Rationale
Vein calcite in Devils Hole has been precipitating continuously in oxygen-isotope equilibrium at a constant temperature for over 500 000 years, providing an unmatched δ18O paleoclimate time series. A substantial issue is that coeval calcite (based on matching δ18O values) has uranium-series ages differing by 12 000 years.
Methods
An unparalleled high-accuracy δ18O chronology series from continuously submerged calcite was used to correct the published uranium-series ages of non-continuously formed calcite in two cores, cyclically exposed by water-table decline during glacial–interglacial transitions. This method relies on the premise that the δ18O values of coevally precipitated calcite are identical, allowing matching calcite δ18O values to establish formation ages.
Results
Exposed calcite can have apparent ages that are 12 000 years too young due to unrecognized uranium mobility and resulting mixed ages identified in over 50 mixed uranium-series ages from previous studies. Secondary uranium in fluids, sourced from the formation or dissolution of porous carbonate deposits (folia) with high uranium-238 (238U) concentrations, has migrated up to 10 mm into vein calcite.
Conclusions
The continuously submerged Devils Hole δ18O chronology is not explained by orbital forcing. Rather, this chronology represents a regional climate record in the southern Great Basin of sea-surface-temperature (SST) variations off California, variations that preceded the last and penultimate deglaciations by 5000 to approximately 10 000 years. Temporal discrepancies between the continuously submerged Devils Hole chronology and other regional δ18O records (e.g., the Leviathan chronology) can be explained by unrecognized cryptic, pernicious uranium mobility, leading to model estimations that may be thousands of years younger than actual ages. Consequently, paleo-moisture availability, water-table, and groundwater recharge models based on these mixed uranium-series ages are too young by as much as 12 000 years. The potential for post-formation uranium addition in subaerial cores and speleothems underscores the need for caution in uranium-series dating, highlighting δ18O time-series comparisons as a method for identifying mixed ages.
","language":"English","publisher":"Wiley","doi":"10.1002/rcm.9926","usgsCitation":"Coplen, T.B., Seal,, R., Reid, L.T., Jordan, J., and Mumford, A.C., 2024, Using stable oxygen isotope dual-inlet isotope-ratio mass spectrometry to elucidate uranium transport and mixed 230Th/U calcite formation ages at the seminal Devils Hole, Nevada, natural laboratory: Rapid Communications in Mass Spectrometry, v. 39, no. 3, e9926, 18 p., https://doi.org/10.1002/rcm.9926.","productDescription":"e9926, 18 p.","ipdsId":"IP-094999","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":481048,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/rcm.9926","text":"External Repository"},{"id":480997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Great Basin, Devils Hole","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.79795852135467,\n 40.12275342984714\n ],\n [\n -116.79795852135467,\n 35.9796450622334\n ],\n [\n -113.93379652706551,\n 35.9796450622334\n ],\n [\n -113.93379652706551,\n 40.12275342984714\n ],\n [\n -116.79795852135467,\n 40.12275342984714\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":924884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seal,, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":141204,"corporation":false,"usgs":true,"family":"Seal,","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":924885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reid, Lauren T 0000-0003-3872-9596","orcid":"https://orcid.org/0000-0003-3872-9596","contributorId":243302,"corporation":false,"usgs":true,"family":"Reid","given":"Lauren","email":"","middleInitial":"T","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":924886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jordan, James A 0000-0002-7419-8465","orcid":"https://orcid.org/0000-0002-7419-8465","contributorId":349815,"corporation":false,"usgs":true,"family":"Jordan","given":"James A","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":924887,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mumford, Adam C. 0000-0002-8082-8910 amumford@usgs.gov","orcid":"https://orcid.org/0000-0002-8082-8910","contributorId":171791,"corporation":false,"usgs":true,"family":"Mumford","given":"Adam","email":"amumford@usgs.gov","middleInitial":"C.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":924888,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261071,"text":"sir20245089 - 2024 - Mapping karst groundwater flow paths and delineating recharge areas for springs in the Little Sequatchie and Pryor Cove watersheds, Tennessee","interactions":[],"lastModifiedDate":"2025-12-22T20:39:12.793493","indexId":"sir20245089","displayToPublicDate":"2024-11-22T16:23:22","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5089","displayTitle":"Mapping Karst Groundwater Flow Paths and Delineating Recharge Areas for Springs in the Little Sequatchie and Pryor Cove Watersheds, Tennessee","title":"Mapping karst groundwater flow paths and delineating recharge areas for springs in the Little Sequatchie and Pryor Cove watersheds, Tennessee","docAbstract":"The Little Sequatchie River and Pryor Cove Branch, in southern Tennessee, drain the eastern escarpment of the Cumberland Plateau to the Sequatchie River near the southern end of the Sequatchie Valley. The Little Sequatchie River is the largest tributary to the Sequatchie River by drainage area, covering over 120 square miles. The hydrology of the two drainage areas has been largely altered by karst processes, which has caused the majority of the streams to sink at the contact between the Mississippian Pennington Formation and the underlying Mississippian Bangor Limestone. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service and Tennessee Department of Environment and Conservation, initiated a study in 2021 to map the karst groundwater pathways in both watersheds in order to delineate recharge areas for several springs. One of these springs, Sequatchie Cave, represents a significant habitat for two Species of Greatest Conservation Need, the Glyphopsyche sequatchie (Sequatchie caddisfly) and the federally endangered Marstonia ogmorhaphe (royal marstonia). Springs and springflow-dominated streams in the Little Sequatchie River valley and Pryor Cove also provide water for agricultural practices and serve as a drinking water source for nearby communities. During the study, a total of 25 dye injections were conducted over eight rounds from January 2022 through March 2023. Dye traces from these injections helped to delineate recharge areas for six major springs, ranging from 7.3 to 65.2 square miles in area. The majority of the dye traces remained subsurface (from sinkpoint to recovery site) for long distances, with karst groundwater travelling nearly 8 miles before resurfacing. The dye traces also had rapid traveltimes, often travelling hundreds to thousands of feet per hour. The goal of this project was to provide scientific data related to karst groundwater pathways and spring recharge areas to aid State and Federal agencies in making informed decisions to protect and preserve this unique and vulnerable karst system.
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Contact Us- USGS Publications Warehouse
","tableOfContents":"The U.S. Geological Survey constructed a two-dimensional hydrodynamic model that was applied to a 15.8-mile tailwater reach of the Colorado River in Glen Canyon that begins 0.25 mile downstream from Glen Canyon Dam and extends to Lees Ferry in Glen Canyon National Recreation Area, Arizona. The model used the Flow and Sediment Transport with Morphological Evolution of Channels (FaSTMECH) solver in the International River Interface Cooperative (iRIC) modeling interface. The model grid was developed from a full channel digital elevation model derived by combining bathymetric and topographic data collected from March 2013 to February 2016. The model was used to predict water-surface elevations, depths, depth-averaged flow velocities, and bed shear stresses for discharges ranging from 1,000 to 70,000 cubic feet per second. Modeled water-surface elevations matched well with measured values at cross sections throughout the reach, with a mean absolute error of 0.14 meter over the range of typical discharge releases from Glen Canyon Dam. The mean error on discharge, a measure of how well the model solution converged, averaged 0.6 percent and did not exceed 2 percent over the range of discharges modeled. These results indicate that model predictions of hydraulic parameters are reasonably accurate and suitable for use for a variety of purposes, such as ecological and geomorphic modeling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1197","usgsCitation":"Wright, S.A., Kaplinski, M.A., and Grams, P.E., 2024, Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona: U.S. Geological Survey Data Report 1197, 9 p., https://doi.org/10.3133/dr1197.","productDescription":"Report: v, 9 p.; Data Release","numberOfPages":"9","onlineOnly":"Y","ipdsId":"IP-161399","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":464434,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1197/dr1197.XML"},{"id":464432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1197/coverthb.jpg"},{"id":497908,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117828.htm","linkFileType":{"id":5,"text":"html"}},{"id":464437,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1QTRNEB","text":"USGS Data Release","description":"Wright, S.A., Kaplinski, M., and Grams, P.E., 2024, Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona—Tables of model results and accuracy assessment: U.S. Geological Survey data release, https://doi.org/10.5066/P1QTRNEB.","linkHelpText":"Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona—Tables of model results and accuracy assessment"},{"id":464436,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1197/full"},{"id":464435,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1197/images"},{"id":464433,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1197/dr1197.