Birds are vital to our economy, ecosystems, and cultural heritage. Investing in bird conservation benefits communities, businesses, and working lands while reinforcing our nation’s legacy of stewardship and biodiversity. By valuing birds, we ensure a richer, healthier, and more vibrant future for all Americans. The USGS leads two national bird monitoring programs Thriving bird populations contribute over $100 billion in related purchases to the U.S. economy annually, helping to support 1.4 million jobs and $90 billion in labor-related income. Across our nation, Federal and State wildlife agencies, Flyway Councils, non-governmental organizations, and more consider data from the U.S. Geological Survey’s (USGS) Bird Banding Laboratory (BBL) and Breeding Bird Survey (BBS) to be critical to meeting their mandates to set healthy harvest levels and in identifying species of conservation need. However, without stable and sufficient resources for the BBL and BBS, the capacity to monitor and address the rapidly evolving needs of migratory bird populations is at risk, jeopardizing the foundation of collaborative conservation efforts across North America.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253011","programNote":"Species Management Research Program","usgsCitation":"Ziolkowski, D., Celis-Murillo, A., Malpass, J., Pardieck, K., Martin, J., and Walker, L., 2025, Foundational science in flight—USGS bird programs support conservation, culture, and a thriving U.S. economy: U.S. Geological Survey Fact Sheet 2025–3011, 4 p., https://doi.org/10.3133/fs202533011.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-175892","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":483152,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3011/fs20253011_print.pdf","text":"Report","size":"3.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3011 PDF","linkHelpText":"Printer-friendly version"},{"id":483073,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3011/images"},{"id":483072,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3011/fs20253011.XML","description":"FS 2025-3011 XML"},{"id":483070,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3011/fs20253011.pdf","text":"Report","size":"2.61 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3011 PDF"},{"id":483069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3011/coverthb2.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.02943301109039,\n 15.410306981738572\n ],\n [\n -86.44265063211188,\n 21.842039182358832\n ],\n [\n -79.453241061223,\n 26.64186789245565\n ],\n [\n -78.50306906661305,\n 32.979705227993094\n ],\n [\n -50.77847439442888,\n 48.892922136315434\n ],\n [\n -66.2635829932419,\n 75.41047680539205\n ],\n [\n -74.57496425238357,\n 78.3457781585499\n ],\n [\n -58.13072469895427,\n 83.1029782866932\n ],\n [\n -168.32855790630842,\n 70.40594475176928\n ],\n [\n -166.93127284689004,\n 55.679378483117404\n ],\n [\n -121.64076199951083,\n 32.65515564988158\n ],\n [\n -109.15060725080741,\n 19.965527030937324\n ],\n [\n -93.8127347824803,\n 12.893183633264144\n ],\n [\n -92.02943301109039,\n 15.410306981738572\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
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11649 Leetown Rd.
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This report chapter summarizes the effect of hydroclimatic variability of annual peak streamflow in Minnesota and is part of a larger U.S. Geological Survey multistate study to assess potential nonstationarity in annual peak streamflows across the Midwest. Spatial and temporal patterns were examined for nonstationarity in annual peak streamflow, daily mean streamflow, and modeled climatic data in four analysis periods: (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. Upward trends in annual peak streamflow were detected in northwest to southeast and north to south directions. Downward trends in annual peak streamflow were detected in northeastern and southeastern areas. Trends in peak-flow timing indicated that peak streamflows are being detected later in the water year (the period from October 1 to September 30 designated by the year in which it ends) mainly in the southern areas and earlier in the water year mainly in the northern areas.
Changes in climate data point to wetter conditions in southern areas and drier conditions in northern areas. Annual precipitation was determined to be increasing in a northwest to southeast direction and in the east. In contrast, some areas in the north and northwest indicated decreasing annual precipitation. Annual snowfall was determined to be decreasing except in the extreme northeast, where annual snowfall was determined to be increasing. Decreases in annual potential evapotranspiration were detected in the south, and increases were detected in the north. Annual soil moisture increased in southern areas and decreased in northern and eastern areas. The potential spatial and temporal nonstationarity violations detected in the four analysis periods have important implications for flood-frequency analysis and point to the need for guidance on how to incorporate nonstationarities into future flood-frequency analysis in Minnesota.
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\"}}]}","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
Standardized guidelines for completing flood-flow frequency analyses are presented in a U.S. Geological Survey Techniques and Methods report known as Bulletin 17C, https://doi.org/10.3133/tm4B5. In recent decades (since about 2000), a better understanding of long-term climatic persistence (periods of clustered floods or droughts, or wet or dry periods) and concerns about potential climate change and land-use change have caused a reexamination of the stationarity assumptions underlying methods in Bulletin 17C. Bulletin 17C does not offer guidance on incorporating nonstationarities and further identifies a need for flood-frequency studies that incorporate changing climate or basin characteristics. As part of that reexamination, a study of annual peak streamflow (peak flow) has begun in the Midwest. This chapter of the study summarizes how hydroclimatic variability affects peak flows in North Dakota.
In this analysis of peak flow, daily streamflow, and climate metrics, four periods were selected: (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. Output from a monthly water-balance model was used for the climate data. Statistical analysis of peak flow consisted of evaluations of autocorrelation, trends, and change points and was augmented with analyses of seasonality and daily streamflow. The long-term pattern of decreasing peak flow in the west and increasing peak flow in the east is a pattern of opposing signals on either side of the 100th meridian. Analyses indicate that a key factor in changing hydroclimatology is the increase in fall precipitation. The trends in soil moisture closely match the trends in annual precipitation. Nonstationary flood-frequency analysis necessitates detailed exploratory data analysis and additional data and information about climate, land use, and other factors. This study provides extensive exploratory analysis for peak flow, daily streamflow, and climate data for North Dakota, setting the stage for informed nonstationary flood-frequency analysis.
Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Bedrock roadcuts developed with blasting along the New Hampshire State Route 111 bypass in Windham expose the metasedimentary Silurian Berwick Formation and intrusions of multiple phases of foliated to nonfoliated granite to granitic pegmatite of the Devonian New Hampshire Plutonic Suite. Fracture characterization at two roadway rock cuts (roadcuts) included measurement of fractures over a distance of approximately 225 and 85 meters. The Berwick Formation consists of medium-gray biotite-plagioclase-quartz granofels, biotite schist, and lesser calc-silicate rock. The Berwick Formation is locally sulfidic. Fresh, unweathered roadcuts are mostly gray but exhibit locally rusty weathering. The most conspicuous foliation in the region around the studied roadcuts is steeply northwest dipping to subvertical and northeast-southwest striking. Regionally, the strike of the foliation is consistently to the northeast-southwest, but the dip is locally variable to both the southeast and northwest. About 8 percent of the observed foliation surfaces exhibit limited fracture parting. The limited degree of parting agrees with observations for rocks within the garnet zone of metamorphism elsewhere in the Windham 7.5-minute quadrangle. The most prominent fracture trend is subvertical to steeply northeast-dipping and northwest-southeast striking (strike and dip of about 295°, 80°). The peak trend of steeply dipping fractures at the two exposures is 295°±12° and 289°±6°. Veins observed in the granite occur parallel to the peak fracture trend and consist primarily of quartz, tourmaline, and ankerite with minor amounts of sulfides (arsenopyrite, galena, and rare sphalerite), and trace amounts of apatite and rutile. The observed peak fracture trend at these roadcuts closely agrees with the most prominent fracture trend recognized within the Windham quadrangle. Gently south- to southeast-dipping and east- to northeast-striking fractures occur as joints and as parting fractures along a weak S3 cleavage. Water-bearing fractures at one exposure occur along joints and gently dipping contacts between the Berwick Formation and the granite to granitic pegmatite of the New Hampshire Plutonic Suite. About 8 percent of the fractures are water-bearing and most water-bearing fractures are gently dipping to the southeast. Fracture data separated by rock type shows a similar distribution for steeply dipping northwest-striking trends, but with much fewer observed steeply north-dipping fractures in the granitic rocks. Both rock types show a cluster of gently south-dipping fractures. The granites show far fewer steeply dipping northeast-striking fractures, which reflects a greater degree of parting along the foliation in the metasedimentary rocks than in the granites. No foliation-parallel fractures were observed in the granites, but some contacts between granites and the Berwick Formation do exhibit parting. Fracture termination classification yields 3 percent abutting, 76 percent dead end, and 21 percent crossing (or throughgoing) fractures.
