Sylvatic plague is a widespread, primarily flea-vectored disease in western North America. Because plague is highly lethal to endangered black-footed ferrets (Mustela nigripes, BFFs) and the prairie dogs (Cynomys spp., PDs) on which BFFs depend for habitat and prey, minimizing the impacts of plague is a priority at BFF reintroduction sites. We developed a new, flour-based bait pellet containing 0.84 mg of fipronil and weighing ∼1.25 g (FipBits). We measured the degree and duration of flea control on black-tailed PDs (C. ludovicianus) in Montana and on Gunnison's PDs (C. gunnisoni) in Arizona, USA from 2018–2020. FipBits were distributed on treated plots one time at a rate of 125/ha. Fleas were virtually eliminated in Montana from 1 mo posttreatment to 1 yr later and remained substantially depressed 2 yr posttreatment. With the split colony design, we probably underestimated the degree of flea control achieved with FipBits due to crossover edge effects along the arbitrary line dividing the plots. Flea control in Arizona was significant from 1 mo posttreatment to 1 yr later, but flea abundance had recovered by 2 yr posttreatment. Flea control was evaluated from 2020–2021 in South Dakota, USA on four plots treated with three concentrations of fipronil in FipBits (0.68, 0.71, and 0.83 mg/FipBit). Fleas were essentially eliminated for 10 mo on the 0.83-mg plot and were substantially reduced on the two 0.71-mg plots. Fleas were reduced on the 0.68-mg plot, but the degree of control was less than observed on other treated plots. Impacts of plague on PDs and BFFs would probably be greatly reduced by the levels of flea control observed with FipBits. Options for expanded FipBit evaluations are being pursued for what may become a highly practical, affordable, and effective plague mitigation tool.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-22-00008","usgsCitation":"Matchett, M.R., Eads, D.A., Cordova, J., Livieri, T., Hicks, H., and Biggins, D.E., 2023, Flea control on prairie dogs (Cynomys spp.) with fipronil bait pellets: Potential plague mitigation tool for rapid field application and wildlife conservation: Journal of Wildlife Diseases, v. 59, no. 1, p. 71-83, https://doi.org/10.7589/JWD-D-22-00008.","productDescription":"13 p.","startPage":"71","endPage":"83","ipdsId":"IP-137291","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":444971,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/jwd-d-22-00008","text":"Publisher Index Page"},{"id":435524,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PJUWC2","text":"USGS data release","linkHelpText":"Data on flea control using FipBit fipronil bait pellets with black-tailed prairie dogs, South Dakota, 2020-2021"},{"id":419298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Montana, South Dakota","otherGeospatial":"Buffalo Gap National Grassland, Charles M. Russell National Wildlife Refuge, Double O Ranch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.19,\n 43.55\n ],\n [\n -102.19,\n 43.4167\n ],\n [\n -102,\n 43.4167\n ],\n [\n -102,\n 43.55\n ],\n [\n -102.19,\n 43.55\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113,\n 35.6\n ],\n [\n -112.95,\n 35.6\n ],\n [\n -112.95,\n 35.67\n ],\n [\n -113,\n 35.67\n ],\n [\n -113,\n 35.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.84,\n 47.6333\n ],\n [\n -107.84,\n 47.6167\n ],\n [\n -107.816,\n 47.6167\n ],\n [\n -107.816,\n 47.6333\n ],\n [\n -107.84,\n 47.6333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Matchett, Marc R.","contributorId":193409,"corporation":false,"usgs":false,"family":"Matchett","given":"Marc","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":879037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":879038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cordova, Jennifer","contributorId":73496,"corporation":false,"usgs":false,"family":"Cordova","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":879039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Livieri, Travis","contributorId":279912,"corporation":false,"usgs":false,"family":"Livieri","given":"Travis","affiliations":[{"id":6753,"text":"Prairie Wildlife Research","active":true,"usgs":false}],"preferred":false,"id":879040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hicks, Holly","contributorId":317301,"corporation":false,"usgs":false,"family":"Hicks","given":"Holly","email":"","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":879041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":879042,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70239813,"text":"70239813 - 2023 - Epistylis spp. infestation in two species of mud turtles (Kinosternon spp.) in the American Southwest","interactions":[],"lastModifiedDate":"2023-05-01T15:41:04.058158","indexId":"70239813","displayToPublicDate":"2023-01-03T07:13:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Epistylis spp. infestation in two species of mud turtles (Kinosternon spp.) in the American Southwest","title":"Epistylis spp. infestation in two species of mud turtles (Kinosternon spp.) in the American Southwest","docAbstract":"The protistan genus Epistylis contains freshwater colonial species that attach to aquatic organisms in an epibiotic or parasitic relationship. They are known to attach to the epidermis and shells of aquatic turtles, but have not been reported to cause heavy infestations or morbidity in turtles. We documented heavy infestations of Epistylis spp. in several populations of Sonoran mud turtles (Kinosternon sonoriense) inhabiting livestock ponds in Arizona, USA, and rough-footed mud turtles (Kinosternon hirtipes) from livestock ponds in Texas, USA, over the course of several years. Severe Epistylis spp. infestations on mud turtles appeared to alter diving and swimming behavior when compared to uninfested conspecifics. Infestations were cleared in captivity using tap water or a 10% salt solution, and the turtles had no permanent damage to their shell or epidermis upon clearing. While several of the mud turtles we observed had poor body condition, it is possible that the severe infestations we observed were caused by a comorbidity associated with a pathogen, parasite, or poor habitat quality that made the turtles more susceptible to the Epistylis spp. infestation. Further research on causes for these severe infestations are warranted because they contribute to changes in behavior of the heavily infested turtles and may contribute to morbidity in Kinosternon spp. when mud turtles inhabit extremely warm, shallow, eutrophic aquatic habitats, such as livestock ponds.
Cover crops are planted to reduce soil erosion, increase soil fertility, and improve watershed management. In the Delmarva Peninsula of the eastern United States, winter cover crops are essential for reducing nutrient and sediment losses from farmland. Cost-share programs have been created to incentivize cover crops to achieve conservation objectives. This program required that cover crops be planted and terminated within a specified time window. Usually, farmers report cover crop termination dates for each enrolled field (∼28,000 per year), and conservation district staff confirm the report with field visits within two weeks of termination. This verification process is labor-intensive and time-consuming and became restricted in 2020–2021 due to the COVID-19 pandemic. This study used Harmonized Landsat and Sentinel-2 (HLS, version 2.0) time-series data and the within-season termination (WIST) algorithm to detect cover crop termination dates over Maryland and the Delmarva Peninsula. The estimated remote sensing termination dates were compared to roadside surveys and to farmer-reported termination dates from the Maryland Department of Agriculture database for the 2020–2021 cover crop season. The results show that the WIST algorithm using HLS detected 94% of terminations (statuses) for the enrolled fields (n = 28,190). Among the detected terminations, about 49%, 72%, 84%, and 90% of remote sensing detected termination dates were within one, two, three, and four weeks of agreement to farmer-reported dates, respectively. A real-time simulation showed that the termination dates could be detected one week after termination operation using routinely available HLS data, and termination dates detected after mid-May are more reliable than those from early spring when the Normalized Difference Vegetation Index (NDVI) was low. We conclude that HLS imagery and the WIST algorithm provide a fast and consistent approach for generating near-real-time cover crop termination maps over large areas, which can be used to support cost-share program verification.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.srs.2022.100073","usgsCitation":"Gao, F., Jennewein, J., Hively, W.D., Soroka, A.M., Thieme, A., Bradley, D., Keppler, J., Mirsky, S., and Akumaga, U., 2023, Near real-time detection of winter cover crop termination using harmonized Landsat and Sentinel-2 (HLS) to support ecosystem assessment: Science of Remote Sensing, v. 7, 100073, 14 p., https://doi.org/10.1016/j.srs.2022.100073.","productDescription":"100073, 14 p.","ipdsId":"IP-144149","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":444975,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.srs.2022.100073","text":"Publisher Index Page"},{"id":411274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Chesapeake Bay, Delmarva Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.069544467364,\n 37.94756618819288\n ],\n [\n -75.94812876408099,\n 37.94131461385136\n ],\n [\n -75.95701283993044,\n 37.899264516752396\n ],\n [\n -75.79709947463141,\n 37.901601263962206\n ],\n [\n -75.75564045399823,\n 37.94131461385136\n ],\n [\n -75.6993746402825,\n 37.950655814583385\n ],\n [\n -75.64014746794955,\n 37.94131461385136\n ],\n [\n -75.61053388178237,\n 37.99734400246169\n ],\n [\n -75.22555726161829,\n 38.02534265907727\n ],\n [\n -75.08341204801894,\n 38.27684897319932\n ],\n [\n -75.0389916687707,\n 38.447926991945224\n ],\n [\n -75.69049056443372,\n 38.45952234969701\n ],\n [\n -75.78229268154962,\n 39.723597608598226\n ],\n [\n -75.88594023313227,\n 39.71676420384449\n ],\n [\n -76.03993088119832,\n 39.44058615652014\n ],\n [\n -76.16430794309719,\n 39.36507397284154\n ],\n [\n -76.30053043946273,\n 39.1839704250678\n ],\n [\n -76.3390281014787,\n 39.046110820719235\n ],\n [\n -76.4219461427451,\n 38.850348316275074\n ],\n [\n -76.36568032902868,\n 38.47343431903974\n ],\n [\n -76.069544467364,\n 37.94756618819288\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gao, Feng 0000-0002-1865-2846","orcid":"https://orcid.org/0000-0002-1865-2846","contributorId":70671,"corporation":false,"usgs":false,"family":"Gao","given":"Feng","email":"","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":860675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jennewein, Jyoti","contributorId":243442,"corporation":false,"usgs":false,"family":"Jennewein","given":"Jyoti","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":860676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hively, W. 