Understanding the role that an environmental prion reservoir plays in the outbreak dynamics of chronic wasting disease (CWD) in free ranging white-tailed deer (Odocoileus virginianus) is critical for the allocation of disease surveillance resources by state and provincial wildlife agencies. We hypothesized that demographic, ecological, and epidemiological configurations naturally attenuate epidemic risk despite the introduction of infectious prions into a susceptible population of deer, but the magnitude of infectious prions in the environmental prion reservoir complicate outbreak expectations. We developed a Susceptible-Latent-Exposed-Infective (SLEI) compartment model to represent the dynamics of CWD epidemics in free-ranging white-tailed deer, then used the basic reproductive ratio (
In oil spill research, a topic of increasing attention during the last decade has been the environmental impact of the partial oxidation products that result from transformation of the petroleum in freshwater, marine, and terrestrial ecosystems. This report describes the isolation and characterization of the partial oxidation products from crude oil contaminating groundwater at the long-term U.S. Geological Survey Bemidji research site in Minnesota. As the result of a pipeline burst in August 1979, a body of light aliphatic crude oil is present from the land surface to 2 meters below the water table in a shallow sand and gravel aquifer in a remote area outside Bemidji, Minnesota, United States. Biodegradation has resulted in the formation of a plume of dissolved organic carbon (DOC) downgradient from the oil body. Groundwater has also been contaminated in an area known as the spray zone, from vertical infiltration of DOC resulting from biodegradation of oil in the soil column, and possibly from photooxidation of oil at the soil surface. The majority of DOC in the contaminated groundwater is in the form of nonvolatile organic acids (NVOAs) which represent the partial oxidation products of the crude oil constituents. The NVOAs have been classified into three fractions according to their isolation on XAD resins: hydrophobic neutrals (HPON), hydrophobic acids (HPOA), and hydrophilic acids (HPIA). These fractions of NVOAs were isolated from wells downgradient from the oil body (sampling well numbers 533, 532, 530, 515), in the spray zone (603), and from an uncontaminated well upgradient of the oil body (310) between the years 1986 and 1989, and again from wells 530 and 603 in 1998. The samples have been characterized by elemental analysis, radiocarbon dating, carbon-13 nuclear magnetic resonance spectroscopy (13C NMR), and negative-mode (-) electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FTICR-MS), with a particular focus on fractions from wells 310, 530, and 603.
All the characterization data indicate that the NVOAs from contaminated wells are distinguishable from the background DOC. Carbon-14 (14C) ages of NVOAs from contaminated wells ranged from 3,615 to 18,985 years before the present, whereas the background DOC from the aquifer was post-bomb (post 1950). By elemental analysis, NVOAs from contaminated wells had higher sulfur but lower nitrogen contents than the background. By electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry, number average molecular weights determined from assigned molecular formulas ranged from 416 to 486 daltons for the HPOA and HPIA fractions from both background and contaminant wells. NVOAs from contaminated wells had significantly greater numbers of assigned molecular formulas containing sulfur, with elevated concentrations of the S1O4-10 species in particular. Compared to the background, HPOA and HPIA fractions from contaminant wells had a broader range of double bond equivalents (DBEs) within On compound classes (n is number of atoms). Additionally, within On compound classes, contaminant well HPOA fractions had a greater abundance of lower n (less than eight) than the background. Contaminant well double bond equivalents versus carbon number (C#) plots of oxygen compound classes suggest oil-derived aliphatic compounds in the range from C12 to C22 in HPOA and HPIA fractions and oil-derived compounds containing aromatic or saturated rings in the approximate range from C20 to C30 are present in HPOA fractions.
The data suggest the NVOAs originate from biodegradation of several classes of C12 and greater crude oil constituents: sulfur-containing constituents, including possibly the resins and asphaltenes; constituents containing aromatic rings substituted with methyl groups, including alkylaromatic and naph-
thenoaromatic compounds, and C12 to C22 alkyl constituents. The overall similarities of the carbon-13 nuclear magnetic resonance spectra for the well 603 and 530 samples from the two sampling dates suggest that a steady state in the composition of the partial oxidation products in each of the two wells had been reached between 1986–1989 and 1998.
Chief, USGS National Water Quality Laboratory
U.S. Geological Survey
Box 25585, Mail Stop 407
Denver, CO 80225-0585
Traditional methods to assess the probability of storm-induced erosion and flooding from extreme water levels have limited use along the U.S. West Coast where swell dominates erosion and storm surge is limited. This effort presents methodology to assess the probability of erosion and flooding for the U.S. West Coast from extreme total water levels (TWLs), but the approach is applicable to coastal settings worldwide. TWLs were derived from 61 years of wave and water level data at shore-perpendicular transects every 100-m along open coast shorelines. At each location, wave data from the Global Ocean Waves model were downscaled to the nearshore and used to empirically calculate wave run-up. Tides were simulated using the Oregon State University’s tidal data inversion model and non-tidal residuals were calculated from sea-surface temperature and pressure anomalies. Wave run-up was combined with still water levels to generate hourly TWL estimates and extreme TWLs for multiple return periods. Extremes were compared to onshore morphology to determine erosion hazards and define the probability of collision, overwash, and inundation.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41597-022-01313-6","usgsCitation":"Shope, J.B., Erikson, L.H., Barnard, P.L., Storlazzi, C.D., Serafin, K.A., Doran, K., Stockdon, H.F., Reguero, B.G., Mendez, F.J., Castanedo, S., Cid, A., Cagigal, L., and Ruggiero, P., 2022, Characterizing storm-induced coastal change hazards along the United States West Coast: Nature--Scientific Data, v. 9, 224, 20 p., https://doi.org/10.1038/s41597-022-01313-6.","productDescription":"224, 20 p.","ipdsId":"IP-122757","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":447347,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-022-01313-6","text":"Publisher Index Page"},{"id":435798,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LBJEY1","text":"USGS data release","linkHelpText":"Chesapeake Bay Nontidal Network 1985 - 2018: Daily High-Flow and Low-Flow Concentration and Load Estimates"},{"id":402101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"West Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.24609374999999,\n 32.69486597787505\n ],\n [\n -116.3671875,\n 33.284619968887675\n ],\n [\n -120.234375,\n 36.4566360115962\n ],\n [\n -122.6953125,\n 41.77131167976407\n ],\n [\n -122.51953124999999,\n 48.22467264956519\n ],\n [\n -125.5078125,\n 48.45835188280866\n ],\n [\n -125.15625000000001,\n 44.213709909702054\n ],\n [\n -126.03515625,\n 40.84706035607122\n ],\n [\n -123.74999999999999,\n 37.579412513438385\n ],\n [\n -120.41015624999999,\n 32.99023555965106\n ],\n [\n -117.24609374999999,\n 32.69486597787505\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2022-05-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Shope, James B.","contributorId":135949,"corporation":false,"usgs":false,"family":"Shope","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":10653,"text":"University of California at Santa Cruz, Earth and Planetary Science Department","active":true,"usgs":false}],"preferred":false,"id":844586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":844587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick 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A.","contributorId":292447,"corporation":false,"usgs":false,"family":"Serafin","given":"Katherine","email":"","middleInitial":"A.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":844590,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doran, Kara S. 0000-0001-8050-5727","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":292448,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":844591,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":292449,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science 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Sonia","contributorId":292450,"corporation":false,"usgs":false,"family":"Castanedo","given":"Sonia","email":"","affiliations":[{"id":41638,"text":"University of Cantabria","active":true,"usgs":false}],"preferred":false,"id":844595,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cid, Alba","contributorId":292451,"corporation":false,"usgs":false,"family":"Cid","given":"Alba","email":"","affiliations":[{"id":41638,"text":"University of Cantabria","active":true,"usgs":false}],"preferred":false,"id":844596,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cagigal, Laura","contributorId":264473,"corporation":false,"usgs":false,"family":"Cagigal","given":"Laura","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":844597,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ruggiero, Peter","contributorId":15709,"corporation":false,"usgs":false,"family":"Ruggiero","given":"Peter","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":844598,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70232271,"text":"sir20225049 - 2022 - Revisions to the Virginia Coastal Plain hydrogeologic framework southwest of the James River","interactions":[],"lastModifiedDate":"2026-04-09T17:54:31.905597","indexId":"sir20225049","displayToPublicDate":"2022-06-23T08:00:00","publicationYear":"2022","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":"2022-5049","displayTitle":"Revisions to the Virginia Coastal Plain Hydrogeologic Framework Southwest of the James River","title":"Revisions to the Virginia Coastal Plain hydrogeologic framework southwest of the James River","docAbstract":"New drilling information reveals that altitudes of some hydrogeologic units of the Virginia Coastal Plain aquifer system differ by as much as 50 feet (ft) from those previously known, namely the Aquia and Potomac aquifers, the Potomac confining zone, and the Nanjemoy-Marlboro and Saint Marys confining units. In addition, the lateral margins of some hydrogeologic units are located as much as several miles from previously estimated locations. The largest revisions to unit margins were for the Aquia aquifer and the Nanjemoy-Marlboro and Saint Marys confining units. Interpretation of new geophysical logs, sediment core, and cuttings as well as revised interpretations to existing data indicate channels and embayments are also preserved on eroded top surfaces of the shallowest hydrogeologic units including the Yorktown confining zone, Yorktown-Eastover aquifer, Saint Marys confining unit, Potomac confining zone, and Potomac aquifer.
