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
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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
Countless species of animals—big game, birds, bats, insects, amphibians, reptiles, and fish—migrate to reach suitable habitats to feed, reproduce, and raise their young. Animal migrations developed over millennia commonly follow migration corridors—unique routes for each species—to move among seasonal habitats. Changes along those corridors, whether from human development (buildings, roads, dams) or from natural disturbances (for example, climate change, drought, fire, flooding, or invasive species), can make them harder to navigate. The U.S. Geological Survey’s Ecosystems Mission Area provides science that assists land managers in mapping, enhancing, protecting, and reconnecting migration corridors critical for diverse fish and wildlife populations that migrate, such as Odocoileus hemionus (mule deer) and Antilocapra americana (pronghorn), trout and salmon, salamanders, tortoises, bats, and Danaus plexippus (monarch butterflies).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223030","usgsCitation":"Khalil, M., Wimer, M., Hu, D., Adams, M., Steinkamp, M., and Soileau, S.C., 2022, By land, air, and water—U.S. Geological Survey science supporting fish and wildlife migrations throughout North America: U.S. Geological Survey Fact Sheet 2022–3030, 4 p., https://doi.org/10.3133/fs20223030.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-126390","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":402255,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3030/images/"},{"id":402254,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3030/fs20223030.XML"},{"id":402253,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3030/fs20223030.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3030"},{"id":402252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3030/coverthb.jpg"}],"country":"Canada, Mexico, United States","otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -59.765625,\n 82.40242347938855\n ],\n [\n -164.53125,\n 73.42842364106816\n ],\n [\n -168.046875,\n 52.908902047770255\n ],\n [\n -108.28125,\n 1.4061088354351594\n ],\n [\n -85.078125,\n 19.31114335506464\n ],\n [\n -66.09375,\n 34.30714385628804\n ],\n [\n -41.484375,\n 50.736455137010665\n ],\n [\n -59.765625,\n 62.2679226294176\n ],\n [\n -61.17187499999999,\n 71.52490903732816\n ],\n [\n -71.71875,\n 76.84081641443098\n ],\n [\n -59.765625,\n 82.40242347938855\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Associate Director, Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Interbasin water transfers are becoming an increasingly common tool to satisfy municipal and agricultural water demand, but their impacts on movement and gene flow of aquatic organisms are poorly understood. The Grand Ditch is an interbasin water transfer that diverts water from tributaries of the upper Colorado River on the west side of the Continental Divide to the upper Cache la Poudre River on the east side of the Continental Divide. We used single nucleotide polymorphisms to characterize population genetic structure in cutthroat trout (Oncorhynchus clarkii) and determine if fish utilize the Grand Ditch as a movement corridor. Samples were collected from two sites on the west side and three sites on the east side of the Continental Divide. We identified two or three genetic clusters, and relative migration rates and spatial distributions of admixed individuals indicated that the Grand Ditch facilitated bidirectional fish movement across the Continental Divide, a major biogeographic barrier. Previous studies have demonstrated ecological impacts of interbasin water transfers, but our study is one of the first to use genetics to understand how interbasin water transfers affect connectivity between previously isolated watersheds. We also discuss implications on native trout management and balancing water demand and biodiversity conservation.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-022-01455-5","usgsCitation":"Harris, A., Oyler-McCance, S.J., Fike, J., Fairchild, M., Kennedy, C.M., Crockett, H.J., Winkelman, D.L., and Kanno, Y., 2022, Population genetics reveals bidirectional fish movement across the Continental Divide via an interbasin water transfer: Conservation Genetics, v. 23, p. 839-851, https://doi.org/10.1007/s10592-022-01455-5.","productDescription":"13 p.","startPage":"839","endPage":"851","ipdsId":"IP-136388","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":502545,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":409921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Arapaho and Roosevelt National Forests, Rocky Mountain National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.48445207177413,\n 40.56757183578418\n ],\n [\n -106.39934138151587,\n 40.56757183578418\n ],\n [\n -106.39934138151587,\n 39.6680633227534\n ],\n [\n -105.48445207177413,\n 39.6680633227534\n ],\n [\n -105.48445207177413,\n 40.56757183578418\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2022-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Audrey","contributorId":299560,"corporation":false,"usgs":false,"family":"Harris","given":"Audrey","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":858065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fairchild, Matthew P","contributorId":299561,"corporation":false,"usgs":false,"family":"Fairchild","given":"Matthew P","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":858068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Christopher M","contributorId":299562,"corporation":false,"usgs":false,"family":"Kennedy","given":"Christopher","email":"","middleInitial":"M","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":858069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crockett, Harry J","contributorId":299564,"corporation":false,"usgs":false,"family":"Crockett","given":"Harry","email":"","middleInitial":"J","affiliations":[{"id":36246,"text":"CPW","active":true,"usgs":false}],"preferred":false,"id":858070,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":858071,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kanno, Yoichiro","contributorId":210653,"corporation":false,"usgs":false,"family":"Kanno","given":"Yoichiro","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":858072,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70232216,"text":"fs20223040 - 2022 - Evaluating the use of video cameras to estimate bridge scour potential at four bridges in southwestern Montana","interactions":[],"lastModifiedDate":"2026-03-24T21:25:05.594876","indexId":"fs20223040","displayToPublicDate":"2022-06-22T08:03:13","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3040","displayTitle":"Evaluating the Use of Video Cameras to Estimate Bridge Scour Potential at Four Bridges in Southwestern Montana","title":"Evaluating the use of video cameras to estimate bridge scour potential at four bridges in southwestern Montana","docAbstract":"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
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
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.
Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July–December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July–December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July–December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, although may have had even greater impacts, considering the underestimated resurgence magnitude from the model.
","language":"English","publisher":"eLife Sciences Publications, Ltd","doi":"10.7554/eLife.73584","usgsCitation":"Truelove, S., Smith, C.P., Qin, M., Mullany, L., Borchering, R.K., Lessler, J., Shea, K., Howerton, E., Contamin, L., Levander, J., Kerr, J., Hochheiser, H., Kinsey, M., Tallaksen, K., Wilson, S., Shin, L., Rainwater-Lovett, K., Lemaitre, J., Dent, J., Kaminsky, J., Lee, E.C., Perez-Saez, J., Hill, A., Karlen, D., Chinazzi, M., Davis, J., Mu, K., Xiong, X., Pastore y Piontti, A., Vespignani, A., Srivastava, A., Porebski, P., Venkatramanan, S., Adiga, A., Lewis, B., Klahn, B., Outten, J., Orr, M., Harrison, G., Hurt, B., Chen, J., Vullikanti, A., Marathe, M., Hoops, S., Bhattacharya, P., Machi, D., Chen, S., Paul, R., Janies, D., Thill, J., Galanti, M., Yamana, T., Pei, S., Shaman, J.L., Healy, J., Slayton, R.B., Biggerstaff, M., Johansson, M.A., Runge, M.C., and Viboud, C., 2022, Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination: eLife, v. 11, e73584, 17 p., https://doi.org/10.7554/eLife.73584.","productDescription":"e73584, 17 p.","ipdsId":"IP-131448","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447373,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7554/elife.73584","text":"Publisher Index Page"},{"id":406680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.67138671875,\n 54.686534234529695\n ],\n [\n -129.9462890625,\n 55.36662484928637\n ],\n [\n -130.1220703125,\n 56.145549500679074\n ],\n [\n -131.9677734375,\n 56.9449741808516\n ],\n [\n 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USA","interactions":[],"lastModifiedDate":"2023-03-02T16:52:54.585683","indexId":"70240965","displayToPublicDate":"2022-06-21T10:43:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"The geochemical and textural transition between the Reef Package and its hanging wall, Stillwater Complex, Montana, USA","docAbstract":"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. Christopher","contributorId":150356,"corporation":false,"usgs":true,"family":"Jenkins","given":"M.","email":"","middleInitial":"Christopher","affiliations":[],"preferred":false,"id":865510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mungall, James E. 0000-0001-9726-8545","orcid":"https://orcid.org/0000-0001-9726-8545","contributorId":269537,"corporation":false,"usgs":false,"family":"Mungall","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":865511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":865512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butak, Kevin","contributorId":271084,"corporation":false,"usgs":false,"family":"Butak","given":"Kevin","email":"","affiliations":[{"id":56274,"text":"Sibanye-Stillwater","active":true,"usgs":false}],"preferred":false,"id":865513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corson, Sam R.","contributorId":260808,"corporation":false,"usgs":false,"family":"Corson","given":"Sam","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":865514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holick, Paul","contributorId":271083,"corporation":false,"usgs":false,"family":"Holick","given":"Paul","email":"","affiliations":[{"id":56274,"text":"Sibanye-Stillwater","active":true,"usgs":false}],"preferred":false,"id":865515,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKinley, Ryan","contributorId":302807,"corporation":false,"usgs":false,"family":"McKinley","given":"Ryan","email":"","affiliations":[],"preferred":false,"id":865516,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":865517,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70232256,"text":"tm11B13 - 2022 - Planetary geologic mapping protocol—2022","interactions":[],"lastModifiedDate":"2023-11-16T14:09:10.062332","indexId":"tm11B13","displayToPublicDate":"2022-06-21T09:19:57","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"11-B13","displayTitle":"Planetary Geologic Mapping Protocol—2022","title":"Planetary geologic mapping protocol—2022","docAbstract":"The Planetary Geologic Mapping Protocol covers the idealized process of compiling a NASA-funded map product of a non-terrestrial solid surface planetary body for U.S. Geological Survey (USGS) publication and summarizes technical specifications of the Mapping Process for authors and reviewers. Directed by community and