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In June 2021, the National Trust for Historic Preservation listed the islands as one of America’s 11 Most Endangered Historic Places due to climate change. BOHA partners have been working to find climate adaptive solutions to protect and sustain critical ecological and cultural resources on the islands. A range of coastal adaptation efforts are currently under consideration including increased shoreline armoring and nature-based adaptation solutions. Any action taken in the coastal zone will require an assessment of environmental and ecological communities that could potentially be impacted by disturbance caused by restoration or adaptation projects. The primary goals of the initial phase of this project were to: 1) synthesize occurrence and distribution records of biodiversity living in and using mixed coarse substrate habitats of the intertidal zone of the Boston Harbor Islands; and 2) identify and compile potential methods to develop a standard and repeatable monitoring protocol to track changes (natural or anthropogenic) in intertidal biodiversity over time and across locations; and 3) conduct preliminary site scoping of target islands to identify locations for collecting new baseline data. A biodiversity inventory list was compiled, showing a total of 451 unique species were observed in BOHA between 1861-2020. Of this list, 55 species (invertebrates: 47; algae: 8) were considered nonindigenous species; a watchlist was also developed to help BOHA partners identify potential future invaders that could colonize and impact intertidal communities due to ongoing climate change or disturbance events. Native species observed in BOHA were evaluated using existing conservation frameworks and climate vulnerability information to prioritize species at greatest risk from anthropogenic and environmental stressors for future actions. Lastly, site scoping activities during 2021 identified three types of sites for future intertidal monitoring initiatives: (1) sites with relatively high biodiversity and foundational species, (2) erosional sites near cultural areas of importance to NPS, and (3) sites with generic (common across islands) biodiversity. Overall results are anticipated to help the NPS and BOHA partners identify a suite of species and sites for future monitoring given anticipated adaptation projects and ongoing changes due to SLR, coastal storms and other stressors.
","language":"English","publisher":"University of Massachusetts Amherst","usgsCitation":"Staudinger, M., and Albert, M., 2023, A pilot biodiversity inventory and monitoring protocol in support of coastal adaptation projects in tidal and nearshore subtidal habitats of Boston Harbor Islands: Final Report, 47 p.","productDescription":"47 p.","ipdsId":"IP-145055","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":427220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412723,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://necasc.umass.edu/biblio/final-report-novel-monitoring-framework-assess-intertidal-biodiversity-mixed-coarse","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Massachusetts","otherGeospatial":"Boston Harbor Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.9991391660407,\n 42.2869206356915\n ],\n [\n -70.90402210093907,\n 42.32010005169613\n ],\n [\n -70.93270430871492,\n 42.35670402110517\n ],\n [\n -71.02806652089157,\n 42.31774362095834\n ],\n [\n -70.9991391660407,\n 42.2869206356915\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Staudinger, Michelle 0000-0002-4535-2005","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":206655,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":863566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Albert, Marc","contributorId":335163,"corporation":false,"usgs":false,"family":"Albert","given":"Marc","email":"","affiliations":[],"preferred":false,"id":897585,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70274313,"text":"70274313 - 2023 - Planning for future climates at Wrangell-St. Elias: Mainstreaming park-based actions","interactions":[],"lastModifiedDate":"2026-03-26T16:36:35.4627","indexId":"70274313","displayToPublicDate":"2023-01-01T11:21:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":691,"text":"Alaska Park Science","printIssn":"1545- 496","active":true,"publicationSubtype":{"id":10}},"title":"Planning for future climates at Wrangell-St. Elias: Mainstreaming park-based actions","docAbstract":"No abstract available.
","language":"English","publisher":"US National Park Service","usgsCitation":"Reynolds, J.H., Miller, M.E., Runyon, A.C., Schuurman, G.W., Littell, J.S., Sousanes, P., Olliff, T., Perez, L., Carr, W., Lawrence, D.J., and Wright, J.P., 2023, Planning for future climates at Wrangell-St. Elias: Mainstreaming park-based actions: Alaska Park Science, v. 22, no. 1, p. 110-127.","productDescription":"18 p.","startPage":"110","endPage":"127","ipdsId":"IP-156964","costCenters":[{"id":49028,"text":"Alaska Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":501584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501556,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nps.gov/articles/000/aps-22-1-10.htm"}],"country":"United States","state":"Alaska","otherGeospatial":"Wrangell - St Elias National Park & Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":367866,"corporation":false,"usgs":false,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[],"preferred":false,"id":957838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sousanes, Pam","contributorId":367867,"corporation":false,"usgs":false,"family":"Sousanes","given":"Pam","affiliations":[{"id":87634,"text":"NPS Central Alaska Network","active":true,"usgs":false}],"preferred":false,"id":957839,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olliff, Tom","contributorId":152352,"corporation":false,"usgs":false,"family":"Olliff","given":"Tom","email":"","affiliations":[{"id":18907,"text":"National Park Service, Intermountain Region Landscape Conservation and Climate Change Division, 2327 University Way, Suite 2, Bozeman, MT 59715, USA","active":true,"usgs":false}],"preferred":false,"id":957840,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Perez, Larry","contributorId":206254,"corporation":false,"usgs":false,"family":"Perez","given":"Larry","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":957841,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carr, Wylie","contributorId":273040,"corporation":false,"usgs":false,"family":"Carr","given":"Wylie","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":957842,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lawrence, David J","contributorId":242819,"corporation":false,"usgs":false,"family":"Lawrence","given":"David","email":"","middleInitial":"J","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":957843,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wright, Jeneva P.","contributorId":333276,"corporation":false,"usgs":false,"family":"Wright","given":"Jeneva","email":"","middleInitial":"P.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":957844,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70229149,"text":"70229149 - 2023 - Hydrogeologic framework of the Red River alluvial aquifer and Carrizo-Wilcox aquifer in northwestern Louisiana","interactions":[],"lastModifiedDate":"2024-03-27T15:25:22.211038","indexId":"70229149","displayToPublicDate":"2023-01-01T10:17:05","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5505,"text":"Water Resources Technical Report of the Louisiana Department of Transportation and Development, Office of Public Works","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"82","title":"Hydrogeologic framework of the Red River alluvial aquifer and Carrizo-Wilcox aquifer in northwestern Louisiana","docAbstract":"Groundwater in northwestern Louisiana is a valuable resource needed for expanding public-supply needs as well as possible energy development needs arising from Haynesville Formation natural-gas production. The Red River alluvial and the Carrizo-Wilcox aquifers are two of the most important and heavily pumped aquifers in northwestern Louisiana; however, little documentation of the regional hydrogeologic framework is available. The U.S. Geological Survey and the Louisiana Department of Transportation and Development have consolidated information from, and built upon, previous studies of the Red River alluvial and the Carrizo-Wilcox aquifers to characterize and document the regional hydrogeologic framework of northwestern Louisiana.
The study area has been tectonically modified and includes abundant structural features such as salt domes and areally extensive faulting in addition to minor folding related to these features, all of which impact the sedimentological and hydraulic characteristics of the freshwater-bearing strata. The hydrogeologic framework of northwestern Louisiana comprises a sequence of structurally modifi ed, complexly interbedded, varyingly interconnected, clayey, sandy, and gravelly alluvial sediments. The important freshwater hydrogeologic units include the Quaternary Red River alluvial and upland terrace aquifers, and the underlying Tertiary Sparta, Cane River, and Carrizo-Wilcox aquifers. The Midway confining unit underlies the Carrizo-Wilcox aquifer throughout the study area. No freshwater is present in or below the Midway Group.
Tertiary-age formations exposed at land surface in the study area have been incised by the Red River and are hydraulically connected to the Quaternary Red River alluvium in the Red River valley. In 2010, 7.73 million gallons per day (Mgal/d) of water were withdrawn from the Red River alluvial aquifer in the study area, representing an increase of 2.00 Mgal/d, or about 35 percent, over 2005 withdrawal rates.