Enhanced details on the configuration of part of the aquifer system southwest of the James River are provided by sediment cores and cuttings as well as geophysical logs from 36 recently drilled boreholes. These, along with reinterpretation of data from 93 preexisting boreholes, form the basis for revised top-surface altitudes and margins of hydrogeologic units beneath parts of Prince George, Surry, Sussex, Isle of Wight, and Southampton Counties and the cities of Franklin and Suffolk.
Groundwater withdrawals in the Virginia Coastal Plain cause widespread water-level declines, create the potential for saltwater intrusion, and contribute to regionwide land subsidence. A description of the aquifer system, termed a hydrogeologic framework, was developed by the U.S. Geological Survey in 2006 and provides information needed to base withdrawal-permitting decisions by the Virginia Department of Environmental Quality. This revision of part of the hydrogeologic framework southwest of the James River is based on interpretations of both new and previously analyzed borehole data. The revision is strictly confined to the study area extent and hydrogeologic units not found within the study area were not revised and are not discussed in this report. The newly determined hydrogeologic-unit altitudes and margins have implications for groundwater-withdrawal permitting. New interpretations have found that the Yorktown Eastover aquifer is absent in the southwestern part of the City of Suffolk, owing to what is most likely an isolated area of sediment-texture facies change. Most notably, the top-surface altitudes of the Aquia and Potomac aquifers have been lowered by as much as 50 ft from previous interpretations. This means that wells previously believed to be screened in the top of the Potomac aquifer could, based on these new interpretations, be screened in the bottom of the Aquia aquifer. These changes to aquifers in which wells are screened means that there is potentially more room in the groundwater withdrawal permitting for the Potomac aquifer, the largest and most productive aquifer in Virginia, and overpumping occurring in the Aquia aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225049","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"Caldwell, S.H., and McFarland, E.R., 2022, Revisions to the Virginia Coastal Plain hydrogeologic framework southwest of the James River: U.S. Geological Survey Scientific Investigations Report 2022–5049, 24 p., https://doi.org/10.3133/sir20225049.","productDescription":"Report: vii, 24 p.; Data Release","numberOfPages":"24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-134149","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":402411,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5049/images/"},{"id":402409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5049/sir20225049.pdf","text":"Report","size":"3.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5049"},{"id":402412,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5049/sir20225049.XML"},{"id":402408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5049/coverthb.jpg"},{"id":402452,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225049/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5049"},{"id":402410,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91XJ640","text":"USGS data release","linkHelpText":"Shapefiles of hydrogeologic unit extents and top-surface altitude contours used in the revised hydrogeologic framework for the Virginia Coastal Plain Southwest of the James River"},{"id":502404,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113194.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.4151611328125,\n 36.56039393337068\n ],\n [\n -76.63787841796875,\n 36.56039393337068\n ],\n [\n -76.63787841796875,\n 37.199706196161735\n ],\n [\n -77.4151611328125,\n 37.199706196161735\n ],\n [\n -77.4151611328125,\n 36.56039393337068\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
The hydrogeology on and near Cannon Air Force Base (AFB) in eastern New Mexico was assessed to gain a better understanding of preferential groundwater flow paths through paleochannels. In and near the study area, paleochannels incised the top surface of the Dockum Group (Chinle Formation) and were subsequently filled in with electrically resistive coarse-grained sediments of the overlying Ogallala Formation, resulting in a preferential groundwater flow path in the form of a paleochannel network. A better understanding of the spatial characteristics of this preferential groundwater flow path is needed to support ongoing efforts to remediate groundwater contamination at Cannon AFB. Therefore, the U.S. Geological Survey, in cooperation with the U.S. Air Force Civil Engineer Center, used surface geophysical resistivity methods and data compiled from previous studies to better understand the spatial distribution and characteristics of the paleochannel network incised into the top of the Dockum Group.
Previous studies have shown these paleochannels incised into the top of the Dockum Group with increasing resolution, but limited borehole data on and near Cannon AFB continued to make accurately mapping the top of Dockum Group challenging. For this study, surface geophysical resistivity measurements in the form of time-domain electromagnetic soundings made by the U.S. Geological Survey were used in conjunction with data previously published by Architecture, Engineering, Construction, Operations, and Management and borehole data compiled from the New Mexico Water Rights Reporting System database to prepare an updated map of the top of the Dockum Group that includes the location and characteristics of paleochannels incised into the top of the Dockum Group (Chinle Formation). A total of 149 borehole picks (determinations of the tops and bases of geologic units and their hydrogeologic-unit equivalents) were obtained from previous studies, along with 72 additional borehole picks from the New Mexico Water Rights Reporting System database and 43 picks from newly collected time-domain electromagnetic soundings. The data were gridded and contoured using Oasis Montaj v. 9.8.1.
The updated map of the top of Dockum Group has many areas of uncertainty greater than 20 feet, because there are not enough data for the gridding process to reliably determine a value. However, this interpretation of the altitude of the top of the Dockum Group represents a substantial improvement in data resolution compared to previous studies.