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Glen Canyon Dam, Lees Ferry","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.45495155269207,\n 36.96381776712943\n ],\n [\n -111.62114273826977,\n 36.96381776712943\n ],\n [\n -111.62114273826977,\n 36.820663467737276\n ],\n [\n -111.45495155269207,\n 36.820663467737276\n ],\n [\n -111.45495155269207,\n 36.96381776712943\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Director, National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Site 11 is a former landfill at North Chevalier Field Disposal Area in Operable Unit 2 at Naval Air Station Pensacola, in northwest Florida. Site 11 is adjacent to Bayou Grande, a shallow, tidally influenced, saline estuary of the Pensacola Bay watershed. Federal and Florida regulators have expressed concern that contaminants detected in groundwater beneath the inland parts of Site 11 may discharge to Bayou Grande. In 2017, the Department of Defense, U.S. Navy, Naval Facilities Engineering Systems Command Southeast asked the U.S. Geological Survey to assess the occurrence of fresh groundwater discharge to Bayou Grande at Site 11 and to delineate to the extent practicable the location of groundwater discharge. Between 2018 and 2022, the U.S. Geological Survey used a multiple-lines-of-evidence approach that included a visual method and three physical methods based on the temperature difference between groundwater and surface water to assess groundwater discharge. One of the physically based methods also used the difference in specific conductance between fresh groundwater and brackish to saline surface water. Combined, the data indicate that fresh groundwater from across Site 11 discharges primarily along the shoreline of the northern and northeastern part of Site 11. The data also indicate that saline surface water from Bayou Grande intrudes tens of feet into the shallow aquifer beneath Site 11. The combined data indicate that the interface between fresh groundwater and saline surface water changes over space and time. Any new monitoring wells proposed for installation near the shoreline of Site 11 should include approaches to monitor the changes in the location of the freshwater/saltwater interface. Care would need to be taken to collect any groundwater samples at the correct season and tidal period to provide the highest probability of collecting a representative sample of Site 11 groundwater unaffected by saltwater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245058","issn":"2328-0328","collaboration":"Prepared in cooperation with the U.S. Navy Naval Facilities Engineering Systems Command Southeast","usgsCitation":"Landmeyer, J.E., McBride, W.S., Tripp, C.H., and Singletary, M.A., 2024, Assessment of fresh groundwater discharge and saline surface-water intrusion at Operable Unit 2, North Chevalier Field Disposal Area (Site 11), Naval Air Station Pensacola, Florida, 2018–22: U.S. Geological Survey Scientific Investigations Report 2024–5058, 45 p., https://doi.org/10.3133/sir20245058.","productDescription":"Report: x, 45 p.; Data Release","numberOfPages":"60","onlineOnly":"Y","ipdsId":"IP-130056","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":464357,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1WQEBHV","text":"USGS Data Release","linkHelpText":"- Specific conductance and fiber-optic distributed temperature sensing data collected at Operable Unit 2, North Chevalier Field Disposal Area (Site 11), Naval Air Station Pensacola, Florida, 2018–2022"},{"id":464399,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5058/images"},{"id":464356,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245058/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5058 HTML"},{"id":464355,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5058/sir20245058.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5058 XML"},{"id":464354,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5058/sir20245058.pdf","size":"11.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5058"},{"id":464353,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5058/coverthb.jpg"},{"id":497910,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117829.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"Naval Air Station Pensacola, North Chevalier Field Disposal Area (Site 11)","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.27464292788976,\n 30.36430517427192\n ],\n [\n -87.27464292788976,\n 30.355396636678606\n ],\n [\n -87.26488586538576,\n 30.355396636678606\n ],\n [\n -87.26488586538576,\n 30.36430517427192\n ],\n [\n -87.27464292788976,\n 30.36430517427192\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, suite 500
Norcross, GA 30093
Contact Us- USGS Publications Warehouse
","tableOfContents":"The introduction of HPAI H5N1 clade 2.3.4.4b viruses to North America in late 2021 resulted in avian influenza outbreaks in poultry, mortality events in many wild bird species, and spillover into many mammalian species. Reassortment events with North American low pathogenic virus were identified as early as February 2022 and over 100 genotypes have been characterized. Such diversity increases the complexity and time required for monitoring virus evolution. Here, we performed ordination and clustering analyses on sequence data from H5N1 viruses identified in North America between January 2020 to December 2023 to visualize virus genotypic diversity in poultry and wildlife populations. Our results reveal that ordination and cluster-based approaches can complement traditional phylogenetic analyses specifically for the preliminary assignment of H5N1 viruses to genotypic groups or to identify novel genotypes. Our study expands current knowledge on genotype diversity of H5N1 viruses in North America and describes a rapid approach for early virus genotype assignment.
","language":"English","publisher":"MDPI","doi":"10.3390/v16121818","usgsCitation":"Tawidian, P., Torchetti, M.K., Killian, M.L., Lantz, K., Dilione, K.E., Ringenberg, J.M., Bevins, S.N., Lenoch, J., and Ip, H., 2024, Genotypic clustering of H5N1 avian Influenza viruses in North America evaluated by ordination analysis: Viruses, v. 16, no. 12, 1818, 17 p., https://doi.org/10.3390/v16121818.","productDescription":"1818, 17 p.","ipdsId":"IP-170684","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":466747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v16121818","text":"Publisher Index Page"},{"id":465205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Tawidian, Patil 0000-0001-9727-6668","orcid":"https://orcid.org/0000-0001-9727-6668","contributorId":347249,"corporation":false,"usgs":true,"family":"Tawidian","given":"Patil","email":"","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":921139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torchetti, Mia K.","contributorId":252830,"corporation":false,"usgs":false,"family":"Torchetti","given":"Mia","email":"","middleInitial":"K.","affiliations":[{"id":50437,"text":"US Department of Agriculture – Veterinary Services, Ames, Iowa, USA","active":true,"usgs":false}],"preferred":false,"id":921140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Killian, Mary Lea","contributorId":247507,"corporation":false,"usgs":false,"family":"Killian","given":"Mary","email":"","middleInitial":"Lea","affiliations":[{"id":49560,"text":"National Veterinary Services Laboratories, USDA-APHIS, Ames, Iowa 50010, USA","active":true,"usgs":false}],"preferred":false,"id":921141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lantz, Kristina","contributorId":317920,"corporation":false,"usgs":false,"family":"Lantz","given":"Kristina","email":"","affiliations":[{"id":69192,"text":"National Veterinary Services Laboratories, Animal and Plant Health Inspection Service, USDA","active":true,"usgs":false}],"preferred":false,"id":921142,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dilione, Krista E. 0000-0001-6041-7877 kdilione@usgs.gov","orcid":"https://orcid.org/0000-0001-6041-7877","contributorId":347250,"corporation":false,"usgs":false,"family":"Dilione","given":"Krista","email":"kdilione@usgs.gov","middleInitial":"E.","affiliations":[{"id":83108,"text":"WS National Wildlife Disease Program, U.S. Department of Agriculture, Fort Collins, CO 80521, USA","active":true,"usgs":false}],"preferred":false,"id":921143,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ringenberg, Jourdan M.","contributorId":347253,"corporation":false,"usgs":false,"family":"Ringenberg","given":"Jourdan","email":"","middleInitial":"M.","affiliations":[{"id":83108,"text":"WS National Wildlife Disease Program, U.S. Department of Agriculture, Fort Collins, CO 80521, USA","active":true,"usgs":false}],"preferred":false,"id":921144,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bevins, Sarah N.","contributorId":212845,"corporation":false,"usgs":false,"family":"Bevins","given":"Sarah","email":"","middleInitial":"N.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":921145,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lenoch, Juliana","contributorId":347254,"corporation":false,"usgs":false,"family":"Lenoch","given":"Juliana","email":"","affiliations":[{"id":83108,"text":"WS National Wildlife Disease Program, U.S. Department of Agriculture, Fort Collins, CO 80521, USA","active":true,"usgs":false}],"preferred":false,"id":921146,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ip, Hon S. 0000-0003-4844-7533","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":126815,"corporation":false,"usgs":true,"family":"Ip","given":"Hon S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":921147,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260989,"text":"dr1200 - 2024 - Anatidae brood records in Maine during studies of Anas rubripes (American black duck), 1977–94","interactions":[],"lastModifiedDate":"2024-11-22T14:55:22.940618","indexId":"dr1200","displayToPublicDate":"2024-11-22T09:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1200","displayTitle":"Anatidae Brood Records in Maine During Studies of Anas rubripes (American Black Duck), 1977–94","title":"Anatidae brood records in Maine during studies of Anas rubripes (American black duck), 1977–94","docAbstract":"This report describes a compilation of brood observations for Anatidae species breeding in Maine during an 18-year period (1977–94) that were made by the U.S. Geological Survey’s Patuxent Wildlife Research Center while it was operated by the U.S. Fish and Wildlife Service. During four focused studies, variables affecting the declining Anas rubripes (Brewster, 1902) (American black duck, hereafter black duck) population were assessed. Broods were observed on seven geographical study sites within four study areas located in three of Maine’s five biophysical regions. For combined studies, 168 wetlands were monitored for broods.
The 1,907 recorded broods were distributed among study areas: 185 in Dixmont, 241 in Cherryfield and Beddington, 411 in Moosehorn, Baring Unit and Edmunds Unit, and 849 in Aroostook County, Agricultural and Forested sites. Additionally, 221 broods were recorded in the 117-hectare Downing Bog wetland at the Cherryfield site during annual evening visits made between 1985 and 1991. Twelve Anatidae species, mostly black duck (676), Aix sponsa (Linnaeus, 1758) (wood duck; 265), Aythya collaris (Donovan, 1809) (ring-necked duck; 246), and Lophodytes cucullatus (Linnaeus, 1758) (hooded merganser; 163) were observed. Only 139 broods of Anas platyrhynchos (Linnaeus, 1758) (mallard) were found; all but 9 broods were at the Aroostook County, Agricultural site. Branta canadensis (Linnaeus, 1758) (Canada goose) broods were found at the Aroostook County, Agricultural site (58) and Moosehorn, Baring Unit (97).