The Tertiary Carrizo Sand and Wilcox Group crop out across much of the study area. The two units are hydraulically connected and function as a single hydrologic unit referred to as the Carrizo-Wilcox aquifer. In 2010, 19.33 Mgal/d of water were withdrawn from the Carrizo-Wilcox aquifer in the study area, representing an increase of nearly 1.8 Mgal/d, or about 10 percent, over 2005 withdrawal rates. Any expansion in energy development, as well as water needs of an increasing population, could result in an increased demand on groundwater in northwestern Louisiana.
","language":"English","publisher":"Louisiana Department of Transportation and Development","usgsCitation":"Hays, P.D., Nottmeier, A.M., Fendick, R.B., Daugherty, W.J., and Carter, K., 2023, Hydrogeologic framework of the Red River alluvial aquifer and Carrizo-Wilcox aquifer in northwestern Louisiana: Water Resources Technical Report of the Louisiana Department of Transportation and Development, Office of Public Works 82, 35 p.","productDescription":"35 p.","ipdsId":"IP-122443","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":427146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427145,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://wise.er.usgs.gov/dp/pdfs/USGSDOTD_WRTR82.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.04836792990136,\n 33.02200760162475\n ],\n [\n -94.04836792990136,\n 31.205735114403552\n ],\n [\n -91.87339632735423,\n 31.205735114403552\n ],\n [\n -91.87339632735423,\n 33.02200760162475\n ],\n [\n -94.04836792990136,\n 33.02200760162475\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hays, Phillip D. 0000-0001-5491-9272 pdhays@usgs.gov","orcid":"https://orcid.org/0000-0001-5491-9272","contributorId":4145,"corporation":false,"usgs":true,"family":"Hays","given":"Phillip","email":"pdhays@usgs.gov","middleInitial":"D.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":836782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nottmeier, Anna M. 0000-0002-0205-0955 anottmeier@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-0955","contributorId":5283,"corporation":false,"usgs":true,"family":"Nottmeier","given":"Anna","email":"anottmeier@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":836783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fendick, Robert B.","contributorId":287472,"corporation":false,"usgs":false,"family":"Fendick","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":836784,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daugherty, William J.","contributorId":287473,"corporation":false,"usgs":false,"family":"Daugherty","given":"William","email":"","middleInitial":"J.","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":897434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carter, Kayla kcarter@usgs.gov","contributorId":5681,"corporation":false,"usgs":true,"family":"Carter","given":"Kayla","email":"kcarter@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":897435,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240147,"text":"70240147 - 2023 - Maximizing the water quality benefits of wetlands in croplands","interactions":[],"lastModifiedDate":"2023-01-31T16:09:46.160963","indexId":"70240147","displayToPublicDate":"2023-01-01T10:06:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":13286,"text":"Conservation Insight","active":true,"publicationSubtype":{"id":1}},"title":"Maximizing the water quality benefits of wetlands in croplands","docAbstract":"Key Takeaways
Nutrient loads from croplands continue to negatively affect surface water quality, despite considerable investments in and adoption of agricultural conservation practices aimed at reducing nutrient losses.
Numerous studies indicate that effective restoration and management of wetlands in and adjacent to cultivated croplands could reduce surface and subsurface nutrient loads to downstream waters.
Current drainage basin-scale models do not effectively account for the local-scale processes that are important in understanding the functional variability of wetlands and their potential as conservation practices across different spatial and temporal scales.
Findings presented here from a literature review and simulation modeling study help inform bottom-up field-scale modeling of nitrogen and phosphorus dynamics and improve our understanding of the capacity for wetlands to provide nutrient retention services in agricultural drainage basins to inform strategic agricultural wetland restoration
","language":"English","publisher":"U.S. Department of Agriculture","usgsCitation":"McKenna, O.P., Ross, C.D., and Prenger, J., 2023, Maximizing the water quality benefits of wetlands in croplands: Conservation Insight, 4 p.","productDescription":"4 p.","ipdsId":"IP-123979","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":412507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412472,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nrcs.usda.gov/sites/default/files/2023-01/CEAP-Wetlands-2023-ConservationInsight-WetlandsWaterQuality.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, Owen P. 0000-0002-5937-9436 omckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-9436","contributorId":198598,"corporation":false,"usgs":true,"family":"McKenna","given":"Owen","email":"omckenna@usgs.gov","middleInitial":"P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":862766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Caryn D 0000-0002-9125-1424","orcid":"https://orcid.org/0000-0002-9125-1424","contributorId":300667,"corporation":false,"usgs":true,"family":"Ross","given":"Caryn","email":"","middleInitial":"D","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":862767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prenger, Joseph","contributorId":301843,"corporation":false,"usgs":false,"family":"Prenger","given":"Joseph","email":"","affiliations":[{"id":65354,"text":"USDA Natural Resources Conservation Service","active":true,"usgs":false}],"preferred":false,"id":862768,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70234748,"text":"70234748 - 2023 - Status and trends of the Lake Huron prey fish community, 1976-2021","interactions":[],"lastModifiedDate":"2023-04-26T14:56:10.602756","indexId":"70234748","displayToPublicDate":"2023-01-01T09:51:43","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Status and trends of the Lake Huron prey fish community, 1976-2021","docAbstract":"The U.S. Geological Survey Great Lakes Science Center has assessed annual changes in the offshore prey fish community of Lake Huron since 1973. Assessments are based on a bottom trawl survey conducted in October of each year and an acoustics-midwater trawl survey, which began in 2004 and is conducted in September-October. Due to weather delays and continued travel restrictions during 2021, there were no bottom trawl samples off the port of Goderich, Ontario and two acoustic transects were cancelled in Georgian Bay. Prey fish biomass in Lake Huron in 2021 was dominated by two species, Bloater (Coregonus hoyi) and Rainbow Smelt (Osmerus mordax). In the main basin, prey fish biomass remained below levels observed prior to community-wide declines that began in the early to mid 1990s. Bloater was the most abundant prey fish species in the main basin, whereas Rainbow Smelt was the most abundant prey species in the North Channel and in Georgian Bay. Both surveys suggested that Bloater biomass is increasing in the main basin. Low biomass of invasive species like Alewife (Alosa pseudoharengus) and Rainbow Smelt is consistent with fish community objectives focused on restoration of native fish communities. Abundance of invasive Round Goby (Neogobius melanostomus) increased in 2021 relative to 2019-2020. Biomass of the native Cisco (Coregonus artedi) increased in the North Channel in 2021 but remained low in Georgian Bay, possibly as an artifact of reduced sampling. Biomass of Slimy Sculpin (Cottus cognatus) and Deepwater Sculpin (Myoxocephalus thompsoni) in 2021 remained low but within the range observed over the past decade. Reduced lake productivity, predation by a recovering piscivore community, and shifts in food web dynamics that favor fish production in nearshore environments may prevent prey fish biomass in offshore areas from returning to levels observed prior to the early 1990s. However, increased biomass of Bloater and Cisco suggests that lake conditions may favor recovery of native corgonines.","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"O’Brien, T.P., Hondorp, D.W., Esselman, P., and Roseman, E., 2023, Status and trends of the Lake Huron prey fish community, 1976-2021, 36 p.","productDescription":"36 p.","ipdsId":"IP-141614","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":416382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416381,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/lake-huron-committee.php"}],"country":"Canada, United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.7705078125,\n 45.81348649679973\n ],\n [\n -84.4189453125,\n 45.5679096098613\n ],\n [\n -83.81469726562499,\n 45.390735154248894\n ],\n [\n -83.507080078125,\n 45.166547157856016\n ],\n [\n -83.38623046875,\n 44.73892994307368\n ],\n [\n -83.507080078125,\n 44.315987905196906\n ],\n [\n -83.9794921875,\n 44.02442151965934\n ],\n [\n -83.95751953125,\n 43.59630591596548\n ],\n [\n -83.60595703125,\n 43.61221676817573\n ],\n [\n -82.891845703125,\n 44.05601169578525\n ],\n [\n -82.46337890625,\n 42.94838139765314\n ],\n [\n -81.705322265625,\n 43.37311218382002\n ],\n [\n -81.683349609375,\n 44.11125397357155\n ],\n [\n -81.134033203125,\n 44.61393394730626\n ],\n [\n -81.49658203125,\n 45.205263456162385\n ],\n [\n -81.024169921875,\n 44.629573191951046\n ],\n [\n -79.95849609375,\n 44.41024041296011\n ],\n [\n -79.903564453125,\n 44.77793589631623\n ],\n [\n -79.56298828125,\n 44.72332018895825\n ],\n [\n -80.145263671875,\n 45.56021795715051\n ],\n [\n -80.804443359375,\n 46.03510927947334\n ],\n [\n -81.58447265624999,\n 46.18743678432541\n ],\n [\n -82.63916015625,\n 46.255846818480315\n ],\n [\n -84.122314453125,\n 46.39998810407942\n ],\n [\n -83.81469726562499,\n 46.17983040759436\n ],\n [\n -83.8916015625,\n 46.126556302418514\n ],\n [\n -83.968505859375,\n 45.98169518512228\n ],\n [\n -84.6826171875,\n 46.11132565729796\n ],\n [\n -84.7705078125,\n 45.81348649679973\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O’Brien, Timothy P. 0000-0003-4502-5204 tiobrien@usgs.gov","orcid":"https://orcid.org/0000-0003-4502-5204","contributorId":2662,"corporation":false,"usgs":true,"family":"O’Brien","given":"Timothy","email":"tiobrien@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":848938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hondorp, Darryl W. 0000-0002-5182-1963 dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":848939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":848940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":848941,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250602,"text":"70250602 - 2023 - Geologic map of Okmok Volcano","interactions":[],"lastModifiedDate":"2023-12-21T15:32:24.005778","indexId":"70250602","displayToPublicDate":"2023-01-01T09:28:59","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5492,"text":"Report of Investigations of the Alaska Department of Natural Resources, Division of Geological & Geophysical Surveys","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"2023-1","title":"Geologic map of Okmok Volcano","docAbstract":"The geologic map and description of map units presented here cover approximately 880 km2 of northeastern Umnak Island, Aleutian Islands, Alaska. This report focuses on Okmok Volcano and its eruptive products and updates the mid-20th-century geologic map of Byers (1959). Mapped deposits reflect the state of the volcano just prior to the 2008 eruption. Published information about other portions of Umnak Island geology, including Mount Recheshnoi and Mount Vsevidof, can be found in Byers (1959). The 2008 eruption and its deposits are described in Larsen and others (2009, 2013, 2015).
