"family":"Kochert","given":"Michael","email":"mkochert@usgs.gov","middleInitial":"N.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steenhof, Karen karen_steenhof@usgs.gov","contributorId":203439,"corporation":false,"usgs":false,"family":"Steenhof","given":"Karen","email":"karen_steenhof@usgs.gov","affiliations":[],"preferred":false,"id":844414,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249293,"text":"70249293 - 2021 - The products of primary magma fragmentation finally revealed by pumice agglomerates","interactions":[],"lastModifiedDate":"2023-10-03T12:11:05.896246","indexId":"70249293","displayToPublicDate":"2021-07-23T07:07:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"The products of primary magma fragmentation finally revealed by pumice agglomerates","docAbstract":"Following rapid decompression in the conduit of a volcano, magma breaks into ash- to block-sized fragments, powering explosive sub-Plinian and Plinian eruptions that may generate destructive pyroclastic falls and flows. It is thus crucial to assess how magma breaks up into fragments. This task is difficult, however, because of the subterranean nature of the entire process and because the original size of pristine fragments is modified by secondary fragmentation and expansion. New textural observations of sub-Plinian and Plinian pumice lapilli reveal that some primary products of magma fragmentation survive by sintering together within seconds of magma break-up. Their size distributions reflect the energetics of fragmentation, consistent with products of rapid decompression experiments. Pumice aggregates thus offer a unique window into the previously inaccessible primary fragmentation process and could be used to determine the potential energy of fragmentation.
This response is offered to the critique by Gard et al. (2021) of our meta-analysis of polychlorinated biphenyl (PCB)-induced toxicity data in fish (Berninger and Tillitt 2019). Gard et al. (2021) offered numerous comments, the most substantive suggesting that 1) we should have added no-observable–adverse effect residue (NOAER) data from additional studies and all data points from selected studies, and 2) the uncertainty of aggregating data from different PCB mixtures, different species, and different life stages is too great based on a limited data set. The additional studies Gard et al. suggested either were not designed to produce toxicological data, had experimental design issues, were confounded by co-contaminants, or did not contain paired exposure–effects data and as such were not appropriate to add to the data set. Lowest-observable–adverse effect residue (LOAER) values were selected for our analysis because they represent population sensitivities from the central portions of a frequency distribution (the linear portion of dose–response curves). As a consequence, there is less uncertainty in these input data (LOAER values) and greater confidence that they accurately represent the response of fish populations tested. Modeling NOAER values is in the extrapolation portion of a dose–response relationship and subject to enhanced uncertainty. The Gard et al. (2021) critique ignores this fundamental principle of toxicology and adds/deletes data points from our data set without clear selection criteria, which artificially enhances the uncertainty of their models that ultimately are not useful. We reject the premise that it is better to use individual study data as opposed to aggregation of PCB-induced toxicity thresholds in fish.
","language":"English","publisher":"Society for Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/etc.5074","usgsCitation":"Berninger, J., and Tillitt, D.E., 2021, Response to Gard et al.'s (2021) Comments on the Critical Review “Polychlorinated Biphenyl Tissue-Concentration Thresholds for Survival, Growth, and Reproduction in Fish”: Environmental Toxicology and Chemistry, v. 8, no. 40, p. 2098-2109, https://doi.org/10.1002/etc.5074.","productDescription":"12 p.","startPage":"2098","endPage":"2109","ipdsId":"IP-127386","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":498904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5074","text":"Publisher Index Page"},{"id":387596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"40","noUsgsAuthors":false,"publicationDate":"2021-08-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Berninger, Jason P.","contributorId":173602,"corporation":false,"usgs":false,"family":"Berninger","given":"Jason P.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":820064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":820065,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222488,"text":"70222488 - 2021 - Drivers of seedling establishment success in dryland restoration efforts","interactions":[],"lastModifiedDate":"2023-07-20T14:03:49.530468","indexId":"70222488","displayToPublicDate":"2021-07-22T08:23:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6505,"text":"Nature Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of seedling establishment success in dryland restoration efforts","docAbstract":"Restoration of degraded drylands is urgently needed to mitigate climate change, reverse desertification and secure livelihoods for the two billion people who live in these areas. Bold global targets have been set for dryland restoration to restore millions of hectares of degraded land. These targets have been questioned as overly ambitious, but without a global evaluation of successes and failures it is impossible to gauge feasibility. Here we examine restoration seeding outcomes across 174 sites on six continents, encompassing 594,065 observations of 671 plant species. Our findings suggest reasons for optimism. Seeding had a positive impact on species presence: in almost a third of all treatments, 100% of species seeded were growing at first monitoring. However, dryland restoration is risky: 17% of projects failed, with no establishment of any seeded species, and consistent declines were found in seeded species as projects matured. Across projects, higher seeding rates and larger seed sizes resulted in a greater probability of recruitment, with further influences on species success including site aridity, taxonomic identity and species life form. Our findings suggest that investigations examining these predictive factors will yield more effective and informed restoration decision-making.