For the combined studies, 468 of 676 (69.2 percent) of black duck broods reached fledging age (Class IIc-III), whereas 93 of 139 (66.9 percent) of mallard broods reached fledging age. Black ducks used predominantly palustrine, emergent wetland; palustrine, forested wetland; and palustrine, scrub-shrub wetland. Of the 134 mallard broods observed at the Agricultural and Forested sites in Aroostook County, 130 (97.0 percent) were observed at the Agricultural site and 93 (71.5 percent) of them were recorded on two palustrine and two lacustrine, unconsolidated bottom class wetlands. Mean size of black duck, wood duck, and ring-necked duck broods in this report were similar to those reported from historic Maine data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1200","usgsCitation":"Longcore, J.R., Bunck, C.M., McAuley, D.G., and Clugston, D.A., 2024, Anatidae brood records in Maine during studies of Anas rubripes (American black duck), 1977–94: U.S. Geological Survey Data Report 1200, 25 p., https://doi.org/10.3133/dr1200.","productDescription":"Report: vii, 25 p.; Data Release","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-167393","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":464303,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1200/coverthb.jpg"},{"id":464308,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13TOYWG","text":"USGS data release","linkHelpText":"Waterfowl (Anatidae) Brood Data, 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\"}}]}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Population estimates are often required for identifying relationships between predators and their prey and to inform conservation and management actions. The random encounter model (REM) estimates population density of wildlife lacking individually unique markings, based on photographs or videos from remote camera-traps. However, the REM has strict sampling and input requirements that can be problematic, particularly for predators and other species which use landscapes non-randomly. Using data from a predator and its co-occurring prey, we found that placing cameras to target the predator, which may be implemented to achieve minimum sample sizes, inflated both predator and prey density estimates. Further, borrowing movement velocity (day range) values from other studies, species, or time periods caused substantial changes in density estimates. A comprehensive literature review revealed that 91% of REM density estimates in published predator–prey studies used data from non-random cameras or borrowed movement velocities and therefore did not satisfy REM requirements. Consequently, most REM density estimates from predator–prey ecology studies are likely not of the quality or reliability necessary for informing effective wildlife conservation or management.
","language":"English","publisher":"MDPI","doi":"10.3390/ani14233361","usgsCitation":"Murphy, S.M., Nolan, B., Chen, F., Longshore, K., Simes, M., Berr, G.A., and Esque, T., 2024, Most random-encounter-model density estimates in camera-based predator-prey studies are unreliable: Animals, v. 14, no. 23, 3361, 24 p., https://doi.org/10.3390/ani14233361.","productDescription":"3361, 24 p.","ipdsId":"IP-161802","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":489906,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani14233361","text":"Publisher Index Page"},{"id":481261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","city":"Boulder City","otherGeospatial":"Boulder City Conservation Easement","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.22729018400342,\n 35.97057404887106\n ],\n [\n -115.22729018400342,\n 35.82849801220463\n ],\n [\n -114.84083854402814,\n 35.82849801220463\n ],\n [\n -114.84083854402814,\n 35.97057404887106\n ],\n [\n -115.22729018400342,\n 35.97057404887106\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"23","noUsgsAuthors":false,"publicationDate":"2024-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Sean M. 0000-0002-9404-8878","orcid":"https://orcid.org/0000-0002-9404-8878","contributorId":346967,"corporation":false,"usgs":true,"family":"Murphy","given":"Sean","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":925093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nolan, Benjamin S.","contributorId":347691,"corporation":false,"usgs":false,"family":"Nolan","given":"Benjamin S.","affiliations":[],"preferred":false,"id":925094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, Felicia 0000-0002-7408-5946","orcid":"https://orcid.org/0000-0002-7408-5946","contributorId":210469,"corporation":false,"usgs":true,"family":"Chen","given":"Felicia","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":925095,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Longshore, Kathleen 0000-0001-6621-1271","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":216374,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":925096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simes, Matthew T.","contributorId":349895,"corporation":false,"usgs":false,"family":"Simes","given":"Matthew T.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":925097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Berr, Gabrielle A. 0009-0004-1531-7761","orcid":"https://orcid.org/0009-0004-1531-7761","contributorId":333759,"corporation":false,"usgs":false,"family":"Berr","given":"Gabrielle","email":"","middleInitial":"A.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":925098,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":925099,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70270927,"text":"70270927 - 2024 - Using crustal-scale refraction data of joint inversions of Rayleigh-wave dispersion curves and H/V spectral ratios for Atlantic Coastal Plain velocity structure, eastern U.S.","interactions":[],"lastModifiedDate":"2025-08-27T15:34:26.143803","indexId":"70270927","displayToPublicDate":"2024-11-22T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Using crustal-scale refraction data of joint inversions of Rayleigh-wave dispersion curves and H/V spectral ratios for Atlantic Coastal Plain velocity structure, eastern U.S.","docAbstract":"Shallow shear‐wave velocities (Vs) sometimes are estimated from joint inversions of horizontal‐to‐vertical (H/V) spectral ratios and surface‐wave dispersion curves derived from ambient noise or small active sources. Here, we evaluate carrying out these inversions using Rayleigh‐wave dispersion curves computed from crustal‐scale P‐wave seismic refraction data. We use data from the 2014–2015 Eastern North American Margin (ENAM) experiment in Virginia and North Carolina, but similar seismic refraction data sets have been acquired over sedimentary basins of interest for seismic hazard studies, including in major urban areas. The ENAM project deployed a pair of ∼215 km long, northwest–southeast linear arrays with ∼300 m receiver spacing to record 11 dynamite shots, and 80 continuously recording seismometers with 5–6 km spacing along the same arrays to record offshore airguns. The arrays crossed the onland portion of the Atlantic Coastal Plain sediments, which are a seaward‐thickening wedge of Cretaceous and younger sediments deposited mostly on crystalline bedrock. We compute Rayleigh‐wave dispersion curves from 3 to 9 km long portions of the receiver arrays on each side of the dynamite shots, and we compute ambient‐noise H/V ratios from the continuously recording seismometers. We use a genetic inversion algorithm in which forward velocity models in each “generation” are evaluated for misfits compared to the observed data, with subsequent generations constructed from the models with the smallest misfits. Velocities to depths of 500 m are defined well, as shown by a narrow range of velocities in the best‐fit models, by the consistency between multiple inversion runs at a site, and by forward modeling of site responses. The resulting velocity cross‐section of the Coastal Plain strata has seaward‐dipping contours in the thinner portions of the Coastal Plain but smaller dips in the deeper portions. We interpret these results as showing that velocity contours in the ACP strata are influenced by a combination of lithology and overburden pressure. Results demonstrate that existing seismic refraction data have the potential for determining detailed shallow shear‐wave velocity profiles.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230241","usgsCitation":"Pratt, T., Parolai, S., Poggi, V., and Dreossi, I., 2024, Using crustal-scale refraction data of joint inversions of Rayleigh-wave dispersion curves and H/V spectral ratios for Atlantic Coastal Plain velocity structure, eastern U.S.: Bulletin of the Seismological Society of America, v. 115, no. 1, p. 270-295, https://doi.org/10.1785/0120230241.","productDescription":"26 p.","startPage":"270","endPage":"295","ipdsId":"IP-167122","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":494950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"eastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.88300039003173,\n 39.731394919591565\n ],\n [\n -90.88300039003173,\n 24.876206992183768\n ],\n [\n -74.40455609054004,\n 24.876206992183768\n ],\n [\n -74.40455609054004,\n 39.731394919591565\n ],\n [\n -90.88300039003173,\n 39.731394919591565\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"115","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":201084,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":947394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parolai, Stefano 0000-0002-9084-7488","orcid":"https://orcid.org/0000-0002-9084-7488","contributorId":296105,"corporation":false,"usgs":false,"family":"Parolai","given":"Stefano","email":"","affiliations":[{"id":63989,"text":"Instituto Nazionale di Oceonografia","active":true,"usgs":false}],"preferred":false,"id":947395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poggi, Valerio","contributorId":360682,"corporation":false,"usgs":false,"family":"Poggi","given":"Valerio","affiliations":[{"id":86081,"text":"Trieste, Italy","active":true,"usgs":false}],"preferred":false,"id":947396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dreossi, Ilaria","contributorId":296107,"corporation":false,"usgs":false,"family":"Dreossi","given":"Ilaria","email":"","affiliations":[{"id":63991,"text":"National Institute of Oceanography and Applied Geophysics – OGS, Udine, Italy","active":true,"usgs":false}],"preferred":false,"id":947397,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261070,"text":"cir1544 - 2024 - U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33","interactions":[],"lastModifiedDate":"2024-12-02T19:00:36.118426","indexId":"cir1544","displayToPublicDate":"2024-11-21T15:57:46","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1544","displayTitle":"U.S. Geological Survey Earthquake Hazards Program Decadal Science Strategy, 2024–33","title":"U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33","docAbstract":"Earthquakes represent one of our Nation’s most significant and costly natural hazards, with estimated annual loses from earthquakes close to $15 billion in 2023. Over the past two centuries, 37 U.S. States have experienced an earthquake exceeding a magnitude of 5, and 50 percent of States have a significant potential for future damaging shaking; these statistics speak to the need for nationwide interest and investment in earthquake hazard characterization and risk reduction.
Authorized under the Earthquake Hazards Reduction Authorization Act, the U.S. Geological Survey (USGS) Earthquake Hazards Program (EHP) provides the scientific information, situational awareness, and knowledge necessary to reduce deaths, injuries, and economic losses from earthquakes and earthquake-induced tsunamis, landslides, and soil liquefaction. The EHP supports activities in three focused topical areas: (1) earthquake monitoring, (2) hazard assessment, and (3) applied research, using the results of each—and the coordination among them—to further support risk translation and communication in regions at risk nationwide.
For earthquake monitoring, the Advanced National Seismic System (ANSS), a cooperative effort of USGS networks, university partner regional seismic networks, and real-time geodetic networks, collects and analyzes data on earthquakes; issues timely, reliable notifications of their occurrence and impacts; and provides data for earthquake research, hazard, and risk assessment as a foundation for building an earthquake-resilient Nation. The USGS-operated ShakeAlert Earthquake Early Warning system is a recent addition to EHP’s ANSS infrastructure.