Okmok Volcano is one of 54 historically active volcanoes in the Alaska–Aleutian volcanic arc that stretches across southern mainland Alaska and the Aleutian Islands (fig. 1; Wood and Kienle, 1990; Miller and others, 1998; Cameron and others, 2020). The highest point of the modern Okmok Caldera is along the caldera’s northern rim, 967 m in elevation, and formally named “Mount Okmok” (U.S. Board on Geographic Names, www.usgs.gov/core-science-systems/ngp/boardon-geographic-names/domestic-names). Okmok Volcano dominates the northeastern portion of Umnak Island, which is 100 km southwest of Unalaska/Dutch Harbor and 1,400 km southwest of Anchorage (figs. 1, 2). The Port of Dutch Harbor on Unalaska Island produces the highest volume of seafood for any port in the United States (see fisheries.noaa.gov/resource/document/fisheries-united-states-2018-report). Unalaska city and the Port of Dutch Harbor have been impacted by ash fall and drifting ash clouds from Okmok Volcano’s explosive eruptions as recently as 2008. Holocene and late Pleistocene volcanic rocks and deposits of Okmok Volcano rest upon glaciated Tertiary volcanic and sedimentary rocks (Byers, 1959).
The first geologic mapping expedition to Okmok Volcano was by the U.S. Geological Survey (USGS) after the 1945 eruption, largely in response to concerns about volcanic hazards to U.S. military activities in the Aleutians Islands (Byers and others, 1947, 1959; Byers and Brannock, 1949; Byers, 1955, 1959, 1961). The State of Alaska conducted further mapping and geochemical studies as part of its geothermal exploration program in the 1980s (Nye, 1983; Nye and Reid, 1986; Motyka and others, 1993). Additional modern geological work focused on Okmok Volcano and the rest of Umnak Island to address the geochemistry and origin of primary Aleutian arc magmas and subduction zone mass recycling (Marsh, 1982; Brophy and Marsh, 1986; Nye and Reid, 1986; Myers and Marsh, 1987; Miller and others, 1992; Fournelle and others, 1994; Kay and Kay, 1994).
In 1998, the Alaska Volcano Observatory (AVO) began a multi-year effort to expand geophysical monitoring in the central Aleutians Islands, including at Okmok Volcano. As part of this effort, AVO geologists from the University of Alaska Fairbanks Geophysical Institute (UAF/GI), the Alaska Division of Geological & Geophysical Surveys (DGGS), and USGS also began a renewed effort to document Okmok Volcano’s recent eruption products. The project started with reconnaissance fieldwork to document and sample products from the 1997 eruption within Okmok Caldera. This evolved into an effort to produce an updated geologic map of Okmok Volcano and gather more information about its eruptive history and hazards. Three significant eruptions occurred at Okmok Volcano in 1958, 1997, and 2008—after fieldwork had been conducted for the original 1:63,360-scale geologic map produced by Byers (1959)—resulting in new volcanic deposits not previously described.
Okmok Volcano is one of the most frequently active volcanoes in the Aleutian volcanic arc. Seismic and geodetic monitoring indicate ongoing unrest at Okmok Volcano since at least 1997. Geodetic observations of inflation before and after the 1997 and 2008 eruptions indicate a nearly continuous input of new magma from a depth consistent with frequent eruptions of basalt and basaltic andesite magmas over the past 200 years (Larsen and others, 2013; Lu and others, 2000, 2003, 2005; Mann, 2002; Mann and others, 2002). To better understand the likelihood and character of future eruptions from Okmok Volcano, it is necessary to understand its past behavior, including eruptions since the first geologic map was published by Byers (1959).
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","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic mapping forum 22/23 abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Minnesota Geological Survey","usgsCitation":"Phelps, G., 2023, Inferring geologic structure from gravity anomalies: Proceed with caution, in Geologic mapping forum 22/23 abstracts, p. 39-40.","productDescription":"2 p.","startPage":"39","endPage":"40","ipdsId":"IP-147435","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":501306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501305,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/11299/256180"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phelps, Geoffrey 0000-0003-1958-2736 gphelps@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-2736","contributorId":127489,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoffrey","email":"gphelps@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":865326,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70252806,"text":"70252806 - 2023 - 2021–2022 Statewide Abundance Estimates for the Florida Manatee","interactions":[],"lastModifiedDate":"2024-04-05T14:14:20.517907","indexId":"70252806","displayToPublicDate":"2023-01-01T09:10:24","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":138,"text":"Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"TR-27","title":"2021–2022 Statewide Abundance Estimates for the Florida Manatee","docAbstract":"Knowing the population size of Florida manatees (Trichechus manatus latirostris) is critical for conservation and management of this threatened species. Martin et al. (2015) and Hostetler et al. (2018) applied statistical models that incorporated multiple data sources to estimate the statewide abundance of manatees from aerial surveys f lown in 2011–2012 and 2015–2016. We conducted additional aerial surveys in 2021–2022 and applied similar models to provide an updated abundance estimate. This report serves as an update to Hostetler et al. (2018), with most of the text and methodology adapted from the previous report, and provides updated population estimates based on the newly available data. We estimate that the number of manatees in Florida in 2021–2022 was 9,790 (95% Bayesian credible interval 8,350–11,730), of which 4,630 (3,960–5,420) were on the west coast of Florida and 5,160 (3,940–6,980) were on the east coast. These estimates and the associated uncertainty, in addition to being of immediate value to wildlife managers, are essential new data for incorporation into integrated population models and population viability analyses. We also provide context for interpreting the new estimates and perspectives for future modeling improvements.