Hatchery-raised, age-0 Florida bass Micropterus floridanus are commonly used for fish enhancement efforts to support popular recreational fisheries and are ecologically important as both a food source and consumer. Despite their importance and frequent use of submerged aquatic vegetation (SAV) habitats, critical information is lacking on the specific characteristics of SAV that influence habitat occupancy. Using the SAV species Vallisneria americana and Potamogeton illinoensis, which are native to the southeast USA, and the invasive SAV Hydrilla verticillata, we conducted seven different habitat choice experiments to examine hatchery-raised, age-0 M. floridanus habitat use of different SAV populations (i.e., hydrologically isolated collection sources of varied physical characteristics), population diversity (i.e., increased richness of genotypically and phenotypically variable SAV), species, and species diversity (i.e., increased species richness). Fish spent more time in taller, larger V. americana but did not seem to favor any particular P. illinoensis population, SAV species, or species diversity tested. Additionally, fish spent more time in increased V. americana population diversity when the populations used were randomized, but fish spent more time in decreased population diversity when their favored V. americana population was used in all choices. This research adds additional nuance to our understanding of optimal vegetation for fish habitat use and is informative for future SAV plantings and invasive SAV management aimed at maximizing fish habitat and restoring recreational fisheries.
In the Northern Rockies of the United States, predators like wolves (Canis lupus) and mountain lions (Puma concolor) have been implicated in fluctuations or declines in populations of game species like elk (Cervus canadensis) and mule deer (Odocoileus hemionus). In particular, local distributions of these predators may affect ungulate behavior, use of space, and dynamics. Our goal was to develop generalizable predictions of habitat selection by wolves and mountain lions across western Montana. We hypothesized both predator species would select habitat that maximized their chances of encountering and killing ungulates and that minimized their chances of encountering humans. We assessed habitat selection by these predators during summer using within-home range (3rd order) resource selection functions (RSFs) in multiple study areas throughout western Montana, and tested how generalizable RSF predictions were by applying them to out-of-sample telemetry data from separate study areas. Selection for vegetation cover-types varied substantially among wolves in different study areas. Nonetheless, our predictions of 3rd order selection by wolves were highly generalizable across different study areas. Wolves consistently selected simple topography where ungulate prey may be more susceptible to their cursorial hunting mode. Topographic features may serve as better proxies of predation risk by wolves than vegetation cover-types. Predictions of mountain lion distribution were less generalizable. Use of rugged terrain by mountain lions varied across ecosystem-types, likely because mountain lions targeted the habitats of different prey species in each study area. Our findings suggest that features that facilitate the hunting mode of a predator (i.e. simple topography for cursorial predators and hiding cover for stalking predators) may be more generalizable predictors of their habitat selection than features associated with local prey densities.
The management of North American waterfowl is predicated on long-term, continental scale banding implemented prior to the hunting season (i.e., July–September) and subsequent reporting of bands recovered by hunters. However, single-season banding and encounter operations have a number of characteristics that limit their application to estimating demographic rates and evaluating hypothesized limiting factors throughout the annual cycle. We designed and implemented a 2-season banding program for American black ducks (Anas rubripes), mallards (A. platyrhynchos), and hybrids in eastern North America to evaluate potential application to annual life cycle conservation and sport harvest management. We assessed model fit and compared estimates of annual survival among data types (i.e., pre-hunting season only [July–September], post-hunting season only [January–March], and 2-season [pre- and post-hunting season]) to evaluate model assumptions and potential application to population modeling and management. There was generally high agreement between estimates of annual survival derived using 2-season and pre-season only data for all age and sex cohorts. Estimates of annual survival derived from post-season banding data only were consistently higher for adult females and juveniles of both sexes. We found patterns of seasonal survival varied by species, age, and to a lesser extent, sex. Hunter recovered birds exhibited similar spatial distributions regardless of banding season suggesting banded samples were from the same population. In contrast, Goodness-Of-Fit tests suggest this assumption was statistically violated in some regions and years. We conclude that estimates of seasonal and annual survival for black ducks and mallards based on the 2-season banding program are valid and accurate based on model fit statistics, similarity in survival estimates across data and models, and similarities in the distribution of recoveries. The 2-season program provides greater precision and insight into the survival process and will improve the ability of researchers and managers to test competing hypotheses regarding population regulation resulting in more effective management.