In the realm of earthquake hazard assessment, the EHP contributes to earthquake risk mitigation strategies by developing the National Seismic Hazard Model and maps, and other related products, that describe the likelihood and potential effects of earthquakes nationwide, especially in the urban areas of highest risk. The EHP also conducts research on the causes, characteristics, and effects of earthquakes and prioritizes work that directly increases the accuracy and precision of earthquake hazards assessments, earthquake forecasts, and earthquake monitoring and situational-awareness products and that supports the Nation’s earthquake mitigation practices.
Bridging the EHP’s efforts across research, hazard assessments, and earthquake monitoring is a broad and comprehensive collection of earthquake information products, including the National Seismic Hazard Model, ShakeAlert, and other products describing impact, such as ShakeMap and PAGER (Prompt Assessment of Global Earthquakes for Response), which have been developed and integrated into EHP’s real-time monitoring systems.
EHP funds external partners to carry out many important collaborative activities through an active external grants program—one of the largest in the USGS—and through cooperative agreements with other partners such as the university-operated regional seismic networks, funded as part of the ANSS.
To continue its support of earthquake hazard characterization and risk reduction, the EHP aims to strengthen its foundational products and practices while positioning itself to respond to the evolving needs of the Nation and follow best practices of the scientific community. This document describes a strategy for the program to ensure it can meet these demands. The foundational priorities outlined in this strategy represent those activities that remain critical to the core functionality of the program and those that can be supported under current fiscal year 2024-level appropriations. Priorities described as aspirational are important for future growth, and to maintain the program’s position as a leading global resource in earthquake science, but would require increases in appropriated funding to be fully realized.
Across the program’s portfolio of activities, several major themes have been identified as the most critical activities to advance EHP science over the coming decade. Together, these activities provide the framework necessary to integrate critical hazard characterization and risk reduction activities across the program. They provide the structure for research to advance the understanding of where, when, and why earthquakes occur and how we can use improved knowledge to drive short-term and actionable forecasts of seismic activity. They expand the usefulness of critical earthquake products and advance the sophistication of those products to keep pace with the rapidly evolving needs of an ever-expanding user base while maintaining the position of the USGS as a global leader in earthquake science.
This science strategy is organized into three primary sections. The first section provides an overview of the EHP and its budget, governance, and program council. Readers familiar with the program may wish to focus on the second section, which describes the core of the science strategy, including priorities across each of the EHP’s major program activities in monitoring, hazard assessment, and targeted research. The third section outlines science priorities that cut across program activities, including those involving collaborations external to the EHP.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1544","usgsCitation":"Hayes, G.P., Baltay Sundstrom, A.S., Barnhart, W.D., Blanpied, M.L., Davis, L.A., Earle, P.S., Field, N., Franks, J.M., Given, D.D., Gold, R.D., Goulet, C.A., Guy, M.M., Hardebeck, J.L., Luco, N., Pollitz, F., Ringler, A.T., Scharer, K.M., Sobieszczyk, S., Thomas, V.I., and Wolfe, C.J., 2024, U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33: U.S. Geological Survey Circular 1544, 55 p., https://doi.org/10.3133/cir1544.","productDescription":"ix, 55 p.","numberOfPages":"70","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-160564","costCenters":[{"id":234,"text":"Earthquake Hazards 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U.S. Geological Survey
Mail Stop 905
12201 Sunrise Valley Drive
Reston, VA 20192
We assessed amphibian diversity, rarity, and threats across the National Park System (U.S.A.), which covers 3.5% of the country and 12% of federal lands. At least 230 of 354 (65%) amphibian species documented in the country occur on National Park Service lands. Of species in parks, 17% are at-risk globally and 20% are uncategorized, reflecting still-widespread data deficiencies. National parks in the Northwest and Northeast had the steepest species‒area relationships. Non-native crayfishes and amphibians occur within 50 km of 60% and 25% of parks, respectively, illustrating the broad threat of non-native predators. Projected mid-century (2040–2069) changes in climatic water deficit, based on 25 climate futures, produced an expected 34% increase in dryness across all national parks in the conterminous U.S.A. Our analyses highlight the extent and regional differences in current and future threats and reveal gaps in species protection, but also reveal opportunities for targeted expansion and active management.
","language":"English","publisher":"Nature","doi":"10.1038/s44185-024-00067-1","usgsCitation":"LaFrance, B., Ray, A.M., Tercek, M.T., Fisher, R., and Hossack, B., 2024, Amphibian richness, rarity, threats, and conservation prospects across the U.S. National Park System: npj Biodiversity, v. 3, 35, 9 p., https://doi.org/10.1038/s44185-024-00067-1.","productDescription":"35, 9 p.","ipdsId":"IP-171541","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466749,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s44185-024-00067-1","text":"Publisher Index Page"},{"id":465578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n 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Conventional diagnosis of anthrax involves microscopy, culture identification of bacterial colonies and molecular detection. Genetic markers used are often virulence gene targets such as B. anthracis protective antigen (pagA, also called BAPA, occurring on plasmid pXO1), lethal factor (lef, on pXO1), capsule-encoding capB/C (located on pXO2) as well as chromosomal Ba-1. Combinations of genetic markers using real-time/quantitative polymerase chain reaction (qPCR) are used to confirm B. anthracis from culture but can also be used directly on diagnostic samples to avoid propagation and its associated biorisks and for faster identification. We investigated how the presence of closely related species could complicate anthrax diagnoses with and without culture to standardise the use of genetic markers using qPCR for accurate anthrax diagnosis. Using blood smears from 2012–2020 from wildlife mortalities (n = 1708) in Kruger National Park in South Africa where anthrax is endemic, we contrasted anthrax diagnostic results based on qPCR, microscopy, and culture. From smears, 113/1708 grew bacteria in culture, from which 506 isolates were obtained. Of these isolates, only 24.7% (125 isolates) were positive for B. anthracis based on genetic markers or microscopy. However, among these, merely 4/125 (3.2%) were confirmed B. anthracis isolates (based on morphology, microscopy, and sensitivity testing to penicillin and gamma-phage) from the blood smear, likely due to poor survival of spores on stored smears. This study identified B. cereus sensu lato, which included B. cereus and B. anthracis, Peribacillus spp., and Priestia spp. clusters using gyrB gene in selected bacterial isolates positive for pagA region using BAPA probe. Using qPCR on blood smears, 52.1% (890 samples) tested positive for B. anthracis based on one or a combination of genetic markers which included the 25 positive controls. Notably, the standard lef primer set displayed the lowest specificity and accuracy. The Ba-1+BAPA+lef combination showed 100% specificity, sensitivity, and accuracy. Various marker combinations, such as Ba-1+capB, BAPA+capB, Ba-1+BAPA+capB+lef, and BAPA+lef+capB, all demonstrated 100.0% specificity and 98.7% accuracy, while maintaining a sensitivity of 96.6%. Using Ba-1+BAPA+lef+capB, as well as Ba-1+BAPA+lef with molecular diagnosis accurately detects B. anthracis in the absence of bacterial culture. Systematically combining microscopy and molecular markers holds promise for notably reducing false positives. This significantly enhances the detection and surveillance of diseases like anthrax in southern Africa and beyond and reduces the need for propagation of the bacteria in culture.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pntd.0012122","usgsCitation":"Ochai, S.O., Hassim, A., Dekker, E., Magome, T., Lekota, K., Makgabo, S., de Klerk‑Loris, L., van Schalkwyk, O., Kamath, P., Turner, W.C., and van Heerden, H., 2024, Comparing microbiological and molecular diagnostic tools for the surveillance of anthrax: PLoS Neglected Tropical Diseases, v. 18, no. 11, e0012122, 24 p., https://doi.org/10.1371/journal.pntd.0012122.","productDescription":"e0012122, 24 p.","ipdsId":"IP-156613","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466750,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pntd.0012122","text":"Publisher Index Page"},{"id":465488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Ochai, Sunday O.","contributorId":342466,"corporation":false,"usgs":false,"family":"Ochai","given":"Sunday","email":"","middleInitial":"O.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":910601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hassim, Ayesha","contributorId":343065,"corporation":false,"usgs":false,"family":"Hassim","given":"Ayesha","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":910602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dekker, Edgar H.","contributorId":343067,"corporation":false,"usgs":false,"family":"Dekker","given":"Edgar H.","affiliations":[{"id":81972,"text":"Government of South Africa","active":true,"usgs":false}],"preferred":false,"id":910603,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Magome, Thuto","contributorId":343070,"corporation":false,"usgs":false,"family":"Magome","given":"Thuto","affiliations":[{"id":81973,"text":"North West University","active":true,"usgs":false}],"preferred":false,"id":910604,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lekota, Kgaugelo E.","contributorId":343072,"corporation":false,"usgs":false,"family":"Lekota","given":"Kgaugelo E.","affiliations":[{"id":81973,"text":"North West University","active":true,"usgs":false}],"preferred":false,"id":910605,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Makgabo, S. Marcus","contributorId":343073,"corporation":false,"usgs":false,"family":"Makgabo","given":"S. Marcus","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":910606,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"de Klerk‑Loris, Lin‑Mari","contributorId":343074,"corporation":false,"usgs":false,"family":"de Klerk‑Loris","given":"Lin‑Mari","affiliations":[{"id":81972,"text":"Government of South Africa","active":true,"usgs":false}],"preferred":false,"id":910607,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"van Schalkwyk, O. Louis","contributorId":343075,"corporation":false,"usgs":false,"family":"van Schalkwyk","given":"O. Louis","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":910608,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kamath, Pauline L.","contributorId":287148,"corporation":false,"usgs":false,"family":"Kamath","given":"Pauline L.