Six brittle faults were observed, which strike northeast and most dip steeply to the northwest. Calculated paleostress tensors for the faults show an average stress field that is consistent with Late Triassic to Early Jurassic northwest-southeast extension associated with rifting of the New England crust during the initial opening of the Atlantic Basin. Fault data are consistent with brittle reactivation of the northeast striking and northwest dipping dominant foliation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1208","programNote":"National Cooperative Geologic Mapping Program","usgsCitation":"Walsh, G.J., and Powell, N.E., 2025, Bedrock fracture characterization of the New Hampshire State Route 111 bypass, Windham, New Hampshire: U.S. Geological Survey Data Report 1208, 12 p., https://doi.org/10.3133/dr1208.","productDescription":"Report: vi, 12 p.; Data Release","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-173004","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":492694,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118460.htm","linkFileType":{"id":5,"text":"html"}},{"id":482525,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1208/images/"},{"id":482521,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1208/coverthb.jpg"},{"id":482522,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1208/dr1208.pdf","text":"Report","size":"14.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1208 PDF"},{"id":482524,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1208/dr1208.XML","linkFileType":{"id":8,"text":"xml"},"description":"DR 1208 XML"},{"id":482526,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14A6TJY","text":"USGS data release","linkHelpText":"Fracture data collected at the Route 111 bypass in Windham, New Hampshire"},{"id":482523,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1208/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1208 HTML"}],"country":"United States","state":"New Hampshire","city":"Windham","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.3065034148442,\n 42.818705377139935\n ],\n [\n -71.3065034148442,\n 42.7840391932281\n ],\n [\n -71.26391433086863,\n 42.7840391932281\n ],\n [\n -71.26391433086863,\n 42.818705377139935\n ],\n [\n -71.3065034148442,\n 42.818705377139935\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 926A
Reston, VA 20192
Following near extirpation from the fur trade, sea otters (Enhydra lutris) have returned to occupy lower Cook Inlet since the 1950s, or earlier, with numbers increasing to ~11,000 and ~9,000 on the west and east side, respectively, by 2017. Northward range expansion on the west side has been negligible for decades with few animals found north of Kamishak Bay, while northward expansion on the east side has been more pronounced in recent decades. The reasons for these contrasting distribution patterns are not certain. Possible explanations for lack of expansion on the west side included 1) poor sea otter habitat north of Kamishak Bay; 2) adequate habitat north of Kamishak Bay but no incentive for sea otters to move north because of abundant food in Kamishak Bay, and/or sea otters discouraged from moving north of Kamishak Bay; 3) seasonal ice formation; or 4) seasonal presence of killer whales. This project was designed to document current sea otter abundance and distribution in lower Cook Inlet, including seasonal variation, and evaluate drivers of habitat use and foraging conditions, including how these overlap with Bureau of Ocean Energy Management (BOEM) Lease Sale blocks.
We found that the probability of sea otter presence in lower Cook Inlet was significantly related to depth and distance from shore with the highest probabilities of sea otter presence in areas ~7–8 kilometers (km) from shore in water ~20–30 meters (m) deep. Historical survey data suggest sea otter distribution has not changed dramatically since 2002, and while we detected significant seasonal changes including due to presence of heavy sea ice, the seasonal changes were modest and primarily related to locations with consistent winter ice formation on the west side of lower Cook Inlet. Overall, throughout the year, sea otters appeared to be utilizing most of the habitat within the 40-m depth contour on the east side of lower Cook Inlet, including Kachemak Bay. Sea otters on the west side reside largely within Kamishak Bay. Because of the shallow bathymetry of lower Cook Inlet, sea otters consistently occurred farther offshore than in many other areas of Alaska. The presence of sea otters, including females with pups, in these offshore waters indicates that sea otters can forage productively in these open water areas. Importantly, we documented that sea otters, including females with pups, occurred in most of the eastern BOEM lease blocks including the original Lease Sale 244 blocks 7064, 7114, 6162, 6310, 6360, 6410, 6458 and 6457. The relinquishments for these 7 leases were effective September 17, 2024: OCS-Y-02434 (block # 7064), OCS-Y-02435 (7114), OCS-Y-02436 (6162), OCS-Y-02438 (6357), OCS-Y-02442 (6407), OCS-Y02446 (6457), OCS-Y-02447 (6458) https://www.boem.gov/sites/default/files/documents/environment/Map%20of%20Active%20Leases%20 Cook%20Inlet%20OCS_0.pdf
Regarding differential northward expansion on the east and west side of lower Cook Inlet, we found that wind and water circulation patterns make winter sea ice more prominent on the west side, but this had minimal effects on sea otter distribution. In addition, although there have been observations of killer whale (Orcinus orca) predation on sea otters in Cook Inlet, we did not see behavioral or distributional evidence that it was prevalent enough to have strong effects on sea otter habitat use. Benthic surveys using a remotely operated vehicle (ROV) indicated that epibenthic substrate and biological community heterogeneity differed between areas with and without otters, suggesting that these factors may explain the current distribution of otters within lower Cook Inlet. However, ROV surveys cannot assess infaunal prey abundance, making assessments of the role of prey availability difficult. The existence of a healthy Pacific razor clam (Siliqua patula) fishery along western lower Cook Inlet along the Lake Clark coast north of Kamishak Bay suggests there may still be a resource base for eventual expansion of sea otters into this area.
Our shore-based forage observations indicated that sea otters exist near carrying capacity densities relative to nearshore prey resources. However, our distribution model suggests the bulk of the population lives offshore beyond our ability to observe their feeding activity. The fact that sea otters are a consistent presence in offshore areas suggests that prey resources in these areas were relatively abundant in comparison to nearshore prey resources, making foraging in offshore areas, with water depths of 0–40 m, energetically profitable. Prey types in these offshore areas of lower Cook Inlet likely included epifauna such as crabs and large urchins, in addition to infaunal clams based on the soft substrate habitat types that characterize lower Cook Inlet.
Collectively, our results suggest that sea otters occupy most areas of lower Cook Inlet with appropriate benthic habitat types and prey resources, which includes areas within BOEM Lease Sale blocks. With the exception of the Lake Clark coast, sea otters may be approaching a food- and habitat-limited distribution and carrying capacity, suggesting that the current status of sea otters in lower Cook Inlet is likely to remain similar in the absence of significant changes to prey, habitat, predation, or anthropogenic disturbance.
","language":"English","publisher":"Bureau of Ocean Energy Management (BOEM)","usgsCitation":"Monson, D., Kloecker, K.A., LaRoche, N., Power, C., Geissinger, L., Hasan, E., Jones, T., and Weitzman, B., 2025, Quantifying sea otter abundance, distribution, habitat use, and foraging intake in Cook Inlet, Alaska: OCS Study BOEM 2025-019, viii, 73 p.","productDescription":"viii, 73 p.","ipdsId":"IP-176659","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":502683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":502670,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://espis.boem.gov/final%20reports/BOEM_2025-019.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"Cook Inlet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154.3155651543558,\n 60.79849962080206\n ],\n [\n -154.3155651543558,\n 58.54443596757534\n ],\n [\n -149.77946397731765,\n 58.54443596757534\n ],\n [\n -149.77946397731765,\n 60.79849962080206\n ],\n [\n -154.3155651543558,\n 60.79849962080206\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Monson, Daniel 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":196670,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":959185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kloecker, Kimberly A. 0000-0002-2461-968X kkloecker@usgs.gov","orcid":"https://orcid.org/0000-0002-2461-968X","contributorId":3442,"corporation":false,"usgs":true,"family":"Kloecker","given":"Kimberly","email":"kkloecker@usgs.gov","middleInitial":"A.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":959186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaRoche, Nicole 0000-0003-3737-5714","orcid":"https://orcid.org/0000-0003-3737-5714","contributorId":178395,"corporation":false,"usgs":false,"family":"LaRoche","given":"Nicole","email":"","affiliations":[{"id":18890,"text":"formerly USGS Western Ecological Research Center, Santa Cruz Field Station","active":true,"usgs":false}],"preferred":false,"id":959187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Power, Collin","contributorId":303954,"corporation":false,"usgs":false,"family":"Power","given":"Collin","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":959188,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Geissinger, Laura","contributorId":369804,"corporation":false,"usgs":false,"family":"Geissinger","given":"Laura","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":959189,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hasan, Elizabeth","contributorId":369805,"corporation":false,"usgs":false,"family":"Hasan","given":"Elizabeth","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":959190,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Tahzay","contributorId":369806,"corporation":false,"usgs":false,"family":"Jones","given":"Tahzay","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":959191,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weitzman, Ben","contributorId":252838,"corporation":false,"usgs":false,"family":"Weitzman","given":"Ben","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":959192,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70264760,"text":"70264760 - 2025 - Fisheries research and monitoring activities of the Lake Erie Biological Station, 2024","interactions":[],"lastModifiedDate":"2025-03-24T14:18:44.046889","indexId":"70264760","displayToPublicDate":"2025-03-01T09:07:02","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Fisheries research and monitoring activities of the Lake Erie Biological Station, 2024","docAbstract":"A comprehensive understanding of fish populations and their interactions is the cornerstone of modern fishery management and the basis for Lake Erie’s Fish Community Objectives (FCOs) developed in 2020 (Francis et al. 2020). The 2024 U.S. Geological Survey (USGS) Lake Erie Biological Station Annual Report is responsive to these FCOs and the USGS obligations via a Memorandum of Understanding (MOU 2017) with the Great Lakes Fishery Commission (GLFC) Council of Lake Committees (CLC) to provide scientific information in support of fishery management. Goals for the USGS Great Lakes Deepwater Fish Assessment and Ecological Studies were to monitor long-term changes in the fish community and track population dynamics of key fishes of interest to management agencies. Specific to Lake Erie, expectations were sustained investigations of native percids, prey fish populations, and Lake Trout. All work was conducted as part of the Deepwater Science Program under the authority of the Great Lakes Fishery Research Authorization Act of 2019 (16 USC §941h).