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2425","usgsCitation":"Devers, P.K., Emmet, R., Boomer, G.S., Zimmerman, G.S., and Royle, J., 2021, Evaluation of a two-season banding program to estimate and model migratory bird survival: Ecological Applications, v. 31, no. 7, e02425, 18 p., https://doi.org/10.1002/eap.2425.","productDescription":"e02425, 18 p.","ipdsId":"IP-127019","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":387503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Devers, Patrick K.","contributorId":261406,"corporation":false,"usgs":false,"family":"Devers","given":"Patrick","email":"","middleInitial":"K.","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":false,"id":819981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Emmet, Robert L.","contributorId":261407,"corporation":false,"usgs":false,"family":"Emmet","given":"Robert L.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":819982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boomer, G. Scott 0000-0001-5854-3604","orcid":"https://orcid.org/0000-0001-5854-3604","contributorId":261408,"corporation":false,"usgs":false,"family":"Boomer","given":"G.","email":"","middleInitial":"Scott","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":true,"id":819983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmerman, Guthrie S.","contributorId":261410,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":false,"id":819984,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":3504,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819985,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226499,"text":"70226499 - 2021 - Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management","interactions":[],"lastModifiedDate":"2021-11-22T13:10:05.542882","indexId":"70226499","displayToPublicDate":"2021-07-22T07:04:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management","docAbstract":"Vegetation phenology—the seasonal timing and duration of vegetative phases—is controlled by spatiotemporally variable contributions of climatic and environmental factors plus additional potential influence from human management. We used land surface phenology derived from the Advanced Very High Resolution Radiometer and climate data to examine variability in vegetation productivity and phenological dates from 1989 to 2014 in the U.S. Northwestern Plains, a region with notable spatial heterogeneity in climate, vegetation, and land use. We first analyzed interannual trends in six phenological measures as a baseline. We then demonstrated how including annual-resolution predictors can provide more nuanced insights into measures of phenology between plant communities and across the ecoregion. Across the study area, higher annual precipitation increased both peak and season-long productivity. In contrast, higher mean annual temperatures tended to increase peak productivity but for the majority of the study area decreased season-long productivity. Annual precipitation and temperature had strong explanatory power for productivity-related phenology measures but predicted date-based measures poorly. We found that relationships between climate and phenology varied across the region and among plant communities and that factors such as recovery from disturbance and anthropogenic management also contributed in certain regions. In sum, phenological measures did not respond ubiquitously nor covary in their responses. Nonclimatic dynamics can decouple phenology from climate; therefore, analyses including only interannual trends should not assume climate alone drives patterns. For example, models of areas exhibiting greening or browning should account for climate, anthropogenic influence, and natural disturbances. Investigating multiple aspects of phenology to describe growing-season dynamics provides a richer understanding of spatiotemporal patterns that can be used for predicting ecosystem responses to future climates and land-use change. Such understanding allows for clearer interpretation of results for conservation, wildlife, and land management.
As agriculture expands to meet the needs of a growing global population, natural ecosystems are threatened by deforestation and habitat fragmentation. Tropical agroforestry systems offer a sustainable alternative to traditional agriculture by providing food for production while also supporting biodiversity and ecosystem services. Previous studies have shown that these systems may even improve crop pollination, but the mechanisms of how these improvements occur are still poorly understood. Using coffee as a focal crop, we explored how microclimatic conditions affected nectar traits (sugar and caffeine concentration) important for pollinator visitation. We also studied how microclimate, floral traits, floral availability at the coffee plant level, availability of floral resources provided by other plant species in the agroecosystem (neighborhood floral availability), and the presence of other bees affected the amount of time bees spent foraging on coffee flowers and the proportion of coffee pollen carried on their bodies. We explored these factors using the two dominant coffee species farmed on Puerto Rico, Coffea canephora and C. arabica, under sun and shade management. We found that high nectar sugar concentration and temperature were important predictors of short floral visits (<15 seconds), while increased number of bees and open coffee flowers were important predictors of longer floral visits (16-180 seconds). High nectar caffeine concentration was an important predictor of longer visits on C. arabica flowers while the opposite was observed for C. canephora flowers. For both species, high coffee floral availability was the main predicting factor for the proportion of coffee pollen on the bees bodies. Surprisingly, neither neighborhood floral availability nor the type of coffee plantation (agroforest/shade or sun) were important predictors of bee visitation. These results suggest non-coffee flowering plants in coffee plantations were neither competitors nor facilitators of coffee plantes for pollinators. Additionally, most of the bees surveyed were carrying 80% pollen from one species (C. arabica or C. canephora), likely resulting in little heterospecific pollen deposition between Coffea and non-Coffea flowers. Shade trees in coffee plantations do not detract from pollinator visitation to coffee flowers, suggesting that the provision of multiple ecological and wildlife conservation benefits by shade trees is not in conflict with a growers ability to maximize the benefits of insect pollination on fruit production.