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":910609,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Turner, Wendy Christine 0000-0002-0302-1646","orcid":"https://orcid.org/0000-0002-0302-1646","contributorId":287053,"corporation":false,"usgs":true,"family":"Turner","given":"Wendy","email":"","middleInitial":"Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910610,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"van Heerden, Henriette","contributorId":343077,"corporation":false,"usgs":false,"family":"van Heerden","given":"Henriette","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":910611,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70261120,"text":"70261120 - 2024 - Database of surface water diversion sites and daily withdrawals for the upper Colorado River Basin, 1980–2022","interactions":[],"lastModifiedDate":"2024-11-25T15:29:35.758148","indexId":"70261120","displayToPublicDate":"2024-11-21T08:23:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Database of surface water diversion sites and daily withdrawals for the upper Colorado River Basin, 1980–2022","docAbstract":"The Colorado River drains about 8% of the conterminous United States, provides water for 40 million people, and is one of the most overallocated rivers in the world. As the upper Colorado River Basin (UCOL) contributes an estimated 92% of the total basin natural streamflow, knowledge of the location and amount of surface water withdrawals in the UCOL is important for managing the Colorado River system. Since the UCOL encompasses portions of five states, water use data are dispersed among numerous federal and state agency databases, and there is no centralized dataset that documents surface water use within the entire UCOL at a fine spatial and temporal resolution. This article presents an inventory of 1,358 major structures that divert surface water from and within the UCOL with corresponding daily time series withdrawal records from 1980 through 2022. Data compilation efforts, processing methods, and contents of this diversion database are documented, and summary information is provided.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41597-024-04123-0","usgsCitation":"Lopez, S.F., Knight, J., Tillman, F.D., Masbruch, M.D., Wise, D., Jones, C.J., and Miller, M., 2024, Database of surface water diversion sites and daily withdrawals for the upper Colorado River Basin, 1980–2022: Scientific Data, v. 11, 1266, 10 p., https://doi.org/10.1038/s41597-024-04123-0.","productDescription":"1266, 10 p.","ipdsId":"IP-168039","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":466751,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-024-04123-0","text":"Publisher Index Page"},{"id":464464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.23653442041727,\n 45.094514943023796\n ],\n [\n -110.23653442041727,\n 32.70061306772341\n ],\n [\n -106.92766646541669,\n 32.70061306772341\n ],\n [\n -106.92766646541669,\n 45.094514943023796\n ],\n [\n -110.23653442041727,\n 45.094514943023796\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2024-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Lopez, Samuel Francisco 0000-0002-3544-7465","orcid":"https://orcid.org/0000-0002-3544-7465","contributorId":344607,"corporation":false,"usgs":true,"family":"Lopez","given":"Samuel","email":"","middleInitial":"Francisco","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knight, Jacob E. 0000-0003-0271-9011","orcid":"https://orcid.org/0000-0003-0271-9011","contributorId":204140,"corporation":false,"usgs":true,"family":"Knight","given":"Jacob E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wise, Daniel R. 0000-0002-1215-9612","orcid":"https://orcid.org/0000-0002-1215-9612","contributorId":217259,"corporation":false,"usgs":true,"family":"Wise","given":"Daniel","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Casey J.R. 0000-0002-6991-8026","orcid":"https://orcid.org/0000-0002-6991-8026","contributorId":223364,"corporation":false,"usgs":true,"family":"Jones","given":"Casey","email":"","middleInitial":"J.R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919358,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - 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The potential contribution of minerals and heavy metals to tortoise health and susceptibility to disease remains uncertain.
Objective: The objective of this study was to evaluate the results of elemental analysis of trace minerals and macrominerals in scute keratin, kidney, and liver tissue from ill and dying desert tortoises salvaged for necropsy between 1993 and 2000.
Methods: Salvaged tortoises were categorized by age (adult, juvenile), geographic location, and primary disease based on necropsy findings. A subset of tortoises that were injured or killed by vehicular trauma or predation but with no notable pathologic abnormalities were used as controls. A panel of 21 trace minerals and 6 macrominerals was analyzed in scute keratin, kidney, and liver tissue samples by inductively-coupled plasma spectrometry and atomic absorption spectrophotometry.
Results: Necropsies were done on 46 tortoises, including 9 juveniles salvaged from 5 regions in the Colorado and Mojave deserts of California. Primary diseases were cutaneous dyskeratosis (n=9), infection/ inflammation (n=8), malnutrition (n=7), mycoplasmosis (n=5), and urolithiasis (n=3); 14 tortoises were classified as controls. Concentrations of elements differed significantly by tissue, age, desert region, and disease (P < 0.05). Tortoises with cutaneous dyskeratosis had significantly higher Se concentrations, primarily in keratin and liver, than tortoises with other diseases (P < 0.001). Juveniles were more likely than adults to have high Pb, Sn, and Zn levels (P < 0.05). All tortoises had detectable levels of more than one potentially toxic heavy metal, including As, Cd, Cr, Hg, Ni, Pb, Sn and V.
Conclusions: Potentially toxic elements are frequently found in tissue from tortoises in desert regions of California, with significantly higher concentrations in diseased tortoises. Metal exposure from soils, mining, historic and ongoing military activities, and other human activities could increase susceptibility to disease in desert tortoises.
","language":"English","publisher":"Frontiers","doi":"10.3389/fvets.2024.1481367","usgsCitation":"Berry, K.H., Christopher, M., and Jacobson, E., 2024, Potentially toxic elements in wild Agassiz’s desert tortoises: Tissue concentrations and association with disease: Frontiers in Veterinary Sciences, v. 11, 1481367, 15 p., https://doi.org/10.3389/fvets.2024.1481367.","productDescription":"1481367, 15 p.","ipdsId":"IP-166170","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466752,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fvets.2024.1481367","text":"Publisher Index Page"},{"id":465561,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Colorado Desert, Mojave Desert, Sonoran Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.05397514870228,\n 35.97731275545118\n ],\n [\n -118.05397514870228,\n 32.60377435565428\n ],\n [\n -113.73422113613373,\n 32.60377435565428\n ],\n [\n -113.73422113613373,\n 35.97731275545118\n ],\n [\n -118.05397514870228,\n 35.97731275545118\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2024-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christopher, Mary M. 0000-0002-5841-8501","orcid":"https://orcid.org/0000-0002-5841-8501","contributorId":346499,"corporation":false,"usgs":false,"family":"Christopher","given":"Mary M.","affiliations":[],"preferred":false,"id":922131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobson, Elliiott","contributorId":347667,"corporation":false,"usgs":false,"family":"Jacobson","given":"Elliiott","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":922132,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70261040,"text":"ofr20241042 - 2024 - Assessing community needs for terrestrial analog studies","interactions":[],"lastModifiedDate":"2024-11-21T14:52:20.838537","indexId":"ofr20241042","displayToPublicDate":"2024-11-20T12:16:52","publicationYear":"2024","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":"2024-1042","displayTitle":"Assessing Community Needs for Terrestrial Analog Studies","title":"Assessing community needs for terrestrial analog studies","docAbstract":"The U.S. Geological Survey (USGS) developed and released a survey to assess the terrestrial analog needs of the planetary science community. The goal was to assess the current state of terrestrial analog studies and determine community needs related to the use of field sites for training and research, data dissemination and archiving, and sample collections.
The survey was designed to gather feedback from community members who have a self-described interest in the use of terrestrial analogs. The web-based questionnaire contained a total of 33 questions and was designed to take <10 minutes to complete. The questionnaire was divided into four sections: (1) “Respondent Details,” (2) “Field Analog Use,” (3) “Data Portal Use,” and (4) “Geologic Materials Collection Use.” Comment boxes were provided for 12 of the 33 questions, which allowed respondents to provide more detailed comments to individual questions. The questionnaire received a total of 248 responses. We identified 21 notable findings which are matched with one or more recommendations to be addressed by the planetary science community.
In general, the findings highlight the importance of terrestrial analog studies to the planetary science community. The findings address how and why the community uses terrestrial analogs, areas in which further support can lead to a greater return on investment, and how the community can better manage data and samples from these studies.
The results from this survey identify a need for additional training opportunities and analog-focused workshops. There is a gap in formal education related to field techniques for a significant part of researchers who conduct fieldwork. There is also a subset of the community who are interested in conducting field-based studies but are, however, unaware of relevant sites and methods. Workshops would provide an opportunity for scientists at all career stages to share their results and discuss common challenges such as logistics, field safety, funding, and data and sample archiving. Trainings, workshops, and better communication may also lead to increased field-analog work at locations in closer proximity to home institutions, reducing costs associated with large field expeditions and ultimately leading to more available funding for more localized field studies.
The survey also shows that the ability to archive a diverse array of field data is a major challenge for terrestrial studies and finds that existing practices are not compliant with National Aeronautics and Space Administration (NASA) data management policies. The survey points to a strong need for a central data repository, allowing for easier access to existing analog data and the archiving of new field data.
The community would benefit from additional physical sample archiving, consolidated into several key institutions to promote easier access, such as NASA and USGS centers. Though scientists would still need to acquire their own samples in the field for certain studies, many studies would benefit from an archive of existing samples and associated data for widely used analog sites, reducing redundant sampling practices.