\n\nThe USGS 2024 Deepwater Science Program fieldwork began in Lake Erie in March and concluded in December, using trawl, gill net, hydroacoustic, lower trophic sampling devices, and telemetry methods. This work resulted in 44 bottom trawls covering 41 ha of lake bottom and catching 48,936 fish totaling 995 kg in the West Basin of Lake Erie, with detailed results described below. Overnight gill net sets (n=25) for coldwater species were performed in the East Basin of Lake Erie. A total of 8 km of gillnet was deployed during these surveys, which caught 106 fish, 92 of which were native coldwater species: Lake Trout, Burbot, and Lake Whitefish. Results from coldwater species assessments will be reported in the Coldwater Task Group report to the GLFC and the CLC (CTG 2025). These reports are used to inform Lake Trout stocking decisions and direct lamprey control measures (16 USC §939a). USGS hydroacoustic sampling included twenty-six 5-km transects (130 km total) in the Central Basin as part of a collaborative lake-wide survey with details and results reported by the Forage Task Group (FTG 2025). Lower trophic sampling provided data from zooplankton samples (n=12) and water quality profiles (n=12) to populate a database maintained by the Michigan Department of Natural Resources (MDNR), Ontario Ministry of Natural Resources (OMNR), Ohio Department of Natural Resources (ODNR), Pennsylvania Fish and Boat Commission (PFBC), and New York State Department of Environmental Conservation (NYSDEC). USGS also assisted CLC member agencies with deployment and maintenance of Great Lakes Acoustic Telemetry Observation System (GLATOS) infrastructure throughout all three Lake Erie basins and tributaries, supporting multiple coordinated telemetry investigations.\n\nThis report presents biomass-based summaries of fish communities in western Lake Erie derived from USGS bottom trawl surveys conducted from 2013 to 2024 during June and September. The survey design compliments the August ODNR- OMNRF effort by reinforcing stock assessments with more robust data. Analyses herein evaluated trends in total biomass, abundance of dominant predator and forage species, non-native species composition, biodiversity, and community structure. Data from this effort are accessible for download (Keretz et al. 2025)","language":"English","publisher":"Great Lakes Fisheries Commission","usgsCitation":"Dufour, M.R., Guzzo, F., Hilling, C.D., Keretz, K.R., Kraus, R., Oldham, R.C., Roberts, J., and Schmitt, J., 2025, Fisheries research and monitoring activities of the Lake Erie Biological Station, 2024, 18 p.","productDescription":"18 p.","ipdsId":"IP-176058","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":483683,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://glfc.org/publication-media-search.php","linkFileType":{"id":5,"text":"html"}},{"id":483708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.27940568089508,\n 42.15760057509911\n ],\n [\n -83.54993583176982,\n 42.15760057509911\n ],\n [\n -83.54993583176982,\n 41.240913888913184\n ],\n [\n -82.27940568089508,\n 41.240913888913184\n ],\n [\n -82.27940568089508,\n 42.15760057509911\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":931559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guzzo, Francesco 0000-0003-2374-0514","orcid":"https://orcid.org/0000-0003-2374-0514","contributorId":351294,"corporation":false,"usgs":true,"family":"Guzzo","given":"Francesco","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":931560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hilling, Corbin David 0000-0003-4040-9516","orcid":"https://orcid.org/0000-0003-4040-9516","contributorId":298946,"corporation":false,"usgs":true,"family":"Hilling","given":"Corbin","email":"","middleInitial":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":931561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keretz, Kevin R. 0000-0002-4808-8350 kkeretz@usgs.gov","orcid":"https://orcid.org/0000-0002-4808-8350","contributorId":5859,"corporation":false,"usgs":true,"family":"Keretz","given":"Kevin","email":"kkeretz@usgs.gov","middleInitial":"R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":931562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":931563,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oldham, Richard Cole 0000-0002-2331-7612","orcid":"https://orcid.org/0000-0002-2331-7612","contributorId":294345,"corporation":false,"usgs":true,"family":"Oldham","given":"Richard","email":"","middleInitial":"Cole","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":931564,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":931565,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":931566,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70264970,"text":"70264970 - 2025 - Methodology","interactions":[],"lastModifiedDate":"2025-03-27T14:21:22.11373","indexId":"70264970","displayToPublicDate":"2025-03-01T08:58:49","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Methodology","docAbstract":"Following the approach developed by Gregory and van Strien (2010), State of the\nBirds reports focus on composite summaries of population change for collections of\nspecies that share common primary habitat or taxonomic affinity. 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Critically, such extreme weather events can be more important drivers of extirpation and selection than changes in annual or seasonal averages and they pose a particularly large threat to poikilothermic organisms. In this study, we evaluated the transcriptomic response of a coldwater adapted fish species, the eastern brook trout (Salvelinus fontinalis), to two successive heatwaves during July and August 2022. We sampled brook trout at eight time points from four streams (N = 116 fish), sequenced mRNA from gill samples using TagSeq, and quantified expression levels of 32,670 unique transcripts. Multivariate analyses found that overall expression patterns in response to water temperature change were similar among streams. These analyses further detected groups of genes involved in immune response and oxygen carrier activity that were upregulated and downregulated respectively at higher water temperatures. We also detected 43 genes that were differentially expressed at different time points and followed the same expression pattern during the two heatwaves. Of these genes, 42 covaried with water temperature and most (27, 62.8 %) exhibited responses that varied by stream. Some of the differentially expressed genes, including heat shock proteins and cold-inducible RNA binding proteins, have been widely linked to temperature responses in experimental studies, whereas other genes we identified have functions that have not been well-studied in relationship to temperature or have unknown functions. This study shows the utility of landscape transcriptomic approaches to identify important biological processes governing wild organismal responses to short-term stressors. The results of this study can guide future investigations to identify phenotypic and genetic diversity that contribute to adaptive responses to heatwaves and improve predictions of how populations will respond to future climate change.
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Robert","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":929946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Driscoll, Cindy P.","contributorId":190850,"corporation":false,"usgs":false,"family":"Driscoll","given":"Cindy","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":929947,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":929948,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mullinax, Jennifer M.","contributorId":221170,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":929949,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263997,"text":"70263997 - 2025 - A practical decision tool for marine bird mortality assessments","interactions":[],"lastModifiedDate":"2025-03-04T14:44:08.99165","indexId":"70263997","displayToPublicDate":"2025-02-28T08:35:15","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18754,"text":"EcoEvoRxiv","active":true,"publicationSubtype":{"id":32}},"title":"A practical decision tool for marine bird mortality assessments","docAbstract":"Given the rise in anthropogenic, environmental, and disease events contributing to marine bird mortality, there is a critical need to improve the rigor of mortality assessments. Deficits in data collection and mortality estimation can hinder a manager’s ability to document event scales and inform population level impacts. Therefore, to inform decisions required during activities such as conservation status assessments or harvest management, organizations may choose to incorporate mortality assessments into response plans. Resources, capacity, and assets to assess mortality vary across jurisdictions (federal, state, Indigenous, local, etc.), and clear guidance to support mortality assessments is often unavailable or not clearly addressed. Here, we present a decision support tool to help managers identify and evaluate survey options to assess bird mortality in a diverse array of scenarios. The objective of the decision tool is to improve data collection and availability which will increase the ability to robustly estimate mortality, given situation-specific attributes and constraints. This decision tool is designed to guide the response when a mortality event is initially encountered and offers suggestions for assessment and reporting procedures in the absence of other guidance or to complement existing protocols. The decision tool is also meant to inform decision making for response determination and resource allocation. The tool facilitates examination of options for further assessment and monitoring which users determine by examining questions pertaining to species prioritization, mortality spatial extent, and the potential magnitude of impacts on affected species. Finally, identification of appropriate survey methods, that address imperfect detection when a complete census is not possible, are determined by exploring location, spatial and temporal extent, and the type of species affected. Ultimately, this tool aims to facilitate and improve the standardization of mortality assessments, equipping managers with a practical resource to navigate the decision-making process for marine bird mortality estimation.
","language":"English","publisher":"EcoEvoRxiv","doi":"10.32942/X23S6R","usgsCitation":"Harvey, J., Ramey, A.M., Avery-Gomm, S., Robertson, G., Romano, M., Mullinax, J.M., Boldenow, M., Atkinson, P., and Prosser, D.J., 2025, A practical decision tool for marine bird mortality assessments: EcoEvoRxiv, https://doi.org/10.32942/X23S6R.","productDescription":"48 p.","ipdsId":"IP-168193","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":487279,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.32942/x23s6r","text":"Publisher Index Page"},{"id":482790,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Johanna Alexandra 0000-0003-4504-6777","orcid":"https://orcid.org/0000-0003-4504-6777","contributorId":351781,"corporation":false,"usgs":true,"family":"Harvey","given":"Johanna Alexandra","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":929443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":929444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Avery-Gomm, Stephanie","contributorId":213093,"corporation":false,"usgs":false,"family":"Avery-Gomm","given":"Stephanie","email":"","affiliations":[{"id":12552,"text":"University of Queensland","active":true,"usgs":false}],"preferred":false,"id":929445,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robertson, Gregory","contributorId":331077,"corporation":false,"usgs":false,"family":"Robertson","given":"Gregory","affiliations":[],"preferred":false,"id":929446,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romano, Marc","contributorId":200806,"corporation":false,"usgs":false,"family":"Romano","given":"Marc","affiliations":[],"preferred":false,"id":929447,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mullinax, Jennifer M.","contributorId":221170,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":929448,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boldenow, Megan","contributorId":169336,"corporation":false,"usgs":false,"family":"Boldenow","given":"Megan","affiliations":[],"preferred":false,"id":929449,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Atkinson, Philip W.","contributorId":295425,"corporation":false,"usgs":false,"family":"Atkinson","given":"Philip W.","affiliations":[{"id":38864,"text":"British Trust for Ornithology","active":true,"usgs":false}],"preferred":false,"id":929450,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":929451,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70263777,"text":"70263777 - 2025 - Cancer risk and estimated lithium exposure in drinking groundwater in the US","interactions":[],"lastModifiedDate":"2025-02-24T15:22:49.778702","indexId":"70263777","displayToPublicDate":"2025-02-20T09:17:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20081,"text":"JAMA Network Open","active":true,"publicationSubtype":{"id":10}},"title":"Cancer risk and estimated lithium exposure in drinking groundwater in the US","docAbstract":"Importance Lithium is a naturally occurring element in drinking water and is commonly used as a mood-stabilizing medication. Although clinical studies have reported associations between receiving lithium treatment and reduced cancer risk among patients with bipolar disorder, to our knowledge, the association between environmental lithium exposure and cancer risk has never been studied in the general population.