Two methodologies were used to evaluate paleochannels incised in the top of the Dockum Group across the study area: (1) trend-removal grid analysis and (2) analysis with Esri’s ArcMap Hydrology toolset. These two paleochannel analysis techniques show groundwater flow direction as well as areas having the deepest saturated thickness. Hydrologically, these techniques show where aquifer storage is highest (in the deepest parts of the paleochannel network), as well as the spatial distribution of preferential groundwater flow paths (the paleochannels). The analyses indicate a large paleochannel trending to the southeast, with smaller channels feeding in from the west. Areas where groundwater management could be more beneficial are indicated by locations where these flow lines intersect the deeper parts of the paleochannel.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225050","collaboration":"Prepared in cooperation with the Air Force Civil Engineer Center","usgsCitation":"Payne, J.D., Teeple, A.P., McDowell, J., Wallace, D., and Hancock, W.A., 2022, Mapping the altitude of the top of the Dockum Group and paleochannel analysis using surface geophysical methods on and near Cannon Air Force Base in Curry County, New Mexico, 2020: U.S. Geological Survey Scientific Investigations Report 2022–5050, 21 p., https://doi.org/10.3133/sir20225050.","productDescription":"Report: iv, 21 p.; 2 Data Releases; Dataset","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-125577","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":402443,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P6KWR5","text":"USGS data release","linkHelpText":"Surface geophysical data used for mapping the top of the Dockum Group on Cannon Air Force Base in Curry County, New Mexico, 2020"},{"id":402444,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/543e6b86e4b0fd76af69cf4c","text":"USGS data release","linkHelpText":"1 meter digital elevation models (DEMs)—USGS National Map 3DEP downloadable data collection"},{"id":402440,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5050/sir20225050.XML"},{"id":402439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5050/sir20225050.pdf","text":"Report","size":"1.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5050"},{"id":402438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5050/coverthb.jpg"},{"id":402462,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225050/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402442,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://nmwrrs.ose.state.nm.us/nmwrrs/wellSurfaceDiversion.html","text":"New Mexico Office of the State Engineer online database","linkHelpText":"—New Mexico Water Rights Reporting System"},{"id":402441,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5050/images"},{"id":502405,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113200.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Mexico","county":"Curry County","otherGeospatial":"Cannon Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.375,\n 34.333\n ],\n [\n -103.25,\n 34.333\n ],\n [\n -103.25,\n 34.458333\n ],\n [\n -103.375,\n 34.458333\n ],\n [\n -103.375,\n 34.333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
The Community for Data Integration is a community of practice whose purpose is to advance the data integration capabilities of the U.S. Geological Survey. In fiscal year 2020, the Community for Data Integration held 11 monthly forums, facilitated 13 collaboration areas, and supported 13 projects. The activities supported the broad U.S. Geological Survey priority of producing building blocks for doing integrated predictive science. Specifically, the activities supported tools and methods for findable, accessible, interoperable, and reusable (FAIR) data and wildland fire and water prediction. Through these efforts, community members were informed of new and emerging technologies and data topics that helped them accomplish their professional responsibilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20221034","usgsCitation":"Hsu, L., Liford, A.N., and Donovan, G.C., 2022, Community for data integration 2020 annual report: U.S. Geological\nSurvey Open-File Report 2022–1034, 16 p., https://doi.org/10.3133/ofr20221034.","productDescription":"iii, 16 p.","onlineOnly":"Y","ipdsId":"IP-133268","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":402432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1034/coverthb.jpg"},{"id":402433,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1034/ofr20221034.pdf","text":"Report","size":"1.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1034"},{"id":402434,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1034/images"},{"id":402435,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1034/ofr20221034.xml"}],"contact":"Director, Science Analytics and Synthesis
U.S. Geological Survey
P.O. Box 25046, Mail Stop 302
Denver, CO 80225
The U.S. Geological Survey, in cooperation with the Montana Department of Transportation, installed cameras and large-scale particle image velocimetry (LSPIV) recording equipment at four sites where the U.S. Geological Survey and Montana Department of Transportation are monitoring bridge scour using other methods. Determination of stream velocities is an important component of hydraulic engineering, river ecology, and fluvial geomorphology. LSPIV is an emerging technique that can be used to estimate stream surface velocities and streamflow using video cameras. Video from the camera is referenced to known locations on streambanks, and postprocessed using computer software that calculates water surface velocity and flow direction between video frames.
The goal of the study was to determine if LSPIV can increase the accuracy of current bridge scour prediction methods using video recordings from 2019 to 2021. Scour around piers is one of the primary failure mechanisms for bridges and poses threats to public safety and interstate commerce. LSPIV installations can capture the flow velocities and directions near bridge piers where other measurement methods might fail or be too dangerous. Additional benefits to the LSPIV technique were continuous data collection throughout the hydrologic cycle and enhanced safety of the methods for estimating velocity magnitude and direction during flood events. Limitations of the LSPIV technique included the angle of the camera to incoming flow; video recordings that were not usable because of ice cover, night, or high winds; and vegetation along the streambank that interfered with water flow analysis. Future applications of the LSPIV technique may continue to improve the processing of the video and reduce limitations for this process.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223040","usgsCitation":"Armstrong, D.W., Holnbeck, S.R., and Chase, K.J., 2022, Evaluating the use of video cameras to estimate bridge scour potential at four bridges in southwestern Montana: U.S. Geological Survey Fact Sheet 2022–3040, 2 p., https://doi.org/10.3133/fs20223040.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-137820","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":402153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3040/coverthb.jpg"},{"id":402154,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3040/fs20223040.pdf","text":"Report","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3040"},{"id":402155,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3040/fs20223040.XML"},{"id":402156,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3040/images"},{"id":402157,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20223040/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":501493,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113199.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5,\n 45\n ],\n [\n -110.5,\n 45\n ],\n [\n -110.5,\n 46\n ],\n [\n -112.5,\n 46\n ],\n [\n -112.5,\n 45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
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Mauka-to-makai (mountain to sea in the Hawaiian language) hydrologic connectivity – commonly referred to as ridge-to-reef – directly affects biogeochemical processes and socioecological functions across terrestrial, freshwater, and marine systems. The supply of freshwater to estuarine and nearshore environments in a ridge-to-reef system supports the food, water, and habitats utilized by marine fauna. In addition, the ecosystem services derived from this land-to-sea connectivity support social and cultural practices (hereafter referred to as socio-cultural) including fishing, aquaculture, wetland agriculture, religious ceremonies, and recreational activities. To effectively guide island resource management, a better understanding of the linkages from ridge-to-reef across natural and social usages is critical, particularly in the context of climate change, with anticipated increasing temperature and shifting precipitation patterns. The objective of this study was to identify spatial linkages that promote multiple and diverse uses, following the ridge-to-reef concept, at an island-wide scale to identify regions of high conservation importance for aquatic resources. We selected the Island of Maui as a study representative of many Pacific islands. Diverse datasets, including agricultural lands within watersheds, wetland locations, presence of stream species, indicators of freshwater input from streams, coral cover, nearshore fish biomass, socio-cultural data such as fishpond locations, wetland taro cultivation, beach recreation use, and lastly the dynamically downscaled Coupled Model Intercomparison Project Phase (CMIP5) future climate projections scenarios (Representative Concentration Pathway (RCP) 4.5 & 8.5) were used to examine the spatial linkages through hydrological connectivity from land to the sea. Zonation spatial planning software was used to prioritize areas of high management and conservation value and to help inform aquatic resources management. The resulting prioritized areas included many minimally disturbed watersheds in east Maui and western nearshore and coastal zones that are adjacent to diverse coral reefs. These results are driven by the importance of fish biomass and coral reef distribution as well as traditional wetland taro cultivation and coastal access points for recreation. These results underline the importance of examining ridge-to-reef systems for aquatic resource management and including important social and cultural values in resource management upon planning adaptation strategies for climate change. Improving our understanding of diverse natural and socio-cultural influences on habitat conditions and their values in these areas provides an opportunity to strategically plan future management and conservation actions.
This report assesses the status and trends of selected ecological health indicators of the Upper Mississippi River System (UMRS) based on the data collected and analyzed by the Long Term Resource Monitoring element of the Upper Mississippi River Restoration program, supplemented with data from other sources. This report has four objectives: providing a brief introduction of the UMRS, including its significance, history, modern-day stressors, and recent research; using ecological indicators to describe the status of the river system and where and how it has changed from circa 1993 to 2019; discussing management and restoration implications of these changes; and highlighting the fundamental role of long-term monitoring in the understanding, management, and restoration of large-floodplain rivers.