This report finds that a coordinated effort to improve and standardize training, data archiving, sample curation, and communication regarding terrestrial analog studies will best serve the planetary science community in our exploration goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241042","collaboration":"Prepared in cooperation with the National Aeronautics and Space Administration","usgsCitation":"Edgar, L.A., Rumpf, M.E., Skinner, J.A., Jr., Gullikson, A.L., Keszthelyi, L., Hunter, M.A., Gaither, T., 2024, Assessing community needs for terrestrial analog studies: U.S. Geological Survey Open-File Report 2024–1042, 63 p., https://doi.org/10.3133/ofr20241042.","productDescription":"iii, 63 p.","onlineOnly":"Y","ipdsId":"IP-124254","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":464364,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1042/covrthb.jpg"},{"id":464365,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1042/ofr20241042.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
Anadromous fishes play important roles in nutrient dynamics for freshwater ecosystems; however, the trophic pathways have been less documented for iteroparous species like river herring (Alosa pseudoharengus and A. aestivalis) compared to semelparous species like Pacific salmon (Oncorhynchus spp.). Given recent increases in restoration activities to improve connectivity, an understanding of how anadromous river herring influence the morphology, physiology, and life history of predatory fishes can help predict restoration responses. We aimed to quantify the trophic influence of juvenile anadromous river herring on predatory white perch (Morone americana) and yellow perch (Perca flavescens) using a combination of stable isotopes, growth rates, and condition indices. We sampled six lakes in coastal Massachusetts—three lakes with anadromous river herring and three similar lakes without river herring. Bayesian mixing models of δ13C and δ15N indicated white perch consumed juvenile river herring in higher proportions (69–75%) compared to co-occurring prey fishes (11–16%). Lakes with juvenile river herring contained perch with significantly higher condition values, higher immature growth rates (age 1 and 2), lower mature growth rates (> age 3), significantly smaller mature lengths, and lower mortality rates compared to perch in lakes without river herring. These divergent life history traits of perch in response to consumption of juvenile river herring are consistent with observations in other predatory fishes. Direct links between river herring and predator condition, growth, and life history trajectories suggest broad influences on ecosystem structure across trophic levels through physiological, morphometric, and life history modifications.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10641-024-01595-2","usgsCitation":"Mattocks, S., Bittner, S., Luzanau, V., Mohammadi, H., Roy, A.H., Staudinger, M., and Jordaan, A., 2024, River herring influence perch morphology, physiology, and life history: Environmental Biology of Fishes, v. 107, p. 1179-1201, https://doi.org/10.1007/s10641-024-01595-2.","productDescription":"23 p.","startPage":"1179","endPage":"1201","ipdsId":"IP-103045","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.03687326915752,\n 42.873848597989394\n ],\n [\n -71.03687326915752,\n 42.047149016365864\n ],\n [\n -70.5974201441574,\n 42.047149016365864\n ],\n [\n -70.5974201441574,\n 42.873848597989394\n ],\n [\n -71.03687326915752,\n 42.873848597989394\n ]\n ]\n ],\n \"type\": \"Polygon\"\n },\n \"id\": 0\n }\n ]\n}","volume":"107","noUsgsAuthors":false,"publicationDate":"2024-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mattocks, Steven","contributorId":349651,"corporation":false,"usgs":false,"family":"Mattocks","given":"Steven","affiliations":[{"id":83496,"text":"Massachusetts Division of Fisheries and Widlife","active":true,"usgs":false}],"preferred":false,"id":924535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bittner, Steven","contributorId":349652,"corporation":false,"usgs":false,"family":"Bittner","given":"Steven","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luzanau, Vasili","contributorId":349653,"corporation":false,"usgs":false,"family":"Luzanau","given":"Vasili","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mohammadi, Habibollah","contributorId":349654,"corporation":false,"usgs":false,"family":"Mohammadi","given":"Habibollah","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":924534,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Staudinger, Michelle D.","contributorId":349655,"corporation":false,"usgs":false,"family":"Staudinger","given":"Michelle D.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924539,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jordaan, Adrian","contributorId":349656,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924540,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261138,"text":"70261138 - 2024 - Increased mercury concentrations in walleye and yellow perch in lakes invaded by zebra mussels","interactions":[],"lastModifiedDate":"2024-11-26T16:34:22.629421","indexId":"70261138","displayToPublicDate":"2024-11-20T10:27:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Increased mercury concentrations in walleye and yellow perch in lakes invaded by zebra mussels","docAbstract":"Zebra mussels (Dreissena polymorpha) are invasive species that alter ecosystems and food webs with the potential to affect aquatic mercury cycling and bioaccumulation in fishes, although the effect of zebra mussels on fish tissue mercury has not been tested in inland lakes. We assessed differences in fish tissue mercury concentrations and food webs in Minnesota lakes with and without zebra mussels while controlling for other lake and watershed characteristics. Mercury concentrations in adult walleye (Sander vitreus) and yellow perch (Perca flavescens) were 72 % and 157 % higher, respectively, in lakes containing zebra mussels compared to uninvaded lakes. Mercury in young of year (age-0) fish was also elevated, with mercury concentrations 97 % and 82 % higher in age-0 walleye and yellow perch, respectively, in zebra mussel lakes. Walleye mercury concentrations exceeded 0.22 ppm — a threshold triggering more restrictive human consumption advisories for sensitive populations — at a 23 % smaller size, and average-sized walleye (420 mm) exceeded this threshold at a rate of 77 % in invaded lakes, compared to 35 % in uninvaded lakes. Walleye and yellow perch relied more on littoral resources in lakes with zebra mussels but did not feed at meaningfully higher trophic levels. Increased fish tissue mercury in lakes invaded by zebra mussels have consequential implications for fisheries and human health.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2024.177515","usgsCitation":"Blinick, N.S., Link, D., Ahrenstoroff, T.D., Bethke, B.J., Fleishman, A.B., Janssen, S., Krabbenhoft, D.P., Nelson, J.K., Rantala, H.M., Rude, C.L., and Hansen, G.J., 2024, Increased mercury concentrations in walleye and yellow perch in lakes invaded by zebra mussels: Science of the Total Environment, v. 957, 177515, 12 p., https://doi.org/10.1016/j.scitotenv.2024.177515.","productDescription":"177515, 12 p.","ipdsId":"IP-159866","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466753,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2024.177515","text":"Publisher Index Page"},{"id":464530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.44450475587576,\n 44.76946704997556\n ],\n [\n -92.83025695554119,\n 44.71178849475393\n ],\n [\n -93.02272126378875,\n 45.52262408934601\n ],\n [\n -92.78467467108655,\n 46.52137470873771\n ],\n [\n -91.87563497943265,\n 47.44395650508943\n ],\n [\n -96.82965701302123,\n 47.79003353490211\n ],\n [\n -96.44450475587576,\n 44.76946704997556\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"957","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blinick, Naomi S.","contributorId":346507,"corporation":false,"usgs":false,"family":"Blinick","given":"Naomi","email":"","middleInitial":"S.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":919402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Link, Denver","contributorId":346509,"corporation":false,"usgs":false,"family":"Link","given":"Denver","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":919408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahrenstoroff, Tyler D.","contributorId":346508,"corporation":false,"usgs":false,"family":"Ahrenstoroff","given":"Tyler","email":"","middleInitial":"D.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":919403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bethke, Bethany J.","contributorId":275047,"corporation":false,"usgs":false,"family":"Bethke","given":"Bethany","email":"","middleInitial":"J.","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":919404,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fleishman, Abram B. 0000-0002-7209-0899","orcid":"https://orcid.org/0000-0002-7209-0899","contributorId":225023,"corporation":false,"usgs":false,"family":"Fleishman","given":"Abram","email":"","middleInitial":"B.","affiliations":[{"id":41020,"text":"Conservation Metrics","active":true,"usgs":false}],"preferred":false,"id":919405,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919406,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919407,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nelson, Jenna K.R.","contributorId":346510,"corporation":false,"usgs":false,"family":"Nelson","given":"Jenna","email":"","middleInitial":"K.R.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":919409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rantala, Heidi M.","contributorId":330595,"corporation":false,"usgs":false,"family":"Rantala","given":"Heidi","email":"","middleInitial":"M.","affiliations":[{"id":65315,"text":"MN DNR","active":true,"usgs":false}],"preferred":false,"id":919410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rude, Claire L.","contributorId":346514,"corporation":false,"usgs":false,"family":"Rude","given":"Claire","email":"","middleInitial":"L.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":919411,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hansen, Gretchen J.A. 0000-0003-0241-7048","orcid":"https://orcid.org/0000-0003-0241-7048","contributorId":300822,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","email":"","middleInitial":"J.A.","affiliations":[{"id":65266,"text":"Department of Fish, Wildlife, and Conservation Biology, University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":919412,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70264788,"text":"70264788 - 2024 - Themed social networking groups as effective sources of data: A country-wide survey on invasive bigheaded carp (Hipophthalmichthys molitrix and H. nobilis) detection and distribution","interactions":[],"lastModifiedDate":"2025-03-24T15:31:14.707392","indexId":"70264788","displayToPublicDate":"2024-11-20T10:25:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17109,"text":"Citizen Science: Theory and Practice","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Themed social networking groups as effective sources of data: A country-wide survey on invasive bigheaded carp (Hipophthalmichthys molitrix and H. nobilis) detection and distribution","title":"Themed social networking groups as effective sources of data: A country-wide survey on invasive bigheaded carp (Hipophthalmichthys molitrix and H. nobilis) detection and distribution","docAbstract":"Citizen science commonly uses social networking platforms because they provide the easiest way to contact people. Social networking platforms can also be especially effective in that they gather people by interest and region. By sharing questionnaires and collecting photographs in angling-themed Facebook groups, we assessed the applicability of social networking groups in citizen science surveys to evaluate the distribution patterns of invasive bigheaded carp in Hungary. Altogether, we received 1,234 responses from 29 Facebook groups to four survey solicitations, with responses coming from 417 locations from across Hungary. The majority of responses were received in the first (mean ± SD; 74.3% ± 5.3) and second days (12.5% ± 5.5) after a survey questionnaire was posted. Group size was positively correlated with reach but inversely with reach ratio (reached members divided by the total number of group members). We collected 311 photos of 622 bigheaded carp, of which 470 were H. molitrix and 67 were H. nobilis. Although spatial bias occurred both in responses to survey questionnaires and available photographs, presence of bigheaded carp was confirmed in all medium and large rivers and many lentic habitats in Hungary. We demonstrated that social media groups can be used to survey interested members of the public and facilitate rapid data collection, providing an effective platform for citizen science. Repeated, spaced sharing of survey solicitations in as many groups as possible (regardless of group size) is the cornerstone for effective data collection. Our survey provided more effective and inexpensively obtained information about the distribution of bigheaded carp than standard catch-based methods.