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Commission","active":true,"usgs":false}],"preferred":false,"id":898280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":218445,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":898281,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hostetler, J. A. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":11319,"corporation":false,"usgs":true,"family":"Hostetler","given":"J.","middleInitial":"A.","affiliations":[],"preferred":true,"id":898282,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70241524,"text":"70241524 - 2023 - Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities","interactions":[],"lastModifiedDate":"2023-03-22T13:52:48.219679","indexId":"70241524","displayToPublicDate":"2023-01-01T08:44:46","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":13626,"text":"DWH MDBC Data Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"DR-23-01","title":"Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities","docAbstract":"This report is part of the NOAA Mesophotic and Deep Benthic Communities (MDBC) Series of \npublications that share the results of work conducted by the Deepwater Horizon MDBC restoration projects. \n \nThe 2010 Deepwater Horizon oil spill was an unprecedented event. Approximately 3.2 million barrels of oil were released into the deep ocean over nearly three months. The plume of oil moved throughout the water column, formed surface slicks that cumulatively covered an area the size of Virginia, and washed oil onto at least 1,300 miles of shoreline habitats. More than 770 square miles (2,000 square kilometers) of deep benthic habitat surrounding the Deepwater Horizon wellhead and 4-square miles of the Pinnacles mesophotic reef complex, located at the edge of the continental shelf, were injured by the oil spill. \n \nUnder the Oil Pollution Act, state and federal natural resource trustees conducted a Natural Resource Damage Assessment (NRDA). The Trustees assessed damages, quantifying the unprecedented injuries to natural resources and lost services. They also developed a programmatic restoration plan to restore injured resources and compensate the public for lost services. \n \nIn April 2016, a settlement was finalized that included up to $8.8 billion in funding for the Deepwater Horizon Trustees to restore the natural resource injuries caused by the oil spill as described in their programmatic restoration plan, Final Programmatic Damage Assessment and Restoration Plan and Final Programmatic Environmental Impact Statement. The Deepwater Horizon Open Ocean Trustee Implementation Group is responsible for restoring natural resources and their services within the Open Ocean Restoration Area that were injured by the oil spill. The Open Ocean Trustees include NOAA, Department of the Interior, U.S. Environmental Protection Agency, and U.S. Department of Agriculture. \n \nIn 2019, the Open Ocean Trustee Implementation Group committed more than $126 million to \nimplement four restoration projects to address the injury to MDBC. The MDBC projects are: mapping, Ground-truthing, and Predictive Habitat Modeling; Habitat Assessment and Evaluation; Coral Propagation Technique Development; and Active Management and Protection. NOAA and the Department of the Interior are implementing the projects, in cooperation with a range of partners, over eight years. \n \nTogether, the projects take a phased approach to meet the challenges involved in restoring deep-sea habitats. Challenges to restoration include a limited scientific understanding of these communities, limited experience with restoration at the depths at which these communities occur, and remote locations that limit accessibility. \n \nMore information about Deepwater Horizon restoration and the MDBC restoration projects is available at: www.gulfspillrestoration.noaa.gov.","language":"English","publisher":"NOAA","doi":"10.25923/kz7t-4674","usgsCitation":"Bassett, R., Herting, J., Frometa, J., Sharuga, S.M., Howell, J., Siceloff, L., Bourque, J.R., Cromwell, M., Francis, K., Clark, R., Demopoulos, A., David, A., Benson, K., and Harter, S.L., 2023, Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities: DWH MDBC Data Report DR-23-01, 68 p., https://doi.org/10.25923/kz7t-4674.","productDescription":"68 p.","ipdsId":"IP-143985","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research 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under contract to NOAA/NOS","active":true,"usgs":false}],"preferred":false,"id":867107,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bourque, Jill R. 0000-0003-3809-2601","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":215719,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":867108,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cromwell, Megan","contributorId":303303,"corporation":false,"usgs":false,"family":"Cromwell","given":"Megan","email":"","affiliations":[{"id":65754,"text":"NOAA/NCEI","active":true,"usgs":false}],"preferred":false,"id":867109,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Francis, 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Andy","contributorId":302199,"corporation":false,"usgs":false,"family":"David","given":"Andy","email":"","affiliations":[{"id":62397,"text":"NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":867113,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Benson, Kristopher","contributorId":302200,"corporation":false,"usgs":false,"family":"Benson","given":"Kristopher","email":"","affiliations":[{"id":62397,"text":"NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":867114,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Harter, Stacey L.","contributorId":302195,"corporation":false,"usgs":false,"family":"Harter","given":"Stacey","email":"","middleInitial":"L.","affiliations":[{"id":62397,"text":"NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":867115,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70234154,"text":"70234154 - 2023 - The not-so-dead of winter: Underwater light climate and primary productivity under snow and ice cover in inland lakes","interactions":[],"lastModifiedDate":"2024-05-20T13:42:57.274286","indexId":"70234154","displayToPublicDate":"2023-01-01T08:43:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"The not-so-dead of winter: Underwater light climate and primary productivity under snow and ice cover in inland lakes","docAbstract":"As global surface temperatures continue to rise as a result of anthropogenic climate change, effects in temperate lakes are likely to be more pronounced than in other ecosystems. Decreases in snow and ice cover extent and duration, as well as extended periods of summer stratification have been observed in temperate lake systems throughout the Anthropocene. However, the effects of changing snow and ice cover upon lacustrine communities remain largely uninvestigated. Here, we examined underwater light climate and associated primary productivity patterns under snow-covered and clear lake ice in 6 inland lakes in Minnesota, USA, spanning gradients of water column optical properties (blue, green, brown) associated with trophic status and organic material content. In all lakes, snow cover influenced not only the intensity, but also the spectral signature of light penetrating into the water column. Specifically, the wavelength of maximum penetration was shifted towards longer wavelengths under snow cover in green (eutrophic) lakes, while it was shifted towards shorter wavelengths in blue and brown lakes. Volumetric primary productivity was often higher than anticipated (e.g. ∼1200 mg · m-3 · d-1; L. Minnetonka, snow-covered ice). Carbon assimilation rates were lower under snow-covered ice throughout the water column in all lake types, except immediately under cleared ice in eutrophic lakes, where it is likely that phytoplankton were photo-inhibited due to penetration of intense, short-wavelength light. These findings suggest that changing patterns of snow and ice cover under ongoing climate change scenarios can affect patterns of phytoplankton primary productivity in sensitive aquatic ecosystems.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/20442041.2022.2102870","usgsCitation":"Bramburger, A.J., Ozersky, T., Silsbe, G.M., Crawford, C., Olmanson, L., and Shchapov, K., 2023, The not-so-dead of winter: Underwater light climate and primary productivity under snow and ice cover in inland lakes: Inland Waters, v. 13, no. 1, p. 1-12, https://doi.org/10.1080/20442041.2022.2102870.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-117588","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":404654,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Barr's Lake, Lake Minnetonka, Parker's Lake, Pike Lake, Side Lake, South Sturgeon Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n 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Minnesota-Duluth","active":true,"usgs":false}],"preferred":false,"id":848009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silsbe, Greg M.","contributorId":294395,"corporation":false,"usgs":false,"family":"Silsbe","given":"Greg","email":"","middleInitial":"M.","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":848010,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":848011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olmanson, Leif","contributorId":294396,"corporation":false,"usgs":false,"family":"Olmanson","given":"Leif","email":"","affiliations":[{"id":37643,"text":"University of Minnesota-Twin Cities","active":true,"usgs":false}],"preferred":false,"id":848012,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shchapov, Krill","contributorId":294398,"corporation":false,"usgs":false,"family":"Shchapov","given":"Krill","affiliations":[{"id":34699,"text":"University of Minnesota-Duluth","active":true,"usgs":false}],"preferred":false,"id":848013,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70241938,"text":"70241938 - 2023 - What controls suspended-sediment concentration and export in flooded agricultural tracts in the Sacramento-San Joaquin Delta?","interactions":[],"lastModifiedDate":"2023-03-31T13:49:09.714507","indexId":"70241938","displayToPublicDate":"2023-01-01T08:42:06","publicationYear":"2023","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":"What controls suspended-sediment concentration and export in flooded agricultural tracts in the Sacramento-San Joaquin Delta?","docAbstract":"We investigated wind-wave and suspended-sediment dynamics in Little Holland Tract and Liberty Island, two subsided former agricultural tracts in the Cache Slough complex in the northern Sacramento-San Joaquin Delta which were restored to tidal shallows to improve habitat. Turbidity, and thus suspended-sediment concentration (SSC), is important to habitat quality because some species of native fishes, including the Delta Smelt, are found preferentially in more turbid waters. Data from October 2015 to August 2016 show that average SSC was greater within Little Holland Tract than in the primary breach that connects the basin to surrounding channels: approximately twice as great at a shallower station farther from the breach and 15% greater at a deeper station closer to the breach. Suspended-sediment concentration within Little Holland Tract was directly related to wave shear stress and inversely related to water depth, based on linear regression. We used measurements of suspended-sediment flux (SSF) through the largest levee breaches to assess whether the enhanced SSC within Little Holland Tract is exported to surrounding waters, thus potentially increasing turbidity over a wider region. Cumulatively, sediment is exported through the Little Holland Tract breaches in winter and imported in summer, consistent with regional patterns in sediment flux, indicating that wind-wave re-suspension within the basin does not control sediment flux from Little Holland Tract on seasonal time-scales. Some sediment was exported during wind-wave events, and results show that sediment export is greater when primary breaches are located downwind of the basin rather than upwind.