Objectives To evaluate the association between exposure to lithium in drinking groundwater and cancer risk in the general population.
Design, Setting, and Participants This cohort study included participants with electronic health record and residential address information but without cancer history at baseline from the All of Us Research Program between May 31, 2017, and June 30, 2022. Participants were followed up until February 15, 2023. Statistical analysis was performed from September 2023 through October 2024.
Exposure Lithium concentration in groundwater, based on kriging interpolation of publicly available US Geological Survey data on lithium concentration for 4700 wells across the contiguous US between May 12, 1999, and November 6, 2018.
Main Outcome and Measures The main outcome was cancer diagnosis or condition, obtained from electronic health records. Stratified Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% CIs for risk of cancer overall and individual cancer types for increasing quintiles of the estimated lithium exposure in drinking groundwater, adjusting for socioeconomic, behavioral, and neighborhood-level variables. The analysis was further conducted in the western and eastern halves of the US and restricted to long-term residents living at their current address for at least 3 years.
Results A total of 252 178 participants were included (median age, 52 years [IQR, 36-64 years]; 60.1% female). The median follow-up time was 3.6 years (IQR, 3.0-4.3 years), and 7573 incident cancer cases were identified. Higher estimated lithium exposure was consistently associated with reduced cancer risk. Compared with the first (lowest) quintile of lithium exposure, the HR for all cancers was 0.49 (95% CI, 0.31-0.78) for the fourth quintile and 0.29 (95% CI, 0.15-0.55) for the fifth quintile. These associations were found for all cancer types investigated in both females and males, among long-term residents, and in both western and eastern states. For example, for the fifth vs first quintile of lithium exposure for all cancers, the HR was 0.17 (95% CI, 0.07-0.42) in females and 0.13 (95% CI, 0.04-0.38) in males; for long-term residents, the HR was 0.32 (95% CI, 0.15-0.66) in females and 0.24 (95% CI, 0.11-0.52) in males; and the HR was 0.01 (95% CI, 0.00-0.09) in western states and 0.34 (95% CI, 0.21-0.57) in eastern states.
Conclusions and Relevance In this cohort study of 252 178 participants, estimated lithium exposure in drinking groundwater was associated with reduced cancer risk. Given the sparse evidence and unknown mechanisms of this association, follow-up investigation is warranted.
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Chicago","active":true,"usgs":false}],"preferred":false,"id":928232,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hong, Eric","contributorId":351284,"corporation":false,"usgs":false,"family":"Hong","given":"Eric","affiliations":[],"preferred":false,"id":928317,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":928233,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":928234,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ahsan, Habibul","contributorId":351227,"corporation":false,"usgs":false,"family":"Ahsan","given":"Habibul","affiliations":[{"id":36705,"text":"University of Chicago","active":true,"usgs":false}],"preferred":false,"id":928235,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pinto, Jayant M.","contributorId":351228,"corporation":false,"usgs":false,"family":"Pinto","given":"Jayant M.","affiliations":[{"id":36705,"text":"University of 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Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Range-wide ecology, conservation, and research needs for yellow lampmussel (Lampsilis cariosa)","docAbstract":"The freshwater mussel yellow lampmussel (Lampsilis cariosa) is declining throughout its range along the Atlantic Slope of the eastern United States and Canada, and the species is a target for proactive conservation to avoid federal listing. This paper synthesizes information about the ecology (physiology and life history, host fishes, and habitat), species distribution, genetics, and threats to L. cariosa. Identified threats include climate change, habitat alteration, and invasive species, dependent on location. We outline 16 emergent research and conservation management needs based on literature review and discussion with stakeholders (state and federal mussel biologists, researchers, and tribal groups). These needs range from research on the basic physiology and behavior of the species, to creating standardized protocols for surveys and DNA sampling, to ultimately developing a range-wide species conservation and restoration plan. Addressing these information gaps and incorporating the findings into future management may facilitate the implementation and success of large-scale restoration and conservation initiatives such as habitat protection and reintroduction of L. cariosa to historical locations.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10750-024-05765-2","usgsCitation":"Farrington, S., Murphy, C.A., Perkins, D., and Roy, A.H., 2025, Range-wide ecology, conservation, and research needs for yellow lampmussel (Lampsilis cariosa): Hydrobiologia, v. 852, p. 2729-2754, https://doi.org/10.1007/s10750-024-05765-2.","productDescription":"26 p.","startPage":"2729","endPage":"2754","ipdsId":"IP-165902","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":492476,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10750-024-05765-2","text":"Publisher Index Page"},{"id":492135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.2116373830845,\n 44.09913691401181\n ],\n [\n -80.50374108682163,\n 41.85845354508396\n ],\n [\n -80.99912161104155,\n 39.63960771569129\n ],\n [\n -82.43337791555581,\n 37.77339486928925\n ],\n [\n -85.76310658933828,\n 33.88933798331024\n ],\n [\n -84.74697530374709,\n 30.712478092443988\n ],\n [\n -79.6611750181294,\n 30.848363324108078\n ],\n [\n -59.414970432845266,\n 46.31029094614682\n ],\n [\n -64.10136367360452,\n 49.62997543691469\n ],\n [\n -79.2116373830845,\n 44.09913691401181\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"852","noUsgsAuthors":false,"publicationDate":"2025-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Farrington, Stefanie J.","contributorId":357879,"corporation":false,"usgs":false,"family":"Farrington","given":"Stefanie J.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":942736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":942737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perkins, David","contributorId":340494,"corporation":false,"usgs":false,"family":"Perkins","given":"David","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":942738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":942739,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269931,"text":"70269931 - 2025 - Current distribution of the nine-banded armadillo (Dasypus novemcinctus) in the United States","interactions":[],"lastModifiedDate":"2025-08-07T15:03:38.484781","indexId":"70269931","displayToPublicDate":"2025-02-19T09:55:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Current distribution of the nine-banded armadillo (Dasypus novemcinctus) in the United States","title":"Current distribution of the nine-banded armadillo (Dasypus novemcinctus) in the United States","docAbstract":"The nine-banded armadillo (Dasypus novemcinctus: hereafter armadillo) was first recorded in the United States (U.S.) in the state of Texas in 1849 and has been expanding its range northward and eastward since then. With the widespread adoption of participatory science as well as the proliferation of nationwide wildlife game camera studies, occurrence data of armadillos can be compiled more rapidly and thoroughly than at any time in the past. Here, we use disparate data sources to update the current geographic distribution of the armadillo in the United States and use occurrence data from the leading edge of its range expansion to create a species distribution model to understand their relationship with landscape and bioclimatic factors. Since the last report on the geographic distribution of the armadillo in 2014, we show that armadillos have expanded to cover the entirety of Missouri and established in southern Iowa, expanded modestly within Kansas and Illinois, expanded northward and eastward in Indiana, expanded eastward in both Kentucky and Tennessee, established throughout the entirety of South Carolina and Georgia and established in the western third of North Carolina. Our species distribution model indicates that there is substantial opportunity for the species to continue to expand its geographic range, particularly in the Eastern United States. These results provide information to managers who are now or might soon be co-existing with the armadillo to proactively manage the species or inform the public regarding potential conflicts.