The data were collected in the six Long Term Resource Monitoring element study reaches that spanned much of the UMRS and the various gradients contained therein. These study reaches included Navigation Pools 4, 8, 13, and 26; the part of the Unimpounded Reach of the Upper Mississippi River between Grand Tower and Cairo, Illinois; and the La Grange Pool on the Illinois River. The indicators included in this report describe the status and trends for the hydrology, geomorphology, floodplain vegetation, water quality, vegetation, and fishes of the UMRS. Many of the indicators of river ecosystem health changed significantly over the nearly 30 years of our evaluation. However, there was substantial spatial variability in the magnitude and timing of those changes among study reaches. Few indicators changed everywhere or nowhere; most indicators changed in some reaches but not others. The quantitative assessments of these indicators describe how the conditions of the river differ across hydrogeomorphic and climate gradients and through time and are intended to support the restoration and management of the UMRS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221039","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","programNote":"Species Management Research Program and Land Management Research Program","usgsCitation":"Houser, J.N., ed., 2022, Ecological status and trends of the Upper Mississippi and Illinois Rivers (ver. 1.1, July 2022): U.S. Geological Survey Open-File Report 2022–1039, 199 p., https://doi.org/10.3133/ofr20221039.","productDescription":"xiv, 199 p.","numberOfPages":"220","onlineOnly":"N","ipdsId":"IP-125605","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":402335,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1039/coverthb2.jpg"},{"id":402336,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1039/ofr20221039.pdf","text":"Report","size":"41.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1039"},{"id":403771,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2022/1039/versionHist.txt","size":"3.11 kB","linkFileType":{"id":2,"text":"txt"}},{"id":501772,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113198.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois, Indiana, Iowa, Minnesota, Missouri, North Dakota, South Dakota, Wisconsin","otherGeospatial":"Illinois River, upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.329833984375,\n 46.172222978455395\n ],\n [\n -90.340576171875,\n 46.30140615437332\n ],\n [\n -92.384033203125,\n 46.49082901981415\n ],\n [\n -93.087158203125,\n 46.74738913515841\n ],\n [\n -93.262939453125,\n 47.42065432071318\n ],\n [\n -94.3505859375,\n 47.76148371616669\n ],\n [\n -95.712890625,\n 47.30903424774781\n ],\n [\n -96.1083984375,\n 46.912750956378915\n ],\n [\n -96.1083984375,\n 46.18743678432541\n ],\n [\n -96.6357421875,\n 45.89000815866184\n ],\n [\n -97.393798828125,\n 45.867062714815475\n ],\n [\n -97.591552734375,\n 45.72152152227954\n ],\n [\n -96.50390625,\n 44.56699093657141\n ],\n [\n -95.43823242187499,\n 43.51668853502906\n ],\n [\n -95.042724609375,\n 42.70665956351041\n ],\n [\n -94.559326171875,\n 41.82045509614034\n ],\n [\n -94.02099609375,\n 41.20345619205131\n ],\n [\n -93.043212890625,\n 39.66491373749128\n ],\n [\n -92.61474609375,\n 39.172658670429946\n ],\n [\n -91.790771484375,\n 38.84826438869913\n ],\n [\n -90.977783203125,\n 38.762650338334154\n ],\n [\n -90.76904296874999,\n 38.736946065676\n ],\n [\n -91.14257812499999,\n 38.35888785866677\n ],\n [\n -91.58203125,\n 37.43997405227057\n ],\n [\n -90.8349609375,\n 36.86204269508728\n ],\n [\n -89.18701171875,\n 37.046408899699564\n ],\n [\n -88.72558593749999,\n 37.87485339352928\n ],\n [\n -88.87939453125,\n 38.685509760012\n ],\n [\n -87.69287109375,\n 40.863679665481676\n ],\n [\n -86.748046875,\n 41.178653972331674\n ],\n [\n -86.781005859375,\n 41.5579215778042\n ],\n [\n -87.593994140625,\n 41.46742831254425\n ],\n [\n -87.86865234374999,\n 42.374778361114195\n ],\n [\n -88.494873046875,\n 43.31718491566705\n ],\n [\n -89.3408203125,\n 43.810747313446996\n ],\n [\n -89.6484375,\n 43.937461690316646\n ],\n [\n -89.40673828125,\n 44.50434127765394\n ],\n [\n -89.329833984375,\n 46.172222978455395\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: June 22, 2022; Version 1.1: July 14, 2022","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
The natal environment can have long-term fitness consequences for individuals, particularly via ‘silver spoon’ or ‘environmental matching’ effects. Invasive species could alter natal effects on native species by changing species interactions, but this potential remains unknown. Using 17 years of data on 2588 individuals across the entire US breeding range of the endangered snail kite (Rostrhamus sociabilis), a wetland raptor that feeds entirely on Pomacea snails, we tested for silver spoon and environmental matching effects on survival and movement and whether the invasion of a non-native snail may alter outcomes. We found support for silver spoon effects, not environmental matching, on survival that operated through body condition at fledging, explained by hydrology in the natal wetland. When non-native snails were present at the natal site, kites were in better condition, individual condition was less sensitive to hydrology, and kites fledged across a wider range of hydrologic conditions, leading to higher survival that persisted for at least 10 years. Movement between wetlands was driven by the current (adult) environment, and birds born in both invaded and uninvaded wetlands preferred to occupy invaded wetlands post-fledging. These results illustrate that species invasions may profoundly impact the role of natal environments on native species.
There are numerous global ocean wave reanalysis and hindcast products currently being distributed and used across different scientific fields. However, there is not a consistent dataset that can sample across all existing products based on a standardized framework. Here, we present and describe the first coordinated multi-product ensemble of present-day global wave fields available to date. This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, includes general and extreme statistics of significant wave height (Hs), mean wave period (Tm) and mean wave direction (θm) computed across 1980–2014, at different frequency resolutions (monthly, seasonally, and annually). This coordinated global ensemble has been derived from fourteen state-of-the-science global wave products obtained from different atmospheric reanalysis forcing and downscaling methods. This data set has been processed, under a specific framework for consistency and quality, following standard Data Reference Syntax, Directory Structures and Metadata specifications. This new comprehensive dataset provides support to future broad-scale analysis of historical wave climatology and variability as well as coastal risk and vulnerability assessments across offshore and coastal engineering applications.
The highest grade Pd-Pt deposit on Earth, the J-M Reef, is hosted in coarse-grained to pegmatoidal cumulates called the Reef Package. Decades of mine development of the J-M Reef have revealed that a distinct discontinuity in rock fabric marks the top of the rock unit that hosts economic-grade sulfide mineralization. Mine geologists refer to this discontinuity as the hanging wall contact. This contact is the top of the Reef Package and is always locatable—either by the change in rock fabric or by distinctive hanging wall textures of silicate minerals—even when the reef sulfide mineralization is absent. This rather subtle textural feature is used reliably by mine geologists to follow the Reef during exploration and mine development. Although some high tenor sulfides (>1000 ppm Pd in 100% sulfide) are found sporadically in the hanging wall cumulates, these accumulations are too small to be economically viable. We present quantitative rock fabric data for four Reef Package and hanging wall intersections collected by electron back-scattered diffraction (EBSD). Plagioclase fabrics in the hanging wall are characterized by low variance in grain sizes and a strong point maximum concentration of (010) and a perpendicular girdle distribution of [100] consistent with an axial B-type fabric. These fabrics are indicative of either compaction of the crystal mush or crystal settling of nucleated crystals, the bulk magma in a chamber. Conversely, the fabrics of the Reef Package show higher variance grain in size distributions and weak to undeveloped preferred orientation of plagioclase crystals that did not undergo significant alignment or textural equilibration of plagioclase grains. The absence of foliation in the Reef Package stands in contrast both to hanging wall fabrics and to other reported EBSD datasets of plagioclase crystals orientations from the Bushveld Complex, the Skaergaard Intrusion, and the Rum Intrusion. Furthermore, plagioclase crystal size distributions for the Reef Package show flatter slopes and convex profiles with fewer crystals at small size fractions indicating the dissolution of small crystals during partial melting and textural coarsening (i.e. Ostwald ripening) and crystal growth. Crystal growth was favored over the nucleation of new crystals during prolonged interaction with a hot infiltrating melt into the resident mush resulting in the coarse-grained textures of the Reef Package cumulates. The hanging wall contact represents a boundary between partially remelted crystal mush of the Reef Package, where sulfide mineralization formed and accumulated, and an overlying essentially barren cumulate pile. The hanging wall cumulates formed following the cessation of footwall erosion and the resumption of crystal accumulation by normal magma chamber processes.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/petrology/egac053","usgsCitation":"Jenkins, M.C., Mungall, J.E., Zientek, M.L., Butak, K., Corson, S.R., Holick, P., McKinley, R., and Lowers, H.A., 2022, The geochemical and textural transition between the Reef Package and its hanging wall, Stillwater Complex, Montana, USA: Journal of Petrology, v. 63, no. 7, egac053, 30 p., https://doi.org/10.1093/petrology/egac053.","productDescription":"egac053, 30 p.","ipdsId":"IP-136867","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":447376,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egac053","text":"Publisher Index Page"},{"id":435799,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IHERKX","text":"USGS data release","linkHelpText":"Geochemistry of rocks and rock fabric data near the hanging wall contact to the Reef Package, Stillwater Complex, Montana, USA"},{"id":413626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Stillwater Complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.25,\n 45.45\n ],\n [\n -110.25,\n 45.333\n ],\n [\n -109.75,\n 45.333\n ],\n [\n -109.75,\n 45.45\n ],\n [\n -110.25,\n 45.45\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"63","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, M. 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The U.S. Geological Survey (USGS) arm of YVO is also responsible for monitoring and reporting on volcanic activity in the Intermountain West of the United States.