programmatic recommendations, the USGS Planetary Geologic Map Coordination Group assembled the content herein to aid the timely production of USGS map products. This document can be also used as a reference document by those researchers who are completing geologic maps that will be published outside the USGS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm11B13","usgsCitation":"Skinner, J.A., Jr., Huff, A.E., Black, S.R., Buban, H.C., Fortezzo, C.M., Gaither, T.A., Hare, T.M., and Hunter, M.A., 2022, Planetary geologic mapping protocol—2022: U.S. Geological Survey Techniques and Methods 11–B13, 28 p., https://doi.org/10.3133/tm11B13.","productDescription":"v, 28 p.","numberOfPages":"28","onlineOnly":"N","ipdsId":"IP-122424","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":402341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/11/b13/covrthb.jpg"},{"id":413629,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm11B14","text":"TM 11-B14 —","description":"TM 11-B14","linkHelpText":"User’s Guide to planetary image analysis and geologic mapping in ArcGIS Pro"},{"id":402629,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/11/b13/tm11b13.pdf","text":"Report","size":"7 MB","description":"TM 11-B13"}],"contact":"Contact Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
The Yellowstone Volcano Observatory (YVO) is a consortium of nine Federal, State, and academic agencies that: (1) provides timely monitoring and hazards assessment of volcanic, hydrothermal, and earthquake activity in and around Yellowstone National Park, and (2) conducts research to develop new approaches to volcano monitoring and better understand volcanic activity in the Yellowstone region and elsewhere. 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,
Yellowstone Volcano Observatory
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
The young of some altricial bird species hatch asynchronously, which can lead to considerable size differences among siblings. Nestling traits such as body mass, moreover, can carry over and influence post-fledging survival. Despite the potential importance of nestling mass for reproductive outcomes, however, variation in nestling mass and relationships with brood size has been described and quantified rarely. We weighed 453 nestlings from 148 nests of 3 sympatric, sagebrush-associated songbird species in Wyoming, USA, to describe the range of intrabrood mass differences. Intrabrood differences in nestling mass were greatest for the largest species, the Sage Thrasher (Oreoscoptes montanus), for which the smallest nestling in a brood was on average 26.2% smaller than the largest. The smaller Vesper Sparrow (Pooecetes gramineus) and Brewer's Sparrow (Spizella breweri) exhibited similar intrabrood mass ratios, with the smallest nestling being 17.4% and 18.4% smaller on average than the largest for the 2 species, respectively. For each additional nestling within a brood, the smallest nestling was an additional 6.6–13.6% smaller than the largest nestling, depending on species. Understanding the extent of intrabrood variation in nestling traits has important implications for the productivity of species facing unpredictable environments.
","language":"English","publisher":"BioOne","doi":"10.1676/21-00047","usgsCitation":"Rhea, A.M., Carlisle, J., and Chalfoun, A.D., 2022, Intrabrood variation in nestling mass among three sagebrush-associated songbirds: The Wilson Journal of Ornithology, v. 134, no. 2, p. 345-351, https://doi.org/10.1676/21-00047.","productDescription":"7 p.","startPage":"345","endPage":"351","ipdsId":"IP-128963","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"134","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rhea, Ashleigh M.","contributorId":339524,"corporation":false,"usgs":false,"family":"Rhea","given":"Ashleigh","email":"","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":904555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Jason D.","contributorId":339525,"corporation":false,"usgs":false,"family":"Carlisle","given":"Jason D.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":904556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":904557,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232261,"text":"70232261 - 2022 - Rare window into an ancient struggle","interactions":[],"lastModifiedDate":"2022-06-20T17:06:47.751169","indexId":"70232261","displayToPublicDate":"2022-06-20T12:06:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2093,"text":"International Wolf","active":true,"publicationSubtype":{"id":10}},"title":"Rare window into an ancient struggle","docAbstract":"No abstract available.