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The Black and White tegu (Salvator merianae) has become established in several Florida counties and its spread is of significant conservation concern. It is of high priority for state and federal managers to prevent the spread into sensitive ecosystems, including the Greater Everglades. Thus, coordinated EDRR efforts are essential given limited infrastructure and funding for such tasks. While tegus have been observed along the eastern boundary of Everglades National Park, there has been no evidence tegus are established within Big Cypress National Preserve. On 8 August 2024 an individual tegu was sighted by a U.S. Geological Survey (USGS) biologist in Big Cypress National Preserve who alerted National Park Service (NPS) staff and mobilized a response. Live traps were placed at the location of sighting within 24 hours and an individual tegu was captured on 13 August 2024. The individual tegu was determined to be the same individual that was observed five days early based on color, pattern, and other physical characteristics. No additional tegus were captured. The rapid, coordinated response of NPS and USGS likely contributed to this successful EDRR event, and highlights the need for more expansive EDRR frameworks at multiple jurisdictional scales.","language":"English","publisher":"The Regional Euro-Asian Biological Invasions Centre (REABIC)","doi":"10.3391/mbi.2025.16.2.15","usgsCitation":"Sandfoss, M.R., Kissel, A.M., McBride, L.M., Metcalf, M., Sherburne, S., Mangione, T., McCollister, M., and Yackel Adams, A.A., 2025, An early detection rapid response case study of the Black and White Tegu (Salvator merianae) and implications for a broader framework: Management of Biological Invasions, v. 16, no. 2, p. 581-591, https://doi.org/10.3391/mbi.2025.16.2.15.","productDescription":"11 p.","startPage":"581","endPage":"591","ipdsId":"IP-170561","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":490663,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2025.16.2.15","text":"Publisher Index Page"},{"id":489453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"south Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.46866453957387,\n 27.16060350540674\n ],\n [\n -82.46866453957387,\n 24.9925626851346\n ],\n [\n -79.72039698185677,\n 24.9925626851346\n ],\n [\n -79.72039698185677,\n 27.16060350540674\n ],\n [\n -82.46866453957387,\n 27.16060350540674\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sandfoss, Mark Robert 0000-0002-0162-7265","orcid":"https://orcid.org/0000-0002-0162-7265","contributorId":328884,"corporation":false,"usgs":true,"family":"Sandfoss","given":"Mark","email":"","middleInitial":"Robert","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":939007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kissel, Amanda Marie 0000-0002-6346-7455","orcid":"https://orcid.org/0000-0002-6346-7455","contributorId":334356,"corporation":false,"usgs":true,"family":"Kissel","given":"Amanda","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":939008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McBride, Lisa Marie 0000-0003-4558-5391","orcid":"https://orcid.org/0000-0003-4558-5391","contributorId":303824,"corporation":false,"usgs":true,"family":"McBride","given":"Lisa","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":939009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Metcalf, Matthew Fox 0000-0002-5413-5192","orcid":"https://orcid.org/0000-0002-5413-5192","contributorId":356279,"corporation":false,"usgs":true,"family":"Metcalf","given":"Matthew Fox","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":939010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherburne, Sarah Rae 0000-0002-2351-769X","orcid":"https://orcid.org/0000-0002-2351-769X","contributorId":356280,"corporation":false,"usgs":true,"family":"Sherburne","given":"Sarah Rae","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":939011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mangione, Travis R.","contributorId":356281,"corporation":false,"usgs":false,"family":"Mangione","given":"Travis R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":939012,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCollister, Matthew","contributorId":302902,"corporation":false,"usgs":false,"family":"McCollister","given":"Matthew","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":939013,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":939014,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70268813,"text":"70268813 - 2025 - Multispectral red-edge indices accurately estimate nitrogen content in winter cereal cover crops","interactions":[],"lastModifiedDate":"2025-07-08T16:10:56.678715","indexId":"70268813","displayToPublicDate":"2025-02-16T09:05:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":684,"text":"Agronomy Journal","active":true,"publicationSubtype":{"id":10}},"title":"Multispectral red-edge indices accurately estimate nitrogen content in winter cereal cover crops","docAbstract":"Winter cover crops reduce erosion and nutrient runoff from agricultural systems. Although cereal cover crops can decrease field nitrate leaching by 50%–95%, the magnitude of this reduction varies within and between fields, making it challenging to monitor the impact of cover crops on nitrate leaching at large spatial extents. Satellite remote sensing using red-edge bands has been shown to effectively estimate crop nitrogen (N) content (kg ha−1) in later growth-stage crops with a closed canopy. In this study, we evaluated 15 spectral indices derived from Sentinel-2 imagery to estimate N concentration (%) and content (kg ha−1) of cereal cover crops, using 1627 destructive samples collected from 2018 to 2023 in Maryland. Observed N content ranged from 0.1 to 214.7 kg ha−1, while N concentration ranged from 0.6% to 5.5%. The 15 indices considered were poor predictors of N concentration (adj. R2 = 0.089, root mean squared error [RMSE] = 0.802%), but were more successful at measuring N content (biomass × N concentration). Delta red-edge (ΔRE) was the best predictor of N content (adj. R2 = 0.748, RMSE = 13.10 kg ha−1 from cross-validation with 80% train and 20% test splits iterated 100 times) using samples with imagery collected within ±4 days of destructive sampling (n = 1110). Our findings indicate that longer red-edge wavelengths (783 and 740 nm) are more suited for estimating N content in cereal cover crops compared to shorter red-edge wavelengths, which have been shown to be more sensitive to biomass. Leave-one-year-out cross-validation demonstrated that the relationship between ΔRE and N content was robust across all four cover crop sampling years included in the study (adj. R2 = 0.700–0.769, RMSE = 10.70–15.40 kg ha−1). Regression model performance improved with the addition of multiple predictors, including biomass (estimated from Normalized Difference Vegetation Index), weather variables (adj. R2 = 0.765, RMSE = 12.37 kg ha−1), management variables (species, season, adj. R2 = 0.772, and RMSE = 12.13 kg ha−1), and biophysical variables (height, fractional ground cover, adj. R2 = 0.818, and RMSE = 10.29 kg ha−1). These findings demonstrate the feasibility of quantifying N content in cereal cover crops using a red-edge-based spectral index across large geographic extents and indicate the inclusion of additional predictors, such as weather and management data, improves model accuracy. This work has implications for quantifying reductions in N leaching associated with cover crops, aiding in policymaking and evaluation of conservation programs that impact water bodies such as Chesapeake Bay.
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However, geothermal potential across the Great Basin region is thought to be much higher for hidden or blind geothermal systems. Accordingly, exploration techniques that can locate geothermal resources that lack surface thermal features could support future development of these systems. The goal of the INGENIOUS project is to reduce exploration risk and discover new, economically viable hidden geothermal systems in the Great Basin region. This paper summarizes the efforts and preliminary results of blind geothermal resource prospecting in Utah as part of the larger INGENIOUS project. The Lund North site in the Basin and Range province of southwest Utah was designated as the fourth detailed study site for the project. The site was initially identified from the preliminary Play Fairway Analysis (PFA) geothermal favorability map, which is based on various data elements, and the identification of favorable structural settings across Utah. This site contains existing legacy data including a thermal gradient borehole with a heat-flow value exceeding 220 mW/m2. New data collected at this site include terrestrial gravity, magnetotellurics, transient electromagnetics, fluid geochemistry, geologic mapping, UAV-based lidar, paleomagnetism, aeromagnetic surveys, and a shallow temperature survey. Preliminary data and model interpretations corroborate the presence of a large, east-dipping, northeast-southwest-trending normal fault on the edge of a typical Basin and Range graben. Quaternary fault mapping refined by high-resolution lidar surveys suggests a complex step over fault geometry. Utilizing multi-disciplinary datasets for further site assessment at Lund North will facilitate the development of a local-scale PFA and geothermal conceptual model. This new data will be used to site successive thermal gradient drilling to verify heat flow with temperatures at depth at the Lund North site and further investigate the existence of a local geothermal system.
","largerWorkTitle":"Proceedings, 50th workshop on geothermal reservoir engineering","conferenceTitle":"50th Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 10-12, 2025","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford University","usgsCitation":"Hardwick, C.L., Szymanski, E., Hart-Wagoner, N.R., Ashton, S., Christensen, N., Earney, T.E., Faulds, J.E., Glen, J.M., Hiscock, A., Kirby, S., Knudsen, T., Kobe, S., Lindsey, C.R., Morbeck, B., Peacock, J., Rea-Downing, G.H., Schermerhorn, W.D., and Smith, K., 2025, Exploration for blind geothermal systems in the eastern Great Basin of Utah: An update on the “Lund North” INGENIOUS detailed study site, in Proceedings, 50th workshop on geothermal reservoir engineering, v. 50, Stanford, CA, February 10-12, 2025, 14 p.","productDescription":"14 p.","ipdsId":"IP-174820","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science 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Felt reports from local residents were the only available information about the swarm when it started, as American Samoa lacked a seismic monitoring network. We developed a consistent single-station catalog for the entire swarm, using seismic data from the nearest station IU.AFI, ~250 km away. We applied the EQTransformer deep-learning model (Mousavi et al., 2020), automatically picking Pn and Sn arrivals on IU.AFI continuous data. We retained only events with Sn-Pn times of 22.5–25 seconds, consistent with the expected locations based on felt reports, then detected smaller swarm events with subsequent template-matching. This single-station catalog characterized the swarm’s onset and escalation to peak activity before a multi-agency field response team installed a local seismic network in mid-August 2022. This permanent seismic network captured the swarm’s decline. EQTransformer identified short S-P times on the first two locally deployed seismometers, both Raspberry Shake sensors, to constrain the swarm’s distance from Taʻū Island. Modern seismological processing methods, combined with basic observations such as felt reports, can quickly contribute useful information during an earthquake response in a poorly monitored region.