The previous YVO monitoring plan for the Yellowstone region spanned 2006–2015 and focused on strengthening the region-wide coverage, or backbone, of monitoring systems (Yellowstone Volcano Observatory, 2006). The goals of that plan have largely been achieved thanks to significant investments in instrumentation and infrastructure, especially by the National Science Foundation EarthScope Plate Boundary Observatory (now known as the Network Of The Americas, or NOTA) and the American Reinvestment and Recovery Act. This revision of the monitoring plan, covering 2022–2032, builds upon these improvements to monitoring systems in the Yellowstone region while also accounting for new insights into the dynamics of the area’s seismic, volcanic, and hydrothermal activity. These additional improvements are designed to fill gaps in the monitoring network and to better understand and track hazards associated with hydrothermal processes. These improvements include:
The 2022–2032 monitoring plan for the Yellowstone volcanic system also proposes to improve monitoring of hydrothermal areas to better understand these dynamic systems and their associated hazards. To date, only a single seismometer has been placed within one of Yellowstone National Park’s geyser basins because seismic noise associated with boiling water can hinder interpretation of overall seismic and magmatic activity, but this concern has been mitigated by improvements to backbone monitoring. Deployment of geophysical, geochemical, hydrological, and geological monitoring instruments in geyser basins will be accompanied by campaigns to measure gas and water chemistry and flux, as well as aerial and satellite surveys of gas and thermal emissions.
Close collaboration between YVO member institutions and other research agencies is needed to achieve these monitoring goals and to use the derived data to advance understanding of how Yellowstone Caldera and similar volcanic systems work. At the same time, attention must be paid to minimize the impact of monitoring efforts and infrastructure on the environment. YVO thus commits to serving as stewards of the natural, cultural, and historical resources in and around Yellowstone National Park while maximizing scientific gain for the betterment of society.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225032","collaboration":"Prepared in cooperation with Yellowstone National Park, University of Utah, UNAVCO, University of Wyoming, Montana Bureau of Mines and Geology, Idaho Geological Survey, Wyoming State Geological Survey, and Montana State University","usgsCitation":"Yellowstone Volcano Observatory, 2022, Volcano and earthquake monitoring plan for the Yellowstone Caldera system, 2022–2032: U.S. Geological Survey Scientific Investigations Report 2022–5032, 23 p., https://doi.org/10.3133/sir20225032.","productDescription":"v, 23 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-120517","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":402338,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5032/sir20225032.pdf","text":"Report","size":"23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5032"},{"id":402337,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5032/covrthb.jpg"},{"id":502390,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113201.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Caldera, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.04156494140625,\n 44.24716652494939\n ],\n [\n -110.20111083984375,\n 44.24716652494939\n ],\n [\n -110.20111083984375,\n 44.77111175531263\n ],\n [\n -111.04156494140625,\n 44.77111175531263\n ],\n [\n -111.04156494140625,\n 44.24716652494939\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
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U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
Urban street trees are a key part of public green infrastructure in many cities, however, leaf litter on streets is a critical biogenic source of phosphorus (P) in urban stormwater runoff during Fall. This study identified mass of street leaf litter (Mleaf) and antecedent dry days (ADD) as the top two explanatory parameters that have significant predictive power of event end-of-pipe P concentrations through multiple linear regression (MLR) analysis. Mleaf and volume of runoff (Vol) were the top two key explanatory parameters of event end-of-pipe P loads. Two-predictor MLR models were developed with these explanatory parameters using a 40-storm dataset derived from six small urban residential watersheds in Wisconsin, USA, and evaluated using storms specific to each study basin. The MLR model validation results indicated sensitivity to storm composition in the datasets. Our analysis shows selected parameters can be used by environmental managers to facilitate end-of-pipe P prediction in urban areas. This information can be used to reduce the amount of P in stormwater runoff by adjusting the timing and frequency of municipal leaf collection and street cleaning programs in urban areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2022.115171","usgsCitation":"Wang, Y., Thompson, A., and Selbig, W.R., 2022, Predictive models of phosphorus concentration and load in stormwater runoff from small urban residential watersheds in fall season: Journal of Environmental Management, v. 315, 115171, 8 p., https://doi.org/10.1016/j.jenvman.2022.115171.","productDescription":"115171, 8 p.","ipdsId":"IP-122605","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":447380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2022.115171","text":"Publisher Index Page"},{"id":402375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Fond du Lac, Madison, Oshkosh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.58389282226561,\n 42.97752543508356\n ],\n [\n -89.25018310546875,\n 42.97752543508356\n ],\n [\n -89.25018310546875,\n 43.206176810164784\n ],\n [\n -89.58389282226561,\n 43.206176810164784\n ],\n [\n -89.58389282226561,\n 42.97752543508356\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.62533569335938,\n 43.94042832696309\n ],\n [\n -88.48251342773438,\n 43.94042832696309\n ],\n [\n -88.48251342773438,\n 44.11125397357155\n ],\n [\n -88.62533569335938,\n 44.11125397357155\n ],\n [\n -88.62533569335938,\n 43.94042832696309\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.51066589355469,\n 43.72694838956604\n ],\n [\n -88.36578369140625,\n 43.72694838956604\n ],\n [\n -88.36578369140625,\n 43.823629034783124\n ],\n [\n -88.51066589355469,\n 43.823629034783124\n ],\n [\n -88.51066589355469,\n 43.72694838956604\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"315","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Yi 0000-0003-3638-7940","orcid":"https://orcid.org/0000-0003-3638-7940","contributorId":236843,"corporation":false,"usgs":false,"family":"Wang","given":"Yi","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":844871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Anita 0000-0002-6202-1742","orcid":"https://orcid.org/0000-0002-6202-1742","contributorId":236844,"corporation":false,"usgs":false,"family":"Thompson","given":"Anita","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":844872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844873,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232258,"text":"70232258 - 2022 - Demonstration of a novel quantitative microscopy technique for automated characterization of in situ particulate matter in coal miners with progressive massive fibrosis","interactions":[],"lastModifiedDate":"2022-06-28T13:56:28.826441","indexId":"70232258","displayToPublicDate":"2022-06-20T10:55:33","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Demonstration of a novel quantitative microscopy technique for automated characterization of in situ particulate matter in coal miners with progressive massive fibrosis","docAbstract":"Rationale: Increasing exposure to respirable crystalline silica (RCS) linked to changes in mining production processes has been implicated in the resurgence of severe lung disease in U.S. coal miners. Lung mineralogy can provide insight into particle pathogenesis. However, standard approaches to characterizing in situ particulate matter (PM) by pulmonary pathologists have poor inter-rater comparability, and consensus agreement is time consuming. Scanning electron microscopy/energy-dispersive spectroscopy (SEM/EDX) is technically complex and labor intensive. We developed a method for quantitative in situ PM characterization using conventional polarized light microscopy (PLM) and explored PM features in lung tissue of coal miners with progressive massive fibrosis (PMF). \nMethods: With institutional review board approval, PLM images were obtained from 30 miners with PMF, classified by pathologists consensus based on PM profusion; 10 from each profusion group (mild/moderate/severe) were selected. Automated PM counting and characterization (including dimensions and grayscale intensity of PM > 0.3 m diameter) was performed on image samples using PLM with modified cell-counting software (BZ-X800 light microscope, Keyence Corporation, Osaka, Japan) (Figure 1). Quantitative PM density loge(PM count)/mm3 tissue was calculated for each sample and compared to pathologist PM profusion groups. PMF lesion type using consensus pathologist classification (13 coal-type, 9 mixed-type, and 8 silicotic-type) was compared to automated PM birefringence level (% particles with mean grayscale intensity <65, range 0-255). RCS particles are expected to be weakly birefringent (lower intensity) relative to other common minerals (e.g., silicates) contained in coal mine dust. PM features were analyzed in R 4.0.3 using one-way ANOVA for between-group comparisons.