","language":"English","publisher":"Ubiquity Press","doi":"10.5334/cstp.780","usgsCitation":"Vitál, Z., Chapman, D., Halasi-Kovács, B., and Mozsár, A., 2024, Themed social networking groups as effective sources of data: A country-wide survey on invasive bigheaded carp (Hipophthalmichthys molitrix and H. nobilis) detection and distribution: Citizen Science: Theory and Practice, v. 9, no. 1, 29, 14 p., https://doi.org/10.5334/cstp.780.","productDescription":"29, 14 p.","ipdsId":"IP-158985","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":488378,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5334/cstp.780","text":"Publisher Index Page"},{"id":483722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Hungary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 19.905749040559556,\n 48.16445870730942\n ],\n [\n 19.646587056605625,\n 48.262319010335716\n ],\n [\n 19.47381240063592,\n 48.118342076328645\n ],\n [\n 18.825907440751536,\n 48.072184012061996\n ],\n [\n 18.774075043960778,\n 47.84077194152326\n ],\n [\n 18.653132784781832,\n 47.77114616748298\n ],\n [\n 17.651039780159408,\n 47.77114616748298\n ],\n [\n 17.314129201019796,\n 48.02598450726734\n ],\n [\n 17.11543834665531,\n 47.98552594077279\n ],\n [\n 17.003134820275022,\n 47.86395979415386\n ],\n [\n 17.029051018669804,\n 47.71886558279843\n ],\n [\n 16.5625594475527,\n 47.75953279753682\n ],\n [\n 16.407062257180257,\n 47.67234986658315\n ],\n [\n 16.71805663792503,\n 47.520887155888005\n ],\n [\n 16.44161718837492,\n 47.409925547425814\n ],\n [\n 16.44161718837492,\n 46.999097587853385\n ],\n [\n 16.268842532405188,\n 47.016769767732626\n ],\n [\n 16.1047066092342,\n 46.8752285993159\n ],\n [\n 16.28611999800259,\n 46.84569374552734\n ],\n [\n 16.57119818035133,\n 46.46621228452659\n ],\n [\n 17.460987658593552,\n 45.91002968951361\n ],\n [\n 18.065698954485782,\n 45.747503011802735\n ],\n [\n 18.4803581288121,\n 45.747503011802735\n ],\n [\n 18.713603914371276,\n 45.91604008269749\n ],\n [\n 18.869101104743663,\n 45.84988995631136\n ],\n [\n 19.68978072059778,\n 46.16788887622772\n ],\n [\n 20.510460336451843,\n 46.16788887622772\n ],\n [\n 20.648680061226855,\n 46.14993774774203\n ],\n [\n 20.795538518801777,\n 46.26352932418982\n ],\n [\n 21.10653289954655,\n 46.269501321699835\n ],\n [\n 22.24684562894288,\n 47.6897981229599\n ],\n [\n 22.480091414502084,\n 47.82337424756798\n ],\n [\n 22.69605973446386,\n 47.800168248983425\n ],\n [\n 22.89475058882843,\n 47.97396052110528\n ],\n [\n 22.81700199364164,\n 48.118342076328645\n ],\n [\n 22.626949872075784,\n 48.112574584327916\n ],\n [\n 22.46281394890471,\n 48.262319010335716\n ],\n [\n 22.229568163346727,\n 48.44028881239183\n ],\n [\n 21.754437859430936,\n 48.36573198861302\n ],\n [\n 21.41752728029016,\n 48.594788498150564\n ],\n [\n 21.10653289954655,\n 48.52618014157136\n ],\n [\n 20.78689978600312,\n 48.606214177684194\n ],\n [\n 20.510460336451843,\n 48.554778265864115\n ],\n [\n 20.329046947684617,\n 48.3312842835895\n ],\n [\n 19.905749040559556,\n 48.16445870730942\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vitál, Zoltán","contributorId":352562,"corporation":false,"usgs":false,"family":"Vitál","given":"Zoltán","affiliations":[{"id":84260,"text":"Hungarian University of Agriculture and Life Sciences","active":true,"usgs":false}],"preferred":false,"id":931686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":931687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Halasi-Kovács, Béla","contributorId":352563,"corporation":false,"usgs":false,"family":"Halasi-Kovács","given":"Béla","affiliations":[{"id":84260,"text":"Hungarian University of Agriculture and Life Sciences","active":true,"usgs":false}],"preferred":false,"id":931688,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mozsár, Attila","contributorId":352564,"corporation":false,"usgs":false,"family":"Mozsár","given":"Attila","affiliations":[{"id":84261,"text":"Balaton Limnological Research Institute","active":true,"usgs":false}],"preferred":false,"id":931689,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261033,"text":"70261033 - 2024 - Surveying waterfowl broods in wetlands using aerial drones","interactions":[],"lastModifiedDate":"2024-11-20T16:52:17.116684","indexId":"70261033","displayToPublicDate":"2024-11-20T09:46:20","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Surveying waterfowl broods in wetlands using aerial drones","docAbstract":"Effective waterfowl management relies on the collection of relevant demographic data to inform land management decisions; however, some types of data are difficult to obtain. For waterfowl, brood surveys are difficult to conduct because wetland habitats often obscure ducklings from being visually assessed. Here, we used Unoccupied Aerial Systems (UAS) to assess what wetland habitat characteristics influenced brood abundance in Suisun Marsh, California, USA. Using a thermal imaging camera, we surveyed 17 wetland units encompassing 332 ha of flooded area on seven waterfowl hunting clubs during the waterfowl breeding season. Additionally, using a combination of multispectral imagery collected from the UAS flights and LiDAR data from the previous year, we mapped habitat composition within each unit to relate to brood observation counts. From June 3-7, 2019, we identified 113 individual broods comprised of 827 ducklings. We found a positive relationship between the number of broods observed and the proportion of the unit that was flooded. We also found a positive relationship between the number of broods observed and the area of effective habitat, a metric of flooded habitat within a specific distance of flooded vegetation. Brood surveys using UAS could complement the traditional Breeding Population Survey and provide local managers with fine-scale and timely information regarding shifts in brood abundance in the region.","language":"English","publisher":"eScholarship","doi":"10.15447/sfews.2024v22iss3art2","usgsCitation":"Mackell, D.A., Casazza, M.L., Overton, C.T., Buffington, K., Freeman, C., Ackerman, J.T., and Thorne, K., 2024, Surveying waterfowl broods in wetlands using aerial drones: San Francisco Estuary and Watershed Science, v. 22, no. 3, 3, 16 p., https://doi.org/10.15447/sfews.2024v22iss3art2.","productDescription":"3, 16 p.","ipdsId":"IP-159150","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466754,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2024v22iss3art2","text":"Publisher Index Page"},{"id":464360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Suisun Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.08563453767741,\n 38.23592936614091\n ],\n [\n -122.08563453767741,\n 38.115419770174015\n ],\n [\n -122.00107572096182,\n 38.115419770174015\n ],\n [\n -122.00107572096182,\n 38.23592936614091\n ],\n [\n -122.08563453767741,\n 38.23592936614091\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"22","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Mackell, Desmond Alexander 0000-0002-1682-2581","orcid":"https://orcid.org/0000-0002-1682-2581","contributorId":266036,"corporation":false,"usgs":true,"family":"Mackell","given":"Desmond","email":"","middleInitial":"Alexander","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918977,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918978,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918979,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freeman, Chase M. 0000-0003-2284-1380","orcid":"https://orcid.org/0000-0003-2284-1380","contributorId":335090,"corporation":false,"usgs":false,"family":"Freeman","given":"Chase M.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":918980,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918981,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918982,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261527,"text":"70261527 - 2024 - Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D","interactions":[],"lastModifiedDate":"2025-05-13T15:59:07.445123","indexId":"70261527","displayToPublicDate":"2024-11-20T09:00:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D","docAbstract":"Numerical simulation of sediment transport and subsequent morphological evolution rely on accurate parameterizations of sediment characteristics. However, these data are often not available or are spatially and/or temporally limited. This study approaches the problem of limited sediment grain-size data with a series of simulations assessing model sensitivity to sediment parameters and initial bed composition configurations in Delft3D, leading to improved modeling practices. A previously validated Delft3D sediment transport and morphology model for Dauphin Island, Alabama, USA, is used as the benchmark case. A method for the generation of representative sediment grain sizes and their spatially varying distributions is presented via end-member analysis of in situ surficial sediment samples. Derived sediment classes and their spatial distributions are applied to two sensitivity case simulations with increasing bed composition complexity. First, multiple sediment classes are applied in a single fully mixed layer, regardless of sediment type. Second, multiple sediment classes are applied in a thin, fully mixed transport layer with underlayers containing only the non-cohesive sediment classes below. Simulations were carried out in a probabilistic, Delft3D MorMerge configuration to capture long-term morphology change for 10 years. We found there is sensitivity to the inclusion of additional sediment classes and sediment distribution made evident in bed level and morphology change. Inclusion of highly mobile fine sediments altered model results in each sensitivity case. The model was also found to be sensitive to initial bed composition in terms of bed level and morphology change, with notable differences between sensitivity cases on decadal timescales, indicating an armoring effect in the second sensitivity case, which used the transport and underlayer bed configuration. The results of this study offer guidance for numerical modelers concerned with sediment behavior in coastal and estuarine environments.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse12112108","usgsCitation":"Jenkins, R., Smith, C., Passeri, D., and Ellis, A.M., 2024, Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D: Journal of Marine Science and Engineering, v. 12, no. 11, 2108, 29 p., https://doi.org/10.3390/jmse12112108.","productDescription":"2108, 29 p.","ipdsId":"IP-170386","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466755,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse12112108","text":"Publisher Index Page"},{"id":465109,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.39043742176105,\n 30.854668400719234\n ],\n [\n -88.39043742176105,\n 30.17648303472457\n ],\n [\n -87.49364396321667,\n 30.17648303472457\n ],\n [\n -87.49364396321667,\n 30.854668400719234\n ],\n [\n -88.39043742176105,\n 30.854668400719234\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, Robert L. III 0000-0003-2078-4618","orcid":"https://orcid.org/0000-0003-2078-4618","contributorId":202181,"corporation":false,"usgs":true,"family":"Jenkins","given":"Robert L.","suffix":"III","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Passeri, Davina L. 