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320240040","usgsCitation":"Yoon, C., Skoumal, R., Michael, A.J., Jolly, A., Ellis, A.P., Downs, D.T., Dotray, P., Deligne, N.I., Chang, J., Bennington, N.L., Wech, A., Haney, M.M., Hotovec-Ellis, A.J., Lutu-McMoore, E., and Langkilde, M., 2025, Remote single-station seismic monitoring of the July–October 2022 earthquake swarm at Tau volcano, American Samoa: The Seismic Record, v. 5, no. 1, p. 83-96, https://doi.org/10.1785/0320240040.","productDescription":"14 p.","startPage":"83","endPage":"96","ipdsId":"IP-170130","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487646,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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0000-0003-1917-0205","orcid":"https://orcid.org/0000-0003-1917-0205","contributorId":211785,"corporation":false,"usgs":true,"family":"Hotovec-Ellis","given":"Alicia","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":927475,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lutu-McMoore, Elinor","contributorId":341954,"corporation":false,"usgs":false,"family":"Lutu-McMoore","given":"Elinor","email":"","affiliations":[{"id":81814,"text":"NOAA National Weather Service Pago Pago Office","active":true,"usgs":false}],"preferred":false,"id":927476,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Langkilde, Marcus","contributorId":350957,"corporation":false,"usgs":false,"family":"Langkilde","given":"Marcus","affiliations":[{"id":83889,"text":"NOAA NWS Pago Pago","active":true,"usgs":false}],"preferred":false,"id":927477,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70264978,"text":"70264978 - 2025 - Local, regional, and distal recordings of seismic unrest at Tau Island volcano, American Samoa","interactions":[],"lastModifiedDate":"2025-03-27T15:18:39.378071","indexId":"70264978","displayToPublicDate":"2025-02-13T08:09:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Local, regional, and distal recordings of seismic unrest at Tau Island volcano, American Samoa","docAbstract":"A seismic swarm near Taʻū Island, a volcanic island in eastern American Samoa, occurred from July to October 2022. The earliest unrest was noted as felt shaking reports in late July, and instrumentation varied in the beginning of the sequence as the U.S. Geological Survey (USGS) Hawaiian Volcano Observatory responded by installing temporary and then permanent seismometers to monitor the activity. This network variability made it difficult to characterize the earliest seismicity and contextualize the entire sequence to discriminate between an underlying tectonic or volcanic source. Here, we present results analyzing hydroacoustic detections from an International Monitoring System hydrophone array near Wake Island, 4500 km northwest of Taʻū Island volcano. Using least-squares beamforming analysis, we create a catalog of T-wave detections from the direction of Taʻū Island to track the earthquakes, some of which were located by the USGS National EarthquakeInformation Center. Both the rate and hydroacoustic pressures, which we interpret as a proxy for earthquake size, gradually increased from late July to August, peaking on August 19 (rate) and August 24 (size), before decreasing to background in late September. Minutes-long bursts of tremor were also contemporaneously recorded as local network data became avail-able on August 20. Tremor activity continued throughout the rest of August, peaking on August 25, before ending in earlySeptember. These tremor bursts were band-limited to ~ 1–5 Hz and recorded as S waves at a regional station on the island of Upolu in Samoa, 250 km to the west of Taʻū Island. Our results do not constrain the tremor locations, but comparisons of earthquake and tremor reduced displacements recorded locally and regionally suggest a deeper tremor source. We interpret the increase in earthquake size and rate, together with the occurrence, characteristics, and relative depth of the tremor to be the result of magmatic activity beneath Taʻū Island volcano.","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-025-01798-0","usgsCitation":"Wech, A., Haney, M.M., Chang, J., Jolly, A., Yoon, C., and Skoumal, R.J., 2025, Local, regional, and distal recordings of seismic unrest at Tau Island volcano, American Samoa: Bulletin of Volcanology, v. 87, 15, 15 p., https://doi.org/10.1007/s00445-025-01798-0.","productDescription":"15, 15 p.","ipdsId":"IP-172244","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":483947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"American Samoa, Taʻū Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -169.53339284390117,\n -14.197912338111138\n ],\n [\n -169.53339284390117,\n -14.283297461659885\n ],\n [\n -169.4061487117877,\n -14.283297461659885\n ],\n [\n -169.4061487117877,\n -14.197912338111138\n ],\n [\n -169.53339284390117,\n -14.197912338111138\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2025-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":932148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":932149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chang, Jefferson 0000-0002-1258-589X","orcid":"https://orcid.org/0000-0002-1258-589X","contributorId":215608,"corporation":false,"usgs":true,"family":"Chang","given":"Jefferson","email":"","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":932150,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jolly, A.D. 0000-0003-1020-9062","orcid":"https://orcid.org/0000-0003-1020-9062","contributorId":296487,"corporation":false,"usgs":true,"family":"Jolly","given":"A.D.","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":932151,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yoon, Clara 0000-0003-4521-3889","orcid":"https://orcid.org/0000-0003-4521-3889","contributorId":222019,"corporation":false,"usgs":true,"family":"Yoon","given":"Clara","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":932152,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skoumal, Robert J. 0000-0002-5627-6239 rskoumal@usgs.gov","orcid":"https://orcid.org/0000-0002-5627-6239","contributorId":191213,"corporation":false,"usgs":true,"family":"Skoumal","given":"Robert","email":"rskoumal@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":932153,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263819,"text":"70263819 - 2025 - Long-term trends in microseismicity during operational shut-ins at the Coso Geothermal Field, California","interactions":[],"lastModifiedDate":"2025-02-25T15:34:45.908287","indexId":"70263819","displayToPublicDate":"2025-02-10T08:29:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"Long-term trends in microseismicity during operational shut-ins at the Coso Geothermal Field, California","docAbstract":"Pausing injection and production can lead to induced seismicity in a variety of settings, with some of the largest events occurring during these so-called shut-ins. In geothermal fields, shut-ins are periodically conducted for maintenance on wells and surface infrastructure, thereby offering recurring means of estimating stress changes in the subsurface that lead to increased seismicity rates. Here, we examine daily production and microseismicity data from the Coso Geothermal Field (CGF) in California between 1996 and 2010 to investigate the repetitive trends of operational shut-in microseismicity. Using 24 local seismic stations, we first analyze spatial and temporal trends of over 60,000 earthquakes with magnitudes between -0.4 to 3.8. We find that the northern region exhibits no significant seismicity changes during shut-ins, whereas the rest of the field experiences induced seismicity during almost every shut-in with an increasing intensity towards the southern and eastern portions of the field, highlighting local differences in stress within the CGF. Additionally, we cluster the seismicity using waveform cross-correlation, revealing several earthquake clusters primarily occurring during shut-in periods. These observations suggest that certain fracture and fault sections respond quicker to changes in pore pressure and poroelastic stresses within the geothermal system, possibly highlighting main fluid pathways.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320240041","usgsCitation":"Holmgren, J., Kaven, J., and Oye, V., 2025, Long-term trends in microseismicity during operational shut-ins at the Coso Geothermal Field, California: The Seismic Record, v. 5, no. 1, p. 73-82, https://doi.org/10.1785/0320240041.","productDescription":"10 p.","startPage":"73","endPage":"82","ipdsId":"IP-170795","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320240041","text":"Publisher Index Page"},{"id":482446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Coso Geothermal Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.93842593182427,\n 36.34881073898275\n ],\n [\n -117.93842593182427,\n 36.12479363858705\n ],\n [\n -117.62601162670973,\n 36.12479363858705\n ],\n [\n -117.62601162670973,\n 36.34881073898275\n ],\n [\n -117.93842593182427,\n 36.34881073898275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Holmgren, Joanna","contributorId":351460,"corporation":false,"usgs":false,"family":"Holmgren","given":"Joanna","affiliations":[{"id":18074,"text":"NORSAR","active":true,"usgs":false}],"preferred":false,"id":928536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaven, J. Ole 0000-0003-2625-2786 okaven@usgs.gov","orcid":"https://orcid.org/0000-0003-2625-2786","contributorId":3993,"corporation":false,"usgs":true,"family":"Kaven","given":"J. Ole","email":"okaven@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oye, Volker","contributorId":194795,"corporation":false,"usgs":false,"family":"Oye","given":"Volker","email":"","affiliations":[],"preferred":false,"id":928538,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70264040,"text":"70264040 - 2025 - Highly pathogenic avian influenza virus H5N1 in double-crested cormorants (Nannopterum auritum) of the Chesapeake Bay, USA","interactions":[],"lastModifiedDate":"2025-05-28T14:49:29.252868","indexId":"70264040","displayToPublicDate":"2025-02-06T08:00:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Highly pathogenic avian influenza virus H5N1 in double-crested cormorants (Nannopterum auritum) of the Chesapeake Bay, USA","docAbstract":"Double-crested Cormorants (Nannopterum auritum) have historically exhibited low levels of infection and antibodies to avian influenza virus (AIV). The recent global expansion of clade 2.3.4.4b A/goose/Guangdong/1/1996 highly pathogenic (HP) avian influenza virus H5N1 (HPAI H5N1) has resulted in large-scale mortalities across diverse waterbird taxa including cormorants. We sampled 32 and 29 Double-crested Cormorants breeding in the Chesapeake Bay, US, during the summers of 2023 and 2024, respectively, to assess HPAI H5N1 infection and AIV antibodies. Although no mortality was observed in the area, one bird sampled in 2023 was infected with HPAI H5N1. Additionally, 21/31 individuals in 2023 and 10/25 individuals in 2024 for which sera were collected had AIV antibodies. Based on additional testing using hemagglutination inhibition, virus neutralization, and an enzyme-linked lectin assay, 94 and 100% (2023 and 2024, respectively) of the seropositive birds tested positive for antibodies to both H5 and N1, suggesting previous infection with HPAI H5N1. These results are consistent with survival and limited clinical effects related to HPAI H5N1 infections. Furthermore, these results suggest that population immunity to HPAI H5N1 within the Chesapeake Bay might reduce future infections and potential population impacts should HP H5N1 remain on the landscape, though immunity may be waning across time. Because results are based on a single population, additional testing for both infection and antibodies as well as continued monitoring could enhance understanding of antibody persistence.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/jwd-d-24-00111","usgsCitation":"Harvey, J., Sullivan, J., Poulson, R., Carter, D.L., Driscoll, C.P., McGowan, P.C., Callahan, C.R., O'Donnell, A., Mullinax, J.M., Stallknecht, D., and Prosser, D.J., 2025, Highly pathogenic avian influenza virus H5N1 in double-crested cormorants (Nannopterum auritum) of the Chesapeake Bay, USA: Journal of Wildlife Diseases, v. 61, no. 2, p. 348-356, https://doi.org/10.7589/jwd-d-24-00111.","productDescription":"9 p.","startPage":"348","endPage":"356","ipdsId":"IP-166564","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":482915,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.8702033385699,\n 39.65270512692044\n ],\n [\n -76.71510396799904,\n 39.65270512692044\n ],\n [\n -76.71510396799904,\n 36.82223050001578\n ],\n [\n -75.8702033385699,\n 36.82223050001578\n ],\n [\n -75.5415430693737,\n 37.907513139633274\n ],\n [\n -75.8702033385699,\n 39.65270512692044\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"61","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Johanna Alexandra 0000-0003-4504-6777","orcid":"https://orcid.org/0000-0003-4504-6777","contributorId":351781,"corporation":false,"usgs":true,"family":"Harvey","given":"Johanna Alexandra","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":929570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Jeffery Dale 0009-0005-9759-5964","orcid":"https://orcid.org/0009-0005-9759-5964","contributorId":351825,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery Dale","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":929571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":929572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, Deborah L.","contributorId":335924,"corporation":false,"usgs":false,"family":"Carter","given":"Deborah","email":"","middleInitial":"L.