","language":"English","publisher":"University of California Davis","doi":"10.15447/sfews.2023v21iss1art4","usgsCitation":"Lacy, J.R., Dailey, E.T., and Morgan-King, T.L., 2023, What controls suspended-sediment concentration and export in flooded agricultural tracts in the Sacramento-San Joaquin Delta?: San Francisco Estuary and Watershed Science, v. 21, no. 1, 4, 28 p., https://doi.org/10.15447/sfews.2023v21iss1art4.","productDescription":"4, 28 p.","ipdsId":"IP-142229","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.15447/sfews.2023v21iss1art4","text":"Publisher Index Page"},{"id":415008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.63062609782116,\n 38.35052041849974\n ],\n [\n -121.72889259399042,\n 38.35052041849974\n ],\n [\n -121.72889259399042,\n 38.22757247707426\n ],\n [\n -121.63062609782116,\n 38.22757247707426\n ],\n [\n -121.63062609782116,\n 38.35052041849974\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":868284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dailey, Evan T. 0000-0002-4382-3870 edailey@usgs.gov","orcid":"https://orcid.org/0000-0002-4382-3870","contributorId":195607,"corporation":false,"usgs":true,"family":"Dailey","given":"Evan","email":"edailey@usgs.gov","middleInitial":"T.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":868285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morgan-King, Tara L. 0000-0001-5632-5232 tamorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-5632-5232","contributorId":554,"corporation":false,"usgs":true,"family":"Morgan-King","given":"Tara","email":"tamorgan@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":868286,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240785,"text":"70240785 - 2023 - The future of coastal monitoring through satellite remote sensing","interactions":[],"lastModifiedDate":"2023-02-22T14:31:44.228534","indexId":"70240785","displayToPublicDate":"2023-01-01T08:26:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12971,"text":"Cambridge Prisms: Coastal Futures","active":true,"publicationSubtype":{"id":10}},"title":"The future of coastal monitoring through satellite remote sensing","docAbstract":"Satellite remote sensing is transforming coastal science from a “data-poor” field into a “data-rich” field. Sandy beaches are dynamic landscapes that change in response to long-term pressures, short-term pulses, and anthropogenic interventions. Until recently, the rate and breadth of beach change have outpaced our ability to monitor those changes, due to the spatiotemporal limitations of our observational capacity. Over the past several decades, only a handful of beaches worldwide have been regularly monitored with accurate yet expensive in situ surveys. The long-term coastal-change data of these few well-monitored beaches have led to in-depth understanding of many site-specific coastal processes. However, because the best-monitored beaches are not representative of all beaches, much remains unknown about the processes and fate of the other >99% of unmonitored beaches worldwide. The fleet of Earth-observing satellites has enabled multiscale monitoring of beaches, for the very first time, by providing imagery with global coverage and up to daily frequency. The long-standing and ever-expanding archive of satellite imagery will enable coastal scientists to investigate coastal change at sites vulnerable to future sea-level rise, that is, (almost) everywhere. In the past decade, our capability to observe coastal change from space has grown substantially with computing and algorithmic power. Yet, further advances are needed in automating monitoring using machine learning, deep learning, and computer vision to fully leverage this massive treasure trove of data. Extensive monitoring and investigation of the causes and effects of coastal change at the requisite spatiotemporal scales will provide coastal managers with additional, valuable information to evaluate problems and solutions, addressing the potential for widespread beach loss due to accelerated sea-level rise, development, and reduced sediment supply. Monitoring from Earth-observing satellites is currently the only means of providing seamless data with high spatiotemporal resolution at the global scale of the impending impacts of climate change on coastal systems.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/cft.2022.4","usgsCitation":"Vitousek, S., Buscombe, D., Vos, K., Barnard, P.L., Ritchie, A.C., and Warrick, J.A., 2023, The future of coastal monitoring through satellite remote sensing: Cambridge Prisms: Coastal Futures, v. 1, e10, 18 p., https://doi.org/10.1017/cft.2022.4.","productDescription":"e10, 18 p.","ipdsId":"IP-144564","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444986,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/cft.2022.4","text":"Publisher Index Page"},{"id":413282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","noUsgsAuthors":false,"publicationDate":"2022-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":864827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buscombe, Dan","contributorId":302609,"corporation":false,"usgs":false,"family":"Buscombe","given":"Dan","email":"","affiliations":[{"id":65516,"text":"Marda Science","active":true,"usgs":false}],"preferred":false,"id":864828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vos, Kilian","contributorId":302610,"corporation":false,"usgs":false,"family":"Vos","given":"Kilian","affiliations":[{"id":65517,"text":"University of New South Wales - Sydney","active":true,"usgs":false}],"preferred":false,"id":864829,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":864830,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ritchie, Andrew C. aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":864831,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":864832,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70240778,"text":"70240778 - 2023 - Skeletal indicators of locomotor adaptations in shrews","interactions":[],"lastModifiedDate":"2023-02-22T14:24:43.331761","indexId":"70240778","displayToPublicDate":"2023-01-01T08:21:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13293,"text":"Therya","active":true,"publicationSubtype":{"id":10}},"title":"Skeletal indicators of locomotor adaptations in shrews","docAbstract":"The Soricidae (Mammalia: Eulypotyphla) comprises more than 450 species inhabiting a variety of habitats on five continents. As a family, shrews employ a variety of locomotor modes that incorporate ambulatory, fossorial, aquatic, and scansorial behaviors, illustrating an ability to exploit a variety of natural substrates and their associated resources. In this study, the association of skeletal morphology and three of the dominant locomotor modes in the family—ambulatory, semi-fossorial, and semi-aquatic behaviors—was investigated in up to 52 species of 12 genera representing all three subfamilies of Soricidae. From skeletal measures, 34 morphological indices were calculated, most of which have been used previously to characterize substrate use among shrews, rodents, and other mammals, and analyzed for their individual effectiveness for discriminating the three locomotory modes. To assess their effectiveness in combination, subsets of locomotor indices were analyzed using 1) mean percentile ranks, 2) the first principal component from principal components analysis, and 3) plots and classifications from discriminant function analyses. In general, the three methods effectively identified and grouped the three locomotor modes and identified smaller subsets. Additional analyses were then used to classify the locomotor behaviors of five species whose locomotor modes were unknown or ambiguous. The analyses reinforce and broaden the scope of a previously identified observation of the wide range of grades of morphological variation that may permit an equally diverse range of locomotor abilities among the Soricidae.
","language":"English","publisher":"Asociación Mexicana de Mastozoología A. C.","doi":"10.12933/therya-23-2218","usgsCitation":"Woodman, N., 2023, Skeletal indicators of locomotor adaptations in shrews: Therya, v. 14, no. 1, p. 15-37, https://doi.org/10.12933/therya-23-2218.","productDescription":"23 p.","startPage":"15","endPage":"37","ipdsId":"IP-147190","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444989,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.12933/therya-23-2218","text":"Publisher Index Page"},{"id":413281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":864803,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70244228,"text":"70244228 - 2023 - The Searsville Lake Site (California, USA) as a candidate Global boundary Stratotype Section and Point for the Anthropocene series","interactions":[],"lastModifiedDate":"2023-06-08T13:26:30.124744","indexId":"70244228","displayToPublicDate":"2023-01-01T08:09:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13447,"text":"The Anthropocene Review","active":true,"publicationSubtype":{"id":10}},"title":"The Searsville Lake Site (California, USA) as a candidate Global boundary Stratotype Section and Point for the Anthropocene series","docAbstract":"Cores from Searsville Lake within Stanford University’s Jasper Ridge Biological Preserve, California, USA, are examined to identify a potential GSSP for the Anthropocene: core JRBP2018-VC01B (944.5 cm-long) and tightly correlated JRBP2018-VC01A (852.5 cm-long). Spanning from 1900 CE ± 3 years to 2018 CE, a secure chronology resolved to the sub-annual level allows detailed exploration of the Holocene-Anthropocene transition. We identify the primary GSSP marker as first appearance of 239,240Pu (372–374 cm) in JRBP2018-VC01B and designate the GSSP depth as the distinct boundary between wet and dry season at 366 cm (6 cm above the first sample containing 239,240Pu) and corresponding to October-December 1948 CE. This is consistent with a lag of 1–2 years between ejection of 239,240Pu into the atmosphere and deposition. Auxiliary markers include: first appearance of 137Cs in 1958; late 20th-century decreases in δ15N; late 20th-century elevation in SCPs, Hg, Pb, and other heavy metals; and changes in abundance and presence of ostracod, algae, rotifer and protozoan microfossils. Fossil pollen document anthropogenic landscape changes related to logging and agriculture. As part of a major university, the Searsville site has long been used for research and education, serves users locally to internationally, and is protected yet accessible for future studies and communication about the Anthropocene.