\nResults: Measured PM log-density increased significantly with higher qualitative profusion group (mild=10.480.98/mm3, moderate=11.460.81/mm3, severe=12.520.86/mm3, p<0.0001). Prevalence of weakly birefringent particles was significantly higher among silicotic-type PMF samples (31.57.9%) compared to either coal-type (21.510.1%, p=0.022) or mixed-type lesions (21.510.5%, p=0.025). \nConclusion: This pilot study demonstrates the feasibility of a novel quantitative microscopy technique for counting and characterizing in situ lung PM in coal miners with PMF. Quantitative PM burden was comparable to pulmonary pathologists consensus profusion classification, but this method was substantially less time consuming and labor intensive and provided additional information about relevant PM features. The higher prevalence of weakly birefringent particles seen in silicotic-type PMF lesions may help inform mineralogic pathogenesis of RCS. Future efforts will expand the number of PMF cases analyzed, further validate our mineralogic findings using data from SEM/EDX and lung tissue digestate methods, and compare findings in historical versus contemporary coal miners with PMF.","largerWorkTitle":"American Thoracic Society 2022 proceedings","language":"English","publisher":"American Thoracic Society","doi":"10.1164/ajrccm-conference.2022.205.1_MeetingAbstracts.A2489","usgsCitation":"Hua, J.T., Zell-Baran, L.M., Go, L.H., Cool, C.D., Lowers, H.A., Almberg, K.S., Sarver, E.A., Majka, S.M., Pang, K.D., Cohen, R.A., and Rose, C.S., 2022, Demonstration of a novel quantitative microscopy technique for automated characterization of in situ particulate matter in coal miners with progressive massive fibrosis, in American Thoracic Society 2022 proceedings, 2 p., https://doi.org/10.1164/ajrccm-conference.2022.205.1_MeetingAbstracts.A2489.","productDescription":"2 p.","ipdsId":"IP-133920","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":402374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-05-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Hua, Jeremy T.","contributorId":292496,"corporation":false,"usgs":false,"family":"Hua","given":"Jeremy","email":"","middleInitial":"T.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":844860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zell-Baran, Lauren M.","contributorId":265756,"corporation":false,"usgs":false,"family":"Zell-Baran","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":844861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Go, L. H.","contributorId":190733,"corporation":false,"usgs":false,"family":"Go","given":"L.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":844862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cool, Carlyne D.","contributorId":265746,"corporation":false,"usgs":false,"family":"Cool","given":"Carlyne","email":"","middleInitial":"D.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":844863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","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":844864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Almberg, K. S.","contributorId":265745,"corporation":false,"usgs":false,"family":"Almberg","given":"K.","email":"","middleInitial":"S.","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":844865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sarver, Emily A.","contributorId":265758,"corporation":false,"usgs":false,"family":"Sarver","given":"Emily","email":"","middleInitial":"A.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":844866,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Majka, Susan M.","contributorId":292497,"corporation":false,"usgs":false,"family":"Majka","given":"Susan","email":"","middleInitial":"M.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":844867,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pang, Kathy D.","contributorId":292498,"corporation":false,"usgs":false,"family":"Pang","given":"Kathy","email":"","middleInitial":"D.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":844868,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cohen, R. A.","contributorId":290338,"corporation":false,"usgs":false,"family":"Cohen","given":"R.","email":"","middleInitial":"A.","affiliations":[{"id":18133,"text":"University of Illinois Chicago","active":true,"usgs":false}],"preferred":false,"id":844869,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rose, Cecil S.","contributorId":265751,"corporation":false,"usgs":false,"family":"Rose","given":"Cecil","email":"","middleInitial":"S.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":844870,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70262364,"text":"70262364 - 2022 - Special section overview: Effects of ecosystem change on North American percid populations.","interactions":[],"lastModifiedDate":"2025-01-23T16:53:41.316862","indexId":"70262364","displayToPublicDate":"2022-06-20T10:46:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Special section overview: Effects of ecosystem change on North American percid populations.","docAbstract":"Walleye Sander vitreus, Sauger S. canadensis, and Yellow Perch Perca flavescens (referred to as percids herein) are collectively among the most culturally and ecologically important fish species in North America. As ecosystems change in response to environmental drivers, such as climate change, nutrient loading, and invasive species, there is a need to understand how percid populations respond to these changes. To address this need, a symposium was held during the 81st Annual Midwest Fish and Wildlife Conference to bring fishery scientists and managers together to describe and discuss percid population responses to ecosystem change. Prevailing symposium themes included the challenge of identifying mechanisms responsible for population-level changes, developing strategies to adaptively manage for resilient fisheries, and consideration of scale, context, and methods when interpreting variable results. Given the uncertainty of how ecosystem changes affect percid populations, participants emphasized the importance of communicating uncertainties to stakeholders, implementing data-driven management strategies, setting realistic goals, and revising management actions in an adaptive framework. There was universal agreement on both the challenge and necessity of facilitating constructive engagement among stakeholders in cooperative decision making. Symposium participants identified knowledge gaps and discussed future efforts to build on our current understanding of percid populations, including continuation of long-term monitoring, improved standardization of evaluation metrics, implementing adaptive management experiments to identify causal relationships, development of more robust analytical methods, use of historical data sources, and refining techniques to realistically convey management options to stakeholders.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10791","usgsCitation":"Boehm, H., Isermann, D.A., Ermer, M., Eslinger, L., Hansen, G., and Logsdon, D., 2022, Special section overview: Effects of ecosystem change on North American percid populations.: North American Journal of Fisheries Management, v. 42, no. 3, p. 477-483, https://doi.org/10.1002/nafm.10791.","productDescription":"7 p.","startPage":"477","endPage":"483","ipdsId":"IP-138666","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Boehm, Hadley I. A.","contributorId":349025,"corporation":false,"usgs":false,"family":"Boehm","given":"Hadley I. A.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":923938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ermer, Mark J.","contributorId":349026,"corporation":false,"usgs":false,"family":"Ermer","given":"Mark J.","affiliations":[{"id":81859,"text":"South Dakota Department of Game","active":true,"usgs":false}],"preferred":false,"id":923940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eslinger, Lawrence D.","contributorId":349027,"corporation":false,"usgs":false,"family":"Eslinger","given":"Lawrence D.","affiliations":[{"id":81673,"text":"Wisconsin Department of Natural Resources, Bureau of Fisheries Management","active":true,"usgs":false}],"preferred":false,"id":923941,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Gretchen J. A.","contributorId":349029,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen J. A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":923942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Logsdon, Dale E.","contributorId":349031,"corporation":false,"usgs":false,"family":"Logsdon","given":"Dale E.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923943,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232552,"text":"70232552 - 2022 - Controlling skewness in MOVE3 peak-flow record extensions","interactions":[],"lastModifiedDate":"2022-07-07T11:49:15.249922","indexId":"70232552","displayToPublicDate":"2022-06-20T06:47:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Controlling skewness in MOVE3 peak-flow record extensions","docAbstract":"Streamgage record extension methods such as the maintenance of variance Type 3 (MOVE3) method improve flood frequency estimates at a target streamgage by incorporating information from a nearby, hydrologically similar index streamgage. Bulletin 17C recommends using a variation of the MOVE3 method to estimate values at the target streamgage for only a subset of the available data at the index streamgage to account for uncertainty in values estimated using MOVE3. Bulletin 17C recommends the most recent index streamgage data be used for the subset unless these data misrepresent the skewness of the extended record. However, no method is provided to select the subset if the most recent data are inappropriate. The objective of this study is to develop such a method to select the subset of peaks by extending Bulletin 17C’s MOVE3 methodology to control the skewness of the extended streamgage record. The new method allows the extended record skewness to be informed by all available peak-flow data at the index streamgage while accurately computing the variance and resulting confidence intervals for flood frequency estimates. An example is presented comparing three different variations of MOVE3 record extension, which produce extended streamgage records with the same mean and variance, but different values of skewness. In the example, the difference in skewness between the three methods causes the results of flood frequency analysis for the 1% annual exceedance probability flood to differ by about 15%, illustrating the importance of considering skewness when using MOVE3 record extension.