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":929573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Driscoll, Cindy P.","contributorId":190850,"corporation":false,"usgs":false,"family":"Driscoll","given":"Cindy","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":929574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":929575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":929576,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"O'Donnell, Amy W.","contributorId":351827,"corporation":false,"usgs":false,"family":"O'Donnell","given":"Amy W.","affiliations":[{"id":84062,"text":"Fish and Wildlife Health Program","active":true,"usgs":false}],"preferred":false,"id":929577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mullinax, Jennifer M.","contributorId":221170,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":929578,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stallknecht, David E.","contributorId":225107,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David E.","affiliations":[{"id":36701,"text":"Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":929579,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":929580,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70263761,"text":"70263761 - 2025 - AAPG Energy and Minerals Division Tight Oil and Gas Committee Activities and Commodity Report for 2021-2022: Tuscaloosa Marine Shale, Gulf Coast basin, Louisiana and Mississippi","interactions":[],"lastModifiedDate":"2025-06-04T15:03:25.689798","indexId":"70263761","displayToPublicDate":"2025-02-01T09:56:41","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":21809,"text":"AAPG Wiki","active":true,"publicationSubtype":{"id":32}},"title":"AAPG Energy and Minerals Division Tight Oil and Gas Committee Activities and Commodity Report for 2021-2022: Tuscaloosa Marine Shale, Gulf Coast basin, Louisiana and Mississippi","docAbstract":"The Upper Cretaceous Tuscaloosa marine shale (TMS) potential production area encompasses 20.4 million acres across central Louisiana (LA), southern Mississippi (MS), southwestern Alabama (AL), and a small southwestern section of the Florida panhandle (Hackley et al., 2018). It remains a minor and largely undeveloped unconventional shale oil play with production from the TMS confined along the east-west LA-MS State boundary (Fig. 1). The mean undiscovered, technically recoverable resources in the TMS are estimated at 1.5 billion barrels of oil and 4.6 trillion cubic feet of gas (Hackley et al., 2018). Geochemical analyses of source rock solvent extracts and oil samples indicate that, in the play area, the TMS is the primary source of shale oil produced from the TMS as well as of accumulated oils in the underlying conventional reservoirs of the lower Tuscaloosa (Hackley et al., 2020). The API gravity of TMS oils ranges from approximately 34 to 46 degrees (Hackley et al., 2020; Croke et al., 2020).
","language":"English","publisher":"AAPG Energy and Minerals Division Tight Oil and Gas Committee","doi":"10.13140/RG.2.2.29579.40488","collaboration":"American Association of Petroleum Geologists","usgsCitation":"Lohr, C., 2025, AAPG Energy and Minerals Division Tight Oil and Gas Committee Activities and Commodity Report for 2021-2022: Tuscaloosa Marine Shale, Gulf Coast basin, Louisiana and Mississippi: AAPG Wiki, https://doi.org/10.13140/RG.2.2.29579.40488.","productDescription":"8 p.","ipdsId":"IP-176031","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":489572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lohr, Celeste D. 0000-0001-6287-9047 clohr@usgs.gov","orcid":"https://orcid.org/0000-0001-6287-9047","contributorId":3866,"corporation":false,"usgs":true,"family":"Lohr","given":"Celeste D.","email":"clohr@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":928151,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70267865,"text":"70267865 - 2025 - Is sexual size dimorphism in walleye, Sander vitreus, a driver of seasonal movements in Lake Erie?","interactions":[],"lastModifiedDate":"2025-06-06T13:30:52.332192","indexId":"70267865","displayToPublicDate":"2025-02-01T08:15:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"title":"Is sexual size dimorphism in walleye, Sander vitreus, a driver of seasonal movements in Lake Erie?","docAbstract":"Walleye (Sander vitreus) are a sexually dimorphic species in which females are larger than males in adulthood. Walleye can also exhibit sex- and population-based differences in migration behavior. In Lake Erie, we used acoustic telemetry to test the prediction that female walleye exhibit larger broad-scale movements than males during the summer and autumn. This prediction was based on the hypothesis that greater foraging in females would be needed to satisfy their higher energy requirements. We quantified movements of males and females from distinct spawning populations from Lake Erie's west and east basins using a lake-wide grid of acoustic receivers in 2017 and 2018. We found no differences between male and female home range sizes, core range sizes, or distances travelled in either population. Fish length-at-tagging was unrelated to the size of a fish's home range or to its distance travelled, contrary to previous predictions about body size as a driver of migration distance in the Lake Erie population. We found that west basin walleye occupied large and indiscrete portions of the lake, but the core range of females extended into the central basin, whereas males were concentrated in the west basin. Walleye originating from the east basin confined their movements primarily to the east basin and showed stronger home range overlap among members of their population than did walleye from the west basin population. Within either population, walleye had more home range overlap with members of the same sex, which likely reflects differences in the migratory tendencies of males and females.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.15960","usgsCitation":"Bihun, C., Faust, M., Kraus, R., MacDougall, T., Robinson, J., Vandergoot, C., and Raby, G., 2025, Is sexual size dimorphism in walleye, Sander vitreus, a driver of seasonal movements in Lake Erie?: Journal of Fish Biology, v. 106, no. 2, p. 430-441, https://doi.org/10.1111/jfb.15960.","productDescription":"12 p.","startPage":"430","endPage":"441","ipdsId":"IP-165223","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":490640,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/jfb.15960","text":"External Repository"},{"id":489690,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.3340237734879,\n 42.2003107892165\n ],\n [\n -83.76123811265276,\n 41.36759241460828\n ],\n [\n -81.80316880718208,\n 41.3146825621337\n ],\n [\n -78.64522615109004,\n 42.56891605267103\n ],\n [\n -78.69689358833503,\n 42.91401349265345\n ],\n [\n -79.6373646641363,\n 43.07393720267635\n ],\n [\n -81.57717526647028,\n 42.625802175312444\n ],\n [\n -83.3340237734879,\n 42.2003107892165\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"106","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-10-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Bihun, Christian J.","contributorId":356358,"corporation":false,"usgs":false,"family":"Bihun","given":"Christian J.","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":939170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faust, Matthew","contributorId":268770,"corporation":false,"usgs":false,"family":"Faust","given":"Matthew","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":939171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":939172,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacDougall, Thomas","contributorId":354792,"corporation":false,"usgs":false,"family":"MacDougall","given":"Thomas","affiliations":[{"id":84663,"text":"Ontario Ministry of Nat. Res. and Forestry","active":true,"usgs":false}],"preferred":false,"id":939173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robinson, Jason","contributorId":216164,"corporation":false,"usgs":false,"family":"Robinson","given":"Jason","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":939174,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vandergoot, Christopher","contributorId":340837,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christopher","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":939175,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Raby, Graham D.","contributorId":189592,"corporation":false,"usgs":false,"family":"Raby","given":"Graham D.","affiliations":[],"preferred":false,"id":939176,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263174,"text":"ofr20241074 - 2025 - Reproductive parameters in invasive blue catfish (Ictalurus furcatus) from tributaries of the Chesapeake Bay in Maryland and Delaware, 2020–22","interactions":[],"lastModifiedDate":"2025-02-06T19:55:23.808466","indexId":"ofr20241074","displayToPublicDate":"2025-01-31T11:30:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1074","displayTitle":"Reproductive Parameters in Invasive Blue Catfish (Ictalurus furcatus) From Tributaries of the Chesapeake Bay in Maryland and Delaware, 2020–22","title":"Reproductive parameters in invasive blue catfish (Ictalurus furcatus) from tributaries of the Chesapeake Bay in Maryland and Delaware, 2020–22","docAbstract":"Over the past few decades, Ictalurus furcatus (Valenciennes in Cuvier and Valenciennes, 1840; blue catfish) have become a formidable invasive species in tidal tributaries of the Chesapeake Bay in Maryland and Delaware. Knowledge of their reproductive behaviors can support managers in the determination of ideal timing and implementation of mitigation strategies. In 2020–22, the U.S. Geological Survey sampled blue catfish from the Chesapeake Bay’s tidal reaches of the Nanticoke River, Broad Creek, Marshyhope Creek, and Patuxent River in Maryland and Delaware from March to October. All fish were analyzed with histology to assess reproductive stages (immature, pre-spawn [early and late], and post-spawn). Plasma was collected for multiple endpoints including 17β-estradiol (E2), calcium, and total protein. Results indicated that female spawning generally occurred from late April through June, as evidenced by the histological data showing that the number of vitellogenic oocytes in late pre-spawn females began to increase in April, peaked in May, and gradually declined through July. In males, the greatest number of late pre-spawn individuals was observed in April and gradually declined through June. Additionally, female E2 levels were highest in late, pre-spawn females, thus showing a similar trend as the histological results, indicating that this endpoint can be used for assessing reproductive changes over time. Collectively, this study documents typical spawning patterns in blue catfish within the Chesapeake Bay watershed. However, further research across different watersheds would enhance data availability and inform more comprehensive management strategies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20241074","usgsCitation":"Walsh, H.L., Densmore, C.L., Regish, A.M., Norstog, J., Moore, J., Williams, B., Bressman, N., and Crum, Z., 2025, Reproductive parameters in invasive blue catfish (Ictalurus furcatus) from tributaries of the Chesapeake Bay in Maryland and Delaware, 2020–22: U.S. Geological Survey Open-File Report 2024–1074, 17 p., https://doi.org/10.3133/ofr20241074.","productDescription":"Report: vi, 17 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171688","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":481526,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1074/images"},{"id":481525,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13W8K3Y","text":"USGS data release","linkHelpText":"Morphometric and reproductive data from blue catfish (Ictalurus furcatus) collected in tributaries of the Chesapeake Bay, Maryland and Delaware 2020–2022"},{"id":481522,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1074/ofr20241074.pdf","text":"Report","size":"4.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1074"},{"id":481521,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1074/coverthb.jpg"},{"id":481555,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241074/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1074"},{"id":481527,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1074/ofr20241074.xml"}],"country":"United States","state":"Delaware, Maryland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.56331116045253,\n 38.61088599742371\n ],\n [\n -75.82395278530792,\n 38.61088599742371\n ],\n [\n -75.82395278530792,\n 38.38925412638224\n ],\n [\n -75.56331116045253,\n 38.38925412638224\n ],\n [\n -75.56331116045253,\n 38.61088599742371\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Rd.