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellis, Alisha M. 0000-0002-1785-020X aellis@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-020X","contributorId":192957,"corporation":false,"usgs":true,"family":"Ellis","given":"Alisha","email":"aellis@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920898,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261053,"text":"70261053 - 2024 - Methodology for inclusion of produced and stored carbon dioxide in the U.S. Geological Survey Federal lands greenhouse gas inventory","interactions":[],"lastModifiedDate":"2024-11-21T15:07:34.730743","indexId":"70261053","displayToPublicDate":"2024-11-20T08:58:39","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Methodology for inclusion of produced and stored carbon dioxide in the U.S. Geological Survey Federal lands greenhouse gas inventory","docAbstract":"The U.S. Geological Survey (USGS) has developed two new carbon dioxide (CO2) emissions and sequestration accounting methods for use in future reports. The first method is a Federal lease-produced CO2 emissions calculation for an update of the report, “Federal Lands Greenhouse Gas Emissions and Sequestration in the United States.” The methodology to incorporate Federal lease CO2 production emissions into the updated report relies on CO2 sales royalty data from the Office of Natural Resources Revenue (ONRR). The end usage points for the gas include enhanced oil recovery with CO2 (CO2-EOR), food and beverage, and chemical production. CO2-EOR is the main end point for natural CO2 production in the United States; it accounted for 94% of usage in 2022 [1]. Federal lands emissions from this sector are estimated at 460 metric tons of CO2 in 2022, a very small amount relative to most other Federal lands emissions sector estimates.
The second new method, planned for a separate report, is a calculation of the geologic storage of CO2 on Federal lands. The second method estimates the CO2 stored under Federal surface lands and documents Federal climate change mitigation efforts. Currently, there is no storage of CO2 at an industrial level on Federal lands, however multiple proposals and projects are planned. This method was developed on non-Federal lands datasets in an effort to prepare for when these activities on Federal lands will require accounting. National estimates for CO2 geologic storage using this method, but without a Federal lands filtering step, totaled 8.0 million metric tons (Mt) in 2022.
The two methods described here are new benchmark methods in a collection of accounting procedures to document the current state of greenhouse gas emissions and their storage on Federal lands. These benchmarks can then be used to measure any subsequent changes in emissions from or carbon storage beneath Federal lands. While the magnitude of the values is currently non-existent to small, emissions mitigation goals established by decision makers indicate that these values will grow, and their documentation will take on greater value and use.
Flooding rice (Oryza sativa) agricultural fields during winter to facilitate rice straw decomposition has mitigated the loss of some of the natural wetlands in California’s Central Valley. We conducted bird surveys in 253 rice checks (2,158 ha) within 177 rice fields in the Sacramento Valley during the fall and winter of 2021-2022 and 2022-2023 to evaluate factors influencing bird use of winter-flooded, post-harvest rice fields enrolled in the California Winter Rice Habitat Incentive Program. We counted 143,932 birds from 57 species, including dabbling ducks (86.4%), geese (8.0%), shorebirds (0.9%), wading birds (0.7%), and other birds (4.0%). Extrapolating from the lowest densities observed in rice fields during the 70-day mandatory flooding period, we estimated that properties enrolled in this public-private partnership provided habitat for at least 271,312 birds day-1 (16,248 ha; 2021-2022) and 147,315 birds day-1 (8,448 ha; 2022-2023), totaling >10 million bird-use-days each winter. Water depth had the greatest influence on bird abundance and diversity. Relatively shallow water depths (≤13 cm) had greater abundance of shorebirds, wading birds, and geese, and higher diversity, whereas intermediate depths (~23 cm) resulted in the greatest dabbling duck abundance. Duck, goose, and wading bird abundances were greatest and species richness and family diversity were highest 8 days after the onset of flooding in rice fields (typically late October), followed by a decline in bird use until 65-87 days post flooding, after which bird use increased slightly. Bird abundance and species diversity were lowest in rice fields with the greatest hunting intensity (≥3 days week-1). We identified several habitat variables that could be managed and prioritized by landowner incentive programs to increase bird use of winter-flooded rice, including water depth, variation in emergent vegetation height, mudflat habitat availability, rice check shape, hunting intensity, and post-harvest treatment of residual rice straw.
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","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2024.123238","usgsCitation":"Jayasekera, D.H., Melstrom, R., and Pope, K.L., 2024, Economic losses to inland recreational fisheries from harmful algal blooms: Journal of Environmental Management, v. 372, 123238, 8 p., https://doi.org/10.1016/j.jenvman.2024.123238.","productDescription":"123238, 8 p.","ipdsId":"IP-170673","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":503780,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2024.123238","text":"Publisher Index Page"},{"id":503622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"372","noUsgsAuthors":false,"publicationDate":"2024-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Jayasekera, D. Harshanee","contributorId":370631,"corporation":false,"usgs":false,"family":"Jayasekera","given":"D.","middleInitial":"Harshanee","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":960595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melstrom, Richard","contributorId":370632,"corporation":false,"usgs":false,"family":"Melstrom","given":"Richard","affiliations":[{"id":88053,"text":"Loyola University-Chicago","active":true,"usgs":false}],"preferred":false,"id":960596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":960597,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70261011,"text":"70261011 - 2024 - Temporal concentrations of Quaternary ammonium compounds in wastewater treatment effluents during the COVID-19 pandemic, 2020–2021","interactions":[],"lastModifiedDate":"2024-11-20T16:09:06.755316","indexId":"70261011","displayToPublicDate":"2024-11-19T09:29:07","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Temporal concentrations of Quaternary ammonium compounds in wastewater treatment effluents during the COVID-19 pandemic, 2020–2021","docAbstract":"Quaternary ammonium compounds (QAC) are high production chemicals used in many commercial and household disinfection products. During the SARS-CoV-2 (COVID-19) pandemic, QACs were included on lists of COVID-19 disinfectants. Increased QAC use could lead to higher levels of QACs in wastewater treatment plant (WWTP) effluents, which could subsequently be released into the environment. To evaluate QACs in WWTP effluent, three WWTPs in the northeastern United States were monitored from May 2020 through August 2021. Target QACs included six benzylalkyldimethyl ammonium compounds (BAC), three dialkyldimethyl ammonium compounds (DADMAC), two ethylbenzylalkyldimethyl ammonium compounds (EBAC), and benzethonium. At least one QAC was detected in every sample with individual concentrations up to 1600 ng L−1. BAC-C14 was detected most frequently, found in 93% of effluent samples; BAC-C12, BAC-C16, EBAC-C12 and EBAC-C14 were all detected in greater than 80% of samples. Few temporal patterns were observed in QAC concentrations with respect to weekly COVID-19 cases: at WWTP 2, DADMAC-C8:C10 and DADMAC-C10 were positively correlated, and DADMAC-C8 negatively correlated. There were several seasonal trends at WWTP 1, including significant differences of ƩDADMAC, which were higher in fall than summer; ƩBAC was higher during the fall than both spring and summer; and ƩQAC where higher during the fall than spring.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2024.143753","usgsCitation":"Hladik, M.L., Gross, M.S., Black, G.P., Kolpin, D., Masoner, J.R., Phillips, P.J., Bradley, P., and Smalling, K., 2024, Temporal concentrations of Quaternary ammonium compounds in wastewater treatment effluents during the COVID-19 pandemic, 2020–2021: Chemosphere, v. 368, 143753,8 p., https://doi.org/10.1016/j.chemosphere.2024.143753.","productDescription":"143753,8 p.","ipdsId":"IP-164654","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":489869,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemosphere.2024.143753","text":"Publisher Index Page"},{"id":464347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"368","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221087,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gross, Michael S.","contributorId":340328,"corporation":false,"usgs":false,"family":"Gross","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":81579,"text":"California Department of Food and Agriculture","active":true,"usgs":false}],"preferred":false,"id":918908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Black, Gabrielle Pecora 0000-0002-1578-742X","orcid":"https://orcid.org/0000-0002-1578-742X","contributorId":303108,"corporation":false,"usgs":true,"family":"Black","given":"Gabrielle","email":"","middleInitial":"Pecora","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918910,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":918911,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":172757,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918912,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":205668,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918913,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","middleInitial":"L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918914,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}