","language":"English","doi":"10.1016/j.agee.2020.107196","usgsCitation":"Prado, S., Collazo, J.A., Marand, M., and Irwin, R., 2021, The influence of floral resources and microclimate on pollinator visitation in an agro-ecosystem: Agriculture, Ecosystems and Environment, v. 307, 107196, 9 p., https://doi.org/10.1016/j.agee.2020.107196.","productDescription":"107196, 9 p.","ipdsId":"IP-116109","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":451449,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agee.2020.107196","text":"Publisher Index Page"},{"id":395866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Adjuntas Lares,Las Marias, Maricao, Puerto Rico Utuado","volume":"307","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Prado, S.G.","contributorId":242938,"corporation":false,"usgs":false,"family":"Prado","given":"S.G.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":834360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collazo, Jaime A. 0000-0002-1816-7744","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":217287,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marand, M.H.","contributorId":275849,"corporation":false,"usgs":false,"family":"Marand","given":"M.H.","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":834362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irwin, R.E.","contributorId":242940,"corporation":false,"usgs":false,"family":"Irwin","given":"R.E.","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":834363,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":58027,"text":"ofr20041348 - 2021 - Hazard analysis of landslides triggered by Typhoon Chata’an on July 2, 2002, in Chuuk State, Federated States of Micronesia","interactions":[],"lastModifiedDate":"2025-01-29T20:22:29.930774","indexId":"ofr20041348","displayToPublicDate":"2021-07-21T12:00:00","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":"2004-1348","displayTitle":"Hazard Analysis of Landslides Triggered by Typhoon Chata’an on July 2, 2002, in Chuuk State, Federated States of Micronesia","title":"Hazard analysis of landslides triggered by Typhoon Chata’an on July 2, 2002, in Chuuk State, Federated States of Micronesia","docAbstract":"More than 250 landslides were triggered across the eastern volcanic islands of Chuuk State in the Federated States of Micronesia by torrential rainfall from tropical storm Chata’an on July 2, 2002. Landslides triggered during nearly 20 inches of rainfall in less than 24 hours caused 43 fatalities and the destruction or damage of 231 structures, including homes, schools, community centers, and medical dispensaries. Landslides also buried roads, crops, and water supplies. The landslides ranged in volume from a few cubic meters to more than 1 million cubic meters. Most of the failures began as slumps and transformed into debris flows, some of which traveled several hundred meters across coastal flatlands into populated areas. A landslide-inventory map produced after the storm shows that the island of Tonoas had the largest area affected by landslides, although the islands of Weno, Fefan, Etten, Uman, Siis, Udot, Eot, and Fanapanges also had significant landslides. Based on observations since the storm, we estimate the continuing hazard from landslides triggered by Chata’an to be relatively low. However, tropical storms and typhoons similar to Chata’an frequently develop in Micronesia and are likely to affect the islands of Chuuk in the future.
To assess the landslide hazard from future tropical storms, we produced a hazard map that identifies landslide-source areas of high, moderate, and low hazard. This map can be used to identify relatively safe areas for relocating structures or establishing areas where people could gather for shelter in relative safety during future typhoons or tropical storms similar to Chata’an.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20041348","productDescription":"Report: 22 p.; 2 Plates: 35.71 x 40.02 inches","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":387302,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2004/1348/ofr20041348_plate1_Revision.pdf","text":"Plate 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2004-1348 Plate 1","linkHelpText":"Landslide Inventory Map of Chuuk Islands Affected by Typhoon Chata'an"},{"id":182255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2004/1348/coverthb.jpg"},{"id":387301,"rank":2,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2004/1348/versionHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2004-1348 version history"},{"id":387300,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2004/1348/ofr20041348_pamphlet_Revision.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2004-1348 Pamphlet"},{"id":387303,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2004/1348/ofr20041348_plate2_Revision.pdf","text":"Plate 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2004-1348 Plate 2","linkHelpText":"Debris-Flow Hazard Map of Chuuk Islands Affected by Typhoon Chata’an"},{"id":391875,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_69259.htm"}],"country":"Federated States of Micronesia","state":"Chuuk State","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 151.675,\n 7.2789\n ],\n [\n 151.9022,\n 7.2789\n ],\n [\n 151.9022,\n 7.4689\n ],\n [\n 151.675,\n 7.4689\n ],\n [\n 151.675,\n 7.2789\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: July 21, 2021","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
Autumn and winter Santa Ana wind (SAW)–driven wildfires play a substantial role in area burned and societal losses in southern California. Temperature during the event and antecedent precipitation in the week or month prior play a minor role in determining area burned. Burning is dependent on wind intensity and number of human-ignited fires. Over 75% of all SAW events generate no fires; rather, fires during a SAW event are dependent on a fire being ignited. Models explained 40 to 50% of area burned, with number of ignitions being the strongest variable. One hundred percent of SAW fires were human caused, and in the past decade, powerline failures have been the dominant cause. Future fire losses can be reduced by greater emphasis on maintenance of utility lines and attention to planning urban growth in ways that reduce the potential for powerline ignitions.