","language":"English","publisher":"Sage Publishing","doi":"10.1177/20530196221144098","usgsCitation":"Stegner, M.A., Hadly, E.A., Barnosky, A.D., La Selle, S., Sherrod, B.L., Anderson, R., Redondo, S.A., Viteri, M., Weaver, K., Cundy, A., Gaca, P., Rose, N., Yang, H., Roberts, S.A., Hajdas, I., Black, B.A., and Spanbauer, T., 2023, The Searsville Lake Site (California, USA) as a candidate Global boundary Stratotype Section and Point for the Anthropocene series: The Anthropocene Review, v. 10, no. 1, p. 116-145, https://doi.org/10.1177/20530196221144098.","productDescription":"30 p.","startPage":"116","endPage":"145","ipdsId":"IP-143228","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444993,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/20530196221144098","text":"Publisher Index Page"},{"id":417936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Jasper Ridge Biological Preserve, Searsville Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.23674493135238,\n 37.402387907230434\n ],\n [\n -122.23676634716284,\n 37.40303437909546\n ],\n [\n -122.23639157047862,\n 37.403127946929516\n ],\n [\n -122.23567414082538,\n 37.4032215146467\n ],\n [\n -122.23498883488803,\n 37.4035107232161\n ],\n [\n -122.23531007204622,\n 37.40366383318312\n ],\n [\n -122.2355028143412,\n 37.4035447476802\n ],\n [\n -122.23586688312037,\n 37.40347669873654\n ],\n [\n -122.23619882818363,\n 37.403553253794186\n ],\n [\n -122.23658431277329,\n 37.4037063636743\n ],\n [\n -122.23700192107881,\n 37.40367233928362\n ],\n [\n -122.23713041594202,\n 37.4037829184973\n ],\n [\n -122.23721607918426,\n 37.404012582496506\n ],\n [\n -122.23708758432105,\n 37.40423373975594\n ],\n [\n -122.23715183175284,\n 37.40431880006669\n ],\n [\n -122.23734457404748,\n 37.40439535426398\n ],\n [\n -122.2374837768161,\n 37.40463352237683\n ],\n [\n -122.23738740566878,\n 37.40500778502482\n ],\n [\n -122.2368734262156,\n 37.40527997486761\n ],\n [\n -122.23700192107881,\n 37.405416069417726\n ],\n [\n -122.2371625396579,\n 37.40549262249388\n ],\n [\n -122.2373338661424,\n 37.40594343346618\n ],\n [\n -122.23721607918426,\n 37.40628366636611\n ],\n [\n -122.23725891080556,\n 37.40640274751598\n ],\n [\n -122.2371732475633,\n 37.40668343804869\n ],\n [\n -122.23725891080556,\n 37.4069556218041\n ],\n [\n -122.2374730689107,\n 37.40715125326746\n ],\n [\n -122.23761227167932,\n 37.40741492964867\n ],\n [\n -122.23798704836389,\n 37.40725332165387\n ],\n [\n -122.23843678038526,\n 37.4071002190218\n ],\n [\n -122.2385224436272,\n 37.40677700132646\n ],\n [\n -122.23845819619577,\n 37.406368724349704\n ],\n [\n -122.23844748829035,\n 37.40619860828596\n ],\n [\n -122.2386830622063,\n 37.40596044514756\n ],\n [\n -122.23858669105898,\n 37.405475610705764\n ],\n [\n -122.23867235430123,\n 37.404948243364984\n ],\n [\n -122.23875801754315,\n 37.404880195695995\n ],\n [\n -122.23894005193273,\n 37.40486318376881\n ],\n [\n -122.23914350213312,\n 37.40463352237683\n ],\n [\n -122.23902571517499,\n 37.40431029404013\n ],\n [\n -122.23871518592219,\n 37.40435282416388\n ],\n [\n -122.23857598315357,\n 37.404259257859366\n ],\n [\n -122.23860810686946,\n 37.40386797931984\n ],\n [\n -122.23871518592219,\n 37.4035447476802\n ],\n [\n -122.23870447801679,\n 37.40334060066334\n ],\n [\n -122.23854385943768,\n 37.403051391437316\n ],\n [\n -122.23845819619577,\n 37.402966329687786\n ],\n [\n -122.23858669105898,\n 37.402796205899065\n ],\n [\n -122.23860810686946,\n 37.40255803194616\n ],\n [\n -122.23888651240637,\n 37.40239641347523\n ],\n [\n -122.23884368078541,\n 37.40216674452243\n ],\n [\n -122.2386830622063,\n 37.402183757061835\n ],\n [\n -122.23869377011171,\n 37.40185201185126\n ],\n [\n -122.23854385943768,\n 37.40174142978856\n ],\n [\n -122.2382547459957,\n 37.401809480308074\n ],\n [\n -122.23813695903756,\n 37.40193707486574\n ],\n [\n -122.23798704836389,\n 37.40193707486574\n ],\n [\n -122.23775147444792,\n 37.401809480308074\n ],\n [\n -122.2374837768161,\n 37.401945581162266\n ],\n [\n -122.2372053712792,\n 37.40191155597202\n ],\n [\n -122.23700192107881,\n 37.402047656640235\n ],\n [\n -122.23700192107881,\n 37.40224330091844\n ],\n [\n -122.23674493135238,\n 37.402387907230434\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Stegner, M. 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Vulnerable waters include non-floodplain wetlands and headwater streams, abundant watershed components representing the most distal extent of the freshwater aquatic network. Vulnerable waters are hydrologically dynamic and biogeochemically reactive aquatic systems, storing, processing, and releasing water and entrained (that is, dissolved and particulate) materials along expanding and contracting aquatic networks. The hydrological and biogeochemical functions emerging from these processes affect the magnitude, frequency, timing, duration, storage, and rate of change of material and energy fluxes among watershed components and to downstream waters, thereby maintaining watershed states and imparting watershed resilience. We present here a conceptual framework for understanding how vulnerable waters confer watershed resilience. We demonstrate how individual and cumulative vulnerable-water modifications (for example, reduced extent, altered connectivity) affect watershed-scale hydrological and biogeochemical disturbance response and recovery, which decreases watershed resilience and can trigger transitions across thresholds to alternative watershed states (for example, states conducive to increased flood frequency or nutrient concentrations). We subsequently describe how resilient watersheds require spatial heterogeneity and temporal variability in hydrological and biogeochemical interactions between terrestrial systems and down-gradient waters, which necessitates attention to the conservation and restoration of vulnerable waters and their downstream connectivity gradients. To conclude, we provide actionable principles for resilient watersheds and articulate research needs to further watershed resilience science and vulnerable-water management.
Managing impounded river systems is a recurring challenge for aquatic resource professionals because reservoirs serve multiple functions with different ecological and socioeconomic outcomes. However, research on fishes in reservoirs has disproportionally focused on recreationally and economically important species, with less attention directed toward fish assemblages despite the potential for management at the assemblage level. As such, evaluation of relationships between reservoir fish assemblages and biotic and abiotic factors and testing whether assemblage structure is affected by changing environmental conditions may deepen ecological understanding and provide insights for reservoir fisheries management. Our overall objective was to assess these relationships in 11 reservoirs from North Carolina, USA. We sampled fish assemblages in the reservoirs, which spanned five river basins representing a range of habitat conditions, using experimental gillnets and pulsed DC nighttime electrofishing. Multivariate statistical analyses indicated that taxonomic differences in fish assemblage composition among river basins followed a gradient of productivity. The top contributing species to reservoir dissimilarity were bluegill (Lepomis macrochirus), gizzard shad (Dorosoma cepedianum), black crappie (Pomoxis nigromaculatus), and white perch (Morone americana). These four species were positively associated with factors that reflect increasing eutrophic conditions in the 11 reservoirs and could, therefore, serve as indicators of reservoir productivity, anthropogenic influence, and fish assemblage structure, in addition to their key role in reservoir fisheries management. Whereas fisheries research has historically focused on assessing fish populations, our results illustrate the ecological and management insights derived from simultaneously collecting assemblage- and population-level data. Research on reservoir fish assemblages in relation to biotic and abiotic conditions may help advance fish ecology and management alike.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02705060.2023.2241494","usgsCitation":"Parker, S.W., Coleman, T.S., Carlson, A.K., and Fischer, J., 2023, Characterization of fish assemblages in eleven multi-use reservoirs from North Carolina, USA: Journal of Freshwater Ecology, v. 38, no. 1, e2241494, 21 p., https://doi.org/10.1080/02705060.2023.2241494.","productDescription":"e2241494, 21 p.","ipdsId":"IP-135242","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445000,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2023.2241494","text":"Publisher Index Page"},{"id":432884,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North 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Carolina\",\"nation\":\"USA \"}}]}","volume":"38","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-08-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Parker, Stephen W.","contributorId":341050,"corporation":false,"usgs":false,"family":"Parker","given":"Stephen","email":"","middleInitial":"W.","affiliations":[{"id":81695,"text":"North Carolina Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":907857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coleman, Tyler Steven","contributorId":340579,"corporation":false,"usgs":false,"family":"Coleman","given":"Tyler","email":"","middleInitial":"Steven","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":907858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson, Andrew Kenneth 0000-0002-6681-0853","orcid":"https://orcid.org/0000-0002-6681-0853","contributorId":340581,"corporation":false,"usgs":true,"family":"Carlson","given":"Andrew","email":"","middleInitial":"Kenneth","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fischer, Jesse R.","contributorId":86618,"corporation":false,"usgs":true,"family":"Fischer","given":"Jesse R.","affiliations":[],"preferred":false,"id":907859,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263336,"text":"70263336 - 2023 - Latency and geofence testing of wireless emergency alerts intended for the ShakeAlert® earthquake early warning system for the West Coast of the United States of America","interactions":[],"lastModifiedDate":"2025-02-06T15:25:21.459341","indexId":"70263336","displayToPublicDate":"2023-01-01T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20071,"text":"Safety Science","active":true,"publicationSubtype":{"id":10}},"title":"Latency