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During an effusive eruption crisis the initial advance of a lava flow is typically the primary focus of model forecasts and hazard management efforts. Flow branching and lateral expansion of lava flows can pose significant dangers within evolving flow fields throughout the duration of an eruption and are an underappreciated hazard. We use field monitoring, infrasound, time lapse imagery, and lidar data collected during the 2018 lower East Rift Zone eruption of Kīlauea (Hawai‘i) to track the origins, progression, and implications of a flow branching event caused by catastrophic levee failure. Our analyses show that surges in effusion rate, rheologic transitions between pāhoehoe and ‘a‘ā flow regimes, slope-breaks, pre-existing topographic highs, and the structure of perched levee walls all played a role in the failure of the levee and subsequent re-routing of the lava flow. Failure of perched lava structures leads to an acutely hazardous situation because lava impounded by the structure can rapidly inundate the landscape. This is the first time a levee failure event has been observed in such detail with numerous monitoring techniques; this unprecedented level of observation provides quantifiable insights into levee failure processes that have important implications for hazard mitigation and an improved understanding of lava flow emplacement dynamics.
","language":"English","publisher":"Presses universitaires de Strasbourg","doi":"10.30909/vol.08.01.6780","usgsCitation":"Gallant, E., Dietterich, H., Patrick, M.R., Hyman, D., Carr, B., Lyons, J.J., and Meredith, E.S., 2025, Catastrophic lava flow levee failure: Precursors, processes, and implications: Volcanica, v. 8, no. 1, p. 67-80, https://doi.org/10.30909/vol.08.01.6780.","productDescription":"14 p.","startPage":"67","endPage":"80","ipdsId":"IP-166006","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":487712,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol.08.01.6780","text":"Publisher Index Page"},{"id":482644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154.9167,\n 19.5\n ],\n [\n -154.9167,\n 19.4333\n ],\n [\n -154.8,\n 19.4333\n ],\n [\n -154.8,\n 19.5\n ],\n [\n -154.9167,\n 19.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Gallant, Elisabeth 0000-0001-6841-3694","orcid":"https://orcid.org/0000-0001-6841-3694","contributorId":339872,"corporation":false,"usgs":false,"family":"Gallant","given":"Elisabeth","affiliations":[{"id":81292,"text":"University of Hawaiʻi at Hilo","active":true,"usgs":false}],"preferred":false,"id":929079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":929080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":929081,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hyman, David Matthew 0000-0002-9607-7584","orcid":"https://orcid.org/0000-0002-9607-7584","contributorId":351609,"corporation":false,"usgs":true,"family":"Hyman","given":"David Matthew","affiliations":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":929082,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carr, Brett B 0000-0002-1033-3082","orcid":"https://orcid.org/0000-0002-1033-3082","contributorId":251755,"corporation":false,"usgs":false,"family":"Carr","given":"Brett B","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":929083,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":929084,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meredith, Elinor S. 0000-0002-3869-1180","orcid":"https://orcid.org/0000-0002-3869-1180","contributorId":270269,"corporation":false,"usgs":false,"family":"Meredith","given":"Elinor","email":"","middleInitial":"S.","affiliations":[{"id":56128,"text":"Earth Observatory of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":929085,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263441,"text":"70263441 - 2025 - “Leaky weirs” capture alluvial deposition and enhance seasonal mountain-front recharge in dryland streams","interactions":[],"lastModifiedDate":"2025-02-12T14:10:12.583226","indexId":"70263441","displayToPublicDate":"2025-01-25T09:04:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20072,"text":"Applied Water Science","active":true,"publicationSubtype":{"id":10}},"title":"“Leaky weirs” capture alluvial deposition and enhance seasonal mountain-front recharge in dryland streams","docAbstract":"“Leaky weirs” are rock structures installed in dryland streams, which are anchored into exposed bedrock, loosely cemented, and designed to allow water to slowly pass through. They are being tested at a ranch in southeastern Arizona, USA, to restore and conserve the historic range and desert wetlands. Data are collected to assess how leaky weirs impact surface water, subsurface water, and groundwater recharge—including stream discharge, timing, and depth of infiltration, and groundwater elevations. Three adjacent watersheds, two with outlets just below leaky weirs and one with leaky weirs farther upstream, were instrumented with water-level loggers, wildlife cameras, and crest stage instruments with temperature sensors in the soil. As most groundwater recharge is assumed to be focused along the mountain fronts in this region, mountain-block recharge is also evaluated to differentiate between the two using isotope analyses. Finally, a single, late-season flood event is scrutinized to consider the leaky weir effect on all monitored components in the water budget. Results indicated groundwater flow is primarily from the mountains to the east via older, regional mountain-block recharge. However, the development of shallow alluvial aquifers is supported by the leaky weirs, that slow flows, capture permeable sediments, and allow infiltration, thus enhancing mountain-front recharge. In turn, these new pockets of water help support the restoration of historic wetlands. Sediment accumulates where leaky weirs are installed, reducing flashy peak flows, and resulting in a series of infiltration ponds along the channel that support vegetation during growing seasons and recharge the shallow aquifer during non-growing seasons.
","language":"English","publisher":"Springer","doi":"10.1007/s13201-025-02371-y","usgsCitation":"Norman, L., Uhlman, K., Coy, H., Wilson, N., Bennett, A., Gray, F., and Ehrenberg, K., 2025, “Leaky weirs” capture alluvial deposition and enhance seasonal mountain-front recharge in dryland streams: Applied Water Science, v. 15, 29, 27 p., https://doi.org/10.1007/s13201-025-02371-y.","productDescription":"29, 27 p.","ipdsId":"IP-157242","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":488063,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13201-025-02371-y","text":"Publisher Index Page"},{"id":481927,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.333333,\n 32.283333\n ],\n [\n -109.916667,\n 32.283333\n ],\n [\n -109.916667,\n 31.5\n ],\n [\n -109.333333,\n 31.5\n ],\n [\n -109.333333,\n 32.283333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":927001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uhlman, Kristine;","contributorId":167093,"corporation":false,"usgs":false,"family":"Uhlman","given":"Kristine;","email":"","affiliations":[{"id":17599,"text":"Texas Bureau of Economic Geology","active":true,"usgs":false}],"preferred":false,"id":927002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coy, Hanna","contributorId":350793,"corporation":false,"usgs":false,"family":"Coy","given":"Hanna","affiliations":[{"id":83830,"text":"U.S. Geological Survey, Arizona Water Science Center (Ret.)","active":true,"usgs":false}],"preferred":false,"id":927003,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Natalie R. 0000-0001-5145-1221","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":202534,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":927004,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bennett, Andrew M.","contributorId":350794,"corporation":false,"usgs":false,"family":"Bennett","given":"Andrew M.","affiliations":[{"id":83831,"text":"Contracter","active":true,"usgs":false}],"preferred":false,"id":927005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gray, Floyd 0000-0002-0223-8966","orcid":"https://orcid.org/0000-0002-0223-8966","contributorId":201529,"corporation":false,"usgs":true,"family":"Gray","given":"Floyd","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":927006,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ehrenberg, Kurt T.","contributorId":350795,"corporation":false,"usgs":false,"family":"Ehrenberg","given":"Kurt T.","affiliations":[{"id":83832,"text":"U.S. Geological Survey, Arizona Water Science Center, 520 N. Park Avenue, Tucson, AZ 85719","active":true,"usgs":false}],"preferred":false,"id":927007,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}