The transition of sagebrush-dominated (Artemisia spp.) shrublands to pinyon (Pinus spp.) and juniper (Juniperus spp.) woodlands markedly alters resource-conserving vegetation structure typical of these landscapes. Land managers and scientists in the western United States need knowledge and predictive tools for assessment and effective targeting of tree-removal treatments to conserve or restore sagebrush vegetation and associated hydrologic function. This study developed modeling approaches to quantify the hydrologic vulnerability and erosion potential of sagebrush rangelands in the later stages of woodland encroachment and in response to commonly applied tree-removal treatments. Using experimental data from multiple sites in the Great Basin Region, USA, and process-based knowledge from decade-long vegetation and rainfall simulation studies at those sites, we (1) assessed the capability of the Rangeland Hydrology and Erosion Model (RHEM) to accurately predict patch-scale (12 m2) measured runoff and erosion from tree canopy and intercanopy hydrologic functional units in untreated and burned woodlands 9 years postfire, and (2) developed and evaluated multiple RHEM approaches/frameworks to model aggregated effects of tree canopy and intercanopy areas on patch- and hillslope-scale (50 m length) runoff and erosion processes in untreated and treated (burned, cut, and masticated) woodlands. The RHEM accurately predicted measured runoff and sediment yield from patch-scale rainfall simulations as partitioned on untreated and treated tree canopy and intercanopy areas and effectively parameterized the dominant controls on runoff and erosion process in woodlands. With few exceptions, evaluated hillslope-scale RHEM frameworks similarly predicted reduced hydrologic vulnerability and erosion potential for conditions 9 years following tree removal by burning, cutting, and mastication treatments. Regressions of RHEM-predicted hillslope runoff, sediment, and hydraulic/erosion parameters with bare ground and ground cover attributes indicate all RHEM frameworks effectively represented the dominant controls on hydrologic and erosion processes for rangelands and woodlands. The results provide RHEM frameworks and recommendations for assessing hydrologic vulnerability and erosion potential on woodland-encroached sites and predicting the effectiveness of tree removal to reestablish a water and soil resource-conserving vegetation structure on sagebrush rangelands. We anticipate our RHEM or similar modeling approaches may be applicable to analogous water-limited landscapes elsewhere subject to woody plant encroachment.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4145","usgsCitation":"Williams, C.J., Pierson, F.B., Al-Hamdan, O.Z., Nouwakpo, S.K., Johnson, J.C., Polyakov, V.O., Kormos, P.R., Shaff, S., and Spaeth, K.E., 2022, Assessing runoff and erosion on woodland-encroached sagebrush steppe using the Rangeland Hydrology and Erosion Model: Ecosphere, v. 13, no. 6, e4145, 32 p., https://doi.org/10.1002/ecs2.4145.","productDescription":"e4145, 32 p.","ipdsId":"IP-137960","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":447392,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecs2.4145","text":"External Repository"},{"id":402401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.14427185058592,\n 39.44679856427205\n ],\n [\n -115.10032653808594,\n 39.44679856427205\n ],\n [\n -115.10032653808594,\n 39.47807557129829\n ],\n [\n -115.14427185058592,\n 39.47807557129829\n ],\n [\n -115.14427185058592,\n 39.44679856427205\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.47871398925781,\n 40.20824570152502\n ],\n [\n -112.46429443359375,\n 40.20824570152502\n ],\n [\n -112.46429443359375,\n 40.2203056748532\n ],\n [\n -112.47871398925781,\n 40.2203056748532\n ],\n [\n -112.47871398925781,\n 40.20824570152502\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, C. Jason","contributorId":12774,"corporation":false,"usgs":true,"family":"Williams","given":"C.","email":"","middleInitial":"Jason","affiliations":[],"preferred":false,"id":844919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierson, Frederick B.","contributorId":195933,"corporation":false,"usgs":false,"family":"Pierson","given":"Frederick","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":844920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Hamdan, Osama Z.","contributorId":292513,"corporation":false,"usgs":false,"family":"Al-Hamdan","given":"Osama","email":"","middleInitial":"Z.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":844921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nouwakpo, S. Kossi","contributorId":292514,"corporation":false,"usgs":false,"family":"Nouwakpo","given":"S.","email":"","middleInitial":"Kossi","affiliations":[{"id":62926,"text":"Agricultural Research Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":844922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Justin C.","contributorId":261635,"corporation":false,"usgs":false,"family":"Johnson","given":"Justin","email":"","middleInitial":"C.","affiliations":[{"id":47959,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":844923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Polyakov, Viktor O.","contributorId":292516,"corporation":false,"usgs":false,"family":"Polyakov","given":"Viktor","email":"","middleInitial":"O.","affiliations":[{"id":62926,"text":"Agricultural Research Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":844924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kormos, Patrick R.","contributorId":292517,"corporation":false,"usgs":false,"family":"Kormos","given":"Patrick","email":"","middleInitial":"R.","affiliations":[{"id":62927,"text":"National Oceanic and Atmospheric Administration - National Weather Service, US Department of Commerce","active":true,"usgs":false}],"preferred":false,"id":844925,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shaff, Scott 0000-0001-8978-9260 sshaff@usgs.gov","orcid":"https://orcid.org/0000-0001-8978-9260","contributorId":5126,"corporation":false,"usgs":true,"family":"Shaff","given":"Scott","email":"sshaff@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844926,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spaeth, Kenneth E.","contributorId":9387,"corporation":false,"usgs":true,"family":"Spaeth","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":844927,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70266740,"text":"70266740 - 2022 - Cryptic population decrease due to invasive species predation in a long-lived seabird supports need for eradication","interactions":[],"lastModifiedDate":"2025-05-12T14:55:29.381762","indexId":"70266740","displayToPublicDate":"2022-06-18T09:44:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic population decrease due to invasive species predation in a long-lived seabird supports need for eradication","docAbstract":"The Pallid Sturgeon (Scaphirhynchus albus) Conservation Propagation and Stocking Program began stocking in the Missouri River above Fort Peck Reservoir in 1998 with 1997-year-class pallid sturgeon. Within the 1997-year class, all hatchery-origin pallid sturgeon females that reached reproductive maturation by 2016 underwent mass ovarian follicular atresia. Using combined historical and contemporary data, we described the spawning periodicity for female and male pallid sturgeon, characterized age- and size-at-first spawning, and evaluated what proportion of females experience mass ovarian follicular atresia during the first and subsequent reproductive cycles. Pallid sturgeon reached their first reproductive cycle at older ages and larger sizes than described for other populations. Females were functionally and physiologically capable of spawning at 21 years and males at 15 years. Immature pallid sturgeon as old as 20 years were documented. We found that more female pallid sturgeon underwent mass ovarian follicular atresia during the presumed-first reproductive cycle or known-first reproductive cycle than females during subsequent reproductive cycles (62.5% compared to 33.3%) indicating that effects related to reproductive maturation may be occurring. Nonetheless, mass ovarian follicular atresia appears to also occur for reasons not related to reproductive maturation. Females had biennial reproductive cycles, and males had annual and biennial reproductive cycles. Population models should account for females undergoing mass ovarian follicular atresia in their first reproductive cycle and subsequent cycles thereby increasing the age at first-successful spawning and reducing the estimated size of the spawning stock.