and geofence testing of wireless emergency alerts intended for the ShakeAlert® earthquake early warning system for the West Coast of the United States of America","docAbstract":"ShakeAlert, the earthquake early warning (EEW) system for the West Coast of the United States, attempts to provides crucial warnings before strong shaking occurs. However, because the alerts are triggered only when an earthquake is already in progress, and the alert latencies and delivery times are platform dependent, the time between these warnings and the arrival of shaking is variable. The ShakeAlert system uses, among other public alerting platforms like a mobile phone operating system, smartphone apps, and the Federal Emergency Management Agency Integrated Public Alert & Warning System (IPAWS). IPAWS sends Wireless Emergency Alerts (WEAs) informing people via their smartphones and other mobile devices about various events, such as natural hazards, child abductions, or public health information about COVID-19. However, little is known about the IPAWS delivery latencies. Given that people may have only a few seconds of notice after they receive an alert to take a protective action before they feel earthquake shaking, quantifying latencies is critical to understanding whether the IPAWS system is useful for EEW. In this study, we developed new methods to test the IPAWS distribution system's performance, both with devices in a controlled environment and as well as with a 2019 community-based feedback form, in Oakland and San Diego County, California, respectively. The controlled environment test used mobile phones (including smart and non-smart phones) and associated devices to determine alert receipt times; the community research form had participants self-report their receipt times. By triangulating the data between the controlled test environment and the community research, we determined the latency statistics as well as whether the geofence (the geographic area where the alert was intended to be sent) held broadly. We found that the latencies were similar between the two tests despite the large differences in population sizes. WEA messages were received within a median time frame of 6–12 s, and the geofence held with only a few exceptions. We use this latency to assess how the system would have performed in two large earthquakes, the 1989 M6.9 Loma Prieta and 2019 M7.1 Ridgecrest earthquakes, which both occurred near our WEA test locations. Our analysis revealed that had IPAWS been available during those earthquakes, particularly Loma Prieta, it would have provided crucial seconds of notice that damaging shaking was imminent in some locations relatively far from the epicenter. Further, we find affordable non-smart phones can receive WEAs as fast as smartphones. Finally, our new method can be used for latency and geospatial testing going forward for IPAWS and other similar alerting systems.
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estimation","interactions":[],"lastModifiedDate":"2024-02-29T15:59:09.868044","indexId":"70248892","displayToPublicDate":"2022-12-31T09:57:57","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Causality-informed Bayesian inference for rapid seismic ground failure and building damage estimation","docAbstract":"Rapid and accurate estimates of seismic ground failure and building damage are beneficial to efficient emergency response and post-earthquake recovery. Traditional approaches, such as physical and geospatial models, have poor accuracy and resolution due to large uncertainties and the limited availability of informing geospatial layers. The introduction of remote sensing techniques has shown potential in providing supplementary information for rapid hazard estimation by analyzing earthquake-induced correlation changes between pre- and post-event satellite images. However, the changes in satellite images are the result of overlapping ground failure, building damage, and environmental noise, making it challenging to categorize and estimate different seismic hazards and impacts directly from satellite images.Here we design a novel causality-informed Bayesian network that continuously updates seismic ground failure and building damage estimates from satellite images by modeling the physical interdependencies between geospatial features, ground failure, building footprints, building damage, and satellite images. The incorporation of physical interdependencies allows an effective fusion of physical models and rich but noisy information from remote sensing observations and reduces bias and uncertainties in estimations. Our experiments show that integrating satellite images through our Bayesian network improves the accuracy of seismic ground failure and building damage estimations.","conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"June 27-July 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Wald, D.J., Xu, S., Dimasaka, J., and Noh, H., 2023, Causality-informed Bayesian inference for rapid seismic ground failure and building damage estimation, 12th National Conference on Earthquake Engineering, Salt Lake City, UT, June 27-July 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134888","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":426129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421114,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":884115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Susu","contributorId":300127,"corporation":false,"usgs":false,"family":"Xu","given":"Susu","email":"","affiliations":[{"id":65025,"text":"Stony Brook University, NY, USA","active":true,"usgs":false}],"preferred":false,"id":884116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dimasaka, J.","contributorId":330154,"corporation":false,"usgs":false,"family":"Dimasaka","given":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":884117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noh, H.","contributorId":330155,"corporation":false,"usgs":false,"family":"Noh","given":"H.","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":884118,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254987,"text":"70254987 - 2023 - Relative-condition parameters for fishes of Montana, USA","interactions":[],"lastModifiedDate":"2024-06-11T14:47:25.713532","indexId":"70254987","displayToPublicDate":"2022-12-31T09:43:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Relative-condition parameters for fishes of Montana, USA","docAbstract":"Body condition indices are commonly used in the management of fish populations and are a surrogate to physiological attributes such as tissue-energy reserves. Relative condition factor (Kn) describes the condition of species relative to populations in a geographic area. We developed models to allow for the calculation of Kn in Montana, USA by using the weight–length data collected by Montana Fish, Wildlife & Parks. We generated log10weight–log10length relationships to obtain Montana specific parameter estimates for relative condition equations (W′) for 51 species and three subspecies. We developed separate models by water type (e.g., lotic and lentic) and sex for five species due to varying growth based on sexual dimorphism and varying ecosystem types. Relative condition offers the advantage of describing body condition relative to species in Montana, provides a condition index for species that do not have standard-weight models developed for relative weight (Wr), and affords more information for the global database on weight–length relationships of fishes.
","language":"English","publisher":"MDPI","doi":"10.3390/fishes8010028","usgsCitation":"Eckelbecker, R.W., Heili, N.M., Guy, C.S., and Schmetterling, D.A., 2023, Relative-condition parameters for fishes of Montana, USA: Fishes, v. 8, no. 1, 28, 8 p., https://doi.org/10.3390/fishes8010028.","productDescription":"28, 8 p.","ipdsId":"IP-139822","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":445003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes8010028","text":"Publisher Index Page"},{"id":429875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Eckelbecker, Robert W.","contributorId":338225,"corporation":false,"usgs":false,"family":"Eckelbecker","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":903026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heili, Nathaniel M.","contributorId":338227,"corporation":false,"usgs":false,"family":"Heili","given":"Nathaniel","email":"","middleInitial":"M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":903027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmetterling, David A.","contributorId":338230,"corporation":false,"usgs":false,"family":"Schmetterling","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":52338,"text":"Montana Fish, Wildlife & Parks","active":true,"usgs":false}],"preferred":false,"id":903029,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239806,"text":"70239806 - 2023 - Trace elements in blood of sea ducks from Dutch Harbor and Izembek Lagoon, Alaska","interactions":[],"lastModifiedDate":"2023-07-11T15:52:17.015549","indexId":"70239806","displayToPublicDate":"2022-12-31T06:35:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Trace elements in blood of sea ducks from Dutch Harbor and Izembek Lagoon, Alaska","docAbstract":"In 2001, we collected whole blood from sea ducks (Steller’s eider Polysticta stelleri, harlequin duck Histrionicus histrionicus, black scoter Melanitta nigra, and long-tailed duck Clangula hyemalis) wintering at Dutch Harbor, Alaska, and from Steller’s eiders molting at Izembek Lagoon on the Alaska Peninsula. Blood samples were analyzed for 19 trace elements, of which 17 were detected in one or more samples. In Steller’s eiders, mean concentrations of six trace elements (As, B, Fe, Hg, Se, Mo) were greater at Dutch Harbor and mean concentrations of four trace elements (Cr, Cu, Mg, Zn) were greater at Izembek Lagoon. Among sea ducks at Dutch Harbor, mean concentrations of five trace elements (Cu, Hg, Se, Zn, V) differed by species. Steller’s eiders had greater concentrations of Cu, Zn, and V in their blood, black scoters had the highest Se, and harlequin ducks had the highest Hg, with a mean concentration slightly above a threshold effect level. One Steller’s eider and one harlequin duck from Dutch Harbor had blood Pb levels above background concentrations. We have no observations to indicate that concentrations of these trace elements were associated with adverse effects.