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David W","contributorId":261327,"corporation":false,"usgs":false,"family":"Pierce","given":"David","email":"","middleInitial":"W","affiliations":[{"id":52819,"text":"Climate, Atmospheric Science and Physical Oceanography Division, Scripps Institution of Oceanography, University of California, San Diego, San Diego, CA 92093, USA","active":true,"usgs":false}],"preferred":false,"id":819772,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flannigan, Michael","contributorId":261328,"corporation":false,"usgs":false,"family":"Flannigan","given":"Michael","affiliations":[{"id":52822,"text":"Department of Renewable Resources, University of Alberta, Edmonton, Alberta T6G 2H1, Canada","active":true,"usgs":false}],"preferred":false,"id":819773,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brown, Tim J","contributorId":261329,"corporation":false,"usgs":false,"family":"Brown","given":"Tim","email":"","middleInitial":"J","affiliations":[{"id":52823,"text":"Western Regional Climate Center, Desert Research Institute, Reno, NV 89512, USA","active":true,"usgs":false}],"preferred":false,"id":819774,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223466,"text":"70223466 - 2021 - Bomb-produced radiocarbon across the South Pacific Gyre — A new record from American Samoa with utility for fisheries science","interactions":[],"lastModifiedDate":"2022-01-25T16:47:04.317084","indexId":"70223466","displayToPublicDate":"2021-07-21T09:10:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3225,"text":"Radiocarbon","active":true,"publicationSubtype":{"id":10}},"title":"Bomb-produced radiocarbon across the South Pacific Gyre — A new record from American Samoa with utility for fisheries science","docAbstract":"Coral skeletal structures can provide a robust record of nuclear bomb produced 14C with valuable insight into air-sea exchange processes and water movement with applications to fisheries science. To expand these records in the South Pacific, a coral core from Tutuila Island, American Samoa was dated with density band counting covering a 59-yr period (1953–2012). Seasonal signals in elemental ratios (Sr/Ca and Ba/Ca) and stable carbon (δ13C) values across the coral core corroborated the well-defined annual band structure and highlighted an ocean climate shift from the 1997–1998 El Niño. The American Samoa coral 14C measurements were consistent with other regional records but included some notable differences across the South Pacific Gyre (SPG) at Fiji, Rarotonga, and Easter Island that can be attributed to decadal ocean climate cycles, surface residence times and proximity to the South Equatorial Current. An analysis of the post-peak 14C decline associated with each coral record indicated 14C levels are beginning to merge for the SPG. This observation, coupled with otolith measurements from American Samoa, reinforces the perspective that bomb 14C dating can be performed on fishes and other marine organisms of the region using the post-peak 14C decline to properly inform fisheries management in the South Pacific.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/RDC.2021.51","usgsCitation":"Andrews, A., Prouty, N.G., and Cheriton, O.M., 2021, Bomb-produced radiocarbon across the South Pacific Gyre — A new record from American Samoa with utility for fisheries science: Radiocarbon, v. 63, no. 6, p. 1591-1605, https://doi.org/10.1017/RDC.2021.51.","productDescription":"15 p.","startPage":"1591","endPage":"1605","ipdsId":"IP-124813","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":436266,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DTWC3I","text":"USGS data release","linkHelpText":"Geochemistry time series and growth parameters from Tutuila, American Samoa coral record (ver. 2.0, June 2021)"},{"id":388583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"South Pacific Gyre","volume":"63","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Andrews, Allen","contributorId":152569,"corporation":false,"usgs":false,"family":"Andrews","given":"Allen","email":"","affiliations":[],"preferred":false,"id":822102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":822103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":822104,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}