","language":"English","publisher":"International Wolf Center","usgsCitation":"Petersohn, M.C., and Barber-Meyer, S., 2022, Rare window into an ancient struggle: International Wolf, v. 2022, no. Summer, p. 26-27.","productDescription":"2 p.","startPage":"26","endPage":"27","ipdsId":"IP-135095","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":402379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":402378,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://wolf.org/wolf-info/wolf-magazine/current-issue/"}],"volume":"2022","issue":"Summer","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Petersohn, Megan Carolyn 0000-0002-8955-9980","orcid":"https://orcid.org/0000-0002-8955-9980","contributorId":292501,"corporation":false,"usgs":true,"family":"Petersohn","given":"Megan","email":"","middleInitial":"Carolyn","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barber-Meyer, Shannon 0000-0002-3048-2616","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":217939,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844877,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232260,"text":"70232260 - 2022 - Evaluating the paleoenvironmental significance of sediment grain size in Bering Sea sediments during Marine Isotope Stage 11","interactions":[],"lastModifiedDate":"2023-11-20T16:59:28.105602","indexId":"70232260","displayToPublicDate":"2022-06-20T11:54:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the paleoenvironmental significance of sediment grain size in Bering Sea sediments during Marine Isotope Stage 11","docAbstract":"Grain size is an important textural property of sediments and is widely used in paleoenvironmental studies as a means to infer changes in the sedimentary environment. However, grain size parameters are not always easy to interpret without a full understanding of the factors that influence grain size. Here, we measure grain size in sediment cores from the Bering slope and the Umnak Plateau, and review the effectiveness of different grain size parameters as proxies for sediment transport, current strength, and primary productivity, during a past warm interval (Marine Isotope Stage 11, 424-374 ka). \n\nIn general, sediments in the Bering Sea are hemipelagic, making them ideal deposits for paleoenvironmental reconstructions, but there is strong evidence in the grain size distribution for contourite deposits between ~408-400 ka at the slope sites, suggesting a change in bottom current transport at this time. We show that the grain size of coarse (>150 µm) terrigenous sediment can be used effectively as a proxy for ice rafting, although it is not possible to distinguish between iceberg and sea ice rafting processes, based on grain size alone. We find that the mean grain size of bulk sediments can be used to infer changes in productivity on glacial-interglacial timescales, but the size and preservation of diatom valves also exert a control on mean grain size. Lastly, we show that the mean size of sortable silt (10-63 µm) is not a valid proxy for bottom current strength in the Bering Sea, because the input of ice-rafted silt confounds the sortable silt signal.","language":"English","publisher":"Micropaleontology Press","doi":"10.29041/strat.19.2.03","usgsCitation":"Thompson, N., and Caissie, B.E., 2022, Evaluating the paleoenvironmental significance of sediment grain size in Bering Sea sediments during Marine Isotope Stage 11: Stratigraphy, v. 19, no. 2, p. 119-139, https://doi.org/10.29041/strat.19.2.03.","productDescription":"21 p.","startPage":"119","endPage":"139","ipdsId":"IP-130205","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":402377,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Bering Sea, Bering Sea Green Belt, Bering Slope, Umnak Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.76171875,\n 55.1286490684888\n ],\n [\n -177.2314453125,\n 62.24746627771428\n ],\n [\n -182.548828125,\n 60.823494332539646\n ],\n [\n -171.03515625,\n 53.27835301753182\n ],\n [\n -165.76171875,\n 55.1286490684888\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Natalie 0000-0001-5924-6599","orcid":"https://orcid.org/0000-0001-5924-6599","contributorId":292499,"corporation":false,"usgs":false,"family":"Thompson","given":"Natalie","email":"","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":844874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caissie, Beth Elaine 0000-0001-9587-1842","orcid":"https://orcid.org/0000-0001-9587-1842","contributorId":292500,"corporation":false,"usgs":true,"family":"Caissie","given":"Beth","email":"","middleInitial":"Elaine","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":844875,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232259,"text":"70232259 - 2022 - Predictive models of phosphorus concentration and load in stormwater runoff from small urban residential watersheds in fall season","interactions":[],"lastModifiedDate":"2022-06-20T16:34:49.404382","indexId":"70232259","displayToPublicDate":"2022-06-20T11:04:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Predictive models of phosphorus concentration and load in stormwater runoff from small urban residential watersheds in fall season","docAbstract":"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":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":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":70232353,"text":"70232353 - 2022 - The Prairie Pothole Region: A duck factory, and a bee factory too","interactions":[],"lastModifiedDate":"2022-06-30T13:23:35.021179","indexId":"70232353","displayToPublicDate":"2022-06-20T08:17:07","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":10945,"text":"Prairie Pothole Joint Venture News","active":true,"publicationSubtype":{"id":30}},"title":"The Prairie Pothole Region: A duck factory, and a bee factory too","docAbstract":"No abstract available.