","language":"English","publisher":"Wiley","doi":"10.1111/jai.14339","usgsCitation":"Cox, T., Guy, C.S., Holmquist, L., and Webb, M., 2022, Reproductive indices and observations of mass ovarian follicular atresia in hatchery-origin pallid sturgeon: Journal of Applied Ichthyology, v. 38, p. 391-402, https://doi.org/10.1111/jai.14339.","productDescription":"12 p.","startPage":"391","endPage":"402","ipdsId":"IP-137205","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":447396,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.14339","text":"Publisher Index Page"},{"id":429772,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Cox, Tanner L.","contributorId":337305,"corporation":false,"usgs":false,"family":"Cox","given":"Tanner L.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":902341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmquist, Luke M.","contributorId":337306,"corporation":false,"usgs":false,"family":"Holmquist","given":"Luke M.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":902342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Molly A. H.","contributorId":337308,"corporation":false,"usgs":false,"family":"Webb","given":"Molly A. H.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":902343,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232218,"text":"sir20215143 - 2022 - Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019","interactions":[],"lastModifiedDate":"2026-04-08T16:38:21.182332","indexId":"sir20215143","displayToPublicDate":"2022-06-17T10:44:25","publicationYear":"2022","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":"2021-5143","displayTitle":"Application of a Soil-Water-Balance Model to Estimate Annual Groundwater Recharge for Long Island, New York, 1900–2019","title":"Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019","docAbstract":"A soil-water-balance (SWB) model was developed for Long Island, New York, to estimate the potential amount of annual groundwater recharge to the Long Island aquifer system from 1900 to 2019. The SWB model program is a computer code based on a modified Thornthwaite-Mather SWB approach and uses spatially and temporally distributed meteorological, land-cover, and soil properties as input to compute potential daily groundwater recharge. Simulated outputs indicate that island-wide potential groundwater recharge trends, as a percentage of precipitation, have increased approximately 3 percent during the 120-year period. The simulated results account for both climatic and land-cover changes that have occurred during the period. A change from undeveloped (forested land cover) to low- and medium-density residential land cover or land use increased potential groundwater recharge because of a decrease in evapotranspiration. During the 30-year period from 1900 to 1930, the simulated potential average groundwater recharge rate on Long Island was estimated to be 18.50 inches per year (in/yr), or a total of 1,243 million gallons per day, during the 30-year period from 1985 to 2015, the simulated potential average groundwater recharge rate estimate increased to 20.73 in/yr (a total of around 1,393 million gallons per day).
During the 1900–2019 simulation period, the potential average annual groundwater recharge rate was about 19.24 in/yr. The data for that period included values for a 3-year meteorological drought from 1963 to 1965, where the mean precipitation was about 26.5 percent lower than the long-term average of 46.7 in/yr, and the potential groundwater recharge rate was about 12.3 in/yr. During a 3-year wet period from 1982 to 1984, where mean precipitation was about 19.6 percent higher than the long-term average, the estimated potential groundwater recharge rate was about 26.8 in/yr.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215143","usgsCitation":"Finkelstein, J.S., Monti, J., Jr., Masterson, J.P., and Walter, D.A., 2022, Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019: U.S. Geological Survey Scientific Investigations Report 2021–5143, 25 p., https://doi.org/10.3133/sir20215143.","productDescription":"Report: v, 25 p.; 2 Data Releases","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103053","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":435800,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93Z8Y8L","text":"USGS data release","linkHelpText":"Soil-water-balance model archive for Long Island, NY, 1900-2019"},{"id":402201,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V2NMUB","text":"USGS data release","linkHelpText":"Soil-water-balance groundwater recharge model results for Long Island, NY, 1900-2019"},{"id":402197,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5143/coverthb.jpg"},{"id":402196,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5143/sir20215143.pdf","text":"Report","size":"5.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5143"},{"id":402199,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5143/images/"},{"id":402217,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20215143/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402198,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5143/sir20215143.XML"},{"id":402200,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94OLK6Z","text":"USGS data release","linkHelpText":"Soil-water-balance model archive for Long Island, NY, 1900-2019"},{"id":502287,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113197.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.036865234375,\n 40.55554790286311\n ],\n [\n -73.1744384765625,\n 40.56806745430726\n ],\n [\n -71.795654296875,\n 41.03378713521864\n ],\n [\n -72.2186279296875,\n 41.21998578493921\n ],\n [\n -72.6800537109375,\n 41.02135510866602\n ],\n [\n -73.10302734375,\n 40.98819156349393\n ],\n [\n -73.2513427734375,\n 40.93426521177941\n ],\n [\n -73.5369873046875,\n 40.95501133048621\n ],\n [\n -73.7896728515625,\n 40.8595252289932\n ],\n [\n -73.93798828125,\n 40.763901280945866\n ],\n [\n -74.036865234375,\n 40.66397287638688\n ],\n [\n -74.036865234375,\n 40.55554790286311\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
In densely populated coastal areas with sea-level rise (SLR), protecting the shorelines against erosion due to the wave impact is crucial. Along with many engineered structures like seawalls and breakwaters, there are also green structures like constructed oyster reefs (CORs) that can not only attenuate the incident waves but also grow and maintain pace with SLR. However, there is a lack of data and understanding of the long-term wave attenuation capacity of the living shoreline structures under SLR. In this study, we used the phase-resolving Boussinesq model, FUNWAVE-TVD, to examine the hydrodynamics including wave height and wave-induced currents around the CORs in the Gandys Beach living shoreline project area in the upper Delaware Bay, United States. Waves were measured at six locations (offshore to onshore, with and without CORs) in the Gandys Beach living shoreline project area for two winter months, during which four nor’easters occurred. We selected three cases that represent prevailing wind, wave, and tide conditions to examine the fine spatial and temporal changes in wave height and current velocity by the construction of the reefs. Wave heights and wave energy spectra generated from FUNWAVE-TVD were then validated with field observations. It is found that FUNWAVE-TVD is capable of simulating waves and associated hydrodynamic processes that interact with CORs. The model results show that wave attenuation rates vary with the incident wave properties and water depth, and wave-induced circulation patterns are affected by the CORs. The wave attenuation capacity of CORs over the next 100 years was simulated with the incorporation of the oyster reef optimal growth zone. Our study found that sustainable wave attenuation capacity can only be achieved when suitable habitat for COR is provided, thus it can vertically grow with SLR. Suitable habitat includes optimal intertidal inundation duration, current velocity for larval transport and settlement, on-reef oyster survival and growth, and other environmental conditions including salinity, temperature, and nutrient availability. Furthermore, the model results suggest that it would take CORs approximately 9 years after construction to reach and maintain the maximum wave attenuation capacity in sustainable living shorelines.
Hydrologic extremes, whether periods of drought or flooding, are occurring more frequently with greater severity and can have substantial economic impacts. Along with flooding, the timing and volume of streamflow also is changing across the United States. The focus of this report is to characterize a unique trend in mean annual streamflow occurring in eastern North and South Dakota, hereafter referred to as the eastern Dakotas, that is not being observed anywhere else in the conterminous United States.
Streamflow records for 1,853 U.S. Geological Survey streamgages obtained from the U.S. Geological Survey National Water Information System database with a continuous record of mean annual streamflow during water years 1960–2019 were included in this study. Using a Kendall tau statistical test (p-value less than or equal to 0.10), 573 streamgages had a statistically significant upward trend in mean annual streamflow and are primarily located in the Midwest and northeastern United States. Of the streamgages, 182 had a statistically significant downward trend and are located primarily in the western and southeastern States. Several sites had increases in streamflow between 100 and 500 percent. Most of the streamgages with the highest increases in mean annual streamflow are along the same rivers in the eastern Dakotas, regardless of basin size.
A comparison of mean annual streamflow of the last decade (2010–19) to the first decade (1960–69) of the study period shows that the largest increases in annual streamflow volumes in the United States also are in the eastern Dakotas. Among all 1,853 streamgages in the United States, the Sheyenne River near Warwick, North Dakota (U.S. Geological Survey station 05056000), has the greatest percent change, with an increase of 486 percent. Several factors may be contributing to increasing trends in streamflow in the eastern Dakotas and may include, in part, precipitation changes owing to climatic variation within the region, geologic makeup of the subsurface, and land-use changes. A better understanding of these research areas will help producers, resource managers, and infrastructure engineers to make more informed environmental and economic decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225055","usgsCitation":"Norton, P.A., Delzer, G.C., Valder, J.F., Tatge, W.S., and Ryberg, K.R., 2022, Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019: U.S. Geological Survey Scientific Investigations Report 2022–5055, 11 p., https://doi.org/10.3133/sir20225055.","productDescription":"Report: iv, 11 p.; Dataset","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-134818","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":402316,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225055/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402286,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5055/images"},{"id":402284,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5055/sir20225055.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5055"},{"id":402285,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5055/sir20225055.XML"},{"id":402283,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5055/coverthb.jpg"},{"id":402287,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"}],"country":"United States","state":"North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.7666015625,\n 42.90816007196054\n ],\n [\n -96.50390625,\n 42.90816007196054\n ],\n [\n -96.50390625,\n 48.980216985374994\n ],\n [\n -100.7666015625,\n 48.980216985374994\n ],\n [\n -100.7666015625,\n 42.90816007196054\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702