","language":"English","publisher":"Prairie Pothole Joint Venture","usgsCitation":"Simanonok, S.C., and Otto, C., 2022, The Prairie Pothole Region: A duck factory, and a bee factory too: Prairie Pothole Joint Venture News, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-142016","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":402737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":402658,"type":{"id":15,"text":"Index Page"},"url":"https://ppjv.org/the-prairie-pothole-region-a-duck-factory-and-a-bee-factory-too/"}],"country":"Canada, United States","otherGeospatial":"Prairie Potholes Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.08203125,\n 49.1242192485914\n ],\n [\n -113.115234375,\n 47.754097979680026\n ],\n [\n -111.4892578125,\n 47.724544549099676\n ],\n [\n -109.248046875,\n 47.57652571374621\n ],\n [\n -106.34765625,\n 48.019324184801185\n ],\n [\n -102.9638671875,\n 48.16608541901253\n ],\n [\n -101.0302734375,\n 47.57652571374621\n ],\n [\n -100.634765625,\n 46.58906908309182\n ],\n [\n -100.32714843749999,\n 44.62175409623324\n ],\n [\n -99.052734375,\n 43.100982876188546\n ],\n [\n -96.591796875,\n 42.84375132629021\n ],\n [\n -95.6689453125,\n 42.32606244456202\n ],\n [\n -93.9990234375,\n 40.81380923056958\n ],\n [\n -91.97753906249999,\n 41.07935114946899\n ],\n [\n -91.3623046875,\n 42.52069952914966\n ],\n [\n -95.8447265625,\n 48.83579746243093\n ],\n [\n -96.85546875,\n 49.97948776108648\n ],\n [\n -99.1845703125,\n 50.54136296522161\n ],\n [\n -103.3154296875,\n 51.536085601784755\n ],\n [\n -106.9189453125,\n 51.699799849741936\n ],\n [\n -109.951171875,\n 52.82932091031373\n ],\n [\n -112.1484375,\n 52.9883372533954\n ],\n [\n -114.2138671875,\n 53.30462107510271\n ],\n [\n -114.9169921875,\n 52.696361078274485\n ],\n [\n -114.08203125,\n 49.1242192485914\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Simanonok, Stacy C. 0000-0002-0287-3871","orcid":"https://orcid.org/0000-0002-0287-3871","contributorId":229607,"corporation":false,"usgs":true,"family":"Simanonok","given":"Stacy","email":"","middleInitial":"C.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":845324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":845325,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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.
Radium (Ra) is a geogenic contaminant that occurs at high levels in the Midwestern Cambrian-Ordovician aquifer system (MCOAS), a regionally important sandstone and carbonate drinking water aquifer. Water utilities using the MCOAS often must adopt treatment methods or use alternative water sources to maintain high-quality drinking water. Here, we show that Ra in water obtained from a municipal well in Wisconsin remains consistent despite variation in pumping conditions. However, widely used analytical methods (e.g., scintillation counting) for measuring Ra are less precise for quantifying Ra variability given the site conditions. Although not currently used for EPA compliance, mass spectrometry improves the precision of Ra measurements by an order of magnitude over the currently used counting method (e.g., 95 ± 3 mBq/L vs. 110 ± 30 mBq/L) at the concentrations observed in this study. The use of more precise analytical methods will increase understanding of trends in Ra levels important for operating public water systems.